bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying Effective Factors to Alleviate Postnatal Distress and Coronavirus Anxiety in Mothers of Hospitalized Preterm Neonates
Authors: Borghei Narjes Sadat , Mehrbakhsh Zahra , Torklalebaq Fatemeh 
Published: September 2023

Abstract
Background
Given the critical importance of mental health in mothers of preterm neonates during the postpartum period for Population Youth Programs, our research aims to ascertain the correlation between postnatal distress and corona-induced anxiety in women who have hospitalized preterm neonates.
Methods
This descriptive-analytical study was conducted with a sample of 275 mothers of preterm neonates, were hospitalized in Gorgan city in 2020. Data collection was facilitated through the Corona Anxiety (CA) and Postnatal Distress Measured Scale (PDM). For data analysis, Spearman's correlation and univariate and multiple linear regression were employed.
Results
The average age of the participating mothers was 28.61 ± 6.173 years, and the average gestational age of the neonates was 32.8 ± 2.89 weeks. The study found a significant, positive correlation between CA and PDM. Controlling for other variables through multiple regression analysis, the most significantly influenced PDM were employment status (β = 3.88, p < 0.01), education level (β = 1.96, p = 0.032), and gestational age (β=-0.60, p < 0.001). Furthermore, the number of living children (β=-4.77, p = 0.01), education (β=-2.37, p = 0.01), and gestational age (β=-0.91, p < 0.001) were the most significantly impacted CA.
Conclusions
The correlation between CA and PDM suggests that preterm neonate's mothers experienced increased anxiety during the pandemic. Considering the factors influencing these anxieties, targeted programs should be developed to enhance the mental health of these mothers in future pandemics. The finding that women with more children experienced less CA could serve as evidence of the positive impact of having children on the mental health of women with premature infants during a pandemic.
Distributed adaptive fuzzy containment control for high-order nonlinear multi-agent systems with double input constraints: A finite-time approach
Authors: Zeng Xianxian , Liu Dacai , Lin Yishu 
Published: September 2023

Abstract
The finite-time containment control problem of high-order nonlinear multi-agent systems with double input constraints is investigated in this paper. Different from the existing literature on the multi-agent systems with input constraints, this paper considers the finite-time compensation of both unknown dead zones and random stuck faults, and does not set a restrictions on continuous uncertain nonlinearity. To address nonlinearity and avoid singularity in recursive design, both fuzzy logic systems and adding a power integrator technique are introduced. Then, bound estimation method is integrated into adding a power integrator technique, so that two novel finite-time compensation laws are designed to achieve the rapid compensation of unknown dead zones and random faults. Finally, a novel finite-time fuzzy control scheme is developed to achieve finite-time containment with double input constraints, and which is rigorously proved and verified by comparison experiment and application example.
Linking gout-specific patient-reported outcome measurement and lifestyle habits in patients with gout: results from the ULTRA registry
Authors: Do Hyunsue , Choi Hyo Jin , Choi Byoongyong , Son Chang-Nam , Kim Sang-Hyon , Ha You-Jung , Kim Ji Hyoun , Kim Min Jung , Shin Kichul , Kim Hyun-Ok , Song Ran , Lee Sung Won , Ahn Joong Kyong , Lee Seung-Geun , Lee Chang Hoon , Son Kyeong Min , Moon Ki Won 
Published: September 2023

Abstract
Background: The Gout Impact Scale (GIS), a part of the Gout Assessment Questionnaire 2.0, is a gout-specific patient-reported outcome measurement to assess health-related quality of life (HRQOL) of patients with gout. We aimed to investigate the correlation between GIS and lifestyle habits in Korean patients with gout.
Methods: We utilized the data from the aftermath of Urate Lowering TheRApy in gout (ULTRA) registry, a prospective cohort of Korean patients with gout treated in multiple centers nationwide since September 2021. Subjects were 18 years or older and met the 2015 ACR/EULAR gout classification criteria. They were asked to fill out the GIS questionnaire and questions regarding lifestyle habits on enrolment.
Results: The study included 232 patients. The mean (standard deviation) age was 55.1 (17.7) years, and 90.5% of patients were men. The ‘gout concern overall’ score in the GIS was significantly lower in patients who exercised less frequently and consumed soft drinks and meat, and the ‘well-being during attack’ score was significantly lower in patients who consumed vegetables and exercised more frequently. The frequency of vegetable consumption had a negative linear relationship with the ‘well-being during attack’ and ‘gout concern during attack’ scores (P=0.01, P=0.001, respectively). The frequency of exercise had a negative linear relationship with the ‘gout concern overall’ and ‘gout concern during attack’ scores (P=0.04, P=0.002, respectively).
Conclusion: The GIS was highly useful in identifying favorable lifestyle habits for Korean patients with gout. Patients who frequently consumed vegetables and exercised were associated with a better HRQOL.
Decision Support System Selection of Drug Plants for Respiratory System Disease using Complex Proportional Assessment Method
Authors: Hatta Heliza Rahmania , Putro I Ketut Arya , Wati Masna , Hatta Mohammad Zahir Zikri , Justitia Army , Noorcahyati Noorcahyati 
Published: September 2023

Abstract
Medicinal plant is the plant that has medicinal properties of thousands of species. The use of medicinal plants is now abandoned. Modern society is better acquainted the medicines from chemicals used in medicine than the medicinal plants because of a low knowledge of the health benefits of medicinal plants. This can cause the society found it difficult to determine the medicinal plants that are suitable with the disease. Therefore, to enhance the value of medicinal plants requires a system that can develop a person's insight and experience regarding traditional medicine. The developed system aims to make it easier for society to search for information by recommending medicinal plants that are suitable with their health problems, especially respiratory diseases. The system is made by website-based by using the Complex Proportional Assessment (COPRAS) method to search the best alternatives based on criteria. Based on interview with BALITEK KSDA, the system provides a recommendation of medicinal plants with six criteria, they are parts of plant, how to use, availability, rules of use, taste and treatment containing 75 kinds of medicinal plants for 7 respiratory illnesses commonly found in the society, they are asthma, bronchitis, pneumonia, influenza, cough, ISPA and TBC. The system testing uses the black box method by involving 28 respondents. The result of this research shows that the COPRAS method is successfully applied in the decision-making support systems in choice medicinal plants for respiratory disease.
Barriers and Strategies to Improve Men’s Uptake of HIV Care Services in Rural KwaZulu-Natal, South Africa: A Qualitative Study
Authors: Adeagbo Oluwafemi Atanda , Gumede Dumsani , Zulu Zakhele , Naidoo Kammila 
Published: September 2023

Abstract
Background
The 2017 Joint United Nations Programme on HIV/AIDS blind spot report echoes the challenges as well as the benefits of men’s effective utilization of HIV services. However, men have been consistently missing from the HIV care cascade, leading to poor health outcomes in men and ongoing transmission of HIV in young women in South Africa. This study sought to understand key barriers to effective uptake of HIV services among men, and potential strategies to address these challenges.
Methods
Ten telephone interviews and three workshops were conducted (July-November 2020) with a purposive sample of men aged 21–65 years (n = 26) from rural KwaZulu-Natal. Broad themes were identified from the interview transcripts and analyzed inductively.
Results
Masculine norms, stigma and fear of an HIV identity were major barriers to the uptake of HIV testing among men as well as hesitancy due to perceived risks. Participants living with HIV identified various socio-psychological, structural, and COVID-related factors inhibiting HIV treatment uptake and adherence. Besides condoms and circumcision, no participant had prior knowledge of PrEP. Participants suggested that men need tailored HIV/AIDS messaging and education (led by men living with HIV) about the benefits of HIV testing, treatment, and prevention. Importantly, they believed that community delivery of HIV services would encourage more men to engage in care.
Conclusion
To achieve zero new infections and zero AIDS-related deaths among men in South Africa, efforts should be directed towards developing tailored emotive educational and community-based interventions that address identified barriers to improve men’s utilizations of HIV care services.
CDMO: Chaotic Dwarf Mongoose Optimization Algorithm for Feature Selection
Authors: Abdelrazek Mohammed , Elaziz Mohamed Abd , El-Baz A. H. 
Published: September 2023

Abstract
In this paper, a modified version of Dwarf Mongoose Optimization Algorithm (DMO) for feature selection is proposed. DMO is a novel technique of the swarm intelligence algorithms which mimic the foraging behavior of the Dwarf Mongoose. The developed method, named Chaotic DMO (CDMO), is considered a wrapper-based model which select optimal features that give higher classification accuracy. To speed up the convergence and increase the effectiveness of DMO, ten chaotic maps were used to modify the key elements of Dwarf Mongoose movement during the optimization process. To evaluate the efficiency of the CDMO, ten different UCI datasets are used and compared against the original DMO and three other well-known Meta-heuristic techniques, namely Ant Colony optimization (ACO), Whale optimization algorithm (WOA), and Particle Swarm optimization (PSO). The experimental results show that the CDMO gives higher performance than the DMO, PSO, WOA and ACO methods used in feature selection.
Traffic signal optimization using quantum annealing on real map
Authors: Shikanai Reo , Ohzeki Masayuki , Tanaka Kazuyuki 
Published: September 2023

Abstract

The quantum annealing machine manufactured by D-Wave Systems is expected to find the optimal solution for QUBO (Quadratic Unconstrained Binary Optimization) accurately and quickly.This would be useful in future applications where real-time calculation is needed.One such application is traffic signal optimization.Some studies use quantum annealing for this.However, they are formulated in unrealistic settings, such as only crossroads on the map.Therefore, we suggest a QUBO, which can deal with T-junctions and multi-forked roads.To validate the efficiency of our approach, SUMO (Simulation of Urban MObility) is used.This enables us to experiment with geographic information data very close to the real world.We compared results with those using the Gurobi Optimizer in the experiment to confirm that quantum annealing can find a ground state.The results show that the quantum annealing cannot find the ground state, but our model can reduce the time that vehicles wait at a red light.It is also inferior to the Gurobi Optimizer in calculation time. This seems to be due to the D-Wave machine's hardware limitations and noise effects, such as ambient temperature.If these problems are solved, and the number of qubits is increased, the use of quantum annealing is likely to be superior in terms of the speed of calculating an optimal solution.
Thermodynamic equation of state of magnetized PNJL model of 2 + 1 flavor at finite baryonic density
Authors: SINGH SHOUGAIJAM SOMORENDRO 
Published: September 2023

Abstract
We extend our recent research work for 2 flavor magnetized PNJL model to 2 + 1 flavor quarkscooperating the finite baryonic potential in the thermal mass and magnetic field in the potential ofthe Lagrangian density. The evaluation of equation of state (EOS) and its relevant thermodynamicproperties after incorporating the finite chemical potential in the thermal mass and magnetic field inthe potential are represented in the results. The results show that all the thermodynamic parametersare found improved by the inclusion of the finite baryonic chemical potential. The result at the finitebaryonic density also conforms and improves from our earlier work without the baryonic chemicalvalue. It means there is an up-gradation in the outputs predicted by the presence of baryonic chemical potential in the thermal mass.
Theoretical investigation of the physical properties of spinel-type catalysts based on Scandium: CdSc 2 O 4 and ZnSc 2 O 4
Authors: GUERMIT Youcef , HOCINE kamel , DRIEF Mohammed , LANTRI Tayeb , Rekab-Djabri Hamza , Maizia Ahmed , RACHED Habib , RACHED Djamel , BENKHETTOU Nour eddine 
Published: September 2023

Abstract

Magnetic structural, electronic, thermodynamic, and optical properties of the ASc2O4 (A = Cd, Zn) spinel compounds are performed. The density functional theory with the full potential-linearized augmented plane wave method (FP-LAPW) is used in calculations. Our results show that, all compounds exhibit a nonmagnetic (NM) behavior. The electronic structures report the semi-conductor metallic behavior starts to appear in ZnSc2O4 and CdSc2O4 compounds. Direct band gap is detected for both substances at Γ- Γ with bandgap energy of 2.94 eV for CdSc2O4 and 2.98 eV for ZnSc2O4. Thermodynamic properties including Volume, heat capacity, coefficient of thermal expansion, and Debye temperature are investigated using the Debye quasi-harmonic model. The thermodynamic results show the stability of ASc2O4 (A = Zn, Cd) under the action of very high pressures and temperatures. Our analysis of optical parameters suggest them suitable candidates for optoelectronic devices particularly from visible to extreme violet region applications.
Novel oxo-5-(trifluoromethyl)quinazolinyl amide derivatives and their anticancer activity
Authors: Pandiri Sreedhar , Konda Santosh Kumar , Chennuri Bharath Kumar , Akarapu Premalatha , Nuka Mahesh , Saha Amrita , Bhoomandla Srinu 
Published: September 2023

Abstract
A series of novel oxo-5-(trifluoromethyl)quinazolinyl amide derivatives were prepared starting from 2-aminobenzoic acid 1, reacted with 4-Chlorobenzoyl chloride and obtained 2-(4-Chlorophenyl)-5-(trifluoromethyl)-4H-benzo[d][1, 3]oxazin-4-one 2, compound 2 on reaction with hydroxyl amine and obtained 2-(4-Chlorophenyl)-3-(4-hydroxyphenyl)-5-(trifluoromethyl)quinazolin-4(3H)-one 3, compound 3 on further react with bromoethyl acetate to get ethyl 2-(4-(2-(4-chlorophenyl)-4-oxo-5-(trifluoromethyl)quinazolin-3(4H)-yl) phenoxy) acetate 4, compound 4 on reaction with aliphatic and aryl amine to obtain amide functionalized quinazolinyl derivatives 5. All the final compounds evaluated for anti cancer activity against four human cancer cell lines such as ‘HeLa - Cervical cancer (CCL-2); COLO 205- Colon cancer (CCL-222); HepG2- Liver cancer (HB-8065); MCF7 - Breast cancer (HTB-22)’ and promising compounds 5l and 5m have been identified.
Efficient and Privacy-Preserving Image Classification Using Homomorphic Encryption and Chunk-based Convolutional Neural Network
Authors: Jia Huixue , Cai Daomeng , Yang Jie , Qian Weidong , Wang Cong , Li Xiaoyu , Yang Shan 
Published: September 2023

Abstract
Image feature categorization has emerged as a crucial component in many domains, including computer vision, machine learning, and biometrics, in the dynamic environment of big data and cloud computing. It is extremely difficult to guarantee image data security, privacy, and computing efficiency while also lowering storage and transmission costs. This paper introduces a novel method for classifying image features that combines multilevel homomorphic encryption and image data partitioning in an integrated manner. We employ a novel partitioning strategy to reduce computational complexity, significantly reducing computational load and improving classification accuracy. In the quest for increased data security and privacy, we introduce a novel, fully homomorphic encryption approach specialized to partitioned images. To counter the inherent complexity of encryption, we devise a compound encryption strategy that exploits the full potential of homomorphic computation, with an explicit objective to curtail computational and storage overheads. Evidently superior to conventional methods, our methodology showcases pronounced benefits in computational efficiency, storage and transmission cost reduction, and robust security and privacy preservation. Hence, the methodology put forth in this paper presents a pioneering and efficacious resolution to the multifaceted challenges of image feature classification within the intricate milieu of cloud computing and big data.
On Phase Field Approach for Thermal Fracturing in Thermoviscoelasticity Solids and Its Application for Studying Thermal Response Due to Crack Growth: Part I. Kelvin-Voigt Type.
Authors: Alfat Sayahdin 
Published: September 2023

Abstract
The study of thermal response in the crack tip due to crack growth is very important to study the material behavior. Actually, the thermal response in the crack tip is generated by the mechanical dissipation energy properties, e.g., the viscous energy dissipation in viscoelasticity solids. Therefore, we proposed the PFM for crack propagation in thermoviscoelasticity solids and demonstrated several numerical examples. Our present model is derived from the Francfort–Marigo energy with the Ambrosio–Tortorelli regularization, and thermal energy. Our study aims to investigate the thermal response in the material due to crack growth numerically using the proposed model. In the numerical method, since we need the mesh which has to be fine enough to capture the damage variable z, we apply the adaptive finite element method. Several interesting numerical examples are demonstrated, such as; Mode I crack propagation, and scalar Mode III crack propagation in the non-isothermal and adiabatic processes. Numerical experiments demonstrate the capability of the proposed model to capture the temperature increasing around crack tips which is consistent with the viewpoint of laboratory experiments in the literature.
Systematic Review: Risk Factors of Uterine Gangrene Disease in Cervical Cancer With Type 2 Diabetes Mellitus
Authors: Javier R. Mohamad , Pratiwi Dela Hesti , Febrianto Dani Pratama , Rialdi Andisa Fadhila , Umar Muhammad Arfan , Ramadhani Nadia , Kautsari Gafrinda , Munir Badrul , Ananingati Ananingati , Sander Moch. Aleq 
Published: September 2023

Abstract
Cervical disease is among the most widely recognized malignant growths among ladies and positions fourth after bosom, colorectal, and cellular breakdown in the lungs. The occurrence of cervical malignant growth every 36,633 instances in Indonesia in 2021, with a death rate of 21,003. Gram-positive bacteria like Clostridium perfringens commonly produce the extremely lethal infection known as "gas gangrene," which affects the network's inner tissues. It has characteristics similar to those of Type 2 diabetes mellitus, such as muscular necrosis or myonecrosis. recognizing the causes of uterine gas gangrene in women individuals with cervical malignancy and Type 2 DM. This study was conducted as a thorough analysis utilizing the PRISMA (Preferred Reporting Items for Meta-analyses and Systematic Reviews) methodology, which is commonly referred to as PRISMA. The steps or protocols for proper research are followed throughout the process. sources were obtained from the PubMed website and the Google Researcher website, and filtering was carried out to get 17,899 results. There was diary bunching done, and since Scopus Q1 ordered 18 diaries, Q2 ordered 14, and Sinta S1 recorded 2 diaries, 34 diaries were extracted. Age and lifestyle as cervical cancer risk factors are discussed in most journals. Risk factors for cervical disease are resolved in light old enough, HbA1C, way of life, and cervical malignant growth related with type 2 diabetes mellitus and gangrene from uterine gas
Generation and Countermeasures of Adversarial Examples on Vision: A Survey
Authors: Liu Jiangfan , Li Yishan , Guo Yanming , Liu Yu , Tang Jun , Nie Ying 
Published: September 2023

Abstract
Recent studies have found that deep learning models are vulnerable to adversarial examples, demonstrating that applying a certain imperceptible perturbation on clean examples can effectively deceive the well-trained and high-accuracy deep learning models. Moreover, the adversarial examples can achieve a considerable level of certainty with the attacked label. In contrast, human could barely discern the difference between clean and adversarial examples, which raised tremendous concern about robust and trustworthy deep learning techniques. In this survey, we reviewed the existence, generation, and countermeasures of adversarial examples in Computer Vision, to provide comprehensive coverage of the field with an intuitive understanding of the mechanisms and summarized the strengths, weaknesses, and major challenges. We hope this effort will ignite further interest in the community to solve current challenges and explore this fundamental area.
Pre-exams Anxiety and Stress Among Students in Syrian Private University
Authors: Dahdal Gerous , Dahdal Gerous , Mousa Ayham , Mousa Ayham , Latifeh Youssef , Latifeh Youssef 
Published: September 2023

Abstract
Background Anxiety and stress among university students are pervasive global concerns, significantly affecting their mental health and overall well-being. This study explores the prevalence of pre-exam stress and anxiety among students in a Syrian private university and examines their potential impact on the academic and educational environmentMethods A cross-sectional study conducted in April 2023 involved voluntary participation from students at the Syrian Private University. Data was collected through a self-administered questionnaire, encompassing demographic information, stress and anxiety levels before exams, and the Depression, Anxiety, and Stress Scale − 21 Items (DASS-21). Statistical analysis was performed using SPSS.Results The sample consisted of 427 students with an average age of 22.11 years. Female students comprised 53% of the sample, and urban residents accounted for 82%. Most students were in their fifth year (23%), and 38% had GPAs ranging from 76–85%. The majority studied human medicine (45%). Among habits, 38% consumed caffeine, 15% smoked cigarettes, 12% smoked hookah, and 3% consumed alcohol. Nine percent reported chronic illnesses. Most students perceived their parents' personalities as supportive..Conclusions This study highlights the pressing issue of mental health problems among university students in Syria, particularly related to pre-exam stress and anxiety. The findings underscore the need for comprehensive mental health support services, stress management workshops, and awareness campaigns on university campuses to help students cope with these challenges effectively. Addressing these concerns can significantly enhance students' well-being and academic success. Future research should focus on preventive measures and factors contributing to mental health issues among this population.