Miracle-dz/UniFAR-FTUs huggingface dataset:
Disentangling youth non-compliance with COVID-19 restrictions from gender, socioeconomic vulnerability and poor mental health: lessons from the first wave in Catalonia

ABSTRACT The COVID-19 pandemic focused public attention on youth non-compliance with restrictions, but the social and health factors underpinning this behaviour were overlooked. Hereby, we considered the complex relationships between age (16–29 vs. 30+), non-compliance, socioeconomic vulnerabilities and poor mental health using a gender perspective. Data were derived from the ‘Survey on the impact of COVID-19’, fielded on 11–15 April 2020 in Catalonia. In a non-probabilistic sample of 14,123 individuals, we performed gender-stratified mediation analyses using Structural Equation Models. The results suggest that youth was related to non-compliance among men, but not among women. Nonetheless, young women were more frequently fired than older women, which enhanced their likelihood of non-compliance. Mental health outcomes were poorer among young people but did not relate to youth non-compliance. Finally, adverse socioeconomic situations related to non-compliance and poor mental health, but this was not an idiosyncrasy of young people. Lessons from the first COVID-19 wave suggest that young age intersects with gender and socioeconomic factors in determining non-compliance. This highlights the need to incorporate a gender and socioeconomic inequalities perspective in the design and evaluation of policies that tackle non-compliance among young people. Only by using this holistic approach will we effectively manage future public health crises.
Extended Kalman Filter Sensor Fusion in Practice for Mobile Robot Localization

Self-driving vehicles and autonomously guided robots could be very beneficial to today's civilization. However, the mobile robot's position must be accurately known, which referred as the localization with the task of tracking the dynamic position, in order for the robot to be active and useful. This paper presents a robot localization method with a known starting location by a real-time reconstructed environment model that represented as an occupancy grid map. The extended Kalman filter (EKF) is formulated as a nonlinear model-based estimator for fuse Odometry and a LIDAR range finder sensor. Because the occupancy grid map for the area is provided, just the inaccuracies of the LIDAR range finder will be considered. The experimental results on the “turtlebot” robot using robot operating system (ROS) show a significant improvement in the pose of the robot using the Kalman filter compared with sample Odometry. This paper also establishes the framework for using a Kalman filter for state estimation, providing all relevant mathematical equations for differential drive robot, this technique can be used to a variety of mobile robots. Keywords—Autonomous navigation; kalman filter; self-driving vehicle; simultaneous localization and mapping; occupancy grid map; ROS
Monochorionic Twins and the Early Mother-Infant Relationship: An Exploratory Observational Study of Mother-Infant Interaction in the Post-Partum Period

The extraordinary increase in twin rates and specifically monochorionic twin pregnancies represents a major public health issue due to the associated increased risks for the mother, the child and their relationship. The aim of the present study was to examine the quality of mothers’ behaviour during mother–infant interaction in the early postpartum period by comparing mothers of twins and mothers of singletons during face-to-face interaction with their infants. Demographic and clinical information was collected by trained research psychologists from the mothers’ and the childrens’ clinical records and from interviews with the mothers. At three months (corrected for prematurity), the interactions of the dyads (11 mother-twin infant dyads and 11 mother-singleton dyads) were filmed at participants’ homes in accordance with the procedure of the Global Rating Scales. Maternal behaviour during interactions was assessed and rated by two trained research psychologists. With regard to the mothers’ interaction with each twin, no differences were found between mothers’ scores in every GRS subscale, indicating that mothers did not interact differently with their twins. Comparisons between mothers of MC twins and mothers of singletons showed that the quality of maternal sensitive behaviour during the interactions were lower in mothers of twins (0.35) Mothers of twins were also more distant during interactions with their babies and more likely to experience depression symptoms than mothers of singletons (0.05). Future research should examine mother-infant relationships following twin birth with larger samples. Such research will be especially useful in evaluating the potential benefits of interventions to promote positive mother-infant interactions.
Optimal Design of Kinematics Parallel Manipulator Considering Workspace and Control Effort

Several studies have reported the design of kinematics parallel mechanisms based on behavioral features; however, the design of this kind of system with six degrees of freedom considering parallelly volumetric behavior together with control effort remains to be accomplished. This work addresses the design of one type of these mechanisms based on two aspects: workspace and control effort. All aspects are considering and optimizing simultaneously through a multiobjective optimization technique based on a bio-inspired algorithm named Elitist Non-Dominated Sorting Differential Evolution Algorithm, which brings about a Pareto front. The workspace is determined using the inverse kinematics constrained boundaries analysis and a mono-objective optimization method. On the other hand, control effort is resolved by calculating the Euclidian norm of each torque signal of the system, which is controlled by a hybrid technique consisting of sliding modes and differential flatness. Finally, relations between the two studied aspects are depicted and analyzed.
Clinical Significance of Serum Zinc Levels on the Development of Sarcopenia in Cirrhotic Patients.

Background/Aim Sarcopenia increases the mortality in patients with cirrhosis. Approximately 60% of zinc is accumulated in skeletal muscle. We aimed to determine the role of subclinical zinc deficiency on sarcopenia development in patients with cirrhosis. Patients and Methods We enrolled 151 patients with cirrhosis and divided them into the group with normal serum zinc levels (Group N: 80-130 μg/dl; n=38) and group with subclinical zinc deficiency (Group D: <80 μg/dl; n=113). The risk factors for sarcopenia were then investigated. Results Group D had more sarcopenia cases than Group N (31.0% vs. 13.2%). In group D, HGS exhibited a weakly positive but significant correlation with serum zinc levels (R=0.287, p=0.00212), serum zinc levels negatively correlated with both ammonia and myostatin levels (R=-0.254, p=0.0078; R=-0.33, p<0.01), and low zinc levels were independently associated with sarcopenia development. Conclusion Patients with cirrhosis showing subclinical zinc deficiency have a significantly higher risk of developing sarcopenia.
implementasi moving average terhadap efektivitas saldo akun trading bitcoin

Bitcoin saat ini sudah mulai di kenal sebagai asset digital bagi para milenial dan tidak hanya menginvestasikan dana dalam instrument investasi tradisional seperti saham, obligasi, dan reksadana, generasi milenial juga mulai menginvestasikan dana dalam bentuk mata uang Criptocurrency dan menjadi sebuah tren investasi baru yang sedang meningkat di Indonesia dan merupakan instrument investasi paling menguntungkan di decade ini. Permasalahan yang sering muncul yaitu salah satunya adalah Cryptocurrency tidak bisa di prediksi dengan mudah, salah langkah dalam menganalisis dan prediksi akan berakibat fatal terhadap asset yang dimiliki, sehingga dapat menimbulkan kerugian besar ketika pelaku investor/trader melakukan keputusan tanpa berdasarkan analisa dan prediksi yang tepat. Algoritma MA dapat meminimalisir kesalahan dalam prediksi yang sering keliru dilakukan para investor/trader dalam memprediksi yang sering didasarkan pada intuisi dan emosi. Penelitian ini bertujuan untuk melihat hasil akurasi dari algoritma MA terhadap peramalan harga Bitcoin dan menentukan di posisi mana algoritma ini lebih efektif untuk digunakan dalam strategi analisis sehingga diharapkan informasi ini dapat dijadikan acuan untuk para pelaku trader/investor dalam menentukan keputusan Buy, Sell or Hold dalam berinvestasi dan mengurangi kesalahan proses perdagangan jual dan beli pada Bitcoin.
Superstructure-based Optimal Planning of Cogeneration Systems With Storage

In this paper,the storage was introduced into a superstructure-based optimal planning mixed integer linear programming(MILP) model of cogeneration systems.The model can achieve simultaneous optimization of system structure and operation as well as simultaneous optimization of all equipment including storage.At the same time the branch and bound method combined with the simplex method was used as a solution algorithm.Through a case study,the validity and effectiveness of the proposed model and the method were verified.The computational results also indicate that,the introduction of storages in cogeneration systems reduces the capacities of other refrigeration equipment;under time of use electricity rates,storage enhances the system flexibility and economic and energy saving can be obtained through removing some of the strong coupling relationship between cooling/heating demands and generators.The optimal operation strategies of storage are different in typical days,which depend on electricity price,energy demands et al.
High-Efficiency and Durable Flame Retardant Cotton Fabric with Good Physical and Mechanical Properties by Layer-by-Layer Assembly Polyethylenimine/Phytic Acid Coating

ABSTRACT In this study, intumescent flame retardant coating of polyethylenimine/phytic acid (PEI/PA) with gradient structure was constructed on cotton fabric through a facile layer-by-layer (LBL) assembly method. The LOI value of coated cotton fabric reached over 40%, indicating excellent flame retardancy. Reasonable controlling the LBL assembly process of PEI/PA coating brought less influence to the physical properties of cotton fabrics. And the coated cotton fabric revealed good flame retardant washing durability. Thermogravimetric analysis results of coated cotton fabrics showed that PEI/PA flame retardant coating changed the thermal decomposition process and promoted char formation revealing the obviously condensed phase flame retardant action. SEM images of char residues revealed that PEI/PA flame retardant coating promoted to form the intumescent flame retardant (IFR) char layer showing obvious IFR action. This research provides novel strategy for the development of high-efficiency flame retardant cotton fabric with good durability and physical properties using a simple LBL assembly method.
Compact dual-band antenna using inverted-L loop and inner rectangular loop for WLAN applications

A small loop antenna for WLAN applications is proposed, which is comprised of an inverted-L loop and an inner rectangular loop achieving dual-band resonances within a compact size of 4.5 mm × 6.5 mm. A series capacitor in the feeding loop is employed for impedance matching of both bands and a shunt capacitor for high band, respectively. The proposed compact antenna is able to achieve −10 dB impedance bandwidth of 120 and 1260 MHz and average radiation efficiency of 69 and 61% in the 2.4 GHz band and the 5 GHz band, respectively.
AI-TP: Attention-Based Interaction-Aware Trajectory Prediction for Autonomous Driving

Despite the advancements in the technologies of autonomous driving, it is still challenging to study the safety of a self-driving vehicle. Trajectory prediction is one core function of an autonomous vehicle. This study proposes an Attention-based Interaction-aware Trajectory Prediction (AI-TP) for traffic agents around the autonomous vehicle. With an encoder-decoder architecture, the AI-TP model uses Graph Attention Networks (GAT) to describe the interactions of traffic agents and Convolutional Gated Recurrent Units (ConvGRU) to carry out predictions. Based on the attention mechanism, the AI-TP model constructs graphs from various traffic scenes to predict trajectories of different types of traffic agents. Traffic data from both the high-way (i.e., NGSIM) and urban road areas (i.e., ApolloScape and Argoverse) are used to evaluate the performance of the AI-TP model. Numerical results demonstrate that the AI-TP model requires less inference time and achieves better prediction accuracy than state-of-the-art methods. Specifically, the AI-TP model improves the performance with much less inference time on the NGSIM dataset, which shows the promise of predicting trajectories under various scenarios. The code of the AI-TP model will be available at https://github.com/KP-Zhang/AI-TP.
The Relationship Between Parent Attachment and Behavior Problems of Adolescences During the Epidemic of COVID-19: The Mediating Role of Resilience

Objective: The incidence of behavior problems is very high among adolescents. Previous studies have shown that behavior problems can affect the physical and mental health of adolescents. And behavior problems closely relates to adolescences’ academic achievement, interpersonal communication, and personality development. While in 2020, the influence of COVID-19 upon the mental health of the public has received great concern. As a public pandemic, whether it could increase the incidences of behavior problem of adolescents is still unknown. Considering the protective factors of behavior problems, existing studies have found that family-related variables are very important protective factors for problem behaviors. However, whether and how family-related factors could influence behavior problems during this special time is unclear. From the view of positive psychology and attachment theory, the current study investigated the characteristics of behavior problems of adolescence and the influence of parent attachment as well as the mediating role of resilience during the epidemic of COVID-19. Methods: Sixty-nine adolescents aged 12-18 in Jiangxi, Guangdong, and Hebei provinces of China were recruited during the epidemic of COVID-19as participants (Mage=15.83 years old,SDage = 1.06 years old, including 19 boys). They were asked to complete a series of online questionnaires including the Parent Attachment Scale, Strengths and Difficulties Questionnaire, Adolescent Resilience Scale, and some basic information scale. Results: The results showed that during the epidemic of COVID-19: (1) adolescents’ behavior problems were prominent, among which hyperactivity, attention problems, and emotional problems were significantly higher than other behavior problems; (2) among the relationship between parent-child attachment and adolescent problem behavior, the relationship between mother’s trust and behavior problems, parents’ alienation and behavior problems, and resilience and behavior problem were significant; and (3) the mediating analysis revealed that resilience plays a mediating role between mother’s trust, father’s alienation, mother’s alienation, and behavior problem. Conclusion: The results showed that attention problems and emotional problems were the main behavior problems of adolescents during the epidemic period of the COVID-19. During this time, parent attachment could act as a protective factor which relates to adolescents’ behavior problem. What’s more, parent attachment could predict adolescents’ behavior problem through resilience. These results provide some implications for the intervention of problem behaviors during the COVID-19.
Economic analysis and policy

This paper examines frequency dynamic spillovers in return and volatility and the hedging ability of Green Bonds, gold, silver, oil, the US dollar index, and volatility index against downside US stock prices before and during the COVID-19 pandemic outbreak and for the short and long run. To do so, we use the Diebold and Yilmaz (2014), the TVP-VAR model, and the frequency spillover index by Baruník and Křehlík (2018). We show that the short-term volatility spillovers dominate their long-term counterparts. Green Bond is net transmitters of spillovers in the system at the short term and net receivers at the long term. S&P500 and silver (USDX and oil) are net transmitters (receivers) of short- and long-term spillovers. Gold and VIX are net receivers of short-term spillovers and net transmitters of long-term spillovers. COVID-19 crisis has more effects on the short-term spillover, which reaches its highest level early 2020. COVID-19 and time horizons lead the direction and the magnitude of spillovers. The Quantile-on-Quantile regression analysis shows significant nonlinear relationships between markets under study. More interestingly, we show that green bonds and gold are safe haven assets for US equity investors during COVID-19. On the other hand, a mixed portfolio offers higher diversification benefits. Finally, hedging effectiveness is dependent on COVID-19 and time horizon. ©
Internationalization and transformation of the research landscape: Some avenues to apprehend significant challenges for RAM

First and foremost, I would like to thank the selection committee members who appointed me Editor-in-Chief of Recherche et Applications en Marketing (RAM) for their trust. It is a great responsibility to succeed colleagues who have managed the journal so well and contributed to what it has become. I would also like to thank the previous editorial team for their constant support during the handover and the French Marketing Association for their support. Last year, RAM celebrated its 35th anniversary. Former editors-in-chief were invited to talk about their experience or discuss their vision of the future. They recalled the many challenges they faced. They had to establish a new journal and help a young discipline become more scientific (Jallais, 2021). They had to “instill a research spirit in line with international standards” (Pras, 2021: 78) and impose a path of scientific rigor while maintaining the journal’s openness (Pras, 2021). The objectives that the founders set out have been achieved in many respects. The articles published are of great scientific rigor and cover many subjects in marketing, consumer behavior, and Consumer Culture Theory. The journal contributes to theoretical and methodological renewal by regularly publishing “reviews” and “new perspectives” concerning the advances of our discipline. The service provided to authors is a significant concern: the average time to render decisions is relatively short, and most of the evaluations given by the critical reviewers are of high quality. However, we should take nothing for granted. RAM is a generalist journal that still has a very national image (Brée, 2021), and both the environment of research and society are under going profound changes (Özçağlar-Toulouse, 2021). Therefore, in this first editorial, I wish to emphasize two challenges that RAM already faces, which may have practical consequences on authors’ and reviewers’ work. The first challenge regards the internationalization movement. The second relates to essential transformations in the research landscape. In particular, I will touch on the ethical aspects raised by the open science movement and the questions about the purpose of research in marketing.
Lyophilized Gelatin@non-Woven Scaffold to Promote Spheroids Formation and Enrich Cancer Stem Cell Incidence

A gelatin@non-woven fabric (gelatin@NWF) hybrid scaffold with tailored micropore structures was fabricated by lyophilizing, using gelatin to support cells and the NWF matrix as a frame to enforce the mechanical stability of gelatin. By freezing the gelatin and NWF hybrid in liquid nitrogen and subsequently lyophilizing and crosslinking the process, the gelatin@NWF scaffold was prepared to support cell growth and promote cell aggregation and spheroids’ formation. The results indicated that by tuning the lyophilizing temperature, the micropore size on the gelatin could be tailored. Consequently, tumor spheroids can be formed on gelatin@NWF scaffolds with honeycomb-like pores around 10 µm. The cell spheroids formed on the tailored gelatin@NWF scaffold were characterized in cancer stem cell (CSC)-associated gene expression, chemotherapy drug sensitivity, and motility. It was found that the expression of the CSC-associated biomarkers SOX2, OCT4, and ALDH1A1 in gene and protein levels in DU 145 cell spheres formed on gelatin@NWF scaffolds were significantly higher than in those cells grown as monolayers. Moreover, cells isolated from spheroids grown on gelatin@NWF scaffold showed higher drug resistance and motility. Tumor spheroids can be formed on a long-term storage scaffold, highlighting the potential of gelatin@NWF as a ready-to-use scaffold for tumor cell sphere generation and culturing.
Synthesis analysis for data driven model predictive control*

This paper shows our new contributions on data driven model predictive control, such as persistent excitation, optimal state feedback controller, output predictor and stability. After reviewing the definition of persistent excitation and its important property, the idea of data driven is introduced in model predictive control to construct our considered data driven model predictive control, whose state information and output variable are generated by measured data online. Variation tool is applied to obtain the optimal controller or predictive controller through our own derivation. Furthermore, for the cost function in data driven model predictive control, its preliminary stability is analysed by using the linear matrix inequality and one single optimal state feedback controller is given. To bridge the gap between our derived results and other control strategies, output predictor is constructed from the point of data driven idea, i.e. using some collected input–output data from one experiment to establish the output predictor at any later time instant. Finally, one simulation example is given to prove the efficiency of our derived results.
Using riparian plant species to locate the 1:2-year floodline on single channel rivers

Riparian zones can be characterised botanically into two main areas, a wet bank and a dry bank. These areas have been linked to the duration of inundation by river flow, the boundary between the two being the 1:2 year floodline. Therefore the wet bank is inundated regularly by small floods and the dry bank by larger, less frequent floods, and each may support one to a few distinct plant communities laterally up the bank. Understanding these plant distributions helps rehabilitation projects and Environmental Flow (EFlows) studies as it can inform re-vegetation strategies in the former and help understanding of the links between plants and the river’s flow regime in the latter. Systematic sampling and data analysis methods were developed for single channel rivers with relatively undisturbed natural vegetation to identify and locate the different plant communities in the riparian zone. Generic rules using distance and height from the water’s edge, rather than the presence or absence of plant species, were calculated to locate the communities. While these statistics were derived from the riparian vegetation along perennial Western Cape rivers, South Africa, the methods could be applied to other perennial single channel river anywhere.