Radiofrequency ablation of osteoid osteoma at the base of the coracoid process: Report of two cases.

If you encounter an unexplained case of bone marrow edema in a young patient, consider the possibility of osteoid osteoma (OO). Even in the presence of a nidus near vital structures, RFA can safely be used to treat OO.

Investigating the Combined Effects of Fascial Distortion Model Manual Therapy and Balance-Strength Training in Individuals with Chronic Ankle Instability.

BACKGROUND: The Fascial Distortion Model (FDM) is a relatively new manual therapy approach in the field of musculoskeletal physical therapy, and its potential effectiveness in treating chronic ankle instability (CAI) remains unexplored. METHODS: A randomized controlled trial with 23 participants was conducted. Patients were randomly assigned to either the FDM + balance-strength training (BST) group (n = 8), receiving extra FDM sessions weekly in addition to two sessions of BST, or the BST group (n = 7). Healthy controls (n = 8) did not receive any treatment and participated only in pre- and post-test measurements. Objective measurements including Y-Balance Test Lower Quarter (YBT-LQ), Flamingo Balance Test (FBT), Weight-Bearing Lunge Test (WBLT), ankle joint range of motion (ROM), and Cumberland Ankle Instability Tool (CAIT) were recorded at baseline and the end of the intervention. The results demonstrated significant differences between the FDM + BST and BST groups for supination ROM (p = 0.008) and similarly for WBLT (p = 0.041), FBT (p = 0.40), YBT-LQ (p = 0.023), and CAIT score (p = 0.008). Moreover, while both groups demonstrated significant improvement at the post-test compared with their pre-test for plantarflexion and pronation ROM, WBLT, and CAIT score, the FDM + BST group demonstrated significant improvements in supination ROM, FBT, and YBT-LQ. CONCLUSION: Our study suggests that the addition of FDM concepts to a BST may lead to enhanced improvements in ankle ROM, static and dynamic balance, and self-reported outcomes in individuals with CAI compared to BST.

Quantum non-Markovianity, quantum coherence and extractable work in a general quantum process.

A key concept in quantum thermodynamics is extractable work, which specifies the maximum amount of work that can be extracted from a quantum system. Different quantities are used to measure extractable work, the most prevalent of which are ergotropy and the difference between the non-equilibrium and equilibrium quantum free energies. Using the latter, we investigate the evolution of extractable work when an open quantum system undergoes a general quantum process described by a completely-positive and trace-preserving dynamical map. We derive a fundamental equation of thermodynamics for such processes as a relation between the distinct sorts of energy change in such a way that the first and the second law of thermodynamics are combined. We then identify the contributions from the reversible and irreversible processes in this equation and demonstrate that they are respectively responsible for the evolution of heat and extractable work of the open quantum system. Furthermore, we show how this correspondence between irreversibility and extractable work has the potential to provide a clear explanation of how the quantum properties of a system affect its extractable work evolution. Specifically, we establish this by directly connecting the change in extractable work with the change in standard quantifiers of quantum non-Markovianity and quantum coherence during a general quantum process. We illustrate these results with two examples.

Effect of aerobic training with silymarin consumption on glycemic indices and liver enzymes in men with type 2 diabetes.

This study investigated the effect of eight weeks of aerobic training (AT) combined with silymarin (S)consumption on glycemic indices and liver enzymes in men with type 2 diabetes (T2D). In this clinical trial, 60 middle-aged male volunteers were randomly divided into 4 groups, including: (1) C + placebo(C) (2) AT + placebo (3), S and (4) AT + S. AT was performed for eight weeks, three sessions per week, each session for 20-45 minutes at an intensity of 60-85% of maximal heart rate reserve, and S receiving groups consumed 140 mg/kg S daily (in two servings). AT reduced glycemic indices and liver enzymes in men with T2D (p ≤ .05). S decreased blood glucose, insulin, HOMA-IR, AST, ALT and ALP in men with T2D (p ≤ .05). Exercise along with silymarin decreased blood glucose, insulin, HOMA-IR, AST, ALT and ALP. Also, reduction of AST and blood glucose in the AT + S group was more favourable than the effect of S alone (p ≤ .05). It seems that simultaneous AT and S has interactive effects on reducing glycemic indices and liver enzymes in men with T2D.

Sparse representation of brain signals offers effective computation of cortico-muscular coupling value to predict the task-related and non-task sEMG channels: A joint hdEEG-sEMG study.

Cortico-muscular interactions play important role in sensorimotor control during motor task and are commonly studied by cortico-muscular coherence (CMC) method using joint electroencephalogram-surface electromyogram (EEG-sEMG) signals. As noise and time delay between the two signals weaken the CMC value, coupling difference between non-task sEMG channels is often undetectable. We used sparse representation of EEG channels to compute CMC and detect coupling for task-related and non-task sEMG signals. High-density joint EEG-sEMG (53 EEG channels, 4 sEMG bipolar channels) signals were acquired from 15 subjects (30.26 ± 4.96 years) during four specific hand and foot contraction tasks (2 dynamic and 2 static contraction). Sparse representations method was applied to detect projection of EEG signals on each sEMG channel. Bayesian optimization was employed to select best-fitted method with tuned hyperparameters on the input feeding data while using 80% data as the train set and 20% as test set. K-fold (K = 5) cross-validation method was used for evaluation of trained model. Two models were trained separately, one for CMC data and the other from sparse representation of EEG channels on each sEMG channel. Sensitivity, specificity, and accuracy criteria were obtained for test dataset to evaluate the performance of task-related and non-task sEMG channels detection. Coupling values were significantly different between grand average of task-related compared to the non-task sEMG channels (Z = -6.33, p< 0.001, task-related median = 2.011, non-task median = 0.112). Strong coupling index was found even in single trial analysis. Sparse representation approach (best fitted model: SVM, Accuracy = 88.12%, Sensitivity = 83.85%, Specificity = 92.45%) outperformed CMC method (best fitted model: KNN, Accuracy = 50.83%, Sensitivity = 52.17%, Specificity = 49.47%). Sparse representation approach offers high performance to detect CMC for discerning the EMG channels involved in the contraction tasks and non-tasks.

Using latent class clustering and binary logistic regression to model Australian cyclist injury severity in motor vehicle-bicycle crashes.

INTRODUCTION: In recent years, Australia is seeing an increase in the total number of cyclists. However, the rise of serious injuries and fatalities to cyclists has been a major concern. Understanding the factors affecting the fatalities and injuries of bicyclists in crashes with motor vehicles is important to develop effective policy measures aimed at improving the safety of bicyclists. This study aims to identify the factors affecting motor vehicle-bicycle (MVB) crashes in Victoria, Australia and introducing effective countermeasures for the identified risk factors. METHOD: A data set of 14,759 MVB crash records from Victoria, Australia between 2006 and 2019 was analyzed using the binary logit model and latent class clustering. RESULTS: It was observed that the factors that increase the risk of fatalities and serious injuries of bicyclists (FSI) in all clusters are: elderly bicyclist, not using a helmet, and darkness condition. Likewise, in areas with no traffic control, clear weather, and dry surface condition (cluster 1), high speed limits increase the risk of FSI, but the occurrence of MVB crashes in cross intersection and T-intersection has been significantly associated with a reduction in the risk of FSI. In areas with traffic control and unfavorable weather conditions (cluster 2), wet road surface increases the risk of FSI, but the areas with give way sign and pedestrian crossing signs reduce the risk of FSI. Practical Applications: Recommendations to reduce the risk of fatalities or serious injury to bicyclists are: improvement of road lighting and more exposure of bicyclists using reflective clothing and reflectors, separation of the bicycle and vehicle path in mid blocks especially in high-speed areas, using a more stable bicycle for the older people, monitoring helmet use, improving autonomous emergency braking, and using bicyclist detection technology for vehicles.

Data mining approach to model bus crash severity in Australia.

INTRODUCTION: Buses are different vehicles in terms of dimensions, maneuverability, and driver's vision. Although bus traveling is a safe mode to travel, the number of annual bus crashes cannot be neglected. Moreover, limited studies have been conducted on the bus involved in fatal crashes. Therefore, identification of the contributing factors in the bus involved fatal crashes can reduce the risk of fatality. METHOD: Data set of bus involved crashes in the State of Victoria, Australia was analyzed over the period of 2006-2019. Clustering of crash data was accomplished by dividing them into homogeneous categories, and by implementing association rules discovery on the clusters, the factors affecting fatality in bus involved crashes were extracted. RESULTS: Clustering results show bus crashes with all vehicles except motor vehicles and weekend crashes have a high rate of fatality. According to the association rule discovery findings, the factors that increase the risk of bus crashes with non-motor vehicles are: old bus driver, collision with pedestrians at signalized intersections, and the presence of vulnerable road users. Likewise, factors that increase the risk of fatality in bus involved crashes on weekends are: darkness of roads in high-speed zones, pedestrian presence at highways, bus crashes with passenger car by a female bus driver, and the occurrence of multi-vehicle crashes in high-speed zones. Practical Applications: The study provides a sequential pattern of factors, named rules that lead to fatality in bus involved crashes. By eliminating or improving one or all of the factors involved in rules, fatal bus crashes may be prevented. The recommendations to reduce fatality in bus crashes are: observing safe distances with the buses, using road safety campaigns to reduce pedestrians' distracted behavior, improving the lighting conditions, implementing speed bumps and rumble strips in high-speed zones, installing pedestrian detection systems on buses and setting special bus lanes in crowded areas.

A Mixed-Perception Approach for Safe Human-Robot Collaboration in Industrial Automation.

Digital-enabled manufacturing systems require a high level of automation for fast and low-cost production but should also present flexibility and adaptiveness to varying and dynamic conditions in their environment, including the presence of human beings; however, this presence of workers in the shared workspace with robots decreases the productivity, as the robot is not aware about the human position and intention, which leads to concerns about human safety. This issue is addressed in this work by designing a reliable safety monitoring system for collaborative robots (cobots). The main idea here is to significantly enhance safety using a combination of recognition of human actions using visual perception and at the same time interpreting physical human-robot contact by tactile perception. Two datasets containing contact and vision data are collected by using different volunteers. The action recognition system classifies human actions using the skeleton representation of the latter when entering the shared workspace and the contact detection system distinguishes between intentional and incidental interactions if physical contact between human and cobot takes place. Two different deep learning networks are used for human action recognition and contact detection, which in combination, are expected to lead to the enhancement of human safety and an increase in the level of cobot perception about human intentions. The results show a promising path for future AI-driven solutions in safe and productive human-robot collaboration (HRC) in industrial automation.

Iranian Joint Registry (Iranian National Hip and Knee Arthroplasty Registry).

Periodic evaluation and monitoring the health and economic outcome of joint replacement surgery is a common and popular process under the territory of joint registries in many countries. In this article we introduce the methodology used for the foundation of the National Iranian Joint Registry (IJR) with a joint collaboration of the Social Security Organization (SSO) and academic research departments considering the requirements of the Iran's Ministry of Health and Education.

Preparation and characterization of physicochemical properties of N, N-diethyl-meta-toluamide niosomes.

INTRODUCTION: The insect repellent compounds are used to protect humans, animals and plants against insect bites. Aromatic amides have insect repellent effects. N,N-diethyl-meta-toluamide (DEET) (C12 H17 NO) is one of the best insect repellents has been used for many years. DEET is a colorless, odorless liquid that is approximately insoluble in water and soluble in glycerin, ethanol, and isopropyl alcohol. Due to the solubility problem of DEET, its topical formulations usually have alcoholic bases, but these kind of formulations increase skin permeation and also systemic absorption of DEET, which leads to some toxic effects. The main goal of this study was to prepare the formulation of DEET niosomes in a topical dosage form with suitable stability properties. MATERIALS AND METHODS: Three different methods were used to prepare niosome formulations: Dehydration rehydration vesicle method, direct mixing method, homogenizer method. Sorbitan surfactants, cholesterol, polyoxyethylenecetyl, phosphate buffer (pH 7.4), and charge inductive compounds like cetyltrimethylammonium bromide were used to provide a net negative charge to the final membrane structure. A high-performance liquid chromatography method was then used for the determination of the loaded DEET. RESULTS: A large number of niosomes were multi-layered and have a spherical shape. In comparison, syringe method against direct mixing is more appropriate because of creation MLV and uniform niosomes but the best method is homogenizer method. Drug entrapment was between 14% and 21% in selected formulation. CONCLUSION: According to this study, homogenizing method can be used for formulation of DEET in niosome form in topical formulations.