Usability and Feasibility Study of a Remote Cognitive Behavioral Therapy System with Long-Term Unemployed Women

We present the results of the use of a cognitive behavioral therapeutic intervention tool to improve the mental, physical, and social health of a group of long-term unemployed women in Spain. Method: We sent automated text messages (SMS) to the mobile phones of long-term unemployed women selected at random from public social services. During a 28-day intervention period, women received four daily automated text messages on her mobile phone on a predetermined hourly schedule. We measured depression symptoms at the start and end of the intervention and we analyzed qualitative data to determine the acceptability of a remote SMS program. Results: Depression symptoms using the Personal Health Questionnaire-9 (PHQ-9), went from an average of 13.8 at baseline to 4.9 at the end of 28 days (p = 0.89). One hundred percent of the women reported that they liked receiving the text messages and most found them helpful

A Self-Adaptive Penalty Method for Integrating Prior Knowledge Constraints into Neural ODEs

The continuous dynamics of natural systems has been effectively modelled using Neural Ordinary Differential Equations (Neural ODEs). However, for accurate and meaningful predictions, it is crucial that the models follow the underlying rules or laws that govern these systems. In this work, we propose a self-adaptive penalty algorithm for Neural ODEs to enable modelling of constrained natural systems. The proposed self-adaptive penalty function can dynamically adjust the penalty parameters. The explicit introduction of prior knowledge helps to increase the interpretability of Neural ODE -based models. We validate the proposed approach by modelling three natural systems with prior knowledge constraints: population growth, chemical reaction evolution, and damped harmonic oscillator motion. The numerical experiments and a comparison with other penalty Neural ODE approaches and \emph{vanilla} Neural ODE, demonstrate the effectiveness of the proposed self-adaptive penalty algorithm for Neural ODEs in modelling constrained natural systems. Moreover, the self-adaptive penalty approach provides more accurate and robust models with reliable and meaningful predictions

A primer on CFD-DEM for polymer-filled suspensions

This work reports on an evaluation of the computational fluid dynamics–discrete element method (CFD-DEM) numerical approach to study the behavior of polymer-filled suspensions in a parallel-plate rheometer. For this purpose, an open-source CFD-DEM solver is used to model the behavior of such suspensions considering different particle volume fractions and different types of fluid rheology. We first validate the numerical approach for the single-phase flow of the continuum phase (fluid phase) by comparing the fluid’s azimuthal velocity and shear stress components obtained from the open-source solver against the analytical expressions given in cylindrical coordinates. In addition, we compare the numerical torque given by the numerical procedure with analytical expressions obtained for Newtonian and power law fluids. For both cases, there is a remarkable agreement between the numerical and analytical results. Subsequently, we investigated the effects of the particle volume fraction on the rheology of the suspension. The numerical results agree well with the experimentally measured ones and show a yield stress phenomenon with the increase of the particle volume fraction.This research was funded by FEDER through the COMPETE 2020 Programme and National Funds through FCT (Portuguese Foundation for Science and Technology) under projects UID-B/05256/2020, UID-P/05256/2020, UIDB/ 00013/2020, UIDP/00013/2020, UIDB/00532/ 2020, PTDC/EMS-ENE/3362/2014–POCI-01-0145-FEDER-016665

Advanced polymer simulation and processing

[Excerpt] Polymer processing techniques are of paramount importance in the manufacture of polymer parts. The key focus is on producing parts with the desired quality, which usually refers to mechanical performance, dimensional conformity, and appearance. To maximize the overall efficiency of polymer processing techniques, advanced modeling codes are needed along with experimental setups to simulate and optimize the processes. [...]This research was funded by FEDER through the COMPETE 2020 Programme and National Funds through FCT-Portuguese Foundation for Science and Technology under the projects UIDB/05256/2020 and UIDP/05256/2020. It was also funded by FCT through CMAT (Centre of Mathematics of the University of Minho) through projects UIDB/00013/2020 and UIDP/00013/2020

Development of a machine learning model and a user interface to detect illegal swimming pools

Portuguese legislation states the compulsory reporting of the addition of amenities, such as swimming pools, to the Portuguese tax authority. The purpose is to update the property tax value, to be charged annually to the owner of each real estate. According to MarketWatch, this decade will bring a global rise to the number of swimming pools due to certain factors such as: cost reduction, increasing health consciousness, and others. The need for inspections to ensure that all new constructions are communicated to the competent authorities is therefore rapidly increasing and new solutions are needed to address this problem. Typically, supervision is done by sending human resources to the field, involving huge time and resource consumption, and preventing the catalogue from updating at a rate close to the speed of construction. Automation is rapidly becoming an absolute requirement to improve task efficiency and affordability. Recently, Deep Learn- ing algorithms have shown incredible performance results when used for object detection tasks. Based on the above, this work presents a study on the various existing object detec- tion algorithms and the implementation of a Deep Learning model capable of recognizing swimming pools from satellite images. To achieve the best results for this specific task, the RetinaNet algorithm was chosen. To provide a smooth user experience with the developed model, a simple graphical user interface was also created

New boundary conditions for simulating the filling stage of the injection molding process

Purpose The purpose of this paper is to develop new boundary conditions for simulating the injection molding process of polymer melts. Design/methodology/approach The boundary conditions are derived and implemented to simulate real-life air vents (used to allow the air escape from the mold). The simulations are performed in the computational libraryOpenFOAM (R) by considering two different fluid models, namely, Newtonian and generalized Newtonian (Bird-Carreau model). Findings A detailed study on the accuracy of the solverinterFoamfor simulating the filling stage is presented, by considering simple geometries and adaptive mesh refinement. The verified code is then used to study the three-dimensional filling of a more complex geometry. Originality/value The results obtained showed that the numerical method is stable and allows one to model the filling process, simulating the real injection molding process.This work is funded by FEDER funds through the COMPETE 2020 Programme and National Funds through FCT (Portuguese Foundation for Science and Technology) under the projects UID-B/05256/2020, UID-P/05256/2020 and MOLDPRO-Aproximacoes multi-escala para moldacao por injecao de materiais plasticos (POCI-01-0145-FEDER-016665).The research of L.L. Ferras was partially financed by the Portuguese Funds through FCT within the Projects UID-B/00013/2020, UID-P/00013/2020 and the scholarship SFRH/BPD/100353/2014.The authors would like to acknowledge the Minho University Cluster (NORTE-07-0162-FEDER-000086) for providing the HPC resources that contributed to the research results reported within this paper

Development and experimental assessment of a numerical modelling code to aid the design of profile extrusion cooling tools

On the extrusion of thermoplastic profiles, upon the forming stage that takes place in the extrusion die, the profile must be cooled in a metallic calibrator. This stage must be done at a high rate, to assure increased productivity, but avoiding the development of high temperature gradients, in order to minimize the level of induced thermal residual stresses. In this work, we present a new coupled numerical solver, developed in the framework of the OpenFOAM® computational library, that computes the temperature distribution in both domains simultaneously (metallic calibrator and plastic profile), whose implementation aimed the minimization of the computational time. The new solver was experimentally assessed with an industrial case study.SFRH/BPD/100353/2014info:eu-repo/semantics/publishedVersio

Dispersion of graphite nanoplates in polypropylene by melt mixing: the effects of hydrodynamic stresses and residence time

This work combines experimental and numerical (computational fluid dynamics) data to better understand the kinetics of the dispersion of graphite nanoplates in a polypropylene melt, using a mixing device that consists of a series of stacked rings with an equal outer diameter and alternating larger and smaller inner diameters, thereby creating a series of converging/diverging flows. Numerical simulation of the flow assuming both inelastic and viscoelastic responses predicted the velocity, streamlines, flow type and shear and normal stress fields for the mixer. Experimental and computed data were combined to determine the trade-off between the local degree of dispersion of the PP/GnP nanocomposite, measured as area ratio, and the absolute average value of the hydrodynamic stresses multiplied by the local cumulative residence time. A strong quasi-linear relationship between the evolution of dispersion measured experimentally and the computational data was obtained. Theory was used to interpret experimental data, and the results obtained confirmed the hypotheses previously put forward by various authors that the dispersion of solid agglomerates requires not only sufficiently high hydrodynamic stresses, but also that these act during sufficient time. Based on these considerations, it was estimated that the cohesive strength of the GnP agglomerates is in the range of 5-50 kPa.This research was funded by FCT (Portuguese Foundation for Science and Technology) through scholarship SFRH/BPD/100353/2014 and projects UIDB/00013/2020 and UIDP/00013/2020. This work was also funded by FEDER funds through the COMPETE 2020 Programme and National Funds through FCT under the projects UID-B/05256/2020 and UID-P/05256/2020

Maker Club in Pre-School

The project allows pre-school children to develop the problematization of what they are learning and, in secondary school, students’ perspectives of cooperative in the development of scientific literacy. In this type of activity, children, with the help of high school students, deepen and consolidate behavioral values for life, thus enabling a positive change in their attitudes, in the way of believing, innovating, planning and persisting to conquer. Theactivities developed are accessible, both in approach and availability as well as in the cost of materials

Electroosmosis modulated peristaltic biorheological flow through an asymmetric microchannel : mathematical model

A theoretical study is presented of peristaltic hydrodynamics of an aqueous electrolytic nonNewtonian Jeffrey bio-rheological fluid through an asymmetric microchannel under an applied axial electric field. An analytical approach is adopted to obtain the closed form solution for velocity, volumetric flow, pressure difference and stream function. The analysis is also restricted under the low Reynolds number assumption and lubrication theory approximations. Debye-Hückel linearization (i.e. wall zeta potential ≤ 25mV) is also considered. Streamline plots are also presented for the different electro-osmotic parameter, varying magnitudes of the electric field (both aiding and opposing cases) and for different values of the ratio of relaxation to retardation time parameter. Comparisons are also included between the Newtonian and general non-Newtonian Jeffrey fluid cases. The results presented here may be of fundamental interest towards designing lab-on-a-chip devices for flow mixing, cell manipulation, micro-scale pumps etc. Trapping is shown to be more sensitive to an electric field (aiding, opposing and neutral) rather than the electro-osmotic parameter and viscoelastic relaxation to retardation ratio parameter. The results may also help towards the design of organ-on-a-chip like devices for better drug design