392 research outputs found
Исследование информационных процессов в некоторых повторяющихся играх
Рассматривается неантагонистическая повторяющаяся игра с непрерывным временем. Один раз за всю игру может подействовать возмущающий фактор. Он изменяет существующую ситуацию равновесия на другую. При этом выигрыш второго игрока уменьшается. Найдены равновесные стратегии и оптимальный дискретный режим получения информации. Показано, что наблюдатель оценивает режим получения информации как оптимальный или избыточный в зависимости от модели реальности, которой он пользуется.The non-antagonistic repeated game are considered. The disturbance is able to act once the game. It changes the existing situation of equilibrium for another one. For this the second player gain decreases. The equilibrium strategies and the optimum discrete regime of the information receipt are found. It is shown that observer estimates the regime of the information receipt as the optimum or surplus regime depending on the model of reality which is used by him
Assessment of strip tillage systems for maize production in semi-arid Ethiopia: effects on grain yield and water balance
International audienceThe traditional tillage implement, the Maresha plow, and the tillage systems that require repeated and cross plowing have caused poor rainfall partitioning, land degradation and hence low water productivity in Ethiopia. Conservation tillage could alleviate these problems. However, no-till can not be feasible for smallholder farmers in semi-arid regions of Ethiopia because of difficulties in maintaining soil cover due to low rainfall and communal grazing and because of high costs of herbicides. Strip tillage systems may offer a solution. This study was initiated to test strip tillage systems using implements that were modified forms of the Maresha plow, and to evaluate the impacts of the new tillage systems on water balance and grain yields of maize (Zea mays XX). Experiments were conducted in two dry semi arid areas called Melkawoba and Wulinchity, in the central Rift Valley of Ethiopia during 2003?2005. Strip tillage systems that involved cultivating planting lines at a spacing of 0.75 m using the Maresha plow followed by subsoiling along the same lines (STS) and without subsoiling (ST) were compared with the traditional tillage system of 3 to 4 times plowing with the Maresha plow (CONV). Soil moisture was monitored to a depth of 1.8 m using Time Domain Reflectometer while surface runoff was measured using rectangular trough installed at the bottom of each plot. STS resulted in the least surface runoff (Qs=17 mm-season?1), the highest transpiration (T=196 mm-season?1), the highest grain yields (Y=2130 kg-ha?1) and the highest water productivity using total evaporation (WPET=0.67 kg-m?3) followed by ST (Qs=25 mm-season?1, T=178 mm-season?1, Y=1840 kg-ha?1, WPET=0.60 kg-m?3) and CONV (Qs=40 mm-season?1,T=158 mm-season?1, Y=1720 kg-ha?1, WPET=0.58 kg-m?3). However, when the time between the last tillage operation and planting of maize was more than 26 days, the reverse occurred. There was no statistically significant change in soil physical and chemical properties after three years of experimenting with different tillage systems
Nearly one in every six HIV-infected children lost from ART follow-up at Debre Markos Referral Hospital, Northwest Ethiopia: A 14-year retrospective follow-up study.
BackgroundAlthough antiretroviral therapy (ART) significantly improves the survival status and quality of life among human immunodeficiency virus (HIV)-infected children, loss to follow-up (LTFU) from HIV-care profoundly affecting the treatment outcomes of this vulnerable population. For better interventions, up-to-date information concerning LTFU among HIV-infected children on ART is vital. However, only a few studies have been conducted in Ethiopia to address this concern. Thus, this study aims to identify the predictors of LTFU among HIV-infected children receiving ART at Debre Markos Referral Hospital.MethodsAn institution-based retrospective follow-up study was done among 408 HIV-infected children receiving ART at Debre Markos Referral Hospital between 2005 and March 15, 2019. Data were abstracted from the medical records of HIV-infected children using a standardized data abstracted checklist. We used Epi-Data Version 3.1 for data entry and Stata Version 14 for statistical analysis. The Kaplan-Meier survival curve was used to estimate the survival time. A generalized log-rank test was used to compare the survival curves of different categorical variables. Finally, both bi-variable and multivariable Cox proportional hazard regression models were used to identify the predictors of LTFU.ResultsOf 408 HIV-infected children included in the final analysis, 70 (17.1%) children were LTFU at the end of the study. The overall incidence rate of LTFU among HIV-infected children was found to be 4.5 (95%CI: 3.5-5.7) per 100-child years of observation. HIV-infected children living in rural areas (AHR: 3.2, 95%CI: 2.0-5.3), having fair or poor ART drug adherence (AHR: 2.3, 95%CI: 1.4-3.7), children started ART through test and treat approach (AHR: 2.7, 95%CI: 1.4-5.5), and children started protease inhibiter (PI)-based ART regimens (AHR: 2.2, 95%CI: 1.1-4.4) were at higher risk of LTFU.ConclusionThis study found that one in every six HIV-infected children lost form ART follow-up. HIV-infected children living in rural areas, having fair or poor ART drug adherence, started ART based on test and treat approach, and taking PI-based ART regimens were at higher risk of LTFU
Incidence of common opportunistic infections among HIV-infected children on ART at Debre Markos referral hospital, Northwest Ethiopia: a retrospective cohort study.
BACKGROUND:Opportunistic infections (OIs) are the leading cause of morbidity and mortality among children living with human immunodeficiency virus (HIV). For better treatments and interventions, current and up-to-date information concerning occurrence of opportunistic infections in HIV-infected children is crucial. However, studies regarding the incidence of common opportunistic infections in HIV-infected children in Ethiopia are very limited. Hence, this study aimed to determine the incidence of opportunistic infections among HIV-infected children on antiretroviral therapy (ART) at Debre Markos Referral Hospital. METHODS:A facility-based retrospective cohort study was undertaken at Debre Markos Referral Hospital for the period of January 1, 2005 to March 31, 2019. A total of 408 HIV-infected children receiving ART were included. Data from HIV-infected children charts were extracted using a data extraction form adapted from ART entry and follow-up forms. Data were entered using Epi-data™ Version 3.1 and analyzed using Stata™ Version 14. The Kaplan Meier survival curve was used to estimate the opportunistic infections free survival time. Both bi-variable and multivariable Cox proportional hazard models were fitted to identify the predictors of opportunistic infections. RESULTS:This study included the records of 408 HIV-infected children-initiated ART between the periods of January 1, 2005 to March 31, 2019. The overall incidence rate of opportunistic infections during the follow-up time was 9.7 (95% CI: 8.13, 11.48) per 100 child-years of observation. Tuberculosis at 29.8% was the most commonly encountered OI at follow-up. Children presenting with advanced disease stage (III and IV) (AHR: 1.8, 95% CI: 1.2, 2.7), having "fair" or "poor" ART adherence (AHR: 2.6, 95% CI: 1.8, 3.8), not taking OI prophylaxis (AHR:1.6, 95% CI: 1.1, 2.4), and CD4 count or % below the threshold (AHR:1.7, 95% CI: 1.1, 2.6) were at a higher risk of developing opportunistic infections. CONCLUSIONS:In this study, the incidence rate of opportunistic infections among HIV-infected children remained high. Concerning predictors, such as advanced disease stage (III and IV), CD4 count or % below the threshold, "fair" or "poor" ART adherence, and not taking past OI prophylaxis were found to be significantly associated with OIs
Assessment of Improved Tef (Eragrostis tef L.) Varieties for Yield and Yield Related Traits at Nono Benja and Cheliya Districts, Oromia, Ethiopia
Tef (Eragrostis tef) is one of the most important and strategic cereal crop grown to drought prone areas of Ethiopia. Genetic variability, genotypic correlations and yield components are prerequisite for selection of crop breeding, cultivation of improved varieties that provides optimum seed yield is one of the major constraints of the crop. The present study was aimed to investigate the adaptive and best performing tef varieties based on their yield and related traits under rain fed conditions at Nono Benja and Celia districts in Ethiopia. The experiment was conducted by using split plot design with three replications, sixteen improved varieties and one local landrace. The combined analysis of variance revealed that varieties were significantly different for studied characters except panicle length, total tiller number and spikelet length. The mean yields of nine improved varieties (Dukem, Asgori, Tesfa, Negus, Quncho, Kora, Koye, Boset and key tena) were relatively higher than the local check comparing with mean values of grain yield ranged from Welkomi (372.08 kg/ ha) to Dukem (1315.41 kg/ ha).Grain yields were studied high in four varieties across two locations were (Dukem (1315.4 kg/ ha), asgori (1279.6 kg/ ha), Tesfa (1206.02 kg/ ha), Negus (1072.61 kg/ ha) with 72.8%, 68.2%, 58.5 %, and 41% over local check. The genotypic coefficient variation was observed that from 4.6% to 82.9% for loading index and the phenotypic coefficient variation range from 5.8% to 91.0% for loading index at Cheliya, respectively, the fertilizer application (0, 60/40 P/N kgha-1) showed highly differences among all traits except in GFP, PH and TGW traits. The varieties Gibe, Koye, Boset, Gimbichu, Enat and Kora were observed highly strong association with the environment, similarly Asgori and Gedo varieties were showed highly significant and strong connection with the environment Nono Benja with fertilization. Results reveal that the correlation studies provide a better understanding of yield components during the selection of tef genotypes
Assessment of Improved Tef (Eragrostis tef L.) Varieties for Yield and Yield Related Traits at Nono Benja and Cheliya Districts, Oromia, Ethiopia
Tef (Eragrostis tef) is one of the most important and strategic cereal crop grown to drought prone areas of Ethiopia. Genetic variability, genotypic correlations and yield components are prerequisite for selection of crop breeding, cultivation of improved varieties that provides optimum seed yield is one of the major constraints of the crop. The present study was aimed to investigate the adaptive and best performing tef varieties based on their yield and related traits under rain fed conditions at Nono Benja and Celia districts in Ethiopia. The experiment was conducted by using split plot design with three replications, sixteen improved varieties and one local landrace. The combined analysis of variance revealed that varieties were significantly different for studied characters except panicle length, total tiller number and spikelet length. The mean yields of nine improved varieties (Dukem, Asgori, Tesfa, Negus, Quncho, Kora, Koye, Boset and key tena) were relatively higher than the local check comparing with mean values of grain yield ranged from Welkomi (372.08 kg/ ha) to Dukem (1315.41 kg/ ha).Grain yields were studied high in four varieties across two locations were (Dukem (1315.4 kg/ ha), asgori (1279.6 kg/ ha), Tesfa (1206.02 kg/ ha), Negus (1072.61 kg/ ha) with 72.8%, 68.2%, 58.5 %, and 41% over local check. The genotypic coefficient variation was observed that from 4.6% to 82.9% for loading index and the phenotypic coefficient variation range from 5.8% to 91.0% for loading index at Cheliya, respectively, the fertilizer application (0, 60/40 P/N kgha-1) showed highly differences among all traits except in GFP, PH and TGW traits. The varieties Gibe, Koye, Boset, Gimbichu, Enat and Kora were observed highly strong association with the environment, similarly Asgori and Gedo varieties were showed highly significant and strong connection with the environment Nono Benja with fertilization. Results reveal that the correlation studies provide a better understanding of yield components during the selection of tef genotypes
Recommended from our members
A comparison of selected parametric and imputation methods for estimating snag density and snag quality attributes
Snags (standing dead trees) are an essential structural component of forests. Because wildlife use of snags depends on size and decay stage, snag density estimation without any information about snag quality attributes is of little value for wildlife management decision makers. Little work has been done to develop models that allow multivariate estimation of snag density by snag quality class. Using climate, topography, Landsat TM data, stand age and forest type collected for 2356 forested Forest Inventory and Analysis plots in western Washington and western Oregon, we evaluated two multivariate techniques for their abilities to estimate density of snags by three decay classes. The density of live trees and snags in three decay classes (D1: recently dead, little decay; D2: decay, without top, some branches and bark missing; D3: extensive decay, missing bark and most branches) with diameter at breast height (DBH)P12.7 cm was estimated using a nonparametric random forest nearest neighbor imputation technique (RF) and a parametric two-stage model (QPORD), for which the number of trees per hectare was estimated with a Quasipoisson model in the first stage and the probability of belonging to a tree status class (live, D1, D2, D3) was estimated with an ordinal regression model in the second stage. The presence of large snags with DBHP50 cm was predicted using a logistic regression and RF imputation. Because of the more homogenous conditions on private forest lands, snag density by decay class was predicted with higher accuracies on private forest lands than on public lands, while presence of large snags was more accurately predicted on public lands, owing to the higher prevalence of large snags on public lands. RF outperformed the QPORD model in terms of percent accurate predictions, while QPORD provided smaller root mean square errors in predicting snag density by decay class. The logistic regression model achieved more accurate presence/absence classification of large snags than the RF imputation approach. Adjusting the decision threshold to account for unequal size for presence and absence classes is more straightforward for the logistic regression than for the RF imputation approach. Overall, model accuracies were poor in this study, which can be attributed to the poor predictive quality of the explanatory variables and the large range of forest types and geographic conditions observed in the data.Elsevier - Education Use Statement:
This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.
This is the publisher’s final pdf. The published article is copyrighted by Elsevier and can be found at: http://www.elsevier.com/Keywords: Snag size class, Nearest neighbor imputation, Snag decay class, Ordinal regression, Snag densityKeywords: Snag size class, Nearest neighbor imputation, Snag decay class, Ordinal regression, Snag densit
Recommended from our members
A comparison of selected parametric and imputation methods for estimating snag density and snag quality attributes
Snags (standing dead trees) are an essential structural component of forests. Because wildlife use of snags depends on size and decay stage, snag density estimation without any information about snag quality attributes is of little value for wildlife management decision makers. Little work has been done to develop models that allow multivariate estimation of snag density by snag quality class. Using climate, topography, Landsat TM data, stand age and forest type collected for 2356 forested Forest Inventory and Analysis plots in western Washington and western Oregon, we evaluated two multivariate techniques for their abilities to estimate density of snags by three decay classes. The density of live trees and snags in three decay classes (D1: recently dead, little decay; D2: decay, without top, some branches and bark missing; D3: extensive decay, missing bark and most branches) with diameter at breast height (DBH) ≥ 12.7 cm was estimated using a nonparametric random forest nearest neighbor imputation technique (RF) and a parametric two-stage model (QPORD), for which the number of trees per hectare was estimated with a Quasipoisson model in the first stage and the probability of belonging to a tree status class (live, D1, D2, D3) was estimated with an ordinal regression model in the second stage. The presence of large snags with DBH ≥ 50 cm was predicted using a logistic regression and RF imputation. Because of the more homogenous conditions on private forest lands, snag density by decay class was predicted with higher accuracies on private forest lands than on public lands, while presence of large snags was more accurately predicted on public lands, owing to the higher prevalence of large snags on public lands. RF outperformed the QPORD model in terms of percent accurate predictions, while QPORD provided smaller root mean square errors in predicting snag density by decay class. The logistic regression model achieved more accurate presence/absence classification of large snags than the RF imputation approach. Adjusting the decision threshold to account for unequal size for presence and absence classes is more straightforward for the logistic regression than for the RF imputation approach. Overall, model accuracies were poor in this study, which can be attributed to the poor predictive quality of the explanatory variables and the large range of forest types and geographic conditions observed in the data.This is the publisher’s final pdf. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/forest-ecology-and-managemen
Recommended from our members
A comparison of selected parametric and imputation methods for estimating snag density and snag quality attributes
Snags (standing dead trees) are an essential structural component of forests. Because wildlife use of snags depends on size and decay stage, snag density estimation without any information about snag quality attributes is of little value for wildlife management decision makers. Little work has been done to develop models that allow multivariate estimation of snag density by snag quality class. Using climate, topography, Landsat TM data, stand age and forest type collected for 2356 forested Forest Inventory and Analysis plots in western Washington and western Oregon, we evaluated two multivariate techniques for their abilities to estimate density of snags by three decay classes. The density of live trees and snags in three decay classes (D1: recently dead, little decay; D2: decay, without top, some branches and bark missing; D3: extensive decay, missing bark and most branches) with diameter at breast height (DBH) ≥ 12.7 cm was estimated using a nonparametric random forest nearest neighbor imputation technique (RF) and a parametric two-stage model (QPORD), for which the number of trees per hectare was estimated with a Quasipoisson model in the first stage and the probability of belonging to a tree status class (live, D1, D2, D3) was estimated with an ordinal regression model in the second stage. The presence of large snags with DBH ≥ 50 cm was predicted using a logistic regression and RF imputation. Because of the more homogenous conditions on private forest lands, snag density by decay class was predicted with higher accuracies on private forest lands than on public lands, while presence of large snags was more accurately predicted on public lands, owing to the higher prevalence of large snags on public lands. RF outperformed the QPORD model in terms of percent accurate predictions, while QPORD provided smaller root mean square errors in predicting snag density by decay class. The logistic regression model achieved more accurate presence/absence classification of large snags than the RF imputation approach. Adjusting the decision threshold to account for unequal size for presence and absence classes is more straightforward for the logistic regression than for the RF imputation approach. Overall, model accuracies were poor in this study, which can be attributed to the poor predictive quality of the explanatory variables and the large range of forest types and geographic conditions observed in the data.Keywords: Snag size class, Ordinal regression, Snag density, Snag decay class, Nearest neighbor imputatio
- …