bluuebunny/crossref_metadata_2025 huggingface dataset:
North Korea's Nuclear Strategy: Limited Nuclear Use and Escalation Management*
Authors: Yoo Inseok
Published: November 2024

This article speculates on how North Korea will use nuclear weapons if the Korean War resumes and addresses how the ROK‐US Alliance should prepare for it. North Korea has strong incentives to arm itself with nuclear weapons for the regime's survival and for various other political, diplomatic, and economic goals. North Korea's nuclear weapons clearly indicate it is not merely arming itself for deterrence, negotiation, domestic solidarity, or prestige. It is the most likely country to employ nuclear weapons if they are ever used again in battle. North Korea is highly likely to use nuclear weapons in various ways, not only to make up for its weakness in conventional forces but also to coerce the Alliance in wartime. For this reason, there is a growing research trend calling for countermeasures against the possibility of North Korea preemptively using tactical nuclear weapons. Despite this shift in focus and the urgent strategic requirements called for, adequate systematic analyses of North Korea's nuclear strategy have not been made. This article assesses North Korea's nuclear strategy with an introduction to limited nuclear use (LNU) and escalation management (EM), followed by proposals for viable countermeasures by the Alliance. North Korea is most likely to use nuclear weapons in a limited manner to achieve strategic goals while avoiding nuclear retaliation by the USA in all phases of a war. The Alliance faces a challenge to establish an appropriate strategy to manage the dilemma over North Korea's nuclear strategy.
Transfusion‐Associated Graft‐Versus‐Host Disease in Pediatric Patients: Clinical Features and Outcomes
Authors: Araiza‐Atanacio Isabel , Sáez‐de‐Ocariz Marimar , Orozco‐Covarrubias Luz
Published: November 2024

Background

Transfusion‐associated graft‐versus‐host disease (TA‐GVHD) is a rare, usually fatal complication of blood transfusion.

Objective

To describe the characteristics of TA‐GVHD in children.

Methods

The clinical records of pediatric patients diagnosed with TA‐GVHD between January 2007 and December 2021 were reviewed.

Results

We analyzed 94 clinical records of pediatric patients (0–18 years) with a diagnosis of GVHD, of whom 6 (6.38%) were associated with TA‐GVHD; both genders being equally affected. The median age at diagnosis of the underlying disorder was 9 years, 1 month (range 2 months–15 years, 3 months); the median age at diagnosis of TA‐GVHD was 9 years, 5.5 months (range 1 year, 7 months–15 years, 7 months). There were 27 grafts; 8 were irradiated and 12 were filtered. All patients presented with Stage 3 cutaneous TA‐GVHD and histopathological Grade 2. All cases corresponded to classic acute TA‐GVHD with global clinical Grade I–II. Mortality rate was 67%. The median follow‐up of our patients was 2 years and 2 months (range 4 months–3 years, 4 months).

Conclusions

TA‐GVHD, although less frequently encountered than in previous years, is still a concern. Early suspicion of TA‐GVHD is mandatory due to its high mortality rates and rapid progression. Prevention by using irradiated blood products is the sole effective measure against this condition. Failing to identify and preempt TA‐GVHD not only jeopardizes patient survival but also underscores the critical importance of vigilant monitoring and proactive intervention in at‐risk patients.
The Effect of Different Concentrations of Melatonin on the Quality of Frozen and Thawed Semen of Jamnapari Goat
Authors: Alam Kabir , Srivastava Sushant , Verma Sanjeev Kumar , Verma Abhishek Kumar , Saurabh  , Kumar Rajesh , Kumar Rabindra , Jaiswal Ankit , Alam Azeer , Rana Tanmoy
Published: November 2024

Antioxidants help safeguard sperm cells from damage during the freeze–thaw process. Melatonin and its metabolites have an antioxidative effect. The current study aimed to evaluate the impact of melatonin supplementation in tris‐based extenders at various concentrations (0.5, 1.0 and 2 mM) on the freezability of Jamnapari goat spermatozoa. A total of 48 ejaculates were collected twice a week from four Jamnapari bucks (n = 12 × 4) using an artificial vagina during the period of October to November 2023. Selected ejaculates diluted with tris‐citric acid egg yolk extender were divided into four equal aliquots, and melatonin (dissolved in 0.1% dimethyl sulfoxide) was added later at 0.5, 1.0 and 2.0 mM to the control group (C) (extender and 0.1% DMSO) and treatment groups T1, T2 and T3, respectively. Various seminal attributes such as progressive motility, livability, acrosomal integrity, sperm abnormalities, sperm plasma membrane integrity, sperm penetration distance by vanguard spermatozoa in polyacrylamide gel and seminal plasma enzyme leakage (AST, ALT, ACP and AKP) were evaluated at post‐dilution and post‐thawed stages. Our findings revealed that all semen quality parameters were superior in melatonin‐treated groups than the C, and the differences were noticeably higher in the T2 group (1.0 mM) than the other groups. Adding 1.0 mM melatonin proved to be the most effective to safeguard sperm cells from cryopreservation induced cryodamage of Jamnapari buck.
6‐Gingerol and Astaxanthin Mitigate the Effects of Stearic Acid in Pig Oocyte Maturation
Authors: Saeed Hussain Ahmad , Sabir Rabia , Lu Xinyue , Jiang Yuan , Koutonin Bienvenu Odjoubire Mahougnon , Wang Dayu , Fu Yangfeng , Jia Chao , Li Juan
Published: November 2024

Elevated non‐esterified fatty acids (NEFAs), particularly stearic acid (SA), have a deleterious effect on oocyte maturation, leading to developmental damage and reproductive issues. High SA levels disrupt metabolic processes, inducing lipotoxicity that impairs oocyte quality and contributes to reproductive failures through early embryonic losses. This research investigates the lipotoxic effects of SA and assesses the protective potential of 6‐Gingerol (6‐G) and Astaxanthin (AX) on porcine oocytes during in vitro maturation (IVM). Herein, 6100 cumulus‐oocyte complexes (COCs) were exposed to various concentrations of SA (25–250 μM) to elucidate the concentration‐dependent effect on oocyte viability, polar body extrusion (PBE) and cumulus cell expansion index (CCEI). However, the efficacy of 6‐G (5–15 μM) and AX (2.5 μM) in combination with SA at 150 μM (SA6) concentration was evaluated to mitigate these adverse effects. The results indicated that SA6 substantially reduced oocyte viability, PBE and CCEI, demonstrating its toxic impact on oocyte developmental competence (p < 0.0001). Moreover, treatment with antioxidants such as SA6 + 6‐G (10 μM) and SA6 + AX showed a considerable increase in viability and PBE compared to SA6 alone (p < 0.05). These findings demonstrate the importance of lipid metabolism in oocyte health, where dysregulation impairs reproductive capacity. Both 6‐G and AX protected against lipotoxicity induced by SA6 while enhancing lipid homeostasis and the anti‐oxidative defences necessary for maintaining cellular integrity. This study finds substantial evidence that optimising the microenvironment with specific antioxidants can improve oocyte quality and provide invaluable knowledge in reproductive technologies and fertility treatments.
The HLA‐B*40:523 Allele Identified in a Volunteer Donor for Haematopoietic Stem Cell Transplant
Authors: Baek In‐Cheol , Choi Eun‐Jeong , Kim Hyoung‐Jae , Choi Haeyoun , Chung Yeun‐Jun
Published: November 2024

HLA‐B*40:523 differs from HLA‐B*40:92 in codon 167 in exon 3.
The HLA‐B*51:377N Allele Identified in a Volunteer Donor for Haematopoietic Stem Cell Transplant
Authors: Baek In‐Cheol , Choi Eun‐Jeong , Kim Hyoung‐Jae , Choi Haeyoun , Chung Yeun‐Jun
Published: November 2024

HLA‐B*51:377N differs from HLA‐B*51:01:01:01 in codon 13 in exon 2.
The HLA‐B*37:107 Allele Identified in a Volunteer Donor for Haematopoietic Stem Cell Transplant
Authors: Baek In‐Cheol , Choi Eun‐Jeong , Kim Hyoung‐Jae , Choi Haeyoun , Chung Yeun‐Jun
Published: November 2024

HLA‐B*37:107 differs from HLA‐B*37:01:01:01 in codon 25 in exon 2.
Moral Association Graph: A Cognitive Model for Automated Moral Inference
Authors: Ramezani Aida , Xu Yang
Published: November 2024

Automated moral inference is an emerging topic of critical importance in artificial intelligence. The contemporary approach typically relies on language models to infer moral relevance or moral properties of a concept. This approach demands complex parameterization and costly computation, and it tends to disconnect with existing psychological accounts of moralization. We present a simple cognitive model for moral inference, Moral Association Graph (MAG), inspired by psychological work on moralization. Our model builds on word association network for inferring moral relevance and draws on rich psychological data. We demonstrate that MAG performs competitively to state‐of‐the‐art language models when evaluated against a comprehensive set of data for automated inference of moral norms and moral judgment of concepts, and in‐context moral inference. We also show that our model yields interpretable outputs and is applicable to informing short‐term moral change.
Digital animal deathscapes: The online circulation of animals killed for conservation
Authors: Palmer Alexandra
Published: November 2024

This paper brings together animals, death, and digital geographies to examine the sharing of dead animal imagery on social media by conservationists in Aotearoa New Zealand (NZ). It is particularly concerned with two key questions: (1) Why (and how) do dead animals attract support for conservation? (2) How are personal feelings about animal death navigated in the public space of social media? In answering these questions, this paper extends geographical research on animals' affective allures (including online) beyond the realm of the living, and contributes to ongoing conversations around how to live with ‘unwanted others’. I draw on interviews with the leaders of conservation groups about whether, when, and why they post images of dead animals and kill counts, which I collectively refer to as ‘death media’. I show that because some viewers (at times disparaged as ‘precious’) were expected to respond with physical and/or moral disgust, conservationists typically only share death on ‘mainstream’ platforms if it is sufficiently sanitised or incorporated into positive narratives—though more commonly, death is absent from these platforms. Other audiences, particularly volunteer trappers, were described as ‘pragmatic’ or ‘bloodthirsty’; death was shared with these audiences to cultivate affects of hope and solidarity, in a context where killing can affectively feel like success. Yet even those comfortable with both killing and viewing death media at times expressed regret and sadness at the deaths of pests; they simply avoid sharing these feelings online. Death media thus perpetuate the public un‐grievability of ‘pests’, despite indications that even those who do the work of killing may experience sadness privately. I conclude by asking: what would be needed for pests killed for conservation to become grievable online, and how could doing so change relationships between humans and ‘pest’ animals?
Exports and foreign direct investment in the presence of downside risk
Authors: Khotamov Navruz
Published: November 2024

This study analyses the impact of downside risk on the flow of exports, foreign direct investment (FDI), and their joint pattern. Existing studies in this field have not considered the effects of risk asymmetry or downside risk because they describe risk only by variance; therefore, this study attempts to fill this gap. Downside risk is measured by the semi‐deviations of demand shocks and relates to country demand in the destination market. Using a panel of bilateral industry‐level data on trade and affiliate sales, and a panel of bilateral country‐level data on exports and FDI for many home and destination countries, I find that downside deviations of demand shocks affect the flows of exports, FDI, and their joint pattern. By focusing on downside risk, I present novel results. The results show that downside risk explains significant variation in the flow of exports, FDI, and in the proximity‐concentration tradeoff. Additionally, by conducting joint estimations of variance and semi‐deviations, I show that negative effects of demand risk are mostly due to the downside risk, and that downside volatility is more appropriate than the total volatility captured by the variance.
Interpreting Student Performance through Predictive Learning Analytics
Authors: Tan Fei Zhi , Chan Weng Howe
Published: November 2024

In today's information-rich world, accurately predicting student performance is crucial for institutions seeking to support at-risk students and ensure their success, but this task can be challenging. Learning analytics (LA) can help identify students who are struggling and provide them with the tools and opportunities they need to succeed, benefiting both students and institutions. However, data integration from various sources can be challenging in learning analytics, causing educators to struggle with managing and keeping track of students' progress and dropouts. The goal of this project is to generate insights into student performance through the application of machine learning methods, including Random Forest (RF), Artificial Neural Network (ANN), and Support Vector Machine (SVM). These methods were used to predict students' future results and the likelihood of students' dropout based on predictive learning analytics. RF, ANN, and SVM predictive models were constructed to predict students' future final results and dropout. The dataset from The Open University is used in this study, which consists of information from multiple aspects including data about courses, student registration, results, and their interactions with virtual learning environment. RF, ANN, and SVM models were constructed to predict students' future final results based on their learning behaviour. The performance of the models is evaluated based on accuracy, precision, recall, and time taken for training. In this study, the RF model demonstrated the best performance among the three predictive models for predicting final results and dropout with the shortest training time and achieved the highest accuracy. The RF model achieved an accuracy of 87.8% in predicting final results and 82.3% in predicting dropout while maintaining an average training time of 3.6 seconds. At the end of the study, the dashboards visually presented the results, offering valuable insights into students' learning outcomes. This enables educators to effectively support their students by utilizing predictive analytics, which includes identifying potential dropouts and tailoring assistance based on these predictions.
Interactive Course Registration System with Visualized Timetable
Authors: Ahmad Puad Amirul Faiz , Samingan Mohd Razak , Khatibsyarbini Muhammad
Published: November 2024

Course Registration System (CRS) is a web-based application that can be accessed by any platform and device as long as there is the internet that can be connected to the web service. The target user of the system is the student and staff of the school of computing Universiti Teknologi Malaysia (UTM), Johor Bahru. The CRS is a system that can provide a feature that helps the student to perform the course registration process sufficiently. The CRS system is developed through a hybrid agile waterfall methodology. The hybrid methodology provide systematic documentation for the project while offer flexibility during its development phase. A visual timetable generated and able to view the list of course mate in the registration process are major features that CRS provide. These features are the basic things that should be able to be implemented in course registration for it easier for the student to identify the clash course taken and make their study plan. At the end the CRS system able to provide a complete feature that make students register for a course with less burden and less complexity through the visualized table feature.
Justiça Distributiva em Conflitos de Energia Eólica: Análise de Decisões Judiciais sobre Impactos de Parques no Ceará
Authors: Davi Mendes Emilia , Mendes de Almeida Collaço Flávia
Published: November 2024

Os conflitos em projetos de energia eólica destacam as dinâmicas de uso e apropriação dos territórios, equilibrando, de um lado, relações sociais e vínculos materiais e simbólicos, e de outro, a mercantilização para fins industriais. No Ceará, a agenda de transição energética sustentável, focada em fontes renováveis, tem sido fortemente promovida. No entanto, políticas de transição que desconsideram realidades locais podem gerar incoerências na promoção do direito a um ambiente ecologicamente equilibrado para populações afetadas e falhar na garantia do direito à energia de forma ampla e acessível. Este estudo analisa os impactos positivos e negativos de parques eólicos em 81 processos judiciais do Tribunal de Justiça do Ceará (TJCE) nos últimos 20 anos, identificando os atores afetados. Os resultados indicam que as relações de poder e escolhas institucionais distribuem assimetricamente os ônus e bônus dos parques eólicos implantados no estado, proporcionando benefícios mínimos e imprevisíveis para as comunidades locais. Consequentemente, a justiça distributiva não é plenamente realizada pelo judiciário, que muitas vezes refreado pelo fundamento da “utilidade pública”, se limita a compensar danos já sofridos sem redistribuir efetivamente os impactos positivos e negativos. Além disso, a escassez de demandas coletivas impede a consideração de danos ambientais, culturais e socioeconômicos mais amplos, colaborando para a manutenção de privações entre grupos sociais afetados.
Inovação Regulatória na Transição Energética: Cientificidade do Direito e Políticas Públicas
Authors: Mendonça Samuel , Francisco Nagao Menezes Daniel , Pereira da Silva Luiz Carlos , González Rivera Tatiana Vanessa
Published: November 2024

RESUMO: A carta editorial apresenta o tema da inovação regulatória na transição energética no contexto do dossiê intitulado: Direito, Sustentabilidade e Inovação Regulatória: impactos da Transição Energética. Analisa o Direito, de forma breve, em duas perspectivas, quais sejam, na sua cientificidade e na dimensão das políticas públicas. Considera as fragilidades da ciência jurídica e sublinha a dimensão crítica como exemplar do campo. Avança na afirmação das políticas públicas como alternativas à promoção da dignidade humana e da justiça social. Por meio do método analítico, avalia distintos textos e reafirma o sentido do campo jurídico como essencial para a resolução de problemas na sociedade. Apresenta os textos do dossiê de forma breve, enfatizando a dimensão crítica dos autores e enfatizando a afirmação da justiça social.
 
PALAVRAS-CHAVE: Direito; Inovação regulatória; Políticas Públicas; Transição energética
Group B streptococcal infections in pregnancy and early life
Authors: Manuel Gygeria , Twentyman Joy , Noble Kristen , Eastman Alison J. , Aronoff David M. , Seepersaud Ravin , Rajagopal Lakshmi , Adams Waldorf Kristina M.
Published: November 2024

Bacterial infections with Group B
Streptococcus
(GBS) are an important cause of adverse outcomes in pregnant individuals, neonates, and infants. GBS is a common commensal in the genitourinary and gastrointestinal tracts and can be detected in the vagina of approximately 20% of women globally. GBS can infect the fetus either during pregnancy or vaginal delivery resulting in preterm birth, stillbirth, or early-onset neonatal disease (EOD) in the first week of life. The mother can also become infected with GBS leading to postpartum endometritis, and rarely, maternal sepsis. An invasive GBS infection of the neonate may present after the first week of life (late-onset disease, LOD) through transmission from caregivers, breast milk, and other sources. Invasive GBS infections in neonates can result in sepsis, pneumonia, meningitis, neurodevelopmental impairment, death, and lifelong disability. A policy of routine screening for GBS rectovaginal colonization in well-resourced countries can trigger the administration of intrapartum antibiotic prophylaxis (IAP) when prenatal testing is positive, which drastically reduces rates of EOD. However, many countries do not routinely screen pregnant women for GBS colonization but may administer IAP in cases with a high risk of EOD. IAP does not reduce rates of LOD. A global vaccination campaign is needed to reduce the significant burden of invasive GBS disease that remains among infants and pregnant individuals. In this narrative review, we provide a comprehensive overview of the global impact of GBS colonization and infection, virulence factors and pathogenesis, and current and future prophylactics and therapeutics.
Supplemental Material: Spatial and temporal reconstruction of postcollisional potassic rocks: Implications for mantle flow beneath the SE Tibetan Plateau
Authors: Miao Zhuang , Xu Bo , al. et
Published: November 2024

All data used for Hf and Nd isotopic mapping in this study and bulk-rock geochemical analyses results.
The Influence of Football on Mental Health Quality Based on Data Mining Algorithm
Authors: Xiao Chenglong
Published: November 2024

Data mining technology can solve the hidden rules of data when solving problems, which has great advantages. With the increasing maturity of data mining technology, its application in teaching is also more and more. This paper aims to analyze the specific impact of campus football activities on students’ mental health quality through the application of data mining algorithms, especially decision trees and association rule algorithms. On this basis, a data mining algorithm is applied to study the influence of campus football activities on students’ sports quality and mental health state. First, the present situation of campus football is expounded. First, the development status of campus football is described, and the research of data mining algorithms is summarized. This paper establishes an analysis model of the influence of campus football on students’ mental quality and uses a decision tree and association rule algorithm in a data mining algorithm to analyze students’ sports quality and mental health state. The algorithm in this article adopts the method of one-time scanning of the database, and after generating new frequent itemsets, the database continuously decreases. When the pruning severity is set to 30–60, higher accuracy can be achieved, and the pruning severity is set to 40 in the design. Subsequent operations do not require scanning again, which can occupy less space and reduce time complexity. The algorithm test shows that the design accuracy and accuracy of the algorithm have been improved, which can meet the needs. The designed analysis of students’ sports quality and mental health state based on the data mining algorithm can provide effective data for the decision-making of campus football activities.
A Novel Medical Cyber-Physical Systems Based on Digital Twin-Driven Platform
Authors: Zhang LiangMing , Yang Guangqian , Li Jinheng , Liang Jianling
Published: November 2024

A Medical Cyber-Physical System (MCPS) represents a sophisticated healthcare framework seamlessly integrating cyber and physical elements to enhance medical processes, diagnostics, and patients. The integration of Artificial Intelligence (AI) into the healthcare system has been pivotal in advancing intelligent MCPS and ushering in an era of advanced healthcare solutions. The paradigm of smart hospitals aspires to implement intelligent solutions seamlessly integrating hardware and software to control, supervise, and monitor patients while assisting healthcare professionals. Such solution is essential for smart decision-making and enhancing healthcare services. However, complete utilization of this intelligent MCPS relies on an effective framework that should facilitate the interaction among patients, medical devices, AI services and hospital staff. This paper introduces a Digital Twin (DT)-based Smart Medical Cyber-Physical System (DT-MCPS) designed to enhance smart hospitals. Leveraging DT technology, DT-MCPS constructs a virtual replica of the hospital, facilitating precise control and supervision of patient care, coupled with service optimization through comprehensive data integration. DT-MCPS promotes personalized decision-making by seamlessly integrating medical records and real-time monitoring of physiological data, enabling predictive insights into disease progression. Moreover, DT-MCPS employs a model-based platform founded on web services to monitor the patient’s state in real-time while accurately simulating the hospital medical systems workflows and contributing to long-term health management. Experimental results showcase the efficacy of DT-MCPS in enhancing hospitalization services, streamlining real-time control, and achieving highly precise personalized patient diagnostics.
Design of Multimedia Teaching Software Based on Distributed Network Architecture
Authors: Meng Xiao-Ke , Wang Si-Yu , Wang Li-Xin
Published: November 2024

With the leap of network technology and the vigorous development of online teaching, many universities are actively adopting online means to optimize teaching and course management. This paper focuses on building an efficient and comprehensive auxiliary teaching platform that integrates functions such as student learning monitoring, course management, online testing, and teacher–student interaction, aiming to improve the quality of education. Designs based on distributed B/S architecture and web technology to ensure efficient resource allocation and expansion, meet the needs of large-scale concurrent learning, and achieve cross-platform access to enhance user experience. The platform features personalized learning support, enhanced interactive collaboration, and the construction of a multimedia teaching database through data analysis. The innovation lies in using neural network technology to create an intelligent question answering module, utilizing cosine similarity to automatically group teaching resources, and using graph convolution and variational autoencoder techniques to construct a student performance monitoring model. Experimental verification shows that the platform runs stably, effectively reduces the blocking rate, and significantly improves students’ academic performance, pass rate, and learning interest. This design not only successfully completed the teaching task, but also provided valuable experience for the application of online-assisted teaching systems in subject education.
A Smart Tourism Resource Information Management Platform Based on Multi-Source Data Fusion
Authors: Qiang Sha , Lan Ma , Nan Chen
Published: November 2024

Leveraging multiple data sources to enhance tourism resource management and visitor behavior analysis has become a key challenge in the context of the booming smart tourism industry. In this study, we explore how to integrate and optimize multiple data sources including social media activities, user reviews, tourism statistics, and geographic information to build a comprehensive information management platform for smart tourism resources. Given the limitations inherent in isolated and decentralized data processing approaches in the smart tourism domain, we propose a new approach using deep learning autoencoders for efficient extraction and fusion of meaningful features from heterogeneous datasets. Our methodology encompasses a rigorous data collection and preprocessing phase, ensuring data quality and consistency, followed by the application of autoencoders to learn high-level feature representations conducive to data integration. The fused data facilitate the development of strategies for the optimal allocation of tourism resources and nuanced analysis of visitor behavior patterns. Experimental evaluations demonstrate the model’s proficiency in capturing intricate data relationships, significantly enhancing the predictive accuracy for tourism demand forecasting, and enabling personalized visitor recommendations. The results underscore the potential of our approach to revolutionize smart tourism management practices by providing actionable insights into resource optimization and visitor engagement strategies, thereby contributing to the sustainable growth of the tourism sector.
Satellite Image Small Target Super-Resolution Detection Based on ACGAN and Enhanced DETR
Authors: Shen Fangyu , Wei Zikang , Zhang Yang , Zheng Zhi , Su Xinyue
Published: November 2024

In recent years, with the rapid development of deep learning, neural network and other related technologies and their wide application in image processing research, the degree of intelligence in the field of image processing research is getting higher and higher. Especially in the research of image small target detection, because of its relatively small shape, image small target has relatively few and unclear feature information and detail information, which makes it easy to make errors and omissions in recognition and detection. To improve the precision of satellite image small target detection, this paper processes a small image target super-resolution detection based on ACGAN and enhanced DETR. In this paper, ACGAN is used to classify and generate the feature information of small targets in images to enhance the feature information of small targets to be measured. Second, the DETR algorithm model is improved, and a small target detection algorithm model with image super-resolution enhancement is designed to generate high-resolution images by super-resolution reconstruction of images with enhanced target feature information to improve the detection accuracy of image small targets. The experiments in this paper show that after the processing of target feature enhancement and image super-resolution quality enhancement, the detection accuracy of image small targets has been improved significantly.
Diagnostic Ambiguity Caused by an Atypical e18a2 BCR::ABL1 Transcript in a Chronic Myeloid Leukemia Patient
Authors: Pretzsch Thomas , Progscha Steve , Burmeister Thomas
Published: November 2024

We describe the case of a chronic myeloid leukemia (CML) patient with a rare atypical e18a2 BCR::ABL1 transcript. The generation of this transcript was explained by a detailed molecular analysis, including the identification of both chromosomal breakpoints (BCR::ABL1 on der(22) and ABL1::BCR on der(9)) at the genomic level. The use of a cryptic splice site in intron 1 of ABL1 led to the generation of an in‐frame BCR::ABL1 fusion transcript. The diagnostic difficulties caused by this atypical variant and its implications for diagnostic routine are discussed.
Deep Learning Network Comparison and Validation in Landsat Imagery Cloud Detection
Authors: Hui Miao , Xie Huiying , Chi Yufeng
Published: November 2024

Cloud coverage poses a prevalent challenge in optical remote sensing image processing, significantly hindering the visibility and interpretability of ground‐level information. The application of deep learning technology in remote sensing image cloud detection has witnessed a remarkable advancement, rendering it an increasingly pervasive and potent solution to the challenge of cloud coverage. To thoroughly investigate the effectiveness of diverse deep learning architectures in cloud detection tasks, this research selected five seminal models: AlexNet, VGG16, GoogLeNet, ResNet34, and the cutting‐edge Swin Transformer, and performed a comprehensive comparative analysis of their application in identifying clouds within medium‐resolution Landsat 8 satellite imagery. During the training phase, each model distinctly demonstrated unique strengths in enhancing accuracy, refining loss functions, optimizing resource utilization, and accelerating training processes. In the test phase, the models’ performance was rigorously evaluated using overall accuracy (OA) and other quantitative metrics, providing solid empirical evidence for the variations in their performance. Furthermore, an insightful analysis of the visualization outcomes and a meticulous comparison of the nuanced differences between model predictions and actual cloud images underscored the individual models’ exceptional abilities in capturing intricate cloud details and executing precise edge processing. To alleviate the cumbersome process of pixel‐level labeling, this study adopts the effective block‐level labeling approach. This approach drastically streamlines annotation processes, ultimately translating into substantial cost savings and a marked reduction in time required for data preparation. The experimental results demonstrate that the Swin Transformer network performs particularly well in the cloud detection task of Landsat 8 images, achieving an OA of 90.73% under block‐level annotation, significantly higher than other comparison models, showcasing excellent cloud detection capabilities. Furthermore, the study also found that the size of input image blocks has a significant impact on detection results. Under the same network architecture, using 32 × 32 image blocks for cloud detection improves the OA by at least 10 percentage points compared to using 64 × 64 image blocks. This finding provides important insights for optimizing cloud detection algorithms. In summary, this study not only verifies the superiority of Swin Transformer in cloud detection in remote sensing images but also reveals the impact of image block size on detection performance, providing new ideas and directions for future advancements in remote sensing image processing and cloud detection technology.
Effect of Process Parameters and Material Selection on the Quality of 3D Printed Products by Fused Deposition Modeling (FDM): A Review
Authors: Palanisamy Sivasubramanian , Karuppiah Ganesan , Kumar Praveen , Dharmalingam Shanmugam , Mubarak Suhail , Santulli Carlo , Ayrilmis Nadir , Karumuri Srikanth
Published: November 2024

This work presents an investigation on the quality of parts manufactured using fused deposition modeling (FDM), which is influenced by a large number of different elements. Some of which are based on the materials used in the production of the part, though others are rather pertinent to the process parameters. The manufacturing process and filament formulation has also a significant impact on the cost of the final product, as well as its physical, mechanical, and thermal properties. As the result, judicious combination of parameters can effectively act toward fine‐tuning FDM toward three‐dimensional printing (3DP) of pieces with quality fit‐for‐application. In this sense, the use of design of experiments (DOEs) is often needed for the purpose. Printing process parameters, including layer height, wall thickness, temperature, printing velocity, and tool path, have been discussed, in the understanding that 3DP time increases with decreasing layer thickness, and in turn increases production time and overall cost. A specific account is given on recent developments increasingly and more thoroughly focused on recognizing the impact of the process parameters and raw materials on the final product.
A Charger Current–Limiting Scheme to Improve Protection Coordination of Electric Vehicle–Integrated Distribution Systems
Authors: Tavoosi Majid , Fani Bahador , Delshad Majid , Sadeghkhani Iman
Published: November 2024

Although the development of electric vehicle (EV) technology offers opportunities for reducing CO2 emissions through the electrification of transportation, the integration of EVs into distribution systems poses a significant challenge to the reliable operation of existing protection systems. As the penetration level of EVs continues to rise, the fault current characteristic of the distribution system changes, resulting in load de‐energization, equipment damage, and reduced reliability. This paper develops a protection scheme for preserving coordination between main and backup overcurrent relays considering various penetration levels and locations of integrated EVs. By modifying the EV charger control system, the proposed scheme limits the fault current contribution of adopted EV charge stations into the fault point. The developed scheme does not alter the structure of the available protection system of the distribution network and is compatible with both old and nonprogrammable relays. Furthermore, it does not require communication links. The effectiveness of the proposed scheme is validated through several case studies on the Isfahan distribution network. The findings indicate that the operating time of the backup relay in the conventional protection system exceeds the thermal limit at 100% penetration level of EVs installed upstream of this relay as it reaches 1810 ms, while by using the proposed strategy, this time reduces to 776 ms, preserving protection coordination between the main and backup relays.
Analysis of Changes in the Bioglass Coating in the Presence of Simulated Physiological Fluids
Authors: Talavera-Lopez A. , Roque G. , Arias A. N. Ardila , Salazar-Hernández M. , Ruelas-Leyva J. P. , Hernandez-Soto R. , Hernández J. A.
Published: November 2024

Research of new materials for bone substitutes is of the utmost importance. Bioglass (BG) is an excellent material for this necessity due to its biocompatibility with surrounding tissues once implanted. Unfortunately, these implants tend to develop cracks. Therefore, an alternative is to use a hydroxyapatite (HA) coating (BHAC) to prevent crack formation and its consequent damage restoration for better properties. The BHAC formed was analyzed using different nitric acid (HNO3) concentrations. In addition, attenuated total reflectance Fourier transform spectroscopy (ATR‐FTIR), energy dispersive spectrometry (EDS), scanning electron microscopy (SEM), and X‐ray diffraction (XRD) were performed on the HA coating after immersion in simulated body fluid (SBF). The BHAC was submerged in a simulated gastric fluid (SGF) and simulated intestinal fluid (SIF) to evaluate changes in the groups of the biomaterial surface, specifically the Si–OH and P–O groups. Moreover, the variations in the Ca/P molar ratio of BHAC suggested significant changes in the BG cover when subjected to a physiological environment since HA converts into tricalcium phosphate (TCP) and dicalcium phosphate dihydrate (DCPD). Also, the presence of Si ions is modified when BHAC is immersed in SIF.
Wearable Technology for Elderly Care: Integrating Health Monitoring and Emergency Alerts
Authors: Hasan Nowshad , Ahmed Mohammad Faisal
Published: November 2024

With the growing elderly population, ensuring consistent and reliable healthcare monitoring has become increasingly important. This research introduces an innovative solution in the form of a smart glove designed specifically for elderly care. The glove is equipped with advanced features such as fall detection, emergency messaging via hand gestures, and vital signs monitoring, including oxygen saturation (SpO2) and heart rate. The smart glove integrates the MPU6050 and MAX30100 sensors with Arduino and ESP8266 modules to achieve these functionalities. Fall detection is accurately identified by the MPU6050 sensor, while the MAX30100 sensor monitors SpO2 and heart rate. Hand gestures are recognized and interpreted for sending emergency messages. Data from these sensors are transmitted through IFTTT, enabling alerts and notifications via SMS, email, and a secured website, thus facilitating real‐time remote monitoring and communication. This setup provides a comprehensive and reliable method for monitoring the health and safety of elderly individuals, ensuring prompt response and care in emergencies. The proposed system demonstrates significant potential in enhancing the quality of life for elderly individuals by offering a smart, integrated, and user‐friendly healthcare solution.
Motion Characteristics Analysis and Realization of Hydraulic Drive Segment Assembly Machine
Authors: Wang Haiyan , Wang Hongmei , Yu Pulian
Published: November 2024

For the current situation of the intelligence, the level of the segment assembly process was lower than it was expected. This paper took the 6‐DOFs segment assembly machine designed by Shandong Jiaotong University and Jinan Heavy Industries Group Co., Ltd., as an example and specified the difference between the 6‐DOFs segment assembly machine and common 6‐DOFs mechanical arms. The core work of the paper contained two aspects. Firstly, the paper analyzed the kinematics mechanism and pointed out the mechanism characteristics of the segment assembly machine which was driven by six hydraulic cylinders and two hydraulic motors. Secondly, for the relationships between the joint rotative angles and the displacement of the driving hydraulic cylinders being more complex and intricate than they were expected, the paper illustrated the reason why there was no analytical solution for this mechanism and provided a simple method to obtain numerical solutions.
Pharmacological Appraisal of Aqueous Ethanolic Extract of Cuminum cyminum (Cumin Seeds) in Obesity and Endocrinopathies Associated With Polycystic Ovarian Syndrome in Animal Models
Authors: Wang Wenwen , Barkat Muhammad Qasim , Amin Sehrish , Alshammari Abdulrahman , Albekairi Norah A. , Manzoor Hina , Chauhdary Zunera , Bazmi Rizwan Rashid , Hussain Liaqat , Chen Qin
Published: November 2024

A multidisciplinary endocrinopathy affecting women in their reproductive years, polycystic ovarian syndrome, causes insulin resistance, hyperandrogenism, cardiovascular issues, obesity, and menstrual difficulties. Cuminum cyminum (cumin seed) is a famous spice traditionally used for various ailments such as indigestion, headache, diarrhea, obesity, and gynecological disorders. This study explored the pharmacological potential of aqueous ethanolic extract of Cuminum cyminum (AECC) in letrozole‐induced PCOS animals, which were also obese. HPLC analysis revealed the presence of chlorogenic acid, gallic acid, hydroxybenzoic acid (HB acid), caffeic acid, vanillic acid, kaempferol, sinapic acid, ferulic acid, salicylic acid, coumarin, quercetin, benzoic acid, rutin, and p‐coumaric acid. Thirty adult female rats were divided into six groups (5 animals in each group). PCOS was induced by using letrozole (1 mg/kg). The groups were normal control, diseased control, standard (metformin, 20 mg/kg), and AECC (200, 400, and 600 mg/kg). Vaginal smear cytology was used to confirm the PCOS. The animals were euthanized after 12 weeks, and blood was drawn for hormonal and biochemical study. We used isoflurane 5% for euthanasia in a closed chamber. The ovaries were removed for histopathology. Ovarian histopathology showed abnormalities with cystic follicles in PCOS female rats. It also produced hyperinsulinemia, LH surge, lower FSH, perturbed LH/FSH ratio, and higher levels of testosterone and weight gain. Moreover, it also produced oxidative stress with ROS (reactive oxygen species) production. Meanwhile, AECC treatment converted cystic follicles into primary, secondary, and differentiating follicles with healthy granulosa cells and corpus luteum with significant (p < 0.001) weight loss. AECC significantly (p < 0.001) reduced serum insulin levels and normalized LH/FSH ratio, with improved FSH levels and control of LH surge. AECC also reduced oxidative stress and lipid peroxidation with significant (p < 0.001) improvement of antioxidant markers. It has been concluded that AEEC can alleviate PCOS symptoms by improving insulin resistance, reducing weight, addressing hyperandrogenism, regulating the LH/FSH ratio, and overcoming oxidative stress and ROS production.
Table S1 from The Novel Nucleoside Analogue ProTide NUC-7738 Overcomes Cancer Resistance Mechanisms In Vitro and in a First-In-Human Phase I Clinical Trial
Authors: Schwenzer Hagen , De Zan Erica , Elshani Mustafa , van Stiphout Ruud , Kudsy Mary , Morris Josephine , Ferrari Valentina , Um In Hwa , Chettle James , Kazmi Farasat , Campo Leticia , Easton Alistair , Nijman Sebastian , Serpi Michaela , Symeonides Stefan , Plummer Ruth , Harrison David J. , Bond Gareth , Blagden Sarah P.
Published: November 2024

Table S1 related to Figure 1: NUC-7738 has cytotoxic activity
Supplementary Figure 2E from The Novel Nucleoside Analogue ProTide NUC-7738 Overcomes Cancer Resistance Mechanisms In Vitro and in a First-In-Human Phase I Clinical Trial
Authors: Schwenzer Hagen , De Zan Erica , Elshani Mustafa , van Stiphout Ruud , Kudsy Mary , Morris Josephine , Ferrari Valentina , Um In Hwa , Chettle James , Kazmi Farasat , Campo Leticia , Easton Alistair , Nijman Sebastian , Serpi Michaela , Symeonides Stefan , Plummer Ruth , Harrison David J. , Bond Gareth , Blagden Sarah P.
Published: November 2024

Figure S2E related to figure 3: Validation of top hits from genome wide haploid screen. E) mRNA expression levels are given as z-score calculated across all NCI-60 cell lines. mRNA expression levels were obtained from CellMinerTM v2.4.2.
Supplementary Table 1 from Tumor Cell IDO Enhances Immune Suppression and Decreases Survival Independent of Tryptophan Metabolism in Glioblastoma
Authors: Zhai Lijie , Bell April , Ladomersky Erik , Lauing Kristen L. , Bollu Lakshmi , Nguyen Brenda , Genet Matthew , Kim Miri , Chen Peiwen , Mi Xinlei , Wu Jennifer D. , Schipma Matthew J. , Wray Brian , Griffiths John , Unwin Richard D. , Clark Simon J. , Acharya Rajesh , Bao Riyue , Horbinski Craig , Lukas Rimas V. , Schiltz Gary E. , Wainwright Derek A.
Published: November 2024

Supplementary Table 1. Demographics of patient-isolated tissue samples.
Supplementary fig 4 from Ovarian Cancer–Specific BRCA-like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial
Authors: Schouten Philip C. , Richters Lisa , Vis Daniel J. , Kommoss Stefan , van Dijk Ewald , Ernst Corinna , Kluin Roelof J.C. , Marmé Frederik , Lips Esther H. , Schmidt Sandra , Scheerman Esther , Prieske Katharina , van Deurzen Carolien H.M. , Burges Alexander , Ewing-Graham Patricia C. , Dietrich Dimo , Jager Agnes , de Gregorio Nikolaus , Hauke Jan , du Bois Andreas , Nederlof Petra M. , Wessels Lodewyk F. , Hahnen Eric , Harter Philipp , Linn Sabine C. , Schmutzler Rita K.
Published: November 2024

Supplemental Figure 4. Number of segments and variance of segments in misclassified and properly classified ovarian cancer samples with the BRCA1-like classifier.
Supplementary fig 2 from Ovarian Cancer–Specific BRCA-like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial
Authors: Schouten Philip C. , Richters Lisa , Vis Daniel J. , Kommoss Stefan , van Dijk Ewald , Ernst Corinna , Kluin Roelof J.C. , Marmé Frederik , Lips Esther H. , Schmidt Sandra , Scheerman Esther , Prieske Katharina , van Deurzen Carolien H.M. , Burges Alexander , Ewing-Graham Patricia C. , Dietrich Dimo , Jager Agnes , de Gregorio Nikolaus , Hauke Jan , du Bois Andreas , Nederlof Petra M. , Wessels Lodewyk F. , Hahnen Eric , Harter Philipp , Linn Sabine C. , Schmutzler Rita K.
Published: November 2024

Supplemental Figure 2. Error rate of the BRCA1-like ovarian cancer classifier at various thresholds of shrinkage.
Supplementary Data from Ovarian Cancer–Specific BRCA-like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial
Authors: Schouten Philip C. , Richters Lisa , Vis Daniel J. , Kommoss Stefan , van Dijk Ewald , Ernst Corinna , Kluin Roelof J.C. , Marmé Frederik , Lips Esther H. , Schmidt Sandra , Scheerman Esther , Prieske Katharina , van Deurzen Carolien H.M. , Burges Alexander , Ewing-Graham Patricia C. , Dietrich Dimo , Jager Agnes , de Gregorio Nikolaus , Hauke Jan , du Bois Andreas , Nederlof Petra M. , Wessels Lodewyk F. , Hahnen Eric , Harter Philipp , Linn Sabine C. , Schmutzler Rita K.
Published: November 2024

Supplementary Methods
Supplementary Data from Antitumor Activity of the Novel BTK Inhibitor TG-1701 Is Associated with Disruption of Ikaros Signaling in Patients with B-cell Non–Hodgkin Lymphoma
Authors: Ribeiro Marcelo Lima , Reyes-Garau Diana , Vinyoles Meritxell , Profitós Pelejà Núria , Santos Juliana Carvalho , Armengol Marc , Fernández-Serrano Miranda , Sedó Mor Alícia , Bech-Serra Joan J. , Blecua Pedro , Musulen Eva , De La Torre Carolina , Miskin Hari , Esteller Manel , Bosch Francesc , Menéndez Pablo , Normant Emmanuel , Roué Gaël
Published: November 2024

Supplemental Materials and Methods, Results, Tables and Figures