bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk Stratification of New-Onset Psychiatric Disorders Using Clinically Distinct Traumatic Brain Injury Sub-Phenotypes
Authors: Kureshi Nelofar , Nunes Abraham , Feng Cindy , Clarke David B. , Abidi Syed Sibte Raza 
Published: May 2024

Abstract

Background
Traumatic brain injury (TBI) patients constitute a highly heterogeneous population, with varying risks for New-onset Psychiatric Disorders (NPDs). The objectives of this study were to identify TBI phenotypes and determine how NPDs differ among these phenotypes.
Methods
Hospitalized TBI patients from 2003–2019 were obtained from the provincial trauma registry. Propensity score matched samples were used to estimate the risk of TBI on NPDs. To uncover heterogeneity in TBI, latent class analysis-based clustering was applied. The effect of classes on NPDs was assessed using log binomial regression models.
Results
A total of 3,453 TBI patients were included in the analysis. In a conditional regression involving propensity matched TBI and control patients, TBI was significantly associated with the development of NPD-A (OR: 2.78; 95% CI: 2.49–3.09), as well as NPD-P (OR: 2.36; 95% CI: 2.07–2.70). Eight distinct latent classes were identified which differed in the incidence of NPDs. Four classes displayed a 53% (RR:1.53; 95% CI: 1.31–1.78), 48% (RR:1.48; 95% CI: 1.26–1.74), 28% (RR:1.28; 95% CI: 1.08–1.54), and 20% (RR: 1.20, 95%CI: 1.03–1.39), increased NPD risk.
Conclusion
TBI is a significant predictor of NPDs. There are clinically distinguishable phenotypes with different patterns of NPD risk among TBI patients. Identifying individuals with respect to their phenotype may improve risk stratification of TBI patients and promote early intervention for psychiatric care in this vulnerable population.
Pythagorean Cubic Fuzzy Aggregation Operators based on Sine Trigonometric Operational Laws and their Application in Decision Making Problem
Authors: Azam Muhammad , Jadoon Atif Mehmood 
Published: May 2024

Abstract

The implementation of Pythagorean cubic fuzzy set (PCFs) are more extensive as it is a fundamental concept
for addressing higher uncertainty in decision making problems. The symmetry and periodicity of the triangle are
maintained via the natural origin of the well-known sine trigonometric function and as a result it satisfies the
decision maker’s expectations across a number of parameters. Considering this feature and the significance of
the PCFs into the consideration, the main objective of the article is to describe some reliable sine trigonometric
laws (STLs) for PCFs. Associated with these laws, we develop new average and geometric aggregation operators
to aggregate the Pythagorean fuzzy numbers (PCFNs). We also describe the desired characteristics of the
suggested operators. Then, utilizing the created aggregation operators, we create a group decision making
technique to address the multiple attribute group decision making problems and demonstrated this with a
practical example. We compared the proposed aggregating procedures to the existing methods in order to
demonstrate their superiority and validity od our proposed methods. Based on the comparison and sensitivity
analysis, we came to the conclusion that our suggested methodology is more reliable and effective.
Dual Role of Necroptosis in Cervical Cancer: Promoting Tumor Aggression and Modulating the Immune Microenvironment via the JAK2-STAT3 Pathway
Authors: Xu Fangfang , Ye Yingjun , Gao Yueqing , Xu Shaohua 
Published: May 2024

Abstract

Objective
In the dynamic landscape of cervical cancer (CC) pathophysiology, this study aimed to elucidate the role of necroptosis in modulating tumor proliferation, invasion, and the immune microenvironment in CC.
Methods
In this study, the impact of necroptosis on CC was evaluated through a series of bioinformatical analyses and experimental approaches. The impact of necroptosis on CC was illustrated by analyzing its effects on tumor aggression, immune responses, and the JAK2-STAT3 signaling pathway. Bevacizumab, a monoclonal antibody targeting vascular endothelial growth factor (VEGF), was also evaluated for its potential induction of necroptosis in CC cells and its interaction with necroptosis inhibitors. Additionally, the study assessed the influence of necroptosis on the immune microenvironment, particularly in T-cell-related pathways and the expression of tumor suppressor genes in CC.
Results
Necroptosis was found to enhance VEGFA expression through activation of the JAK2-STAT3 pathway, promoting tumor proliferative and invasive capabilities in CC. Bevacizumab induced necroptosis in CC cells, potentially leading to resistance in therapy. The combination of bevacizumab with necroptosis inhibitors attenuated VEGFA expression, suggesting a novel therapeutic strategy. Additionally, necroptosis activated T-cell-related pathways and promoted the infiltration and activation of Jurkat T cells. CD3D—a tumor suppressor gene in CC—was identified as a critical marker and its expression could be upregulated by necroptosis via the JAK2-STAT3 pathway in Jurkat T cells. Treatment of CC cells with supernatants from necroptosis-induced Jurkat cells resulted in reduced tumor cell proliferation and invasion.
Conclusions
This study reveals a complex interaction between necroptosis, tumor progression, and the immune response in CC. The findings propose a nuanced approach to leveraging necroptosis for therapeutic interventions, highlighting the potential of combining necroptosis inhibitors with existing therapies to improve treatment outcomes in CC.
Small neural networks under external forcing: Periodic pulses and Lévy noise
Authors: Rybalova Elena , Semenova Nadezhda 
Published: May 2024

Abstract

Neurons in an excitable mode do not show spiking activity and therefore do not contribute to the information transfer transmission and its processing. However, some external influences, coupling or time delay can lead to the appearance oscillations in individual systems or networks. In this study, we analyze the dynamics of a small network of locally coupled FitzHugh–Nagumo oscillators in the absence and presence of several types of external influence. Firstly, we consider the impact of periodic-pulse exposure generated as a periodic sequence of Gaussian pulses. Secondly, we show what behavior can be induced by Lévy noise and its special case, white Gaussian noise. For both types of influences, we have identified the appropriate parameters (local coupling strength, intensity, and frequency) that induces spiking activity in a small network.
Numerical approaches for constraint stabilization of constrained dynamic system
Authors: An Jae-Hyoung , Kyung JungHyun , Eun Hee-Chng 
Published: May 2024

Abstract

Numerous studies have explored constrained motion within structural and mechanical systems, revealing that numerical integrations of such dynamic responses often exhibit drift errors, diverging from intended trajectories. This study introduces two numerical analysis techniques aimed at mitigating these errors. In 1992, Udwadia and Kalaba introduced the Generalized Inverse Method (GIM), providing a unique, explicit mathematical formulation for describing constrained motion. This paper presents a Modified Generalized Inverse Method (MGIM) that refines the GIM by adjusting the coefficients at the acceleration level constraints. Additionally, a Direct Integration Method (DIM) is developed by minimizing the discrepancy between unconstrained and constrained accelerations, incorporating coefficients into acceleration level constraints. Numerical examples demonstrate that the magnitude of these coefficients significantly influences drift errors. Moreover, it is shown that constrained responses can be stabilized and errors reduced, although this study does not specify the exact coefficients necessary for achieving stabilization.
Monomeric and dimeric complexes of pyrimidine-4,6-dicarboxylic acid with organometallic fac-[M(CO)3]+ (M = Re and 99mTc) core as radiopharmaceutical probes
Authors: Mukiza Janvier , Habarurema Gratien , Sezirahiga Jurdas , Mukabagorora Theonille , Nkuranga Jean Bosco , Uwambajineza Tite , Muyizere Theoneste , Blacque Olivier , Baziga Gervais 
Published: May 2024

Abstract

The current study describes the synthesis of monomeric and dimeric complexes of pyrimidine-4,6-dicarboxylic acid (H2pmdc) ligand with the organometallic fac-[M(CO)3]+ (M = Re and 99mTc) core which are the model for future design of imaging, therapeutic and theranostic radiopharmaceuticals. Monomeric complexes [M(CO)3(OH2)(Hpmdc)] (M = Re (1) and 99mTc (2)) were formed from the reaction of H2pmdc with [Re(CO)5Br] and [99mTc(CO)3(OH2)3]+ in aqueous solution respectively. The reaction of [Re(CO)5Br] with H2pmdc in ethanol (EtOH) led to the monomeric complex [Re(CO)3(OH2)(etpmdc)] (3), where etpmdc− is 6-(ethoxycarbonyl)pyrimidine-4-carboxylate anion which was formed from the mono-esterification of H2pmdc in parallel with its coordination to the fac-[Re(CO)3]+ unit. Dimeric complex (Et3NH)2[(µ-pmdc)2(Re(CO)3)2 (4) was obtained from the reaction of [Re(CO)5Br] with H2pmdc in water with addition of triethylamine (Et3N) as supporting base. The chemical identification of 1, 3 and 4 was achieved by using 1HNMR, 13CNMR, IR, ESI-MS and elemental analysis. Complex 3 was furtherly identified by using single crystal X-ray crystallography. The structural similarities of 1 and 2 was assessed by coinjection in the HPLC with UV/Vis detection coupled with a γ-detector followed by comparison of retention times of the γ-peak of 2 and the UV-peak of 1 which allowed unambiguous identification of 2. Heterodinuclear 99mTc/Re complex [(µ-pmdc)2(Re(CO)3)(99mTc(CO)3)2)]2− (5) was formed by reacting H2pmdc with [99mTc(CO)3(OH2)3]+ and [Re(CO)5Br] in aqueous solution. In parallel, the reaction also yielded complexes 1 and 2. The formation of 5 was assessed by injection in the HPLC with UV/Vis detection coupled with a γ-detector which displayed the radiochemical peak with the corresponding UV peak equivalent to that of the homologous non-radioactive complex 4.
On the Effects of Jacks Correlation on the Secrecy Multicast Capacity of MIMO Fading Channels: A Comparative Study
Authors: Sultana Rezwana , Sarker M. Z. I. , Hossain M. S. 
Published: May 2024

Abstract

A confidential communication over multiple-input multiple-output (MIMO) fading channels is considered, in which a transmitter communicates with a group of receivers in the presence of multiple eavesdroppers. The antenna correlation depends on both the antenna spacing and the angular spectrum of the incoming radio waves. We derive the closed-form analytical expressions of the ergodic secrecy multicast capacity for Rayleigh and Ricean fading MIMO channels considering a linear array with equally spaced antennas and employing the classical Jakes correlation. Then, we compare the performance of Rayleigh and Ricean fading channels showing the effects of fading, antenna correlation and the spacing between antenna elements. Our results show that antenna correlations significantly reduces the ergodic secrecy multicast capacity of Rayleigh as well as Ricean fading MIMO channels and this effect is more severe in the case of Rayleigh fading channel compared to Ricean fading.
Enhancing Thermal Conductivity And Fire Resistance Of Polycotton Via Silica And Titanate Xerogel Coatings: A Comparative Study
Authors: ASSAL Mohamed , WAZNA Mmohamed EL , BOUCHTI Mehdi EL , BOUARI Abdeslam EL , CHERKAOUI Omar 
Published: May 2024

Abstract

Titanate and silicate xerogels have garnered considerable attention in the realm of thermal insulation due to their outstanding attributes, encompassing thermal conductivity and fire resistance. This study focused on pioneering a new multifunctional textile by integrating xerogels—both titanate and silicate—as additives for enhancing polycotton fabric. Microstructural analyses involved SEM observations, while diverse chemical bonds were identified through iTR-IR technique. Evaluation of thermal properties encompassed TGA, DSC, and thermal conductivity measurements. Findings reveal that the treated fabrics exhibit exceptional flame resistance, they do not burn and therefore exhibit good fire resistance compared to untreated polycotton. Additionally, the multifunctional fabric showcases enhanced thermal stability compared to its untreated counterpart. Consequently, the application of titanate and silicate xerogel coatings yields a versatile textile with substantial potential for smart clothing and personal heating applications.
Bacterial and Fungal Communities Impact on Degradation of Plastic Mulch Residuals in Soil
Authors: Romano Ida , Ventorino Valeria , Schettino Mariachiara , Magaraci Giuseppina , Pepe Olimpia 
Published: May 2024

Abstract

Although plastic mulching films can help increase agricultural productivity, their removal poses a significant environmental danger. The use of biodegradable plastic mulches is an appealing eco-sustainable solution to environmental contamination problems for agroecosystems. Because the biodegradation of plastic pieces in soil is strongly dependent on microbial populations, it is critical to investigate whether and how microbial communities affect different types of mulch residuals in the soil. Through the study of the degradation of different mulches residues and of the microbial dynamics for a 6-month incubation of soil trial at three different incubation temperatures (room temperature, 30°C and 45°C) it was possible to evidence that biodegradation of mulch residual depending on of the catabolic activities of specific microbial population and the temperature of incubation. In particular, the increase of temperature up to 45°C determined a reduction of the degradation capacity for all types of mulch considered. Moreover, high-throughput sequencing bacterial alpha diversity was primarily influenced by plastic type and temperature, while fungal populations were mainly affected by temperature. Beta diversity was impacted by all experimental variables. Predicted functional genes crucial for degrading complex substrates, including those encoding hydrolases, cutinases, cellobiosidases, and lipases, were derived from 16S rRNA gene sequencing data. Cluster analysis based on predicted enzyme-encoding gene abundance revealed two clusters, mainly linked to sampling time. Finally, core microbiome analysis identified dominant bacterial and fungal ASVs in various soil-plastic ecosystems during degradation, pinpointing species potentially involved in plastic breakdown.
Functional Characterization of a Lassa Virus Fusion Inhibitor Adaptive Mutant
Authors: Guo Jiao , Zhang Guangshun , Liu Yang , Cao Junyuan , Zhang Mengmeng , Lan Xiaohao , Zhang Yueli , Liu Chenchen , Xiao Gengfu , Wang Wei 
Published: May 2024

Abstract

The LASV glycoprotein complex (GPC) contains a retained stable signal peptide (SSP), GP1, and GP2. SSP interacts with GP2 and provides an interface targeted by numerous fusion inhibitors. Serialpassaging of LASV with inhibitors allowed some adaptive mutants to be obtained, most of which had mutations located in the transmembrane (TM) domain of GP2. In the current study, we focused on the F446L mutant, which is reported to confer resistance to ST-series inhibitors. We found that F446L cells conferred cross-resistance to structurally distinct inhibitors. Furthermore, F446L increased the fusion activities of LASV and Mopeia virus GPC, elevating the pH threshold for the fusion of LASV and promoting the fusion of MOPV at neutral pH. F446L had little effect on the growth profile or thermostability of the pseudotype of the virus. By introducing other residues to the conserved F446 locus, it was found that this site was less compatible with a similar tyrosine residue and was intolerant to charged residues. These results help characterize the fusion inhibitor target located in the TM domain of GP2, which should be useful for drug and vaccine design.
Hybrid key management WSN protocol to enhance network performance using ML Techniques for IoT application in cloud Environment
Authors: M Raghini , Durairaj Selvam , S Sasikala , S Appavu alias Balamurugan 
Published: May 2024

Abstract

As the Internet of Things (IoT) develops, Wireless Sensor Networks (WSNs) must be used to collect and transmit critical data. Ensuring the security and efficiency of these networks is paramount, given the sheer volume and sensitivity of the data they handle. This paper introduces a novel hybrid key management protocol for WSNs in IoT applications, integrating cloud services and harnessing Machine Learning (ML) techniques to enhance network performance and security. The proposed hybrid key management protocol leverages the strengths of symmetric and asymmetric essential management methods, providing a robust foundation for securing communication within the WSN. It also capitalizes on cloud-based services’ scalability and centralized management capabilities to streamline key distribution and facilitate network-wide updates. Machine Learning techniques are seamlessly integrated into the protocol, enabling predictive key distribution, anomaly detection, dynamic key management, and intelligent network load balancing. By analyzing historical data and network patterns, ML algorithms predict optimal times and locations for critical updates, reducing overhead and enhancing security. Additionally, ML-based anomaly detection empowers the protocol to identify and respond to network irregularities and potential security breaches. This framework combines centralized key management, cloud integration, and the intelligence of Machine Learning, resulting in a highly adaptable and efficient protocol for IoT-enabled WSNs. The network performance is enhanced by using exiting techniques and algorithms.
Investigating Bubble-Induced Overpotential, Current Non-Uniformity, and Gas Cross-over in Flow-based Water Electrolyzers: A Numerical Study
Authors: Hadikhani Pooria 
Published: May 2024

Abstract

The transition towards a sustainable energy landscape necessitates efficient and scalable technologies for renewable energy storage. Water electrolysis, a process that converts electrical energy into chemical energy stored in hydrogen, holds immense potential for integration with intermittent renewable sources. However, the performance and efficiency of water electrolyzers are impeded by the complex multiphase flow dynamics involving bubble nucleation, growth, and transport within the electrochemical cell. This study employs state-of-the-art three-dimensional multiphase flow simulations to unravel the intricate interplay between bubbles and the electrochemical processes in a parallel-electrodes flow-based electrolyzer (PE-FBE). By accurately capturing bubble-electrolyte interfaces, the simulations quantify the detrimental effects of bubbles on overpotentials, current density distribution, and gas crossover. Crucially, the impact of critical parameters, including flow rate, bubble nucleation size, surfactant addition, and applied current, on these performance metrics is systematically investigated. The findings reveal strategies to mitigate bubble-induced losses, enhance current uniformity, and improve hydrogen purity, paving the way for optimized electrolyzer designs and efficient renewable energy storage.
RFNet-4D++: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds with Cross-Attention Spatio-Temporal Features
Authors: Vu Tuan-Anh , Nguyen Duc Thanh , Hua Binh-Son , Pham Quang-Hieu , Yeung Sai-Kit 
Published: May 2024

Abstract

Object reconstruction from 3D point clouds has been a long-standing research topic in computer vision and computer graphics, and achieved impressive progress. However, reconstruction from time-varying point clouds (a.k.a. 4D point clouds) remains overlooked. In this paper, we propose a new network architecture, namely RFNet-4D++, that jointly reconstructs 3D objects and their motion flows from 4D point clouds. The key insight is simultaneously performing both the tasks can leverage the individual ones, leading to improved overall performance. To achieve this ability, we design a compositional encoder to learn spatio-temporal representations of 4D point clouds based on dual cross-attention mechanism. In addition, we devise a joint-learning scheme for unsupervised learning of temporal vector fields and supervised learning of occupancy fields. This multi-task learning is achieved by jointly optimising loss functions and sharing spatio-temporal features.
Experiments and analyses on benchmark datasets validate the effectiveness and efficiency of our method. As shown in experimental results, our method achieves state-of-the-art performance on both flow estimation and object reconstruction while performing much faster than existing methods in both training and inference. Our code and data are available at \url{https://github.com/hkust-vgd/RFNet-4D}.
Epidemiology of tuberculosis in two northern Pakistani populations
Authors: Syed Sadia , Ain Qurat ul , Rehman Atta Ur 
Published: May 2024

Abstract

Background: Pakistan is the fifth most heavily afflicted country by tuberculosis (TB) in the world. This study aimed to investigate the epidemiological characteristics of TB in two northern Pakistani populations using retrospective data analysis.
Methods: We analyzed retrospective data ranging in duration from 2015 to 2022 obtained from tertiary care hospitals in theAbbottabad and Mansehra districts. GraphPad Prism software (version 8.0.1) was used for statistical analysis and data visualization.
Results: Data were obtained from a total of 16,140 TB patients who were enrolled in tertiary care hospitals in their respective populations. Among these patients, ~64% had pulmonary TB, and the remaining 36% had extrapulmonary TB. The difference in the TB incidence rate between male and female patients was not significant (50.3% vs. 49.7%, p>0.05). However, the TB incidence rate increased gradually with age, with the highest incidence rate observed in late adolescence and early adulthood. Overall, we noticed a greater proportion of clinically diagnosed patients than of those diagnosed through bacteriological or histopathological testing (64% vs. 36%, respectively,p<0.05). The proportion of patients who experienced relapse wassignificantly lower than that of patients who experienced new disease(6.8% vs. 93.2%, respectively; p<0.05), and more than 90% of the patients who were initially diagnosed in hospitals successfully completed treatment.
Conclusions: Our findings suggest that the incidence of pulmonary TB is greater than that of extrapulmonary TB, regardless of patient demographics.