Time-Delayed Magnetic Control and Narrowing of X-Ray frequency Spectra in Two-Target Nuclear Forward Scattering

Controlling and narrowing x-ray frequency spectra in magnetically perturbed two-target nuclear forward scattering is theoretically studied. We show that different hard-x-ray spectral redistributions can be achieved by single or multiple switching of magnetic field in nuclear targets. Our scheme can generate x-ray spectral lines with tenfold intensity enhancement and spectral width narrower than four times the nuclear natural linewidth. The present results pave the way towards a brighter and flexible x-ray source for precision spectroscopy of nuclear resonances using modern synchrotron radiation.Comment: 5 pages, 5 figure

Construction and verification of digital electronics contestants' indicators for vocational education in Taiwan

No AbstractKeywords: competency indicator, digital electronics, important-performance analysis, skill competitio

Enhanced Antifungal Bioactivity of Coptis Rhizome Prepared by Ultrafining Technology

The aim of this study was to identify and quantify the bioactive constituents in the methanol extracts of Coptis Rhizome prepared by ultrafining technology. The indicator compound was identified by spectroscopic method and its purity was determined by HPLC. Moreover, the crude extracts and indicator compound were examined for their ability to inhibit the growth of Rhizoctonia solani Kühn AG-4 on potato dextrose agar plates. The indicator compound is a potential candidate as a new plant derived pesticide to control Rhizoctonia damping-off in vegetable seedlings. In addition, the extracts of Coptis Rhizome prepared by ultrafining technology displayed higher contents of indicator compound; they not only improve their bioactivity but also reduce the amount of the pharmaceuticals required and, thereby, decrease the environmental degradation associated with the harvesting of the raw products

Refractory gastric variceal bleeding secondary to splenic vein occlusion associated with abdominal lymphadenopathy

SummarySplenic vein occlusion caused by abdominal lymphadenopathy is rare. We herein present the case of a 80-year-old man with refractory isolated gastric variceal bleeding in the absence of pancreatic or liver disease. Left-sided portal hypertension was confirmed by angiography, and para-aortic lymphadenopathy compressing the splenic vein was identified by serial abdominal computed tomography. Endoscopic sclerosing therapy failed to treat the recurring gastric variceal hemorrhage. Therefore, splenectomy was suggested and the patient was successfully treated. The patient had been variceal bleeding free for 12 months since the surgery. In patients with isolated gastric varices but without advanced liver disease, a variety of diagnostic techniques should be attempted to elucidate the nature of portal hypertension, and left-sided portal hypertension should be suspected. For those cases in which endoscopic treatment failed to treat refractory gastric variceal bleeding, splenectomy can be an effective option

MetaSquare: An integrated metadatabase of 16S rRNA gene amplicon for microbiome taxonomic classification

MOTIVATION: Taxonomic classification of 16S ribosomal RNA gene amplicon is an efficient and economic approach in microbiome analysis. 16S rRNA sequence databases like SILVA, RDP, EzBioCloud and HOMD used in downstream bioinformatic pipelines have limitations on either the sequence redundancy or the delay on new sequence recruitment. To improve the 16S rRNA gene-based taxonomic classification, we merged these widely used databases and a collection of novel sequences systemically into an integrated resource. RESULTS: MetaSquare version 1.0 is an integrated 16S rRNA sequence database. It is composed of more than 6 million sequences and improves taxonomic classification resolution on both long-read and short-read methods. AVAILABILITY AND IMPLEMENTATION: Accessible at https://hub.docker.com/r/lsbnb/metasquare_db and https://github.com/lsbnb/MetaSquare. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Autonomous flying WiFi access point

Unmanned aerial vehicles (UAVs), aka drones, are widely used civil and commercial applications. A promising one is to use the drones as relying nodes to extend the wireless coverage. However, existing solutions only focus on deploying them to predefined locations. After that, they either remain stationary or only move in predefined trajectories throughout the whole deployment. In the open outdoor scenarios such as search and rescue or large music events, etc., users can move and cluster dynamically. As a result, network demand will change constantly over time and hence will require the drones to adapt dynamically. In this paper, we present a proof of concept implementation of an UAV access point (AP) which can dynamically reposition itself depends on the users movement on the ground. Our solution is to continuously keeping track of the received signal strength from the user devices for estimating the distance between users devices and the drone, followed by trilateration to localise them. This process is challenging because our on-site measurements show that the heterogeneity of user devices means that change of their signal strengths reacts very differently to the change of distance to the drone AP. Our initial results demonstrate that our drone is able to effectively localise users and autonomously moving to a position closer to them

A Sliced Inverse Regression (SIR) Decoding the Forelimb Movement from Neuronal Spikes in the Rat Motor Cortex

Several neural decoding algorithms have successfully converted brain signals into commands to control a computer cursor and prosthetic devices. A majority of decoding methods, such as population vector algorithms (PVA), optimal linear estimators (OLE), and neural networks (NN), are effective in predicting movement kinematics, including movement direction, speed and trajectory but usually require a large number of neurons to achieve desirable performance. This study proposed a novel decoding algorithm even with signals obtained from a smaller numbers of neurons. We adopted sliced inverse regression (SIR) to predict forelimb movement from single-unit activities recorded in the rat primary motor (M1) cortex in a water-reward lever-pressing task. SIR performed weighted principal component analysis (PCA) to achieve effective dimension reduction for nonlinear regression. To demonstrate the decoding performance, SIR was compared to PVA, OLE, and NN. Furthermore, PCA and sequential feature selection (SFS) which are popular feature selection techniques were implemented for comparison of feature selection effectiveness. Among SIR, PVA, OLE, PCA, SFS, and NN decoding methods, the trajectories predicted by SIR (with a root mean square error, RMSE, of 8.47 ± 1.32 mm) was closer to the actual trajectories compared with those predicted by PVA (30.41 ± 11.73 mm), OLE (20.17 ± 6.43 mm), PCA (19.13 ± 0.75 mm), SFS (22.75 ± 2.01 mm), and NN (16.75 ± 2.02 mm). The superiority of SIR was most obvious when the sample size of neurons was small. We concluded that SIR sorted the input data to obtain the effective transform matrices for movement prediction, making it a robust decoding method for conditions with sparse neuronal information

Current and state of the art on the electrophysiologic characteristics and catheter ablation of arrhythmogenic right ventricular dysplasia/cardiomyopathy

AbstractArrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) is an inherited genetic disease caused by defective desmosomal proteins, and it has typical histopathological features characterized by predominantly progressive fibro-fatty infiltration of the right ventricle. Clinical presentations of ARVD/C vary from syncope, progressive heart failure (HF), ventricular tachyarrhythmias, and sudden cardiac death (SCD). The 2010 modified Task Force criteria were established to facilitate the recognition and diagnosis of ARVD/C. An implantable cardiac defibrillator (ICD) remains to be the cornerstone in prevention of SCD in patients fulfilling the diagnosis of definite ARVD/C, especially among ARVD/C patients with syncope, hemodynamically unstable ventricular tachycardia (VT), ventricular fibrillation, and aborted SCD. Further risk stratification is clinically valuable in the management of patients with borderline or possible ARVD/C and mutation carriers of family members. However, given the entity of heterogeneous penetrance and non-uniform phenotypes, the standardization of clinical practice guidelines for at-risk individuals will be the next frontier to breakthrough.Antiarrhythmic drugs are prescribed frequently to patients experiencing frequent ventricular tachyarrhythmias and/or appropriate ICD shocks. Amiodarone is the recommended drug of choice. Radiofrequency catheter ablation (RFCA) has been demonstrated to effectively eliminate the drug-refractory VT in patients with ARVD/C. However, the efficacy and clinical prognosis of RFCA via endocardial approach alone was disappointing prior to the era of epicardial approach. In recent years, it has been proven that the integration of endocardial and epicardial ablation by targeting the critical isthmus or eliminating abnormal electrograms within the diseased substrates could yield higher acute success and lower recurrence of ventricular tachyarrhythmias during long-term follow-up. Heart transplantation is the final option for patients with extensive disease, biventricular HF with uncontrollable hemodynamic compromise, and refractory ventricular tachyarrhythmias despite aggressive medical and ablation therapies