Predicting the impact of climate change on crop water footprint using CMIP6 in the Shule River Basin, China.

Quantitatively predicting the impacts of climate change on water demands of various crops is essential for developing measures to ensure food security, sustainable agriculture, and water resources management, especially in arid regions. This study explored the water footprints (WFs) of nine major crops in the middle and downstream areas of Shule River Basin, Northwest China, from 1989 to 2020 using the WF theory and CROPWAT model and predicted the future WFs of these crops under four emission and socio-economic pathway (SSPs-RCPs) scenarios, which provides scientific support for actively responding to the negative impacts of climate change in arid regions. Results indicated: (1) an increasing trend of the overall crop WF, with blue WF accounting for 80.31-99.33% of the total WF in the last 30 years. Owing to differences of planting structure, water-conservation technologies, and other factors, the multi-year average WF per unit area of crops was 0.75 × 104 m3 hm-2 in downstream area, which was higher than that in midstream area (0.57 × 104 m3 hm-2) in the last 30 years; therefore agricultural water use efficiency in the downstream area was lower than that in the midstream area, implying that the midstream area has more efficient agricultural water utilization. (2) an initial increase and then decrease of crop WFs in the study area under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios by the end of the century, reaching their peak in 2030s which was higher than that from 1989 to 2020; with the maximum growth rates in the midstream area ranging from -0.85% in SSP5-8.5 to 5.33% in SSP2-4.5 and 29.74% in SSP5-8.5 to 34.71% in SSP2-4.5 in the downstream area. The local agricultural water demand would continue to increase and water scarcity issues would be more severe in the next 10-20 years, affecting downstream areas more. Under the SSP3-7.0 scenario, crop WF values of the midstream and downstream regions will be 2.63 × 108 m3 and 4.22 × 108 m3 in 2030, respectively, which is significantly higher than those of other scenarios and show a long-term growth trend. The growth rate of the midstream and downstream regions will reach 44.71% and 81.12%, respectively, by the end of this century, so the local agricultural water use would be facing more strain if this scenario materializes in the future. Therefore, the Shule River Basin should encourage development of water-saving irrigation technologies, adjust the planting ratio of high water consuming crops, and identify other measures to improve water resource utilization efficiency to cope with future water resource pressures.

Willingness to participate in a personalized health cohort - insights from the swiss health study pilot phase.

BACKGROUND: This paper explores the feasibility of establishing a large-scale population-based cohort and biobank in Switzerland by assessing potential participants' needs, expectations, and concerns about such an infrastructure providing information on health, lifestyle, and exposure trajectories, the development of disease, and risk factors over time. METHODS: We utilized a scenario-based questionnaire in the Swiss Health Study pilot phase (2020-2021), involving 1349 adults aged 20-69 from the cantons Vaud and Bern. We conducted descriptive statistics supported by R and qualitative content analysis of n = 374 open responses related to attitudes towards research. RESULTS: We highlight the benefits and challenges of the scenario-based approach, discuss the sample represented in the pilot phase, and present implications for building a full cohort. We also report on participants' attitudes towards and previous experience with health research. We analyze references regarding informed consent and feedback, attitudes towards the Swiss Health Study, and recommendations on improving its scope, design, and instruments. Results indicate a high interest (90%) in participating in a national health study, with 85% of a random population sample willing to join a long-term cohort. Only 43% were familiar with biobanks, and 44% preferred general consent. Trust was high for Swiss-based public research but lower for researchers from other countries or private sector. Over 95% expressed willingness to complete online questionnaires, undergo physical examination, and donate biosamples. Almost all participants wanted to know the outcomes of the medical tests (99.5%) and the exposure to environmental stressors (95%) from their study center visit. Preferred tools for monitoring sleep, physical activity, and diet were known smartphone apps with automatic data management. CONCLUSION: Overall, the study reveals a positive attitude towards personalized health research, with a strong willingness to share data and samples. Key insights focus the meaning of informed consent for participation, the relevance of sampling and representativeness, as well as the significance and challenges of personalized feedback, especially regarding environmental health concerns. Findings emphasize participants' supportive yet reflexive stances, underscoring the importance of aligning research values with individual values in personalized health research. These insights contribute valuable considerations for refining the scope, design, and instruments of future cohort studies.

Source Attribution of Health Burdens From Ambient PM2.5, O3, and NO2 Exposure for Assessment of South Korean National Emission Control Scenarios by 2050.

We quantify anthropogenic sources of health burdens associated with ambient air pollution exposure in South Korea and forecast future health burdens using domestic emission control scenarios by 2050 provided by the United Nations Environment Programme (UNEP). Our health burden estimation framework uses GEOS-Chem simulations, satellite-derived NO2, and ground-based observations of PM2.5, O3, and NO2. We estimate 19,000, 3,300, and 8,500 premature deaths owing to long-term exposure to PM2.5, O3, and NO2, respectively, and 23,000 NO2-associated childhood asthma incidences in 2016. Next, we calculate anthropogenic emission contributions to these four health burdens from each species and grid cell using adjoint sensitivity analysis. Domestic sources account for 56%, 38%, 87%, and 88% of marginal emission contributions to the PM2.5-, O3-, and NO2-associated premature deaths and the NO2-associated childhood asthma incidences, respectively. We project health burdens to 2050 using UNEP domestic emission scenarios (Baseline and Mitigation) and population forecasts from Statistics Korea. Because of population aging alone, there are 41,000, 10,000, and 20,000 more premature deaths associated with PM2.5, O3, and NO2 exposure, respectively, and 9,000 fewer childhood asthma incidences associated with NO2. The Mitigation scenario doubles the NO2-associated health benefits over the Baseline scenario, preventing 24,000 premature deaths and 13,000 childhood asthma incidences by 2050. It also slightly reduces PM2.5- and O3-associated premature deaths by 9.9% and 7.0%, unlike the Baseline scenario where these pollutants increase. Furthermore, we examine foreign emission impacts from nine SSP/RCP-based scenarios, highlighting the need for international cooperation to reduce PM2.5 and O3 pollution.

Faculty Perception of Scenario-Based MCQs, SAQs, and MEQs in Medical Education at an Apex Institute.

Purpose: This study explores the current knowledge and overall awareness of the faculty at an Apex institute about the use and difficulties of scenario-based multiple-choice questions (SB-MCQs), short-answer questions (SB-SAQs), and modified essay questions (SB-MEQs) in the assessment of the undergraduate and postgraduate students. Objectives: To assess faculty perception of awareness and use of SB-MCQs, SB-SAQs, and SB-MEQs and to understand the challenges encountered while designing scenario-based questions (SBQs) and the ways to overcome them. Study Procedure: The tool used for data collection was a Google form questionnaire designed with a total of 16 questions-12 Likert-scale format items and four open-ended questions. The quantitative data collected as a response to close-ended questions was analyzed by descriptive statistics and percentage values. For qualitative data, thematic analysis was done for open-ended questions. Conclusion: The study showed that the faculty has the motivation and agreeability to switch over from traditional questions to scenario-based questions but constant training in the form of regular faculty development programs and workshops is required for its effective implementation. On the administrative level, challenges like lack of sufficient faculty and proper inter-departmental integration for designing scenarios must be addressed. Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-024-02052-6.

Investigating agricultural water sustainability in arid regions with Bayesian network and water footprint theories.

Water scarcity is a significant constraint in agricultural ecosystems of arid regions, necessitating sustainable development of agricultural water resources. This study innovatively combines Bayesian theory and Water Footprint (WF) to construct a Bayesian Network (BN). Water quantity and quality data were evaluated comprehensively by WF in agricultural production. This evaluation integrates WF and local water resources to establish a sustainability assessment framework. Selected nodes are incorporated into a BN and continuously updated through structural and parameter learning, resulting in a robust model. Results reveal a nearly threefold increase of WF in the arid regions of Northwest China from 1989 to 2019, averaging 189.95 × 108 m3 annually. The region's agricultural scale is expanding, and economic development is rapid, but the unsustainability of agricultural water use is increasing. Blue WF predominates in this region, with cotton having the highest WF among crops. The BN indicates a 70.1 % probability of unsustainable water use. Sensitivity analysis identifies anthropogenic factors as primary drivers influencing water resource sustainability. Scenario analysis underscores the need to reduce WF production and increase agricultural water supply for sustainable development in arid regions. Proposed strategies include improving irrigation methods, implementing integrated water-fertilizer management, and selecting drought-resistant, economically viable crops to optimize crop planting structures and enhance water use efficiency in current agricultural practices in arid regions. This study not only offers insights into water management in arid regions but also provides practical guidance for similar agricultural contexts. The BN model serves as a flexible tool for informed decision-making in dynamic environments.

Scenario analysis and multi-criteria decision analysis to explore alternative reimbursement pathways for whole genome sequencing for blood cancer patients.

BACKGROUND: Whole genome sequencing (WGS) has transformative potential for blood cancer management, but reimbursement is hindered by uncertain benefits relative to added costs. This study employed scenario planning and multi-criteria decision analysis (MCDA) to evaluate stakeholders' preferences for alternative reimbursement pathways, informing future health technology assessment (HTA) submission of WGS in blood cancer. METHODS: Key factors influencing WGS reimbursement in blood cancers were identified through a literature search. Hypothetical scenarios describing various evidential characteristics of WGS for HTA were developed using the morphological approach. An online survey, incorporating MCDA weights, was designed to gather stakeholder preferences (consumers/patients, clinicians/health professionals, industry representatives, health economists, and HTA committee members) for these scenarios. The survey assessed participants' approval of WGS reimbursement for each scenario, and scenario preferences were determined using the geometric mean method, applying an algorithm to improve reliability and precision by addressing inconsistent responses. RESULTS: Nineteen participants provided complete survey responses, primarily clinicians or health professionals (n = 6; 32 %), consumers/patients and industry representatives (both at n = 5; 26 %). "Clinical impact of WGS results on patient care" was the most critical criterion (criteria weight of 0.25), followed by "diagnostic accuracy of WGS" (0.21), "cost-effectiveness of WGS" (0.19), "availability of reimbursed treatment after WGS" (0.16), and "eligibility criteria for reimbursed treatment based on actionable WGS results" and "cost comparison of WGS" (both at 0.09). Participants preferred a scenario with substantial clinical evidence, high access to reimbursed targeted treatment, cost-effectiveness below $50,000 per quality-adjusted life year (QALY) gained, and affordability relative to standard molecular tests. Reimbursement was initially opposed until criteria such as equal cost to standard tests and better treatment accessibility were met. CONCLUSION: Payers commonly emphasize acceptable cost-effectiveness, but strong clinical evidence for many variants and comparable costs to standard tests are likely to drive positive reimbursement decisions for WGS.

HornBase: An audio dataset of car horns in different scenarios and positions.

In recent years, there has been significant growth in the development of Machine Learning (ML) models across various fields, such as image and sound recognition and natural language processing. They need to be trained with a large enough data set, ensuring predictions or results are as accurate as possible. When it comes to models for audio recognition, specifically the detection of car horns, the datasets are generally not built considering the specificities of the different scenarios that may exist in real traffic, being limited to collections of random horns, whose sources are sometimes collected from audio streaming sites. There are benefits associated with a ML model trained on data tailored for horn detection. One notable advantage is the potential implementation of horn detection in smartphones and smartwatches equipped with embedded models to aid hearing-impaired individuals while driving and alert them in potentially hazardous situations, thus promoting social inclusion. Given these considerations, we developed a dataset specifically for car horns. This dataset has 1,080 one-second-long .wav audio files categorized into two classes: horn and not horn. The data collection followed a carefully established protocol designed to encompass different scenarios in a real traffic environment, considering diverse relative positions between the involved vehicles. The protocol defines ten distinct scenarios, incorporating variables within the car receiving the horn, including the presence of internal conversations, music, open or closed windows, engine status (on or off), and whether the car is stationary or in motion. Additionally, there are variations in scenarios associated with the vehicle emitting the horn, such as its relative position-behind, alongside, or in front of the receiving vehicle-and the types of horns used, which may include a short honk, a prolonged one, or a rhythmic pattern of three quick honks. The data collection process started with simultaneous audio recordings on two smartphones positioned inside the receiving vehicle, capturing all scenarios in a single audio file on each device. A 400-meter route was defined in a controlled area, so the audio recordings could be carried out safely. For each established scenario, the route was covered with emissions of different types of horns in distinct positions between the vehicles, and then the route was restarted in the next scenario. After the collection phase, the data preprocessing involved manually cutting each horn sound in multiple one-second windowing profiles, saving them in PCM stereo .wav files with a 16-bit depth and a 44.1 kHz sampling rate. For each horn clipping, a corresponding non-horn clipping in close proximity was performed, ensuring a balanced model. This dataset was designed for utilization in various machine learning algorithms, whether for detecting horns with the binary labels, or classifying different patterns of horns by rearranging labels considering the file nomenclature. In technical validation, classifications were performed using a convolutional neural network trained with spectrograms from the dataset's audio, achieving an average accuracy of 89% across 100 trained models.

Nutritional Composition of Post-Catastrophic Foods.

In addition to current challenges in food production arising from climate change, soil salinization, drought, flooding, and human-caused disruption, abrupt sunlight reduction scenarios (ASRS), e.g., a nuclear winter, supervolcano eruption, or large asteroid or comet strike, are catastrophes that would severely disrupt the global food supply and decimate normal agricultural practices. In such global catastrophes, teragrams of particulate matter, such as aerosols of soot, dust, and sulfates, would be injected into the stratosphere and block sunlight for multiple years. The reduction of incident sunlight would cause a decrease in temperature and precipitation and major shifts to climate patterns leading to devastating reductions in agricultural production of traditional food crops. To survive a catastrophic ASRS or endure current and future disasters and famines, humans might need to rely on post-catastrophic foods, or those that could be foraged, grown, or produced under the new climate conditions to supplement reduced availability of traditional foods. These foods have sometimes been referred to as emergency, alternate, or resilient foods in the literature. While there is a growing body of work that summarizes potential post-catastrophic foods and their nutritional profiles based on existing data in the literature, this article documents a list of protocols to experimentally determine fundamental nutritional properties of post-catastrophic foods that can be used to assess the relative contributions of those foods to a balanced human diet that meets established nutritional requirements while avoiding toxic levels of nutrients. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Total digestible glucans Basic Protocol 2: Apparent protein digestibility Basic Protocol 3: Vitamins B1, B3, B9, C, and D2 by HPLC Basic Protocol 4: Total antioxidant activity (DPPH-scavenging activity) Basic Protocol 5: Total phenolic compounds (Folin-Ciocalteu reagent method) Basic Protocol 6: Mineral content by ICP-OES.

A social-ecological approach to support equitable land use decision-making.

Human-driven land use change can result in unequitable outcomes in the provision and appropriation of ecosystem services (ES). To better address equity-related effects of land use change in decision-making, analyses of land use and ES changes under different land use management alternatives should incorporate ecological and social information and take a disaggregated approach to ES analysis. Because such approaches are still scarce in the literature, we present a generalized social-ecological approach to support equitable land use decision-making (in terms of process and outcomes) and an example of its application to a case study in southwestern Ethiopia. We propose a six-step approach that combines scenario planning with equity-focused, disaggregated analyses of ES. Its application in our study area made equity-related effects of land use change explicit through the recognition of different beneficiary groups, value types, and spatial locations. We recommend the application of our approach in other contexts, especially in the Global South.

Qualification rate and associated factors regarding COVID-19 clinical skills training based on scenario simulation teaching to medical staffs in China: a hospital-based cross-sectional study.

BACKGROUND: The coronavirus disease (COVID-19) pandemic has accentuated the need for effective clinical skills training in infectious diseases. This study aimed to explore the influencing factors of infectious disease clinical skills training based on scenario simulation teaching for medical staff in China. METHODS: This hospital-based, cross-sectional study was conducted at the Third People's Hospital of Shenzhen between March and December 2022. Scenario simulation teaching was applied, and factors such as gender, educational level, professional background, and previous experience were examined to determine their impact on qualification outcomes. RESULTS: The study included participants primarily between the ages of 20-40 years, with a higher proportion of women holding university degrees. Nurses and physicians were more likely to qualify, indicating the significance of professional backgrounds. Women showed a higher likelihood of qualifying than men and higher educational attainment correlated with better qualification rates. Prior experience with protective clothing in isolation wards was a significant determinant of successful qualification. Multivariate analysis underscored the influence of sex, education, and previous experience on training effectiveness. CONCLUSION: Scenario simulation is an effective strategy for training clinical skills in treating infectious diseases. This study highlights the importance of considering sex, education, professional background, and prior experience when designing training programs to enhance the efficacy and relevance of infectious disease training.

The impacts of thermocouple insulation failure on the accuracy of temperature measurement data in forensic fire-death scenarios-Part I: Physical disintegration.

Thermocouples are utilized to monitor a wide range of temperatures in industrial applications. They are also used in both fire and forensic science research to measure temperatures of fires and of materials exposed to fire. Taking accurate temperature measurements during forensic fire-death scenarios is very difficult due to direct fire exposure to thermocouples, shrinkage and destruction of tissues, and movements from pyre collapse and pugilistic posturing of human donors. This two-part study investigates the impacts on the accuracy of temperature data if the selected thermocouples are unable to withstand fire exposure. Part I (this article) provides an overview of thermocouple theory along with evidence of the physical deterioration that occurs when glass fiber-insulated thermocouple wires are overheated by exposure to fire-level temperatures in a muffle furnace. This study verified that insulation overheating causes embrittlement and disintegration, which can cause the indicated temperature to reflect a new location of measurement located far away from the original measuring junction at the thermocouple tip. Part II will discuss the measurement errors that occurred due to low electrical resistance of insulation when three different thermocouple models were passed through fire-level temperatures to measure an ice bath at a constant temperature of 0°C.

The impacts of thermocouple insulation failure on the accuracy of temperature measurement data in forensic fire-death scenarios-Part II: Low electrical resistance and contamination.

Part II of this two-part article investigates the impact of thermocouple insulation failure on temperature measurement data in forensic fire-death scenarios. Two different models of glass fiber-insulated thermocouple wires (GG-K-24-SLE and HH-K-24 from Omega Engineering) were passed through a ceramic kiln at temperatures up to 1093°C to measure an ice bath at a constant 0°C. In a separate experiment, the same two models of thermocouple wire plus a BLMI-XL-K-18U-120 mineral-insulated metal-sheathed thermocouple probe were passed through a wood pallet fire to measure an ice bath. In the ceramic kiln, the effect on measurement errors was determined for short vs. long exposure lengths and clean insulation vs. insulation contaminated with pork fat. Glass fiber-insulated thermocouple wires showed severe failure in both experiments, with errors ranging from -270°C to almost 2200°C. The metal-sheathed probe showed no evidence of insulation failure and continued to accurately measure the ice bath temperature within expected margins of error around 0°C. This study highlights how exposure of inadequate thermocouples to fire-level temperatures produces severe errors in temperature data. Consequently, it will not be possible to use this data to draw any accurate conclusions about the effects of fire exposure to human donors or animal proxies.

Simulation dataset of annual crop growth, GHG emission and SOC stock dynamics under current and projected climate conditions for major crops with current and reduced fertiliser inputs in Southwest, England.

For mitigating the unintended environmental impacts associated with intensive farming across the world, it is crucial to understand the complex impacts of potential reductions in fertiliser use on multiple ecosystem services, including crop production, GHG emissions and changes in soil organic carbon (SOC) stocks. Using site specific spatial data and information, a novel integrated modelling approach using established agroecosystem models (SPACSYS and RothC) was implemented to evaluate the impacts of various fertiliser reductions (10 %, 30 % and 50 %) under current / baseline and projected (RCP2.6, RCP4.5 and RCP8.5) climate scenarios in a study catchment in southwest England. 48 unique combinations of soil types, climate conditions and fertiliser inputs were evaluated for five major arable crops (winter wheat, maize, winter barley, spring barley, winter oilseed rape) plus ryegrass. Modelled annual estimates of crop yields and biomass, emissions of gases with warming potentials (nitrous oxide, methane, carbon) and SOC stocks in the topsoil (0-30 cm) were tabulated for all combinations considered. These simulated data series could be further analysed to evaluate inter-annual variations and their implications for climate resilience and combined with additional data to quantify nutrient use efficiency and undertake cost- benefit analysis, and to contribute to inter-regional comparisons of fertiliser management at broad scale.

Study on factors influencing carbon dioxide emissions and carbon peak heterogenous pathways in Chinese provinces.

Implementing a Carbon Peak Action Plan at the regional level requires comprehensive consideration of the developmental heterogeneity among different provinces, which is an effective pathway for China to realize the goal of carbon peak by 2030. However, there is currently no clear provincial roadmap for carbon peak, and existing studies on carbon peak pathways inadequately address provincial heterogeneity. Therefore, this paper employs the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to decompose assess 8 factors influencing carbon emissions of 30 provinces. According to scenario analysis, the paper explores the differentiated pathways for provincial carbon peaks based on policy expectation indicators (including population, economy, and urbanization rate) and comprises policy control indicators (including the energy structure, energy efficiency, industrial structure, transportation structure, and innovation input). The results indicate that population, per capita GDP, urbanization rate, and innovation input are the primary factors for influencing (negatively) the growth of carbon emissions. In contrast, the optimization and upgrading of the industrial structure, energy intensity, energy structure, and transportation structure have mitigating effects on carbon emissions, especially for the first two factors. The forecasting results reveal that robust regulations of the energy and industry can effectively accelerate carbon peak at a reduced magnitude. If developed at BAU, China cannot achieve carbon peak by 2030, continuing an upward trend. However, by maximizing the adjustment strength of energy and industrial transformation within the scope of provincial capabilities, China could achieve carbon peak as early as 2025, with a peak of 12.069 billion tons. In this scenario, 24 provinces could achieve carbon peak before 2030. Overall, this study suggests the feasibility of differentiated pathway to achieve carbon peaks in China, exploring the carbon peak potential and paths of 30 provinces, and identifying provinces where carbon peak is more challenging. It also provides a reference for the design of carbon peak roadmaps at both provincial and national levels and offers targeted recommendations for the implementation of differentiated policy strategies for the government.

The Dynamic Change in the Reliability Function Level in a Selected Fire Alarm System during a Fire.

This article discusses fundamental issues associated with the functional reliability of selected fire alarm systems (FASs) in operation during building fires. FASs operate under diverse external or internal natural environmental conditions, and the operational process of FAS should take into account the impacts of physical phenomena that occur during fires. Their operation is associated with the constant provision of reliability. FAS designers should also consider the system's reliability when developing fire control matrices, tables, algorithms, or scenarios. All functions arising from an FAS control matrix should be implemented with a permissible reliability level, RDPN(t), prior to, as well as during, a fire. This should be assigned to the controls saved in the fire alarm control unit (FCP). This article presents the process by which high temperatures generated during a fire impact the reliability of FAS functioning. It was developed considering selected critical paths for a specific scenario and the control matrix for an FAS. Such assumptions make it possible to determine the impact of various temperatures generated during a fire on the reliability of an FAS. To this end, the authors reviewed that the waveform of the R(t) function changes for a given FAS over time, Δt, and then determined the fitness paths. The critical paths are located within the fire detection and suppression activation process, using FAS or fixed extinguishing devices (FEDs), and the paths were modeled with acceptable and unacceptable technical states. The last section of this article defines a model and graph for the operational process of a selected FAS, the analysis of which enables conclusions to be drawn that can be employed in the design and implementation stages.

Designing Evidence-based Simulation Scenarios for Clinical Practice.

Simulation-based education is a widely used teaching technique in healthcare education. Simulation can provide a rich learning environment for caregivers at all levels. Creating simulation-based scenarios is a systematic, evidence-based, learner-centered process that requires skill and expertise. There are 11 known criteria of best practice in simulation design. Using best practices in simulation scenario design development can provide the bedrock for learners to engage in clinical practice with competency, confidence, and caring. Examples and suggestions are provided to guide readers to create quality, learner-centered simulation scenarios using the Healthcare Simulation Standards of Best Practice: Simulation Design.

Effectiveness and satisfaction with virtual and donor dissections: A randomized controlled trial.

In recent years, human anatomy education has faced challenges with traditional donor dissection, leading to the emergence of virtual dissection as an alternative. This study aims to investigate the academic performance and satisfaction of medical students by comparing the virtual and donor dissections. An open-labeled crossover randomized controlled trial was conducted with 154 first-year medical students in Human Anatomy and Neuroanatomy laboratories, which were divided into three classes. Students were randomly assigned to either the virtual (virtual dissection followed by donor dissection) or donor (donor dissection followed by virtual dissection) groups in each class. A curriculum, incorporating head-mounted displays (HMDs), a life-sized touchscreen, and tablets, was developed. Data was evaluated through quizzes and surveys. In the Human Anatomy laboratory, each class of the donor group conducted heart extraction, dissection and observation. In observation class, the virtual group had a significantly higher mean quiz score than the donor group (p < 0.05). Compared to the donor, satisfaction was significantly higher for the HMD (understanding of concept and immersion), life-size touchscreen (esthetics, understanding of the concept, and spatial ability), and tablet (esthetics, understanding of the concept, spatial ability, and continuous use intention). In the Neuroanatomy laboratory, the virtual group showed significantly higher mean quiz scores than the donor group (p < 0.05), and tablet showed a significantly higher satisfaction than donor in terms of esthetics, understanding of the concept, and spatial ability. These results suggest that virtual dissection has the potential to supplement or replace donor dissection in anatomy education. This study is innovative in that it successfully delivered scenario-based virtual content and validated the efficacy in academic performance and satisfaction when using virtual devices compared to donor.Trial registration: This research has been registered in the Clinical Research Information Service (CRIS, https://cris.nih.go.kr/cris/search/detailSearch.do?search_lang=E&focus=reset_12&search_page=L&pageSize=10&page=undefined&seq=26002&status=5&seq_group=26002 ) with registration number "KCT0009075" and registration date "27/12/2023".

Multi-scenario analysis and optimization strategy of ecological security pattern in the Weihe river basin.

For many years, the Weihe River Basin (WRB) has struggled to achieve a balance between ecological protection and economic growth. Constructing an Ecological Security Pattern (ESP) is extremely important for ensuring ecological security (ES). This study employed a coupling of multi-objective programming (MOP) and the patch-generating land use simulation (PLUS) model to project land use change (LUCC) in 2040 across three scenarios. Leveraging circuit theory, we generated ecological corridors and identified key ecological nodes, enabling a comparative analysis of ESPs within the WRB. The main results showed that: (1) The Ecological Protection (EP) scenario showed the highest proportions of forestland, grassland, and water, indicating an optimal ecological environment. Conversely, the Economic Development (ED) scenario features the greatest proportion of construction land, particularly evident in the rapid urban expansion. The Natural Development (ND) scenario exhibits a more balanced change, aligning closely with historical trends. (2) The ecological source areas in the EP scenario is 13,856.70 km2, with the largest and most intact patch area. The ecological source patches that have been identified in the ED scenario exhibit fragmentation and dispersion, encompassing a total area of 8018.82 km2. The ecological source areas in the ND scenario is most similar to the actual situation in 2020, encompassing 8474.99 km2. (3) The EP scenario demonstrates minimal landscape fragmentation. The ED scenario presents a more intricate corridor pattern, hindering species and energy flow efficiency. The ND scenario is more similar to the actual distribution in 2020. Protecting and restoring key ecological nodes, and ensuring the integrity and connectivity of ecological sources are crucial for ESP optimization in various scenarios. Combining all results, we categorize the WRB's spatial pattern into "three zones, three belts, and one center" and offer strategic suggestions for ecological preservation, promoting sustainable local ecological and socioeconomic development.

Climate change impacts on magnitude and frequency of urban floods under scenario and model uncertainties.

Many studies have confirmed that climate change leads to frequent urban flooding, which can lead to significant socioeconomic repercussions. However, most existing studies have not evaluated the impacts of climate change on urban flood from both event-scale and annual-scale dimensions. In addition, there are only few studies that simultaneously consider scenario and model uncertainties of climate change, and combine flood risk assessment and uncertainty analysis results to provide practical suggestions for urban drainage system management. This study uses the statistical downscaling method to calculate the design rainfall under ten rainfall return periods of four climate models and three climate change scenarios in 2040s, 2060s, and 2080s in various prefecture-level cities in China. The four climate models are HadGEM2- ES, MPI-ESM-MR, NorESM1-M and FGOALS-g2 models and the three climate change scenarios are constructed by different representative concentration pathways (RCP), namely RCP2.6, RCP4.5 and RCP8.5. On this basis, relying on the generated drainage systems using geographical information and other data, event-scale and annual-scale precipitation are combined to calculate the change ratio of annual flood volume expectation in prefecture-level cities in each future year compared with the current situation. Furthermore, the study evaluates scenario and model uncertainties of climate change, and then comprehensively integrates the flood risk and its uncertainties to provides suggestions for urban drainage system management.

A comprehensive emission inventory of air pollutants from municipal solid waste incineration in China's megacity, Beijing based on the field measurements.

The rising of municipal solid waste incineration (MSWI), constituting 5 % of NOx emissions in Beijing, poses a significant challenge to improving air quality. This study establishes a comprehensive historical inventory of air pollutants (APs) emitted from MSWI plants between 2004 and 2023. The inventory was developed using both the continuous emissions monitoring systems (CEMS)-based method and the EF (emission factors) -based method, incorporating detailed plant-level activity data and localized EF derived from field measurements. These include data from CEMS and manual monitoring. Analysis of CEMS data reveals high compliance rates with emission limits for MSW in Beijing, with 99.9 %, 99.5 %, 99.8 %, 98.7 %, and 99.5 % of units meeting standards for PM, SO2, NOx, CO and HCl, respectively. This suggests effective implementation of emission standards in Beijing, although further strengthening of policies, particularly for CO emissions, is warranted. Overall, total AP emissions have increased annually largely attributed to measures implemented for DeSOx, DeNOx, and DePM since 1998. Most MSWI facilities are located in suburban areas rather than urban cores. Emissions of SO2, HCl, CO, Hg, Cd + Ti, other metals, dioxins, VOCs, and NH3 exhibit a spatially homogeneous distribution at the district level, while PM and NOx emissions demonstrate heterogeneity. Scenario analysis underscores the importance of continuous improvement and upgrading of advanced air pollution control devices. This study contributes a methodological framework for estimating emissions, reducing uncertainties, and informing policy-making to mitigate APs emissions in megacities. It serves as a valuable reference for similar cities grappling with air quality challenges.