bluuebunny/crossref_metadata_2025_split huggingface dataset:
The verification of quantum non-local correlation in ΛΛ- system
Authors: Liao Guangrui , Ping Ronggang , Qiao Cong-Feng 
Published: October 2024

Abstract

The non-locality of quantum correlations is a fundamental feature of
quantum theory. The Bell inequality serves as a benchmark for
distinguishing between predictions made by quantum theory and local
hidden variable theory (LHVT). Recent advancements in
photon-entanglement experiments have addressed potential loopholes and
have observed significant violations of variants of Bell inequality. However,
these violations do not completely disprove LHVT. To further rule out
LHVT, experiments involving massive-entangled particles are necessary,
in addition to those conducted with massless photons, which interact
electromagnetically. In this study, we utilize
(10.087±0.044)×109 J/ψ events collected with the BESIII
detector at the BEPCII collider. We present the non-local
correlation test of spin entanglement using a massive
ΛΛbar bipartite system, which is formed and decays through strong and weak interactions, respectively. Through measurements of the angular distribution
of p pbar in J/ψ→ γηc and subsequent
ηc→Λ(pπ-)Λbar(pbar π+) cascade decays,
a significant violation of LHVT predictions is observed in a
loophole-free test of a variant of the Bell inequality, which is given
by the Clauser-Horne inequality. The exclusion of LHVT is
determined to be significant at a level of 5.2σ.
Evaluating Cognitive Decline Detection in Aging Populations with Single-Channel EEG Features: Insights from Studies and Meta-Analysis
Authors: Molcho Lior , Maimon Neta B. , Zeimer Talya , Chibotero Ofir , Rabinowicz Sarit , Armoni Vered , On Noa Bar , Intrator Nathan , Sasson Ady 
Published: October 2024

Abstract

Timely detection of cognitive decline is paramount for effective intervention, prompting researchers to leverage EEG pattern analysis, focusing particularly on cognitive load, to establish reliable markers for early detection and intervention. This comprehensive report presents findings from two studies and a meta-analysis, involving a total of 237 senior participants, aimed at investigating cognitive function in aging populations. In the first study, 80 seniors were classified into two groups: 40 healthy individuals (MMSE > 28) and 40 at risk of cognitive impairment (MMSE 24–27). Dimensionality reduction models, such as Lasso and Elastic Net, were employed to analyze EEG features correlated with MMSE scores. These models achieved a sensitivity of 0.90 and a specificity of 0.57, indicating a robust capability for detecting cognitive decline. The second study involved 77 seniors, divided into three groups: 30 healthy individuals (MMSE > 27), 30 at risk of MCI (MMSE 24–27), and 17 with mild dementia (MMSE < 24). Results demonstrated significant differences between MMSE groups and cognitive load levels, particularly for A0 and Gamma band. A meta-analysis, combining data from both studies and additional data, included 237 senior participants and 112 young controls. Significant associations were identified between EEG biomarkers, such as A0 activity, and cognitive assessment scores including MMSE and MoCA, suggesting their potential as reliable indicators for timely detection of cognitive decline. EEG patterns, particularly Gamma band activity, demonstrated promising associations with cognitive load and cognitive decline, highlighting the value of EEG in understanding cognitive function. The study highlights the feasibility of using a single-channel EEG device combined with advanced machine learning models, offering a practical and accessible method for evaluating cognitive function and identifying individuals at risk in various settings.
Investigating the Mediating Effects of Urinary Phenols and Parabens on the Relationship Between Phthalate Exposure and Metabolic Changes in Adults
Authors: Ripon Rezaul Karim 
Published: October 2024

Abstract

Background
Phthalates and other environmental contaminants, such as phenols and parabens, have been implicated in metabolic health disturbances. This study investigates the mediating effects of urinary phenols and parabens on the relationship between phthalate exposure and Metabolic Changes in adults. Methods: Data from the National Health and Nutrition Examination Survey (NHANES) 2009–2010 cycle were utilized, encompassing 1,669 adults. Phthalate exposure was measured via urinary Ethyl Paraben. BMI served as a proxy for metabolic health changes. The analysis employed mediation models to explore whether urinary phenols and parabens mediate the relationship between phthalate exposure and metabolic Changes, adjusting for covariates. Results: The median age of participants was 46 years, with nearly equal gender distribution (51% males and 49% females). The mediation analysis revealed significant mediation effects for Benzophenone-3 and Propyl Paraben. For Benzophenone-3, the Average Causal Mediation Effect (ACME) was − 0.000773 (95% CI: -0.001242 to 0.000, p < 2e-16), and the direct effect (ADE) was − 0.004198 (95% CI: -0.008295 to 0.000, p = 0.016). Similarly, Propyl Paraben presented significant mediation with an ACME of -0.00105 (95% CI: -0.00159 to 0.000, p = 0.020), and the direct effect (ADE) was − 0.00393 (95% CI: -0.00789 to 0.000, p = 0.036). Conclusion: This study provides robust evidence that specific urinary phenols and parabens significantly mediate the relationship between phthalate exposure and metabolic Changes, shedding light on the pathways through which environmental contaminants might influence metabolic health. The findings underscore the necessity for further research and regulatory measures to mitigate exposure to these chemicals and their impacts on metabolic health.
VaxSeer: Selecting influenza vaccine strains through evolutionary and antigenicity models
Authors: Shi Wenxian , Wohlwend Jeremy , Wu Menghua , Barzilay Regina 
Published: October 2024

Abstract

Current vaccines provide limited protection against rapidly evolving viruses. For example, the influenza vaccine's effectiveness has averaged below 40% for the past ten years. Today, clinical outcomes of vaccine effectiveness can only be assessed retrospectively. Prospective estimation of their effectiveness is crucial but remains under-explored. In this paper, we propose an in-silico method named VaxSeer that predicts expected vaccine effectiveness by considering both the future dominance of circulating viruses and antigenic profiles of vaccine candidates. Based on ten years of historical WHO data, our approach consistently selects superior strains than the annual recommendations. Finally, the prospective score we propose exhibits a strong correlation with retrospective vaccine effectiveness and reduced disease burden, highlighting the promise of this framework in driving the vaccine selection process. Predictions from our model for the 2024 and future winter seasons are available at https://wxsh1213.github.io/vaxseer.github.io/.
Minimally invasive flexible, wireless multimodal probe to detect compartment syndrome
Authors: Jin Sung Hun , Seo Seung Gi , Kim Seungyeob , Yoo Seonggwang , Oh Seyong , Luan Haiwen , Lv Zengyao , Lu Di , Park Yaeshin , Lee Jae Hee , Jo Hyeon-Bin , Westman Amanda , Moritz William , Ribaudo Joseph , Huang Yonggang , Pet Mitchell , Rogers John 
Published: October 2024

Abstract

Acute Compartment Syndrome (ACS) is a serious medical condition that arises from increased pressure within muscle compartments, leading to impaired blood flow and potential tissue damage. Early and accurate diagnosis is critical for preventing permanent damage. Current methods rely largely on qualitative assessments with limited accuracy, and those that exploit invasive pressure measurements often prove inadequate. Herein, we introduce a multimodal probe designed to monitor pressure, tissue oxygen saturation (StO2), and blood flow simultaneously at a common location within an affected compartment. The system integrates three sensors into a thin, flexible probe capable of real-time, wireless data transmission. The device allows for continuous monitoring with high reproducibility and sensitivity, to enhance diagnostic accuracy relative to current clinical practice, with the potential to reduce unnecessary fasciotomies. Large animal model studies, including short- and intermediate-term reliability assessments, highlight the key engineering features. The results reveal expected inverse relationships between pressure, StO2, and flow rate under simulated compartment syndrome conditions. This multimodal approach enhances diagnostic precision, offers real-time insights, and promises to yield improved outcomes through a comprehensive, quantitative assessment of compartment syndrome.
Trends and cross-country disparity in the burden of pulmonary arterial hypertension: results from Global Burden of Disease Study 2021
Authors: Zeng Zhilin , Pan Lanyue , Li Qinghai , Wang Qi , Cheng Sheng , Chen Qiuying , Huang Jiaquan , Yang Ruonan , Chen Huilong , Zhan Yuan 
Published: October 2024

Abstract

Background
Pulmonary hypertension (PH) is a cardiopulmonary disease with complicated etiologies and classifications, gradually attracting extensive attention due to its ever-growing disease burden. Here, we aim to elucidate the PH burden and trends at global, regional and country levels over the past thirty-two years.
Methods
Data about PH prevalence, death and disability-adjusted life-years (DALYs) were obtained from Global Burden of Disease Study 2021. Moreover, the relationship between PH burden and social development index was explored. Eventually, the relevance of PH to four cardiopulmonary comorbidities were verified.
Results
From the global perspective, PH prevalence was annually rising from 1990 to 2021, primarily affecting females and young adults (age from 15 to 49). While PH death also elevated during the past 32 years and was the elder predomination. DALYs of PH presented a slightly overall decrease but surged in underdeveloped areas. Nevertheless, age-standardized death rate and DALYs exhibited significantly declines, especially in relatively developed regions with advanced healthcare resources. At meanwhile, correlation analysis demonstrated a certain negative association of SDI with age-standardized death rate or age-standardized DALYs either across 21 regions or 204 countries. Eventually, the prevalence of PH showed strongly positive associations with that of four cardiopulmonary disorders including chronic obstructive pulmonary disease, interstitial lung disease, ischemic heart disease and hypertensive heart disease.
Conclusion
The current report suggested an increasingly serious burden of PH, particularly in less developed regions. Comprehensive understanding of PH epidemiology and high-risk comorbidities can benefit those dedicated to PH prevention and control.
Determination of design discharge and environmental flow in micro hydropower plants based on flow duration curve in small rivers: A Case Study of Hhaynu River -
Mbulu,Tanzania
Authors: Ngoma Daniel H. 
Published: October 2024

Abstract

In designing micro hydropower plants capacity, the amount of water flow discharge determination is very essential in estimating the power output for the micro hydropower scheme due to the fact that in recent years there has been an increase in water demand due irrigation activities because of an increase in agriculture activities [1]. From the literature, there are several methods that are used to determine hydro turbine water flow discharge but the most widely used method is the hydrological method which is based on the formulation of flow duration curve or hydrograph for the respective river flow based on site historical and measured hydrological data.
The hydrograph represents the amount of water flow in m3/s that is available for a particular river or stream in percentage from the historical hydrological data which has been computed over a period of more than one year. From the study of Hhaynu River which is a small river in Tanzania, the computed flow results show that, 8% of the time the flow is at 2.3 m3/s while at 50% of the time the river flow was at 1.86 m3/s and at 100% of the time the water flow was at 0.60 m3/s. When determining design discharge for run-of-river schemes, provision have to be considered for environmental flow on which for the Hhaynu River this has been analysed to be 0.2 m3/s (33.3% of river base flow) which resulted to the hydro-turbine development design water flow discharge of 0.4 m3/s from the computed flow duration curve with provision for environmental flow.
The usefulness of developing flow duration curve for rivers is to determine the available water flow in a particular small river and its suitability for micro hydropower development from estimates of the amount of water flow discharge.
Botnet Prevention using Blockchain for SDN based IoT Devices
Authors: Kamran Shehryar , Shafi Qaisar 
Published: October 2024

Abstract

The Internet of Things (IoT) sector is being targeted by increasing botnets that can disrupt networks. This paper solves this problem by introducing a Software Defined Networks (SDNs) and blockchain integrated system focused on blocking IOT device botnets, such as Mirai.
Their goal is to construct a model that combines the controllability of SDN with the unchangeable and distributed features in blockchain. It would detect botnet activities through network traffic analysis, improve security with blockchain and be a scalable solution for large networks of devices.
The efficacy of this model was tested in a simulated environment, which resembles actual network situations. Ryu controllers synced Open vSwitch instances with emulated IoT devices using a blockchain platform made of Hyperledger Fabric. Finally, testing was carried out in Mininet, for network emulation and also ger- mini, for botnet attack simulation. Ryu applications running over x-trust-domain interfaces were developed to capture and detect botnet behaviours; as necessary, they both dropped malicious packets and took enforcement actions.
The results proved the efficiency of the developed model to detect botnet attacks and to increase network security. Peripheral nature and scope of centralized model meant it could be deployed at a larger scale. This study paves the way for implementing proactive security solutions within IoT ecosystems.
Enhancing Healthcare Delivery Through Digital Health Interventions: A Systematic Review on Telemedicine and Mobile Health Applications in Low and Middle-Income Countries (LMICs)
Authors: Jones-Esan Lawrence , Somasiri Nalinda , Lorne Keda 
Published: October 2024

Abstract

This study explores the role of telemedicine and mobile health (mHealth) technologies in improving healthcare delivery within low- and middle-income countries (LMICs). A thorough review of existing literature reveals that these technologies have made significant strides in enhancing healthcare access, diagnostics, and patient outcomes, particularly in underserved and remote areas. Key findings indicate that telemedicine has played a crucial role in enabling early disease detection, boosting maternal and child health, and promoting improved medication adherence among patients. Nevertheless, the study also uncovers significant barriers that impede the effective implementation of these technologies, including inadequate infrastructure, unreliable internet connections, limited digital literacy, regulatory challenges, lack of funding, and a shortage of trained healthcare professionals. Additionally, the review notes its limitations, such as the omission of grey literature and inconsistencies in regional research coverage, which may impact the overall findings. To address these challenges, the study emphasises the need for LMICs to invest in technological infrastructure, improve digital literacy, create comprehensive regulatory frameworks, and secure sustainable funding sources. Furthermore, integrating telemedicine into national healthcare strategies and enhancing public awareness are critical steps to fully leverage the advantages of these technologies, ultimately fostering equitable healthcare access and improved health outcomes in resource-constrained environments.
Hybrid Red Fox and Improved Whale Optimization Algorithm-based Clustering scheme for improving network longevity in Wireless Sensor Networks
Authors: Rajaboina Nagendra Babu 
Published: October 2024

Abstract

Guaranteeing energy stability is highly challenging in Wireless Sensor Networks (WSNs) as it contributes towards an enhanced network lifespan. Clustering with improved energy efficacy is found to be an NP-hard optimization problem with the possibility of offering extended network lifespan. Several computational methods that comprise of nature inspired meta-heuristic as well as reinforcement schemes along with evolutionary algorithms are used for supporting effectual clustering in WSNs. The heuristic and meta-heuristic schemes of CH selection designed for dealing with optimization problems using empirical behaviour was identified to be ideal in better clustering process. In this paper, Hybrid Red Fox and Improved Whale Optimization Algorithm (HRFIWOA)-based Clustering scheme is proposed enhancing lifespan expectation and energy constancy in WSNs. This HRFIWOA is proposed with the global optimization competence of the Red Fox Optimization Algorithm (RFOA) and local optimization capability of Improved Whale Optimization Algorithm (IWOA). It specifically included IWOA into RFOA for achieving and sustaining a balance amid the stages of exploration and exploitation which is demanded for optimised CH selection. The adopted IWOA helps in better exploitation of the solution that comprises of information pertaining to the sensor nodes which can be potentially identified as CH in the network. The simulation results of the proposed HRFIWOA confirmed promising capability in improving the packet deliver rate by 20.96%, network lifespan by 18.54%, throughput by 17.62% with reduced latency of 19.28%, and minimized energy consumption of 22.39%, better than the competitive CH selection schemes used for investigation.
Behavioural and biochemical studies of Schumanniophyton magnificum (K.schum) leaves in mice.
Authors: Olusola Ayomide , Asowata-Ayodele Abiola M. , Afolabi Felix , Salemcity Aanuoluwa J. , Olatuyi Olalekan 
Published: October 2024

Abstract

Current evidences indicate that efforts to develop novel antipsychotic agents with multipronged mechanisms of action have been limited. The study evaluated the behavioural activities of ethanolic extract of Schumanniophyton magnificum leaves in mice. It investigated the neuro-behavioral and antioxidant properties of the ethanolic extract of Schumanniophyton magnificum leaves administered through the oral route of mice at different doses for 14 days. The behavioral assessment was demonstrated using the Open Field Test for assessing the ketamine-induced hyperlocomotion, Y-Maze test was used for assessing the behavior, learning and memory (cognition) and novel object recognition test to evaluate the willingness of the mice to explore new environment or object in animal models of the central nervous disorders. This research shows that after 14 days of administration, the animals were sacrificed and antioxidant bioassay was carried out on the brain. Schumanniophyton magnificum treatment (100, 200, and 400 mg/kg) significantly (P < 0.05) reduced hyper-locomotion induced by ketamine, which is a predictor of positive symptoms. Schumanniophyton magnificum treatment (100 and 400 mg/kg) significantly enhanced spatial memory formation preventing cognitive deficits by ketamine. Additionally, Schumanniophyton magnificum treatment (100, 200, and 400 mg/kg) significantly increased the SOD & CAT activities, as well as decreased MDA levels, this is suggesting that the antipsychotic-like action of Schumanniophyton magnificum maybe through inhibition of oxidative crises induced by ketamine. Therefore this plant might be one of the plants to watch out for the treatment of psychosis.
Synthesis, Characterization and Catalytic Activity of Polyethylene Glycol (PEG) Functionalized MXene (Ti3C2Tx) for Methylene Blue Dye Degradation Under UV Light Irradiation
Authors: Mamun Muhammad Shamim Al , Rahman Maisha , Takaoka Tsuyoshi , Komeda Tadahiro , Aly Mohamed Aly Saad , Nasiruddin Md , Alahmad Waleed 
Published: October 2024

Abstract

The emerging field of two-dimensional (2D) transition metal carbides and nitrides, collectively known as MXene (Ti3C3Tx), has garnered significant attention in recent years due to their remarkable properties and multifaceted applications. This work explores the synthesis, characterization and functionalization of MXene with polyethylene glycol (PEG) and its influence on the degradation process of organic dye methylene blue (MB) is investigated. The functionalization of MXene with PEG is detailed, showcasing the diverse chemistries and functionalities these organic compounds bring to the MXene nanosheets. PEG imparts hydrophilicity and stability, and promotes catalytic activity. Further the mechanisms of dye degradation involving MXene-PEG materials are elucidated, highlighting the synergistic effects of MXene and functional groups on the enhanced degradation rates. This work underscores the versatility of MXene as a platform for environmental applications and the significant impact of functionalization with organic molecules on their performance. The findings of this work revealed that when MXene-based nanomaterials suitably functionalized with PEG, they exhibit immense potential in the reduction of methylene blue (MB) dye with a record breaking first order rate constant of 0.16581 ± 0.030 min− 1.