Search results

This chapter presents a case study on smallholder vulnerability and adaptation to long-term desiccation in the West African Sahel. Climatologists recognize Sahelian desiccation as a long-term multi-decadal dry period that persisted from roughly 1968 to 1995. This study draws on fine-scale ethnographic and daily rainfall data to elucidate local perspectives on this broad regional process. As such, this provides a window on the local lived experience of regional climate variability.

This study draws on multiple periods of ethnographic fieldwork in two different Mossi areas in north-central Burkina Faso (West Africa). Fieldwork consisted of key informant interviews, household surveys, and participant observation. The authors incorporate daily precipitation data from two meteorological stations provided by the General Directorate of Meteorology of Burkina Faso. Researchers assembled this data and graphed daily rainfall totals for individual rainfall seasons in the years preceding each period of fieldwork. The qualitative and quantitative data are analyzed by using a Sustainable Livelihoods (SL) framework.

The study finds that local perceptions of increased rainfall variability correspond to patterns evident in daily rainfall records for individual stations. Additionally, the authors document how rural producers are negatively affected by both intra-seasonal and multi-decadal rainfall variability. Mossi smallholders have adapted through new cropping patterns, livelihood diversification, and investments in agricultural intensification. These adaptations have been largely successful and could be adopted by other Sahelian groups in their efforts to adapt to climate change.

Fieldwork took place over several years in two different departments and five localities. The two anthropologists used a common livelihoods analytical framework but different research protocols over this time span. Thus, the data collection was not systematic across all locations and time periods. This limits the degree to which results are representative beyond surveyed localities at their respective points in time.

This study presents local views and perceptions of regional climate variability and ecological change. It is a rare bottom-up perspective supplemented with precipitation data.

This study implements inflation adjustments, as proposed by International Accounting Standard 15 (IAS15), to determine an inflation‐adjusted version of Economic Value Added (EVA). The relationships between the nominal (EVAnom) and inflation‐adjusted (EVAreal) versions of EVA, and market‐adjusted share returns are investigated, and compared with those of residual income, earnings and operating cash flow. Relative information content tests suggest that earnings have the strongest relationship with share returns, while the results of the incremental tests indicate that the EVAnom and EVAreal components do not provide statistically significant information content beyond that provided by residual income.

Community perception of climate change is a factor in increasing local awareness of climate disaster risk. This encourages more disaster risk reduction actions by the communities themselves, and thus, provides a driver for sustainable community disaster risk management (DRM) initiatives. Using these hypotheses, this chapter assesses whether the communities’ climate change perceptions, awareness of climate hazardous risk, and subsequent actions on DRR enable local DRM capacity to reduce the increasing climate disaster risk. The study conducts household surveys with an original questionnaire in four communities in Cartago City, Costa Rica.

The main aim of this paper is to examine the claim that economic value added (EVA) advocates its superiority over the traditional accounting-based financial performance measures, i.e. profit after tax (PAT), earnings per share (EPS), return on assets (ROA), return on equity (ROE) and return on investment (ROI) in the Indian manufacturing sector and at the same time, give empirical facts. It also tests and examines the information content of various performance measures and their relationship with stock returns.

The paper uses the sample of 534 Indian manufacturing companies from the Bombay Stock Exchange (BSE) during the period 2000–2018. Multiple regression models are applied to examine the information content of EVA and traditional performance measures in explaining shareholders’ returns.

Relative information content tests revealed that traditional accounting-based measures such as EPS, ROE and ROA performed better than EVA in explaining the returns of Indian manufacturing companies. Incremental information content of EVA adds little contribution to information content above traditional performance measures. The claim of superiority of EVA over accounting-based measures in association with shareholder returns is proved invalid in Indian manufacturing companies.

This study concludes that EVA has no superiority over traditional accounting-based financial performance measures in explaining stock returns of Indian manufacturing companies. To achieve heftiness in outcomes, panel data are tested by using Breusch–Pagan–Godfrey (BPG) test for heteroskedasticity, Hausman’s test for fixed and random effect, variance inflation factor (VIF) test for multicollinearity and Durbin–Watson test for autocorrelation.

Develop a method for the optimal placement of sensors in order to detect the largest number of contaminant release scenarios with the minimum amount of sensors.

The method considers the general sensor placement problem. Assuming a given number of sensors, every release scenario leads to a sensor input. The data recorded from all the possible release scenarios at all possible sensor locations allow the identification of the best or optimal sensor locations. Clearly, if only one sensor is to be placed, it should be at the location that recorded the highest number of releases. This argument can be used recursively by removing from further consideration all releases already recorded by sensors previously placed.

The method developed works well. Examples showing the effect of different wind conditions and release locations demonstrate the effectiveness of the procedure.

The method can be used to design sensor systems for cities, subway stations, stadiums, concert halls, high value residential areas, etc.

The method is general, and can be used with other physics‐based models (puff, mass‐conservation, RANS, etc.). The investigation also shows that first‐principles CFD models have matured sufficiently to be run in a timely manner on PCs, opening the way to optimization based on detailed physics.

With heightened national attention placed on race and gender identity, the ability and preparedness of students to engage in critical conversations on such topics and with diverse groups is of much concern to educators. High school student-athletes are frequently thrust into the spotlight on topics related to race and racial identity, due to their hypervisibility and role as representatives of their schools. This chapter uses current events involving Black girl, high school, student-athletes to demonstrate how racialized and gendered experiences may shape how they understand themselves as well as their school and non-school environments. Further, this chapter includes a study that highlights the narratives of two Black female college athletes who, when prompted to discuss racialized and gendered experiences, shared stories that highlighted their primary and secondary educational experiences. These narratives identify school diversity and fitting in, and the coach as influencer as salient themes from the study. This illuminates the influence of early racialized encounters and the salience of those occurrences in shaping the way Black girls think about their own racial and gender identity development. In closing, this chapter calls on educators to prepare themselves to facilitate conversations about race through the use of equity audits, effective programming for Black girls, and a call for education advocates for Black girls in preK-12 environments.

Atherosclerosis tends to occur in the distinctive carotid sinus, leading to vascular stenosis and then causing death. The purpose of this paper is to investigate the effect of sinus sizes, positions and hematocrit on blood flow dynamics and heat transfer by different numerical approaches.

The fluid flow and heat transfer in the carotid artery with three different sinus sizes, three different sinus locations and four different hematocrits are studied by both computational fluid dynamics (CFD) and fluid-structure interaction (FSI) methods. An ideal geometric model and temperature-dependent non-Newtonian viscosity are adopted, while the wall heat flux concerning convection, radiation and evaporation is used.

With increasing sinus size, the average velocity and temperature of the blood fluid decrease, and the area of time average wall shear stress (TAWSS)with small values decreases. As the distances between sinuses and bifurcation points increase, the average temperature and the maximum TAWSS decrease. Atherosclerosis is more likely to develop when the sinuses are enlarged, when the sinuses are far from bifurcation points, or when the hematocrit is relatively large or small. The probability of thrombosis forming and developing becomes larger when the sinus becomes larger and the hematocrit is small enough. The movement of the arterial wall obviously reduces the velocity of blood flow, blood temperature and WSS. This study also suggests that the elastic role of arterial walls cannot be ignored.

The hemodynamics of the internal carotid artery sinus in a carotid artery with a bifurcation structure have been investigated thoroughly, on which the impacts of many factors have been considered, including the non-Newtonian behavior of blood and empirical boundary conditions. The results when the FSI is considered and absent are compared.