Environmental Measures Research Articles

Investigating students’ perceptions of the medical education environment and learning autonomy in blended learning in pediatrics: a cross-sectional study

BackgroundIn the process of education reform, carrying out continuous educational environment measurement is necessary. This study aimed to evaluate the perceptions of the medical education environment and learning autonomy in blended learning in pediatrics among clinical medicine students, as well as the relationship between these two constructs.MethodsA cross-sectional study was conducted on clinical medical students from the First Clinical School of Wuhan University who had completed the blended learning courses of pediatrics. Perceptions of the medical education environment and learning autonomy were surveyed using the Dundee Ready Education Environment Measure (DREEM) and the Autonomy in Learning Rating Scale for college students (ALRS), respectively. Independent samples t-test, one-way ANOVA, correlation, and multiple linear regression analyses were conducted.ResultsA total of 487 students participated in the survey (valid response rate: 83.53%). Students’ perceptions of the current medical education environment and learning autonomy were generally positive. Among the average scoring rates of DREEM, students’ perception of teachers (SPT) > students’ perception of learning (SPL) > students’ perception of atmosphere (SPA) > students’ academic self-perceptions (SASP) > students’ social self-perception (SSSP), while learning strategies > learning motivation > self-regulation > content and environment among the average scoring rates of ALRS. Correlation analyses revealed that all subscales of the two were significantly associated with each other (P < 0.05). Regression analyses showed that SPA and SASP were significant factors for students’ learning autonomy.ConclusionClinical medicine students who experienced blended learning in pediatrics had positive perceptions of the medical education environment, and their learning autonomy was good and closely related to the perceptions of the medical education environment. In the implementation of blended learning, continuous optimization of teaching content and proactive enhancement of the medical education environment will help enhance clinical medicine students’ satisfaction with the educational environment and their learning autonomy.Clinical trial numberNot applicable.

Correction: The Impact of Environmental Measures on Trade and Innovation: Evidence from the WTO Environmental Database (EDB)

Correction: The Impact of Environmental Measures on Trade and Innovation: Evidence from the WTO Environmental Database (EDB)

Perception of medical students at public universities in Uganda on their education environment: a cross-sectional study

BackgroundThe healthcare workforce is one of the six core components of a well-functioning and sufficient health system. The WHO highlights that improving education and training of the health workforce is critical to improving health systems. Medical education is a pillar of the healthcare workforce. The educational environment - the physical circumstances or conditions under which learning takes place - is an important factor determining medical education’s effectiveness. Its academic and clinical effects significantly determine medical students’ attitudes, knowledge, skills, progression, and behaviors. To ensure strong health systems, there is a need for improvement in medical education. Improvement must be contextual and informed by locally relevant data. This study, which assessed Ugandan medical students’ perception of their learning environment, provides crucial context-specific data highly relevant to the current state of medical education in Uganda.MethodsThis quantitative cross-sectional study was conducted among medical students across five medical schools in Uganda between December 2021 and February 2022. Participants completed an online questionnaire with a demographics section and the Dundee Ready Education Environment Measure (DREEM) tool. The data was analyzed using R in R Studio version 2021.09.0 + 351. The average score for each DREEM sub-scale and the total DREEM score were calculated, and their relationship with demographic characteristics was examined.ResultsThe average total DREEM score of the 335 participants was 112.27/200 (56.12%). We found that 69% (231/335) of the students had a positive perception. The sub-scale mean scores were as follows: Perception of Atmosphere – 25.14/48, Social Self-perception − 14.94/28, Perception of Teachers − 24.86/44, Perception of Learning − 28.8/48, and Academic Self-perceptions – 19.04/32. “There is a good support system for students who get stressed” was the item with the lowest mean score (1.41/5).ConclusionsThe study’s findings indicate that medical students’ perceptions of their learning environment are just above average. This suggests a need for improvement, particularly in the atmosphere and social support, to ensure the training of a robust health workforce. The results of this study should motivate stakeholders to initiate changes that will enhance the quality of medical education in Uganda.

USE OF GEO-INFORMATION SYSTEMS FOR GROUNDWATER MONITORING

Abstract . The article is devoted to the study of the possibilities of using geographic information systems (GIS) for monitoring the state of groundwater, which is important for ensuring environmental safety and sustainable management of water resources. Groundwater is an important source of fresh water for the population, industry and agriculture, but it is vulnerable to various pollutions caused by both natural and anthropogenic factors. Therefore, the implementation of reliable monitoring systems that allow timely detection, assessment and forecasting of changes in water quality is necessary to prevent the deterioration of the ecological situation and prevent the spread of pollution. Geographic information systems (GIS ) offer significant opportunities for the collection and integration of large volumes of spatial data, including satellite images, remote sensing results, automated sensor data, and field observations. GIS allow creating multi-layered maps reflecting the ecological state of underground aquifers, modeling pollution processes and predicting their possible impact on nearby ecosystems and water sources. Thanks to the use of GIS, it is possible to combine data from different sources in a single interactive system, which simplifies analysis and provides the ability to quickly respond to any detected deviations. The article examines in detail the key methods used within GIS for groundwater monitoring, including satellite sounding to analyze changes in the earth's surface, spectral indices to assess the state of vegetation and soil salinity, and radar methods to determine soil electrical conductivity. Particular attention is paid to the application of three-dimensional modeling, which allows visualization of the spread of pollution in underground aquifers, which facilitates decision-making regarding the optimal location of monitoring stations and the design of protective structures. In combination with automated sensors recording water parameters in real time, GIS provides continuous monitoring of the physico-chemical indicators of groundwater and allows for prompt assessment of their condition. The article also analyzes the possibilities of using predictive modeling in GIS to assess the further spread of pollution and develop environmental risk management measures. It is described how mathematical models in GIS can help predict the impact of anthropogenic and natural factors on groundwater, which ensures the development of scientifically based solutions to reduce pollution and maintain water quality at a safe level. The implementation of GIS in groundwater monitoring is an important step towards increasing the efficiency of water resources management, ensuring their protection from pollution and preserving the ecological stability of the regions.

The Ecological Silence: Producing Green Policies outside the Environmental Discourse

The development of the green policies of the European Union (EU) has established a framework in which national governments had to introduce environmental measures with serious social and economic consequences. The present article examines the relationship political initiative – environmental awareness – pro-environmental behavior through the prism of a specific case study related to the 2023 protests in Bulgaria against the closure of coal plants. The analysis of public attitudes and of media discourse reveals that the Bulgarian government avoided legitimizing its decisions through ecological motivations. Low levels of trust in political institutions and the perceived lack of prestige of ecological issues are shifting research attention to the barriers to pro-environmental behavior in contemporary European societies.

Environmental consequences of maintenance dredging in the port of Sabetta (Gulf of Ob) and compensation measures

In this work, we assess possible negative effects associated with regular maintenance dredging in the port of Sabetta on the marine biological resources and coastal environment of the Gulf of Ob. The costs of environmental protection measures and сountervailing payments are determined. As a restoration activity for fish fauna, it is proposed to implement the artificial reproduction of young fish of valuable species, such as peled, siberian sturgeon, or muksun, followed by their release into the natural environement of the lakes and rivers of the West-Siberian fishery water basin.

Active Perception in SLAM Exploration: Problem Formulation and Methods Review

Active SLAM (A-SLAM) aims to enable an agent’s autonomous exploration and mapping task, provide robustness and accuracy in both localization and mapping and enhance environmental adaptivity in applications. Its working principle, as a holistic probabilistic-based problem in model formulation, can be divided into three decoupled working stages and accordingly solved, these stages are brief action identification, cost and utility computation, and action execution. The identification stage needs reasoning on what and where to look at in order to diminish uncertainty in an efficient fashion, by employing sensory methods and performing searching or optimization tasks with appropriate environmental representations, to feed the following stages with a discretized set of planning goals. This is the active perception problem by definition. The activeness of active SLAM is mostly decided at the perception stage with appropriate quantifying measures. This paper revisits the formulation of the A-SLAM problem especially by the stage of active perception, reviews its environmental representations (maps) and related modeling measures for information and uncertainty, underlines a sample-based aim of maximizing the information gain from sensors with respect to corresponding maps, and make comments on some novel approaches.

Multi-Modal Dataset of Human Activities of Daily Living with Ambient Audio, Vibration, and Environmental Data

The detection of human activities is an important step in automated systems to understand the context of given situations. It can be useful for applications like healthcare monitoring, smart homes, and energy management systems for buildings. To achieve this, a sufficient data basis is required. The presented dataset contains labeled recordings of 25 different activities of daily living performed individually by 14 participants. The data were captured by five multisensors in supervised sessions in which a participant repeated each activity several times. Flawed recordings were removed, and the different data types were synchronized to provide multi-modal data for each activity instance. Apart from this, the data are presented in raw form, and no further filtering was performed. The dataset comprises ambient audio and vibration, as well as infrared array data, light color and environmental measurements. Overall, 8615 activity instances are included, each captured by the five multisensor devices. These multi-modal and multi-channel data allow various machine learning approaches to the recognition of human activities, for example, federated learning and sensor fusion.

Blood pressure measurement technique in clinical practice in the NHS Greater Glasgow and Clyde.

Blood pressure (BP) measurement is a common procedure conducted in various disciplines and is widely available on clinical reports. The diagnosis and management of hypertension require reliable measurement of BP in outpatient clinics. Published studies suggest the standardised method for BP measurement is difficult to apply in routine clinical practice. This study aimed to assess the current practice of BP measurement in outpatient clinics in relevant secondary care clinical specialties across the 15 separate hospital sites of the NHS Greater Glasgow and Clyde region (population 1.2 million) compared to the recommended standardised method. An online questionnaire was developed and disseminated to the supervising clinician of each of 268 regular outpatient clinics. The questionnaire focused on the standardised BP method (patient preparation, environment, and BP measurement technique). The questionnaire was returned for 110 clinics. 73 (66.4%) of the participating clinics measure BP routinely and these formed the basis for further analysis. 3 clinics (4.1%) apply all components of the standardised BP method. 5 (6.9%) clinics deliver advice to patients prior to clinic attendance on how to prepare for BP measurement. 61 (83.6%) of participating clinics have a dedicated quiet environment for BP measurement. 50 (68.5%) clinics always place the cuff on bare upper arm and 63.0% use a cuff size appropriate to upper arm circumference. In a wide range of secondary care out-patient clinic settings, we found that BP measurement rarely adheres to the recommended standards. This has important implications for the quality of treatment decisions that are based on BP measurement.

Spatial dynamics of Culex quinquefasciatus abundance: geostatistical insights from Harris County, Texas

Mosquito-borne diseases pose a significant public health threat, prompting the need to pinpoint high-risk areas for targeted interventions and environmental control measures. Culex quinquefasciatus is the primary vector for several mosquito-borne pathogens, including West Nile virus. Using spatial analysis and modeling techniques, we investigated the geospatial distribution of Culex quinquefasciatus abundance in the large metropolis of Harris County, Texas, from 2020 to 2022. Our geospatial analysis revealed clusters of high mosquito abundance, predominantly located in central Houston and the north-northwestern regions of Harris County, with lower mosquito abundance observed in the western and southeastern areas. We identified persistent high mosquito abundance in some of Houston’s oldest neighborhoods, highlighting the importance of considering socioeconomic factors, the built environment, and historical urban development patterns in understanding vector ecology. Additionally, we observed a positive correlation between mosquito abundance and neighborhood-level socioeconomic status with the area deprivation index explaining between 22 and 38% of the variation in mosquito abundance (p-value < 0.001). This further underscores the influence of the built environment on vector populations. Our study emphasizes the utility of spatial analysis, including hotspot analysis and geostatistical interpolation, for understanding mosquito abundance patterns to guide resource allocation and surveillance efforts. Using geostatistical analysis, we discerned fine-scale geospatial patterns of Culex quinquefasciatus abundance in Harris County, Texas, to inform targeted interventions in vulnerable communities, ultimately reducing the risk of mosquito exposure and mosquito-borne disease transmission. By integrating spatial analysis with epidemiologic risk assessment, we can enhance public health preparedness and response efforts to prevent and control mosquito-borne disease.

Evaluation of Heath Care Commitment with Prevention and Infectious Control Protocols in Mofid Children Hospital, IRAN

Background: The dedication of healthcare teams to adhering to protocols for the use of personal protective equipment (PPE), maintaining vaccination coverage among healthcare workers (HCWs), and ensuring environmental health are crucial elements in managing hospital-acquired infections. Objectives: This study aimed to evaluate adherence to PPE use, vaccination history, hand hygiene protocols, and environmental health practices in a tertiary children's hospital in Iran. Methods: This cross-sectional study evaluated compliance with PPE use, vaccination history among doctors, nurses, and hospital staff, adherence to strict hygiene practices, patient isolation protocols, and environmental health measures based on an Iranian Health Ministry query. Data collection was conducted over three months, from May to August 2023. Results: During the study, 285 staff members were assessed for compliance with hand hygiene protocols. Nurses demonstrated the highest level of compliance, reaching 51%. The highest compliance with hand hygiene protocols at the five designated moments was approximately 79%, with the transplantation and hemodialysis wards achieving the highest rates. Nurses also showed the most positive vaccination records. Personal protective equipment was used correctly in various wards, with an overall compliance rate of 79%. Conclusions: This study revealed that compliance with health protocols in different parts of the hospital was suboptimal and required significant improvement.

Prenatal and Postnatal Exposure to Organophosphate Esters and Replacement Flame Retardant Mixtures and Childhood Respiratory Outcomes

BackgroundEarly life exposure to single organophosphate esters (OPEs) and replacement brominated flame retardants (RBFRs) has been associated with adverse childhood respiratory outcomes, but the effects of OPE and RBFR mixtures are unknown. Methods377 pregnant women were recruited to the Health Outcomes and Measures of Environment (HOME) Study from 2003 to 2006 in Cincinnati, Ohio and later delivered singleton infants. We measured house dust OPEs and RBFRs prenatally at 20 weeks of gestation and postnatally at child age of 12 months and urinary OPEs prenatally at 16 and 26 weeks of gestation and at delivery and postnatally at child ages of 12 and 24 months. We performed Quantile G-computation (QG-computation) and Bayesian Kernel Machine Regression (BKMR) to assess the association of the exposure mixtures with wheeze and hay fever by child age of 5 years and evaluate the individual exposure effects and their interactions within the mixtures. ResultsIn QG-computation, a quartile increase in all urinary OPEs sampled at age 12 months was associated with 16% higher risk of wheeze (RR: 1.16, 95% CI: 1.01, 1.35). In BKMR, mixtures of prenatal OPEs and RBFRs, urinary OPEs at 16 weeks of gestation or 12 months of age and prenatal average urinary OPEs were associated with higher risk of childhood wheeze. Mixtures of prenatal average urinary OPEs were positively associated with childhood hay fever. When other exposures were fixed at their median value, prenatal dust tris(2-chloroethyl) phosphate (TCEP) and urinary bis(1,3-dichloro-2-propyl) phosphate (BDCIPP) were associated with higher hay fever risk, while dust prenatal tris(1-chloro-2-propyl) phosphate (TCIPP) was associated with lower risk. ConclusionsThese results suggest that early life exposure to OPE and RBFR mixtures may be risk factors for adverse respiratory outcomes in childhood.

Test Flight of a Stratospheric Sonic Anemometer Prototype

Abstract Stratospheric sonic anemometers are an emerging technology for making wind velocity measurements in low pressure environments. This paper explores the challenges, design, and high-altitude testing of a digital sonic anemometer for applications including high-altitude balloon navigation, atmospheric gravity wave research, solar activity research, and planetary science on Mars. The system was flown on NASA’s Sensor Package for Attitude, Rotation, and Relative Observable Winds (SPARROW-3) balloon test flight out of Fort Sumner, New Mexico, in August 2022. The mission recorded relative wind data throughout the flight at temperatures as low as −40°C and at the balloon’s float altitude of 38 km (3.8-mb pressure; 1 mb = 1 hPa). The device surpassed all previous sonic anemometers regarding maximum operational altitude. However, only two of the three axes operated well above 32 km, leading to some validation challenges. The system achieved a velocity resolution of 0.1 m s−1 (standard deviation) and recorded three-dimensional wind measurement every 2.25 s. Future plans anticipate addressing the faulty axis and increasing performance to a resolution of 0.01 m s−1 and a wind sampling rate of 10 Hz.

A generalized TODIM approach based on information measurement and consensus building model in probabilistic hesitant fuzzy environment

Information measurement and decision-making methods are two important aspects in the application of probabilistic hesitant fuzzy elements (PHFEs), and these issues are crucial for improving decision quality and enhancing the applicability of PHFSs. This paper focuses on the entropy measure and score function of PHFEs, and then proposes a generalized TOIDM method based on information measurement and consensus building. In this contribution, we develop a novel non-probabilistic entropy measure by two non-fuzzy elements and a novel score function based on sigmoid function. The novel non-probabilistic entropy of PHFEs can comprehensively reflect the dynamic changes of fuzzy uncertainty and hesitant uncertainty, and provide a new axiomatic framework. The novel score function of PHFEs can synthesize multiple information effectively with strong integrity. In the sequel, the two proposed information measurement methods are compared with existing methods to further verify the validity of the developed methods. Eventually a consensus building model is constructed based on the proposed information measurement method, and then a generalized TODIM approach based on information measurement and consensus building is proposed for probabilistic hesitant fuzzy environment. The developed approach is demonstrated with an emergency rescue planning decision-making problem. Sensitivity analysis and comparative analysis are employed to verify the validity and stability of the approach and information measures proposed in this paper. Based on the findings of this study, we conclude that the proposed methods effectively enrich the existing information measurement methods and decision-making methods in the field of probabilistic hesitant fuzzy.

Noise reduction in non-invasive brain-computer interfaces for robot control

Abstract To employ a brain-computer interface to control an assistance robot could help disabled people to achieve a minimum degree of autonomy and reduce their dependence on caregivers for simple tasks. In this project, we use a textile, capacitive brain computer interface (BCI) to control an assistant robot. Our BCI is based on Steady State Visual Evoked Potentials (SSVEP), which are a response of the brain to a periodic visual stimulus at a fixed frequency. Since the brain signals are in the microvolt range, the noise reduction of external disturbances has a high relevance. Here, we demonstrate a correlation method for detecting and eliminating phase shifts between different measurements for averaging. This method allows measurements in unshielded environment of two microvolts (uV) with an averaging factor of 100 in our non-invasive BCI set-up.

Airline environmental efficiency measures through a non-convex meta-frontier DEA model

Airline environmental efficiency measures through a non-convex meta-frontier DEA model

Lifestyle, Environment, and Dietary Measures Impacting Cognitive Impairment: The Evidence Base for Cognitive Subtypes

: Cognition includes all phases of valid functions and processes, e.g., sensitivity, judgment, assessment, and decision-making. Thinking is also a cognitive procedure since it involves considering potential opportunities. There are various types of cognition. Hot cognition involves mental procedures where emotion plays a role, while cold cognition includes mental processes that do not include feelings or emotions. Cognitive memories of various types include sensor memory, sensing touch, smell, and sight; short-term memory allows one to recall, e.g., what one had for lunch a few days ago; working memory includes remembering telephone numbers or directions to a destination; and long-term memory comprises of major milestones in life and recalling one’s childhood events. These are further classified as episodic, e.g., the first day in primary school, and semantic memories, such as recalling the capital city of a country and filling out crossword puzzles. Declarative memories include remembering significant past events, such as global information. Cognition is affected by factors, such as nutrition, aging, addiction, environment, mental health, physical activity, smoking, and keeping the brain active. Consumption of plant- based foods plays a prominent role in the prevention of cognitive memory. Playing games and instruments, reading books, and being socially active make life more satisfying, thus assisting in the preservation of mental function and slowing mental decline.

Post-Adaptive Reuse Evaluation of Heritage Buildings using Multi-Criteria Decision-Making Techniques

Evaluating the condition of heritage buildings after being used for their new functions is important because eventually, issues start to surface. Most studies conducted about post-adaptive reuse evaluation are either theoretical or incomprehensive. Therefore, the aim of this paper is to develop a multi-disciplinary evaluation framework, which can quantify the linguistic evaluation by experts and building users. This is accomplished by integrating fuzzy logic and grey systems theory with multi-criteria decision-making techniques as well as gathering evaluation criteria from the literature and heritage experts related to architectural, functional, structural, sustainable, and heritage aspects. The proposed methodology is applied to a case study in Egypt, where three heritage buildings reused as banks are prioritized for rehabilitation to extend their service lives. The obtained results reveal that the aesthetic and structural aspects received more attention in the building with the best condition than conducting environmental measures. Additionally, the sensitivity analysis shows that the decision-making problem is more sensitive to the structural condition than the heritage aspect, which has the highest weight. Further, no rank reversal was observed when one of the alternatives was removed, indicating a robust decision-making process. Consequently, the developed evaluation framework can accommodate the conflicting interests of the involved stakeholders, protect the cultural values of these heritage buildings, as well consider the sustainability dimensions which have become more important than ever before. Additionally, it does not require sophisticated skills from the decision-maker and allows modifying the evaluation criteria and their corresponding weights to suit different contexts.

A detailed kinetic submechanism for OH* chemiluminescence in hydrocarbon combustion

Here, we propose a new physically consistent modeling scheme, JIHT-OHex(CxHy), that accurately predicts the formation and consumption of electronically excited chemiluminescent OH∗ molecules in hydrocarbon flames over a wide range of temperatures, pressures, and mixture compositions. It incorporates (unchanged) our recent well-founded JIHT-OHex(H2) reaction submodel (Sharipov et al., 2024, Combust. Flame, 263, 113417), aimed at describing the OH∗ evolution in hydrogen oxidation, and contains a necessary set of elementary processes involving OH∗ and carbon-containing species with the rate constants that are based either on a critical review of known, sometimes conflicting literature data on the elementary reaction kinetics of OH∗ or, where necessary and appropriate, on semiempirical estimates. To improve the JIHT-OHex(CxHy) performance against a representative data set for the observed OH(A2Σ+→X2Π) chemiluminescent emission (near 309 nm) accompanying high-temperature oxidation of various (from C1 to C10) hydrocarbon-based mixtures that we aggregated at the preparatory stage of the work, the rate coefficients of reaction and quenching processes that the overall OH∗ kinetics is most sensitive to (or for which there is a particular scatter in the available kinetic data, if any) were jointly optimized within their theoretical expectations and experimental uncertainties. It is shown that our universal detailed OH∗ submechanism, which includes a much larger pool of elementary processes (32 reactions and 36 quenching partners) than previous essentially global models (consisting of only a few processes and tailored to specific mixtures and combustion conditions), clearly outperforms the competitors in terms of integral accuracy (when tested against the multitude of the collected OH∗ emission measurements). Accordingly, there is reason to believe, as exemplified for the conditions of the laminar premixed methane-air flame, that our detailed OH∗ submodel with physically realistic (to the extent possible) rate constants will perform adequately over a wider range of burning conditions and flow parameters than that for which it was validated and tuned.Novelty and significance statementAlthough it is widely accepted that UV chemiluminescent OH(A2Σ+−X2Π) emission as an optical signature of the combustion process as a whole and of the underlying chemistry offers unique diagnostic capabilities, in recent years, definitely insufficient attention has been paid to the development of the detailed reaction mechanisms for quantitative interpretation of the OH∗ chemiluminescence measurements in various burning environments. This is especially true for the oxidation of hydrocarbons. Indeed, the pertinent OH∗ models known to date are essentially global, meaning that they all contain a surprisingly small number of processes (in most cases, only a couple of OH∗-forming reactions are involved alongside the quenching processes) and their rate constants are adjusted to specific hydrocarbon-based mixtures and burning conditions. Accordingly, a revision of the current understanding of the OH∗ kinetics in the presence of hydrocarbons is highly desired; therefore, our detailed physically-based reaction mechanism, which comprises dozens of plausible pathways of OH∗ formation and depletion with realistic rate coefficients and thus is capable of simulating the OH∗ emission in hydrocarbon flames more accurately than previous models, is in itself a fundamentally significant and novel contribution to the practice of chemiluminescence modeling. No less importantly, the rate constant fits, recommended here, are also of independent interest in the context of excited-state chemistry.

Eco-social divides in public policy preferences in Great Britain.

Environmental and social policy measures can both complement and contradict each other. Recent environmental sociology literature suggests that this dual relationship can give rise to eco-social divides in European societies, as some people either endorse or reject both types of measures, while some support one set of policies but not the other. In the current paper, we use data from the British Social Attitudes survey to investigate eco-social divides in Great Britain. The results confirm the presence of four sizeable attitudinal groups with distinct combinations of welfare and environmental preferences. The sizes of the groups have nevertheless changed considerably over time, with people who are simultaneously in favour of welfare and environmental measures becoming more numerous, and the opponents of both measures becoming fewer. Cultural conservatism/progressiveness, age and political party allegiance are key predictors of eco-social attitudinal group membership.