Creating a Poverty Map for Azerbaijan

"Poverty maps"-that is, graphic representations of spatially disaggregated estimates of welfare-are being increasingly used to geographically target scarce resources. But the development of detailed poverty maps in many low resource settings is hampered because of data constraints. Data on income or consumption are often unavailable and, where they are, direct survey estimates for small areas are likely to yield unacceptably large standard errors due to limited sample sizes. Census data offer the required level of coverage but do not generally contain the appropriate information. This has led to the development of a range of alternative methods aimed either at combining survey data with unit record data from the census to produce estimates of income or expenditure for small areas or at developing alternative welfare rankings, such as asset indices, using existing census data. This paper develops a set of poverty maps for Azerbaijan that can be used by different users. Two alternative approaches to the measurement and mapping of welfare are adopted. First, a map is derived using imputed household consumption. This involves combining information from the 2002 Household Budget Survey (HBS) with 1999 census data. Second, an alternative map is constructed using an asset index based on data from the 1999 census to produce estimates of welfare at the rayon level. This provides a unique opportunity to compare the welfare rankings obtained at the regional level under the two alternative approaches. In order to visually present the spatially disgaggregated estimates of welfare in Azerbaijan, this paper has also produced a digital census map of Azerbaijan. This involved matching the census enumeration areas to a digital settlement map of Azerbaijan. Therefore, it is now possible for the State Statistical Committee of Azerbaijan to display graphically the results of the 1999 census of Azerbaijan along with other data.Rural Poverty Reduction,Economic Theory&Research,Poverty Lines,Poverty Diagnostics,Technology Industry

High-Intensity Variable Stepping Training in Patients With Motor Incomplete Spinal Cord Injury: A Case Series

Background and Purpose: Previous data suggest that large amounts of high-intensity stepping training in variable contexts (tasks and environments) may improve locomotor function, aerobic capacity, and treadmill gait kinematics in individuals poststroke. Whether similar training strategies are tolerated and efficacious for patients with other acute-onset neurological diagnoses, such as motor incomplete spinal cord injury (iSCI), is unknown. Individuals with iSCI potentially have greater bilateral impairments. This case series evaluated the feasibility and preliminary short- and long-term efficacy of highintensity variable stepping practice in ambulatory participants for more than 1 year post-iSCI. Case Series Description: Four participants with iSCI (neurological levels C5-T3) completed up to 40 one-hour sessions over 3 to 4 months. Stepping training in variable contexts was performed at up to 85% maximum predicted heart rate, with feasibility measures of patient tolerance, total steps/session, and intensity of training. Clinical measures of locomotor function, balance, peak metabolic capacity, and gait kinematics during graded treadmill assessments were performed at baseline and posttraining, with more than 1-year follow-up. Outcomes: Participants completed 24 to 40 sessions over 8 to 15 weeks, averaging 2222 ± 653 steps per session, with primary adverse events of fatigue and muscle soreness. Modest improvements in locomotor capacity where observed at posttraining, with variable changes in lower extremity kinematics during treadmill walking. Discussion: High-intensity, variable stepping training was feasible and tolerated by participants with iSCI although only modest gains in gait function or quality were observed. The utility of this intervention in patients with more profound impairments may be limited

Earth observation and geospatial data can predict the relative distribution of village level poverty in the Sundarban Biosphere Reserve, India

There is increasing interest in leveraging Earth Observation (EO) and geospatial data to predict and map aspects of socioeconomic conditions to support survey and census activities. This is particularly relevant for the frequent monitoring required to assess progress towards the UNs' Sustainable Development Goals (SDGs). The Sundarban Biosphere Reserve (SBR) is a region of international ecological importance, containing the Indian portion of the world's largest mangrove forest. The region is densely populated and home to over 4.4 million people, many living in chronic poverty with a strong dependence on nature-based rural livelihoods. Such livelihoods are vulnerable to frequent natural hazards including cyclone landfall and storm surges. In this study we examine associations between environmental variables derived from EO and geospatial data with a village level multidimensional poverty metric using random forest machine learning, to provide evidence in support of policy formulation in the field of poverty reduction. We find that environmental variables can predict up to 78% of the relative distribution of the poorest villages within the SBR. Exposure to cyclone hazard was the most important variable for prediction of poverty. The poorest villages were associated with relatively small areas of rural settlement (&lt;∼30%), large areas of agricultural land (&gt;∼50%) and moderate to high cyclone hazard. The poorest villages were also associated with less productive agricultural land than the wealthiest. Analysis suggests villages with access to more diverse livelihood options, and a smaller dependence on agriculture may be more resilient to cyclone hazard. This study contributes to the understanding of poverty-environment dynamics within Low-and middle-income countries and the associations found can inform policy linked to socio-environmental scenarios within the SBR and potentially support monitoring of work towards SDG1 (No Poverty) across the region.</p

Mapping habitat indices across river networks using spatial statistical modelling of River Habitat Survey data

Freshwater ecosystems are declining faster than their terrestrial and marine counterparts because of physical pressures on habitats. European legislation requires member states to achieve ecological targets through the effective management of freshwater habitats. Maps of habitats across river networks would help diagnose environmental problems and plan for the delivery of improvement work. Existing habitat mapping methods are generally time consuming, require experts and are expensive to implement. Surveys based on sampling are cheaper but provide patchy representations of habitat distribution. In this study, we present a method for mapping habitat indices across networks using semi-quantitative data and a geostatistical technique called regression kriging. The method consists of the derivation of habitat indices using multivariate statistical techniques that are regressed on map-based covariates such as altitude, slope and geology. Regression kriging combines the Generalised Least Squares (GLS) regression technique with a spatial analysis of model residuals. Predictions from the GLS model are ‘corrected’ using weighted averages of model residuals following an analysis of spatial correlation. The method was applied to channel substrate data from the River Habitat Survey in Great Britain. A Channel Substrate Index (CSI) was derived using Correspondence Analysis and predicted using regression kriging. The model explained 74% of the main sample variability and 64% in a test sample. The model was applied to the English and Welsh river network and a map of CSI was produced. The proposed approach demonstrates how existing national monitoring data and geostatistical techniques can be used to produce continuous maps of habitat indices at the national scale

Small Water Bodies in Great Britain and Ireland: Ecosystem function, human-generated degradation, and options for restorative action

© 2018 Small, 1st and 2nd-order, headwater streams and ponds play essential roles in providing natural flood control, trapping sediments and contaminants, retaining nutrients, and maintaining biological diversity, which extend into downstream reaches, lakes and estuaries. However, the large geographic extent and high connectivity of these small water bodies with the surrounding terrestrial ecosystem makes them particularly vulnerable to growing land-use pressures and environmental change. The greatest pressure on the physical processes in these waters has been their extension and modification for agricultural and forestry drainage, resulting in highly modified discharge and temperature regimes that have implications for flood and drought control further downstream. The extensive length of the small stream network exposes rivers to a wide range of inputs, including nutrients, pesticides, heavy metals, sediment and emerging contaminants. Small water bodies have also been affected by invasions of non-native species, which along with the physical and chemical pressures, have affected most groups of organisms with consequent implications for the wider biodiversity within the catchment. Reducing the impacts and restoring the natural ecosystem function of these water bodies requires a three-tiered approach based on: restoration of channel hydromorphological dynamics; restoration and management of the riparian zone; and management of activities in the wider catchment that have both point-source and diffuse impacts. Such activities are expensive and so emphasis must be placed on integrated programmes that provide multiple benefits. Practical options need to be promoted through legislative regulation, financial incentives, markets for resource services and voluntary codes and actions

Delivering a childhood obesity prevention intervention using Islamic religious settings in the UK : What is most important to the stakeholders?

Ten per cent of the childhood population in the UK are of South Asian (SA) origin. Within this population, over 40% are living with overweight or obesity. The majority of SA children are Muslim and attend Islamic religious settings (IRS) daily after school. Because of their reach and influence, IRS may be an appropriate channel for obesity prevention initiatives. We conducted 20 in-depth interviews with parents of children attending IRS, 20 with Islamic leaders, and 3 focus group discussions with 26 managers and workers of IRS in Bradford and Birmingham. Topic guides were developed, interviews and focus group discussions were audio-recorded, transcribed, and analysed thematically. Muslim parents, Islamic leaders and IRS staff were supportive of the delivery of obesity prevention interventions for children using IRS. Participants identified important components of an intervention including: Prophet Muhammad (PBUH) as a role model for healthy lifestyle; healthy diet, physical activity, and organisational behaviour change within IRS. Participants suggested that Islamic narrative on healthy diet and physical fitness could increase delivery uptake. Staff showed willingness to conduct physical activity sessions for boys and girls. Barriers for the intervention delivery were poor funding systems and time constraints for staff. All participant groups thought that it would be possible to deliver a childhood obesity prevention intervention. Interventions should be co-designed, culturally and religiously sensitive and combine the scientific guidelines on healthy living with Islamic narrative on importance of healthy diet consumption and physical activity

Calibration of Traffic Simulation Models using SPSA

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Γεωπληροφορική

Endocannabinoids-related compounds in gastrointestinal diseases

The endocannabinoid system (ECS) is an endogenous signalling pathway involved in the control of several gastrointestinal (GI) functions at both peripheral and central levels. In recent years, it has become apparent that the ECS is pivotal in the regulation of GI motility, secretion and sensitivity, but endocannabinoids (ECs) are also involved in the regulation of intestinal inflammation and mucosal barrier permeability, suggesting their role in the pathophysiology of both functional and organic GI disorders. Genetic studies in patients with irritable bowel syndrome (IBS) or inflammatory bowel disease have indeed shown significant associations with polymorphisms or mutation in genes encoding for cannabinoid receptor or enzyme responsible for their catabolism, respectively. Furthermore, ongoing clinical trials are testing EC agonists/antagonists in the achievement of symptomatic relief from a number of GI symptoms. Despite this evidence, there is a lack of supportive RCTs and relevant data in human beings, and hence, the possible therapeutic application of these compounds is raising ethical, political and economic concerns. More recently, the identification of several EC-like compounds able to modulate ECS function without the typical central side effects of cannabino-mimetics has paved the way for emerging peripherally acting drugs. This review summarizes the possible mechanisms linking the ECS to GI disorders and describes the most recent advances in the manipulation of the ECS in the treatment of GI diseases