bluuebunny/crossref_metadata_2025_split huggingface dataset:
Smart data augmentation: One equation is all you need
Authors: Zhang Yuhao , Tang Lu , Huang Yuxiao , Ma Yan 
Published: March 2024

AbstractClass imbalance is a common and critical challenge in machine learning classification problems, resulting in low prediction accuracy. While numerous methods, especially data augmentation methods, have been proposed to address this issue, a method that works well on one dataset may perform poorly on another. To the best of our knowledge, there is still no one single best approach for handling class imbalance that can be uniformly applied. In this paper, we propose an approach named smart data augmentation (SDA), which aims to augment imbalanced data in an optimal way to maximize downstream classification accuracy. The key novelty of SDA is an equation that can bring about an augmentation method that provides a unified representation of existing sampling methods for handling multi‐level class imbalance and allows easy fine‐tuning. This framework allows SDA to be seen as a generalization of traditional methods, which in turn can be viewed as specific cases of SDA. Empirical results on a wide range of datasets demonstrate that SDA could significantly improve the performance of the most popular classifiers such as random forest, multi‐layer perceptron, and histogram‐based gradient boosting.
The impact of 24/7 news coverage on the mental health of Israelis in the ‘Iron Swords’ War: A cross‐sectional analysis among television audience
Authors: Kaim Arielle , Bodas Moran 
Published: March 2024

AbstractThis study aims to assess the impact of continuous 24/7 news broadcasting on the mental well‐being of Jewish Israelis during the ‘Iron Swords’ War and compare it to findings from the 2014 Conflict. An internet‐based cross‐sectional panel survey was conducted on 11–12 October 2023, during the ‘Iron Swords’ War. The study focused on Israel's adult Jewish population, enabling comparisons with a previous 2014 study. Participants reported news consumption changes, attitudes towards newscasts (burdensome, relaxing, stressful, addictive, Fear Of Missing Out [FOMO], avoidance), opinions on 24/7 news, and anxiety symptoms. Among 802 adult Jewish participants in Israel, 83.8% increased news consumption. While more than 70% of respondents found the newscast stressing at least a medium level, more than 40% said they do not try to avoid them at all. Nearly 24% found it much addictive. Women and younger individuals reported more FOMO, stress, and addiction. More than 70% reported experiencing at least one anxiety symptom, and 21% of all four. Linear regression explained 42.9% of the variance of reported anxiety, with gender, age, news stress, addiction, and FOMO as predictors. The current study results show an increase in all measurements compared to a separate study conducted using the same tools in 2014. Jewish Israelis struggled with news consumption during the recent war, harming mental health. Heightened anxiety was observed, compared to 2014, and affected all demographics.
Fire resistance of concrete‐filled steel tube beam‐column under elevated temperatures and cyclic loading
Authors: Bayrak Barış , Maali Mahyar , Kılıç Mahmut , Maali Merve , Aydın Abdulkadir Cüneyt 
Published: March 2024

AbstractThis article aims to provide an overview of the fire resistance of concrete‐filled steel tube beam columns and the importance of fire resistance in building design and construction. Ten experimental models were developed to predict the behavior of different types of concrete‐filled steel tubes and beams‐columns under Fire resistance conditions (ISO‐834) under cyclic loading in two groups. The results show the type of concrete effect on moment‐rotation characteristics. Also, increasing the length of the stiffener on the column increases the load and moment capacity, but also affects the failure mode. Moreover, the ideal situation is to use PP fiber concrete in concrete‐filled steel tube structural elements where displacement and rotation capacity are prominent. Withal, the recycling of fire‐exposed steel beam‐to‐column tube element is available by filling the inner space with C50 and/or polypropylene fiber reinforced concrete, also as a fireproof member.
Domain Adaptation Curriculum Learning for Scene Text Detection in Inclement Weather Conditions
Authors: Liu Yangxin , Zhou Gang , Tian Jiakun , Deng En , Lin Meng , Jia Zhenhong 
Published: March 2024

AbstractScene text detection has been widely studied on haze‐free images with reliable ground truth annotation. However, detecting scene text in inclement weather conditions remains a major challenge due to the severe domain distribution mismatch problem. This paper introduces a domain adaptation curriculum learning method to address this problem. The scene text detector is self‐trained in an easy‐to‐hard manner using the pseudo‐labels predicted from foggy images. Thus, our method reduces the pseudo‐labeling noise level. Then, a feature alignment module is introduced to help the network learn domain‐invariant features by training a domain classifier. Experimental results show that our method improved significantly on both synthetic foggy data sets and natural foggy data sets, outperforming many state‐of‐the‐art scene text detectors. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Circ_0027791 contributes to the growth and immune evasion of hepatocellular carcinoma via the miR‐496/programmed cell death ligand 1 axis in an m6A‐dependent manner
Authors: Yu Furong , Fang Peifei , Fang Yonghong , Chen Daojun 
Published: March 2024

AbstractEmerging evidence indicates the critical roles of circular RNAs in the development of multiple cancers, containing hepatocellular carcinoma (HCC). Herein, our present research reported the biological function and mechanism of circ_0027791 in HCC progression. Circ_0027791, microRNA‐496 (miR‐496), programmed cell death ligand 1 (PDL1), and methyltransferase‐like 3 (METTL3) levels were detected by real‐time quantitative polymerase chain reaction (RT‐qPCR). Cell viability, proliferation, invasion, and sphere formation ability were detected using 3‐(4,5‐dimethyl‐2‐thiazolyl)‐2,5‐diphenyl‐2‐H‐tetrazolium bromide, 5‐ethynyl‐2′‐deoxyuridine, transwell, and sphere formation assays. Macrophage polarization was detected using flow cytometry assay. To understand the role of circ_0027791 during the immune escape, HCC cells were cocultured with peripheral blood mononuclear cells or cytokine‐induced killer (CIK) cells in vitro. A xenograft mouse model was applied to assess the function of circ_0027791 in vivo. After prediction using circinteractome and miRDB, the binding between miR‐496 and circ_0027791 or PDL1 was validated based on a dual‐luciferase reporter assay. Interaction between METTL3 and circ_0027791 was determined using methylated RNA immunoprecipitation (MeRIP)‐qPCR, RIP‐qPCR, and RNA pull‐down assays. Circ_0027791, PDL1, and METTL3 expression were upregulated, and miR‐496 was decreased in HCC patients and cells. Moreover, circ_0027791 knockdown might repress proliferation, invasion, sphere formation, M2 macrophage polarization, and antitumor immune response. Circ_0027791 knockdown repressed HCC tumor growth in vivo. In mechanism, circ_0027791 functioned as a sponge for miR‐496 to increase PDL1 expression. In addition, METTL3 mediated the m6A methylation of circ_0027791 and stabilized its expression. METTL3‐induced circ_0027791 facilitated HCC cell progression partly regulating the miR‐496/PDL1 axis, which provided a new prognostic and therapeutic marker for HCC.
Exploring gene biomarkers and targeted drugs for ferroptosis and cuproptosis in osteosarcoma: A bioinformatic approach
Authors: Ji Yingnan , Liu Lv , Liu Yu , Ma Yudong , Ji Zhenhua , Wu Xiaodan , Zhu Qi 
Published: March 2024

AbstractOsteosarcoma predominantly affects adolescents and young adults and is characterized as a malignant bone tumor. In recent decades, substantial advancements have been achieved in both diagnosing and treating osteosarcoma. Resulting in enhanced survival rates. Despite these advancements, the intricate relationship between ferroptosis and cuproptosis genes in osteosarcoma remains inadequately understood. Leveraging TARGET and GEO datasets, we conducted Cox regression analysis to select prognostic genes from a cohort of 71 candidates. Subsequently, a novel prognostic model was engineered using the LASSO algorithm. Kaplan–Meier analysis demonstrated that patients stratified as low risk had a substantially better prognosis compared with their high‐risk counterparts. The model's validity was corroborated by the area under the receiver operating characteristic (ROC) curve. Additionally, we ascertained independent prognostic indicators, including clinical presentation, metastatic status, and risk scores, and crafted a clinical scoring system via nomograms. The tumor immune microenvironment was appraised through ESTIMATE, CIBERSORT, and single‐sample gene set enrichment analysis. Gene expression within the model was authenticated through PCR validation. The prognostic model, refined by Cox regression and the LASSO algorithm, comprised two risk genes. Kaplan–Meier curves confirmed a significantly improved prognosis for the low‐risk group in contrast to those identified as high‐risk. For the training set, the ROC area under the curve (AUC) values stood at 0.636, 0.695, and 0.729 for the 1‐, 3‐, and 5‐year checkpoints, respectively. Although validation set AUCs were 0.738, 0.668, and 0.596, respectively. Immune microenvironmental analysis indicated potential immune deficiencies in high‐risk patients. Additionally, sensitivity to three small molecule drugs was investigated in the high‐risk cohort, informing potential immunotherapeutic strategies for osteosarcoma. PCR analysis showed increased mRNA levels of the genes FDX1 and SQLE in osteosarcoma tissues. This study elucidates the interaction of ferroptosis and cuproptosis genes in osteosarcoma and paves the way for more targeted immunotherapy.
N, P co‐doped carbon quantum dot and ammonium polyphosphate as the synergistic flame retardant for epoxy resin
Authors: Wang Song , Zhou Yue , Wu Weidong , Hong Jiayi , Li Sanxi , Zhang Ailing 
Published: March 2024

AbstractAn N, P co‐doped carbon quantum dot (NP‐CQD) was prepared using citric acid as the carbon source and hexachlorotripolyphosphonitrile as the nitrogen and phosphorus source. The structure and morphology of NP‐CQD were characterized. Subsequently, NP‐CQD was blended with ammonium polyphosphate (APP) to come into being a synergistic phosphorus‐nitrogen flame retardant system (SPFRS). The SPFRS was applied in epoxy resin (EP) to enhance the flame retardancy of EP. Thermal stability, flame retardancy, combustion behavior, and char residue morphology of the EP samples were determined by multiple testing methods such as thermogravimetric analysis, vertical burning (UL‐94) and limiting oxygen index (LOI) tests, microscale combustion calorimetry test, and scanning electron microscopy. When the weight ratio of NP‐CQD to APP was kept at 1:9 and 8% SPFRS was added to EP, the obtained flame‐retardant EP (EP/CQD‐APP2:18) passed the UL‐94 V‐0 level and the LOI value of EP/CQD‐APP2:18 reached 33.2%. The MCC test showed that the heat release capacity (HRC) of EP/CQD‐APP2:18 was reduced by 48.7% compared with pure EP. Morphology observation on the char residue of EP/CQD‐APP2:18 after the UL‐94 test indicated that the addition of SPFRS promoted the formation of the dense char residue layer to improve the flame retardancy of EP.Highlight
An N, P co‐doped carbon quantum dot (NP‐CQD) was prepared and applied as a flame retardant.
NP‐CQD and ammonium polyphosphate (APP) showed synergistic flame retardancy in epoxy resin.
The proper weight ratio of NP‐CQD to APP was 1:9.
Enhancing Student Services: Machine Learning Chatbot Intent Recognition for High School Inquiries
Authors: Assayed Suha Khalil , Alkhatib Manar , Shaalan Khaled 
Published: March 2024

AbstractPurpose- This paper aims to develop a novel chatbot to improve student services in high school by transferring students’ enquiries to a particular agent, based on the enquiry type. In accordance to that, comparison between machine learning and neural network is conducted in order to identify the most accurate model to classify students’ requests.Methodology- In this study we selected the data from high school students, since high school is one of the most essential stages in students’ lives, as in this stage, students have the option to select their academic streams and advanced courses that can shape their careers according to their passions and interests. A new corpus is created with (1004) enquiries. The data is annotated manually based on the type of request. The labelhigh-school-coursesis assigned to the requests that are related to elective courses and standardized tests during high school. On the other hand, the labelmajors & universitiesis assigned to the questions that are related to applying to universities along with selecting the majors. Two novel classifier chatbots are developed and evaluated, where the first chatbot is developed by using a Naive Bayes Machine Learning Algorithm, while the other is developed by using Recurrent Neural Networks (RNN)-LSTM.Findings- Some features and techniques are used in both models in order to improve the performance. However, both models have conveyed a high accuracy score which exceeds (91%). The models have been validated as a pilot testing by using high school students as well as experts in education and six questions and enquiries are presented to the chatbots for the evaluation.Implications and future work- This study can add value to the team of researchers and developers to integrate such classifiers into different applications. As a result, this improves the users’ services, in particular, those implemented in educational institutions. In the future, it is certain that intent recognition will be developed with the addition of a voice recognition feature which can successfully integrated into smartphones.
The Impact of Fostering Parasocial Relationship Between Influencing Entrepreneurs and Social Media Followers on the Brand Image and the Purchase Intentions of Start-Up Companies
Authors: Awawdeh Esraa , Alhassan Rouaa , Alalya Amer 
Published: March 2024

AbstractPurpose:this research tends to study the parasocial relationship between influencers on social media and their followers, and how it impacts the purchase intentions of the startup companies and their brand images.Findings: The parasocial relationship has a moderate impact on the purchase intentions, while it has a strong impact on the brand image, while the brand image has a strong positive impact on the purchase intentions.Conclusion:parasocial relationship can be used in an effective way to build the brand image of the company and to increase the purchase intentions.
A cosmic window on the dark axion portal
Authors: Hong Heejoung , Min Ui , Son Minho , You Tevong 
Published: March 2024

Abstract
Axions and dark photons are common in many extensions of the Standard Model. The dark axion portal — an axion coupling to the dark photon and photon — can significantly modify their phenomenology. We study the cosmological constraints on the dark axion portal from Cosmic Microwave Background (CMB) bounds on the energy density of dark radiation, ∆Neff. By computing the axion-photon-dark photon collision terms and solving the Boltzmann equations including their effects, we find that light axions are generally more constrained by ∆Neff than from supernova cooling or collider experiments. However, with dark photons at the MeV scale, a window of parameter space is opened up above the supernova limits and below the experimental exclusion, allowing for axion decay constants as low as fa ~ 104 GeV. This region also modifies indirectly the neutrino energy density, thus relaxing the cosmological upper bound on the sum of neutrino masses. Future CMB measurements could detect a signal or close this open window on the dark axion portal.
Bootstrapping high-energy observables
Authors: Bhat Faizan , Chowdhury Debapriyo , Sinha Aninda , Tiwari Shaswat , Zahed Ahmadullah 
Published: March 2024

Abstract
In this paper, we set up the numerical S-matrix bootstrap by using the crossing symmetric dispersion relation (CSDR) to write down Roy equations for the partial waves. As a motivation behind examining the local version of the CSDR, we derive a new crossing symmetric, 3-channels-plus-contact-terms representation of the Virasoro-Shapiro amplitude in string theory that converges everywhere except at the poles. We then focus on gapped theories and give novel analytic and semi-analytic derivations of several bounds on low-energy data. We examine the high-energy behaviour of the experimentally measurable rho-parameter, introduced by Khuri and Kinoshita and defined as the ratio of the real to the imaginary part of the amplitude in the forward limit. Contrary to expectations, we find numerical evidence that there could be multiple changes in the sign of this ratio before it asymptotes at high energies. We compare our approach with other existing numerical methods and find agreement, with improvement in convergence.
The work of art in the age of artificial intelligibility
Authors: McLoughlin John 
Published: March 2024

AbstractThe emergence of complex deep-learning models capable of producing novel images on a practically innumerable number of subjects and in an equally wide variety of artistic styles is beginning to highlight serious inadequacies in the ethical, aesthetic, epistemological and legal frameworks we have so far used to categorise art. To begin tackling these issues and identifying a role for AI in the production and protection of human artwork, it is necessary to take a multidisciplinary approach which considers current legal precedents, the practice of software engineering, historical attitudes towards technological innovation and a sustained technical analysis of the models themselves. This paper queries the location and nature of substantive artistic work in the developmental stages of an AI-generated image, offering critiques of existing assumptions and posing questions for future research. The emergence of convincing AI creative output, artistic or literary, has significant long-term implications for the humanities, including the need for re-appraisal of foundational ideas about authorship and creativity in general. The effects of artificial intelligence, whether generalised or task-specific, cannot be ignored or displaced now that easy-access, scalable image and text production is a reality.
Flank fractures on spiral bevel gears—transfer of analytical methods for the estimation of residual stresses from cylindrical gears to bevel gears
Authors: Truong Thi Tra My , Ulrich Carsten , Schumann Stefan , Schlecht Berthold 
Published: March 2024

AbstractThe classic flank and root load capacity calculation on the component surface forms the basis for the design of power gears today. However, flank fractures also occur in practice, particularly with large-module gears and/or low case-hardening depths. It is a fatigue damage with crack initiation in the tooth interior, its prevention requires the calculation of the stresses below the surface. In addition to understanding the load stresses, the inhomogeneous load bearing capacity and the residual stress profile in case-hardened gears are also of great importance. There are various calculation approaches for this in the area of cylindrical gears, but these have not yet been transferred to the complex geometry of spiral bevel gears. The focus of this publication is on estimating the residual stresses in the tooth volume by generating a three-dimensional residual stress tensor field in the bevel gear tooth based on the two-dimensional calculation approaches used to date on cylindrical gears. In combination with the stress tensor-time curves from a tooth contact simulation with the LTCA tool BECAL, this can be fed into different failure hypotheses, which is illustrated using an example.
Gaps in treatment of epileptic seizures in a Zambian rural area
Authors: Mambo Richard , Phiri Andrew M. , Trevisan Chiara , Zulu Gideon , Mubanga Chishimba M. , Mwelwa Chembensofu , Phiri Isaac K. , Schmidt Veronika , Magnussen Pascal , Dorny Pierre , Gabriël Sarah , Winkler Andrea S. , Mwape Kabemba E. 
Published: March 2024

Abstract
Background
Epilepsy is a multifactorial neurological disorder, including parasitic infections of the brain such as neurocysticercosis (NCC). People with epileptic seizures (PWES) in low and middle-income countries often do not receive appropriate treatment, which besides epileptic seizures, may also lead to reduced quality of life and possibly death. The objective of this study was to describe gaps in treatment of epileptic seizures in a Zambian rural area.

Methods
A cross-sectional study was conducted in Sinda district of Zambia between August and October 2018. PWES identified from clinic records and with the help of community healthcare workers were recruited. Two questionnaires, one to PWES and the other to local healthcare workers, were administered to describe the treatment gap.

Results
A total of 146 PWES and 43 healthcare workers were interviewed. Of the 146 PWES, 131 had taken anti-seizure medication (ASM) at some point since their seizure onset, of which 49.6% were on current treatment. Only 18.3% were on continuous ASM, an overall treatment gap of 83.6%. Over 55% of healthcare workers did not know the relationship between epilepsy and NCC. The risk factors associated with lack of appropriate treatment were stock-outs of ASMs, lack of diagnostic equipment, poor patient follow-up, and PWES opting for traditional medicine.

Conclusion
The treatment gap is substantial in Sinda district. The causes are multifactorial, involving shortcomings at the level of healthcare facilities, communities, and individuals. Directed training of healthcare workers and significant improvements in the supply and dispensing of ASMs will be key in substantially reducing the gap.
Extracellular matrix protein 1 (ECM1) is a potential biomarker in B cell acute lymphoblastic leukemia
Authors: Wu Li-Xin , Zhao Ming-Yue , Yan Nan , Zhou Ya-Lan , Cao Lei-Ming , Qin Ya-Zhen , Jiang Qian , Xu Lan-Ping , Zhang Xiao-Hui , Huang Xiao-Jun , Jiang Hao , Ruan Guo-Rui 
Published: March 2024

AbstractB cell acute lymphoblastic leukemia (ALL) is characterized by the highly heterogeneity of pathogenic genetic background, and there are still approximately 30–40% of patients without clear molecular markers. To identify the dysregulated genes in B cell ALL, we screened 30 newly diagnosed B cell ALL patients and 10 donors by gene expression profiling chip. We found that ECM1 transcription level was abnormally elevated in newly diagnosed B cell ALL and further verified in another 267 cases compared with donors (median, 124.57% vs. 7.14%, P < 0.001). ROC analysis showed that the area under the curve of ECM1 transcription level at diagnosis was 0.89 (P < 0.001). Patients with BCR::ABL1 and IKZF1 deletion show highest transcription level (210.78%) compared with KMT2A rearrangement (39.48%) and TCF3::PBX1 rearrangement ones (30.02%) (all P < 0.05). Also, the transcription level of ECM1 was highly correlated with the clinical course, as 20 consecutive follow-up cases indicated. The 5-year OS of patients (non-KMT2A and non-TCF3::PBX1 rearrangement) with high ECM1 transcription level was significantly worse than the lower ones (18.7% vs. 72.9%, P < 0.001) and high ECM1 transcription level was an independent risk factor for OS (HR = 5.77 [1.75–19.06], P = 0.004). After considering transplantation, high ECM1 transcription level was not an independent risk factor, although OS was still poor (low vs. high, 71.1% vs. 56.8%, P = 0.038). Our findings suggested that ECM1 may be a potential molecular marker for diagnosis, minimal residual disease (MRD) monitoring, and prognosis prediction of B cell ALL.Trial registration Trial Registration Registered in the Beijing Municipal Health Bureau Registration N 2007–1007 and in the Chinese Clinical Trial Registry [ChiCTR-OCH-10000940 and ChiCTR-OPC-14005546]; http://www.chictr.org.cn.