as moderate quality, we recommend additional well-designed RCTs with larger sample sizes to validate these findings.

Around 15% of the Hong Kong population was found to suffer from overactive bladder (OAB), but the current available treatments, such as medication, behavioral therapy and physical therapy are unsatisfactory. Previous studies have suggested that acupuncture may have promising effect for OAB, but some limitations on the study design render the evidence questionable. This study aimed to evaluate the effectiveness and safety of acupuncture treatment for patients with OAB in Hong Kong.

One hundred patients with OAB were enrolled. The patients were randomized to receive either active acupuncture or sham needle intervention twice a week for 8 consecutive weeks, and had a follow-up consultation 12weeks after the completion of acupuncture intervention. The primary outcome assessment was the 3-Day Voiding Diary, which records daytime and night-time urinary frequency and symptoms, at the baseline, the end of the 8-week intervention and 12weeks after acupuncture intervention. Secondary outcomes included Urine NGF lev sham acupuncture treatment were able to improve the symptoms of frequency of urgency urinary incontinence, and the daytime and night-time urinary frequency, while only mild adverse effects were found. This project was unable to establish the specific effect of acupuncture for OAB.

Chinese Clinical Trial Registry, ChiCTR-INR-16010048. Registered on 29 Nov 2016.

This study suggests a beneficial effect of acupuncture on improving OAB symptoms. Both active and sham acupuncture treatment were able to improve the symptoms of frequency of urgency urinary incontinence, and the daytime and night-time urinary frequency, while only mild adverse effects were found. This project was unable to establish the specific effect of acupuncture for OAB.Trial registration Chinese Clinical Trial Registry, ChiCTR-INR-16010048. Registered on 29 Nov 2016.Since the first confirmed case of SARS-CoV-2 coronavirus (COVID-19) on March 02, 2020, Saudi Arabia has not reported quite a rapid COVD-19 spread as seen in America and many European countries. Possible causes include the spread of asymptomatic COVID-19 cases. To characterize the transmission of COVID-19 in Saudi Arabia, a susceptible, exposed, symptomatic, asymptomatic, hospitalized, and recovered dynamical model was formulated, and a basic analysis of the model is presented including model positivity, boundedness, and stability around the disease-free equilibrium. It is found that the model is locally and globally stable around the disease-free equilibrium when R0 less then 1. The model parameterized from COVID-19 confirmed cases reported by the Ministry of Health in Saudi Arabia (MOH) from March 02 till April 14, while some parameters are estimated from the literature. The numerical simulation showed that the model predicted infected curve is in good agreement with the real data of COVID-19-infected cases. An analytical expression of the basic reproduction number R0 is obtained, and the numerical value is estimated as R0 ≈ 2.7.In the field of brain-computer interfaces, it is very common to use EEG signals for disease diagnosis. In this study, a style regularized least squares support vector machine based on multikernel learning is proposed and applied to the recognition of epilepsy abnormal signals. The algorithm uses the style conversion matrix to represent the style information contained in the sample, regularizes it in the objective function, optimizes the objective function through the commonly used alternative optimization method, and simultaneously updates the style conversion matrix and classifier during the iteration process parameter. TH5427 chemical structure In order to use the learned style information in the prediction process, two new rules are added to the traditional prediction method, and the style conversion matrix is used to standardize the sample style before classification.

To systematically analyze the existing intelligent rehabilitation mobile applications (APPs) related to distal radius fracture (DRF) and evaluate their features and characteristics, so as to help doctors and patients to make evidence-based choice for appropriate intelligent-assisted rehabilitation.

Literatures which in regard to the intelligent rehabilitation tools of DRF were systematic retrieved from the PubMed, the Cochrane library, Wan Fang, and VIP Data. The effective APPs were systematically screened out through the APP markets of iOS and Android mobile platform, and the functional characteristics of different APPs were evaluated and analyzed.

A total of 8 literatures and 31 APPs were included, which were divided into four categories intelligent intervention, angle measurement, intelligent monitoring, and auxiliary rehabilitation games. These APPs provide support for the patients’ home rehabilitation guidance and training and make up for the high cost and space limitations of traditional rehabilitt. Intelligent rehabilitation APPs play a positive role in the rehabilitation of patients, but the acceptance of the utilization for intelligent rehabilitation APPs is relatively low, which might need follow-up research to address the conundrum.Recently, the hair loss population, alopecia areata patients, is increasing due to various unconfirmed reasons such as environmental pollution and irregular eating habits. In this paper, we introduce an algorithm for preventing hair loss and scalp self-diagnosis by extracting HLF (hair loss feature) based on the scalp image using a microscope that can be mounted on a smart device. We extract the HLF by combining a scalp image taken from the microscope using grid line selection and eigenvalue. First, we preprocess the photographed scalp images using image processing to adjust the contrast of microscopy input and minimize the light reflection. Second, HLF is extracted through each distinct algorithm to determine the progress degree of hair loss based on the preprocessed scalp image. We define HLF as the number of hair, hair follicles, and thickness of hair that integrate broken hairs, short vellus hairs, and tapering hairs.