bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the Casual Impact of Oil Price Dynamics on Inflation Using Wavelet Analysis on G20 Countries
Authors: Khoj Haitham zaker , Saeed Mohammed Ahmed
Published: May 2024

This study examines the nexus between oil prices and inflation in G20 economies, addressing critical gaps by adopting a comparative approach across three pivotal oil price downturns in 2008, 2014, and 2020 (COVID-19). The study utilized monthly time series data from January 2000 to December 2023 and the Bayesian Structural Time Series (BSTS) approach for causal impact analysis. The study found that during the global financial crisis (December 2007 to June 2014), advanced economies like Australia and the UK displayed varying degrees of negative absolute causal impact, aligning with the deflationary impact of falling oil prices. In contrast, emerging economies faced significant negative causal impacts. From June 2014 to January 2020, diverse inflation impacts were observed across G20 economies after a significant oil price decline. Advanced economies like Australia and emerging economies like Brazil experienced negative impacts, while others showed negligible effects. In the subsequent period from January 2020 to December 2023, amid the COVID-19 pandemic and substantial oil price decline, G20 countries exhibited varied inflation outcomes. Positive absolute effects indicated a notable rise in inflation with China standing out with a substantial negative impact. The wavelet coherence analyses also showed an asymmetrical impact of oil prices on inflation. The findings suggest that policymakers should adopt proactive and adaptive policy frameworks, considering the asymmetric responses of G20 economies to oil price dynamics.
Prevalence of Overweight, Obesity, and Associated Risk Factors among Students at the Faculty of Medicine, Jazan University
Authors: Alqassimi Sameer , Elmakki Erwa , Oraibi Omar , Darraj Majid Ahmed , Madkhali Mohammed Ali , Mohrag Mostafa , AREESHI Areej Siddiq , Aburasain Amani B. , Majrabi Aisha H. , Masmali Enas M. , Refaei Eman A. , Mobaraki Raghad A , Qahtani Reem Mohammed
Published: May 2024

Background: Obesity is a global health crisis with a rapidly increasing prevalence among university students. Medical students are a unique population that may be at a higher risk of obesity due to the demanding nature of their studies and the associated stress.
Objective: This study aimed to determine the prevalence of overweight, obesity, and the associated risk factors among medical students at Jazan University in Saudi Arabia.
Methods: A cross-sectional study was conducted among 228 medical students from their 2nd to 6th academic years at the Faculty of Medicine, Jazan University. A self-administered questionnaire was used to collect data regarding sociodemographic characteristics, physical activity, dietary habits, comorbidities, medication use, family history, and lifestyle factors. Anthropometric measurements including height, weight, and waist circumference were recorded. Chi-square test and binary logistic regression were used to identify the risk factors associated with obesity.
Results: The prevalence of overweight and obesity among the participants was 13.3% and 15% respectively. Hence, the combined prevalence of overweight and obesity is 28.3%. The mean weight was 63.39 ± 18.93 kilograms, and the mean height was 163.48 ± 9.78 centimeters. On the other hand, 17.3% of participants had underweight whereas 54.4% had normal BMI. Most of the participants (61%) did not engage in regular exercise. A high proportion consumed fruits (82.9%) and vegetables (58.8%) 3 or fewer days per week, and 84.2% consumed 3 or fewer meals per day. Fast food consumption more than 3 days per week was reported by 42.1% of participants. Obesity was not significantly associated with sociodemographic factors, physical activity, dietary habits, comorbidities, medication use, or family histories. However, those with a monthly family income of 15,000-24,999 riyals had significantly lower odds of obesity than those in the lowest income group (OR 0.230, p = 0.045).
Conclusion: The prevalence of overweight and obesity among medical students at Jazan University is high. Although no significant associations were found between obesity and most risk factors, this study highlights the need for interventions that promote healthy lifestyles among medical students. Further research is needed to identify effective strategies for preventing and managing obesity in this population.
Open Source SDN Controllers – Operational and Security Issues
Authors: Mardaus Aleksandra , Biernacka Edyta , Wójcik Robert , Domżał Jerzy
Published: May 2024

The Software-Defined Networking concept plays an important role in network management. The central controller, which is the main element of SDN, allows to provide traffic engineering and security solutions in single and multiple-layer networks based on optical transmission. In this work, we compare selected open-source implementations of SDN controllers. Throughput and latency measurements were analyzed using the CBench program. The simulation of a link failure and a controller failure were conducted using the API provided by the Mininet network simulator. For detecting security vulnerabilities, a dedicated program, called sdnpwn, was used. The work provides an overview of the selected controllers, indicating their strengths and weaknesses. Moreover, some implemention suggestions and recommendations are presented.
Effect of Modulator Therapies on Nutritional Risk Index in Adults with Cystic Fibrosis: A Prospective Cohort Study
Authors: Yalcin Nadir , Akman Esen Deniz , Karcıoğlu Oğuz , Allegaert Karel , Demirkan Kutay , Damadoglu Ebru , Kalyoncu Ali Fuat
Published: May 2024

Background: Modulator therapies improve weight and body mass index (BMI) in cystic fibrosis (CF) patients. We aimed to compare the nutritional risk index (NRI) in adult CF patients receiving modulator (MT) or only non-modulator (conventional) therapies (non-MT).
Methods: A single-center prospective cohort study was conducted between June-December 2023. The NRI based on weight gain and albumin was calculated at beginning and end of a 12 weeks period in both groups. This design was pragmatic, since based on individual patient access to MT for 12 weeks.
Results: 107 patients were included [mean (SD) age: 23.85 (4.98) years, 54.7% male, 46.7% MT]. In the MT group, mean (SD) weight (kg) and albumin (g/dL) increased significantly [changes: +3.09 (2.74) and +0.17 (0.37); p
Fractal and Complex Patterns Existing in Music: Application to the Composition Diaphonies of Michael Paouris
Authors: Nikolopoulos Dimitrios , Petraki Ermioni
Published: May 2024

This is a study on fractals existing in music. The application case is the composition DIAPHONIES of Michael Paouris. Sliding-window fractal analysis indicate areas of continuous fractality dipped in non-fractal areas of possibly deterministic and stochastic nature. Diverging cases of pronounced non-fractal areas are addressed and also areas of mixed fractality and non-fractality. Many segments exhibit persistency-P (2
Analysis and Optimization of Quantitative Casting Motion of a Casting and Pouring Robot
Authors: Xie Biaoxiong , Miao Xingang
Published: May 2024

According to the requirement of 20kg load of casting barrel, we design a three-dimensional model of the robot and analyze the three stages of liquid level change in the casting barrel during the casting process. Through the analysis, it is determined that the time and angle function is an implicit function, and it is impossible to find the analytical expression of time about angle. The kinetic function of the casting barrel is simulated by MATLAB, and it is found that the function image has mutation points, and when the original function is fitted and approximated by fifth-degree polynomial interpolation, the fifth-degree polynomial function image of the time versus the angular acceleration has a large amplitude of oscillation, especially the mutation points. A PID algorithm based on the discretization of the time and acceleration function is introduced for correction, and the results show that this method effectively reduces the oscillation amplitude of the image and improves the coincidence with the original function.
Morphology Behavior of Polysulfone Membranes Made from Sustainable Solvents
Authors: Kluge Steven , Hartenauer Karla , Tutuş Murat
Published: May 2024

In a previous study we could show a change of membrane morphology and gas separation performance by varying the recipe of a casting solution based on polysulfone in a determined solvent system. Although all results were very reproducible, all used solvents were harmful and not sustainable. In this study therefore, the solvents tetrahydrofuran (THF) and N,N-dimethylacetamide (DMAc) are replaced by the more sustainable solvents 2-methyl-tetrahydrofuran (2M-THF), N-butyl pyrrolidinone (NBP) and cyclopentyl methyl ether (CPME). The gas permeation performance and for the first time morphology of the membranes before and after solvent replacement were determined and compared by single gas permeation measurements and SEM microscopy. It is shown, that THF can be replaced by 2M-THF and NBP without decreasing the gas permeation performance. With CPME replacing THF no membranes were formed. Best gas permeation results showed systems with 2M-THF as THF alternative. Permeances for the tested gases oxygen (O2), nitrogen (N2), carbon dioxide (CO2) and methane (CH4) were 2.66·10-4, 3.89·10-5, 1.53·10-3 and 4.52·10-5 mL(STP)/cm²·min·bar, respectively. permselectivities of those membranes for the gas pairs O2/N2, CO2/N2 and CO2/CH4 were 6.7, 38.3 and 34.0, respectively. When additionally replacing DMAc in the solvent system no or only porous membranes were obtained, even if the precipitation procedure was adjusted. These findings indicate that a complete replacement of the solvent system without affecting the membrane morphology or gas permeation performance is not possible. By varying the temperature of the precipitation bath an easy adjustment to mechanically stable PSU membranes is possible, if just THF was replaced by 2M-THF.
Variations & Claims in International Construction Contracts (FIDIC) from Statistical Perspective in MENA Region for the Last Decade
Authors: Abdelalim Ahmed Mohammed , Ezz Al Regal Mohamed Ramadan , AL Nasser AlJawharah A. , Alwahaibi Rawan , Tantawy Mohamed
Published: May 2024

This study delves into the dynamics of 'Variations' and 'Claims' within construction projects, specifically under the FIDIC-Red Book 1999 (FIDIC 1999) framework. It aims to identify, categorize, and devise mitigation strategies for key types of Variations and Claims, aligning with the FIDIC Conditions of Contract. The research, drawing on inputs from construction industry professionals including Contract Administrators and Project Managers, focuses on the MENA re-gion. This choice is driven by the region's extensive adoption of FIDIC standards and its rapidly growing construction sector.
Data collection encompassed a questionnaire distributed to 80 industry experts, predominantly through interviews, focusing on countries like Saudi Arabia, UAE, Kuwait, and Egypt. These locations were chosen to reflect diverse construction practices and the involvement of international firms. Utilizing SPSS-V.25 for statistical analysis, the study uncovers the most prevalent and impactful causes of Variations and Claims, highlighting the critical need for managerial intervention.
A key feature of this study is the integration of Scientometric Analysis for a quantitative review of current literature, providing a comprehensive academic context. A significant addition to the methodology is the implementation of a k-means clustering analysis. This advanced statistical technique further classifies the data into distinct clusters, each representing unique combinations of 'Frequency' and 'Impact' of Variations and Claims. The k-means analysis elucidates intricate patterns and potential solutions, offering profound insights into effectively managing these issues. These analytical advancements are crucial in identifying significant and manageable responses to reduce the frequency and impact of Variations and Claims in construction projects.
Thermographic Measurements in Electrical Power Engineering – Discussion on How to Interprete the Results
Authors: Minkina Waldemar , Gryś Sławomir
Published: May 2024

An important issue concerning the inspection of the technical condition of electrical power components and systems is thermal imaging investigation. This paper presents how the thermograms obtained from these measurements should be interpreted correctly according different standards and how operators should react when a specific anomaly is detected. It is also a review article in which all currently applicable international standards are referred to. The motivation of the article relates to the fact that these standards seems to be too general and not cover all practical situations even though in many countries thermal imaging diagnostics of overhead lines or overhead outdoor and indoor power stations has been used for years on the basis of industry standards or good practices. The purpose of writing this article is precisely to encourage and provoke the global community of metrologists, scientists and engineers involved in thermographic measurements to discuss, strengthen efforts and establish relevant international standards for the interpretation of thermograms containing the relevant temperature anomalies.
Matching of Water Breakthrough in Low Resistivity Oil Reservoir Using Permeability Anisotropy
Authors: Rudyk Svetlana , Al Musalhi Majid , Taura Usman , Spirov Pavel
Published: May 2024

Uncertainties in initial water saturation and early water breakthroughs of un-known sources and paths, which occurred in the low resistivity Lower Haushi sand-stone (LHS) reservoir at the beginning of oil production, imply that the bypassed oil can yet remain in the reservoir. In addition, the upper part of LHS is a tight oil reser-voir, which can still contain a significant amount of unrecovered oil. This opens the opportunity to produce the remaining oil instead of abandoning this reservoir.
Low resistivity can exaggerate water saturation, leading to misinterpretation and premature water flooding due to inadequate oil-water contrast. Our analysis revealed a correlation between low resistivity and robust porous network connectivity, along-side elevated formation water salinity in highly porous layers. In regions of high po-rosity, sufficient oil-water contrast facilitates precise water saturation determination, affirming oil presence in all wells. However, within tight oil zones, near-complete wa-ter saturation contradicts actual oil presence. Factors contributing to saturation un-certainty and water breakthroughs were reassessed. Utilizing a 1:1 verti-cal-to-horizontal permeability ratio derived from core data enhanced simulation alignment with water production rates. Investigation into the impact of relative per-meabilities on water production was conducted. Water saturation maps were gener-ated to pinpoint remaining oil reserves. Depletion around wells is evident in lower po-rous regions, while oil persists across the entire tight reservoir, notably in two unex-plored sections.
Strategic Dimensions of Eco-Innovation Adoption in Manufacturing SMEs in the Context of Mexico City
Authors: Barragán-Hernández Andrés David , Aguilar-Fernández Mario
Published: May 2024

This paper delves into the strategic dimensions influencing the adoption of environmental innovations (EIs) in small and medium-sized manufacturing enterprises (SMEs) in Mexico City. Employing a mixed-methods approach combining documentary analysis and expert interviews, the study aims to provide a comprehensive understanding of integrating EI practices in the context of manufacturing SMEs. Qualitative methodology was chosen to explore experiences, perceptions, and practices related to EI adoption, acknowledging its ability to capture the complexity and richness of data. Through systematic literature review and semi-structured interviews with Corporate Social Responsibility experts, causal relationships and key factors influencing EI adoption were identified. The data analysis involved constructing causal maps and applying the Viable System Model to comprehend the interactions and dynamics within the organizational systems.
Turning Features Detection from Aerial Images: Model Development and Application on Florida’s Public Roadways
Authors: Antwi Richard Boadu , Kimollo Michael , Ozguven Eren Erman , Sando Thobias , Moses Ren , Dulebenets Maxim A.
Published: May 2024

Advancements in computer vision are rapidly revolutionizing the way traffic agencies gather roadway geometry data, leading to significant savings in both time and money. Utilizing aerial and satellite imagery for data collection proves to be more cost-effective, more accurate, and safer compared to traditional field observations, considering factors such as equipment cost, crew safety, and data collection efficiency. Consequently, there is a pressing need to develop more efficient methodologies for promptly, safely, and economically acquiring roadway geometry data. While image processing has previously been regarded as a time-consuming and error-prone approach for capturing these data, recent developments in computing power and image recognition techniques have opened up new avenues for accurately detecting and mapping various roadway features from a wide range of imagery data sources. This research introduces a novel approach combining image processing with a YOLO-based methodology to detect turning lane pavement markings from high-resolution aerial images, specifically focusing on Florida's public roadways. Upon comparison with ground truth data from Leon County, Florida, the developed model achieved an average accuracy of 87% at a 25% confidence threshold for detected features. Implementation of the model in Leon County identified approximately 3,026 left turn, 1,210 right turn, and 200 center lane features automatically. This methodology holds paramount significance for transportation agencies in facilitating tasks such as identifying deteriorated markings, comparing turning lane positions with other roadway features like crosswalks, and analyzing intersection-related accidents. The extracted roadway geometry data can also be seamlessly integrated with crash and traffic data, providing crucial insights for policymakers and road users.
Proton Decay and Inverse Neutron Decay
Authors: Gerardo Flores Hector , Jain Harshit , Gonçalves de Souza Maria Isabel
Published: May 2024

Here, using the theory of electrical-quantum modelling of the neutron and proton as a three-phase alternating current electrical generator, we will analyse the proton decay and the inverse neutron decay and determine the following subatomic particles, Dproton, Protoniu, Dneutron and Neutroniumd.
Quantifying Emissions in Vehicles Equipped with Energy-Saving Start-Stop Technology: THC and NOx Modeling Insights
Authors: Mądziel Maksymilian
Published: May 2024

Creating accurate emission models capable of capturing the variability and dynamics of modern propulsion systems is crucial for future mobility planning. This paper presents a methodology for creating THC and NOx emission models for vehicles equipped with start-stop technology. A key aspect of this endeavor is to find techniques that accurately replicate the engine stop stages when there are no emissions. To this end, several machine learning techniques were tested using the Python programming language. Random forest and gradient boosting methods demonstrated the best predictive capabilities for THC and NOx emissions, achieving R2 scores of approximately 0.9 for both cold and hot engine emissions. Additionally, recommendations for effective modeling of such emissions from vehicles are presented in the paper.
Mitochondrial Dysfunction, Its Oxidative Stress-Induced Pathologies and Redox Bioregulation through Low-Dose Medical Ozone. A Systematic Review.
Authors: Viebahn-Haensler Renate , León Fernández Olga
Published: May 2024

Our hypothesis that controlled ozone applications interfere into the redox balance of the biological organism (first published in 1998 with a preclinical trial on protecting the liver from CCl4 intoxication), has been verified over the last 2 decades in reactive oxygen species (ROS)-induced mitochondrial pathologies, such as rheumatoid arthritis, osteoarthritis, aging processes, diabetes-2 and in prevention of intoxications. Low-dose ozone acts as a redox bioregulator: The restoration of the disturbed redox balance is comprehensible in a number of preclinical and clinical studies by a remarkable increase of the antioxidant repair markers, here mainly shown as glutathione increase and a reduction in oxidative stress markers, mainly malondialdehyde. The mechanism of action is shown, relevant data are displayed, evaluated and comprehensively discussed: The repair side of the equilibrium increases by 21% up to 140% compared to the non-ozone treated groups and depending on the indication; the stress markers are simultaneously reduced, the redox system regains its balance.
Explainable Graph Neural Networks: An Application to Open Statistics Knowledge Graphs for Estimating House Prices
Authors: Karamanou Areti , Brimos Petros , Kalampokis Evangelos , Tarabanis Konstantinos
Published: May 2024

In the rapidly evolving field of real estate economics, the prediction of house prices continues to be a complex challenge, intricately tied to a multitude of socio-economic factors. However, traditional predictive models have often overlooked the spatial interdependencies that play a vital role in shaping housing prices. This study applies Graph Neural Networks (GNNs) on Open Statistics Knowledge Graphs to model spatial dependencies and predict house prices across Scotland’s 2011 data zones. To this end, integrated statistical indicators are retrieved from the official Scottish Open Government Data portal. The three representative GNN algorithms employed - ChebNet, GCN, and GraphSAGE - demonstrate higher prediction accuracy than traditional models, including the tabular-based XGBoost and a simple Multi-Layer Perceptron (MLP). In addition, local and global explainability are employed to increase transparency and trust in the predictions made by the most accurate GNN - GraphSAGE. The global feature importance is determined by a logistic regression surrogate model while the local, region-level understanding of the GNN predictions is achieved through the use of GNNExplainer. Explainaibility results are compared with those from a previous work that applied the XGBoost machine learning algorithm and the SHapley Additive exPlanations (SHAP) explainability framework on the same dataset. Interestingly, both global surrogate model and the SHAP approach underscored the Comparative Illness Factor, a health indicator, and the ratio of detached dwellings as the most crucial features in the global explainability. In the case of local explanations, while both methods showed similar results, the GNN approach provided a richer, more comprehensive understanding of the predictions for two specific data zones.
Genomic Investigation for Potential Therapeutic Use of Abiraterone in the Amazonian Indigenous Population
Authors: Nobre Jonatas Monteiro , Fernandes Marianne R. , Venancio Jose Oliveira , da Costa Nunes Giovanna Gilioli , DOS SANTOS NEY PEREIRA CARNEIRO , ASSUMPÇÃO PAULO PIMENTEL , RIBEIRO-DOS-SANTOS ÂNDREA , DOS SANTOS SIDNEY EMANUEL BATISTA , RODRIGUES Juliana CARLA GOMES , Monte Natasha , Burbano Rommel M. R. , Guerreiro João Farias , Aguiar Kaio Evandro Cardoso
Published: May 2024

Prostate cancer, according to the World Health Organization (WHO), ranks as the fourth most prevalent type in the population, even though it is highly frequent when detected early and promptly treated, resulting in a low mortality rate. However, in some cases, despite adherence to proper clinical protocols, there is a progression to castration-resistant prostate cancer (CRPC). In these cases, as outlined in clinical guidelines such as those developed by the National Comprehensive Cancer Network (NCCN), one approach involves the utilization of the pharmaceutical agent abiraterone to implement androgen deprivation therapy (ADT), aimed at suppressing the production of hormones directly implicated in disease progression. Another noteworthy aspect is the limited literature on clinical protocols and their efficacy concerning the Amazonian indigenous population, which often exhibits unique genomic profiles, with descriptions of variants not yet documented in the literature. Building upon these considerations, this study aims to survey the variants identified in genes associated with the abiraterone signaling pathway, their frequencies in the Amazonian indigenous population, and the correlation of these frequencies with those observed in other global populations. The objective is to contribute to the refinement of clinical practices in the treatment of prostate cancer within this population.
Analysis of Altitude and Ambient Temperature Effects on the Reactivity of Oxidation Catalysts in the Presence of H2
Authors: Serrano José Ramón , Piqueras Pedro , Sanchis Enrique José , Conde Carla
Published: May 2024

Worldwide emission standards are now required to cover engine operation under extreme ambient conditions, which affect the raw emissions and the efficiency of the exhaust aftertreatment systems. These regulations also target new combustion technologies for decarbonization, such as neat hydrogen (H2) combustion or dual-fuel strategies, which involve a challenge to the analysis of exhaust aftertreatment systems requirements and performance. This work addresses the impact of high altitude and low ambient temperature conditions on the reactivity of an oxidation catalyst in the presence of H2. A reaction mechanism is proposed to cover the main conversion paths of CO, HC, and H2, including the formation and consumption of high-energy surface reaction intermediates. The mechanism has been implemented into a faster-than-real-time reduced-order model for multi-layer washcoat honeycomb catalytic converters. The model was utilized to investigate the effect of H2 concentration on the reactivity of CO and HC within the catalyst under various operating and ambient conditions. By applying the model and examining the selectivity towards different reaction pathways in the presence H2, insights into surface intermediates and reactivity across different cross-sections of the monolith were obtained. This analysis discusses the underlying causes of reactivity changes promoted by H2 and its relative importance as a function of driving boundary conditions.
Neuronal Ceroid Lipofuscinosis in a Mixed Breed Dog with a Splice Site Variant in CLN6
Authors: Mhlanga-Mutangadura Tendai , Bullock Garrett , Cerda-Gonzalez Sofia , Katz Martin L
Published: May 2024

A 23-month-old neutered male dog of unknown ancestry presented with a history of progressive neurological signs that included anxiety, cognitive impairment, tremors, seizure activity, ataxia, and pronounced visual impairment. The clinical signs were accompanied by global brain atrophy. Due to progression in the severity of disease signs, the dog was euthanized at 26 months of age. Examination of tissues collected at necropsy revealed dramatic intracellular accumulations of autofluorescent inclusions in the brain, retina, and cardiac muscle. The inclusions were immunopositive for subunit c of mitochondrial ATP synthase, and their ultrastructural appearances were similar to those of lysosomal storage bodies that accumulate in some of the neuronal ceroid lipofuscinosis (NCL) diseases. The also dog exhibited widespread neuroinflammation. Based on these findings, the dog was deemed likely to have suffered from a form of NCL. A whole genome sequence analysis of the proband’s DNA revealed a homozygous C to T substitution that altered the intron 3 – exon 4 splice site of CLN6. Other mutations in CLN6 cause NCL diseases in humans and animals including dogs. CLN6 protein was undetectable with immunolabeling in the tissues of the proband. Based on the clinical history, fluorescence and electron-microscopy, immunohistochemistry, and molecular genetic findings, the disorder in this dog is classified as an NCL resulting from the absence of CLN6 protein. Screening the dog’s genome for a panel of breed-specific polymorphisms indicated that its ancestry included numerous breeds, with no single breed predominating. This suggests that the CLN6 disease variant is likely to be present in other mixed breed dogs and at least some of the ancestral breeds.
Risk Factors Associated with Lost to Follow Up Tuberculosis Treatment in the Sanatorium Hospital of Luanda, Angola
Authors: Vita Domingos , Aznar Maria Luisa , Camprecios Joan Martinez , Maindo Sebastiao Kansietoko Debora Cristina , Molina Israel
Published: May 2024

Background: Tuberculosis (TB) continues to be a serious public health threat that affects the most vulnerable population. Patients who are LTFU after TB diagnosis still represent one of the biggest challenges to TB control.
Method: In this prospective observational study, we aimed to identify and analyse the risk factors associated with LTFU among TB patients who started first-line TB treatment in the Sanatorium Hospital in Luanda.
Result: A total of 113 patients with TB were included between August 2018 and September 2019. Seventy-six (67.3%) patients were cured, 27 (23.9%) were LTFU, 5 (4.4%) died, 4 (3.5%) were transferred and 1 (0.9%) presented a treatment failure. After excluding those dead, transferred or who failed to treatment, we observed that severe TB at the time of diagnosis (OR 9.24, 95% CI 2.18-39.04) and food insecurity were significantly associated with LTFU (OR 5.96, 95% CI 1.66-21.41).
Conclusion: The findings of our study are of enormous value to understand the reasons for the LTFU of patients with TB and can guide polices and facilitate designing measures to allow better adherence, and therefore, greater treatment success
Probiotic-Enriched Ice Cream with Fermented White Kidney Bean Homogenate: Survival, Antioxidant Activity, and Potential Health Benefits
Authors: Ziarno Malgorzata , Cichońska Patrycja , Kowalska Ewa , Zaręba Dorota
Published: May 2024

This study investigated a novel probiotic-enriched ice cream containing fermented white kidney bean homogenate to explore its potential health benefits. We assessed the viability of various probiotic strains during ice cream production and storage, focusing on their potential to reach the gut, and evaluated the overall antioxidant activity using DPPH, ABTS, FRAP, and TPC assays. The incorporation of fermented white bean homogenate significantly increased antioxidant capacity compared to the control group. Notably, strains like L. rhamnosus GG and L. plantarum 299v demonstrated the most pronounced effects on antioxidant activity, suggesting potential synergistic benefits between probiotics and bioactive compounds in fermented white beans. Although all probiotic strains experienced decreased viability during storage, certain strains, particularly L. plantarum 299v and L. casei DN-114001, showed promising survival rates even after 6 months. These results suggest the potential for developing probiotic ice cream containing viable bacteria capable of reaching the gut and contributing to a healthy gut microbiota. This could potentially improve digestion, reduce inflammation, and boost the immune system. Overall, this study highlights the potential of probiotic-enriched ice cream with fermented white kidney bean homogenate to combine the established benefits of probiotics for gut health with the enjoyment of consuming ice cream.
Paradoxes: Cholesterol and Hypoxia in Preeclampsia
Authors: Hart Nancy R
Published: May 2024

Preeclampsia, a hypertensive disease of pregnancy of unknown etiology, is intensely studied as a model of cardiovascular (CVD) disease not only due to multiple shared pathologic elements, but also because changes that develop over decades in CVD disease appear and resolve within days in preeclampsia. Those affected by preeclampsia and their offspring experience increased lifetime risks of CVD. At the systemic level, preeclampsia is characterized by increased cellular, membrane, and blood levels of cholesterol, however, cholesterol dependent signaling such as canonical Wnt/βcatenin, Hedgehog, and endothelial nitric oxide synthase is downregulated indicating a cholesterol deficit with upregulation of cholesterol synthesis and efflux. Hypoxia related signaling in preeclampsia also appears paradoxical with increased Hypoxia Inducible Factors (HIF) in the placenta but measurably increased oxygen in maternal blood in placental villous spaces. This review addresses the molecular mechanisms by which excessive systemic cholesterol and deficient cholesterol dependent signaling may arise from the effects of dietary lipid variance causing the cellular hypoxia which characterizes preeclampsia.
A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia
Authors: Blair David Sutherland , Miller Robyn L. , Calhoun Vince D.
Published: May 2024

Over the past decade and a half, dynamic functional imaging has revolutionized the neuroimaging field. Since 2009, it has revealed low dimensional brain connectivity measures, has identified potential common human spatial connectivity states, has tracked the transition patterns of these states, and has demonstrated meaningful alterations in these transition and spatial patterns in neurological disorders, psychiatric disorders, and over the course of development. Recently, researchers have begun to analyze this data from the perspective of dynamic system and information theory in the hopes of understanding how these dynamics support less easily quantified processes, such as information processing, cortical hierarchy, and consciousness. Consciousness, in particular, appears to be strongly linked to entropy production in the brain. Little attention has been paid to the effects of psychiatric disease on entropy production in the human brain, however. Even disorders characterized by substantial changes in conscious experience have not been widely analyzed from this perspective. We begin to rectify this by examining the complexity of subject trajectories in state space through the lens of information theory. Specifically, we identify a basis for the dynamic functional connectivity state space and track subject trajectories through this space over the course of the scan. The dynamic complexity of these trajectories is assessed along each dimension of the proposed basis space. Using these estimates, we demonstrate that schizophrenia patients display substantially simpler trajectories than demographically matched healthy controls, and that this drop in complexity concentrates along specific dimensions. We also demonstrate that entropy generation in at least one of these dimensions is linked to cognitive performance. Overall, results suggest great value in applying dynamic systems theory to problems of neuroimaging and reveal a substantial drop in the complexity of schizophrenia patients’ brain function.
Evaluating the Influence of Value-Added Tax Policy Changes on the Liquidity and Performance of Banking Sector Stocks: An Event Study Analysis
Authors: Al-Otaibi Mohammed , Nor Normaziah Mohd , Yusri Yusniati
Published: May 2024

This paper aims to provide an evaluation of how Value Added Tax (VAT) policy alterations influence market liquidity, trading volume, and stock performance. To fill the existing literature gap on the direct effect of (VAT) adjustments on stock market dynamic, particulate within the banking industry. The study employs an event study methodology to analyse the immediate and medium-term effects on bank stocks listed in markets subject to a (VAT) adjustments. The core of the study analysis is anchored around two pivotal events, the initial application of (VAT) on 1st January 2018, and the subsequent (VAT) increase to 15% on 1st July 2020 using MATLAB R2022b. The study analysis encompasses the period immediately before and after the introduction and subsequent increase (VAT) in kingdom Saudi Ariba (KSA) employing an eleven sample comprises the (KSA) largest banks with a ±7 days window period from the event. The analysis revels that the imposition of 5% (VAT) lead a substation downturn in trading volume and stock returns of 9.5%, and 39.5%, subsequently. While when the (VAT) was increased by 15% the market exhibited a mixed but ultimately positive response of 3.3% trading volumes increases and 128.7% average stock return recovery.
Reversal of Autism among Dizygotic Twins through a Personalized Lifestyle and Environmental Modification Approach: A Case Report and Review of the Literature
Authors: D’Adamo Christopher R. , Nelson Josephine L. , Miller Sara N. , Rickert Hong Maria , Lambert Elizabeth , Tallman Ruhm Heather
Published: May 2024

The prevalence of autism has been increasing at an alarming rate. Even accounting for the expansion of autism spectrum disorder diagnostic (ASD) criteria throughout the 1990’s, there has been an over 300% increase in ASD prevalence since the year 2000. The often debilitating personal, familial, and societal sequelae of autism are generally believed to be lifelong. However, there have been several encouraging case reports demonstrating reversal of autism diagnoses with a therapeutic focus on addressing the environmental and modifiable lifestyle factors believed to be largely underlying the condition. This case report describes the reversal of autism among dizygotic, female twin toddlers and provides a review of related literature describing associations between modifiable lifestyle factors, environmental exposures, and various clinical approaches to treating autism. The twins were diagnosed with Level 3 severity ASD “requiring very substantial support” at approximately 20 months of age following concerns of limited verbal and non-verbal communication, repetitive behaviors, rigidity around transitions, and extensive gastrointestinal symptoms, among other common symptoms. A parent-driven, multidisciplinary, therapeutic intervention involving a variety of licensed clinicians focusing primarily on addressing environmental and modifiable lifestyle factors was personalized to each of the twin’s symptoms, labs, and other outcome measures. Dramatic improvements were noted within several months in most domains of the twins’ symptoms, which was manifested in reductions of Autism Treatment Evaluation Checklist (ATEC) scores from 76 to 32 in one of the twins and from 43 to 4 in the other twin. The improvement in symptoms and ATEC scores has remained relatively stable for six months at last assessment. While prospective studies are required, this case offers further encouraging evidence of ASD reversal through a personalized, multidisciplinary approach focusing predominantly on addressing environmental and lifestyle risk factors.
Trends and Characteristics of Brown Rice Consumption among Adults in Japan: An Analysis of the National Health and Nutrition Surveys, 2012–2019
Authors: Ikeda Nayu , Yamaguchi Miwa , Nishi Nobuo
Published: May 2024

Brown rice is a familiar whole grain in Japan. We examined national trends in brown rice consumption among Japanese adults aged ≥ 20 years old, using individual-level data from the National Health and Nutrition Surveys conducted between 2012 and 2019. We employed multivariable logistic regression to identify factors associated with brown rice consumption. The 95th percentile of daily brown rice intake remained at 0.0 grams throughout the study period. The percentage of brown rice consumers increased from 1.8% (95% confidence interval: 1.6–2.1) in 2012 to 2.3% (95% confidence interval: 1.8–3.0) in 2019. Compared with individuals who consumed only white rice, brown rice consumers had significantly higher mean intake levels of macronutrients, legumes, vegetables, fruits, and nuts. Brown rice consumption was positively associated with certain sociodemographic characteristics (being female, older age, residing in a major city, living without very young children, and having higher education levels) and health behaviors (lower body mass index, engaging in regular exercise, and being a former or never smoker). Despite its potential nutritional benefits in balanced diets, only a small fraction of adults in Japan consume brown rice, indicating a need for further promotion, particularly among individuals with characteristics associated with brown rice consumption.
Exhibition of Corallopyronin A an Antibiotic from Different Soil Environments in Egypt
Authors: Kassab Mohammed Mahmoud Shawky
Published: May 2024

Background:
Across the world, antibiotic resistance is a critical challenge. To address such a problem, it has to be done to investigate new antibiotic sources.
Aim of the study:
Study of the antibacterial activity of Corallopyronin A in preclinical animal testing and randomized human clinical trials stages 1/2, as well as investigating the purification of Corallopyronin A from different soil conditions in Egypt.
Type of the study:
Screening experimental study.
Methodology:
Egypt's various soil conditions were tested to develop bacterial isolates that produced the antibiotic compound Corallopyronin A. Reversed phase HPLC was used to purify Myxopyronin A. The broth microdilution method and the paper disc diffusion assay determined the test antibiotic's minimum inhibitory concentration( MIC) and in vitro antibacterial activity. Moreover, in vivo antibacterial spectrum, adverse medication responses, and pharmacokinetics were found in phases 1/2 of randomized clinical studies involving humans and animal models.

Results:
Corallopyronin A was generated from the culture supernatant of the soil bacterial isolate Corallococcus coralloides M2, cultivated on a Casein yeast peptone( CYP) plate. The test antibiotic prevented the growth of several Gram-ve bacteria, including Escherichia coli, at MICs higher than 100 mcg/ ml; while blocking the development of many Gram +ve bacteria, with MICs ranging from 3 to 15 mcg/ ml. However, eukaryotic cells—such as those found in fungi and humans—were unaffected. A bactericidal consequence of the test antibiotic was detected in the inhibition of prokaryotic DNA-dependent RNA polymerase( RNLP). Conclusion:
The synthesis of the bactericidal antibiotic Corallopyronin A from Corallococcus coralloides M2 isolated from different soil settings in Egypt intrigued the current investigation.
Are the Comorbidities Constitute an Intrinsic Factor for Long COVID?
Authors: Ashmawy Rasha , Hammouda Esraa Abdellatif , El-Maradny Yousra A. , Aboelsaad Iman , Hussein Mai , Uversky Vladimir N. , Redwan Elrashdy M.
Published: May 2024

Long COVID, a name often given to the persistent symptoms following acute SARS-CoV-2 infection, poses a multifaceted challenge for health. This review explores the intrinsic relationship between comorbidities and autoimmune responses in shaping the trajectory of long COVID. Autoantibodies have emerged as significant players in COVID-19 pathophysiology, with implications for disease severity and progression. Studies show immune dysregulation persisting months after infection, marked by activated innate immune cells and high cytokine levels. The presence of autoantibodies against various autoantigens suggests their potential as comorbid factors in long COVID. Additionally, the formation of immune complexes may lead to severe disease progression, highlighting the urgency for early detection and intervention. Furthermore, long COVID is highly linked to cardiovascular complications and neurological symptoms, posing challenges in diagnosis and management. Multidisciplinary approaches, including vaccination, tailored rehabilitation, and pharmacological interventions, are used for mitigating long COVID's burden. However, numerous challenges persist, from evolving diagnostic criteria to addressing the psychosocial impact and predicting disease outcomes. Leveraging AI-based applications holds promise in enhancing patient management and improving our understanding of long COVID. As research continues to unfold, unravelling the complexities of long COVID remains paramount for effective intervention and patient care.
Coupling Fault Diagnosis Based on Dynamic Vertex Interpretable Graph Neural Network
Authors: Wang Shenglong , Jing Bo , Pan Jinxin , Meng Xiangzhen , Huang Yifeng , Jiao Xiaoxuan
Published: May 2024

Mechanical equipment is composed of several parts, the interaction between the parts exists throughout whole life cycle leads to the widespread phenomenon of fault coupling and the diagnosis of independent faults cannot meet the requirements of the health management of mechanical equipment under actual working conditions. In this paper, the topological structure of graph neural network is used to describe the correlation of coupling faults and multiple fault types are regarded as network nodes respectively. The fault features are fused and extracted by graph convolution to achieve the classification of coupling faults. In this paper, dynamic vertexes are defined in data topology and the parameters of DIGNN classification model are optimized by changing the fault type of dynamic vertexes during training stage. The data is loaded into dynamic vertexes for classification and analysis during testing stage. The one-dimensional vibration data is converted into two-dimensional time-frequency domain data by wavelet transform making the input features of the model interpretable to reduce the uncertainty of model training. The data topology is then fed into DIGNN for fault classification, and GCN's node aggregation gives interpretability to each layer of network data processing. The method proposed in this paper can realize accurate diagnosis of independent faults on the data set, and can effectively judge the coupling mode of coupling faults, which is suitable for coupling fault analysis of mechanical equipment.
Analytic Formulae for T Violation in Neutrino Oscillations
Authors: Yasuda Osamu
Published: May 2024

Recently, a concept known as μTRISTAN, which involves the acceleration of μ+, has been proposed. This initiative has led to considerations of a new design for a neutrino factory. Additionally, leveraging the polarization of μ+, measurements of T violation in neutrino oscillations are also being explored. In this paper, we present analytical expressions for T violation in neutrino oscillations within the framework of standard three flavor neutrino oscillations, a scenario involving nonstandard interactions, and a case of unitarity violation. We point out that examining the energy spectrum of T violation may be useful for probing new physics effects.
Implementation of IoT Sensors in Fog Collector Systems and Flowmeters for the Control of Eater Collection and Distribution
Authors: Carrera-Villacrés David Vinicio , Gallegos-Ríos Diego Fernando , Chiliquinga-López Yadira Alexandra , Córdova-Córdova José Javier , Arroba-Giraldo Andrea Mariela
Published: May 2024

This study describes the implementation of IoT sensors in drinking water systems and fog collector systems in low-income communities in Ecuador. The influence and handling of these sensors are analyzed, as well as the materials and methods used in their implementation. The importance of validating the accuracy and reliability of IoT sensors compared to professional devices, especially in mountain areas, is highlighted. In addition, it is mentioned that the cost-benefit of using IoT sensors in fog catchers and drinking water networks depends on several factors, such as the scale of the project, specific objectives, and available resources. Finally, it is highlighted that the use of IoT sensors in smart construction and water collection systems has proven to be beneficial in preventing effects on the operation.