bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epac1 increases myosin regulatory light-chain phosphorylation, energetic cost of contraction, and susceptibility to heart failure
Authors: Ohnuki Yoshiki , Suita Kenji , Ishikawa Misao , Mototani Yasumasa , Nariyama Megumi , Ito Aiko , Matsuo Ichiro , Hayakawa Yoshio , Morii Akinaka , Kiyomoto Kenichi , Tsunoda Michinori , Mitsubayashi Takao , Saeki Yasutake , Ishikawa Yoshihiro , Okumura Satoshi 
Published: September 2024

Abstract

β-Adrenergic receptor (β-AR) stimulation of the heart, leading to increased cardiac output, is mediated by cyclic AMP (cAMP), which induces protein kinase A (PKA)-mediated phosphorylation of the myofilament proteins troponin I (TnI) and myosin binding protein-C (MyBP-C). The aim of this study was to investigate the contribution of the exchange protein activated by cAMP (Epac1), a PKA-independent cAMP effector, to the response of cardiac myofilaments to β-AR stimulation. The calcium sensitivity of force and ATPase activity, and the tension cost (ATPase activity/force) were significantly greater in skinned myocardium from transgenic mice specifically overexpressing Epac1 in the heart (Epac1TG) and wild-type (WT) mice treated with 8CPT-AM, an Epac-selective cAMP analogue, as compared with non-transgenic (NTG) or control mice, respectively. In addition, myosin regulatory light chain (RLC) phosphorylation was significantly greater in Epac1TG and WT mice treated with 8CPT-AM than in NTG or control mice via phospholipase C/phosphokinase C, without any change in the phosphorylation of TnI or MyBP-C. We also examined the effects of chronic β-AR stimulation on cardiac function in Epac1TG. The left ventricular ejection fraction was significantly decreased from baseline in both NTG and Epac1TG after isoproterenol infusion (60 mg/kg/day for 1 week), but the magnitude of the decrease was much greater in Epac1TG. Our results suggest that Epac1 activation might induce an imbalance between force-generating capacity and ATPase activity in skinned myocardium. This could increase oxygen consumption and the energetic cost of contraction in living myocardium under conditions of chronic β-AR stimulation, leading to the development of heart failure.
An Innovative Method to Deal with the Spread of Aedes albopictus in the Urban Centers of Alessandria used by Citizen
Authors: Talbalaghi Asghar , Abbasi Ebrahim , Hassandoust Sahar 
Published: September 2024

Abstract

Studies have demonstrated that Aedes albopictus thrives in micro-breeding sites predominantly on private properties, including abandoned containers and manholes used for rainwater and irrigation. This study investigates an innovative methodology, the TombiniNet, to mitigate the proliferation of Aedes albopictus by engaging citizens in the active management of micro-breeding sites on their properties. Researchers conducted a comprehensive survey and analysis of Aedes albopictus micro-breeding sites on private and communal properties. The study identified that up to 70% of micro-breeding sites for Aedes albopictus in northern Alessandria were located on private properties. Citizen participation was critical to the success of the intervention, with a marked decrease in the number of adult tiger mosquitoes observed in areas where residents actively managed breeding sites using the TombiniNet. The TombiniNet was particularly effective in private areas, as residents could regularly maintain it, preventing debris accumulation that could hinder drainage. The findings highlight the importance of engaging citizens in mosquito control programs to manage Aedes albopictus populations in urban areas effectively. The TombiniNet intervention demonstrated that a simple, cost-effective solution could significantly reduce mosquito breeding sites on private properties.
Elementary School Teachers' and Counselors’ Decisions on Referring Students for Evaluation: The Impact of ADHD Traits, Achievement, and Giftedness
Authors: Tamsut Avital 
Published: September 2024

Abstract

The present study examined the effect of ADHD-related traits, academic-achievement level, and giftedness label on elementary school teachers’ and counselors’ referral recommendations for assessment. 532 teachers and counselors were presented with one of 12 vignettes describing a hypothetical pupil. Participants were asked to report the likelihood they would refer the pupil for ADHD diagnosis and address them during a high-level interdisciplinary school-team meeting (HISTM). High ADHD-related traits (effect size 0.359) and low academic-achievement (effect size 0.070) and their interaction were significantly related to higher likelihood of referral. Further analysis revealed that lower academic achievement was related to higher likelihood of referral only when ADHD-related traits were not indicated (p < .005). Status of giftedness label was not found to be significant (p > .05). These findings indicate that mainly ADHD-related traits and to a lesser degree low academic-achievement, influence teachers' decisions to refer pupils for ADHD diagnosis and address them in HISTM.
A bi-level optimization model and hybrid evolutionary algorithm for wind farm layout with different turbine types
Authors: Erping Song 
Published: September 2024

Abstract

In order to reduce the influence of wake effect between wind turbines under complex terrain in wind farm layout, it is feasible to adopt a deployment scheme of multiple types of wind turbines to maximize the benefits. In this paper, both the cost function and the output power of the wind farm are considered, where the cost functions include of different diameter, hub-height, and types of wind turbines. Therefore, a mode of bi-level constrained optimization is established, where decision variable at the upper-level is the deployment of wind turbine type, and decision variable at the lower-level is the deployment of wind turbine micro-location. Then, according to the characteristics of the decision variables, a hybrid algorithm based on genetic algorithm and differential evolution is proposed, and the above evolution operations and parameter values are improved to improve the performance of the algorithm. Finally, the feasibility of the proposed scheme is verified by extensive simulations.
High-Throughput Discovery of Ferrocene Mechanophores with Enhanced Reactivity and Network Toughening
Authors: Kulik Heather , Kevlishvili Ilia , Vakil Jafer , Kastner David , Huang Xiao , Craig Stephen 
Published: September 2024

Abstract

The concept of the mechanophore1 was only established in the past two decades, during which time their discovery and study have led to new insights and opportunities in fundamental chemical reactivity2, imaging3, drug delivery4, and molecularly guided material properties5,6. Despite many successes in mechanophore design, the plausible design space in the field still far exceeds what has been realized synthetically. For example, ferrocenes are particularly attractive targets as mechanophores due to their combination of high thermal stability and mechanochemical lability.7,8 However, the handful of demonstrated ferrocene mechanophores is sparse7–9 in comparison to several thousands of unique ferrocene complexes that have been synthesized. Herein, we report computational, machine learning guided discovery of synthesizable ferrocene mechanophores. We identify over one hundred potential target ferrocene mechanophores with wide-ranging mechanochemical activity and use data-driven computational screening to identify a select number of promising complexes. We highlight design principles to alter mechanochemical activation of ferrocenes, including regio-controlled transition state stabilization through sterically bulky groups and a change in mechanism through non-covalent ligand–ligand interactions. The computational screening is validated experimentally both at the polymer strand level through sonication experiments and at the network level by mechanical testing. These experiments indicate that a computationally discovered ferrocene mechanophore cross-linker leads to greater than 4-fold enhancement in material tearing energy. We expect the computational approach to serve as a blueprint for high-throughput discovery in other families of mechanophores by providing fundamental insights into mechanically coupled reactivity, supporting the elucidation of mechanophore-to-material structure–activity relationships, and leading to polymer networks with new combinations of desired material properties.
Influence of soil salinity on the structural attributes and aboveground biomass carbon in a mangrove community of Mallorquin swamp in Barranquilla, Colombia
Authors: Rodriguez-Reales Rodrigo Rafael , Gómez Juan Pablo , Bohórquez-Herrera Jimena , Martínez-Habibe María C. 
Published: September 2024

Abstract

Recent studies suggest that mangrove forests have an exceptional capacity of capturing and storing carbon. However, the relationship between this ecosystem service and environmental factors is less studied. Here, we evaluate how environmental conditions influence tree community composition and carbon storage in Mallorquin swamp, an urban mangrove ecosystem in Barranquilla, Colombia. We measured mangrove tree community composition, vegetation structure, soil pH and salinity in 18 circular plots located in areas with Low, Medium, and High salinity. Using published allometric equations and wood density database, we estimated total aboveground biomass. Our results show significant soil salinity differences among the sampling areas, especially during the dry season. Nonetheless, we found small differences in soil pH across stations regardless of the season. Avicennia germinans was mostly associated with Low salinity areas, Laguncularia racemosa with Medium salinity areas, and Rhizophora mangle in High salinity areas. Observed differences in tree height, abundance, and vertical structure were noteworthy, with the Low salinity area hosting significantly taller and bigger trees and a larger carbon stock. Carbon stock estimates were 4098.6 Mg C for Low, 104.6 Mg C for Medium, and 1761 Mg C for High salinity areas. These findings highlight the significance of local environmental factors in mangrove conservation efforts, particularly in urban areas like Barranquilla; contributing to our understanding of the relationship between mangrove ecosystems and carbon cycling; emphasizing the need for targeted conservation efforts to protect these vital coastal habitats.
Physics of transport in the oligohaline reach of the Delaware Estuary
Authors: Duzinski Philip J , Chant Robert 
Published: September 2024

Abstract

A study of transport mechanisms in the oligohaline reach of the Delaware Estuary examines several locations with rapid changes in cross-sectional area that increase the horizontal salinity gradient, the exchange flow, and the upstream salt flux. This study is motivated by the proximity of municipal drinking water intakes upstream of the oligohaline range of the estuary, which can advance to just below the City of Philadelphia during low flow events. A Regional Ocean Model System (ROMS) numerical model was used to analyze the potential mechanisms of dispersion in the tidal Delaware River. While the model domain is largely within the tidal-fresh upper estuary, the domain below Philadelphia becomes oligohaline during low-flow events. Results found that landward transport of salt is facilitated by a combination of steady vertical shear dispersion and tidal oscillatory salt flux, with the latter becoming increasingly important approaching the upstream extent of salt intrusion. Frontogenesis is also an important intrusion mechanism in the vicinity of specific bathymetric features. Moreover, the tidal advection of these fronts produces strong lateral gradients that drive secondary flows and produce stronger tidal oscillatory salt flux away from the regions of frontogenesis.
WITHDRAWN: Ethylene-induced postharvest changes in five Chinese bayberry cultivars affecting the fruit shelf life and quality preservation
Authors: Saeed Mostafa , Zhao Lan , Rashwan Ahmed K. , Osman Ahmed I. , Chen Zhuyun , Wang Guoyun , Zhou Chaochao , Tu Ting , Alabd Ahmed , Jiao Yun , Gao Zhongshan 
Published: September 2024

Abstract

The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
Towards a Minimum Universal Features Set for IoT DDoS Attack Detection
Authors: Ebrahem Osama , Dowaji Salah , Alhammoud Suhel 
Published: September 2024

Abstract

Dimensionality reduction is one basic and critical technology for data mining, especially in current “big data” era. It is the process of reducing the number of features (or dimensions) in a dataset while retaining as much information as possible. This can be done for a variety of reasons, such as to reduce the complexity of a model, to improve the performance of a learning algorithm, or to make it easier to visualize the data. Motivated from aforementioned reasons, this paper proposed a new feature reduction approach which reduce and weight the most important features from of universal features set to fit the big data analytics on IoT based cybersecurity systems. The minimal number of features are chosen by using feature selection methods (ANOVA, Variance Threshold, Information Gain, Chi Square) which performed with two files from IoT-23 dataset. According to the approach, we divided the universal features into several subgroups, and evaluated the performance of ML Algorithms (NB, KNN, RF, LR). Extensive experiments are performed with the CICIDS2017 dataset to validate the effectiveness of the proposed approach. As a result, the Random Forest algorithm was the best in terms of performance, as the lowest value of all metrics (Accuracy, Precision, Recall, F1-Score) we obtained was 95%, except for the case in which we used features that we assumed were the least important feature subset. The proposed approach reduced the number of features to only two features and achieved high results.
White Blood Cell-to-Haemoglobin Ratio as a Predictor of 30-Day Mortality in ICU Patients with Pulmonary Hypertension: Analysis of the MIMIC-IV Database
Authors: Li Shuangping , Huang Shenshen , Feng Yuxuan , Mao Yimin 
Published: September 2024

Abstract

The white blood cell-to-haemoglobin ratio (WHR) is a comprehensive indicator of inflammation and anaemia status. However, the relationship between the WHR and the risk of 30-day mortality among intensive care unit (ICU) patients with pulmonary hypertension (PH) remains unclear. The purpose of this study was to investigate the association between the WHR and 30-day mortality in critically ill patients with PH. Clinical data of patients with PH were extracted from the MIMIC-IV (2.2) database. Restricted cubic splines and logistic regression analysis were used to investigate the relationship between the WHR and 30-day mortality. Subgroup analysis was used to assess the robustness of the results. The predictive model was constructed based on the logistic regression results. A total of 451 patients with PH were enrolled, with 78 (17.3%) dying within 30 days. Restricted cubic spline analysis revealed a linear relationship between the WHR and 30-day mortality. The WHR was an independent predictor for 30-day mortality in PH patients (OR, 1.58; 95% CI, 1.05–2.37; P = 0.028). The AUC of the WHR was 0.646 (95% CI: 0.60–0.69). Subgroup analyses revealed no significant interaction effect of the WHR on each subgroup (P for interaction: 0.134–0.942). A predictive model including the WHR, sepsis status, age, anion gap, respiratory rate and Charlson Comorbidity score had high predictive value for 30-day mortality in PH patients [AUC 0.8 (95% CI: 0.74–0.86)].
HIV-related misinformation, testing, and disclosure among selected urban dwellers in Uganda; a cross-sectional survey
Authors: Nakalembe Doreen , Tamale Bridget Nagawa , Kyomugisha Trinah , Nalugya Aisha , Galiwango Jovan , Nakiggala Joana , Oputan Patience , Wejuli Junior Mike , Ndibalekera Joselyn , Isunju John Bosco , Mugambe Richard K. , Ssekamatte Tonny , Bukenya Justine 
Published: September 2024

Abstract

Background
In Uganda, urban centers face a high prevalence of HIV, exacerbated by misinformation, low testing rates, and non-disclosure of HIV status. However, evidence on the prevalence and determinants of HIV-related misinformation, testing, and disclosure within these urban centers remains limited. This study assessed the prevalence of HIV testing, misinformation, and non-disclosure in selected urban centers of West Nile, Eastern and Northern Uganda to inform targeted interventions aimed at improving HIV awareness, increasing the uptake of HIV testing services, and facilitating disclosure.
Methods
A cross-sectional study was conducted among 930 households in five urban centres in Uganda. A multistage sampling technique was employed in the selection of participants. A digitized structured questionnaire preloaded on the KoboCollect mobile application. Data were downloaded in Microsoft Excel and exported into Stata version 14 for statistical analysis. Modified Poisson regression was used to determine the factors associated with the outcome variables.
Results
About 93.2% of respondents were misinformed about HIV, 20.8% had not disclosed their HIV status, and 3.3% had never been tested for HIV. Having a primary level of education (PR:0.96, 95% CI:0.93–0.99, p = 0.035) and spending more than 6 years in the area (PR: 1.05, 95% CI:1.00-1.10, p = 0.029) were associated with “HIV-related misinformation.” Being knowledgeable about some special drugs that a doctor or a nurse could give to a woman infected with the HIV/AIDs virus to reduce the risk of transmission to the baby (PR:1.03, 95% CI:1.00-1.07, p = 0.024) was associated with “HIV testing”. Being married (PR:0.89, 95% CI:0.65 − 0.12, p < 0.001 was associated with “non-disclosure” of HIV status.
Conclusion
A high proportion of respondents were misinformed about HIV/AIDS, although the majority had been tested and disclosed their serostatus to partners. HIV/AIDS-related misinformation was associated with having a primary education and residing in the area for more than six years. Additionally, knowledge of special medications that healthcare providers can give to women with HIV to reduce the risk of transmission to their babies predicted HIV testing. Disclosure of HIV status was more common among those who were married or widowed. This study suggests the need for intentional educative interventions with clear and correct HIV/AIDs messages to improve knowledge, increase testing, and facilitate the disclosure of HIV status.
An Edge-Based Neural Network Architecture for Instance Segmentation in Machining Feature Recognition
Authors: Li Yang , Mann Stephen , Li Eugene , Bedi Sanjeev , Lenover Michael 
Published: September 2024

Abstract

Recent advances in the field of artificial intelligence have yielded promising results with regards to the prospect of automating the task of machining feature recognition (MFR). Popular among the proposed methods for MFR are learning-based methods using deep neural networks, which have achieved impressive results. However, the real-world applicability of learning-based methods for MFR is hindered by the amount of data required to train such methods. We propose the Edge Adjacency Graph Instance Segmentor (EAGIS), a graph neural network that uses a graph-based data structure representing the topological and geometric relationships of edges in a boundary representation model to identify the machining features within the input 3D model of a component. Evaluation of EAGIS is performed on the open-source MFInstSeg dataset. Designed to be incorporated into larger autonomous CNC machining pipelines, the main benefit of EAGIS over existing approaches for instance segmentation is that EAGIS requires fewer samples to train to competency.
SILTD: Structural Information for LLM-generated Text Detection
Authors: Yang Jing , Wang Shi , Zi Kangli , Sun Yanshun , Huang Yuwei , Luo Tianyu 
Published: September 2024

Abstract

The rapid development of large language models (LLMs) has significantly improved the quality and diversity of AI-generated content(AIGC). LLMs-generated text detection plays an important role in preventing the harmful misuse of large language models. Although many detection methods have been proposed, they all have room for improvement and lack generality when detecting multiple models. To tackle these drawbacks, an unsupervised-based Structural Information for LLM-generated Text Detection(SILTD) method is proposed. First, we construct a multi-relational text graph based on the similarity of text features, which aims to model the intricate similarities and correlations between texts in the generative statistical space. Second, we propose a novel unsupervised graph clustering method. The multi-relational graph is transformed into an encoding tree, which is then optimized based on a two-dimensional structure entropy minimization algorithm to achieve hierarchical clustering of texts. Structural entropy minimization enables achieving high-quality clusters, by measuring the uncertainty of random walks within the graph. Finally, we introduce a new method that measures text similarity and computes the intensity of text aggregation within each cluster, to perform in-cluster label inference. Extensive experiments show that, compared to baseline methods, our approach is more effective and generalizable in detecting six popular LLMs across three datasets.
Meta-Analysis Study: The Relationship Between Nutritional Status And Physical Fitness
Authors: Akkase Arfandi , Husnul Darul , Sulaeman Sulaeman , Wahid Wahyana Mujari , Jayadilaga Yadi 
Published: September 2024

Abstract

Physical fitness refers to a person's ability to perform daily activities energetically and efficiently without experiencing excessive fatigue. Various kinds of research on physical fitness have been conducted and one of them is that nutritional status has a relationship in determining a person's degree of physical fitness. This meta-analysis study research aims to examine the relationship between nutritional status and physical fitness. Researchers reviewed 15 journal studies related to nutritional status and physical fitness in the last 8 years with a total of 584 respondents. The results of this meta-analysis study showed a medium effect size correlation of r=0.438 (95%CI = 0.319.0.557). The results of the analysis showed that the 15 effect sizes of the studies analyzed were heterogeneous (Q = 25.267; 0.032 <0.05) so this analysis used a random effect sizeI. These results indicate that nutritional status has a moderate effect on physical fitness, suggesting that there are other variables that have a correlation value to physical fitness.