bluuebunny/crossref_metadata_2025_split huggingface dataset:
A rapid diagnosis and treatment of Ornithonyssus bacoti infection
Authors: Xu Huimin , Wang Ying , Fang Jiaqi , Wang Jiaxin , Li Weiguo , Zhou Yun 
Published: March 2023

Abstract
Mites serve as pathogens, allergens, or microbial containers, which can seriously damage the health of humans and animals. The substantial amount of mite species and their similar morphology make it complicated to identify and classify. Our mouse breeder incidentally noticed papular-type erythema with itching and peeling of the skin in several places, and an investigation revealed that this symptom was caused by an uncommon parasite that appeared on the skin and around the nest of the mice. By morphological observation, DNA extraction, PCR amplification, and DNA sequencing, we roughly identified the category of the parasite as a mite. We then designed a specific primer Cox1, amplified and sequenced the mitochondrial cox1 gene fragment of the mite, calculated the intra and interspecific differences, and reconstructed the phylogenetic tree for comparative analysis. We named this species Ornithonyssus bacoti - KF. According to the ivermectin gradient test, we found that 0.1 mg/ml concentration of ivermectin solution was the most effective for mite removal in the bath, with no recurrence after 6 months of treatment. This study provides a new specific primer sequence for the detection of Ornithonyssus bacoti, which provides a new method for the rapid identification of Ornithonyssus bacoti. This study provides accurate diagnosis and precise treatment for the feeding and breeding of rodents to prevent mite infection.
Performance evaluation of political teaching MOOC system based on task scheduling and AI system
Authors: Cui Wanru 
Published: March 2023

Abstract
In the network control system, due to the limitation of network bandwidth and control system conditions, the information transmission of sampling and control must be completed in a certain time, otherwise it will cause information transmission delay, thus reducing the control performance of the network system. This paper builds a MOOC political teaching platform based on task scheduling and artificial intelligence system, and the use of MOOC ideological and political education model can improve students' participation and practicability. Under the MOOC model, students should be able to learn by participating in online video courses, skillfully applying theoretical knowledge of ideological and political education, and then by participating in physical classroom discussions. The simulation results show that the system can realize real-time data transmission, and the information transmission of sampling and control must be completed in a certain time, otherwise it will cause information transmission delay, thus reducing the control performance of the network system. Due to the limitation of network bandwidth, if multiple control systems work together, there will be transmission delays and other situations, which will directly affect the control performance of the system and cause system instability.
Light-controlling nucleation, growth and patterning of metal carbonate crystals using resonant near-infrared laser heating
Authors: Bistervels Marloes , Kamp Marko , Schoenmaker Hinco , Noorduin Willem 
Published: March 2023

Abstract
Spatiotemporal control over crystal nucleation and growth is of fundamental interest for understanding how organisms assemble high-performance biominerals, and promises new manufacturing routes for functional materials. Many methods have been developed towards static or global control, however gaining simultaneously dynamic and local control over crystallization remains challenging. Here, near-infrared (NIR) laser light locally heats water to induce crystallization of retrograde (inverse) soluble compounds with spatiotemporal control. Using a custom-build optical setup, the NIR light intensity is modulated to start, steer, and stop crystallization of calcium carbonate and laser-write with micrometer precision. Tailoring the crystallization conditions enables overcoming the inherently stochastic crystallization behavior and position single crystals of vaterite, calcite, and aragonite. Straightforward extension of these principles towards other compounds is demonstrated by adjacent patterning barium-, strontium-, and calcium carbonate crystals. Since many important compounds exhibit retrograde solubility behavior, NIR-induced heating opens unprecedented opportunities for light-controlled crystallization with precise spatiotemporal control.
Work- and Health-related Events and Changes in Body Mass Index during the Covid-19 lockdown. Evidence from the Lifelines Cohort Study in the Netherlands.
Authors: Mangot-Sala Lluis , Smidt Nynke , Liefbroer Aart 
Published: March 2023

Abstract
Background
The aim of this study was to identify the main trends in terms of changes in body mass index (BMI) during the Covid-19 pandemic in the Netherlands. Moreover, we aimed to investigate whether work- and health-related disruptive events triggered by the pandemic, such as job insecurity or mental health issues, were associated with such changes in BMI.
Methods
Longitudinal data from the Lifelines Covid Questionnaire was used (21 waves between April 2020 and July 2021; n=64,630). Overall BMI trends were analysed using growth curve modelling. Different trajectories were identified using group-based trajectory models. Multinomial regression models were fitted to analyse the main determinants of experiencing changes in BMI during the pandemic.
Results
Experiencing disruptive work-related events (e.g. being laid-off or having a temporary contract) and health-related events (e.g. anxiety or depression) during the pandemic were associated with changes in BMI, particularly weight gain.
Conclusions
Work- and health-related events were strongly associated with changes in BMI during the Covid-19 pandemic. Although such changes may be partly explained by lifestyle factors, such as diet or physical activity, this study aligns with the existing evidence on the embodiment of stress, suggesting a strong association between disruptive events and changes in body weight.
Framework for Credit Card Fraud Detection Using Benefit-Based Learning and Periodic Features
Authors: Sooklal Shellyann , Hosein Patrick 
Published: March 2023

Abstract
Online credit card fraud is an ongoing problem and with the recent COVID-19 pandemic, there has been a surge of merchants moving their businesses online. It is therefore crucial to identify fraudulent activities before it causes loss to both the bank and its customers. Due to the dynamic nature of fraudsters as well as customer spending behavior, machine learning algorithms are appropriate for this task. However, credit card fraud data is typically imbalanced, favoring the positive class (legitimate transactions), causing traditional machine learning algorithms to err on the side of this majority class; since they consider equal costs and benefits for different decision outcomes when training. Nevertheless, it is more beneficial to correctly identify fraudulent transactions. Therefore, in this paper, we propose a technique for identifying credit card fraud that first accounts for customer spending patterns by aggregating transactions to creative new features based on periodic data. Then, we consider benefits and costs when training an XGBoost classifier in order to achieve maximum benefits. We also evaluate the performance of the classifier using benefits and costs. We demonstrate the effectiveness of our approach using data provided by a bank.
Email Spam detection in IoT based on Hybrid deep learning model and multi-objective optimization by NSGA II
Authors: Dehghani Samira , Ahmadinia Mohammad , Ghafoori Seyed Hamid 
Published: March 2023

Abstract
The Internet of Things (IoT) connects a range of things, including sensors, physical devices, controllers, and intelligent computer processors. Physical objects with the ability to organize and control independently are referred to as smart devices in the IoT architecture. These smart devices are becoming an integral aspect of human life, from smart homes to large industrial and organizational sectors. Despite the numerous benefits of email regarding information generation and reminders based on predefined regulations, spam emails sent by thingbots pose a potential concern in the Internet of Things. Recently, several studies have used machine learning systems and deep learning models to detect email spam in the internet of things. The presence of unbalanced data, which impacts classification accuracy, is one of the challenges associated with spam detection. In this study, bidirectional gated recurrent unit (BiGRU) and Convolution neural network (CNN) are combined with the Non-dominated Sorting Genetic Algorithm-II (NSGA II) multi-objective optimization method to effectively address imbalance problems. This solution utilizes the two classification criteria TPR and FPR, as NSGA II objective functions and is capable of resolving the imbalance problem in email spam data. The proposed technique is evaluated using the Enron dataset, and the results indicate that the proposed method is more accurate at detecting spam than other baseline methods.
SARS-COV-2: Analysis of mutational impacts on non-structural proteins
Authors: Senthilazhagan Kavya , Sakthimani Seshagiri , Kallanja Deepthi , Venkataraman Sangita 
Published: March 2023

Abstract
The global pandemic that peaked in 2019 was caused by the SARS-CoV-2 (severe acute respiratory syndrome coronavirus), which had China as its whenua. The whys and wherefores of this outbreak are attributed to the structural competency of the single-stranded RNA virus that continues to evolve posing major health concerns. SARS-CoV-2 with an increased level of genetic mutations alters the characteristics of the virus, such as transmissibility, and antigenicity alongside the development of drug and vaccine resistance. The deeper examination of prominent mutating sites and structures of the virus can give insights into the development of better and more efficient vaccine candidates. This research is steered to delve into the viral dynamics using full genome sequences and decode the genesis behind the structural and functional variances. The genomic data of SARS-CoV-2 variants were obtained from the Global Initiative on Sharing Avian Influenza Data (GISAID), and a set of significant mutations in each of the non-structural proteins (NSPs) 1 through 16 and structural proteins, including envelope, nucleocapsid, membrane, and spike, were identified. The mutations were characterized as stabilizing or destabilizing and their significance was analyzed with respect to self and in the context of interacting partners. Among all the proteins, NSP6 stands out as a dark horse with extremely high mutability. The results augment our understanding of how mutational events influence virus pathogenicity and evolution.
Barriers and Contributing Factors to the Manifestation of Creativity of a Person
Authors: Poghosyan Sona , Aghuzumtsyan Ruben , Khachatryan Ani , Ghazeyan Khachatur 
Published: March 2023

Abstract
The manifestation of a person's creativity is determined by the complex interaction of the conducive and obstructive factors of the environment. We propose a model for the study of creativity, which takes into account the conducive and obstructive factors. The purpose of the article is to study the ratio of conducive and obstructive factors to the manifestation of a person's creativity. The characteristics of the creativity of modern managers are determined by a unique ratio of conducive and obstructive factors, according to which the impossibility of making independent decisions is an obstructive factor for them; and the freedom to express their thoughts is an conducive factor, the fear of making mistakes and the fear of criticism are obstructive factors; and the spark of new thoughts and ideas, the inspiration and enthusiasm to create new ideas are considered to be conducive factors. Such a correlation of contributing and hindering factors of personal creativity is the basis for developing a new model of studying and developing personal creativity. Thus, the creativity study model is built from the level of creativity, standards, personal qualities of creativity, the relationship between them, the factors contributing to and hindering creativity, their unique relationship.
Assessment of a new economic xeno-free and serum-free human mesenchymal stem cells culture medium with optimal proliferation and differentiation capacities
Authors: Chen Shanshan , Meng Li , Wang Shanshan , Xu Yan , Chen Wenbin , Wei Jianfeng 
Published: March 2023

Abstract
Human mesenchymal stem cells (hMSCs) possess broad prospects in pre-clinical research. In vitro amplification requires appropriate medium to reach the number of seed cells with clinical significance. However, the uncertainty of the heterologous components of the traditional fetal bovine serum (FBS) culture medium has great safety risks. Then existing commercial hMSCs medium is very expensive, a safer and more economical hMSCs medium is urgently needed. Therefore, we developed a noval hMSCs medium without xenogenic components, it is mainly composed of knockout serum replacement (KSR), constituting additionally four components such as fibroblast growth factor and transferrin, named E5 SFM. Here, we mainly compared the E5 SFM with traditional FBS-containing medium and a commercial medium by surface markers testing, proliferation assay, adipogenic and osteogenic differentiation assessment. We demonstrated that hMSCs cultured in the E5 SFM showed similar morphological characteristics and immunophenotypes to those in other media. Notably, cell proliferative capability was similar to that in the commercial medium, but higher than that in the FBS-containing medium and other media, their capabilities of adipogenic and osteogenic differentiation was significantly higher than other media. Consequently, we concluded that the E5 SFM medium can not only effectively promote cell proliferation of hMSCs, but also has low price and clear and simple ingredients.
Upregulation of KLK8 contributes to CUMS-induced hippocampal neuronal apoptosis by cleaving NCAM1
Authors: Liu Yu-Jian , Xu Dan-Hong , Du Jian-Kui , Liu Shi-Yu , Zhang Hui , Yang Lu , Zhu Xiao-Yan 
Published: March 2023

Abstract
Neuronal apoptosis has been well-recognized as a critical mediator in the pathogenesis of depressive disorders. Tissue kallikrein-related peptidase 8 (KLK8), a trypsin-like serine protease, has been implicated in the pathogenesis of several psychiatric disorders. The present study aimed to explore the potential function of KLK8 in hippocampal neuronal cell apoptosis associated with depressive disorders in rodent models of chronic unpredictable mild stress (CUMS)-induced depression. It was found that depression-like behavior in CUMS-induced mice was associated with hippocampal KLK8 upregulation. Transgenic overexpression of KLK8 exacerbated, whereas KLK8 deficiency attenuated CUMS-induced depression-like behaviors and hippocampal neuronal apoptosis. In HT22 murine hippocampal neuronal cells and primary hippocampal neurons, adenovirus-mediated overexpression of KLK8 (Ad-KLK8) was sufficient to induce neuron apoptosis. Mechanistically, it was identified that the neural cell adhesion molecule 1 (NCAM1) may associate with KLK8 in hippocampal neurons as KLK8 proteolytically cleaved the NCAM1 extracellular domain. Immunofluorescent staining exhibited decreased NCAM1 in hippocampal sections obtained from mice or rats exposed to CUMS. Transgenic overexpression of KLK8 exacerbated, whereas KLK8 deficiency largely prevented CUMS-induced loss of NCAM1 in the hippocampus. Both adenovirus-mediated overexpression of NCAM1 and NCAM1 mimetic peptide rescued KLK8-overexpressed neuron cells from apoptosis. Collectively, this study identified a new pro-apoptotic mechanism in the hippocampus during the pathogenesis of CUMS-induced depression via the upregulation of KLK8, and raised the possibility of KLK8 as a potential therapeutic target for depression.
Housing Insecurity among Black Women Surviving Intimate Partner Violence during the COVID-19 Pandemic: An Intersectional Qualitative Approach
Authors: Willie Tiara , Linton Sabriya , Whittaker Shannon , Phillips Karlye , Knight Deja , Gray Mya , Gardner Gretta , Overstreet Nicole 
Published: March 2023

Abstract
Background. To investigate housing experiences during the COVID-19 pandemic among Black women experiencing intimate partner violence (IPV) who are also navigating racism, sexism, and classism.
Methods. From January to April 2021, we conducted in-depth interviews with 50 Black women experiencing IPV in the United States. Guided by intersectionality, a hybrid thematic and interpretive phenomenological analytic approach was used to identify sociostructural factors shaping housing insecurity.
Results. Our findings demonstrate the various ways in which the COVID-19 pandemic shaped Black women IPV survivors’ ability to obtain and sustain safe housing. Five themes were derived to capture factors contributing to housing experiences: challenges with separate and unequal neighborhoods; pandemic-related economic inequalities; economic abuse limitations; mental toll of eviction; and strategies to maintain housing.
Conclusions. Obtaining and maintaining safe housing during the COVID-19 pandemic was difficult for Black women IPV survivors who were also navigating racism, sexism, and socioeconomic position. Structural-level interventions are needed to reduce the impact of these intersecting systems of oppression and power in order to facilitate the resources necessary for Black women IPV survivors to identify safe housing.
Reproductive characteristics of the hermaphroditic four-finger threadfin, Eleutheronema tetradactylum (Shaw, 1804), in tropical coastal waters
Authors: Soe Kay Khine , Iqbal Teuku Haris , Lim Apiradee , Wang Wen‑Xiong , Tsim Karl W. K. , Takeuchi Yutaka , Hajisamae Sukree , Petchsupa Nirattisai 
Published: March 2023

Abstract
This study investigates reproductive traits of the hermaphroditic four-finger threadfin, Eleutheronema tetradactylum, along the coasts of Thailand during January 2021 and January 2022. Fish sample from Pattani Bay, Thailand was collected to assess sex ratio, gonadosomatic index (GSI), maturity stage and fecundity. Additional samples from other provinces were used to investigate length and weight at first sex change (Ls50 and Ws50) and length at first maturity (Lm50). It was found that the overall sex ratio for male and female was 1:0.69 with male predominated throughout the year. This fish spawned the whole year round with peak during moderate rainy season. Results from histological examination confirmed its protandrous hermaphrodite posing multiple spawning behavior. The average fecundity was 1.85 x 105 ± 1.05 x 105 eggs and positively related with standard length, body weight, gonad weight and egg diameter (P < 0.05). The Ls50 and Ws50 for fishes from Pattani Bay and Samut Prakan province were 27.58 cm, 419.39 g and 29.71 cm, 457.28 g, respectively. The Lm50 of male from Pattani Bay and Samut Prakan were 25.78 cm and 25.56 cm, respectively, considered larger than those from Satun and Nakhon Sri Thammarat provinces. The Lm50 of female from Pattani Bay was slightly smaller than that of Samut Prakan province. This study provides fundamental information on the reproductive characteristics of E. tetradactylum and can be implemented for both management of natural fish stock and future aquaculture development.
Effects of chest movements while sitting on Navon task performance and stress levels
Authors: Arima Yoshiko 
Published: March 2023

Abstract
Background: This study explored physical activity during remote work, most of which takes place while sitting in front of a computer. The purpose of Experiment 1 was to develop a classification for body motion by creating a neural net that can distinguish among several kinds of chest movement. Experiment 2 examined the effects of chest movements on stress and performance on the Navon test to validate the model developed in Experiment 1.
Method and Results: The procedures for this study were as follows.
Experiment 1: Creation of the body movement classification model and preliminary experiment for Experiment 2.
Data from five participants were used to construct a machine-learning categorization model. The other three participants participated in a pilot study for Experiment 2.
Experiment 2: Model validation and confirmation of stress measurement validity.
We recruited 34 new participants to test the validity of the model developed in Experiment 1. We asked 10 of the 34 participants to retake the stress measurement since the results of the stress assessment were unreliable.
Using LSTM models, we classified six categories of chest movement in Experiment 1: walking, standing up and sitting down, sitting still, rotating, swinging, and rocking. The LSTM models yielded an accuracy rate of 83.8%. Experiment 2 tested the LSTM model and found that Navon task performance correlated with swinging chest movement. Due to the limited reliability of the stress measurement results, we were unable to draw a conclusion regarding the effects of body movements on stress. In terms of cognitive performance, swinging of the chest reduced RT and increased accuracy on the Navon task (β=.015 [-.003,.054], R2=.31).
Conclusions: LSTM classification successfully distinguished subtle movements of the chest; however, only swinging was related to cognitive performance. Chest movements reduced the reaction time, improving cognitive performance. However, the stress measurements were not stable; thus, we were unable to draw a clear conclusion about the relationship between body movement and stress. The results indicated that swinging of the chest improved reaction times in the Navon task, while sitting still was not related to cognitive performance or stress. The present article discusses how to collect sensor data and analyze it using machine-learning methods as well as the future applicability of measuring physical activity during remote work.