bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leishmania donovani persistence and transmission causing cutaneous leishmaniasis in unusual-foci of Nepal
Authors: Rai Tinmaya , Shrestha Srijan , Prajapati Sabita , Bastola Anup , Parajuli Niraj , Ghimire Pragya Gautam , Bhandari Parmananda , Pandey Kishor , Jain Manju , Matlashewski Greg , Goncalves Rachel Bras , Manandhar Krishna Das 
Published: March 2023

Abstract
Cutaneous leishmaniasis cases have increased dramatically in recent years in Nepal. The study offers molecular identification of the Leishmaniaspecies using 40 patient's aspiration biopsy samples, targeting markers kinetoplast minicircle DNA (kDNA) and internal transcribed spacer-1 (ITS1). Among molecularly diagnosed 22 cutaneous leishmaniasis cases, L. donovani complex was identified in 13 instances and L. major in 9 cases. The ITS1 PCR was positive in 12 of the positive nested- kDNA PCR cases (12/22), confirming L. donovani complex in seven of the cases and L. major in five of the cases. In addition, the study conclude that concurrent occurrence of atypical cutaneous infections caused by L. donovani parasite in 59.1% of cases and typical cutaneous infections caused by L. major parasite in 40.9% of cases. The detected L. donovani species present null genetic distances from seven references of L. donovani, but slight differences between ITS1 sequences and not grouped into a significant monophyletic cluster indicating the possibility of new variant of or hybrid circulating in the country.
Performance Analysis of Hybrid Underwater Wireless System for Shallow Sea Monitoring.
Authors: Bhatnagar Romya , Garg Parul 
Published: March 2023

Abstract
This paper investigates the performance of hybrid dual hop underwater system which has been proposed for monitoring vast region under shallow sea environment. This hybrid underwater opto-acoustic sensor network (UOASN) is designed to provide higher data rates and less propagation delay with respect to traditional acoustic underwater systems, by including optical carrier. An acoustic sensor and an optical sensor are mounted on shallow water floor at different locations that acquire the surrounding information and transmit it continuously to the underwater vehicle based on round-robin scheduling. Such vehicle is comprised of decode-and-forward relaying mechanism. The underwater acoustic link is determined by alpha-F fading distribution and underwater optical link follows the mixture Exponential-Generalized Gamma (EGG) model to characterize channel irradiance fluctuations. The novel closed form expressions for various end to end (E2E) signal to noise ratio (SNR) statistics such as equivalent probability density function (PDF), cumulative distribution function (CDF) and moments have been derived. The analytical expressions are also obtained for outage probability, average bit error rate, ergodic capacity and outage capacity. Besides, the closed form asymptotic expressions for outage probability and average bit error rate are derived.
Fabrication of g-C3N4 nanosheet on stainless steel mesh for effective separation of oil from water
Authors: Al-Kindi Nada Saeed , Marzouqi Faisal Al , Khraisheh Majeda , Kim Younghun , Selvaraj Rengaraj 
Published: March 2023

Abstract
Nowadays, most of the industries depend mainly on oil and oil-based processes, which resulted in producing large volumes of oily wastewater. One of the most common methods used for the treatment of oily contaminated water is the filtration method by modified surfaces. In this research g-C3N4 nanostructured material was prepared via thermal condensation method. g-C3N4 were crystallized in tri-s-triazine phases and their mean crystalline sizes of these nanostructures were 12.17 nm. The high-magnification microscopy images show that the morphology of g-C3N4 were nanosheets. A stainless-steel meshes were modified and coated with the prepared g-C3N4 nanostructured materials to be used for the separation of oil and water mixture. Due to the hydrophobic nature of the modified meshes, oil drops spread over the mesh surface and the water drops form spherical shapes. The most efficient coating among all the modified meshes was g-C3N4, which was functionalized using silane moiety. The separation efficiency of this coated mesh reached 74.87% and it resulted to fast separation. This mesh can separate different types of oil from the oil/water mixture such as toluene, mineral oil, 2-ethyl-1-hexanol, and n-pentane with good efficiency. In addition, the modified mesh can be used up to 40 times and still gives good separation efficiency.
A combination of urinary antibiotics as a new potential biomarker for adolescent depression
Authors: Jin Yaling , Jin Xia , Ge Zhenhua , Zhang Jianbiao , Ding Yaqin , Wang Peijuan , Qiu Jiancheng , Liu Chao , Yi Zhenghui , Zhao Ningwei , Shen Ning , Wu Xuming , Yan Qi 
Published: March 2023

Abstract
Background: By exposing to various sources of antibiotics, such as medication, meat and contaminated water, the accumulation of antibiotics is considered a pathogenic factor in the mental disorders of adolescents. The purpose of this study was to investigate the relationship between urinary antibiotics and adolescent depression.
Methods: 62 participants were divided into two groups according to their diagnosis: 32 healthy control group and 30 adolescent depression group. All the urine samples were collected in the morning and subjected to the analysis of urinary antibiotics by liquid chromatography tandem mass spectrometry (HPLC-MS). This study detected the urinary levels of four commonly used antibiotics azithromycin, sulfadimidine, ofloxacin and ampicillin.
Results: Urinary levels of azithromycin, sulfadimidine, ofloxacin and ampicillin were significantly higher in the depression patients group compared to the control group. All the antibiotics were positively correlated with the HAMA score. Binary logistic analysis showed azithromycin (OR=1.05, P=0.002), sulfadimidine (OR=1.22, P<0.001), ofloxacin (OR=3.79, P<0.001), ampicillin (OR=352.57, P<0.001) were risk factors for adolescent depression. The ROC curve showed each of the four urinary antibiotics had a good potential to predict the adolescent depression (azithromycin (AUC=0.778, P<0.001), sulfadimidine (AUC=0.741, P=0.001), ofloxacin (AUC=0.772, P<0.001) and ampicillin(AUC=0.810, P<0.001)), while the combination of all the four urinary antibiotics showed the best prediction accuracy for the diagnosis of the adolescent depression (AUC=0.814, P<0.001).
Limitation: Due to the cross-sectional study design, the result cannot demonstrate causality.
Conclusion: Our study revealed the novel possibility of urinary antibiotics as a potential external exposure biomarker for the early diagnosis of adolescent depression.
Fire safety prediction for polypropylene composites in flammable environments
Authors: Dong Xinxin , Zhang Daniel Xiaotian , Liu Jian , Dong Fanfei , Sun Jun , Gu Xiaoyu , Zhang Sheng 
Published: March 2023

Abstract

The modeling of polymer combustion is a big challenge due to the fast speed and complexity of various reactions during the flammable environments. Limiting oxygen index (LOI), heat release rate (HRR), and total heat release (THR) are three key parameters to evaluate the flammability of polymeric composites. In this work, cubic interpolation and Lagrange interpolation methods are used to simulate the data and predict the flammability of PP containing different loads of aluminum hydroxide (ATH). Simple formulations containing ATH were designed to avoid the influence of other fillers on the combustion process. The LOI, HRR, and THR are simulated and verified by the experimental data. The advantages and disadvantages of the two modeling methods in predicting the combustion data are compared. It was demonstrated that the cubic method was more precise than the Lagrange method in predicting the LOI value of PP composite. Both methods were suitable for predicting HRR and THR values of PP composites containing low amount of ATH (less than 35%). This work has important reference significance in predicting the fire performance of polymers containing inorganic additives.
Membranes prime the RapGEF EPAC1 to transduce cAMP signaling
Authors: Cherfils Jacqueline , Sartre Candice , Ferrandez Yann , Peurois François , Ley Marie , Zhang Wenhua , Kryszke Marie-Hélène , Courilleau Delphine , Fischmeister Rodolphe P. , Ambroise Yves , Zeghouf Mahel , Cianferani Sarah , Peyroche Gérald 
Published: March 2023

Abstract
EPAC1, a cAMP-activated GEF for Rap GTPases, is a major physiological transducer of cAMP signaling and a therapeutic target in cardiac diseases. The recent discovery that cAMP is compartmentalized in membrane-proximal nanodomains challenged the current model of EPAC1 activation in the cytosol. Here, we discover that anionic membranes are a major component of EPAC1 activation. We find that anionic membranes activate EPAC1 in the absence of cAMP, that they increase its affinity for cAMP by 2 orders of magnitude, and that they synergize with cAMP to yield maximal GEF activity. Thus, EPAC1 has four states that differ in their affinity for cAMP and GEF efficiency. In the cell cytosol, where cAMP is low, EPAC1 must thus be primed by membranes to bind cAMP. Examination of the cardiomyocyte-active chemical CE3F4 in this new framework further reveals that inhibition affects only membrane- and cAMP-activated EPAC1. Together, our findings reformulate previous concepts of cAMP signaling to include a hitherto overlooked role of membranes through EPAC proteins, with important implications for drug discovery.
WITHDRAWN: Generalized translation operator and Heat equation for the generalized canonical Fourier Bessel transform
Authors: SADIK Zakaria , AKHLIDJ Abdellatif 
Published: March 2023

Abstract

Note: Please see pdf for full abstract with equations.
The aim of this paper is to introduce a translation operator associated to the generalized linear canonical Fourier Bessel transform Fmα,n and study some of the important properties, and we derive a convolution product for this transform and as application we study the heat equation and the heat semigroup related to the conjugate of the generalized Bessel operator Δmα,n.
MSC Classification: 33D15; 47A05; 47B90
Impact of Corona virus disease 2019 on antenatal care services in rural western Uganda; a retrospective study
Authors: Abeza Diana , Tayebwa Beckson , Muhumuza Joshua , Nabakka Majoreen , Ngonzi Joseph 
Published: March 2023

Abstract
Introduction: The Coronavirus 2019 (COVID-19) outbreak poses an important threat to public health but also unique challenges to healthcare workers. The pandemic has resulted into redirection of funds and attention by governments, donors, and stakeholders towards COVID-19 containment efforts, thereby diverting focus from other important issues including sexual and reproductive health. This study was aimed at determining the impact of Covid-19 on antenatal care services at Kampala international university teaching hospital (KIU-TH) between March and May 2020.
Methods: This was a retrospective study in which we reviewed records of mothers who attended antenatal care clinic at KIU-TH for the months of March, April and May in both 2019 and 2020. The health workers attached to the antenatal care clinic during the periods filled a questionnaire to report on challenges faced. The data obtained was analyzed using SPSS version 22.
Results: Data for 2,379 clients was analyzed in total. The percentage reduction in antenatal care attendance was 7.1% in the year 2020. The services that were significantly affected were fetal heart listening and administration of intermittent preventive treatment (IPT) for malaria prophylaxis. The main challenges reported were lack of transport means, excessive work and exhaustion plus fear of contracting COVID-19 infection.
Conclusion: COVID-19 pandemic significantly reduced antenatal care service provision. Measures should be put in place to ensure that antenatal services can be offered appropriately and safely without compromising the clients nor the health care workers during outbreaks.
Spatiotemporal Variability of the Relationship Between Seasonal Temperatures and Precipitation in the Iberian Peninsula, 1951-2019
Authors: Rodrigo F. S. 
Published: March 2023

Abstract
This paper studies the spatiotemporal variability of the IRt index (defined as the difference between the percentage of precipitation corresponding to warm days and cold days in year t) calculated at 35 stations in the Iberian Peninsula during 1951-2019. Spatial variability is estimated using cluster analysis (Euclidean distance, Ward's method), which allows regionalization of the data set for each year's season. For each cluster, the <IRt> index is defined as the average of the indexes corresponding to each cluster element. The temporal evolution of the <IRt> indices is analyzed by studying the appearance of trends using the Mann-Kendall test and the possible existence of various subperiods using the cumulative sum of deviations and the t-test for the difference between the means. The role of EA, EA/WR, NAO, SCAN and WeMO teleconnection patterns in modulating the relationship between temperature and precipitation is analyzed by applying multiple regression analysis. The results show a trend towards positive (or less negative) values in the relationship between temperatures and precipitation (of varying magnitude depending on the region and season) and the contribution of atmospheric dynamics to these changes.
Efficient Deep Learning based Code Retrieval using Unified Graph Structure and Semantic Graph Matching Encoder
Authors: Bashir Shariq , Rahman Hanif Abdul 
Published: March 2023

Abstract
Computer programmers frequently use code retrieval systems to reuse existing code snippets from open-source repositories. These systems search a large collection of code snippets to retrieve the most relevant ones based on a text query. However, capturing semantic information between user queries and code snippets presents a key challenge in this task. Previous works have primarily used natural language processing (NLP) approaches to calculate relevance, but these approaches cannot capture deep structural and semantic dependencies between queries and snippets. In this study, we proposed a novel approach called Deep Graph-Based Semantic Representation and Matching (DeepGSR) for code retrieval. Our approach transforms queries and code snippets into a unified graph-structure representation and then retrieves relevant code snippets using a novel graph matching and retrieval approach. DeepGSR learns fine-grained relevance between queries and code snippets using cross-attention-based semantic matching operators, in addition to extracting structural information. We evaluated our approach using two publicly available code retrieval datasets, and the experiments demonstrate that DeepGSR efficiently retrieves relevant code snippets for a given query and significantly outperforms existing code retrieval approaches.
A predictive model for vascular complications of free flap transplantation based on machine learning
Authors: YANG Jijin , Liang Yan , WANG Xiaohua , LONG Wenyan , WEI Zhengang , Liqin LU , LI Wen 
Published: March 2023

Abstract
Objective: Exploring the risk factors for vascular complications after free flap transplantation and establishing a clinical auxiliary assessment tool for vascular complications in patients undergoing free flap transplantation based on machine learning methods.
Methods:Collecting patients who underwent free flap transplantation at a tertiary hospital in Guizhou Province from January 1, 2019 to December 31, 2021, using synthetic minority oversampling technique to oversample the training set, and constructing Logistic regression model, random forest model and neural network model three machine learning models and verifying them using the sampled data. Using the test set to evaluate the performance of the model through the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity indices.
Results: A total of 570 patients who underwent free flap transplantation were included in this study, of which 46 patients developed postoperative vascular complications. The neural network model performed best in the test set, with an AUC of 0.828. Multivariate logistic regression analysis showed that preoperative hemoglobin, preoperative fibrinogen, operation time, smoking history, number of anastomoses, and peripheral vascular injury were statistically significant independent risk factors for vascular complications after free flap transplantation. The top five predictive factors in the neural network were fibrinogen content, operation time, donor site, BMI, and platelet count.
Conclusion: The predictive model for vascular complications of free flap transplantation constructed in this study has good predictive ability, which can provide reference for medical personnel to take preventive measures to prevent vascular complications in high-risk patients undergoing free flap transplantation.
Magnetic resonance imaging-based radiomics assesses the level of immune cell infiltration in the breast cancer tumor microenvironment
Authors: Qian Hua , Ren Xiaojing , Xu Maosheng , Fang Zhen , Zhang Ruixin , Bu Yangyang , Zhou Changyu 
Published: March 2023

Abstract
Purpose The tumor immune microenvironment provides information regarding prognosis and prediction. To screen the immune cells associated with the prognosis of breast cancer (BRCA) patients from the Cancer Genetic Atlas (TCGA) and establish an MRI-based radiomics model for evaluating the level of immune cell infiltration in breast cancer patients.
MethodsCIBERSORT was used to assess the level of infiltration of 22 immune cell types from retrospective data of 1096 breast cancer patients from the TCGA database, and univariate and multivariate Cox regressions were applied to assess the prognostic value of the level of immune cell infiltration in BRCA patients to obtain independent prognostic factors for BRCA patients. We extracted imaging features from the Cancer Imaging Archive (TCIA) database for 73 patients with preoperative MRI data. The best imaging features were selected using the Least absolute shrinkage and selection operator (LASSO) to establish an MRI-based radiomics model for evaluating the level of immune cell infiltration in breast cancer patients.
Results M2 macrophages were found to be an independent prognostic factor for BRCA patients based on the results of Cox regression analysis (HR=32.288, 95% CI: 3.100-357.478). A total of nine important features were selected for calculating radscore, A intratumoral model was established with AUCs (95% CI) of 0.662 (0.495-0.802) and 0.678 (0.438-0.901) in the training and testing cohorts, respectively. A peritumoral model was established with AUCs (95% CI) of 0.826 (0.710-0.924) and 0.752 (0.525-0.957). A combined model was established with AUCs (95% CI) of 0.843 (0.723-0.938) and 0.744 (0.491-0.965). The peritumoral model had the highest diagnostic efficacy, with accuracy, sensitivity and specificity of 0.773, 0.727 and 0.818 respectively in its testing cohort.
ConclusionMRI-based radiomics model may evaluate the level of immune cell infiltration in breast cancer and might provide a non-invasive imaging biomarker for the assessment of the tumor microenvironment in breast cancer.
Basic physical properties and potential application of graphene oxide fibers synthesized from rice husk
Authors: Castro-Ladino J. R. , Cuy-Hoyos C. A. , Prías-Barragán J. J. 
Published: March 2023

Abstract
The synthesis method and correlation between compositional, vibrational, and electrical properties in graphene oxide fibers (GOF) are presented and discussed here, and a potential application through the development of a heater device based on GOF. The GOF samples were synthesized from rice husk (RH), via a thermal decomposition method, employing an automated pyrolysis system with a controlled nitrogen atmosphere, varying carbonization temperature (TCA) from 773 to 1273 K. The compositional analysis shows peaks in XPS spectrum associated with C1s and O1s, with presence of hydroxyl and epoxy bridges; the oxide concentration (OC) of samples varied from 0.21 to 0.28, influenced by TCA. The GOF samples exhibits morphology of fibers, vibrational characteristics, typical of graphene oxide multilayers and electrical behavior that scale with OC. The electrical response shows that OC decreases and increases electrical conductivity at the polycrystalline phase, possibly attributed to the desorption of some oxides and organic compounds. Likewise, the physical correlations between OC and vibrational response, revealed that decreased OC and increases in boundary defects density and decreased crystal size, as a consequence of thermal decomposition processes. The correlation between OC and physical properties suggests that by controlling the OC in GOF, it was possible to modify vibrational and electrical properties of great interest in fabrication of advanced electronics; consequently, we show a potential application of GOF samples developing an electrically controlled heater device.