Unsupervised, piecewise linear decoding enables an accurate prediction of muscle activity in a multi-task brain computer interface.

Objective: Creating an intracortical brain-computer interface (iBCI) capable of seamless transitions between tasks and contexts would greatly enhance user experience. However, the nonlinearity in neural activity presents challenges to computing a global iBCI decoder. We aimed to develop a method that differs from a globally optimized decoder to address this issue.

Tactile edges and motion via patterned microstimulation of the human somatosensory cortex.

Intracortical microstimulation (ICMS) of somatosensory cortex evokes tactile sensations whose properties can be systematically manipulated by varying stimulation parameters. However, ICMS currently provides an imperfect sense of touch, limiting manual dexterity and tactile experience. Leveraging our understanding of how tactile features are encoded in the primary somatosensory cortex (S1), we sought to inform individuals with paralysis about local geometry and apparent motion of objects on their skin.

Optimising fatigue, abdominal pain and faecal incontinence in people with inflammatory bowel disease (IBD-BOOST Optimise): feasibility study of a checklist and algorithm for initial nurse-led management.

Objective: Many people with inflammatory bowel disease (IBD) experience fatigue, pain and faecal incontinence that some feel are inadequately addressed. It is unknown how many have potentially reversible medical issues underlying these symptoms.

Methods: We conducted a study testing the feasibility of a patient-reported symptom checklist and nurse-administered management algorithm ('Optimise') to manage common medical causes of IBD-related fatigue, pain and faecal incontinence.

EdgeNet: An End-to-End Deep Neural Network Pretrained with Synthetic Data for a Real-World Autonomous Driving Application.

This paper presents a novel end-to-end architecture based on edge detection for autonomous driving. The architecture has been designed to bridge the domain gap between synthetic and real-world images for end-to-end autonomous driving applications and includes custom edge detection layers before the Efficient Net convolutional module. To train the architecture, RGB and depth images were used together with inertial data as inputs to predict the driving speed and steering wheel angle.

Replication-competent recombinant porcine reproductive and respiratory syndrome (PRRS) virus expressing antiviral cytokine interferon-ω5 as a modified live virus vaccine.

Porcine reproductive and respiratory syndrome (PRRS), caused by the highly variable PRRS virus (PRRSV), presents a significant challenge to the swine industry due to its pathogenic and economic burden. The virus evades host immune responses, particularly interferon (IFN) signaling, through various viral mechanisms. Traditional vaccines have shown variable efficacy in the field, prompting the exploration of novel vaccination strategies.