Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational analysis of cell orientation in response to mechanical stimuli : implications for myocardial repair strategies

Stem cell therapy after myocardial infarction may be improved by combining cells with a biomaterial. One such approach is to embed the cells in small, tissue-like constructs to form microtissues. After delivery, these microtissues will mechanically interact with the myocardium surrounding them. In this study, reasonable levels of microtissue deformation, a possible mechanical stimulus for cells in the microtissue, are estimated using finite element analysis. Our axisymmetric model represents a spherical microtissue embedded in a cylindrical environment, simulating the myocardium. A uniaxial elongation is prescribed to represent macroscale deformation, and microtissue stiffness is varied to simulate the controllability of microtissue mechanical properties. Local strain in the microtissue was between zero and four times the applied strain, indicating that this is a reasonable range of strains to be applied to cells experimentally. Strain heterogeneity depended on the microtissue-environment contact definition, showing the importance of adhesion of the microtissue to the environment.
Adaptive Iterative Splitting Methods for Convection-Diffusion-Reaction Equations

This article proposes adaptive iterative splitting methods to solve Multiphysics problems, which are related to convection–diffusion–reaction equations. The splitting techniques are based on iterative splitting approaches with adaptive ideas. Based on shifting the time-steps with additional adaptive time-ranges, we could embedded the adaptive techniques into the splitting approach. The numerical analysis of the adapted iterative splitting schemes is considered and we develop the underlying error estimates for the application of the adaptive schemes. The performance of the method with respect to the accuracy and the acceleration is evaluated in different numerical experiments. We test the benefits of the adaptive splitting approach on highly nonlinear Burgers’ and Maxwell–Stefan diffusion equations.
Gender and Prison Recidivism: The Influence of Protective and Risk Factor

Recidivism after incarceration is a fundamental concern for the criminal justice system. Although men remain the largest percentage of the prison population, women are entering prison at an increasing frequency. Insufficient research has looked at the influence of prison protective and risk factors on recidivism by gender or any theoretical model to consider this increase in the female prison population. Using data from a large western state in the USA, all male and female inmates incarcerated from 2009 through 2011 are evaluated in terms of protective (education, programming, community ties, relationship status) and risk factors (race/ethnicity, age, homelessness, prison conduct, gang membership, prison sentence length and type) associated with their initial incarceration or recidivism. The findings and implications are subsequently discussed.
Location-Based Social Network's Data Analysis and Spatio-Temporal Modeling for the Mega City of Shanghai, China

The aim of the current study is to analyze and extract the useful patterns from Location-Based Social Network (LBSN) data in Shanghai, China, using different temporal and spatial analysis techniques, along with specific check-in venue categories. This article explores the applications of LBSN data by examining the association between time, frequency of check-ins, and venue classes, based on users’ check-in behavior and the city’s characteristics. The information regarding venue classes is created and categorized by using the nature of physical locations. We acquired the geo-location information from one of the most famous Chinese microblogs called Sina-Weibo (Weibo). The extracted data are translated into the Geographical Information Systems (GIS) format, and after analysis the results are presented in the form of statistical graphs, tables, and spatial heatmaps. SPSS is used for temporal analysis, and Kernel Density Estimation (KDE) is applied based on users’ check-ins with the help of ArcMap and OpenStreetMap for spatial analysis. The findings show various patterns, including more frequent use of LBSN while visiting entertainment and shopping locations, a substantial number of check-ins from educational institutions, and that the density extends to suburban areas mainly because of educational institutions and residential areas. Through analytical results, the usage patterns based on hours of the day, days of the week, and for an entire six months, including by gender, venue category, and frequency distribution of the classes, as well as check-in density all over Shanghai city, are thoroughly demonstrated.
The Attitudes of Physiotherapy Students Toward Occupational Medicine

Diseases and work-related injuries make an important part in the global burden of disease. These are studied, prevented and treated by occupational professionals as well as other health care professionals. Physiotherapists have an important role in rehabilitation of the people suffering from different workrelated injuries and diseases. Our study aims to know the attitudes of the students of Physiotherapy regarding the Occupational Medicine, in its general character, as well as their perceptions about the Albanian reality, the future of this medical science in Albania, and the relations with their profession. An anonymous questionnaire was distributed to the third year students of Physiotherapy at the University Luigj Gurakuqi in Shkodra, in their first lesson of Occupational Medicine. It consisted of 23 questions, some of them in the form of a 5 point Likert. The questionnaire was made in two parts: demographic data and the research data. The questionnaire was completed by 31 students. There is a good level of knowledge of foreign languages, 27 of them know English. The need to study the subject resulted in 3.90 points on a 5 point Likert. The degree of awareness of occupational medicine in Albania resulted in 2.03 points and the implementation of the laws in just 1.90 points, but more than 90% of the students affirm that there is an increased interest on occupational medicine during last 5 years in the country. They unanimously agree about the relationships between their profession and the occupational medicine. The majority of the students are interested about more training, and for more than one half it is a career option, too.
Atomoxetine Does Not Improve Complex Attention in Idiopathic Parkinson's Disease Patients with Cognitive Deficits: A Meta-Analysis

Objectives To evaluate the effects of atomoxetine on complex attention and other neurocognitive domains in idiopathic Parkinson's disease (PD). Methods Interventional trials reporting changes in complex attention and other neurocognitive functions (Diagnostic and Statistical Manual of Mental Disorders-5) following administration of atomoxetine for at least 8 weeks in adults with idiopathic PD were included. Effect sizes (Cohen's d), the standardized mean difference in the scores of each cognitive domain, were compared using a random-effects model (MetaXL version 5.3). Results Three studies were included in the final analysis. For a change in complex attention in PD with mild cognitive impairment (MCI), the estimated effect size was small and nonsignificant (0.16 (95% CI: −0.09, 0.42), n = 42). For changes in executive function, perceptual-motor function, language, social cognition, and learning and memory, the estimated effect sizes were small and medium, but nonsignificant. A deteriorative trend in executive function was observed after atomoxetine treatment in PD with MCI. For a change in global cognitive function in PD without MCI, the estimated effect size was large and significant. Conclusion In idiopathic PD with MCI, atomoxetine does not improve complex attention. Also, a deteriorative trend in the executive function was noted.
Bidirectional Charging in V2G Systems: An In-Cell Variation Analysis of Vehicle Batteries

Vehicle-to-grid (V2G) technology enables bidirectional charging of electric vehicle (EV) and facilitates power grid ancillary services. However, battery pack in EV may develop in-cell dynamic variations over time. This is due to the structural complexity and electrochemical operations in the battery pack. These variations may arise in V2G systems due to: first, additional charging and discharging cycles to power grid; second, external shocks; and third, long exposures to high temperatures. A particular source of these variations is due to faulty sensors. Therefore, it can be argued that the battery packs in EV are highly reliant on the monitoring of these in-cell variations and their impact of propagation with each involved component. In this article, a prediction-based scheme to monitor the health of variation induced sensors is proposed. First, a propagation model is developed to predict the in-cell variations of a battery pack by calculating the covariance using a median-based expectation. Second, a hypothesis model is developed to detect and isolate each variation. This is obtained by deriving a conditional probability-based density function for the measurements. The proposed monitoring framework is evaluated using experimental measurements collected from Li-ion battery pack in EVs. The in-cell variation profiles have been verified using D-SAT Chroma 8000ATS hardware platform. The performance results of the proposed scheme show accurate analysis of these emerged variations.
Is there not a better way to prevent venousthromboembolism after total knee arthroplasty

Background: aspirin at 325 mg twice daily is now included as a nationally approved venous thromboembolism prophy­laxis protocol for low risk total knee arthroplasty patients. The purpose of this study is to examine if there is a difference in deep vein thrombosis occurrence after a limited tourni­quet total knee arthroplasty using aspirin-based prophylaxis with or without extended use of mechanical compression device therapy. Methods: one hundred limited tourniquet total knee ar­throplasty patients, whose deep vein thrombosis risk was managed with aspirin 325 mg twice daily for 3 weeks, were ran­domized to either utilizing an mechanical compression device during hospitalization only or extended use at home up to six weeks post-op. Lower extremity Duplex venous ultrasonogra­phy was completed on the second post-op day, 14 days post-op, and at 3 months post-op to confirm absence of deep vein thrombosis after treatment. Results: the deep vein thrombosis rate for the post-discharge mechanical compression device therapy group was 0 % and 23.1 % for the inpatient mechani­cal compression device group (p < 0.001). All deep vein throm­bosis resolved by 3 months postop. Patient satisfaction was 9.56 ± 0.82 for post-discharge mechanical compression device patients versus 8.50 ± 1.46 for in patient mechanical compres­sion device patients (p < 0.001). Conclusion: limited tourniquet total knee arthroplasty patients that were mobilized early, managed with Aspirin for 3 weeks post-op, and mechanical com­pression device therapy for up to 6 weeks post-op experienced superior deep vein thrombosis prophylaxis than patients receiv­ing mechanical compression device therapy only as an inpatient (p < 0.05). The 0 % incidence of non-symptomatic deep vein thrombosis prevented by Aspirin and extended use mechanical compression device further validates this type of prophylaxis in low deep vein thrombosis risk total knee arthroplasty pa­tients.
Single-pixel hyperspectral imaging using Hadamard transformation

In this paper, we present a single-pixel hyperspectral imager based on Hadamard transformat ion. The imager uses a micromirror array and a resonant scanning mirror to implement spatial and spectral encoding. For a proof of concept, the sensing wavelength of the imager is 450nm to 750nm, but it can easily be applied to the infrared wavelengths. It has high robustness and high frame rate compared with conventional single-pixel hyperspectral imagers. We also introduce a cascading method that can enhance the spatial resolution of the single-pixel hyperspectral imager. Some experimental results are presented in the paper to demonstrate the performance of our proposed system.
Assessment of insulin sensitivity and resistance in non diabetic Punjabi population

Introduction: The pathogenesis of type 2 diabetes mellitus has been closely associated with dysfunctions observed in Insulin formation and pancreatic b cell functioning. Hepatic glucose output and insulin secretion from fasting levels of glucose and insulin have been widely validated clinically and epidemiologically to form a mathematical tool for estimating insulin resistance and b cell function. The tool has been named as the homeostasis Model Assessment tool (HOMA) and QUICK I index. The present study was designed to evaluate various biochemical parameters in two insulin resistance groups established by cutoffs of HOMA index and QUICK I. Materials and Methods: Total 5 00 non diabetic subjects attending the out-patient department of Sri Guru Ram Das Institute Of Medical Sciences and research Vallah, Sri Amritsar were included in the present study. After excluding 23 persons having HBA1C > 7 % we were left with 477 subjects. They were analyzed for Fasting Blood Glucose, HBA1C, S. Insulin and Lipid Profile. HOMA-IR index and QUICK I index were calculated using formulas. On the basis of the cutoffs of the above indices, the non diabetic persons were divided into High and Low insulin resistance groups. Results: Prevalence of insulin resistance in non diabetic general population was 41.5 % as estimated by cutoffs established by QUICK I index. It was much lower when HOMA IR index was used. Conclusion: Quick I is the more sensitive index as compared to HOMA IR for the screening of Insulin resistance. Moreover, the amount of adipose tissue is the risk factor for Insulin resistance and not the sex. Keywords: Insulin Resistance, QUICK I, Modified QUICK I, HOMA Ir.
Complete Evaluation of Cell Mixing and Hydrodynamic Performance of Thin-Layer Cascade Reactor

Microalgae are a great source of food and supplements as well as a potential source for the production of biofuels. However, the operational cost must be reduced to allow viable productions of bulk chemicals such as biofuels from microalgae. One approach to minimize the cost is to increase the efficiency of the photobioreactor. Photobioreactor efficiency is correlated to hydrodynamic mixing, which promotes single cell exposure to sunlight, keeps algae cells in suspension, and homogenizes the distribution of nutrients. Thus, a possible route to enhance the efficiency of the photobioreactor can be identified through an improved understanding of the mixing phenomenon. Therefore, for the current thin-layer cascade reactor, two aspects of its performance—namely, cell mixing and hydrodynamic characteristics—are evaluated under varying mass flow rates, slope angles, water depths, and aspect ratios of the channel by using computational fluid dynamics. The resulting model is validated with experimental data. Results reveal that limited cell mixing is achieved in the thin-layer cascade reactor with increased water depth and large aspect ratios. However, cell mixing is significantly increased at high mass flow rates. The increase in the mass flow rate and slope angle results in increased flow velocity and power consumption.
SIMPLEs: a single-cell RNA sequencing imputation strategy preserving gene modules and cell clusters variation

A main challenge in analyzing single-cell RNA sequencing (scRNASeq) data is to reduce technical variations yet retain cell heterogeneity. Due to low mRNAs content per cell and molecule losses during the experiment (called “dropout”), the gene expression matrix has substantial zero read counts. Existing imputation methods either treat each cell or each gene identically and independently, which oversimplifies the gene correlation and cell type structure. We propose a statistical model-based approach, called SIMPLEs, which iteratively identifies correlated gene modules and cell clusters and imputes dropouts customized for individual gene module and cell type. Simultaneously, it quantifies the uncertainty of imputation and cell clustering. Optionally, SIMPLEs can integrate bulk RNASeq data for estimating dropout rates. In simulations, SIMPLEs performed significantly better than prevailing scRNASeq imputation methods by various metrics. By applying SIMPLEs to several real data sets, we discovered gene modules that can further classify subtypes of cells. Our imputations successfully recovered the expression trends of marker genes in stem cell differentiation and can discover putative pathways regulating biological processes.
Infrastructures of Intimate Data: Mapping the Inbound and Outbound Data Flows of Dating Apps

In this article we engage with methodological challenges that apps pose for empirical analysis and develop an approach to study how apps operate and exchange data between platforms and networks. Complementing previous research on dating apps, our approach involves close attention to the intimacy of app data informed by a relational understanding of infrastructure. We experiment with the research persona as a methodological perspective to collect data at the intersection of five app-infrastructure relations – between app-user, app-device, app-social media, app-network and app-developer –, and initiate or advance an empirical inquiry into the specific materialisations of the data relationships. The final part of the article reflects on the conceptual and methodological implications of this approach beyond the study of dating apps.
Dose-dependent effects of magnesium supplementation on serum and intracellular magnesium concentrations in healthy horses

For magnesium supplementation in horses, dosages for MgO, MgCO3, and MgSO4 were described previously. However, for magnesium as magnesiumaspartate-hydrochloride (MAH) dose-dependent effects on the magnesium levels have not yet been determined in horses. Therefore, the magnesium concentrations in blood lymphocytes, serum, urine and the fractional magnesium excretion in the urine were measured in five healthy adult horses before and after oral supplementation with 15, 30 and 60 mg/kg bodyweight (BW) magnesium as MAH respectively for seven days. There was no wash-out period in between experimental periods. In erythrocytes, the intracellular baseline magnesium concentration and the intracellular magnesium concentration after one week of supplementation with 60 mg/kg BW magnesium were determined. All horses were exclusively fed with hay of which the magnesium concentration was measured each week. All horses were clinically examined daily, including signs of colic and soft feces. There were no significant changes in the magnesium concentration in the diet. Signs of colic, soft feces or other side effects were not observed. The serum magnesium concentration after supplementation with 60 mg/kg BW magnesium as MAH was significantly higher than the baseline and exceeded the reference range in four of five horses. After 15 and 30 mg/ kg BW magnesium as MAH, the serum magnesium concentration showed a significant increase over time. Neither a significant increase of the intracellular magnesium concentration nor significant changes in urine magnesium concentration or fractional excretion were observed. In erythrocytes, a trend for higher magnesium concentrations was found after supplementation with 60 mg/kg BW magnesium as MAH. For short-term supplementation in cases of increased magnesium requirements, these dosages seem effective and the dosages of 15 mg/kg BW and 30 mg/kg BW safe to use. For supplementation with 60 mg/kg magnesium as MAH, veterinary supervision and monitoring of the serum magnesium concentration is recommended.
Online monitoring scheme using principal component analysis through Kullback-Leibler divergence analysis technique for fault detection

Principal component analysis (PCA) is a common tool in the literature and widely used for process monitoring and fault detection. Traditional PCA is associated with the two well-known control charts, the Hotelling’s T2 and the squared prediction error (SPE), as monitoring statistics. This paper develops the use of new measures based on a distribution dissimilarity technique named Kullback-Leibler divergence (KLD) through PCA by measuring the difference between online estimated and offline reference density functions. For processes with PCA scores following a multivariate Gaussian distribution, KLD is computed on both principal and residual subspaces defined by PCA in a moving window to extract the local disparity information. The potentials of the proposed algorithm are afterwards demonstrated through an application on two well-known processes in chemical industries; the Tennessee Eastman process as a reference benchmark and three tank system as an experimental validation. The monitoring performance was compared to recent results from other multivariate statistical process monitoring (MSPM) techniques. The proposed method showed superior robustness and effectiveness recording the lowest average missed detection rate and false alarm rates in process fault detection.
Endocrine Disorders in Beta thalassemia Major Patients

Background Thalassemia is the most common hereditary disorder worldwide. The patient's’ survival is dependent on lifetime blood transfusion which leads to iron overload and its toxicity on various organs including endocrine glands. The study aimed to investigate endocrine disorders in patients with Beta-thalassemia major in the Southern Khorasan province, Iran. Materials and Methods In this descriptive cross sectional study of the 42 patients with Beta thalassemia major blood samples were taken in the fasting to check laboratory tests such as fasting blood sugar, calcium, phosphorous, thyroid stimulating hormone (TSH), thyroxine (T4), luteinizing hormone (LH), follicle stimulating hormone (FSH), parathyroid hormone (PTH), Ferritin. Data analyzed using SPSS version 16.0 software. Results 85.7% of patients had endocrine disorders. The most common endocrine abnormalities were hypogonadism (71.4%), hypoparathyroidism (21.4%), diabetes (14.3%), and hypothyroidism (7.2%), respectively. Conclusion Our results concluded that endocrine evaluation must be carried out regularly in patients with thalassemia major. Patients who have abnormal endocrine laboratory results should be reevaluated for compliance with chelation therapy and the transfusion program.
Social Inclusion beyond Borders : Utilization of Migrant Capital in Transnational and Diaspora Communities

This thematic issue explores the processes and dynamics involved in how different forms of migrant capital are employed and how these relate to processes of social inclusion. Leaning on a Bourdieusian approach, we wish to move beyond existing descriptive studies and theorise the role migration plays in the accumulation, conversion and utilisation of various forms of capital by migrant communities and their members. The articles demonstrate how migrant capital can function as a resource created by migrants during the migration process, or as an outcome of it, and are potentially available to their family members. The articles illustrate via case studies from different national contexts how transnational migrants or members of migrant communities create, accumulate and employ diverse forms of capital in their efforts to achieve inclusion in destination and sending societies.