Scientific Advances in STEM: From Professor to Students

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Topic Information

Dear Colleagues, 

The aim of this article collection is to contribute to the advancement of the Science and Engineering fields and their impact on the industrial sector, which requires a multidisciplinary approach.

The University generates and transmits knowledge to serve society. Social demands continuously evolve, mainly as a consequence of cultural, scientific, and technological development. Researchers must contextualize the subjects they investigate to their application to the local industry and community organizations, frequently using a multidisciplinary point of view, to enhance the progress in a wide variety of fields (aeronautics, automotive, biomedical, electrical and renewable energy, communications, environmental, electronic components, etc.).

Most investigations in the fields of science and engineering require the work of multidisciplinary teams, representing a stockpile of research projects in different stages (final year projects, master’s or doctoral studies). In this context, this Topic offers a framework for integrating interdisciplinary research, drawing together experimental and theoretical contributions in a wide variety of fields. Topics of interest could include, but are not limited to:

General topics:

• Science and technology of materials;
• Physics and applied mathematics;
• Industrial and environmental chemistry;
• Analytic chemistry;
• Intelligent systems and electronic technology;
• Product design, development, and engineering;
• Computerized, robotic, and neuromorphic industrial systems;
• Computer architecture and technology.

Particular Themes:

• Coatings and nanostructured materials for solar energy applications (in particular for high-temperature concentrated solar power applications);
• Development of functional materials for additive manufacturing (i.e., applications in biomedicine);
• Advanced optical characterization or nano- and microstructures and thin films;
• Biopolymer-based superabsorbent materials from agro-food bioresidues;
• Biodegradable protein‐based polymer materials for the controlled release of micronutrients in horticulture;
• Interfacial rheology and its applications to protein-based emulsion processing and stability;
• Deep-learning systems for diagnosis, prevention, and pattern recognition;
• Bio-inspired systems for sensory fusion and control;
• Current advances in computer architecture;
• Artificial intelligence in smart cities applications;
• Energy forecasting and flexibility services;
• Advances in food and by-products development and characterization;
• New trends in sustainable cities and industries;
• Intelligent and sustainable optimization of industrial engineering projects;
• Multifunctional and smart toys for children with autism spectrum disorder;
• Weighting with life-cycle assessment and cradle-to-cradle (methodology for global sustainability design social and socio-economic life cycle assessment: towards quantitative methods in small and medium-sized enterprises);
• Work of separation in metal–metal interfaces;
• Emerging pollutants in the urban water cycle;
• Analysis of emerging pollutants in environmental samples;
• Design, manufacture, and characterization of WC-Co/WC-Co laminates;
• Wear and scratch resistance of porous materials for biomedical applications;
• Biomechanical and biofunctional behavior of porous titanium parts coated with hydroxyapatite using the sol–gel technique;
• Bioactive glass bilayer coatings on porous titanium samples.

Prof. Dr. Yadir Torres Hernández
Dr. Manuel Félix Ángel
Dr. Ana María Beltrán Custodio
Prof. Dr. Francisco Garcia Moreno

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Metals metals	2.6	4.9	2011	17.8 Days	CHF 2600
Polymers polymers	4.7	8.0	2009	14.5 Days	CHF 2700
Foods foods	4.7	7.4	2012	14.5 Days	CHF 2900
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400
Sensors sensors	3.4	7.3	2001	18.6 Days	CHF 2600

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Published Papers (20 papers)

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14 pages, 58850 KiB  

Open AccessArticle

Development of Elastoplastic-Damage Model of AlFeSi Phase for Aluminum Alloy 6061

by Hailong Wang, Wenping Deng, Tao Zhang, Jianhua Yao and Sujuan Wang

Metals 2021, 11(6), 954; https://doi.org/10.3390/met11060954 - 12 Jun 2021

Cited by 3 | Viewed by 3049

Abstract

Material properties affect the surface finishing in ultra-precision diamond cutting (UPDC), especially for aluminum alloy 6061 (Al6061) in which the cutting-induced temperature rise generates different types of precipitates on the machined surface. The precipitates generation not only changes the material properties but also [...] Read more.

Material properties affect the surface finishing in ultra-precision diamond cutting (UPDC), especially for aluminum alloy 6061 (Al6061) in which the cutting-induced temperature rise generates different types of precipitates on the machined surface. The precipitates generation not only changes the material properties but also induces imperfections on the generated surface, therefore increasing surface roughness for Al6061 in UPDC. To investigate precipitate effect so as to make a more precise control for the surface quality of the diamond turned Al6061, it is necessary to confirm the compositions and material properties of the precipitates. Previous studies have indicated that the major precipitate that induces scratch marks on the diamond turned Al6061 is an AlFeSi phase with the composition of Al_86.1Fe_8.3Si_5.6. Therefore, in this paper, to study the material properties of the AlFeSi phase and its influences on ultra-precision machining of Al6061, an elastoplastic-damage model is proposed to build an elastoplastic constitutive model and a damage failure constitutive model of Al_86.1Fe_8.3Si_5.6. By integrating finite element (FE) simulation and JMatPro, an efficient method is proposed to confirm the physical and thermophysical properties, temperature-phase transition characteristics, as well as the stress–strain curves of Al_86.1Fe_8.3Si_5.6. Based on the developed elastoplastic-damage parameters of Al_86.1Fe_8.3Si_5.6, FE simulations of the scratch test for Al_86.1Fe_8.3Si_5.6 are conducted to verify the developed elastoplastic-damage model. Al_86.1Fe_8.3Si_5.6 is prepared and scratch test experiments are carried out to compare with the simulation results, which indicated that, the simulation results agree well with those from scratch tests and the deviation of the scratch force in X-axis direction is less than 6.5%. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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<p>Chemical composition of AlFeSi in Al6061 from the previous study [<a href="#B15-metals-11-00954" class="html-bibr">15</a>]: (<b>a</b>) SEM of the Al6061 samples; (<b>b</b>) EDX results of the Al6061 samples (Atomic %).</p> Full article ">Figure 2
<p>The temperature-phase transition characteristics of α-AlFeSi and β-AlFeSi from JMatPro.</p> Full article ">Figure 3
<p>The characterization results of (<b>a</b>) density; (<b>b</b>) thermal conductivity; (<b>c</b>) Young’s modulus; (<b>d</b>) Poisson’s ratio; (<b>e</b>) specific heat; (<b>f</b>) thermal expansion coefficient.</p> Full article ">Figure 4
<p>The yield strength of AlFeSi phase under quasi-static conditions.</p> Full article ">Figure 5
<p>The stress–strain curve of AlFeSi phase under different strain rates: (<b>a</b>) strain rate 0.001 s^–1; (<b>b</b>) strain rate 0.01 s^–1; (<b>c</b>) strain rate 0.1 s^–1; (<b>d</b>) strain rate 10 s^–1; (<b>e</b>) strain rate 100 s^–1; (<b>f</b>) strain rate 1000 s^–1.</p> Full article ">Figure 5 Cont.
<p>The stress–strain curve of AlFeSi phase under different strain rates: (<b>a</b>) strain rate 0.001 s^–1; (<b>b</b>) strain rate 0.01 s^–1; (<b>c</b>) strain rate 0.1 s^–1; (<b>d</b>) strain rate 10 s^–1; (<b>e</b>) strain rate 100 s^–1; (<b>f</b>) strain rate 1000 s^–1.</p> Full article ">Figure 6
<p>Solutions of three parameters (<math display="inline"><semantics> <mrow> <mi>A</mi> <mo>,</mo> </mrow> </semantics></math> <math display="inline"><semantics> <mi>B</mi> </semantics></math> and<math display="inline"><semantics> <mrow> <mo> </mo> <mi>n</mi> </mrow> </semantics></math>).</p> Full article ">Figure 7
<p>Solution of parameter <math display="inline"><semantics> <mi>C</mi> </semantics></math>.</p> Full article ">Figure 8
<p>Solution of parameter <math display="inline"><semantics> <mi>m</mi> </semantics></math>.</p> Full article ">Figure 9
<p>FE simulated tensile fracture damage of AlFeSi phase.</p> Full article ">Figure 10
<p>The stress–strain curve of AlFeSi phase with <math display="inline"><semantics> <mrow> <msub> <mi>D</mi> <mn>1</mn> </msub> <mo>–</mo> <msub> <mi>D</mi> <mn>5</mn> </msub> </mrow> </semantics></math>: (<b>a</b>) strain rate of 1000 s^–1, temperature of 20 °C; (<b>b</b>) strain rate of 0.01 s^–1, temperature of 500 °C.</p> Full article ">Figure 11
<p>Preparation of the AlFeSi phase.</p> Full article ">Figure 12
<p>The scratch experiment of AlFeSi phase.</p> Full article ">Figure 12 Cont.
<p>The scratch experiment of AlFeSi phase.</p> Full article ">Figure 13
<p>The parameters of the scratch tool (L = 10.5 mm, D = 6.01 mm, D1 = 2.56 mm, S = 2.74 mm, r = 0.4 mm).</p> Full article ">Figure 14
<p>(<b>a</b>) The measured surface and (<b>b</b>) scratch of AlFeSi sample from the optical profiler.</p> Full article ">Figure 14 Cont.
<p>(<b>a</b>) The measured surface and (<b>b</b>) scratch of AlFeSi sample from the optical profiler.</p> Full article ">Figure 15
<p>FE simulation model for the scratch experiment of AlFeSi phase.</p> Full article ">Figure 16
<p>Comparison between FE simulation results and the scratch experiment.</p> Full article ">

18 pages, 41138 KiB  

Open AccessArticle

WS-RCNN: Learning to Score Proposals for Weakly Supervised Instance Segmentation

by Jia-Rong Ou, Shu-Le Deng and Jin-Gang Yu

Sensors 2021, 21(10), 3475; https://doi.org/10.3390/s21103475 - 17 May 2021

Cited by 4 | Viewed by 2598

Abstract

Weakly supervised instance segmentation (WSIS) provides a promising way to address instance segmentation in the absence of sufficient labeled data for training. Previous attempts on WSIS usually follow a proposal-based paradigm, critical to which is the proposal scoring strategy. These works mostly rely [...] Read more.

Weakly supervised instance segmentation (WSIS) provides a promising way to address instance segmentation in the absence of sufficient labeled data for training. Previous attempts on WSIS usually follow a proposal-based paradigm, critical to which is the proposal scoring strategy. These works mostly rely on certain heuristic strategies for proposal scoring, which largely hampers the sustainable advances concerning WSIS. Towards this end, this paper introduces a novel framework for weakly supervised instance segmentation, called Weakly Supervised R-CNN (WS-RCNN). The basic idea is to deploy a deep network to learn to score proposals, under the special setting of weak supervision. To tackle the key issue of acquiring proposal-level pseudo labels for model training, we propose a so-called Attention-Guided Pseudo Labeling (AGPL) strategy, which leverages the local maximal (peaks) in image-level attention maps and the spatial relationship among peaks and proposals to infer pseudo labels. We also suggest a novel training loss, called Entropic OpenSet Loss, to handle background proposals more effectively so as to further improve the robustness. Comprehensive experiments on two standard benchmarking datasets demonstrate that the proposed WS-RCNN can outperform the state-of-the-art by a large margin, with an improvement of $11.6\%$ on PASCAL VOC 2012 and $10.7\%$ on MS COCO 2014 in terms of mAP${}_{50}$, which indicates that learning-based proposal scoring and the proposed WS-RCNN framework might be a promising way towards WSIS. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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<p>Illustration of the motivation of our work. Existing proposal-based approaches to WSIS commonly follow a heuristic way to exploit attention maps for proposal scoring. In order to assign high scores to the proposals of true objects, the attention maps are expected to be aware of the spatial extents of objects, which is also the main focus of previous efforts on WSIS. But unfortunately, this is by nature a very difficult perceptual grouping task, since attention maps can only have very coarse resolution sparsely highlighting some discriminative sites (unaware of object extents). For intuition, we show some exemplary results obtained by the poineering approach of PRM [<a href="#B8-sensors-21-03475" class="html-bibr">8</a>], where (<b>a</b>) is the original image, (<b>b</b>) is the PRM of the <span class="html-italic">cow</span> class, and (<b>c</b>,<b>d</b>) are two proposals and the obtained classification scores. As can be seen, the more favorable proposal in (<b>c</b>) is undesirably assigned with a lower score.</p> Full article ">Figure 2
<p>Overview of the proposed Weakly Supervised R-CNN (WS-RCNN) framework for weakly supervised instance segmentation. WS-RCNN adapts Fast R-CNN (FRCNN) [<a href="#B21-sensors-21-03475" class="html-bibr">21</a>], a representative model for general object detection, to the particular setting of weak supervision, which can be roughly interpretted as to derive pseudo labels from the image-level CNN classifier to initiate the FRCNN. The network mainly consists of two streams, i.e., the proposal scoring stream and the image-level classification stream. The former learns to score proposals, trained by the Entropic Open-Set Loss, and the latter performs pseudo labeling using the Attention-Guided Pseudo Labeling.</p> Full article ">Figure 3
<p>Illustration of the SegAlign operation. SegAlign adapts the widely-used RoIAlign [<a href="#B2-sensors-21-03475" class="html-bibr">2</a>] to segment masks.</p> Full article ">Figure 4
<p>Illustration of Attention-Guided Pseudo Labeling (AGPL). AGPL leverages the localization ability of CNNs and the spatial relationship among proposals to achieve pseudo labeling.</p> Full article ">Figure 5
<p>(<b>a</b>,<b>b</b>) are visualization of two sets of representative proposal scores obtained by various methods. In each set, from top to bottom are the results of PRM [<a href="#B8-sensors-21-03475" class="html-bibr">8</a>], WSDDN-seg [<a href="#B44-sensors-21-03475" class="html-bibr">44</a>] and our WS-RCNN respectively. In each row, the first column is the final WSIS result, and the second to sixth columns are the scores of the five proposals obtained by the method.</p> Full article ">Figure 6
<p>Representative results on VOC obtained by various methods. In each row, from left to right are (<b>a</b>) the input image, (<b>b</b>) the ground truth, and the results of (<b>c</b>) PRM [<a href="#B8-sensors-21-03475" class="html-bibr">8</a>], (<b>d</b>) IRnet [<a href="#B14-sensors-21-03475" class="html-bibr">14</a>], (<b>e</b>) WSDDN-seg [<a href="#B44-sensors-21-03475" class="html-bibr">44</a>] and (<b>f</b>) our WS-RCNN, respectively. Notice that we always output the same number of instances as that in the ground truth for all the methods to enable in-depth comparison.</p> Full article ">Figure 7
<p>Representative results on COCO obtained by various methods. In each row, from left to right are (<b>a</b>) the input image, (<b>b</b>) the ground truth, and the results of (<b>c</b>) PRM [<a href="#B8-sensors-21-03475" class="html-bibr">8</a>], (<b>d</b>) IRnet [<a href="#B14-sensors-21-03475" class="html-bibr">14</a>], (<b>e</b>) WSDDN-seg [<a href="#B44-sensors-21-03475" class="html-bibr">44</a>] and (<b>f</b>) our WS-RCNN, respectively. Notice that we always output the same number of instances as that in the ground truth for all the methods to enable in-depth comparison.</p> Full article ">Figure 8
<p>Impacts of varying the key parameters (<b>a</b>) the number of proposals <span class="html-italic">N</span> and (<b>b</b>) the threshold value <math display="inline"><semantics> <mi>β</mi> </semantics></math> in AGPL.</p> Full article ">Figure 9
<p>Typical failure cases of WS-RCNN. (<b>a</b>) Poor proposals. (<b>b</b>) Picking up large proposals covering multiple instances. (<b>c</b>) Picking up small proposals covering only a part of a instance.</p> Full article ">

11 pages, 3857 KiB  

Open AccessArticle

Analysis of Styrene-Butadiene Based Thermoplastic Magnetorheological Elastomers with Surface-Treated Iron Particles

by Arturo Tagliabue, Fernando Eblagon and Frank Clemens

Polymers 2021, 13(10), 1597; https://doi.org/10.3390/polym13101597 - 15 May 2021

Cited by 17 | Viewed by 2688

Abstract

Magnetorheological elastomers (MRE) are increasing in popularity in many applications because of their ability to change stiffness by applying a magnetic field. Instead of liquid-based 1 K and 2 K silicone, thermoplastic elastomers (TPE), based on styrene-butadiene-styrene block copolymers, have been investigated as [...] Read more.

Magnetorheological elastomers (MRE) are increasing in popularity in many applications because of their ability to change stiffness by applying a magnetic field. Instead of liquid-based 1 K and 2 K silicone, thermoplastic elastomers (TPE), based on styrene-butadiene-styrene block copolymers, have been investigated as matrix material. Three different carbonyl iron particles (CIPs) with different surface treatments were used as magneto active filler material. For the sample fabrication, the thermoplastic pressing method was used, and the MR effect under static and dynamic load was investigated. We show that for filler contents above 40 vol.-%, the linear relationship between powder content and the magnetorheological effect is no longer valid. We showed how the SiO₂ and phosphate coating of the CIPs affects the saturation magnetization and the shear modulus of MRE composites. A combined silica phosphate coating resulted in a higher shear modulus, and therefore, the MR effect decreased, while coating with SiO₂ only improved the MR effect. The highest performance was achieved at low deformations; a static MR effect of 73% and a dynamic MR effect of 126% were recorded. It was also shown that a lower melting viscosity of the TPE matrix helps to increase the static MR effect of anisotropic MREs, while low shear modulus is crucial for achieving high dynamic MR. The knowledge from TPE-based magnetic composites will open up new opportunities for processing such as injection molding, extrusion, and fused deposition modeling (FDM). Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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<p>(<b>a</b>) Warm-pressing of the MRE samples, (<b>b</b>) pre-structuring the MRE sample under magnetic field H, and (<b>c</b>) CPI alignment in the TPE-based MR elastomer.</p> Full article ">Figure 2
<p>(<b>a</b>) Sample preparation in the dynamic mechanical analyzer. (<b>b</b>) A sketch of the sample with applied magnets at the edges of the sample.</p> Full article ">Figure 3
<p>(<b>a</b>) Calculated magnetic field intensity using 1 pair of permanent magnets and (<b>b</b>) the variability of the field across the MRE.</p> Full article ">Figure 4
<p>(<b>a</b>) Static and (<b>b</b>) dynamic tests procedure to investigate the MR effect of SEBS-based composites.</p> Full article ">Figure 5
<p>The influence of the CIP content on the MR effect (<b>a</b>) for the static test, a strain amplitude of 1% and pre-strain of 1.53% was used; (<b>b</b>) for the dynamic test, a strain amplitude of 0.66% was investigated. STL matrix with different concentrations of HS-type CIP; a constant frequency of 10 Hz and field strength of 0.54 T was selected for all tests.</p> Full article ">Figure 6
<p>The torque at the end of the mixing process and density of the SEBS-based composite in relation to the volume concentration of CIP. The red line shows the calculated density based on the mixing rule. The blue line presents the measured density, and the stars are torque measured in Nm.</p> Full article ">Figure 7
<p>The magnetization loop for (<b>a</b>) STL type styrene-ethylene-butadiene-styrene thermoplastic elastomers with HS filler content between 10 and 60 vol.-%, (<b>b</b>) 30 vol.-% filler content of three different CIP grades in STL type styrene-ethylene-butadiene-styrene thermoplastic elastomers.</p> Full article ">Figure 8
<p>The saturation magnetization in relation to the CIP content and extrapolation of the results to 100% carbonyl iron.</p> Full article ">Figure 9
<p>The influence of matrix material during static (<b>a</b>) and dynamic (<b>b</b>) strain on the MR effect. Composites STL30CC and STT30CC were used for this analysis. A constant strain amplitude of 1%was used for the static tests. A constant frequency of 10 Hz and field strength of 0.54 T were used for both test conditions.</p> Full article ">Figure 10
<p>The effect of static (<b>a</b>) and dynamic (<b>b</b>) strain on MR effect. For this investigation, STL30HS, STL30CC, and STL30EW-I composites were used. All samples contain 30 vol.-% CIP in an STL matrix. A constant strain amplitude of 1%was used for the static tests. A constant frequency of 10 Hz and field strength of 0.54 T were used for both test conditions.</p> Full article ">Figure A1
<p>Calculated magnetic field intensity using (<b>a</b>) 2 pairs of permanent magnets and (<b>b</b>) 3 pairs of permanent magnets.</p> Full article ">

22 pages, 5629 KiB  

Open AccessArticle

Analysis of the Main Aspects Affecting Bonding in Stainless Steel Rebars Embedded in a Hydraulic Medium

by Fernando Ancio, Esperanza Rodriguez-Mayorga and Beatriz Hortigon

Metals 2021, 11(5), 786; https://doi.org/10.3390/met11050786 - 12 May 2021

Cited by 4 | Viewed by 2581

Abstract

The use of stainless steel rebars to reinforce masonry structures has become established as an eminently efficient methodology. From among the numerous techniques available, bed-joint structural repointing and superficial reinforcement with rebars or meshes attached to surfaces have become widespread, thanks to the [...] Read more.

The use of stainless steel rebars to reinforce masonry structures has become established as an eminently efficient methodology. From among the numerous techniques available, bed-joint structural repointing and superficial reinforcement with rebars or meshes attached to surfaces have become widespread, thanks to the excellent results they have produced in recent decades. Both techniques imply the use of diameters less than 6 mm and thin coverings. This article deals with the characterization of the bonding behavior of the rebar under these special circumstances. To this end, several finite element analyses have been carried out to identify the possible relationships between pull-out forces in various situations. These models allow certain conclusions to be drawn regarding the influence of the thickness of covering, boundary conditions, and geometrical aspects of the rebars in bonding. Certain mathematical expressions that relate the various conclusions from this research are finally laid out. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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<p>Standard stainless-steel rebar.</p> Full article ">Figure 2
<p>Finite element model for the rebar embedded in a prism of mortar whose base measures 12 mm × 12 mm: (<b>a</b>) model of the rebar; (<b>b</b>) model of the prism of mortar that surrounds the rebar.</p> Full article ">Figure 3
<p>Comparison of the stress-strain behavior of samples of hydraulic mortars obtained in the laboratory (M1 and M3) from literature [<a href="#B39-metals-11-00786" class="html-bibr">39</a>] and analyzed by finite elements for this research (MPlane).</p> Full article ">Figure 4
<p>Values of the reaction force transferred from the bar to the surrounding media (100-mm-edge cube) for a displacement equal to 5 × 10⁻⁵ mm.</p> Full article ">Figure 5
<p>Bond shear stress (MPa) measured at the rebar–mortar interface for a displacement equal to 5 × 10⁻⁵ mm from a 100-mm-edge cube, where maximum bond shear stress and bond tensile stress (both in MPa) were set to (<b>a</b>) 0.10/0.10; (<b>b</b>) 0.10/1.00; (<b>c</b>) 1.00/0.10; (<b>d</b>) 1.00/1.00.</p> Full article ">Figure 6
<p>Diagram depicting the parameterization of samples to set the different mechanical and geometrical characteristics of each of the finite element analyses carried out.</p> Full article ">Figure 7
<p>Displacement (mm) vs. force transferred to the mortar joints by rebars embedded in mortar with 5.6 GPa Young’s modulus and 7.5 mm of effective covering up to failure under two different boundary conditions.</p> Full article ">Figure 8
<p>Bonding stresses (MPa) in the interface of a rebar embedded in a prism of mortar with Young’s modulus of 5.6 GPa and 7.5 mm of effective covering when the base face (face number 1) was fixed. Bonding shear stress distribution when the force transferred from the rebar to the mortar was (<b>a</b>) 40% of that transferred under failure; (<b>b</b>) 60% of that transferred under failure; and (<b>c</b>) 100% of that transferred under failure. Bonding normal stress distribution when the force transferred from the rebar to the mortar was (<b>d</b>) 40% of that transferred under failure; (<b>e</b>) 60% of that transferred under failure; and (<b>f</b>) 100% of that transferred under failure.</p> Full article ">Figure 9
<p>Bonding stresses (MPa) in the interface for a rebar embedded in a prism of mortar with Young’s modulus of 5.6 GPa and 7.5 mm of effective covering when three lateral faces (faces number 2, 3, and 4) were fixed. Bonding shear stress distribution when the force transferred from the rebar to the mortar was (<b>a</b>) 40% of that transferred under failure; (<b>b</b>) 60% of that transferred under failure; and (<b>c</b>) 100% of that transferred under failure. Bonding normal stress distribution when the force transferred from the rebar to the mortar was (<b>d</b>) 40% of that transferred under failure; (<b>e</b>) 60% of that transferred under failure; and (<b>f</b>) 100% of that transferred under failure.</p> Full article ">Figure 10
<p>Geometrical parameters of the rebar that ranged in iterative analyses.</p> Full article ">Figure 11
<p>Chart depicting the reaction force <span class="html-italic">F</span> (N) produced by a 5 × 10⁻⁵ mm displacement of a rebar embedded in mortar prisms with different edges, different Young’s modulus and different boundary conditions: (<b>a</b>) Mortar with Young’s modulus of 5.6 GPa; (<b>b</b>) mortar with Young’s modulus of 10 GPa; (<b>c</b>) mortar with Young’s modulus of 20 GPa; (<b>d</b>) mortar with Young’s modulus of 50 GPa.</p> Full article ">Figure 12
<p>Equivalent strain energy distribution in the mortar joints (E = 5.6 GPa) when face 1 of the prism is fixed and 5 × 10⁻⁵ mm displacement is applied to the base of the rebar: (<b>left</b>) base section of 50 x 50 mm²; (<b>right</b>) base section of 12 × 12 mm².</p> Full article ">Figure 13
<p>Distribution of bond shear stress (MPa) in the interface in a prism of mortar (E = 5.6 MPa) for a displacement equal to 5 × 10⁻⁵ mm when Faces 2, 3, and 4 are fixed, for a prism with dimensions: (<b>a</b>) 12 × 12 mm²; (<b>b</b>) 50 × 50 mm².</p> Full article ">

19 pages, 1793 KiB  

Open AccessArticle

Instrumentalization of a Model for the Evaluation of the Level of Satisfaction of Graduates under an E-Learning Methodology: A Case Analysis Oriented to Postgraduate Studies in the Environmental Field

by Eduardo García Villena, Silvia Pueyo-Villa, Irene Delgado Noya, Kilian Tutusaus Pifarré, Roberto Ruíz Salces and Alina Pascual Barrera

Sustainability 2021, 13(9), 5112; https://doi.org/10.3390/su13095112 - 3 May 2021

Viewed by 2449

Abstract

The purpose of this article was to evaluate the level of satisfaction of a sample of graduates in relation to different online postgraduate programs in the environmental area, as part of the process of continuous improvement in which the educational institution was immersed [...] Read more.

The purpose of this article was to evaluate the level of satisfaction of a sample of graduates in relation to different online postgraduate programs in the environmental area, as part of the process of continuous improvement in which the educational institution was immersed for the renewal of its accreditation before the corresponding official bodies. Based on the bibliographic review of a series of models and tools, a Likert scale measurement instrument was developed. This instrument, once applied and validated, showed a good level of reliability, with more than three quarters of the participants having a positive evaluation of satisfaction. Likewise, to facilitate the relational study, and after confirming the suitability of performing a factor analysis, four variable grouping factors were determined, which explained a good part of the variability of the instrument’s items. As a result of the analysis, it was found that there were significant values of low satisfaction in graduates from the Eurasian area, mainly in terms of organizational issues and academic expectations. On the other hand, it was observed that the methodological aspects of the “Auditing” and “Biodiversity” programs showed higher levels of dissatisfaction than the rest, with no statistically significant relationships between gender, entry profile or age groups. The methodology followed and the rigor in determining the validity and reliability of the instrument, as well as the subsequent analysis of the results, endorsed by the review of the documented information, suggest that the instrument can be applied to other multidisciplinary programs for decision making with guarantees in the educational field. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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<p>Number of accesses and connection hours of different programs of an educational institution. Note. The overprinted circle illustrates the increase in accesses and connection hours to an educational institution’s online programs, starting in the first quarter of 2020.</p> Full article ">Figure 2
<p>Residuals vs. fitted values.</p> Full article ">Figure 3
<p>Frequency distribution of the “level of satisfaction” variable and normal distribution curve (mean = 44.58 and standard deviation = 3.876) overprinted. Note. The lower (42) and upper (47) cut-off values for determining the categories are shown.</p> Full article ">Figure 4
<p>Level of satisfaction referring to methodology by program.</p> Full article ">Figure 5
<p>Level of satisfaction referring to the organization by origin.</p> Full article ">Figure 6
<p>Level of satisfaction referring to academic expectations by origin.</p> Full article ">

12 pages, 2799 KiB  

Open AccessCommunication

Incremental Learning in Modelling Process Analysis Technology (PAT)—An Important Tool in the Measuring and Control Circuit on the Way to the Smart Factory

by Shivani Choudhary, Deborah Herdt, Erik Spoor, José Fernando García Molina, Marcel Nachtmann and Matthias Rädle

Sensors 2021, 21(9), 3144; https://doi.org/10.3390/s21093144 - 1 May 2021

Cited by 1 | Viewed by 2691

Abstract

To meet the demands of the chemical and pharmaceutical process industry for a combination of high measurement accuracy, product selectivity, and low cost of ownership, the existing measurement and evaluation methods have to be further developed. This paper demonstrates the attempt to combine [...] Read more.

To meet the demands of the chemical and pharmaceutical process industry for a combination of high measurement accuracy, product selectivity, and low cost of ownership, the existing measurement and evaluation methods have to be further developed. This paper demonstrates the attempt to combine future Raman photometers with promising evaluation methods. As part of the investigations presented here, a new and easy-to-use evaluation method based on a self-learning algorithm is presented. This method can be applied to various measurement methods and is carried out here using an example of a Raman spectrometer system and an alcohol-water mixture as demonstration fluid. The spectra’s chosen bands can be later transformed to low priced and even more robust Raman photometers. The evaluation method gives more precise results than the evaluation through classical methods like one primarily used in the software package Unscrambler. This technique increases the accuracy of detection and proves the concept of Raman process monitoring for determining concentrations. In the example of alcohol/water, the computation time is less, and it can be applied to continuous column monitoring. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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Figure 1
<p>Experimental setup of Raman measurement.</p> Full article ">Figure 2
<p>Schematic representation of the incremental learning ensemble classifier (altered from [<a href="#B20-sensors-21-03144" class="html-bibr">20</a>]).</p> Full article ">Figure 3
<p>Raman spectra of water and ethanol with evaluated intervals.</p> Full article ">Figure 4
<p>Raman spectra of ethanol dilution series (sample number 1–9).</p> Full article ">Figure 5
<p>Comparison of the accuracy from The Unscrambler X and the MATLAB code.</p> Full article ">

29 pages, 15098 KiB  

Open AccessArticle

KEYme: Multifunctional Smart Toy for Children with Autism Spectrum Disorder

by Raquel Cañete, Sonia López and M. Estela Peralta

Sustainability 2021, 13(7), 4010; https://doi.org/10.3390/su13074010 - 3 Apr 2021

Cited by 5 | Viewed by 7341

Abstract

The role that design engineering plays in the quality of life and well-being of people with autism spectrum disorder around the world is extremely relevant; products are highly helpful when used as “intermediaries” in social interactions, as well as in the reinforcement of [...] Read more.

The role that design engineering plays in the quality of life and well-being of people with autism spectrum disorder around the world is extremely relevant; products are highly helpful when used as “intermediaries” in social interactions, as well as in the reinforcement of cognitive, motor and sensory skills. One of the most significant challenges engineers have to face lies in the complexity of defining those functional requirements of objects that will efficiently satisfy the specific needs of children with autism within a single product. Furthermore, despite the growing trends that point toward the integration of new technologies in the creation of toys for typically developing children, the variety of specialized smart products aimed at children with autism spectrum disorder is very limited. Based on this evidence the KEYme project was created, where a multifunctional smart toy is developed as a reinforcement system for multiple needs which is adaptable to different kinds of autism for therapies, educational centers or family environments. This approach involves the knowledge transfer from the latest neuroscience, medicine and psychology contributions to the engineering and industrial design field. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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Figure 1
<p>Application of USERfit in design project planning.</p> Full article ">Figure 2
<p>Product design methodology.</p> Full article ">Figure 3
<p>Generation and selection of design alternatives.</p> Full article ">Figure 4
<p>Product Structure.</p> Full article ">Figure 5
<p>Anthropometric requirements: (<b>1</b>) stature (body height); (<b>2</b>) shoulder (bideltoid) breadth; (<b>3</b>) hip breadth, sitting; (<b>4</b>) elbow height, erect and sitting; (<b>5</b>) sitting height (erect); (<b>6</b>) lower leg length (popliteal height); (<b>7</b>) body height, sitting; (<b>8</b>) buttock-popliteal length; (<b>9</b>) hand measurement (circumferences, breadths, palm length, middle finger length, proximal phalanx length of middle finger, finger grip and hand grasp); and body mass (weight).</p> Full article ">Figure 6
<p>Interface components and usability analysis of the different game modes.</p> Full article ">Figure 7
<p>Color Selection.</p> Full article ">Figure 8
<p>KEYme validation prototype.</p> Full article ">Figure 9
<p>Wiring diagrams for sub-game 2.1.</p> Full article ">Figure 10
<p>Integration of KEYme in different contexts of use.</p> Full article ">

17 pages, 6975 KiB  

Open AccessArticle

Experimental and Numerical Study on the Flexural Performance of Assembled Steel-Wood Composite Slab

by Guodong Li, Zhibin Liu, Wenjia Tang, Dongpo He and Wei Shan

Sustainability 2021, 13(7), 3814; https://doi.org/10.3390/su13073814 - 30 Mar 2021

Cited by 4 | Viewed by 2317

Abstract

This paper presents research on a new type of fabricated steel–wood composite floor material in the style of a slab-embedded beam flange, using test methods and finite element numerical analysis to study the flexural load-bearing performance of the composite slabs. Through experimental phenomena, [...] Read more.

This paper presents research on a new type of fabricated steel–wood composite floor material in the style of a slab-embedded beam flange, using test methods and finite element numerical analysis to study the flexural load-bearing performance of the composite slabs. Through experimental phenomena, the failure process and mechanism of the composite floor are analyzed, and the deformation performance and ultimate bearing capacity of the composite floor material are assessed. Through numerical analysis of the finite element model, the influence of the connection mode of the floor and the composite beam, the type and number of connectors, and the width of the flange of the composite beam on the bending performance of the composite beam–slab system is studied. The research results show that the fabricated steel–wood composite floor slab has good load-bearing and deformation performance. The self-tapping screw connection of the floor slab is better than the ordinary steel nail connection, and the reasonable screw spacing is 100–150 mm. Increasing the flange width of the composite beam can significantly improve the load-bearing capacity of the steel–wood composite floor component. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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Figure 1
<p>Schematic diagram of multi-span continuous plate–beam system and simplified model. (<b>a</b>) 1-1 Multi-span continuous beam-and-slab system; (<b>b</b>) simplified model (mm).</p> Full article ">Figure 2
<p>Schematic diagram of steel–wood composite beam section (mm).</p> Full article ">Figure 3
<p>(<b>a</b>) 1-1 section picture of the prefabricated steel–wood composite floor test piece; (<b>b</b>) structure drawing of the composite floor test piece (mm).</p> Full article ">Figure 4
<p>(<b>a</b>) Diagram of loading device for compression test of glulam prism. (<b>b</b>) Tensile test of glulam specimen. (<b>c</b>) Destruction phenomenon of steel tensile test.</p> Full article ">Figure 5
<p>Layout of measuring points for bending test of steel–wood composite floor. The strain sensors were attached to the measuring point tightly and the displacement sensors were fixed at the measuring point. (<b>a</b>) Plan view of combined floor measuring points; (<b>b</b>) elevation view of OSB measuring points. (<b>c</b>) Elevation view of composite beam measuring point (mm).</p> Full article ">Figure 6
<p>Failure phenomenon of ZHLB-1 test. (<b>a</b>) Bending deformation of steel–wood composite floor; (<b>b</b>) vertical cracks appear on the left flange of glulam; (<b>c</b>) glued wood laminates are broken; (<b>d</b>) the iron nails connected to the glulam laminate are pulled out.</p> Full article ">Figure 7
<p>Failure phenomenon of ZHLB-2 test. (<b>a</b>) Vertical cracks appear in the flange of glued wood; (<b>b</b>) the flange on one side of the glulam span is pulled off along the plywood; (<b>c</b>) cracks and deformation of glulam bearings; (<b>d</b>) gluing failure of steel-wood cementing surface as a whole.</p> Full article ">Figure 8
<p>Mid-span load–deflection curve of composite floor specimen.</p> Full article ">Figure 9
<p>Steel–wood composite floor section mid–span height–strain curve. (<b>a</b>) ZHLB–1 section mid–span height–strain curve; (<b>b</b>) ZHLB–2 section mid–span height–strain curve.</p> Full article ">Figure 10
<p>ZHLB–1 mid–span load–strain curve. (<b>a</b>) Load–strain curve of steel–wood composite beam; (<b>b</b>) load–strain curve of OSB and glulam beam. G7, G8, G9: Corresponding curves of strain measuring points 7, 8 and 9 for thin–walled steel; M3, M4, M5, M6: Corresponding curve of glulam strain measuring points 3, 4, 5 and 6; OSB1, OSB2: Corresponding curve of OSB plate strain measuring points 1 and 2.</p> Full article ">Figure 11
<p>ZHLB–2 mid–span load–strain curve. (<b>a</b>) Mid–span load–strain curve of steel and wood composite beams; (<b>b</b>) mid–span load–strain curve of OSB slab and glued timber beam. G7, G8, G9: Corresponding curves of strain measuring points 7, 8 and 9 for thin–walled steel; M3, M4, M5, M6: Corresponding curve of glulam strain measuring points 3, 4, 5 and 6; OSB1, OSB2: Corresponding curve of OSB plate strain measuring points 1 and 2.</p> Full article ">Figure 12
<p>Grid division of composite floor.</p> Full article ">Figure 13
<p>Stress–field nephogram of ZHLB–2 specimen. (<b>a</b>) Combined floor deformation stress–field nephogram. (<b>b</b>) Stress–field nephogram of thin–walled steel beam; (<b>c</b>) stress–field nephogram of glulam beams; (<b>d</b>) OSB plate stress–field nephogram; (<b>e</b>) extruded board + glued wood stress–field nephogram.</p> Full article ">Figure 14
<p>Comparison of ZHLB-2 specimen and finite element test results.</p> Full article ">Figure 15
<p>Comparison of finite element test results of different self-tapping screw spacings.</p> Full article ">Figure 16
<p>Comparison of finite element test results of different glulam flange widths.</p> Full article ">

12 pages, 7209 KiB  

Open AccessArticle

Assessment of Fennel Oil Microfluidized Nanoemulsions Stabilization by Advanced Performance Xanthan Gum

by Rubén Llinares, Pablo Ramírez, José Antonio Carmona, Luis Alfonso Trujillo-Cayado and José Muñoz

Foods 2021, 10(4), 693; https://doi.org/10.3390/foods10040693 - 24 Mar 2021

Cited by 11 | Viewed by 2823

Abstract

In this work, nanoemulsion-based delivery system was developed by encapsulation of fennel essential oil. A response surface methodology was used to study the influence of the processing conditions in order to obtain monomodal nanoemulsions of fennel essential oil using the microchannel homogenization technique. [...] Read more.

In this work, nanoemulsion-based delivery system was developed by encapsulation of fennel essential oil. A response surface methodology was used to study the influence of the processing conditions in order to obtain monomodal nanoemulsions of fennel essential oil using the microchannel homogenization technique. Results showed that it was possible to obtain nanoemulsions with very narrow monomodal distributions that were homogeneous over the whole observation period (three months) when the appropriate mechanical energy was supplied by microfluidization at 14 MPa and 12 passes. Once the optimal processing condition was established, nanoemulsions were formulated with advanced performance xanthan gum, which was used as both viscosity modifier and emulsion stabilizer. As a result, more desirable results with enhanced physical stability and rheological properties were obtained. From the study of mechanical spectra as a function of aging time, the stability of the nanoemulsions weak gels was confirmed. The mechanical spectra as a function of hydrocolloid concentration revealed that the rheological properties are marked by the biopolymer network and could be modulated depending on the amount of added gum. Therefore, this research supports the role of advanced performance xanthan gum as a stabilizer of microfluidized fennel oil-in-water nanoemulsions. In addition, the results of this research could be useful to design and formulate functional oil-in-water nanoemulsions with potential application in the food industry for the delivery of nutraceuticals and antimicrobials. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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<p>(<b>A</b>) Droplet mean diameters and (<b>B</b>) polydispersity index values for emulsions aged for 24 h as a function of the number of passes and homogenization pressure. Vertical bars indicate standard deviation of the mean (three replicates).</p> Full article ">Figure 2
<p>Droplet size distributions for emulsions aged for 24 h as a function of (<b>A</b>) the number of passes at a fixed homogenization pressure of 140 MPa and (<b>B</b>) homogenization pressure processed at a fixed number of passes of 18.</p> Full article ">Figure 3
<p>Response surface 3D plot of (<b>A</b>) droplet mean diameter and (<b>B</b>) polydispersity index as a function of the number of passes and homogenization pressure for emulsions aged for 24 h.</p> Full article ">Figure 4
<p>Storage (G’) and loss (G’’) moduli at 1 Hz as a function of shear stress for the fennel oil nanoemulsion with 0.70 g/100 g of the AP xanthan gum. Standard deviation of the mean (three replicates) for all the data are below 5%. (T = 20 °C).</p> Full article ">Figure 5
<p>Mechanical spectra for fennel oil nanoemulsions with different xanthan gum concentration at 20 °C. Data shown are the average values of three replicates. The standard deviation for all the experiments was lower than 5%.</p> Full article ">Figure 6
<p>Mechanical spectra as a function of aging time for fennel oil nanoemulsion formulated with advanced performance xanthan gum (0.70 g/100 g) at 20 °C. Data shown are the average values of three replicates. The standard deviation of for all the experiments was lower than 5%.</p> Full article ">Figure 7
<p>Steady state viscosity as a function of shear rate for the fennel oil nanoemulsion with different AP xanthan gum concentrations at 20 °C. The lines are the best fit to the Carreau model, whose parameters are given in <a href="#foods-10-00693-t002" class="html-table">Table 2</a>. Data shown are the average value of three replicates with a standard deviation for all the experiments lower than 10%.</p> Full article ">Figure 8
<p>Representative Cryo-SEM micrographs for (<b>A</b>) the emulsion formulated with 0.25 g/100 g of advanced performance xanthan gum and (<b>B</b>) an aqueous solution that contains 0.25 g/100 g of advanced performance xanthan gum.</p> Full article ">

attachment

Supplementary material:
Supplementary File 1 (PDF, 76 KiB)

15 pages, 2877 KiB  

Open AccessArticle

Total Saponins Isolated from Corni Fructus via Ultrasonic Microwave-Assisted Extraction Attenuate Diabetes in Mice

by Shujing An, Dou Niu, Ting Wang, Binkai Han, Changfen He, Xiaolin Yang, Haoqiang Sun, Ke Zhao, Jiefang Kang and Xiaochang Xue

Foods 2021, 10(3), 670; https://doi.org/10.3390/foods10030670 - 22 Mar 2021

Cited by 15 | Viewed by 4203

Abstract

Saponins have been extensively used in the food and pharmaceutical industries because of their potent bioactive and pharmacological functions including hypolipidemic, anti-inflammatory, expectorant, antiulcer and androgenic properties. A lot of saponins-containing foods are recommended as nutritional supplements for diabetic patients. As a medicine [...] Read more.

Saponins have been extensively used in the food and pharmaceutical industries because of their potent bioactive and pharmacological functions including hypolipidemic, anti-inflammatory, expectorant, antiulcer and androgenic properties. A lot of saponins-containing foods are recommended as nutritional supplements for diabetic patients. As a medicine and food homologous material, Corni Fructus (CF) contains various active ingredients and has the effect of treating diabetes. However, whether and how CF saponins attenuate diabetes is still largely unknown. Here, we isolated total saponins from CF (TSCF) using ultrasonic microwave-assisted extraction combined with response surface methodology. The extract was further purified by a nonpolar copolymer styrene type macroporous resin (HPD-300), with the yield of TSCF elevated to 13.96 mg/g compared to 10.87 mg/g obtained via unassisted extraction. When used to treat high-fat diet and streptozotocin-induced diabetic mice, TSCF significantly improved the glucose and lipid metabolisms of T2DM mice. Additionally, TSCF clearly ameliorated inflammation and oxidative stress as well as pancreas and liver damages in the diabetic mice. Mechanistically, TSCF potently regulated insulin receptor (INSR)-, glucose transporter 4 (GLUT4)-, phosphatidylinositol 3-kinase (PI3K)-, and protein kinase B (PKB/AKT)-associated signaling pathways. Thus, our data collectively demonstrated that TSCF could be a promising functional food ingredient for diabetes improvement. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic diagram of the experimental process. i.p., intraperitoneal injection; i.g., intragastric administration; HFD, high-fat diet; OGTT, oral glucose tolerance test; FBG, fasting blood glucose; STZ, streptozotocin; NC, normal control group; DM, diabetes mellitus model group; PC, positive (metformin-treated) control group; TSCF, total saponins from Corni Fructus; TSCF-L, low-dose TSCF group; TSCF-M, middle-dose TSCF group; TSCF-H, high-dose TSCF group.</p> Full article ">Figure 2
<p>Screening of the variable factors that affect TSCF extraction yield. TSCF was extracted under certain conditions, including solid/liquid ratio (<b>A</b>), ultrasonic power (<b>B</b>), microwave power (<b>C</b>), and extraction time (<b>D</b>), and the extraction yield was determined.</p> Full article ">Figure 3
<p>Three-dimensional response surface plot for TSCF production. The contour plots showed the interactive effects of the solid/liquid ratio and microwave power (<b>A</b>), solid/liquid ratio and ultrasonic power (<b>B</b>), solid/liquid ratio and extraction time (<b>C</b>), microwave power and ultrasonic power (<b>D</b>), microwave power and extraction time (<b>E</b>), and ultrasonic power and extraction time (<b>F</b>), respectively.</p> Full article ">Figure 4
<p>Effects of TSCF on the organ indexes of diabetic mice. (<b>A</b>) Liver index; (<b>B</b>) kidney index; (<b>C</b>) spleen index. NC, normal control group; DM, diabetic mice treated with PBS; PC, diabetic mice treated with 100 mg/kg metformin each day; TSCF-L, TSCF-M, and TSCF-H, diabetic mice treated with 50, 100, and 200 mg/kg TSCF each day. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 compared with the NC group; ^Δ <span class="html-italic">p</span> &lt; 0.05, ^ΔΔ <span class="html-italic">p</span> &lt; 0.01, compared with the DM group.</p> Full article ">Figure 5
<p>Effects of TSCF on glycemic modulation of T2DM mice. (<b>A</b>) FBG; (<b>B</b>) OGTT; (<b>C</b>) AUC; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 compared with the NC group; ^Δ <span class="html-italic">p</span> &lt; 0.05, ^ΔΔ <span class="html-italic">p</span> &lt; 0.01 compared with the DM group.</p> Full article ">Figure 6
<p>Effects of TSCF on inflammation and oxidative stress in T2DM mice. Sera of diabetic mice were prepared and (<b>A</b>) IL-6, (<b>B</b>) TNF-α, (<b>C</b>) CRP, (<b>D</b>) MDA, and (<b>E</b>) SOD levels were measured. NC, normal control group; DM, T2DM model group; PC, Metformin group; TSCF-L, TSCF-M, and TSCF-H, diabetes mice treated with 50 mg/kg, 100 mg/kg and 200 mg/kg TSCF per day, respectively. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 compared with NC group; ^Δ <span class="html-italic">p</span> &lt; 0.05, ^ΔΔ <span class="html-italic">p</span> &lt; 0.01 compared with DM group.</p> Full article ">Figure 7
<p>Histopathological changes of diabetic mice treated with TSCF. Pancreas (<b>A</b>) and liver (<b>B</b>) tissues were isolated from diabetic mice and H&amp;E staining was performed according to standard methods. Apoptotic hepatocytes (black arrow), focal mononuclear cell aggregation (red arrow), diffuse hydropic degeneration (black arrowheads), fatty change (red arrowheads). NC, normal control group; DM, T2DM model group; PC, Metformin group; TSCF-L, TSCF-M, and TSCF-H, diabetes mice treated with 50, 100 and 200 mg/kg TSCF per day, respectively. Bar = 100 μm.</p> Full article ">Figure 8
<p>The effects of TSCF on MDA (<b>A</b>) INSR, (<b>B</b>) GLUT4, (<b>C</b>) PI3K, and (<b>D</b>) AKT signaling pathways in T2DM mice. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 compared with NC group; ^△ <span class="html-italic">p</span> &lt; 0.05, ^△△ <span class="html-italic">p</span> &lt; 0.01 compared with DM group.</p> Full article ">

18 pages, 6875 KiB  

Open AccessFeature PaperArticle

Synergistic Effect of rhBMP-2 Protein and Nanotextured Titanium Alloy Surface to Improve Osteogenic Implant Properties

by Andrea Mesa-Restrepo, Ana Civantos, Jean Paul Allain, Edwin Patiño, Juan Fernando Alzate, Norman Balcázar, Robinson Montes, Juan José Pavón, José Antonio Rodríguez-Ortiz and Yadir Torres

Metals 2021, 11(3), 464; https://doi.org/10.3390/met11030464 - 11 Mar 2021

Cited by 7 | Viewed by 2789

Abstract

One of the major limitations during titanium (Ti) implant osseointegration is the poor cellular interactions at the biointerface. In the present study, the combined effect of recombinant human Bone Morphogenetic Protein-2 (rhBMP-2) and nanopatterned Ti6Al4V fabricated with Directed irradiation synthesis (DIS) is investigated [...] Read more.

One of the major limitations during titanium (Ti) implant osseointegration is the poor cellular interactions at the biointerface. In the present study, the combined effect of recombinant human Bone Morphogenetic Protein-2 (rhBMP-2) and nanopatterned Ti6Al4V fabricated with Directed irradiation synthesis (DIS) is investigated in vitro. This environmentally-friendly plasma uses ions to create self-organized nanostructures on the surfaces. Nanocones (≈36.7 nm in DIS 80°) and thinner nanowalls (≈16.5 nm in DIS 60°) were fabricated depending on DIS incidence angle and observed via scanning electron microscopy. All samples have a similar crystalline structure and wettability, except for sandblasted/acid-etched (SLA) and acid-etched/anodized (Anodized) samples which are more hydrophilic. Biological results revealed that the viability and adhesion properties (vinculin expression and cell spreading) of DIS 80° with BMP-2 were similar to those polished with BMP-2, yet we observed more filopodia on DIS 80° (≈39 filopodia/cell) compared to the other samples (<30 filopodia/cell). BMP-2 increased alkaline phosphatase activity in all samples, tending to be higher in DIS 80°. Moreover, in the mineralization studies, DIS 80° with BMP-2 and Anodized with BMP-2 increased the formation of calcium deposits (>3.3 fold) compared to polished with BMP-2. Hence, this study shows there is a synergistic effect of BMP-2 and DIS surface modification in improving Ti biological properties which could be applied to Ti bone implants to treat bone disease. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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<p>Schematic design of materials and methods of this research study. (<b>a</b>) surface characterization and (<b>b</b>) biological characterization. Abbreviations: Scanning electron microscopy (SEM), X-ray diffraction (XRD), Alkaline Phosphatase (ALP), NoBMP (without BMP-2 protein), BMP (with BMP-2 protein), DIS 60° (Ti6Al4V irradiated using argon ions and 60 incidence angle), DIS 80° (Ti6Al4V irradiated using argon ions and 80 incidence angle), Sandblasted and acid etched Ti6Al4V (SLA), Acid etched and anodized Ti6Al4V (Anodized).</p> Full article ">Figure 2
<p>Scanning electron micrographs of modified Ti samples, white arrows indicate nanostructures.</p> Full article ">Figure 3
<p>XRD pattern of modified Ti samples. Black arrows indicate (110) β peak.</p> Full article ">Figure 4
<p>Determination of hydrophilicity/hydrophobicity of Ti samples by contact angle measurement. Mean + SE, N = 3 * <span class="html-italic">p</span>-values &lt; 0.05 compared to polished, DIS 60° and DIS 80°.</p> Full article ">Figure 5
<p>Evaluation of cell morphology on Ti alloy surfaces with and without the incorporation of BMP-2. (<b>a</b>) SEM micrographs of C2C12 cultured on modified Ti samples for 4 h, white arrows indicate filopodia prolongations (<b>b</b>) Filopodia number quantification. Median and IQR, N = 3 fields.</p> Full article ">Figure 6
<p>Determination of cellular attachment. (<b>a</b>) Confocal microscopy images of C2C12 cells cultured on Ti samples with and without the incorporation of BMP-2. Vinculin protein was stained green (white arrows), actin filaments in red and cell nuclei in blue; (<b>b</b>) Vinculin mean grey value of samples with and without the incorporation of BMP-2 normalized to total cells. Mean + SE N = 5 fields, *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.001, * <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 7
<p>Cell spreading. (<b>a</b>) Confocal microscopy of C2C12 cultured on Ti samples with and without the incorporation of BMP-2. The cytoskeleton actin filaments were stained red and nuclei blue; (<b>b</b>) Cell area measured by FIJI software. Mean + SE, N = 3 fields, * <span class="html-italic">p</span> &lt; 0.05; (<b>c</b>) Nucleus area. Mean + SE, N &lt; 3 fields.</p> Full article ">Figure 8
<p>Relative C2C12 viability on Ti samples with and without the incorporation of BMP-2 normalized to polished without BMP-2 after 3 days in culture. Mean + SE, N = 3.</p> Full article ">Figure 9
<p>C2C12 osteoblast differentiation and mineralization. (<b>a</b>) ALP production after 3 days on Ti samples with and without the incorporation of BMP-2. Mean + SE, N = 3, *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.001, * <span class="html-italic">p</span> &lt; 0.05; (<b>b</b>) Cell mineralization. Cell culture with mineralization media on Ti sample with and without the incorporation of BMP-2, black bar indicates 0.5 cm (left panel), quantification of mineralization area compared to the culture area of samples with BMP-2 (right panel). Mean + SD, N = 3 fields.</p> Full article ">

17 pages, 4245 KiB  

Open AccessArticle

A Straightforward and Efficient Instance-Aware Curved Text Detector

by Fan Zhao, Sidi Shao, Lin Zhang and Zhiquan Wen

Sensors 2021, 21(6), 1945; https://doi.org/10.3390/s21061945 - 10 Mar 2021

Cited by 2 | Viewed by 2753

Abstract

A challenging aspect of scene text detection is to handle curved texts. In order to avoid the tedious manual annotations for training curve text detector, and to overcome the limitation of regression-based text detectors to irregular text, we introduce straightforward and efficient instance-aware [...] Read more.

A challenging aspect of scene text detection is to handle curved texts. In order to avoid the tedious manual annotations for training curve text detector, and to overcome the limitation of regression-based text detectors to irregular text, we introduce straightforward and efficient instance-aware curved scene text detector, namely, look more than twice (LOMT), which makes the regression-based text detection results gradually change from loosely bounded box to compact polygon. LOMT mainly composes of curve text shape approximation module and component merging network. The shape approximation module uses a particle swarm optimization-based text shape approximation method (called PSO-TSA) to fine-tune the quadrilateral text detection results to fit the curved text. The component merging network merges incomplete text sub-parts of text instances into more complete polygon through instance awareness, called ICMN. Experiments on five text datasets demonstrate that our method not only achieves excellent performance but also has relatively high speed. Ablation experiments show that PSO-TSA can solve the text’s shape optimization problem efficiently, and ICMN has a satisfactory merger effect. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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<p>Illustration of the overall pipeline, (<b>a</b>) proposal detection module, (<b>b</b>) CCs extraction module, (<b>c</b>) shape approximation module and (<b>d</b>) component merging module.</p> Full article ">Figure 2
<p>The framework of the PSO-TSA algorithm, (<b>a</b>) particle initialization process, (<b>b</b>) generating polygon by once approximation, (<b>c</b>) generating polygon by optimal approximation.</p> Full article ">Figure 3
<p>ICMN architecture.</p> Full article ">Figure 4
<p>Some qualitative results of the proposed method on IC15 (<b>a</b>), IC17 (<b>b</b>), and TD500 (<b>c</b>).</p> Full article ">Figure 5
<p>Some qualitative results of the proposed method on Total-Text.</p> Full article ">Figure 6
<p>Comparison results of several methods, (<b>a</b>) CTD + TOLC [<a href="#B8-sensors-21-01945" class="html-bibr">8</a>], (<b>b</b>) CRAFT [<a href="#B34-sensors-21-01945" class="html-bibr">34</a>], and (<b>c</b>) LOMT.</p> Full article ">Figure 7
<p>Some qualitative results of the proposed method on CTW1500.</p> Full article ">

21 pages, 5296 KiB  

Open AccessArticle

AnkFall—Falls, Falling Risks and Daily-Life Activities Dataset with an Ankle-Placed Accelerometer and Training Using Recurrent Neural Networks

by Francisco Luna-Perejón, Luis Muñoz-Saavedra, Javier Civit-Masot, Anton Civit and Manuel Domínguez-Morales

Sensors 2021, 21(5), 1889; https://doi.org/10.3390/s21051889 - 8 Mar 2021

Cited by 22 | Viewed by 3775

Abstract

Falls are one of the leading causes of permanent injury and/or disability among the elderly. When these people live alone, it is convenient that a caregiver or family member visits them periodically. However, these visits do not prevent falls when the elderly person [...] Read more.

Falls are one of the leading causes of permanent injury and/or disability among the elderly. When these people live alone, it is convenient that a caregiver or family member visits them periodically. However, these visits do not prevent falls when the elderly person is alone. Furthermore, in exceptional circumstances, such as a pandemic, we must avoid unnecessary mobility. This is why remote monitoring systems are currently on the rise, and several commercial solutions can be found. However, current solutions use devices attached to the waist or wrist, causing discomfort in the people who wear them. The users also tend to forget to wear the devices carried in these positions. Therefore, in order to prevent these problems, the main objective of this work is designing and recollecting a new dataset about falls, falling risks and activities of daily living using an ankle-placed device obtaining a good balance between the different activity types. This dataset will be a useful tool for researchers who want to integrate the fall detector in the footwear. Thus, in this work we design the fall-detection device, study the suitable activities to be collected, collect the dataset from 21 users performing the studied activities and evaluate the quality of the collected dataset. As an additional and secondary study, we implement a simple Deep Learning classifier based on this data to prove the system’s feasibility. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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Figure 1
<p>Wearable acquisition device: (<b>a</b>) wearable device placed in the ankle; (<b>b</b>) firmware’s state machine.</p> Full article ">Figure 2
<p>Monitoring application and videoclip during a Fall event recording sequence (in order, from step 1 to 6).</p> Full article ">Figure 3
<p>Long Short-Term Memory (LSTM) (<b>a</b>) and Gated Recurrent Units (GRU) (<b>b</b>) units.</p> Full article ">Figure 4
<p>Diagram of the Gated RNN architectures assessed.</p> Full article ">Figure 5
<p>Labelling criteria based on occurrence percentage in each block.</p> Full article ">Figure 6
<p>Resulting dataset.</p> Full article ">Figure 7
<p>AnkFall internal structure: (<b>a</b>) Folder structure; (<b>b</b>) Data collected from user 21 during activity 10, repetition 1; (<b>c</b>) Labels for each sample of data collected during activity “(<b>b</b>)”.</p> Full article ">Figure 8
<p>Confusion matrices for best LSTM and GRU models. Each specific box in the confusion matrix represents the percentage of samples of the class indicated by the row that have been classified as the class indicated in the column.</p> Full article ">Figure 9
<p>ROC curves for best LSTM and GRU hmodels.</p> Full article ">

12 pages, 12231 KiB  

Open AccessArticle

Strengthening of Porcine Plasma Protein Superabsorbent Materials through a Solubilization-Freeze-Drying Process

by Estefanía Álvarez-Castillo, Carlos Bengoechea and Antonio Guerrero

Polymers 2021, 13(5), 772; https://doi.org/10.3390/polym13050772 - 3 Mar 2021

Cited by 3 | Viewed by 2218

Abstract

The replacement of common acrylic derivatives by biodegradable materials in the formulation of superabsorbent materials would lessen the associated environmental impact. Moreover, the use of by-products or biowastes from the food industry that are usually discarded would promote a desired circular economy. The [...] Read more.

The replacement of common acrylic derivatives by biodegradable materials in the formulation of superabsorbent materials would lessen the associated environmental impact. Moreover, the use of by-products or biowastes from the food industry that are usually discarded would promote a desired circular economy. The present study deals with the development of superabsorbent materials based on a by-product from the meat industry, namely plasma protein, focusing on the effects of a freeze-drying stage before blending with glycerol and eventual injection molding. More specifically, this freeze-drying stage is carried out either directly on the protein flour or after its solubilization in deionized water (10% w/w). Superabsorbent materials obtained after this solubilization-freeze-drying process display higher Young’s modulus and tensile strength values, without affecting their water uptake capacity. As greater water uptake is commonly related to poorer mechanical properties, the proposed solubilization-freeze-drying process is a useful strategy for producing strengthened hydrophilic materials. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Torque and temperature profile developed within the mixer cavity during the mixing stage for porcine plasma protein-glycerol blends using UF, FD, and SFD protein systems.</p> Full article ">Figure 2
<p>Evolution of the compressional storage modulus (E′) and loss tangent (tan δ) of blends from porcine plasma protein (PPP) and glycerol materials using UF, FD, and SFD protein systems, obtained through temperature sweep tests ranging from 30 to 140 °C at 1 Hz within the lineal viscoelastic range.</p> Full article ">Figure 3
<p>DSC thermograms for the UF and SFD porcine plasma protein systems run at a heating rate of 10 °C/min.</p> Full article ">Figure 4
<p>Evolution of the storage (G′) and viscous (G″) moduli in torsion mode for porcine plasma protein-glycerol materials using UF, FD, and SFD protein systems, obtained through temperature sweep tests from 30 to 140 °C at 1 Hz within the lineal viscoelastic range.</p> Full article ">Figure 5
<p>Mechanical parameters of porcine plasma protein-glycerol materials using UF, FD, and SFD protein systems, obtained through uniaxial tensile tests at a deformation rate of 1 mm/s. Average values marked with different lower-case or upper-case Greek letters are statistically different (<span class="html-italic">p</span> &lt; 0.05).</p> Full article ">Figure 6
<p>Proposed scheme for the main interactions promoted when protein unfolding takes place.</p> Full article ">Figure 7
<p>Water uptake capacities of porcine plasma protein-glycerol materials using UF, FD, or SFD protein systems, obtained through deionized water immersion over 24 h. The dashed line indicates the superabsorbent threshold. Average values marked with different lower-case Greek letters are statistically different (<span class="html-italic">p</span> &lt; 0.05).</p> Full article ">Figure 8
<p>SEM micrographs of matrices obtained after swelling and freeze-drying of injection-molded reference (<b>A</b>), FD (<b>B</b>), and SFD (<b>C</b>) porcine plasma protein samples.</p> Full article ">

24 pages, 4657 KiB  

Open AccessArticle

Superficial Characteristics and Functionalization Effectiveness of Non-Toxic Glutathione-Capped Magnetic, Fluorescent, Metallic and Hybrid Nanoparticles for Biomedical Applications

by C. Fernández-Ponce, J. M. Mánuel, R. Fernández-Cisnal, E. Félix, J. Beato-López, J. P. Muñoz-Miranda, A. M. Beltrán, A. J. Santos, F. M. Morales, M. P. Yeste, O. Bomati-Miguel, R. Litrán and F. García-Cózar

Metals 2021, 11(3), 383; https://doi.org/10.3390/met11030383 - 26 Feb 2021

Cited by 5 | Viewed by 2697

Abstract

An optimal design of nanoparticles suitable for biomedical applications requires proper functionalization, a key step in the synthesis of such nanoparticles, not only for subsequent crosslinking to biological targets and to avoid cytotoxicity, but also to endow these materials with colloidal stability. In [...] Read more.

An optimal design of nanoparticles suitable for biomedical applications requires proper functionalization, a key step in the synthesis of such nanoparticles, not only for subsequent crosslinking to biological targets and to avoid cytotoxicity, but also to endow these materials with colloidal stability. In this sense, a reliable characterization of the effectiveness of the functionalization process would, therefore, be crucial for subsequent bioconjugations. In this work, we have analyzed glutathione as a means to functionalize four of the most widely used nanoparticles in biomedicine, one of which is a hybrid gold-magnetic-iron-oxide nanoparticle synthetized by a simple and novel method that we propose in this article. We have analyzed the colloidal characteristics that the glutathione capping provides to the different nanoparticles and, using information on the Z-potential, we have deduced the chemical group used by glutathione to link to the nanoparticle core. We have used electron microscopy for further structural and chemical characterization of the nanoparticles. Finally, we have evaluated nanoparticle cytotoxicity, studying cell viability after incubation with different concentrations of nanoparticles, showing their suitability for biomedical applications. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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Figure 1
<p>Diagram of the glutathione (GSH)-capped hybrid gold/iron oxide magnetic nanoparticles (NPs).</p> Full article ">Figure 2
<p>High-angle annular dark field (HAADF) image (<b>a</b>), as well as the histogram displaying particle size distribution (<b>b</b>) of Au-GSH NPs. (<b>c</b>) UV-Visible absorption spectrum and PL emission spectrum (<b>d</b>) of Au-GSH NPs. The inset in <a href="#metals-11-00383-f002" class="html-fig">Figure 2</a>c shows a digital photo image of an Au-GSH colloidal solution.</p> Full article ">Figure 3
<p>Bright field TEM (BF-TEM) micrograph (<b>a</b>), as well as the histogram displaying the particle size distribution (<b>b</b>) of Mag-GSH NPs. Magnetization curve of Mag-GSH NPs (<b>c</b>). The inset in this figure shows a digital photo image of Mag-GSH NPs placed in the absence and presence of a magnet located close to the vials.</p> Full article ">Figure 4
<p>HAADF image (<b>a</b>), as well as the histogram displaying particle size distribution (<b>b</b>) of quantum dot (QD)-GSH1 NPs. (<b>c</b>) PL-emission spectra for QD-GSH1 (blue) as well as for QD-GSH2 (green) and QD-GSH3 (red), with higher average size. The inset in this figure shows a digital photo image of the three QD-GSH colloidal solutions used in this figure, under UV irradiation.</p> Full article ">Figure 5
<p>Ultraviolet (UV)–visible spectra for Au-GSH and Au-Mag-GSH colloidal solutions (<b>a</b>); TEM micrograph of Au-Mag-GSH (<b>b</b>) and its corresponding histogram displaying NP size distribution (<b>c</b>).</p> Full article ">Figure 6
<p>High-resolution TEM (HRTEM) (<b>a</b>) and HR-HAADF (<b>b</b>) images of NPs in sample Au-GSH. Punctual energy-dispersive X-ray (EDX) spectrum from QD-GSH (<b>c</b>) and from Au-Mag-GSH (<b>d</b>) NPs.</p> Full article ">Figure 7
<p>DLS size distributions of Au-GSH (<b>a</b>), Mag-GSH (<b>b</b>), CdTe-GSH1 (<b>c</b>) and Au-Mag-GSH (<b>d</b>) in PBS (phosphate-buffered saline) colloidal solutions.</p> Full article ">Figure 8
<p>Z-potential versus pH for the different GSH capped NPs (<b>a</b>). Diagram of the cysteamine (CYS)-capped (<b>b</b>) and GSH-capped (<b>c</b>) magnetic-iron-oxide NPs. Diagram of the CYS-capped (<b>d</b>) and GSH-capped (<b>e</b>) gold NPs.</p> Full article ">Figure 9
<p>Fourier transform infrared (FTIR) spectra for free GSH ligand as well as for Au-Mag-GSH, Au-GSH and Mag-GSH NPs.</p> Full article ">Figure 10
<p>MTT cell viability assay for Jurkat tumor cells incubated with the indicated type of NP at 1.5 μg/mL (<b>a</b>) or 15 μg/mL (<b>b</b>). Percentage of viable cells as compared to cells cultured in the absence of NP (considered as 100% viability) is shown. Mean and standard error are shown for each sample. A representative experiment out of three is shown. Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) are marked with a star (*).</p> Full article ">Figure 11
<p>MTT cell viability assay for Jurkat tumor cells incubated with the indicated NP at 1.5; 15; 30; 60; 120; 240; 480 and 960 μg/mL. Percentage of viable cells, as compared to cells cultured in the absence of NP (considered as 100% viability), is shown. Mean values and standard error for three experiments are shown. Viability of cells cultured in the presence of 10% dimethyl sulfoxide (DMSO) is 8.79%.</p> Full article ">

18 pages, 3017 KiB  

Open AccessArticle

Instantaneous Disturbance Index for Power Distribution Networks

by María Dolores Borrás-Talavera, Juan Carlos Bravo and César Álvarez-Arroyo

Sensors 2021, 21(4), 1348; https://doi.org/10.3390/s21041348 - 14 Feb 2021

Cited by 2 | Viewed by 2932

Abstract

The stability of power systems is very sensitive to voltage or current variations caused by the discontinuous supply of renewable power feeders. Moreover, the impact of these anomalies varies depending on the sensitivity/resilience of customer and transmission system equipment to those deviations. From [...] Read more.

The stability of power systems is very sensitive to voltage or current variations caused by the discontinuous supply of renewable power feeders. Moreover, the impact of these anomalies varies depending on the sensitivity/resilience of customer and transmission system equipment to those deviations. From any of these points of view, an instantaneous characterization of power quality (PQ) aspects becomes an important task. For this purpose, a wavelet-based power quality indices (PQIs) are introduced in this paper. An instantaneous disturbance index (ITD(t)) and a Global Disturbance Ratio index (GDR) are defined to integrally reflect the PQ level in Power Distribution Networks (PDN) under steady-state and/or transient conditions. With only these two indices it is possible to quantify the effects of non-stationary disturbances with high resolution and precision. These PQIs offer an advantage over other similar because of the suitable choice of mother wavelet function that permits to minimize leakage errors between wavelet levels. The wavelet-based algorithms which give rise to these PQIs can be implemented in smart sensors and used for monitoring purposes in PDN. The applicability of the proposed indices is validated by using a real-time experimental platform. In this emulated power system, signals are generated and real-time data are analyzed by a specifically designed software. The effectiveness of this method of detection and identification of disturbances has been proven by comparing the proposed PQIs with classical indices. The results confirm that the proposed method efficiently extracts the characteristics of each component from the multi-event test signals and thus clearly indicates the combined effect of these events through an accurate estimation of the PQIs. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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Figure 1
<p>Comparative frequency response of mother wavelets.</p> Full article ">Figure 2
<p>Voltage signal with harmonics: (<b>a</b>) Instantaneous representation, (<b>b</b>) FFT spectrum, (<b>c</b>) distribution of the energy percentage of the signal according to the coefficients of the mother wavelets.</p> Full article ">Figure 3
<p>Developed system scheme: Voltage generator with preset disturbances, power amplifier, and signal conditioner, load and Power Quality Analyzer.</p> Full article ">Figure 4
<p>Graphical user interface of the <span class="html-italic">Sigen</span> system.</p> Full article ">Figure 5
<p>Graphical user interface of the power quality (PQ) System Analyzer.</p> Full article ">Figure 6
<p>FFT spectra for several signals used on case A.</p> Full article ">Figure 7
<p>Single-phase voltage disturbances with similar THD. (<b>a</b>) Voltage sag1. (<b>b</b>) Voltage swell1. (<b>c</b>) Harmonic disturbances. (<b>d</b>) Flicker disturbance. (<b>e</b>) Transient1 disturbance.</p> Full article ">Figure 8
<p>Instantaneous Transient Disturbance ratio index <span class="html-italic">ITD</span>(<span class="html-italic">t</span>) of voltage disturbances corresponding to <a href="#sensors-21-01348-f005" class="html-fig">Figure 5</a>.</p> Full article ">Figure 9
<p>Instantaneous Transient Disturbance ratio index <span class="html-italic">ITD</span>(<span class="html-italic">t</span>) of voltage disturbances combination.</p> Full article ">

21 pages, 5402 KiB  

Open AccessArticle

OpenADR and Agreement Audit Architecture for a Complete Cycle of a Flexibility Solution

by Antonio Parejo, Sebastián García, Enrique Personal, Juan Ignacio Guerrero, Antonio García and Carlos Leon

Sensors 2021, 21(4), 1204; https://doi.org/10.3390/s21041204 - 9 Feb 2021

Cited by 3 | Viewed by 3369

Abstract

Nowadays, the presence of renewable generation systems and mobile loads (i.e., electric vehicle) spread throughout the distribution network is increasing. The problem is that this type of system introduces an added difficulty since they present a strong dependence on the meteorology and the [...] Read more.

Nowadays, the presence of renewable generation systems and mobile loads (i.e., electric vehicle) spread throughout the distribution network is increasing. The problem is that this type of system introduces an added difficulty since they present a strong dependence on the meteorology and the mobility needs of the users. This problem forces the distribution system operators to seek tools that make it possible to balance the relationship between consumption and generation. In this sense, automated demand response systems are an appropriate solution that allow the operator to request specific reductions in customers’ consumption, offering a discount to the customer and avoiding network congestion. This paper analyzes the implementation and architecture of a demand response solution based on OpenADR standard and its possible integration with a building management system through a use case. As will be analyzed, a key part of the architecture is the measurement system based on smart meters acting as sensors. This is the base of the auditing system which makes it possible to verify compliance with the consumption reduction agreements. Additionally, this study is completed with a parallel auditing system which makes it possible to verify compliance with the consumption reduction agreements. All of the proposed demand response cycle is implemented as a proof of concept in a classroom in the Escuela Politécnica Superior at the University of Seville, which makes it possible to identify the advantages of this architecture in the ambit of connection between distribution network and buildings. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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<p>PLC (Power Line Communication)-based smart metering infrastructure [<a href="#B38-sensors-21-01204" class="html-bibr">38</a>].</p> Full article ">Figure 2
<p>Structure and communication of DSO and customer systems for DSM/DR and auditing.</p> Full article ">Figure 3
<p>OpenADR communication services.</p> Full article ">Figure 4
<p>Architecture of the developed VTN with the different layers.</p> Full article ">Figure 5
<p>Complete flexibility cycle. (1) Flexibility offers calculation [BMS]; (2) Send offers to market [BMS-Market]; (3) Services selection [DSO-Market]; (4) Service request [DSO-BMS]; (5) Load control for requested service [BMS-Loads]; (6) Auditory of the requested service [DSO].</p> Full article ">Figure 6
<p>DERBis systems overview. DRMS: Demand Response Management System; VTN: Virtual Top Node; VEN: Virtual End Node; BMS: Building Management System.</p> Full article ">Figure 7
<p>DERBis control and measurement devices.</p> Full article ">Figure 8
<p>Smart metering system.</p> Full article ">Figure 9
<p>BMS HVAC control interface.</p> Full article ">Figure 10
<p>(<b>a</b>) Occupancy-based (from BMS) and historical-based (baseline) expected power; (<b>b</b>) Expected flexibility Margin (only values &gt;0). Reduction really requested by the DSO (in green); (<b>c</b>) Actual power and baseline. Requested power reduction (in red); (<b>d</b>) Reduction achieved vs. Expected flexibility margin. Requested power reduction (in red).</p> Full article ">Figure 10 Cont.
<p>(<b>a</b>) Occupancy-based (from BMS) and historical-based (baseline) expected power; (<b>b</b>) Expected flexibility Margin (only values &gt;0). Reduction really requested by the DSO (in green); (<b>c</b>) Actual power and baseline. Requested power reduction (in red); (<b>d</b>) Reduction achieved vs. Expected flexibility margin. Requested power reduction (in red).</p> Full article ">Figure 11
<p>(<b>a</b>) Occupancy-based (from BMS) and Historical-based (baseline) expected power; (<b>b</b>) Occupancy-based (from BMS) and Historical-based (baseline) expected power—Load reduction considered; (<b>c</b>) Expected flexibility Margin (only values &gt; 0). Reduction really requested by the DSO (in green); (<b>d</b>) Actual power and baseline. Requested power reduction (in red); (<b>e</b>) Reduction achieved vs. Expected Flexibility Margin. Requested power reduction (in red); (<b>f</b>) Temperature (red) and humidity (blue).</p> Full article ">Figure 12
<p>(<b>a</b>) Occupancy-based (from BMS) and Historical-based (baseline) expected power; (<b>b</b>) Expected flexibility Margin (only values &gt;0); (<b>c</b>) Actual power and baseline.</p> Full article ">Figure 12 Cont.
<p>(<b>a</b>) Occupancy-based (from BMS) and Historical-based (baseline) expected power; (<b>b</b>) Expected flexibility Margin (only values &gt;0); (<b>c</b>) Actual power and baseline.</p> Full article ">

13 pages, 1755 KiB  

Open AccessArticle

Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model’s Complexity on Its Processing Speed

by Lourdes Duran-Lopez, Juan P. Dominguez-Morales, Antonio Rios-Navarro, Daniel Gutierrez-Galan, Angel Jimenez-Fernandez, Saturnino Vicente-Diaz and Alejandro Linares-Barranco

Sensors 2021, 21(4), 1122; https://doi.org/10.3390/s21041122 - 5 Feb 2021

Cited by 14 | Viewed by 3164

Abstract

Prostate cancer (PCa) is the second most frequently diagnosed cancer among men worldwide, with almost 1.3 million new cases and 360,000 deaths in 2018. As it has been estimated, its mortality will double by 2040, mostly in countries with limited resources. These numbers [...] Read more.

Prostate cancer (PCa) is the second most frequently diagnosed cancer among men worldwide, with almost 1.3 million new cases and 360,000 deaths in 2018. As it has been estimated, its mortality will double by 2040, mostly in countries with limited resources. These numbers suggest that recent trends in deep learning-based computer-aided diagnosis could play an important role, serving as screening methods for PCa detection. These algorithms have already been used with histopathological images in many works, in which authors tend to focus on achieving high accuracy results for classifying between malignant and normal cases. These results are commonly obtained by training very deep and complex convolutional neural networks, which require high computing power and resources not only in this process, but also in the inference step. As the number of cases rises in regions with limited resources, reducing prediction time becomes more important. In this work, we measured the performance of current state-of-the-art models for PCa detection with a novel benchmark and compared the results with PROMETEO, a custom architecture that we proposed. The results of the comprehensive comparison show that using dedicated models for specific applications could be of great importance in the future. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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<p>Block diagram detailing each of the steps considered for processing a whole-slide image (WSI) in the proposed benchmark.</p> Full article ">Figure 2
<p>PROMETEO average patch processing time (in seconds) per step for each of the hardware configurations detailed in <a href="#sensors-21-01122-t0A1" class="html-table">Table A1</a>.</p> Full article ">Figure 3
<p>PROMETEO average WSI processing time (in seconds) and standard deviation per step for each of the hardware configurations detailed in <a href="#sensors-21-01122-t0A1" class="html-table">Table A1</a>.</p> Full article ">Figure 4
<p>PROMETEO average WSI processing time (in seconds) and standard deviation of the hardware configurations detailed in <a href="#sensors-21-01122-t0A1" class="html-table">Table A1</a>.</p> Full article ">Figure 5
<p>Average patch processing time (in seconds) per step for each of the CNN architectures using computer M (see <a href="#sensors-21-01122-t0A1" class="html-table">Table A1</a>).</p> Full article ">Figure 6
<p>Average WSI processing time (in seconds) and standard deviation for each of the CNN architectures using computer M (see <a href="#sensors-21-01122-t0A1" class="html-table">Table A1</a>).</p> Full article ">Figure 7
<p>Impacts of the CPU and the GPU in the different WSI processing steps. (<b>a</b>) Same PC, different CPU frequency. Left: 1.2 GHz; right: 2.6 GHz. (<b>b</b>) Same PC. Left: without using GPU; right: using GPU.</p> Full article ">

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Supplementary material:
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14 pages, 3752 KiB  

Open AccessArticle

Incorporation of ZnO Nanoparticles into Soy Protein-Based Bioplastics to Improve Their Functional Properties

by Mercedes Jiménez-Rosado, Víctor Perez-Puyana, Pablo Sánchez-Cid, Antonio Guerrero and Alberto Romero

Polymers 2021, 13(4), 486; https://doi.org/10.3390/polym13040486 - 4 Feb 2021

Cited by 22 | Viewed by 4045

Abstract

The union of nanoscience (nanofertilization) with controlled release bioplastic systems could be a key factor for the improvement of fertilization in horticulture, avoiding excessive contamination and reducing the price of the products found in the current market. In this context, the objective of [...] Read more.

The union of nanoscience (nanofertilization) with controlled release bioplastic systems could be a key factor for the improvement of fertilization in horticulture, avoiding excessive contamination and reducing the price of the products found in the current market. In this context, the objective of this work was to incorporate ZnO nanoparticles in soy protein-based bioplastic processed using injection moulding. Thus, the concentration of ZnO nanoparticles (0 wt%, 1.0 wt%, 2.0 wt%, 4.5 wt%) and mould temperature (70 °C, 90 °C and 110 °C) were evaluated through a mechanical (flexural and tensile properties), morphological (microstructure and nanoparticle distribution) and functional (water uptake capacity, micronutrient release and biodegradability) characterization. The results indicate that these parameters play an important role in the final characteristics of the bioplastics, being able to modify them. Ultimately, this study increases the versatility and functionality of the use of bioplastics and nanofertilization in horticulture, helping to prevent the greatest environmental impact caused. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Flexural properties of bioplastics with different ZnO nanoparticle concentrations (0 wt%, 1.0 wt%, 2.0 wt% and 4.5 wt%) processed at different mould temperatures: 70 °C (<b>A</b>), 90 °C (<b>B</b>) and 110 °C (<b>C</b>). Elastic modulus (E’) and loss tangent (tan δ) profile in frequency interval.</p> Full article ">Figure 2
<p>Tensile parameters of bioplastics with different ZnO nanoparticle concentrations (0 wt%, 1.0 wt%, 2.0 wt% and 4.5 wt%) processed at different mould temperatures (70 °C, 90 °C and 110 °C). (<b>A</b>): maximum stress. (<b>B</b>): strain at break. (<b>C</b>). Young’s modulus. Different letters in the bars mean that the values are significantly different (<span class="html-italic">p</span> &lt; 0.05).</p> Full article ">Figure 3
<p>Macrographs (<b>A</b>–<b>C</b>) and micrographs of bioplastics with different ZnO nanoparticle concentrations (0 wt%, 1.0 wt%, 2.0 wt% and 4.5 wt%) processed at different mould temperatures (70 °C, 90 °C and 110 °C), using a secondary electron detector and a scattered electron detector before ((<b>A’</b>–<b>C’</b>) and (<b>A’’</b>–<b>C’’</b>), respectively) and after water uptake capacity (WUpC) tests (<b>A’’’</b>–<b>C’’’</b>).</p> Full article ">Figure 4
<p>Water uptake capacity (<b>A</b>) and soluble matter loss (<b>B</b>) of the bioplastics with different ZnO nanoparticle concentrations (0 wt%, 1.0 wt%, 2.0 wt% and 4.5 wt%) processed at different mould temperatures (70 °C, 90 °C and 110 °C). Different letters (a,b, …, g) in the bars mean that the values are significantly different (<span class="html-italic">p</span> &lt; 0.05).</p> Full article ">Figure 5
<p>Accumulation of conductivity in the water release tests of bioplastics with different ZnO nanoparticle concentrations (1.0 wt%, 2.0 wt% and 4.5 wt%) processed at a mould temperature of 90 °C.</p> Full article ">

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Supplementary material:
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12 pages, 2740 KiB  

Open AccessEditor’s ChoiceArticle

Effects of Mould Temperature on Rice Bran-Based Bioplastics Obtained by Injection Moulding

by María Alonso-González, Manuel Felix, Antonio Guerrero and Alberto Romero

Polymers 2021, 13(3), 398; https://doi.org/10.3390/polym13030398 - 27 Jan 2021

Cited by 24 | Viewed by 4393

Abstract

The high production rate of conventional plastics and their low degradability result in severe environmental problems, such as plastic accumulation and some other related consequences. One alternative to these materials is the production of oil-free bioplastics, based on wastes from the agro-food industry, [...] Read more.

The high production rate of conventional plastics and their low degradability result in severe environmental problems, such as plastic accumulation and some other related consequences. One alternative to these materials is the production of oil-free bioplastics, based on wastes from the agro-food industry, which are biodegradable. Not only is rice bran an abundant and non-expensive waste, but it is also attractive due to its high protein and starch content, which can be used as macromolecules for bioplastic production. The objective of this work was to develop rice-bran-based bioplastics by injection moulding. For this purpose, this raw material was mixed with a plasticizer (glycerol), analysing the effect of three mould temperatures (100, 130 and 150 °C) on the mechanical and microstructural properties and water absorption capacity of the final matrices. The obtained results show that rice bran is a suitable raw material for the development of bioplastics whose properties are strongly influenced by the processing conditions. Thus, higher temperatures produce stiffer and more resistant materials (Young’s modulus improves from 12 ± 7 MPa to 23 ± 6 and 33 ± 6 MPa when the temperature increases from 100 to 130 and 150 °C, respectively); however, these materials are highly compact and, consequently, their water absorption capacity diminishes. On the other hand, although lower mould temperatures lead to materials with lower mechanical properties, they exhibit a less compact structure, resulting in enhanced water absorption capacity. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Viscoelastic properties at a constant frequency (1 Hz) of the doughs obtained after mixing. (<b>a</b>) Evolution of the elastic modulus (E′) and moisture content (%) over time. (<b>b</b>) Temperature sweep test of the stabilized dough between 30 and 160 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C.</p> Full article ">Figure 2
<p>DMTA tests performed on the final bioplastics. (<b>a</b>) Frequency sweep tests from 0.01 to 20 Hz at room temperature and (<b>b</b>) temperature sweep tests from 30 to 140 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C at 1 Hz.</p> Full article ">Figure 3
<p>Stress–strain curves obtained from tensile tests for the bioplastics obtained for different mould temperatures (100, 130 and 150 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C).</p> Full article ">Figure 4
<p>(<b>a</b>) Water uptake capacity (WUC) and (<b>b</b>) Soluble Matter Loss (SML) for the bioplastics obtained for different mould temperatures (100, 130 and 150 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C). Different letters above each bar indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p> Full article ">Figure 5
<p>SEM micrographs after lyophilization of the different samples at (<b>a</b>) 100 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C; (<b>b</b>) 130 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C; (<b>c</b>) 150 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C.</p> Full article ">

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