Starkbentzen6962

This paper reviews the latest research on scenarios including the processes and products for socio-environmental systems (SES) analysis, modeling and decision making. A group of scenario researchers and practitioners participated in a workshop to discuss consolidation of existing research on the development and use of scenario analysis in exploring and understanding the interplay between human and environmental systems. This paper presents an extended overview of the workshop discussions and follow-up review work. It is structured around the essential challenges that are crucial to progress support of decision making and learning with respect to our highly uncertain socio-environmental futures. It identifies a practical research agenda where challenges are grouped according to the process stage at which they are most significant before, during, and after the creation of the scenarios as products. These challenges for SES include enhancing the role of stakeholder and public engagement in the co-development of scenarios, linking scenarios across multiple geographical, sectoral and temporal scales, improving the links between the qualitative and quantitative aspects of scenario analysis, addressing uncertainties especially surprise, addressing scenario diversity and their consistency together, communicating scenarios including visualization methods, and linking scenarios to decision making.Soil organic carbon (SOC) and soil total nitrogen (STN) are important indicators of soil health and play a key role in the global carbon and nitrogen cycles. High-resolution radar Sentinel-1 and multispectral Sentinel-2 images have the potential to investigate soil spatial distribution information over a large area, although Sentinel-1 and Sentinel-2 data have rarely been combined to map either SOC or STN content. In this study, we applied machine learning techniques to map both SOC and STN content in the southern part of Central Europe using digital elevation model (DEM) derivatives, multi-temporal Sentinel-1 and Sentinel-2 data, and evaluated the potential of different remote sensing sensors (Sentinel-1 and Sentinel-2) to predict SOC and STN content. Four machine-learners including random forest (RF), boosted regression trees (BRT), support vector machine (SVM) and Bagged CART were used to construct predictive models of SOC and STN contents based on 179 soil samples and different combinations of environment results of this study illustrate the potential of free high-resolution radar Sentinel-1 and multispectral Sentinel-2 data as input when developing SOC and STN prediction models.Oil refining produces vast quantities of wastewater with harmful contaminants that can be released back into the environment with a possible risk of toxicity to aquatic wildlife and human populations. Hence the importance of adequate wastewater treatment to achieve safe effluents that protect both ecological and human health. However, some refining effluents are linked to serious pollution problems even after treatment, partly because little progress has been made in determining the causative agents of the observed biological effects, resulting in non-targeted treatment. Here, we followed an effect-directed analysis (EDA) approach using Aliivibrio fischeri as biosensor to show that naphthenic acids (NAs) are important components of refining wastewater resulting from the processing of heavy crude oil. Furthermore, we demonstrate that besides mixture effects, NAs have a significant contribution to the toxicity exerted by these effluents. Profiling of the NA mixture was conducted using high resolution liquid chromatography-Orbitrap, which evidenced that O2 NAs corresponded to 90% of the NAs detected. Our findings contrast with previous reports where classic NAs have been found between 15% and 72% and could explain the significant biological effects observed in A. fischeri. This study broadens the body of evidence pointing at mixture effects and low-concentration pollutants as the cause of toxicity from RWW, in addition to NAs resulting from the processing of heavy crude oil. Our results can serve as a starting point for setting better effluent discharge standards relevant to oil refining wastewater resulting from heavy crude oil and help improve wastewater treatment plants to reduce effluent toxicity.Objectives Aging is assumed to be accompanied by greater health care expenditures. The objective of this retrospective, bottom-up micro-costing study was to identify and analyze the variables related to increased health care costs for the elderly from the provider's perspective. Methods The analysis included all elderly inpatients who were admitted in 2017 to a hospital in Tehran, Iran. In total, 1288 patients were included. The Mann-Whitney and Kruskal-Wallis tests were used. Results Slightly more than half (51.1%) of patients were males, and 81.9% had a partial recovery. The 60-64 age group had the highest costs. selleck products Cancer and joint/orthopedic diseases accounted for the highest proportion of costs, while joint/orthopedic diseases had the highest total costs. The surgery ward had the highest overall cost among the hospital departments, while the intensive care unit had the highest mean cost. No statistically significant relationships were found between inpatient costs and sex or age group, while significant associations (p less then 0.05) were observed between inpatient costs and the type of ward, length of stay, type of disease, and final status. Regarding final status, costs for patients who died were 3.9 times higher than costs for patients who experienced a partial recovery. Conclusions Sex and age group did not affect hospital costs. Instead, the most important factors associated with costs were type of disease (especially chronic diseases, such as joint and orthopedic conditions), length of stay, final status, and type of ward. Surgical services and medicine were the most important cost items.Objectives This study aimed to analyze the mortality of heart disease (HD), ischemic heart disease (IHD), and cerebrovascular disease (CeVD) through an age-period-cohort (APC) analysis. Methods We used data on mortality due to cardiovascular disease from 1995 to 2018 in Japan, as determined by Vital Statistics. Age groups from 0 years to 99 years were defined by 5-year increments, and cohorts were defined for each age group of each year with a 1-year shift. We used Bayesian APC analysis to decompose the changes in the diseases' mortality rates into age, period, and cohort effects. Results The period effects for all diseases decreased during the analyzed periods for both men and women. The cohort effects for men increased substantially in cohorts born from around 1940 to the 1970s for all types of cardiovascular diseases. The cohort effects of HD decreased in the cohorts born in the 1970s or later for both men and women. Regarding IHD and CeVD, either a non-increase or decrease of cohort effects was confirmed for cohorts born in the 1970s or later for men, but the effects for women showed a continuously increasing trend in the cohorts born in the 1960s or later.