bluuebunny/crossref_metadata_2025 huggingface dataset:
Examination of experienced coaches and physical education teachers' teaching methods and their perceptions regarding these methods—2023
Authors: Demiral Şengül , Nazıroğlu Meltem
Published: June 2024

Introduction

It is widely acknowledged that coaches and physical education teachers play an important role in supporting holistic development in children and ensuring optimal performance in the training processes carried out to acquire fundamental movements and sport-specific basic skills. However, there is a need for further information on how both groups utilize and value different teaching methods during the training. The present study aims to examine the perceptions of coaches and physical education teachers regarding the use and value of teaching methods.

Methods

The “Coaches’ Instructional Methods Utilization Scale” for coaches and the “Physical Education Teachers’ Perception of Teaching Methods Scale” for physical education teachers were administered to 114 coaches and 115 physical education teachers voluntarily participating from three randomly selected provinces of Türkiye. The Cronbach Alpha values ranged between .89 and .93 for the “Coaches’ Instructional Methods Utilization Scale” and between .90 and .96 for the “Physical Education Teachers’ Perception of Teaching Methods Scale”. Descriptive statistics were used in research, t-tests in binary comparisons, One-Way ANOVA in multiple comparisons, and Tukey's test in determining the source of differences.

Results

Similarities were observed in the most and least used methods by coaches and physical education teachers, as well as in their perceptions of the highest and lowest values for these methods. Additionally, coaches and physical education teachers exhibited similarities in their perceptions of value in terms of entertainment, learning, and motivation. It was observed that female physical education teachers had lower value perceptions among the levels of use of teaching methods and value perceptions according to gender. Comparing the usage levels and value perceptions of teaching methods by professional experience, significant differences were found in Exercise (B), Learner-Designed Individual Program (I), and Learner-initiated (J) methods for coaches, whereas no statistically significant difference was observed in value perceptions. Moreover, considering the physical education teachers, significant differences were found in Command (A), Self-Check (D), Guided Discovery (F), Problem-Solving: Single Solution (G) methods, and in value perceptions for the Exercise (B), Guided Discovery (F), Problem-Solving: Single Solution (G), Problem-Solving: Crating Different Paths (H), and Learner-initiated (J) values.
Linear System Identification-Oriented Optimal Tampering Attack Strategy and Implementation Based on Information Entropy with Multiple Binary Observations
Authors: Bai Zhongwei , Yu Peng , Liu Yan , Guo Jin
Published: June 2024

With the rapid development of computer technology, communication technology, and control technology, cyber-physical systems (CPSs) have been widely used and developed. However, there are massive information interactions in CPSs, which lead to an increase in the amount of data transmitted over the network. The data communication, once attacked by the network, will seriously affect the security and stability of the system. In this paper, for the data tampering attack existing in the linear system with multiple binary observations, in the case where the estimation algorithm of the defender is unknown, the optimization index is constructed based on information entropy from the attacker’s point of view, and the problem is modeled. For the problem of the multi-parameter optimization with energy constraints, this paper uses particle swarm optimization (PSO) to obtain the optimal data tampering attack solution set, and gives the estimation method of unknown parameters in the case of unknown parameters. To implement the real-time improvement of online implementation, the BP neural network is designed. Finally, the validity of the conclusions is verified through numerical simulation. This means that the attacker can construct effective metrics based on information entropy without the knowledge of the defense’s discrimination algorithm. In addition, the optimal attack strategy implementation based on PSO and BP is also effective.
Exploring the Aerodynamic Effect of Blade Gap Size via a Transient Simulation of a Four-Stage Turbine
Authors: Hu Xinlei , Cai Le , Chen Yingjie , Li Xuejian , Wang Songtao , Fang Xinglong , Fang Kanxian
Published: June 2024

With the impact of size on low-pressure turbines (LPTs) increasing, the gap between the blades has shrunk, inevitably influencing the unsteady effects inside the turbine. In this study, the aerodynamic effect of the blade gap size is investigated using a compressible unsteady Reynolds-averaged Navier–Stokes (URANS) model on the basis of a four-stage LPT. Simulations are conducted in which the gap between the third-stage stator (S3) and rotor (R3) varies from 0.2 to 0.8 times the axial chord length of the R3 blade. The multi-stage environment reflects the complexity of real low-Reynolds flow fields. Computational fluid dynamics is used to analyze the flow field in detail. The results demonstrate that in the small-gap (AG-0.2) case, the turbulence kinetic energy (TKE) level of the S3 wake close to the R3 leading edge is four-thirds of that in the large-gap (AG-0.8) case. The higher intensity of the wake impacting on the blade results in a higher inverse pressure gradient in the rear part of the R3 suction surface, which increases the profile loss. However, the AG-0.2 case leads to fewer losses caused by the passage vortex in the hub area under the influence of the higher intensity of the wake.
Does the Trade of Livestock Products Enhance Micro-Nutrient Availability While Minimizing Environmental Impact?
Authors: Liu Xia , Li Qianqian , Liu Ling , Bai Zhaohai
Published: June 2024

Providing sufficient, high-quality food without compromising efforts in climate change and environmental pollution control is a long-term imperative for humanity. Livestock product trade may help bridge the gap in micro-nutrient supply; however, its potential environmental impacts remain underexplored. Using data from 200 countries and 77 different livestock commodities from 1961 to 2019, this study uncovers the impact of livestock trade on micro-nutrient productivity per livestock unit and per feed nitrogen input. Our results indicate that livestock trade has improved productivity for all seven studied micro-nutrients over the past 59 years, except for vitamin A. This improvement has led to a substantial reduction in the number of livestock units and feed nitrogen requirements needed to deliver the same amount of micro-nutrients, thereby reducing related greenhouse gas emissions and nitrogen losses globally. Generally, livestock trade has become more optimal and functional in terms of livestock productivity and feed use efficiency, particularly in the most recent decade, although there were slight differences between various micro-nutrients. We recommend continuing and potentially increasing international livestock trade, given the higher efficiency gap between exporting and importing countries; however, this should be structured more appropriately.
Remediation of Pb-, Zn-, Cu-, and Cd-Contaminated Soil in a Lead–Zinc Mining Area by Co-Cropping Ilex cornuta and Epipremnum aureum with Illite Application
Authors: Li Qi , Tang Yanxin , Dong Dubin , Wang Xili , Wu Xuqiao , Gul Saima , Li Yaqian , Xie Xiaocui , Liu Dan , Xu Weijie
Published: June 2024

Phytoremediation is considered an effective strategy for remediation of heavy-metal-contaminated soil in mining areas. However, single-species plants cannot reach the highest potential for uptake of heavy metals due to inhibition of their growth by high concentrations of heavy metals in the soil. Therefore, this study has explored the effects of illite application and two plant species’ co-cropping on soil quality, plant growth, and heavy metal transformation in a soil–plant system. The results reveal that the addition of 1% (mass fraction) of illite significantly enhances soil pH. The co-cropping of Ilex cornuta and Epipremnum aureum is beneficial for improving the organic matter content of the soil. The contents of EDTA-extractable Pb, Zn, and Cu were significantly reduced by 29.8–32.5%, 1.85–5.72%, and 30.0–32.9%, respectively, compared to the control. The co-cropping of Ilex cornuta and Epipremnum aureum promoted enrichment effects of Epipremnum aureum on Pb and Ilex cornuta on Cd (p < 0.05). The co-cropping pattern lowered the biomass of Ilex cornuta and Epipremnum aureum; however, co-cropping of Ilex cornuta and Epipremnum aureum promoted the elimination of Pb, Zn, Cu, and Cd from the soil at 13.0–75.8%, 11.1–38.2%, 8.39–88.4%, and 27.8–72.5%, respectively. It is concluded that illite application combined with co-cropping of Ilex cornuta and Epipremnum aureum is highly effective for the elimination of Pb, Zn, Cu, and Cd from contaminated soil. This study provides a theoretical basis and pathway for the restoration of heavy-metal-contaminated soil in mining with the application of bentonite combined with phytoremediation.
Effects of Different Essential Oil Blends and Fumaric Acid on In Vitro Fermentation, Greenhouse Gases, Nutrient Degradability, and Total and Molar Proportions of Volatile Fatty Acid Production in a Total Mixed Ration for Dairy Cattle
Authors: Ike Kelechi A. , Adelusi Oludotun O. , Alabi Joel O. , Olagunju Lydia K. , Wuaku Michael , Anotaenwere Chika C. , Okedoyin Deborah O. , Gray DeAndrea , Dele Peter A. , Subedi Kiran , Kholif Ahmed E. , Anele Uchenna Y.
Published: June 2024

The present study evaluated the inclusion of fumaric acid and essential oil blends (EOBs) containing anise, cedarwood, clove, cumin, eucalyptus, garlic, ginger, lavender, lemongrass, nutmeg, oregano, and peppermint at different proportions on in vitro dry matter (DM) disappearance (DMD), fiber fraction disappearance, the efficiency of microbial production, and the total volatile fatty acids (VFAs). Ten treatments without (control treatment) or with different EOB/fumaric combinations were used in the study with eight replicates. The EOB inclusion level was 200 μL/g of feed (total mixed ration, (TMR)) while fumaric acid was administered at 3% of the TMR (DM basis). The highest DMD, in vitro true degradable DM, partitioning factor (PF24), and in vitro apparent degradable DM were recorded for the fumaric only treatment and the control. Neutral detergent fiber disappearance was reduced with the inclusion of EOB/fumaric combinations. The production of microbial mass and undegraded DM were higher (p < 0.001) for all EOBs and EOB and fumaric treatments. The inclusion of EOB and fumaric combinations reduced (p < 0.001) the total gas production, methane, and ammonia, with a higher PF24 value noted for EOB3 treatment. The inclusion of individual EOB1 containing garlic, lemongrass, cumin, lavender, and nutmeg in a ratio of 4:2:2:1:1 or combined with fumaric acid yielded the highest propionate concentration across all treatments. We concluded that EOBs decreased methane production and nutrient degradability with better results with the individual EOB1 or EOB1/fumaric combination, which showed a potential enhancement in energy production.
Correction: Park et al. Identification of a Novel KTi-1 Allele Associated with Reduced Trypsin Inhibitor Activity in Soybean Accessions. Agriculture 2023, 13, 2070
Authors: Park Aron , Kang Se-Hee , Kang Byeong-Hee , Chowdhury Sreeparna , Shin Seo-Young , Lee Won-Ho , Lee Jeong-Dong , Lee Sungwoo , Choi Yu-Mi , Ha Bo-Keun
Published: June 2024

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A Multi-Farm Global-to-Local Expert-Informed Machine Learning System for Strawberry Yield Forecasting
Authors: Beddows Matthew , Leontidis Georgios
Published: June 2024

The importance of forecasting crop yields in agriculture cannot be overstated. The effects of yield forecasting are observed in all the aspects of the supply chain from staffing to supplier demand, food waste, and other business decisions. However, the process is often inaccurate and far from perfect. This paper explores the potential of using expert forecasts to enhance the crop yield predictions of our global-to-local XGBoost machine learning system. Additionally, it investigates the ERA5 climate model’s viability as an alternative data source for crop yield forecasting in the absence of on-farm weather data. We find that, by combining both the expert’s pre-season forecasts and the ERA5 climate model with the machine learning model, we can—in most cases—obtain better forecasts that outperform the growers’ pre-season forecasts and the machine learning-only models. Our expert-informed model attains yield forecasts for 4 weeks ahead with an average RMSE of 0.0855 across all the plots and an RMSE of 0.0872 with the ERA5 climate data included.
Low-Cadmium Wheat Cultivars Limit the Enrichment, Transport and Accumulation of Cadmium
Authors: Bai Liyong , Ding Suo , Li Xiaoli , Ning Chuanli , Liu He , Sun Mei , Liu Dongmei , Zhang Ke , Li Shuangshuang , Yu Xiaojing , Dai Jiulan
Published: June 2024

Low-cadmium (Cd) accumulating wheat cultivars (LAWC-Cds) can effectively reduce the total Cd content in wheat grains (Grain-Cd). Thirteen LAWC-Cds were planted in three fields to study the enrichment, transport, and accumulation patterns of Cd in LAWC-Cds. Compared with the soil properties before planting, the soil pH and the total Cd content in the soil decreased, while the Cd content in the diethylenetriaminepentaacetic acid extract, soil conductivity, and soil organic matter increased at wheat maturity. The Cd enrichment capacity of the different organs of wheat decreased in the following order: root > leaf > rachis > stem > glume > grain. The dynamics of Cd accumulation in roots affected Grain-Cd, and these factors were negatively correlated. The Cd content and Cd accumulation in all organs of LAWC-Cds showed strong negative correlations with the lengths of the first and second internodes and highly significant positive correlations with both grains per spike and awn length. Structural equation modeling showed that the Cd content of wheat organs had the most direct effect (0.639) in determining Grain-Cd, and soil properties had the largest effect (0.744) in influencing Grain-Cd. This study is important for screening wheat cultivars with stable low Cd-accumulation characteristics.
Genetic and Molecular Regulation of Cotton Fiber Initiation and Elongation
Authors: Bai Fang , Scheffler Jodi
Published: June 2024

Cotton fiber, a crucial and sustainable resource for global textile production, undergoes a complex five-stage developmental process, encompassing initiation, elongation, transition, secondary cell wall biosynthesis, and maturation. These elongated single-cell fibers originate from the outer ovule epidermis. The development of cotton fibers involves intricate changes in gene expression and physiological processes, resulting in a nearly pure cellulose product that is vital for the global cotton industry. Decoding the genes associated with fiber development enhances our understanding of cotton fiber mechanisms and facilitates the cultivation of varieties with enhanced quality. In recent decades, advanced omics approaches, including genomics, transcriptomics, and proteomics, have played a pivotal role in identifying the genes and gene products linked to cotton fiber development, including the MYB transcription factor family, which coordinates cotton fiber development. Molecular studies have revealed the transcription factors, like MYB, WRKY, Homeodomain Leucine Zipper (HD-ZIP), and basic helix–loop–helix (bHLH), influencing fiber initiation and elongation. The intricate interplay of phytohormones, like auxin, gibberellic acid (GA), brassinosteroids (BRs), jasmonic acid (JA), ethylene, abscisic acid (ABA), and cytokinin, is explored, providing a comprehensive perspective on the shaping of cotton fibers. Numerous candidate genes and cellular processes affecting various aspects of fiber development hold promise for genetic engineering or marker-assisted breeding to improve fiber quality. This review presents a comprehensive overview of key achievements in cotton molecular biology, with a specific emphasis on recent advancements in understanding the transcription factors and phytohormones involved in cotton fiber initiation and elongation.
Cardiac Disease Related to Primary Hyperthyroidism in a 20-Year-Old Mule
Authors: Brown Kaitlin , Williams Louie Elizabeth , Pinn-Woodcock Toby , Pearson Erin , Pearson Garett B. , Marr Jacqueline , Hackett Eileen S. , Rath Brown Laura , Mitchell Katharyn J.
Published: June 2024

Primary hyperthyroidism is a rarely diagnosed endocrinopathy in equids and there have been no previous reports of structural and functional cardiac changes associated with hyperthyroidism in these species. This case report investigates a 20-year-old mule gelding that presented for a three-month history of thin body condition despite polyphagia, with a heart murmur and elevated free and total thyroid hormone concentrations. On presentation, physical exam revealed a body condition score of two out of nine, persistent tachycardia, pansystolic heart murmur and firm bilateral ventral proximal cervical masses. Bloodwork confirmed markedly elevated free T4, total T4 and T3 concentrations. Echocardiogram demonstrated left ventricular concentric hypertrophy with increased ventricular and atrial systolic function. Bilateral thyroidectomy was performed under standing sedation without complications. Histopathology demonstrated adenocarcinoma of the left thyroid gland and multiple adenomas with osseous metaplasia within the right thyroid. The mule was supplemented with levothyroxine sodium two weeks post-op after a thyroid panel demonstrated undetectable concentrations. Polyphagia resolved following surgery and the mule began gaining weight. Echocardiographic changes improved but did not resolve at two years post-operative. Continued bi-annual follow up and monitoring of thyroid levels was recommended. This case represents the first documentation of hemodynamically relevant cardiac remodeling in an equid associated with primary hyperthyroidism.
Feeding a Novel Mannan-Rich Yeast Carbohydrate Product Improves Production Performance and Humoral Immunity of Broiler Chickens
Authors: Wang Anhao , Archile Anangelina , Patterson Rob
Published: June 2024

The current study examined the benefits of a novel mannan-rich yeast carbohydrate product (YM) on broiler chicken growth performance and immune response against sheep red blood cells (SRBCs). A total of 144 newly hatched male Cornish cross broiler chicks were randomly assigned to four treatments with 12 cages per treatment and three birds per cage. The treatments were (1) control, basal diet; (2) YCW, basal diet + 1 g/kg yeast cell wall; (3) YM1, basal diet + 0.5 g/kg of a novel yeast mannan-rich product (YM); and (4) YM2, basal diet + 1 g/kg YM. Growth performance was measured at 14, 28, and 35 days of age (d). At 26 and 27 d, nine birds per treatment were immunized intravenously with SRBCs, and antibody responses against SRBCs were analyzed through a hemagglutination assay 7 days post-inoculation. Supplementing YM tended to improve broiler chicken weight gain from 29 to 35 d (p = 0.053). An improvement in the feed conversion ratio (FCR) was observed in the birds fed YM diets during 29–35 d and over the entire experimental period (0–35 d; p < 0.05). Furthermore, birds fed YM2 diets had more robust antibody responses against SRBCs than the control birds (p = 0.033). In conclusion, dietary supplementation of YM improved broiler chicken growth performance and antibody response against SRBCs.
The Germanic Model of Liability for Diseases of Animals in Sale Transactions: Historical Heritage or the Dead Weight of Past Generations? Factors Affecting the Form of Legal Standards for Warranty
Authors: Dzikowski Andrzej
Published: June 2024

The subject of the analysis is the Germanic model of liability for the physical defects of animals examined through examples in Europe. Methods of legal analysis and interpretation are used. Contemporary (Austria, Belgium, France, Luxembourg and Switzerland) and historical examples (Germany and Poland) are examined and described. The characteristics of this model and the historical conditions which shaped the current legal state are demonstrated. It is shown where particular civil law systems in Europe have maintained the Germanic model of warranty to this day, where other systems have replaced it with another model and what factors have influenced this. The analysis is comparative in regard to legal systems and oriented toward veterinary science.
The Animal Welfare Consequences and Moral Implications of Lethal and Non-Lethal Fox Control Methods
Authors: de Ridder Nathalie , Knight Andrew
Published: June 2024

Control methods are applied worldwide to reduce predation on livestock by European red foxes (Vulpes vulpes). Lethal methods can inflict suffering; however, moral debate about their use is lacking. Non-lethal methods can also inflict suffering and can unintentionally lead to death, and yet both the welfare consequences and ethical perspectives regarding their use are rarely discussed. The aim of this study was to investigate the animal welfare consequences, the level of humaneness, the ethical considerations and the moral implications of the global use of fox control methods according to Tom Regan’s animal rights view and Peter Singer’s utilitarian view. According to Regan, foxes ought not to be controlled by either lethal or potentially harmful non-lethal methods because this violates the right of foxes not to be harmed or killed. According to Singer, if an action maximises happiness or the satisfaction of preferences over unhappiness or suffering, then the action is justified. Therefore, if and only if the use of fox control methods can prevent suffering and death in livestock in a manner that outweighs comparable suffering and death in foxes is one morally obligated to use them. It is clear that lethal fox control methods and some non-lethal methods are inhumane.
The Molecular Mouse System: A New Useful Tool for Guiding Antimicrobial Therapy in Critically Ill Septic Patients
Authors: Mauri Carola , Consonni Alessandra , Briozzo Elena , Giubbi Chiara , Meroni Elisa , Tonolo Silvia , Luzzaro Francesco
Published: June 2024

Bloodstream infections (BSI) caused by multidrug-resistant (MDR) bacteria, pose a major threat for patients, especially for those who are immunosuppressed. Rapid pathogen detection and characterization from positive blood cultures are crucial in the management of patients with BSI to enable an adequate and timely antimicrobial therapy. This study aimed to investigate the potential role of the Molecular Mouse system, a new CE IVD molecular test designed to rapidly detect the causative agents of bacteremia and their resistance determinants, in the management of the therapy in critically ill patients. Agreement between the results of the Molecular Mouse and the conventional routine method was also considered. Overall, 100 positive blood cultures were collected from septic critically ill patients from May 2023 to January 2024 and analyzed with Molecular Mouse and routine protocols. The new instrument consistently agreed with the routine protocols in the case of monomicrobial blood cultures, while some discrepancies were obtained in the polymicrobial samples. Antimicrobial resistance genes were detected in 35 samples, with vanA and CTX-M-1/9 groups being the most frequently detected targets. Therapy was adjusted in 42 critically ill patients confirming the importance of new rapid molecular tests in the management of positive blood cultures, to adjust empirical therapy and use new antibiotics accurately.
Emergence of Rarely Reported Extensively Drug-Resistant Salmonella Enterica Serovar Paratyphi B among Patients in East China
Authors: Peng Jiefu , Feng Jingchao , Ji Hong , Kong Xiaoxiao , Hong Jie , Zhu Liguo , Qian Huimin
Published: June 2024

Background: In recent years, global concern over increasing multidrug resistance (MDR) among various Salmonella serotypes has grown significantly. However, reports on MDR Salmonella Paratyphi B remain scarce, let alone the extensively drug-resistant (XDR) strains. Methods: In this retrospective study, we investigated the isolates of Salmonella Paratyphi B in Jiangsu Province over the past decade and carried out antimicrobial susceptibility tests, then the strains were sequenced and bioinformatics analyses were performed. Results: 27 Salmonella Paratyphi B strains were identified, of which the predominant STs were ST42 (11), ST86 (10), and ST2814 (5). Among these strains, we uncovered four concerning XDR Salmonella Paratyphi B ST2814 strains (4/5) which were previously unreported. These alarmingly resistant isolates showed resistance to all three major antibiotic classes for Salmonella treatment and even the last resort treatment tigecycline. Bioinformatics analysis revealed high similarity between the plasmids harbored by these XDR strains and diverse Salmonella serotypes and Escherichia coli from China and neighboring regions. Notably, these four plasmids carried the ramAp gene responsible for multiple antibiotic resistance by regulating the AcrAB-TolC pump, predominantly originating from China. Additionally, a distinct MDR ST42(1/11) strain with an ICE on chromosome was also identified. Furthermore, phylogenetic analysis of global ST42/ST2814 isolates highlighted the regional specificity of these strains, with Jiangsu isolates clustering together with domestic isolates and XDR ST2814 forming a distinct branch, suggesting adaptation to local antibiotic pressures. Conclusions: This research underscores the pressing need for closely monitoring the MDR/XDR Salmonella Paratyphi B, particularly the emerging ST2814 strains in Jiangsu Province, to effectively curb its spread and protect public health. Moreover, surveillance should be strengthened across different ecological niches and genera to track resistance genes and horizontal gene transfer elements under the concept of “ONE HEALTH”.
Creating Interactive Scenes in 3D Educational Games: Using Narrative and Technology to Explore History and Culture
Authors: Kaźmierczak Rafał , Skowroński Robert , Kowalczyk Cezary , Grunwald Grzegorz
Published: June 2024

Three-dimensional games are an indispensable tool in education and cultural transmission, offering users immersive experiences that facilitate learning through engagement and direct experience. The aim of this study was to design and implement an advanced cutscene sequencer in Unity 3D, targeted at educational and cultural games, to assist game developers in producing cinematic interludes, which are a key narrative element in games. The project methodology encompassed a detailed process of planning, design, and implementation. This involved the comprehensive use of various tools, including Unity 3D for game development, C# for scripting, Visual Studio for integrated development, Git for version control, Blender for 3D modeling, Substance Painter for texturing, and Audacity for audio editing. These tools collectively facilitated the development of a robust cutscene sequencer system designed to create engaging and dynamic narrative scenes. The project’s results indicate that the use of an advanced sequencer can significantly impact the efficiency and creativity of the game and educational material creation process, offering developers the opportunity to explore practically unlimited viewing perspectives. This tool enables the creation of rich and diverse visual experiences, which is crucial for engaging and educating players.
Analysis of Electromagnetic Field Characteristics of Wave Glider
Authors: Xie Taotao , Zhang Jiawei , Xiao Dawei , Ji Qing
Published: June 2024

A wave glider is an ocean observation platform that utilizes wave energy to drive and solar energy to power. Its metal structure will generate related electromagnetic fields due to corrosion and underwater motion. In the detection of weak electromagnetic field signals underwater, its own electromagnetic field characteristics will have an impact on signal detection. To study the applicability of electric field sensors and magnetic field sensors on wave glider platforms, the structural characteristics of the wave glider were analyzed, and the installation positions of electric field sensors and magnetic field sensors were designed based on the different motion states of the water surface mother body and underwater towing body. The measured electromagnetic field data of the wave glider platform were measured, and the measured data were analyzed. It was determined that the interference electric field energy under typical working conditions of the wave glider was mainly concentrated within 1 Hz, which decreased with increasing frequency, and the magnitude was mV/m. The magnitude of the interference magnetic field is several tens of nT, indicating that the electromagnetic field interference is significant during the working state of the wave glider. Installing an electric field sensor directly at the bottom of the wave glider will cause significant noise interference, while installing the magnetic field sensor directly at the bottom of the tractor will affect the servo and the shaking-induced magnetic field. Moreover, wave gliders should not use electric field signals below 1 Hz as signal sources, but they can utilize axial frequency electromagnetic fields to detect weak electromagnetic signals underwater.
Particle Sizing and Surface Area Measurements: A Comparative Assessment of Commercial Air Permeability and Laser Light Diffraction Instruments
Authors: Konstanty Janusz , Tyrala Dorota
Published: June 2024

Six different commercial powders, finer than 45 μm, were used for examining the effects of particle characteristics on mean particle size and specific surface area. The measurements were carried out using the most commonly used air permeability- and laser light diffraction (scattering) techniques. As the air permeability method has been used as a benchmark for decades in the powder metallurgy (P/M) industry, the physical phenomena that govern the passage of gas through the powder bed under laminar flow conditions were also presented. The experimental data indicate that both methods give similar results for spherical powders. The advantage of laser light systems over gas permeameters is the ability to provide additional information on particle size distribution. Irregularly shaped powders should be analyzed by both techniques, relying on gas permeametry for surface area measurements and on laser light diffraction for the estimation of mean particle size and size distribution. Application of scanning electron microscopy as a complementary technique was found very helpful in the interpretation of data through visualization of individual particles.
Pyramid Feature Attention Network for Speech Resampling Detection
Authors: Zhou Xinyu , Zhang Yujin , Wang Yongqi , Tian Jin , Xu Shaolun
Published: June 2024

Speech forgery and tampering, increasingly facilitated by advanced audio editing software, pose significant threats to the integrity and privacy of digital speech avatars. Speech resampling is a post-processing operation of various speech-tampering means, and the forensic detection of speech resampling is of great significance. For speech resampling detection, most of the previous works used traditional methods of feature extraction and classification to distinguish original speech from forged speech. In view of the powerful ability of deep learning to extract features, this paper converts the speech signal into a spectrogram with time-frequency characteristics, and uses the feature pyramid network (FPN) with the Squeeze and Excitation (SE) attention mechanism to learn speech resampling features. The proposed method combines the low-level location information and the high-level semantic information, which dramatically improves the detection performance of speech resampling. Experiments were carried out on a resampling corpus made on the basis of the TIMIT dataset. The results indicate that the proposed method significantly improved the detection accuracy of various resampled speech. For the tampered speech with a resampling factor of 0.9, the detection accuracy is increased by nearly 20%. In addition, the robustness test demonstrates that the proposed model has strong resistance to MP3 compression, and the overall performance is better than the existing methods.
Enhancing Livestock Detection: An Efficient Model Based on YOLOv8
Authors: Fang Chengwu , Li Chunmei , Yang Peng , Kong Shasha , Han Yaosheng , Huang Xiangjie , Niu Jiajun
Published: June 2024

Maintaining a harmonious balance between grassland ecology and local economic development necessitates effective management of livestock resources. Traditional approaches have proven inefficient, highlighting an urgent need for intelligent solutions. Accurate identification of livestock targets is pivotal for precise livestock farming management. However, the You Only Look Once version 8 (YOLOv8) model exhibits limitations in accuracy when confronted with complex backgrounds and densely clustered targets. To address these challenges, this study proposes an optimized CCS-YOLOv8 (Comprehensive Contextual Sensing YOLOv8) model. First, we curated a comprehensive livestock detection dataset encompassing the Qinghai region. Second, the YOLOv8n model underwent three key enhancements: (1) incorporating a Convolutional Block Attention Module (CBAM) to accentuate salient image information, thereby boosting feature representational power; (2) integrating a Content-Aware ReAssembly of FEatures (CARAFE) operator to mitigate irrelevant interference, improving the integrity and accuracy of feature extraction; and (3) introducing a dedicated small object detection layer to capture finer livestock details, enhancing the recognition of smaller targets. Experimental results on our dataset demonstrate the CCS-YOLOv8 model’s superior performance, achieving 84.1% precision, 82.2% recall, 84.4% mAP@0.5, 60.3% mAP@0.75, 53.6% mAP@0.5:0.95, and 83.1% F1-score. These metrics reflect substantial improvements of 1.1%, 7.9%, 5.8%, 6.6%, 4.8%, and 4.7%, respectively, over the baseline model. Compared to mainstream object detection models, CCS-YOLOv8 strikes an optimal balance between accuracy and real-time processing capability. Its robustness is further validated on the VisDrone2019 dataset. The CCS-YOLOv8 model enables rapid and accurate identification of livestock age groups and species, effectively overcoming the challenges posed by complex grassland backgrounds and densely clustered targets. It offers a novel strategy for precise livestock population management and overgrazing prevention, aligning seamlessly with the demands of modern precision livestock farming. Moreover, it promotes local environmental conservation and fosters sustainable development within the livestock industry.
Precipitation Simulation and Dynamic Response of a Transmission Line Subject to Wind-Driven Rain during Super Typhoon Lekima
Authors: Sun Jianping , Huang Mingfeng , Liao Sunce , Lou Wenjuan
Published: June 2024

Typhoons bring great damages to transmission line systems located in coastal areas. Strong wind and extreme precipitation are the main sources of damaging effects. Transmission lines suffered from wind-driven rain exhibit more susceptibility to damage due to the coupled effect of wind and rainwater. This paper presents an integrated numerical simulation framework based on mesoscale WRF model, multiphase CFD model and FEM model to analyze the motions of a transmission line subjected to coupled wind and rain loads during typhoon events. A full-scale transmission line in Zhoushan Island is employed to demonstrate the effectiveness of the proposed framework by simulating typhoon evolution in terms of wind fields and rainfall, solving the coupled wind and rain fields around the conductor and predicting the dynamic responses of the transmission line during Super Typhoon Lekima in 2019. The results show that the horizontal displacements of the transmission line under the joint actions of wind and rain increase approximately 17–18% compared to those of wind loads only. It is important to consider the coupled effects of wind-driven rain on conductors in the design of transmission lines under typhoon conditions.
Novel Insights in Soil Mechanics: Integrating Experimental Investigation with Machine Learning for Unconfined Compression Parameter Prediction of Expansive Soil
Authors: Alnmr Ammar , Hosamo Haidar Hosamo , Lyu Chuangxin , Ray Richard Paul , Alzawi Mounzer Omran
Published: June 2024

This paper presents a novel application of machine learning models to clarify the intricate behaviors of expansive soils, focusing on the impact of sand content, saturation level, and dry density. Departing from conventional methods, this research utilizes a data-centric approach, employing a suite of sophisticated machine learning models to predict soil properties with remarkable precision. The inclusion of a 30% sand mixture is identified as a critical threshold for optimizing soil strength and stiffness, a finding that underscores the transformative potential of sand amendment in soil engineering. In a significant advancement, the study benchmarks the predictive power of several models including extreme gradient boosting (XGBoost), gradient boosting regression (GBR), random forest regression (RFR), decision tree regression (DTR), support vector regression (SVR), symbolic regression (SR), and artificial neural networks (ANNs and proposed ANN-GMDH). Symbolic regression equations have been developed to predict the elasticity modulus and unconfined compressive strength of the investigated expansive soil. Despite the complex behaviors of expansive soil, the trained models allow for optimally predicting the values of unconfined compressive parameters. As a result, this paper provides for the first time a reliable and simply applicable approach for estimating the unconfined compressive parameters of expansive soils. The proposed ANN-GMDH model emerges as the pre-eminent model, demonstrating exceptional accuracy with the best metrics. These results not only highlight the ANN’s superior performance but also mark this study as a groundbreaking endeavor in the application of machine learning to soil behavior prediction, setting a new benchmark in the field.
An Ergonomic Risk Assessment System Based on 3D Human Pose Estimation and Collaborative Robot
Authors: Menanno Marialuisa , Riccio Carlo , Benedetto Vincenzo , Gissi Francesco , Savino Matteo Mario , Troiano Luigi
Published: June 2024

Human pose estimation focuses on methods that allow us to assess ergonomic risk in the workplace and aims to prevent work-related musculoskeletal disorders (WMSDs). The recent increase in the use of Industry 4.0 technologies has allowed advances to be made in machine learning (ML) techniques for image processing to enable automated ergonomic risk assessment. In this context, this study aimed to develop a method of calculating joint angles from digital snapshots or videos using computer vision and ML techniques to achieve a more accurate evaluation of ergonomic risk. Starting with an ergonomic analysis, this study explored the use of a semi-supervised training method to detect the skeletons of workers and to estimate the positions and angles of their joints. A criticality index, based on RULA scores and fuzzy rules, is then calculated to evaluate possible corrective actions aimed at reducing WMSDs and improving production capacity using a collaborative robot that supports workers in carrying out critical operations. This method is tested in a real industrial case in which the manual assembly of electrical components is conducted, achieving a reduction in overall ergonomic stress of 13% and an increase in production capacity of 33% during a work shift. The proposed approach can overcome the limitations of recent developments based on computer vision or wearable sensors by performing an assessment with an objective and flexible approach to postural analysis development.
The Intersection of Architectural Conservation and Energy Efficiency: A Case Study of Romanian Heritage Buildings
Authors: Șerban Simona Elena , Catalina Tiberiu , Popescu Razvan , Popescu Lelia
Published: June 2024

In Europe, it is estimated that 14% of existing buildings were built before 1919, whereas 26% were built before 1945. In Romania, about 31% of the buildings date from before 1961, contributing to the current stock of old buildings with historic and architectural value in the country. This paper illustrates the current state of buildings with historic and architectural value in Romania, alongside a case study of a representative administrative building in Câmpulung, Romania. The analysis of the Town Hall building in Câmpulung, Romania, demonstrates that potential energy savings of up to 47.53% can be achieved by implementing interventions such as upgrading windows, insulating the attic, and installing photovoltaic panels. The highest energy reduction is obtained by replacing the window glass with a value of 18.16% with attic insulation with a value of 16.1%. This paper also presents indoor measurements of temperature and humidity in different offices positioned in the north and the south. The study conducted on the south façade office revealed consistent temperatures ranging from 21.7 °C to 24.4 °C, with an average of 23.31 °C. However, the humidity levels fluctuated considerably, ranging from 17.1% to 39.1%, with an average of 26.89%. The sun-exposed section of the building saw relatively stable temperature conditions, but the varying humidity levels could have a detrimental impact on the quality of the indoor atmosphere and potentially decrease the effectiveness of the workforce. By contrast, the north façade office exhibited lower and more fluctuating temperatures, ranging from 19.8 °C to 23.6 °C, with an average of 21.74 °C. Additionally, it had higher and more stable humidity levels, ranging between 19.5% and 41.7%, with an average of 29.83%. A thermographic analysis was performed on the north façade of the Câmpulung Town Hall, utilizing thermal imaging technology to detect areas of heat loss, and thus identifying the energy inefficiency problems of the building’s exterior. The investigation found notable variations in temperature, especially around the windows, where temperatures could be as high as 14.1 °C, highlighting the insufficiency of the building’s antiquated timber-framed windows in preventing energy loss.
Probabilistic Mixture Model-Based Spectral Unmixing
Authors: Hoidn Oliver , Mishra Aashwin Ananda , Mehta Apurva
Published: June 2024

Spectral unmixing attempts to decompose a spectral ensemble into the constituent pure spectral signatures (called endmembers) along with the proportion of each endmember. This is essential for techniques like hyperspectral imaging (HSI) used in environment monitoring, geological exploration, etc. Several spectral unmixing approaches have been proposed, many of which are connected to hyperspectral imaging. However, most extant approaches assume highly diverse collections of mixtures and extremely low-loss spectroscopic measurements. Additionally, current non-Bayesian frameworks do not incorporate the uncertainty inherent in unmixing. We propose a probabilistic inference algorithm that explicitly incorporates noise and uncertainty, enabling us to unmix endmembers in collections of mixtures with limited diversity. We use a Bayesian mixture model to jointly extract endmember spectra and mixing parameters while explicitly modeling observation noise and the resulting inference uncertainties. We obtain approximate distributions over endmember coordinates for each set of observed spectra while remaining robust to inference biases from the lack of pure observations and the presence of non-isotropic Gaussian noise. As a direct impact of our methodology, access to reliable uncertainties on the unmixing solutions would enable robust solutions to noise, as well as informed decision-making for HSI applications and other unmixing problems.
A Deep Learning Approach for the Fast Generation of Synthetic Computed Tomography from Low-Dose Cone Beam Computed Tomography Images on a Linear Accelerator Equipped with Artificial Intelligence
Authors: Vellini Luca , Zucca Sergio , Lenkowicz Jacopo , Menna Sebastiano , Catucci Francesco , Quaranta Flaviovincenzo , Pilloni Elisa , D'Aviero Andrea , Aquilano Michele , Di Dio Carmela , Iezzi Martina , Re Alessia , Preziosi Francesco , Piras Antonio , Boschetti Althea , Piccari Danila , Mattiucci Gian Carlo , Cusumano Davide
Published: June 2024

Artificial Intelligence (AI) is revolutionising many aspects of radiotherapy (RT), opening scenarios that were unimaginable just a few years ago. The aim of this study is to propose a Deep Leaning (DL) approach able to quickly generate synthetic Computed Tomography (CT) images from low-dose Cone Beam CT (CBCT) acquired on a modern linear accelerator integrating AI. Methods: A total of 53 patients treated in the pelvic region were enrolled and split into training (30), validation (9), and testing (14). A Generative Adversarial Network (GAN) was trained for 200 epochs. The image accuracy was evaluated by calculating the mean and mean absolute error (ME and ME) between sCT and CT. RT treatment plans were calculated on CT and sCT images, and dose accuracy was evaluated considering Dose Volume Histogram (DVH) and gamma analysis. Results: A total of 4507 images were selected for training. The MAE and ME values in the test set were 36 ± 6 HU and 7 ± 6 HU, respectively. Mean gamma passing rates for 1%/1 mm, 2%/2 mm, and 3%/3 mm tolerance criteria were respectively 93.5 ± 3.4%, 98.0 ± 1.3%, and 99.2 ± 0.7%, with no difference between curative and palliative cases. All the DVH parameters analysed were within 1 Gy of the difference between sCT and CT. Conclusion: This study demonstrated that sCT generation using the DL approach is feasible on low-dose CBCT images. The proposed approach can represent a valid tool to speed up the online adaptive procedure and remove CT simulation from the RT workflow.
Variation in and Regulation of Carbon Use Efficiency of Grassland Ecosystem in Northern China
Authors: Feng Zhuoqun , Zhou Li , Zhou Guangsheng , Wang Yu , Zhou Huailin , Lv Xiaoliang , Liu Liheng
Published: June 2024

Ecosystem carbon use efficiency (CUE) is a key parameter in the carbon cycling of terrestrial ecosystems. The magnitude of CUE reflects the ecosystem’s potential for CO2 sequestration. China’s grasslands play an important role in the carbon cycle. Here, we aimed to investigate the comparation of CUE and its environmental regulation among different grassland in Northern China based on eddy covariance carbon fluxes measurements of 31 grassland sites. The results showed that the average CUE of grassland in Northern China was 0.05 ± 0.22, with a range from −0.42 to 0.66. It was demonstrated that there were significant differences in CUE among different grassland types, and CUE values were ranked by type as follows: alpine grassland > temperate meadow steppe > temperate typical steppe > temperate desert steppe, driven by a combination of climatic, soil, and biological factors, with net ecosystem productivity (NEP) having the greatest impact on them. Except for meadow steppes, moisture had a greater impact on grassland CUE in Northern China than temperature. While temperate desert grassland CUE decreased with increasing soil water content (SWC), the CUE of other grassland types increased with higher precipitation and SWC. These findings will advance our ability to predict future grassland ecosystem carbon cycle scenarios.