Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional effects of kinesiology taping for medial plica syndrome: a prospective randomized controlled trial

ABSTRACT Background Medial plica syndrome (MPS) is a common yet overlooked cause of anterior knee pain. The treatment options for MPS include a variety of conservative approaches, however, the effect of kinesiology taping (KT), which is a feasible and effective treatment choice for musculoskeletal pathologies, has not been studied. Objectives We investigated the efficacy of KT in addition to exercise in terms of pain severity, pain threshold, functional muscle strength of lower extremity, dynamic balance, functional status, and quality of life in patients with MPS. Methods Eighty participants with MPS were randomly and equally divided into two groups: 1) the KT group, which received KT in addition to a 6-week exercise program; and 2) the control group, which received the 6-week exercise program alone. The following evaluations were conducted before and after the treatment; pain threshold, pain severity, disability level, functional strength and dynamic balance of the lower extremity, and quality of life. Results Pain intensity decreased during activity, at rest, and night (KT group p < .001; control group p ≤ 0.013), and pain thresholds increased (KT group p < .001; control group p = .008) in both groups, however, the after treatment measures were better in the KT group (p ≤ 0.012). The time taken to complete the stairs up and down test decreased in both groups (KT group p < .001, control group p = .007) with a better outcome in the KT group (p = .024). Disability scores improved significantly in the KT only (p < .001). The quality of life improved in both groups (KT group p < .001; control group p = .005). Conclusions While exercise therapy is beneficial in MPS treatment for functionality and pain relief; KT, in addition to exercise, improved symptoms and decreased impairment more efficiently than exercise alone in patients with MPS in our study, and it is thus a favorable treatment option for MPS.
The Nature of the Static and Kinetic Coefficients of Friction

Experiments have been carried out to determine the transition between static and kinetic conditions when stationary metal surfaces are set into motion, a simple method being used which measures the energy that has to be given to one of the bodies to start it moving. The method is confined to cases in which the static coefficient exceeds the kinetic. Using a load of 1 kg and metal surfaces of various kinds, it is found that the static coefficient persists for distances of the order of 10−4 cm, and then gradually falls off to values corresponding to the kinetic coefficient. This behavior is shown to be consistent with a simple model based on the assumption that the friction force is needed to shear metallic junctions formed between the metal surfaces. The action of boundary lubricants is discussed, and it is shown that they can act either by diminishing the metallic interaction directly, or by preventing its increase during the sliding process.
Artificial intelligence-based myocardial texture analysis in etiological differentiation of left ventricular hypertrophy

Background Transthoracic echocardiography (TTE) is widely used in clinics to evaluate left ventricular hypertrophy (LVH). However, TTE is usually insufficient for the etiological diagnoses when morphological and functional features are nonspecific. With the booming of computer science and artificial intelligence (AI), previous literature has reported the application of radiomics based on cardiac magnetic resonance imaging, cardiac computed tomography and TTE in diagnosing several myocardial abnormalities, such as myocardial infarction, myocarditis, cardiac amyloidosis, and hypertrophic cardiomyopathy (HCM). In this study, we explored the possibility of using myocardial texture features in differentiating HCM, hypertensive heart disease (HHD) and uremic cardiomyopathy (UCM) based on echocardiography. To our knowledge, this was the first study to explore TTE myocardial texture analysis for multiple LVH etiology differentiation. Methods TTE images were reviewed retrospectively from January 2018 to collect 50 cases for each group of HHD, HCM and UCM. The apical four chamber view was retrieved. Seventeen first-order statistics and 60 gray level co-occurrence matrix (GLCM) features were extracted for statistics and classification test by support vector machine (SVM). Results Of all the parameters, entropy of brightness (EtBrt), standard deviation (Std), coefficient of variation (CoV), skewness (Skew), contrast7 (Cont7) and homogeneity5 (Hm5) were found statistically significant among the three groups (all P<0.05) and with acceptable reproducibility (intraobserver and interobserver ICC >0.50). As a result, HCM showed the most homogeneous myocardial texture, and was significantly different from HHD and UCM (all six features: P≤0.005). HHD appeared slightly more homogeneous than UCM, as only EtBrt and CoV were significant (P=0.011 and P=0.008). According to higher areas under the receiver operating characteristic curve (AUC) (>0.50), EtBrt, Std, and CoV were selected for test of classification as a combination of features. The AUC derived from SVM model was slightly improved compared with those of EtBrt, Std and CoV individually. Conclusions AI-based myocardial texture analysis using ultrasonic images may be a potential approach to aiding LVH etiology differentiation.
Effects of the Attention Training Technique on Brain Activity in Healthy University Students Assessed by EEG Source Imaging

This study aimed to investigate the neurocognitive effects of the Attention Training Technique (ATT) on brain activity in healthy participants. The participants included 20 university students who were asked to practice ATT as a homework assignment for 20 days. The intracerebral source localization of their electroencephalogram during rest and the ATT task, which comprised selective attention, attention switching, and divided attention conditions, was evaluated by standardized low-resolution brain electromagnetic tomography. Brain activity during rest was subtracted from that during the ATT task, and that was compared before and after the homework assignment. The results for the divided attention condition indicated significantly decreased alpha 1 frequency band power in the left orbital frontal cortex (OFC) and alpha 2 power in the right inferior temporal cortex. Further, decreased alpha 1 power in the left OFC correlated with reduced subjective difficulty during the divided attention condition. One possibility is that the brain activity changed as the effect of ATT practice, although this study cannot confirm causality. Further studies are required which include a control group that would complete similar training without the ATT task.
Immunobiology and Application of Aloe vera-Based Scaffolds in Tissue Engineering

Aloe vera (AV), a succulent plant belonging to the Liliaceae family, has been widely used for biomedical and pharmaceutical application. Its popularity stems from several of its bioactive components that have anti-oxidant, anti-microbial, anti-inflammatory and even immunomodulatory effects. Given such unique multi-modal biological impact, AV has been considered as a biomaterial for regenerative medicine and tissue engineering applications, where tissue repair and neo-angiogenesis are vital. This review outlines the growing scientific evidence that demonstrates the advantage of AV as tissue engineering scaffolds. We particularly highlight the recent advances in the application of AV-based scaffolds. From a tissue engineering perspective, it is pivotal that the implanted scaffolds strike an appropriate foreign body response to be well-accepted in the body without complications. Herein, we highlight the key cellular processes that regulate the foreign body response to implanted scaffolds and underline the immunomodulatory effects incurred by AV on the innate and adaptive system. Given that AV has several beneficial components, we discuss the importance of delving deeper into uncovering its action mechanism and thereby improving material design strategies for better tissue engineering constructs for biomedical applications.
Characteristics of the Oxidative Status in Dairy Calves Fed at Different Milk Replacer Levels and Weaned at 14 Weeks of Age

A paradigm shift in the way of rearing heifer calves from restricted feeding and early weaning towards greater feed allowances and later weaning ages is ongoing. We aimed at characterizing the oxidative status in Holstein heifer calves fed with milk replacer (MR) at either a restrictive (RES) or a high (HIGH) level for 14 weeks. We compared two groups: HIGH (10 L MR/d, n = 18) and RES (5.7 L/d, n = 19) from day five until week 14 of life. In blood samples collected at birth, and then fortnightly from week 8–16, and in week 20, the antioxidative capacity measured as ferric reducing ability of plasma (FRAP), oxidative damage of lipids measured as thiobarbituric acid reactive substances (TBARS) and oxidative damage of proteins measured as advanced oxidation products of proteins (AOPP), free radicals measured as reactive oxidative metabolites (dROM), and the glutathione peroxidase (GSH-Px) activity, as well as leptin, adiponectin and haptoglobin were assessed. The time course of these variables during the first 20 weeks of life showed characteristic patterns; group differences were limited to adiponectin, AOPP, and FRAP. RES calves had lower growth rates, showed signs of hunger, but did not differ from HIGH in their intake of solid starter feed and in health status. This work characterizes the changes in oxidative status of dairy calves with increasing age and confirms the benefits of a high feeding plane with regard to welfare and development.
Simulation as a Training Method for Electricity Workers’ Safety

Background: Simulation is a useful method to improve learning and increase the safety of work operations, both for technical and non-technical skills. However, the observation, assessment, and feedback about these skills is particularly complex, because the process needs expert observers, and the feedback could be judgmental and ineffective. Therefore, a structured process to develop effective simulation scenarios and tools for the observation and feedback about performance is crucial. To this aim, in the present research, we developed a training model for electricity distribution workers, based on high fidelity simulation. Methods: We designed simulation scenarios based on real cases, developed, and tested a set of observation and rating forms for the non-technical skills behavioral markers, and we tracked behaviors based on non-verbal cues (physiological and head orientation parameters). Results: The training methodology proved to be highly appreciated by the participants and effective in fostering reflexivity. An in-depth analysis of physiological indexes and behaviors compliant to safety procedures revealed that breath rate and heart rate patterns commonly related with mindful and relaxed states were correlated with compliant behaviors, and patterns typical of stress and anxiety were correlated with non-compliant behaviors. Conclusions: a new training method based on high fidelity simulation, addressing both technical and non-technical skills is now available for fostering self-reflection and safety for electricity distribution workers. Future research should assess the long-term effectiveness of high-fidelity simulation for electricity workers, and should investigate non-invasive and real-time methods for tracking physiological parameters.
Lipid peroxidation metabolites associated with biomarkers of inflammation and oxidation stress in workers handling carbon nanotubes and metal oxide nanoparticles

Abstract The purpose of this study was to assess the effects of lipid peroxidation with occupational exposure to different types of nanomaterials (NMs). In this cross-sectional study, urine and exhaled breath condensate (EBC) samples were collected from 80 NM-handling workers [30 workers handling nano-titanium oxide (nano-TiO2), 28 handling nano-silicon dioxide (nano-SiO2), 22 handling carbon nanotubes (CNTs)], and 69 controls (office workers) from 2010 to 2012. Urinary 8-isoPGF2α, 2,3 dinor-8-isoPGF2α, PGF2α, and EBC 8-iso PGF2α were measured as lipid peroxidation biomarkers in 2013. A significant positive correlation was found between 8-isoPGF2α, 2,3 dinor-8-isoPGF2α, PGF2α, and total isoprostane in urine. Furthermore, significant positive correlations were noted between EBC 8-iso PGF2α and urinary 2,3 dinor-8-isoPGF2α (Spearman correlation r = 0.173, p = 0.035). Exposure to nano-TiO2 resulted in significantly higher levels of urinary 8-isoPGF2α, 2,3 dinor-8-isoPGF2α and PGF2α, even after controlling for confounding factors. Moreover, significant associations and exposure intensity–response relationships between EBC 8-iso PGF2α and NMs were observed in workers, whether handling nano-TiO2, nano-SiO2, or CNTs. Among them, the significant trends were identified based on the intensity of risk levels. These results provided evidence that exposure to nano-TiO2, nano-SiO2, and CNTs may lead to lipid peroxidation in EBC. For routine biomonitoring purposes, this finding, which came through noninvasive methods, may be useful for workers exposed to NMs. Highlights Data regarding the effects of nano-titanium oxide (nano-TiO2), nano-silicon dioxide (nano-SiO2), and carbon nanotubes (CNTs) on lipid peroxidation in workers are limited. 8-Iso PGF2α in exhaled breath condensate of workers exposed to nanoparticles was higher than that of office workers. Exposure to titanium oxide (TiO2) and silica (SiO2) may lead to lipid peroxidation, as indicated by 8-isoPGF2α, 2,3 dinor-8-isoPGF2α, and PGF2α. Examination of lipid peroxidation in EBC has seems to be a useful technique for noninvasive monitoring of workers exposed to nanoparticles.
Direct measurement of the nitrogen content by XPS in self‐passivated TaNx thin films

The nitrogen content in tantalum nitride (TaNx) thin films, where x indicates that TaNx is not generally stoechiometric, can be measured directly by XPS. This is the purpose of the present study. However, the XPS spectra of TaNx present electron energy loss spectroscopy (EELS) peaks that lead to a complex peak fitting, particularly for self‐passivated thin films. A complete peak fitting procedure based upon Tougaard's background, the Doniach‐Sunjic Function and EELS peaks, is presented. It is applied to two self‐passivated TaNx thin films elaborated by reactive sputtering and presenting a different nitrogen content. The physical properties of these surfaces are interpreted in terms of Ta 4f7/2 chemical states directly dependent on the nitrogen content. The main results are discussed and improvements are proposed to the method. Copyright © 2008 John Wiley & Sons, Ltd.
Social Network Analysis in Farm Animals: Sensor-Based Approaches

Simple Summary Social behaviour of farm animals significantly impacts management interventions in the livestock sector and, thereby, animal welfare. Evaluation and monitoring of social networks between farm animals help not only to understand the bonding and agonistic behaviours among individuals but also the interactions between the animals and the animal caretaker. The interrelationship between social and environmental conditions, and the subtle changes in the behaviours of farm animals can be understood and precisely measured only by using sensing technologies. This review aims to highlight the use of sensing technologies in the investigation of social network analysis of farm animals. Abstract Natural social systems within animal groups are an essential aspect of agricultural optimization and livestock management strategy. Assessing elements of animal behaviour under domesticated conditions in comparison to natural behaviours found in wild settings has the potential to address issues of animal welfare effectively, such as focusing on reproduction and production success. This review discusses and evaluates to what extent social network analysis (SNA) can be incorporated with sensor-based data collection methods, and what impact the results may have concerning welfare assessment and future farm management processes. The effectiveness and critical features of automated sensor-based technologies deployed in farms include tools for measuring animal social group interactions and the monitoring and recording of farm animal behaviour using SNA. Comparative analyses between the quality of sensor-collected data and traditional observational methods provide an enhanced understanding of the behavioural dynamics of farm animals. The effectiveness of sensor-based approaches in data collection for farm animal behaviour measurement offers unique opportunities for social network research. Sensor-enabled data in livestock SNA addresses the biological aspects of animal behaviour via remote real-time data collection, and the results both directly and indirectly influence welfare assessments, and farm management processes. Finally, we conclude with potential implications of SNA on modern animal farming for improvement of animal welfare.
Overfishing and habitat loss drive range contraction of iconic marine fishes to near extinction

We used a novel approach to estimate the spatial contraction of sawfish populations and guide recovery efforts. Extinctions on land are often inferred from sparse sightings over time, but this technique is ill-suited for wide-ranging species. We develop a space-for-time approach to track the spatial contraction and drivers of decline of sawfishes. These iconic and endangered shark-like rays were once found in warm, coastal waters of 90 nations and are now presumed extinct in more than half (n = 46). Using dynamic geography theory, we predict that sawfishes are gone from at least nine additional nations. Overfishing and habitat loss have reduced spatial occupancy, leading to local extinctions in 55 of the 90 nations, which equates to 58.7% of their historical distribution. Retention bans and habitat protections are urgently necessary to secure a future for sawfishes and similar species.
An Open-Source Test Environment for Effective Development of MARG-Based Algorithms

This paper presents an open-source environment for development, tuning, and performance evaluation of magnetic, angular rate, and gravity-based (MARG-based) filters, such as pose estimators and classification algorithms. The environment is available in both ROS/Gazebo and MATLAB/Simulink, and it contains a six-degrees of freedom (6 DOF) test bench, which simultaneously moves and rotates an MARG unit in the three-dimensional (3D) space. As the quality of MARG-based estimation becomes crucial in dynamic situations, the proposed test platform intends to simulate different accelerating and vibrating circumstances, along with realistic magnetic perturbation events. Moreover, the simultaneous acquisition of both the real pose states (ground truth) and raw sensor data is supported during these simulated system behaviors. As a result, the test environment executes the desired mixture of static and dynamic system conditions, and the provided database fosters the effective analysis of sensor fusion algorithms. The paper systematically describes the structure of the proposed test platform, from mechanical properties, over mathematical modeling and joint controller synthesis, to implementation results. Additionally, a case study is presented of the tuning of popular attitude estimation algorithms to highlight the advantages of the developed open-source environment.
Synthesis and characterization of polyacrylamide-grafted chitosan hydrogel microspheres for the controlled release of indomethacin†

Microspheres of polyacrylamide-grafted-chitosan crosslinked with glutaraldehyde were prepared and used to encapsulate indomethacin, a nonsteroidal anti-inflammatory drug. The microspheres were produced by the water/oil emulsion technique and encapsulation of indomethacin was carried out before crosslinking of the matrix. The extent of crosslinking was analyzed by Fourier transform infrared spectroscopy and differential scanning calorimetry. Microspheres were characterized for drug-entrapment efficiency, particle size, and water transport into the polymeric matrix as well as for drug-release kinetics. Scanning electron microscopy confirmed the spherical nature and surface morphology of the particles with a mean particle size of 525 μm. Dynamic swelling experiments suggested that, with an increase in crosslinking, the transport mechanism changed from Fickian to non-Fickian. The release of indomethacin depends upon the crosslinking of the network and also on the amount of drug loading. This was further supported by the calculation of drug-diffusion coefficients using the initial time approximation. The drug release in all the formulations followed a non-Fickian trend and the diffusion was relaxation-controlled. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 1525–1536, 2003
A Dynamic Event-Triggered Approach to Recursive Nonfragile Filtering for Complex Networks With Sensor Saturations and Switching Topologies

In this article, the nonfragile filtering issue is addressed for complex networks (CNs) with switching topologies, sensor saturations, and dynamic event-triggered communication protocol (DECP). Random variables obeying the Bernoulli distribution are utilized in characterizing the phenomena of switching topologies and stochastic gain variations. By introducing an auxiliary offset variable in the event-triggered condition, the DECP is adopted to reduce transmission frequency. The goal of this article is to develop a nonfragile filter framework for the considered CNs such that the upper bounds on the filtering error covariances are ensured. By the virtue of mathematical induction, gain parameters are explicitly derived via minimizing such upper bounds. Moreover, a new method of analyzing the boundedness of a given positive-definite matrix is presented to overcome the challenges resulting from the coupled interconnected nodes, and sufficient conditions are established to guarantee the mean-square boundedness of filtering errors. Finally, simulations are given to prove the usefulness of our developed filtering algorithm.
Preoperative Patient-Reported Outcomes in Suspected Low-Grade Glioma: Markers of Disease Severity and Correlations with Molecular Subtypes

This prospective study aims to determine the overall health-related quality of life (HRQoL), functioning, fatigue, and psychological distress preoperatively in patients with suspected diffuse low-grade glioma (dLGG). We were particularly interested if these parameters differed by molecular tumor subtypes: oligodendroglioma, IDHmut astrocytoma and IDHwt astrocytoma. Fifty-one patients answered self-assessed questionnaires prior to operation (median age 51 years; range 19–75; 19 females [37%]). Thirty-five (69%) patients had IDH-mutated tumors, of which 17 were 1p/19q codeleted (i.e., oligodendroglioma) and 18 non-1p/19q codeleted (i.e., IDHmut astrocytoma). A lower overall generic HRQoL was associated with a high level of fatigue (rs = −0.49, p < 0.001), visual disorder (rs = −0.5, p < 0.001), motor dysfunction (rs = −0.51, p < 0.001), depression (rs = −0.54, p < 0.001), and reduced functioning. Nearly half of the patients reported high fatigue (23 out of 51 patients) and anxiety (26/51 patients). Patients with IDHwt had worse generic HRQoL, worse functioning, and more severe fatigue, though differences were not statistically significant between the molecular subtypes. In conclusion, fatigue and anxiety are prominent self-assessed symptoms of patients with suspected dLGG in a preoperative setting, but do not seem to be a reliable method to make assumptions of underlying biology or guide treatment decisions.