bluuebunny/crossref_metadata_2025 huggingface dataset:
Association of circadian rhythms, CLOCK, MTNR1A, and MTNR1B gene polymorphisms and their interactions with type 2 diabetes in coal miners
Authors: Cao Haoyue , Li Qinglin , Yuan Juxiang
Published: November 2024

Objective: To construct comprehensive indicators of circadian rhythm disorder (CICRD) and explore the interaction effects between CICRD and circadian rhythm-related gene polymorphisms (SNPs) on the risk of type 2 diabetes mellitus (T2DM).
Methods: Baseline data were collected from the Xingtai coal site of the Occupational Cohort Study on Health Effects. A cross-sectional study was initially conducted, involving 4,070 coal miners who underwent occupational health examinations during 2017 and 2018. We performed factor analysis to construct the CICRD and logistic regression models to estimate the association between CICRD and T2DM. Restricted cubic spline (RCS) function was used to determine the exposure-response association. In the subsequent case-control analysis, 424 cases and 464 controls were randomly selected from 3,878 male coal miners. Logistic regression model was employed to examine the association between selected SNPs and T2DM. Gene-gene and gene-environment interactions were evaluated using log-linear models and the generalized multifactor dimensionality reduction (GMDR) method.
Results: The CICRD constructed by factor analysis explained 79.771% of the original variance. After adjusting for confounding factors, CICRD was associated with the increased risk of T2DM. Variants at rs10830963 in the MTNR1B gene, rs7958822 in the BMAL2 gene, and rs11605924 in the CRY2 gene were associated with the increased risk of T2DM. Interactions between rs10830963 in the MTNR1B gene and rs11605924 in the CRY2 gene (RERI: 0.2; AP: 0.46), as well as between rs7958822 in the BMAL2 gene and rs11605924 in the CRY2 gene (RERI: 1.55; AP: 0.56), were associated with increased risk of T2DM. A CICRD score ≥ 0.2782 combined with high-risk genotypes at four SNPs (rs10830963 and rs1387153 in MTNR1B, rs7958822 in BMAL2, and rs11605924 in CRY2) was associated with increased risk of T2DM (P < 0.05). The complex intersection of four-factor interaction model (rs10830963-rs1387153-rs7958822-rs11605924) and five-factor interaction model (rs10830963-rs7950226-rs7958822-rs11605924-CICRD) based on GMDR method interactions increased the risk of T2DM in the full data set (P < 0.05).
Conclusion: An increase in CICRD, along with variants at rs10830963 in the MTNR1B gene, rs7958822 in the BMAL2 gene, and rs11605924 in the CRY2 gene, was associated with an increased risk of T2DM among coal miners. The four-factor model (rs10830963-rs1387153-rs7958822-rs11605924) and the five-factor model (rs10830963-rs7950226-rs7958822-rs11605924-CICRD) exhibited significant high-order interactions associated with an increased risk of T2DM among coal miners.
Bioactive Metabolites from Aspergillus niger Associated with Moringa oleifera: Potential for Anti-Infective Agents
Authors: Ali Markwo , Kingsford-Adaboh Robert , Ghoran Salar Hafez , Wahab Atia-tul , Choudhary Muhammad Iqbal
Published: November 2024

This study explores the metabolic profiling of secondary metabolites from the endophytic fungus Aspergillus niger associated with the medicinal plant Moringa oleifera for the discovery of anti-infective agents. Aspergillus niger was isolated and characterised based on morphological traits and molecular phylogenetic analysis, confirmed via nucleotide sequence comparison with sequences on the NCBI database. The effects of cultivation parameters – including medium composition, volume, extraction solvent, and cultivation duration – on metabolite recovery and biological activity were evaluated. Bioassays identified active extracts, which were further fractionated and purified using chromatographic techniques. Mass spectrometry and nuclear magnetic resonance spectroscopy were employed to analyse the isolated metabolites. The results demonstrated that cultivation conditions significantly influenced metabolite production and extract recovery. The study revealed notable antibacterial and antifungal activities against Escherichia coli, Staphylococcus aureus, and Candida albicans among others, although no significant anti-leishmanial, antioxidant, or anti-inflammatory effects were observed. Metabolites identified include fumaric acid, succinic acid, 4-(2-hydroxyethyl)phenol, 5-hydroxymethyl-2-furancarboxylic acid, 4-hydroxybenzoic acid, and N-[2-(4-hydroxyphenyl)ethyl]acetamide. Notably, this study marks the first report of 4-(2-hydroxyethyl)phenol and N-[2-(4-hydroxyphenyl)ethyl]acetamide as isolated from Aspergillus niger. These findings highlight Aspergillus niger as a promising source of bioactive metabolites and provide valuable insights into its potential for the development of novel anti-infective agents.
Genomic surveillance reveals geographical heterogeneity and differences in known and novel insecticide resistance mechanisms in Anopheles arabiensis across Kenya
Authors: Polo Brian , Bennett Kelly L. , Barasa Sonia , Brenas Jon , Agumba Silas , Mwangangi Joseph , Wachira Lucy , Kitur Stanley , Matoke-Muhia Damaris , Mburu David , Ramaita Edith , Juma Elijah O. , Mbogo Charles , Ochomo Eric , Clarkson Christopher , Miles Alistair , Kamau Luna
Published: November 2024

Background
Insecticide resistance in disease vectors poses a significant threat to the control of transmission globally. In Anopheles mosquitoes, resistance has jeopardized gains made in malaria control and led to the resurgence of cases. Although Anopheles arabiensis is a major malaria vector, little is known about its genetic diversity and insecticide resistance mechanisms across geographical space. There is an urgent need to incorporate genomics in resistance monitoring to allow preemptive detection of adaptive alleles.
Methods
We analyzed whole-genome data from 498 An. arabiensis specimens collected across five regions in Kenya. Population structure was assessed and both known and novel resistance mechanisms were investigated through SNP and CNV frequency analysis, genome-wide selection scans and haplotype clustering.
Results
Analyses of whole-genome data revealed geographical population structure between the northwestern region and central coastal Kenya, which was likely influenced by the Great Rift Valley. Distinct geographical differences in insecticide resistance profiles were observed across Kenya, reflecting differences in ecology, land use and selection pressure. For instance, in central Kenya, copy number variants at the Cyp6aa/p gene cluster and carboxylesterase genes associated with metabolic resistance to pyrethroids and organophosphates are fixed. In contrast, northwestern Kenya had mutations associated with both the target site and metabolic resistance to pyrethroids and DDT at high frequencies. Vgsc-L995F mutations occurred at frequencies of up to 44%, and duplications of Cyp9k1 occurred at frequencies of up to 66%. Genome-wide selection scans identified novel candidates under selection in central Kenya, including the Keap1 gene, which is involved in the regulation of multiple detoxification genes, likely due to high insecticide pressure in the region.
Conclusion
Restricted gene flow coupled with heterogeneity in molecular insecticide resistance across Kenya suggests that localized control measures may be more effective in preventing the spread of insecticide resistance in An. arabiensis. This study highlights the importance of incorporating genomics in the routine monitoring of malaria vector populations to identify the emergence of new resistance signatures and their geographic distribution and spread.
Inter-Patch Spatio-Temporal Relation Prediction for Video Anomaly Detection
Authors: Shen Hao , Shi Lu , Zhang Linna , Xu Wanru , Cen Yigang , An Gaoyun
Published: November 2024

Video Anomaly Detection (VAD), aiming to identify abnormalities within a specific context and timeframe, is crucial for intelligent Video Surveillance Systems. While recent deep learning-based VAD models have shown promising results by generating high-resolution frames, they often lack competence in preserving detailed spatial and temporal coherence in video frames. To tackle this issue, we propose a self-supervised learning approach for VAD through an inter-patch relationship prediction task. Specifically, we introduce a two-branch vision transformer network designed to capture deep visual features of video frames, which can address spatial and temporal dimensions responsible for modeling appearance and motion patterns, respectively. The inter-patch relationship in each dimension is decoupled into inter-patch similarity and the order information of each patch. To mitigate memory consumption, we convert the order information prediction task into a multi-label learning problem, and the inter-patch similarity prediction task into a inter-patch distance matrix regression problem. Comprehensive experiments demonstrate the effectiveness of our method, surpassing pixel-generation-based methods by a significant margin across three public benchmarks. Additionally, our approach outperforms other self-supervised learning-based methods.
Factors Contributing to Anxiety in Adolescents Surviving Thalassemia Major in Indonesia
Authors: Mediani Henny Suzana , Fuadah Novitasari Tsamrotul
Published: November 2024

Background
Thalassemia major leads to severe anaemia, necessitating lifelong blood transfusions. Inconsistencies in blood transfusions and iron chelation therapy result in physical changes that can cause psychological issues, with anxiety being the most prominent. This study aimed to examine the factors influencing anxiety levels among adolescent thalassemia major survivors.
Methods
The research utilized a quantitative approach with a correlational analytic design and cross-sectional method. It included a population of 122 adolescent survivors, all of whom were included using a total sampling technique. Data analysis involved univariate analysis by frequency distribution, bivariate analysis using the chi-square test, and multivariate analysis with logistic regression.
Results
The study findings revealed that 70.5% of adolescents experienced mild anxiety. Significant correlations were found between body image (p < 0.001), self-esteem, and coping mechanisms with anxiety levels, while social support was not significantly related. Body image emerged as the most influential factor, with poor body image increasing the likelihood of severe anxiety by 11.6 times.
Conclusions
Adolescents with Thalassemia major in West Java primarily exhibit mild anxiety. These findings highlight the necessity for comprehensive psychological support that addresses body image concerns and boosts self-esteem and coping skills to enhance the mental health of adolescent thalassemia major survivors.
Nocardioides piscium sp. nov. , an Epsilon-poly-L-lysine producing actinobacterium isolated from the fish intestine
Authors: Li Jiawei , Zhao Aolin , Yang Quan , Liu Haifei , Yang Lifang , Huang Ying , Wu Shujing , Jiang Mingguo
Published: November 2024

A Gram-positive, irregular short-stemmed, non-motile, non-acid-fast, non-spore-forming, aerobic actinomycete strain, designated GXZ039T, was isolated from the fish gut of grouper from the Beibu Gulf, Guangxi, China. Analysis of the growth state and conditions showed that colonies on medium 2216E for 5 days of incubation were light-white, rounded, glossy, smooth, raised, and opaque, diameter 1.0–2.0 mm. Strain growth conditions ranged from pH 6.0–10.0 (optimum pH 7.5), 4–40°C (optimum 30°C)and 0–10% NaCl (w/v) (optimum 3.5%). Chemical histological showed that the major menaquinone of strain GXZ039T was MK-8, with a small amount of MK-7. The main cellular fatty acids were iso-C16:0 (39.2%), C17:1ꞷ6c (11.59%) and anteiso-C15:0 (10.97%). The type of the cell wall peptidoglycan was LL-diaminoheptanedioic acid and the polar lipids consisted of phosphatidylglycerol (PG), diphosphatidylglycerol (DPG), an uncharacterised lipid (L) and two unknown phospholipids (PL1-2). Total cell sugars were xylose, arabinose, glucose and galactose. The DNA G + C ratio of the strain was 71.1 mol%. Sequence comparison of 16S rRNA genes showed that strain GXZ039T belonged to the genus Nocardioides and its close relatives were with Nocardioides plantarum NCIMB 12834T (98.03%),, Nocardioides dongxiaopingii S-1144T (97.54%) and Nocardioides litoris 002-2T(97.54%), respectively. Calculations showed that GXZ039T had ANI values of 77.12–85.13% and dDDH values of 21.6–27.7%. On the basis of phenotypic, chemical components and phylogenetic data, strain GXZ039T was defined as a novel species of the genus Nocardioides under the name Nocardioides piscium sp. nov. The strain type is GXZ039T (= MCCC 1K09118T = KCTC 59248T).
IL-13 gene polymorphism at the -1055 locus and severe malaria – Is there a link?
Authors: Hassan Dalin A. , Elhussein Amar Babikir , Ali Mariam Siddig Balla , Fadlelseed Omar Elteyb , Qadri Marwa , Mawkili Wedad , Mohanan Anugeetha Thacheril , Ahmed Zeyad M. , Elmobark Mohamed Eltaib , Ali Eman Merghani , Dawod Ogail Yousif , Alfadol Soad M. A. , Ahmed Eman O. A. , Abu Ibrahim Ismail Mohammed , Rahma Nour Elhouda A. A. , Shalayel Mohammed Helmy Faris
Published: November 2024

Objective
This research examined how the IL-13-1055C/T promoter polymorphism affects the likelihood of Sudanese children developing severe malaria.
Method
The research was carried out in 2020 and included 115 children with malaria and 49 healthy youngsters from Al Gadaref, Sudan. To analyze the IL-13 1055C/T SNP, the DNA product was digested by the restriction enzyme BstFNI. The ELISA Sandwich method was used to investigate serum IL-13 and IgE.
Results
The IL-13 gene1055C/T SNP differed significantly between malaria patients and healthy individuals. The results revealed a highly significant difference between various alleles of the IL-13 gene 1055C/T position and malaria severity groups (P-value < 0.001). The IL-13 SNP was found to be closely associated with the allele frequency in the healthy control group. (C: T% = 70.4:29.6), with a p-value < 0.001. The findings show a significant positive relationship between IL-13 and IgE levels in individuals with malaria. (r = 811; P value < 0.001). IL-13 levels differ significantly between malaria patients and healthy individuals, with a P value = 0.000. Malaria patients exhibited considerably greater IgE levels than healthy children, P value < 0.001.
Conclusion
Our findings revealed substantial relationships between the IL-13 gene polymorphism at the − 1055 locus and severe malaria anemia, uncomplicated malaria, and cerebral malaria cases, implying that the IL-13 gene could have a significant impact on the development of severe malaria.
The associations between work stress load, Advance care planning practice preferences and self-efficacy in Intensive care unit nurses
Authors: Wang HaoJie , Zhang Weiqing , Wang Kun , Song Jielu , Cao Yabing , Wei ZhiHua
Published: November 2024

Objective: Given that Intensive care unit (ICU) patients are mostly in critical condition, unable to participate in decision-making communication, family members are prone to make medical care decisions against the patient's wishes, to safeguard the patient's right to autonomous decision-making. ICU nurses serve as vital conduits for Advance Care Planning (ACP) communication due to their professional expertise and understanding of patient conditions. However, they carry out the incidence of ACP is relatively low, the present study to investigate the communication self-efficacy level of advanced care planning (ACP) among ICU nurses in a tertiary care hospital and the factors affecting it, and to provide a reference for developing an intervention program.
Methods: From January 2024 to April 2024, 330 ICU nurses from six tertiary hospitals in *** Province were conveniently selected for the survey and analysis using the General Information Questionnaire, ACP Knowledge, Belief and Conduct Questionnaire, ACP Practice Preferences Scale, Work Stress Load Scale, and ACP Self-Efficacy Scale (Chinese version).
Results: ICU nurses' ACP self-efficacy score (44.42±9.14), Pearson's analysis of the correlation between variables, and multiple linear regression to analyze the main influencing factors of ICU nurses' ACP communication self-efficacy showed that marital status, participation in hospice training, ACP knowledge-attitude-behavioral willingness, ACP practice preference, and work stress load P <0.05,explaining 79.1% of the total variance.
Conclusion：ICU nurses' ACP communication self-efficacy is at a moderate level with many influencing factors, and it is recommended to implement interventions for the influencing factors to improve the level of ICU nurses' ACP communication self-efficacy.
SRHPENet: Super-Resolution Network for human pose estimation
Authors: Zou Xuelian , Bi Xiaojun
Published: November 2024

Human pose estimation is a basic task in the field of computer vision, so improving recognition accuracy is of great significance for advanced computer vision tasks. At present, there are many methods to solve the human pose estimation task of high-resolution images, and have achieved excellent results. However, current high-resolution human pose estimation methods still face two problems in solving low-resolution human pose estimation tasks. (1) Low-resolution images usually lose a lot of key information, such as texture information, joint point positions becoming blurred, etc., which will cause the recognition accuracy to decrease. (2) Existing super-resolution images generally have a fixed receptive field, and cannot extract features and fuse multi-scale information well for images with different magnifications. To fill the problem of super-resolution images, we proposed a method suitable for low-resolution images. Super-Resolution Human Pose Estimation Network (SRHPENet) for human pose estimation tasks. The network is composed of two parts. First, we designed SReNe super-resolution network. The network is composed of the MSE module we designed, which can effectively extract multi-scale information content and alleviate the problem of fixed receptive fields. Secondly, we input the high-resolution images obtained by the super-resolution network into the human pose estimation network. Additionally, during the training phase, we introduce real high-resolution images into the human pose estimation network in order to improve the accuracy of human pose estimation. Finally, through joint training of the two parts, we obtain low-resolution performance close to the performance of state-of the-art with high-resolution images as input.
Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits
Authors: Nguyen Hoang-Quan , Nguyen Xuan Bac , Chen Samuel Yen-Chi , Churchill Hugh , Borys Nicholas , Khan Samee U. , Luu Khoa
Published: November 2024

Parameterized Quantum Circuits (PQCs) have been acknowledged as a leading strategy to utilize near-term quantum advantages in multiple problems, including machine learning and combinatorial optimization. When applied to specific tasks, the parameters in the quantum circuits are trained to minimize the target function. Although there have been comprehensive studies to improve the performance of the PQCs on practical tasks, the errors caused by the quantum noise downgrade the performance when running on real quantum computers. In particular, when the quantum state is transformed through multiple quantum circuit layers, the effect of the quantum noise happens cumulatively and becomes closer to the maximally mixed state or complete noise. This paper studies the relationship between the quantum noise and the diffusion model. Then, we propose a novel diffusion-inspired learning approach to mitigate the quantum noise in the PQCs and reduce the error for specific tasks. Through our experiments, we illustrate the efficiency of the learning strategy and achieve state-of-the-art performance on classification tasks in the quantum noise scenarios.
Intracytoplasmic sperm injection hampers fertilization rate and pregnancy per initiated cycle in patients with extremely poor ovarian response
Authors: Chen Jinghua , Liu Lanlan , Liu Zhenfang , Pan Luxiang , Zhou Liying , Chen Kaijie , Yang Xiaolian , Chen Yurong , Jiang Xiaoming , Cai Jiali , Ren Jiangzhi
Published: November 2024

Purpose: To compare the clinical outcomes of extremely poor responders with one or two oocytes who receive in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI).
Methods: A retrospective study was carried out in 2572 patients with one or two oocytes retrieved from 2013 to 2022, of which 2159 patients were scheduled to receive IVF treatment and 413 patients were scheduled to receive ICSI treatment. The laboratory parameters and clinical outcomes were compared with adjusted multivariate regression and propensity score (PS) matching.
Results: In both matched and non-matched cohorts, the total fertilization failure (TFF) rate of the ICSI group was significantly higher than that of the IVF group (P < 0.05), but the multiple fertilization rate of the IVF group was significantly higher than the ICSI group (P < 0.05). After matching, the cumulative pregnancy rate per initiated cycle in the IVF group was significantly higher than in the ICSI group (28.7% vs 21.7, P=0.028). However, the difference in cumulative live births did not reach significant (21.2 % vs 17.2 %, P =0.179). The adjusted odds ratios for TFF, cumulative pregnancy, and cumulative live birth comparing ICSI versus IVF in multivariate models were 1.65(95%CI: 1.12, 2.43), 0.65(95%CI: 0.46, 0.91), and 0.76(95%CI:0.55, 1.04) respectively.
Conclusion: In poor responders with one or two oocytes retrieved, ICSI insemination cannot avoid TFF, and it may hamper the cumulative pregnancy rate.
MIND-HOPE: Multilingual Identification of Nuanced Dimensions of HOPE
Authors: Sidorov Grigori , Balouchzahi Fazlourrahman , Ramos Luis , Gómez-Adorno Helena , Gelbukh Alexander
Published: November 2024

Hope plays a crucial role in human psychology, yet research on its expression and detection across languages is limited. This study addresses this gap by developing the first multiclass hope speech detection datasets for Spanish and German. The research includes a comprehensive review of existing datasets and techniques and employs various learning approaches—traditional machine learning, deep learning, and transformer-based models—to evaluate their effectiveness. The new datasets significantly advance hope speech detection by incorporating diverse linguistic contexts. Comparative analyses reveal that transformer models, such as xlm-roberta-base for Spanish and uklfr/gottbert-base for German, achieve superior performance with F1 scores of 0.6801 and 0.6977, respectively, in multiclass detection tasks compared to the rest of the models. Multilingual transformers are also promising in cross-lingual applications but require further refinement. This study sets the groundwork for future advancements by enhancing dataset diversity and model performance, with future research focusing on refining multilingual models and expanding to various languages.
Plasma protein increase as a chronological aging factor in healthy toy poodles
Authors: Ozaki Satoru , Honme Yoshiko , Higashi Seiichiro , Hattori Kouya , Morifuji Masashi , Mizuno Eriko , Yoshida Minoru , Ito Takashi K.
Published: November 2024

Although extensive research has examined aging markers in larger dog breeds, little is known about small breeds. This study assesses the relevance of aging biomarkers examined in larger breeds and other biological species, focusing on toy poodles (N = 40) as a model of small breeds and retrievers (N = 17) serving as a large-sized reference. Healthy individuals with no significant health declines for up to a year post-data collection were studied for age-related changes in various parameters, excluding disease factors. Our cross-sectional analysis identified significant correlations between age and increases in plasma protein concentration and amylase levels across both breeds, with breed-specific age-related declines in vaccine responses to various viruses observed only in toy poodles. Longitudinal analysis over one year confirmed a significant temporal increase in plasma protein in toy poodles, with a similar, albeit non-significant, trend in retrievers. Unlike in other species, NAD⁺ levels and fecal microbiota showed no age-related changes. Additionally, the previously reported frailty index correlated with age in retrievers but not in toy poodles. Notably, including deceased individuals during the study strengthened correlations. These results suggest plasma protein increase as a chronological aging factor in toy poodles and enhance our understanding of aging in healthy small dog breeds.
Quantitative Analysis of Medical Image Data for Improved Diagnostic Accuracy
Authors: Umukoro Emmanuel Ediri , Agbajor Godwin Kparobo , Kemefa Christian Oyinkuro , Umukoro Oghenerukevwe Fiona
Published: November 2024

Background Quantitative analysis of medical image data has become essential for improving diagnostic accuracy by reducing subjectivity and enhancing clinical decision-making. With advancements in imaging technologies such as MRI, CT, and X-rays, large volumes of medical images are now available. However, traditional qualitative assessments are prone to errors and inconsistencies due to subjective interpretation. This study investigates how quantitative metrics like precision, recall, F1 score, and area under the curve (AUC) can enhance diagnostic performance by automating and standardizing medical image analysis.
Main text This research employed a diverse dataset of 1,000 medical images, including scans from MRI, CT, and X-ray modalities. These images were stratified to cover conditions such as tumors, fractures, and internal bleeding. Advanced image processing and machine learning techniques were used to extract quantitative features, allowing us to develop robust diagnostic models. Compared to traditional methods, the quantitative analysis demonstrated improved accuracy and consistency across all modalities. MRI scans, in particular, showed the highest accuracy at 85%, indicating their superiority in precise diagnostics.
Conclusion The findings highlight the potential of quantitative analysis in medical imaging to outperform existing diagnostic methods. With statistically significant improvements across all metrics—including precision, recall, and AUC—this method offers a reliable solution to reduce diagnostic errors. Adopting quantitative analysis tools in clinical practice could lead to better patient outcomes, especially in detecting complex medical conditions.
Hitchlearning: A general free-lunch paradigm for single-image enhancement by unifying inference and training
Authors: Liu Jiaxin , Guo Yuchen , Fang Lu , Dai Qionghai
Published: November 2024

Deep learning (DL) has ushered in a suite of promising tools for image processing, including denoising (DN), deblurring (DB), and super-resolution (SR). However, traditional DL methods assume independent and identically distributed (i.i.d.) data for model training and inference, which does not hold in practice due to factors such as sample variation, variability in imaging conditions, and temporal effects in living cells. This discrepancy prevents models, even when trained on extensive datasets, from reaching their full performance potential during inference. This practical issue, unfortunately, is still unexplored. To address this issue, drawing inspiration from the way biological intelligence adapts through past experiences to shape future learning, we introduce HitchLearning—a revolutionary paradigm that breaks away from the conventional separation of training and inference. In HitchLearning, we leverage a single inference image to unsupervisedly optimize the model by aligning the training images with it. Subsequently, we employ this optimized model for processing individual inference images. This approach allows the model to adapt to the specific characteristics of each inference image, leading to improved results in a manner reminiscent of a "free lunch." We conducted a thorough evaluation of our method across three distinct tasks within both supervised and unsupervised frameworks, utilizing four diverse datasets. Compared to conventional training methods, HitchLearning demonstrated average performance increases of 4.34 dB, 4.08 dB, and 0.54 dB for the DN, DN, and SR tasks, respectively. The experimental results unequivocally demonstrate that our algorithm offers a universally applicable and cost-free optimization solution for processing image and can be used in other fields as well.
Unveiling hidden risks in healthcare from flood-induced transportation disruption
Authors: Bryant Seth , Wassmer Jonas , Schimansky Paul , Keegan Lindsay , Pregnolato Maria , Kurths Jürgen , Marwan Norbert , Merz Bruno
Published: November 2024

Despite ongoing investments in disaster resilience, flooding continues to disrupt healthcare systems directly and indirectly through transportation network failures. Existing models used for mitigation planning from such disruptions often miss critical dynamics, particularly traffic rerouting, especially at the regional and national scales needed for robust resilience planning. To address this gap, we present a generalizable and scalable method to identify healthcare facilities that are prone to overcrowding, delays in emergency response, and subsequent declines in service induced by flood-related traffic disruptions. Our method joins a regional processes-based flood model chain with a gravity-based traffic model to simulate the flow of traffic before and after flooding on a road network constructed from open-source data. By using continuous simulation flood maps at 5-meter resolution, within a framework that captures post-disruption congestion caused by traffic rerouting, we provide simulations that are both plausible and computationally feasible at the regional scale. To quantify the implications of such flood-related traffic disruptions on the health sector, we compute the change in service population due to flooding for all healthcare facilities in Germany as a proxy for health-traffic system resilience. Our findings reveal hidden risks for healthcare facilities located far from flood zones, demonstrating how traffic rerouting caused by flood-related road disruptions can lead to a loss of healthcare service. In particular, we identified 75 (of 2,475) healthcare facilities at risk of patient surges beyond their regular capacity, driven solely by flood-related traffic disruptions. Of these, a third are more than 10 kilometers from the nearest inundation, suggesting these facilities may be unaware and thus under-prepared — risks that have, until now, remained hidden from assessments. To support improved resilience planning and facilitate communication with decision-makers, we provide interactive maps of all facilities found to be at risk of capacity exceedance, along with the corresponding flood simulations. This study underscores the necessity of integrating flood hazards and transportation dynamics during resilience planning to ensure healthcare services are not interrupted. Furthermore, the method developed here can be applied to other regions to identify similar vulnerabilities, ultimately enhancing the overall disaster preparedness and response capabilities of coupled healthcare-transportation systems.
The Effect of Social Support on Maternal Functional Status and Postpartum Depression Risk in COVID-19 Pandemic
Authors: Akkuş Miray , Yağcan Hande
Published: November 2024

Background
Coronavirus infection has also negatively affected women during pregnancy, labor, and postpartum periods. In the postpartum period, mothers need social support from their environment. Existing studies show that women did not receive sufficient social support in the postpartum period before the pandemic, and their expectations were not met.
Methods
A correlational and descriptive study was conducted by online interviews with 384 mothers who gave birth in a university between March 2021 and December 2021. In data analysis, independent t-test, one-way analysis of variance, Bonferroni, Pearson correlation, simple and multiple linear regression analysis were used.
Results
The mothers’ 92.3% needed help with baby care, and 22.1% received support from their husbands during the COVID-19 pandemic. Apart from their husbands, their mothers assisted 44.5% of women, and 39.6% could not find any assistance. It was found that 82.3% of the women had a high Edinburgh Postpartum Depression Scale score. The mean total score of the Multidimensional Perceived Social Support Scale was 30.92 ± 9.22 and the Barkin Maternal Functioning Scale was 62.22 ± 10.91.
Conclusions
During the COVID-19 pandemic, it was determined that mothers were in the risky group in terms of postpartum depression, received inadequate social support, and had good maternal functional status. However, their maternal functional status decreased compared to before the pandemic. The social support was found to be effective in reducing the risk of postpartum depression and increasing maternal functioning during the COVID-19 pandemic. It was determined that the risk of postpartum depression decreased as maternal functional status increased.
Expanding LAM’s use case: A new rapid urine assay for diagnosing tuberculosis with high sensitivity in HIV-positive and -negative South African and Ugandan outpatients, including in people with sputum-scarce tuberculosis
Authors: Hamasur Beston , Okunola Anna O. , Sserubiri James , Dube-Nwamba Welile V. , Abdulgader Shima M. , Ignatowich Lech , Rasool Omid , Nabatanzi Rose , Lorente Sara Puertas , Giraldos David , Joloba Moses , Warren Robin M. , Ssengooba Willy , Theron Grant
Published: November 2024

Introduction: Non-sputum tuberculosis (TB) tests are a global priority. Next-generation urine lipoarabinomannan (LAM) diagnostics with utility beyond only people with advanced immunosuppression are urgently needed.
Methods: We performed a two-centre diagnostic accuracy study to evaluate the performance of Biopromic TB LAM assay (BP-LAM assay) and the lateral flow Determine TB LAM Ag test (LF-LAM) on stored urine from 629 adults with presumptive pulmonary TB (315 with TB, 314 without) from primary care in South Africa and Uganda. Diagnostic accuracy was assessed against an extended sputum microbiological reference standard (eMRS) and sputum induction done if people could not expectorate.
Results: BP-LAM assay had higher sensitivity than LF-LAM [95% confidence interval (CI) 63% (58, 69) vs. 22% (18, 27); p<0.001] and similar specificities [93% (90, 96) vs. 89% (85, 92)], respectively. BP-LAM assay sensitivity did not differ in HIV-positive vs. -negative people [67% (58, 76) vs. 62% (55, 69)] nor its accuracy affected by CD4 counts. The design-locked version of BP-LAM assay had improved specificity compared to its prototype-version. BP-LAM assay diagnosed TB in people who could not expectorate sputum resulting in similar diagnostic yield amongst those tested (DYT) to Xpert MTB/RIF Ultra and culture (64% vs. 61-55%) in a scenario where sputum induction was unavailable. BP-LAM assay false-negatives had, compared to true-positives, less severe disease,and more previous TB. False-positive results were, vs. true-negatives, more likely to be non-tuberculous mycobacteria (NTM)-positive [19% (4/21) vs. 4% (12/293)].
Conclusions: BP-LAM assay has higher sensitivity than LF-LAM, including in HIV-negative people. BP-LAM assay holds promise and warrants further evaluation, especially in groups where non-sputum tests are a priority.
Funding: The Global Health Technology Fund (GHIT) programs RFP-TRP-2018-001 and RFP-PD-2020-002, SAMRC (MRC-RFA-IFSP-01-2013), EDCTP2 (RIA2018D-2509, PreFIT; RIA2018D-2493, SeroSelectTB; RIA2020I-3305, CAGE-TB; TMA2020CDF-3209, RADIANT).
Forecasting field rice grain moisture content using Sentinel-2 and weather data
Authors: Brinkhoff James , Dunn Brian W. , Dunn Tina , Schultz Alex , Hart Josh
Published: November 2024

Optimizing the timing of rice paddy drainage and harvest is crucial for maximizing yield and quality. These decisions are guided by rice grain moisture content (GMC), which is typically determined by destructive sampling fields at point locations. Providing spatial forecasts of grain moisture to rice farmers will reduce the time required to gather, thresh and measure sample moistures, and will reduce errors due to samples being taken from unrepresentative areas and allow advanced planning of end-of-season drain and harvest timing. This work demonstrates consistent relationships between rice GMC and indices derived from Sentinel-2 satellite imagery, particularly those involving selected shortwave infrared and red edge bands (r=0.84, 1620 field samples, 3 years). A methodology was developed to allow forecasts of grain moisture past the latest image date to be provided, by fusing remote sensing and accumulated weather data as inputs to machine learning models. The moisture content predictions had root mean squared error between 1.6 and 2.6 % and R2 of 0.7 with forecast horizons from 0 to 28 days. Time-series grain moisture dry-down predictions were summarised per field to find the optimal harvest date (22% grain moisture), with an average RMSE around 6.5 days. The developed methodology was operationalized to provide rice growers with current and forecast grain moisture, enabling data-driven decisions, ultimately enhancing operational efficiency and crop outcomes.
A Comprehensive Analysis of the Effect of BaO Incorporation on Gamma-Ray Attenuation Characteristics in SiO₂-B₂O₃-SrO-ZrO₂ Glass Systems
Authors: kaya Selim
Published: November 2024

This work presents an analysis of the effect of BaO incorporation on the gamma-ray attenuation properties of systematically evaluated SiO₂-B₂O₃-SrO-ZrO₂ glass matrices. Radiation shielding parameters determined using XCOM and EGS4 calculation codes were compared. There was an increase in glass density from 5.84 g/cm³ to 6.32 g/cm³ when the BaO content rose from roughly 10–40%. Using sophisticated WinXCom and EGS-4 calculations, the mass attenuation values (µ/ρ) of BaO doped SiO₂-B₂O₃-SrO-ZrO₂ glass systems (abbreviated BaSiBSZ) were found. This study systematically and thoroughly evaluated the effect of BaO integration on the radiation shielding capabilities of the glass system over a wide range of gamma-ray photon energies, specifically between 59.5 keV and 1332 keV. Initially, HVL (half-value layer) and MFP (mean free path) values were derived from the calculated mass attenuation coefficients. The evaluation of several crucial shielding parameters, including RPE, Zeff, ΣR, and , came next. The steady reduction of SrO oxide concentration and substitution of BaO in BaSiSBZ glass systems resulted in notable modifications in radiation protection properties. The BaSiBSZ glass systems showed a similar decrease in both HVL and MFP at a constant energy level as the BaO doping concentration was progressively raised. Concurrently, a notable enhancement was noted in RPE, Zeff, ΣR, and coefficients. The results demonstrate that higher BaO concentrations greatly enhance the material's radiation-shielding capabilities, enhancing both photon and neutron attenuation and bolstering the overall performance of the glass system.
Mapping Policy Priorities Across Diverse Stakeholder Groups in the Swiss Energy and Climate Subsystems
Authors: Zhang Meixi , Patt Anthony , Kober Tom , Panos Evangelos
Published: November 2024

The transition to decarbonized energy systems requires addressing diverse stakeholder interests. This study examines priorities and coalitions among Swiss stakeholders in energy and climate policies, by applying topic modeling based on Latent Dirichlet Allocation, a Natural Language Processing method, on 463 position papers submitted during revisions of the Swiss Energy Law 2020 and CO2 Act 2021. The analysis highlights key policy trade-offs to balance, such as those between renewable energy expansion and biodiversity, landscape and historic building preservation. Three main coalitions were identified for energy policy— environmental advocates, base-load security proponents, and subsidy focused stakeholders. At the same time, five coalitions emerge for climate policy — those interested in fossil-fuel heating replacement, international standards alignment, heritage site preservation, clean fuels, and agriculture’s role in decarbonization. This research provides insights into effective and inclusive policy-making by applying topic modeling to identify distinct policy priorities from a broad spectrum of stakeholders beyond the conventional ones, offering a practical alternative to traditional qualitative methods.
Initial management of ballistic trauma: feedback through observational study of 32 Cases
Authors: khallikane said , Mehdi Didi , Monsef ELabdi , Seddiki Rachid
Published: November 2024

Ballistic trauma poses significant challenges in trauma care due to the diverse clinical presentations and severity of injuries caused by projectiles such as bullets, birdshot, or explosive fragments. We conducted a retrospective study over two years at Hassan II Laayoune military hospital to analyze the circumstances, injury profiles, and management outcomes of ballistic trauma patients. The study involved 32 patients, all male, predominantly aged between 31-40 years. Most patients (62.5%) were stable hemodynamically and respiratorily upon admission, with half of them sustaining limb injuries. The overall recovery was favorable in 62.5% of cases, while mortality stood at 37.5% (12 out of 32 cases). Effective management strategies are crucial in improving outcomes for ballistic trauma patients. Early assessment of injury severity guides appropriate prehospital interventions and directs patients to specialized care facilities promptly, reducing the need for later inter-hospital transfers. The "Golden Hour" principle underscores the urgency of rapid transfer to definitive care centers, prioritizing immediate hemorrhage control over prolonged prehospital procedures. Small Volume Resuscitation advocates for hypertonic solutions to maintain targeted blood pressure levels, minimizing fluid volumes to prevent clotting issues. Permissive Hypotension recommends controlled low blood pressure until definitive hemostasis is achieved, avoiding excessive fluid administration that could worsen bleeding. Understanding ballistic injury mechanisms, including temporary cavitation and specific wound characteristics, informs tailored trauma care protocols. Prehospital strategies like "scoop and run" versus "stay and play" aim to balance swift transportation with on-scene stabilization efforts. Techniques such as tourniquet application and early medical interventions are critical in reducing mortality rates associated with severe trauma, emphasizing the importance of timely and effective trauma care practices.
How the functioning mechanisms and the economic and financial incentives of the U.S. renewable electricity market sustain wind energy adoption
Authors: BETTANTI ALBERTO , LEONARDI STEFANO , AGOSTI FILIPPO
Published: November 2024

This paper critically examines the challenges of wind energy adoption in the U.S. electricity market. It focuses on how the U.S. renewable electricity market supports wind energy through its mechanisms and economic and financial standards, as well as incentives and metrics for evaluating wind projects. Using a systematic literature review (SLR) methodology, this study offers a critical analysis of existing academic and technical literature to reveal the complexities and opportunities in the U.S. energy landscape. The findings emphasize the role of policy-based, market-based, and contract-based incentives in reducing the levelized cost of energy (LCOE) and marginal LCOE (mLCOE) for wind power, which in turn lowers overall electricity prices and promotes wind energy adoption. However, the complexity of deploying these incentives, the intricacies of LCOE evaluations, and the challenges of grid integration hinder the broader transition to renewable energy, especially wind energy. This article contributes to academics, investors, and policymakers by providing a holistic view of the U.S. wind energy market's functioning mechanisms, presenting refined strategic guidance to promote further wind energy adoption.
RUNX3 is a Potential Marker for Vaso-Occlusive Crises by a Whole Blood Transcriptomic Analysis in Sickle Cell Disease
Authors: Taha Safa , Abdulwahab Hawra , aljishi Muna , Sultan Ameera , Bakheit Moiz , Belhocine Mohamed
Published: November 2024

Sickle cell disease is the commonest hemoglobinopathy which results from a mutation in the β-globin gene of hemoglobin and predisposes to painful Vaso-occlusive crisis (VOC) and multi-organ dysfunctions. The huge phenotypical variation makes it challenging to define and predict the disease severity and outcomes. This study aimed to characterize the whole blood gene expression profile using Microarray technology in Bahraini patients with sickle cell disease determining the differentially expressed genes in steady-state (n=10) and during VOC (n=10) in comparison to healthy controls (n=8). The analysis identified 2073 and 3363 genes that were dysregulated during steady-state and VOC, respectively, compared to healthy controls. Additionally, 1078 genes were differentially expressed during VOC compared to steady state. The GO terms enrichment analysis revealed significant deregulation in terms related to immune and hematopoietic regulation, with downregulation in pathways critical for immune modulation and hematopoietic balance; one of the interesting genes identified among the 668 down-regulated genes was RUNX3. The RUNX3 gene was four folds down-regulated in microarray, three-fold in polymerase chain reaction, and a mean protein concentration of 11.13 pg/ml was observed in enzyme-linked immunosorbent assay during VOC compared to steady-state (457.93 pg/ml) (p<0.01). In conclusion, the RUNX3 gene plays a role in immune cell differentiation and inflammation predisposing to tissue inflammation and injury. It may serve as a potential biomarker for VOC, and future large-scale validation and proteomic assessments are recommended.
Uniform generation of graphs and non-linear preferential attachment
Authors:   , Allendorf Daniel
Published: November 2024

Entities and the connections between them are prevalent in all facets of our reality. Commonly, we refer to such structures as networks, or in mathematical terminology, as graphs. It follows that the sciences --- by their nature concerned with the study of reality --- should be concerned with the study of networks as well, and indeed, networks play important roles in such diverse areas as mathematics, computer science, physics, biology and the social sciences. Recently, this widespread emergence of networks has given rise to the interdisciplinary field of network science, which is both concerned with the development of mathematical and computational methods to study networks, as well as the application of those methods in particular areas. One of the most important tools in this context are models of networks, and algorithms which generate random instances of those models. Oftentimes, these networks models imply a complex structure and maximum entropy or uniform distribution. As a consequence, the development of algorithms which efficiently generate random networks from such models presents a challenging problem and interesting object of study in its own right. In this thesis, we present several novel results on the efficient generation of complex networks. The network models we address roughly fall into two categories. The first category is uniform graphs with given degrees. Here, we describe efficient algorithms for generating networks with a power-law degree distribution, temporal networks, in which the connections between entities are augmented with presence times, and approximatively uniform but highly efficient parallel Markov chains. The second category are preferential attachment models, and in particular, generalizations of these models to non-linear attachment kernels. Finally, we develop new efficient methods for maintaining discrete probability distributions, which is a common subroutine in network generation and simulation.