Learning, environment

Fuel treatments and other forest restoration thinning practices aim to reduce wildfire risk while building forest resilience to drought, insects, and diseases and increasing aboveground carbon (C) sequestration. However, fuel treatments generate large amounts of unmerchantable woody biomass residues that are often burned in open piles, releasing significant quantities of greenhouse gases and particulates, and potentially damaging the soil beneath the pile. Air curtain burners offer a solution to mitigate these issues, helping to reduce smoke and particulates from burning operations, more fully burn biomass residues compared to pile burning, and eliminate the direct and intense fire contact that can harm soil beneath the slash pile...

Interaction with chemicals, present in drugs, food, environments, and consumer goods, is an integral part of our everyday life. However, depending on the amount and duration, such interactions can also result in adverse effects. With the increase in computational methods, the in silico methods can offer significant benefits to both regulatory needs and requirements for risk assessments and the pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox 3.0, which incorporates molecular similarity and machine-learning models for the prediction of 61 toxicity endpoints such as acute toxicity, organ toxicity, clinical toxicity, molecular-initiating events (MOE), adverse outcomes (Tox21) pathways, several other toxicological endpoints and toxicity off-targets...

OBJECTIVES: Health professionals' education presents unique challenges including clinical application of knowledge and interprofessional collaboration. Additionally, institutions suffer from faculty shortages while class sizes increase. Therefore, educators seek innovative andragogical techniques utilizing minimal resources. Several active learning methods have been introduced as a solution. The aim of this study is to assess the impact of lecture (LBL), case (CBL), and team (TBL) based learning on the students' satisfaction and knowledge attainment...

PURPOSE: Students with intellectual disabilities (ID) typically have difficulties with literacy learning, often not acquiring basic literacy skills. Research and practical experience indicate that when these students are provided with evidence-based instruction, including comprehension as well as phonemic strategies, literacy may develop. METHODS: In this study, four pairs of teachers were interviewed regarding their perceptions of a 12-week digital literacy intervention that focused on both phonics and comprehension strategies...

We established the optimal model by using the automatic machine learning method to predict the degradation efficiency of herbicide atrazine in soil, which could be used to assess the residual risk of atrazine in soil. We collected 494 pairs of data from 49 published articles, and selected seven factors as input features, including soil pH, organic matter content, saturated hydraulic conductivity, soil moisture, initial concentration of atrazine, incubation time, and inoculation dose. Using the first-order reaction rate constant of atrazine in soil as the output feature, we established six models to predict the degradation efficiency of atrazine in soil, and conducted comprehensive analysis of model performance through linear regression and related evaluation indicators...

The rapid advance of nanotechnology has led to the development and widespread application of nanomaterials, raising concerns regarding their potential adverse effects on human health and the environment. Traditional (experimental) methods for assessing the nanoparticles (NPs) safety are time-consuming, expensive, and resource-intensive, and raise ethical concerns due to their reliance on animals. To address these challenges, we propose an in silico workflow that serves as an alternative or complementary approach to conventional hazard and risk assessment strategies, which incorporates state-of-the-art computational methodologies...

Fish diseases pose a significant threat to food security in aquaculture, as they can lead to considerable reductions in fish production, quality, and profitability. Globally, salmon aquaculture is the quickest-expanding food production system. Detecting and diagnosing fish diseases in their early stages is essential to prevent the spread of diseases and reduce the negative impact on aquaculture's economy and environment. To serve this purpose, we introduce the SalmonScan dataset, a novel and comprehensive collection of images of healthy and infected salmon fish, which can be used for various applications in computer science and aquaculture...

OBJECTIVES: The purpose of this study has been to evaluate the use of gamification in the classroom, in terms of its effects on attention, concentration, creativity, and generic capabilities, for university students enrolled in a Bachelor's degree program in Physiotherapy. METHODS: An experimental design was implemented, using three groups differentiated by their time of exposure to the game (0 min, 30 min, or 60 min per week). The sample consisted of 73 s-year students from a Bachelor's degree program in Physiotherapy...

INTRODUCTION: In the post-epidemic era, blended learning has become a social trend for the future of higher education, and scholars have endeavored to understand the factors that influence student learning in these blended communities. Communities of Inquiry is a conceptual framework that describes the components of blended learning environments, indicating teaching presence, social presence, and cognitive presence. However, the framework fails to adequately explore how individual learning motivational factors influence student learning...

OBJECTIVE: We applied a user experience (UX) design approach to clinical decision support (CDS) tool development for the specific use case of pediatric asthma. Our objective was to understand physicians' workflows, decision-making processes, barriers (ie, pain points), and facilitators to increase usability of the tool. MATERIALS AND METHODS: We used a mixed-methods approach with semi-structured interviews and surveys. The coded interviews were synthesized into physician-user journey maps (ie, visualization of a process to accomplish goals) and personas (ie, user types)...

It is important that principles of laboratory-based studies with implications for academic performance be implemented in naturalistic learning environments to gauge their feasibility. Here, an adaptation of a laboratory-based study of exercise breaks during a single video lecture was implemented during large, in-person lectures at Ohio State University for the duration of a semester. The rationale for this approach was based on findings that research participants who took exercise breaks during a video lecture were more likely to be on task towards the end of the lecture and performed significantly better on a multiple choice exam...

Oil-bearing sandstone samples were collected from the Lower Cretaceous sequence in the Kharir-2 exploration well, Kharir oilfields (Eastern Yemen). The current study integrates biomarker of the aliphatic hydrocarbon fraction of the extracted oil with a new finding from the molecular structure of the oil-asphaltene, in order to learn more about their properties, including organic matter (OM) input, depositional environment, and thermal maturity. The overall oil composition results show that the extracted oils have a high saturated hydrocarbon of up to 50% and significant levels of aromatic hydrocarbon and polar components, indicating generally paraffinic to naphthenic oil...

We performed a systematic study on the activity of pristine, Fe-doped, N-doped, and Fe/N-codoped graphdiyne (GDY) for oxygen reduction reactions (ORRs). We found that the pristine GDY has a high overpotential because of the weak binding of the intermediates. The sp-hybridized N-doped GDY enhances the binding of the intermediates at the adjacent sp-hybridized C site, which greatly enhances its ORR activities with a low overpotential of 0.45 V. On the other hand, on Fe-doped GDY, the binding of the intermediates at the Fe site and its neighboring C sites becomes too strong, while the C site at the second nearest acetylene chain becomes the most active site with an overpotential of 0...

Time-lapse microscopy has emerged as a crucial tool in cell biology, facilitating a deeper understanding of dynamic cellular processes. While existing tracking tools have proven effective in detecting and monitoring objects over time, the quantification of signals within these tracked objects often faces implementation constraints. In the context of infectious diseases, the quantification of signals at localized compartments within the cell and around intracellular pathogens can provide even deeper insight into the interactions between the pathogen and host cell organelles...

Impulsive choices prioritize smaller, more immediate rewards over larger, delayed, or potentially uncertain rewards. Impulsive choices are a critical aspect of substance use disorders and maladaptive decision-making across the lifespan. Here, we sought to understand the neuronal underpinnings of expected reward and risk estimation on a trial-by-trial basis during impulsive choices. To do so, we acquired electrical recordings from the human brain while participants carried out a risky decision-making task designed to measure choice impulsivity...

Using spatial mapping processes to learn about threat and safety in an environment is crucial for survival. Research using conditioning paradigms has explored the effects of state (transient arousal) and trait anxiety (anxiety as an aspect of personality) on threat learning and acquisition. However, results are mixed, and little is known regarding why some individuals do not learn to discriminate between threat and safety during contextual conditioning. We used a virtual reality (VR) contextual threat conditioning paradigm to elucidate the effects of state and trait anxiety on contextual threat learning...

This study delves into the intricate dynamics of internet addiction among university students, leveraging a comprehensive quantitative approach to unravel the myriad factors influencing this modern-day malaise. Utilizing logistic regression analysis, this research delineates the predictive significance of Daily Internet Usage Time (DIUT) and Communicative Internet Use Frequency (CIUF) on the propensity for internet addiction, with the analysis substantiating these variables as potent predictors. The model elucidates a significant variance in internet addiction, affirming the complexity of internet addiction as influenced by a constellation of behavioral patterns...

The Covid-19 pandemic has forced the educational sector to quickly adapt to the crisis and shift to online learning environments (OLEs). Therefore, a critical area for research is assessing the readiness of teachers in terms of their familiarity and preference for OLEs. In this study, we aimed to improve the experience and preference of in-service teacher trainees with OLEs during the Covid-19 pandemic in Ethiopia. To achieve this goal, questionnaires were used to gather data from in-service teacher trainees...

This qualitative study was conducted with the aim of investigating the experience of mothers in Tehran in the field of virtual education during the COVID-19 pandemic. The participants in this study were 17 mothers of school children who experienced virtual education in Tehran during the COVID-19 pandemic. Data collection was done through semi-structured interviews, over the phone, and lasted for approximately 30-45 min. The interviews were audio recorded with the permission of the participants, transcribed verbatim, and analyzed using the method of conventional content analysis...

Long-term coal mining could lead to a serious of geo-environmental problems. However, less comprehensive identification of factors controlling the groundwater dynamics were involved in previous studies. This study focused on 68 groundwater samples collected before and after mining activities, Self-Organizing Maps (SOM) combining with Principal Component Analysis (PCA) derived that the groundwater samples were classified into five clusters. Clusters 1-5 (C1-C5) represented the groundwater quality affected by different hydrochemical processes, mainly including mineral (carbonate and evaporite) dissolution and cation exchange, which were controlled by the hydrochemical environment at different stages of mining activities...