Dietary Patterns in Portuguese Children and Adolescent Population: The UPPER Project.

Considering the nature, extent, and purpose of food processing, this study aims to identify dietary patterns (DPs) and their associations with sociodemographic factors and diet quality in Portuguese children and adolescents. Cross-sectional data were obtained from the National Food, Nutrition and Physical Activity Survey (2015-2016) of the Portuguese population. Dietary intake was obtained from two non-consecutive days and food items were classified according to the NOVA system.

Flight Planning Optimization of Multiple UAVs for Internet of Things.

This article presents an approach to autonomous flight planning of Unmanned Aerial Vehicles (UAVs)-Drones as data collectors to the Internet of Things (IoT). We have proposed a model for only one aircraft, as well as for multiple ones. A clustering technique that extends the scope of the number of IoT devices (e.

A Deep Learning Approach for Foot Trajectory Estimation in Gait Analysis Using Inertial Sensors.

Gait performance is an important marker of motor and cognitive decline in older adults. An instrumented gait analysis resorting to inertial sensors allows the complete evaluation of spatiotemporal gait parameters, offering an alternative to laboratory-based assessments. To estimate gait parameters, foot trajectories are typically obtained by integrating acceleration two times.

Neverland or Tomorrowland? Addressing (In)compatibility among the SDG Pillars in Europe.

The 2015-2030 agenda framed Sustainable Development as a Universal venture. This decision has a great historic significance as it encompasses building a better future for the whole of humanity, enrolling the millions who have been denied the chance to live a decent, dignified and fulfilling life and to achieve their potential. For the first time, an entire generation will have the chance to succeed in ending poverty while being the last to have a chance of saving the planet.

Presbylarynx: is diabetes mellitus a risk factor for vocal atrophy? A prospective case-control study.

Objective: To evaluate the prevalence of diabetes mellitus type 2 in subjects with presbylarynx.

Method: A case-control, prospective study was carried out on consecutive subjects who presented to the otorhinolaryngology department.

Results: The study comprised 174 subjects (60 males and 114 females) with a mean age of 73.

Perceptions of Patients and Physicians on Teleconsultation at Home for Diabetes Mellitus: Survey Study.

Background: Diabetes mellitus (DM) is one of the most challenging diseases in the 21st century and is the sixth leading cause of death. Telemedicine has increasingly been implemented in the care of patients with DM. Although teleconsultations at home have shown to be more effective for inducing HbA reduction than other telemedicine options, before the 2019 coronavirus disease crisis, their use had been lagging behind.

Simulation of the Transmission Spectrum of Long-Period Fiber Gratings Structures with a Propagating Acoustic Shock Front.

In this paper, we investigate modification of transmission spectra of long-period fiber grating structures with an acoustic shock front propagating along the fiber. We simulate transmission through inhomogeneous long-period fiber gratings, π-shift and reflective π-shift gratings deformed by an acoustic shock front. Coupled mode equations describing interaction of co-propagating modes in a long-period fiber grating structures with inhomogeneous deformation are used for the simulation.

Toward a Common Performance and Effectiveness Terminology for Digital Proximity Tracing Applications.

Digital proximity tracing (DPT) for Sars-CoV-2 pandemic mitigation is a complex intervention with the primary goal to notify app users about possible risk exposures to infected persons. DPT not only relies on the technical functioning of the proximity tracing application and its backend server, but also on seamless integration of health system processes such as laboratory testing, communication of results (and their validation), generation of notification codes, manual contact tracing, and management of app-notified users. Policymakers and DPT operators need to know whether their system works as expected in terms of speed or yield (performance) and whether DPT is making an effective contribution to pandemic mitigation (also in comparison to and beyond established mitigation measures, particularly manual contact tracing).

Systematic Comparison of Left Ventricular Geometry Between 3D-Echocardiography and Cardiac Magnetic Resonance Imaging.

Left ventricular (LV) volumes estimated using three-dimensional echocardiography (3D-echo) have been reported to be smaller than those measured using cardiac magnetic resonance (CMR) imaging, but the underlying causes are not well-understood. We investigated differences in regional LV anatomy derived from these modalities and related subsequent findings to image characteristics. Seventy participants (18 patients and 52 healthy participants) were imaged with 3D-echo and CMR (<1 h apart).

A Neural Network Approach towards Generalized Resistive Switching Modelling.

Resistive switching behaviour has been demonstrated to be a common characteristic to many materials. In this regard, research teams to date have produced a plethora of different devices exhibiting diverse behaviour, but when system design is considered, finding a 'one-model-fits-all' solution can be quite difficult, or even impossible. However, it is in the interest of the community to achieve more general modelling tools for design that allows a quick model update as devices evolve.

Optical Fiber Sensors for Structural Monitoring in Power Transformers.

Power transformers are central elements of power transmission systems and their deterioration can lead to system failures, causing major disruptions in service. Catastrophic failures can occur, posing major environmental hazards due to fires, explosions, or oil spillage. Early fault detection can be accomplished or estimated using electrical sensors or a chemical analysis of oil or gas samples.

Record linkage of population-based cohort data from minors with national register data: a scoping review and comparative legal analysis of four European countries.

: The GDPR was implemented to build an overarching framework for personal data protection across the EU/EEA. Linkage of data directly collected from cohort participants, potentially serving as a prominent tool for health research, must respect data protection rules and privacy rights. Our objective was to investigate law possibilities of linking cohort data of minors with routinely collected education and health data comparing EU/EEA member states.

Programming Robots by Demonstration Using Augmented Reality.

The world is living the fourth industrial revolution, marked by the increasing intelligence and automation of manufacturing systems. Nevertheless, there are types of tasks that are too complex or too expensive to be fully automated, it would be more efficient if the machines were able to work with the human, not only by sharing the same workspace but also as useful collaborators. A possible solution to that problem is on human-robot interaction systems, understanding the applications where they can be helpful to implement and what are the challenges they face.

Provisioning, Authentication and Secure Communications for IoT Devices on FIWARE.

The increasing pervasiveness of the Internet of Things is resulting in a steady increase of cyberattacks in all of its facets. One of the most predominant attack vectors is related to its identity management, as it grants the ability to impersonate and circumvent current trust mechanisms. Given that identity is paramount to every security mechanism, such as authentication and access control, any vulnerable identity management mechanism undermines any attempt to build secure systems.

Towards a Modular On-Premise Approach for Data Sharing.

The growing demand for everyday data insights drives the pursuit of more sophisticated infrastructures and artificial intelligence algorithms. When combined with the growing number of interconnected devices, this originates concerns about scalability and privacy. The main problem is that devices can detect the environment and generate large volumes of possibly identifiable data.

A Survey on Data-Driven Predictive Maintenance for the Railway Industry.

In the last few years, many works have addressed Predictive Maintenance (PdM) by the use of Machine Learning (ML) and Deep Learning (DL) solutions, especially the latter. The monitoring and logging of industrial equipment events, like temporal behavior and fault events-anomaly detection in time-series-can be obtained from records generated by sensors installed in different parts of an industrial plant. However, such progress is incipient because we still have many challenges, and the performance of applications depends on the appropriate choice of the method.

A Comparative Analysis for 2D Object Recognition: A Case Study with Tactode Puzzle-Like Tiles.

Object recognition represents the ability of a system to identify objects, humans or animals in images. Within this domain, this work presents a comparative analysis among different classification methods aiming at Tactode tile recognition. The covered methods include: (i) machine learning with HOG and SVM; (ii) deep learning with CNNs such as VGG16, VGG19, ResNet152, MobileNetV2, SSD and YOLOv4; (iii) matching of handcrafted features with SIFT, SURF, BRISK and ORB; and (iv) template matching.

Diffuse reflectance and machine learning techniques to differentiate colorectal cancer ex vivo.

In this study, we used machine learning techniques to reconstruct the wavelength dependence of the absorption coefficient of human normal and pathological colorectal mucosa tissues. Using only diffuse reflectance spectra from the ex vivo mucosa tissues as input to algorithms, several approaches were tried before obtaining good matching between the generated absorption coefficients and the ones previously calculated for the mucosa tissues from invasive experimental spectral measurements. Considering the optimized match for the results generated with the multilayer perceptron regression method, we were able to identify differentiated accumulation of lipofuscin in the absorption coefficient spectra of both mucosa tissues as we have done before with the corresponding results calculated directly from invasive measurements.

Sharing Biomedical Data: Strengthening AI Development in Healthcare.

Artificial intelligence (AI)-based solutions have revolutionized our world, using extensive datasets and computational resources to create automatic tools for complex tasks that, until now, have been performed by humans. Massive data is a fundamental aspect of the most powerful AI-based algorithms. However, for AI-based healthcare solutions, there are several socioeconomic, technical/infrastructural, and most importantly, legal restrictions, which limit the large collection and access of biomedical data, especially medical imaging.

Systematic Literature Review of Realistic Simulators Applied in Educational Robotics Context.

This paper presents a systematic literature review (SLR) about realistic simulators that can be applied in an educational robotics context. These simulators must include the simulation of actuators and sensors, the ability to simulate robots and their environment. During this systematic review of the literature, 559 articles were extracted from six different databases using the (PICOC) method.

A Standard-Based Internet of Things Platform and Data Flow Modeling for Smart Environmental Monitoring.

The environment consists of the interaction between the physical, biotic, and anthropic means. As this interaction is dynamic, environmental characteristics tend to change naturally over time, requiring continuous monitoring. In this scenario, the internet of things (IoT), together with traditional sensor networks, allows for the monitoring of various environmental aspects such as air, water, atmospheric, and soil conditions, and sending data to different users and remote applications.

Orientation-Invariant Spatio-Temporal Gait Analysis Using Foot-Worn Inertial Sensors.

Inertial sensors can potentially assist clinical decision making in gait-related disorders. Methods for objective spatio-temporal gait analysis usually assume the careful alignment of the sensors on the body, so that sensor data can be evaluated using the body coordinate system. Some studies infer sensor orientation by exploring the cyclic characteristics of walking.

Extracting neuronal activity signals from microscopy recordings of contractile tissue using B-spline Explicit Active Surfaces (BEAS) cell tracking.

Ca imaging is a widely used microscopy technique to simultaneously study cellular activity in multiple cells. The desired information consists of cell-specific time series of pixel intensity values, in which the fluorescence intensity represents cellular activity. For static scenes, cellular signal extraction is straightforward, however multiple analysis challenges are present in recordings of contractile tissues, like those of the enteric nervous system (ENS).

Ordinal losses for classification of cervical cancer risk.

Cervical cancer is the fourth leading cause of cancer-related deaths in women, especially in low to middle-income countries. Despite the outburst of recent scientific advances, there is no totally effective treatment, especially when diagnosed in an advanced stage. Screening tests, such as cytology or colposcopy, have been responsible for a substantial decrease in cervical cancer deaths.