bluuebunny/crossref_metadata_2025_split huggingface dataset:
Secure and Efficient Routing in Wireless Sensor Networks: LD2FA-PSO Intrusion Detection and Cluster HeadSelection
Authors: Dubey Ayushi 
Published: May 2024

Abstract

A wireless sensor network comprised of numerous sensors randomly distributed within a specific region, which aimed at detecting and collecting information within that region. Although they cannot be recharged or replaced, but sensor devices can detect, store, and transport data and energy, Data communication is another potential use of case for sensor devices. Since energy resources are limited in sensors, wireless sensor networks are constantly developing energy-efficient protocols to extend their ability to last long. Developing the routing protocol is extremely essential in order to maximize the longevity of the network by optimizing its energy efficiency. The key essential role play by Wireless sensor networks (WSNs) in the monitoring of the environment, which gains special focus on attaining energy efficiency and guaranteeing the secure transferring of data as key objectives in their design. Attacks that are network-based there has been gains increased focus, as the complexity of computer networks continues to grows. This, in turn, has prompted research activities that are focused at developing Intrusion Detection Systems that are more resistant to vulnerabilities. This research aims to develop an automated intrusion detection system (IDS) that enhances energy efficiency in wireless sensor networks (WSNs) using LD2FA and Particle Swarm Optimization. The Learning Dynamic Deterministic Finite Automata (LD2FA) that has been presented which is capable of dynamically adapting to the nature of the network. It offers insights into the examination of nodes, packets, and routes in order to efficiently discover and eliminate intrusions. Data transmission that is more energy-efficient as a consequence is accomplished via the use of improved routing. The essential goal of the LD2FA-PSO approach is to optimize routing patterns in order to ensure that transfer of data is as energy-efficient as possible. DFA strengthen the intrusion detection system's which has the ability to recognize and to eliminate variety of network security threats, which includes denial of service attacks, worms, viruses, and malware, while PSO refines the routing process and picks the most effective data transfer channels.
Analysis of cuproptosis-related genes signature in prognosis and immune landscape in Head and neck squamous cell carcinoma
Authors: Ai Maomao , Guo Ruoyu , Lin Ying , Wu Jian , Liu Zeyang , Yu Feng 
Published: May 2024

Abstract

Background: Cuproptosis is a copper-dependent cell death mechanism that is associated with tumor progression, prognosis, and immune response. The potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment in Head and neck squamous cell carcinoma (HNSC) is unclear，and a gene marker is needed to predict clinical outcomes of HNSC.
Patients and methods: In total, 546 HNSC samples were collected from The Cancer Genome Atlas database(TCGA) and 98 samples from Gene Expression Omnibus datasets(GEO).The CRGs were identified in the literature, while the member genes of Signaling by Receptor Tyrosine Kinases(RTKs) pathway were identified by Metascape, Gene-related prognostic models were established and validated in a training set and GEO verification set. Samples were classified using R software packages. A nomogram and calibration curve were constructed to predict patient survival probability to improve the clinical applicability of the genes. Through unsupervised clustering analysis, identified three distinct Cuproptosis Clusters, we further explored the differences of immune cell infiltration, and immunotherapy among the three Clusters.
Results: 4487 differentially expressed genes were identified between 44 adjacent non-tumorous tissues and 502 tumor tissues samples. 11 gene(FLT3, MAP2K2, CDKN2A,PTPRU,IRS2, FGF9,FGFR2,IL6, JUND, FDX1, SHC3)signature was identified.The gene signature used to establish a Prognostic Risk Score,then to construct cases into high- and low-risk groups in terms of overall survival. The 5-year survival AUC in the training and verification sets were 0.693 and 0.642. The corresponding multifactor COX regression analysis found that low-risk group, pathologic N2c, lymphovascular-invasion(NO) and age had clinical independence. The low-risk group has higher ESTIMATEScore and ImmuneScore (P<0.05).
Conclusion: This study revealed the potential effects of CRGs and RTKs gene signature on the TME, clinicopathological features, and prognosis of HNSC，and may offer novel insights into the cancer treatment.
Practical Object and Flow Structure Segmentation using Artificial Intelligence
Authors: KHOJASTEH Ali Rahimi , de Water Willem van , Westerweel Jerry 
Published: May 2024

Abstract

This paper explores integrating artificial intelligence (AI) segmentation models, particularly the Segment Anything Model (SAM), into fluid mechanics experiments. SAM's architecture, comprising an image encoder, prompt encoder, and mask decoder, is investigated for its application in detecting and segmenting objects and flow structures. Additionally, we explore the integration of natural language prompts, such as BERT, to enhance SAM's performance in segmenting specific objects. Through case studies, we found that SAM is robust in object detection in fluid experiments. However, segmentations related to flow properties, such as scalar turbulence and bubbly flows, require fine-tuning. To facilitate the application, we have established a repository (\href{https://github.com/AliRKhojasteh/Flow_segmentation}{github.com/AliRKhojasteh/Flow\_segmentation}) where models and usage examples can be accessed.
The Multi-attribute Impact of Hyperlinks in Blogs: An Emotion-Centric Approach
Authors: Mbila-Uma Stella , Koleoso Oyindamola , Umoga Ifeanyichukwu , Alassad Mustafa , Agarwal Nitin 
Published: May 2024

Abstract

As a digital social medium, blogs have transformed into arenas where individuals can express their perspectives, concepts, and feelings. This research delves into the spread of information in blog posts related to the Uyghur discourse, utilizing topic modeling to classify and prioritize pertinent content. The analysis reveals a significant emphasis on the Chinese Government’s suppression of Uyghur Muslims, as demonstrated by the hyperlinks embedded within the blog network. We mapped the discovered topics onto a network of hyperlinks, forming a topic-induced hyperlink network. Additionally, we conducted a toxicity analysis, which revealed a high level of toxicity in blog posts during that period. A morality assessment was also performed, revealing exceedingly high scores for all vices in the blog posts. Furthermore, we conducted an emotion analysis on the text and image data, which underscored a dominant sentiment of sadness pervading the blog posts and corresponding images. This reflects the severity of the Uyghur persecution. The research highlights the effectiveness of topic modeling, toxicity evaluation, and hyperlink analysis in shedding light on intricate social issues. Future studies could augment these results by expanding keyword scope and refining image recognition models within the context of Uyghur discourse.
Neuroinflammatory Responses and Blood–Brain Barrier Injury in Chronic Alcohol Exposure: Role of Purinergic P2X7 Receptor Signaling
Authors: Togre Namdev S. , Melaka Naveen , Bhoj Priyanka S. , Mogadala Nikhita , Winfield Malika , Trivedi Jayshil , Grove Deborah , Kotnala Sudhir , Rom Slava S , Sri Uma , Persidsky Yuri 
Published: May 2024

Abstract

Alcohol consumption leads to neuroinflammation and blood‒brain barrier (BBB) damage, resulting in neurological impairment. We previously demonstrated that ethanol-induced disruption of barrier function in human brain endothelial cells was associated with mitochondrial injury, increased ATP and extracellular vesicle (EV) release, and purinergic receptor P2X7R activation. Therefore, we aimed to evaluate the effect of P2X7r blockade on peripheral and neuro-inflammation in EtOH-exposed mice. In a chronic intermittent ethanol (CIE)-exposed mouse model, P2X7R was inhibited by two different methods: Brilliant Blue G (BBG) or gene knockout. We assessed blood ethanol concentration (BEC), plasma P2X7R and P-gp, number of extra-cellular vesicles (EV), serum ATP and EV-ATP levels. Brain microvessel gene expression and EV mtDNA copy numbers were measured by RT2 PCR array and digital PCR, respectively. A RT2 PCR array of brain microvessels revealed significant upregulation of proinflammatory genes involved in apoptosis, vasodilation, and platelet activation in CIE-exposed animals, which were decreased 15–50-fold in BBG-treated CIE-exposed animals. Plasma P-gp levels and serum P2X7R shedding were significantly increased in CIE-exposed animals. Pharmacological or genetic suppression of P2X7R decreased P2X7R shedding to levels equivalent to those in control group. The increase in EV number and EV-ATP content in the CIE-exposed mice was significantly reduced by P2X7R inhibition. CIE mice showed augmented EV-mtDNA copy numbers which were reduced in EVs after P2X7R inhibition or receptor knockout. These observations suggested that P2X7R signaling plays a critical role in ethanol-induced brain injury. Increased eATP, EV-ATP, EV numbers, and EV-mtDNA copy numbers highlight a new mechanism of brain injury during alcohol exposure via P2X7R and biomarkers of such damage. In this study, for the first time, we report the in vivo involvement of P2X7R signaling in CIE-induced brain injury.
Modeling ML Efficiency in Telecommunications
Authors: Corona Julio , Teixeira Rafael , Antunes Mário , Aguiar Rui L. 
Published: May 2024

Abstract

Machine learning (ML) models are envisioned to play a fundamental role in Beyond 5G networks. However, training these models presents significant challenges due to the vast amounts of data involved and the complexity of the algorithms, requiring substantial training time and computing resources. This study offers a comprehensive analysis of how dataset characteristics, model complexity, and the number of iterations influence model performance and training time. Furthermore, we take pioneering steps towards modeling the performance and training time of ML models, specifically within the telecommunications sector. Our findings can pave the way for informed decision-making processes in telecommunications, enabling a comprehensive understanding of expected performance and training time requirements. Leading to reduced development times and optimized energy consumption and resource allocation.
Low-intensity endurance exercise increases physical functioning among breast cancer survivors: a randomized controlled trial
Authors: Mulero-Portela Ana L. , Colón-Santaella Carmen L. , Rogers Lara Q. , Missaghian Mariam 
Published: May 2024

Abstract

Purpose: This study assessed the effect of low- versus moderate-intensity endurance exercise on the physical functioning of women who are breast cancer survivors.
Methods: Women who had completed treatment for breast cancer at stages 0 to III, aged 50 years and above, were randomly assigned to a low-intensity or moderate-intensity exercise group. Both groups participated in seven intervention sessions distributed over 26 weeks. Women were instructed to walk for 30 minutes five days a week. Flexibility, strengthening, and balance exercises were included for both groups. The Theory of Planned Behavior guided the interventions. Outcomes were assessed at baseline, post-intervention, and 12 months after baseline. The primary outcomes were PROMIS Physical Functioning, PROMIS Global Health, and the six-minute walk test.
Results: Sixty-five of 101 women randomized (64.4%) completed the study. No statistically significant between-group differences were found at post-intervention or 12 months. In both exercise groups, statistically significant improvements were demonstrated for the PROMIS Physical Functioning at post-intervention (p = 0.01 for low intensity; p=.002 for moderate intensity), and the PROMIS Global Health physical health subscale (p = 0.001 for low intensity; p=.005 for moderate intensity). No statistically significant within-group changes were observed in the PROMIS Global Health mental subscale or the six-minute walk test.
Conclusion: A seven-intervention session program at both low and moderate-intensity walking significantly improved physical functioning in breast cancer survivors.
Implications for cancer survivors: Women who are breast cancer survivors aged 50 years and above who would like to increase their physical functioning, have the option of exercising at both low and moderate intensity.
Trial registration number: ClinicalTrials.gov identifier: NCT02982564
Date of registration: December 5, 2016
Evaluation of Water Quality Assessment Through Machine Learning: A Water Quality Index-Based Approach
Authors: Islam Md. Jahidul , Salekin Siraj Us , Abdullah Md Shahriar , Zaman Nafis , Khan Abdullah Al Ahad 
Published: May 2024

Abstract

Water is an essential element for the survival of all forms of life. The lack of access to clean and safe water can cause various waterborne diseases. Water quality monitoring is vital for ensuring access to clean and safe water. The Water Quality Index (WQI) is a widely used tool to assess water quality, but traditional Water Quality Index (WQI) methods, despite their utility, often suffer from inconsistencies and limitations. Moreover, these methods are not immune to laboratory and human errors. This study aimed to addresses these challenges by integrating advanced machine learning (ML) techniques to refine WQI predictions. Using a dataset comprising physicochemical parameters, such as pH, Cl-, SO42-, Na+, K+, Ca + 2, Mg + 2, Total Hardness & Total Dissolved Solids from diverse water sources, authors implemented several ML algorithms—including Gradient Boosting, Random Forest, and XGBoost—enhanced with explainable AI (XAI). To develop the prediction models, the dataset was divided into three groups: training (70%), testing (15%) and validating (15%). In order to evaluate the models’ performance, the RMSE, MSE, MAE, and R2 metrics were used in this study. The results of model performance indicated that the Gradient Boosting model has superior predictive capabilities after fine-tuning with 96% accuracy on the test dataset. This study suggests a shift towards leveraging ML for more reliable water quality evaluations, promoting enhanced decision-making in environmental health policies.
A cash transfer plus gender transformative economic empowerment intervention seeking to improve the wellbeing of caregivers of children and adolescents living with HIV in South Africa: a feasibility study protocol for a pilot cluster randomised trial
Authors: Govindasamy Darshini , Shai Nwabisa , Mwandacha Nelly , Carries Stanley , Sithole Nokwanda , Closson Kalysha , Bhana Arvin , Sigwadhi Lovemore , Washington Laura , Gibbs Andrew , Kaida Angela 
Published: May 2024

Abstract

Background In sub-Saharan Africa, HIV care is dependent on informal caregiving, typically by female family members. Informal caregiving has been associated with numerous negative effects on caregivers (i.e. depression, intimate partner violence (IPV), financial insecurity). These factors impact both caregivers’ ability to provide care and their own wellbeing. South Africa is home to approximately 17% of the world’s children and adolescents living with HIV (CALHIV), making the development of initiatives that mitigates the negative effects of caregiving critical. This protocol details the design of a cluster randomised trial seeking to assess the feasibility, preliminary effectiveness, cost-effectiveness, and acceptability of a cash transfer plus gender transformative economic empowerment intervention for improving psychological wellbeing, depressive symptoms, gender equality, and economic outcomes of caregivers of CALHIV.Methods Caregivers of CALHIV will be recruited from public sector HIV clinics within the eThekwini municipality, KwaZulu-Natal, South Africa. Clusters will be randomly assigned to the intervention or control groups. Participants in the intervention arm (n = 120) will receive cash transfers (ZAR350, USD $18,79) and enrol in a programme (10 workshop sessions) over a 6-month period. Participants in the control arm (n = 120) will receive a monthly cash transfer (ZAR350, USD $18,79) for a 6-month period and a once-off standard mobile message at the beginning of the trial, encouraging linkage to healthcare services. Participants will be interviewed at baseline and endline, at the 7-month mark, to collect socio-demographic, health and wellbeing status, IPV, costs and earnings, and food security data. The primary outcomes (psychological wellbeing, depressive symptoms, IPV) will be measured using the Mental Health Continuum Short Form, the CES-D-10 scale, and the WHO’s Violence Against Women scale. A qualitative study and economic evaluation will be conducted alongside the main trial to probe participants perceptions on the intervention and assess economic cost and costs-effectiveness.Discussion This trial has the potential to inform a larger confirmatory trial which will be valuable for informing post-pandemic recovery efforts for caregivers of CALHIV and others disproportionally burdened by compounding health and social crises.Trial registration PACTR202311618532061. Registry name: Pan African Clinical Trial Registry (PACTR); URL: https://pactr.samrc.ac.za/; Registration date: 21-November-2023 (retrospectively registered); Date first participant enrolled: 24-August-2023
A New Measure of the Parental Phubbing-Mother and Father Form for Turkish Adolescents: Evaluation of Validity and Reliability
Authors: Akbağ Müge , Aydoğdu Fuat , Rizzo Amelia 
Published: May 2024

Abstract

Phubbing, which has captured researchers' attention in recent years and is being studied daily, is defined as snubbing someone in favor of a smartphone in a social setting. This behavior, when observed in parent–child interactions, is termed parental phubbing. To conduct robust empirical studies that examine parental phubbing in depth, it is important to create a new and specific parental phubbing scale. The present study aimed to develop a reliable tool for assessing perceived parental phubbing and evaluating its psychometric properties. Initially, a draft scale with 13 items was created from a literature review and essays by 70 middle school adolescents. After providing parental consent, the scale's construct validity was tested using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) on two groups of 10- to 15-year-old adolescents (NEFA=325, NCFA=210). The EFA identified a 10-item structure with two factors—"interaction interruptions" and "emotional reactions", which accounted for 58.81% and 65.02%, respectively—of the total variance in the mother (PPS-M) and father (PPS-F) forms. The CFA confirmed this structure, with both forms showing a good fit. Criterion validity was examined through correlations with the Smartphone Addiction Scale and the UCLA Loneliness Scale-Short Form, revealing significant relationships. Reliability was established through Cronbach's alpha and McDonald's omega coefficients, which exceeded .70 for both total and subdimensions. Additionally, test-retest reliability coefficients ranged between 0.70 and 0.82 for the PPS-M and between 0.70 and 0.81 for the PPS-F, reinforcing the scale's consistency. In conclusion, the PPS-M and PPS-F are valid and reliable tools for assessing adolescents' perceptions of their parents' phubbing behaviors.
Are Binary Codes assigned to Bases in Codons A Matter of Choice Or specific ?
Authors: Mohanty Bijan Bihari 
Published: May 2024

Abstract

Since discovery by Russian Physicist Rumer of three types of traits (purine/pyrimidine, Strong/Weak, amino/keto ) in each of the bases A,G,C,U/T constituting the codons and anti-codons ,theoretical biologists have hit upon a close analogy between binary representation of information and the traits of the bases. As a result , binary values have been assigned to the four bases and efforts are made to unearth the underlying symmetry and information content. There are altogether 24 choices available and these choices have been exercised by researchers based upon individual assumptions or in a random manner. Till date, the following vital issue remains unresolved:--
Whether all binary choices or cluster of choices are equally suitable depending on assumptions. OR there is no choice and nature has chosen a specific set of binary configuration.
The current research article, by logical and mathematical deduction, has arrived at the conclusion that there is no choice and only 2 configurations out of 24 choices are picked up by nature for representation of base in codons/anti-codons and the rest 22 choices are not suitable.
Designing the Vaccine against the Omicron Variants of COVID-19 Virus as a Target by using Immunoinformatics Approach
Authors: Nag Aditi , Varun Pratika 
Published: May 2024

Abstract

COVID-19 vaccines have been a key determinant in humanity’s fight against the pandemic. It has been observed that vaccinated individuals have shown decline in instances of symptoms occurring and even in the overall severity of symptoms in the individuals where they do appear. However, due to this upgraded defence in hosts several variants have emerged. The most recent VOCs of SARS-CoV-2 in these newly emerged variants is the omicron variant. Reports shows that the surface glycoprotein of omicron, has changed with as many as around 52 mutations than its preceding variant Delta. Thus, despite the availability of COVID-19 vaccines against ancestral strains, their effectiveness is predicted to decreases with each variant, necessitating more potent vaccines against emerging variants. Therefore, the aim was to identify a vaccine candidate against the Omicron (BA.2 and XBB.1.5) by targeting stable structural proteins using immunoinformatic. Tools like, the IEDB, and VaxiJen v2.0, have been used for the identification of the T-cell and B-cell epitopes. The interaction of receptors and the validated 3D model of vaccine candidate were predicted. Promising antigenic peptides, from the structural proteins of Omicron (BA.2) were predicted to MHC class I (HLA)-A*11-01allele, exhibiting high antigenicity. The study has identified promising vaccine candidates using immunoinformatic against Omicron variants of SARS-CoV-2.