bluuebunny/crossref_metadata_2025_split huggingface dataset:
Longitudinal adaptive immune profiling of vaccinated children reveals correlates of protection against symptomatic SARS-CoV-2 infection
Authors: Youjia Zhong , Kang Alicia , Tay Carina , Li Hui’ En , Elyana Nurul , Lim Joey , Bert Nina Le , Chan Kuan Rong , Ong Eugenia , Low Jenny , Shek Lynette , Tham Elizabeth , Ooi Eng Eong 
Published: October 2023

Abstract

The development of evidence-based COVID-19 vaccination policies for new birth cohorts is hindered by the lack of systematic examination of the protective capacity of elements of adaptive immunity besides neutralising antibodies. To address this knowledge gap, we conducted a longitudinal cohort study of healthy 5- to 12-year-olds vaccinated with BNT162b2. We serially measured binding and neutralising antibody titres, Spike (S)-specific memory B cell (MBC) and S-reactive T cell responses over 1 year; SARS-CoV-2 infections were ascertained using antigen rapid tests, and serological and cellular responses against nucleocapsid. We found that children mounted antibody, MBC and T cell responses after 2 doses, with continual expansion of SARS-CoV-2 variant neutralising capacity up to 1 year in the absence of wild-type infection. A booster (third) dose only improved neutralising antibody titres without impacting MBC and T cell responses. Hybrid immunity was greater in those infected after 2 vaccine doses than those infected before dose 2. Binding IgG titres, MBC and T cell responses were predictive of protection against symptomatic infection prior to attaining hybrid immunity; neutralising antibody titres only correlated with protection after hybrid immunity. The stable MBC and T cell responses over time suggest sustained protection against symptomatic SARS-CoV-2 infection, even when antibody levels wane.
Comparative Analysis of Viral Load Quantification Using RT-PCR and Digital Droplet PCR
Authors: Cabral Paula Gebe Abreu , de Souza Sávio Bastos , Arruda Raul Ferraz , Cabral Sheila Passos de Figueiredo , de Assis Arícia Leone Evangelista Monteiro , Junior Antônio Brazil Viana , Silva Renato Martins da 
Published: October 2023

Abstract
In the year 2019, a highly virulent coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged, precipitating the outbreak of the illness known as coronavirus disease 2019 (COVID-19). The commonly employed reverse transcription–polymerase chain reaction (RT-PCR) methodology serves to estimate the viral load in each patient's sample by employing a standard curve. However, it is imperative to recognize that this technique exhibits limitations with respect to clinical diagnosis and therapeutic applications, since an advancement of the conventional polymerase chain reaction methods, digital polymerase chain reaction (digital PCR or ddPCR), enables the direct quantification and clonal amplification of nucleic acid strands. The primary divergence between dPCR and traditional PCR resides in their approaches to measuring nucleic acid quantities. In this study, we investigated the viral loads of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) within 461 participants. By employing both RT-qPCR and ddPCR techniques, we established a comparison between the quantification methodologies of the two approaches. Our findings illustrate that the quantification through ddPCR affords a superior means of monitoring viral load within lower respiratory tract samples, thus enhancing the assessment of disease progression, particularly in scenarios characterized by low viral loads.
Relationship of valproic acid, hepatosteatosis and serum betatrophin
Authors: Cetin Huriye , Cokyaman Turgay , Ertem Şenay Bengin , Şehitoğlu Hilal , Doğan Durmuş 
Published: October 2023

Abstract
Purpose:With weight gain and/or obesity, adipocytokine levels in the blood change and nonalcoholic fatty liver disease (NAFLD) develops. In this study, we aimed to evaluate how serum betatrophin and homeostasis model assessment insulin resistance (HOMA-IR) are affected in children receiving valproic acid (VPA) monotherapy and whether shear wave elastography (SWE) accurately detects NAFLD in these patients.
Methods:Children aged 8-18 years with a diagnosis of epilepsy who received VPA monotherapy for at least 6 months (A group) and overweight and/or obese children (B group) in the similar age range were included in the study. Demographic characteristics, body mass index (BMI), epilepsy type, VPA dose-blood level and duration of use, HOMA-IR, serum lipid and betatrophin levels and liver SWE measurements were made.
Results:In our study, there were 36 cases in group A and 40 cases in group B. In the A group, 60% of the patients were diagnosed with generalized epilepsy and the mean VPA exposure time was 4 years. Body weight, BMI, insulin, ALT, HOMA-IR and lipids were found to be statistically significantly higher in group B.Interestingly, serum betatrophin was found to be high in group A. Hepatomegaly and hepatosteatosis were more common in group B, but SWE measurements were not different between the two groups.
Conclusion:VPA is still a reliable antiseizure drug in children in relatively low doses and long-term use. Serum betatrophin can be used together with SWE in the follow-up of weight gain and for early detection in those with the potential to develop NAFLD.
Small Body Precise Orbit Determination Toolkit（SPOT） and its application
Authors: Jianguo Yan , Wutong Gao , Bo Wang , Shangbiao Sun , Wanling Yang , Barriot Jean-Pierre 
Published: October 2023

Abstract
The orbiting and positioning of probes in deep-space exploration missions cannot be separated from the support of a software platform for precise orbit determination. The development of a software platform is essential in engineering and scientific applications. Thus, the Wuhan University planetary geodesy group has independently developed a software platform, called Small Body Precise Orbit Determination Toolkit (SPOT), in response to the demand for spacecraft precise orbit determination. Moreover, based on the goal of serving the first asteroid exploration mission to be implemented in China will enrich China's scientific radio science outputs. This paper briefly introduces the design concept, core structure, and main functions of SPOT, and subsequently focuses on some simulation experiments and real tracking data analysis based on SPOT. The functionality and self-consistency of the SPOT were verified through simulation experiments, and construction of some new measurement models and inversions of small body gravity fields. The reliability of the software platform was further verified from the processing of radio tracking data and landmark data from the Rosetta mission, as well as from the Neptunian gravity estimated from the motion of Triton based on astrometric observations. The computational efficiency and accuracy of SPOT have reached international equivalent level.
Plasmon-Enhanced Deep-Subwavelength Lateral Nanowire Solar Cells
Authors: Li Yao , Zha Chaofei , Yan Xin , Yuan Xueguang , Zhang Yangan , Zhang Jinnan , Zhang Xia 
Published: October 2023

Abstract
High performance deep-subwavelength lateral GaAs nanowire solar cells decorated with Au nanoblocks are proposed and studied through coupled three-dimensional optoelectronic simulations. The results show that Au nanoblocks significantly improve the absorption for TE polarized light mainly due to the excitation of localized surface plasmon. Surface local and near-field enhancement are two unique properties of surface plasmon, which concentrate light and transfer energy to nanowires. In addition, the absorption cutoff wavelength is remarkably extended due to the effect of localized surface plasmon resonance which enhances the confinement of long-wavelength modes for deep-subwavelength nanowires. For the nanowire with diameter less than 150 nm, the photoelectric conversion efficiency is improved by 37%~43% after introducing Au nanoblocks, which can reach 12% for 90 nm-diameter nanowire. This work provides a feasible way for the advancement of high-performance deep-subwavelength nanoscale solar cells.
Factors contributing to antibiotic misuse among parents of school-going children in Dhaka City, Bangladesh
Authors: Islam Md. Wahidul , Shahjahan Muhibullah , Azad Abul Kalam , Hossain Md. Jubayer 
Published: October 2023

Abstract
Antimicrobial resistance (AMR) is a pressing global health concern, especially in constrained-resource countries such as Bangladesh. This study aimed to identify the factors contributing to antibiotic misuse by assessing knowledge, attitude, and practice (KAP). A cross-sectional study was conducted from August 20 to August 30, 2022, among 704 parents of school-going children in Dhaka South City. Descriptive statistics were used to analyze KAP, and multivariate models, including linear and ordinal logistic regression, were used to explore the associations between these factors. The findings revealed that approximately 22% of the participants were male and 78% were female. Most parents (58%) had completed higher secondary education. Approximately 45% of respondents demonstrated moderate knowledge, 53% held uncertain attitudes, and 64% exhibited antibiotic misuse. Factors such as parental age, educational level, employment status, income, child's age, and family type significantly influenced KAP. These findings emphasize the importance of targeted education and awareness initiatives to enhance knowledge and responsible antibiotic use among parents, contributing to global efforts against antibiotic resistance. The government should enforce laws and regulations regarding antibiotic misuse.
Transition from natal downs to juvenile feathers: conserved regulatory switches in Neoaves
Authors: Li Wen-Hsiung , Chuong Cheng Ming , Chen Chih-Kuan , Wu Ping , Jiang Ting-Xin , Harn Hans I-Chen , Liu Tzu-Yu , Yu Zhou , Lu Jiayi , Chang Yao-Ming , Yue Zhicao , Lin Jinnjy , Vu Trieu-Duc , Huang Tao-Yu , Ng Chen Siang 
Published: October 2023

Abstract

The transition from natal downs for heat conservation to juvenile feathers for simple flight is a remarkable environmental adaptation process in avian evolution. However, the underlying epigenetic mechanism for this primary feather transition is mostly unknown. Here we conducted time-ordered gene co-expression network construction, epigenetic analysis, and functional perturbations in developing feather follicles to elucidate four downy-juvenile feather transition events. We discovered that LEF1 works as a key hub of Wnt signaling to build rachis and converts radial downy to bilateral symmetry. Extracellular matrix reorganization leads to peripheral pulp formation, which mediates epithelial - mesenchymal interactions for branching morphogenesis. ACTA2 compartments dermal papilla stem cells for feather cycling. Novel usage of scale keratins strengthens feather sheath with SOX14 as the epigenetic regulator. We found this primary feather transition largely conserved in chicken (precocious) and zebra finch (altricial) and discussed the possibility that this evolutionary adaptation process started in feathered dinosaurs.
mid-DeepLabv3+ : A Novel Approach for Image Semantic Segmentation applied to African Food Dietary Assessment
Authors: EREP Thierry Roland BABAN A , CHAARI Lotfi , ELE Pierre , SOBNGWI Eugene 
Published: October 2023

Abstract
Recent decades have seen the development of vision-based dietary assessment systems (VBDA). These systems generally consist of three main stages: food image analysis, portion estimation and nutrient derivation. The effectiveness of the initial step is highly dependent on the use of accurate segmentation and image recognition models, and the availability of high-quality training datasets. Food image segmentation still faces various challenges, while most existing research has focused mainly on Asian and Western food images. For this reason, this study is based on food images from sub-Saharan Africa, which pose their own problems, such as inter-class similarity and dishes presentation with mixed-class food. This work focuses on the first stage of VBDA, where we introduce two notable contributions. Firstly, we propose mid-DeepLabv3+, an enhanced food image segmentation model based on DeepLabv3+ with a ResNet50 backbone. Our approach involves adding a middle layer in the decoder path and SimAM attention mechanism after each extracted backbone features layers. Secondly, we present CamerFood10, the first food images dataset specifically designed for sub-Saharan African food segmentation. It includes 10 classes of most consumed food items in Cameroon. On our dataset, mid-DeepLabv3+ outperforms existing image segmentation benchmark models with an mIoU (mean Intersection over Union) of 65.20\%, representing more than +10.74\% improvement over the DeepLabv3+ with the same backbone.
Study of failure consequences and visualization of buried gas pipelines
Authors: Kang Yong , Ma Shuye , Wu Zhuang , Zhao Mengmeng , Xia Xiaoxue 
Published: October 2023

Abstract
In recent years, accidents on buried gas pipelines have happened often in China's cities, mostly when moving natural gas. Natural gas is primarily transported by buried gas pipeline networks, and natural gas pipeline leakage has explosive and flammable properties. It can cause environmental pollution and resource loss, and even cause serious harm to people's lives and a lot of property damage. This paper presents a method for visualizing the consequences of buried gas pipeline accidents based on FLACS software and applies the method to the "7.4" gas pipeline leakage and explosion accident in Songyuan, Jilin. The accident was studied by numerical simulation and visualization of its consequences. The method combines numerical simulation data with mapping software to more precisely recreate the explosion's danger zone and use visualization to analyze the consequences of the gas pipeline network accident. Therefore, the method has some theoretical and practical significance for the risk prevention and accident consequences of urban buried gas pipelines.
Utilizing Deep Learning Algorithm and Image Processing Techniques for the Localization and Quantitative Analysis of Infographics in Resumes
Authors: Nazar Talha , Kausar Shujaat Hussain 
Published: October 2023

Abstract
Infographics have proven to be more effective than traditional prose in conveying complex subjects. In recent years deep learning approaches have demonstrated their capability in an array of applications, including image identification, which encompasses pattern recognition and the application of artificial intelligence. A variety of infographics are employed in order to gauge skills in resumes. The aim of this study is to identify the existing infographics present in resume, locate the associated text pertaining to each infographic, and subsequently quantify each infographic with numerical values. For the purpose of detecting infographics, the You Only Look Once (YOLO) algorithm was utilized, while the Optical Character Recognition (OCR) was applied for detecting the associated text. The differentiation between the filled and empty sections of the infographic was accomplished through the implementation of image intensity histogram analysis, thresholding, and contouring.
Integrated using UMI-77 and Curcumin Synergistic Treating Osteosarcoma by Targeting a Cuproptosis-Related Prognostic Model
Authors: Fu Zhaoyu , Wang Nan , Ren Jia , Kong Yuanhang , Yang Jihao , Su Gao , Yang Guohui 
Published: October 2023

Abstract
Background
Among malignant bone sarcomas, osteosarcoma (OS) is the most frequent among young people. In recent studies, cuproptosis has been shown to play an important role in tumor progression. Evidence demonstrates that the combinatorial treatment with traditional Chinese medicine and western medicine improves the therapeutic effect on cancer, including OS. However, the combinatorial treatment targeting cuproptosis for OS remains elusive.
Materials and Methods
LASSO regression analysis was employed to establish and evaluate a cuproptosis-related prognostic model. The CIBERSORT algorithm was performed to demonstrate the significant differences in immune cell infiltration between low- and high-risk groups. Next, the CellMiner database was used to obtain potential drugs which target the risk score-related genes. Finally, we performed the network pharmacology and molecular docking studies to explore the combination of Chinese and western medicine on treatment of osteosarcoma.
Results
We found that the Chinese medicine, curcumin, and the western medicine, UMI-77 synergistic treating OS both in vivo and vitro. LASSO regression analysis was employed to establish and evaluate a cuproptosis-related prognostic model. Moreover, the CIBERSORT algorithm was performed to demonstrate the significant differences in immune cell infiltration between low- and high-risk groups. Notably, prognostic genes were related to 106 drugs obtained from the CellMiner database. Network pharmacology and molecular docking studies demonstrated that curcumin, the main active ingredient of curcumaelongae Rhizoma, targeted the suppressor gene, CLTC.
Conclusion
Our findings demonstrated that the combination of curcumin and UMI possess certain effect on osteosarcoma. And this study provides a theoretical framework for the integration of traditional Chinese medicine with western medicine for treating OS.
A Sustainable Energy Approach for Pumping and Irrigation in the Barind Region of Bangladesh
Authors: Hossain Md. Sanowar , Chowdhury Miftahul Mobin , Das Barun K. , Islam Mohammad Rofiqul , Kibria Md. Golam , Banik Sujan 
Published: October 2023

Abstract
The continuous use of fossil fuels has prompted scientists and researchers to convert to renewable sources for powering water pumps. By converting sunlight into electrical energy, the photovoltaic (PV) panels are able to drive the water pump or produce electricity through an inverter. Over the past few years, scientists have been working on developing more efficient solar-powered water pumps. A summary of existing research and development activities for developing a dependable and cost-effective solar irrigation system is described in this study. The paper outlines Bangladesh's present irrigation scenario, the problems associated with solar irrigation systems, and government policies and actions promoting solar irrigation. The main objectives and aims of the proposed project are to develop an efficient standalone hybrid solar PV-pyro-oil generator-based water pumping system for the Barind tract and off-grid remote areas. Moreover, the techno-econo-environmental feasibility of the proposed project has also been evaluated. The total life cycle cost and investment payback period of the 20-year project were found to be 14,377.32 dollars and 7.04 years, respectively. Moreover, the project's internal rate of return and CO2 reduction potential were found to be 21% and 197.1 tons, respectively. Therefore, the project is sustainable and feasible, which provides a guideline for researchers and investors.
Inductive nanopore synapse element for iontronic neuromorphic computing
Authors: Bisquert Juan , Ramirez Patricio , Bou Agustin , Cervera Javier 
Published: October 2023

Abstract
The rapid expansion of artificial intelligence (AI) technologies necessitates the resolution of data handling and storage limitations inherent in the von Neumann computer architecture. Drawing inspiration from biology, which initially sparked the development of artificial neural networks, we explore a new avenue in computer architecture known as neuromorphic computing. Based on the emergence of iontronic fluidic ionic/electronic components, here we show the application of a nanopore ionic rectifier as a synapse element that exhibits conductance modulation in response to a train of voltage impulses, producing programmable resistive states. The memristive properties and their connection to hysteresis phenomena are elucidated by the combined analysis in time and frequency domains. Notably, our findings underscore the prevalence of an inductor mechanism, which arises from the interplay between fast and slow conduction modes. The activation time of this mechanism governs the biomimetic attributes of synaptic conductance potentiation, depression, and paired pulse facilitation. This innovative approach enables the creation of high-fidelity memory elements reminiscent of biological systems and holds promise for significantly enhancing the efficiency and sustainability of AI systems.
Accessing Eye-level Greenness Visibility from Open-Source Street View Images: A methodological development and implementation in multi-city and multi-country contexts
Authors: Sánchez Ilse Abril Vázquez , Labib SM 
Published: October 2023

Abstract
The urban natural environment provides numerous benefits, including augmenting the aesthetic appeal of urban landscapes and improving mental wellbeing. While diverse methods have been used to evaluate urban greenery, the assessment of eye-level greenness visibility using street-view level images is emerging due to its greater compatibility with human perception. Many existing studies predominantly rely on proprietary street view images provider such as Google Street View (GSV) data; the usage restrictions and lack of alignment with FAIR (Findability, Accessibility, Interoperability, and Reusability) principles present challenges in using proprietary images at scale. Therefore, incorporating Volunteered Street View Imagery (VSVI) platforms, such as Mapillary, is emerging as a promising alternative. In this study, we present a scalable and reproducible methodological framework for utilising Mapillary images for Green View Index (GVI) assessment using image segmentation approach and evaluate the completeness and usefulness of such data in diverse geographical contexts, including seven cities (i.e., Amsterdam, City of Melbourne, Dhaka, Kampala, Mexico City, Seattle, and Tel Aviv). We also evaluate the use of globally available satellite-based vegetation indices (e.g., Normalised Difference Vegetation Index-NDVI) to estimate GVI in locations where street-view images are unavailable. Our approach demonstrates the applicability of Mapillary data for GVI assessments, although revelling considerable disparities in image availability and usability between cities located in developed and developing countries. We also identified that the NDVI could be used effectively to estimate GVI values in locations where direct street-level imagery is limited. Additionally, the analysis reveals notable differences in greenness visibility across cities, particularly in high-density, lower-income cities in Africa and South Asia, compared to low-density, high-income cities in the USA and Europe.