Vulnerability assessment of debris flow in the central Peruvian rainforest – An intercultural approach
Ontology highlight
ABSTRACT:
SUBMITTER:
PROVIDER: S-EPMC10590786 | biostudies-literature | 2023 Oct
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:This paper proposes a new debris flow risk assessment method based on the Monte Carlo Simulation and an Improved Cloud Model. The new method tests the consistency of coupling weights according to the characteristics of the Cloud Model firstly, so as to determine the weight boundary of each evaluation index. Considering the uncertain characteristics of weights, the Monte Carlo Simulation is used to converge the weights in a minimal fuzzy interval, then the final weight value of each evaluation index is obtained. Finally, a hierarchical comprehensive cloud is established by the Improving Cloud Model, which is used to input the comprehensive expectation composed of weights to obtain the risk level of debris flow. Through statistical analysis, this paper selects Debris flow scale (X1), Basin area (X2), Drainage density (X3), Basin relative relief (X4), Main channel length (X5), Maximum rainfall (X6) as evaluation indexes. A total of 20 debris flow gullies were selected as study cases (8 debris flow gullies as model test, 12 debris flow gullies in reservoir area as example study). The comparison of the final evaluation results with those of other methods shows that the method proposed in this paper is a more reliable evaluation method for debris flow prevention and control.
| S-EPMC9894451 | biostudies-literature
Project description:Periprosthetic osteolysis remains the leading complication of total hip arthroplasty, often resulting in aseptic loosening of the implant, and a requirement for revision surgery. Wear-generated particular debris is the main cause of initiating this destructive process. The purpose of this article is to review recent advances in our understanding of how wear debris causes osteolysis, and emergent strategies for the avoidance and treatment of this disease. The most important cellular target for wear debris is the macrophage, which responds to particle challenge in two distinct ways, both of which contribute to increased bone resorption. First, it is well known that wear debris activates proinflammatory signaling, which leads to increased osteoclast recruitment and activation. More recently, it has been established that wear also inhibits the protective actions of antiosteoclastogenic cytokines such as interferon gamma, thus promoting differentiation of macrophages to bone-resorbing osteoclasts. Osteoblasts, fibroblasts, and possibly lymphocytes may also be involved in responses to wear. At a molecular level, wear particles activate MAP kinase cascades, NFkappaB and other transcription factors, and induce expression of suppressors of cytokine signaling. Strategies to reduce osteolysis by choosing bearing surface materials with reduced wear properties (such as metal-on-metal) should be balanced by awareness that reducing particle size may increase biological activity. Finally, although therapeutic agents against proinflammatory mediators [such as tumor necrosis factor (TNF)] and osteoclasts (bisphosphonates and molecules blocking RANKL signaling) have shown promise in animal models, no approved treatments are yet available to osteolysis patients. Considerable efforts are underway to develop such therapies, and to identify novel targets for therapeutic intervention.
| S-EPMC2488166 | biostudies-other
Project description:ObjectivesWe aimed to explore healthcare students' intercultural sensitivity profiles and their relationship with empathy to develop effective education methods that promote non-discriminatory patient care.MethodsWe conducted a cross-sectional questionnaire study, involving a total of 508 international (n= 100) and local (n= 408) healthcare students in Hungary by convenience sampling. The survey included demographics, the Intercultural Sensitivity Scale, and the Interpersonal Reactivity Index. We applied latent profile analysis to identify distinct sensitivity profiles and used multinomial logistic regression to estimate the predictive power of several background variables on profile group membership.ResultsA four-profile solution emerged: "Interculturally average" (n= 241), "Interculturally uncertain" (n= 76), "Interculturally sensitive" (n= 132), and "Interculturally refusing" (n= 54). The model (R2= 0.123; p= 0.001) revealed that psychology major tended to predict "uncertain" group membership (OR= 0.56, p= 0.08) and higher personal distress was a significant predictor of this group (OR=1.11, p= 0.002). Male gender (OR= 3.03, p= 0.001), medicine major (OR= 5.49, p= 0.01), lower perspective-taking (OR= 0.91, p= 0.007) and higher personal distress (OR= 1.09, p= 0.028) were identified as predictors of "refusing" group membership, compared to the "average" group.ConclusionsBy exploring the ways students experience intercultural situations, a more personalized medical education can be developed with a special focus on vulnerable subgroups. For the "uncertain" group, the focus should be more on developing confidence, and intercultural experiences, whereas in the "refusing" group on strengthening empathy. In general, it can be useful to create mixed-gender, multidisciplinary, and intercultural learning environments.
| S-EPMC11687379 | biostudies-literature
Project description:Central blood pressure (cBP) is a highly prognostic cardiovascular (CV) risk factor whose accurate, invasive assessment is costly and carries risks to patients. We developed and assessed novel algorithms for estimating cBP from noninvasive aortic hemodynamic data and a peripheral blood pressure measurement. These algorithms were created using three blood flow models: the two- and three-element Windkessel (0-D) models and a one-dimensional (1-D) model of the thoracic aorta. We tested new and existing methods for estimating CV parameters (left ventricular ejection time, outflow BP, arterial resistance and compliance, pulse wave velocity, and characteristic impedance) required for the cBP algorithms, using virtual (simulated) subjects (n = 19,646) for which reference CV parameters were known exactly. We then tested the cBP algorithms using virtual subjects (n = 4,064), for which reference cBP were available free of measurement error, and clinical datasets containing invasive (n = 10) and noninvasive (n = 171) reference cBP waves across a wide range of CV conditions. The 1-D algorithm outperformed the 0-D algorithms when the aortic vascular geometry was available, achieving central systolic blood pressure (cSBP) errors ≤ 2.1 ± 9.7 mmHg and root-mean-square errors (RMSEs) ≤ 6.4 ± 2.8 mmHg against invasive reference cBP waves (n = 10). When the aortic geometry was unavailable, the three-element 0-D algorithm achieved cSBP errors ≤ 6.0 ± 4.7 mmHg and RMSEs ≤ 5.9 ± 2.4 mmHg against noninvasive reference cBP waves (n = 171), outperforming the two-element 0-D algorithm. All CV parameters were estimated with mean percentage errors ≤ 8.2%, except for the aortic characteristic impedance (≤13.4%), which affected the three-element 0-D algorithm's performance. The freely available algorithms developed in this work enable fast and accurate calculation of the cBP wave and CV parameters in datasets containing noninvasive ultrasound or magnetic resonance imaging data.NEW & NOTEWORTHY First, our proposed methods for CV parameter estimation and a comprehensive set of methods from the literature were tested using in silico and clinical datasets. Second, optimized algorithms for estimating cBP from aortic flow were developed and tested for a wide range of cBP morphologies, including catheter cBP data. Third, a dataset of simulated cBP waves was created using a three-element Windkessel model. Fourth, the Windkessel model dataset and optimized algorithms are freely available.
| S-EPMC7612539 | biostudies-literature
Project description:Clinically relevant polymorphisms often demonstrate population-specific allele frequencies. Central and South America remain largely uncategorized in the context of pharmacogenomics.We assessed 15 polymorphisms from 12 genes (ABCB1 3435C>T, ABCG2 Q141K, CYP1B1*3, CYP2C19*2, CYP3A4*1B, CYP3A5*3C, ERCC1 N118N, ERCC2 K751Q, GSTP1 I105V, TPMT 238G>C, TPMT 460G>A, TPMT 719A>G, TYMS TSER, UGT1A1*28 and UGT1A1 -3156G>A) in 81 Peruvian and 95 Mexican individuals.Six polymorphism frequencies differed significantly between the two populations: ABCB1 3435C>T, CYP1B1*3, GSTP1 I105V, TPMT 460G>A, UGT1A1*28 and UGT1A1 -3156G>A. The pattern of observed allele frequencies for all polymorphisms could not be accurately estimated from any single previously studied population.This highlights the need to expand the scope of geographic data for use in pharmacogenomics studies.
| S-EPMC4515450 | biostudies-literature
Project description:Why does someone thrive in intercultural situations; while others seem to struggle? In 2014, Leung and colleagues summarized the literature on intercultural competence and intercultural effectiveness into a theoretical framework. This integrative framework hypothesizes that the interrelations between intercultural traits, intercultural attitudes and worldviews, and intercultural capabilities predict the effectiveness with which individuals respond to intercultural situations. An empirically verified framework can contribute to understanding intercultural competence and effectiveness in health care workers, thus contributing to more equity in health care. The present study sets out to test this integrative framework in a specific health care context. Future health care practitioners (N = 842) in Flanders (Belgium) were questioned on all multidimensional components of the framework. Structural equation modeling showed that our data were adequate to even a good fit with the theoretical framework, while providing at least partial evidence for all hypothesized relations. Results further showed that intercultural capabilities remain the major gateway toward more effective intercultural behavior. Especially the motivation and cognition dimensions of cultural intelligence seem to be key factors, making these dimensions an excellent target for training, practical interventions, and identifying best practices, ultimately supporting greater intercultural effectiveness and more equity in health care.
| S-EPMC9026297 | biostudies-literature
Project description:Preserving biodiversity under rapidly changing climate conditions is challenging. One approach for estimating impacts and their magnitude is to model current relationships between genomic and environmental data and then to forecast those relationships under future climate scenarios. In this way, understanding future genomic and environmental relationships can help guide management decisions, such as where to establish new protected areas where populations might be buffered from high temperatures or major changes in rainfall. However, climate warming is only one of many anthropogenic threats one must consider in rapidly developing parts of the world. In Central Africa, deforestation, mining, and infrastructure development are accelerating population declines of rainforest species. Here we investigate multiple anthropogenic threats in a Central African rainforest songbird, the little greenbul (Andropadus virens). We examine current climate and genomic variation in order to explore the association between genome and environment under future climate conditions. Specifically, we estimate Genomic Vulnerability, defined as the mismatch between current and predicted future genomic variation based on genotype-environment relationships modeled across contemporary populations. We do so while considering other anthropogenic impacts. We find that coastal and central Cameroon populations will require the greatest shifts in adaptive genomic variation, because both climate and land use in these areas are predicted to change dramatically. In contrast, in the more northern forest-savanna ecotones, genomic shifts required to keep pace with climate will be more moderate, and other anthropogenic impacts are expected to be comparatively low in magnitude. While an analysis of diverse taxa will be necessary for making comprehensive conservation decisions, the species-specific results presented illustrate how evolutionary genomics and other anthropogenic threats may be mapped and used to inform mitigation efforts. To this end, we present an integrated conceptual model demonstrating how the approach for a single species can be expanded to many taxonomically diverse species.
| S-EPMC8127712 | biostudies-literature
Project description:Flooding is among the most common and costly natural disasters in the United States. Flood impacts have been on the rise as flood mitigating habitats are lost, development places more people and infrastructure potentially at risk, and changing rainfall results in altered flood frequency. Across the nation, communities are recognizing the value of flood mitigating habitats and employing green infrastructure alternatives, including restoring some of those ecosystems, as a way to increase resilience. However, communities may under value green infrastructure, because they do not recognize the current benefits of risk reduction they receive from existing ecosystems or the potential benefits they could receive through restoration. Freshwater wetlands have long been recognized as one of the ecosystems that can reduce flood damages by attenuating surface water. Small-scale community studies can capture the flood-reduction benefits from existing or potentially restored wetlands. However, scalability and transferability are limits for these high resolution and data intensive studies. This paper details the development of a nationally consistent dataset and a set of high-resolution indicators characterizing where people benefit from reduced flood risk through existing wetlands. We demonstrate how this dataset can be used at different scales (regional or local) to rapidly assess flood-reduction benefits. At a local scale we use other national scale indicators (CRSI, SoVI) to gauge community resilience and recoverability to choose Harris County, Texas as our focus. Analysis of the Gulf Coast region and Harris County, Texas identifies communities with both wetland restoration potential and the greatest flood-prone population that could benefit from that restoration. We show how maps of these indicators can be used to set wetland protection and restoration priorities.
| S-EPMC8312689 | biostudies-literature
Project description:Debris flows are dense and fast-moving complex suspensions of soil and water that threaten lives and infrastructure. Assessing the hazard potential of debris flows requires predicting yield and flow behavior. Reported measurements of rheology for debris flow slurries are highly variable and sometimes contradictory due to heterogeneity in particle composition and volume fraction ([Formula: see text]) and also inconsistent measurement methods. Here we examine the composition and flow behavior of source materials that formed the postwildfire debris flows in Montecito, CA, in 2018, for a wide range of [Formula: see text] that encapsulates debris flow formation by overland flow. We find that shear viscosity and yield stress are controlled by the distance from jamming, [Formula: see text], where the jamming fraction [Formula: see text] is a material parameter that depends on grain size polydispersity and friction. By rescaling shear and viscous stresses to account for these effects, the data collapse onto a simple nondimensional flow curve indicative of a Bingham plastic (viscoplastic) fluid. Given the highly nonlinear dependence of rheology on [Formula: see text], our findings suggest that determining the jamming fraction for natural materials will significantly improve flow models for geophysical suspensions such as hyperconcentrated flows and debris flows.
| S-EPMC9636957 | biostudies-literature
Project description:Climate change poses significant challenges to marginalised communities, particularly in regions with highly vulnerable populations like rural and tribal communities. This study aims to assess the livelihood vulnerability of tribal households to climate change impacts in the Chhindwara and Dhar districts in Central India, identifying key determinants and geographical variations in vulnerability. Primary data collection involved a multistage sampling procedure where a household survey was conducted across both districts, yielding a sample size of 535 respondents. The climatic data was collected from the India Meteorological department from 1954 to 2023. This study employs a mixed method, including innovative trend analysis for shifts in climatic patterns, standardised precipitation index-1 (SPI-1) for evaluating wet and dry conditions, LVI-IPCC framework applied using survey data to assess vulnerability, and multiple linear regression (MLR) model to determine the determinants of vulnerability. The results indicate significant changes in rainfall and temperature patterns in both regions, indicating increased vulnerability among tribal communities. SPI-1 analysis highlights the shift in precipitation patterns, with implications for agriculture and water availability. The LVI-IPCC results reveal a moderate level of vulnerability among surveyed households, with Dhar exhibiting higher vulnerability than Chhindwara. Furthermore, LVI-IPCC results were validated using other vulnerability assessment approaches. The MLR analysis highlights the significant influence of key determinants, such as primary income source, extreme weather events, access to safe drinking water, and livelihood strategies, on vulnerability, emphasising the importance of addressing socioeconomic disparities and enhancing adaptive capacity. Integrating primary and secondary data enables an inclusive investigation of vulnerability determinants and geographical variations within the study area. It offers evidence-based policy recommendations for augmenting resilience and encouraging sustainable development among tribal communities facing climate change challenges.
| S-EPMC11909276 | biostudies-literature