bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning risk estimation and prediction of death in continuing care facilities using administrative data
Authors: Shahidi Faezehsadat , Rennert-May Elissa , D’Souza Adam G. , Crocker Alysha , Faris Peter , Leal Jenine 
Published: October 2023

AbstractIn this study, we aimed to identify the factors that were associated with mortality among continuing care residents in Alberta, during the coronavirus disease 2019 (COVID-19) pandemic. We achieved this by leveraging and linking various administrative datasets together. Then, we examined pre-processing methods in terms of prediction performance. Finally, we developed several machine learning models and compared the results of these models in terms of performance. We conducted a retrospective cohort study of all continuing care residents in Alberta, Canada, from March 1, 2020, to March 31, 2021. We used a univariable and a multivariable logistic regression (LR) model to identify predictive factors of 60-day all-cause mortality by estimating odds ratios (ORs) with a 95% confidence interval. To determine the best sensitivity–specificity cut-off point, the Youden index was employed. We developed several machine learning models to determine the best model regarding performance. In this cohort study, increased age, male sex, symptoms, previous admissions, and some specific comorbidities were associated with increased mortality. Machine learning and pre-processing approaches offer a potentially valuable method for improving risk prediction for mortality, but more work is needed to show improvement beyond standard risk factors.
AST/ALT-to-platelet ratio (AARPRI) predicts gynaecological cancers: a 8-years follow-up study in 653 women
Authors: Crudele Lucilla , De Matteis Carlo , Graziano Giusi , Novielli Fabio , Petruzzelli Stefano , Piccinin Elena , Gadaleta Raffaella Maria , Cariello Marica , Moschetta Antonio 
Published: October 2023

AbstractNon-alcoholic fatty liver disease (NAFLD), specifically liver steatosis and fibrosis with steatohepatitis (NASH), is often associated with visceral adiposopathy, whose pathogenetic features have been proposed as tumorigenic triggers. We performed a prospective analysis in 653 metabolic women to reveal any conditions that may predict and concur to cancer development during a 8-years period of follow-up. Among clinical and biochemical variables, only AST and non-invasive liver fibrosis scores (AARPRI, APRI, FIB-4, mFIB4) significantly distinguished cancer-developer women (n = 62, 9.5%) from those who did not develop cancer (p < 0.001). In ROC analysis, these scores also showed good sensitivity and specificity in differentiating women who developed cancer (all p < 0.001). We then calculated OR for these indexes finding that increased AARPRI was associated with the highest risk (OR = 6, p < 0.001) of gynaecological cancers development. We further validated these cut-off values in women who had developed other types of cancer, confirming that AARPRI is able to identify the risk for cancer development (OR = 5, p < 0.001). Our findings support the hypothesis that NAFLD, more than obesity per se, is directly associated with the clinical and pathogenic metabolic scenario of gynaecological cancers and encourage the use of liver fibrosis indexes to detect risk of cancer onset in women. Preventing adiposopathy and NAFLD through lifestyle and therapies may represent an instrumental strategy for cancer prevention and/or co-treatment in oncology.
Real-world treatment patterns of rheumatoid arthritis in Brazil: analysis of DATASUS national administrative claims data for pharmacoepidemiology studies (2010–2020)
Authors: Birck Marina G. , Ferreira Rafaela , Curi M. , Krueger Whitney S. , Julian Guilherme S. , Liede Alexander 
Published: October 2023

AbstractOur study assessed DATASUS as a potential source for pharmacoepidemiologic studies in rheumatoid arthritis (RA) in the Brazilian population focusing on treatment patterns and determinants of initiating or switching to a novel therapy. This was a descriptive database study of RA patients with at least one claim of RA and ≥ 2 claims of disease-modifying anti-rheumatic drug (DMARD); conventional synthetic (cs), biologic (b) or targeted synthetic (ts) DMARD with more than 6 months of follow-up from 01-Jan-2010 to 31-Dec-2020. Analyses were stratified for SUS-exclusive and SUS+ private user cohorts. We identified 250,251 patients with RA in DATASUS: mean age of 58.4 years, majority female (83%) and white (58%). 62% were SUS-exclusive and 38% SUS+ private. Most common bDMARDs were adalimumab and etanercept. Age (adjusted odds ratio 1.78 [50+]; 95% CI 1.57–2.01), SUS exclusive status (0.53; 0.47–0.59), distance to clinic [160+ km] (0.57; 0.45–0.72), and pre-index csDMARD claims (1.23; 1.08–1.41) were independent predictors of initiating a novel oral tsDMARD. Switching from bDMARD to tsDMARD, associations were similar, except for the direction of associations for SUS exclusive status (adjusted hazard ratio 1.10; 1.03–1.18), distance to clinic (1.18; 1.03–1.35), and number of previous bDMARD (0.15; 0.14–0.16). DATASUS is a source suitable for treatment-related analyses in RA reflecting the public health system in Brazil.
Prevalence of Cryptosporidium infection and associated risk factors in calves in Egypt
Authors: Gattan Hattan S. , Alshammari Ayed , Marzok Mohamed , Salem Mohamed , AL-Jabr Omar A. , Selim Abdelfattah 
Published: October 2023

AbstractCryptosporidium is one of the causative parasitic agents that causes gastrointestinal diseases in calves. The parasite poses a zoonotic risk to immunocompromised individuals and children. Thus, this study aimed to determine the prevalence of Cryptosporidium infection in calves in three Egyptian governorates situated in Nile Delta and assess the associated risk factors. The Cryptosporidium oocysts were detected in 81 out of 430 calves (18.84%). In addition, the univariant analysis showed that age, feeding source, hygienic status, presence of diarrhea and contact with other animals were significantly (P < 0.05) associated with Cryptosporidium prevalence in calves. Furthermore, the risk factors related with Cryptosporidium prevalence were age (OR 1.96, 95%CI 0.97–3.94), feeding on milk and pasture (OR 2.07, 95%CI 1.15–3.72), poor hygienic condition (OR 2.25, 95%CI 1.28–3.94), presence of diarrhea (OR 2.47, 95%CI 1.23–4.96) and contact with other domestic animals (OR 2.08, 95%CI 1.24–3.50). In addition, the PCR assay targeting 18srRNA showed that the most prevalent species among calves was C. parvum. Although additional researches are required to understand the most effective steps that farmers and veterinary professionals should take to decrease the occurrence of Cryptosporidium infection.
Mechanical properties and sustainable bacterial resistance effect of strontium-modified phosphate-based glass microfiller in dental composite resins
Authors: Go Hye-Bin , Lee Myung-Jin , Seo Ji-Young , Byun Sung-Yun , Kwon Jae-Sung 
Published: October 2023

AbstractDental composite resins are widely used in dental restorations. However, their clinical application is limited by the occurrence of secondary caries. Strontium-modified phosphate-based glass (Sr-PBG) is a material known to have a sustainable bacterial resistance effect. The mechanical properties (in particular, flexural strength, modulus of elasticity, and hardness) of dental materials determine their function. Therefore, this study aimed to investigate the mechanical and ion-releasing properties as well as the sustainable bacterial resistance effect of bioactive resin composites containing Sr-PBG. The data were analyzed by ANOVA and Tuckey’s tests (p < 0.05). We incorporated a Sr-PBG microfiller at 3, 6, and 9 wt.% concentrations into a commercially available composite resin and investigated the mechanical properties (flexural strength, elastic modulus, and micro hardness), ion release characteristics, and color of the resultant resins. In addition, we examined the antibacterial effects of the composite resins against Streptococcus mutans (S. mutans). The mechanical properties of the Sr-PBG groups differed only slightly from those of the control group (p > 0.05). However, the optical density at 600 nm of S. mutans incubated on the experimental group was significantly lower compared to that observed with the control (p < 0.05) both before and after thermocycling between 5 and 55 ℃ for 850 cycles (dwell time: 45 s). Therefore, strontium-modified resin materials exhibited a sustainable bacterial resistance effect in vitro while maintaining some of the mechanical properties of ordinary acrylic resins.
Research on the impact of rotor wear on the effectiveness of the aluminium refining process
Authors: Socha Ladislav , Prášil Tomáš , Gryc Karel , Svizelova Jana , Saternus Mariola , Merder Tomasz , Pieprzyca Jacek , Nuska Petr 
Published: October 2023

AbstractPhysical modelling is successfully used to understand mechanisms involved in the aluminium refining process by injecting inert gas into the liquid metal through rotors. Two types of industrial impellers, which are extremely different in construction, were tested in the research. The aim of the research was to determine the effectiveness of their operation depending on their degree of wear. This type of research has not been tested on water models so far. During the process, the parameters were changed, such as the gas flow rate from 13 to 19 L/min, the rotor speed from 325 to 400 rpm and the height of the rotor from the bottom of the refining reactor. Tests were carried out for new and worn rotors. Oxygen removal rate curves were prepared on the basis of tests determining changes in oxygen content in the model liquid as a function of time for changing rotor speed values. It was found that the efficiency of hydrogen removal from the model liquid was higher when worn impellers were used in the model. In order to verify results of model tests, a metallographic analysis of samples obtained in industrial conditions and using the analysed process parameters was carried out.
Common modelling assumptions affect the joint moments measured during passive joint mobilizations
Authors: Koussou Axel , Dumas Raphaël , Desailly Eric 
Published: October 2023

AbstractJoint resistance to passive mobilization has already been estimated in-vivo in several studies by measuring the applied forces and moments while manipulating the joint. Nevertheless, in most of the studies, simplified modelling approaches are used to calculate this joint resistance. The impact of these simplifications is still unknown. We propose a protocol that enables a reference 3D inverse dynamics approach to be implemented and compared to common simplified approaches. Eight typically developed children and eight children with cerebral palsy were recruited and underwent a passive testing protocol, while applied forces and moments were measured through a 3D handheld dynamometer, simultaneously to its 3D kinematics and the 3D kinematics of the different segments. Then, passive joint resistance was estimated using the reference 3D inverse dynamics approach and according to 5 simplified approaches found in the literature, i.e. ignoring either the dynamometer kinematics, the measured moments alone or together with the measured tangential forces, the gravity and the inertia of the different segments, or the distal segments kinematics. These simplifications lead to non-negligible differences with respect to the reference 3D inverse dynamics, from 3 to 32% for the ankle, 4 to 34% for the knee and 1 to 58% for the hip depending of the different simplifications. Finally, we recommend a complete 3D kinematics and dynamics modelling to estimate the joint resistance to passive mobilization.
Effects of visual-electrotactile stimulation feedback on brain functional connectivity during motor imagery practice
Authors: Phunruangsakao Chatrin , Achanccaray David , Bhattacharyya Saugat , Izumi Shin-Ichi , Hayashibe Mitsuhiro 
Published: October 2023

AbstractThe use of neurofeedback is an important aspect of effective motor rehabilitation as it offers real-time sensory information to promote neuroplasticity. However, there is still limited knowledge about how the brain’s functional networks reorganize in response to such feedback. To address this gap, this study investigates the reorganization of the brain network during motor imagery tasks when subject to visual stimulation or visual-electrotactile stimulation feedback. This study can provide healthcare professionals with a deeper understanding of the changes in the brain network and help develop successful treatment approaches for brain–computer interface-based motor rehabilitation applications. We examine individual edges, nodes, and the entire network, and use the minimum spanning tree algorithm to construct a brain network representation using a functional connectivity matrix. Furthermore, graph analysis is used to detect significant features in the brain network that might arise in response to the feedback. Additionally, we investigate the power distribution of brain activation patterns using power spectral analysis and evaluate the motor imagery performance based on the classification accuracy. The results showed that the visual and visual-electrotactile stimulation feedback induced subject-specific changes in brain activation patterns and network reorganization in the$$\alpha$$αband. Thus, the visual-electrotactile stimulation feedback significantly improved the integration of information flow between brain regions associated with motor-related commands and higher-level cognitive functions, while reducing cognitive workload in the sensory areas of the brain and promoting positive emotions. Despite these promising results, neither neurofeedback modality resulted in a significant improvement in classification accuracy, compared with the absence of feedback. These findings indicate that multimodal neurofeedback can modulate imagery-mediated rehabilitation by enhancing motor-cognitive communication and reducing cognitive effort. In future interventions, incorporating this technique to ease cognitive demands for participants could be crucial for maintaining their motivation to engage in rehabilitation.
Stability of non-Newtonian nanofluid movement with heat/mass transportation passed through a hydro magnetic elongating/contracting sheet: multiple branches solutions
Authors: Yasmin Humaira , Alshehry Azzh Saad , Zeeshan  , Ghanie Abdul Hamid , Shah Rasool 
Published: October 2023

AbstractNanomaterials have found wide applications in many fields, leading to significant interest in the scientific world, in particular automobile thermal control, heat reservoirs, freezers, hybrid control machines, paper creation, cooling organisms, etc. The aim of the present study is to investigate the MHD non-Newtonian nanofluid and time-based stability analysis to verify the stable branch by computing the smallest eigenvalue across a slendering, extending, or shrinking sheet with thermal radiation and chemical reactions. The basic flow equations have been obtained in terms of PDEs, which are then converted to ODEs in dimensionless form via a suitable transformation. Based on the MATLAB software package bvp4c, the numerical solution has been obtained for the system of equations. A comparative study of the present and published work is impressive. The influence of evolving factors such as Prandtl number, Schmidt number, magnetic factor, heat generation/absorption, thermal, thermophoresis factor, chemical factor, second-grade fluid factor, and Brownian number on the velocities, energy, and concentration patterns is discussed through graphs. It is perceived that the temperature distribution enriches owing to the greater magnitude of the heat source. Furthermore, it is observed that a greater magnitude of radiation improves the temperature curves. It is also investigated from the present analysis that concentration and temperature profiles increase due to the growing values of the thermophoresis factor.
The effect of brief exposure to virtual nature on mental wellbeing in adolescents
Authors: Owens Matthew , Bunce Hannah 
Published: October 2023

AbstractAdolescence is a time of multiple transitions and a vulnerability period for mental health difficulties. There are many barriers to the treatment of mental health conditions which is one reason for developing alternatives to help improve efficacy in treatment and prevention. One approach is to use nature-based interventions (NBIs) to improve mental wellbeing. In this experimental proof-of-principle intervention study, we randomly allocated a sample of adolescents to brief exposure (6 min) to either a virtual woodland nature video or a busy train journey and tested the effect on mental wellbeing. Results showed beneficial effects in the nature condition on several self-reported outcomes including stress, relaxation, affect, mood, attention, nature connection and nature spirituality. The intervention was mainly acceptable and feasible to do suggesting that overall brief virtual nature interventions may have utility in a range of mental health contexts for adolescents including as self-help universal or targeted prevention strategies, adjunct to psychological therapy and as preparation for more intensive NBIs. Additionally, brief virtual nature interventions support accessibility for those who may be limited on time, unable to access real-life nature or who may be more biophobic.
Characterisation of AZ31 metal matrix composites reinforced with carbon nanotubes
Authors: Mukunda Sandeep Ganesh , Boppana Satish Babu , Palani I. A. , Dayanand Samuel , Aravinda T. 
Published: October 2023

AbstractThe focus of this study revolves around the synthesis of AZ31 metal matrix composites (MMCs) reinforced with carbon nanotubes (CNTs) using the powder metallurgy technique. Various compositions of CNTs were incorporated into the AZ31 alloy matrix. The sintered specimens were analysed using microstructural characterization and Fourier transform infrared (FTIR) spectroscopy. Furthermore, differential scanning calorimetry (DSC) were conducted to investigate the impact of sintering on the processed composites. Corrosion studies were performed in a sodium chloride (NaCl) medium, and Tafel curves were plotted to assess corrosion behaviour. It was observed that composites enriched with 0.5 wt.% CNTs demonstrated the highest level of corrosion resistance among the synthesized AZ31 metal specimens.
Integrated single-cell and bulk RNA sequencing analysis identified pyroptosis-related signature for diagnosis and prognosis in osteoarthritis
Authors: Chen Yanzhong , Zhang Yaonan , Ge Yongwei , Ren Hong 
Published: October 2023

AbstractOsteoarthritis (OA), a degenerative disease of the joints, has one of the highest disability rates worldwide. This study investigates the role of pyroptosis-related genes in osteoarthritis and their expression in different chondrocyte subtypes at the individual cell level. Using OA-related datasets for single-cell RNA sequencing and RNA-seq, the study identified PRDEGs and DEGs and conducted Cox regression analysis to identify independent prognostic factors for OA. CASP6, NOD1, and PYCARD were found to be prognostic factors. Combined Weighted Gene Correlation Network Analysis with PPI network, a total of 15 hub genes related to pyroptosis were involved in the notch and oxidative phosphorylation pathways, which could serve as biomarkers for the diagnosis and prognosis of OA patients. The study also explored the heterogeneity of chondrocytes between OA and normal samples, identifying 19 single-cell subpopulation marker genes that were significantly different among 7 chondrocyte cell clusters. AGT, CTSD, CYBC, and THYS1 were expressed differentially among different cell subpopulations, which were associated with cartilage development and metabolism. These findings provide valuable insights into the molecular mechanisms underlying OA and could facilitate the development of new therapeutic strategies for this debilitating disease.
Association between latent profile of dietary intake and cardiovascular diseases (CVDs): Results from Fasa Adults Cohort Study (FACS)
Authors: Ariya Mohammad , Sharafi Mehdi , Afrashteh Sima 
Published: October 2023

AbstractCardiovascular diseases (CVDs) have been among the most significant non-communicable diseases. Dietary risks account for the most cause of CVDs mortalities. Evaluating overall dietary patterns (through the Latent profile of dietary intake) can provide a more accurate prediction regarding the prevalence of CVDs. The present cross-sectional study aimed to investigate the relationship between the latent profile of dietary intake and CVDs prevalence. The population of the Fasa Adults Cohort Study was employed to gather the data (n = 8319). A modified FFQ was employed to assess eating behaviors. Minerals, as well as the energy intake and total fiber, were measured using Nutritionist IV software (version 7.0). To estimate the prevalence of CVDs, accurate records of patients' histories were made. Individuals were clustered according to their dietary intake using latent profile analysis. The mean age was 48.75 ± 9.59 years, and 53.28% (4430) were women. 63.9% of participants with low Socioeconomic Status (SES) were in the low-intake profile (P < 0.001), and high SES increases the odds of being in the high-intake profile (ORhigh/low = 2.87, 95% CI 2.55–3.24). The low-intake group had the lowest amount of physical activity (Met) (P < 0.001). The result of multivariate logistic regression revealed that categorized in the low-intake group significantly increased the development of CVDs (OR = 1.32, 95% CI 1.07–1.63, P = 0.010). The mean micronutrients and total fiber, in individuals with a low intake profile, were significantly lower than other groups (P < 0.001). Overall, we estimated that a low intake of all food groups increases the odds of developing CVDs significantly.
Geographically distributed data management to support large-scale data analysis
Authors: Emara Tamer Z. , Trinh Thanh , Huang Joshua Zhexue 
Published: October 2023

AbstractNowadays, several companies prefer storing their data on multiple data centers with replication for many reasons. The data that spans various data centers ensures the fastest possible response time for customers and workforces who are geographically separated. It also provides protecting the information from the loss in case a single data center experiences a disaster. However, the amount of data is increasing at a rapid pace, which leads to challenges in storage, analysis, and various processing tasks. In this paper, we propose and design a geographically distributed data management framework to manage the massive data stored and distributed among geo-distributed data centers. The goal of the proposed framework is to enable efficient use of the distributed data blocks for various data analysis tasks. The architecture of the proposed framework is composed of a grid of geo-distributed data centers connected to a data controller (DCtrl). The DCtrl is responsible for organizing and managing the block replicas across the geo-distributed data centers. We use the BDMS system as the installed system on the distributed data centers. BDMS stores the big data file as a set of random sample data blocks, each being a random sample of the whole data file. Then, DCtrl distributes these data blocks into multiple data centers with replication. In analyzing a big data file distributed based on the proposed framework, we randomly select a sample of data blocks replicated from other data centers on any data center. We use simulation results to demonstrate the performance of the proposed framework in big data analysis across geo-distributed data centers.