bluuebunny/crossref_metadata_2025_split huggingface dataset:
Secure and efficient authentication framework for IoT-based smart home using dynamic key
Authors: Bettahar Maroua Hadjer , Louazani Ahmed , Sekhri Larbi 
Published: July 2024

Abstract

The great development in different technologies as Internet of Things (IoT) has changed the lifestyle of inhabitants. Therefore, the greater need for new technologies is also increased and new smart applications have emerged. The smart home (SH) is one of the most important and popular smart application giving the possibility to his users to control smart home devices. Unfortunately, this control is performed under insecure channel opening the door to many attacks. In this paper, we propose a new secure authentication and session-key agreement in a smart home environment. The proposed scheme combines a lightweight to mitigate the smart devices requirements and security to ensure reliable communication. To avoid the synchronization problem, our method uses local timestamp and increment number. The proposed scheme resists to several types of attacks and it is validated using Burrows-Abadi-Needham (BAN) logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool.
A robust federated biased learning algorithm for time series forecasting
Authors: Song Mingli , Zhao Xinyu , Pedrycz Witold 
Published: July 2024

Abstract

The federated averaging algorithm (FedAvg) is extensively used for multi-sensor data modeling but often overlooks the unique characteristics of local models when privacy and data security are not considered. This study introduces a novel federated learning algorithm built upon the FedAvg framework, which emphasizes the specificity of each local model to optimize global knowledge aggregation. The algorithm's effectiveness is demonstrated through an air quality index prediction problem, showcasing superior prediction performance and robustness in noisy data scenarios. Additionally, the study delves into the reliability and robustness of the proposed approach, addressing the prevalent notion that centralized learning methods often surpass federated learning when data security is not a concern. Our experiments affirm the necessity and superiority of federated learning methods, even in the absence of privacy considerations, by effectively managing real-world noisy data.
C4D-YOLOv8: Improved YOLOv8 for Object Detection on Drone-captured Images
Authors: Zeng Weihui , Wu Pengcheng , Wang Junyan , Hu Gensheng , Zhao Jinling 
Published: July 2024

Abstract

Unmanned aerial vehicles (UAVs), as an emerging technology with vast application prospects, produce distinctive images due to factors, such as their shooting environment, altitude, and equipment. These UAV-captured images possess unique characteristics compared with traditional pictures, including high resolution, abundant presence of small objects, and object density. However, most existing object detection networks primarily focus on detecting large objects, resulting in limitations in terms of detecting small targets. The current detection networks frequently lose significant information whilst extracting features of small targets, resulting in a substantial decrease in detection accuracy. Accordingly, we have employed an improved version of YOLOv8 to address these issues, taking into consideration the aforementioned challenges,. We have devised a novel feature extraction module called C4, which aims to regain the crucial feature information of small targets that may have been overshadowed by the background. In contrast to the previous C2F or C3 modules, the C4 module incorporates a pathway with a larger convolutional kernel. Additionally, we have introduced a small target detection layer and an attention mechanism-based target detection head called ‘DyHead’ into the original yolov8s architecture. This approach has yielded a remarkable improvement in performance, achieving a mean average precision value of 45.8% on the VisDrone dataset, which represents a 4.9% accuracy enhancement compared with YOLOv8s (baseline).
Subject classification codes: include these here if the journal requires them
The proviral factor NUP153 binds viral proteins and RNA to modulate protein translation at viral amplification site early in flavivirus infection
Authors: Överby Anna , Peters Marie , Lindqvist Richard , Kassa Eszter , Yau Wai-Lok , Sengupta Pallabi , Sabouri Nasim , Ivarsson Ylva , Lundmark Richard 
Published: July 2024

Abstract

Flaviviruses are RNA viruses that cause serious diseases in humans, with currently no antivirals available. Targeting host factors is emerging as an attractive antiviral approach, but first we need to understand basics of which host proteins are hijacked and why. Here, using a combination of fluorescence microscopy, knock-down, crosslinking immunoprecipitation sequencing, mass spectrometry, and biophysical assays, we identify nucleoporin-153 (NUP153) as a proviral factor during flavivirus infection. We show that NUP153 is recruited to the virus amplification site on the endoplasmic reticulum and needed early on during infection. We find that NUP153 interacts with the viral proteins NS3 and NS5, and a highly conserved G-rich motif on the viral RNA. The interactions promote the production of viral structural proteins, leading to an efficient virion assembly, virus release and spread to new cells. Importantly, we identifyNUP153 as a key regulator in viral polyprotein translation, a mechanism that appears conserved among flaviviruses.
Genetic Factor Analysis for Characterizing Phenome-Wide Patterns
of Genetic Pleiotropy
Authors: Morrison Jean , Willwerscheid Jason , Sylvertooth Dhajanae , He Xin , Stephens Matthew 
Published: July 2024

Abstract

Genetic associations shared by multiple traits provide evidence about the biological role of disease associated variants. We propose Genetic Factor Analysis (GFA), a multi-phenotype analysis method that identifies common patterns of cross-trait associations, the signatures of shared biological processes. GFA overcomes many limitations of alternative methods by automatically selecting the number of factors, accounting for sample overlap, and allowing factors to be non-orthogonal. We apply GFA to analysis of 22 common risk factors for coronary artery disease (CAD), and type 2 diabetes (T2D), allowing us to partition the heritability of CAD, T2D, and risk factors into 13 pleiotropic components. This analysis reveals, among other findings, that about 8% of the heritability of BMI is mediated by factors that do not contribute do CAD or T2D risk. In a second application, we use GFA to obtain a biologically meaningful decomposition of a large set of blood cell composition phenotypes and show that accounting for overlapping samples is critical to obtaining this result.
Evaluating Cancer Patients’ Experiences with Doctor-Patient Communication: Development and Validation of a New Assessment Instrument
Authors: Yang Hsin-Yi , Lin Yung-Chang , Shen Wen-Chi , Chen Shin-Cheh , Wang Chao-Hui , Chen Mei-Ling 
Published: July 2024

Abstract

Introduction:
Effective communication between doctors and patients is crucial for the well-being of individuals diagnosed with cancer. This study aimed to develop and validate a cancer-specific Doctor-Patient Communication Satisfaction Scale (DPCSS-Cancer) from the patients' perspective.
Methods
Initial items were generated through literature review. Content validity was assessed via feedback from five experts, while face validity was determined through cognitive interviews with 13 patients. The revised DPCSS-Cancer was subsequently tested in a sample of 200 cancer patients to assess test-retest stability, internal consistency, factor structure, and criterion-related validity.
Results
The development process resulted in a 15-item DPCSS-Cancer across two dimensions, using a 4-point rating scale (1 = strongly disagree to 4 = strongly agree). The item-level Content Validity Index (I-CVI) ranged from 0.8 to 1.0, with a scale-level CVI of 0.96. Following expert and patient feedback, no items were eliminated, but modifications were made to item wording. In formal testing, the overall Cronbach’s alpha was 0.96, with 0.89 for the first dimension and 0.95 for the second. Test-retest reliability was established at 0.82. The two-dimensional structure was partially confirmed. Criterion-related validity was supported through a significant positive correlation with a measure of trust in the physician (r = 0.86). Factors contributing to higher DPCSS-Cancer scores were identified.
Conclusion
The DPCSS-Cancer shows satisfactory reliability and validity, making it a viable patient-reported outcome measure for assessing cancer patients' satisfaction with doctor-patient communication.
Study Protocol of a Prospective Phase 2 Study of Chlorophyllin for the Management of Brain Radionecrosis in Patients with Diffuse Glioma (CHROME)
Authors: Dasgupta Archya , Sawant Saranga , Chatterjee Abhishek , Gota Vikram , Sahu Arpita , Choudhari Amitkumar , Bhattacharya Kajari , Puranik Ameya , Dev Indraja , Moiyadi Aliasgar , Shetty Prakash , Singh Vikas , Menon Nandini , Epari Sridhar , Sahay Ayushi , Shah Aekta , Bano Nazia , Shaikh Farnaz , Jirage Aabha , Gupta Tejpal 
Published: July 2024

Abstract

Introduction:
Chlorophyllin (CHL) effectively decreases the side effects of radiotherapy (RT) by scavenging radiation-induced free radicals and reactive oxygen species in preclinical trials. This study aims to assess the efficacy of oral CHL for the treatment of brain radionecrosis in patients with diffuse glioma.
Methods
This is a phase 2 trial prospective, interventional study. Adults (> 18 years) with a histological diagnosis of diffuse glioma developing radionecrosis will be eligible for the study. Radionecrosis will be identified using standard imaging protocols with magnetic resonance imaging (MRI) with or without positron emission tomography (PET). Patients will be accrued in two strata: symptomatic (stratum A) and asymptomatic (stratum B). Chlorophyllin will be prescribed to all patients using a morning oral dose of 750 mg before breakfast for 3 months. In addition, participants in stratum A will be given a tapering dose of dexamethasone for 1 month, while stratum B won’t be receiving any steroids. Imaging with an MRI brain protocol and PET scan will be planned at 1 month and MRI at 3 months after starting CHL. The primary endpoint is the clinical-radiological response at 1 month. Secondary endpoints include response at 3 months, biological responses, survival analysis, and quality-of-life scores. The total sample size is 118 (60 and 58 in stratum A and B, respectively), with one interim analysis planned.
Discussion
Radionecrosis leads to significant morbidity and is usually treated with corticosteroids, which can lead to several side effects on both acute and long-term use. Refractory radionecrosis requires treatment with bevacizumab or surgical resection. Chlorophyllin is a cheap, safe, and readily available phytopharmaceutical drug, which is being investigated in the phase 2 study and, if proven effective, can be considered an alternative for treating radionecrosis.
Trial Registration:
The trial is registered on the Clinical Trial Registry India (CTRI): CTRI/2023/08/056166 and ClinicalTrials.gov: NCT06016452.
Mecanismos de governança e valor de mercado das concessionárias De rodovias listadas na B3 (BM&FBOVESPA)
Authors: Carlos Santos Ruan , Raupp Fabiano Maury , Orso Lidinei Éder 
Published: July 2024

Objetivo do estudo: Esse estudo visa, integrar a teoria da agência, os mecanismos de governança corporativa e as características do Programa de Exploração de Rodovias (PER) administrado pela ANTT (Agencia Nacional de Transporte Terrestre), partir da análise das características dos mecanismos de governança das 33 concessionárias de rodovias listadas na B3 (BMF&Bovespa) no período de 2010 a 2022, e a influência no seu valor de mercado.
Metodologia/abordagem: Em termos metodológicos, a pesquisa teve caráter documental, utilizando como base de pesquisa os relatórios da B3 (BMF&Bovespa), CVM que operam tanto na Bolsa de Valores do Brasil quanto nos Estados Unidos. A pesquisa utilizou o modelo de regressão de dados em painel, com efeitos fixos e aleatórios.
Originalidade/Relevância: Ao relacionar as características dos mecanismos de governança e o valor de mercado das concessionárias brasileiras, os resultados foram significantes para as variáveis: a presença de investidores estrangeiros, o que confirma a teoria de que a presença de estrangeiro como acionista influencia positivamente o valor de mercado das empresas reguladas; os membros independentes do conselho de administração, possui efeito positivo na gestão e maximização de valor para os acionistas e, a fiscalização efetuada pela agência reguladora como processos do sistema regulatório que afeta positivamente o controle e o desenvolvimento de novos regulamentos, destinados a reduzir benefícios do acionista controlador e conflitos na gestão.
Principais resultados: A Governança Corporativa vem ganhando destaque e se desenvolvendo nos últimos anos no meio empresarial, especialmente a partir do ano de 2002, após os escândalos de fraudes envolvendo grandes empresas norte-americanas, quando o assunto passou a ser mais valorizado e de maior exigência dentro das organizações. Foram operacionalizados indicadores que trazem um capital de investidores estrangeiros atrás de processo de concessão de rodovias, as empresas já estão cumprindo política internacionais e as implicadas legais exigidas pela B3, CVM, ANTT pelos órgãos nacionais.
Review of the occurrence, treatment technologies, and detection methods for saxitoxins in freshwaters
Authors: Gawankar Shardula , Masten Susan J. , Lahr Rebecca H. 
Published: July 2024

ABSTRACT

The increasing occurrence of saxitoxins in freshwaters is becoming a concern for water treatment facilities owing to its structural properties which make it resistant to oxidation at pH &lt; 8. Hence, it is crucial to be able to monitor these toxins in surface and drinking water to protect public health. This review aims to outline the current state of knowledge related to the occurrence of saxitoxins in freshwaters and its removal strategies and provide a critical assessment of the detection methods to provide a basis for further development. Temperature and nutrient content are some of the factors that influence the production of saxitoxins in surface waters. A high dose of sodium hypochlorite with sufficient contact time or activated carbon has been shown to efficiently remove extracellular saxitoxins to meet the drinking water guidelines. While HILIC-MS has proven to be a powerful technology for more sensitive and reliable detection of saxitoxin and variants after solid phase extraction, ELISA is cost-effective and easy to use and is used by Ohio EPA for surveillance with a limit of detection of 0.015 μg/L. However, there is a need for the development of cost-effective and sensitive techniques that can quantify the variants of saxitoxin.
DNA Binding Protein Prediction based on Multi-feature Deep Metatransfer Learning
Authors: Wang Chunliang , kong Fanfan , Wang Yu , Wu Hongjie , Yan Jun 
Published: July 2024

Background:
In recent years, the rapid development of deep learning technology has had
a significant impact on the prediction of DNA-binding proteins. Deep neural networks can automatically
learn complex features in protein and DNA sequences, improving prediction accuracy and
generalization capabilities.

Objective:
This article mainly establishes a meta-migration model and combines it with a deep learning
model to predict DNA-binding proteins.

Methods:
This study introduces a meta-learning algorithm based on transfer learning, which helps
achieve rapid learning and adaptation to new tasks. In addition, normalized Moreau-Broto autocorrelation
attributes (NMBAC), position-specific scoring matrix-discrete cosine transform (PSSMDCT),
and position-specific scoring matrix-discrete wavelet transform (PSSM-DWT) are also used
for feature extraction. Finally, the prediction of DBP is achieved through the deep neural network
model based on the attention mechanism.

Results:
This paper first establishes the basis of deep meta-transfer learning and uses the PDB186
data set as the benchmark to extract features using NMBAC, PSSM-DCT, and PSSM-DWT, respectively,
and compare the fused features in pairs, and finally obtain the fused feature process. Through
deep learning processing, it is concluded that the fused feature prediction effect is the best. At the
same time, compared with the currently popular models, there are obvious improvements in the
ACC, MCC, SN and Spec evaluation indicators.

Conclusion:
Finally, it was concluded that the method used in this article can effectively predict
DNA-binding proteins and show more significant performance.
Factors Influencing Adolescent Resilience and Human Immunodeficiency Virus-acquired Immune Deficiency Syndrome Prevention Behavior: A Cross-sectional Study of Adolescents in DKI Jakarta Province, Indonesia
Authors: Ratnawati Diah , Setiawan Agus , Widyatuti   , Hastono Sutanto Priyo , Susanto Tantut , Asih Sali Rahadi , Siregar Tatiana , Pramono Rahmat Aji 
Published: July 2024

Background
The incidence of human immunodeficiency virus (HIV)-acquired immune deficiency syndrome (AIDS) remains high in Indonesia. Therefore, HIV-AIDS prevention and control programs have been established for adolescents aged 15–24 years based on the United Nations Sustainable Development Goals. Internal risk factors related to risky sexual behavior and external risk factors associated with exposure to pornography through the media are major hurdles that need to be overcome in efforts to prevent HIV-AIDS among adolescents. Meanwhile, individual protective factors through self-control and adolescent resilience strongly impact the enhancement of HIV-AIDS prevention behavior. This study aimed to determine whether internal and external risk factors and individual and sociocultural protective factors exert influences on adolescent resilience and HIV-AIDS prevention behavior among adolescents.

Methods
This research employed a descriptive quantitative design with a cross-sectional approach. The population consisted of high school students aged 15–19 years in Jakarta, and a sample of 619 students was taken through proportional stratified random sampling. Inferential analysis was conducted using partial least squares structural equation modeling.

Results
The data analysis revealed that adolescent resilience (β-value = 0.423; t = 12.129), internal risk factors (β-value = 0.292; t = 10.903), and external risk factors (β-value = -0.088; t = 6.127) most significantly influenced HIV-AIDS prevention behavior, with significant negative impacts. The sub-variable that most strongly determined the presence of HIV-AIDS prevention behavior (Y2) was self-control (λ = 0.983), and the one that did so most weakly was negative cognition (λ = 0.875).

Conclusion
Adolescent resilience is a crucial factor in enhancing HIV-AIDS prevention behavior among adolescents as it influences adolescents’ beliefs, boosts their self-confidence, fosters emotional insight, and develops social skills and empathy toward others. Thus, enhancing it through HIV-AIDS prevention programs is essential.
Investigation of the Effects of Different Phases of TiO2 Nanoparticles on PVA Membranes
Authors: Mehto Akanksha , Chauhan Jyotsna , Mehto Varsha R. 
Published: July 2024

Introduction:
PVA/TiO2 nanocomposite membranes are prepared by solution
casting technique where different phases of TiO2 nanoparticles like brookite, brookiterutile
and rutile are dispersed in PVA matrix. Sol-gel method was employed to prepare
TiO2 nanoparticles, while different phases of TiO2 have been obtained by controlling the
calcination temperature.

Methods:
PVA/TiO2 nanocomposite membranes were characterized by XRD, FTIR,
AFM, TEM, UV-visible and PL techniques. XRD results confirmed the presence of different
phases of TiO2, exhibiting 3.3 nm, 8.4 nm, and 35.7 nm mean crystalline size. The
XRD studies also confirmed that TiO2 nanoparticles became properly dispersed to the
PVA matrix, leading to increased PVA crystallinity after doping of different phases of
TiO2 nanoparticles. UV-visible analysis revealed an increase in absorption intensity and
peak position shifts slightly towards longer wavelengths, which indicates that nanofillers
tuned the band gap of PVA. The doping of the TiO2 (brookite) phase in the PVA matrix
results in a decreased in PL intensity.

Results:
This suggests that the PVA/TiO2 (brookite) membrane exhibits a greater degree
of photocatalytic activity in comparison to the other two composites. According to the
FTIR investigation, the hydroxyl (OH) groups present in PVA interact with the dopants
Ti+ ions via intra- and intermolecular hydrogen bonds to produce charge transfer complexes
(CTC). The AFM study shows surface roughness details for PVA and PVA/TiO2
composite membranes. The average grain size of TiO2 nanoparticles calculated from
TEM images is in good agreement with the grain size calculated by XRD.

Conclusion:
By adjusting the phase of TiO2 nanoparticles into PVA matrix, composites
can be developed that are optimized for a variety of applications such as water purification,
UV protection, self-cleaning surfaces, lithium-ion batteries, and optoelectronic devices.
Multi-factor Authentication Framework for Secured Data Access in Cloud Computing
Authors: Rajakumar P. , Partheeban N. 
Published: July 2024

Aims and Background:
Accessing data services on the cloud raises serious concerns
about security and privacy. To verify a client's stated identity, the existing authentication approach
uses just one authentication factor. However, traditional techniques of one-factor authentication
are inefficient since they demand an excessive amount of user information and expose their private
data to eavesdropping.

Methods:
Cloud-based data storage is susceptible to both external and internal threats. Information
security relies heavily on authentication, which is a method for verifying user identities
before granting them access to protected data. When it comes to protecting data in a cloud computing
environment from the most cutting-edge methods of attack, traditional password authentication
simply isn't enough. For the purpose of protecting user identities in the cloud, this study presents
interactive multi-layer authentication systems. Various access control policies are used when
validating users in the cloud. Registration, permissions, and authentication factors for users are all
parts of the cloud app's security process.

Results:
An intrusion detection system is built into the security mechanism to help identify people
who could be malevolent. Various techniques are available for user identity verification, including
intrusion detection, access control, and multi-factor authentication. The last step is to encrypt the
data so that no one else can read it.

Conclusion:
To guarantee the effectiveness and accuracy of the suggested frameworks and methodology,
they are experimentally evaluated. There were few false positives and a high detection rate.