bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on highway rain monitoring based on rain monitoring coefficient
Authors: Wang Xingyu , Feng Haixia , Wang Na , Zhu Maoxin , Ning Erwei , Li Jian 
Published: February 2024

AbstractThe real-time and accurate monitoring of severe weather is the key to reducing traffic accidents on highways. Currently, rainy day monitoring based on video images focuses on removing the impact of rain. This article aims to build a monitoring model for rainy days and rainfall intensity to achieve precise monitoring of rainy days on highways. This paper introduces an algorithm that combines the frequency domain and spatial domain, thresholding, and morphology. It incorporates high-pass filtering, full-domain value segmentation, the OTSU method (the maximum inter-class difference method), mask processing, and morphological opening for denoising. The algorithm is designed to build the rain coefficient model Prain coefficient and determine the intensity of rainfall based on the value of Prain coefficient. To validate the model, data from sunny, cloudy, and rainy days in different sections and time periods of the Jinan Bypass G2001 line were used. The aim is to raise awareness about driving safety on highways. The main findings are: the rain coefficient model Prain coefficient can accurately identify cloudy and rainy days and assess the intensity of rainfall. This method is not only suitable for highways but also for ordinary road sections. The model's accuracy has been verified, and the algorithm in this study has the highest accuracy. This research is crucial for road traffic safety, particularly during bad weather such as rain.
Valproic acid exposure affects social visual lateralization and asymmetric gene expression in zebrafish larvae
Authors: Messina Andrea , Sovrano Valeria Anna , Baratti Greta , Musa Alessia , Gobbo Alessandra , Adiletta Alice , Sgadò Paola 
Published: February 2024

AbstractCerebral asymmetry is critical for typical brain function and development; at the same time, altered brain lateralization seems to be associated with neuropsychiatric disorders. Zebrafish are increasingly emerging as model species to study brain lateralization, using asymmetric development of the habenula, a phylogenetically old brain structure associated with social and emotional processing, to investigate the relationship between brain asymmetry and social behavior. We exposed 5-h post-fertilization zebrafish embryos to valproic acid (VPA), a compound used to model the core signs of ASD in many vertebrate species, and assessed social interaction, visual lateralization and gene expression in the thalamus and the telencephalon. VPA-exposed zebrafish exhibit social deficits and a deconstruction of social visual laterality to the mirror. We also observe changes in the asymmetric expression of the epithalamic marker leftover and in the size of the dorsolateral part of the habenula in adult zebrafish. Our data indicate that VPA exposure neutralizes the animals’ visual field bias, with a complete loss of the left-eye use bias in front of their own mirror image, and alters brain asymmetric gene expression and morphology, opening new perspectives to investigate brain lateralization and its link to atypical social cognitive development.
Motivation levels and white matter microstructure in children living with HIV
Authors: Wedderburn Catherine J. , Sevenoaks Tatum , Fouche Jean-Paul , Phillips Nicole J. , Lawn Stephen D. , Stein Dan J. , Hoare Jacqueline 
Published: February 2024

AbstractCentral nervous system involvement in HIV infection leads to neurobehavioural sequelae. Although apathy is a well-recognised symptom in adults living with HIV linked to alterations in brain structure, there is scarce research examining motivation in children living with HIV (CLWH). We used the Children’s Motivation Scale (CMS; normative mean = 50, SD = 10) to assess motivation levels in 76 CLWH aged 6–16 years (63 on antiretroviral therapy [ART]; 13 ART-naïve slow progressors) in South Africa. Overall, CLWH scored low on the CMS (mean = 35.70 [SD = 5.87]). Motivation levels were significantly reduced in children taking ART compared to ART-naïve slow progressors (p = 0.02), but were not correlated with markers of HIV disease (CD4 + cell count or viral load), or neurocognitive function (p > 0.05). CMS scores were correlated with diffusion tensor imaging metrics of white matter microstructure in specific frontostriatal brain regions (p < 0.05). On multiple regression, associations with the anterior limb of the internal capsule, a subcortical white matter region, remained significant after adjusting for potential confounders. These findings suggest that reduced motivation may be an important neurobehavioural symptom in CLWH and may reflect changes in white matter microstructure of frontostriatal brain regions.
A novel low light object detection method based on the YOLOv5 fusion feature enhancement
Authors: Peng Daxin , Ding Wei , Zhen Tong 
Published: February 2024

AbstractLow-light object detection is an important research area in computer vision, but it is also a difficult issue. This research offers a low-light target detection network, NLE-YOLO, based on YOLOV5, to address the issues of insufficient illumination and noise interference experienced by target detection tasks in low-light environments. The network initially preprocesses the input image with an improvement technique before suppressing high-frequency noise and enhancing essential information with C2fLEFEM, a unique feature extraction module. We also created a multi-scale feature extraction module, AMC2fLEFEM, and an attention mechanism receptive field module, AMRFB, which are utilized to extract features of multiple scales and enhance the receptive field. The C2fLEFEM module, in particular, merges the LEF and FEM modules on top of the C2f module. The LEF module employs a low-frequency filter to remove high-frequency noise; the FEM module employs dual inputs to fuse low-frequency enhanced and original features; and the C2f module employs a gradient retention method to minimize information loss. The AMC2fLEFEM module combines the SimAM attention mechanism and uses the pixel relationship to obtain features of different receptive fields, adapt to brightness changes, capture the difference between the target and the background, improve the network's feature extraction capability, and effectively reduce the impact of noise. The AMRFB module employs atrous convolution to enlarge the receptive field, maintain global information, and adjust to targets of various scales. Finally, for low-light settings, we replaced the original YOLOv5 detection head with a decoupled head. The Exdark dataset experiments show that our method outperforms previous methods in terms of detection accuracy and performance.
Deep neural networks for crack detection inside structures
Authors: Moreh Fatahlla , Lyu Hao , Rizvi Zarghaam Haider , Wuttke Frank 
Published: February 2024

AbstractCrack detection is a long-standing topic in structural health monitoring. Conventional damage detection techniques rely on intensive, time-consuming, resource-intensive intervention. The current trend of crack detection emphasizes using deep neural networks to build an automated pipeline from measured signals to damaged areas. This work focuses on the seismic-wave-based technique of crack detection for plate structures. Previous work proposed an encoder–decoder network to extract crack-related wave patterns from measured wave signals and predict crack existence on the plate. We extend previous work with extensive experiments on different network components and a data preprocessing strategy. The proposed methods are tested on an expanded crack detection dataset. We found that a robust backbone network, such as Densely Connected Convolutional Network (DenseNet) can effectively extract the features characterizing cracks of wave signals, and by using the reference wave field for normalization, the accuracy of detecting small cracks can be further improved.
Complex changes in serum protein levels in COVID-19 convalescents
Authors: Pushalkar Smruti , Wu Shaohuan , Maity Shuvadeep , Pressler Matthew , Rendleman Justin , Vitrinel Burcu , Jeffery Lauren , Abdelhadi Ryah , Chen Mechi , Ross Ted , Carlock Michael , Choi Hyungwon , Vogel Christine 
Published: February 2024

AbstractThe COVID-19 pandemic, triggered by severe acute respiratory syndrome coronavirus 2, has affected millions of people worldwide. Much research has been dedicated to our understanding of COVID-19 disease heterogeneity and severity, but less is known about recovery associated changes. To address this gap in knowledge, we quantified the proteome from serum samples from 29 COVID-19 convalescents and 29 age-, race-, and sex-matched healthy controls. Samples were acquired within the first months of the pandemic. Many proteins from pathways known to change during acute COVID-19 illness, such as from the complement cascade, coagulation system, inflammation and adaptive immune system, had returned to levels seen in healthy controls. In comparison, we identified 22 and 15 proteins with significantly elevated and lowered levels, respectively, amongst COVID-19 convalescents compared to healthy controls. Some of the changes were similar to those observed for the acute phase of the disease, i.e. elevated levels of proteins from hemolysis, the adaptive immune systems, and inflammation. In contrast, some alterations opposed those in the acute phase, e.g. elevated levels of CETP and APOA1 which function in lipid/cholesterol metabolism, and decreased levels of proteins from the complement cascade (e.g. C1R, C1S, and VWF), the coagulation system (e.g. THBS1 and VWF), and the regulation of the actin cytoskeleton (e.g. PFN1 and CFL1) amongst COVID-19 convalescents. We speculate that some of these shifts might originate from a transient decrease in platelet counts upon recovery from the disease. Finally, we observed race-specific changes, e.g. with respect to immunoglobulins and proteins related to cholesterol metabolism.
Utilization of aquatic biomass as biosorbent for sustainable production of high surface area, nano- microporous, for removing two dyes from wastewater
Authors: Abdallah Maha Ahmed Mohamed , Alprol Ahmed E. 
Published: February 2024

AbstractThe majority of environmental researchers are becoming increasingly concerned with the manufacture of inexpensive adsorbents for the detoxification of industrial effluents. To address one of the significant and well-known pollution issues with certain drains that act as hotspots and contribute to coastal pollution in Alexandria, this study aims to develop an economical, ecologically friendly sorbent. This study assessed the efficacy of a biomass-coated magnetic composite and a magnetic active adsorbent for the removal of two dyes from an industrially contaminated sewer using a wetland plant (Phragmites australis). Using magnetic biosorbent, the biosorption of Xylenol orange and Congo red ions from polluted drain discharge in Abu Qir Bay was evaluated in the current study. Using scanning electron microscopy imaging and Fourier transform infra-red analysis; the surface function and morphology of the nano-biosorbent were examined. At room temperature, the effects of initial dye concentration, pH, contact time, and nano-biosorbent concentration have all been investigated. The greatest percentages that nano-biosorbent can remove from Congo red and Xylenol orange are 97% and 47%, respectively. The removal of the initial Congo red concentration varied from 42 to 97%, while the removal of the initial Xylenol orange concentration varied from 30 to 47%. The adsorption capacity was shown to be strongly pH-dependent; capacity dose as pH value increased, with pH 10 being the ideal pH for Congo red and pH 6 being the ideal pH value for Xylenol orange. The adsorption capacity for Congo red varied between 0.96 and 3.36 and the adsorption capacity for Xylenol orange varied between 0.18 and 17.58. The removal capacity decreased from 3.36 to 0.96 mg/g when the biosorbent dosage was increased from 0.05 to 0.5 g/L for Congo red, in case of Xylenol orange, the removal capacity increased from 0.18 to 17.58 mg/g when the biosorbent dosage was increased from 0.05 to 0.5 g/L. The removal capacity of Congo red increases quickly with time and varied from 1.66 to 1.88 of contact time; while the removal capacity of Xylenol orange varied between 3.08 and 4.62 of contact time. For the dyes under study, kinetics and adsorption equilibrium were examined. Within 180 min, the equilibrium was attained because to the quick adsorption process. For Congo red and Xylenol orange, the highest adsorption capacities were 3.36 and 17.58 mg g−1, respectively. The equilibrium data were assessed using a number of isotherm models, including Langmuir, Freundlich, BET, and Tempkin, while the kinetic data were examined using a variety of kinetic models, including pseudo-first- and pseudo-second-order equations. The pseudo-second-order equation provides the greatest accuracy for the kinetic data and Langmuir model is the closest fit for the equilibrium data.
13C MRI of hyperpolarized pyruvate at 120 µT
Authors: Kempf Nicolas , Körber Rainer , Plaumann Markus , Pravdivtsev Andrey N. , Engelmann Jörn , Boldt Johannes , Scheffler Klaus , Theis Thomas , Buckenmaier Kai 
Published: February 2024

AbstractNuclear spin hyperpolarization increases the sensitivity of magnetic resonance dramatically, enabling many new applications, including real-time metabolic imaging. Parahydrogen-based signal amplification by reversible exchange (SABRE) was employed to hyperpolarize [1-13C]pyruvate and demonstrate 13C imaging in situ at 120 µT, about twice Earth’s magnetic field, with two different signal amplification by reversible exchange variants: SABRE in shield enables alignment transfer to heteronuclei (SABRE-SHEATH), where hyperpolarization is transferred from parahydrogen to [1-13C]pyruvate at a magnetic field below 1 µT, and low-irradiation generates high tesla (LIGHT-SABRE), where hyperpolarization was prepared at 120 µT, avoiding magnetic field cycling. The 3-dimensional images of a phantom were obtained using a superconducting quantum interference device (SQUID) based magnetic field detector with submillimeter resolution. These 13C images demonstrate the feasibility of low-field 13C metabolic magnetic resonance imaging (MRI) of 50 mM [1-13C]pyruvate hyperpolarized by parahydrogen in reversible exchange imaged at about twice Earth’s magnetic field. Using thermal 13C polarization available at 120 µT, the same experiment would have taken about 300 billion years.
The underlying molecular mechanism of ciliated epithelium dysfunction and TGF-β signaling in children with congenital pulmonary airway malformations
Authors: Zhang Gang , Lou Lei , Shen Linghui , Zeng Huiyi , Cai Chun , Wu Rongde , Liu Dandan 
Published: February 2024

AbstractThe aim of this study was to investigate the variation in gene expression in the complete transcripts of Congenitalpulmonary airwaymalformation (CPAM) of the lung using Next Generation Sequencing (NGS) technology. There were 20 cases involving children with CPAM were used for selection of study sample. NGS was used to establish RNA-Seq libraries for the two groups of samples separately, and both groups were conducted to differential expression analysis and Gene Ontology (GO) functional enrichment analysis. The pathways of the differential genes were analyzed to find the enriched target pathways. A total of 592 genes were expressed with significant differences (CPAM vs. normal tissue, P < 0.05). GO functional analysis of DEGs indicated that abnormal ciliary function played a role in the development of CPAM. Subsequently, analysis of these genes pathways showed the TGF-β signaling pathway was significantly enriched. Finally, the results of immunohistochemical analysis of some DEGs showed that a significant reduction in the expression of SMAD6, a gene related to the TGF-β signaling pathway, led to abnormal activation of the pathway. TGF-β signaling pathway involved in the evolution of the disease obtained by DEGs enrichment pathway analysis. SMAD6, a gene involved in this pathway, might be a potential biomarker for the diagnosis and treatment of CPAM.
GIS-based non-grain cultivated land susceptibility prediction using data mining methods
Authors: Hao Qili , Zhang Tingyu , Cheng Xiaohui , He Peng , Zhu Xiankui , Chen Yao 
Published: February 2024

AbstractThe purpose of the present study is to predict and draw up non-grain cultivated land (NCL) susceptibility map based on optimized Extreme Gradient Boosting (XGBoost) model using the Particle Swarm Optimization (PSO) metaheuristic algorithm. In order to, a total of 184 NCL areas were identified based on historical records, and a total of 16 NCL susceptibility conditioning factors (NCLSCFs) were considered, based on both a systematic literature survey and local environmental conditions. The results showed that the XGBoost model optimized by PSO performed well in comparison to other machine learning algorithms; the values of sensitivity, specificity, PPV, NPV, and AUC are 0.93, 0.89, 0.88, 0.93, and 0.96, respectively. Slope, rainfall, fault density, distance from fault and drainage density are most important variables. According to the results of this study, the use of meta-innovative algorithms such as PSO can greatly enhance the ability of machine learning models.
Correlation of MRI quantitative perfusion parameters with EGFR, VEGF and EGFR gene mutations in non-small cell cancer
Authors: Zou Mingyue , Zhang Bingqian , Shi Lei , Mao Haijia , Huang Yanan , Zhao Zhenhua 
Published: February 2024

AbstractTo explore the relationship between quantitative perfusion histogram parameters of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) with the expression of tumor tissue epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF) and EGFR gene mutations in non-small cell lung cancer (NSCLC). A total of 44 consecutive patients with known NSCLC were recruited from March 2018 to August 2021. Histogram parameters (mean, uniformity, skewness, energy, kurtosis, entropy, percentile) of each (Ktrans, Kep, Ve, Vp, Fp) were obtained by Omni Kinetics software. Immunohistochemistry staining was used in the detection of the expression of VEGF and EGFR protein, and the mutation of EGFR gene was detected by PCR. Corresponding statistical test was performed to compare the parameters and protein expression between squamous cell carcinoma (SCC) and adenocarcinoma (AC), as well as EGFR mutations and wild-type. Correlation analysis was used to evaluate the correlation between parameters with the expression of VEGF and EGFR protein. Fp (skewness, kurtosis, energy) were statistically significant between SCC and AC, and the area under the ROC curve were 0.733, 0.700 and 0.675, respectively. The expression of VEGF in AC was higher than in SCC. Fp (skewness, kurtosis, energy) were negatively correlated with VEGF (r =  − 0.527, − 0.428, − 0.342); Ktrans (Q50) was positively correlated with VEGF (r = 0.32); Kep (energy), Ktrans (skewness, kurtosis) were positively correlated with EGFR (r = 0.622, r = 0.375, 0.358), some histogram parameters of Kep, Ktrans (uniformity, entropy) and Ve (kurtosis) were negatively correlated with EGFR (r =  − 0.312 to − 0.644). Some perfusion histogram parameters were statistically significant between EGFR mutations and wild-type, they were higher in wild-type than mutated (P < 0.05). Quantitative perfusion histogram parameters of DCE-MRI have a certain value in the differential diagnosis of NSCLC, which have the potential to non-invasively evaluate the expression of cell signaling pathway-related protein.
The disparate impacts of college admissions policies on Asian American applicants
Authors: Grossman Joshua , Tomkins Sabina , Page Lindsay , Goel Sharad 
Published: February 2024

AbstractThere is debate over whether Asian American students face additional barriers, relative to white students, when applying to selective colleges. Here we present the results from analyzing 685,709 applications submitted over five application cycles to 11 highly selective colleges (the “Ivy-11”). We estimate that Asian American applicants had 28% lower odds of ultimately attending an Ivy-11 school than white applicants with similar academic and extracurricular qualifications. The gap was particularly pronounced for students of South Asian descent (49% lower odds). Given the high yield rates and competitive financial aid policies of the schools we consider, the disparity in attendance rates is likely driven, at least in part, by admissions decisions. In particular, we offer evidence that this pattern stems from two factors. First, many selective colleges give preference to the children of alumni in admissions. We find that white applicants were substantially more likely to have such legacy status than Asian applicants. Second, we identify geographic disparities potentially reflective of admissions policies that disadvantage students from certain regions of the United States. We hope these results inform discussions on equity in higher education.
Neurocognitive responses to spatial design behaviors and tools among interior architecture students: a pilot study
Authors: Şekerci Yaren , Kahraman Mehmet Uğur , Özturan Özgü , Çelik Ertuğrul , Ayan Sevgi Şengül 
Published: February 2024

AbstractThe impact of emotions on human behavior is substantial, and the ability to recognize people's feelings has a wide range of practical applications including education. Here, the methods and tools of education are being calibrated according to the data gained over electroencephalogram (EEG) signals. The issue of which design tools would be ideal in the future of interior architecture education, is an uncertain field. It is important to measure the students’ emotional states while using manual and digital design tools to determine the different impacts. Brain-computer interfaces have made it possible to monitor emotional states in a way that is both convenient and economical. In the research of emotion recognition, EEG signals have been employed, and the resulting literature explains basic emotions as well as complicated scenarios that are created from the combination of numerous basic emotions. The objective of this study is to investigate the emotional states and degrees of attachment experienced by interior architecture students while engaging in their design processes. This includes examining the use of 2D or 3D tools, whether manual or digital, and identifying any changes in design tool usage and behaviors that may be influenced by different teaching techniques. Accordingly, the hierarchical clustering which is a technique used in data analysis to group objects into a hierarchical structure of clusters based on their similarities has been conducted.