bluuebunny/crossref_metadata_2025 huggingface dataset:
PROFESSIONAL TRAINING OF POLISH TEACHERS OF SCIENCE AND MATHEMATICAL DISCIPLINES IN THE CONTEXT OF EUROPEAN INTEGRATION
Authors: Yevtushenko Natalia
Published: November 2023

The article analyzes the issue of professional retraining of science and mathematics teachers in the Republic of Poland in the context of European integration processes. The development of the system of retraining and improvement of teachers' qualifications in the Republic of Poland under the influence of socio-political changes that took place in the country starting from the 90s of the XX century is being studied. The analysis of scientific and pedagogical sources regarding the state of retraining and improvement of teachers before the accession of Poland to the European Union was carried out. The regulatory and legal support of the educational process, including international regulations and documents, which became the basis for changes in the training of Polish teachers, was considered. The author described and analyzed modern forms of the organization of retraining of teachers of natural and mathematical subjects in postgraduate education of the country, offered by educational institutions in Poland. The form and content of retraining for teachers of science and mathematical subjects under the postgraduate education programme in the areas of “Pedagogical training” and “Teaching the next subject” were studied.
DEVELOPMENT OF THE INFORMATION TECHNOLOGY FOR IT-PROJECT TEAM CREATION
Authors: Sushko Hlib , Balandin Danylo
Published: November 2023

Team creation is a critical aspect of successful IT project realisation. Implementation of effective project management in modern conditions of dynamic technologies requires the presence of a highly qualified team, taking into account the constraits of the project. Working with such a set of data could be simplified by development of an information technology for creation IT project teams. Such technology simplifies the process of selecting a project team, choosing highly qualified members who meet the unique requirements of IT projects. The implementation of such automatisation helps to solve the issue of distribution of competences, coordination and monitoring of work processes related to the creation of the project team. In addition, taking into account the constant development of technologies, information technology allows users to quickly adapt to changes in market requirements and innovations in the field of IT, which is a key factor for ensuring competitiveness. Therefore, the purpose of this work is the development of information technology for the IT project team creation. An additional goal is to create a web application "Teamform" aimed at the process of creation the IT project team. Information technology uses a method of the IT project team creation previously developed by the authors. The method consists of three stages. At the first stage, a set of candidates is determined, the assessment of whose competences meets the requirements of the project. At the second stage, team options are formed in accordance with project requirements. The third step of the method is the selection of a team in accordance with the chosen statement of the problem. The developed information technology and web-application "Teamform" allow creating an effective team of software developers that meets the requirements of the project.
OPTIMIZATION OF THE DC MOTOR MODEL COMPLEXITY LEVEL SELECTION FOR THE SYSTEM USING A NEURAL NETWORK
Authors: Vorobiov Bohdan , Senchenko Serhii , Rybakov Vadym , Likhno Yaroslav , Khan Liu
Published: November 2023

A mathematical and computer model of the torque control system of a DC motor with independent excitation was built using the NARMA 2 neurocontroller. NARMA - a nonlinear moving average autoregressive model is one of the basic structures of a discrete and nonlinear model. The task was to conduct a comparative analysis of the operation of the neurocontroller-based control system using plant model of varying complexity. For the experiment, three models of the object were built with different degrees of detail, and therefore the reliability of the object. The full model includes an independently excited DC motor model that takes into account all the main parameters of the DC machine, internal friction parameters, excitation circuits, etc. The simplified model is a linear approximation of the DC motor by a second-order system that takes into account both mechanical and electrical time constants. The simplest model is a linear approximation of a DC motor by a first-order aperiodic link that takes into account only the mechanical time constant. The neurocontroller was trained using the above object models and an experiment was conducted to process the reference torque signal by the system. For each of the three training cases, the neurocontroller was set to 1000 epochs, since further training performance improvement is unnecessary due to the huge loss of computation time. The NARMA-L2 neurocontroller, which is also called feedback linearization control, was used. This controller can be implemented using a pre-identified NARMA-L2 object model. Neural networks that are trained on simplified object models do not take into account most of the electrical processes in a DC motor, especially the excitation winding is not modeled at all. The obtained results were compared with the use of a neurocontroller as a torque regulator. Further research in this direction involves the study of the necessary computing power for the microprocessor implementation of the neurocontroller.
PROSPECTS FOR THE APPLICATION OF FULLERENE ADDITIVES IN MODERN AVIATION OILS
Authors: Yefymenko Valerij , Oleksandrenko Viktor , Kalmykova Natalii , Rudenko Vira , Yefimenko Okeksandr
Published: November 2023

The possibilities and expediency of using fullerene additives and their influence on the tribological properties of modern synthetic aviation oils are analyzed. The method of increasing anti-wear properties of synthetic oils for turbojet aircraft engines Mobil Jet Oil II and Mobil Jet Oil 254 by adding fullerene additive C60 is considered. It is shown that the antiwear properties of synthetic Mobil Jet Oil 254 oil for turbojet aircraft engines exceed more than 5% of Mobil Jet Oil II oil, which, along with other factors, was the reason for the complete transfer of Airbus Helicopters H-145 helicopters to Mobil Jet Oil 254 oil. The increase in the concentration of fullerene additives in oils does not significantly affect the amount of wear of the rolling bearings of the turbine shaft of helicopters, although there is a tendency to decrease the diameter of the wear spot and an increase in the critical load of the transition to seizing. This is explained by the fact that, in contrast to sliding friction, in which the coefficient of friction decreases tenfold due to the possibility of rolling of fullerene molecules on the graphite surface, which is characterized by much lower friction compared to the sliding of graphite surfaces relative to each other due to the higher contact area in the last case. It follows that fullerenes act as micro-rolling bearings that reduce the coefficient of sliding friction. It is assumed that the balls in the rolling bearings may grind fullerenes like ball mills, therefore no significant effect of improving the anti-wear properties of oils when using fullerene additives is observed. It was established that an increase in the concentration of the fullerene additive in oils shifts the critical load to higher values. The use of fullerenes as an anti-wear additive to oils for turbojet engines requires further research and justification.
Evaluation of pastoral grasses and legumes as potential host plants for Fall armyworm Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) development
Authors: Adnan Saleh Mohammad , Cattermole Holly , Saligari Kim , Spafford Helen
Published: November 2023

The fall armyworm, Spodoptera frugiperda author (Lepidoptera: Noctuidae) is a highly polyphagous, migratory pest native to the tropical and subtropical region of Americas. Grass crops particularly corn have been most heavily impacted since fall armyworm invaded Australia in 2020. In northern Western Australia, fall armyworm is primarily a problem in dry season (May to October) crops when there are abundant host plants available in monocultures. During the wet season (November to April) it is not known what host plants may support larval growth and development. Accordingly, this present study undertook a no-choice feeding bioassay to assess larval and pupal development on several grasses and legumes that are present over the wet season in northern Western Australia to evaluate their potential as suitable host plants for fall armyworm. Maize (control) and sorghum were the most suitable hosts for fall armyworm development as they supported greater larval and pupal survival, heavier larvae and pupae, and shorter development period. Following maize and sorghum, pastoral grasses, particularly blue grass, and a weedy grass, barnyard grass, had comparable effects on larval and pupal development. Legume pastures (Cavalcade, butterfly pea, and siratro) were unsuitable hosts in this bioassay as very few larvae completed their development to adults. This study demonstrates the potential for rangeland pasture grasses and weedy grasses as wet season host plants for fall armyworm. They provide the necessary green bridge for fall armyworm populations to survive. It is recommended that pastoralists monitor their grass forage for fall armyworm and consider management if significant reductions in biomass are detected.
Observed northward shift of large hailstorms in the eastern United States since 2000
Authors: Leung Jeremy Cheuk-Hin , Liu Jimmy , Huang Hong , Xu Daosheng , Li Weijing , Qian Weihong , Zhang Banglin
Published: November 2023

Given its high population density and degree of urbanization, the eastern United States (US) is a region vulnerable to the impacts from hailstorms. Small changes in hail activity may indicate large impacts on the potential hail risks faced by the region. While contrasting hailstorm-favorable environmental changes between the northeastern and southeastern US have been documented, the meridional shift of hail activity in the eastern US has not been directly revealed based on observed hailstorm records. Here, using the official hailstorm database, we find a significant northward migration of hail activity (+0.33°N/decade) in the eastern US since 2000, which is mainly contributed by the increasing proportion of large hailstorm events (hail size 0.75–2.0 inch) hitting the northeastin July and August (+0.93°N/decade). The spatially inhomogeneous climatic mean state changes over the past two decades contribute a leading role: the intensified Bermuda High and the weakened upper-level jet stream over the central US tended to moisten (dry) the atmosphere over the northeastern (southeastern) US by enhancing the low-level poleward moisture transport. This not only provides more moisture for hailstorm formation in the northeast but also destabilizes (stabilizes) the atmosphere in the northeast (southeast) under an overall increase in dry instability over the eastern US. These factors together lead to a northward shift of large hailstorms toward the northeastern US, where hailstorms were relatively seldom reported. Incorporating this shift in knowledge may improve contingency and risk management strategies of both the public and private sectors in future climate change.
Ocular and Orbital Manifestations in VEXAS Syndrome
Authors: Abumanhal Muhammad , Leibovitch Igal ,   Michael Zisapel2, Eviatar Tali , Edel Yonatan , Cnaan Ran Ben
Published: November 2023

Background VEXAS (V- vacuoles, E- E1 enzyme, X- X-linked, A- autoinflammatory, S- somatic) is an adult onset hematoinflammatory disease, resulting from somatic mutation of the E1 ubiquitin conjugating enzyme encoded by the UBA1 gene. It is frequently accompanied by myelodysplastic syndrome (MDS). The purpose is to describe the ocular and orbital manifestations of VEXAS patients in a case series in our medical center
Methods A retrospective chart review was performed for all patients who were diagnosed with VEXAS syndrome in a tertiary medical center over two years.
Results Eight patients were identified with VEXAS. In six patients, the diagnosis was confirmed by genomic sequencing. Two patients, were identified based on their phenotype. All patients were males. The mean age at diagnosis was 78.7 years. In two patients, the ocular manifestation was the presenting symptom for VEXAS. Seven patients (87.5%) had history of MDS. Systemic inflammation manifestations include: skin rash (n=5), recurrent fevers (n=2), relapsing polychondritis (n=2), pleuritis and pleural effusion (n=2), poly arthritis nodosa- PAN (n=1) and thrombophlebitis (n=1). Seven (87%) patients were presented with periorbital edema. Three patients showed orbital inflammation. Dacryoadenitis was observed in two patients, and extraocular muscle (EOM) myositis was detected in two patients. Four patients demonstrated ocular inflammation such as: episcleritis, scleritis and anterior uveitis.
Conclusion ocular manifestations in VEXAS include orbital inflammation, dacryoadenitis, myositis, uveitis, scleritis, episcleritis and periorbital edema. We recommend that in old male patients, with history of hematological disorder, presenting with ocular symptom, VEXAS investigation should be taken into consideration.
Influence of Sample Size, Feature Set, and Algorithm on Cluster Analyses for Patients with Autism Spectrum Disorders
Authors: Cox David J. , Sosine Jacob
Published: November 2023

Researchers conducting cluster analyses on data collected from autistic individuals have identified two-to-seven clusters depending on data used. Given the spectrum nature of autism spectrum disorders, it seems unlikely only a handful of patient types exist. Past findings might be due to: smaller sample sizes, more focused variables used, or clustering algorithm used. In this study, we systematically analyzed clustering results from 48 combinations of four sample sizes (40, 395, 3948, 39475), three sets of clinically relevant variables (7 medical/diagnostic features; 31 behavioral features; 50 total features), and four clustering algorithms (agglomerative hierarchical, BIRCH, DBSCAN, k-means). Clusters identified ranged 2-to-100 with a median of eight and average of 20. Increasing the sample size led to no change in clusters identified (behavioral features), an increase in the number of clusters identified (medical/diagnostic features), or influenced clusters dependent on the algorithm (all features). On average, the greatest number and most well-defined clusters were identified with the medical/diagnostic features (58) and the fewest clusters were identified using behavioral features (6). Lastly, on average, fewer clusters were identified using the BIRCH (18) and DBSCAN (15) algorithms than agglomerative hierarchical (24) and k-means algorithms (25). In total, this study suggests that the patient sample size, specific feature set used, and the algorithm chosen for clustering will influence the number of clusters identified. The “right” number of clusters likely depends on how the information obtained through clustering analyses are practically used in clinical contexts.
Altitudinal distribution of myopia: big data analysis based on biogeographic regions in India
Authors: Cehelyk Eli , Garrigan Hannah , Das Anthony Vipin , Zhang Qiang (Ed) , Prashanthi Gumpili , Verkicharla Pavan
Published: November 2023

Objective
Considering the potential role of various aspects of light on myopia, we aimed to investigate the altitudinal distribution of myopia based on 10 distinctive biogeographic regions in India.
Methods
This cross-sectional retrospective study involved analysis of refractive error and demographics of 135,927 individuals with myopia aged 11–30 years seen at a large multi-tiered ophthalmology network in India captured through electronic medical records. Using the refractive error of the eye with worse vision in either eye, individuals were classified as having low (-0.5D to -5.75 D), or high myopia (≤ -6.0D). Residential districts were assigned a biogeographical zone using nationally reported boundaries and altitude was determined using Google Earth at the geographic centroid. Descriptive statistics, hypothesis testing, and multiple ordinal logistic regression analysis were performed.
Results
While low myopia was not associated with altitude, a trend of increased risk of high myopia was observed with higher altitudes. Compared to living at an altitude of 0-100m, the odds of having high myopia compared was 0.96 in the 101-250m range (95% CI: 0.93, 0.99), 2.31 times higher for 251-500m (95% CI: 2.21, 2.42), 1.28 times higher for 501-750m (95% CI: 1.25, 1.32), and 1.62 times higher for > 750m (95% CI: 1.30, 2.04).
Conclusions
The smaller proportion of high myopes observed in lower altitudes compared to those living in higher altitudes hints at a possible association of altitude with myopia which needs further exploration.
Enhancing the efficiency of magnetically-driven carbon nitride-based nanocomposites with magnetic nanoflowers for the removal of methylene blue dye at neutral pH
Authors: Rodovalho Fernanda Lopes , Rosa Eliane Vieira , Silva Atailson Oliveira da , Moya Sergio Enrique , Campos Alex Fabiano Cortez , Sousa Marcelo Henrique
Published: November 2023

The present survey focuses on the elaboration of magnetic nanocomposites by the in-situ incorporation of magnetite (Fe3O4) nanoparticles (NPs) with spherical and nanoflower-like) morphologies in graphitic carbon nitride (g-C3N4) sheets using two different synthetic routes. Nanomaterials are characterized by TEM, SEM, XRD, FTIR, BET, zetametry, vibrating sample magnetometry, and UV–vis absorption spectroscopy. The decoration of the carbon nitride matrix with the magnetic NPs enhanced optical and textural properties. The influence of the shape of the magnetic NPs on the adsorptive and photocatalytic properties of the nanocomposites under different pH conditions was assessed from batch tests to remove methylene blue (MB) from aqueous solutions. In extreme pH conditions, the nanocomposites exhibited lower or equivalent MB removal capacity compared to the pure g-C3N4. However, at neutral medium, the nanocomposite with incorporated Fe3O4 nanoflowers showed a significantly higher removal efficiency due to the combination of a high adsorption capacity and a good photocatalytic activity in this pH region. The proposed nanocomposite is a promising alternative to remove cationic dyes from water by magnetic assistance, since no pH adjustment of the polluted effluent is required, reducing costs and environmental impact in the dyeing industry.
Dysregulated fetal heart contraction underlies complex genetics of congenital heart disease
Authors: Shi Hongjun , Luo Xiaoxi , Liu Lifeng , Rong Haowei , Liu Xiangyang
Published: November 2023

The etiology of most CHD is believed to be multifactorial, potentially involving multiple concurrent genetic mutations. This study employed a large-scale ENU-based forward dominant screen in mice to explore potential novel oligogenic causes of CHD. Through screening 10,000 mice, we identified over 1,000 CHD fetuses, with ventricular septal defects and bicuspid aortic valves being the most prevalent types of defects. Analysis of whole exomes from 720 CHD and 611 control littermates revealed that the CHD group exhibited a significant excess of induced damaging mutations involved in heart contraction and nervous system development. A subsequent gene-based burden test on rare inherited damaging variants from 1457 human CHD probands also revealed enrichment of genes associated with heart contraction and nervous system development. By combining the data from both mice and humans, we proposed a list of oligo gene groups that were found to co-occur in mice and multiple CHD patients but not in control subjects. Our findings shed light on the importance of early hemodynamic perturbations in the developing heart as a previously unrecognized major risk factor for CHD. Further validation and investigation of the identified candidate genes will contribute to a deeper understanding of the molecular mechanisms underlying CHD and may offer insights into novel diagnostic and therapeutic approaches.
Assessing the Impacts of Climate Change on Snow Avalanche-Induced Risk in Alpine Regions
Authors: Ortner Gregor , Michel Adrien , Kropf Chahan M. , Bründl Michael , Bresch David N.
Published: November 2023

Climate change is a global challenge with serious impacts on human populations. Numerous studies have highlighted the impacts of climate change on natural hazard processes and associated risks for communities. Understanding future hazard and risks is crucial for effective risk management. This study focuses on assessing snow avalanche risks for inhabited areas in the context of climate-induced changes.Using hazard scenarios based on CH2018 climate projections and the RAMMS avalanche model, we generated large-scale hazard indication maps for future avalanche hazards. By employing the open-source probabilistic risk assessment platform CLIMADA, along with building data and vulnerability functions, we estimated risks for the present time and two future time frames: mid-century (2060) and the end of the century (2085). An uncertainty and sensitivity analysis complemented the study to account for potential fluctuations in model assumptions.Our mean-based approach, considering different CH2018 model chains, indicates an overall decline in avalanche risks for the future. This reduction is driven by assumed decreases in snow accumulation, rising snowpack temperatures, and a rising snowline. To cover more extreme developments, we also examined boundary model chains, which suggest that future risks can both increase and decrease, with a general trend of decreasing affected objects towards the end of the century. It is worth noting that some individual objects depending on their location may remain at consistently high avalanche risk despite climate change.This study provides a valuable tool for decision-makers to compare future risk scenarios with the present situation, supporting effective mitigation and adaptation strategies to address the challenges of climate change. By providing risk maps and identifying potential future risk hot spots, our approach contributes to enhancing community resilience and protecting their assets in a changing climate.
Precision-cut liver slices as an ex vivo model to assess impaired hepatic glucose production
Authors: Bakker Barbara , Kiyuna Ligia Akemi , Krishnamurthy Kishore Alagere , Langelaar-Makkinje Miriam , Gerding Albert , Bos Trijnie , Oosterhuis Dorenda , Overduin Ruben , Schreuder Andrea B. , De Meijer Vincent , Olinga Peter , Derks Terry G.J. , Eunen Karen van , Oosterveer Maaike H.
Published: November 2023

Fasting hypoglycemia is a severe and incompletely understood symptom of various inborn errors of metabolism (IEM). Precision-cut liver slices (PCLS) represent a promising model to study glucose production ex vivo. This study aimed to provide a comprehensive characterization of glucose production in human and murine PCLS. We quantified net glucose production rate of PCLS derived in the presence of commonly used gluconeogenic precursors and from fed and fasted mice. Dihydroxyacetone (DHA) yielded the highest rate, which was further stimulated by forskolin and dibutyryl-cAMP. Moreover, using 13C isotope tracing, we assessed the contribution of glycogenolysis and gluconeogenesis to net glucose production over time, showing faster incorporation of DHA than glycerol in the gluconeogenesis. Pharmacological inhibition of the glucose 6-phosphate transporter SLC37A4 markedly reduced net glucose production and increased lactate secretion and glycogen storage, while glucose production was completely abolished in PCLS from glycogen storage disease (GSD) type Ia and Ib patients. This indicates that PCLS allow to model the primary clinical symptoms of GSD type I, an inborn error of carbohydrate metabolism. In conclusion, this study identifies PCLS as an effective ex vivo model to study hepatic glucose production and opens opportunities for its future application in IEM research and beyond.
Identification and analysis of Verbena bonariensis WRKY transcription factor gene family members
Authors: Yuan Dandan , Cai Ju , Zhang Tao , Wang Sisi , Yang Xiuliu , Li Yan
Published: November 2023

Background: The WRKY transcription factor gene family is one of the unique gene families in plants, it plays an important role in response to abiotic stresses such as cold and drought, hormone signal transduction, regulation of biosynthesis, leaf senescence and seed germination etc. However, little information is available about WRKY transcription factors in Verbena bonariensis.
Results: In this study, 70 members of VbWRKY were identified by bioinformatics tool analysis and named VbWRKY1-VbWRKY70. The phylogenetic analysis of the WRKYgene family in Verbena bonariensis and Arabidopsis shows that the WRKY genes in Verbena bonariensis can be divided into three groups: I, II, and III, which contains 13, 47 and 10 members respectivelys. Group II can be further divided into five subclasses: IIa (5), IIb (10), IIc (18), IId (6), and IIe (8). Conservative motif analysis showed that 64 proteins encoded by VbWRKY gene had conserved motifs 1,2 and 3, and the same subclass motif elements were approximately the same. The collinearity analysis showed that there were 44 homologous gene pairs among the VbWRKRs, and these homologous gene pairs may have the same function. Promoter sequence analysis showed that the VbWRKY gene has multiple cis acting elements, including not only cis acting elements related to low temperature and light responses, but also cis acting elements related to hormone regulation, Among them, most VbWRKY genes contain response elements related to low temperature, 30 VbWRKY genes contain low temperature response elements (LTR) , and 61 VbWRKY genes contain abscisic acid response elements (ABRE), indicating that VbWRKYplays a crucial role in plant growth and abiotic stress. According to the expression of VbWRKY in the cold stress transcriptome, 52 VbWRKYsshowed significant differences in expression, and 37 VbWRKY genes were up-regulated under stress
Conclusions: Ultimately, the present study provides a comprehensive analysis of predicted Verbena bonariensis WRKY family genes, which provided a theoretical basis for the study of low temperature resistance and growth and development of Verbena bonariensis.
Chronic disseminated candidiasis in a patient with acute leukemia - an illustrative case and brief review for clinicians.
Authors: Graeter Allison I , Lee Dasom , Handley Guy , Baluch Aliyah , Klinkova Olga
Published: November 2023

Chronic disseminated candidiasis (CDC) is a severe but rarely seen fungal infection presenting in patients with hematologic malignancies after a prolonged duration of neutropenia. A high index of suspicion is required to diagnose CDC as standard culture workup is often negative. While tissue biopsy is the gold standard of diagnosis, it is frequently avoided in patients with profound cytopenias and increased bleeding risks. A presumptive diagnosis can be made in patients with recent neutropenia, persistent fevers unresponsive to antibiotics, imaging findings of hypoechoic, non-rim enhancing target-like lesions in the spleen and liver, and mycologic evidence. Here, we describe the case of an 18-year-old woman with relapsed B-cell acute lymphoblastic leukemia treated with re-induction chemotherapy who subsequently developed CDC with multi-organ involvement. The patient was treated with a long course of amphotericin B, micafungin, and splenectomy. The diagnosis, treatment, and common challenges of CDC are outlined here to assist with better understanding, diagnosis, and treatment of this rare condition.
Depressive symptoms and gender differences in the risk of post-COVID-19 persistent symptoms: a prospective population-based cohort study
Authors: Lemogne Cédric , Matta Joane , Pignon Baptiste , Robineau Olivier , Carrat Fabrice , Severi Gianluca , Touvier Mathilde , Blanché Hélène , Deleuze Jean-François , Gouraud Clément , Vedrines Charles Ouazana , Pitron Victor , Tebeka Sarah , Ranque Brigitte , Hoertel Nicolas , Kab Sofiane , Goldberg Marcel , Zins Marie
Published: November 2023

Women are unexplainedly more affected than men by post-COVID-19 persistent symptoms. Depressive symptoms may partially explain these gender differences. In the French population-based CONSTANCES cohort, depressive symptoms were measured with the 9-item Patient Health Questionnaire (PHQ-9) between April 6 and May 4, 2020. Between December 2020 and January 2021, among 2093 infected participants [mean (SD) age, 43.0 years (11.9); 55.3% women], 453 (21.6%) reported ≥1 new persistent symptom that emerged from March 2020. Accounting for several confounders, women were more likely than men to have ≥1 symptom [OR (95%CI): 1.45 (1.17-1.80)]. Further adjusting for PHQ-9, participants in the highest (versus the lowest) quartile were more likely to have ≥1 symptom [2.97 (2.09-4.23)], while the association with female gender substantially dropped [1.28 (1.02-1.60)]. Depressive symptoms mediated 38.6% of this association. A biopsychosocial model, integrating gender and mental health, is warranted to understand long COVID and inform preventive and therapeutic strategies.
Hybridization of multi-step iterative process with double direction method for solving a system of nonlinear equations and application to motion control
Authors: Waziri Muhammed Yusuf , Bala Naziru Idris , Halilu Abubakar Sani
Published: November 2023

This article presents a multi-step algorithm for solving a system of nonlinear equations using a double direction approach with application to motion control. In order to offer a useful derivative-free technique, the acceleration parameter is calculated to rougthly approximate the Jacobian matrix. With the aid of an inexact line search approach, the step-length was calculated. In addition, the proposed method is proving to be globally convergent under some appropriate conditions. Numerical experiment for some large-scale benchmark test problems reported in 1 this article shows the efficiency of the suggested methods compared with the current methods in the literature.
A comparative evaluation of landslide susceptibility mapping using machine learning-based methods in Bogor area of Indonesia
Authors: Melati Dian Nuraini , Umbara Raditya Panji , Astisiasari Astisiasari , Wisyanto Wisyanto , Trisnafiah Syakira , Trinugroho Trinugroho , Prawiradisastra Firman , Arifianti Yukni , Ramdhani Taufik Iqbal , Arifin Samsul , Anggreainy Maria Susan
Published: November 2023

Landslide is one of the most highly frequent natural hazards that can bring serious casualties. One of the most susceptible landslide regions in Indonesia is Bogor area (the Regency and City of Bogor), which records the highest landslide events in the Province of West Java, Indonesia. An assessment of landslide susceptibility is one of the mitigation measures that can spatially model the zone of landslide hazard. Recently, the Landslide Susceptibility Mapping (LSM) model has been developed by using Machine Learning (ML) algorithms. However, there is still no agreement yet on which ML technique is the most appropriate for LSM. Accordingly, this paper aims to explore and compare the 7 ML algorithms for generating the most promising LSM. The LSM uses the available 13 landslide causal factors and a dataset consisting of 822 authorized landslide records and 822 prepared non-landslide points. The resulting LSMs are classified into 5 susceptibility levels, and evaluated through the Area Under Curve (AUC) of the Receiver Operating Curve (ROC) and statistical indices (sensitivity, specificity, precision, F1-score, and accuracy). The resulting LSMs present that: (1) the very-high (VH) class has the largest area percentage in all LSM models, (2) generally, the 7 MLs perform excellent for achieving >90% AUC value, except for the Decision Tree (DT) (87.84%) in model classification, (3) moreover, the overall accuracy (ACC) reflects that Random Forest (RF) outperforms the other MLs in model prediction. With this promising result, ML-based LSM models can be promoted as one of the mitigation measures for landslide disaster management.
Radiomics Features on Computed Tomography Combined with Clinical Factors Predicting Hypoproteinemia in Patients with Traumatic Brain Injury
Authors: Li Yuping , Jiang Yong’An , Zhang Yan , Yuan Raorao , Fan Hengyi , Fan Xinjiang , Zhang Yichen , Cheng Shiqi
Published: November 2023

Background
Traumatic brain injury (TBI) is a major cause of death and disability in all age groups, placing a heavy burden on society and families, serum albumin levels have a significant impact on mortality and length of hospitalization patients. This study was made to develop a predictive model based on Computed Tomography (CT) and clinical parameters to explore the predictable power of the model in the development of hypoproteinemia with TBI patients.
Methods
A total of 72 TBI patients were prospectively recruited and confirmed as hypoproteinemia in 26 cases. A cranial CT and clinical parameters such as age, gender, admission Glasgow score were collected to establish the clinical model. The least absolute shrinkage and selection operator (LASSO) was applied to extract radiological features. Then a total of five different machine learning methods (RF, SVM, GNB, XGB, KNN) were used to establish the prediction model of radiomics. Finally, a combined model: clinical-radiological was constructed. The average area under the curve (AUC) were used to evaluate the performance of each model.
Results
Comparing these three different models, we found that the radiomic models combined with clinical parameters showed the best performance, which had an AUC with 0.8704 compared with clinical model only AUC = 0.8512 and radiomics model only AUC = 0.7040, respectively.
Conclusions
The model of radiomics features combined with clinical parameters is superior to the radiomics model and clinical model alone, and the model of radiomics combined with clinical parameters is a useful tool for predicting the occurrence of hypoproteinemia in patients with traumatic brain injury.
Life-threatening gastrointestinal bleeding caused by cytomegalovirus-induced duodenal ulcer in a patient with AIDS： a case report
Authors: Song Shihui , Guo Wei , Zou Shi , Zhou Feng , Luo Mingqi , Chen Li , Liang Ke
Published: November 2023

Background Diagnosis and treatment for
gastrointestinal bleeding among patients with acquired immune deficiency syndrome (AIDS) were challenging. Here we present a rare case of life-threatening gastrointestinal bleeding in an AIDS patient.
Case presentation
A 31-year-old male with a three-month history of HIV infection was admitted on July 18, 2023, complaining of abdominal pain for over one month and hematochezia for the past twelve days. During his hospitalization, gastrointestinal endoscopy identified the source of bleeding as a duodenal ulcer associated with cytomegalovirus(CMV) infection confirmed through comprehensive determination methods involving metagenomic next-generation sequencing (mNGs), hematoxylin-eosin(HE), and immunohistochemistry (IHC) staining of biopsy tissue from the ulcer. The patient received interventional embolization to manage emergency gastrointestinal bleeding in addition to four-week anti-CMV treatment and remained in stable clinical condition during two months follow-up.
Conclusions
This case highlights potential complexity of CMV infection in HIV-infected patients with gastrointestinal bleeding.
Genome-wide identification, transcript profiling and functional analyses of PCP gene family in Wucai (Brassica campestris)
Authors: Wang Ying , Liu Xueqing , Zhao Longlong , Tang Xiaoyan , Wang Wenjie , Khan Afrasyab , Pang Xiaoke , Yang Danni , Wang Yongkang , Wang Chenggang , Yuan Lingyun , Hou Jinfeng , Chen Guohu
Published: November 2023

Pollen coat proteins (PCPs) are cysteine-rich small-molecule proteins, which exhibit high levels of polymorphism and are expressed in gametocytes. Previous investigations have revealed that PCP genes are involved in pollen wall synthesis, pollen-stigma recognition, pollen development and germination. However, gene expression and function of PCP family in pollen development is not well understood in Wucai (Brassica campestris L.). In this study, genome-wide identification and expression analysis of the BcPCPgene family members were conducted, including their physical and chemical properties, chromosome localization, phylogenetic tree, gene structure, and tertiary structure. A total of 20 BcPCP genes were identified and classified into three subfamilies with high homology to Arabidopsis thaliana. Furthermore, PCP members associated with male sterility were screened based on several transcriptome and proteome datasets, and BraA02g002400.3C was identified as a candidate gene. Gene sequence analysis revealed that this gene was homologous to GRP20 gene, and was named BcGRP20. Functional analysis of this gene showed that overexpression of BcGRP20 gene in the Arabidopsis grp20 mutant could restore anther fertility.
Xanthohumol inhibits proliferation via increasing reactive oxygen species and inducing G1/S phase cell cycle arrest in NG108-15 cells
Authors: Hu Chenyu , Tian Jiazhen , Yan Hanyu , Zhang Ting , Abulizi Amier , Mi Xiangquan
Published: November 2023

Xanthohomul (XN), a naturally prenylated flavonoid, is extracted from hops (Humulus lupulus L.; Cannabaceae). XN treated NG108-15 cells significantly decreased cell viability through increased ROS and arrested the cell cycle at G1/S phase. Notably, XN treatment did not induce apoptotic responses. Further research revealed XN-treatment increased reactive oxygen species (ROS) levels which was alleviated by N-acetyl-L-cysteine (NAC). Moreover, XN triggered the phosphorylation of the estrogen-regulated kinase (ERK1/2) and p38 mitogen activated protein kinase (MAPK). Intriguingly, our observations indicated that only ERK inhibitor could partly relieve XN-induced G1/S cycle arrest and proliferation inhibition. Hence, XN emerges as a prospective candidate for an anti-neurotumor pharmaceutical agent.
Influences of laser on the energy parameters of the electric arc in the case of laser-MIG hybrid welding
Authors: Bidi Lyes , Masson Philippe Le , Cicala Eugen
Published: November 2023

The work presented in this paper deals with the relationship between the laser and the electric arc during welding and chamfer filling operations using the hybrid laser welding process. This unconventional welding process requires perfect mastery, in order to increase the productivity and quality of welds, especially in nuclear facilities. Mastering the hybrid process involves a phase of understanding the phenomena involved in a welding operation. To better understand the role of each process in the combination of laser and MIG, we carried out a laser-only and MIG-only tests using the same operating parameters as those used in hybrid welding. Test results show that the laser preheats the surface, with some of the energy deposited on the side walls of the chamfer. The role of MIG is to deposit metal to fill the chamfer. We can therefore consider that its main role is to provide a volumetric energy deposit. Using the experimental design, we studied the influence of five parameters such as wire speed, distance between the laser and the MIG, welding speed, laser power and laser defocusing on the power of the MIG. The results show that the interaction between laser power and wire speed has the greatest effect on arc power, followed by wire speed and other interactions. To verify the arc energy values given by the FRONIUS generator, we carried out additional measurements using a SEFRAM device. The results measured by FRONIUS are always higher than those of SEFRAM. Both series of measurements follow the same variations.
Water Quality Prediction in Urban Waterways Based on Wavelet Packet Denoising and LSTM
Authors: pang jiafeng , Luo Wei , Y Zeyu , Chen Jing , Dong Chunyu , Lin Kairong
Published: November 2023

The prediction of water quality in urban rivers plays a crucial role in supporting water environment management. This study collected and organized real-time water quality monitoring data from four water quality monitoring stations in the Fenjiang River Basin of Foshan City, spanning from 2016 to 2021. To reduce noise interference in historical monitoring data, we applied a wavelet packet denoising (WPD) technique. Subsequently, we developed a single-factor water quality prediction model based on Long Short-Term Memory (LSTM), focusing on two key factors of water quality degradation: chemical oxygen demand (COD) and ammonia nitrogen (NH3-N). The results of this study demonstrate that the integration of WPD with LSTM, referred to as WPD-LSTM, outperformed conventional LSTM models in terms of predictive accuracy. Notably, the WPD-LSTM model exhibited superior performance in predicting the impact of COD and NH3-N on water quality in the Fenjiang River, surpassing the traditional LSTM model over a prediction period of 12 hours and 3 days. In the 12-hour prediction, the RMSE values of NH3-N predictions in the four monitoring sections decreased by 55% to 67%, with an average decrease of 61%; the RMSE values of COD predictions in the four monitoring sections decreased by 18% to 51%, with an average decrease of 29%. In the 3-day prediction, the RMSE values of NH3-N predictions in the four monitoring sections decreased by 40% to 83%, with an average decrease of 65%; the RMSE values of COD predictions in the four monitoring sections decreased by 50% to 69%, with an average decrease of 60%. By employing the WPD-LSTM method, this study contributes to improving the precision of water quality prediction, thereby providing valuable insights for effective water environment management in urban river systems.
Beneficial effects of imagination of successful action after an actual error on baseline performances in non-expert tennis players
Authors: Robin Nicolas , Carien Robbin , Ouarti Younès , Dominique Laurent
Published: November 2023

The aim of this original study was to evaluate the effects of positive motor imagery (MI: imagining the success of a forehand or backhand shot) according to an internal visual modality centred on the movement and the target to be reached on tennis performance. 24 young non-expert players were randomly divided into two groups: control and MI, and performed 3 experimental phases. The first (pre-test) consisted of performing 6 blocks of 5 forehand and backhand groundstrokes, sent randomly by a ball launcher, towards the baseline and then a super tie-break. The second phase consisted of 12 acquisition sessions, each including, after a standardized warm-up, 15 minutes of background rally in pairs. The participants of the MI group were instructed, after unprovoked errors on their part, to imagine performing the previous shot correctly. The last phase (post-test) was identical to the pre-test. The efficiency score of shots made and the number of errors committed at the pre- and post-test served as dependent variables. The results of this study indicate that participants in the MI group performed better than the control group at post-test. The MI, performed after errors, has positive effects on the quality of the shot and reduces the number of unforced errors of tennis players. The use of this strategy is discussed and applied recommendations are proposed.
A Ball-Jointed Tendon-Driven Continuum Robot with Multi-Directional Operability for Grasping Objects
Authors: Onose Ryo , Sawada Hideyuki
Published: November 2023

A continuum robot, inspired by biological features, flexibly bends its body and conform to various shapes. The high compliance and low stiffness, however, causes low rigidity and ambiguity in control when it is applied to grasping and manipulating an object. In this study, we develop a ball-jointed tendon-driven continuum robot that can bend to arbitrary directions for manipulating and grasping an object. Discs are connected by ball joints, together with coil springs coupled with tendon threads, and form a backbone of the robotic body. The continuum robot is operated to bend to an arbitrary direction by pulling the tendons using three servomotors, and returns to the original straight shape by releasing the pulling force of the contracted coil springs. The robot is constructed by using 3D-printed parts. In the experiment, the manipulator's grasping performance was demonstrated by preparing five objects that have various shapes, sizes and softness. The robot successfully grasped all the objects by wrapping around them, adapting its shape to the object's shapes. Furthermore, the ability of the multi-directional operation was tested by bending the continuum body to specific directions, and then performing arc-following motion. The experiments verified the satisfactory operability of the continuum robot.
Comparative Assessment of WINISI and Unscrambler for NIRS Modelling of Phytate and Antioxidants in Brown Rice
Authors: John Racheal , Bhardwaj Rakesh , Jeyaseelan Christine , Bollinedi Haritha , Singh Rakesh , Singh G P
Published: November 2023

Brown rice has been known to be a better alternative to polished rice due to greater amounts of nutrients including antioxidants. Phytic acid and phenols in brown rice are also known to impart antioxidant capacity. Near infrared reflectance spectroscopy is renowned to estimate the nutritional composition of brown rice. The present study was conducted to develop the prediction models of total phenolic content (TPC), phytic acid (TPA) and antioxidant capacity (TAC) of brown rice. While both WIN ISI and The Unscrambler® software produce crisp models, certain limitations such as principle component analysis (PCA) descriptives in WIN ISI and inverse multiple scatter correction (iMSC) in The Unscrambler® lead to uncertainty of the results. Hence, the models in this study were generated using PCA and partial least square (PLS) regression, which were compared on both WIN ISI and The Unscrambler® separately. The reference data of 226 rice landraces was subjected to both the softwares and optimal models were obtained from standard normal variate (SNV-DT) for TPA and TPC over The Unscrambler®, while multiplicative scatter correction (MSC) was found better for TPC model development on WIN ISI. According to regression analysis the best prediction model was obtained for TPC employing MSC with RSQ = 0.925 and RPD = 3.11 in WIN ISI, while the rest were better validated in The Unscrambler® using SNV-DT with RSQ = 0.888, 0.958 RPD = 2.97, 2.93 for TPA and TAC respectively. The results are indicative of the NIRS ability and the effect of different scatter corrections to rapidly predict antioxidant content in brown rice.