bluuebunny/crossref_metadata_2025_split huggingface dataset:
Feasibility and efficacy of pre-sleep dim light therapy for adults with insomnia: A pilot randomized, open-label, two-arm study
Authors: Yoon Jihyun , Heo Seok-Jae , Lee Hyangkyu , Sul Eun Gyeong , Han Taehwa , Kwon Yu-Jin 
Published: December 2023

Abstract
This study assesses the effectiveness of pre-sleep dim light therapy (LT) as a non-pharmacological intervention for insomnia in adults, focusing on its impact on sleep quality and circadian rhythms. Conducted over two weeks, the randomized trial involved 40 adults with sleep disorders. Participants were divided into a control group and an LT group, the latter receiving warm-colored light exposure before bedtime. The methodology combined subjective sleep questionnaires, objective sleep assessments through actigraphy, and molecular analyses of circadian clock gene expression in blood cells. Key results indicated significant improvements in the LT group’s sleep quality and efficiency, and a 30-minute advancement in Dim Light Melatonin Onset compared to the control group. Molecular analysis revealed a notable reduction in CRY1 gene expression, implicating LT’s influence on circadian sleep regulation. While the study’s small sample size and short duration limit its scope, the findings suggest LT’s potential as an effective, non-drug approach for insomnia treatment. The study advocates for expanded research with larger, more diverse cohorts over longer periods to further validate LT’s efficacy in sleep medicine.
Incidence and Impact of Adverse Childhood Experiences in the Neonatal Intensive Care Unit
Authors: Sacotte Kaitlyn , Torr Carrie 
Published: December 2023

Abstract
Objective
The objective of this study is to determine the incidence of documented ACEs for infants admitted to a neonatal intensive care unit (NICU) and assess for an association between neonatal ACEs and adverse outcomes.
Study Design:
A retrospective chart review was performed on all infants admitted to a Level III NICU for 6 months. Neonatal and maternal charts were reviewed for five ACEs: intimate partner violence, parental mental illness, incarceration, separation, and substance use.
Result
Data was collected for 203 infants. One or more ACEs were documented in 118 (58%) of infants and 3 or more ACEs in 12 (6%) of infants. Paternal mental illness was documented in only 1% (2) of infants.
Conclusion
The true incidence of neonatal ACEs remains unknown as most paternal data is not documented in the infant’s chart. There is an increased need to screen and document ACEs in infants admitted to the NICU to better understand the impact in this at risk population.
D-Pinitol extends antioxidant activity and longevity of Caenorhabditis elegans via insulin-like signaling pathway
Authors: Shi Lin , Liu Jin-Feng , Yu Xin-Tian , Leng Yan-En , Hou Yi , Quan Tian , Zeng Yue 
Published: December 2023

Abstract
D-Pinitol is a cyclic polyol mainly derived from pinaceae and legume. It has the functions of regulating blood glucose balance, anti-inflammation and cardiovascular protection. D-Pinitol is a 3-methoxy analogue of D-chiral-inositol. In our previous study, we found that D-chiral-inositol could prolong the lifespan of Caenorcaditis elegans. D-Pinitol and D-chiral-inositol are commonly used in the treatment of diabetes and polycystic ovary syndrome. We therefore proceeded to investigate the anti-aging effect of D-Pinitol in Caenorhabditis elegans. Our findings demonstrate that D-Pinitol significantly extends the lifespan of Caenorhabditis elegans by 25.41%, enhances body bend frequency, and reduces lipofuscin accumulation. Moreover, it effectively delays neurodegenerative disease development in this model organism. Mechanistically, D-Pinitol promotes gene expression related to insulin-like signaling pathway in Caenorhabditis elegans while also reducing malondialdehyde levels and increasing total antioxidant capacity as well as superoxide dismutase and catalase activities. Consequently, our results indicate that through activation of the insulin-like signaling pathway, D-Pinitol improves both antioxidant capacity and lifespan in Caenorhabditis elegans—a testament to its remarkable antioxidative properties—thus highlighting the significance for further research on this compound.
Identification of mitochondria-related biomarkers in childhood allergic asthma
Authors: Zhao Wei , Fang Hongjuan , Wang Tao , Yao Chao 
Published: December 2023

Abstract
Background
The mechanism of mitochondria-related genes (MRGs) in childhood allergic asthma (CAS) was unclear. The aim of this study was to find new biomarkers related to MRGs in CAS.
Methods
This research utilized two CAS-related datasets (GSE40888 and GSE40732) and extracted 40 MRGs from the MitoCarta3.0 Database. Initially, differential expression analysis was performed on CAS and control samples in the GSE40888 dataset to obtain the differentially expressed genes (DEGs). Differentially expressed MRGs (DE-MRGs) were obtained by overlapping the DEGs and MRGs. Protein protein interactions (PPI) network of DE-MRGs was created and the top 10 genes in the degree ranking of Maximal Clique Centrality (MCC) algorithm were defined as feature genes. Hub genes were obtained from the intersection genes from the Least absolute shrinkage and selection operator (LASSO) and EXtreme Gradient Boosting (XGBoost) algorithms. Additionally, the expression validation was conducted, functional enrichment analysis, immune infiltration analysis were finished, and transcription factors (TFs)-miRNA-mRNA regulatory network was constructed.
Results
A total of 1505 DEGs were obtained from the GSE40888, and 44 DE-MRGs were obtained. A PPI network based on these 44 DE-MRGs was created and revealed strong interactions between ADCK5 and MFN1, BNIP3 and NBR1. Four hub genes (NDUFAF7, MTIF3, MRPS26, and NDUFAF1) were obtained by taking the intersection of genes from the LASSO and XGBoost algorithms based on 10 signature genes which obtained from PPI. In addition, hub genes-based alignment diagram showed good diagnostic performance. The results of Gene Set Enrichment Analysis (GSEA) suggested that hub genes were closely related to mismatch repair. The B cells naive cells were significantly expressed between CAS and control groups, and MTIF3 was most strongly negatively correlated with B cells naive. In addition, the expression of MTIF3 and MRPS26 may have influenced the inflammatory response in CAS patients by affecting mitochondria-related functions. The quantitative real-time polymerase chain reaction (qRT‒PCR) results showed that four hub genes were all down-regulated in the CAS samples.
Conclusion
NDUFAF7, MTIF3, MRPS26, and NDUFAF1 were identified as an MRGs-related biomarkers in CAS, which provides some reference for further research on CAS.
Design of Efficient Binary Multiplier Architecture using Hybrid Compressor with FPGA implementation
Authors: Thamizharasan V , Parthipan V 
Published: December 2023

Abstract
In emerging digital world, the high-performance arithmetic computing module with low power and reduced area are required to compute the Signal processing application operations. In that signal processing applications, the multipliers are essential component of arithmetic functional units in many applications, like digital signal processors, image/video processing, Machine Learning, Cryptography and arithmetic & logical units (ALU). In recent years, Profuse multipliers are there. In that, Vedic multiplier is one of the high-performance multiplication and it used to signal/image processing applications. In order to ameliorate the performance of this multiplier further, by proposed a novel multiplier using hybrid compressor for application of Cryptography and signal processing system. The proposed hybrid compressor-based multiplier is designed and implemented in FPGA (spartan 6). The synthesis result shows that the speed of proposed hybrid compressor-based multiplier gets improved as compared to Array multiplier (35.83%), Wallace tree multiplier (34.58%), Vedic Multiplier based on CLA (28.49%), Vedic Multiplier based on RCA (20.65%), Booth Multiplication (21.65%) and Vedic Multiplication based on HCA (20.10%) and Hybrid multiplier using CSELA (17.81%) and Hybrid Vedic Multiplier (7.15%).
Study on the hysteresis performance of X-type round steel pipe stiffening rib coherent node based on microscopic fracture model
Authors: Wang Jiaxing , Yang Yong 
Published: December 2023

Abstract
The cyclic cavity expansion model (CVGM model) is programmed into the VUSDFLD subroutine of ABAQUS software using the Frotran language to simulate the N-type circular steel tubular joints. Compared with the experimental results, it is found that the finite element simulation is in good agreement with the experimental results, which verifies the feasibility of using the CVGM model to predict the plane circular steel tubular joints. 14 X-type circular steel tubular joints and stiffener-reinforced X-type circular steel tubular joints were designed, The CVGM model was used to predict the fracture of these 14 joints, and the hysteretic behavior of the joints was studied. The results show that when the node is cracked, it is not destroyed immediately, and the node bearing capacity can continue to improve, at which time the hysteretic performance of the node is controlled by the degree of crack extension; The stiffening ribs can improve the ultimate bearing capacity, stiffness, ductility, and energy dissipation capacity of X-type round steel pipe coherent nodes so that the rate of node stiffness degradation is reduced and the seismic performance of the nodes is improved. An increase in the diameter-to-thickness ratio γ of the nodal main tube increases the ultimate load-carrying capacity, stiffness, ductility, and energy dissipation capacity of the coherent nodes of the stiffened rib-reinforced X-type circular steel tube but has a smaller effect on the rate of stiffness degradation; Node branch pipe and main pipe outer diameter ratio β increases, stiffening rib reinforced X-type round steel pipe coherent node of the ultimate bearing capacity, stiffness will increase, but the node ductility and energy dissipation capacity will be reduced, stiffness degradation of the speed of acceleration; Stiffening rib length L increases, the ultimate load carrying capacity, stiffness, ductility, and energy dissipation capacity of the coherent node of X-type round steel pipe reinforced by stiffening ribs will be increased, and the rate of node stiffness degradation will be less affected; The thickness of the stiffening rib tp increase, the ultimate bearing capacity, stiffness, ductility, and energy dissipation capacity of the coherent node of the stiffening rib reinforced X-type round steel pipe will increase, and the effect on the node stiffness degradation rate is small.
UISS-Net:Underwater Image Semantic Segmentation Network for Improving Boundary Segmentation Accuracy of Underwater Images
Authors: he zhiqian , Cao Lijie , Luo Jialu , Xu Xiaoqing , Tang Jiayi , Xu Jianhao , Xu Gengyan 
Published: December 2023

Abstract
Image semantic segmentation t is widely used in aquatic product measurement, aquatic biological cell segmentation, and aquatic biological classifications. However, underwater image segmentation has low accuracy and poor robustness because of turbid underwater environments and insufficient light. Therefore, this paper proposes an Underwater Image Semantic Segmentation Network (UISS-Net) for underwater scenes. Firstly, the backbone network uses an auxiliary feature extraction network to improve the extraction of semantic features for the backbone network. Secondly, the channel attention mechanism enhances the vital attention information during feature fusion. Then, multi-stage feature input up-sampling is used to recover better semantic features in the network during up-sampling. Finally, the cross-entropy loss function and dice loss function are used to focus on the boundary semantic information of the target. The experimental results show that the network effectively improves the boundary of the target object after segmentation, avoids aliasing with other classes of pixels, improves the segmentation accuracy of the target boundary, and retains more feature information. The mIoU and mPA of UISS-Net in the semantic Segmentation of Underwater IMagery (SUIM) dataset achieve 72.09% and 80.37%, respectively, 9.68% and 7.63% higher than the baseline model. In the Deep Fish dataset, UISS-Net achieved 95.05% mIoU, 12.3% higher than the baseline model.
Potential mechanisms for predicting comorbidity between multiple myeloma and femoral head necrosis based on multiple bioinformatics
Authors: Li Jie , Dong Jing , Li Ming , Zhu Hongbo , Xin Peicheng 
Published: December 2023

Abstract
Objective: To explore Multiple myeloma (MM) through multiple bioinformatics analysis
The potential mechanism of comorbidity with Osteonecrosis of the femoral head (ONFH).
Method:According to the inclusion criteria, download the MM and ONFH high-throughput chip datasets from the GEO database and preprocess them separately. Using weighted gene co expression network analysis (WGCNA) to construct co expression networks on MM self datasets, further screening modules and genes related to MM clinical characteristics, enriching and analyzing potential co disease genes of NAFLD and IS, and preliminarily screening key genes for MM and ONFH co disease through Cytoscape. Validate the ability of gene expression and performance evaluation through two disease related datasets. And evaluate the relationship between the difference and consistency of the two in the immune microenvironment.
Results: Through screening 418 co pathogenic genes with immunity, we found that the biological process of the two kinds of diseases in the ribosome synthesis process was consistent, especially the protein synthesis. Further screening key genes through PPI, and analyzing the dataset of the validation queue, the average area (ROC) of the 5 genes under the operating characteristics of the subjects was between 0.8 and above. Comparing the analysis of the two groups of data in the immune microenvironment, it is found that the infiltration of plasma cell is consistent with the comorbidity of diseases, and it can be used as the relevant immune target for subsequent targeting.
Conclusion: MM and ONFH share common pathogenic genes, which in turn mediate differential changes in related signaling channels and immune cells, affecting the high incidence of OA and MDS and the phenomenon of these two diseases. In terms of biological mechanism, MM and ONFH co disease may be mainly associated with RPS19, RPL35, RPL24, RPL36, EIF3G as key genes, as well as plasma cell as key immune infiltration, which can serve as the central mechanism for the development of the two diseases. This study provides ideas and references for further research.
Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation
Authors: Wu Ziyang , Qiao Yong , Yan Gaoliang , Qin Yuhan , Tang Huihong , Liu Shiqi , Wang Dong , Tang Chengchun 
Published: December 2023

Abstract

Background
This study developed two nomograms to predict the incidence of acute heart failure (AHF) in patients of atrial fibrillation (AF) and evaluated the predictive value of the nomograms.
Methods
18179 patients of AF from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were randomly divided into two groups in a seven-to-three ratio to form a training cohort (n = 12725) and a validation cohort (n = 5454). Least absolute shrinkage and selection operator (LASSO) regression analyses were used to identify associated risk variables. Two nomograms were established. The new models were assessed in terms of the concordance index (C-index), the area under the curve (AUC) of receiver operating characteristic (ROC) analysis, calibration curve, and decision curve analysis (DCA).
Results
Least absolute shrinkage and selection operator (LASSO) regression analysis identified seven potential predictors of acute heart failure in nomogram 1 and three potential predictors in nomogram 2. Multivariate logistic regression analysis was used to evaluate the effects of these predictors and create final models. The concordance index values were 0.768 and 0.696, respectively. The areas under the curves for the training and validation sets in nomogram 1 were 0.768 and 0.763, respectively. The areas under the curves for the training and validation sets in nomogram 2 were 0.696 and 0.692, respectively.
Conclusion
Seven variables were identified as predictors in nomogram 1 and three variables were identified in nomogram 2. Our nomograms are reliable convenient approaches for predicting acute heart failure in patients with atrial fibrillation.
Inversion of shallow water depth from GF-6 multispectral remote sensing image
Authors: Zhang Yunling , Hou Yun , Cui Yuping , Xu Yibin , Chen Muyin , Wang Jiaqi , Shen Wei 
Published: December 2023

Abstract
Aiming at the shallow water depth which is difficult to be measured by traditional ship-borne acoustics, this paper establishes four machine learning models, namely Random forest (RF) model, Gradient Boosting Decision Tree(GBDT) model, extreme gradient boos(XGBoost) model and Support Vector Regression(SVR) model, by using the domestic GaoFen-6 hyperspectral remote sensing image and the measured water depth, carries out the water depth inversion research in the experimental area, and compares and analyzes the inversion accuracy. The experimental results show that the stochastic forest water depth inversion model has the highest accuracy and efficiency, which is superior to the other three models. In this paper, the ability of shallow water depth detection by multi-spectral data of domestic GaoFen-6 satellite is demonstrated, and its research methods, ideas, inversion models and other results have important reference significance for other multi-spectral image water depth inversion research.
Molecular Inspection of Avian Influenza HA1 Gene through Protein Homology Modeling and Prediction of Antibody-Binding Epitopes
Authors: Ali Norhan M . , Elsayed Eman , Fawzy Mohamed , Mohamed Maarouf , Eltarabilli Mokhtar 
Published: December 2023

Abstract

The study analyzed avian influenza in seven bird species including wild and Domestic birds: Eurasian Coot, Eurasian Teal, Common Moorhen, Northern Pintail, Tufted Duck, domestic duck and domestic chickens - by collecting tissue samples from dead birds, and nasal and cloaca swabs from some living birds ducks and local domestic chickens. This comprehensive approach respected the birds' well-being while providing valuable insights into the virus's prevalence. Highly contagious avian influenza virus (AIV) threatens Egypt's poultry industry, prompting a deep dive into its molecular and epidemiological landscape. Focusing on H5 and H9 subtypes in both domestic and wild birds across five provinces, researchers uncovered a diverse array of circulating strains. H5N8 AIV detected in 4 flocks, mixed H5N1 AIV and NDV infections in 3, and H9N2 AIV in 22. One flock harbored both H9N2 and H5N1, raising concerns about co-circulation and reassortment. Vaccine mismatch, Genetic analysis revealed significant divergence between circulating strains and commercially used vaccines, particularly for H5N8 and H9N2, suggesting potential ineffectiveness. Predicted antibody-binding epitopes further corroborated this, showing higher similarity to a specific older vaccinal strain than currently used ones. A critical gap exists between vaccines and circulating AIV strains in Egypt. Updated vaccines based on prevalent viruses are urgently needed. This study highlights the importance of integrating molecular and epidemiological approaches for developing informed vaccine strategies and improving avian influenza control.
Quantifying stress corrosion cracking performance of additively manufactured aluminum alloys via micro digital image correlation
Authors: Raghavan Seetha , Esteves Remelisa , Ghosh Ranajay 
Published: December 2023

Abstract
Additive manufacturing (AM) has the capability to efficiently produce complex parts while saving manufacturing time and costs in industry. However, the AM process can also introduce defects within printed parts, which negatively impacts their performance during service life. Defects can reduce corrosion resistance in AM alloys. AlSi10Mg is a commercially available material for automotive and aerospace applications that is produced via powder bed fusion (PBF). While its mechanical behavior and characteristics have been studied extensively, there are contradictory conclusions on how the PBF process affects its corrosion perfor- mance. Consequently, its behavior under stress corrosion cracking (SCC) is not well understood. It was demonstrated in this work that AlSi10Mg had better SCC performance than its counterpart standard manufactured alloy, AA6061-T6. It was found that PBF AlSi10Mg experienced crack initiation 126 minutes later and withstood failure 18 minutes beyond its counterpart AA6061-T6. At failure, PBF AlSi10Mg experienced three times less strain. This work presents a unique capa- bility of correlating SCC performance in AM alloys to SCC initiation captured via micro digital image correlation (DIC). The results provide useful informa- tion on how AM alloys behave under SCC as a function of time and strain. This information can aid in improving or developing new AM processes for producing reliable and corrosion-resistant alloys.
Classification of Sugar Content of Kiwi Fruit Based on Deep Learning and Near Infrared Spectrum
Authors: Liu Tingting , Zuliang Wang , Ting Zhang , Bingwan Shang , Wenshun Tang , Fengkang Qiao , Yanan Xue , Zhipeng Li , Liu Feifan 
Published: December 2023

Abstract
In recent years, the kiwifruit industry has undergone rapid development. The quality of kiwifruit significantly impacts its market price. The current manual grading system for kiwifruit is inefficient and lacks accuracy. Therefore, the application of intelligent methods for the rapid classification of kiwifruit has become a prominent topic in kiwifruit research. Sugar content is a critical factor in evaluating kiwifruit quality. This study establishes a non-destructive detection and classification model for sugar content using near-infrared spectroscopy and deep learning techniques. Initially, near-infrared spectra and sugar content values of kiwifruit were gathered. Following the classification of kiwifruit samples based on sugar content standards, two preprocessing methods – MSC and SNV – along with four deep learning network structures – LeNet, AlexNet, VGG, and ResNet – were utilized to construct classification models for the spectra and sugar content. Through comparison of training set accuracy, test set accuracy, and confusion matrix of the test set, the combination of MSC preprocessing and the ResNet classification model was identified as the optimal approach, achieving a test set accuracy of 100%. These findings indicate that the classification model established using near-infrared spectrum and deep learning effectively promotes kiwifruit classification based on sugar content.