bluuebunny/crossref_metadata_2025 huggingface dataset:
Physics of transport in the oligohaline reach of the Delaware Estuary
Authors: Duzinski Philip J , Chant Robert
Published: September 2024

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WITHDRAWN: Ethylene-induced postharvest changes in five Chinese bayberry cultivars affecting the fruit shelf life and quality preservation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

The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint.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

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

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

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

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

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

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.
Development and comparison of two 3D printed scaffolds of biosilica from marine sponges for bone tissue engineering
Authors: Santo Giovanna do Espirito , de Souza Amanda , Amaral Gustavo Oliva , Alqualo Amanda Sardeli , Sousa Karolyne dos Santos Jorge , Viegas Beatriz Louise Mendes , Prado João Paulo dos Santos , Santos Francisco Vieira dos , Correa Daniel Souza , Granito Renata Neves , Rennó Ana Claudia Muniz
Published: September 2024

This study compared the physicochemical characteristics and biological effects of two 3D printed biosilica (BS) scaffolds (grid and gyroid). Methods included Scanning Electron Microscopy (SEM), Micro-Computed Tomography (Micro-CT), Mass Loss and pH Assessment, Fourier-Transform Infrared Spectroscopy (FTIR), and Energy-Dispersive X-ray Spectroscopy (EDS). The mechanical evaluation involved a Compression Test, and in vitro tests used cell adhesion assays with osteoblastic (MC3T3-E1) and fibroblastic (L929) cell lines. SEM showed BS spicules in both models on day 0, with signs of degradation along the experimental periods of immersion, forming a homogeneous network with the interaction with alginate. Micro-CT revealed rough surfaces in both models, with the gyroid model being more homogeneous and porous, with larger pores compared to the grid model. The gyroid model demonstrated higher values in the compression test and a decrease in pH on the first day and no differences for both models on days 3, 7, and 14. The mass loss was higher in the gyroid model by day 21. FTIR tests showed characteristic peaks for ALG and BS. EDS detected silica (Si), chlorine (Cl), calcium (Ca), carbon (C), and oxygen (O). In cell adhesion assays, both models supported adhesion and proliferation of L929 and MC3T3-E1 cells, with the gyroid model showing better cell elongation and morphology. Overall, the gyroid model demonstrated superior physicochemical properties, greater mechanical strength, and enhanced biological performance compared to the grid model, making it more promising for tissue engineering applications.
A facile optical sensing strategy for glyphosate detection based on the structure-switching signaling aptamers
Authors: Liu Ziping , Wang Xin , Huang Xinru , Bai Edith , Zhao Yuhan , Liu Shasha
Published: September 2024

Herein, a facile optical sensing strategy for glyphosate (GLYP) detection is established with high specificity using structure-switching signaling aptamers. The specific structure-switching aptamers (F-SSSAs) with fluorescence signal reporting functionality were initially designed. It involves two domains: the FITC-labeled signal transduction domain that controls the fluorescence signal reporting, and the functional domain (specific structure-switching aptamers) that controls the target recognition as well as high affinity for graphene oxide (GO). In this strategy, GO works as a robust quencher for F-SSSAs in the absence of GLYP. However, the structure of F-SSSAs switched in the presence of GLYP, which prominently affected the interaction between F-SSSAs and GO. And the fluorescence of the structure-switching signaling aptamer-based sensing system subsequently restored. The present optical sensing strategy exhibited two dynamic linear relationships for GLYP detection within the range from 0.2 to 80 ng·mL− 1 and from 100 to 800 ng·mL− 1 respectively, with a low detection limit (LOD) of 0.07 ng·mL− 1. Significantly, the fluorescence-based sensing strategy was successfully utilized to detect GLYP in water, soil and rice with satisfactory outcomes, which suggested that it held potential applications prospect in monitoring GLYP.
Generalized subsampled Newton methods for optimization and its application
Authors: Moghaddam Ali Shahmoradi , Ketabchi Saeed
Published: September 2024

In this paper, we introduce a novel generalized subsampling Newton method designed to effectively address finite-sum optimization problems. This method is particularly effective for solving iterative techniques for solving a system of linear inequalities in the form of \(Ax \leq b\) and when the objective function is not necessarily twice differentiable. The implementation of this method significantly impacts increasing speed, saving resources, and optimizing system memory usage, thereby improving algorithm performance, especially on large-scale problems. The convergence of the mentioned method is proven under the conditions of convexity and Lipschitz continuity of the objective function's gradient. Preliminary numerical experiments on large-scale generated random problems and various datasets from the UCI benchmark data sets and Netlib repositories provide empirical evidence supporting our theoretical findings of the proposed method compared to similar methods.
A Machine Learning Approach for Forecasting the Efficacy of Pyridazine Corrosion Inhibitors
Authors: Trisnapradika Gustina Alfa , Akrom Muhamad , Rustad Supriadi , Dipojono Hermawan Kresno , Maezono Ryo , Diño Wilson Agerico
Published: September 2024

This paper presents a machine learning (ML) methodology grounded in quantitative structure-property relationship (QSPR) principles for the prediction of corrosion inhibition efficiency (CIE) values, specifically focusing on pyridazine inhibitor compounds. The training phase incorporates the kernel density estimation (KDE) function to generate virtual samples, aiming to enhance the prediction accuracy of the ML model. The study evaluates the performance of three models, namely gradient boosting (GB), random forest (RF), and k-nearest neighbor (KNN). The results exhibit a substantial enhancement in predictive ability following the incorporation of virtual samples. Specifically, coefficient of determination (R2) values for GB, RF, and KNN models increase from − 0.33 to 0.97, -0.20 to 0.96, and − 0.17 to 0.95, respectively, with the addition of 1000 virtual samples. Correspondingly, root mean square error (RMSE) values for each model experience a significant decrease, reducing from 9.20 to 1.57, 9.07 to 1.81, and 8.60 to 2.12., respectively. This augmentation enhances the correlation between features and targets, resulting in more accurate predictions and eliminating the necessity for feature selection. Furthermore, it implies resilience to model variations, eliminating the need for model selection. The proposed methodology is a crucial link between theoretical research and experimental synthesis, providing a reliable and accurate prediction tool. This tool proves instrumental in efficiently designing and exploring corrosion inhibitor candidates, thereby contributing to the advancement of effective corrosion inhibition strategies.
Exploring Intersections of Race and Disability in the context of Canadian Employment Support Systems through the Experiences of Job Seekers/Workers, Employers, and Service Providers
Authors: Grewal Eakam , Durocher Evelyne , Premji Stephanie , Gewurtz Rebecca
Published: September 2024

Purpose: Racism and ableism have impacts at individual and organizational levels and can produce and reproduce inequities and injustices in diverse contexts. However, their intersection remains largely unexamined in the provision of employment supports. The objective of this qualitative study is to identify barriers and facilitators within employment supports to seek strategies to improve the employment outcomes of racialized disabled job seekers and workers and address gaps faced by service providers and employers.Methods: This study used interpretive description (1). Four racialized disabled job seekers and workers, two employers and four service providers participated in semi-structured interviews. Thematic analysis (2) was used to analyze the data.Results: Five core themes were identified: 1) managing intersectional confusion; 2) employer education; 3) contextual barriers; 4) client-service provider relationships; and 5) urgency for solutions.Conclusion: This study provides grounding evidence about common concerns and barriers within existing employment support systems and can assist policymakers and service providers to better understand the complex and nuanced lived experiences of racialized disabled job seekers and workers.
Multi-sensor Fusion Simultaneous Localization and Mapping: A Systematic Review
Authors: Fan Zheng , Zhang Lele , Wang Xueyi , Shen Yilan , Deng Fang
Published: September 2024

Simultaneous Localization and Mapping (SLAM) is a crucial technology for intelligent unnamed systems to estimate their motion and reconstruct unknown environments. However, the SLAM system with merely one sensor has poor robustness and stability due to the defects in the sensor itself. Recent studies have demonstrated that SLAM systems with multiple sensors, mainly consisting of LiDAR, camera, and IMU, achieve better performance due to the mutual compensation of different sensors. This paper investigates recent progress on multi-sensor fusion SLAM. The review includes a systematic analysis of the advantages and disadvantages of different sensors and the imperative of multi-sensor solutions. It categorizes multi-sensor fusion SLAM systems into four main types by the fused sensors: LiDAR-IMU SLAM, Camera-IMU SLAM, LiDAR-Camera SLAM, and LiDAR-IMU-Camera SLAM, with detailed analysis and discussions of their pipelines and principles. Meanwhile, the paper surveys commonly used datasets and compares the effects of different algorithms. Finally, it concludes with a summary of the existing challenges and future opportunities for multi-sensor fusion SLAM.
A Literature Survey: AQI Prediction Using ML, DL and Hybrid Models
Authors: Sarkar Nairita , Keserwani Pankaj Kumar , Govil Mahesh Chandra
Published: September 2024

The existence of human being is not worth considering without fresh air. Rapidurbanization and industrialization is degrading air quality, which puts people’shealth at risk by causing various lung and heart diseases. It is necessary to raisepublic awareness to safeguard their well-being from these detrimental effects.An effective solution that must be implemented in conjunction with awarenesscampaigns are the use of modelling and monitoring systems for air quality predictions.Many air quality monitoring stations are installed to monitor and analysethe air quality of the respective regions. Many Machine Learning (ML) andDeep Learning (DL) models have shown their effectiveness to enhance predictivecapabilities and address the challenges of air pollution forecasting. This articleprovides a comprehensive survey based on thorough analysis of several ML,DL and hybrid models presented by the various researchers for air quality prediction.The selected papers are categorized based on the models used by theresearchers. This comprehensive survey of air quality prediction is an asset thatprovides insights that can greatly help to address the pressing problems broughton by poor air quality and its monitoring. In this survey diverse pollutants, meteorologicalfactors, several ML models, DL models and hybrid models with theirperformance efficacy are being analysed thoroughly to report the effect of thesemodels in the area of air quality forecasting. This survey facilitates the creationof realistic and efficient plans to protect public health from the adverse effects ofair pollution.
Fuzzy Logic Controller and P&O-Based MPPT Techniques for Stand-Alone PV Systems: A Comparison
Authors: Kumar Rajesh , Bhattacharya Ananyo , Vardhan Aanchal Singh S.
Published: September 2024

The proposed work focuses on photovoltaic (PV) system monitoring and the use of maximum power point tracking (MPPT) techniques for optimal power generation. It emphasizes the widespread application of artificial intelligence (AI) in MPPT methods in solar power systems, which can significantly improve performance and efficiency. However, AI-based MPPT techniques may be more computationally intensive and costly. Hybrid MPPT methods combine traditional and AI techniques to balance performance and complexity, addressing these issues. Fuzzy logic control (FLC) emerges as a viable technique, though synchronization is required for optimal performance under variable irradiation and weather conditions. This paper uses MATLAB/Simulink to compare the four main MPPT techniques: fuzzy-based variable step size P&O, FLC, and hybrid P&O-FLC algorithms. Further, a symmetric fuzzy controller, the perturb-and-observe (P&O) method, and a mixed method that combines both fuzzy and P&O-based controllers were compared. At the same time, many other FLC-based MPPT strategies were also examined. All tests were performed in a solar PV system with a DC-DC boost converter, considering varying atmospheric conditions. Overall, the study's aim is to provide insights into the relative effectiveness of various MPPT techniques, with a particular emphasis on the use of FLC and its hybrids in a variety of environmental scenarios.
Ungrading as a Feminist Technique in the Counseling Theories Course
Authors: Horton Emily , Everett Brenda , Bradley Kailey , Schoonover TJ
Published: September 2024

Ungrading dismantles traditional approaches to grading and moves into growth-focused assessment. Due to its inclusive and innovative pedagogical roots, ungrading appears to align with the purpose of counseling training programs. This research study focused on how ungrading role-plays can foster a more equitable classroom environment and cultivate student autonomy in counselor education, specifically in a counseling theories course. The study used data from 40 counselors-in-training in a counseling theories course and was collected and analyzed using reflexive thematic analysis.
Mobile Applications for Diabetes Management in Iran: An App Review and Quality Assessment Using the Mobile Application Rating Scale (MARS)
Authors: Alizadeh-dizaj Ghasem , Mehrabi Nahid , Ardalan Mohammad Afshar , Gholamhosseini Leila
Published: September 2024

Background The increasing prevalence of diabetes worldwide necessitates the development of effective mobile applications (apps) to assist individuals in managing their condition. Despite the growing number of these applications, there is limited understanding of their quality, which is essential for ensuring that they serve their intended purpose effectively. We aimed to perform a systematic search and evaluate the content and quality of diabetes applications available in Iranian app stores on the basis of the Mobile App Rating Scale (MARS). Methods Iranian app stores for iOS and Android were searched using diabetes-related terms in August 2024. Apps that met the inclusion and exclusion criteria were added to the content and quality assessment. Two researchers independently reviewed, rated, and evaluated the retrieved apps. The Mobile Application Rating Scale (MARS) was employed to assess the included apps. MARS rates apps on a scale from 1 to 5, providing an overall score along with scores for engagement, functionality, information, aesthetics, and subject quality. Results The search terms yielded 809 apps, after removing duplicate and irrelevant apps, 33 met the inclusion criteria and were included in this review. The assessment revealed an average quality score of 2.78 (SD 1.04) across the evaluated applications, indicating a moderate level of overall performance. While certain applications demonstrated promising potential by offering valuable educational content and robust features, the overall quality exhibited significant variability, with scores ranging from 1.71 to 4.53. This variability underscores a pressing need for improvements in user engagement and functionality among many of the assessed apps. Conclusions The findings highlight the critical need for targeted enhancements in mobile health applications for diabetes management to better serve the needs of users. Collaboration among developers, healthcare professionals, and researchers is essential to create high-quality, effective tools that can significantly aid individuals in managing their diabetes. Future research should prioritize the identification of best practices and address the gaps identified in this study, thereby maximizing the potential of mobile applications as indispensable resources in diabetes care.
CALHM2 is a mitochondrial protein import channel that regulates fatty acid metabolism
Authors: Jonas Elizabeth , Mnatsakanyan Nelli , Rivera-Molina Felix , Robson Andrew , Garfinkel Alexandra MacColl , Kumar Amrendra , Batter Stephen , Padovano Valeria , Webster Kaitlin , Cardone Rebecca , Berg Justin , Toomre Derek , IV Richard Kibbey , Caplan Michael , Khokha Mustafa
Published: September 2024

For mitochondrial metabolism to occur in the matrix, multiple proteins must be imported across the two (inner and outer) mitochondrial membranes. Classically, two protein import channels, TIM/TOM, are known to perform this function, but whether other protein import channels exist is not known. Here, using super-resolution microscopy, proteomics, and electrophysiological techniques, we identify CALHM2 as the import channel for the ECHA subunit of the mitochondrial trifunctional protein (mTFP), which catalyzes β-oxidation of fatty acids in the mitochondrial matrix. We find that CALHM2 sits specifically at the inner mitochondrial and cristae membranes and is critical for membrane morphology. Depletion of CALHM2 leads to a mislocalization of ECHA outside of the mitochondria leading to severe cellular metabolic defects. These defects include cytosolic accumulation of fatty acids, depletion of tricarboxylic acid cycle enzymes and intermediates, and reduced cellular respiration. Our data identify CALHM2 as an essential protein import channel that is critical for fatty acid- and glucose-dependent aerobic metabolism.
Metodologia da problematização no desenvolvimento de uma ação educativa sobre infecções vulvovaginais
Authors: TERRA Bruna Emilia da Costa , PANZO Lívia Cristina Soares , ALVIM Gabriela Fernandes Nóbrega , SILVA Raul Vitor Nascimento Severi , SILVA João Gabriel Machado , MARQUEZ Isabela Salgueiro , MENDES-RODRIGUES Clesnan , SILVA Patrícia Costa dos Santos da
Published: September 2024

As infecções vulvovaginais representam uma das doenças mais comuns nos consultórios ginecológicos. Dentre as queixas mais recorrentes, estão os corrimentos vaginais causados por infecções como candidíase, tricomoníase e vaginose bacteriana. Sendo assim, o objetivo é descrever a experiência dos alunos de graduação em Enfermagem de uma Universidade Federal do Triângulo Mineiro com a utilização da metodologia da problematização no desenvolvimento de uma ação educativa. Tal ação foi desenvolvida pelosalunos da disciplina de Projeto Interdisciplinar II. A ação educativa sobre infecções vulvovaginais realizada em 2019, foi planejada a partir do Arco de Maguerez e implementada em um ambulatório de Ginecologia e Obstetrícia focada nas mulheres como público-alvo. A metodologia da problematização propiciou o trabalho em equipe, incentivou a pesquisa, o protagonismo dos estudantes na busca por soluções que contribuíram na construção do conhecimento sobre infecções vulvovaginais.
Comparison between modulus of toughness and compressive strength of bamboo fiber reinforced mortar under impact loading
Authors: Aditama Vega , Dewi Sri Murni , Wibowo Ari , Wijaya Ming Narto
Published: September 2024

The presence of bamboo fiber has been distributed to improve the structural integrity of construction. It has been used to resist impact loads and reduce crack widths in composite materials. This can be utilized for reinforcement in construction, particularly in mortar elements. Bamboo fiber has been used to resist impact loads and reduce crack widths in composite materials. This can be utilized for reinforcement in construction, particularly in mortar elements. By combining good treatment with alkaline NaOH, the quality of the fiber used as a mortar mix will increase and the capacity to absorb impact energy will be greater. In this study there were 2 stages, the first stage was to look at the effect of the effective length of bamboo fiber and alkaline molarity. The effect of treatment using alkaline is to reduce the lignin and hemicellulose substances which reduce the bond in the mortar mixture. The optimal value for the Pull-out test, which involved manipulating the molarity of NaOH as a treatment and the effective length of bamboo fiber, was determined to be 2.5 cm of embedded fiber or a total length of 5 cm when 4 molar NaOH was utilized. All fiber bamboo-composite bars had a cross section of average at 1×1 mm. And the second stage tested Charpy for impact load resistance in mortar with the optimum effective fiber length while varying the alkaline molarity. The objective of the Charpy impact test was to determine the optimal quantity of bamboo fiber to be incorporated into mortar when subjected to impact loads. standard Charpy impact test specimen is 55×10×10 mm in dimension. Experimental data show that the effective length and treatment of bamboo fiber affected the bond strength with mortar. A proportional relationship was observed between the addition of fiber to the mortar and an increase in compressive strength; The research findings indicate that the lowest modulus of toughness is 0.329 MPa, or equivalent compressive strength at 15.583 MPa, while employing 3.25 % bamboo fiber in mortar with a fiber length of 5 cm and a 12 % alkaline treatment
Efficient construction of the Feynman-Vernon influence functional as matrix product states
Authors: Guo Chu , Chen Ruofan
Published: September 2024

The time-evolving matrix product operator (TEMPO) method has become a very competitive numerical method for studying the real-time dynamics of quantum impurity problems. For small impurities, the most challenging calculation in TEMPO is to construct the matrix product state representation of the Feynman-Vernon influence functional. In this work we propose an efficient method for this task, which exploits the time-translationally invariant property of the influence functional. The required number of matrix product state multiplication in our method is almost independent of the total evolution time, as compared to the method originally used in TEMPO which requires a linearly scaling number of multiplications. The accuracy and efficiency of this method are demonstrated for the Toulouse model and the single impurity Anderson model.
(RE)PENSANDO AS (IN)DIFERENÇAS: TEMAS TRANSVERSAIS COMO POSSIBILIDADE PARA AS AULAS DE QUÍMICA
Authors: S. M. dos Santos Mariana , D. M. Salgado Tania
Published: September 2024

(RE)THINKING THE (IN)DIFFERENCES: CROSS-CUTTING THEMES AS POSSIBILITIES FOR CHEMISTRY CLASSES. The focus of this manuscript is to present the extension project “(Re)thinking the (in)differences: the deconstructions and resistance to transversal themes in the teaching of Natural Sciences”, as well as analyzing its potential when working with continued training work by teachers, promoting debate, discussion, and reflection on the use of contemporary cross-cutting themes in chemistry and science classes. It was also intended to stimulate class planning, the production of strategies and teaching material by educators motivated by the need to reform thinking and regenerate teaching, considering social themes that seek the empowerment of groups placed on the margins of the education system, so that they undertake training that is a collective achievement and built with social discussions.
The Effectiveness of Scientific Literacy-Based Student Worksheets in Improving Student Learning Outcomes in Colloid Chemistry Learning
Authors: Rahmi Chusnur , Maisarah Maisarah , Sabarni Sabarni
Published: September 2024

Low student learning outcomes are a significant issue in high school colloid chemistry learning. Correspondingly, this research aimed to determine the effectiveness of scientific literacy-based student worksheets (LKPD) in colloid chemistry learning. A quasi-experimental approach, specifically the pretest-posttest control group design, was employed in this study. The experimental class, XI IPA-2, consisted of 15 students, while the control class, XI IPA-1, also included 15 students, with total sampling techniques used to select the sample. Test instruments were developed to collect student learning outcome data through pretest and posttest techniques. The effectiveness of student worksheets was analyzed using the N-gain test, independent sample t-test, and effect size tests. The N-gain results exhibited an average score of 0.7319, which was a high category for the experimental class, while the control class obtained a score of 0.5308, which was categorized as moderate. The independent sample t-test results indicated a 2-taliled significance score of 0.002 ( 0.05), demonstrating a significant difference between the learning outcomes of the experimental and control classes. Based on these findings, it can be concluded that scientific literacy-based student worksheets effectively improved student learning outcomes in colloid chemistry learning at the senior high school level.
Development of an Ethnoscience Electronic Student Worksheet on Buffer Solutions Material to Inculcate Islamic Values
Authors: Kamilah Sofi Nihayatul , Suprihatiningrum Jamil
Published: September 2024

Human actions that exploit natural resources and the environment without limits have caused global conditions to become increasingly concerning. A lack of environmental awareness is also evident in students who neglect to care for and protect the environment, such as by littering. This issue requires serious attention and can be addressed by fostering an environmentally caring character through an integrated ethnoscience approach incorporating Islamic values. Ethnoscience-based learning, integrated with Islamic values, can be facilitated through an electronic student worksheet. This worksheet was designed to help students connect cultural elements with scientific concepts and the teachings of the Quran. Correspondingly, this study developed an electronic student worksheet using a 4D model, encompassing three stages: Define, Design, and Develop. Data from the product development and assessment process were analyzed quantitatively and descriptively. The final product featured character education based on Islamic values. It received an “excellent” rating from material and media experts, while teachers and students responded positively to the media. Overall, this electronic worksheet could potentially improve environmental awareness and instill Islamic values in students.
Cultivating Work Engagement and its Related Factors in Saudi Nurses: A Cross-Sectional Study
Authors: Al-Ahmari Khulud A. , Kattan Waleed M.
Published: September 2024

Background

Work engagement in nursing is pivotal for quality care and workforce stability. Under the healthcare goals of Vision 2030, understanding and improving the engagement of nurses is critical in Saudi Arabia. Yet, the current literature on the work engagement of Saudi nurses is scant, presenting a knowledge gap.

Objective

This study aimed to evaluate work engagement levels among Saudi nurses at King Abdulaziz Hospital, Jeddah, and identify key contributing factors.

Methods

A quantitative cross-sectional study design was utilized. A structured questionnaire assessing demographic information, work-related characteristics, and levels of work engagement using the Utrecht Work Engagement Scale was distributed electronically to 466 Saudi nurses at the hospital in November, 2019. Two hundred twenty-four nurses responded. Data were analyzed using descriptive statistics, Mann-Whitney, Kruskal-Wallis tests, and Spearman's correlation and linear regression analysis to examine relationships between engagement and factors.

Results

The mean engagement score was 66.16%, with absorption scoring the highest. Work engagement was significantly associated with years of experience, work position, and employment status. Engagement was higher in nurses with over 20 years of experience and managers. Income level approached a significant relationship with engagement. Demographic factors did not correlate significantly with engagement.

Conclusion

The study found that work engagement among Saudi nurses was significantly influenced by experience, work position, and employment status. These findings highlight the need for a strategic focus on career development and job satisfaction to boost engagement. Future research should explore interventions that enhance engagement and their effects on healthcare outcomes.
Forecasting Delivery Time of Low-Risk Pregnant Women by Applying Linear Regression
Authors: Chaisitsa-nguan Kunnikar , Sitkulanan Piyaporn
Published: September 2024

Background

The period of normal childbirth is the shortest, lasting no more than 24 hours, but it is the most important because up to 1 in 3 fetal deaths occur during birth. Accurate predictions of the time of birth can help health professionals provide effective care for the women during the time they give birth.

Objective

The aim of this research is to investigate the influence of cervical dilatation, the effacement of the cervix, station of the presentation, body mass index, maternal height, fetal weight, dose and duration of oxytocin exposure. The study also reviews the time a number of pregnancies take in low-risk pregnant women and to create a mathematical equation model for use in predicting the time to delivery.

Methods

This study is a retrospective descriptive study conducted from July 2023 to December 2023 at Thammasat Hospital. One hundred and eight low-risk pregnant women who had 37+ 0 to 41+ 6 weeks of gestation were selected by stratified random-sampling technique and systematic random sampling technique. The sample size was 108 participants. The research tool consisted of observation sheets and questions. Data analysis was obtained using multiple linear regression with the Stepwise regression method to examine the factor that influenced the time to delivery and create the equation.

Results

The obtained model had an R2 value of 0.316. The significant variables that mostly influence the time of delivery were the timing of oxytocin exposure (β = 0.31, p < .01) and cervical dilatation (β = -31.51, p < .01). The explanatory power of the regression model was statistically significant at 31.03%.

Conclusion

This study was designed for improving the prediction of time to delivery, which can be useful for enhancing the preparation pathways of normal childbirth. In this way, multiple regression analysis showed that the timing of oxytocin exposure and cervical dilatation can predict the time of birth.
Past, Present, and Future of Judo in South Africa: A Systematic Review
Authors: Hlasho Temba Selvin , Mathunjwa Musa Lewis , Shaw Brandon , Shaw Ina
Published: September 2024

Introduction

There is a wide gap in judo participation between developing and developed countries. In South Africa (SA), there are only 2139 (0.00004% of the population) registered judokas compared to 122 000 (0,001% of the population) in Japan. This may be attributed to the fact that in developing countries such as SA, judo participation is dominated by a single race, generally the white race.

Methods

This disjuncture is said to be informed by a combination of factors, including affordability, preferences, and the legacy of apartheid. Interestingly, despite being a popular sport amongst the white population in SA, judo is practiced by more black people than whites in some provinces, namely, the Eastern and Western Cape. The purpose of the research is to reflect on how judo has navigated, and migrated to its current form and what the future holds. A substantial literature search was done using PubMed, SCOPUS, SportDiscuss, Google Scholar, and Web of Science (2001 - June 2020). The synthesis of the literature suggests that the management of judo requires more than just financial resources; it also needs a well-defined organizational strategy.

Results

This study used 65 full-text English-language papers from 90 citations found through electronic searches. After removing duplicates and reviewing the full-text versions, 18 articles remained central to athlete success in the professionalization of federations. Federations that are run on a voluntary basis are seen as inefficient and unsustainable to successfully plan an athlete’s international success pathway.

Conclusion

Furthermore, there is a consensus amongst researcher’s that professionalism and commercialization are central to improving athlete’s performance, participation, and efficacy in the athlete’s management system. Evidently, financial resources, a clear long-term plan and full-time coaching and administration staff play a critical role in the successful management of any Federation.
Maternal, Child, and Household Risk Factors for Children with Stunting
Authors: Garina Lisa Adhia , Dewi Miranti Kania , Trusda Siti Annisa Devi , Purbaningsih Wida , Muflihah Heni , Tursina Alya , Respati Titik , Rahimah Santun Bhekti
Published: September 2024

Background

Stunting is a major public health issue in Indonesia. It affects children's physical and cognitive development, educational outcomes, and quality of life, increasing the risk of chronic diseases in adulthood. Addressing the determinants of stunting is vital for achieving the sustainable development goal of zero hunger.

Objective

The study aims to identify maternal, child, and household risk factors for stunting in West Bandung Regency, Indonesia.

Methods

This cross-sectional study was conducted on 122 children from 10 villages in the Padalarang area. Stunting status was measured by a doctor and verified by a pediatrician based on WHO growth standards. The demography, household, maternal, and child risk factors were collected using the standard Indonesia Basic Household Health Research (Riskesdas) questionnaire. Statistical analysis was used for the Chi-square and Fisher Exact test, while logistic regression was used to determine a model on the most important risk factors. Data analysis was done using the SPSS v.25 program.

Results

Out of 119 evaluable datasets, 87 children were classified as stunted, with 44 stunted and 43 severely stunted. The majority of stunting was observed in boys aged 24‒59 months, mostly with low parental education levels and underweight status. Significant risk factors for stunting included a history of low birth weight, lack of maternal immunization against Tetanus Toxoid, and insufficient intake of animal-based proteins. The multivariate analysis identified age, protein deficiency, and diarrhea as critical predictors.

Conclusion

Stunting is predominantly influenced by demographic factors, low parental educational level, nutritional insufficiency, and diarrhea. Targeted nutritional interventions and healthcare strategies focusing on protein intake and managing diarrhea among young children can effectively mitigate stunting rates in this region.