Muscle synergies after stroke are correlated with perilesional high gamma.

Movements can be factored into modules termed "muscle synergies". After stroke, abnormal synergies are linked to impaired movements; however, their neural basis is not understood. In a single subject, we examined how electrocorticography signals from the perilesional cortex were associated with synergies. The measured synergies contained a mix of both normal and abnormal patterns and were remarkably similar to those described in past work. Interestingly, we found that both normal and abnormal synergies were correlated with perilesional high gamma. Given the link between high gamma and cortical spiking, our results suggest that perilesional spiking may organize synergies after stroke

Training Neural Networks to Pilot Autonomous Vehicles: Scaled Self-Driving Car

This project explores the use of deep convolutional neural networks in autonomous cars. Successful implementation of autonomous vehicles has many societal benefits. One of the main benefits is its potential to significantly reduce traffic accidents. In the United States, the National Highway Traffic Safety Administration states that human error is at fault for 93% of automotive crashes. Robust driverless vehicles can prevent many of these collisions. The main challenge in developing autonomous vehicles today is how to create a system that is able to accurately perceive and process the world around it. In 2016, NVIDIA successfully trained a deep convolutional neural network to map raw images from a single front-facing camera into steering commands. Today, automotive companies such as Google’s Waymo, and Tesla’s Autopilot, utilize deep convolutional neural networks to control their autonomous vehicles. The goal of this project is to evaluate how well a recurrent neural network and categorical output perform when combined with NVIDIA’s platform. These models’ performances are then evaluated on a scaled self driving car and compared to a human driver. NVIDIA’s model combined with a RNN is able to keep the car within 6.1 cm of a human driver’s path

Ethanol Ablation of a Peripheral Nerve Sheath Tumor Presenting as a Small Bowel Obstruction.

Ethanol has historically been used as an ablative agent for a variety of lesions. One of the more common applications of this technique is celiac plexus neurolysis; however, recent reports have suggested a role for the endoscopic alcohol ablation of a variety of solid and cystic lesions. We report a novel case of endoscopic ethanol ablation of a peripheral nerve sheath tumor presenting as a small bowel obstruction

Computer Assisted Language Learning Based on Corpora and Natural Language Processing : The Experience of Project CANDLE

This paper describes Project CANDLE, an ongoing 3-year project which uses various corpora and NLP technologies to construct an online English learning environment for learners in Taiwan. This report focuses on the interim results obtained in the first eighteen months. First, an English-Chinese parallel corpus, Sinorama, was used as the main course material for reading, writing, and culture-based learning courses. Second, an online bilingual concordancer, TotalRecall, and a collocation reference tool, TANGO, were developed based on Sinorama and other corpora. Third, many online lessons, including extensive reading, verb-noun collocations, and vocabulary, were designed to be used alone or together with TotalRecall and TANGO. Fourth, an online collocation check program, MUST, was developed for detecting V-N miscollocation and suggesting adequate collocates in student’s writings based on the hypothesis of L1 interference and the database of BNC and the bilingual Sinorama Corpus. Other computational scaffoldings are under development. It is hoped that this project will help intermediate learners in Taiwan enhance their English proficiency with effective pedagogical approaches and versatile language reference tools

EUS-guided portal pressure gradient measurement with a simple novel device: a human pilot study.

Background and aimsPortal hypertension is a serious adverse event of liver cirrhosis. Recently, we developed a simple novel technique for EUS-guided portal pressure gradient (PPG) measurement (PPGM). Our animal studies showed excellent correlation between EUS-PPGM and interventional radiology-acquired PPGM. In this video we demonstrate the results of the first human pilot study of EUS-PPGM in patients with liver disease.MethodsEUS-PPGM was performed by experienced endosonographers using a linear echoendoscope, a 25-gauge FNA needle, and a novel compact manometer. The portal vein and hepatic vein (or inferior vena cava) were targeted by use of a transgastric or transduodenal approach. Feasibility was defined as successful PPGM in each patient. Safety was based on adverse events captured in a postprocedural interview.ResultsTwenty-eight patients underwent EUS-PPGM with 100% technical success and no adverse events. PPG ranged from 1.5 to 19 mm Hg and had excellent correlation with clinical parameters of portal hypertension, including the presence of varices (P = .0002), PH gastropathy (P = .007), and thrombocytopenia (P = .036).ConclusionThis novel technique of EUS-PPGM using a 25-gauge needle and compact manometer is feasible and appears safe. Given the availability of EUS and the simplicity of the manometry setup, EUS-guided PPG may represent a promising breakthrough for procuring indispensable information in the management of patients with liver disease

Integrating spatial and temporal approaches for explaining bicycle crashes in high-risk areas in Antwerp (Belgium)

The majority of bicycle crash studies aim at determining risk factors and estimating crash risks by employing statistics. Accordingly, the goal of this paper is to evaluate bicycle-motor vehicle crashes by using spatial and temporal approaches to statistical data. The spatial approach (a weighted kernel density estimation approach) preliminarily estimates crash risks at the macro level, thereby avoiding the expensive work of collecting traffic counts; meanwhile, the temporal approach (negative binomial regression approach) focuses on crash data that occurred on urban arterials and includes traffic exposure at the micro level. The crash risk and risk factors of arterial roads associated with bicycle facilities and road environments were assessed using a database built from field surveys and five government agencies. This study analysed 4120 geocoded bicycle crashes in the city of Antwerp (CA, Belgium). The data sets covered five years (2014 to 2018), including all bicycle-motorized vehicle (BMV) crashes from police reports. Urban arterials were highlighted as high-risk areas through the spatial approach. This was as expected given that, due to heavy traffic and limited road space, bicycle facilities on arterial roads face many design problems. Through spatial and temporal approaches, the environmental characteristics of bicycle crashes on arterial roads were analysed at the micro level. Finally, this paper provides an insight that can be used by both the geography and transport fields to improve cycling safety on urban arterial roads