A Mobile Money Solution for Illiterate Users

Existing mobile money platforms have text based interfaces and target literate people. Illiterate people, without the assistance of literate individuals, cannot use such platforms. Applying user-centered requirements gathered in an Ethiopian context, this paper presents the design and development of a mobile money solution that targets illiterate people. Particular emphasis is given to how illiterate users deal with cash money in their everyday life and how such practices can be mapped into financial technology design. Given the ubiquity of mobile telephony in Africa, our solution is based on the widely available, relatively inexpensive and open source Android mobile web platform. The proposed system enables illiterate individuals to count money bills, while providing the facility to accept and make payments. In so doing, we provide an example of how a pervasive technology such as smartphones can empower a hitherto often neglected user category of illiterate users

Evaluating usability of cross-platform smartphone applications

The computing power of smartphones is increasing as time goes. However, the proliferation of multiple different types of operating platforms affected interoperable smartphone applications development. Thus, the cross-platform development tools are coined. Literature showed that smartphone applications developed with the native platforms have better user experience than the cross-platform counterparts. However, comparative evaluation of usability of cross-platform applications on the deployment platforms is not studied yet. In this work, we evaluated usability of a crossword puzzle developed with PhoneGap on Android, Windows Phone, and BlackBerry. The evaluation was conducted focusing on the developer's adaptation effort to native platforms and the end users. Thus, we observed that usability of the cross-platform crossword puzzle is unaffected on the respective native platforms and the SDKs require only minimal configuration effort. In addition, we observed the prospect of HTML5 and related web technologies as our future work towards evaluating and enhancing usability in composing REST-based services for smartphone applications

The water footprint assessment manual: setting the global standard

This book contains the global standard for \u27water footprint assessment\u27 as developed and maintained by the Water Footprint Network (WFN). It covers a comprehensive set of definitions and methods for water footprint accounting. It shows how water footprints are calculated for individual processes and products, as well as for consumers, nations and businesses. It also includes methods for water footprint sustainability assessment and a library of water footprint response options. A shared standard on definitions and calculation methods is crucial given the rapidly growing interest in companies and governments to use water footprint accounts as a basis for formulating sustainable water strategies and policies

Incidence and Predictors of Tuberculosis Among Adult PLWHA at Public Health Facilities of Hawassa City

Tuberculosis (TB) is the most frequently diagnosed opportunistic infection (OI) and disease in people living with HIV/AIDS (PLWHA), world-wide. This study aimed at determining the incidence and predictors of tuberculosis among people living with HIV.A Six year retrospective follow up study was conducted among adult PLHIV. The Cox proportional hazards model was used to identify predictors.A total of 554 patients were followed and produced 1830.3 person year of observation. One hundred sixty one new TB cases occurred during the follow up period. The overall incidence density of TB was 8.79 per 100 person-year (PY). It was high (148.71/100 PY) in the first year of enrolment. The cumulative proportion of TB free survival was 79% and 67% at the end of first and sixth years, respectively. Not having formal education(AHR=2.68, 95%CI: 1.41, 5.11 ), base line WHO clinical stage IV (AHR = 3.22, 95% CI=1.91-5.41), CD4 count <50 cell/ul (AHR=2.41, 95%CI=1.31, 4.42), Being bed redden (AHR= 2.89, 95%CI=1.72, 3.78), past TB history (AHR=1.65, 95% CI = 1.06,2.39), substance use (AHR=1.46, 95% CI=1.03,2.06) and being on pre ART (AHR=1.62, 95%CI:1.03-2.54 ) were independently predicted tuberculosis occurrence. Advanced WHO clinical stage, limited functional status, past TB history, addiction and low CD4 (<50cell/ul) count at enrollment were found to be the independent predictor of tuberculosis occurrence. Therefore early initiation of treatment and intensive follow up is important

Global gray water footprint and water pollution levels related to anthropogenic nitrogen loads to fresh water

This is the first global assessment of nitrogen-related water pollution in river basins with a specification of the pollution by economic sector, and by crop for the agricultural sector. At a spatial resolution of 5 by 5 arc minute, we estimate anthropogenic nitrogen (N) loads to freshwater, calculate the resultant gray water footprints (GWFs), and relate the GWFs per river basin to runoff to calculate the N-related water pollution level (WPL) per catchment. The accumulated global GWF related to anthropogenic N loads in the period 2002–2010 was 13 × 1012 m3/y. China contributed about 45% to the global total. Three quarters of the GWF related to N loads came from diffuse sources (agriculture), 23% from domestic point sources and 2% from industrial point sources. Among the crops, production of cereals had the largest contribution to the N-related GWF (18%), followed by vegetables (15%) and oil crops (11%). The river basins with WPL > 1 (where the N load exceeds the basin’s assimilation capacity), cover about 17% of the global land area, contribute about 9% of the global river discharge, and provide residence to 48% of the global population

The green, blue and grey water footprint of farm animals and animal products. Volume 1: Main Report

The projected increase in the production and consumption of animal products is likely to put further pressure on the globe’s freshwater resources. The size and characteristics of the water footprint vary across animal types and production systems. The current study provides a comprehensive account of the global green, blue and grey water footprints of different sorts of farm animals and animal products, distinguishing between different production systems and considering the conditions in all countries of the world separately. The following animal categories were considered: beef cattle, dairy cattle, pig, sheep, goat, broiler chicken, layer chicken and horses. The study shows that the water footprint of meat from beef cattle (15400 m3/ton as a global average) is much larger than the footprints of meat from sheep (10400 m3/ton), pig (6000 m3/ton), goat (5500 m3/ton) or chicken (4300 m3/ton). The global average water footprint of chicken egg is 3300 m3/ton, while the water footprint of cow milk amounts to 1000 m3/ton. Per ton of product, animal products generally have a larger water footprint than crop products. The same is true when we look at the water footprint per calorie. The average water footprint per calorie for beef is twenty times larger than for cereals and starchy roots. When we look at the water requirements for protein, we find that the water footprint per gram of protein for milk, eggs and chicken meat is about 1.5 times larger than for pulses. For beef, the water footprint per gram of protein is 6 times larger than for pulses. In the case of fat, we find that butter has a relatively small water footprint per gram of fat, even lower than for oil crops. All other animal products, however, have larger water footprints per gram of fat when compared to oil crops. The study shows that from a freshwater resource perspective, it is more efficient to obtain calories, protein and fat through crop products than animal products. Global animal production requires about 2422 Gm3 of water per year (87.2% green, 6.2% blue, 6.6% grey water). One third of this volume is for the beef cattle sector; another 19% for the dairy cattle sector. Most of the total volume of water (98%) refers to the water footprint of the feed for the animals. Drinking water for the animals, service water and feed mixing water account only for 1.1%, 0.8% and 0.03%, respectively. The water footprints of animal products can be understood from three main factors: feed conversion efficiency of the animal, feed composition, and origin of the feed. The type of production system (grazing, mixed, industrial) is important because it influences all three factors. A first explanatory factor in the water footprints of animal products is the feed conversion efficiency. The more feed is required per unit of animal product, the more water is necessary (to produce the feed). The unfavourable feed conversion efficiency for beef cattle is largely responsible for the relatively large water footprint of beef. Sheep and goats have an unfavourable feed conversion efficiency as well, although better than cattle. A second factor is the feed composition, in particular the ratio of concentrates versus roughages and the percentage of valuable crop components versus crop residues in the concentrate. Chicken and pig have relatively large fractions of cereals and oil meal in their feed, which results in relatively large water footprints of their feed and abolishes the effect of the favourable feed conversion efficiencies. A third factor that influences the water footprint of an animal product is the origin of the feed. The water footprint of a specific animal product varies across countries due to differences in climate and agricultural practice in the regions from where the various feed components are obtained. Since sometimes a relatively large fraction of the feed is imported while at other times feed is mostly obtained locally, not only the size but also the spatial dimension of the water footprint depends on the sourcing of the feed

National water footprint accounts: The green, blue and grey water footprint of production and consumption. Volume 1: Main Report

This study quantifies and maps the water footprints of nations from both a production and consumption perspective and estimates international virtual water flows and national and global water savings as a result of trade. The entire estimate includes a breakdown of water footprints, virtual water flows and water savings into their green, blue and grey components. The main finding of the study can be summarized as: The global water footprint in the period 1996-2005 was 9087 Gm3/yr (74% green, 11% blue, 15% grey). Agricultural production contributes 92% to this total footprint. About one fifth of the global water footprint relates to production for export. The total volume of international virtual water flows related to trade in agricultural and industrial products was 2320 Gm3/yr (68% green, 13% blue, 19% grey). Trade in crop products contributes 76% to the total volume of international virtual water flows; trade in animal and industrial products contribute 12% each. As a global average, the blue and grey shares in the total water footprint of internationally traded products are slightly larger than in the case of domestically consumed products. Mexico and Spain are the two countries with the largest national blue water savings as a result of trade. The global water saving as a result of trade in agricultural products in the period 1996-2005 was 369 Gm3/yr (59% green, 27% blue, 15% grey), which is equivalent to 4% of the global water footprint related to agricultural production. The global blue water saving is equivalent to 10% of the global blue water footprint related to agricultural production, which indicates that virtual water importing countries generally depend more strongly on blue water for crop production than the virtual water exporting countries. The largest global water saving (53%) is due to trade in cereal crops, followed by oil crops (22%) and animal products (15%). International trade in industrial products can be associated with an increased global water footprint that is equivalent to 4% of the global water footprint related to industrial production. The water footprint of the global average consumer in the period 1996-2005 was 1385 m3/yr. About 92% of the water footprint is related to the consumption of agricultural products, 5% to the consumption of industrial goods, and 4% to domestic water use. The average consumer in the US has a water footprint of 2842 m3/yr, while the average citizens in China and India have water footprints of 1071 m3/yr and 1089 m3/yr respectively. Consumption of cereal products gives the largest contribution to the water footprint of the average consumer (27%), followed by meat (22%) and milk products (7%). The contribution of different consumption categories to the total water footprint varies across countries. The volume and pattern of consumption and the water footprint per ton of product of the products consumed are the main factors determining the water footprint of a consumer. The study illustrates the global dimension of water consumption and pollution by showing that several countries heavily rely on water resources elsewhere (for example Mexico depending on virtual water imports from the US) and that many countries have significant impacts on water consumption and pollution elsewhere (for example Japan and many European countries due to their large external water footprints)

The green, blue and grey water footprint of farm animals and animal products. Volume 2: Appendices

Contents Appendix I: Feed conversion efficiencies – in kg of feed (dry mass) per kg of output – per animal category and region Appendix II: Estimated consumption of feed per animal category and world region (103 ton dry mass/yr) Appendix III. Estimated consumption of feed per production system and world region (103 ton dry mass/yr) Appendix IV. Drinking and service water footprint per animal Appendix V. Water footprint of animals and animal products (m3/ton). Period 1996-200

Global Anthropogenic Phosphorus Loads to Freshwater and Associated Grey Water Footprints and Water Pollution Levels:A High-Resolution Global Study

We estimate the global anthropogenic phosphorus (P) loads to freshwater and the associated grey water footprints (GWFs) for the period 2002–2010, at a spatial resolution of 5 × 5 arc min, and compare the GWF per river basin to runoff to assess the P-related water pollution level (WPL). The global anthropogenic P load to freshwater systems from both diffuse and point sources is estimated at 1.5 Tg/yr. More than half of this total load was in Asia, followed by Europe (19%) and Latin America and the Caribbean (13%). The domestic sector contributed 54% to the total, agriculture 38%, and industry 8%. In agriculture, cereals production had the largest contribution to the P load (31%), followed by fruits, vegetables, and oil crops, each contributing 15%. The global total GWF related to anthropogenic P loads is estimated to be 147 × 10 12 m 3/yr, with China contributing 30%, India 8%, USA 7%, and Spain and Brazil 6% each. The basins with WPL &gt; 1 (where GWF exceeds the basin's assimilation capacity) together cover about 38% of the global land area, 37% of the global river discharge, and provide residence to about 90% of the global population. </p