bluuebunny/crossref_metadata_2025_split huggingface dataset:
Solution of engineering design and truss topology problems with improved forensic-based investigation algorithm based on dynamic oppositional based learning
Authors: Kutlu Onay Funda 
Published: May 2024

AbstractThe forensic-based investigation (FBI) is a metaheuristic algorithm inspired by the criminal investigation process. The collaborative efforts of the investigation and pursuit teams demonstrate the FBI’s involvement during the exploitation and exploration phases. When choosing the promising population, the FBI algorithm’s population selection technique focuses on the same region. This research aims to propose a dynamic population selection method for the original FBI and thereby enhance its convergence performance. To achieve this objective, the FBI may employ dynamic oppositional learning (DOL), a dynamic version of the oppositional learning methodology, to dynamically navigate to local minima in various locations. Therefore, the proposed advanced method is named DOLFBI. The performance of DOLFBI on the CEC2019 and CEC2022 benchmark functions is evaluated by comparing it with several other popular metaheuristics in the literature. As a result, DOLFBI yielded the lowest fitness value in 18 of 22 benchmark problems. Furthermore, DOLFBI has shown promising results in solving real-world engineering problems. It can be argued that DOLFBI exhibits the best convergence performance in cantilever beam design, speed reducer, and tension/compression problems. DOLFBI is often utilized in truss engineering difficulties to determine the minimal weight. Its success is comparable to other competitive MAs in the literature. The Wilcoxon signed-rank and Friedman rank tests further confirmed the study’s stability. Convergence and trajectory analyses validate the superior convergence concept of the proposed method. When the proposed study is compared to essential and enhanced MAs, the results show that DOLFBI has a competitive framework for addressing complex optimization problems due to its robust convergence ability compared to other optimization techniques. As a result, DOLFBI is expected to achieve significant success in various optimization challenges, feature selection, and other complex engineering or real-world problems.
Vibration analysis for early pitting detection during operation
Authors: Häderle Philipp , Merkle Lukas , Dazer Martin 
Published: May 2024

AbstractThe economic efficiency of machinery operation is significantly impacted by maintenance strategies. In the realm of condition-based or predictive maintenance strategies, the early detection of fatigue-induced damages is crucial. Therefore, this study focuses on the early detection of pitting damages during operation. Experimental investigations are conducted on a test gearbox acquiring acceleration data for different sizes of pitting damages under diverse operating conditions. A successful detection of the pitting damages during operation is achieved at a very early stage of progression, with a minimum size of 0.41% of an active tooth flank area. The utilization of design of experiments techniques facilitates the identification of factors influencing the detectability of pitting damages. The obtained results are analysed to elucidate the physical basis for the reliable detection of pitting damages across diverse operating conditions.
Antimicrobial susceptibility testing reveals reduced susceptibility to azithromycin and other antibiotics in Legionella pneumophila serogroup 1 isolates from Portugal
Authors: Minetti Corrado , Barton Rachael , Farley Caitlin , Spiller Owen Brad , Rodrigues Raquel , Gonçalves Paulo 
Published: May 2024

Abstract
Backgroud
Although not fully investigated, studies show that Legionella pneumophila can develop antibiotic resistance. As there is limited data available for Portugal, we determined the antibiotic susceptibility profile of Portuguese L. pneumophila serogroup 1 (LpnSg1) isolates against antibiotics used in the clinical practice in Portugal.

Methods
Minimum inhibitory concentrations (MICs) were determined for LpnSg1 clinical (n = 100) and related environmental (n = 7) isolates, collected between 2006–2022 in the context of the National Legionnaire´s Disease Surveillance Programme, against azithromycin, clarithromycin, erythromycin, levofloxacin, ciprofloxacin, moxifloxacin, rifampicin, doxycycline, tigecycline, and amoxicillin/clavulanic acid, using three different assays. Isolates were also PCR-screened for the presence of the lpeAB gene.

Results
Twelve isolates had azithromycin MICs above the EUCAST tentative highest WT MIC, 9 of which were lpeAB negative; for erythromycin and clarithromycin, all isolates tested within the susceptible range. The number of isolates with MICs above the tentative highest WT MIC for the remaining antibiotics was: ciprofloxacin: 7; levofloxacin: 17; moxifloxacin: 8; rifampicin: 11; doxycycline: 82; tigecycline: 4. EUCAST breakpoints are not available for amoxicillin/clavulanic acid. We estimated the ECOFFs and one isolate had a MIC eightfold higher than the E-test ECOFF. Additionally, a clinical isolate generated three colonies growing on the E-test inhibition zone that resulted in MICs fourfold higher than for the parental isolate.

Conclusions
We report, for the first time, elevated MICs against first-line and other antibiotics (including azithromycin, fluoroquinolones and amoxicillin/clavulanic acid commonly used to treat pneumonia patients in Portugal) in Portuguese L. pneumophila strains. Results point towards decreased susceptibility in circulating strains, justifying further investigation.
The theory of screws derived from a module over the dual numbers
Authors: Minguzzi Ettore 
Published: May 2024

AbstractThe theory of screws clarifies many analogies between apparently unrelated notions in mechanics, including the duality between forces and angular velocities. It is known that the real 6-dimensional space of screws can be endowed with an operator $$\mathcal {E}$$
E
, $$\mathcal {E}^2=0$$

E

2

=
0

, that converts it into a rank 3 free module over the dual numbers. In this paper we prove the converse, namely, given a rank 3 free module over the dual numbers, endowed with orientation and a suitable scalar product ($$\mathbb {D}$$
D
-module geometry), we show that it is possible to define, in a canonical way, a Euclidean space so that each element of the module is represented by a screw vector field over it. The new approach has the effectiveness of motor calculus while being independent of any reduction point. It gives insights into the transference principle by showing that affine space geometry is basically vector space geometry over the dual numbers. The main results of screw theory are then recovered by using this point of view.
Molecular characterization of m6A RNA methylation regulators with features of immune dysregulation in IgA nephropathy
Authors: Wang Yihao , Sun Nan , He Rui , Wang Zida , Jin Jingsi , Gao Ting , Qu Junwen 
Published: May 2024

AbstractThe role of RNA N6-methyladenosine (m6A) modification in immunity is being elucidated. This study aimed to explore the potential association between m6A regulators and the immune microenvironment in IgA nephropathy (IgAN). The expression profiles of 24 m6A regulators in 107 IgAN patients were obtained from the Gene Expression Omnibus (GEO) database. The least absolute shrinkage and selection operator (LASSO) regression and logistic regression analysis were utilized to construct a model for distinguishing IgAN from control samples. Based on the expression levels of m6A regulators, unsupervised clustering was used to identify m6A-induced molecular clusters in IgAN. Gene set enrichment analysis (GSEA) and immunocyte infiltration among different clusters were examined. The gene modules with the highest correlation for each of the three clusters were identified by weighted gene co-expression network analysis (WGCNA). A model containing 10 m6A regulators was developed using LASSO and logistic regression analyses. Three molecular clusters were determined using consensus clustering of 24 m6A regulators. A decrease in the expression level of YTHDF2 in IgAN samples was significantly negatively correlated with an increase in resting natural killer (NK) cell infiltration and was positively correlated with the abundance of M2 macrophage infiltration. The risk scores calculated by the nomogram were significantly higher for cluster-3, and the expression levels of m6A regulators in this cluster were generally low. Immunocyte infiltration and pathway enrichment results for cluster-3 differed significantly from those for the other two clusters. Finally, the expression of YTHDF2 was significantly decreased in IgAN based on immunohistochemical staining. This study demonstrated that m6A methylation regulators play a significant role in the regulation of the immune microenvironment in IgAN. Based on m6A regulator expression patterns, IgAN can be classified into multiple subtypes, which might provide additional insights into novel therapeutic methods for IgAN.
Long non-coding RNA LOXL1-AS1: a potential biomarker and therapeutic target in human malignant tumors
Authors: Fu Xiao-Ping , Ji Chun-Yan , Tang Wen-Qian , Yu Ting-Ting , Luo Lei 
Published: May 2024

AbstractLong non-coding RNAs (lncRNAs) are transcripts that contain more than 200 nucleotides. Despite their inability to code proteins, multiple studies have identified their important role in human cancer through different mechanisms. LncRNA lysyl oxidase like 1 antisense RNA 1 (LOXL1-AS1), a newly discovered lncRNA located on human chromosome 15q24.1, has recently been shown to be involved in the occurrence and progression of various malignancies, such as colorectal cancer, gastric cancer, hepatocellular carcinoma, prostate cancer, non-small cell lung cancer, ovarian cancer, cervical cancer, breast cancer, glioma, thymic carcinoma, pancreatic carcinoma. LOXL1-AS1 acts as competitive endogenous RNA (ceRNA) and via sponging various miRNAs, including miR-374b-5p, miR-21, miR-423-5p, miR-589-5p, miR-28-5p, miR-324-3p, miR-708-5p, miR-143-3p, miR-18b-5p, miR-761, miR-525-5p, miR-541-3p, miR-let-7a-5p, miR-3128, miR-3614-5p, miR-377-3p and miR-1224-5p to promote tumor cell proliferation, invasion, migration, apoptosis, cell cycle, and epithelial–mesenchymal transformation (EMT). In addition, LOXL1-AS1 is involved in the regulation of P13K/AKT and MAPK signaling pathways. This article reviews the current understanding of the biological function and clinical significance of LOXL1-AS1 in human cancers. These findings suggest that LOXL1-AS1 may be both a reliable biomarker and a potential therapeutic target for cancers.
Maximum Drift Demands of Earthquake Damaged Reinforced Concrete Columns Based on Residual Flexure Cracks
Authors: Aydin Beyazit Bestami , Binici Baris , Aktas Saime Selin , Hendriks Max A. N. , Tuncay Kagan 
Published: May 2024

AbstractAssessment of existing reinforced concrete (RC) structures after an earthquake is a challenging task that must somehow relate qualitative and quantitative observations in the plastic hinge regions and the associated residual deformation capacity of damaged structures. Having an estimate available for the remaining drift capacity will result in more economical and informed decisions regarding demolition or strengthening options. This study aims to develop a practical methodology to estimate the maximum drift demand of an RC column based on the residual crack width. For this purpose, fiber-based frame elements are used to model the RC column considering appropriately concrete behavior in compression and tension stiffening effects. Afterwards, the accuracy and reliability of the proposed methodology are demonstrated by validating the computational approach with two cyclic experimental results from literature and new test data for a one-bay one-story RC frame conducted within the course of this study. A comprehensive parametric study is performed for RC columns with different axial loads, longitudinal and transverse reinforcement ratios, and ground motions to exhibit the stochastic behavior. The study identifies the axial load ratio as the predominant parameter. Key findings include strong correlations between maximum drift ratios and total residual crack widths, as well as maximum compressive strains, with regression analysis yielding equations for accurate drift ratio estimation. Simple predictive models are proposed to estimate the maximum deformation demands based on observed residual crack widths. Residual cracking exceeding 5 mm poses significant risk for the columns with axial load ratios above 0.4, with 90% probability of exceedance 2% drift ratio.
Invisible invaders: range expansion of feral Neocaridina davidi offers new opportunities for generalist intracellular parasites
Authors: Prati Sebastian , Grabner Daniel S. , Hupało Kamil , Weiperth András , Maciaszek Rafał , Lipták Boris , Bojko Jamie , Bérces Fanni , Sures Bernd 
Published: May 2024

AbstractThe release of ornamental pets and associated pathogens outside their native range might directly or indirectly impact the recipient community. In temperate regions, e.g., central Europe, feral freshwater species of tropical and sub-tropical origins are mainly constrained to thermally polluted waters and thermal springs. However, species with high environmental plasticity and reproduction rates, such as the shrimp Neocaridina davidi, may adapt to colder water regimes over time. A widening thermal niche may eventually overcome thermal barriers, further expanding the range and enhancing transmission opportunities for host generalist parasites. This study assesses the observed (field observations) and theoretical (species distribution models) range expansion of N. davidi and associated parasites in Europe. We report three newly established N. davidi populations from thermally polluted waters in central Europe (Germany, Hungary, and Slovakia) and provide further evidence of its range expansion into colder environments. Species distribution models predict thermally suitable habitats in the Mediterranean and a foreseeable expansion into Western Europe and the Balkans by 2050. We confirm the presence of the microsporidian parasite Ecytonucleospora hepatopenaei in feral N. davidi populations across Europe and expand the list of microsporidians found in this host from two to four. Furthermore, we provide the first evidence of parasite spillover from/to the invasive crayfish Procambarus clarkii, suggesting that parasite exchange with native biota might be possible. Such possibility, coupled with an ongoing range expansion of N. davidi bolstered by human-mediated introductions and climate change, will likely exacerbate the impact on native biota.
Exosomes as mediators of signal transmitters in biotoxins toxicity: a comprehensive review
Authors: Xu Tongxiao , Huangfu Bingxin , He Xiaoyun , Huang Kunlun 
Published: May 2024

AbstractSmall membranes known as exosomes surround them and are released by several cell types both in vitro and in vivo. These membranes are packed with a variety of biomolecules, including proteins, lipids, deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and non-coding RNA (ncRNA). As a source of biological nanomaterials, exosomes play a role in information and substance transmission between cells and have been identified as a general method of facilitating communication during interactions between the body, target organs, and toxins.. In order to understand the changes and mechanism of the composition and level of exosomes after biotoxin infection, this review focuses on current findings on the exosomes and highlights their novel uses in the toxicity mechanism. Exosomes are mainly used as a delivery carrier or mediated by receptors, and play an immune role after the toxin enters the body. This review expounds on the importance of exosomes in the toxicological mechanism of biotoxins and provides new insights for further diagnosis of toxic biomarkers, detoxification, and treatment development.
Graphical abstract
ChatGPT in higher education - a synthesis of the literature and a future research agenda
Authors: Bhullar Pritpal Singh , Joshi Mahesh , Chugh Ritesh 
Published: May 2024

AbstractChatGPT has emerged as a significant subject of research and exploration, casting a critical spotlight on teaching and learning practices in the higher education domain. This study examines the most influential articles, leading journals, and productive countries concerning citations and publications related to ChatGPT in higher education, while also shedding light on emerging thematic and geographic clusters within research on ChatGPT’s role and challenges in teaching and learning at higher education institutions. Forty-seven research papers from the Scopus database were shortlisted for bibliometric analysis. The findings indicate that the use of ChatGPT in higher education, particularly issues of academic integrity and research, has been studied extensively by scholars in the United States, who have produced the largest volume of publications, alongside the highest number of citations. This study uncovers four distinct thematic clusters (academic integrity, learning environment, student engagement, and scholarly research) and highlights the predominant areas of focus in research related to ChatGPT in higher education, including student examinations, academic integrity, student learning, and field-specific research, through a country-based bibliographic analysis. Plagiarism is a significant concern in the use of ChatGPT, which may reduce students’ ability to produce imaginative, inventive, and original material. This study offers valuable insights into the current state of ChatGPT in higher education literature, providing essential guidance for scholars, researchers, and policymakers.
Multivariate analysis applied to X-ray fluorescence to assess soil contamination pathways: case studies of mass magnetic susceptibility in soils near abandoned coal and W/Sn mines
Authors: Milinovic Jelena , Santos Patrícia , Sant’Ovaia Helena , Futuro Aurora , Pereira Carlos M. , Murton Bramley J. , Flores Deolinda , Azenha Manuel 
Published: May 2024

AbstractDetermining the origin and pathways of contaminants in the natural environment is key to informing any mitigation process. The mass magnetic susceptibility of soils allows a rapid method to measure the concentration of magnetic minerals, derived from anthropogenic activities such as mining or industrial processes, i.e., smelting metals (technogenic origin), or from the local bedrock (of geogenic origin). This is especially effective when combined with rapid geochemical analyses of soils. The use of multivariate analysis (MVA) elucidates complex multiple-component relationships between soil geochemistry and magnetic susceptibility. In the case of soil mining sites, X-ray fluorescence (XRF) spectroscopic data of soils contaminated by mine waste shows statistically significant relationships between magnetic susceptibility and some base metal species (e.g., Fe, Pb, Zn, etc.). Here, we show how qualitative and quantitative MVA methodologies can be used to assess soil contamination pathways using mass magnetic susceptibility and XRF spectra of soils near abandoned coal and W/Sn mines (NW Portugal). Principal component analysis (PCA) showed how the first two primary components (PC-1 + PC-2) explained 94% of the sample variability, grouped them according to their geochemistry and magnetic susceptibility in to geogenic and technogenic groups. Regression analyses showed a strong positive correlation (R2 > 0.95) between soil geochemistry and magnetic properties at the local scale. These parameters provided an insight into the multi-element variables that control magnetic susceptibility and indicated the possibility of efficient assessment of potentially contaminated sites through mass-specific soil magnetism.
Comparative analysis of real issues in open-source machine learning projects
Authors: Lai Tuan Dung , Simmons Anj , Barnett Scott , Schneider Jean-Guy , Vasa Rajesh 
Published: May 2024

Abstract
Context
In the last decade of data-driven decision-making, Machine Learning (ML) systems reign supreme. Because of the different characteristics between ML and traditional Software Engineering systems, we do not know to what extent the issue-reporting needs are different, and to what extent these differences impact the issue resolution process.

Objective
We aim to compare the differences between ML and non-ML issues in open-source applied AI projects in terms of resolution time and size of fix. This research aims to enhance the predictability of maintenance tasks by providing valuable insights for issue reporting and task scheduling activities.

Method
We collect issue reports from Github repositories of open-source ML projects using an automatic approach, filter them using ML keywords and libraries, manually categorize them using an adapted deep learning bug taxonomy, and compare resolution time and fix size for ML and non-ML issues in a controlled sample.

Result
147 ML issues and 147 non-ML issues are collected for analysis. We found that ML issues take more time to resolve than non-ML issues, the median difference is 14 days. There is no significant difference in terms of size of fix between ML and non-ML issues. No significant differences are found between different ML issue categories in terms of resolution time and size of fix.

Conclusion
Our study provided evidence that the life cycle for ML issues is stretched, and thus further work is required to identify the reason. The results also highlighted the need for future work to design custom tooling to support faster resolution of ML issues.
Leveraging the potential of the German operating room benchmarking initiative for planning: A ready-to-use surgical process data set
Authors: Korzhenevich Grigory , Zander Anne 
Published: May 2024

AbstractWe present a freely available data set of surgical case mixes and surgery process duration distributions based on processed data from the German Operating Room Benchmarking initiative. This initiative collects surgical process data from over 320 German, Austrian, and Swiss hospitals. The data exhibits high levels of quantity, quality, standardization, and multi-dimensionality, making it especially valuable for operating room planning in Operations Research. We consider detailed steps of the perioperative process and group the data with respect to the hospital’s level of care, the surgery specialty, and the type of surgery patient. We compare case mixes for different subgroups and conclude that they differ significantly, demonstrating that it is necessary to test operating room planning methods in different settings, e.g., using data sets like ours. Further, we discuss limitations and future research directions. Finally, we encourage the extension and foundation of new operating room benchmarking initiatives and their usage for operating room planning.