bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Early Ciprofloxacin Administration on Growth Performance, Meat Quality, Food Safety, and Metabolomic Profiles in Xueshan Chickens
Authors: Huang Lan , Sun Jialuo , Guo Qixin , Jiang Yong , Hao Bai , Chang Guobin
Published: August 2024

To investigate the effects of early administration of ciprofloxacin (CIP) on Xueshan chickens, in this study Xueshan chickens were measured for growth performance, tested for drug residues, evaluated for meat quality, and muscle metabolism changes were explored using a non-target metabolomics approach. Experimental findings revealed that early CIP use did not significantly impact the overall growth rate of Xueshan chickens (p > 0.05). However, notable alterations in meat quality were observed: the CIP-treated group exhibited a significant decrease in muscle pH (pH1 and pH24) and a marked increase in drip loss and moisture content (p > 0.05). No CIP residues were detected in muscle tissue. Untargeted metabolomics analyses unveiled significant alterations in the metabolic profile of market-age chickens following CIP treatment. Both functional enrichment and metabolic network analyses indicated significant effects on the ko01120 (microbial metabolism in diverse environments) and ko00350 (tyrosine metabolism) pathways, implying that CIP treatment may influence chicken meat quality by modulating microbial communities and amino acid metabolism. This study provides a crucial foundation for understanding the impact of antibiotics on meat quality and metabolism in poultry production, offering scientific insights for optimizing antibiotic-use strategies and safeguarding poultry product quality.
Probabilistic Risk Assessment of Polioencephalomalacia from Texas Beef Consuming Rations Containing Multiple Sources of Dietary Sulfur
Authors: Brown Ashli A. , Herrman Timothy
Published: August 2024

The purpose of this probabilistic assessment was to estimate the risk of sulfur-induced polioencephalomalacia (S-PEM) for beef raised across Texas, from a dietary perspective. Ruminant nutritionists in Amarillo, TX, formulated two typical nutritional regimens based on cattle production stages, each containing six feed ingredients and well water. The Office of the Texas State Chemist (OTSC), National Research Council (NRC), and the published literature provided S data for feed ingredients. The Texas Water Development Board provided data for S content in Texas well water, categorized into twelve districts established by the Texas A&M AgriLife Research Extension Service. The S-PEM risk was estimated at five different eNDF levels ranging from 0% to 8% in 2% increments, using rumen degradable S (RDS) as an input value. Findings identified cattle raised in the South Plains district as the most susceptible population to S toxicity, with beef in the finishing production stage experiencing increased sensitivity. The most potential (MP) risk scenario suggested that the S-PEM risk could reach 28.5% for growers and 100% for finishers. Results further revealed that when S concentrations in well water exceeded 14.5 mg/L, water became the greatest contributor to RDS content for Texas beef, suggesting that high S content in well water is the most prominent concern for Texas beef.
Persistent Illegal Hunting of Wildlife in an African Landscape: Insights from a Study in the Luangwa Valley, Zambia
Authors: Zyambo Paul , Mwitwa Jacob , Kalaba Felix Kanungwe , Kazonga Eustarckio
Published: August 2024

Decades of illegal hunting (poaching) have adversely affected wildlife populations and thereby limited sustainable wildlife conservation in the Luangwa Valley, Zambia. Despite intervention efforts to address the problem, the illegal hunting of wildlife has persisted. Therefore, this study was conducted to understand the persistence of illegal hunting by investigating the drivers of poaching and intervention measures using a mixed methods approach. Stratified random sampling was used to collect data from 346 respondents through structured questionnaires. Purposive sampling was used to collect data through nine focus group discussions and three in-depth interviews with experts. The study revealed that persistent illegal hunting was mainly driven by people’s critical need for survival and sustaining their livelihoods and not by inadequate law enforcement as presumed by resource managers. Although law enforcement was the most prevalent intervention measure, it did not deter local illegal hunters because their main motivations for poaching were not effectively addressed. The key implication of these findings is that where the illegal harvesting of natural resources in protected areas by local resource users is driven by people’s critical need for survival and a livelihood, which is ineffectively addressed, illegal harvesting may persist even with increased law enforcement. This study provides empirical evidence, novel conceptual knowledge and an understanding of how prevalent drivers of poaching and other factors may have influenced persistent illegal hunting in the Luangwa Valley.
Chromium Affects Mitochondrial Function, Leading to Apoptosis and Autophagy in Turtle Primary Hepatocytes
Authors: Lin Shuqin , Xiao Yunjuan , Lin Jing , Yuan Yue , Shi Haitao , Hong Meiling , Ding Li
Published: August 2024

Hexavalent chromium (Cr(VI)), a pervasive industrial contaminant, is highly toxic to both humans and animals. However, its effects on turtles are largely unexplored. Our study aimed to investigate the toxic effects of Cr(VI) on the Reeves’ turtles (Mauremys reevesii) primary hepatocytes. We exposed hepatocytes to two concentrations (25 μM and 50 μM) of Cr(VI) for 24 h. The results showed that compared to controls, Cr(VI)-treated cells showed elevated antioxidant enzyme activity (catalase (CAT) and superoxide dismutase (SOD)) and increased reactive oxygen species (ROS) levels. Adenosine triphosphatae (ATP) levels decreased, indicating mitochondrial dysfunction. Additionally, we found significant changes in mitochondrial dynamics related genes, with downregulation of mitofusin 2 (Mfn2) and silent information regulator 1 (SIRT1) and a decrease in sirtuin 3 (SIRT3) and tumor protein 53 (p53) mRNA levels. Annexin V-FITC fluorescence staining-positive cells increased with higher Cr(VI) concentrations, marked by elevated bcl-2-associated X protein (Bax) and cysteinyl aspartate specific proteinase (Caspase3) mRNA levels and reduced B-cell lymphoma-2 (Bcl2) expression. Autophagy-related genes were also affected, with increased microtubule-associated protein 1 light chain 3 (LC3-I), microtubule-associated protein light chain 3II (LC3-II), unc-51-like autophagy-activating kinase 1 (ULK1), and sequestosome 1 (p62/SQSTM1) mRNA levels and decreased mammalian target of rapamycin (mTOR) and Beclin1 expression. Taken together, Cr(VI) promotes cell apoptosis and autophagy in turtle hepatocytes by inducing oxidative stress and disrupting mitochondrial function. These findings highlight the serious health risks posed by Cr(VI) pollution and emphasize the need for protecting wild turtle populations.
Protective Effect of Coated Benzoic Acid on Intestinal Epithelium in Weaned Pigs upon Enterotoxigenic Escherichia coli Challenge
Authors: Qi Jiawen , Yu Bing , Hu Youjun , Luo Yuheng , Zheng Ping , Mao Xiangbing , Yu Jie , Zhao Xiaonan , He Taiqian , Yan Hui , Wu Aimin , He Jun
Published: August 2024

The study was designed to investigate the protective effect of dietary supplementation with coated benzoic acid (CBA) on intestinal barrier function in weaned pigs challenged with enterotoxigenic Escherichia coli (ETEC). Thirty-two pigs were randomized to four treatments and given either a basal diet or a basal diet supplemented with 3.0 g/kg CBA, followed by oral administration of ETEC or culture medium. The results showed that CBA supplementation increased the average daily weight gain (ADWG) in the ETEC-challenged pigs (p < 0.05). CBA also increased the serum activity of total superoxide dismutase (T-SOD) and the total antioxidant capacity (T-AOC), as it decreased the serum concentrations of endotoxin, interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in the ETEC-challenged pigs (p < 0.05). Interestingly, the CBA alleviated the ETEC-induced intestinal epithelial injury, as indicated by a reversal of the decrease in D-xylose absorption and a decrease in the serum levels of D-lactate and diamine oxidase (DAO) activity, as well as a decrease in the quantity of apoptotic cells in the jejunal epithelium following ETEC challenge (p < 0.05). Moreover, CBA supplementation significantly elevated the mucosal antioxidant capacity and increased the abundance of tight junction protein ZO-1 and the quantity of sIgA-positive cells in the jejunal epithelium (p < 0.05). Notably, CBA increased the expression levels of porcine beta defensin 2 (PBD2), PBD3, and nuclear factor erythroid-2 related factor 2 (Nrf-2), while downregulating the expression of toll-like receptor 4 (TLR4) in the jejunal mucosa (p < 0.05). Moreover, CBA decreased the expression levels of interleukin-1β (IL-1β), myeloid differentiation factor 88 (MyD88), and nuclear factor-kappa B (NF-κB) in the ileal mucosa upon ETEC challenge (p < 0.05). These results suggest that CBA may attenuate ETEC-induced damage to the intestinal epithelium, resulting in reduced inflammation, enhanced intestinal immunity and antioxidant capacity, and improved intestinal epithelial function.
EDBD—3,6-Epidioxy-1,10-Bisaboladiene—An Endoperoxide Sesquiterpene Obtained from Drimys brasiliensis (Winteraceae) Exhibited Potent Preclinical Efficacy against Schistosoma mansoni Infection
Authors: Umehara Eric , Teixeira Thainá R. , Cajás Rayssa A. , Amaro Monique C. , de Moraes Josué , Lago João Henrique G.
Published: August 2024

Schistosomiasis, a neglected tropical disease impacting over 250 million individuals globally, remains a major public health challenge due to its prevalence and significant impact on affected communities. Praziquantel, the sole available treatment, highlights the urgency of the need for novel anthelmintic agents to achieve the World Health Organization (WHO) goal of schistosomiasis elimination. Previous studies reported the promising antiparasitic activity of different terpenoids against Schistosoma mansoni Sambon (Diplostomida: Schistosomatidae). In the present work, the hexane extract from branches of Drimys brasiliensis afforded a diastereomeric mixture of endoperoxide sesquiterpenes, including 3,6-epidioxy-bisabola-1,10-diene (EDBD). This compound was evaluated in vitro and in vivo against S. mansoni. EDBD exhibited a significant reduction in S. mansoni viability in vitro, with an effective concentration (EC50) value of 4.1 µM. Additionally, EDBD demonstrated no toxicity to mammalian cells. In silico analysis predicted good drug-likeness properties, adhering to pharmaceutical industry standards, including favorable ADME profiles. Furthermore, oral treatment of S. mansoni-infected mice with EDBD (400 mg/kg) resulted in a remarkable egg burden reduction (98% and 99% in tissues and feces, respectively) surpassing praziquantel’s efficacy. These findings suggest the promising potential of EDBD as a lead molecule for developing a novel schistosomiasis treatment.
The Potential Health Benefits of Gallic Acid: Therapeutic and Food Applications
Authors: Hadidi Milad , Liñán-Atero Rafael , Tarahi Mohammad , Christodoulou Marios C. , Aghababaei Fatemeh
Published: August 2024

Gallic acid (GA), a phenolic acid found in fruits and vegetables, has been consumed by humans for centuries. Its extensive health benefits, such as antimicrobial, antioxidant, anticancer, anti-inflammatory, and antiviral properties, have been well-documented. GA’s potent antioxidant capabilities enable it to neutralize free radicals, reduce oxidative stress, and protect cells from damage. Additionally, GA exerts anti-inflammatory effects by inhibiting inflammatory cytokines and enzymes, making it a potential therapeutic agent for inflammatory diseases. It also demonstrates anticancer properties by inhibiting cancer cell growth and promoting apoptosis. Furthermore, GA offers cardiovascular benefits, such as lowering blood pressure, decreasing cholesterol, and enhancing endothelial function, which may aid in the prevention and management of cardiovascular diseases. This review covers the chemical structure, sources, identification and quantification methods, and biological and therapeutic properties of GA, along with its applications in food. As research progresses, the future for GA appears promising, with potential uses in functional foods, pharmaceuticals, and nutraceuticals aimed at improving overall health and preventing disease. However, ongoing research and innovation are necessary to fully understand its functional benefits, address current challenges, and establish GA as a mainstay in therapeutic and nutritional interventions.
Refined Land Use Classification for Urban Core Area from Remote Sensing Imagery by the EfficientNetV2 Model
Authors: Wang Zhenbao , Liang Yuqi , He Yanfang , Cui Yidan , Zhang Xiaoxian
Published: August 2024

In the context of accelerated urbanization, assessing the quality of the existing built environment plays a crucial role in urban renewal. In the existing research and use of deep learning models, most categories are urban construction areas, forest land, farmland, and other categories. These categories are not conducive to a more accurate analysis of the spatial distribution characteristics of urban green space, parking space, blue space, and square. A small sample of refined land use classification data for urban built-up areas was produced using remote sensing images. The large-scale remote sensing images were classified using deep learning models, with the objective of inferring the fine land category of each tile image. In this study, satellite remote sensing images of four cities, Handan, Shijiazhuang, Xingtai, and Tangshan, were acquired by Google Class 19 RGB three-channel satellite remote sensing images to establish a data set containing fourteen urban land use classifications. The convolutional neural network model EfficientNetV2 is used to train and validate the network framework that performs well on computer vision tasks and enables intelligent image classification of urban remote sensing images. The model classification effect is compared and analyzed through accuracy, precision, recall, and F1-score. The results show that the EfficientNetV2 model has a classification recognition accuracy of 84.56% on the constructed data set. The testing set accuracy increases sequentially after transfer learning. This paper verifies that the proposed research framework has good practicality and that the results of the land use classification are conducive to the fine-grained quantitative analysis of built-up environmental quality.
Calculation Method of New Assembled Corrugated Steel Initial Support Structure of Highway Tunnel
Authors: Ding Wenqi , Huang Xuanbo , Yu Chengshuo , Zhang Qingzhao , Wu Tianxiang
Published: August 2024

The assembled corrugated steel initial support structure is a new prefabricated structure in highway tunnel engineering, achieving a balance between economy and safety. This study proposes a simplified calculation method and elucidates the mechanical mechanisms of assembled corrugated steel initial support structures. Firstly, the stiffness characteristics of corrugated steel plates were studied based on full-scale tests. A general equivalent stiffness coefficient table was established. Numerical simulations of corrugated steel flange joints were conducted to explore their bending mechanical properties. A two-stage rotational stiffness model for corrugated steel flange joints was proposed. Finally, a plane strain-spring simplified calculation method for the assembled corrugated steel initial support structure was developed, and the monitoring data from the Qipanshan Tunnel validated the correctness and reliability of the proposed method. The results demonstrate that (1) the plane strain-spring simplified model consists of the planar strain equivalent calculation method for corrugated steel plates and the two-line stiffness equivalent spring of the corrugated steel flange joint. The simplified model was validated as effective by monitoring data. (2) Corrugated steel plates exhibit two stages under loading, namely gap elimination and elastic stages. The elastic stage stiffness of corrugated steel plates decreases with increasing ratio of depth to pitch (RDP), positively correlating with plate thickness when the RDP exceeds 0.333 and otherwise negatively correlated. (3) Corrugated steel lining flange joints exhibit distinct elastic and plastic stages in their linear moment–rotation curves under loading.
Research on an Evaluation Method of Snowdrift Hazard for Railway Subgrades
Authors: Qiu Shumao , Bai Mingzhou , Lin Daming , Zhang Yufang , Xia Haoying , Fan Jiawei , Zhou Wenjiao , Tang Zhenyu
Published: August 2024

The objective of this study is to investigate the potential risks posed by snowdrifts, a prevalent cause of natural disasters in northern China, on railway subgrades, and to assess their risk level. As a wind-driven process of snow migration and redeposition, snowdrifts pose a significant threat to the safety of transportation infrastructures. This study focuses on the Afu Railway in Xinjiang, situated on the northern slopes of the Eastern Tianshan Mountains, where it experiences periodic snowdrifts. We employed a combination of the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation (FCE) to construct an integrated evaluation system for assessing the risk of snowdrift to railway subgrades. The results indicate that subgrade design parameters and regional snowfield conditions are two key metrics affecting the extent of snowdrift disasters, with topography, vegetation coverage, and wind speed also exerting certain impacts. The evaluation method of this study aligns with the results of on-site observations, verifying its accuracy and practicality, thereby providing a solid risk assessment framework for snowdrifts along the railway. The scientific and systematic hazard assessment method of railway subgrades developed in this research provides basic data and theoretical support for future research, and provides a scientific basis for relevant departments to formulate countermeasures, so as to improve the safety and reliability of railway operations.
Reconfigurable Robotic Exercising Companion
Authors: Sachinthana W. K. R. , Wijegunawardana I. D. , Samarakoon S. M. Bhagya P. , Muthugala M. A. Viraj J. , Elara Mohan Rajesh
Published: August 2024

Regular exercise plays a crucial role in promoting overall well-being in today’s lifestyle. However, individuals often find it challenging to properly execute exercises, including maintaining correct postures and appropriate movement speeds. Robotic companions have emerged as potential solutions to assist and motivate users during exercise sessions. This research paper proposes a novel robot companion designed for exercise scenarios using a reconfigurable robot. In contrast to existing non-reconfigurable robotic companions, the use of a reconfigurable robot provides added flexibility in generating emotions. The system incorporates a module that utilizes fuzzy logic to evaluate the correctness of exercise performance based on posture variations and movement speeds. The robot generates emotions and provides feedback to users based on the exercise correctness score. The robot expresses emotions through reconfigurations, motion patterns, and variations in robot speed. This emotion-based feedback could be helpful for creating engaging and interactive exercise experiences. Apart from emotion generation, the robot utilizes vocal cues as feedback. Experimental results validate the effectiveness of the proposed system in evaluating exercise correctness and demonstrating meaningful emotion transitions. The findings of this work contribute to the development of innovative robotic companions for improving exercise adherence and overall well-being.
Study on Denoising Method of Weld Defect Signal Based on SSA-VMD-WPD
Authors: Chen Xiangqing , Gong Sifan , Pan Wei , Kang Youqing , Gong Weili
Published: August 2024

Defects in welds can affect the structural safety and reliability of workpieces. Currently, the method of using phased array ultrasonic inspection technology for non-destructive testing of weld structures with high detection efficiency, good sensitivity, and good visualization of the results is widely used. However, the defective A-scan data collected by the ultrasonic phased array detector inevitably contain noise data, including the test piece material structure noise, equipment noise, and environmental noise, which undoubtedly affects the analysis of the A-scan signal. In addition, when defects are interpreted, the presence of noise also interferes with the process, which affects the accuracy of the interpretation. Therefore, to enhance the accuracy of defect identification based on phased array ultrasonic inspection technology, we must prevent the series of consequences caused by misjudgments. In this study, ultrasonic phased array inspection experiments were carried out, and the specific process flow of ultrasonic phased array inspection of flat plate butt welds was summarized. Utilizing pre-fabricated flat plate butt specimen blocks containing five types of typical defects, defect A-sweep signals based on ultrasonic phased array inspection were obtained. Combining the sparrow optimization algorithm (SSA), variational mode decomposition (VMD), and wavelet packet decomposition (WPD), a defect signal noise reduction method based on parameter optimization was studied. A noise reduction study was carried out using the noise-added simulated signal, and the results indicated that the noise reduction method proposed in this paper had a better noise reduction effect and the proposed method could effectively retain the detailed features of the ultrasonic phased array defective A-scan signal and realize the noise reduction processing of the defective A-scan signal.
Enhancing E-Commerce Recommendation Systems with Multiple Item Purchase Data: A Bidirectional Encoder Representations from Transformers-Based Approach
Authors: Park Minseo , Oh Jangmin
Published: August 2024

This study proposes how to incorporate concurrent purchase data into e-commerce recommendation systems to improve their predictive accuracy. We identified that concurrent purchases account for about 23% of total orders on Katcher’s, a Korean e-commerce platform. Despite the prevalence of concurrent purchases, existing algorithms often overlook this aspect. We introduce a novel transformer-based recommendation algorithm to process a user’s order history, including concurrent purchases. Each order is represented as a natural language sentence, capturing the order timestamp, product names and their attribute values, their corresponding categories, and whether multiple products were purchased together in a single order (i.e., a concurrent purchase). These sentences form a sequence, which serves as a training dataset for fine-tuning Bidirectional Encoder Representations from Transformers (BERT) with the Next Sentence Prediction objective. We validate our ideas by conducting experiments on Katcher’s platform, demonstrating the proposed method’s improved prediction performance compared to existing recommendation systems, with enhanced accuracy and F1 score. Notably, the normalized discounted cumulative gain (NDCG) showed a significant improvement with a large margin. Furthermore, we demonstrate the beneficial impact of integrating concurrent purchase information on prediction performance.
Research Status and Prospects of High-Voltage Pulse Plasma Rock-Fracturing Technology
Authors: Zhang Yuanyuan , Wang Jin , Xue Qilong , Liu Jiawei , Li Hufeng , Fang Song
Published: August 2024

With the continuous development of the geological engineering field, high-voltage electric pulse plasma rock-fracturing technology has become a research hotspot in recent years. It is now widely recognized that this fracturing technology has many application prospects and great economic benefits. Through the research process of this technology, it has proven to be an efficient and new type of rock-fracturing technology, which overcomes the problems of high cost, low efficiency, high safety risk, and serious pollution associated with traditional rock-fracturing technology. Also, it has unique advantages in terms of protecting the environment and reducing damage to the surrounding buildings. This paper reviews the research history of plasma shock wave influencing factors and pulsed discharge plasma rock-fracturing technology, summarizes the research on this technology from the perspectives of the mechanism of high-voltage electric pulse plasma rock fracturing and practical application, and discusses the feasibility of this technology when applied to the field of tunnel boring as well as the future development direction. This technology can be better used in the tunnel-boring field, which can greatly improve the tunnel-boring efficiency, but at present, the research on plasma rock-fracturing-assisted tunnel boring is still in the laboratory research stage, which lacks systematic research equipment and judging indexes, and the follow-up should focus on improving the systematic research capabilities of the plasma rock-fracturing-assisted tunnel-boring equipment, and systematically and comprehensively carry out research on rock-fracturing by plasma-assisted excavation equipment.
A Comprehensive Approach for an Interpretable Diabetic Macular Edema Grading System Based on ConvUNext
Authors: Garcia-Nonoal Zaira , Fierro-Radilla Atoany , Nakano Mariko
Published: August 2024

Diabetic macular edema (DME) is a leading cause of vision impairment in diabetic patients, necessitating a timely and accurate diagnosis. This paper proposes a comprehensive system for DME grading using retinal fundus images. Our approach integrates multiple deep learning modules, each designed to address key aspects of the diagnostic process. The first module employs the ConvUNeXt model for segmenting hard exudates (HaEx), crucial indicators of DME. The second module uses RetinaNet for precise optic disc (OD) localization, which is essential for subsequent macula localization. The third module refines macula localization, leveraging preprocessing techniques to enhance image clarity. Finally, our system consolidates these results to provide interpretable DME grading. Experimental evaluations were conducted on the Messidor dataset, demonstrating the system’s robust performance. The HaEx segmentation module achieved a mean IoU of 70.5% and a Dice coefficient of 0.64. The OD localization module showed perfect accuracy, recall, and precision at 1.0. For macula localization, our method satisfied the 1R criterion with 99.38% accuracy. The DME grading module achieved an overall accuracy of 91.12%, with an AUC of 0.9334. Our method offers a balanced performance across accuracy, sensitivity, and specificity compared to other non-interpretable and partially interpretable methods.
Efficient Method for Enhancing Reverse-Time Migration Images Using Vertical Seismic Profiling Data
Authors: Lu Cai , Liu Youming
Published: August 2024

Vertical seismic profiling has garnered widespread attention in the industry as a supplement to seismic exploration due to its higher data quality compared to surface seismic data. However, its unique observation system in which geophones are only distributed within observation wells results in uneven coverage of subsurface structures. This can lead to significant noise when directly applying conventional reverse-time migration techniques used in surface seismic imaging. This study addresses the issue of noise suppression in reverse-time migration imaging associated with walk-away vertical seismic profiling and presents two main innovations. First, a common-receiver reverse-time migration imaging method is proposed, which uses the observation signals as excitation signals for the corresponding shots after reverse-time processing. Second, an excitation-time-constrained cross-correlation imaging condition is introduced to eliminate non-contributing portions of the wavefield, thereby modifying the traditional cross-correlation imaging condition to include an excitation time constraint. The combination of these methods enhances imaging quality by effectively suppressing noise, as demonstrated through theoretical analysis and numerical simulations with synthetic models.
Characterization of Multi-Layer Rolling Contact Fatigue Defects in Railway Rails Using Sweeping Eddy Current Pulse Thermal-Tomography
Authors: Zhang Hengbo , Zhang Shudi , Chen Xiaotian , Li Yingying , Zou Yiling , Zeng Yizhao
Published: August 2024

Railways play a pivotal role in national economic development, freight transportation, national defense, and regional connectivity. The detection of rolling contact fatigue (RCF) defects in rail tracks is essential for railway safety and maintenance. Due to its efficiency and non-contact capability in detecting surface and near-surface defects, Eddy Current Pulsed Thermography (ECPT) has garnered significant attention from researchers. However, detecting multi-layer RCF defects remains a challenge. This paper introduces a sweeping Eddy Current Pulsed Thermal-Tomography system (ECPTT) to detect multi-layer RCF defects effectively. This system utilizes varying excitation frequencies to heat defects, altering skin depth and facilitating feature extraction to distinguish multi-layer RCF defects. Skewness and thermographic signal reconstruction (TSR) values are employed as features in the experiments. These features are qualitatively analyzed to differentiate the layers and depths of multi-layer RCF defects. Additionally, five different coils were compared and analyzed quantitatively. The results indicate that the ECPTT system can effectively detect and distinguish multi-layer RCF defects, thereby providing more detailed defect information and enhancing railway safety and maintenance efficiency.
Prediction of Structural Fracture Distribution and Analysis of Controlling Factors in a Passive Continental Margin Basin—An Example of a Clastic Reservoir in Basin A, South America
Authors: Guo Rong , Shi Jinxiong , Jiang Shuyu , Jiang Shan , Cai Jun
Published: August 2024

Structural fracture distribution is essential in oil and gas transportation and development in passive continental margin basins. In this paper, taking as an example the clastic reservoirs in the A-Basin, a passive continental margin in northeastern South America, the paleotectonic stress field of the Late Cretaceous Maastrichtian formation in Basin A was numerically simulated by finite element technique through the integrated interpretation of seismic total data, logging data and core data, and the distribution of tectonic fractures was later predicted based on rock fracture criterion. The results of the study show that: (1) The distribution of tectonic stress and fractures during the Late Cretaceous Maastrichtian formation of Basin A is affected by the fracture zone, mechanical properties of rocks and tectonic stress, regions with extensive fracture development are susceptible to stress concentrations, resulting in significant stress gradients. (2) The development of structural fractures in the study area was predicted using the Griffiths criterion, and the tensile rupture coefficient T was introduced to quantitatively characterise the intensity of fracture development, with larger values reflecting a higher degree of fracture development. The well-developed and relatively well-developed fractures are mainly located in the fracture zones and the interior of submarine fans. (3) Fracture zones and sedimentary phases mainly control structural fractures in Basin A; within 5 km outside the fracture zones, the development of fractures is controlled by the fracture zones, beyond which the regional tectonic stress field controls them; inside the sedimentary fan, the development of fractures is controlled by the sedimentary subphase, which decreases in the order of the upper fan, the middle fan, and the lower fan; inside the subphase, they are controlled by the regional tectonic stress field, and the fractures show the increasing trend in the direction of NW-NE.
Effects of Exercise and Pomegranate–Black Carrot Juice Interventions on Mineral Metabolism and Fatty Acids
Authors: Bozbay Kenan , Çinar Vedat , Akbulut Taner , Aydemir Isa , Yasul Yavuz , Aytac Kursat Yusuf , Ozkaya Ahmet , Russo Luca , Fusco Andrea , Migliaccio Gian Mario
Published: August 2024

In this study, the effects of exercise applied to sedentary individuals and the use of pomegranate–black carrot juice on minerals, fatty acids and some biochemical parameters were examined. Twenty healthy sedentary men participated in this study. This research consisted of three stages. Blood samples were taken from the participants before this study (Baseline), after the participants exercised (60 min/day) for 10 days (Exerciseonly), after the participants were given pomegranate–black carrot juice mixture (100 mL/100 mL) along with exercise (60 min/day) for 10 days (Exercise+supp). While AST and ALT levels increased in the Exerciseonly phase, they showed a relative decrease in the Exercise+supp phase. It was determined that Mg level in the Exerciseonly phase decreased compared to the Baseline and the Exercise+supp phase. It was determined that the Zn level in the Exercise+supp phase increased compared to the Zn level in the Exerciseonly phase. It was determined that 6:0, 12:0 and 14:0 fatty acid levels increased in the Exerciseonly phase compared to the Baseline. A decrease was detected in the Exerciseonly phase compared to the Baseline 18:2n6c, 18:3n6 and 18:3n3 fatty acid levels. It can be said that exercise and the use of pomegranate–black carrot juice mixture in sedentary individuals have supportive and corrective effects on serum mineral, fatty acids and some biochemical parameters.
Optimizing Sustainable Thread Design for Motorized Leg-Lengthening Devices: A Structural and Performance Assessment
Authors: Kok Chiang Liang , Ho Chee Kit , Ng Hong Wei , Koh Yit Yan , Teo Tee Hui
Published: August 2024

This study offers an in-depth structural analysis of the threading mechanism in a motorized leg-lengthening nail, a key device used in bone-lengthening surgeries. The primary aim is to assess the structural integrity and performance of the nail during the lengthening process. The paper starts with a comprehensive overview of the nail’s design, historical background, and functionality, emphasizing the critical components of the lengthening mechanism. The methodology section details the structural analysis approach, incorporating both finite element analysis (FEA) and manual calculations. FEA simulations are employed to analyze the nail’s behavior under compressive loads, considering realistic conditions such as the 95th percentile of human body weight. The analysis focuses on stress concentrations, deflections, and overall structural stability to pinpoint the potential weaknesses. Due to budget limitations that prevented the creation of physical prototypes, manual calculations were utilized to validate the FEA results. The findings identify stress concentrations, especially in the areas where male and female threads engage, leading to the design of recommendations to enhance strength and reliability. Experimental results corroborate the accuracy of the FEA simulations. The study concludes with suggestions for improving thread design, emphasizing safety, durability, and functionality. These recommendations aim to guide the future iterations of the motorized leg-lengthening nail, thereby promoting the development of safer and more effective devices for bone-lengthening surgeries. This structural analysis significantly contributes to understanding the mechanical behavior of the motorized leg-lengthening nail, playing a crucial role in advancing medical devices for bone-lengthening procedures.
In-Plane Material Handling: A Systematic Review
Authors: Bianchi Edoardo , Brosed Dueso Francisco Javier , Yagüe-Fabra José A.
Published: August 2024

With the dynamic nature of today’s market demands, industries increasingly require flexible and adaptable systems to navigate through variable operational needs. In-plane manipulation systems, characterized by their ability to handle objects over an active surface, have emerged as promising solutions to address these challenges. This systematic literature review (SLR) investigates the landscape of in-plane manipulation systems, focusing on their classification, technological aspects, and emerging trends. Drawing upon a comprehensive search strategy, this review identifies and synthesizes relevant literature on the topic. Through structured data extraction and analysis, the review categorizes these devices based on their fields of application, employed technologies, common characteristics, advantages, disadvantages, and existing gaps in research and development. The main technologies identified for material handling include MEMS, vibrations, cilia, pneumatic surfaces, variable-morphology surfaces, the use of rotors, and mobile platforms. These technologies are described based on their primary features and fields of application and are compared to highlight their unique advantages and limitations. Accordingly, this SLR aims to provide insights into the current state of the art, identify areas for further investigation, and inform future developments in in-plane material handling. Additionally, the findings of this review contribute to a deeper understanding of the capabilities, limitations, and potential applications of this kind of manipulation across various industries. Furthermore, the identification of gaps in existing literature, particularly regarding the complexity and efficiency of rotor systems, serves as a foundation for future research aimed at advancing the field and addressing the evolving needs of industries in an increasingly dynamic market landscape.
Combinatorial Identities with Multiple Harmonic-like Numbers
Authors: Adegoke Kunle , Frontczak Robert
Published: August 2024

Multiple harmonic-like numbers are studied using the generating function approach. A closed form is stated for binomial sums involving these numbers and two additional parameters. Several corollaries and examples are presented which are immediate consequences of the main result. Finally, combinatorial identities involving harmonic-like numbers and other prominent sequences like hyperharmonic numbers and odd harmonic numbers are offered.
A Generalised Additive Model and Deep Learning Method for Cross-Validating the North Atlantic Oscillation Index
Authors: Wahiduzzaman Md , Yeasmin Alea
Published: August 2024

This study introduces an innovative analytical methodology for examining the interconnections among the atmosphere, ocean, and society. The primary area of interest pertains to the North Atlantic Oscillation (NAO), a notable phenomenon characterised by daily to decadal fluctuations in atmospheric conditions over the Northern Hemisphere. The NAO has a prominent impact on winter weather patterns in North America, Europe, and to some extent, Asia. This impact has significant ramifications for civilization, as well as for marine, freshwater, and terrestrial ecosystems, and food chains. Accurate predictions of the surface NAO hold significant importance for society in terms of energy consumption planning and adaptation to severe winter conditions, such as winter wind and snowstorms, which can result in property damage and disruptions to transportation networks. Moreover, it is crucial to improve climate forecasts in order to bolster the resilience of food systems. This would enable producers to quickly respond to expected changes and make the required modifications, such as adjusting their food output or expanding their product range, in order to reduce potential hazards. The forecast centres prioritise and actively research the predictability and variability of the NAO. Nevertheless, it is increasingly evident that conventional analytical methods and prediction models that rely solely on scientific methodologies are inadequate in comprehensively addressing the transdisciplinary dimension of NAO variability. This includes a comprehensive view of research, forecasting, and social ramifications. This study introduces a new framework that combines sophisticated Big Data analytic techniques and forecasting tools using a generalised additive model to investigate the fluctuations of the NAO and the interplay between the ocean and atmosphere. Additionally, it explores innovative approaches to analyze the socio-economic response associated with these phenomena using text mining tools, specifically modern deep learning techniques. The analysis is conducted on an extensive corpora of free text information sourced from media outlets, public companies, government reports, and newspapers. Overall, the result shows that the NAO index has been reproduced well by the Deep-NAO model with a correlation coefficient of 0.74.
Evolution of Dew and Rain Water Resources in Gujarat (India) between 2005 and 2021
Authors: Budhbhatti Rupal , Roy Anil K. , Muselli Marc , Beysens Daniel
Published: August 2024

The present study, carried out in Gujarat (India) between 2005 and 2021, aims to prepare dew and rain maps of Gujarat over a long period (17 years, from 2005 to 2021) in order to evaluate the evolution of the potential for dew and rain in the state. The ratio of dew to precipitation is also determined, which is an important metric that quantifies the contribution of dew to the overall water resources. Global warming leads, in general, to a reduction in precipitation and non-rainfall water contributions such as dew. The study shows, however, a rare increase in the rainfall and dew condensation, with the latter related to an increase in relative humidity and a decrease in wind amplitudes. Rain primarily occurs during the monsoon months, while dew forms during the dry season. Although dew alone cannot resolve water scarcity, it nonetheless may provide an exigent and unignorable contribution to the water balance in time to come. According to the site, the dew–rain ratios, which are also, in general, well correlated with dew yields, can represent between 4.6% (Ahmedabad) and 37.2% (Jamnagar). The positive trend, observed since 2015–2017, is expected to continue into the future.
Spatial Mapping of Air Pollution Hotspots around Commercial Meat-Cooking Restaurants Using Bicycle-Based Mobile Monitoring
Authors: Yong Gwang-Soon , Mun Gun-Woo , Kwak Kyung-Hwan
Published: August 2024

Mobile measurement techniques are increasingly utilized to monitor urban emissions, regional air quality, and air pollutant exposure assessments. This study employed a bicycle measurement method to obtain the detailed distribution of air pollutant concentrations in roadside, commercial, residential, and recreational areas. The study area is located in Chuncheon, South Korea, with approximately 280,000 residents. Black carbon (BC), PM2.5, and NO2 were monitored using portable devices equipped on an electric bicycle. Results showed that in the evening (6–8 p.m.), the concentrations were higher in both commercial and residential areas compared to the background location, while concentrations were notably elevated only in roadside areas in the morning (8–10 a.m.). Spatial mapping of measured concentrations revealed that the highest concentrations corresponded to areas with densely operated charbroiling meat-cooking restaurants. Additionally, it was confirmed that BC and PM2.5 emitted from the commercial areas influenced nearby recreational areas (e.g., streamside roads). In conclusion, this study demonstrated that air pollutant hotspots resulting from human activities, such as dining at commercial restaurants, significantly worsen the local air quality on a small scale. Efforts to reduce the uncontrolled emissions of air pollutants from charbroiling meat-cooking restaurants are necessary.
Evaluation of Scikit-Learn Machine Learning Algorithms for Improving CMA-WSP v2.0 Solar Radiation Prediction
Authors: Wang Dan , Shen Yanbo , Ye Dong , Yang Yanchao , Da Xuanfang , Mo Jingyue
Published: August 2024

This article aims to evaluate the performance of solar radiation forecasts produced by CMA-WSP v2.0 (version 2 of the China Meteorological Administration Wind and Solar Energy Prediction System) and to explore the application of machine learning algorithms from the scikit-learn Python library to improve the solar radiation prediction made by the CMA-WSP v2.0. It is found that the performance of the solar radiation forecasting from the CMA-WSP v2.0 is closely related to the weather conditions, with notable diurnal fluctuations. The mean absolute percentage error (MAPE) produced by the CMA-WSP v2.0 is approximately 74% between 11:00 and 13:00. However, the MAPE ranges from 193% to 242% at 07:00–08:00 and 17:00–18:00, which is greater than that observed at other daytime periods. The MAPE is relatively low (high) for both sunny and cloudy (overcast and rainy) conditions, with a high probability of an absolute percentage error below 25% (above 100%). The forecasts tend to underestimate (overestimate) the observed solar radiation in sunny and cloudy (overcast and rainy) conditions. By applying machine learning models (such as linear regression, decision trees, K-nearest neighbors, random forests regression, adaptive boosting, and gradient boosting regression) to revise the solar radiation forecasts, the MAPE produced by the CMA-WSP v2.0 is significantly reduced. The reduction in the MAPE is closely connected to the weather conditions. The models of K-nearest neighbors, random forests regression, and decision trees can reduce the MAPE in all weather conditions. The K-nearest neighbor model exhibits the most optimal performance among these models, particularly in rainy conditions. The random forest regression model demonstrates the second-best performance compared to that of the K-nearest neighbor model. The gradient boosting regression model has been observed to reduce the MAPE of the CMA-WSP v2.0 in all weather conditions except rainy. In contrast, the adaptive boosting (linear regression) model exhibited a diminished capacity to improve the CMA-WSP v2.0 solar radiation prediction, with a slight reduction in MAPE observed only in sunny (sunny and cloudy) conditions. In addition, the input feature selection has a considerable influence on the performance of the machine learning model. The incorporation of the time series data associated with the diurnal variation of solar radiation as an input feature can further improve the model’s performance.
Midterm Results of Severe Hip Dysplasia after Using a Cementless Acetabular Component with Bulk Bone Graft in Total Hip Arthroplasty: A Minimum Five-Year Follow-Up Study
Authors: Konno Takuya , Shimizu Tomohiro , Inoue Masahiro , Masuda Takeshi , Terkawi Mohamad Alaa , Iwasaki Norimasa , Takahashi Daisuke
Published: August 2024

In patients with severe hip dysplasia, total hip arthroplasty (THA) using bulk bone graft (BBG) enhances anatomic cup positioning and provides early structural support. This study assesses the mid-term outcomes of THA with BBG in patients with over 50% graft bone coverage. Among 1951 patients who underwent THA between 2003 and 2007, 183 had BBG. After excluding early dropouts and infections, 151 patients remained. They were classified into uncovered (<50% coverage, 79 patients) and covered (>50% coverage, 72 patients) groups. The efficacy of cup fixation was compared between these groups. After ten years, the survival rate for not needing THA revision was 98% in the uncovered group and 100% in the covered group, while the rate for radiographic stability was 93% versus 99%, respectively. Although the cutoff value for the uncovered portion could not be clarified in this study, the mid-term results for 50% to approximately 70% uncovered were comparable to those for 50% or lesser, which have previously been expected to perform well. Recently, biomechanically advantageous bone grafting techniques have been identified, and based on the results of this study, it may be possible to expand the indications for THA with bone grafting for developmental dysplasia of the hip.