Enhancing Autonomous Driving in Urban Scenarios: A Hybrid Approach with Reinforcement Learning and Classical Control.

The use of Deep Learning algorithms in the domain of Decision Making for Autonomous Vehicles has garnered significant attention in the literature in recent years, showcasing considerable potential. Nevertheless, most of the solutions proposed by the scientific community encounter difficulties in real-world applications. This paper aims to provide a realistic implementation of a hybrid Decision Making module in an Autonomous Driving stack, integrating the learning capabilities from the experience of Deep Reinforcement Learning algorithms and the reliability of classical methodologies.

Combination of In Situ Diffraction Experiments and Acoustic Emission Testing to Understand Compression Behavior of Mg-Gd Alloys.

The compressive deformation of the extruded binary Mg-Gd with gadolinium in solid solution has been studied in situ by combining synchrotron diffraction and acoustic emission techniques during compression tests. These two techniques are useful in investigating the evolution of twinning in all its stages. The extruded bars develop a fiber texture with the basal plane parallel to the extrusion direction.

Diagnosis of multiple sclerosis using optical coherence tomography supported by explainable artificial intelligence.

Background/objectives: Study of retinal structure based on optical coherence tomography (OCT) data can facilitate early diagnosis of relapsing-remitting multiple sclerosis (RRMS). Although artificial intelligence can provide highly reliable diagnoses, the results obtained must be explainable.

Subjects/methods: The study included 79 recently diagnosed RRMS patients and 69 age matched healthy control subjects.

Reinforcement Learning-Based Autonomous Driving at Intersections in CARLA Simulator.

Intersections are considered one of the most complex scenarios in a self-driving framework due to the uncertainty in the behaviors of surrounding vehicles and the different types of scenarios that can be found. To deal with this problem, we provide a Deep Reinforcement Learning approach for intersection handling, which is combined with Curriculum Learning to improve the training process. The state space is defined by two vectors, containing adversaries and ego vehicle information.

Early Diagnosis of Multiple Sclerosis Using Swept-Source Optical Coherence Tomography and Convolutional Neural Networks Trained with Data Augmentation.

Background: The aim of this paper is to implement a system to facilitate the diagnosis of multiple sclerosis (MS) in its initial stages. It does so using a convolutional neural network (CNN) to classify images captured with swept-source optical coherence tomography (SS-OCT).

Methods: SS-OCT images from 48 control subjects and 48 recently diagnosed MS patients have been used.

Early diagnosis of multiple sclerosis by OCT analysis using Cohen's d method and a neural network as classifier.

Background: The consequences of inflammation, demyelination, axonal degeneration and neuronal loss in the central nervous system, typical of the development of multiple sclerosis (MS), are manifested in thinning of the retina and optic nerve. The purpose of this work is to diagnose early-stage MS patients based on analysis of retinal layer thickness obtained by swept-source optical coherence tomography (SS-OCT).

Method: OCT (Triton® SS-OCT device -Topcon, Tokyo, Japan-) recordings were obtained from 48 control subjects and 48 recently diagnosed MS patients.

Drive-By-Wire Development Process Based on ROS for an Autonomous Electric Vehicle.

This paper presents the development process of a robust and ROS-based Drive-By-Wire system designed for an autonomous electric vehicle from scratch over an open source chassis. A revision of the vehicle characteristics and the different modules of our navigation architecture is carried out to put in context our Drive-by-Wire system. The system is composed of a Steer-By-Wire module and a Throttle-By-Wire module that allow driving the vehicle by using some commands of lineal speed and curvature, which are sent through a local network from the control unit of the vehicle.

Hepatitis C and HIV combined screening in primary care: A cluster randomized trial.

Hepatitis C virus (HCV) and HIV are major causes of worldwide disease. We aimed to evaluate the effect of a combined screening programme, which included a risk-assessment questionnaire and rapid tests for point-of-care diagnosis, on screening and new diagnosis rates. This prospective, cluster randomized study was carried out in primary care.

Clinical features and evolution of bacterial infection-related acute-on-chronic liver failure.

Background & Aims: Bacterial infections can trigger the development of organ failure(s) and acute-on-chronic liver failure (ACLF). Geographic variations in bacteriology and clinical practice could lead to worldwide differences in ACLF epidemiology, phenotypes and associated outcomes. Herein, we aimed to evaluate regional differences in bacterial infection-related ACLF in patients with cirrhosis admitted to hospital.

A Waypoint Tracking Controller for Autonomous Road Vehicles Using ROS Framework.

Automated Driving Systems (ADSs) require robust and scalable control systems in order to achieve a safe, efficient and comfortable driving experience. Most global planners for autonomous vehicles provide as output a sequence of waypoints to be followed. This paper proposes a modular and scalable waypoint tracking controller for Robot Operating System (ROS)-based autonomous guided vehicles.

Prevalence of HCV infection in a health area of Madrid (Spain): The first step towards microelimination.

Objective: To estimate the prevalence of HCV infection in the general population of a health area through an intervention in Primary Care, differentiating between new diagnoses and infections previously diagnosed but not treated.

Methods: Participants were selected through a risk assessment questionnaire, with all those who gave at least one affirmative answer and all those over 50 years of age undergoing a rapid test. Positive tests were confirmed in the lab by determination of anti-HCV antibodies by chemiluminescent microparticle immunoassay and determination of viraemia.

Impact of a structured HIV testing program in a hospital emergency department and a primary care center.

Introduction: HIV testing guidelines are poorly implemented in most clinical settings. The best screening strategy and healthcare scenario are still unknown. The aim of our study is to evaluate the impact of a structured HIV testing intervention (DRIVE), compared to HIV testing as routinely performed in clinical practice, in two different clinical settings: a primary care center and an emergency department.

Outcome of an HIV education program for primary care providers: Screening and late diagnosis rates.

Background: Late HIV diagnosis remains one of the challenges in combating the epidemic. Primary care providers play an important role in screening for HIV infection. Our study aims to evaluate the relationship between knowledge and barriers to HIV testing and screening outcomes.

A computer-aided diagnosis of multiple sclerosis based on mfVEP recordings.

Introduction: The aim of this study is to develop a computer-aided diagnosis system to identify subjects at differing stages of development of multiple sclerosis (MS) using multifocal visual-evoked potentials (mfVEPs). Using an automatic classifier, diagnosis is performed first on the eyes and then on the subjects.

Patients: MfVEP signals were obtained from patients with Radiologically Isolated Syndrome (RIS) (n = 30 eyes), patients with Clinically Isolated Syndrome (CIS) (n = 62 eyes), patients with definite MS (n = 56 eyes) and 22 control subjects (n = 44 eyes).

Prevalence of vascular risk factors in patients with and without type 2 diabetes mellitus admitted to hospital for stroke in the 2011-2013 period.

Introduction: Stroke and type 2 diabetes mellitus (T2DM) are among the leading causes of morbidity and mortality in Europe.

Objective: To describe the vascular risk factors most prevalent in the Spanish population with and without type 2 diabetes mellitus admitted to hospital for a stroke during the 2011-2013 period.

Material And Methods: Using the Spanish Minimum Basic Data Set from 2011 to 2013, a descriptive, observational epidemiological study was conducted comparing the prevalence rates of vascular risk factors in Spanish patients admitted to hospital for stroke.

Maintaining High Strength in Mg-LPSO Alloys with Low Yttrium Content Using Severe Plastic Deformation.

Alternative processing routes such as powder metallurgy, the extrusion of recycled chips, or equal channel angular pressing (ECAP) have been considered for effective methods of maintaining the high mechanical strength of Mg-Y-Zn alloys containing long-period stacking ordered structures with respect to the alloy processed by the conventional extrusion of as-cast ingots with the advantage of minimizing the yttrium content. A yield stress similar to that found for extruded MgY₂Zn₁ alloy can be attained with only half of the usual yttrium and zinc additions thanks to the grain refinement induced by ECAP processing. The properties of MgY₁Zn subjected to ECAP are maintained up to 200 °C, but superplastic behavior is found above this temperature when the alloy is processed through a powder metallurgy route.

Model-Based Real-Time Non-Rigid Tracking.

This paper presents a sequential non-rigid reconstruction method that recovers the 3D shape and the camera pose of a deforming object from a video sequence and a previous shape model of the object. We take PTAM (Parallel Mapping and Tracking), a state-of-the-art sequential real-time SfM (Structure-from-Motion) engine, and we upgrade it to solve non-rigid reconstruction. Our method provides a good trade-off between processing time and reconstruction error without the need for specific processing hardware, such as GPUs.

Induced gamma band activity from EEG as a possible index of training-related brain plasticity in motor tasks.

The aim of this study was proposing gamma band activity (GBA) as an index of training-related brain plasticity in the motor cortex. Sixteen controls underwent an experimental session where electroencephalography (EEG) activity was recorded at baseline (resting) and during a motor task (hand movements). GBA was obtained from the EEG data at baseline and during the task.

Analysis of Gamma-Band Activity from Human EEG Using Empirical Mode Decomposition.

The purpose of this paper is to determine whether gamma-band activity detection is improved when a filter, based on empirical mode decomposition (EMD), is added to the pre-processing block of single-channel electroencephalography (EEG) signals. EMD decomposes the original signal into a finite number of intrinsic mode functions (IMFs). EEGs from 25 control subjects were registered in basal and motor activity (hand movements) using only one EEG channel.

A Multi-Sensorial Simultaneous Localization and Mapping (SLAM) System for Low-Cost Micro Aerial Vehicles in GPS-Denied Environments.

One of the main challenges of aerial robots navigation in indoor or GPS-denied environments is position estimation using only the available onboard sensors. This paper presents a Simultaneous Localization and Mapping (SLAM) system that remotely calculates the pose and environment map of different low-cost commercial aerial platforms, whose onboard computing capacity is usually limited. The proposed system adapts to the sensory configuration of the aerial robot, by integrating different state-of-the art SLAM methods based on vision, laser and/or inertial measurements using an Extended Kalman Filter (EKF).

Development and Validation of an HIV Risk Exposure and Indicator Conditions Questionnaire to Support Targeted HIV Screening.

The aim of our study was to develop a Spanish-structured HIV risk of exposure and indicator conditions (RE&IC) questionnaire. People attending to an emergency room or to a primary clinical care center were offered to participate in a prospective, 1 arm, open label study, in which all enrolled patients filled out our developed questionnaire and were HIV tested. Questionnaire accuracy, feasibility, and reliability were evaluated.

A signal-to-noise-ratio-based analysis of multifocal visual-evoked potentials in multiple sclerosis risk assessment.

Objective: To study the value of using the signal-to-noise ratio (SNR) of multifocal visual-evoked potentials (mfVEPs) in assessment of subjects at risk of developing multiple sclerosis (MS).

Methods: MfVEP signals were obtained from 15 patients with radiologically isolated syndrome (RIS), from 28 patients with clinically isolated syndrome (CIS), from 28 with clinically definite MS and from 24 control subjects. The CIS and MS groups were divided into two subgroups: those with eyes affected by optic neuritis (ON) and those without (non-ON).

Induced Gamma-Band Activity During Voluntary Movement: EEG Analysis for Clinical Purposes.

Objective: Propose a simplified method applicable in routine clinical practice that uses EEG to assess induced gamma-band activity (GBA) in the 30-90 Hz frequency range in cerebral motor areas.

Design: EEG recordings (25 healthy subjects) of cerebral activity (at rest, motor task). GBA was obtained as power spectral density (PSD).

Continuous-wavelet-transform analysis of the multifocal ERG waveform in glaucoma diagnosis.

The vast majority of multifocal electroretinogram (mfERG) signal analyses to detect glaucoma study the signals' amplitudes and latencies. The purpose of this paper is to investigate application of wavelet analysis of mfERG signals in diagnosis of glaucoma. This analysis method applies the continuous wavelet transform (CWT) to the signals, using the real Morlet wavelet.