bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifying risk factors for vomiting during diarrhea: A secondary analysis of a randomized trial of zinc supplementation
Authors: Edwards Jeffrey G. , Dhingra Pratibha , Liu Enju , Dhingra Usha , Dutta Arup , Sudfeld Christopher R. , Deb Saikat , Somji Sarah , Aboud Said , Kisenge Rodrick , Sazawal Sunil , Ashorn Per , Simon Jonathan , Manji Karim P. , Duggan Christopher P.
Published: January 2025

Objectives

Supplemental zinc during acute diarrhea reduces illness duration but also increases vomiting. In a recent trial, we found that children receiving lower daily doses of zinc (5 mg or 10 mg vs. 20 mg) had lower rates of vomiting with comparable stool output and duration of diarrhea. We performed a secondary analysis to identify sociodemographic and clinical factors associated with vomiting in children with acute diarrhea.

Methods

We performed a secondary data analysis of 4500 children aged 6–59 months with an acute episode of diarrhea (<72 h before enrollment) in a randomized, double‐blind controlled trial in India and Tanzania. To identify clinically important risk factors for overall, regimen‐related, and regimen‐unrelated vomiting, we created log‐binomial models with relative risks (RRs) and 95% confidence intervals (CIs).

Results

The trial enrolled 4500 children, of whom 1203 (26.7%) had any vomiting. After adjusting for multiple demographic and clinical characteristics, the presence of dehydration (RR: 1.45, 95% CI: 1.10–1.92), being underweight (RR: 1.22, 95% CI: 1.05–1.41), receipt of the rotavirus vaccine (RR: 1.89, 95% CI: 1.69–2.12), and household wealth above the median (RR: 1.17, 95% CI: 1.07–1.29) were factors associated with an increased risk of vomiting. Rotavirus vaccine receipt was nearly 100% concordant with the study site of Tanzania. Older age and lower zinc dosing were associated with a lower risk of vomiting.

Conclusions

Young, underweight, or dehydrated children are more likely to have concurrent vomiting with zinc supplementation. Identification of these factors may allow providers to better monitor such children, thus reducing the chances of recurrent dehydration or inadequate dietary intake.
Multiple Environmental Variables as Covariates to Improve the Accuracy of Spatial Prediction Models for SOM on Karst Aera
Authors: Jiang Yongcheng , Li Fupeng , Gong Yufeng , Yang Xiuyuan , Zhang Zhenming
Published: January 2025

Aims accurately predicting the spatial distribution of soil organic matter (SOM) is essential for environmental management and carbon storage estimation. However, the diversity of sources of variables poses a challenge in studying the spatial distribution of SOM. Methods in order to address this issue, we propose leveraging multiple environmental variables and employing machine learning models, specifically Lightweight gradient boosting machine learning (LightGBM) and random forest (RF), for predicting SOM spatial distribution. 128 soil samples were collected from the Caohai National Nature Reserve, and their SOM content was measured. Results the study found that the average SOM content was 36.75 g/kg. Compared to traditional linear regression models such as ordinary kriging (OK), ordinary least squares (OLS), and geographically weighted regression (GWR), the machine learning models based on nonlinear regression, LightGBM and RF, demonstrated higher cross‐validated coefficients of determination (R2) of 0.62 and 0.60, respectively, outperforming the other models. Additionally, RF exhibited lower mean absolute error (MAE) and root mean square error (RMSE), indicating higher stability and generalization capability. The spatial distribution of SOM among the models showed consistency, with higher SOM content observed in southern and near‐Caohai Lake regions and lower SOM content in northern and farther regions from Caohai Lake. Results from the Shapley additive explanations (SHAP) model highlighted agricultural land (AL), pH, and Elevation (ELV) as primary covariates influencing SOM spatial distribution. Conclusions this study provides valuable insights and support for environmental management and carbon storage estimation in the karst plateau region.
LungDiag: Empowering artificial intelligence for respiratory diseases diagnosis based on electronic health records, a multicenter study
Authors: Liang Hengrui , Yang Tao , Liu Zihao , Jian Wenhua , Chen Yilong , Li Bingliang , Yan Zeping , Xu Weiqiang , Chen Luming , Qi Yifan , Wang Zhiwei , Liao Yajing , Lin Peixuan , Li Jiameng , Wang Wei , Li Li , Wang Meijia , Zhang YunHui , Deng Lizong , Jiang Taijiao , He Jianxing
Published: January 2025

Respiratory diseases pose a significant global health burden, with challenges in early and accurate diagnosis due to overlapping clinical symptoms, which often leads to misdiagnosis or delayed treatment. To address this issue, we developed LungDiag, an artificial intelligence (AI)‐based diagnostic system that utilizes natural language processing (NLP) to extract key clinical features from electronic health records (EHRs) for the accurate classification of respiratory diseases. This study employed a large cohort of 31,267 EHRs from multiple centers for model training and internal testing. Additionally, prospective real‐world validation was conducted using 1142 EHRs from three external centers. LungDiag demonstrated superior diagnostic performance, achieving an F1 score of 0.711 for top 1 diagnosis and 0.927 for top 3 diagnoses. In real‐world testing, LungDiag outperformed both human experts and ChatGPT 4.0, achieving an F1 score of 0.651 for top 1 diagnosis. The study emphasizes the potential of LungDiag as an effective tool to support physicians in diagnosing respiratory diseases more accurately and efficiently. Despite the promising results, further large‐scale multicenter validation with larger sample sizes is still needed to confirm its clinical utility and generalizability.
Comparison of diet and exercise on cardiometabolic factors in young adults with overweight/obesity: multiomics analysis and gut microbiota prediction, a randomized controlled trial
Authors: Lin Zongyu , Li Tianze , Huang Fenglian , Wu Miao , Zhu Lewei , Zhou Yueqin , Ming Ying‐An , Lu Zhijun , Peng Wei , Gao Fei , Zhu Yanna
Published: January 2025

The optimal strategy for improving cardiometabolic factors (CMFs) in young obese individuals through diet and exercise remains unclear, as do the potential mechanisms. We conducted an 8‐week randomized controlled trial to compare the effects of different interventions in youth with overweight/obesity. Gut microbes and serum metabolites were examined to identify regulating mechanisms. A total of 129 undergraduates were randomly assigned to fiber‐rich (FR) diet, rope‐skipping (RS), combined FR–RS and control groups. The results showed that single interventions were as effective as combined interventions in improving weight, waist circumference, body fat, and lipid profile compared with control group. Notably, the FR group further reduced low‐density lipoprotein (LDL‐C) and uric acid (UA) (all p < 0.05). Mediation analysis revealed four gut microbiota–metabolite–host axes in improving CMFs. Additionally, we used machine learning algorithms to further predict individual responses based on baseline gut microbiota composition, with specific microbial genera guiding targeted intervention selection. In conclusion, FR diet and/or RS were effective in improving CMFs, with the FR diet particular effectiveness in reducing LDL‐C and UA levels. These benefits may drive by gut microbiome–metabolite–host interactions. Moreover, the predictability of gut microbiota composition supports making targeted decisions in selecting interventions. Trial Registration: NCT04834687.
Tissue‐resident memory T cells in diseases and therapeutic strategies
Authors: Xie Daoyuan , Lu Guanting , Mai Gang , Guo Qiuyan , Xu Guofeng
Published: January 2025

Tissue‐resident memory T (TRM) cells are crucial components of the immune system that provide rapid, localized responses to recurrent pathogens at mucosal and epithelial barriers. Unlike circulating memory T cells, TRM cells are located within peripheral tissues, and they play vital roles in antiviral, antibacterial, and antitumor immunity. Their unique retention and activation mechanisms, including interactions with local epithelial cells and the expression of adhesion molecules, enable their persistence and immediate functionality in diverse tissues. Recent advances have revealed their important roles in chronic inflammation, autoimmunity, and cancer, illuminating both their protective and their pathogenic potential. This review synthesizes current knowledge on TRM cells’ molecular signatures, maintenance pathways, and functional dynamics across different tissues. We also explore the interactions of TRM cells with other immune cells, such as B cells, macrophages, and dendritic cells, highlighting the complex network that underpins the efficacy of TRM cells in immune surveillance and response. Understanding the nuanced regulation of TRM cells is essential for developing targeted therapeutic strategies, including vaccines and immunotherapies, to enhance their protective roles while mitigating adverse effects. Insights into TRM cells’ biology hold promise for innovative treatments for infectious diseases, cancer, and autoimmune conditions.
Investigation of the Relationship Between Intolerance of Uncertainty, Metacognitions, Maladaptive Coping, and Fear of Cancer Recurrence via Moderated Mediation Model
Authors: Babadostu Mübeccel Kübra , Eyrenci Aslı
Published: January 2025

Objective

In recent years, many studies have investigated the triggers, perpetuating factors, and outcomes of Fear of Cancer Recurrence (FCR), highlighting its complexity with multiple dimensions that encompass both antecedents and consequences. In this sense, the cognitive approach to FCR has explored variables such as metacognition, maladaptive coping strategies, and intolerance of uncertainty (IU). On the other hand, the findings of a restricted number of studies investigating the relationship between FCR and stated variables appear to be inconsistent. The objective of this study was thus to examine the relationship that existed among these variables in breast cancer survivors by moderated mediation model.

Methods

In this cross‐sectional study, 130 breast cancer survivors completed the Fear of Cancer Recurrence Inventory (FCRI), the Intolerance of Uncertainty Scale Short Form (IUS‐12), Metacognitions Questionnaire‐30 (MCQ‐30), and Brief COPE Scale (BCS) Short Form. The mediated moderation analysis was conducted using Process Macro.

Results

There was a significant positive correlation found between FCR and IU (r = 0.87, p < 0.001), and between FCR and negative metacognitions (r = 0.72, p < 0.001). A weak to moderate positive correlation was identified between IU and maladaptive coping strategies (r = 0.19, p < 0.05), and between negative metacognitions and maladaptive coping strategies (r = 0.31, p < 0.001). The relationship between FCR and maladaptive coping strategies was nonsignificant (r = 0.16, p > 0.05). As a result of hierarchical regression analysis, controlling for demographic and clinical variables, IU, positive metacognitions, and negative metacognitions significantly explained 45%, 2%, and 1% of the variance in FCR, respectively.

Conclusion

The results of the current study contribute to the literature in terms of supporting the views that cognitive models of worrying could be used to understand the FCR mechanism and address the IU been which has limitedly studied in the FCR literature. The current study's findings have also contributed to the clinical field by highlighting the importance of incorporating breast cancer survivors' metacognitions and IU in FCR intervention programs.
Insomnia Prevalence and Correlates in Cancer Patients Undergoing Treatment
Authors: Page Jessica M. , Morgans Alicia K. , Hassett Michael J. , Haakenstad Ellana , Manni Michael , McCleary Nadine J. , Zhou Eric S.
Published: January 2025

Background

Insomnia is the most common sleep disturbance among cancer patients undergoing active treatment. If untreated, it is associated with significant physical and psychological health consequences. Prior efforts to determine insomnia prevalence and correlates have primarily assessed patients in clinical trials, in limited disease groups, and excluding important patient subgroups. These findings are likely to be influenced by research participation effects, which could bias outcomes. We sought to address these limitations in a large, real‐world sample.

Methods

Between 2018 and 2021, all patients seen at our institution were offered an electronic patient‐reported outcomes (PRO) questionnaire where they could self‐report on a range of symptoms based on the National Cancer Institute's PRO‐CTCAE. Medical records were abstracted for demographics and cancer diagnosis/treatment. We evaluated N = 9350 patients for whom there was complete data.

Results

During cancer treatment, 21% of patients reported insomnia symptoms. Demographically, prevalence was higher in patients who were female (22% vs. 19%), younger than 60 years of age (22% vs. 20%), non‐White (24% vs. 20%), and on public insurance (22% vs. 20%). Medically, patients undergoing palliative treatment were more likely to report insomnia symptoms, irrespective of cancer site (23% vs. 19%). The prevalence of insomnia symptoms ranged from 18% (genitourinary) to 23% (gastrointestinal).

Conclusion

More than 1 in 5 cancer patients suffer from symptoms of insomnia. It is important that oncologists and cancer centers routinely assess insomnia severity in their patients. Leveraging the use of existing patient‐reported outcomes at an institution may be important to help with the identification of insomnia symptoms.
Analysis of Chemical Components of Penicillium chrysogenum Crude Extract Using Liquid Chromatography Coupled With Q‐Exactive Orbitrap Mass Spectrometry Combined With GNPS Molecular Networking
Authors: Lu Ya , Yang Jiao , Ma Kun , Qi Jiahui , Villegas‐Moreno Jessica
Published: January 2025

A Chinese isolate of the fungus Penicillium chrysogenum was analyzed using liquid chromatography coupled with Q‐Exactive Orbitrap mass spectrometry combined with Global Natural Products Social Networking (GNPS) on culture condition leading to the rapid identification of 20 secondary metabolites. Among them are eight polyketones, two phthalides, six diketopiperazine alkaloids, and others. A meleagrine network was examined and proposed as a promising candidate for new natural products.
Organized Crimes, Cultural Heritage, and Sustainable Tourism: A Configurational Analysis
Authors: Al‐Ansi Amr
Published: January 2025

The global recognition of the rise in organized crimes targeting cultural heritage during times of war and political conflicts has prompted the need to assess its impact on the development and sustainability of tourism. This study aims to investigate the responses and behavioral intentions of communities in safeguarding cultural heritage, considering the intricate nature of the problem. Specifically, the research explores a configurational model that encompasses governance, community engagement, and sustainable tourism dimensions, employing a fuzzy set Qualitative Comparative Analysis (fsQCA). The findings put forth several viable solutions that not only foster support for tourism development but also encourage behavioral intentions to combat the looting of cultural heritage. Furthermore, the analysis of necessary conditions (NCA) underscores the significance of community involvement, as well as legal policies and regulations, in achieving desirable outcomes. The study concludes by discussing the practical and academic contributions of the research.
On Demand Copper Electrochemical Deposition on Laser Induced Graphene for Flexible Electronics
Authors: Liang Chao , Zhang Wenqiang , Fan Yuxuan , Mei Ziqi , Zhang Lingyun , Sun Zhenci , You Rui , You Zheng , Zhao Xiaoguang
Published: January 2025

The rapid development of flexible electronics necessitates simplified processes that integrate heterogeneous materials and structures. In this study, laser engraving is combined with electrochemical deposition (ECD) to directly fabricate various micro/nano‐structured components and flexible electronic circuits. A theoretical framework and simulation model are developed to design the on‐demand ECD on laser induced graphene (LIG), enabling the generation of multi‐scale copper (Cu) materials with controllable oxidation states. The Cu‐LIG composites exhibit high surface quality and reliability, meeting the requirements of flexible circuits. The study fabricates and characterizes multilayer circuits and complex functional devices, including electrochemical sensors, thin‐film heaters, and wireless humidity sensors, to showcase the versatility of the LIG‐ECD process. This approach can be extended to various polymer and metal deposition processes, paving the way for the development of high‐performance flexible electronic devices.
BaFS: Birefringence Enhanced by the Transformation from Optical Isotropy to Anisotropy via Interlayer Anion Substitution
Authors: Xie Chao‐Hong , Jiang Xiao‐Ming , Liu Bin‐Wen , Guo Guo‐Cong
Published: January 2025

Improved birefringence, given its capacity to modulate polarized light, holds a lively role in the optoelectronic industry. Traditionally, alkaline‐earth metal halides have possessed low birefringence due to their nearly optical isotropic properties. Herein, the substitution of interlayer anion with linear S─S unit that meticulously engineered by reduced valence state and strong covalent bond is integrated into the optically isotropic BaF2, offering the new salt‐inclusion chalcogenide BaFS. Notably, it has dramatically enhanced optical anisotropy, thereby significantly boosting birefringence of 0.238@546 nm, achieved by overall considering experimental observations with theoretical analysis. Theoretical investigation has established the significant effect of the covalent S─S bond on the birefringence index. Additionally, BaFS demonstrates a remarkable laser‐induced damage threshold (LIDT, 12.0 × AgGaS2@1064 nm), illuminating a promising pathway for designing materials with significant birefringence properties in laser applications.
Amorphous Ni(OH)2 Coated Cu Dendrites with Superaerophobic Interface for Bipolar Hydrogen Production Assisted with Formaldehyde Oxidation
Authors: Jiang Shaojian , Liu Yuhang , Yang Ruidong , Zhang Lijun , Liu Wenke , Deng Kai , Yu Hongjie , Wang Hongjing , Wang Liang
Published: January 2025

Since formaldehyde oxidation reaction (FOR) can release H2, it is attractive to construct a bipolar hydrogen production system consisting of FOR and hydrogen evolution reaction (HER). Although copper‐based catalysts have attracted much attention due to their low cost and high FOR activity, the performance enhancement mechanism lacks in‐depth investigation. Here, an amorphous‐crystalline catalyst of amorphous nickel hydroxide‐coated copper dendrites on copper foam (Cu@Ni(OH)2/CF) is prepared. The modification of Ni(OH)2 resulted in hydrophilic and aerophobic states on the Cu@Ni(OH)2/CF surface, facilitating the transport of liquid‐phase species on the electrode surface and accelerating the release of H2. The Open circuit potential (OCP) and density functional theory (DFT) calculations indicate that this core–shell structure facilitates the adsorption of HCHO and OH−. In addition, the catalytic mechanism and reaction pathway of FOR are investigated through in situ FTIR and DFT calculations, and the results showed that the modification of Ni(OH)2 lowered the energy barrier for C─H bond breaking and H─H bond formation. In the HER//FOR system, Pt/C//Cu@Ni(OH)2/CF can provide a current density of 0.5 A cm−2 at 0.36 V and achieve efficient and stable H2 production. This work offers new ideas for designing electrocatalysts for bipolar hydrogen production system assisted with formaldehyde oxidation.
The Evolution of Nucleic Acid Nanotechnology: From DNA Assembly to DNA‐Encoded Library
Authors: Nie Qigui , Fang Xianfu , Huang Jiale , Xu Tingting , Li Yangfeng , Zhang Gong , Li Yizhou
Published: January 2025

Deoxyribonucleic acid (DNA), a fundamental biomacromolecule in living organisms, serves as the carrier of genetic information. Beyond its role in encoding biological functions, DNA's inherent ability to hybridize through base pairing has opened new avenues for its application in biological sciences. This review introduces DNA nanotechnology and DNA‐encoded library (DEL), and highlights their shared design principles related to DNA assembly. First, a foundational overview of structural DNA nanotechnology, including its design strategies and historical development is provided. Subsequently, various approaches are examined to dynamic DNA nanotechnology, from strand displacement reactions to DNA‐templated polymer synthesis. Second, how the principle of DNA assembly has facilitated the development of diverse formats of self‐assembly‐based DEL synthesis, DNA‐template reactions (DTS), and DNA template‐mediated proximity induction effects are examined. These advancements are all underpinned by the unique property of DNA assembly. Finally, this review summarizes the common principles shared by DNA nanotechnology and DEL in terms of methodology and design. Additionally, the potential synergies are explored between these two technologies, envisioning future applications where they can be combined to create more versatile and exquisite functionalities.
Vector AutoRegressive Moving Average Models: A Review
Authors: Düker Marie‐Christine , Matteson David S. , Tsay Ruey S. , Wilms Ines
Published: January 2025

Vector AutoRegressive Moving Average (VARMA) models form a powerful and general model class for analyzing dynamics among multiple time series. While VARMA models encompass the Vector AutoRegressive (VAR) models, their popularity in empirical applications is dominated by the latter. Can this phenomenon be explained fully by the simplicity of VAR models? Perhaps many users of VAR models have not fully appreciated what VARMA models can provide. The goal of this review is to provide a comprehensive resource for researchers and practitioners seeking insights into the advantages and capabilities of VARMA models. We start by reviewing the identification challenges inherent to VARMA models thereby encompassing classical and modern identification schemes and we continue along the same lines regarding estimation, specification, and diagnosis of VARMA models. We then highlight the practical utility of VARMA models in terms of Granger Causality analysis, forecasting and structural analysis as well as recent advances and extensions of VARMA models to further facilitate their adoption in practice. Finally, we discuss some interesting future research directions where VARMA models can fulfill their potentials in applications as compared to their subclass of VAR models.
Distribution of responsibility for AI development: expert views
Authors: Hedlund Maria , Persson Erik
Published: January 2025

The purpose of this paper is to increase the understanding of how different types of experts with influence over the development of AI, in this role, reflect upon distribution of forward-looking responsibility for AI development with regard to safety and democracy. Forward-looking responsibility refers to the obligation to see to it that a particular state of affairs materialise. In the context of AI, actors somehow involved in AI development have the potential to guide AI development in a safe and democratic direction. This study is based on qualitative interviews with such actors in different roles at research institutions, private companies, think tanks, consultancy agencies, parliaments, and non-governmental organisations. While the reflections about distribution of responsibility differ among the respondents, one observation is that influence is seen as an important basis for distribution of responsibility. Another observation is that several respondents think of responsibility in terms of what it would entail in concrete measures. By showing how actors involved in AI development reflect on distribution of responsibility, this study contributes to a dialogue between the field of AI governance and the field of AI ethics.
Complex transcription regulation of acidic chitinase suggests fine-tuning of digestive processes in Drosera binata
Authors: Mikitova Veronika , Jopcik Martin , Rajninec Miroslav , Libantova Jana
Published: January 2025

Main conclusion

DbChitI-3, Drosera binata's acidic chitinase, peaks at pH 2.5 from 15 °C to 30 °C. Gene expression is stimulated by polysaccharides and suppressed by monosaccharide digestion, implying a feedback loop in its transcriptional regulation.

Here, we characterised a novel chitinase gene (DbChitI-3) isolated from the carnivorous plant species Drosera binata with strong homology to other Drosera species' extracellular class I chitinases with a role in digestive processes. The capability to cleave different forms of chitin was tested using recombinantly produced chitinase in Escherichia coli (rDbChitI-3S−His) and subsequent purification. The recombinant protein did not cleave chitin powder, the mono-, di- and tri- N-acetyl-D-glucosamine substrates, but cleaved acetic acid-swollen chitin. Fluorometric assay with acetic acid-swollen FITC-chitin as a substrate revealed the maximum enzyme activity at pH 2.5, spanning from 15 °C to 30 °C. Comparing enzymatic parameters with commercial chitinase from Streptomyces griseus showed rDbChitI-3S-His efficiency reaching 64.3% of S. griseus chitinase under optimal conditions. The highest basal expression of DbChitI-3 was detected in leaf blades. In other organs, the expression was either fivefold lower (petioles) or almost nondetectable (stems, roots and flowers). Application of gelatin, chitin, and pachyman resulted in a 3.9-, 4.6- and 5.7-fold increase in the mRNA transcript abundance of DbChitI-3 in leaves. In contrast, monosaccharides and laminarin decreased transcription of the DbChitI-3 gene by at least 70%, 5 h after treatment. The simultaneous application of suppressor and inducer (glucose and pachyman) indicated the predominant effect of the suppressor, implying that sufficient monosaccharide nutrients prioritize absorption processes in D. binata leaves over further digestion of the potential substrate.
Polyp image segmentation based on improved planet optimization algorithm using reptile search algorithm
Authors: Abd Elaziz Mohamed , Al-qaness Mohammed A. A. , Al-Betar Mohammed Azmi , Ewees Ahmed A.
Published: January 2025

To recognize the potential for colon polyps to develop into cancer over time, early diagnosis is crucial for preventative healthcare. Timely identification significantly improves the prognosis and treatment outcomes for colorectal cancer patients. Image segmentation is crucial in medical image analysis for accurate diagnosis and treatment planning. Therefore, in this study, we present an alternative multilevel thresholding polyp segmentation method (MPOA) to enhance the segmentation of polyp images. The proposed method is based on enhancing the planet optimization algorithm (POA) by integrating operators from the reptile search algorithm (RSA). The evaluation of the developed MPOA is tested with different polyp images and compared with other image segmentation approaches. The results highlight the superior capability of MPOA, as evidenced by various performance measures in effectively segmenting polyp images. Furthermore, metrics such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and fitness values demonstrate that MPOA outperforms the basic version of POA and other methods. The evaluation outcomes underscore the significant impact of RSA in enhancing the performance of POA for the segmentation of polyp images.
Correlation-based pruning algorithm with weight compensation for feedforward neural networks
Authors: Ebid Shaimaa E. K. , El-Tantawy Samah , Shawky Doaa , Abdel-Malek Hany L.
Published: January 2025

Optimizing neural network architectures through effective pruning techniques has become essential to balancing model complexity and accuracy. This study introduces a novel correlation-based approach to systematically reduce network size by identifying and removing redundant neurons based on their activation correlations. By selectively pruning neurons while compensating for their contributions, the method maintains model fidelity across diverse datasets. Results demonstrate substantial architecture reductions with minimal performance impact: For the MNIST dataset, the number of neurons in hidden layers was reduced from 128-128 to 118-93, while maintaining a high accuracy of 97.59%. Comparative analysis indicates that this pruning approach achieves competitive or superior results compared to state-of-the-art methods while reducing computational complexity and memory requirements by up to 25%. The findings highlight the potential of correlation-driven pruning strategies to optimize neural networks, making them more efficient and adaptable to resource-constrained environments.
Mandibular trabecular bone pattern before and two years after medical or surgical obesity treatment in young Swedish women
Authors: Östberg Anna-Lena , Wallenius Ville , Taghat Negin , Jonasson Grethe
Published: January 2025

Objective

To investigate if changes in body mass index (BMI) result in changes of the mandibular trabecular bone structure.

Materials and methods

Females (18–35 years at baseline, mean BMI 42,3) were followed from before (n = 117) until two years (n = 66) after obesity treatment (medical or surgical). The mandibular bone trabeculation was classified as sparse, dense, or mixed on intraoral radiographs (Lindh’s index). A digitized method (Jaw-X) assessed the size and intensities of intertrabecular spaces. The main predictor variable was BMI reduction over the period.

Results

Before treatment, the group with a high BMI (≥ 45) had a significantly denser bone than those with a lower BMI (p = 0.035). Two years after treatment, fewer were classified with sparse bone (Lindh’s index p = 0.001, Jaw-X p = 0.009). The physical activity increased with fewer having a sedentary lifestyle (40% before, 17% after treatment). The association between BMI reduction and the difference in Jaw-X was significant in regression models and not influenced by obesity treatment method but by baseline factors as age, trabecular bone pattern and level of ionized calcium.

Conclusions

Before obesity treatment, high BMI was associated with dense bone trabeculation in the jaw. The group with sparse bone had decreased at follow-up. The association between BMI reduction and bone trabeculation was influenced by individual and medical factors.

Clinical relevance

Bone trabeculation in the mandible was maintained during the first years after obesity treatment but new health habits should be encouraged, and patients need to be monitored and followed up further.
The Use of Motivational Interviewing with Chronically Unhoused Veterans
Authors: Mera Scarlett
Published: January 2025

The Housing First model is embedded in a supportive housing federal program aimed at reducing homelessness by offering housing vouchers and case management services to chronically unhoused veterans with co-occurring disorders. Despite the successes Housing First programs have achieved with the chronic unhoused population, including veterans, the cycle of homelessness continues to exist in this subgroup. These veterans have significant vulnerabilities, such as severe mental health and addiction histories, that contribute to their housing instability. The case narrative in this paper illustrates the story of a chronically unhoused veteran who cycled through episodes of homelessness due to ongoing substance use and evictions. On the veteran's third entry into a Housing First program, the social worker utilized the transtheoretical model (TTM) to evaluate the veteran's readiness to change and applied motivational interviewing (MI) principles to find a representative payee who would support housing stability, even if the veteran experienced a relapse. This approach can be considered harm reduction in supportive housing. Through the application of MI, the veteran exercised self-efficacy, opted for implementing a protective factor, and experienced long-term stable housing.
From self and career perceptions to life satisfaction: A sequential mediation approach to general self-efficacy, future work self, career anxiety, and life satisfaction in the emerging workforce
Authors: Gerçek Merve , Özveren Cem Güney
Published: January 2025

General self-efficacy (GSE) and life satisfaction (LS) are crucial to overall well-being, especially for young adults, for whom future envisioning and employment concerns significantly impact their vocational paths. Given the limited research on how future work self (FWS) and career anxiety (CA) function as mediators in this relationship, this study examines the connections between GSE, FWS, CA, and LS. The study sample consists of 532 undergraduate students from Türkiye. Using structural equation modeling, the results show that GSE, FWS, CA, and LS are significantly related, with the relationship between GSE and LS being sequentially mediated by FWS and CA.
The Divine in the Clinic: Assisted Reproduction and Religious Practice in Ghana and South Africa
Authors: Whittaker Andrea , Gerrits Trudie , Manderson Lenore
Published: January 2025

Drawing on studies with 40 informants in Ghana and 74 informants in South Africa, we explore spiritual interventions among staff and patients that accompany their use of assisted reproduction. These practices and expressions of faith reinforce staff and patients as moral subjects who have done everything possible to assist in the vagaries of assisted reproduction—another form of care to enable, complement, and enhance high-tech intervention. We consider the creation of sacred spaces in the clinics, the rituals that form part of IVF practice, and the dilemmas of translation when assisted reproductive technologies (ARTs) travel to different cultural and religious contexts.
The attenuation of spider avoidance action tendencies in spider-fearful individuals and its impact on behavioural and emotional responding to spiders
Authors: Basanovic Julian , Ranjbar Seyran , MacLeod Colin
Published: January 2025

Studies using the Approach/Avoidance Task (AAT) paradigm have demonstrated that individuals with heightened levels of spider-fear, as compared to lower levels of spider-fear, are characterised by biased action tendencies, indicated by speeded completion of movements that increase apparent distance between spider-stimuli and themselves (push movements), compared to movements that decrease apparent distance between spider-stimuli and themselves (pull response). Research using training variants of the AAT has also demonstrated that this pattern of action tendencies can be attenuated amongst individuals with heightened spider-fear. However, the effect of this manipulation on behaviour and emotion in the presence of a spider has not been examined. Eighty-eight participants who reported relatively high levels of spider-fear completed a procedure designed to either attenuate avoidance action tendencies for spider stimuli (Approach Spider Condition) or have no impact on action tendencies for spider stimuli (Control Condition). Action tendencies were assessed before and after the manipulation. Participants then completed a Behavioural Approach Task that recorded the number of steps voluntarily taken toward a spider and level of self-reported anxiety at each step. Analyses revealed that avoidance action tendencies to spider stimuli were attenuated in the Approach Spider Condition as compared to the Control Condition following the experimental manipulation, as intended. However, participants in each condition did not differ in behavioural or emotional measures recorded during the approach task. These findings replicate research indicating avoidance action tendencies to spider stimuli can be manipulated amongst individuals with heightened spider-fear, though suggest that their manipulation may not influence ‘real world’ behavioural or emotional responding to spiders.
Aufarbeitung der Pandemie und Bedenken der Impfbereitschaft: Auswirkungen individueller Aufklärungsgespräche vor der COVID-19-Impfung
Authors: Wüller Moritz , Grotemeyer Alexander , Thürauf Norbert
Published: January 2025

Hintergrund

Durch verfügbare Impfungen gegen SarsCov‑2 („severe acute respiratory syndrome coronavirus 2“) zeigten sich lautstarke Ablehnungen gegen die Präventionsmaßnahme. Unter medizinischem Personal zeigten sich Trends zur Ablehnung der Impfung und die Frage über eine Impflicht wurde politisch diskutiert. Welche Bedenken und Ängste vor und nach der Impfung bestehen und wie diese abgebaut werden können? Ist es möglich eine Aufklärung adressatengerecht zu gestalten?

Ziele

Das Ziel dieser Arbeit ist es, das Aufklärungsgespräch besser den Wünschen und evtl. bestehenden Sorgen des zu Impfenden anzupassen. Dafür ist es notwendig, beeinflussende Faktoren in der Entscheidungsfindung zu erkennen und wichtige Aspekte verschiedener Gruppen herauszuarbeiten.

Methode

Nach Literaturrecherche Erfahrungen der Autoren wurde ein Fragebogen zum Thema COVID-Impfung („coronavirus disease 2019“) erstellt. Dieser wurde von Mai bis Juli 2021 per Online-Befragung an Mitarbeiter der Psychiatrie der Universitätsklinik Erlangen. Office-Programme halfen bei der Auswertung und die Statistik wurde mit Prism9 erstellt.

Ergebnisse

Wir fanden, dass die Akzeptanz der Impfung 97 % betrug. 83 % verlangten das persönliche Aufklärungsgespräch, 17 % zeigten sich unsicher über eine Impfung und profitierten von einer persönlichen Aufklärung. Es konnte gezeigt werden, dass bereits getroffene Entscheidung über die Impfung nicht durch das Impfgespräch beeinflusst wurden.

Schlussfolgerungen

Es konnte gezeigt werden, dass bereits getroffene Entscheidungen über die Impfung nicht durch das Impfgespräch beeinflusst wurden. Diese Studie zeigt nicht nur den Einfluss einer persönlichen Aufklärung, sondern auch die Notwendigkeit eines solchen Gesprächs im Vorfeld. Dabei spielt das Bildungsniveau einen entscheidenden Faktor in der Aufklärung.
The Effect of Phase Changes on Optoelectronic Properties of Lead-Free CsSnI3 Perovskites
Authors: Nematov Dilshod D. , Burkhonzoda Amondulloi S. , Kurboniyon Mekhrdod S. , Zafari Umar , Kholmurodov Kholmirzo T. , Brik Mikhail G. , Yamamoto Tomoyuki , Shokir Farhod
Published: January 2025

First-principles calculations were carried out within the framework of density functional theory to investigate the influence of phase changes on the electronic and optical properties of CsSnI3. The lattice parameter and band gap of four different phases, i.e., α-, β-, γ-, and δ-phases, of CsSnI3 are estimated by employing different exchange–correlation functionals in order to explore their ability to reproduce geometric and electronic structures adequately. Comparison of the calculated total energies shows the non-perovskite orthorhombic (δ-phase) modification of CsSnI3 is the most stable, followed by the orthorhombic (γ-CsSnI3) perovskite phase. Thermal stability calculations in the form of temperature dependence of entropy as well as the absence of imaginary frequencies in the phonon dispersion diagrams also confirmed the dynamical stability of the δ-CsSnI3. The influence of the structural phase changes on the band gap and Fermi level shifts of CsSnI3 were assessed. Contribution of the electronic states on the formation of the valence and conduction band of four phases of CsSnI3 were determined, which were calculated using various exchange–correlation functionals, including the high-precision hybrid functional HSE06, and compared with available experimental ones. The calculated energy band distribution diagrams showed that all three perovskite modifications of CsSnI3 have direct transitions, while δ-CsSnI3 has an indirect transition. It was found that during the transition from δ- to α-phase, the Fermi level descends to the low energy region (towards the valence band), and the band gap decreases from 2.99 eV to 1.33 eV. During the transition from α- to β-phase, the band gap width again decreases to 1.23 eV and the Fermi level mixes by 1.65 eV towards the conduction band (CB). On the contrary, the band gap increases from β- to γ-phase and the Fermi level shifts by 0.41 eV towards the conduction band. The values of the complex dielectric constant and the refractive index of four phases of CsSnI3 were also calculated.
Large language model for table processing: a survey
Authors: Lu Weizheng , Zhang Jing , Fan Ju , Fu Zihao , Chen Yueguo , Du Xiaoyong
Published: January 2025

Tables, typically two-dimensional and structured to store large amounts of data, are essential in daily activities like database queries, spreadsheet manipulations, Web table question answering, and image table information extraction. Automating these table-centric tasks with Large Language Models (LLMs) or Visual Language Models (VLMs) offers significant public benefits, garnering interest from academia and industry. This survey provides a comprehensive overview of table-related tasks, examining both user scenarios and technical aspects. It covers traditional tasks like table question answering as well as emerging fields such as spreadsheet manipulation and table data analysis. We summarize the training techniques for LLMs and VLMs tailored for table processing. Additionally, we discuss prompt engineering, particularly the use of LLM-powered agents, for various table-related tasks. Finally, we highlight several challenges, including diverse user input when serving and slow thinking using chain-of-thought.
3D-printed drill guide versus fluoroscopic-guided free-hand technique for pedicle screw insertion in the upper cervical spine: a systematic review and meta-analysis
Authors: Al-Saadawi A. , Tehranchi S. , Chekuri R. , Oehlen A. , Sedra F.
Published: January 2025

3D-printed (3DP) drill guides have demonstrated significant potential to accurately guide pedicle screw insertion in spinal surgery. However, their role in the upper cervical spine is not well established. This review aimed to compare the efficacy and safety of 3DP drill guides to the conventional fluoroscopic-guided free-hand technique for pedicle screw insertion in the upper cervical spine. A comprehensive literature search was conducted across five databases (Medline, Scopus, CENTRAL, Web of Science, and Embase). The meta-analysis compared the accuracy of pedicle screw placement, screw placement time, operative time, blood loss, fluoroscopy usage, and post-operative JOA and VAS scores between the two approaches. Seven studies were included in the review, encompassing 386 patients and 1,512 screws. The meta-analysis demonstrated that 3DP drill guides increased the rate of perfect screw insertion (OR: 4.34, P < 0.00001) and lowered the incidence of moderate (OR: 0.26, P < 0.00001) and poor (OR: 0.09, P < 0.00001) screw insertion compared to the free-hand technique. Additionally, operative time (MD: -36.07, P < 0.00001), blood loss (MD: -83.82, P < 0.00001), and fluoroscopy usage (MD: -3.47, P < 0.0001) was significantly reduced in the 3DP cohort. No significant difference was detected in screw placement time (MD: -2.65, P = 0.07), or post-operative JOA (MD: 0.17, P = 0.47), and VAS (MD: -0.09, P = 0.19) scores between the two cohorts. The review demonstrated that 3DP drill guides are a safe and effective tool to assist pedicle screw fixation in the upper cervical spine.
UniEmbed: A Novel Approach to Detect XSS and SQL Injection Attacks Leveraging Multiple Feature Fusion with Machine Learning Techniques
Authors: Bakır Rezan
Published: January 2025

Web applications are essential in the digital age, but their security vulnerabilities expose sensitive data and organizational integrity to sophisticated attacks. Among the most prevalent and damaging vulnerabilities in web applications are cross-site scripting (XSS) and SQL injection attacks. In this paper, we introduce UniEmbed, a unified approach for detecting XSS and SQL injection attacks using machine learning classifiers. This novel approach leverages natural language processing techniques, combining features from Word2Vec, the Universal Sentence Encoder (USE), and FastText to extract meaningful data from web applications. Extensive experiments were conducted using various machine learning classifiers on three benchmark datasets to evaluate the performance of the unified detection approach, demonstrating exceptional results. Experimental results demonstrate the superior performance of the MLP classifier. For the XSS attack dataset, the MLP classifier achieved an accuracy of 0.9982 and an F1-score of 0.9983, with minimal false positives and false negatives. Similarly, the hard voting classifier yielded the same outstanding results. For SQL injection attacks, the MLP classifier maintained exceptional performance, achieving an F1-score of 0.9980 and accuracy rates exceeding 0.9980 across two datasets. The classifier effectively minimized false positives and false negatives. The ROC curves further corroborate the effectiveness of the proposed method, indicating high true positive rates and low false positive rates. Furthermore, comparative analysis showed that the UniEmbed method consistently outperformed individual feature extraction methods across all classifiers. These findings indicate that the proposed UniEmbed method, particularly when combined with the MLP classifier, is highly effective in detecting both XSS and SQL injection attacks, making it a promising approach for enhancing web application security.
Detecting geodesic circles in hyperbolic surfaces with persistent homology
Authors: Jelenc Blaž , Virk Žiga
Published: January 2025

In this paper we provide conditions under which a geodesic circle on a hyperbolic surface admits arbitrarily small geodesically convex neighborhoods. This implies that persistent homology using selective Rips complexes detects the length and the position of such a loop via persistent homology in dimensions one, two, or three. In particular, if a surface has a unique systole, then the systole can always be detected with persistent homology. The existential results of the paper are complemented by the corresponding quantitative treatments which explain the choice of parameters of selective Rips complexes as well as conditions, under which the detection occurs via the standard Rips complexes. In particular, if a surface has a unique systole, then the parameters depend on the first spectral gap in the length spectrum.