Search Results (28,184)

Aiming at the problems of serious soil desertification, increased soil and water loss, and reduced soil-available nutrients in the agro-pastoral ecotone in Northeast Inner Mongolia, this study took corn variety A6565 as the planting crop and analyzed seven different tillage measures, deep tillage, deep loosening, shallow tillage, rotary tillage, heavy harrow, no-tillage, and control, combined with straw returning at an experimental field in Arong Banner. The analysis results are as follows: the urease activity and microbial biomass nitrogen content of the tillage method combined with straw-returning treatment were higher than other treatments. Compared with the seedling stage, the alpha diversity index of bacteria increased in the harvest stage, while that of fungi was the opposite. β diversity comparison showed that sampling time was the main factor affecting the bacterial community and composition. It was found that the dominant bacteria were Proteobacteria and Actinomycetes, and the dominant fungus was Ascomycetes. Conservation tillage combined with straw-returning treatment has a positive impact on soil microbial diversity, which is more helpful for improving soil-available nutrients and soil quality. All the findings in this study may contribute to restricting a series of important factors affecting sustainable agricultural development, such as soil degradation. Full article

This paper presents a novel methodology to estimate the harmonic transfer impedances in electric power systems with multiple harmonic sources (HSs). The purpose is to determine the responsibility of each HS for the total harmonic distortion at a specific bus within the system, addressing a critical issue in the power quality field. To achieve this objective, it is necessary to estimate not only the individual HS, but also the transfer impedances between each source and the bus under analysis (BUA). Most methods for solving this problem are based on proper network modeling or restrict variations in harmonic sources to a single source at a time. The proposed methodology has overcome this limitation. For this, synchronized current and voltage phasors are measured at the BUA. Once the measurements are gathered, the Independent Component Analysis (ICA) method is applied to estimate the Norton equivalent. The harmonic transfer impedance (HTI) is then determined using the information provided by the ICA. To enhance the accuracy of HTI estimation, three procedures are employed for data mining the parameters provided by ICA over time to generate a well-conditioned system. Once the HTI is satisfactorily determined, the individual harmonic contributions (IHCs), i.e., the harmonic responsibility, can be estimated accurately. The effectiveness and performance of the method are demonstrated based on computational simulations using distribution and transmission systems. Additionally, the methodology is validated with real data collected from a Brazilian transmission system monitored by synchronized power quality measurement units. Simulated results show that the Total Vector Error (TVE) is less than 0.4%, and for the field data test, the TVE is less than 2%. Full article

(1) Background: Targeted alpha therapy is an emerging field in nuclear medicine driven by two advantages: overcoming resistance in cancer-suffering patients to beta therapies and the practical application of lower activities of ²¹²Pb- and ²²⁵Ac-labelled peptides to achieve the same doses compared to beta therapy due to the highly cytotoxic nature of alpha particles. However, quality control of the ²¹²Pb/²²⁵Ac-radiopharmaceuticals remains a challenge due to the low activity levels used for therapy (100 kBq/kg) and the formation of several free daughter nuclides immediately after the formulation of patient doses; (2) Methods: The routine alpha detection on thin-layer chromatograms (TLC) of ²¹²Pb- and ²²⁵Ac-labelled peptides using a MiniScanPRO+ scanner combined with an alpha detector head was compared with detection using an AR-2000 scanner equipped with an open proportional counter tube. Measurement time, resolution and validity were compared for both scanners; (3) Results: For ²²⁵Ac, the quality control values of the radiochemical purity (RCP) were within the acceptance criteria 2 h after TLC development, regardless of when the TLC probe was taken. That is, if the TLC probe was taken 24 h after radiosynthesis, the true value of the RCP was not measured until 5 h after TLC development. For ²¹²Pb-labelled peptides, the probe sampling did not have a high impact on the value of the RCP for the MiniScanPRO+ and AR-2000. A difference was observed when measuring TLC with the AR-2000 in different modes; (4) Conclusions: The MiniScanPRO+ is fast, does not require additional equipment and can also measure the gamma spectrum, which may be important for some radiopharmaceutical production sites and regulatory authorities. The AR-2000 has a better signal-to-noise ratio, and this eliminates the need for additional waiting time after TLC development. Full article

(1) Background: A parsimonious test battery is deemed necessary to efficiently assess the functional performance of athletes avoiding redundant measurements. This study investigates the interrelationships between elements of an experimental field-based test battery during pre-season assessment (PA), with the purpose of enhancing comprehension of the underlying structure of the assessed variables and suggesting guidelines for the tests incorporated in a PA. (2) Methods: Sixty-two professional football athletes performed a PA, including isometric muscle strength, triple hop and core stability tests, the LESS, and evaluation of landing performance through kinetic and electromyographic data. (3) Results: For the dominant lower limb, the factor analysis resulted in six factors, explaining 79.04% of the variance including core stability, ground reaction forces, dynamic balance, hamstrings strength, quadriceps–hamstring EMG ratio, and quadriceps performance. For the non-dominant lower limb, factor analysis resulted in five factors, explaining 76.60% of the variance including core stability, dynamic balance, ground reaction force, quadriceps–hamstring EMG ratio, and quadriceps–abductors strength. The LESS was loaded with various factors. (4) Conclusions: Given the need for efficient field-based assessments that can be repeated throughout the season without sacrificing data quality, we suggest incorporating the LESS, the prone bridge test, and force-plate-based landing performance evaluation as key elements of the PA. Full article

The latest changes on the distribution network due to the presence of distributed energy resources (DERs) and electric vehicles make it necessary to monitor the grid using a real-time high-precision system. The present work centers on the development of an open-source software platform that allows for the joint management of, at least, power quality monitors (PQMs), phasor measurement units (PMUs), and smart meters (SMs), which are three of the most widespread devices on distribution networks. This framework could work remotely while allowing access to the measurements in a comfortable way for grid analysis, prediction, or control tasks. The platform must meet the requirements of synchronism and scalability needed when working with electrical monitoring devices while considering the large volumes of data that these devices generate. The framework has been experimentally validated in laboratory and field tests in two photovoltaic plants. Moreover, real-time Artificial Intelligence capabilities have been validated by implementing three Machine Learning classifiers (Neural Network, Decision Tree, and Random Forest) to distinguish between three different loads in real time. Full article

Various industries see digital transformation (DT) as the pillar to coping with intensified competition, energy crises, and climate change. As a critical sector for DT, the construction industry’s project-oriented paradigm and immature industrialized production method limit the research on emerging digital technology and ignore the theoretical mechanism. Through the lens of system adaptability, this study proposes a multifaceted model to examine the DT effectiveness and unveil the driving mechanism. (1) An extensive literature review, action research, and the nominal group technique identified 21 determinants, which were categorized into a technological–organizational–environmental (TOE) framework to analyze the construction industry’s DT determinants from multiple dimensions. (2) This research utilizes data from 272 respondents collected through field research, with a survey designed to measure the relationships among variables. (3) Structural equation modeling (SEM) through Analysis of Moment Structures (AMOSs) has been used to analyze the hypotheses and analyze the impact of determinants from various dimensions on DT and examine their influence pathways. The results indicate that determinants in the technological, organizational, and environmental dimensions positively affect DT’s success in the construction industry. The influence of the technological dimension is the strongest, and the organizational dimension is the weakest. The research findings offer valuable recommendations and insights for stakeholders in the construction industry, highlighting the importance of considering these three dimensions to enhance the overall effectiveness of DT when driving industry transformation and upgrading. Additionally, this study uses the TOE framework to reveal determinants from multiple dimensions. It combines SEM to explore the pathways of their effects, offering key theoretical insights for the body of knowledge. Full article

Tree height and vertical forest structure are important attributes in forestry, but their traditional measurement or assessment in the field is expensive, time-consuming, and often inaccurate. One of the main advantages of using remote sensing data to estimate vertical forest structure is the ability to obtain accurate data for larger areas in a more time- and cost-efficient manner. Temporal changes are also important for estimating and analysing tree heights, and in many countries, national airborne laser scanning (ALS) surveys have been conducted either only once or at specific, longer intervals, whereas aerial surveys are more often arranged in cycles with shorter intervals. In this study, we reviewed all freely available national airborne remote sensing data describing three-dimensional forest structures in Slovenia and compared them with traditional field measurements in an area dominated by uneven-aged forests. The comparison of ALS and digital aerial photogrammetry (DAP) data revealed that freely available national ALS data provide better estimates of dominant forest heights, vertical structural diversity, and their changes compared to cyclic DAP data, but they are still useful due to their temporally dense data. Up-to-date data are very important for forest management and the study of forest resilience and resistance to disturbance. Based on field measurements (2013 and 2023) and all remote sensing data, dominant and maximum heights are statistically significantly higher in uneven-aged forests than in mature, even-aged forests. Canopy height diversity (CHD) information, derived from lidar ALS and DAP data, has also proven to be suitable for distinguishing between even-aged and uneven-aged forests. The CHD_ALS 2023 was 1.64, and the CHD_CAS 2022 was 1.38 in uneven-aged stands, which were statistically significantly higher than in even-aged forest stands. Full article

Due to their inherent advantages, optical fiber sensors (OFSs) can substantially contribute to the monitoring and performance enhancement of energy infrastructure. However, optical fiber sensor systems often are standalone solutions and do not connect to the main energy infrastructure control systems. In this paper, we propose a solution for the digitalization of an optical fiber sensor system realized by the Open Platform Communications Unified Architecture (OPC UA) protocol and the Internet of Things (IoT) platform Insights Hub. The optical fiber sensor system is based on bidirectional incoherent optical frequency domain reflectometry (biOFDR) and is used for the interrogation of fiber Bragg grating (FBG) arrays. To allow for an automated sensor identification and thus measurement procedure, an optical sensor identification marker based on a unique combination of fiber Bragg gratings (FBGs) is established. To demonstrate the abilities of the digitalized sensor network, a field test was performed in a power plant test facility of Siemens Energy. Temperature measurements of a packaged FBG sensor fiber were performed with a portable demonstrator, illustrating the system’s robustness and the comprehensive data processing stream from sensor value formation to the cloud. The realized network services promote sensor data quality, fusion, and modeling, expanding opportunities using digital twin technology. Full article

This study developed and validated the Interpreting Learning Engagement Scale (ILES), which was designed to measure the engagement of students in the interpreting learning context. Recognizing the crucial role of learning engagement in academic success and the acquisition of interpreting skills, which demands considerable cognitive effort and active involvement, this research addresses the gap in empirical studies on engagement within the field of interpreting. The ILES, comprising 18 items across four dimensions (behavioral, emotional, cognitive, and agentic engagement), was validated with data collected from a cohort of 306 students from five universities in China. The study employed exploratory and confirmatory factor analyses to establish the scale’s theoretical underpinnings and provided further reliability and validity evidence, demonstrating its adequate psychometric properties. Additionally, the scale’s scores showed a significant correlation with grit, securing the external validity of the ILES. This study not only contributes a validated instrument for assessing student engagement in interpreting learning but also provides implications for promoting engagement through potential interventions, with the ultimate aim of achieving high levels of interpreting competence. Full article

Deep space exploration is one of the key development directions in the aerospace field. With the significant increase in detection distance, the traditional space exploration methods may be ineffective due to effects such as signal energy attenuation and channel delay. There is an urgent need for a miniaturized, quasi-real-time, high-precision space velocity measurement instrument to be mounted on deep space aircraft and provide autonomous navigation. Spatial heterodyne spectral velocimetry technology is a newly proposed high-precision velocimetry method in recent years, and relevant research units have also obtained excellent measurement results in applications. However, this technology originally used laser light sources for active detection, which differs from the passive detection based on stellar light sources required for deep space vehicles in terms of prerequisites. Therefore, this article focuses on the technical route and feasibility exploration of using spatial heterodyne spectral velocimetry technology for stellar absorption spectrum and proposes a practical measurement scheme based on the technical principle of the background light synchronous cancellation method. We measured the radial velocity difference caused by the sun’s rotation at different positions on the solar image plane through outside validation experiments built in a simulated environment on the ground and obtained the experimental data with measurement deviation about 90 m/s and standard deviation about 55 m/s. The experimental results indicate that, under the current stability conditions of ground-based solar observation, we have achieved the same level of measurement accuracy as large ground-based telescopes by using instruments and equipment of much smaller size. It can be considered that the spatial heterodyne spectral velocity measurement scheme proposed in this article has achieved feasibility verification based on stellar spectral detection capability under the premise of instrument miniaturization and quasi-real-time processing. The research content provides a preliminary verification for the development of spatial heterodyne spectral velocimetry technology in the aerospace field and also provides reference for the realization of high-precision autonomous navigation capability in future aerospace technology. Full article

Many studies in the literature have assessed the blue–green infrastructure (BGI) characteristics that influence its cooling potential for sustainable urban development. Common assessment methods include satellite remote sensing, numerical simulations, and field measurements, each defining different cooling efficiency indicators. This methodological diversity creates uncertainties in optimizing BGI management. To address this, a literature review was conducted using Google Scholar, Web of Science, and Scopus, examining how the BGI cools urban space, which spatial data and methods are most effective, which methodological differences may affect the results, and what the current research gaps and innovative future directions are. The results suggest that remote sensing is ideal for large-scale BGI comparisons, numerical simulations for local development scenarios, and field measurements for assessing conditions closest to residents. Maximum BGI cooling intensity averages show 4 °C from remote sensing, 3 °C from field measurements, and 2 °C from numerical simulations. Differences in conclusions may arise from differences in the data resolution, model scale, BGI delineation method, and cooling range calculation. The key BGI characteristics include object size, vegetation fraction, foliage density, and spatial connectivity. Future research should prioritize the different methods of integration, BGI shape complexity effectiveness assessment, and effects of urban morphology on evaluating BGI characteristics’ effectiveness, and explore digital twin technology for BGI management optimization. This study integrates key information on BGI’s cooling capabilities, serving as a useful resource for both practitioners and researchers to support resilient city development. Full article

This article aims to highlight the importance of including quantitative measurements when conducting flow visualization tests, such as those performed in towing tanks, within fluid mechanics analysis. It investigates the possibility of measuring velocity fields with an economically accessible technique compared to other techniques that require large financial investments, such as traditional PIV. The development of a MATLAB R2024b code based on image recognition and the use of 3D-printed tracer particles is proposed. Code workflow and how to make a correct selection of the processing parameters and its activity are explained and demonstrated on artificial images, generated by a computer, as well as real images, obtained in a 2D-test in the tank, achieving an accuracy, in absolute values, of 95%. However, the proposed velocimetry system currently has one important limitation, the impossibility of distinguishing between particles in different planes, which limits the study to two-dimensional tests. Then, the opportunity to include this technique in the study of more complex tests requires further investigation. Full article

Carrier-phase measurements are essential in precise Global Navigation Satellite System (GNSS) positioning applications. The quality of those observations, as well as the final positioning result, is influenced by an extensive list of GNSS error sources, one of which is the receiver antenna phase center (PC) model. It has been well established that the antenna PC exhibits variability depending on the frequency, direction, and intensity of the incoming GNSS signal. To mitigate the corresponding range errors, phase center corrections (PCCs) are determined through a specialized procedure known as receiver antenna calibration and subsequently applied in data processing. In 2023, the Laboratory for Measurements and Measuring Technique (LMMT) of the Faculty of Geodesy, University of Zagreb, Croatia, initiated the development of a new robotic GNSS receiver antenna calibration system. The system implements absolute field calibration and PCC modeling through triple-difference (TD) carrier-phase observations and spherical harmonics (SH) expansion. This study presents and documents dual-frequency (L1 and L2) Global Positioning System (GPS) calibration results for several distinct receiver antennas. Furthermore, the main goals of this contribution are to evaluate the accuracy of dual-frequency GPS calibration results on the pattern level with respect to independent calibrations obtained from Geo++ GmbH and to extensively experimentally validate LMMT calibration results in the spatial (coordinate) domain, i.e., to investigate how the application of LMMT PPC models reflects on geodetic-grade GNSS positioning. Our experimental research results showed a submillimeter calibration accuracy, i.e., 0.36 mm for GPS L1 and 0.54 mm for the GPS L2 frequency. Furthermore, our field results confirmed that the application of LMMT PCC models significantly increases baseline accuracy and GNSS network solution accuracy when compared to type-mean PCC models of the International GNSS Service (IGS). Full article

Oyster aquaculture helps mitigate coastal eutrophication by assimilating organic nitrogen for biomass and by denitrification in both the oyster digestive tract and sediment below. Efforts are needed in the quantitative assessment of oysters’ multiple nitrogen removal pathways at large-scale aquaculture sites, especially removal in oyster bodies, which has been much less quantified among these pathways. This study takes a subtropical estuary (Shenzhen Bay in South China) as a testbed to conduct laboratory rearing experiments and field investigation. The laboratory results show that an oyster individual of harvest size can remove 0.59 mg-N day⁻¹ through denitrification within the body, which can be proportionally extrapolated to 4.6 kg-N km⁻² day⁻¹ in Shenzhen Bay. Assimilating field measurements into a “flux inventory model” yields the oyster-induced total nitrogen removal of Shenzhen Bay as 33.3 kg-N km⁻² day⁻¹, in which biomass harvest, denitrification in oysters, and sediment contributed 26%, 14%, and 60%, respectively. Additionally, the oyster’s filter-feeding lifestyle exports nitrogen from the water column to the sediment, which can contribute to ~3% of the daily nitrogen input into the bay. This study confirms the potential of oyster nitrogen removal, especially within the body, and provides a working framework for quantitative assessment of coastal nitrogen removal by the growing scale floating oyster aquaculture. Full article

This study emphasizes the role of Prosopis cineraria (Druce) in promoting sustainability through its contribution to carbon sequestration and climate change mitigation. The accurate quantification of the aboveground biomass (AGB) of Druce trees is essential for assessing their potential in reducing carbon emissions, yet remains a significant challenge. To address this, the study aimed to (1) estimate the AGB using destructive sampling; (2) analyze variability in existing allometric biomass equations; (3) evaluate remote sensing and machine learning techniques for estimating AGB and carbon sequestration; and (4) develop and validate new allometric equations based on field and remote sensing data. The Druce trees, with diameters at breast height ranging from 20.7 to 28.97 cm, exhibited an AGB of 208.3 kg per tree, which corresponds with a carbon sequestration stock of 97.89 kg C/tree. This translates to an annual carbon dioxide sequestration potential of 0.36 t C/tree. The newly developed allometric model (Model-2) was found to demonstrate superior accuracy, with performance metrics including a mean absolute percentage error (MAPE) of 2.6%, relative bias of 5.3%, R² of 0.906, mean absolute error (MAE) of 0.151, and root mean square error (RMSE) of 0.189. These improvements highlight the significant role of remote sensing technologies in advancing sustainable carbon monitoring and offer a more precise tool for enhancing global carbon sequestration models. By integrating field-based measurements and advanced technologies, this study strengthens our ability to assess the carbon sequestration potential of trees, contributing to more sustainable management and climate resilience strategies. Full article