bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cavitation and crack nucleation in thin hyperelastic adhesives
Authors: Rheinschmidt Florian , Drass Michael , Schneider Jens , Rosendahl Philipp Laurens 
Published: October 2023

Abstract
The present study investigates in the failure of adhesive bondings with structural silicone sealants. Point connectors of two circular metal adherends bonded with DOWSILTM TSSA are subjected to tensile loading. We formulate and use a constitutive law that captures volumetric softening owing to the formation of cavities. Therein, cavitation is considered a process of elastic instability which is homogenized with a pseudo-elastic approach. Ultimate failure initiating from the free edges is predicted employing the framework of finite fracture mechanics. The concept requires both a strength-of-materials condition and a fracture mechanics condition to be satisfied simultaneously for crack nucleation. For the former, we use a novel multiaxial equivalent strain criterion. For the latter, we employ literature values of the fracture toughness of DOWSILTM TSSA. The predicted onset of cavitation and ultimate failure loads are in good agreement with our experiments. The proposed model provides initial crack lengths that allow for the derivation of simple engineering models for both initial designs and proof of structural integrity while simultaneously extending the range of usability of the structural silicone compared to standardized approaches.
Multiple Layers Complexity Allocation with Dynamic Control Scheme for High-Efficiency Video Coding
Authors: Fang Jiunn-Tsair , Chen Ju-Kai 
Published: October 2023

Abstract
High-efficiency video coding (HEVC) has significantly improved coding efficiency; however, its quadtree (QT) structures for coding units (CU) substantially raise the overall coding complexity. This study introduces a novel complexity control scheme aimed at enhancing HEVC encoding efficiency. The proposed scheme operates at multiple layers, including the group of pictures (GOP) layer, frame layer, and coding tree unit (CTU) layer. Each coding layer is assigned a limited coding complexity based on the remaining coding time. Particularly noteworthy is the dynamic scheme implemented to activate the complexity control method. To further expedite encoding, an efficient algorithm is developed for the CTU layer. Experimental results indicate that the 0.46% and 0.98% increases in BD-rate under the target complexity are reduced to 80% and 60% of the complexity constraint, respectively. The rate-distortion performance surpasses existing state-of-the-art complexity control methods, demonstrating the effectiveness of the proposed approach in enhancing HEVC encoding efficiency.
Reliability and validity of the cancer-related dysfunctional beliefs and attitudes about sleep scale in cancer patients
Authors: Gao Ziyun , Gao Zihan , Zheng Chen , Ma Jianing , Zhao Ying , Zhang Lin , Guo Leilei 
Published: October 2023

Abstract

Background:Insomnia is a common health problem among cancer patients, which is not only a physical problem but also a psychological problem. Sleep plays an important role in the mental and somatic rehabilitation of cancer patients, and the sleep beliefs and attitudes of cancer patients are key factors in improving their sleep situation and quality of life. The aim of this study was to translate the Cancer-Related Dysfunctional Beliefs and Attitudes about Sleep (C-DBAS-14) scale into Chinese and to validate its reliability and validity in cancer patients.Method:This study utilized a cross-sectional design. The C-DBAS-14 scale was translated into Chinese. The reliability of the scale was measured by internal consistency, split-half reliability and retest reliability. The validity of the scale was assessed through the content validity indicators, exploratory factor analysis and validation factor analysis.Result:The Cronbach’s coefficient of the Chinese version of the C-DBAS-14 was 0.932, the split-half reliability coefficient was 0.908, and the test-retest reliability was 0.857. The four-factor model was obtained using exploratory factor analysis, explaining 75.360% of the variance, with each item loading greater than 0.4 on the common factor. The results of the confirmatory factor analysis revealed that all indicators of model fit were within an acceptable range, indicating a well-fitting model.Conclusion:The Chinese version of the C-DBAS-14 has good reliability and validity among cancer patients. It can be used to measure the sleep beliefs and attitudes of Chinese cancer patients.
Associations between left-behind characteristics and children’s psychological symptoms: A cross-sectional study from China
Authors: Liu Cong , Xu Yan , Sun Hao , Yuan Yan , Lu Jinkui , Jiang Jing , Liu Ningling 
Published: October 2023

Abstract

Background
Parents-child separation poses a significant challenge for children who are left behind (LBC). However, limited empirical evidence exists regarding the correlation between left-behind characteristics and the psychological symptoms of LBC. This study investigated psychological symptoms among LBC and explored associations between left-behind characteristics and those symptoms.
Methods
Using stratified cluster sampling, 1,832 LBC aged 13–18 years from three cities in East China were selected for analysis. Participants’ depression and anxiety symptoms were assessed with the Patient Health Questionnaire 9 (PHQ-9) and the General Anxiety Disorder 7 (GAD-7), respectively. Chi-square tests were used to compare differences in detection rates of psychological symptoms among LBC in different groups. Binary logistic regression analysis was used to infer associations between left-behind characteristics and psychological symptoms.
Results
our study showed that depression and anxiety symptoms were detected in 32.86% and 33.24%, respectively, of participating LBC. Univariate analysis showed statistically significant differences in detection rates of depression symptoms by gender, grade, and timing of parent-child separation. Statistically significant differences were observed in anxiety symptom rates by gender, grade, type of caregiver, and timing of mother-child separation. Multivariate analysis indicated a positive association between LBC’s anxiety symptoms and mother-child separation that occurred during post-primary school, and type of caregiver (father only or mother only). Our findings confirm a positive correlation between left-behind characteristics and anxiety symptoms among LBC.
Conclusion
The timing of mother-child separation and type of caregiver are potential risk factors for the development of anxiety symptoms in this population.
Altered DNA methylation and Dnmt expression in obese uterus may cause implantation failure
Authors: Bozdemir Nazlican , Kablan Tuba , Sukur Gozde , Cinar Ozgur , Uysal Fatma 
Published: October 2023

Abstract

Obesity is defined by increased adipose tissue volume and has become a major risk factor for reproduction. Recent studies have revealed a substantial link between obesity and epigenetics. Epigenome is dynamically regulated mainly by DNA methylation. DNA methylation, which is controlled by DNA methyltransferases (Dnmts), has been widely investigated since it is essential for imprinting and regulation of gene expression. In our previous study we showed that level of Dnmt1, Dnmt3a and global DNA methylation was dramatically altered in testis and ovary of high-fat diet (HFD)-induced obese mice. However, it has not yet been demonstrated that effect of HFD on Dnmts and global DNA methylation in mice uterus. Therefore, in the present study, we aimed to evaluate the impact of HFD on the level of Dnmt1, Dnmt3a, Dnmt3b, Dnmt3l and global DNA methylation in uterus. Our results showed that HFD significantly altered levels of Dnmts and global DNA methylation in the uterus. Total expression of Dnmt1, Dnmt3a and Dnmt3b significantly upregulated while level of Dnmt3l and global DNA methylation dramatically decreased (p < 0.05). Furthermore, we observed that expression of Dnmt3b and Dnmt3l significantly increased in endometrium including gland and epithelium (p < 0.05). Although Dnmt3b was the only protein whose expression significantly increased, level of global DNA methylation and Dnmt3l remarkably decreased in stroma and myometrium (p < 0.05). In conclusion, for the first time, our results show that obesity dramatically changes global DNA methylation and expression of Dnmts, and decreased DNA methylation and Dnmt expression may cause abnormal gene expression, especially in the endometrium.
Application of lipid metabolism-based indicators in constructing prognostic prediction models for anemia with end-stage renal disease and genomics to explore gene-chemical-anemia relationships
Authors: Du Yinke , Yin Shuhui , Zhang Mo , Geng Ye , Guo Guangying , Yao Li 
Published: October 2023

Abstract
Background
Patients on hemodialysis (HD) for end-stage renal disease (ESRD) have poor anemia and prognosis, and this retrospective study from a multicenter in China aimed to investigate the effects of anemia prediction and treatment attainment by constructing model.
Methods
1652 patients with ESRD on maintenance hemodialysis (MHD) from September 2021 to June 2022 were selected. After screening the validated factors into the prediction model of random forest regression (RF), the interaction effect was subsequently validated by applying the boosted regression tree method (BRT) and generalized additive model (GAM), and finally the gene-chemical-disease triad was used to verify the potential mechanism of the main predictors.
Results
Patients with anemia were mainly affected by social cognitive function and renal burden in quality of life. Low levels of HGB under biochemical indicators synergistically predicted anemia onset in ESRD patients with low levels of TRF and high levels of GLU, Meanwhile, the combined effect of high MCHC and low WBC, high TC and high TSAT affected the effect of Hb compliance. The key chemical predictors of anemia are GLU, TC, HDL, Cr, etc., which are influenced by key genes such as EPO and TNF through lipid and atherosclerosis and other mechanisms of lipid metabolism and energy metabolism.
Conclusions
We developed models for predicting the onset of anemia and Hb attainment effects in ESRD patients and validated the potential mechanisms of their lipid metabolism-associated factors by establishing a gene-chemical-disease triad.
Enhancing Security in Mobile Ad Hoc Networks: Detection and Isolation of Smart Black Hole Attacks using Universal Sink Detection Technique in Graph Theory
Authors: MEKKAOUI Kheireddine , TEGGAR Hamza , Houacine Abdelkrim 
Published: October 2023

Abstract
Network security is of utmost importance due to the ever-increasing number of connected devices and the growing sophistication of threats. Mobile Ad hoc networks (MANETs), characterized by their non-infrastructure and self-configured peer networks, are particularly vulnerable to various types of attacks. Therefore, it is imperative to implement an efficient Intrusion Detection System (IDS) capable of rapidly detecting attacks and alerting users to any malicious activities occurring on the network. Among the numerous threats faced by MANETs, the black hole attack stands out as one of the most serious. Originating from Denial of Service attacks, this type of threat has been extensively studied, and several solutions have been proposed. However, these solutions have become ineffective against the emergence of a new generation of black holes, known as smart black holes, which can circumvent most existing countermeasures. To address the challenge posed by smart black holes, we propose an IDS that focuses on early detection and isolation of malicious nodes. Our approach leverages locally shared information from neighboring nodes and utilizes the universal sink detection method derived from graph theory. Through simulations conducted in NS2, we have evaluated the effectiveness of our proposed approach. The results validate the efficiency of our system, as it enables prompt detection and isolation of smart black holes, leading to significant improvements in Packet Delivery Ratio (PDR) and throughput, with average enhancements of 97% and 90%, respectively. Consequently, our approach not only preserves network performance but also mitigates the impact of smart black hole attacks.
Linking cerebral malaria pathogenesis to APOE-mediated amyloidosis
Authors: Kioko Mwikali , Mwangi Shaban , Njunge James , Berkley James , Bejon Philip , Abdi Abdirahman 
Published: October 2023

Abstract
Although most children with cerebral malaria fully recover, about a fifth of the survivors develop post-discharge neurodevelopmental sequelae suggestive of advanced neuronal injury. However, the cerebral molecular processes initiating neurological dysfunction in cerebral malaria are still debatable. In this article, we explore available data and hypothesise that cerebral malaria might be linked to APOE-mediated amyloidosis, the primary pathological process that initiates neurodegeneration in Alzheimer's disease. If our hypothesis is tested and found to be true, it could have far-reaching implications for what we know about cerebral malaria pathogenesis.
Modeling ion constituents in the Sacramento-San Joaquin Delta using multiple machine learning approaches
Authors: Namadi Peyman , He Minxue , Sandhu Prabhjot 
Published: October 2023

AbstractSalinity is of paramount importance in shaping water quality, ecosystem health, and the capacity to sustain diverse human and environmental demands in estuarine environments. Electrical conductivity (EC) is commonly utilized as an indirect measure of salinity, serving as a proxy for estimating other ion constituents within the Sacramento-San Joaquin Delta (Delta) of California, United States. This study investigates and contrasts four machine learning (ML) models (Regression Trees, Random Forest, Gradient Boosting, and Artificial Neuronal Networks) for approximating ion constituent concentrations based on EC measurements, emphasizing the enhancement of conversion for constituents exhibiting pronounced non-linear relationships with EC. Among the four models, the Artificial Neuronal Networks model outshines the others in predicting ion constituents from EC, especially for those displaying strong non-linear relationships with EC. All four ML models surpass traditional parametric regression equations in terms of accuracy in estimating ion concentrations. Furthermore, an interactive web browser-based dashboard is developed, catering to users with or without programming expertise, enabling ion level simulation within the Delta. By furnishing more precise ion constituent estimations, this research enriches the understanding of salinity's effects on water quality in the Delta and fosters well-informed water management decisions.
Boosting flood routing prediction performance through a hybrid approach using empirical mode decomposition and neural networks: a case study of the Mera River in Ankara
Authors: katipoğlu Okan Mert , Sarıgöl Metin 
Published: October 2023

Abstract
Flood routing is vital in helping to reduce the impact of floods on people and communities by allowing timely and appropriate responses. In this study, the empirical mode decomposition (EMD) signal decomposition technique is combined with cascade forward backpropagation neural network (CFBNN) and feed-forward backpropagation neural network (FFBNN) machine learning (ML) techniques to model 2014 floods in Ankara, Mera River. The data are split in order to avoid the underfitting and overfitting problems of the algorithm. While establishing the algorithm, 70% of the data were divided into training, 15% testing and 15% validation. Graphical indicators and statistical parameters were used for the analysis of model performance. As a result, the EMD signal decomposition technique has been found to improve the performance of ML models. In addition, the EMD-FFBNN hybrid model showed the most accurate estimation results in the flood routing calculation. The study's outputs can assist in designing flood control structures such as levees and dams to help reduce flood risk.
Socio-demographic Differences in Prosocial Tendencies Aimed at the LGBTQIA+ Community from a Sample of Slovak Heterosexual Adults
Authors: Lenghart Daniel , Čerešník Michal 
Published: October 2023

Background:
Incidents against gender and sexual orientation minorities have increased significantly in recent months. This discrimination is taking place in a global context, and the Slovak Republic is no exception. However, the increased level of discrimination also creates room for people to get involved in trying to help reduce discrimination while increasing helping and pro-social behaviors towards these minorities in their cultural epicenters. To date, it is unclear and uncertain what role social and demographic characteristics play in this type of behavior toward the LGBTQIA+ community.

Objective:
This study analyzed public, digital, and overall prosocial behavior toward the LGBTQIA+ community in an online sample of Slovak heterosexual adults.

Methods:
One thousand fourteen (N = 1,014) heterosexual participants completed an online questionnaire focused on prosocial behavior towards the LGBTQIA+ community in Slovakia. Prosocial behavior towards the LGBTQIA+ community was determined using the authors’ Prosocial Tendencies towards the LGBTQIA+ Community questionnaire. This questionnaire captures public, digital, and overall levels of pro-social tendencies towards the LGBTQIA+ community. Participants also answered basic social and demographic background questions.

Results:
People in older adulthood also display more digital and overall prosocial behaviors, but not publicly prosocial. Residence-based differences were identified only in the area of public prosocial behavior in favor of people with urban residence. Differences in the context of personal experience with an LGBTQIA+ person demonstrated that people with a positive experience with an LGBTQIA+ person display significantly more public, digital and overall prosocial behavior compared to people with a negative experience and those with no experience. We also identified inter-sex differences in all areas studied in favour of women.

Conclusion:
People differ in their prosocial actions towards the LGBTQIA+ community based on social and demographic characteristics.
Effect of Surfactant Concentration on Physicochemical and Antibacterial
Properties of Eugenol Nanoemulsions
Authors: Bhusan Basumatary Indra , Kumar Santosh 
Published: October 2023

Introduction::
Nanoencapsulation has gained popularity in recent decades due to its numerous benefits, such as improved stability, oxidation resistance, retention
of volatile ingredients, controlled release, delivery of multiple active ingredients in a row, improvement in organoleptic properties, reduction of
toxic side effects, and water solubility.

Methods::
The present study was aimed to prepare eugenol nanoemulsions (EuNEs) using non-ionic surfactant (Tween 80) by ultrasound-assisted techniques
and to evaluate the effects of surfactant concentration on their droplets size, polydispersity index (PDI), zeta potential, storage stability,
antioxidant, and antibacterial activities. Antimicrobial activity of the prepared nanoemulsions was tested against Gram-positive; Staphylococcus
aureus, Bacillus subtilis and Gram-negative; Escherichia coli, and Alcaligenes faecalis bacteria using well diffusion method.

Results::
The results showed that the droplet size decreased after a threshold Tween 80 concentration (10%), while PDI value increased with the increase in
surfactant concentration (Tween 80).

method:
The droplets size, poly dispersity index (PDI), zeta potential, storage stability, antioxidant, and antibacterial activities of the prepared nanoemusions were characterized.

Conclusion::
The prepared EuNEs exhibited good antibacterial activity against all the four bacterial strains: E. coli, A. faecalis, S. aureus, and B. subtilis.

conclusion:
No phase separation, creaming, layering or deposition of large oil droplet were observed in the prepared nanoemulsions (EuNE-5, EuNE-7.5, and EuNE-10) except in case of 15%, v/v Tween 80 (EuNE-15) during 30 days of storage
Combating Biofilm Formation by Modulating Iron Concentration, using
Nanoparticles and Plant Extracts
Authors: Rodge Seema , Kulkarni Gayatri , Mahale Poorva , Joshi Shraddha , Dhanawade Sneha 
Published: October 2023

Abstract:
Biofilm formation often has detrimental effects from clinical and industrial perspectives. They are found to be resistant to antibiotics, detergents,
etc., causing their treatment and cure to be onerous. Therefore, it becomes a necessity to develop novel methods to inhibit it. Iron is an essential
regulator of bacterial biofilm formation. Studies suggest that by modulating iron concentration using either iron-chelating substances or iron salts,
biofilm inhibition can be achieved depending on the mechanism of biofilm formation. This approach inhibits the expression of several genes
responsible for adherence and colonization of bacteria. The use of nanoparticles is gaining rapid interest for biofilm inhibition. The ability of
nanoparticles to act as antibacterial agents depends on their surface-to-mass ratio. Owing to their small size, certain metal nanoparticles can
penetrate the EPS and inhibit bacterial adhesion and biofilm formation. Nanoparticles (NP) bring about cell lysis by interacting with cell
membranes or producing Reactive Oxygen Species (ROS). Owing to the mechanical, thermal, or physiochemical properties of nanocomposite
material, it is also studied for biofilm inhibition in various organisms. A widely appreciated method of NP synthesis is green synthesis, which
makes use of plant extracts and microorganisms. Interestingly, plant extracts inherently are known to possess antimicrobial and anti-biofilm effects
owing to their bioactive compounds. Plants synthesize secondary metabolites such as steroids, terpenoids, alkaloids, quinones, tannins, flavonoids,
etc., for their defense, pollination, flavor, etc. Plant extracts made using appropriate solvents can be used to inhibit biofilm formed on various
surfaces. They have been known to reduce biofilm by hindering exopolysaccharide formation and quorum sensing. In this review, we aim to
describe these potential methods of biofilm inhibition.