bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultrasensitive determination of quercetin using electrochemical sensor based on nickel-doping Zinc-based zeolite imidazole frame with a four-point star morphology
Authors: Gu Jianxia , Wei Yankun , Li Yongxia , Wei Tingting , Jin Zhanbin 
Published: March 2024

Abstract
At present, the electrochemical trace detection (picomole per liter level) with high sensitivity of quercetin is rare. In this work, the nickel-doped zinc-based zeolite imidazole framework with a four-point star morphology (Ni-ZIF-8-S) was successfully prepared by simple stirring and pH adjusting at room temperature. The strategies of nickel doping and morphology control endow Ni-ZIF-8-S with large specific surface area, unique hierarchical pore structure (micropores and mesopores), abundant active sites and excellent electron transport ability. Therefore, under optimal conditions, the electrochemical sensor based on Ni-ZIF-8-S can detect quercetin with a very high sensitivity of 622.0 µA µM− 1 and limit of detection is as low as 48 pM, which realizes ultrasensitive quantitative determination of quercetin in picomole per liter level. In addition, the proposed sensor also shows other excellent analytical performances, including good reproducibility, anti-interference and stability. As expected, the electrochemical sensor based on Ni-ZIF-8-S can perform quantitative detection of quercetin in complex real samples (urine) with acceptable results. The prepared sensor can be potentially applied in monitoring and quality control of quercetin.
Strategic Data Navigation: Information Value-based Sample Selection
Authors: Balogh Csanád Levente , Pelenczei Bálint , Kővári Bálint , Bécsi Tamás 
Published: March 2024

Abstract

Artificial Intelligence represents a rapidly expanding domain, with several industrial applications demonstrating its superiority over traditional techniques. Despite numerous advancements within the subfield of Machine Learning, it encounters persistent challenges, highlighting the importance of ongoing research efforts. Among its primary branches, this study delves into two categories, being Supervised and Reinforcement Learning, particularly addressing the common issue of data selection for training. The inherent variability in informational content among data points is apparent, wherein certain samples offer more valuable information to the neural network than others. However, evaluating the significance of various data points remains a non-trivial task, generating the need for a robust method to effectively prioritize samples. Drawing inspiration from Reinforcement Learning principles, this paper introduces a novel sample prioritization approach, applied to Supervised Learning scenarios, aimed at enhancing classification accuracy through strategic data navigation, while exploring the boundary between Reinforcement and Supervised Learning techniques. We provide a comprehensive description of our methodology, while revealing the identification of an optimal prioritization balance and demonstrating its beneficial impact on model performance. Although classification accuracy serves as the primary validation metric, the concept of information density-based prioritization encompasses wider applicability. Additionally, the paper investigates parallels and distinctions between Reinforcement and Supervised Learning methods, declaring that the foundational principle is equally relevant, hence completely adaptable to Supervised Learning with appropriate adjustments due to different learning frameworks. Project page and source codes are available at: https://csanad-l-balogh.github.io/sl_prioritized_sampling/.
An Optimization Method for Accelerating UAV Trajectory Planning
Authors: Liu Yinghuang 
Published: March 2024

Abstract
Trajectory planning is a very important task in the flight of UAVs. Through trajectory planning, the autonomous flight of UAVs can be realised and the flight efficiency and safety can be improved. Particle swarm algorithm is a commonly used trajectory planning method, but there are some shortcomings in practical applications, such as easy to fall into local minimal values and other problems. Therefore, previous research on particle swarm trajectory planning has been carried out and some improved algorithms have been proposed. However, there are still some problems with these algorithms, such as excessive computational power and slow convergence speed.
To address these problems, this paper proposes a method for deep residual learning to optimise the problem of local minima and slow convergence of traditional particle swarm trajectory planning. Specifically, a complete mathematical model for UAV path planning is established in this paper, and path planning results are obtained using the conventional improved particle swarm algorithm by means of cubic spline interpolation. Thereafter, to address the problems that path planning based on the particle swarm optimisation algorithm tends to reach local optimality at a later stage and the slow convergence speed of the improved algorithm, this paper introduces a deep residual learning network to improve the convergence speed and stability of the particle swarm algorithm. Finally, the performance of the algorithm before and after the improvement is compared according to four benchmark test functions. The simulation results show that the improved particle swarm algorithm has a significant enhancement in the late search capability.
Security-Aware Resource Allocation in Fog Computing using a Meta-Heuristic Algorithm
Authors: Mohammadi Mina , Bahrani-Pour Fatemeh , Ebrahimi-Mood Sepehr , Farshi Mohammad 
Published: March 2024

Abstract
In recent years, the number of smart devices and wireless data transmissions has increased worldwide.
These emerging applications and services require not only extensive computing capabilities and high battery power, but also elevated data transmissions as well.
Nonetheless, the computing capacity of this equipment is constrained,
resulting in significant consequences on the performance and operating costs of services in 5th-generation
wireless networks.
Recent advantages of Fog computing have increased the use of this model to fulfill above requirements in the IoT context.

A new Fog computing network model has been proposed in order to address these issues by providing cloud computing services at the network's edge.
In Fog computing, mobile devices are not required to offload all their tasks to remote and central servers. However, since other users are exposed to offloaded tasks, they are vulnerable to malicious attacks and eavesdropping.

In this paper, we investigate security-aware resource allocation in device-to-device based fog computing systems.
In order to enhance task offloading, a novel multi-objective function is proposed to optimize delay and
energy savings compared to local computing, as well as security breach costs.
In order to address this issue, a modified version of the NSGA-II algorithm is proposed that employs sigma scaling.

According to the results, the defined objective function is successful in optimizing objectives simultaneously.
Using sigma scaling made the NSGA-II algorithm better at spreading out solutions.
Moreover, the algorithm's exploration and exploitation capabilities are well controlled.
Proteome profile of Nucleus Accumbens (NAc) uncovers the differential and sex-specific role of CRMP2 in CVMS induced mouse model of depression
Authors: Karisetty Bhanu Chandra , Duscharla Divya , Vijay Vincy , Patel Shashikant , Soren Kalyani , Kumar Arvind , Ummanni Ramesh , Chakravarty Sumana 
Published: March 2024

Abstract

Chronic stress plays a very important role in building pathogenesis of psychiatric disorders including major depressive disorder (MDD). Despite of the fact that the human females are more prone to stress vulnerability, molecular mechanisms of depression-like pathophysiology in female rodent models is less studied as compared to that in males. Previous reports showed that 6-days of chronic unpredictable stress (CUS) paradigm can induce depression-like mood disorders in female mice whereas 21-days of chronic variable multiple stress (CVMS) paradigm induces the similar phenotypes in both the sexes. The gene array studies on critically affected areas like nucleus accumbens (NAc) and hypothalamus have indicated that the molecular mechanisms underlying the stress susceptibility might be differentially regulated across the sexes. However, there is scarcity of studies on proteome changes associated with MDD. In this study we specifically attempted to identify altered protein expression in NAc of OVX, as well as both male and female mice on CVMS using 2-DE followed by MALDI-LC-MS/MS. From 2D gel analysis total of 46 significantly altered protein spots were selected (20 proteins in OVX female, 7 in the male and 19 in the intact female) and identified by MALDI-LC-MS/MS. Proteomics data followed by validation revealed dysregulation of neuropeptide, Collapsin response mediator protein-2, CRMP2 (also known as DPYSL2), crucial for neuronal growth and is known to be associated with neurodegenerative/psychiatric disorders. These findings suggest the importance of comprehending the function of these proteins in a significantly affected brain area under long-term stress conditions to address the occurrence and symptoms of depression in both men and women.
Mumps resurgence in India in the decade 2014-2023: A Trend and Geospatial Analysis
Authors: MD. Bashar , Gnanasekaran Sridevi 
Published: March 2024

Abstract

Background
Mumps, caused by the paramyxovirus, primarily affects children and adolescents and presents with parotiditis. Complications such as orchitis and meningitis can occur, especially in young adult males and vaccination reduces complications. Global mumps cases surged in the past decade, including regions like North and South America, Australia, and Iran. In India, a recent surge in mumps cases was reported in 2023. The current analysis was performed to assess the burden and trend of mumps in India over the last decade and geographical variations in its burden across India.
Methods
Using the weekly outbreak reports of Integrated Disease Surveillance Programme(IDSP) for the period of 2014 to 2023, number of mumps cases and outbreaks in India were plotted to see the trend of mumps in past 10 years. State wise spatial distribution of the number of mumps cases and outbreaks were also performed using QGIS for 2023 to ascertain geographical variation in mumps burden across India.
Results
Distinct peaks and troughs in mumps cases were observed, with notable increases in 2015, 2016, and 2019. Absence of reported cases in 2021 and a resurgence in 2023 were noted. Spatial analysis identified hot spots and clusters, indicating hyperendemic areas. State-wise wide variations were evident, with some states reported disproportionately higher number of outbreaks like Jammu and Kashmir. The impact of COVID-19 on mumps incidence was seen, with a decrease in 2020 and an increase in 2023.
Conclusion
Total number of mumps outbreaks and cases were reported to be highest in 2023 which is alarming and emphasizes the need for inclusion of mumps containing vaccine in form of MMR vaccine in the Universal immunization Programme (UIP) of India along with strengthening the mumps surveillance. These findings also underscore the importance of state-specific analyses and evidence-based interventions to address mumps outbreaks effectively in India.
Stoichiometric characteristics and weight analysis of soil carbon, nitrogen and phosphorus in urban park green space
Authors: Yang Fan , Zhang Jin , Feng Yumeng , Li Wenfang , Yang Xiuyun , Wu Xiaogang 
Published: March 2024

Abstract
In this paper, 136 surface soil samples (0 ~ 10cm, 10 ~ 20cm) were collected from 37 urban parks in the main urban area of Taiyuan City. Mathematical models were used to systematically analyze the effects of urban expansion, park years and different plant allocation patterns on soil carbon, nitrogen and phosphorus content. The purpose of this study is to provide guiding opinions on the sustainable and healthy development of land use management and landscaping in small and medium-sized cities represented by Taiyuan City. The results of the study show that: Soil SOC content in 0-10cm and 10-20cm soil layers decreased by 55.08% and 61.38% with the gradient of urban expansion, and soil TN content increased significantly by 54.38% and 54.48% with the increase of the years of park construction, respectively. The maximum soil TN content appeared in shrub woodland and shrub woodland, respectively. Were 2.02 ± 0.25 g·kg− 1 and 1.76 ± 0.27 g·kg− 1, respectively. C: N decreased significantly with the increase of urban gradient (P < 0.01), C: P decreased first and then increased with the increase of urban gradient (P < 0.01), and there was a significant difference between C: P and plant allocation mode (P < 0.05). SOC, TN and TP contents were significantly correlated with their stoichiometric ratios. Soil SOC and TN contents were the main factors affecting soil in this study area.
Enhanced compatibility and toughness of PHBV/PCL blends by ring-opening polymerization and hydrogen bonding of epoxy- terminated hyperbranched polyester
Authors: Huang jiawei , Jin Yujuan , Tian Huafeng , Kumar Rakesh , Fang Yiqi , Zhou Sudan , Tie Rui , Zhou Shuyi 
Published: March 2024

Abstract
Melt extrusion process was followed in order to improve the high crystallinity and poor toughness of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) blend materials. It was achieved by the incorporation of epoxy-terminated hyperbranched polyester (EHBP) elastomer into PHBV and polycaprolactone (PCL). EHBP cross-links PHBV and PCL through ring-opening polymerization of epoxy-terminated and carboxyl groups. Therefore, when the EHBP content was 3phr, the Young's modulus and tensile strength of the blends are increased to 750MPa and 15MPa, respectively, which was comparable to the biodegradable polymers used for packaging. Simultaneously, compatibility between PHBV and PCL has been improved and the particle size reduction of blends can be obviously observed in scanning electron microscope (SEM) images. Dynamic mechanical analysis (DMA) analysis revealed that PHBV and PCL showed improved compatibility with each other by the addition of EHBP. Differential scanning calorimetry (DSC) revealed that the decrease of crystallinity of the blend was consistent with the increase in mechanical properties. Additionally, all the bio-blends show good thermal stability. Food overall migration studies showed that the amount of migration of composite materials in contact with food was also far lower than the national standard value. Therefore, PHBV/PCL/EHBP blends are expected to be used in the field of food packaging.
Factor affecting Time-to-Recovery from Major Depressive Disorder (MDD): Case Study at Jimma University Specialized Hospital, Ethiopia
Authors: Barsisa Temesgen Soboka 
Published: March 2024

Abstract

Background
Major Depressive Disorder (MDD) is depression that leads to disability and know days it is ranked as the 3rd burden of disease through the whole world and predicted to be 1st at 2030. Despite majority of MDD patients delay recovery during treatment, factor affecting time to recovery is unstudied. Hence, the main objective of this study was to explore the factors that affect time to recovery of MDD patients.
Methods
The data was taken from Jimma University Specialized Hospital (JUSH), South West Ethiopia. The retrospective study design was used. The time until the recovery of 204 patients chart were checked for 3 year follow up period from January 2018 to January 2021. The AFT models were employed after checking the restrictive assumption of Cox-PH model.
Result
Then, the study resulted, 134 (66%) were recovered and 70(34%) censored out of 204 patients. The median recovery time of the patients was 31 months but it varies depending on the covariates included in the study. Weibull AFT model was selected as the best model based on AIC. Accordingly, MDD patients of age: \(\ge 57 (\widehat{{\upvarphi }}=1.61[95\text{\%}: 1.12, 2.32\left]\right)\), marital status: widowed \((\widehat{{\upvarphi }}=1.61[95\text{\%}: 1.28, 2.04\left]\right)\), and substance use: yes \((\widehat{{\upvarphi }}=1.31[95\text{\%}: 1.12, 1.52\left]\right)\) had significantly prolonged time to recovery relative to their reference group 18–30 age, single marital status and no substance use respectively and MDD patients of sex: male \((\widehat{{\upvarphi }}=0.75[95\text{\%}: 0.66, 0.84\left]\right)\), education level: high school \((\widehat{{\upvarphi }}=0.69[95\text{\%}: 0.53, 0.88\left]\right)\) and college & above \((\widehat{{\upvarphi }}=0.55[95\text{\%}: 0.42, 0.71\left]\right)\) and living style: not alone \((\widehat{{\upvarphi }}=0.77[95\text{\%}: 0.67, 0.89\left]\right)\) had significantly shorten time to recovery relative to their reference group sex: female, education level: illiterate and living style: alone respectively.
Conclusion
In conclusion, the finding of this study showed that age, sex, marital status, education level, living style and status of substance use were major factors affecting recovery time of MDD patients. It is recommended to make interventions based on these factors.
Psychosocial Factors Influencing Vaccine Hesitancy: A Study in the Context of COVID-19
Authors: Rahel  
Published: March 2024

Abstract
The COVID-19 pandemic has underscored the critical need to comprehend vaccine hesitancy, a multifaceted issue with substantial repercussions for the success of vaccination campaigns. This study delves into vaccine hesitancy within a cohort of 560 individuals. Within this group, 157 individuals (28%) opted to receive the Pfizer vaccine, while the remaining 403 (72%) expressed hesitancy towards vaccination. Hesitant individuals were further classified into five distinct categories: 210 harbored concerns about potential vaccine side effects, 172 were influenced by misinformation and disinformation, and 21 exhibited a historical mistrust of vaccines. Notably, our survey did not unearth any instances of vaccine hesitancy stemming from political polarization or access barriers. Furthermore, we conducted a comprehensive analysis of biological markers in the 157 vaccinated individuals to evaluate vaccine side effects. This analysis unveiled significant variations in blood test parameters, such as D-Dimer, CRP, and WBC levels, between the first week and three weeks following vaccination (p < 0.0001 and p = 0.001, respectively). To sum it up, our results indicate that the vaccination process is a standard and medically valid procedure. Nevertheless, several factors play a role in individuals' vaccine hesitancy. It is imperative for both the government and healthcare systems to provide accurate information to the public about the significance of vaccination. Recognizing and tackling these factors are essential for successful vaccination initiatives and, in the end, attaining widespread immunity.
Occupational Hazards/ Risks Among Dental Staff in Afghanistan
Authors: Azimi Shamila , Azimi Susan , Azami Mashal 
Published: March 2024

Abstract
Background: The risks that are exclusive to the dental care setting are known as occupational hazards in dentistry.
Aims: Dangers. This research analyses the prevalence of occupational hazards among dental staff in Afghanistan.
Methodology: A cross-sectional study, using an online survey including qualitative and quantitative questions. Data collection was started from 16th .03.2021 till 12th.05.2021 and completed by 206 dentists. The questionnaire was designed in Google form and data was collected by online link via social media such as “Facebook, and WhatsApp”.
Result: According to a survey the most common occupational hazards among dentists are musculoskeletal problems in Afghanistan. Among musculoskeletal problems, most of the responders had complained of backache while nobody had noticed any pain in their elbow joint. 55% of dentists were vaccinated for common diseases (HBV, HCV, HAV, etc.) and 41.6% were not vaccinated. 74% of participants strongly agreed that dentistry is a stressful field and 26.7% had a high level of fatigue due to work at the end of the day.
Conclusion: musculoskeletal problems especially backache are the most prevalent hazards among Afghan dentists and Continuing education programs have to be conducted to overcome these hazards.
السجع في القرآن الكريم سورة عبس و التكوير و الانفطار (دراسة بلاغية)
Authors: Fitriah Maulidah , Abdul Hakim Muhammad Kamal Bin , Tajuddin Shafruddin 
Published: March 2024

البحث العلمي، قسم تربية اللغة العربية كلية اللغات والفنون جامعة جاكرتا الحكومية، يناير 2022 م. يهدف البحث إلى الحصول على وصف البيانات عن السجع في القرآن الكريم سورة عبس والتكوير والانفطار لمساعدة الطلبة على فهم دراسة البلاغة بوضوح لأن العلماء راجعوا علومهم إلى القرآن. المنهج المستخدم في هذا البحث هو المنهج الوصفي التحليلي في سورة القرآن في عبس والتكوير والانفطار. يركز هذا البحث على القصائد الموجودة في سورة القرآن الكريم عبس والتكوير والانفطار. يعتمد مصدر بيانات البحث على دراسة مكتبية من آيات من القرآن الكريم، وكتب في تفسير القرآن، وكتب بلاغية، وصحف، وغيرها من الكتب المتعلقة بهذا البحث. واستنادا إلى تحليل البحث خلص إلى أن آيات القرآن في سورة عبس والتكوير والانفطار، هناك السجع المطرف والمتوزي والمرصع. والآية القرآنية في سورة عبس والتكوير والانفطار التي توجد السجع المطرف والمتوزي والمرصع التي تتكون من ٣2 شاهدا السجع : السجع المطرف (عبس : 3 شواهد، التكوير : ٨ شواهد، الانفطار : ٤ شواهد)، السجع المتوزي (عبس : ٨ شواهد، التكوير : ٥ شواهد، الانفطار : شاهد واحد)، السجع المرصع (التكوير : شاهد واحد، الانفطار : شاهدان).
الكلمة الرئيسية: السجع، القرآن، عبس، التكوير، الانفطار
Arabic Learning Curriculum Based on Santri Adaptation in the Era of Society 5.0: Concepts and Implications
Authors: Ngarifah Imroatul , Bahtiyar Fadhli Hakim , Mufliha Mufliha , Ainiy Nurul , Mufidah Nuril , R. Taufiqurrochman R. Taufiqurrochman 
Published: March 2024

Society 5.0 gives a new nuance to learning Arabic. Optimizing the use of cyber as a learning medium adds to the attractiveness of santri in learning Arabic. The purpose of this study is to determine the concepts and implications of the Arabic language learning curriculum based on the adaptation of students in the era of society 5.0. This research is library research that collects secondary data from various kinds of literature such as books, journal articles, and information from relevant official websites. The data that has been collected will be clasificated, followed by an in-depth discussion. The result of this research is that the Arabic language learning curriculum based on the adoption of santri in the era of society 5.0 combines the pesantren curriculum and other appropriate modern curriculum. It utilizes the latest technology as a media for Arabic learning.