bluuebunny/crossref_metadata_2025_split huggingface dataset:
Open Defecation Free status and its determinants in rural Uganda: a cross-sectional survey
Authors: Ntaro Moses , Isunju John Bosco , Mulogo Edgar , Ssempebwa John C. 
Published: April 2024

Abstract
Introduction
Globally, the progress to attain the open defecation free (ODF) environment has remained very slow. This study examined context specific factors influencing household open defecation free status in Uganda
Methods
A cross-sectional study was conducted in Kabale district in southwestern Uganda and 492 participants were randomly selected at household level. Data was obtained through conducting a face-to-face interview using the mobile data collection software KoBoCollect v2021.3.4 installed on tablet devices. The bivariate analysis was conducted using Pearson’s chi-square test to determine if there existed significant associations between the outcome Household Open Defecation Free (HODF) status and independent variables. The variables with P<0.2 at bivariate analysis comprised the global model and were considered for multivariate analysis.
Results
The average age of the participants was 49 (SD 23.4) years. Most (67.68%) of the study participants, were females while 144 (29.27%) of the participants had no formal education. The households that were open defecation free were as few as 15 (3%). At multivariable logistic regression analysis, gender of the participants, remembering handwashing, latrine and household cleanliness factors were significantly association with Household Open Defecation Free status. Male participants had more odds of having open defecation free households (aOR: 4.95; 95% CI: 1.57 - 15.60) compared to female participants. Also households with clean compounds and with latrines not having their holes soiled with feces had more odds of being open defecation free (aOR: 4.39; 95% CI: 1.44 - 13.37 and aOR: 13.86; 95% CI: 1.77 - 108.68 respectively).
Conclusion
The prevalence of HODF was very low and factors associated with it were; the gender of the participants, the latrine and household cleanliness and the behavioral factor of remembering handwashing. We propose behavioral change interventions that empower communities to adapt improved sanitation behavior, such as Community Led Total Sanitation and Hygiene (CLTSH) in order to increase households with the Open Defecation Free status.
A ratiometric fluorescence probe based on silver nanoclusters and CdSe/ZnS quantum dots for the detection of hydrogen peroxide by aggregation and etching
Authors: Zhang Yuanyuan , Zhang Xin , Xu Hedan , Zhao Sitian , Yang Zirui , Pi Zijie , Yang Xiaoling , Liao Xiaoling 
Published: April 2024

Abstract
In this study, a ratiometric fluorescence nanoprobe is developed for the analysis of hydrogen peroxide (H2O2). Silver nanoclusters (AgNCs) were synthesized by chemical reduction method using sodium borohydride (NaBH4) as reducing agent, and were coupled with CdSe/ZnS quantum dots (QDs) to form the ratiometric fluorescence nanoprobe silver nanoclusters-quantum dots (AgNCs-QDs). The effect of the volume ratio of CdSe/ZnS QDs to AgNCs on the fluorescence ratio of AgNCs-QDs was investigated. The fluorescence characterization results show that two emission peaks of AgNCs-QDs are located at 473 nm and 661 nm, respectively. Transmission electron microscope (TEM) and X-ray photoelectron spectroscopy (XPS) results show that H2O2 can cause the fluorescence probe to aggregate, while etching AgNCs to produce silver ions, which together cause the fluorescence of the QDs in the ratiometric fluorescent probe to be quenched. Based on this strategy, the fluorescence intensity ratio of the two emission peaks F473/F661 exhibits a strong linear correlation with the concentration of H2O2. The detection range is 3.32 μM ~ 2.65 mM with a detection limit of 3.32 μM. In addition, the ratiometric fluorescence probe can specifically recognize H2O2 and has excellent anti-interference performance and good fluorescence stability. Importantly, the probe was utilized for the detection of H2O2 in serum, showing the possibility of the probe in clinical detection applications.
A IoT-based System for Enhanced Home Security using Intelligent Solutions
Authors: Nandi Avhishek , Paul Barnali , Roy Deepsubhra Guha 
Published: April 2024

Abstract

The Internet of Things has evolved in our smart environment, smart devices can function without human involvement. As a result, homes can be converted into intelligent home automation systems that execute computations automatically. This paper mainly focuses on exploring and designing a state-of-the-art Smart Security System by implementing the latest machine learning algorithms and IoT devices. The research highlights the integration of piezo sensors for precisely detecting pressure changes within the household and using a variety of Arduino boards to transmit this signal to a control system. The paper also examines how to trigger cameras equipped with image recognition technology to identify unfamiliar faces or suspicious behaviours, along with motion-based multiple object tracking and face identification when pressure changes are detected. Additionally, the paper discusses future developments, such as deep-learning-based object recognition and enhanced encryption methods, to uphold accuracy, privacy, and security.
Hydrological Influences on Landslide Dynamics in the Three Gorges Reservoir Area: An SBAS-InSAR Study in Yunyang County, Chongqing
Authors: Cui jinhu , Tao Yuxiang , Kou Pinglang , Jin Zhao , Huang Yijian , Zhang Jinlai 
Published: April 2024

Abstract

Landslide hazards pose a significant threat to lives and infrastructure, especially in mountainous regions like the Three Gorges Reservoir area. While the mechanisms driving landslide initiation and progression in reservoir environments are not fully understood. This study aimed to leverage the capabilities of Sentinel-1 satellite imagery and the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to detect and monitor potential landslide deformations in Yunyang County, Chongqing, China. We utilized Sentinel-1 data acquired between January 1, 2020, and December 28, 2022, to generate deformation velocity maps. Twelve potential landslides were identified, primarily concentrated near residential areas and along the Yangtze River. Precipitation emerged as the primary driver of surface deformation and landslide initiation, with potential landslides in residential vicinities and along the river exhibiting significantly higher deformation rates during the wet season compared to the dry season. These sites are susceptible to slope failures and geological disasters upon reaching critical antecedent rainfall thresholds, highlighting the necessity for continuous monitoring. Other potential landslides maintained consistent deformation rates across seasons but experienced brief accelerations following heavy precipitation events. Notably, potential landslides adjacent to the Yangtze River experienced accelerated deformation during periods of significant river water level reductions, suggesting that the river's cyclical water level fluctuations influence slope stability. The study demonstrated the effectiveness of SBAS-InSAR in detecting millimetric deformations in incipient landslides, a crucial step in averting landslide disasters and ensuring public safety.
Performance study of indirect perforated dew-point evaporative coolers
Authors: Liu Xuliang , Jing Chengjun , Lyu Siqiang 
Published: April 2024

Abstract

The Maisotsenko cycle-based coolers have gained increasing attention in recent years due to their advantages of low energy consumption and environmental friendliness. The optimization of model structure and operating conditions is the primary approach for enhancing the cooling performance of dew-point evaporation systems. In this paper, a new mathematical model of the perforated dew-point evaporative cooler was developed to study the cooling performance. The key findings that emerged from this investigation were: (1) The impact of model size and inlet air parameters on the performance of both perforated and non-perforated dew-point evaporative cooling systems exhibited similar trends. (2) The performance of the dew-point evaporative cooler could be enhanced by employing the perforation method when the total air supply ratio was below 0.5, and optimal performance was achieved with a single-perforation design. (3) When the supply air ratio was 0.3, the outlet air temperature of the dry channel initially decreased and subsequently exhibited a gradual increase with an elevated supply air ratio at the outlet of the dry channel. Notably, when the supply air ratio ranged from 0.5 to 0.6 at the outlet of the dry channel, it resulted in the lowest recorded air temperature.
Deubiquitinase USP18 inhibits hepatic stellate cells activation and alleviates liver fibrosis via regulation of TAK1 activity
Authors: Zhang Yan , Gao Jing , Liu Yi , Zhong Li , He Song , Qiu Chan 
Published: April 2024

Abstract

Background & Aims:
Activation of hepatic stellate cells (HSCs) is the key process underlying liver fibrosis. Unveiling its molecular mechanism may provide an effective target for inhibiting liver fibrosis. Like other post-translational modifications, protein ubiquitination modification is a dynamic and reversible process. Deubiquitinases (DUBs) catalyze the removal of ubiquitin chains from substrate proteins, thereby inhibiting the biological processes regulated by ubiquitination modification signals. However, there are currently few studies revealing the role of deubiquitination in the activation of HSCs.
Methods & Results:
Single-cell RNA sequencing (scRNA-seq) revealed significantly decreased USP18 expression in activated HSCs when compared to quiescent HSCs. In mouse primary HSCs, continuous activation of HSCs led to a gradual decrease in USP18 expression whilst restoration of USP18 expression significantly inhibited HSC activation. Injection of USP18 lentivirus into the portal vein of a CCl4-induced liver fibrosis mouse model confirmed that overexpression of USP18 can significantly reduce the degree of liver fibrosis. In terms of mechanism, we screened some targets of USP18 in mouse primary HSCs and found that USP18 could directly bind to TAK1. Furthermore, we demonstrated that USP18 can inhibit TAK1 activity by interfering with the K63 ubiquitination modification of TAK1.
Conclusions
Our study demonstrated that USP18 inhibited HSC activation and alleviated liver fibrosis in mice via modulation of TAK1 activity; this may prove to be an effective target for inhibiting liver fibrosis.
Discovery of A Novel Hemp Branching Mutant
Authors: Kim Juyoung , Kim Dong-Gun , Kim Jin-Baek , Ryu Jaihyuk , Kim Sang Hoon 
Published: April 2024

Abstract
Cannabis (Cannabis sativa L.) is a unique crop producing cannabinoids, including tetrahydrocannabinol (THC) and cannabidiols, but it is largely prohibited or strictly regulated in most countries because of the psychoactive effects of THC on humans. However, there has recently been increasing interest in cannabis because of clinical research suggesting it has therapeutic effects. Because of its physiological properties and limited accessibility, ensuring homozygosity in cannabis is challenging. Most cannabis plants that are currently sold are hybrids. The SupwerowomanS1 cultivar was used to develop a new cultivar, document genetic variation, and identify a novel hemp mutant following self-pollination during polyploid breeding. A mutant with fewer axillary stems than SuperwomanS1 and round floral organs with many sugar leaves (like rosette leaves) was identified. A quantitative real-time PCR analysis indicated the expression levels of the main genes regulating axillary bud formation (SHOOT MERISTEMLESS, LATERAL SUPPRESSOR, REVOLUTA, WUSCHEL) were higher in the mutant than in SuperwomanS1. These findings may be relevant to hemp breeding and cultivation.
Seismic Behavior Assessment of Special Concentrically X-Braced Frame with Through Gusset Plate
Authors: Asghari Abazar , Hosseini Sohrab 
Published: April 2024

Abstract
Concentrically braced frames exhibit adequate stiffness against lateral loads. However, a critical issue with these frames lies in the connection between the brace and beam/column. The compressive and tensile forces in the braces induce significant shear at the end of the beam, leading to yielding of the beam and failure of the connection to the column. Additionally, in many cases, welds at the edge of the gusset plate to the beam experience premature failure due to stress concentration before brace yielding or buckling. In this study, it is proposed to replace the I-shaped beam with a double channel beam (2-UNP) and to allow the gusset plate to pass continuously through the beam. Consequently, in consecutive stories, there will be a continuous connection plate passing through. The research results demonstrate that in this configuration, the stress level in the beam web, connection of the beam to the column, and weld at the edge of the connection plate are significantly reduced. In frames with through gusset plates, as a portion of the brace force is transferred through the connection plate passing through the U-shaped beam, less force is absorbed by the weld, preventing premature brace yielding or buckling before weld failure. Furthermore, due to increased allowable drift in frames with through gusset plate, the ductility of the frame enhances compared to frames with a conventional gusset plate.
Meta-QTL analysis and candidate genes identification for lodging resistance in maize: Ⅰ. stalk related traits
Authors: Fang Haiyue , Qu Wenli , Zhang Chunxiao , Cui Haiyan , Zhou Xiaohui , Dong Jing , Liu Xueyan , Li Xiaohui , Jin Fengxue 
Published: April 2024

Abstract
Lodging seriously affects maize yield and quality, complicating mechanical harvest. Lodging can be caused by environmental and genetic factors. While many quantitative trait loci (QTL) have been identified from different types of genetic populations using different mapping methods, to identify the genetic mechanisms that affect maize stalk lodging resistance, few QTLs have been successfully used in maize breeding programs. Therefore, identifying QTLs that are stable and that can be introgressed into elite cultivars using marker-assisted selection has commercial and agricultural implications. Following a review of 31 published studies on stalk lodging resistance in maize we collected 546 QTLs. After synthesizing data from these studies, a meta-QTL analysis is performed using BiomercatorV4.2 to identify 70 MQTLs for maize lodging resistance, and six candidate genes in meta-QTL intervals base on orthologous analysis with rice lodging cloned genes. Specific expression patterns reveal these genes to be involved in stalk development. These candidate genes may be important for engineering lodging-resistance in maize.
Tailoring band gap and photocatalytic activity of ZnO via Cu doping for enhanced Congo Red degradation
Authors: Deshwal Tamanna , Kumar Pawan , Ahlawat Simran , Kumar Sanjeev , Kaur Harpreet , Kumar Ashish , Kumar Abhishek 
Published: April 2024

Abstract

This paper reports the improvement in the photocatalytic performance of ZnO by substituting Cu with a variable concentration. ZnO and Cu 0.5%, 1.0%, and 2.0% doped ZnO nanoparticles have been synthesized by the sol-gel combustion method. Before measuring photocatalytic properties, we have confirmed the HCP structure and granular nanoparticle morphology of all samples with XRD and SEM analysis. Function groups have been ascertained by FTIR peak assignment. Small variations in structural parameters and ZnO stretching mode indicate substitution of Cu at the ZnO site of the ZnO nanostructure. The band gap engineering with variable Cu concentration successfully reduces the apparent band gap, which helps improve the photocatalytic This research shows that Cu-doped ZnO nanoparticles are better at breaking down Congo red (CR) dye than pure ZnO nanoparticles. Remarkably, ZnO: Cu 2% (also used at a concentration of 120 mg/L) has an outstanding removal efficiency of 97.21%. This accomplishment highlights the substantial impact of pseudo-first-order kinetics, offering a precise and thorough explanation of the photodegradation process.
Association of fatty pancreas and subclinical atherosclerosis: A cross-sectional analysis
Authors: Liu Qingxie , Liu Xinyi , Wang Yaodong , Luo Weiwei , Dong Xiaowu , Zhu Qingtian , Yuan Chenchen , Lu Guotao , Xiao Weiming , Yu Xiaoping 
Published: April 2024

Abstract
Background:
To date, no correlation between fatty pancreas and carotid plaque has been reported. Therefore, this study used a large medical examination cohort from Yangzhou to investigate the association between fatty pancreas and subclinical atherosclerosis.
Methods:
Clinical data were collected between January 2018 and December 2021 from a population undergoing health check-ups at the Health Management Centre of the Affiliated Hospital of Yangzhou University. Carotid vascular ultrasound findings were used to divide the participants into carotid plaque and non-carotid plaque groups on the basis of independent risk factors for carotid plaque.
Results:
A total of 6976 cases in the carotid plaque group and 17 069 cases in the non-carotid plaque group were included in this study. Logistic regression model analysis of carotid plaque showed that men (odds ratio [OR] = 1.479, P < 0.001), age (OR = 1.110, P < 0.001), body mass index (OR = 1.005, P < 0.001), history of smoking (OR = 1.446, P < 0.001), history of alcohol consumption (OR = 1.160, P < 0.001), hypertension (OR = 3.296, P < 0.001), diabetes mellitus (OR = 4.077, P < 0.001), fatty pancreas (OR = 1.490, P < 0.001), hypercholesterolaemia (OR = 1.175, P < 0.001), and low-density lipoprotein cholesterol atheroma (OR = 1.174, P < 0.001) were independent risk factors for carotid plaque. Subgroup analysis indicated that fatty pancreas was an independent risk factor for carotid plaque in participants without these complications compared with participants with a history of hypertension or diabetes.
Conclusion:
Fatty pancreas is an independent risk factor for carotid plaque and has a greater impact in individuals without a history of hypertension or diabetes than in those with.
Identification, evolutionary and expression analysis under high-salt stress of ACC synthase gene family in Glycine max (L.)
Authors: Zhang Xingzheng , Liu Xin , Yang Jing , Sun Yiwen , Huang Haojie , He Hongli , Piao Jingpei , Shen Jie , Qiao Xuqiang , Cheng Yunqing 
Published: April 2024

Abstract
ACC synthase (ACS) is an important rate-limiting enzyme in the plant endogenous ethylene biosynthesis process and has been associated with growth and development and response to abiotic stresses s, including salt stress, in plants. The roles of ACS genes in soybean involved in salt response remains poorly understood. The findings in this study provide a crucial foundation and potential functional genes for the investigation of salt stress in soybean. In this study, 20 ACS homologs with conserved Aminotransferase class I and II domain were screened from the soybean genome. Furthermore, an expression database and Real-time quantitative reverse transcription (qRT-PCR) were used to identify the gene expression patterns in specific tissues in response to high-salt stress. Phylogenetic analysis revealed that the ACS homologs were distributed on 10 chromosomes and divided into 3 groups (Group I ~ III). 18 pairs of GmACS genes shared collinearity, and they originated from segmental replication after the second round whole genome duplication of soybean. The promoter regions of GmACS genes also contained several diverse elements related to plant hormones and stress response by cis-acting elements analysis. Gene expression analysis revealed that some genes exhibited tissue-specific expression patterns. Moreover, we identified candidate functional genes involved in response to high-salt stress in different tissues of young seedlings, including GmACS1 in root tissue. Our findings reveal novel candidate molecular components for subsequent studies on the molecular regulatory mechanisms of ACS in response to high salinity stress in soybean and functional components to facilitate further breeding of salinity-tolerant germplasm in soybean.
Adapting Triple-BigGAN for Image Detection Tasks: Challenges and Opportunities
Authors: Quaicoo Russell , Acheampong Richmond , Gyamenah Pius , Dodoo Albert Ankomah , Soli Michael Agbo Tettey , Appati Justice Kwame 
Published: April 2024

Abstract
Recent years have seen notable progress in generative modeling, leading to the emergence of the Triple-BigGAN model as an extension of the pioneering BigGAN model. This thesis scrutinizes the Triple-BigGAN model, investigating its role in augmenting image quality and its integration with a co-trained classifier. Through comprehensive experimentation and analysis, this research probes into the complexities encountered during experimentation and the insights gleaned from employing varied computational environments such as Google Colab, Kaggle Notebooks, and Google Vertex AI. Utilizing metrics like Fréchet Inception Distance (FID), Inception Score (IS), categorical cross-entropy loss, and accuracy, the dissertation evaluates the algorithm's efficacy in both image generation and classification tasks. It delineates the delicate balance among the generator, discriminator, and classifier elements within the model. This exploration of the Triple-BigGAN algorithm contributes to a deeper comprehension of advanced generative models, elucidating their potentials and challenges while laying the groundwork for further advancements at the nexus of generative and discriminative AI techniques.
Efficient Multi-Class Image-Based Rosemary Variety Verification and Classification Model Using Deep Learning:
Authors: Asresa Tsega 
Published: April 2024

Abstract
Artificial intelligence (AI) has a subfield called computer vision that allows systems and computers to extract replacement data from digital photos and videos. It is used in many fields, including agriculture, health care, education, self-driving cars, and daily living. In Ethiopia, rosemary is a well-known aromatic and therapeutic plants. It is an evergreen herb that belongs to the shrub family and it is widely used specious in Ethiopia and it is classified in to three varieties such as WG rosemary I, WG rosemary II, WG rosemary III. Botanists, researchers, herbal industries, pharmacists and domain experts are facing challenges to classify appropriate varieties. And no research is conducted that identify and classify those varieties. However; there is lack of technologies’ that identify the varieties of rosemary in Ethiopia. The proposed study is employed supervised machine learning and multi class image classification. This study is conducted using convolutional neural network by employing softmax activation function as a last layers. Due to this reason we are going to implement the classification model of rosemary using multi class classification. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3 and Xception. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 98.8% and 97.7%, respectively.