Search Results (16,583)

Objectives: This study aimed to compare ultrasound (US) findings between automated and handheld breast ultrasound (ABUS and HHUS, respectively) in small breast cancers, based on the breast imaging reporting and data system (BI-RADS) category. Methods: We included 51 women (mean age: 52 years; range: 39–66 years) with breast cancer (invasive or DCIS), all of whom underwent both ABUS and HHUS. Patients with tumors measuring ≤1 cm on either modality were enrolled. Two breast radiologists retrospectively evaluated multiple imaging features, including shape, orientation, margin, echo pattern, and posterior characteristics and assigned BI-RADS categories. Lesion sizes were compared between US and pathological findings. Statistical analyses were performed using Bowker’s test of symmetry, a paired t-test, and a cumulative link mixed model. Results: ABUS assigned lower BI-RADS categories than HHUS while still maintaining malignancy suspicion in categories 4A or higher (54.8% consistent with HHUS; 37.3% downcategorized in ABUS, p = 0.005). While ABUS demonstrated less aggressive margins in some cases (61.3% consistent with HHUS; 25.8% showing fewer suspicious margins in ABUS), this difference was not statistically significant (p = 0.221). Similarly, ABUS exhibited slightly greater height–width ratios compared to HHUS (median, interquartile range: 0.98, 0.7–1.12 vs. 0.86, 0.74–1.10, p = 0.166). No significant differences were observed in other US findings or tumor sizes between the two modalities (all p > 0.05). Conclusions: Small breast cancers exhibited suspicious US features on both ABUS and HHUS, yet they were assigned lower BI-RADS assessment categories on ABUS compared to HHUS. Therefore, when conducting breast cancer screening with ABUS, it is important to remain attentive to even subtle suspicious findings, and active consideration for biopsy may be warranted. Full article

Recreational Ecological Parks (REPs) play a pivotal role in advancing sustainable development by promoting ecotourism, conserving biodiversity, and providing inclusive recreational opportunities with minimal environmental impact. Assessing the potential for REP development is crucial to optimize the sustainable use of natural resources and enhance ecological and socio-economic benefits. This study introduces a sustainability-oriented Spatial Multi-Criteria Decision Analysis (SMCDA) framework to evaluate and optimize REP development in Mazandaran Province, Iran. The framework incorporates 33 criteria across five categories: 13 for network connectivity and accessibility; 10 for facilities, services, and tourism potential; 4 for landform and land use; 3 for natural hazards; and 3 for climate conditions. Criteria were standardized using the minimum–maximum method and weighted based on expert input via the Best–Worst Method. A weighted linear combination approach was then applied to generate REP suitability maps. Existing recreational and tourism (R&T) sites were assessed against these maps, and a non-parametric bootstrapping method quantified uncertainties in suitability classifications. The results revealed that approximately 8%, 17%, 26%, 30%, and 19% of the study area fell into very low, low, moderate, high, and very high suitability classes, respectively. Among 151 R&T sites, 33% and 34% were situated in areas classified as very high and high suitability. Prediction rates were most accurate in the very high suitability category, while uncertainty analysis indicated a mean of 13% and a standard deviation of 1.7%, with uncertainties predominantly concentrated in lower suitability classes. The findings underscore the SMCDA framework’s efficacy in guiding sustainable REP development by identifying optimal sites and managing uncertainties. This study contributes to sustainability by integrating ecological, economic, and social dimensions into decision-making processes, thereby fostering resilience and long-term environmental stewardship in tourism planning. Full article

The conflict between environmental conservation and agricultural production highlights the need for precise land use and land cover (LULC) mapping to support agro-environmental-related policies. Satellite image time series from the Moderate Resolution Image Spectroradiometer (MODIS) sensor are essential for current LULC mapping efforts. However, most approaches focus on pixel data, and studies exploring object-based spatiotemporal heterogeneity and correlation features in its time series are limited. The objective of this study is to mix the data cube architecture (analysis-ready data—ARD) and the geo-object-oriented time series segmentation via Geographic Object-Based Image Analysis (GEOBIA) to assess its performance in identifying natural vegetation and double-cropping practices over a crop season. The study area was the state of Mato Grosso, Brazil. Results indicate that, by combining GEOBIA and time series analysis (materialized by the multiresolution segmentation algorithm to derive spatiotemporal geo-objects of the MODIS data cube), representative training data collected after a quality control process, and the Support Vector Machine to classify the ARD, the overall accuracy was 0.95 and all users’ and producers’ accuracies were higher than 0.88. By considering the heterogeneity of Mato Grosso’s landscape, the results indicate the potential of the approach to provide accurate mapping. Full article

Additive manufacturing is a technology that creates objects by adding successive layers of material. The 3D method is an alternative to subtractive production, in which production involves removing material from the initial solid. 3D printing requires the initial design of the manufactured object using computer design, for example, one of the following programs: CAD, 3DCrafter, Wings 3D, Cinema 3, Blender, 3ds Max, Autodesk Inventor, and others. It is also possible to scan an existing object to be manufactured using 3D printing technology. An important element of Industry 5.0 is 3D printing technology, due to its favorable environmental orientation and production flexibility. Three-dimensional printing technology uses recycled materials such as powders. Therefore, it can be part of a circular economy, contributing to environmental protection. Additive manufacturing not only complements existing technologies by enabling rapid prototyping but also plays a fundamental role in sectors such as dentistry and medicine. This article consists of seven chapters relating to various aspects of 3D printing technology in the context of the assumptions and challenges of Industry 5.0. It examines the environmental impact and recycling potential of 3D printing technology, illustrates the economic integration of this technology within various industries, and discusses its future development prospects. Full article

In this work, the behavior of a 3D blood clot located inside a vein under the influence of the mechanical effect of blood flow was analyzed. It has been observed that the mechanical properties of the blood vessel play an important role in the behavior of a blood clot. When the blood vessel changes its shape and/or diameter over time, the position and orientation of the clot in space and time is not constant, and consequently, it influences the blood flow. Moreover, the changed lumen of the blood vessel has a direct impact on the blood velocity, and thus the pressure is exerted not only on the blood vessel wall but also on the thrombus itself. Under these different conditions, it is important to understand the behavior of the blood clot, where each factor with a mechanical influence could potentially lead to clot detachment. Therefore, several variants of numerical simulations were analyzed, including models with different blood vessel properties, considering when the blood vessel wall has (flexible) or does not have (fixed) elastic properties. The results show the blood flow velocity, vessel wall, and blood clot deformations and/or stresses using different vessel wall rigidity levels as well as different blood clot viscoelasticity parameters. Full article

Crack detection and quantification play crucial roles in assessing the condition of concrete structures. Herein, a novel real-time crack detection and quantification method that leverages binocular vision and a lightweight deep learning model is proposed. In this methodology, the proposed method based on the following four modules is adopted: a lightweight classification algorithm, a high-precision segmentation algorithm, a semi-global block matching algorithm (SGBM), and a crack quantification technique. Based on the crack segmentation results, a framework is developed for quantitative analysis of the major geometric parameters, including crack length, crack width, and crack angle of orientation at the pixel level. Results indicate that, by incorporating channel attention and spatial attention mechanisms in the MBConv module, the detection accuracy of the improved EfficientNetV2 increased by 1.6% compared with the original EfficientNetV2. Results indicate that using the proposed quantification method can achieve low quantification errors of 2%, 4.5%, and 4% for the crack length, width, and angle of orientation, respectively. The proposed method can contribute to crack detection and quantification in practical use by being deployed on smart devices. Full article

The microstructure, texture, and mechanical properties of Inconel 718 fabricated via hybrid wire-arc additive manufacturing (WAAM) with inter-pass forging, and the subsequent modified post-deposition heat treatment (PDHT), were investigated. The modified PDHT included homogenization at 1185 °C and double ageing at 720 °C, with furnace-cooling to 620 °C; this process was first used for Inconel 718 obtained via WAAM and inter-pass forging. In the as-printed material, two characteristic zones were distinguished, as follows: (i) columnar grains with a preferable <100> orientation and (ii) fine grains with a random crystallographic orientation. The development of static recrystallization induced via inter-pass forging and further heating during the deposition of the next (upper) layer provoked the formation of the fine-grained zone. In the as-printed material, particles of (Nb,Ti)C and TiN, and precipitates of a Nb-rich Laves phase that caused premature cracking and failure during mechanical testing, were detected. In the PDHT material, two zones were found, as follows: (i) a zone with coarse uniaxial grains and (ii) a zone with a gradient grain size distribution. PDHT resulted in the precipitation of γ″ nanoparticles in the γ-Ni matrix and the dissolution of the brittle Laves phase. Therefore, significant hardening and strengthening, as well as increases in ductility and impact toughness, occurred. Full article

To provide insight into the interface structure in Ti particle-reinforced Mg matrix composites, this study investigates the inherent Mg/Ti interface structure formed during the solidification of supercooled Mg melt on a (0001)Ti substrate using ab initio molecular dynamics (AIMD) simulations and density function theory (DFT) calculation. The resulting interface exhibits an orientation relationship of ${\left(0001\right)}_{\mathrm{Mg}}{//\left(0001\right)}_{\mathrm{Ti}}$ with a lattice mismatch of approximately 8%. Detailed characterizations reveal the occurrences of ${\left(0001\right)}_{\mathrm{Mg}}$ plane rotation and vacancy formation to overcome the lattice mismatch at the inherent Mg/Ti interface while allowing Mg atoms to occupy the energetically favorable hollow sites above the Ti atomic layer. The atomic diffusion behaviors of rare-earth elements Gd and Y at the Mg/Ti interface was examined using the climbing image nudged elastic band (CI-NEB) method, demonstrating a strong segregation tendency towards the interface promoted by the inherent interface structure. Additionally, the calculated Griffith work indicates enhanced interfacial adhesion due to the segregation of Gd and Y, which is beneficial for the mechanical properties of the composite. Full article

Terrestrial laser scanners (TLS) are portable dimensional measurement instruments used to obtain 3D point clouds of objects in a scene. While TLSs do not require the use of cooperative targets, they are sometimes placed in a scene to fuse or compare data from different instruments or data from the same instrument but from different positions. A contrast target is an example of such a target; it consists of alternating black/white squares that can be printed using a laser printer. Because contrast targets are planar as opposed to three-dimensional (like a sphere), the center of the target might suffer from errors that depend on the orientation of the target with respect to the TLS. In this paper, we discuss a low-cost method to characterize such errors and present results obtained from a short-range TLS and a long-range TLS. Our method involves comparing the center of a contrast target against the center of spheres and, therefore, does not require the use of a reference instrument or calibrated objects. For the short-range TLS, systematic errors of up to 0.5 mm were observed in the target center as a function of the angle for the two distances (5 m and 10 m) and resolutions (30 points-per-degree (ppd) and 90 ppd) considered for this TLS. For the long-range TLS, systematic errors of about 0.3 mm to 0.8 mm were observed in the target center as a function of the angle for the two distances (5 m and 10 m) at low resolution (28 ppd). Errors of under 0.3 mm were observed in the target center as a function of the angle for the two distances at high resolution (109 ppd). Full article

Background: This is a novel rat study using native peptide therapy, focused on reversing quadriceps muscle-to-bone detachment to reattachment and stable gastric pentadecapeptide BPC 157 per-oral therapy for shared muscle healing and function restoration. Methods: Pharmacotherapy recovering various muscle, tendon, ligament, and bone lesions, and severed junctions (i.e., myotendinous junction), per-oral in particular (BPC 157/kg/day 10 µg, 10 ng), provides muscle-to-bone reattachment after quadriceps muscle detachment, both complete (rectus muscle) and partial (vastus muscles). Results: Immediately post-injury, and at 1, 2, 3, 5, 7, 14, 21, 28, 60, and 90 days post-injury, quadriceps muscle-to-bone detachment showed definitive healing failure (impaired walking and permanent knee flexure). Contrarily, macro/microscopic, ultrasonic, magnetic resonance, biomechanical, and functional assessments revealed that BPC 157 therapy recovering effects for all time points were consistent. All parameters of the walking pattern fully improved, and soon after detachment and therapy application, muscle approached the bone, leaving a minimal gap (on ultrasonic assessment), and leg contracture was annihilated. The healing process occurs immediately after detachment from both sides: the muscle and the bone. The reattachment fibers from the ends of the muscle could be traced into the new bone formed at the surface (note, at day 3 post-detachment, increased mesenchymal cells occurred with periosteum reactivation). Consequently, at 3 months, the form was stable, and the balance between the muscle and bone was the following: well-organized bone, newly formed as more cortical bone providing a narrower bone marrow space, and the muscle and mature fibers were oriented parallel to the bone axis and were in close contact with bone. Conclusions: Therefore, to achieve quadriceps muscle-to-bone reattachment, the BPC 157 therapy reversing course acts from the beginning, resolving an otherwise insurmountable deleterious course. Full article

Background: Diffusion weighted imaging (DWI) is used for monitoring purposes for lower-grade glioma (LGG). While the apparent diffusion coefficient (ADC) is clinically used, various DWI models have been developed to better understand the micro-environment. However, the validity of these models and how they relate to each other is currently unknown. Therefore, this study assesses the validity and agreement of these models. Methods: Fourteen post-treatment LGG patients and six healthy controls (HC) underwent DWI MRI on a 3T MRI scanner. DWI processing included diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), white matter tract integrity (WMTI), neurite orientation dispersion and density imaging (NODDI), and fixel-based analysis (FBA). Validity was assessed by delineating surgical cavity, peri-surgical cavity, and normal-appearing white matter (NAWM) in LGG patients, and white matter (WM) in HC. Spearman correlation assessed the agreement between DWI parameters. Results: All obtained parameters differed significantly across tissue types. Remarkably, WMTI showed that intra-axonal diffusivity was high in the surgical cavity and low in NAWM and WM. Most DWI parameters correlated well with each other, except for WMTI-derived intra-axonal diffusivity. Conclusion: This study shows that all parameters relevant for tumour monitoring and DWI-derived parameters for axonal fibre-bundle integrity (except WMTI-IAS-D_a) could be used interchangeably, enhancing inter-DWI model interpretability. Full article

Globally, agriculture is facing significant challenges due to climate change, which is seriously affecting grain yields. This research aims to analyze the significant effect of climate change (temperature and rainfall) on cereal production in Benin. The choice of Benin is explained by its strong dependence on agriculture and its vulnerability to climatic variations. This study employed climate and agricultural data from FAO and ASECNA (1990–2020) to evaluate the impacts of climate change on cereal production. SARIMA time-series models were used for forecasting, while the PLS-SEM approach assessed the relationships between climate variables and cereal production. The findings reveal a rise in temperatures and a gradual decline in precipitation. Despite these challenges, the time-series analysis suggests that Beninese farmers are expanding cultivated areas, successfully increasing production levels, and improving yields. Projections to 2050 indicate an increase in areas and production for maize and rice, while sorghum shows a constant trend. However, even with these projections, it is recommended to explore, in more depth, the resilience strategies used by cereal producers to better understand their influence and refine the orientations of future agricultural policies. Full article

This article offers a concise overview of the best practices for safety in offshore oil and gas operations, focusing on the risks associated with various types of equipment, particularly on the risk of fire. It identifies specific machinery and systems that could pose hazards, assesses their potential impact on safety, and explores conditions that may lead to accidents. Some of the largest accidents were analyzed for their associations with fire hazards and specific equipment. Two primary regulatory approaches to offshore safety are examined: the prescriptive approach in the United States (US) and the goal-oriented approach in Europe. The prescriptive approach mandates strict compliance with specific regulations, while in the goal-oriented approach a failure to adhere to recognized best practices can result in legal accountability for negligence, especially concerning human life and environmental protection. This article also reviews achievements in safety through the efforts of regulatory authorities, industry collaborations, technical standards, and risk assessments, with particular attention given to the status of Mobile Offshore Drilling Units (MODUs). Contrary to common belief, the most frequent types of accidents are not those involving a fire/explosion caused by the failure of the Blowout Preventer (BOP) after a well problem has already started. Following analysis, it can be concluded that the most frequent type of accident typically occurs without fire and is due to material fatigue. This can result in the collapse of the facility, capsizing of the platform, and loss of buoyancy of mobile units, particularly in bad weather or during towing operations. It cannot be concluded that accidents can be more efficiently prevented under a specific type of safety regime, whether prescriptive or goal-oriented. Full article

A growing need to reduce the environmental impact and cost of manufacturing stainless steels has led to the development of ferritic stainless steel as an alternative to austenitic and duplex steels. The development of new stainless steels involves the optimization of their hot rolling processes, with the aim of minimizing the occurrence of defects and improving productivity. In this context, numerical simulation using the finite element method (FEM) is presented as a key tool to reduce the time and cost associated with traditional trial-and-error optimization methods. Previous work oriented towards the simulation of stainless steels has been focused on the study of small samples, on the performance of laboratory-scale tests, and on the use of 2D FEM models. In this study, a three-dimensional FEM model is proposed to simulate the hot rolling process of large-scale AISI 430 ferritic stainless-steel slabs using an industrial rolling schedule employed in the actual manufacturing process of flat products. Model optimization is performed in order to reduce the computational cost of the simulations, based on the simulation of the first pass of the hot rolling process of AISI 430 stainless steel. The results show that model optimization reduces the computational time by 90.2% without compromising the accuracy of the results. Thus, it was found that the results for thickness and rolling load showed a good correlation with the experimental values. In addition, the simulations performed allowed for the analysis of the distribution of temperature and effective plastic strain. Full article

The paper aims to identify the powerful forces of Generation Z’s (Gen Z) work motivations, considering four key drivers: recognition, appreciation, well-being, and skills. Four hypotheses were developed, and Gen Z-triggering motivational factors at work were analyzed using a survey approach. Using the collected data, a logistic regression model was constructed to investigate the effects on work motivation. An in-depth interview of managers from different companies was applied to identify Gen Z’s perceptions about the workplace. All four predictors proved to influence work motivation significantly. According to the answers of Gen Z’s members, wage is the primary motivator for them to increase work efficiency, with other financial and non-financial factors being less significant. Gen Z is generally not teamwork-oriented and prefers working alone to demonstrate their abilities and achieve greater efficiency. Gen Z switches jobs frequently and shows low loyalty to organizations, often prioritizing personal preferences over long-term commitment. This study explores Romanian Gen Z-triggering motivational factors and shows the motivators for increasing work efficiency. It provides unique insights into a less teamwork-oriented, low loyalty to organizations segment, filling a literature gap and offering business recommendations for connecting with this generation. Full article