bluuebunny/crossref_metadata_2025_split huggingface dataset:
Morpho-Molecular Characterization and Virulence Confirmation of Fungal Pathogens Associated with Citrus Fruit in Pakistan
Authors: Zaheer Iram , Iram Shazia , Hyder Sajjad , Gondal Amjad Shahzad , Iqbal Rashid , Alwahibi Mona S , Elshikh Mohamed S , Arslan Muhammad 
Published: August 2023

Abstract
Background: In all of Pakistan's citrus-growing regions, losses related to fungi that cause infections of citrus fruits were investigated. However, the Khanpur city of the Haripur district, a significant citrus-growing area in Pakistan, has not addressed this issue. Citrus fruit quality and quantity deteriorate as a result of various fungi impairing their quiet standards, resulting in economic losses.
Results: The current investigation involves three steps that are morphological, pathological, and molecular identification of the fungal pathogens linked to citrus fruit diseases. Firstly the pathogens from infected fruit samples were isolated by culturing them on potato dextrose agar (PDA) for morphological characterization. Secondly, the 5.8S rDNA molecular sequencing was used to identify the crucial species at the molecular level. The results showed that they belonged to the seven important genera of Colletotrichum, Alternaria, Aspergillus, Botryosphaeria, Lasiodiplodia, Penicillium, and Fusarium. And thirdly the three different citrus cultivars were subjected to pathogenicity assays to identify the most resistant variety to fungal diseases.
Conclusions: Current work associated with the comprehension of disease development points towards effective managerial practices in the form of a cost-effective spray program. Furthermore, the findings are indicative of the need for biological and physical pre-harvest management interventions to increase storage and marketability.
Exploratory analysis of key factors in the habitat use of a Neotropical primate in an urban environment: The White-footed tamarin (Saguinus leucopus, Callitrichidae)
Authors: Soto-Calderón Iván Darío , Pérez-Estrada Ana María , Acosta-Madrigal Tatiana , Jurado-Gutiérrez Ana María , Delgado-Villegas Vanessa , Mesa-Alarcón Vanesa , Hidalgo-García Cristian Camilo 
Published: August 2023

Abstract

High levels of species diversity and endemism in developing countries contrast with high rates of human population expansion and urban development. This poses a challenge for wildlife and their ability to adapt to transformed and fragmented habitats. In the Neotropics, tamarins and marmosets (Primates: Callitrichidae) have established populations in urbanized areas, including the White-footed tamarin in north-western Colombia, where it is prone to metabolic syndrome presumably due to nutritional issues and reduced physical activity. We explored the habitat use and activity budget of a social group of the White-footed tamarin established in an isolated forest patch in Medellín, Colombia over a 12-month period. We applied multiple linear regressions to assess 1) the seasonal variation of diet and 2) the role of landscape features on the use of the available habitat. Resting was the most dominant behavior. The diet comprised a range of animal and plant items as well as a smaller proportion of anthropogenic food. The diet diversity showed an inverse relationship with the within-month humidity variation, indicating an adaptation to seasonal changes. The use of available area was associated with tree density and abundance of key plant species that are either consumed or used as part of corridors. Our results show that flexible and generalist diet habits are critical in adaptation to cities. However, food oversupply in isolated forest patches in cities may lead to sedentarism and compromise the health of urban fauna. Strategic planting of key tree species that provide food sources and facilitate dispersal is recommended.
How Positive Childhood Experiences Fostering College Students Adjustment: The Role of Siblings Number and Self-Esteem
Authors: Li Juan , Wang Wenzhuang 
Published: August 2023

AbstractIn recent years, there has been growing concern about the mental health and well-being of college students, as they face numerous challenges and transitions during their higher education journey. This research aims to investigate the influence of Positive childhood experiences on the adaptability of college students and the underlying mechanisms. A cross-sectional survey was conducted on 5,787 college students from Chinese universities. Participants completed an online questionnaire measuring positive childhood experiences, self-esteem, the number of siblings, and China College Students' Adjustment. The results showed that positive childhood experiences positively predicted China College Students' Adjustment, and self-esteem played a mediating role in the positive effect of positive childhood experiences on China College Students' Adjustment. Moreover, sibling played an antagonistic moderating role in the positive effect of Positive childhood experiences on China College Students' Adjustment. Therefore, it is recommended to enrich positive childhood experiences, improve self-esteem, and provide more care and support to students from multi-sibling families to enhance China College Students' Adjustment.
Predictive Analytics and Risk Management of Property Insurance
Authors: Amirhosseini Morteza , Vanani Iman Raeesi , Taghavifard Mohammad Taghi , Sohrabi Babak 
Published: August 2023

Abstract

Claim prediction plays a leading role in risk management for insurance companies. This research proposes a risk management model by evaluating property policy's risk and classifying risk levels to reduce uncertainty for decision-makers. The approach consists of three phases. Phase I is claims prediction; It integrates three claim predictions: occurrence probability, claim severity, and time of loss; we use machine learning for each prediction. Algorithms have been implemented on about 2 million records of a large insurance company between 2011 and 2022. Results showed that the best algorithm is a deep neural network. In Phase II, risk metric results are calculated to determine the risk level score; we present the prediction results into a quadrant risk-grouped associated measure. Phase III is risk management. The risk level score is linked to the decision-makers action list to keep, reject or transfer the risk of each insurance policy. The final model is a risk management tool combining risk prediction metrics and the risk matrix. To assess the efficacy of this new model, 500 sample records were provided to the risk management system, and its output was compared with that of expert opinion. 72% correct matching indicates the accuracy of the model.
Health-Related Quality of Life and Recovery Capital Among Recovery Residents Taking Medication for Opioid Use Disorder in Texas
Authors: Obekpa Elizabeth O , Mccurdy Sheryl A. , Schick Vanessa , Markham Christine , Wilkerson J. Michael 
Published: August 2023

Abstract
Background
Recovery from opioid use disorder (OUD) includes improvements in health-related quality of life (HRQOL) and is supported by recovery capital (RC). Little is known about RC and HRQoL among recovery residents taking medication for OUD (MOUD).
Methods
Cross-sectional analyses of data collected from 355 residents in 14 recovery homes were conducted. We described HRQOL (EQ-5D-5L health dimensions- mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) and RC (the Assessment of Recovery Capital scores) and examined their associations using T-, Chi-squared, and Fisher's exact tests.
Results
Most participants were 35 + years (50.7%), male (58.9%), non-Hispanic White (68.4%), heterosexual (82.8%), and unemployed (66.0%). The majority reported anxiety/depression (78.4%) and pain/discomfort (55.7%) problems. Most participants had high social (65.4%), personal (69.0%), and total (65.6%) RC. Age, sex, marital status, sexual orientation, and comorbid diagnoses were associated with HRQOL. Low personal RC was associated with mobility problems (aOR = 0.43, CI = 0.24–0.76). Low personal (aOR = 0.13, CI = 0.04–0.41) and total (aOR = 0.20, CI = 0.07–0.60) RC were associated with problems conducting self-care. Low personal (aOR = 0.25, CI = 0.11–0.57) and total (aOR = 0.43, CI = 0.22–0.83) RC were associated with problems conducting usual activities. Low personal (aOR = 0.37, CI = 0.20–0.68) and total (aOR = 0.55, CI = 0.34–0.90) RC were associated with pain/discomfort problems. Low personal (aOR = 0.33, CI = 0.15–0.73) and total (aOR = 0.20, CI = 0.10–0.41) RC were associated with anxiety/depression problems. Social RC was not associated with HRQOL.
Conclusions
Personal and total RC predict HRQOL. Our findings underscore the importance of ensuring residents are not only linked to MOUD but their RC should be routinely assessed and enhanced to support their recovery and improve HRQOL.
Preoperative scoring system for prediction of extended resection during emergency surgery for acute appendicitis
Authors: Kobayashi Toshimichi , Hidaka Eiji , Ando Akitoshi , Koganezawa Itsuki , Nakagawa Masashi , Yokozuka Kei , Ochiai Shigeto , Gunji Takahiro , Sano Toru , Tomita Koichi , Tabuchi Satoshi , Chiba Naokazu , Kawachi Shigeyuki 
Published: August 2023

Abstract
Purpose: Appendectomy is the primary treatment for acute appendicitis. However, extended resection (ER) may be required in difficult cases. Preoperative prediction of ER may identify challenging cases but remains difficult. We aimed to establish a preoperative scoring system for ER prediction during emergency surgery for acute appendicitis.
Methods: This single-center retrospective study included patients who underwent emergency surgery for acute appendicitis between January 2014 and December 2022 and were divided into ER and appendectomy groups. Independent variables associated with ER were identified using multivariate logistic regression analysis. A new scoring system was established based on these independent variables. The discrimination of the new scoring system was assessed using the area under the receiver operating characteristic curve (AUC). The risk categorization of the scoring system was also analyzed.
Results: Of the 179 patients included in this study, 12 (6.7%) underwent ER. A time intervalfrom symptom onset to surgery ≥4 days, retrocecal or retrocolic appendix, and the presence of an abscess were identified as independent preoperative predictive factors for ER. A new scoring system was established based on these three variables, and scores ranged from 0 to 6. The AUC of the scoring system was 0.877, and the rates of ER among patients in the low- (score, 0–2), medium- (score, 4), and high- (score, 6) risk groups were estimated to be 2.5%, 28.6%, and 80%, respectively.
Conclusions: Our scoring system may help surgeons identify patients with acute appendicitis requiring ER and facilitate treatment decision-making.
Salvianolic acid B exerts a protective effect against ZBP1-mediated PANoptosis in macrophages infected by Mycobacterium tuberculosis through its inhibition of the TNF- α/TNFR1 signaling pathway
Authors: Shen Jingjing , Fu Yan , Liu Fanglin , Wu Jianchao , Zhang Hemin , Sun Jinxia , Miao Zhulei , Jiang Xin 
Published: August 2023

Abstract
Tuberculosis (TB) is a deadly infectious disease caused by Mycobacterium tuberculosis (Mtb). The increasing rates of drug resistance in Mtb have made controlling TB more challenging, creating an urgent need for new treatment strategies. The interplay between macrophages and Mtb governs host susceptibility and immune evasion by manipulating programmed cell death (PCD) pathways and inflammatory responses. During Mtb infection, excessive programmed cell death can harm the host, as it aids in clearing the pathogen and promotes Mtb growth. If the infection is not cleared in a timely manner, excessive inflammation can further damage the host's tissues. A recent discovery called PANoptosis refers to a type of regulated inflammatory cell death that involves pyroptosis, necroptosis, and apoptosis, and it may occur after Mtb infection. Here, we report that Salvianolic acid B (Sal B), a water-soluble extract of Salvia miltiorrhiza, may act as a potential host-directed therapy (HDT) agent to inhibit Mtb-induced PANoptosis and suppress the intense inflammatory response. Mechanistically, Sal B could inhibit the TNF-α/TNFR1 signaling pathway, thereby inhibiting the innate immune sensor ZBP1 and achieving a regulatory effect on macrophage PANoptosis. We also observed that Sal B inhibited a large multi-protein signaling complex formed by ZBP1, ASC, caspase-8, RIPK1 and RIPK3, ultimately inhibiting inflammatory cell death. Overall, this study provides a deeper understanding of the roles these biomolecules play in innate immunity and inflammatory cell death during Mtb infection. The findings highlight Sal B as a potential HDT agent capable of inhibiting PANoptosis in macrophages and mitigating the excessive inflammatory response induced by Mtb infection. Notably, further research is needed to explore the therapeutic potential of Sal B in combatting Mtb and its implications as a potential future treatment option.
Mitochondrial Calcium Uniporter (MCU) Involves in Ischemic Postconditioning Effect Against Ischemic Reperfusion Brain Injury in Mouse
Authors: Sasaki Hiromitsu , Nakagawa Ichiro , Furuta Takanori , Yokoyama Shohei , Morisaki Yudai , Saito Yasuhiko , Nakase Hiroyuki 
Published: August 2023

Abstract
Ischemic postconditioning (PostC) phenomenon is known as the neuroprotection against ischemic reperfusion (I/R) injury. One of the key processes in PostC is opening of mitochondrial ATP dependent potassium (mito-KATP) channel and depolarization of mitochondrial membrane potential, which triggers the release of calcium ion from mitochondria through the low conductance opening of mitochondrial permeability transition pore (mPTP). Mitochondrial calcium uniporter (MCU) is known as the highly sensitive transporter for uptake of Ca2+ inwardly existed on the inner mitochondrial membrane. Furthermore, it has attracted attention as a new target of treatments in disease such as neurodegenerative disease, cancer and ischemic stroke. Thus, we considered that MCU may involve in PostC and trigger its mechanism. In this research, we used the whole-cell patch clamp technique to hippocampal CA1 pyramidal cells from C57BL mice and measured changes in spontaneous excitatory post-synaptic currents (sEPSCs), intracellular Ca2+ concentration, mitochondrial membrane potential and N-methyl-D-aspartate receptor (NMDAR) currents under the inhibition of MCU by Ruthenium red 265 (Ru265) in PostC. Inhibition of MCU increased sEPSCs occurrence (p = 0.008), NMDAR currents (p < 0.001), intracellular Ca2+ concentration (p < 0.001) and dead cells (p < 0.001) significantly after reperfusion, indicating the removal of the neuroprotective effects in PostC. Moreover, the mitochondrial depolarization in PostC with Ru265 was weakened, compared to it in PostC (p = 0.03). These results suggest that MCU affects the mitochondrial depolarization in the PostC mechanism to suppress NMDAR over-activation and prevent the elevation of intracellular Ca2+ concentration against I/R injury.
Is it possible to delay stereotactic radiotherapy of brain metastasis of lung cancer?
Authors: Musset Xavier , Guillerm Sophie , Gounant Valérie , Quero Laurent , Dumont Clément , Terrisse Safae , Bollet Marc , Zalcman Gerard , Hennequin Christophe 
Published: August 2023

Abstract
Purpose
Because modern medical treatments of lung cancer had a potential efficacy on brain metastases, the optimal timing of stereotactic radiosurgery (SRT) could be discussed. The aim of this retrospective study is to evaluate the outcomes according to the timing of SRT during the course of the disease.
Materials and Methods
all patients receiving SRT for BM of a lung cancer were included in the study, except those receiving whole brain radiotherapy (WBRT). We defined three groups of patients, according to the timing of SRT: L1 for those receiving SRT during the first line of medical treatment, L2 during the second line and L3 for others line. We analyzed local control of the treated metastases (LC), occurrence of new BM and overall survival (OS). For the two last variables, we calculated the probability of event from the date of SRT and from the first day of medical treatment (D1L1).
Results
109 patients were included in the study and 102 evaluable for all parameters. LC did not differ if SRT was performed during L1, L2 or L3. Occurrence of new BM is delayed when SRT is performed in L1 and the initial point the time of SRT, but this difference disappeared when the probability of new BM is calculated from D1L1. No difference in OS was observed according to the timing of SRT.
Conclusion
this study underlines the important role of medical treatment to prevent new BM. In view of our results, SRT could be delayed if the medical treatment has a good probability of controlling BM progression.
Feature Engineering Impact on Position Falsification Attacks Detection in Vehicular Ad-Hoc Network
Authors: Abdelkreem Eslam , Hussein Sherief , Tammam Ashraf 
Published: August 2023

Abstract
The vehicular ad-hoc network (VANET) is a technology that enables vehicles to interact with each other and with the surrounding infrastructure. This technology aims to enhance road safety and alleviate traffic congestion. However, it is susceptible to various security attacks and concerns. Among these concerns, the position falsification attack is regarded as one of the most serious, in which, the malicious nodes tamper with their transmitted location. Thus, the development of effective misbehavior detection schemes capable of identifying such attacks is crucial. Many of these schemes employ machine learning techniques to classify vehicles based on the features of the exchanged information. Despite the relation between the performance of these systems and the features used to train them, the current understanding of this relation remains limited. In this paper, a comprehensive literature review is combined with a set of experiments to study the impact of feature engineering on the performance of position falsification attack detection in VANETs. The review is used to identify the key features and algorithms used in the literature. Then, various experiments were conducted using the VeReMi dataset, which is publicly available, and different machine learning algorithms to compare two feature sets: one comprising selected and derived features, and the other including all available features. The results of this study show a substantial improvement in the performance of the detectors achieved by employing feature engineering techniques, where the average accuracy of the experimented models is increased by 6.31% to 47.03% depending on the algorithm used.
Dynamical analysis and numerical simulation of a stochastic influenza transmission model with human mobility and Ornstein-Uhlenbeck process
Authors: Zhang Xinhong , Su Tan , Jiang Daqing 
Published: August 2023

Abstract
With the inevitable environmental perturbations and complex population movements, the analysis of troublesome influenza is harder to proceed. Studies about the epidemic mathematical models can not only forecast the development trend of influenza, but also have a beneficial influence on the protection of health and the economy. Motivated by this, a stochastic influenza model incorporating human mobility and the Ornstein-Uhlenbeck process is established in this paper. Based on the existence of the unique global positive solution, we obtain sufficient conditions for influenza extinction and persistence, which are related to the basic reproduction number in the corresponding deterministic model. Notably, the analytical expression of the probability density function of stationary distribution near the quasi-endemic equilibrium is obtained by solving the challenging Fokker–Planck equation. Finally, numerical simulations are performed to support the theoretical conclusions, and the effect of main parameters and environmental perturbations on influenza transmission are also investigated.
Integrated Solid Waste Management for Closed Community: An Experiment on Jahangirnagar University Campus
Authors: Hossain Md. Jakir , Mahmud Md. Munir , Moinuddin Golam 
Published: August 2023

Abstract
This study examines community participation in integrated solid waste management (ISWM) at Jahangirnagar University in Bangladesh. The university faces significant challenges in waste management, with negative social, environmental and economic consequences. The goal is to identify barriers to community involvement in ISWM and provide recommendations for enhancing engagement. The research uses a mixed-methods approach, surveying 397 respondents using cluster random sampling from the university's population of 20,000. Data collection methods include interviews, observations, focus groups, and document analysis. The findings highlight obstacles to community participation, such as limited community empowerment, mobilization, organization, and resource coordination. Household waste segregation is practiced by only 30% of respondents. However, 74% of participants express willingness to oversee door-to-door waste collection and dispose of waste at designated points, influenced by socioeconomic factors. Non-compliance with ISWM regulations is observed in 26% of respondents, and 12% lack sufficient knowledge about ISWM, indicating a need for improved organization and coordination. Additionally, some university authorities rely on outdated methods, resulting in weak enforcement of environmental regulations. Ineffective policies exacerbate the situation, failing to align with the market economy. The study recommends fostering cooperation between university authorities and the community, revising and enforcing regulations, and emphasizing waste generators' responsibility for proper disposal. Addressing these challenges can significantly improve solid waste management and environmental outcomes at Jahangirnagar University.
Integrating Optimized Item Selection with Active Learning for Continuous Exploration in Recommender Systems
Authors: Kadioglu Serdar , Kleynhans Bernard , Wang Xin 
Published: August 2023

Abstract
Recommender Systems have become the backbone of personalized services that provide tailored experiences to individual users, yet designing new recommendation applications with limited or no available training data remains a challenge. To address this issue, we focus on selecting the universe of items for experimentation in recommender systems by leveraging a recently introduced combinatorial problem. On the one hand, selecting a large set of items is desirable to increase the diversity of items. On the other hand, a smaller set of items enables rapid experimentation and minimizes the time and the amount of data required to train machine learning models. We first present how to optimize for such conflicting criteria using a multi-level optimization framework. Then, we shift our focus to the operational setting of a recommender system. In practice, to work effectively in a dynamic environment where new items are introduced to the system, we need to explore users' behaviors and interests continuously. To that end, we show how to integrate the item selection approach with active learning to guide randomized exploration in an ongoing fashion. Our hybrid approach combines techniques from discrete optimization, unsupervised clustering, and latent text embeddings. Experimental results on well-known movie and book recommendation benchmarks demonstrate the benefits of optimized item selection and efficient exploration.