Participation of People in Participatory Forest Management in Jawi District, North West, Ethiopia

The study intended to coduct on determinant factors for participation in participatory forest management in Shimelegir Forest, Jawi district, Awi Administration Zone, Ethiopia from October, 2012 to February, 2014. By using stratified random sampling method, 151 households were selected to carry out a questionnaire survey with the aim to generate data on the socio-economic and physical conditions. Binary logistic regressions, STATA version 16, were used to analyze willingness of participation. From explanatory variables, land holding size (7%), livestock owned by respondents (1.7%), poverty (53%), understanding about the CBO (40%), education (27%) and gender (30%) were found to have a significant effect on participation and significant power to influence household decision on participation. Distance from market and distance from forest, HH size and age found to have insignificant effect on the decision of participation. Hence, different stackhoolder should conceder those factors specially; the researcher was come upwith as insignificant effect on peoples to decide participating in participatory forest management user group. Keywords: Participatory Forest Management, socioeconomic and biophysical factors and Shimelegir state fores

CoCoNet—boosting RNA contact prediction by convolutional neural networks

Co-evolutionary models such as direct coupling analysis (DCA) in combination with machine learning (ML) techniques based on deep neural networks are able to predict accurate protein contact or distance maps. Such information can be used as constraints in structure prediction and massively increase prediction accuracy. Unfortunately, the same ML methods cannot readily be applied to RNA as they rely on large structural datasets only available for proteins. Here, we demonstrate how the available smaller data for RNA can be used to improve prediction of RNA contact maps. We introduce an algorithm called CoCoNet that is based on a combination of a Coevolutionary model and a shallow Convolutional Neural Network. Despite its simplicity and the small number of trained parameters, the method boosts the positive predictive value (PPV) of predicted contacts by about 70% with respect to DCA as tested by cross-validation of about eighty RNA structures. However, the direct inclusion of the CoCoNet contacts in 3D modeling tools does not result in a proportional increase of the 3D RNA structure prediction accuracy. Therefore, we suggest that the field develops, in addition to contact PPV, metrics which estimate the expected impact for 3D structure modeling tools better. CoCoNet is freely available and can be found at https://github.com/KIT-MBS/coconet

Soil Drying Effects on Soil Strength and Depth of Hardpan Layers as Determined from Cone Index Data

Site-specific detection of a soil hardpan is an important step in precision farming. Different methods have been developed including the ASABE standard soil cone penetrometer to detect presence of hardpan layers. Most of the newly developed methods use results obtained by a soil cone penetrometer as a reference to validate their potential. Soil factors, mainly soil moisture and bulk density, may influence the cone index measurement and the prediction of the relative strength and depth of the hardpan layer. The effects of soil drying on hardpan characterizing attributes of peak cone index, depth to the peak cone index and depth to the top of the hardpan layer were studied for three compaction levels on a Norfolk sandy loam soil in a soil bin. The soil in the bin was wetted to near saturation and then subjected to four levels of soil drying. A multiple-probe soil cone penetrometer (MPSCP) was used to measure soil cone index. The results showed that soil drying had a significant effect on peak cone index for the single pass compaction (1.78 Mg m-3 within hardpan) and the double pass compaction (1.83 Mg m-3 within hardpan). The peak cone index increased two-fold and 1.3 times due to soil drying from ‘day-1’ to ‘day-4’ for the single pass compaction and for the double compaction, respectively. The depths to the top of the hardpan determined from the depth to the peak cone index and the depth to the top of the hardpan showed a statistically significant decreasing trend for the single pass compaction. The differences, however, were too small (< 2 cm) to justify varying prescription tillage depth due to soil drying

Phenolic composition and antioxidant activities of cladodes of the two varieties of cactus pear (Opuntia ficus-indica) grown in Ethiopia

In this study, young cladodes corresponding to two (thorn-less and thorn-containing) varieties of cactus pear (Opuntia ficus-indica) from four different areas of Tigray region, Ethiopia, were investigated for their phenolic contents and antioxidant activities. Quantitative estimation of total phenolic contents and antioxidant activities in the cladodes was carried out using spectrophotometric methods. A 1,1-diphenyl-2-picrylhydrazyl (DPPH) scavenging assay was used for the determination of the antioxidant activities, while Folin-Ciocalteau reagent, aluminum chloride and protein (albumin) precipitation methods were used for the determination of total polyphenol, flavonoid and tannin contents, respectively. The cladodes were found to be rich in polyphenols, with values in the range 18.0-71.4 mg gallic acid equivalent (GAE)/g of dry weight (DW). The predominant part of the polyphenols is represented by tannins, 9.00-41.2 mg GAE/g of DW, followed by flavonoids, 6.40-25.0 mg catchin equivalent (CE)/g of DW. The cladodes showed strong antioxidant activities, 59.3-85.8% inhibition compared to ascorbic acid. Application of paired t-test on the overall mean total polyphenol contents of samples collected from the different areas revealed the presence of significant variation between the thorn-less (31.6 GAE/g of DW) and thorn-containing (47.7 GAE/g of DW) varieties. One-way ANOVA also revealed that there are significant variations among samples from the same variety but collected from different areas

Preliminary Assessment of Low Cost Local Sorbent Materials for Water Defluoridation in Keren, Eritrea

Water in some parts of Eritrea has fluoride level above WHO guideline of 1.5 mg/L. One of the communities in Eritrea exposed to high fluoride in water is Keren community and as a result, they suffer dental and skeletal fluorosis. Fluoride sorbent local materials named crushed burnt clay pot, household ash, Keren and Adigerghish soil were studied in a batch defluoridation. The effect of amount of adsorbent, pH, contact time, particle size and fluoride concentration were examined

Future and potential spending on health 2015-40 : development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings We estimated that global spending on health will increase from US$9.21 trillion in 2014 to$24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and$195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.Peer reviewe

Future and potential spending on health 2015-40: Development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods: We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings: We estimated that global spending on health will increase from US$9.21 trillion in 2014 to$24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and$195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential

A randomized, comparative pilot trial of family-based interpersonal psychotherapy for reducing psychosocial symptoms, disordered-eating, and excess weight gain in at-risk preadolescents with loss-of-control-eating: SHOMAKER et al.

Preadolescent loss-of-control-eating (LOC-eating) is a risk factor for excess weight gain and binge-eating-disorder. We evaluated feasibility and acceptability of a preventive family-based interpersonal psychotherapy (FB-IPT) program. FB-IPT was compared to family-based health education (FB-HE) to evaluate changes in children’s psychosocial functioning, LOC-eating, and body mass