bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unlocking Growth: A Comprehensive Analysis of Indian Exports through ARDL Methodology and the Catalytic Role of Advanced Technology in Enhancing Exports and GDP.
Authors: Singh Vipul 
Published: January 2024

Abstract
This study examines the relationship between exports, export instability, foreign currency reserves, and economic growth in India from 2001 to 2021. The Autoregressive Distributed Lag model is used to analyze the data, while Granger causality analysis is utilized to determine the causative relationships among the variables and additionally, explain how new technology will help to boost trade and economic growth. The data used in this study was sourced from reputable academic publications, including the Handbook of Statistics on Indian Economy published by the Reserve Bank of India (RBI), the World Integrated Trade Solution (WITS) database, and many editions of the Economic Survey. This study also examines several statistical tests such as Autocorrelation, Heteroskedasticity, and Normality tests. The finding of the study shows the Error Correction Term (ECT) had a statistically significant effect with a p-value of 0.00. The rate of adjustment is at a level of 33 percent. The findings of the Granger Causality test indicate the existence of a bidirectional relationship between exports and GDP, as well as a unidirectional relationship between export instability and economic growth. Export instability has been shown to have a positive impact on economic growth. However, it has been observed that economic growth does not have a causal effect on export instability. Furthermore, there is no association between foreign currency reserves and GDP.
Downscaling daily fine Particulate Matter (PM2.5) concentration maps for Ho Chi Minh City
Authors: Nguyen Phuong D.M. , Phan An H. , Ngo Truong X. , Ho Bang Q. , Pham Vu T. , Nguyen Thanh T.N. 
Published: January 2024

Abstract
The problem of PM2.5 pollution is a major concern in both Vietnam and around the world, with adverse effects on human health, animals, and the environment. It is crucial to monitor PM2.5 levels regularly on a large scale to assess air pollution and develop effective solutions. Besides, fine particulate matter (PM2.5) mapping at high resolution can have significance in studying pollution at a small scale. Nevertheless, most current researches on high-resolution PM2.5 mapping depend on high-resolution aerosol optical depth products. In this study, we propose a method to enhance the spatial resolution of low-resolution (3km) PM2.5 products and improve the quality of model output. The proposed method utilized a machine learning-based downscaling approach to generate high-resolution (1km) PM2.5 maps for Ho Chi Minh City in 2021. We also incorporated additional data sources such as meteorological data and land use information to improve the accuracy of the products. The proposed method was evaluated through numerical experiments, and the results showed a significant enhancement of the spatial resolution of PM2.5 products, from 3km to 1km and improved the accuracy of the output. Four models were trained and validated using data collected from 2018 to 2021. Catboost model yielded the best results in terms of predictive power with a Pearson R of 0.80, RMSE of 6.46 µg/m3, and MRE of 0.21 out of 2891 samples. The aggregated monthly and annual average maps of PM2.5 concentration in Ho Chi Minh City in 2021 exhibited exceptional quality compared to the 3km-resolution PM2.5 product. These concentration maps effectively depicted the spatial distribution and seasonal variations of PM2.5 in Ho Chi Minh City.
Machine Learning-Aided Molecular Dynamics Simulation for Prediction of Binding Kinetics
Authors: Shahbazi Fatemeh , Esfahani Mohammad Nasr , Keshmiri Amir , Jabbari Masoud 
Published: January 2024

Abstract

Chemical sensors provide new solutions to address some of the world’s biggest challenges, including climate change, energy and healthcare. Understanding molecule binding kinetics and thermodynamics is essential in enhancing the design and functionality of chemical sensors. To contribute to this field, we have developed a numerical framework to predict the binding kinetics without requiring experimental inputs. Once the target molecules and fictional surface are identified, the details alongside the environment and mass transport are included as input to this code. The output would be the predictive model of target molecule behaviour passing by the surface. This framework comprises an all-atom molecular dynamics model and a Bayesian machine learning model for predicting affinity. Different predictive models have been trained, and the Bayesian-based Gaussian process regression (GPR) best predicts the binding reaction amongst them all. The predictive model is validated for an aluminium-based platform. The proposed numerical framework has the potential to be generalised and, therefore, contribute to future low-cost binding reaction estimations, providing a valuable tool for industry and experimentalists.
Optimization of Culture Conditions and Batch-Process Control for the Augmented Production of Bacteriocin by Bacillus Species
Authors: Elazzazy Ahmed M. , Mobarki Mona O. , Baghdadi Afra M. , Bataweel Noor M. , Alhejin Ahmed 
Published: January 2024

Abstract
Background: The rise of antibiotic-resistant microorganisms is a major global health concern. This study explores the potential of soil-derived bacterial isolates in combating such pathogens, focusing on their antimicrobial properties.
Results: Fifteen bacterial isolates from agricultural and polluted soils in Jizan and Jeddah were screened for their ability to inhibit common human pathogens. Two Bacillus strains, Bacillus atrophaeus and Bacillus amyloliquaefacins, were identified via 16S rDNA analysis. These strains showed notable antibacterial activity against various pathogens, including Methicillin-Resistant Staphylococcus aureus(MRSA) and Pseudomonas aeruginosa. Optimizing production conditions for their bacteriocin revealed that nutrient and Muller Hinton broths were ideal media, with optimal production observed at 37°C and pH levels of 7 and 8 for Bacillus atrophaeus and Bacillus amyloliquaefacins, respectively. Enhanced production was achieved in a 10-L bioreactor with controlled pH, doubling bacteriocin yield. The study monitored growth, substrate utilization, pH variation, and bacteriocin production over time.
Conclusions: The isolated Bacillus strains show promise as sources of potent antimicrobials against antibiotic-resistant bacteria. The optimization of culture conditions significantly boosts bacteriocin production, highlighting the potential of these strains in developing new antimicrobial agents.
Quantile Transformation Gabor and Edge Techniques for Brain Tumour Segmentation in MRI Images
Authors: G shruthi , M krishna raj P 
Published: January 2024

Abstract

The segmentation of a brain tumor is an exciting and exigent research task in the field of medical image analysis. An early finding of a brain tumor aids to obtain effective treatment and boosting the survival time of the patients. The brain tumor segmentation segregates the abnormal tissues region from the normal tissues region. The major challenges are the complex structure, size, and location of the tumor region. In this proposed methodology, quantile transformation, Gabor filter, and various edge techniques are implemented to segment the tumor tissues in the MRI brain images. The quantile transformation computes the Gaussian probability distribution values to increase the semantic gap between tumor region and the non-tumor region. Gabor technique analyses the texture information for identifying specific frequency contents in the brain image. Various edge techniques such as Canny, Robert, Scharr, Prewitt, and Sobel edges are applied to extract the actual location and effective boundary regions. Gaussian low pass filter and median filter concept is applied to eliminate the external factors like unwanted noise. At last, the collected properties are then fed into the Random Forest classifier to isolate tumor tissue regions from the brain MRI images. Accuracy, precision, recall, and f-measures are used to estimate the performance of the proposed methodology. The results of the experiments reveal that our proposed strategy produced better outcomes.
Diallel analysis for seed yield and yield-related traits in tepary bean (Phaseolus acutifolius A. Gray) under non-stress and drought-stress conditions
Authors: Mwale Saul Eric , Shimelis Hussein , Nkhata Wilson , Sefasi Abel , Fandika Isaac , Mashilo Jacob 
Published: January 2024

Abstract
Tepary bean (Phaseolus acutifolius A. Gray) cultivation is not expansive in Southern Africa due to the unavailability of high-yielding and locally adapted varieties. To deliver well-adapted and new-generation tepary beans in Africa, pre-breeding and breeding of drought tolerant and high-yielding varieties is a critical need. Therefore, the objective of this study was to determine the combining ability effects and genetic components for seed yield and yield-related traits in selected tepary bean genotypes under non-stressed (NS) and drought-stressed (DS) conditions. Seven parents and 21 F2 progenies derived from a half-diallel design were evaluated at two sites in Malawi under NS and DS conditions using a 4 × 7 lattice design with three replications. The genotype × location interaction effect was significant (p < 0.05) for days to 50% flowering (DTF), number of pods per plant (NPP), and seed yield (SY) traits under both NS and DS conditions, implying a differential performance of genotypes across the two locations. The specific combining ability (SCA) × Location interaction effect was significant (p < 0.05) for DTF, NPP, and SY under both water regimes, implying the genetic effects of crosses were affected by test locations. General combining ability (GCA) and SCA mean squares were significant for number of seeds per pod (NSP) and SY under DS condition, indicating additive and non-additive gene effects controlled these traits. Baker’s ratio (BR) > 0.50 for NPP and NSP under DS condition, suggested the preponderance of additive gene effects. The narrow-sense heritability estimates of > 0.60 for NSP under DS condition suggested relatively better trait transmissibility from parents to offspring. G40145, G40148, and G40150 were good general combiners for NPP and SY under both NS and DS conditions. F2 families Zimbabwe landrace x G40138, Zimbabwe landrace × G40150, G40059 × G40145, G40059 × G40148, G40138 × G40150, and G40145 × G40150 were best-specific combiners with enhanced SY of 1.67 tons/ha under DS condition. The selected parents are valuable genetic resources for breeding programs to enhance the NPP and SY. High-performing early-generation families are recommended for genetic advancement and selection across representative growing environments for variety release and commercialization.
Suicidal Ideation, Psychological Distress and Depression in Medical Students of Pakistan: Surviving or Thriving
Authors: Sarwar Anum , Waris Hira , Khan Hina , Umar Muhammad Hamza , Karmani Vikash kumar 
Published: January 2024

Abstract
Background: In recent years, psychological stress has lead to increase in suicide cases readily among medical students of many countries. This study aims determine the prevalence of psychological stress, major depressive disorder, and suicidal ideation in Bachelor of Medicine and Bachelor of Surgery (MBBS) students of a government setup medical university in Pakistan.
Methods: The data was gathered using a valid questionnaire containing 10 items Kessler psychological distress scale. The scale consists of the severity of the psychological distress from well, mild, moderate, and severe. Physical health questionnaire 2(PHQ2) was used for identifying the students with major depressive illness. Suicidal ideation was assessed using item no. 9 from PHQ9 questionnaire.11,17
Results: The overall prevalence of suicidal ideation, distress and major depression among 353 students of MBBS was 22.9%, 63.1%, 27.8% respectively. The students with major depression and moderate/severe distress are more probable to think about suicide. Moreover, Students who choose medicine under the family influence are more likely to have suicidal ideation. Besides this, we found that particularly females experience higher psychological distress as compared to males.
Conclusion: In the overall study, it is identified that suicidal ideation is strongly correlated to depression and distress. However, controlling these factors at an early stage can prevent the suicidal thoughts, which inevitably can reduce the suicide attempts not only in medical students but could also be valuable for students of different fields.
Quantum Chemical Investigation of (E)-2-(2-hydroxy-5- methoxybenzylidene)hydrazinecarbothioamide and its N-methyl Variant by Using DFT Methods
Authors: Srisha K. , Ravindranath L. , Ramesh Gaddam. , Praveena D. , V Sunil kumar , Kumar Danikonda. Suresh , Muthu S. , Rao G. Ramana 
Published: January 2024

Abstract

Geometry optimization for 2-(2-hydroxy-5-methoxybenzylidene)hydrazinecarbothioamide (HMHC) and 2-(2-hydroxy-5methoxybenzylidene)-N-methylhydrazinecarbothioamide (HMNHC) was attempted using DFT/B3LYP/6-311 + + G(d,p) formalism. The computations identified the existence of both intra-molecular and bifurcated intra-molecular hydrogen bonds in both the molecules. Time-dependent density functional theory (TD-DFT) was employed to simulate Ultra-Violet spectra for both HMHC and HMNHC in order to substantiate experimental spectra in a solution of dimethyl formamide. For the two compounds under investigation, specific global reactivity descriptors were estimated with the help of frontier molecular orbital (FMO) analysis to understand the origin of UV-Vis spectra. Nonlinear optical (NLO) profile, for each of the two molecules, was computed, with in the frame work of the DFT/B3LYP/6-311 + + G(d,p) formalism to determine their utility for NLO applications. NBO analysis of hyper conjugate interactions made it possible to interpret the molecules NLO behavior in terms of intramolecular charge transfer (ICT). The reactive sites around the molecules were identified using Fukui function investigations and Molecular Electrostatic Potential (MEP).
Trends and Incidence of Reported Events Associated with Ureteral Stents: An Analysis of the Food and Drug Administration's Manufacturer and User Facility Device Experience (MAUDE) Database
Authors: Lombardo Riccardo , Guidotti Alessio , Turchi Beatrice , Franco Giorgio , Tubaro Andrea , De Nunzio Cosimo 
Published: January 2024

Abstract
Aim of this study is to summarize medical device reports (MDRs) between 2012 and 2022 relating to ureteral stents within the Manufacturer and User Facility Device Experience (MAUDE) database maintained by The Food and Drug Administration (FDA). The MAUDE database was analyzed for all MDRs relating to each FDA-approved ureteral stent. Event descriptions were reviewed and characterized into specific event types. Outcome measures include specific ureteral stent and reported events as detailed by the MDRs. All data is de-identified and in compliance with the Health Insurance Portability and Accountability Act (HIPAA). Data is presented as number of specific event/total events. Pooled Relative risk was used to compare data. Overall, 2652 reports were retrieved in 10 years and a progressive rise in reported events was recorded (Fig. 1). 831/2652 (31%) were reported as injury while 1810/2652 (68%) as malfunction of the ureteral stent and 4 events of death. The most frequently reported adverse events (AEs) were stent break (627/2652: 23%); material problems (384/2652: 14%); calcification (222/2652: 8%); difficulty to insert, advance or remove the device (155/2652: 6%). Bard stents were associated with most material problems (19%), Resonance stents were associated with most difficulty to insert, advance or remove the device (9%) and calcification (15%) while filiform double pigtail stent set were associated with most breakage reports (56%) when compared to the other stents (PRR > 1, p < 0,05) (Table 1, 2, 3). According to MAUDE database the most frequent complications related to ureteral stents are breakage, material problems, calcification and difficulty to insert, advance or remove the device. As well Resonance ureteral stents seem to be associated with a higher risk of device problems.
The double Burden of Stressful Life Events among professional nurses: public mass shootings during the COVID-19 Pandemic
Authors: Imkome Ek-uma 
Published: January 2024

Abstract
Background
Stress is a significant consequence of frontline care. Nurses have recently been at the forefront of care for victims of both public mass shootings and the coronavirus disease 2019 (COVID-19) pandemic. They have been coping with stressful life events, fearing potential infection and the possibility of transmitting the virus to their patients and families, experiencing heavy workloads, high patient-nurse ratios, and extended shifts—all of which lead to exhaustion and stress. Nurses’ perceptions of mass shooting events during the COVID-19 pandemic should be explored to ensure that these professionals receive more efficient support to deliver high-quality care. This study explored nurses’ perceptions in the era of mass shootings and the COVID-19 pandemic.
Methods
This phenomenological-hermeneutic research was performed to examine the perspectives of 16 nurses caring for patients who were either injured during a public mass shooting or infected with COVID-19. Participants were selected through purposeful sampling. Data were collected using semi-structured questionnaires during online interviews using Microsoft Teams. Themes derived from structural understanding illuminated participant nurses' perceptions of patient care during the COVID-19 pandemic.
Results
Qualitative data analysis revealed five main themes: stressful life events, flashbulb memories, service-oriented mindset, team collaboration key, and professional needs. The theoretical interpretation points to the multidimensional perceptions of nurses and the need to confirm these perceptions and reconcile them with the psychological impact of stressful life events, making future adjustments and adaptations possible.
Conclusions
Interested stakeholders must consider service-oriented mindsets, team collaboration is key, and the professional needs of nurses to support and prepare novice to expert nurses for the delivery of optimal care during public health crises.
Molecular mechanism of N-acetylcysteine regulating proliferation and hormone secretion of granulosa cells in sheep
Authors: Wang Jine , Ma Junyuan , Li Yang , yang yahua , Yang Chongfa , Hu Songming , Huo Shengdong , Yang Yanmei , 扎 西英派 , Luo Wenxue 
Published: January 2024

Abstract

Granulosa cells are not only important supporting cells in follicular development, but also the main cells secreting steroids. The proliferation of GCs and steroid hormone synthesis play a key role in follicular development and atresia. In this experiment, GCs were isolated by follicular fluid aspiration, and identified by immunofluorescence technique. The effects of different concentrations of NAC (50, 100, 500, 1000 µmol/L) on sheep GCs with regards to the antioxidant levels, proliferation, apoptosis, and steroid hormone secretion were investigated. PI3K/AKT inhibitor LY294002 was used to explore the molecular mechanism of NAC on GCs proliferation and steroid hormone secretion in sheep. The results showed that in sheep GCs, all concentration of NAC group could promote the proliferation of GCs and inhibit their apoptosis. Among them, 100 µmol/L NAC had the most significant promote on the proliferation of sheep GCs for 48 h. The expression of CCND1, CDK4 and Bcl-2 in all NAC concentration group was significantly increased, and the expression of Bax was significantly decreased. All concentrations of NAC significantly decreased reactive oxygen species (ROS) concentration and increased the expression of CAT and SOD1. NAC significantly increased the expression of CYP19A1, 3β-HSD and the secretion of estradiol (E2) and progesterone (P4) in GCs. In conclusion, NAC activates the PI3K/AKT signaling pathway to promote the proliferation of GCs, E2 and P4 secretion of sheep GCs in vitro.
Determination of the Expression Levels of Hym, AmNrx1, and CYP9Q3 Genes in the Anatolian Honey Bee (Apis mellifera anatoliaca)
Authors: Kabakcı Dilek , Karataş Ümit , Tunca Rahşan Ivgin , Çankaya Murat , Karabağ Kemal , Akdeniz Gökhan , Kuzucu Mehmet 
Published: January 2024

Abstract

The Varroa destructor poses a significant threat to honey bees, leading to substantial yield losses and colony declines. Defence behaviour (such as grooming behavior: auto and allogrooming) in honey bees serves as a crucial mechanism against Varroa infestations, but the many genes responsible for this behavior remain unidentified. This study focuses on the expression levels of hymenoptaecin (Hym), neurexin-1 (AmNrx1), and CYP9Q3 which could be associated with defence behavior, in Muğla honey bee ecotype (Apis mellifera anatoliaca) colonies subjected to a against Varroa selection program. Using the qPCR method, researchers analyzed worker bees from 23 control groups and 23 colonies under the selection program. The results revealed a remarkable increase in the expression levels of Hym, AmNrx1, and CYP9Q3 genes in the selected group, with respective fold changes of 2.9, 2.95, and 3.26 compared to the control group (p < 0.01). This finding suggests that selection against Varroa infestations induces alterations in gene expression linked to behaviour related to exposure of Varroa in honey bees. These outcomes propose the potential use of Hym, AmNrx1, and CYP9Q3 genes in preselection for future Varroa-resistant programs in honey bees. The genes used in the study that may be related to this behavior are supported by other studies in the future, they may help create an initial population with advanced defence behaviours (such as autogrooming and allogrooming).
Error analysis of blade milling considering surface features and deformation
Authors: Wu Shi , Chunfeng Wang , Xianli Liu , Yupeng Wang , Yong Zhang 
Published: January 2024

Abstract

Thin-walled impeller blade curvature changes in the milling process, low stiffness and other reasons lead to large milling processing error, in order to compensate for online blade milling processing error,A milling machining error prediction method is proposed by considering the curved surface features and deformation of the blade. First, based on the tool-worker contact relationship of blade curvature and machining deformation individually, the undeformed and deformation chip thickness models considering curvature and deformation are constructed to analyze influence law of curvature change and deformation on the chip thickness individually; Then, change amount of the chip thickness considering undeformed and deformed in the tool coordinate system is converted to the surface coordinate system. The surface normal vector of variation is taken as the predicted machining error; Finally, corresponding experiments are conducted on five-axis machine to indicate that the error between the predicted and the experimentally measured machining error during stable milling falls within 21%.