Infrared glucose portable device

There are quite a few persons worldwide with severe issues to control the glucose level on its blood. Only in Mexico, there are about 10 million persons with this disease and well over 13 deaths in 100 in this country are due to diabetes. In order to help to control this health issue, we are proposing a device to measure in a swift, simple and efficient way abnormality glucose levels in blood by using infrared sensors. Glucose shows a high absorbance to infrared wavelength. By using such characteristic, it is possible to develop a mobile, low-cost electronic device capable to analyse a blood sample by measuring the absorbance in it. The process is performed by using an array of infrared diodes controlled by a low-power consumption microcontroller as well as by several algorithms within a case. A blood sample is put in a substrate within the case. Once analysed, the glucose level of such sample is analysed and displayed on a scree

Diurnal timing of nonmigratory movement by birds: the importance of foraging spatial scales

Timing of activity can reveal an organism's efforts to optimize foraging either by minimizing energy loss through passive movement or by maximizing energetic gain through foraging. Here, we assess whether signals of either of these strategies are detectable in the timing of activity of daily, local movements by birds. We compare the similarities of timing of movement activity among species using six temporal variables: start of activity relative to sunrise, end of activity relative to sunset, relative speed at midday, number of movement bouts, bout duration and proportion of active daytime hours. We test for the influence of flight mode and foraging habitat on the timing of movement activity across avian guilds. We used 64 570 days of GPS movement data collected between 2002 and 2019 for local (non‐migratory) movements of 991 birds from 49 species, representing 14 orders. Dissimilarity among daily activity patterns was best explained by flight mode. Terrestrial soaring birds began activity later and stopped activity earlier than pelagic soaring or flapping birds. Broad‐scale foraging habitat explained less of the clustering patterns because of divergent timing of active periods of pelagic surface and diving foragers. Among pelagic birds, surface foragers were active throughout all 24 hrs of the day while diving foragers matched their active hours more closely to daylight hours. Pelagic surface foragers also had the greatest daily foraging distances, which was consistent with their daytime activity patterns. This study demonstrates that flight mode and foraging habitat influence temporal patterns of daily movement activity of birds.We thank the Nature Conservancy, the Bailey Wildlife Foundation, the Bluestone Foundation, the Ocean View Foundation, Biodiversity Research Institute, the Maine Outdoor Heritage Fund, the Davis Conservation Foundation and The U.S. Department of Energy (DE‐EE0005362), and the Darwin Initiative (19-026), EDP S.A. ‘Fundação para a Biodiversidade’ and the Portuguese Foundation for Science and Technology (FCT) (DL57/2019/CP 1440/CT 0021), Enterprise St Helena (ESH), Friends of National Zoo Conservation Research Grant Program and Conservation Nation, ConocoPhillips Global Signature Program, Maryland Department of Natural Resources, Cellular Tracking Technologies and Hawk Mountain Sanctuary for providing funding and in-kind support for the GPS data used in our analyses

Large birds travel farther in homogeneous environments

Aim: Animal movement is an important determinant of individual survival, population dynamics and ecosystem structure and function. Nonetheless, it is still unclear how local movements are related to resource availability and the spatial arrangement of resources. Using resident bird species and migratory bird species outside the migratory period, we examined how the distribution of resources affects the movement patterns of both large terrestrial birds (e.g., raptors, bustards and hornbills) and waterbirds (e.g., cranes, storks, ducks, geese and flamingos). Location: Global. Time period: 2003–2015. Major taxa studied: Birds. Methods: We compiled GPS tracking data for 386 individuals across 36 bird species. We calculated the straight‐line distance between GPS locations of each individual at the 1‐hr and 10‐day time‐scales. For each individual and time‐scale, we calculated the median and 0.95 quantile of displacement. We used linear mixed‐effects models to examine the effect of the spatial arrangement of resources, measured as enhanced vegetation index homogeneity, on avian movements, while accounting for mean resource availability, body mass, diet, flight type, migratory status and taxonomy and spatial autocorrelation. Results: We found a significant effect of resource spatial arrangement at the 1‐hr and 10‐day time‐scales. On average, individual movements were seven times longer in environments with homogeneously distributed resources compared with areas of low resource homogeneity. Contrary to previous work, we found no significant effect of resource availability, diet, flight type, migratory status or body mass on the non‐migratory movements of birds. Main conclusions: We suggest that longer movements in homogeneous environments might reflect the need for different habitat types associated with foraging and reproduction. This highlights the importance of landscape complementarity, where habitat patches within a landscape include a range of different, yet complementary resources. As habitat homogenization increases, it might force birds to travel increasingly longer distances to meet their diverse needs.National Trust for Scotland; Penguin Foundation; The U.S. Department of Energy, Grant/Award Number: DE-EE0005362; Australian Research Council; NASA's Arctic Boreal Vulnerability Experiment (ABoVE), Grant/Award Number: NNX15AV92A; Netherlands Organization for Scientific Research, Grant/Award Number: VIDI 864.10.006; BCC; NSF Award, Grant/Award Number: ABI-1458748; U.K. Department for Energy and Climate Change; ‘Juan de la Cierva ‐ Incorporación’ postdoctoral grant; Irish Research Council, Grant/Award Number: GOIPD/2015/81 ; DECC; Goethe International Postdoctoral Programme, People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007‐2013/ under REA grant agreement no [291776]; German Aerospace Center Award, Grant/Award Number: 50JR1601; Scottish Natural Heritage; Solway Coast AONB Sustainable Development Fund; COWRIE Ltd.; Heritage Lottery Fund; Robert Bosch Stiftung; NSF Division of Biological Infrastructure Award, Grant/Award Number: 1564380; Spanish Ministry of Economy and Competitiveness, Grant/Award Number: IJCI-2014-19190; Energinet.dk; NASA Award, Grant/Award Number: NNX15AV92A; MAVA Foundation; Fundação para a Ciência e Tecnologia, Grant/Award Number: SFRH/BPD/118635/2016; National Key R&D Program of China, Grant/Award Number: 2016YFC0500406; Green Fund of the Greek Ministry of Environmen

Baseline and endline socio-economic data from a randomised control trial of the Watershared intervention in the Bolivian Andes 2010-2016

Household level data - some variables were not collected in the end line (due to problems of comprehension, some questins were dropped from the end line and these are not included in the archived data). Some variables were processed when it made sense and reintroduced in the database. This sheet therefore contains all variables that were collected in both the baseline and the end line and additional variables which were added in the end line, and some calculated variables. The number of entries are different in the baseline (2623) and the end line (1751). This is because some households were only surveyed in the baseline and not in the end line, as they could not be contacted again (they may have moved away or were not available during the end line survey despite multiple visits). An additional 57 households not in the baseline are included in the endline. The collection also contains a table which links to the household survey via the unique indentifier ID_HOGAR and presents data on cases of diarrhea among children (Child_Diarrhea). Each entry of this table presents the information for each child under 16 years old belonging to each household. If the household (linked to the household table through ID_HOGAR) has no children one line is still added mentioning “0” under “Nb_of_children”. The sheet gives information about the number of times each child under 16 years old had diarrhoea in the last 12 months before both baseline and end line surveys. The third dataset provides information (from the end line only) on the management of a selected number of conservation contracts per household (Conservation_Contract). It is structured according to the conservation agreements (each entry corresponds to one agreement). Each household in the Household dataset (linked here through the unique identifier ID_HOGAR can have several contracts). This information was collected for all the household’s level 1 and level 2 contracts and was only collected on level 3 contracts if the household had less than 4 level 1 and 2 contracts. Baseline and endline data for control and treatment communities in an RCT evaluation of the Watershared scheme. The Rio Grande catchment in the eastern Bolivian Andes plays an important role by providing irrigation and drinking water services to villages, towns and cities downstream. However, deforestation and extensive cattle ranching due to unsustainable agricultural practices along the rivers adversely affect ecosystem services. In 2011, a Bolivian NGO, Fundación Natura Bolivia (known as Natura), launched a Payment for Watershed Services-like scheme aiming at connecting ecosystem service users (Municipal Government, Water Cooperatives and downstream villages) with services providers (upstream farmers and cattle-ranchers). Known as Watershared internationally and Acuerdos Reciprocos por Agua (Reciprocal Watershed Agreement) within Bolivia, the scheme is based on an in-kind contribution (beehives, fruit seedlings, irrigation tubing, barbed wire and other similar products) paid by downstream water-users (with additional support from Natura’s international donors) to upstream small holder farmers ranging from $1 to 10/year/hectare (with an additional joining incentive of$100). The aim is to support farmers reducing the impact of unsustainable agriculture practices on watershed ecosystems. The scheme emphasizes reciprocal relationships over market-based incentives. Because of Natura’s interest in how this novel scheme would work and its potential to deliver benefits, they took the highly unusual steps of setting the project up as a Randomised Control Trial (with support from the UK-government’s Ecosystem Services for Poverty Alleviation programme and technical input from Harvard University). Baseline studies were carried out before the implementation of the project in 2010 in 2623 households in 129 villages in the area. This included surveys on water quality, biodiversity and (most relevant to this data archive) a socio-economic survey. Data from the socio-economic survey was used to stratify communities into Control or Intervention and only households in the 65 intervention communities were offered the intervention when the scheme was rolled out in 2011. In 2015/2016 an endline survey was carried out, again with support from a grant from the Ecosystem Services for Poverty Alleviation programme. This time Bangor University also played a large role through a project funded by the Leverhulme Trust. The aim was to use the baseline survey, and the randomized trial to evaluate the impacts of the Watershared scheme on farmer livelihoods and environmental sustainability. The endline reached a total of 1694 of the initial baseline (plus 57 additional hosueholds). Research funders: The baseline data (2010) was collected under a grant from espa (Ecosystem Services for Poverty Alleviation) to Fundacion Natura Bolivia (PI Nigel Asquith) “What types of investment can most cost-effectively ensure ecosystem service provision? A randomized program evaluation” (NE/I00436X/1) The endline data (2015/2016) was collected with funding from two projects: an espa funded project to Fundacion Natura Bolivia (PI Nigel Asquith) “Under what conditions can Payments for Environmental Services deliver sustainable improvements in welfare? Learning from a Randomized Control Trial” (NE/L001470/1) and a Leverhulme Trust funded research project to Bangor University (PI Julia Jones) “Can payment for ecosystem services deliver environmental and livelihood benefits” (RPG-2014-056). </p

Baseline and endline socio-economic data from a Randomised Control Trial of the Watershared intervention in the Bolivian Andes

Household level data - some variables were not collected in the end line (due to problems of comprehension, some questins were dropped from the end line and these are not included in the archived data). Some variables were processed when it made sense and reintroduced in the database. This sheet therefore contains all variables that were collected in both the baseline and the end line and additional variables which were added in the end line, and some calculated variables. The number of entries are different in the baseline (2623) and the end line (1751). This is because some households were only surveyed in the baseline and not in the end line, as they could not be contacted again (they may have moved away or were not available during the end line survey despite multiple visits). An additional 57 households not in the baseline are included in the endline. The collection also contains a table which links to the household survey via the unique indentifier ID_HOGAR and presents data on cases of diarrhea among children (Child_Diarrhea). Each entry of this table presents the information for each child under 16 years old belonging to each household. If the household (linked to the household table through ID_HOGAR) has no children one line is still added mentioning “0” under “Nb_of_children”. The sheet gives information about the number of times each child under 16 years old had diarrhoea in the last 12 months before both baseline and end line surveys. The third dataset provides information (from the end line only) on the management of a selected number of conservation contracts per household (Conservation_Contract). It is structured according to the conservation agreements (each entry corresponds to one agreement). Each household in the Household dataset (linked here through the unique identifier ID_HOGAR can have several contracts). This information was collected for all the household’s level 1 and level 2 contracts and was only collected on level 3 contracts if the household had less than 4 level 1 and 2 contracts. Baseline and endline data for control and treatment communities in an RCT evaluation of the Watershared scheme. The Rio Grande catchment in the eastern Bolivian Andes plays an important role by providing irrigation and drinking water services to villages, towns and cities downstream. However, deforestation and extensive cattle ranching due to unsustainable agricultural practices along the rivers adversely affect ecosystem services. In 2011, a Bolivian NGO, Fundación Natura Bolivia (known as Natura), launched a Payment for Watershed Services-like scheme aiming at connecting ecosystem service users (Municipal Government, Water Cooperatives and downstream villages) with services providers (upstream farmers and cattle-ranchers). Known as Watershared internationally and Acuerdos Reciprocos por Agua (Reciprocal Watershed Agreement) within Bolivia, the scheme is based on an in-kind contribution (beehives, fruit seedlings, irrigation tubing, barbed wire and other similar products) paid by downstream water-users (with additional support from Natura’s international donors) to upstream small holder farmers ranging from $1 to 10/year/hectare (with an additional joining incentive of$100). The aim is to support farmers reducing the impact of unsustainable agriculture practices on watershed ecosystems. The scheme emphasizes reciprocal relationships over market-based incentives. Because of Natura’s interest in how this novel scheme would work and its potential to deliver benefits, they took the highly unusual steps of setting the project up as a Randomised Control Trial (with support from the UK-government’s Ecosystem Services for Poverty Alleviation programme and technical input from Harvard University). Baseline studies were carried out before the implementation of the project in 2010 in 2623 households in 129 villages in the area. This included surveys on water quality, biodiversity and (most relevant to this data archive) a socio-economic survey. Data from the socio-economic survey was used to stratify communities into Control or Intervention and only households in the 65 intervention communities were offered the intervention when the scheme was rolled out in 2011. In 2015/2016 an endline survey was carried out, again with support from a grant from the Ecosystem Services for Poverty Alleviation programme. This time Bangor University also played a large role through a project funded by the Leverhulme Trust. The aim was to use the baseline survey, and the randomized trial to evaluate the impacts of the Watershared scheme on farmer livelihoods and environmental sustainability. The endline reached a total of 1694 of the initial baseline (plus 57 additional hosueholds). Research funders: The baseline data (2010) was collected under a grant from espa (Ecosystem Services for Poverty Alleviation) to Fundacion Natura Bolivia (PI Nigel Asquith) “What types of investment can most cost-effectively ensure ecosystem service provision? A randomized program evaluation” (NE/I00436X/1) The endline data (2015/2016) was collected with funding from two projects: an espa funded project to Fundacion Natura Bolivia (PI Nigel Asquith) “Under what conditions can Payments for Environmental Services deliver sustainable improvements in welfare? Learning from a Randomized Control Trial” (NE/L001470/1) and a Leverhulme Trust funded research project to Bangor University (PI Julia Jones) “Can payment for ecosystem services deliver environmental and livelihood benefits” (RPG-2014-056). </p