bluuebunny/crossref_metadata_2025_split huggingface dataset:
Source Apportionment and Ecological Risk of Heavy Metals in Taihu Lake from 2020 to 2022
Authors: Bao Guangjing , Zhao Hongrun , Ji Chao , Hou Dawei , Deng Aiping , Li Fazhi 
Published: August 2024

Abstract

To determine the source apportionment and ecological risk of heavy metals in water from a spatiotemporal perspective, the 7 samples were monitored from 2020 to 2022 in Taihu Lake. The correlation analysis and principal component analysis were employed to identify the sources of heavy metals, and the temporal and spatial characteristics of ecological risk were analyzed using the Mann-Kendall test, mean gravity center, and standard-deviation ellipse. The results indicated an increase in median concentration of heavy metals in the following order: Cd < Pb < Hg < Cu < As < Ni < Zn, These metals were primarily derived from industrial and agricultural activities. Overall, the ecological risks posed by heavy metals were deemed acceptable, with the exception of Hg, which showed considerable potential ecological risk. Furthermore, the potential ecological risk exhibited a significant decreasing trend, with Z-values passing the 95% confidence interval significance test, except for S3. The mean gravity centers of the potential ecological risk were located within an ellipse with center coordinates of (120.2553, 31.3718), major axis of 44525m, minor axis of 28225m, and a direction of 0.4463°. This study contributes to the enrichment of research perspectives for ecological risk and provides valuable insights for the development of mitigation strategies for heavy metals in Taihu Lake.
Optimizing Smart Home Task Scheduling with the Octopus Adaptive Intelligence Algorithm in Fog Computing
Authors: BHAKHAR RUCHIKA , Chhillar Rajender Singh 
Published: August 2024

Abstract

The integration of fog computing within the Internet of Things (IoT) ecosystem necessitates advanced solutions for optimizing task scheduling to enhance responsiveness and resource utilization effectively. Traditional methods often struggle to dynamically adapt to the fluctuating demands of fog computing environments, particularly in minimizing latency and optimizing energy consumption. This paper introduces the Octopus Adaptive Intelligence Algorithm (OAIA), a novel approach inspired by the highly adaptive behaviors of octopuses. OAIA dynamically adjusts task allocations based on real-time changes in environmental conditions and workloads, aiming to optimize resource utilization and reduce response times. The innovation of OAIA lies in its flexible, condition-responsive mechanism that allows for continuous tuning of scheduling parameters in response to varying task demands and node capacities. This adaptive capability ensures the rapid processing of latency-sensitive tasks by utilizing the proximity of fog nodes and efficiently manages latency-tolerant tasks within the cloud. The performance of OAIA was rigorously evaluated through a series of controlled simulations within a fog computing environment, examining its response to different variables such as the number of tasks, fog nodes, cloud nodes, and the maximum number of iterations. Empirical results from these simulations demonstrate that OAIA not only effectively handles increasing complexities and adapts to varied resource distributions but also significantly improves fitness scores—indicative of enhanced latency, energy consumption, and resource utilization—compared to traditional scheduling strategies. Our comparative results reveal that OAIA consistently outperforms established algorithms such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) in achieving lower fitness values, indicative of more efficient task management. These findings underscore the potential of adaptive algorithms in efficiently managing the complex and variable demands of fog computing systems, setting the stage for future advancements in intelligent task scheduling for IoT environments. This study paves the way for further exploration into adaptive and intelligent solutions that can cater to the nuanced needs of modern fog computing frameworks, enhancing their efficacy and applicability across diverse real-world applications.
Microstrip plastic scintillating detector system for quality assurance in synchrotron microbeam radiotherapy
Authors: Thevenet Florian , Keshmiri Sarvenaz , Degouttes Jerome , Livingstone Jayde , Lu Guo-Neng , Adam Jean-François , Pittet Patrick 
Published: August 2024

Abstract

Synchrotron microbeam radiotherapy (MRT), which has entered the clinical transfer phase, requires the development of appropriate quality assurance (QA) tools due to very high dose rates and spatial hyperfractionation. A microstrip plastic scintillating detector system with associated modules was proposed in the context of real-time MRT QA. A prototype of such a system with 105 scintillating microstrips was developed and tested under MRT conditions. The signal obtained from each microstrip when irradiated was reproducible, linear with the dose, and independent of both the dose rate and the beam energy. The detector prototype was capable of measuring an entire 52-microbeam field in real time and exhibited outstanding radiation hardness. It could withstand more than 100 kGy absorbed dose, which is at least ten times higher than the doses reported in the literature for plastic scintillators before deterioration. The potential of this detector system in MRT QA was demonstrated in this study.
An In Vitro Study Evaluating The Intrarenal Pressure During RIRS of Suction Ureteral Access Sheath Versus Traditional Sheath
Authors: Liu Shusheng , Zhang Guanghan , Chai Chu ann , Limudomporn Pasin , Liu Weijie , Zhong Jian , Pang Xuliang , Ai Guoyao , Huang Zhicong , Zeng Guohua , Zhu Wei 
Published: August 2024

Abstract

Introduction: Flexible ureteroscopy (fURS) is widely recognized as an effective treatment for ureteral or renal stones. The used of flexible urinary endoscopy provides an effective treatment for ureteral stones, and the development of vacuum suction ureteral access sheaths has significantly improved the stone clearance rate. Our experimental aim is to prove the effectiveness of negative suction ureteral access sheath on decreasing intraluminal pressure in various settings, utilizing by stimulating an in vitroflexible ureteroscope model. Methods: An 8.6Fr disposable flexible ureteroscope was used to measure intraluminal pressure through a manufactured silicone urinary model using 3D printing technology. We conducted on three settings use of ureteral access sheaths (UAS), which are (1) conventional UAS, (2) negative pressure suction sheath with an open vent, and (3) negative pressure suction sheath with a fully closed vent. Intrarenal pressure and irrigation flow rate were recorded on various sizes of UAS under irrigation pressures ranging from 10 to 240 mmHg. Results: Under different infusion pressure conditions, the negative pressure sheath with an opened vent demonstrated marginally lower intraluminal ureteral pressure than the traditional sheath, but this difference was not statistically significant (P = 0.56). In contrast, when employing the closed vent method, the negative pressure aspiration sheath shwed a notably significantly distinct intraluminal pressure change from the traditional sheath and its opened vent mode (P < 0.01). Additionally, The choice of ureteral sheath size profoundly impacted intraluminal pressure; larger sheath sizes were associated with more reduced pressure levels under the same infusion pressure (P < 0.01). Conclusions: In ureteroscopy procedures, the intraluminal pressure in the ureter increases with the rise in irrigation pressure. However, applying negative pressure with a closed vent can effectively reduce the intraluminal pressure.
Enhancing Code Security with CodeSheriff: A Multi-Language Vulnerability Scanner
Authors: M Aravind , SD Kausal , G Saranya , Jamal Sajjad shaukat , Aljaedi Amer , Alblehai Fahad 
Published: August 2024

Abstract

Securing code has become a significant challenge in software development due to cyber threats. Identifying vulnerabilitiesduring development is crucial to reduce security risks. The solution, Codesheriff, is a Telegram bot that scans for vulnerabilitiesautomatically. Codesheriff uses a fastText model trained on the Rosetta Code dataset to detect programming languagesprecisely and employs customized models for detecting vulnerabilities in C, C++, Python, Java, PHP, and JavaScript. Itsperformance is measured against tools like Veracode and Fortify using various metrics. Experiments show Codesheriffachieved precision rates of 93.6% for Python, 93.5% for C/C++, 94.5% for Java, 91.8% for PHP, and 92.4% for JavaScript,demonstrating its robustness and practicality in secure code development.
The motivations, interests and concerns of prospective peer leaders of nature-based mental health interventions
Authors: Reeves Jonathan P. , Freeman Will , Patel-Calverley Raksha , Newth Julia L. , Plimpton Ben 
Published: August 2024

Abstract

BackgroundThere is renewed, cross-sectoral interest in nature's contributions to health and how they can be maximised for public and planetary health. Current enquiry is focused on practicalities and what strategies and collaborations are needed to operationalise the nature-health relationship for both people and the environment. Nature-based health interventions (NBIs), especially those within the framework of nature-based social prescribing (NBSP), show promise. However, in the UK, there are limitations to initiating and scaling activities due to issues like: navigating multi-stakeholder partnerships, building a work force and sustaining the provision. The short ‘course’, finite format of NBSP programmes also creates a ‘what next’ moment for participants despite willingness and interest from many participants in peer leadership type activity i.e. offering social support and leadership to help others in their community to partake in nature-based health activities.
Aim: To explore peer-led community delivery options for NBIs with prospective peer leaders.
Method: We recruited seventeen study participants for a daylong workshop exploring motivations, activities and perceived challenges of prospective peer leaders of NBIs. The study participants had a) been through, or supported delivery/participation of, a UK wetland-based NBSP programme for poor mental health and b) expressed an interest in peer leadership activities. The data underwent reflexive thematic analysis.
Results.Motivations of prospective peer leaders to offer nature-based health activities related to the promotion of personal and community wellbeing through learning, sharing nature experiences, creating social connections, and through interests in facilitating a wide range of nature-based and salutogenic activities (e.g. arts/creative, conservation, nature appreciation, mental wellbeing activities). Concerns from peer leaders centred on the practicalities of establishing and safely delivering nature-based activity, on the personal competencies required to deliver NBIs, nervousness with the medicalised nature of social prescribing, and on resource needs for delivery; the latter highlighted the importance of local nature provision for community-led NBI delivery.
Conclusions: Community-led NBIs offer potential to broaden public health options, but community concerns need to be addressed first. There is a role for allied NGO organisations, or social prescribing networks, to share resources and support communities and prospective peer leaders to overcome these concerns.
Detecting departures from the conditional independence assumption in diagnostic latent class models: A simulation study
Authors: Okkaoglu Yasin , Welton Nicky J , Jones Hayley E 
Published: August 2024

Abstract

Background
Latent class models can be used to estimate diagnostic accuracy without a gold standard test. Early studies often assumed independence between tests given the true disease state, however this can lead to biased estimates when there are inter-test dependencies. Residual correlation plots and chi-squared statistics have been commonly utilized to assess the validity of the conditional independence assumption and, when it does not hold, identify which test pairs are conditionally dependent. We aimed to assess the performance of these tools with a simulation study covering a wide range of scenarios.
Methods
We generated data sets from a model with four tests and a dependence between tests 1 and 2 within the diseased group. We varied sample size, prevalence, covariance, sensitivity and specificity, with 504 combinations of these in total, and 1000 data sets for each combination. We fitted the conditional independence model in a Bayesian framework, and reported absolute bias, coverage, and how often the residual correlation plots, G2 and χ2 statistics indicated lack-of-fit globally or for each test pair.
Results
Across all settings, residual correlation plots, pairwise G2 and χ2 detected the correct correlated pair of tests only 12.1%, 10.3%, and 10.3% of the time, respectively, but incorrectly suggested dependence between tests 3 and 4 64.9%, 49.7%, and 49.5% of the time. We observed some variation in this across parameter settings, with these tools appearing to perform more as intended when tests 3 and 4 were both much more accurate than tests 1 and 2. Residual correlation plots, G2 and χ2 statistics identified a lack of overall fit in 74.3%, 64.5% and 67.5% of models, respectively. The conditional independence model tended to overestimate the sensitivities of the correlated tests (median bias across all scenarios 0.094, 2.5th and 97.5th percentiles − 0.003, 0.397) and underestimate prevalence and the specificities of the uncorrelated tests.
Conclusions
Residual correlation plots and chi-squared statistics cannot be relied upon to identify which tests are conditionally dependent, and also have relatively low power to detect lack of overall fit. This is important since failure to account for conditional dependence can lead to highly biased parameter estimates.
Effect of high temperature on two major stored product insects and the effect on germination of cowpea seeds (Vigna unguiculata L.)
Authors: AL-Huqail Arwa , Alkot Walaa M. , El-Talpanty Doaa M. , Khalil Fatma Mohamed Ameen , Abouelatta Ahmed , Omar Ahmed Fayez , Gharsan Fatehia N. , Alghamdi Tariq Saeed , Almozini Reem Nasser , Al-Harbi Nadi Awad , El‐Tokhy Ahmed I. , Abdelaal Khaled , Negm Eslam A. 
Published: August 2024

Abstract

Background
The importance of the control of stored product insects is highlighted with a loss of more than one billion dollars per year. The present study included one of the most important natural bioassay methods (the effect of high temperature) for controlling stored-product insects.
Results
In the current study, the range used for high temperature (45–80°C) influenced the criteria (% mortality of adults and immature stages, %hatchability, and % reduction): as well as the effect on % weight loss and % germination. The Complete mortality 100% of Callosobruchus maculatus was obtained with the treatment 55oC/40 minutes, 60oC/30 min, 65 oC/20 min, 70 oC/20 min., 75 oC/15 min and 80oC/5 min. The Complete mortality 100% of Rhizopertha dominica was obtained with the treatment 55oC/30 min, 60oC/25 min, 65 oC/20 min, 70oC/15 min, 75oC/10 min and 80oC/5 minutes. Furthermore, the temperature at 45oC/30 minutes, 55 oC/20 min, 60 oC and 65oC/15 min, 70oC and 75 oC/10 min and 80oC/5 min did not have any harmful effects on wheat grain and cowpea seed germination. All treatments were similar to the untreated control.
Conclusions
The application of temperature has no side effects on humans or on the environment. The best results were achieved with application of temperature at 45oC/30 minutes, 55 oC/20 min, 60 oC and 65oC/15 min, 70oC and 75 oC/10 min and 80oC/5 min without injurious effects on grain and seed germination.
Effect of the Supplementation of L-aspartic Acid, L-ascorbic Acid, and Silver Nanoparticles (AgNPs) to the In Vitro Fertilization (IVF) Media on the NMRI Mouse IVF Rates
Authors: Mohsennezhad Atefe , Jamshidvand Hadis , Goudarzi Sahar Moazami , Sahbafar Hossein , Mardaneh Jalal 
Published: August 2024

Abstract

Numerous lifestyle factors contribute to the incidence of infertility, which is a major concern for couples throughout the globe. The effectiveness of in vitro fertilization (IVF) is highly dependent on the characteristics of culture media used. The present research aimed to determine the effects of L-aspartic acid, L-ascorbic acid, and silver nanoparticles (AgNPs) on the success rate of IVF in NMRI mice. The solutions of L-aspartic acid, L-ascorbic acid, and synthesized silver nanoparticles (AgNPs) were prepared. The 6–8 weeks-old NMRI male mice were used as sperm donors, and 6–8 weeks-old NMRI mice were used for oocyte donation. In addition, the IVF procedure was performed in 50 µL drops of KSOM + 15%BSA under mineral oil. Seven different experimental groups were investigated in addition to the control group. Oocytes were exposed to sperm for 4–6 h in the KSOM medium as a control group. According to the results, the groups containing supplements "AgNPs", "L-aspartic acid", and "AgNPs + L-ascorbic acid" were not suitable for the 2PN stage. In contrast, the group containing "L-aspartic acid + L-ascorbic acid" was the best group for the 2PN stage. In addition, supplementation of the mixture of L-aspartic acid and AgNPs solutions in KSOM + BSA culture medium can be considered as the most suitable group for the 2Cell stage. Gaining knowledge on how particular additives affect the success rates of IVF may lead to the development of advanced compositions, which will enhance assisted reproductive technologies (ART) throughout time and improve the lives of infertile couples.
Non-specific yet selective interactions contribute to small molecule condensate partitioning behavior
Authors: Zhang Bin , Wang Cong , Kilgore Henry , Latham Andrew 
Published: August 2024

Abstract

Biomolecular condensates are essential in various cellular processes, and their misregulation has been demonstrated to be underly disease. Small molecules that modulate condensate stability and material properties offer promising therapeutic approaches, but mechanistic insights into their interactions with condensates remain largely lacking. We employ a multiscale approach to enable long-time, equilibrated all-atom simulations of various condensate-ligand systems. Systematic characterization of the ligand binding poses reveals that condensates can form diverse and heterogeneous chemical environments with one or multiple chains to bind small molecules. Unlike traditional protein-ligand interactions, these chemical environments are dominated by non-specific hydrophobic interactions. Nevertheless, the chemical environments feature unique amino acid compositions and physicochemical properties that favor certain small molecules over others, resulting in varied ligand partitioning coefficients within condensates. Notably, different condensates share similar sets of chemical environments but at different populations. This population shift drives ligand selectivity towards specific condensates. Our approach can enhance the interpretation of experimental screening data and may assist in the rational design of small molecules targeting specific condensates.
Research on the self-healing ability of polycystic ovarian syndrome (PCOS) in mice model and its impact on offspring
Authors: He Rui , Ma Cunling , Yu Leyi , Wu Xin , Xie Haibo , Yang Yuanyuan , Chen Xiaojiang , Liang Xiaoxia , Peng Qingjie , Huang Bincheng , Fan Shuzhe , Chen Hua , Chen Shensi , Li Guangyong 
Published: August 2024

Abstract

Polycystic ovarian syndrome (PCOS) is a prevalent metabolic endocrine disorder in reproductive-age women. This study aims to investigate the self-healing ability of PCOS and its potential impact on offspring. Methods: Female C57 BL/6J mice aged 4-5 weeks were administered letrozole (1 mg/kg/d) and a high-fat diet for 21 days to establish a PCOS model, and a control group was established. After modeling, the mice were divided into a PCOS model group and a self-healing group. After 14 days, the mice were mated, and the growth of their offspring was recorded. Subsequently, all mice were euthanized to collect serum, ovaries, and testes. The results showed that the self-healing group PCOS phenotype has shown improvement when compared to the model group. The findings from the offspring study indicate that all offspring in the model group died, while the self-healing group had offspring with a lower weight at 7 days and higher blood glucose levels. Additionally, the testicular morphology of male offspring in the self-healing group was poor. The conclusion drawn is that, after removing the pathogenic factors, the PCOS model group can self-heal. However, fertility remains impaired, which has an impact on their offspring.
Seeing more with less: Extensible Immunofluorescence (ExIF) accessibly generates high-plexity datasets by integrating standard 4-plex imaging data
Authors: Lock John , Gunawan Ihuan , Kohane Felix , Nguyen Kathy , Zheng Ye , Neumann Daniel , Vafaee Fatemeh , Meijering Erik 
Published: August 2024

Abstract

Standard immunofluorescence imaging captures just ~4 molecular markers (‘4-plex’) per cell, limiting dissection of complex biology. Inspired by multimodal omics-based data integration approaches, we propose an Extensible Immunofluorescence (ExIF) framework that transforms carefully designed but easily produced panels of 4-plex immunofluorescence into a unified dataset with theoretically unlimited marker plexity, using generative deep learning-based virtual labelling. ExIF enables integrated analyses of complex cell biology, exemplified here through interrogation of the epithelial-mesenchymal transition (EMT), driving significant improvements in downstream quantitative analyses usually reserved for omics data, including: classification of cell phenotypes; manifold learning of cell phenotype heterogeneity, and; pseudotemporal inference of molecular marker dynamics. Introducing data integration concepts from omics to microscopy, ExIF provides a blueprint empowering life scientists to use routine 4-plex immunofluorescence methods to achieve previously inaccessible high-plex imaging-based quantitative single-cell analyses.