bluuebunny/crossref_metadata_2025 huggingface dataset:
Tracking Evapotranspiration Patterns on the Yinchuan Plain with Multispectral Remote Sensing
Authors: Meng Junzhen , Yang Xiaoquan , Li Zhiping , Zhao Guizhang , He Peipei , Xuan Yabing , Wang Yunfei
Published: September 2024

Evapotranspiration (ET) is a critical component of the hydrological cycle, and it has a decisive impact on the ecosystem balance in arid and semi-arid regions. The Yinchuan Plain, located in the Gobi of Northwest China, has a strong surface ET, which has a significant impact on the regional water resource cycle. However, there is a current lack of high-resolution evapotranspiration datasets and a substantial amount of time is required for long-time series remote sensing evapotranspiration estimation. In order to assess the ET pattern in this region, we obtained the actual ET (ETa) of the Yinchuan Plain between 1987 and 2020 using the Google Earth Engine (GEE) platform. Specifically, we used Landsat TM+/OLI remote sensing imagery and the GEE Surface Energy Balance Model (geeSEBAL) to analyze the spatial distribution pattern of ET over different seasons. We then reproduced the interannual variation in ET from 1987 to 2020, and statistically analyzed the distribution patterns and contributions of ET with regard to different land use types. The results show that (1) the daily ETa of the Yinchuan Plain is the highest in the central lake wetland area in spring, with a maximum value of 4.32 mm day−1; in summer, it is concentrated around the croplands and water bodies, with a maximum value of 6.90 mm day−1; in autumn and winter, it is mainly concentrated around the water bodies and impervious areas, with maximum values of 3.93 and 1.56 mm day−1, respectively. (2) From 1987 to 2020, the ET of the Yinchuan Plain showed an obvious upward and downward trend in some areas with significant land use changes, but the overall ET of the region remained relatively stable without dramatic fluctuations. (3) The ETa values for different land use types in the Yinchuan Plain region are ranked as follows: water body > cultivated land > impervious > grassland > bare land. Our results showed that geeSEBAL is highly applicable in the Yinchuan Plain area. It allows for the accurate and detailed inversion of ET and has great potential for evaluating long-term ET in data-scarce areas due to its low meteorological sensitivity, which facilitates the study of the regional hydrological cycle and water governance.
Distribution Characteristics and Genesis Mechanism of Ground Fissures in Three Northern Counties of the North China Plain
Authors: Xue Chao , Zang Mingdong , Zhang Zhongjian , Yang Guoxiang , Xu Nengxiong , Wang Feiyong , Hong Cheng , Li Guoqing , Wang Fujiang
Published: September 2024

The North China Plain is among the regions most afflicted by ground fissure disasters in China. Recent urbanization has accelerated ground fissure activity in the three counties of the northern North China Plain, posing significant threats to both the natural environment and socioeconomic sustainability. Despite the increased attention, a lack of comprehensive understanding persists due to delayed recognition and limited research. This study conducted field visits and geological surveys across 43 villages and 80 sites to elucidate the spatial distribution patterns of ground fissures in the aforementioned counties. By integrating these findings with regional geological data, we formulated a causative model to explain ground fissure formation. Our analysis reveals a concentration of ground fissures near the Niuxi and Rongxi faults, with the former exhibiting the most extensive distribution. The primary manifestations of ground fissures include linear cracks and patch-shaped collapse pits, predominantly oriented in east-west and north-south directions, indicating tensile failure with minimal vertical displacement. Various factors contribute to ground fissure development, including fault activity, ancient river channel distribution, bedrock undulations, rainfall, and ground settlement. Fault activity establishes a concealed fracture system in shallow geotechnical layers, laying the groundwork for ground fissure formation. Additionally, the distribution of ancient river channels and bedrock undulations modifies regional stress fields, further facilitating ground fissure emergence. Rainfall and differential ground settlement serve as triggering mechanisms, exposing ground fissures at the surface. This research offers new insights into the causes of ground fissures in the northern North China Plain, providing crucial scientific evidence for sustaining both the natural environment and the socio-economic stability of the region.
The Different Strategies of the Italian Regions within the 2023 2027 Rural Development Programme
Authors: Piras Francesco , Pulina Antonio , Milone Pierluigi
Published: September 2024

Following the European Commission’s approval of the CAP Strategic Plan and the 21 Italian region (CSR)-related strategic documents, the financial aspect that characterized the single national CAP plan was made available. Here, we present and analyze the final data on the distribution of public resources for interventions between 2023 and 2027. This marks a pivotal period of strategic information for those who follow the evolution of the rural development policy, providing vital indications of policymakers’ priorities. In Italy, where rural development policy is highly regionalized, it is difficult to acquire an overall view of the strategic choices adopted by the individual regions. The primary objective of this article is to offer a comprehensive and enlightening synopsis of the regional choices in the CSRs. It aims to identify shared strategic paths in rural development, with a specific focus on the financial allocation in each of the three historical macro-objectives of the CAP: the competitiveness of the agri-food sector, the protection of the environment, and the revitalization of rural areas. Cluster analysis classification allows for aggregating the strategies adopted, allowing for comparisons across the Italian regions. The results show three regional groups focused on environmental strategy, structural investment measures, and resource distribution that is more balanced between these two approaches. Identifying the strategic choices made by the regions allows policymakers to predict different development trajectories and the progress of the expenditure indicators over the years. At the moment, it is impossible to verify whether the policy mix defined in the budget allocation is consistent with the strategic statements.
The Role of Digital Supply Chain on Inventory Management Effectiveness within Engineering Companies in Jordan
Authors: Ali Ahmad Ali Atieh , Fayad Abdallah A. S. , Alomair Abdulrahman , Al Naim Abdulaziz S.
Published: September 2024

This research enters deeply into the critical dynamics of characteristics within digital supply chains and their collective eventual influence on inventory management efficiency. The study uses an exhaustive survey of 350 engineering company representatives to reveal the complex interactions between different qualities of supply chain systems-on-time data and inventory practice efficiency. By applying advanced techniques of regression analysis, the authors worked out three hypotheses and exhaustively tested them to find out the impact of digital adaptivity, dynamism and flexibility on both the visibility of information and inventory management effectiveness. This study has many interesting findings. First, this paper found strong positive connections between Digital Adaptability Supply Chain and Digital Flexibility Supply Chain in terms of both information visibility and inventory management effectiveness. These results argue that to effectively manage inventory levels with optimal information transparency across its network of links, companies must establish supply chain systems that can adapt to change and embrace flexibility. Digital Agility Supply Chain did not show any significant relationships with these variables, but it could be important. We need to study its nuances until we know how it is going to affect supply chain performance indices. This paper encourages investment in new supply chain technologies that will help all the engineering companies in Jordan be more adaptable and flexible. It also calls for adding data analysis capabilities across the company directly into supply chain processes through real-time tracking solutions. These solutions will make it easier to see and give decision-makers quick, reliable information about inventory management practices and agreement practices. By incorporating these recommendations, all Jordanian engineering companies can enhance their supply capacity and appropriate inventory management procedures to compete in the evolving marketplace now finally taking effect.
Bi-Objective Circular Multi-Rail-Guided Vehicle Scheduling Optimization Considering Multi-Type Entry and Delivery Tasks: A Combined Genetic Algorithm and Symmetry Algorithm
Authors: Li Xinlin , Wu Xuzhen , Wang Peipei , Xu Yalu , Gao Yue , Chen Yiyang
Published: September 2024

Circular rail-guided vehicles (RGVs) are widely used in automated warehouses, and their efficiency directly determines the transportation efficiency of the entire system. The congestion frequency of RGVs greatly increases when facing dense multi-type entry and delivery tasks, affecting overall transportation efficiency. This article focuses on the RGV scheduling problem of multi-type parallel transportation tasks in a real-world automated warehouse, considering maximizing efficiency while reducing energy consumption and thus establishing the RGV scheduling optimization model. At the same time, an improved genetic algorithm (GA) based on symmetry selection function and offspring population structure symmetry is proposed to solve the above RGV scheduling problem, achieving the model solution. The case study demonstrates the superiority of the proposed method in breaking local optima and achieving bi-objective optimization in genetic algorithms.
Sparse Fuzzy C-Means Clustering with Lasso Penalty
Authors: Parveen Shazia , Yang Miin-Shen
Published: September 2024

Clustering is a technique of grouping data into a homogeneous structure according to the similarity or dissimilarity measures between objects. In clustering, the fuzzy c-means (FCM) algorithm is the best-known and most commonly used method and is a fuzzy extension of k-means in which FCM has been widely used in various fields. Although FCM is a good clustering algorithm, it only treats data points with feature components under equal importance and has drawbacks for handling high-dimensional data. The rapid development of social media and data acquisition techniques has led to advanced methods of collecting and processing larger, complex, and high-dimensional data. However, with high-dimensional data, the number of dimensions is typically immaterial or irrelevant. For features to be sparse, the Lasso penalty is capable of being applied to feature weights. A solution for FCM with sparsity is sparse FCM (S-FCM) clustering. In this paper, we propose a new S-FCM, called S-FCM-Lasso, which is a new type of S-FCM based on the Lasso penalty. The irrelevant features can be diminished towards exactly zero and assigned zero weights for unnecessary characteristics by the proposed S-FCM-Lasso. Based on various clustering performance measures, we compare S-FCM-Lasso with the S-FCM and other existing sparse clustering algorithms on several numerical and real-life datasets. Comparisons and experimental results demonstrate that, in terms of these performance measures, the proposed S-FCM-Lasso performs better than S-FCM and existing sparse clustering algorithms. This validates the efficiency and usefulness of the proposed S-FCM-Lasso algorithm for high-dimensional datasets with sparsity.
Synergy between Artificial Intelligence and Hyperspectral Imagining—A Review
Authors: Khonina Svetlana N. , Kazanskiy Nikolay L. , Oseledets Ivan V. , Nikonorov Artem V. , Butt Muhammad A.
Published: September 2024

The synergy between artificial intelligence (AI) and hyperspectral imaging (HSI) holds tremendous potential across a wide array of fields. By leveraging AI, the processing and interpretation of the vast and complex data generated by HSI are significantly enhanced, allowing for more accurate, efficient, and insightful analysis. This powerful combination has the potential to revolutionize key areas such as agriculture, environmental monitoring, and medical diagnostics by providing precise, real-time insights that were previously unattainable. In agriculture, for instance, AI-driven HSI can enable more precise crop monitoring and disease detection, optimizing yields and reducing waste. In environmental monitoring, this technology can track changes in ecosystems with unprecedented detail, aiding in conservation efforts and disaster response. In medical diagnostics, AI-HSI could enable earlier and more accurate disease detection, improving patient outcomes. As AI algorithms advance, their integration with HSI is expected to drive innovations and enhance decision-making across various sectors. The continued development of these technologies is likely to open new frontiers in scientific research and practical applications, providing more powerful and accessible tools for a wider range of users.
Enhanced YOLOv8-Based System for Automatic Number Plate Recognition
Authors: Al-Hasan Tamim Mahmud , Bonnefille Victor , Bensaali Faycal
Published: September 2024

This paper presents an advanced automatic number plate recognition (ANPR) system designed specifically for Qatar’s diverse license plate landscape and challenging environmental conditions. Leveraging the YOLOv8 deep learning model, particularly the YOLOv8s variant, we achieve state-of-the-art accuracy in both license plate detection and number recognition. Our innovative approach includes a comprehensive dataset enhancement technique that simulates adverse conditions, significantly improving the model’s robustness in real-world scenarios. We integrate edge computing using a Raspberry Pi with server-side processing, demonstrating an efficient solution for real-time ANPR applications. The system maintains greater than 93% overall performance across various environmental conditions, including night-time and rainy scenarios. We also explore the impact of various pre-processing techniques, including edge detection, k-mean thresholding, DBSCAN, and Gaussian mixture models, on the ANPR system’s performance. Our findings indicate that modern deep learning models like YOLOv8 are sufficiently robust to handle raw input images and do not significantly benefit from additional pre-processing. With its high accuracy and real-time processing capability, the proposed system represents a significant advancement in ANPR technology and is particularly suited for Qatar’s unique traffic management needs and smart city initiatives.
Regularizing Lifetime Drift Prediction in Semiconductor Electrical Parameters with Quantile Random Forest Regression
Authors: Sommeregger Lukas , Pilz Jürgen
Published: September 2024

Semiconductors play a crucial role in a wide range of applications and are integral to essential infrastructures. Manufacturers of these semiconductors must meet specific quality and lifetime targets. To estimate the lifetime of semiconductors, accelerated stress tests are conducted. This paper introduces a novel approach to modeling drift in discrete electrical parameters within stress test devices. It incorporates a machine learning (ML) approach for arbitrary panel data sets of electrical parameters from accelerated stress tests. The proposed model involves an expert-in-the-loop MLOps decision process, allowing experts to choose between an interpretable model and a robust ML algorithm for regularization and fine-tuning. The model addresses the issue of outliers influencing statistical models by employing regularization techniques. This ensures that the model’s accuracy is not compromised by outliers. The model uses interpretable statistically calculated limits for lifetime drift and uncertainty as input data. It then predicts these limits for new lifetime stress test data of electrical parameters from the same technology. The effectiveness of the model is demonstrated using anonymized real data from Infineon technologies. The model’s output can help prioritize parameters by the level of significance for indication of degradation over time, providing valuable insights for the analysis and improvement of electrical devices. The combination of explainable statistical algorithms and ML approaches enables the regularization of quality control limit calculations and the detection of lifetime drift in stress test parameters. This information can be used to enhance production quality by identifying significant parameters that indicate degradation and detecting deviations in production processes.
Wearable Fall Detectors Based on Low Power Transmission Systems: A Systematic Review
Authors: Villa Manny , Casilari Eduardo
Published: September 2024

Early attention to individuals who suffer falls is a critical aspect when determining the consequences of such accidents, which are among the leading causes of mortality and disability in older adults. For this reason and considering the high number of older adults living alone, the development of automatic fall alerting systems has garnered significant research attention over the past decade. A key element for deploying a fall detection system (FDS) based on wearables is the wireless transmission method employed to transmit the medical alarms. In this regard, the vast majority of prototypes in the related literature utilize short-range technologies, such as Bluetooth, which must be complemented by the existence of a gateway device (e.g., a smartphone). In other studies, standards like Wi-Fi or 3G communications are proposed, which offer greater range but come with high power consumption, which can be unsuitable for most wearables, and higher service fees. In addition, they require reliable radio coverage, which is not always guaranteed in all application scenarios. An interesting alternative to these standards is Low Power Wide Area Network (LPWAN) technologies, which minimize both energy consumption and hardware costs while maximizing transmission range. This article provides a comprehensive search and review of that works in the literature that have implemented and evaluated wearable FDSs utilizing LPWAN interfaces to transmit alarms. The review systematically examines these proposals, considering various operational aspects and identifying key areas that have not yet been adequately addressed for the viable implementation of such detectors.
Impact of Temperature Elevation on Microbial Communities and Antibiotic Degradation in Cold Region Soils of Northeast China
Authors: Ni Zijun , Zhang Xiaorong , Guo Shuhai , Pan Huaqi , Gong Zongqiang
Published: September 2024

This study systematically investigated the effects of temperature changes on the degradation of antibiotics in soil, as well as the alterations in microbial community structure and aggregation, through a field warming experiment in a greenhouse. Compared to non-warming soil, the warming treatment significantly accelerated the degradation rate of tetracyclines during soil freezing and mitigated the impact of environmental fluctuations on soil microbial communities. The greenhouse environment promoted the growth and reproduction of a wide range of microbial taxa, but the abundance of Myxococcota was positively correlated with antibiotic concentrations in both treatments, suggesting a potential specific association with antibiotic degradation processes. Long-term warming in the greenhouse led to a shift in the assembly process of soil microbial communities, with a decrease in dispersal limitation and an increase in the drift process. Furthermore, co-occurrence network analysis revealed a more loosely structured microbial community in the greenhouse soil, along with the emergence of new characteristic taxa. Notably, more than 60% of the key taxa that connected the co-occurrence networks in both groups belonged to rare taxa, indicating that rare taxa play a crucial role in maintaining community structure and function.
Emamectin Poisoning in Thailand: Clinical Characteristics and Outcomes
Authors: Trakulsrichai Satariya , Sittiyuno Perapatn , Tansuwannarat Phantakan , Tongpoo Achara
Published: September 2024

Emamectin benzoate (Emamectin) is a broad-spectrum insecticide. Current data regarding emamectin poisoning in humans are very limited. We performed a 10-year retrospective cross-sectional study (2011–2020) using data from the Ramathibodi Poison Center database to examine the clinical characteristics and outcomes in patients exposed to emamectin. Eighty-eight patients were included. Most of the patients were male (72.7%) and exposure was frequently oral (86.4%) and intentional (67.0%).Their mean age was 42.8 years. The clinical presentations included gastrointestinal tract symptoms (62.5%), neurological symptoms (27.3%) including seizures, respiratory symptoms (6.8%), and local effects (12.5%). At presentation, the majority of patients exhibited normal consciousness and vital signs. Eleven patients showed no obvious clinical effects. Initially, 15 patients had metabolic acidosis and 11 had hypokalemia. Overall, 46 and 52 patients were administered gastric lavage and activated charcoal, respectively. Most patients (78.4%) were hospitalized, with a median hospital stay of 40 h, and generally received supportive treatment. Eight patients were intubated for ventilator support and one received inotropic drugs. Most patients (90.9%) showed no or minor outcomes; however, two patients died. The presence of Glasgow Coma Scale (GCS) <15 differed significantly (p < 0.001) between patients with no or minor outcomes (n = 80) and those with moderate or fatal outcomes (n = 8). In conclusion, emamectin poisoning mainly caused no or minor clinical effects. A low GCS at presentation was associated with worse outcomes. Therefore, patients who present with low GCS should be closely observed, monitored, and properly managed during hospitalization.
Spatial Analysis on the Service Coverage of Emergency Facilities for Fire Disaster Risk in an Urban Area Using a Web Scraping Method: A Case Study of Chiang Rai City, Thailand
Authors: Arreeras Saharat , Phonsitthangkun Suchada , Arreeras Tosporn , Arimura Mikiharu
Published: September 2024

Emergency service facilities play a pivotal role in mitigating the impact of fire disasters in urban areas. This research article delves into the critical aspects of analyzing service coverage for emergency facilities in relation to fire disaster risk in Chiang Rai city—a strategic hub in northern Thailand. Focusing on fire disaster risk merchandise and shops, categorized by the type of hazardous materials they store and sell, this study leverages facility location data obtained through web scraping from Google Maps. Utilizing spatial analysis and Geographic Information Systems (GISs), this research evaluates the reachability of emergency services, assessing travel times and coverage efficiency. The findings reveal significant disparities, particularly within the critical 3 min response window, highlighting the need for strategic improvements. This study offers actionable insights for urban planners and policymakers, advancing the integration of spatial technology in urban disaster management to enhance public safety and resilience.
Coxsackievirus B3 Activates Macrophages Independently of CAR-Mediated Viral Entry
Authors: Mohamud Yasir , Lin Jingfei Carly , Hwang Sinwoo Wendy , Bahreyni Amirhossein , Wang Zhihan Claire , Luo Honglin
Published: September 2024

Enteroviruses are a genus of small RNA viruses that are responsible for approximately one billion global infections annually. These infections range in severity from the common cold and flu-like symptoms to more severe diseases, such as viral myocarditis, pancreatitis, and neurological disorders, that continue to pose a global health challenge with limited therapeutic strategies currently available. In the current study, we sought to understand the interaction between coxsackievirus B3 (CVB3), which is a model enterovirus, and macrophage cells, as there is limited understanding of how this virus interacts with macrophage innate immune cells. Our study demonstrated that CVB3 can robustly activate macrophages without apparent viral replication in these cells. We also showed that myeloid cells lacked the viral entry receptor coxsackievirus and adenovirus receptor (CAR). However, the expression of exogenous CAR in RAW264.7 macrophages was unable to overcome the viral replication deficit. Interestingly, the CAR expression was associated with altered inflammatory responses during prolonged infection. Additionally, we identified the autophagy protein LC3 as a novel stimulus for macrophage activation. These findings provide new insights into the mechanisms of CVB3-induced macrophage activation and its implications for viral pathogenesis.
Characterization of Genetic Diversity in the Capsid Protein Gene of Grapevine Fleck Virus and Development of a New Real-Time RT-PCR Assay
Authors: de Souza Juliana Osse , Klaassen Vicki , Stevens Kristian , Erickson Teresa M. , Heinitz Claire , Al Rwahnih Maher
Published: September 2024

The grapevine fleck virus (GFkV) is a ubiquitous grapevine-infecting virus found worldwide, is associated with the grapevine fleck complex, and is often found in mixed infections with viruses of the grapevine leafroll complex and/or vitiviruses. Although GFkV has been studied for a long time, limited sequence information is available in the public databases. In this study, the GFkV sequence data available in GenBank and data generated at the Foundation Plant Services, University of California, Davis, were used to perform nucleotide sequence comparisons, construct a phylogenetic tree, and develop a new RT-qPCR assay. Sequence comparisons showed high genetic diversity among the GFkV isolates, and the phylogenetic analyses revealed a new group comprised of GFkV isolates identified in the present study. A new assay, referred to as GFkV-CP, was designed and validated using an existing GFkV positive control together with 11 samples known to be infected with combinations of different marafiviruses and maculaviruses but not GFkV. In addition, the newly designed assay was used in a field survey to screen grapevines from diverse geographical locations that are maintained at the United States Department of Agriculture (USDA) National Clonal Germplasm Repository (NCGR) in Winters, CA.
Dupilumab and House Dust Mite Immunotherapy in Patients with Atopic Dermatitis: A Preliminary Study
Authors: Bogacz-Piaseczyńska Agnieszka , Bożek Andrzej , Krupka-Olek Magdalena , Kawczyk-Krupka Aleksandra , Zalejska-Fiolka Jolanta , Canonica Giorgio Walter
Published: September 2024

Background: Severe atopic dermatitis (AD) is a complex disease requiring systemic treatment. This study aimed to assess the effectiveness of combined therapy consisting of dupilumab and sublingual dust mite allergen immunotherapy (SLIT-HDM) in patients with severe AD and HDM allergies. Methods: Patients diagnosed with severe AD were included in this randomised, placebo-controlled, double-blind 12-month trial; they received SLIT for HDMs and/or dupilumab for 12 months and were compared with patients on cyclosporine. The primary outcomes for the treatment arms were changes in the Eczema Area and Severity Index (EASI), body surface area (%BSA), and Investigator Global Assessment (IsGA) over 12 months. The secondary outcomes were the proportion of patients who achieved IsGA success and reduced medication scores. Results: Significant improvements were observed in all analysed groups after 12 months of therapy based on the EASI, %BSA, and IsGA. However, the most substantial changes were observed in the groups treated with dupilumab or a combination of SLIT-HDM and dupilumab. Additionally, the proportion of patients who achieved an IsGA reduction was significantly greater in the group receiving combination therapy than in the other groups (9/14 [64% of the group receiving SLIT-HDM] vs. 11/14 [73% of the group receiving dupilumab] vs. 15/17 [88% of the group receiving dupilumab and SLIT-HDM] vs. 7/13 [53% of the group receiving cyclosporine]) (p < 0.05). Conclusions: In patients with severe AD and HDM allergies, combination treatment with dupilumab and allergen immunotherapy for HDMs may increase the therapeutic benefit over treatment with these methods separately.
Trends in Vaccination Coverage among Children Aged 2–6 Years in Tennessee Counties, 2017–2023
Authors: Alali Walid Q. , Huang Qian , Goodin Kate , Gonzalez-Lozano Adrian
Published: September 2024

Background/Objectives: This study examines trends in county-level vaccination coverage before, during, and after the COVID-19 pandemic among children aged 2–3 and 4–6 years in Tennessee, with a focus on rurality; Methods: Data from the Tennessee Immunization Information System (January 2017 to September 2023) were analyzed for vaccination coverage in children in both age groups. The study categorized the COVID-19 pandemic into three periods: pre-pandemic (P1: January 2017 to December 2019), stay-at-home (P2: January 2020 to May 2021), and reopening (P3: June 2021 to September 2023). Vaccination trends were stratified by vaccine type, rurality, sex, race and ethnicity; Results: During P1, there were no significant changes in trends of vaccination coverage percentages in both rural and urban counties for both age groups. However, vaccination coverage declined significantly during P2 and P3 compared to P1 for most vaccines, except for influenza, which initially increased but later declined. Rural counties experienced a more pronounced decline compared to urban counties during P2 and P3 for both age groups. Within rural and urban counties, vaccination coverage was higher among white children compared to black children, and among non-Hispanic compared to Hispanic children. There were higher coverage percentages in age group 4–6 for all vaccines, except for influenza, compared to 2–3 year group; Conclusions: The COVID-19 pandemic has exacerbated disparities in childhood vaccination coverage, particularly in rural areas. These findings highlight the need for targeted public health interventions to address barriers to vaccination and ensure equitable access to vaccines for all children.
Impact of Toceranib Phosphate and Carprofen on Survival and Quality of Life in Dogs with Inflammatory Mammary Carcinomas
Authors: Garcia-de la Virgen Miguel , Del Portillo Miguel Isabel , Maiques Elisa , Pérez Roger Ignacio , Poch Enric , Borrego Juan
Published: September 2024

Canine inflammatory mammary carcinoma (IMC) is an aggressive and rare type of mammary gland cancer in dogs where vascular endothelial growth factor and cyclooxigenase-2 overexpression usually occur, which contribute to its invasive and angiogenic nature. This study aimed to evaluate the efficacy and safety of a combined treatment regimen of toceranib phosphate and carprofen in dogs with measurable IMC. Fifteen female dogs with histopathologically confirmed IMC were included, undergoing a regimen of toceranib (2.4–2.75 mg/kg PO, three times weekly) and carprofen (4.4 mg/kg/24 h PO). Initial evaluations included physical exams, tumor measurements, complete blood count, biochemistry, urinalysis, three view thoracic radiographs, and abdominal ultrasound. Follow-up assessments of physical condition and quality of life (QOL) were conducted bi-weekly, with tumor response evaluations monthly, using RECIST v1.0 criteria. While no complete or partial responses were observed, 60% of the dogs maintained stable disease, with a median progression-free survival of 76 days and an overall survival of 90 days. Notably, 60% of the dogs showed clinical benefit through improved QOL and disease stabilization. The treatment was well-tolerated, with only grade I/II toxicities reported. Despite limited biological activity against the cancer, this protocol may enhance QOL in dogs with IMC, offering a valuable palliative option.
Reflections on Small-Class Teaching in Veterinary Medicine Undergraduate Programs in China
Authors: Xia Pengpeng , Chen Ziyue , Luo Yi , Li Xiangyu , Ma Xin , Lian Siqi
Published: September 2024

As a cornerstone of higher education in China, the quality of undergraduate teaching is crucial for nurturing high-caliber innovative talents that meet the needs of national and social development. Small-class teaching has emerged as a focal point in the reform of undergraduate education and represents an important approach to cultivating top-notch innovative talents. Veterinary medicine is a scientific discipline that encompasses the prevention, control, diagnosis, and treatment of animal diseases. It also involves efforts to prevent the transmission of animal diseases to humans. The training of professionals in this field should emphasize the integration of theoretical knowledge with practical skills. Therefore, small-class teaching facilitates open communication between educators and students, which is instrumental in fostering a new generation of veterinarians equipped with robust professional knowledge, excellent practical abilities, and strong scientific literacy. This paper provides a preliminary exploration into the strategy and direction of small-class teaching within China’s veterinary medicine undergraduate programs by summarizing its characteristics, advantages, and existing challenges. The unique traits of veterinary medicine are also taken into consideration during this analysis.
Assisting the Learning of Clinical Reasoning by Veterinary Medical Learners with a Case Example
Authors: Ferlini Agne Gustavo , Carr Amanda (Mandi) Nicole , Kirkwood Roy Neville , Petrovski Kiro Risto
Published: September 2024

Effective clinical reasoning is essential for veterinary medical education, particularly in managing complex cases. This review explores strategies for learning clinical reasoning by veterinary medical learners, using a case example of mastitis to illustrate key concepts. Clinical reasoning encompasses cognitive, metacognitive, social, and situational activities, yet the literature on practical applications in veterinary education remains limited. The review discusses various stages of clinical reasoning, including data collection, problem representation, differential diagnosis, and management planning. It emphasizes the importance of integrating client-centered care and iterative evaluation into the clinical decision-making process. Key learning strategies include facilitation in using the domains of clinical reasoning—concepts, data collection, and analysis, taking action, and reflection on encounters. This review highlights best practices such as forward and backward reasoning, reflective practice, and the use of practical examples to enhance learners’ diagnostic accuracy and patient outcomes. The insights provided aim to enhance the training of veterinary learners, ensuring they can navigate day 1 as well as complex cases with improved diagnostic accuracy and patient outcomes.
Accurate Preoperative Localization of Thoracolumbar Disc Extrusion in Dogs: A Prospective Controlled Study
Authors: McCartney William , Ober Ciprian , Yiapanis Christos
Published: September 2024

Intervertebral disc disease (IVDD) is a very common cause of spinal cord compression in dogs. The errors of human surgeons operating on the wrong level or wrong side is a recognized problem and has been largely analyzed. To date, little information is available regarding these errors in dogs. The objective of this study was to assess the accuracy of disc localization prior to possible surgery for IVDD to ensure the surgeon begins their incision directly over the extruded disc. Eighty-five chondrodystrophic or brachycephalic dogs that presented with IVDD confirmed by CT or MRI scan were included in the study. Two small Backhaus clamps were placed cranial and caudal to the lesion site and a control clamp placed at the wing of the ilium. The main interest was whether the surgeon was able to preoperatively pinpoint the correct site for the surgery. Dorsoventral radiographs were taken to verify by another person if the clamps had been placed in the correct position. If the result was incorrect, the surgeon was asked to try again without knowing that the clamps were incorrect, and another radiograph was taken. This was repeated until the position was correct. The results were recorded as correct or incorrect and the number of attempts were registered. The results suggested no significant trend over time for any of the outcomes examined. There were some slight improvements over time, but none of the results was close to statistical significance. The findings of the study showed that in the thoracolumbar region the surgeon has a higher chance of incorrectly marking the exact site for surgery.
Effects of Ditch Water and Yellow River Irrigation on Saline–Alkali Characteristics of Soil and Paddy
Authors: Fan Liqin , Shen Jingli , Wang Xu , Zhang Yonghong
Published: September 2024

This study examined the agricultural water resource shortage and abundant ditch water resources in the Yinbei region of Ningxia. The effects of ditch water and Yellow River irrigation on the saline–alkali characteristics of soil and paddy were investigated using field monitoring and indoor detection methods in Pingluo County, Ningxia (106°31′ E, 38°51′ N). In addition to monitoring ditch water, four treatment groups were established: direct ditch water irrigation (T1), mixed ditch water and Yellow River water irrigation (T2), alternate ditch water and Yellow River water irrigation (T3), and irrigation solely with Yellow River water (CK). The results show the following: (1) The salinity of ditch water samples collected from the experimental field during the rice growth period was less than 1.60 g/L, and the pH of the samples was lower than 8.62; thus, they were classified as mildly brackish water. The application of ditch water irrigation did not result in soil saline–alkali aggravation and the accumulation of excessive amounts of heavy metals in soils and paddies in Pingluo County, Ningxia. (2) The rice yields for the CK, T1, T2, and T3 treatments were 10,437.5, 8318.4, 9182.1, and 9016.2 kg/hm2, respectively. Compared with Yellow River irrigation, the rice yields for the T1, T2, and T3 treatments were 20.3, 12.1, and 13.6% lower than that of CK, respectively, with minimal differences observed among them. Hence, under the condition of a water resource shortage in the Yellow River region, ditch water can be appropriately applied for mixed or alternate irrigation to ensure food security. This research has revealed the influences of ditch water irrigation on the saline–alkali properties of soil and the heavy metal contents of paddies.
An Early Warning System for Urban Fluvial Floods Based on Rainfall Depth–Duration Thresholds and a Predefined Library of Flood Event Scenarios: A Case Study of Palermo (Italy)
Authors: Pumo Dario , Avanti Marco , Francipane Antonio , Noto Leonardo V.
Published: September 2024

Several cities are facing an increasing flood risk due to the coupled effect of climate change and urbanization. Non-structural protection strategies, such as Early Warning Systems (EWSs), have demonstrated significant potential in mitigating hydraulic risk and often become the primary option when the implementation of structural measures is impeded by the complexities of urban environments. This study presents a new EWS designed specifically for fluvial floods in the city of Palermo (Italy), which is crossed by the Oreto River. The system is based on the preliminary definition of various Flood Event Scenarios (FESs) as a function of typical precursors, such as rainfall forecasts, and antecedent wetness and river flow conditions. Antecedent conditions are derived from real-time water stage observations at an upstream river section, while rainfall forecasts are provided by the Italian National Surveillance Meteorological Bulletins with a preannouncement time of up to 36 h. An innovative feature of the system is the use of rainfall Depth–Duration Thresholds to predict the expected hydrograph peak, significantly reducing warning issuing times. A specific FES, immediately accessible from a pre-built library, can be linked to any combination of precursors. Each FES predicts the timing and location of the first points of flooding; flood-prone areas and water depths; and specific hazard maps for elements typically exposed in cities, such as people, vehicles, and buildings. The EWS has been tested on a historical flood event, demonstrating satisfactory accuracy in reproducing the location, extent, and severity of the flood.
Numerical Analysis of Flow Characteristics and Energy Dissipation on Flat and Pooled Stepped Spillways
Authors: Farooq Umar , Li Shicheng , Yang James
Published: September 2024

The hydraulic performance of pooled stepped spillways has received less recognition compared to the traditional stepped spillways. Regarding the effectiveness of pooled stepped spillways in managing flow dynamics, previous studies have focused on investigating how different step configurations and varying chute angles can enhance energy dissipation in gravity flow over the chute. However, the potential for optimal performance and the importance of proper design have not been thoroughly explored in the existing literature. This study aims to explore new configurations of pooled stepped spillways and compare them to traditional stepped spillway designs to enhance hydraulic efficiency and maximize energy dissipation. The study examines two types of configurations of stepped spillways—two flat and two pooled configurations, each with ten steps. Using the computational Fluid Dynamics (CFD) technique, such as Volume of Fluid Method (VOF) and the realizable k-ε turbulence model for two-phase flow analysis with a 26.6° chute slope. Initially, the model was validated with experimental data by comparing various hydraulic parameters. These parameters include water depth, roller length, jump length, ratio of critical depth, and sequent depth. The hydraulic performance of both stepped geometric configurations was evaluated through numerical simulations to examine how the geometries of flat and pooled stepped spillways influence flow characteristics, energy dissipation, velocity, pressure distribution, and the Froude number at the downstream. The study analyzed downstream flow characteristics, maximum energy dissipation rates, depth-averaged velocity, static pressure, and pressure contours at the lateral direction under six different flow rates in flat and pooled stepped spillways. The findings indicate that flat-step configurations exhibit lower energy dissipation compared to pooled configurations. The relative energy loss of flow on pooled steps dissipates more energy than on flat steps. Furthermore, it is observed that the pooled configurations performed better for energy dissipation and flow stability compared to the flat configurations. The energy dissipation increased in pooled stepped spillways by 34.68% and 25.81%, respectively. Additionally, the depth-averaged flow velocity and pressure distribution decreased in case 2 and case 4 compared to the flat-step configurations.
An Integrated Analysis of Electric Battery Charging Station Selection—Thailand Inspired
Authors: Suvittawat Adisak , Suvittawat Nutchanon
Published: September 2024

The growing adoption of electric vehicles (EVs) necessitates a well-distributed network of charging stations. However, selecting optimal locations for these stations is a complex issue influenced by geographic, demographic, technical, and economic factors. This study aims to fill the gaps in previous research by providing a comprehensive analysis of factors influencing the selection of EV battery charging stations. This research focuses on integrating geographic, demographic, technical, and infrastructure considerations to inform strategic placement decisions. A quantitative approach was employed, using questionnaires distributed to 300 entrepreneurs in Thailand’s EV charging station sector. The data were analyzed using descriptive statistics and structural equation modeling (SEM) to evaluate the relationships among the influencing factors. The results reveal that technical and infrastructure factors significantly impact economic and financial considerations, which in turn influence the selection of charging stations. Additionally, geographic and demographic factors play a crucial role in shaping economic outcomes and the strategic placement of these stations. A holistic approach that integrates these diverse factors is essential for the strategic deployment of EV charging infrastructure, which supports increased EV adoption and contributes to environmental sustainability.
PENGARUH KOMITMEN ORGANISASI, IKLIM KERJA DAN PENGEMBANGAN KARIR TERHADAP SEMANGAT KERJA KARYAWAN PADA SEKOLAH TINGGI X JAKARTA
Authors: EZPERANZA REZA , PUJIANTO SURAHMAN
Published: September 2024

This studies are intended to determine the effect of Organizational Commitment, Work Climate and Career Development on Employee Morale at Sekolah Tinggi X Jakarta. The population of this study were all employees at Sekolah Tinggi X Jakarta. Researchers chose 60 respondents as a sample from this study, using saturated samples and data collected using questionnaires. This study use a statistical methods, with the SPSS Version 25 as a test tool. The results of this study indicate that the Work Climate and Career Development have an influence on Work Spirit. However, Organizational Commitment has no influence on the Employees' Morale at Sekolah Tinggi X Jakarta.