bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cloud based Stacking and Bending Ensemble Approach for the classification of Brain Haemorrhage using Meta Diverse Model
Authors: Seeli D.jeni Jeba , Thanammal K.K. 
Published: June 2024

Abstract

In the medical field, disease diagnosis through cloud computing is a promising technology to focus more on patient care. It offers benefits for both patients and doctors. We aimed to develop a cloud based classification method for patients with brain haemorrhage in rural (or) remote areas. The detection of brain haemorrhage is critical for neurological diagnosis and treatment. Although deep learning models have shown promise in medical image analysis, predicting brain haemorrhage remains challenging due to its complexity and variability. To address this, we propose an ensemble approach for detection of Intracranial Haemorrhage diagnosis using cloud computing. Cloud services enable data to be stored on remote servers and then be accessed via the Internet. The user does not need to be in a specific location to access it, which allows the user to work remotely. The ensemble comprises diverse deep learning models (ResNet50, VGG16, and DenseNet121) with Global Average Pooling 2D layers, benefiting from the cloud's computational resources for efficient training. Each model brings unique strengths, enabling us to capture a wider range of data patterns and improve prediction accuracy. Data pre-processing involves dividing the dataset into training and validation sets. The base models are trained on the training data, and hyper parameters are fine-tuned via cross-validation on the validation set. The stacking and blending techniques combine base model predictions. Stacking uses validation predictions to train a meta-model that intelligently combines individual predictions, while blending directly averages predictions for a simpler ensemble. To overcome the Challenges of privacy preserving, data protection, improve the performance and fast diagnosis, the proposed work is also deployed in a cloud based framework. Performance evaluation employs standard metrics on a separate test set. Results show that the ensemble approach significantly enhances Intracranial Haemorrhage Prediction, improving clinical decision-making for neurological emergencies and fast diagnosis. Our approach incorporates strategies to handle class imbalance, such as using suitable loss functions and data augmentation during training.
Small Convolutional Neural Networks and Random Forest in Land Use, Land-Use Change and Forestry (LULUCF)
Authors: Carneiro Gabriel A. , Svoboda Jan , Cunha António , Sousa Joaquim J. , Štych Přemysl 
Published: June 2024

Abstract

The focus of this paper is to present an innovative approach to classify land cover, with specific emphasis on Land Use, Land-Use Change and Forestry (LULUCF) monitoring. LULUCF is a sector in greenhouse gas inventory that tracks changes in greenhouse gas levels in the atmosphere due to land use and land-use change. In this study, we employed Deep Learning classifiers and Random Forest to classify land cover/land use in Czechia, adhering to LULUCF regulations. We evaluated the effectiveness of 2D and 3D Convolutions in Convolutional Neural Networks, with varying filter sizes and training methods, alongside the use of Random Forest classifier. We used Sentinel-2 bands with 10 m and 20 m spatial resolution, NDVI, NDVI variance, and SRTM altitude data to create input paths of 5×5 pixels. The results indicate that the 3D model trained with classical training and 3×3-pixel filters achieved the best F1 Score of 0.84. One significant advantage of using convolutional neural networks is their ability to include information from a pixel’s neighbourhood in the classification process, in contrast to solely considering the pixel itself.
Quercetin loaded and alginate sealed β-Glucan particles-based drug delivery system against DU145 a prostate cancer cell line: Integrating network pharmacology, molecular docking and in vitro studies
Authors: TRIVEDI RASHMI , Upadhyay Tarun Kumar , Prabhakar Pranav Kumar 
Published: June 2024

Abstract

Background
Prostate cancer remains a challenge in healthcare, being the second most common male cancer demanding innovative therapeutic approaches and treatment techniques. This study integrates in silico and in vitro methods for the investigation of the potential anticancer effects of quercetin-loaded and alginate-sealed β-Glucan particles derived from mushroom Agaricus bisporus and yeast against the DU145 cell line.
Methods
Prostate cancer-related genes were identified from DisGeNET and GeneCards databases, followed by target prioritization using Swiss Target Prediction software. Venny 2.1 was used for the determination of common targets between β-Glucan, Quercetin, and prostate cancer and PPI network was constructed using STRING database. CB dock online server was used for molecular docking and DU145, RAW264.7 cell lines were used for the determination of cytotoxicity against prostate cancer and healthy cells.
Results
Molecular docking revealed that quercetin has superior binding affinity compared to β-Glucan with selected prostate cancer-related targets. In vitro evaluation using MTT assays demonstrated the cytotoxic effects of quercetin-loaded and alginate-sealed particles against DU145 prostate cancer cells. Apoptosis induction, ROS generation, and lysosomal pH alterations underscore the potential of quercetin-loaded and alginate-sealed β-Glucan particles as promising therapeutic agents for prostate cancer.
Conclusions
Our study showed systematic analyses of the effect of hollow β-Glucan particles, Quercetin, and Quercetin alginate sealed particles against DU145 cells and found that formulation exhibits superior anticancer activity against prostate cancer cell line. Quercetin-loaded alginate-sealed particles showed very little cytotoxicity against healthy cell line RAW264.7. Future studies focusing on preclinical validation, pharmacokinetic profiling, and clinical trials to assess translational potential and optimize therapeutic strategies can help get impactful findings.
Donor’s seral creatinine as a predictor of early allograft dysfunction after liver transplantation: A retrospective cohort study with propensity score analysis
Authors: Taipov Tagir , Wang Shou-Ping , Hou Yi-Fu , Yi Peng-Sheng , Yang Jia-Yin , Song Jiu-Lin 
Published: June 2024

Abstract

Background: There are several risk factors for early allograft dysfunction (EAD) after donation after citizen death (DCD) liver transplantation. This study explored whether elevated donor’s seral creatinine increases the risk of EAD after DCD liver transplantation.
Materials and Methods: The study enrolled 224 primary adult DCD liver transplantation recipients. Univariate and multivariate logistic regression analyses were performed, and receiver operating characteristic curves were constructed. Perioperative clinical and laboratory variables were assessed for their association with the prevalence of EAD using the inverse probability of treatment weighting (IPTW) and 1:3 propensity score (PS) matching (Group A, n=53; Group B, n=124) analysis.
Results: Forty-eight recipients (21.4%) developed EAD. All cases were divided into two groups (Group 1 [donor’s seral creatinine > 170μmol/L, n = 55] and Group 2 [donor’s seral creatinine ≤ 170μmol/L, n = 169]). Multivariate logistic regression analyses revealed that the donor’s age >60 years old (OR 5.927, 95CI% 2.144-16.387, p=0.001), BMI >24 (OR 2.818, 95CI% 1.359-5.845, p=0.005), with hypertension (OR 2.308, 95%CI 1.086-4.902, p=0.030), ICU stay >7 days (OR 3.369, 95% CI 1.449-7.832, p=0.005), and seral creatinine >170 μmol/L (OR 2.841, 95%CI 1.309-6.164, p=0.008) were independent risk factors for EAD. Moreover, the donor’s seral creatine >170 μmol/L was associated with incidence of EAD after adjusting for IPTW (OR 2.714, 95%CI 1.407-5.234, p=0.003), and after 1:3 PS matching (34.0% vs 18.5%, OR 2.258, 95%CI 1.092-4.671, p < 0.05).
Conclusions: Elevated donor’s seral creatinine increased the risk of postoperative EAD, which might be a novel predictor of EAD after DCD liver transplantation.
Combined plasma lens and rephasing stage for a laser wakefield accelerator
Authors: Gustafsson Cornelia , Löfquist Erik , Persson Anders , Angella Andrea , Svendsen Kristoffer , Lundh Olle 
Published: June 2024

Abstract

Electrons from a laser wakefield accelerator have a limited energy gain due to dephasing, and are prone to emittance growth causing a large transverse divergence. In this paper, we experimentally show that both of these issues can be addressed in a single step, by adjusting the plasma density profile. Shock-assisted ionisation injection is used to produce 100 MeV quasi-monoenergetic electron bunches in the primary part of the accelerator. Downstream from accelerator, a second, independently tuneable density region is added which can be used to both boost the energy of the electron bunches, and as a plasma lens for significant divergence reduction. An additional energy gain of 25% and a 40% divergence reduction is obtained. The effects are validated by theoretical models.
Plant growth promotion mechanisms of Bacillus sp. NYG5
Authors: Sudakov Kobi , Rana Anuj , Faigenboim-Doron Adi , Gordin Alexander , Carmeli Shmuel , Shimshoni Jacob A. , Cytryn Eddie , Minz Dror 
Published: June 2024

Abstract

Background
Bacterial strains in the rhizosphere may secrete an array of volatile organic compounds (VOCs), many of which are vital for inter- and intra-kingdom signaling, modulating microbe-microbe and microbe-plant interactions. In this study, we tested the plant growth promoting effect of VOCs emitted by Bacillus sp. NYG5 on several plants, focusing on VOC-induced changes in plant metabolic pathways, soil chemical properties and rhizo-microbiome.
Results
NYG5 emitted VOCs were found to promote growth of Arabidopsis thaliana, Nicotiana tabacum and Cucumis sativus, while also altering the community composition of the rhizosphere microbiome. Furthermore, fluorescent spectral analysis of the soil showed a significant decrease in concentration of humic substances following exposure to NYG5-emitted VOCs. Utilizing SPME-GC-MS analysis, several novel VOCs were identified, some of which were shown to promote plant growth. Transcriptomic analysis of N. tabacum plants exposed to NYG5-emitted VOCs revealed the induction of several plant growth related pathways such as phenylpropanoid biosynthesis, metabolism of sugars, and signal transduction of plant hormones.
Conclusions
Exposure to NYG5-emitted VOCs significantly impacted several plant growth related pathways, increasing plant biomass. Additionally, these VOCs altered the community composition of the rhizosphere microbiome, and decreased the concentration of humic substances in the soil. These findings may suggest that bacterial VOCs significantly impact plant growth via various mechanisms.
B cell-mediated antigen presentation promotes adverse cardiac remodeling in chronic heart failure
Authors: Adamo Luigi , Lovell Jana , Duque Carolina , Rousseau Sylvie , Bhalodia Aashik , Bermea Kevin , Cohen Charles 
Published: June 2024

Abstract

Cardiovascular disease remains the leading cause of death worldwide. A primary driver of cardiovascular mortality is ischemic heart failure, a form of cardiac dysfunction that can develop in patients who survive myocardial infarction. Acute cardiac damage triggers robust changes in the spleen with rapid migration of immune cells from the spleen to the heart. Activating this “cardio-splenic” axis contributes to progressive cardiac dysfunction. The cardio-splenic axis has, therefore, been identified as a promising therapeutic target to prevent or treat heart failure. However, our understanding of the precise mechanisms by which specific immune cells contribute to adverse cardiac remodeling within the cardio-splenic axis remains limited. Here, we show that splenic B cells contribute to the development of heart failure via MHC II-mediated antigen presentation. We found that the adoptive transfer of splenic B cells from mice with ischemic heart failure promoted adverse cardiac remodeling and splenic inflammatory changes in naïve recipient mice. Based on single-cell RNA sequencing analysis of splenic B cells from mice with ischemic heart failure, we hypothesized that B cells contributed to adverse cardiac remodeling through antigen presentation by MHC II molecules. This mechanism was confirmed using transgenic mice with B cell-specific MHC II deletion, and by analyzing circulating B cells from humans who experienced myocardial infarction. Our results broaden our understanding of B lymphocyte biology, reshape current models of immune activation in response to myocardial injury, and point towards MHC II-mediated signaling in B cells as a novel and specific therapeutic target in chronic heart failure.
Development of Multiplex One-step Point-of-Care Diagnostic Test for SARS- CoV-2 Using Portable Biomeme Thermocycler
Authors: Lee Seonghyeon , Rajoriya Shivani , Park Jieun , Kim Bohyeon , Natasha Augustine , Prayitno Sara Puspareni , Misra Divya , Park Kyungmin , Song Jin-Won , Lee Taek-Kyun , Shin Kyu Sung , Lee Hyungdon , Kim Won-Keun 
Published: June 2024

Abstract

Coronavirus disease-19 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), poses a critical public health threat due to the high transmissibility, infectivity, and prolonged incubation in humans. The urgent demand for swift and efficient detection assays during the pandemic led to the establishment of Point-of-Care Testing (POCT) methods using RT-qPCR for SARS-CoV-2 detection. However, an accurate and portable diagnostic method for SARS-CoV-2 remains to be developed. To address this challenge, we developed the multiplex one-step RT-qPCR for POC diagnosis of SARS-CoV-2 using a portable Biomeme Franklin™ Real-Time PCR thermocycler. The performance of the Biomeme assay was evaluated and validated for the POCT of SARS-CoV-2, based on multiplex detection of the nucleocapsid, envelope, and spike genes. The Biomeme assay demonstrated high sensitivity by detecting the RNA of multiple SARS-CoV-2 variants, including 19A, B.1.617.2, BA.1, BA.2, BA.2.75, BA.5, and BN.1 from 0.01 ng/µl of total RNA and showed no cross-reactivity with other human coronaviruses, such as HCoV-OC43, HCoV-NL63, and HCoV-229E. The diagnostic method exhibited a clinical sensitivity of 95% and a specificity of 100%. Therefore, this study reports a POCT method for the prompt and reliable molecular diagnosis of SARS-CoV-2 in resource-limited settings.
The Impact of Positive Emotions on Academic Performance and Well-being among Students and Teachers in Language Learning: A Bibliometric Analysis
Authors: Shubina Ivanna , Kwiatek Piotr 
Published: June 2024

Abstract

This bibliometric study investigates the impact of positive emotions without neglecting the benefits of negative emotions on academic performance and well-being among teachers and students in language education. 382 relevant studies published between 2013 and 2023 were retrieved from highly ranked databases using LENS software. Current study synthesized retrieved data and provided suggestions on current gaps in knowledge and future studies in the field. Descriptive characteristics of the publications showed an increased number of publications in 2015 (n = 76) and 2018 (n = 75). The top two leading authors by publication amount and citation score were J-M. Dewaele (29 papers, 2,090 citations) and P.D. Macintyre (7 papers, 1,097 citations). The results indicated that positive emotions have a significant impact on academic success, development of students’ skills and abilities, what increases overall well-being among students and teachers involved in language education. The findings of this study are useful for researchers interested in an overview of the publication trends in language education, as well as for teachers and students since they encourage a deeper understanding of impact of positive emotions on academic performance in the language learning context and creating efficient learning environment.
Third-order non-linear optical switching and threshold limiting of NiO thin films
Authors: Bhakta Sourav , Panda Rudrashis , Sahoo Pratap Kumar 
Published: June 2024

Abstract

This study discusses the nonlinear optical properties of as-grown and annealed NiO thin films using the Z-scan technique. In open aperture measurements, pristine reveal saturable absorption (SA) with a negative sign of nonlinearity, while annealed samples exhibit reverse saturable absorption (RSA) with a positive sign of nonlinearity. In closed aperture conditions, all samples show prefocal minima and postfocal maxima, indicating self-focusing behavior. The observed RSA phenomena are attributed to the two-photon absorption (TPA) process. The influence of surface plasmon resonance on nonlinear absorption is successfully ruled out due to insufficient excitation energy (1.20 eV) to induce resonance in the samples. The increase in bandgap with annealing temperature, associated with TPA, is elucidated with the shifting of Ni-dx2-y2 and Ni-dz2 orbitals in the conduction band, under the framework of Density Functional Theory (DFT). The DFT results are correlated with the observed nonlinear SA and RSA processes. The Ni d-d and Ni-d to O-p transitions contribute to the modulation of nonlinearity in the TPA process. The study suggests that the sample annealed at 4000C exhibits superior optical limiting properties with the highest nonlinear absorption coefficients compared to the other annealed sample, while the as-grown sample is suitable for passive Q-switching applications.
The Role of Puff Volume in Vaping Emissions, Inhalation Risks, and Metabolic Perturbations: A Pilot Study
Authors: Jeon Jennifer , He Xiaojia , Shinde Akshada , Meister Maureen , Barnett Lillie , Zhang Qian , Black Marilyn , Shannahan Jonathan , Wright Christa 
Published: June 2024

Abstract

Secondhand vaping exposure is an emerging public health concern that remains understudied. In this study, saliva and exhaled emissions from ENDS users (secondhand) and non-ENDS users (baseline) were collected, firsthand emissions were generated using an automated ENDS aerosol generation system programmed to simulate puffing topography profiles collected from ENDS users. Particulate concentrations and sizes along with volatile organic compounds were characterized. We revealed puffing topography metrics as potential mediators of firsthand and secondhand particle and chemical exposures, as well as metabolic and respiratory health outcomes. Particle deposition modeling revealed that while secondhand emissions displayed smaller deposited mass, total and pulmonary particle deposition fractions were higher than firsthand deposition levels, possibly due to smaller secondhand emission particle diameters. Lastly, untargeted metabolomic profiling of salivary biomarkers of lung injury due to firsthand ENDS exposures revealed potential early indicators of respiratory distress that may also be relevant in bystanders exposed to secondhand vaping scenarios. By leveraging system toxicology, we identified 10 metabolites, including leukotriene D4, that could potentially serve as biomarkers for ENDS use, exposure estimation, and the prediction of vaping-related disease. This study highlights characterization of vaping behavior is an important exposure component in advancing our understanding of potential health effects in ENDS users and bystanders.
Avifaunal assemblages within fresh and saltwater resources around a national park; the case of Lake Munyanyange, Lake Edward, and Kazinga Channel in Southwestern Uganda
Authors: Aggrey Siya , Akisiimire Hindrah , Nicholas Muhesi , Augustine Hakiza , Moses Tasiwuka , Joel Ongom , Enyel Eric Morris , Baluku Robert 
Published: June 2024

Abstract

Background
Birds play a critical role in sustaining global ecosystems as well as human livelihoods. Despite this value, their populations are declining at unprecedented rates with anthropogenic factors being the main driver. Local monitoring strategies provides data for enhancing monitoring activities while designing conservation interventions. Herein, we present preliminary results from bird monitoring activities undertaken within fresh and salt water sites in Southwestern parts of Uganda.
Methods
Point count method was used during the survey. This included recording of birds seen and or heard from within 100 m radius. This was done periodically (every 10 minutes) in the morning and evening along a transect and birds were identified using identification keys. Diversity indices were computed for the data and One-Way ANOVA was used to compute the differences in counts across different sites. Post-Hoc analysis was computed using Tukey’s HSD test. All analyses were done in R software.
Results
A total of 7476 individuals of birds of 68 different species were recorded during the 558 observations made across the different sites. The freshwater lakes had the highest bird diversity and abundance with Kazinga Channel inside the park scoring the highest (H' = 2.211). Ceryle rudis (29%, n= 7476) had the highest number of individuals followed by Ploceus melanocephalus. The choice of the different sites by the birds did not vary across Lake Edward and Kazinga Channel (P =0.852). Meanwhile for these sites in comparison with Lake Munyanyange, there was a significant difference in being chosen by the birds i.e. P = 0.009 and P = 0.015 respectively. All these lakes had migratory birds that fly across national boundaries
Conclusion
There is a high diversity of birds around salt and fresh water sites in Southwestern Uganda. This includes migratory bird species. Conservation interventions thus ought to be designed targeting these selected sites to enhance stability of bird populations across different scales. This can be done with improved data generated through monitoring activities.
A Multidimensional Approach for Formal Modeling and Analyzing Medical Cyber-Physical Systems
Authors: Bouheroum Ayoub , Benmerzoug Djamel , Hemam Sofiane Mounine , Belala Faiza 
Published: June 2024

Abstract

The combination of integrated software controlling devices, networking capabilities, and sensing/actuation technologies in Medical Cyber-Physical Systems (M-CPS) highlights some research challenges specific to this class of Cyber-Physical Systems (CPS). The major challenge is ensuring the confidentiality of the data or resources that they handle. In this paper, we tackle this problem by proposing a formal approach that combines CA-BRS (Control Agent and Bigraphical Reactive Systems) and BPMN (Business Process Model Notation) to specify and analyze CPS in general, while respecting several dimensions. The CPS structural dimension, which represents the space (physical and cyber entities) in which agents exist and interact, is defined by the Bigraphs. Control agents constituting the virtual dimension observe and control the physical and cyber entities of their environment. The complex and adaptive behavior of a CPS (behavioral dimension) is defined through several types of rules; each manages a possible evolution of a CPS component (physical, cyber or virtual). Two distinctive perspectives are associated with the semantic interpretation of these rules: states and activities. Both perspectives are defined with a particular semantics and notations.
This study focuses on the activities perspective that specifies the behavior of control agents using a BPMN activity diagram. This highlights how these two models (CA-BRS and BPMN) complement each other to assist designers in defining formal models for CPS. Additionally, it reveals how to provide the CA-BRS model with means of controlling unauthorized access to an Electronic Health Record system.