Deep Learning Techniques to Characterize the Pseudogene and the - Gene as Drug Potential Targets in Pancreatic Cancer Patients.

The molecular explanation about why some pancreatic cancer (PaCa) patients die early and others die later is poorly understood. This study aimed to discover potential novel markers and drug targets that could be useful to stratify and extend expected survival in prospective early-death patients. We deployed a deep learning algorithm and analyzed the gene copy number, gene expression, and protein expression data of death versus alive PaCa patients from the GDC cohort.

Forearm sEMG data from young healthy humans during the execution of hand movements.

This work provides a complete dataset containing surface electromyography (sEMG) signals acquired from the forearm with a sampling frequency of 1000 Hz. The dataset is named WyoFlex sEMG Hand Gesture and recorded the data of 28 participants between 18 and 37 years old without neuromuscular diseases or cardiovascular problems. The test protocol consisted of sEMG signals acquisition corresponding to ten wrist and grasping movements (extension, flexion, ulnar deviation, radial deviation, hook grip, power grip, spherical grip, precision grip, lateral grip, and pinch grip), considering three repetitions for each gesture.

Home-care nursing controlled mobile robot with vital signal monitoring.

This study describes the development (design, construction, instrumentation, and control) of a nursing mobile robotic device to monitor vital signals in home-cared patients. The proposed device measures electrocardiography potentials, oxygen saturation, skin temperature, and non-invasive arterial pressure of the patient. Additionally, the nursing robot can supply assistance in the gait cycle for people who require it.

Puma () in the Neighborhood? Records Near Human Settlements and Insights into Human-Carnivore Coexistence in Central Chile.

The wildland-urban interface lies at the confluence of human-dominated and wild landscapes-creating a number of management and conservation challenges. Wildlife sightings near human settlements have appeared to increase in the last years. This article reports 51 records of presences, sightings, and livestock attacks of , a large-sized felid, collected from 2012 to 2020 across the O'Higgins region in central Chile.

Adaptive sliding-mode controller of a lower limb mobile exoskeleton for active rehabilitation.

This study describes the design, instrumentation and control of an exoskeleton for lower limb children rehabilitation with nine degrees of freedom. Three degrees of freedom in each leg exert the movements of hip, knee and ankle in the sagittal plane, and three control the drive track system composed by a caterpillar-like robot. The control scheme presents a model free decentralized output feedback adaptive high-order sliding mode control to solve the trajectory tracking problem in each degree of freedom of the exoskeleton.

Robust synchronization of master-slave chaotic systems using approximate model: An experimental study.

Robust synchronization of master slave chaotic systems are considered in this work. First an approximate model of the error system is obtained using the ultra-local model concept. Then a Continuous Singular Terminal Sliding-Mode (CSTSM) Controller is designed for the purpose of synchronization.

Quasi-minimal active disturbance rejection control of MIMO perturbed linear systems based on differential neural networks and the attractive ellipsoid method.

This study addresses the problem of designing an output-based controller to stabilize multi-input multi-output (MIMO) systems in the presence of parametric disturbances as well as uncertainties in the state model and output noise measurements. The controller design includes a linear state transformation which separates uncertainties matched to the control input and the unmatched ones. A differential neural network (DNN) observer produces a nonlinear approximation of the matched perturbation and the unknown states simultaneously in the transformed coordinates.

Adaptive Unknown Input Estimation by Sliding Modes and Differential Neural Network Observer.

In this paper, a differential neural network (DNN) implemented as a robust observer estimates the dynamics of perturbed uncertain nonlinear systems affected by exogenous unknown inputs. In the first stage, the identification error converges into a neighborhood around the origin. Then, the second-order sliding mode supertwisting algorithm implemented as a robust exact differentiator reconstructed the unknown inputs.

Super-twisting sliding mode differentiation for improving PD controllers performance of second order systems.

Designing a proportional derivative (PD) controller has as main problem, to obtain the derivative of the output error signal when it is contaminated with high frequency noises. To overcome this disadvantage, the supertwisting algorithm (STA) is applied in closed-loop with a PD structure for multi-input multi-output (MIMO) second order nonlinear systems. The stability conditions were analyzed in terms of a strict non-smooth Lyapunov function and the solution of Riccati equations.