Miracle-dz/UniFAR-FTUs huggingface dataset:
A Noncontact Emotion Recognition Method Based on Complexion and Heart Rate

This article proposes a noncontact emotion recognition method based on complexion and heart rate (HR). Unlike most existing noncontact emotion recognition methods, our method uses complexion and heart rate as contactless emotion recognition indicators, effectively avoiding the possibility of disguised facial expressions or acoustic features in noncontact methods. Different from most existing contact emotion recognition methods, our method only employs an ordinary device, Kinect, to achieve the complexion and heart rate, which can effectively avoid subjects’ psychological oppression when using wearable devices. Convolutional neural network (CNN) and bidirectional long short-term memory-conditional random fields (Bi-LSTM-CRF) are developed to extract the features of complexion and heart rate for contactless emotion recognition, respectively. We experimentally compared our methods with the existing five emotion recognition methods in practical application. The results show that our methods can outperform the existing five methods and obtain an emotion recognition accuracy higher than 80% in detection of anger, depression, doubt, and indignation. This indicates that the fusion of complexion and heart rate can effectively improve the emotional recognition accuracy. Note that our method requires neither expensive equipment nor conscious emotional acquisition by the participant, thereby promoting the development of emotion recognition in various fields such as the interrogation process and psychological counseling.
Financial flows of five leading banks in Sweden since the Paris Agreement: a report for the Swedish Environmental Protection Agency.

This study sheds light on the domestic and international financial flows from the largest lenders in Sweden and their alignment with the Paris Agreement. The results show the extent to which banks’ financial flows contribute to achieving climate goals consistent with Article 2.1c of the Paris Agreement on climate change, or to delaying that achievement, with some limitations.
Learning All Dynamics: Traffic Forecasting via Locality-Aware Spatio-Temporal Joint Transformer

Forecasting traffic flow and speed in the urban is important for many applications, ranging from the intelligent navigation of map applications to congestion relief of city management systems. Therefore, mining the complex spatio-temporal correlations in the traffic data to accurately predict traffic is essential for the community. However, previous studies that combined the graph convolution network or self-attention mechanism with deep time series models (e.g., the recurrent neural network) can only capture spatial dependencies in each time slot and temporal dependencies in each sensor, ignoring the spatial and temporal correlations across different time slots and sensors. Besides, the state-of-the-art Transformer architecture used in previous methods is insensitive to local spatio-temporal contexts, which is hard to suit with traffic forecasting. To solve the above two issues, we propose a novel deep learning model for traffic forecasting, named Locality-aware spatio-temporal joint Transformer (Lastjormer), which elaborately designs a spatio-temporal joint attention in the Transformer architecture to capture all dynamic dependencies in the traffic data. Specifically, our model utilizes the dot-product self-attention on sensors across many time slots to extract correlations among them and introduces the linear and convolution self-attention mechanism to reduce the computation needs and incorporate local spatio-temporal information. Experiments on three real-world traffic datasets, England, METR-LA, and PEMS-BAY, demonstrate that our Lastjormer achieves state-of-the-art performances on a variety of challenging traffic forecasting benchmarks.
Humanoid robot in healthcare: A Systematic Review and Future Research Directions

Historically, progress in automation systems has been motivated by the need for collaborative robots in the manufacturing sector. There is a need for technological adoption in the healthcare sector. Robots are the best options to help and assist doctors in healthcare activities. The healthcare sector’s lack of focus on technological innovations has created new opportunities to enhance service robots that can assist patients in dealing with their illnesses and providing better solutions. Humanoid robots can benefit healthcare by increasing the patient’s satisfaction level. They can also perform precise surgery in tiny rooms and transport hazardous substances. This study conducted a systematic literature review by extracting articles from three databases. This paper highlights the critical role of humanoid Robots in the healthcare sector. This article also discusses the future trends of humanoid robots for the health sector.
Estimation of Fractional Plant Lifeform Cover for the Conterminous United States Using Landsat Imagery and Airborne LiDAR

In this study, we produced annual 30-m resolution maps of vegetation lifeform cover (tree, shrub, herb, and an additional class denoted as “other”) and their spatially explicit uncertainties for the conterminous United States for the period of 1984–2018, modeled using a quantile regression forest calibrated from a fusion of airborne light detection and ranging (LiDAR)/multispectral data and Landsat imagery. The resulting predictions were compared to available fractional cover products with the same temporal and spatial resolution and to different types of documented land cover change to determine the relative accuracy of the percent cover predictions. We found that our approach yielded a higher accuracy of the shrub, herb, and “other” cover estimates than existing products and had a similar performance of the resulting tree cover estimate compared to other products. Our results indicate that the use of spatially dense training and validation data from airborne multisensor acquisitions facilitates the incorporation of a large range of variability in the response variables into model construction. The produced percent lifeform cover maps, which are publicly available through the Oak Ridge National Laboratory Distributed Active Archive Center, represent a consistent dataset of medium spatial resolution and long temporal record that can be a valuable input into a variety of applications such as the analysis of vegetation change processes, as well as ecosystem conservation and management.
A new species of the genus Prosopistoma Latreille, 1833 (Ephemeroptera, Prosopistomatidae) from Morocco

﻿Abstract We describe a new species of Prosopistoma collected in the High Atlas Mountains of Morocco. Prosopistomamaroccanumsp. nov. appears to be morphologically more similar to the European highly endangered P.pennigerum (Müller, 1785) than to the other Maghrebian species, P.alaini Bojkova & Soldán, 2015. A gene tree including the few available barcode sequences of Palearctic Prosopistoma specimens is provided. Possible affinities with West African species are also discussed.
Informing State-Wide Coalition Efforts to Implement and Integrate Nutrition Best Practices in Early Care and Education: Focus Group Insights from Child Care Providers

A healthy diet in early childhood is an important contributor to ensuring lifelong health and in reducing risk for obesity. The child care environment is critical to supporting nutrition as a majority of young children less than 5 years of age are enrolled in out-of-home care. In order to better understand barriers to implementing and integrating nutrition best practices, we conduced focus groups with child care providers (n = 25) in Illinois. Providers from low-income communities, rural communities, and communities of color were prioritized. Focus group participants reported several challenges including the high cost of nutritious food, picky eating, and their perception that parents did not set good examples at home. Many providers identified the Child and Adult Care Food Program (CACFP) as a critical resource in helping them implement best practices. Providers discussed needing and wanting more training, more money for food, and more parental support. These results indicate support for additional resources and sustained training and technical assistance to address perceived challenges. The evidence of the importance of CACFP in helping providers engage in nutrition best practices indicates support for expansion and strengthening of the program.
Skeletal-Muscle-Specific Overexpression of Chrono Leads to Disruption of Glucose Metabolism and Exercise Capacity

Disruption of circadian rhythms is related to disorders of glucose metabolism, and the molecular clock also exists in skeletal muscle. The ChIP-derived repressor of network oscillator (Chrono) and brain and muscle ARNT-like 1 (Bmal1) are core circadian components. Chrono is considered to be the repressor of Bmal1, and the Chrono–Bmal1 pathway is important in regulating the circadian rhythm; it has been speculated that this pathway could be a new mechanism for regulating glucose metabolism. The purpose of this study was to investigate the effects of Chrono on glucose metabolism in skeletal muscle and exercise capacity by using mice with skeletal-muscle-specific overexpression of Chrono (Chrono TG) and wild-type (WT) mice as the animal models. The results of this cross-sectional study indicated that the Chrono TG mice had an impaired glucose tolerance, lower exercise capacity, and higher levels of nonfasted blood glucose and glycogen content in skeletal muscle compared to WT mice. In addition, the Chrono TG mice also showed a significant increase in the amount of Chrono bound to Bmal1 according to a co-IP analysis; a remarkable decrease in mRNA expression of Tbc1d1, Glut4, Hk2, Pfkm, Pdp1, Gbe1, and Phka1, as well as in activity of Hk and protein expression of Ldhb; but higher mRNA expression of Pdk4 and protein expression of Ldha compared with those of WT mice. These data suggested the skeletal-muscle-specific overexpression of Chrono led to a greater amount of Chrono bound to Bmal1, which then could affect the glucose transporter, glucose oxidation, and glycogen utilization in skeletal muscle, as well as exercise capacity.
Development RPP Based on Flipped Learning Model Material of Human Respiratory System

The existence of the Covid-19 pandemic condition makes learning in each region different, including limited online and face-to-face learning as well as circulars from the government regarding the simplification of lesson plans into 1 sheet with 3 main components, making it a challenge for a teacher to reconstruct lesson plans globally. by adapting to the current situation. The purpose of this study was to develop Reconstruction RPP based on the Flipped Learning Model of Human Respiratory System Material to determine the feasibility of learning design based on a validation questionnaire of learning design experts and the attractiveness of RPP based on student responses. This study uses the ADDIE development model which has five stages, namely: 1) Analyze 2) Design 3) Develop 4) Implement, and 5) Evaluation. The subjects of this study were 2 experts on learning design validation and 10 students of class XI IPA 1 MAN 10 Jombang. The instrument used is a validation questionnaire of learning design experts and student response questionnaires. Data analysis techniques are quantitative and qualitative. The results showed that the validation of learning design experts obtained an average score of 93.75% with appropriate criteria and the results of the student questionnaire obtained a score of 84% with very interesting criteria. Based on these results, this RPP reconstruction can be applied to the respiratory system material in class XI humans at MAN 10 Jombang and it is hoped that in the future this Inspirational RPP reconstruction can be applied to other materials.
GraphClusNet: A Hierarchical Graph Neural Network for Recovered Circuit Netlist Partitioning

Hardware assurance (HA) is imperative to ensure the integrity of integrated circuits (ICs) after manufacturing. To verify the integrity of an IC would require the extraction of relevant functional block of interest through circuit partitioning. This is usually done by converting a recovered circuit netlist into a circuit graph and subsequently performing unsupervised clustering on the graph. However, circuit graphs are difficult to cluster due to the existence of inherent hierarchies and clusters of imbalanced sizes. In this article, we propose a novel hierarchical graph neural network (GNN), termed as GraphClusNet, to perform circuit graph clustering in a multistage process to achieve near-optimal results. We analytically derive a normalized-cut-based loss function, which allows for clusters of imbalanced sizes. We train our GraphClusNet in a multistage hierarchical fashion to regularize intermediate node embedding, which greatly alleviates the oversmoothing effect in deep GNNs. We further propose a multiscale location-based node feature and feature concatenation to provide a good initialization to stabilize the training of our GNN. Based on the experiments of synthetic graphs, we show that our proposed GraphClusNet obtained solutions with n-cut values up to $\mathbf {65\times }$ closer to the global optimum. On FPGA circuit graphs, our proposed GraphClusNet outperformed the reported methods with up to 30% improvement in normalized mutual information for circuit graph clustering.
Actividades profesionales a confiar: hacia una estandarización del lenguaje y significado en español y portugués

El enfoque de EPAs ha tenido un gran impacto en la educación médica desde que surgió en 2005. Su difusión a través de diferentes regiones del mundo ha requerido traducción a varios idiomas, y en algunas ocasiones ha generado confusiones terminológicas y de significado. Este artículo es el resultado de un consenso respecto de la traducción de términos clave para la comprensión del enfoque en español y portugués. Se llevó a cabo a través de un proceso de análisis de significado de cada término en el contexto idiomático y de la realidad de la formación de profesionales de la salud en Latinoamérica. Estuvo a cargo de doce profesionales, docentes y académicos involucrados en la implementación y formación con EPAs en ocho países, que formaron parte como responsables, facilitadores o participantes del International Course Ins and Outs of EPAs 2021 para Latinoamérica.
Structural Concrete Design in the 21st Century: are Limit Analysis Methods obsolete?

Limit analysis methods, whose origins date back to the early days of reinforced concrete, are powerful tools for the design, dimensioning and detailing of concrete structures. They are transparent, allow to trace the flow of forces and give the engineer control over the design. However, they are typically used as hand calculations, making their application tedious and time-consuming since iterations are required and several load-cases need to be considered. In addition, they are not directly applicable for checking serviceability criteria. Therefore, design in engineering practice is ever more often based on linear elastic finite element calculations. In order to ensure that limit analysis methods such as stress fields and truss models will continue to be used for reinforced concrete dimensioning and detailing, these models must be brought up-to-date by implementing them in user-friendly computer programs without impairing their advantages of transparency and control over the design. Currently, the authors are involved in the development of such a program, which will hopefully contribute to the survival of stress field and truss modelling in structural concrete design.
Single Blade Installation for Large Wind Turbines in Extreme Wind Conditions: A Quasi-Steady Aeroelastic Study in High Wind Speeds under Different Inflow Angles

Energy demand from wind greatly increases, as such more remote sites need to be explored in order to find good wind resources. These remote sites are driving the industry further offshore and therefore into extreme wind and sea conditions. This push towards extreme conditions requires technological advancements concerning the wind turbine loads, power production and installation. The levelised cost of wind energy is strongly dependent on the capital expenditures and thus on the installation and logistics of erecting a wind turbine offshore. Improving the robustness of the installation to higher wind velocity and turbulence will increase the weather window and therefore drastically decrease the levelised cost of energy (LCoE). This thesis will focus on one particular technique of wind turbine installation: Horizontal Single Blade Mounting (HSBM). HSBM is a wind turbine blade lifting technique performed by Siemens Wind Power (SWP). This technique is currently limited to low wind speeds, which contradicts the fact that the industry is targeting high wind speed offshore sites. This technical problem is the basis of the thesis study. This thesis study will answer three research questions in order to improve future lifting methods. In a nutshell these questions are: one, how to model the aerodynamic forces and dynamic behaviour of a hoisted wind turbine blade? , two, what are the critical parameters affecting the blade response? and three, how can single blade mounting be improved for higher wind speeds?
Out of Africa: Juvenile Dispersal of Black-Shouldered Kites in the Emerging European Population

Simple Summary Black-shouldered Kite (Elanus caeruleus) is a relative recent colonizer in Europe. The study of juvenile dispersal may help to better understand the patterns of range expansion and colonization. In this study, we provide some information about patterns of juvenile dispersal according to sex, habitat quality, timing of reproduction, and nesting hatching order to test two competing hypotheses about natal dispersal in this poorly studied raptor. We found some evidence supporting the Resources Competition Hypothesis since nestlings hatched from high quality territories and hatched first within the brood stayed closer from natal areas than nestlings hatched from low quality territories or later hatched nestlings. Abstract Knowledge of animal dispersal patterns is of great importance for the conservation and maintenance of natural populations. We here analyze juvenile dispersal of the poorly studied Black-shouldered Kite (Elanus caeruleus) monitored in southwestern Spain in an ongoing long-term study initiated in 2003. The European population of Black-shouldered kites is thought to be a recent one funded by colonizing African birds, as no kites have been found in the European fossil record, and the breeding population has progressively expanded to the North in the late 20th and 21st centuries. We obtained information on movements behavior during dispersal from 47 juveniles Kites after marking 384 nestlings with wing tags and three nestlings with radio transmitter. We have tested two competing hypotheses (i.e., the Resources Competition Hypothesis and the Wandering Hypothesis (WH)) that may explain the leptokurtic distribution of the natal dispersal distance in Elanus. After independence, juvenile females dispersed farther from the natal areas than males, as is common in birds. On average, males and females dispersed from their natal areas over 9 (i.e., 26.15 km) and 15 (i.e., 43.79 km) breeding territories, respectively. A male and two females dispersed further than 100 km from their natal nest. Our results indicated some evidence supporting the competition-for-resources hypotheses since nestlings hatched from high quality territories stayed closer from natal areas than nestlings hatched from low quality territories and also nestlings hatched first within the brood also tend to recruit closer to their natal area than later hatched nestlings which tend to disperse further away from their natal area. The information provided by these crucial demographic parameters will be used for the elaboration of future conservation plans for the management of this colonizing species in Europe.
Experimental and Numerical Simulation of Girth Welded Joints of Dissimilar Metals in Clad Pipes

Welding of two dissimilar materials was carried out in-house with the aid of a Tungsten Arc weld having dynamic measurement of temperature profiles in the vicinity areas of the welding track using high temperature thermocouples. Comparison was shown previously of the simulated and measured transient temperatures versus finite element simulation. Stress analyses of the pipe were carried out using FEA simulations with two different clad thicknesses. Results of thermal analysis showed a close match and laboratory tests revealed the occurrences at the welded joints, FZ and HAZ; the result of stress analysis also showed a good agreement when validated with ND experimental results.
“ACTIVE VALUES”: An Interdisciplinary Educational Programme to Promote Healthy Lifestyles and Encourage Education in Values—A Rationale and Protocol Study

Numerous investigations show the need to intervene with school children and young students in order to mitigate socio-educational difficulties such as social conflict, and public health problems such as sedentary lifestyles and childhood obesity. This study seeks to explain the rationale and protocol of an educational programme called “ACTIVE VALUES” as an intervention strategy for the reduction of sedentary lifestyles and the promotion of education in values in schools. The present research used a mixed methods approach with a quasi-experimental design of repeated measures (pre-test and post-test), with a non-randomised control group (CG) and an experimental group (EG). The sample was composed of approximately 250 students and 30 teachers from different autonomous communities in Spain, divided into EG and CG. The EG implemented a teaching methodology based on the incorporation of Active Breaks (AB) into the structure of the Teaching Personal and Social Responsibility (TPSR) model, during one academic year, while the CG used conventional teaching based on the direct instruction teaching technique. A specific two-stage professional development procedure was followed: (1) initial training and (2) continuing professional development (CPD). The fidelity of the programme was checked by observational analysis of the sessions which were analysed by two observers with expertise in educational research and active methodologies. Currently, “ACTIVE VALUES” is the first study that examines the effectiveness of an educational programme that integrates into the teaching methodology, elements that foster education in values and promote healthy lifestyle habits through physical-sports activity within the classroom.
Optimization-Based Methodology to Design the MMC's Sub-Module Capacitors

This paper proposes an optimization-based size reduction methodology for Modular Multilevel Converters (MMC), focusing on minimizing the converter's sub-module capacitor $C_{SM}$. The analysis is performed considering both the converter's current and voltage limitations and the Transmission System Operator (TSO) Fault Ride Through (FRT) requirements. By means of a steady-state analysis, the time-domain expressions of the converter's arms energies are obtained and their behavior throughout the MMC's operating range is shown. Based on these expressions, the optimization-based problem to reduce the $C_{SM}$ size is developed and its constraints are imposed to ensure that the converter's voltage and current levels are within its design limitations. The suggested method is compared with different approaches for distinct active and reactive power set-points, where it is shown that the SM capacitor size can be reduced up to 24% in comparison with the method with worst performance and up to 7% regarding the best method used for comparison purposes. Furthermore, time-domain simulations of the MMC considering several AC voltage sags are performed in order to demonstrate that the dynamics of the SM capacitor and the arm applied voltages are within acceptable margins during the different operations.