bluuebunny/crossref_metadata_2025_split huggingface dataset:
Serum vitamin D levels as a potential risk factor for olfactory abnormalities in children with autism spectrum disorders: a case-control study
Authors: Zhang Zhepei , Ren Pengcheng , Zhao Chanjuan , Chen Miancong , Li Hongai , Xiang Wei 
Published: February 2024

Abstract
Objective
To explore the relationship between blood 25-hydroxyvitamin D (25(OH)D) levels and olfactory abnormalities in patients with autism spectrum disorder (ASD).
Methods
A pathology-controlled study method was used to enroll 115 children with ASD who were admitted to the HITS Dahealth Children's Rehabilitation Center in Haikou City, Hainan Province, China, from August 2022 to August 2023. The children with ASD were divided into an abnormal olfactory group and a normal olfactory group according to the SPSRC scale. 32 children with ASD with abnormal olfaction were used as the case group, and 1:1 age- and sex-matched children with normal olfaction with ASD were used as the control group, and the differences in 25(OH)D levels and clinical phenotypic data between the two groups were compared. Serum 25(OH)D levels were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Clinical characterization of the children in the two groups was assessed using the short version of the Sensory Processing Proficiency Scale (SSP), the Revised Stereotyped Repetitive Behavior Scale (RBS-R), the Social Reactivity Scale, Second Edition (SRS-2), and the Autism Spectrum Questionnaire Scale (AQ).
Results
Blood 25(OH)D levels, SSP scores, and SRS-2 scores were lower in the olfactory abnormality group than in the control group, and the difference was statistically significant (t = 4.460, P < 0.001). Logistic regression analysis showed that 25(OH)D < 25 ng/mL (β = 1.433, OR = 4.192) and SSP < 115 (β = 1.838, OR = 6.286) were independent risk factors for the disease (all P < 0.05).
Conclusion
Blood 25(OH)D levels were lower in children with ASD associated with olfactory abnormalities and correlated with olfaction and some clinical phenotypes, but the specific mechanisms need further investigation.
Occurrence, mobility, and potential risk of uranium in an abandoned stone coal mine of Jiangxi Province, China
Authors: Wei Xinxiang , Xu Naizheng , Li Jiang 
Published: February 2024

Abstract

Metal sulfide oxidation in abandoned exposed stone coal mines leads to the generation of Acid Mine Drainage (AMD), characterized with high uranium concentration, which is a major concern for local public health. This work employs an approach of geochemical analysis and modelling to determined the mode of occurrence of uranium. Additionally, potential environmental risks were evaluated.
The results revealed that the primary source of uranium pollutants in the surrounding environmental media was attributed to the weathering of mine waste. Concentrations of harmful elements (e.g., U, Fe, sulfate) and acidity in water rapidly decreased to background levels with increasing distance from the mine. The geochemical distribution characteristics of sediments and water exhibit notable similarities. The species of uranium underwent a transformation as uranium in mine waste rocks migrated to environmental media. In acidic pit water, uranium primarily existed as uranyl sulfate, gradually transitioning downstream to complexes dominated by hydrophosphate and carbonate. This transition was accompanied by the coprecipitation of significant amounts of uranium with phosphate and iron hydroxides. Results from the geoaccumulation index (Igeo) and risk assessment codes (RAC) indicated that uranium in unweathered coal waste rocks and newly formed pit sediments posed a high environmental risk, with a bioavailable fraction reaching up to 26.44% and 48.0%, respectively. This research holds significant importance in devising remediation and management strategies for abandoned coal mines to mitigate the impact of uranium release and mobility on the surrounding ecological environment.
Venture Capital and the Survival of Entrepreneurial Firms in Crisis Periods: The Case of Covid-19.
Authors: Kacer Marek , Wilson Nicholas , Zouari Sana , Cowling Marc 
Published: February 2024

Abstract

This paper investigates the survival of entrepreneurial firms during the pandemic period. Specifically, we focus on UK companies that received equity finance during their developmental stages before the onset of Covid-19. The equity finance investors in our study include venture capital and growth finance funds (both domestic and foreign), crowd funding platforms, business angels, and government venture capital funds. We build on the resource-based view (RBV) and signalling theories to develop our hypotheses. We analyse the bankruptcy processes of companies during the Covid-19 period, comparing it to the pre-Covid period. We examine various characteristics of these firms, such as their investor type, deal history (including timing, magnitude, and duration), as well as a range of financial and non-financial factors. Furthermore, we identify the equity-backed companies that utilized policy interventions in the form of guaranteed loans. We gather details about the loan contracts, lenders, and instances of loan default. This study explores the relationship between bankruptcy and loan default in relation to the firm's characteristics, investor type, investment dimensions and financial constraints. The results provide valuable insights into the link between equity financing and venture survival during crises, with important implications for policy interventions.
JEL classifications G12. G33. H81. L26
Simple Central Algorithms for Capturing Contact-Discontinuity in Multi-Component Mixture Equations with Stiffened Gas Equation of State.
Authors: Kolluru Ramesh , V Raghurama Rao S , N Sekhar G 
Published: February 2024

Abstract

This study introduces the creation of straightforward and reliable algorithms aimed at simulating compressible Euler equations featuring a stiffened gas equation of state (EOS). These algorithms are crafted to faithfully depict gaseous mixtures in thermal equilibrium, excluding chemical reactions. The methodology relies on a fully conservative approach within a finite volume framework, employing central schemes with controlled numerical diffusion. The RICCA and MOVERS+ algorithms implement two models, specifically Mass fraction (Y) and Mixture gamma $(\gamma)$ based models. These models adeptly capture the fundamental characteristics of flow fields. Rigorous testing of the numerical schemes ensures the minimization of pressure oscillations and the preservation of mass fraction positivity, especially in first-order numerical methods. A series of one-dimensional (1D) and two-dimensional (2D) test cases are presented to showcase the effectiveness and precision of the developed algorithms. These tests provide compelling evidence of the algorithms' resilience and accuracy in simulating the intended flow phenomena.
Augmentation-Enhanced Deep Learning for Face Detection and Emotion Recognition in Elderly Care Robots
Authors: Tran Hoang N. , Phan Phuc H. , Nguyen Khang H. , Hua Huy K. , Nguyen Anh Q. , Nguyen Huynh N.V. , Nguyen Nghi V. 
Published: February 2024

Abstract

Facial recognition and emotion detection are crucial for meaningful interactions between elderly individuals and healthcare robots. These technologies allow the robot to identify and understand facial expressions, adapting its responses accordingly. In our research, we propose an innovative approach that combines CNN-based face detection with LBC (Local Binary Convolution) for deep-learning emotion classification. We use a BlazeFace-based face detection model and a robust LBC-Xception emotion classification model. Additionally, we introduce a Multi-Augmentation data method, including seven basic data augmentation techniques and a combination of image super-resolution (ISR) and Conditional Generating Adversarial Network (cGAN) to enhance system robust-ness and accuracy. This combined approach not only improves accuracy through advanced feature extraction capabilities but also provides a lightweight network , suitable for hardware-constrained devices. To validate our method, we will compare face recognition and classification accuracy using the BlazeFace model against other popular classification models like MobileNetV2, VGG16, and Incep-tionV3. We’ll also compare datasets, including FER2013, FER2013Plus, and our augmented dataset (FER2013-MultiX). Finally, we develop an elderly care robot (ECR) and a robot control web application (RCWA) on the Robot Operating System 2 (ROS2) to evaluate performance under real conditions.
Securing the Diagnosis of Medical Imaging: An In-depth Analysis of AI-Resistant Attacks
Authors: Biswas Angona , Nasim Abdullah Al , Gupta Kishor Datta , George Roy , Shujaee Khalil , Rashid Abdur 
Published: February 2024

Abstract
Machine learning (ML) is a rapidly developing area of medicine that uses significant resources to apply computer science and statistics to medical issues. ML's proponents laud its capacity to handle vast, complicated, and erratic medical data. It's common knowledge that attackers might cause misclassification by deliberately creating inputs for machine learning classifiers. Research on adversarial examples has been extensively conducted in the field of computer vision applications. Healthcare systems are thought to be highly difficult because of the security and life-or-death considerations they include, and performance accuracy is very important. Recent arguments have suggested that adversarial attacks could be made against medical image analysis (MedIA) technologies because of the accompanying technology infrastructure and powerful financial incentives. Since the diagnosis will be the basis for important decisions, it is essential to assess how strong medical DNN tasks are against adversarial attacks. Simple adversarial attacks have been taken into account in several earlier studies. However, DNNs are susceptible to more risky and realistic attacks. The present paper covers recent proposed adversarial attack strategies against DNNs for medical imaging as well as countermeasures. In this study, we review current techniques for adversarial imaging attacks, detections. It also encompasses various facets of these techniques and offers suggestions for the robustness of neural networks to be improved in the future.
Cloud Elasticity of Microservices-based Applications: A Survey
Authors: Fourati Mohamed Hedi , Marzouk Soumaya , Jmaiel Mohamed 
Published: February 2024

Abstract
Elasticity is an essential treatment in Cloudenvironment employed in academic and industrial contexts. The main purpose of elasticity is to reduce thedeployment cost while optimizing computing resources.Multiple studies were conducted to tackle classic applications using monolithic architecture deployed withvirtual machines (VMs). However, with the spread ofmicroservice pattern, recent studies have been investigating this new trend using containers. This paperclassifies and discusses existing approaches dealing withcloud elasticity. It provides a novel taxonomy for elasticapproaches while focusing on microservices-based solutions. We additionally specify the strength and theshortcomings of each class of works. As a conclusion,we report the challenges for microservices-based applications elasticity and provide requirements for futureinvestigations.
A novel methodology to track nitrogen transfer in a grass-legume mixture using enriched 15N2
Authors: Queiroz Luana M. Dantas , Dubeux Jose Carlos Batista , Sollenberger Lynn E. , Vendramini Joao M. Bueno , Liao Hui-Ling , Jaramillo David Mirabedini , Santos Erick Rodrigo Silva , Abreu Daciele Sousa , Lira Mario Andrade , Casagrande Daniel Rume , Mackowiak Cheryl L. , Ruiz-Moreno Martin 
Published: February 2024

Abstract

Background and Aims – Legumes are a potentially important N source in pasture systems, but quantifying the transfer of biologically fixed N from the legume to the grass component is difficult. A greenhouse H-pot system was developed to directly estimate biological N2 fixation (BNF) and belowground N transfer using 15N2. The system was tested with annual ryegrass (Lolium multiflorum L.) and crimson clover (Trifolium incarnatum L.). Methods – Legume and grass root systems growing in either individual or H pots were exposed to 15N2. Control H pots were separated by mesh to prevent contact between roots and mycorrhizae from each side of the pot. To reduce volume demand and avoid cross-contamination in the greenhouse, the gas was supplied through underground tubes in the root zone. Results – Ryegrass and clover were enriched in 15N when the respective root system was supplied with 15N2. Ryegrass was also enriched when clover roots were supplied with the gas and there was free root and mycorrhizal contact between both sides of the H pot, but not when this contact was precluded. Plants grown singly did not enrich when the gas was not supplied to their root systems. Conclusions – The H-pot construction allows the evaluation of belowground transmission, an important mechanism of N transfer. The method of gradually supplying 15N2 directly to the root system may be a valuable labeling technique for monitoring the transfer of nitrogen. The lack of enrichment when plants were not directly supplied indicates negligible atmospheric enrichment. Ryegrass enrichment, when supplied with the gas, suggests BNF by other mechanisms.
Accurate Detection of Ellipses based on Co-clustering
Authors: Wu Zihan , Yan Hong 
Published: February 2024

Abstract

Ellipse detection plays a vital role in computer vision, primarily due to the absence of efficient techniques to incorporate information from arcs in a global view. In this paper, we present a novel co-clustering-based approach that captures the global compatibility of arc pairs. Specifically, we compute the probability distributions of arcs and measure their similarity using Jensen-Shannon divergence to construct a compatibility matrix. Co-clustering extracts low-rank substruc-tures, each representing an ellipse. Experiments on synthetic images show a 10% improvement in accuracy and 15% in recall compared to previous methods. We also demonstrate performance on real images containing occlusions and overlapping ellipses from the Prasad dataset, the Coins dataset, the Tableware dataset and the Iris V dataset. Compared to techniques relying solely on local information , our method achieves higher accuracy in detecting small and occluded ellipses owing to its global perspective. The proposed technique provides an efficient, robust solution to ellipse detection across diverse scenarios.
An Unmanned Tank Combat Game Driven by FPSO-MADDPG Algorithm
Authors: Wang Fei , Liu Yi , Zhou Yudong , Zhou Dianle , Yan Dan 
Published: February 2024

Abstract

With the development of artificial intelligence and unmanned technology, unmanned vehicles have also been applied to a variety of situations which may be hazardous to human beings, even in real battle fields. An intelligent unmanned vehicle can be aware of around situations and make appropriate responding decisions. In this paper, an FPSO-MADDPG framework is proposed for unmanned tanks, where multi-agent deep reinforcement learning algorithm is used in an unmanned tank game, and an improved particle swarm optimization (FPSO) algorithm is proposed to optimize key factors, like vehicle attitude and position. Simulation results show that our method not only can obtain higher winning rate, but also higher reward and faster convergence than other algorithms.
Behavioral Problems Among Young Adolescents in the Family and Neighborhood Context: a Case Control Study
Authors: Sitnik-Warchulska Katarzyna , Izydorczyk Bernadetta , Markevych Iana , Baumbach Clemens , Mysak Yarema , Buczyłowska Dorota , Szwed Marcin , Lipowska Małgorzata 
Published: February 2024

Abstract
Background: This study aimed to determine whether family and neighborhood social cohesion directly or indirectly impact the reduction of behavioral problems, including internalizing and externalizing behaviors in young adolescents. From a systemic approach, adolescent behavioral problems are influenced by family cohesion and mediated by neighborhood social cohesion.
Methods: Data from 700 parents of adolescents aged 10–13 years from southern Poland were analyzed. Within the total, 207 adolescents had diagnoses of Attention Deficit Hyperactivity Disorder (ADHD). The structural equation modeling (SEM) approach, adjusting for financial situation and ADHD was used. Gender, ADHD, single-parent household, presence of siblings, and social media use were explored as moderators via stratified SEM models. The data come from the Child Behavior Checklist (CBCL), the Family Adaptation and Cohesion Evaluation Scales (FACES-IV), and the Brief Form of the Perceived Neighborhood Social Cohesion Questionnaire (PNSC-BF).
Results: Family and neighborhood social cohesion were both related to behavioral problems. Neighborhood social cohesion was a significant mediator of the relationship between family cohesion and internalizing and externalizing behaviors. Presence of siblings was a significant moderator for the indirect effect on externalizing behaviors.
Conclusion: The findings of the study support the thesis, that family and neighborhood social cohesion serve as protective factors for adolescent behavioral problems.
Clinical Trial: The clinical trial identifier is NCT04574414.
Efficacy and safety of oral semaglutide in older patients with type 2 diabetes: a retrospective observational study (the OTARU-SEMA study)
Authors: Oe Yuki , Nomoto Hiroshi , Cho Kyu Yong , Yokozeki Kei , Ono Tsubasa , Miya Aika , Kameda Hiraku , Nakamura Akinobu , Arimura Yoshiaki , Atsumi Tatsuya 
Published: February 2024

Abstract

Background: Oral semaglutide in older subjects with type 2 diabetes was as effective as in younger subjects, according to phase 3 clinical trials. However, its efficacy can be limited in very aged population, due to the presence of impaired cognitive function and the complex instructions for its use. Here, we investigated its efficacy and safety by further age bracket in older subjects in real-world.
Methods: We retrospectively studied subjects >65 years of age with type 2 diabetes who started oral semaglutide treatment. The primary outcome was the change in glycosylated hemoglobin (HbA1c) over 6 months. Adverse events and cognitive function were evaluated using the Common Terminology Criteria for Adverse Events (CTCAE) and the Hasegawa Dementia Rating Scale-revised (HDS-R). The achievement rate of glycemic targets was evaluated based on the age, health status of subjects and their use of anti-diabetic agents which can cause hypoglycemia, with additional analysis between two subgroups; early (65-74) versus late (≥ 75) older. Furthermore, we evaluated the relationships between their improvements in HbA1c and the baseline characteristics of the subjects, including their cognitive function and insulin secretory capacity.
Results: We studied the efficacy of the drug in 24 subjects. Their HbA1c and body weight significantly decreased (−13.1 ± 7.5 mmol/mol and −3.0±2.4 kg, respectively; P<0.01). Although cognitive function was lower in the late older group (r=−0.57, P<0.01), changes in HbA1c showed no difference between the two subgroups (P=0.66) and it correlated with the insulin secretory capacity rather than cognitive function (r=−0.49, P<0.05). Glycemic targets were more likely to be achieved (P<0.01), but HbA1c excessively decreased in late older subjects who were also using insulin or an insulin secretagogue. The frequency of adverse events was similar to that in the clinical trial, whereas discontinuation of medication were more frequent among the late older subjects (Early; n=2, Late; n=4).
Conclusions: Oral semaglutide improves the glycemic control of older subjects, but it might be a risk for potential hypoglycemia and discontinuation in subjects of ≥75 years. Attention should be paid to insulin secretory capacity and concomitant medications rather than concern about adherence.
An experimental study on aging effects of fuel cut events including sound optimized torque reduction on modern three-way catalysts
Authors: Eickenhorst René , Koch Thomas 
Published: February 2024

Abstract
Continuously increasing country-specific emission standards for passenger vehicles demand additional development steps in complex exhaust gas aftertreatment systems for a more effective reduction of harmful gases. The efficiency of the aftertreatment system declines over its lifecycle due to specific load profiles and other boundary conditions, resulting in increasing emissions over vehicle mileage. As a result, the durability of the exhaust system becomes more important. Fuel cut is an intended, temporary interruption of the fuel supply of modern combustion engines of passenger cars to reduce fuel consumption and emissions. During this fuel reduction event, unconsumed oxygen of rich and cool fresh air is introduced to the combustion chamber and to the exhaust system. Besides a catalyst cool down, oxidation effects are provoked by enhanced oxygen reactions processes within the catalyst’s washcoat and surface layers. In this publication, specific aging cycles with a variation of fuel cut programs were examined on their effects on a modified modern eight-cylinder turbocharged engine, especially on their oxidation effects correlating to catalyst aging. Light-off curves and conversion heat maps were used to evaluate possible damaging impacts of fuel cut events on the aging behavior of the catalyst systems. Results indicate that higher frequency of fuel cut events results in a stronger catalyst aging, whereas thermal sintering might be reduced due overall lower temperature load. Temporary oxidation processes on catalyst’s surfaces occur only in a short timespan after changing the air fuel ratio to lean, resulting in a weaker thermal sintering during longer fuel cut events. Sound optimized torque reduction functions, used in sports cars for a better drivability and powertrain response, exhibit a stronger aging influence due to additional thermal shock effects on the catalysts front face, as demonstrated via optical infrared sensor technology during catalyst aging cycles on the modified engine bench setup. A theoretical calculation of aging processes as a combination of thermal sintering by Arrhenius equation as well as oxidation process is discussed to describe an aging classification induced via oxidation processes. Additional physisorption measurements of different catalyst probes support the results indicate the direction of future experimental approaches.