Miracle-dz/UniFAR-FTUs huggingface dataset:
Loneliness is associated with poor mental health, social-environmental factors, and health risk behaviours among national samples of in-school adolescents in four Caribbean countries

ABSTRACT The goal of the study was to estimate associations of loneliness with poor mental health, social-environmental and health risk behaviour indicators among adolescents in the Caribbean. Cross-sectional national ‘Global School-Based Student Health Survey (GSHS)’ data of four Caribbean countries (N = 9,143 adolescents) in 2016–2017 were analysed. In adjusted logistic regression analysis, loneliness was significantly positively associated with all five poor mental health outcomes (having no close friends, anxiety-induced sleep disturbance, suicidal ideation, suicide plan and suicide attempt). Regarding social-environmental outcomes, loneliness was significantly positively associated with bullying victimization, having been physically attacked, involvement in fighting, frequent experiences of hunger and passive smoking (in particular among boys). In terms of health risk behaviour outcomes, loneliness significantly increased the odds for current tobacco use, ever drunk, trouble from alcohol use, ever amphetamine use, multiple sexual partners, leisure-time sedentary behaviour, injury and frequent soft drink consumption. In addition, among boys, loneliness increased the likelihood for current cannabis use. Loneliness is associated with poorer mental health, social-environmental risk factors and health risk behaviours. Results show the importance of taking loneliness into account in a number of mental, social, and physical health factors.
Perioperative anemia: clinical practice update

ABSTRACT Perioperative medicine is an evolving area of medicine in which collaboration between internists, hospitalists, surgeons and anesthesiologists is the key to delivering high-quality care. Research in all areas of perioperative medicine, including perioperative anemia, is constantly evolving. Perioperative anemia is a major contributor to mortality and morbidity in the perioperative period. It is associated with an increased likelihood of postoperative wound complications, infections, delirium, increased length of stay and increased risk of readmissions. However, there is a lack of comprehensive guidelines for management of perioperative anemia. We performed an exhaustive review of contemporary literature on perioperative anemia and present evaluation and management recommendations that have the potential to impact clinical practice in the perioperative period.
Reaction kinetics during the thermal activation of the silicon surface passivation with atomic layer deposited Al2O3

The excellent surface passivation of crystalline silicon provided by Al2O3 requires always an activation by a thermal post-deposition treatment. In this work, we present an indirect study of the reaction kinetics during such thermal activation treatments for Al2O3 synthesized by atomic layer deposition. The study was performed for Al2O3 deposited at varying temperatures, which results in different micro-structures of the films and, in particular, different hydrogen concentrations. The effective carrier lifetime was measured sequentially as a function of the annealing time and temperature. From these data, the reaction rate Ract and the activation energy EA were extracted. The results revealed a rather constant EA in the range of 1.4 to 1.5 eV, independent of the deposition temperature. The reaction rate, however, was found to increase with decreasing deposition temperature, which correlates with an increasing amount of hydrogen being incorporated in the Al2O3 films. This is a strong indication for an inte.
Health risk assessment of volatile organic compounds at daycare facilities.

Children are particularly vulnerable to many classes of the volatile organic compounds (VOCs) detected in indoor environments. The negative health impacts associated with chronic and acute exposures of the VOCs might lead to health issues such as genetic damage, cancer, and disorder of nervous systems. In this study, 40 VOCs including aldehydes and ketones, aliphatic hydrocarbons, esters, aromatic hydrocarbons, cyclic terpenes, alcohols, and glycol ethers were identified and qualified in different locations at the University of Missouri (MU) Child Development Laboratory (CDL) in Columbia, Missouri. Our results suggested that the concentrations of the VOCs varied significantly among classrooms, hallways, and playground. The VOCs emitted from personal care and cleaning products had the highest indoor levels (2-ethylhexanol-1, 3-carene, homomenthyl salicylate with mean concentration of 5.15 µg/m3 , 1.57 µg/m3 , and 1.47 µg/m3 , respectively). A cancer risk assessment was conducted, and none of the 95th percentile dose estimates exceeded the age-specific no significant risk levels (NSRL) in all classrooms. Dimensionless toxicity index scores were calculated for all VOCs using a novel web-based framework called Toxicological Prioritization Index (ToxPi), which integrates multiple sources of toxicity data. According to the method, homomenthyl salicylate, benzothiazole, 2-ethylhexyl salicylate, hexadecane, and tridecane exhibited diverse toxicity profiles and ranked as the five most toxic indoor VOCs. The findings of this study provide critical information for policy makers and early education professionals to mitigate the potentially negative health impacts of indoor VOCs in the childcare facilities.
Synthesis and crystal structure of bis(N-o-methylphenyl-N ′-ethoxycarbonylthiourea) copper(I) chloride

The complex bis(N-o-methylphenyl-N′-ethoxycarbonylthiourea)copper(I) chloride was prepared by reaction of cupric chloride with the corresponding thiourea derivative. The complex was characterized by IR and 1H NMR and its structure determined by X-ray diffraction methods. The complex is monoclinic, space group P21/n with cell dimensions a = 8.014(3), b = 21.018(7), c = 15.891(5) Å and β = 101.537(6). Two thiourea ligands and one Cl atom bond to Cu(I) to form a three-coordinate complex with trigonal planar coordination geometry. Intramolecular H-bonds influence the thiourea coordination properties and stabilize the configuration of the complex.
Sampling the complex energy landscape of a simple β-hairpin

The folding trajectories of a 16-residue β-hairpin are studied using the activation–relaxation technique with a generic energy model. From more than 70 trajectories, three folding pathways emerge. All involve a simultaneous optimization of the complete hydrophobic and hydrogen bonding interactions. The first two follow closely those observed by previous theoretical studies, while the third can be described as a reptation move of one strand of the β-sheet with respect to the other. This reptation move indicates that non-native interactions can play a dominant role in the folding of secondary structures.
Tracer diffusion of polyorganosiloxane nanoparticles in solution: Effects of tracer topology and particle concentration

Spherical polyorganosiloxane nanoparticles containing photoreactive dye labels have been used to study self-diffusion in concentrated colloidal dispersions by forced Rayleigh scattering (FRS). Samples studied contained about 0.5 wt. % of these tracer particles and the order of 50 wt. % nonfunctional host particles dissolved in cyclohexane. To avoid any influence of the label molecules on the particle mobility, the tracers have been equipped with a nonfunctional protective shell. The effect of the thickness of this shell as well as of the label content on particle diffusion has been examined carefully. A much lower tracer mobility has been found for particles with protective shell of thickness less than 1 nm. In some cases, even complementary grating effects have been found in the FRS signals, indicating a different tracer mobility of bleached and nonbleached particles. By diffusion studies using tracers with protective shell sufficiently thick to avoid such unwanted effects, the single particle mobility f.
Serious Game Design to Promote Energy Literacy Among Younger Children

Today's children are tomorrow's home owners and policymakers. Engaging children with energy literacy can help equip them with the knowledge, skills and environmentally sustainable attitudes needed in later life. This paper discusses the development of a serious game called Power Pets designed to help children understand where energy comes from, how to save energy, and its connection to the environment. In the game, children adopt a digital pet that they care for by feeding it saved energy accumulated during gameplay as they complete energy saving tasks. In one of the few qualitative studies involving children to date, we investigated the potential of Power Pets to increase engagement with energy literacy with a specific age group between the ages of 5 and 9. Our findings suggest Power Pets provided preliminary indications for improvements in children's understanding of energy saving and the link between energy saving and the environment, both at a cognitive and affective level, however usability and the steep developmental curve in this age group are key considerations.
Local Perspectives for Sharing Economy Design on a Remote Tourist Island

While the HCI community has interest in the role of sharing economy platforms and their impact on large cities, less attention has been given to smaller isolated populations and the perspectives of their local residents in terms of understanding actual use and to benefit those who use them. This paper contributes to this discourse by reporting on a series of participatory-design based workshops that investigate local perspectives on the sharing economy, and opportunities for platform design that serves the needs of residents, on the remote island of Madeira. The context of the Island, including its restrictions on the types of sharing economy activity, inform a discussion on opportunities for design in transportation, homesharing, and community engagement. Finally, we contribute to the understanding of existing principles of participation that would serve to foster social and economic inclusion in the sharing economy in this particular context.
Mediscape: Preliminary Design Guidelines for Interactive Rhythmic Soundscapes for Entraining Novice Mindfulness Meditators

Mindfulness meditation is a beneficial approach to managing stress; however, establishing a practice can be difficult for novice meditators. Interactive soundscapes using brainwave data offer new avenues, yet how to design such novel interfaces is underexplored. We present Mediscape, an interactive ocean soundscape modulated by brainwave data to teach awareness of breathing to novices. Through an exploratory study with 20 participants, we collected interview and questionnaire data on their experience with Mediscape and impact on their stress and wellbeing. Findings revealed the complex nature of the meditation experience for novices, analysed as key themes of shifting state, attention, self-regulation strategy, and immersion. Preliminary design guidelines are proposed to assist designers in creating interactive soundscapes for breath-awareness meditation, through consideration of how sound can be used for rhythmic entrainment of breathing, information on the state of meditation, and the creation of immersive environments.
Home Energy Management System Optimization Strategy Based on Reinforcement Learning

At present, the household load base number is large and the intelligent level is low. Artificial intelligence technology can provide novel ideas for improving the intelligent degree of home energy management. Household load has great demand response potential, which can provide support for the consumption of renewable energy, participate in the peak regulation and frequency regulation, reduce the peak valley difference, as well as stabilize the fluctuation of power grid. The home energy management optimization strategy based on reinforcement learning is presented in this paper. Firstly, long short term memory is used to predict the output of photovoltaic power and electricity price. And then they are transmitted to the decision-making scheduling model as state variables. On this basis, combining with the load characteristics of household electrical equipment, the Markov decision process model based on reinforcement learning is established, and the optimal scheduling process of home energy management system is related. Finally, simulation examples are designed to verify the effectiveness of the method proposed in this paper. The results show that the proposed methodology can meet user's comfort demand while reducing the power consumption cost.
A Task Assignment Framework in Skill-Aware Spatial Crowdsourcing

Spatial Crowdsourcing (SC) is a popular outsourcing platform that assigns tasks to some individual workers, groups and communities through network. Commonly, the SC needs workers to upload their private information to untrust-worthy entities, which may cause a privacy breach. In this paper, we propose a framework for protecting privacy of workers participating in SC tasks. And we consider a complex scenario that the workers may have some different skills and a task may require a set of skills. What's more, in this framework, we propose an incentive mechanism which considered the feedbacks from task publishers and then adjust the skill level of workers. Experimental results based on synthetic datasets show the obvious improvement on completion quality and efficiency of our framework.
Feature Selection Technique for Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a developmental disorder that restricts the development of behaviors, communication, and learning skills. People with ASD have difficulties in communicating and engaging with other people. Presently, a questionnaire called Autism Spectrum Quotient 10 (AQ-10) has been used to diagnose ASD symptoms for individuals [1]. However, using AQ-10 for ASD diagnosis is based on the observation from an individual's behavior and evaluate the result. It cannot show the outstanding attribute or relationship between ASD symptoms in different age-groups. Thus, this research proposed the novel feature selection technique for identifying the important attributes in AQ-10 results from three different age-groups, which are children at age of 7--12, adolescents at age of 13--20, and adults at age over 20. The results will represent the outstanding features and relationships between ASD symptoms in different age-groups, and lead to the proper design of ASD treatment programs for individuals.
Efficient Low-Latency Dynamic Licensing for Deep Neural Network Deployment on Edge Devices

Along with the rapid development in the field of artificial intelligence (AI), especially deep learning, deep neural network (DNN) applications are becoming more and more popular in reality. To be able to withstand the heavy load from mainstream users, deployment techniques are essential in bringing neural network models from research to production. Among the two popular computing topologies for deploying neural network models in production are cloud-computing and edge-computing. Recent advances in communication technologies, along with the great increase in the number of mobile devices, has made edge-computing gradually become an inevitable trend. In this paper, we propose an architecture to solve deploying and processing deep neural networks on edge-devices by leveraging their synergy with the cloud and the access-control mechanisms of the database. Adopting this architecture allows low-latency DNN model updates on devices. At the same time, with only one model deployed, we can easily make different versions of it by setting access permissions on the model weights. This method allows for dynamic model licensing, which benefits commercial applications.
Privacy by Design in Aged Care Monitoring Devices? Well, Not Quite Yet!

Aged Care Monitoring Devices (ACMDs) collect and share information about older adults to ensure their wellbeing. While monitoring devices enable older adults to live independently at home, they pose significant privacy challenges. Within HCI, research has sought to understand users’ privacy concerns, but technology developers’ perceptions of privacy have been explored less. According to the Privacy by Design (PbD) framework, developers should incorporate privacy safeguards into devices prior to deployment. However, little is known about how this is done in practice. To better understand developers’ views on privacy, we interviewed 12 developers from ACMD companies and found five factors that affect how they address privacy: 1) users’ requirements, 2) presumptions about users’ privacy perceptions, 3) privacy laws and regulations, 4) third-party providers, and 5) financial challenges. These factors interconnect with other internal organisational challenges. Our research demonstrates the constraints that make it difficult for developers to implement PbD in practice.
Semantic Engineering Platform: Case Research on Humanoid Resolving Primary Mathematics Application Problems

To solve the problem of sparse semantic representation in semantic processing, this paper designs and develops a semantic engineering platform, which involves the accumulation of knowledge and common sense in the whole process of resolving primary mathematics application problems. Firstly, this paper analyzes the steps and technology of resolving primary mathematics application problems; secondly, it discusses various examples, knowledge and common sense types accumulated by the semantic engineering platform, as well as the internal management technologies of the semantic engineering platform; thirdly, an example is used to explain the steps and results of simulated running of humanoid resolving; finally, the paper summarizes the full paper and puts forward the future work directions.
Designing Community Technology Initiatives: A Literature Review

Citizens and communities play a significant role in shaping the cities they live in, providing a human touch to the development of smart cities. Designers and researchers aim to support this movement through developing (partly) digital technologies together with citizens and communities. However, while the body of examples on this topic is steadily growing, less effort has been made to aggregate existing research and map the underlying processes. In order to contribute to a better understanding of community technology initiatives, this article presents a qualitative systematic literature review on the design and deployment of (partly) digital technologies for civic communities. The article outlines five important topics in these community technology initiatives, based on a qualitative analysis of findings from 36 empirical studies. The five topics are: connectedness to the community context, establish(ed) networks and relationships, balanced roles and responsibilities, diverse and inclusive involvement, and collaborative development of community technologies. The article provides a starting point for future research and design of community technology initiatives and offers an introduction for researchers new to the field.
Research on Gait Recognition of Exoskeleton Robot Based on DTW Algorithm

The control strategy of exoskeleton robots is currently a hot research topic at home and abroad. How to accurately recognize human gait and improve the real-time performance of the system has always been the main research direction in this field. First, a human gait recognition program is designed, mainly, the human gait information is collected through the sensor, and then the S-G filter is used to preprocess the gait data, then the RLS algorithm is used to predict the gait data, and finally the DTW algorithm is used for Human gait phase recognition. Then, the realization principle of the DTW algorithm is introduced, and corresponding improvement methods are proposed for the shortcomings of the algorithm. Finally, the gait phase recognition test of the human body is carried out on the DTW algorithm before and after the improvement. The experimental results show that compared with the traditional DTW algorithm, the improved DTW algorithm has a certain enhancement in recognition rate and real-time performance.
Identification and Estimation of Intensive Margin Effects by Difference-in-Difference Methods

Abstract This paper discusses identification and estimation of causal intensive margin effects. The causal intensive margin effect is defined as the treatment effect on the outcome of individuals with a positive outcome irrespective of whether they are treated or not, and is of interest for outcomes with corner solutions. The main issue is to deal with a potential selection problem that arises when conditioning on positive outcomes. We propose using difference-in-difference methods - conditional on positive outcomes - to estimate causal intensive margin effects. We derive sufficient conditions under which the difference-in-difference estimator identifies the causal intensive margin effect. We apply the methodology to estimate the causal intensive margin effect of reaching the full retirement age on working hours.
A quantitative analysis of the dynamics of the sorption of hydrophobic organic chemicals to suspended sediments

Recent long-term adsorption and desorption experiments with hexachlorobenzene and three polychlorinated biphenyl congeners have clearly demonstrated that the rates of adsorption and desorption for hydrophobic organic chemicals to natural suspended sediments can be relatively slow and therefore that the assumption of chemical equilibrium may not be valid in many realistic situations. These experiments have also led to a better understanding of the adsorption, desorption, and partitioning processes. Based on this experimental work, a theoretical model of the adsorption, desorption, and partitioning of hydrophobic organic chemicals to suspended sediments has been developed. In the present article, a description of this model is given, and results of numerical calculations using this model are compared with experimental results. In the modeling, the emphasis is on the dynamics of sorption. The model is relatively simple, with retarded chemical diffusion within the particle/floc as the basic transport process. A complicating factor is the variations in the particle/floc size and density distributions; these distributions are dependent on local conditions and may also vary with time. In the modeling, they were chosen on the basis of measurements taken during the sorption experiments. In general, good agreement between the numerical and experimental results was obtained for all casesmore » considered. « less