bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing Half Precision Winograd Convolutions on Multi-Core Vector Processors
Authors: Xu Jinwei , Jiang Jingfei , Li Yalin , Su Huayou , Yang Xi , Gao Lei 
Published: July 2024

Abstract

Winograd-based algorithm is currently one of the optimization methods in convo-lutional computation. It can effectively reduce the number of multiplications and computational complexity. This paper proposes a Winograd-based convolution accuracy compensation method for low precision vector processor based on the architecture of low precision multi-core vector processors. And The we implement a multi-level parallel optimization scheme for Winograd-based convolution on the multi-core vector processor. The proposed low precision compensation scheme for Winograd-based convolution can effectively improve the adverse effects of accuracy loss caused by Winograd-based convolution on low precision platforms. The implemented parallel optimization scheme develops parallelism from different dimensions, and effectively improves computational performance. The experimental results show that the proposed parallel optimization method achieves a performance acceleration of 26.81 ∼ 131.18 times compared with the fast con-volution implementation in NNPACK. Compared with direct convolution on the same platform, it can achieve an acceleration ratio of 1.18 ∼ 3.28 times.
Smart Driver Assistance: Real-Time Drowsiness Detection Leveraging Facial Cues with MediaPipe and OpenCV
Authors: Reddy Ariveeti Karthikeya , Khan Ibrahim Ahmed , T Neethu C , Thampi Lidiya Lilly , A Aswathy M , Kumar Abhishek , Kumar Sunny 
Published: July 2024

Abstract

The primary aim of this research is to identify driver drowsiness to prevent car accidents and improve road safety. This study explores and proposes potential solutions to mitigate drowsiness-related accidents and enhance overall road security by monitoring the driver's eye, mouth, and head movements, which are key indicators of drowsiness. An algorithm has been developed to track these movements. The study involves analyzing CNN models and computer vision models for eye detection, yawn detection, and head movement, with the objective of identifying the most effective approach among the models. For building CNN models, we use the MRL Eye Dataset and YawDD datasets for eye and mouth tracking. The performance of the models developed using these datasets will be assessed based on various metrics such as accuracy and loss. We achieved an accuracy of 84.53\% using the CNN approach for the MRL Eye Dataset, while for the YawDD Dataset, we obtained an accuracy of 96.42\%. Despite these impressive results, CNN techniques encounter several challenges, including poor performance in low light conditions, varying outcomes for different ethnicities, and unreliability in dynamic environments. To address these challenges, we utilize Dlib and MediaPipe for tracking facial landmarks. By leveraging these techniques, we can simultaneously monitor head movement, eye movements, and detect yawns. Between Dlib and MediaPipe, we prefer MediaPipe due to its capability to detect the 3D coordinates of key points.
Characteristics of Anopheles gambiae s.l larval breeding sites and spatiotemporal analysis of malaria transmission risk in Djilakh, a hotspot village in central Senegal
Authors: Ndiaye Assane , Morlighem Camille , Diène Aminata Niang , Kane Moussa , Diallo Abdoulaye , Tahirou Fassiath , Nourdine Mohamed Abderemane , Sarr Pape Cheikh , Konaté Lassana , Faye Ousmane , Gaye Oumar , Niang El Hadji Amadou , Linard Catherine , Sy Ousmane 
Published: July 2024

Abstract

Background:
The progress made in the fight against malaria has resulted in a reduction of the burden in Senegal on a national scale. Transmission levels tend to be low overall, but there is considerable spatial heterogeneity, which necessitates the identification of the factors responsible for regional or local disparities in order to accelerate the elimination process. The objective of this study is to demonstrate the impact of the functionality of larval breeding sites on the evolution of malaria risk in Djilakh, a hotspot village beloging to Mbour health district in central Senegal.
Methods
This study cover the period from 2013 to 2017. Cartographic and biological data collection occurred during the rainy season (June-November), with three outings per year. Only malaria cases confirmed by RDT (rapid diagnostic test) were considered. Rainfall data were gathered at the synoptic station of the Mbour department. To assess the impact of larval breeding sites on malaria transmission, logistic regression and Poisson models were employed. Some data were analysed using Excel, with cumulative means and frequencies calculated. The QGIS Desktop 2.2.0 mapping software was used to create the maps.
Results
The results of this study demonstrate that the deposits explored in this village correspond to natural temporary ponds, characterised by clayey and clayey-sandy soils. A review of data on meteorology and malaria morbidity indicates that malaria transmission is influenced by precipitation. The correlation between malaria morbidity and breeding site positivity varied throughout the rainy season, depending on the size and stability of breeding sites. Additionally, the results indicate that the type of land use and its spatial distribution play an important role in estimating the risk of malaria transmission in the village. The incidence of malaria cases is significantly higher in hamlets situated in close proximity to larval breeding sites, exhibiting a gradual decline with increasing distance from these hamlets.
Conclusions
The findings of this study represent a preliminary step towards a more comprehensive understanding of the environmental factors influencing the persistence of residual malaria transmission in Senegalese hotspot villages, despite the deployment of various vector control measures. The results of this study indicate a need for targeted control actions in identified risk areas in order to better control the malaria endemic.
Correlating p53 immunostaining patterns with somatic TP53 mutation and functional properties of mutant p53 in triple-negative breast cancer
Authors: Kang Jun , Kim Meejeong , Lee Miseon , Lee Ahwon , Choi Byung-Ock , Park Woo-Chan , Kim Sung Hun , Lee Jieun 
Published: July 2024

Abstract

Immunohistochemical (IHC) staining pattern of p53 has been recognized as a potential surrogate marker for TP53 mutations across diverse cancer types. Nevertheless, interpretative criteria for p53 IHC expression as a predictive tool for TP53 mutation in triple-negative breast cancer (TNBC) have not been established yet. A total of 113 TNBC cases were analyzed for p53 IHC pattern and somatic TP53 mutation using whole exome sequencing. Functional properties of TP53 mutations were determined using the National Cancer Institute (NCI) TP53 database. P53 IHC staining patterns fell into three distinct categories: nuclear overexpression (n = 58), absence of staining indicating null pattern (n = 40), and wild-type expression (n = 15). The cutoff for predictive p53 nuclear overexpression was determined to be 80%. This threshold correlated strongly with TP53 mutations. Notably, nuclear overexpression had a positive predictive value (PPV) of 83% for missense or in-frame mutations, while the null pattern showed a PPV of 85% for detecting nonsense, frameshift, or splicing mutations. Furthermore, p53 overexpression was significantly linked to missense mutations within the DNA-binding domain (DBD) exhibiting gain-of-functon(GOF) or dominant-negative effect (DNE). Cases exhibiting both nuclear overexpression and cytoplasmic expression (n = 5) were correlated with nonsense or frameshift mutations affecting the DBD, NLS, or splice sites. Subclonal p53 staining patterns observed in 7 cases were found to be associated with TP53 mutations. Our study proposes newly defined criteria for interpreting p53 immunostaining patterns in TNBC, potentially allowing for the prediction of TP53 mutation types and their functional implications.
Using shock index, pediatric age adjusted (SIPA) to predict prolonged length of stay in perforated appendicitis
Authors: Barone-Camp Alexandra , Louiselle Amanda , Bothwell Samantha , Diaz-Miron Jose , Hills-Dunlap Jonathan , Gosain Ankush , Blakely Martin , Acker Shannon 
Published: July 2024

Abstract

Purpose
Hospital length of stay (LOS) following admission for appendicitis is difficult to predict. Shock index, pediatric age adjusted (SIPA) accurately identifies severely injured trauma patients and predicts mortality among children admitted to the ICU. Our aim was to determine if elevated SIPA at presentation, and time to normalization of SIPA, can identify children with perforated appendicitis and predict hospital LOS.
Methods
This was a retrospective cohort study of children 1–17 years admitted to a quaternary care referral center with appendicitis after appendectomy in 2021. The primary outcomes were presence of perforated appendicitis and hospital LOS. Generalized linear regressions were performed. Covariates included in all models were age, sex, fecalith, initial temperature, and time from diagnosis to OR.
Results
We included 169 patients; 53 (31.4%) had perforated appendicitis. After adjustment, elevated SIPA was associated with presence of perforated appendicitis (p = 0.0002) and longer LOS (p < 0.0001). A patient presenting with appendicitis and elevated SIPA had 5.447 times higher odds of having perforated appendicitis (95% CI: 2.262, 13.826), a mean hospital LOS 2.047 times longer (95% CI: 1.564, 2.683), a mean time to toleration of regular diet 4.995 times longer (95% CI: 2.914, 8.918), and a mean duration of antibiotics that is 1.761 times longer (95% CI: 1.383, 2.243) than a patient with normal SIPA.
Conclusion
In children with appendicitis, elevated SIPA at presentation is associated with higher risk of perforation. These findings support the incorporation of SIPA during triage of patients with appendicitis and counseling families after surgery.
A Deep Learning-Based Pipeline for Segmenting the Cerebral Cortex Laminar Structure in Histology Images
Authors: Wang Jiaxuan , Gong Rui , Heidari Shahrokh , Rogers Mitchell , Tani Toshiki , Abe Hiroshi , Ichinohe Noritaka , Woodward Alexander , Delmas Patrice J. 
Published: July 2024

Abstract

Characterizing the anatomical structure and connectivity between cortical regions is a critical step towards understanding the information processing properties of the brain and will help provide insight into the nature of neurological disorders. A key feature of the mammalian cerebral cortex is its laminar structure, with the neocortex differentiated into up to six layers. Identifying these layers in neuroimaging data is important for providing a foundation for understanding the axonal projection patterns of neurons in the brain. These patterns can be seen in experiments using anterograde tracer or are reflected in the brain activity seen in layer-fMRI, etc. We studied Nissl-stained histological slice images of the brain of the common marmoset (Callithrix jacchus), which is a new world monkey that is becoming increasingly popular in the neuroscience community as an object of study. We present a novel computational framework that first acquired the cortical labels using AI-based tools followed by a trained deep learning model to segment cerebral cortical layers. We cross-tested and compared our pipeline with the existing advanced pipeline.
Diastereomers of the anticancer peptide CIGB-300 with altered b-turn structures
Authors: Moya Celia Gonzalez , Rodriguez Rafael , Martínez Carlos S. Perez , Garay Hilda , Wiesent Julian , Gröger Stefan , Masforrol Yordanka , Perera Yasser , Perea Silvio E. , Balbach Jochen 
Published: July 2024

Abstract

The next-generation anti-tumor drug peptide CIGB-300, developed by the Center for Genetic Engineering and Biotechnology (CIGB), targets casein kinase 2 (CK2) and its substrates, implicating significant therapeutic potential in cancer treatment. A key focus of this study was to compare CIGB-300 and a primary synthetic byproduct, CIGB-300iso, which shares the amino acid sequence with CIGB-300 but was proposed to differ due to racemization. This study explores the synthesis, characterization, and structural elucidation of CIGB-300 and its isomer CIGB-300iso. A comprehensive NMR analysis of seven synthesized diastereomers including amino acid residues C15, H21, and C25 revealed that CIGB-300iso contains one D enantiomer at position H21. The structures of both isoforms derived from NMR constraints disclosed that the L and D enantiomers have an altered peptide supersecondary structure, with a β-turn type IV3 found in CIGB-300 and a type I β-turn in CIGB-300iso, significantly impacting the peptide's conformations, sidechain orientations and, potentially, its biological activity. These findings highlight the importance of enantiomerically pure peptides for the design and synthesis of drug peptides.
Intercellular adhesion boots collective cell migration through elevated membrane tension
Authors: Wegner Seraphine , Bijonowski Brent , Park Jongkwon , Bergert Martin , Teubert Christina , Diz-Muñoz Alba , Galic Milos 
Published: July 2024

Abstract

In multicellular systems, the migration pattern of individual cells critically relies on the interactions with neighboring cells. Depending on the strength of these interactions, cells either move as a collective, as observed during morphogenesis and wound healing, or migrate individually, as it is the case for immune cells and fibroblasts. Transducers of cell-cell adhesions, such as cadherins coordinate collective dynamics by linking the cytoskeleton of neighboring cells. However, whether intercellular binding alone triggers signals that originate from within the plasma membrane itself, remains unclear. To address this question, we designed photoswitchable cell-cell adhesions that selectively connect adjacent plasma membranes without linking directly to cytoskeletal elements. We find that these intercellular adhesions are sufficient to achieve collective cell migration. Here, linking adjacent cells increases membrane tension, which activates the enzyme phospholipase D2. The resulting increase in phosphatidic acid, in turn, stimulates the mammalian target of rapamycin, a known actuator of collective cell migration. Collectively, these findings introduce a membrane-based signaling axis as promotor of collective cell dynamics, which is independent of the direct coupling of cell-cell adhesions to the cytoskeleton.
Effects of vitamin A and D in cord blood on infantile eczema: A Bidirectional Cohort Study
Authors: Pu Rui , Zhang Shuangshuang , Li Xuening , Liu Ying 
Published: July 2024

Abstract

Background
The incidence of infantile eczema is increasing annually. However, the associations between cord blood vitamin A and D and infantile eczema have been less studied. This study aimed to explore the factors influencing vitamin A and D in neonatal cord blood and the effects of vitamin A and D in cord blood on infantile eczema.
Methods
Questionnaire surveys, vitamin A and D detection and outcome measures were administered to 118 pairs of pregnant women and newborns. Follow-up for infantile eczema patients was based on a structured questionnaire.
Results
Significant correlations were detected between the vitamin A and D levels in the cord blood and venous blood of women in the third trimester of pregnancy (r = 0.256 and 0.697, respectively; all P < 0.05). The vitamin A intake of pregnant women (OR = 0.381, 95% CI: 0.147–0.989) and consumption of more vegetables (> 1 time/day) during pregnancy (OR = 0.334, 95% CI: 0.124–0.902) improved the protection of cord blood vitamin A levels. Pregnant women who exercised more (> 1 h/day) (OR = 0.103, 95% CI: 0.028–0.379) and who consumed more vitamin D during pregnancy (OR = 0.332, 95% CI: 0.118–0.933) presented with a lower risk of having cord blood vitamin D levels ≥ 20 ng/mL. Higher cord blood vitamin D levels were an independent protective factor for infantile eczema within 6 months and within 12 months (OR = 0.896, 95% CI: 0.834–0.963; OR = 0.927, 95% CI: 0.869–0.990, respectively). However, cord blood vitamin A levels were not associated with infantile eczema within 6 months or 12 months of age.
Conclusions
This study demonstrated a positive correlation between cord blood and vitamin A and D levels in maternal venous blood in the third trimester of pregnancy. Cord blood vitamin D levels can affect the development of infantile eczema.
Exploring the Influence of Different Learning Activities on Medical Students' Psychological Pathways in Ultrasound Acquisition
Authors: Huang Yu-Ting , Kang Enoch Yi-No , Salcedo Daniel , Lin Che-Wei , Hu Kai-Chun , Hsu Chin-Wang , Cheng Chung-Yi , Huang Wen-Cheng 
Published: July 2024

Abstract

Background
Acquiring proficiency in medicine typically necessitates a combination of foundational knowledge and hands-on experience. However, how do lecture and hands-on practice affect the psychological learning process in ultrasound education remains unclear. The purpose of this research was to test how the different learning activities associated with the psychomotor domain, elucidating their connections with cognitive and affective domains in the context of ultrasound education.
Method
This study is originally based on the post-course survey of the Parallel Ultrasound Hands-on (PUSH) trial. The survey was done by 127 third-year medical students with information regarding attending times and learning self-efficacy scale that consisted of 12 items with adequate reliability (Cronbach's α=0.9). A partial least square structural equation modeling was used for analyzing the data.
Results
Attending times of lecture was positively associated with cognitive (β=0.343; 95% CI: 0.093 to 0.567) and psychomotor domain (β=0.252; 95% CI: 0.066 to 0.452), but hands-on practice was only significantly associated with psychomotor domain (β=0.208; 95% CI: 0.043 to 0.376).
Conclusion
Lectures and hands-on practice exert varying impacts on medical students' psychological pathways involved in learning ultrasound. The combination learning design could be flexible at the time table of the course, but also be required with minimal attendance to the class.
Metamaterial Parameter Estimation by Machine Learning Method
Authors: Tiwari Shipra , Sharma Pramod , Ali Shoyab 
Published: July 2024

Abstract

Artificial neural network modeling is used to synthesize the metamaterial unit cell. Artificial neural networks are powerful tools to establish the relation between inputs and outputs parameters under highly nonlinear conditions. Artificial neural networks captured the synaptic weights according to their training data set. In artificial neural networks, the back propagation technique is the fastest learning method, which reduces the computer’s processing time and provides the best results under the nonlinear relationship between input and output. This work is divided into three parts. In the first part, we design a metamaterial unit cell, which is in the shape of square split rings. This shape is widely used to realize a metamaterial unit cell. In the second part, we develop a regression model using artificial neural networks to estimate the output resonance frequency when design parameters are used as input of artificial neural networks. In the last part, we use three different machine learning method to estimate the output parameter and then do the comparison in between them. Therefore, the objective of this research work is to develop a hypothesis using feed forward backpropagation method, Bayesian regularization and Elman backpropagation method, to find the resonance frequency when dimension of the metamaterial unit cell is given.
Charging Dynamic of Graphene Oxide-Water Interface Dominated by Sulfate Groups
Authors: Gudarzi Mohsen Moazzami , Sanjari Ali , Hosseini Mohammad , Aboutalebi Seyed Hamed 
Published: July 2024

Abstract

Graphene oxide (GO) has emerged as a versatile and technologically significant 2D material due to its chemical flexibility, allowing for sophisticated structural manipulation and efficient exfoliation from graphite oxide. Despite its extensive applications, the inconsistency in various aspects of GO processing, arising from unidentified factors that impact the precise chemical structure of GO, has significantly stalled progress in the field. Herein we show that the often-overlooked organosulfate groups play a decisive role throughout the entire GO lifecycle. Their influence extends from governing charging behaviour and self-assembly to impacting material properties, which in turn affect storage, processing, and applications. Detailed elemental analysis combined with modelling results reveal a high surface charge density, explaining the spontaneous exfoliation observed in widely used methods. Understanding the chemistry of GO enables us to tailor synthesis for enhanced material stability and ionic conductivity. Our results shed light on the electrical double layer around atomically thin membranes, paving the way for further exploration into 2D polyelectrolytes.
Assessment of serum Homocysteine levels in congenital heart disease and with rubella infection: A hospital- based case-control study in North Indian population
Authors: Tripathi Sumedha , Awasthi Shally , Tripathi Shalini , Jain Amita , Sharma Akhil 
Published: July 2024

Abstract

Objective
Circulating homocysteine and Rubella infection are independent risk factors for congenital heart disease (CHD). The primary objective of the study was to assess the association of serum homocysteine levels in cases of CHD and healthy controls and the secondary objective was to assess the association of serum homocysteine levels with rubella infection among CHD cases.
Methods
This case-control study was conducted in King George’s Medical University, Lucknow. Total 245 echo-graphically confirmed cases of CHD and age-gender matched 245 healthy controls of aged 0–11 months were recruited from the outpatient clinic and wards of paediatric and cardiology department and controls were recruited from immunization clinic of the hospital. Samples were tested for rubella specific IgM and IgG antibody and homocysteine levels using enzyme-linked-immunosorbent-assay.
Results
From July 2022 - December 2023, 245 cases of CHD and 245 healthy controls were recruited. The mean (SD) age of the cases were 4.40 ± 3.34 months and controls were 4.33 ± 3.63. In cases, 70.20% males were recruited while 68.57% in controls. The mean serum homocysteine levels (µmol/L) in CHD cases were 15.70 ± 7.6 while in controls 9.51 ± 3.1 (p = < 0.0001). Within CHD cases, 7.8% (19/245) were found seropositive for rubella infection. The crude odd ratio of homocysteine levels against seropositive rubella infection was 1.08 (95% CI 1.02–1.14) as compare to seronegative.
Conclusion
Levels of serum homocysteine in cases of CHD were significantly higher as compared to controls, whereas among CHD cases, those who had rubella seropositive showed significantly higher serum homocysteine levels.