Penalized EM algorithm and copula skeptic graphical models for inferring networks for mixed variables

In this article, we consider the problem of reconstructing networks for continuous, binary, count and discrete ordinal variables by estimating sparse precision matrix in Gaussian copula graphical models. We propose two approaches: $\ell_1$ penalized extended rank likelihood with Monte Carlo Expectation-Maximization algorithm (copula EM glasso) and copula skeptic with pair-wise copula estimation for copula Gaussian graphical models. The proposed approaches help to infer networks arising from nonnormal and mixed variables. We demonstrate the performance of our methods through simulation studies and analysis of breast cancer genomic and clinical data and maize genetics data

Effect of Deficit Irrigation Levels at Different Growth Stages on Yield and Water Productivity of Onion (Allium cepa L.) at Raya Azebo Woreda, Northern Ethiopia

አህፅሮት በደረቅና ከፊል በረሃማ አካባቢዎች ለግብርና ዕድገት ከፍተኛ ማነቆ የሆነው የውኃ እጥረት ነው፡፡ በእንደዚህ ያሉ ሁኔታዎች ውስጥ የሚገኘውን ውኃ ኢኮኖሚያው እና ውጤታማ በሆነ መንገድ የመጠቀም አስፈላጊነት የማይካድ ነው፡፡  በእነዚህ ውኃ አጠር አካባቢዎች፤ የውኃ ምርታማነትን ለማሳደግና የውኃ አጠቃቀምን ውጤታማነት ለማሻሻል፤ የመስኖ ውኃ አሳንሶ መስጠት ሁነኛ መፍትሄ እና የመስኖ ስትራቴጂ ነው፡፡ የመስክ ሙከራው የተከናወነው በመሆኒ ግብርና ምርምር ማዕከል በመስኖ  ሲሆን፤ ዓላማው ደግሞ የመስኖ ውኃ አሳንሶ መስጠት  በሽንኩርት የውኃ ምርታማነት ላይ የሚያመጣው ተፅዕኖን ለማጥናትና የትኛው የሽንኩርት የዕድገት ደረጃ ለውኃ ዕጥረት ይበልጥ ሊጎዳ እንደሚችል ጥናት ለማድረግ ነበር፡፡ ሙከራው አራት አይነት የሽንኩርት የዕድገት ደረጃ (መጀመሪያ፣ ዕድገት ላይ፣ ማኮረቻና መድረሻ ወቅት) እና አራት ዓይነት የመስኖ ውሃ መጠን (40፣ 60፣ 80 እና 100%) ያካተተ ሲሆን ትክለኛውን የጥናት ንድፍ በመጠቀም ተከናዉኗል፡፡ ተጨባጭ የሰብል ውኃ አጠቃቀም በዕለታዊ የአየር ንብረት መረጃን በመጠቀም ተገምቷል፡፡ የሙከራው ውጤት እንደሚያሳየው ከሆነ የመስኖ ውኃ መጠን ማሳነስ ከተለያዩ የዕድገት ደረጃዎች እና የእነሱ መስተጋብር በሽንኩርት ምርት ላይ ከፍተኛ ተፅዕኖ ሊፈጥር ችሏል፡፡ ከፍተኛ የሆነ ምርት የተገኘው መቶ በመቶ የሰብሉ የመስኖ ውኃ መጠን በዕድገት ወቅት በመጠቀም ሲሆን የምርቱ መጠን 30.67 ቶን በሄ/ር ነው፤ ይህም በመጀመሪያና መድረሻ ወቅቶች ላይ 60በመቶ ቅናሽ የመስኖ ውኃ መጠን በመጠቀም ከተገኘው ምርት ጋር ሲነፃፀር በስታትስቲክስ ቁጥር መረጃ መሰረት ልዩነት የለውም፡፡ የጥናቱ ውጤት እንደሚያሳየው ብዙ ምርት ሳይቀንስ በመጀመሪያና መድረሻ ወቅቶች ላይ የመስኖ ውሃ አሳንሶ መስጠትን ለመተግበር ትክክለኛ ወቅቶች ናቸው፡፡ በመድረሻ ወቅት 60በመቶ ቅናሽ የመስኖ ውኃ መጠን በመጠቀም ከፍተኛ የውኃ ምርታማነት (8.96 ኪ.ግ/ሜ3) የተገኘ ስሆን 0.17 ሄ/ር ተጨማሪ ቦታ ማልማት የሚችል የመስኖ ውኃ መቆጠብም ችሏል፡፡ በዕድገትና ማኮረቻ ወቅቶች ቅናሽ የመስኖ  ውኃ መጠቀም በሽንኩርት ምርት ላይ ከፍተኛ የሆነ ተፅዕኖ ሲኖረው፤ ቅናሽ መስኖ በትክክለኛ ወቅቶች ላይ መጠቀም ግን የውኃ ምርታማነት ከመጨመር ባሻገር በተቆጠበው ውኃ ተጨማሪ የመስኖ ቦታ ማልማት ይቻላል፡፡    Abstract The scarcity of water is the most severe constraint for the development of agriculture in arid and semi-arid areas. Under such conditions, the need to use the available water economically and efficiently is unquestionable. The important strategy for increasing water productivity and improving water use efficiency in the area of water scarcity was deficit irrigation. A field experiment was conducted at Mehoni Agricultural Research Center during offseason aimed at investigating the effect of deficit irrigation levels on water productivity of onion (Bombey Red variety) and the most sensitive growth stages of onion crop. The experiment was carried out in split plot design with sixteen treatment combinations and three replications. The treatments include four growth stages (initial, development, bulb formation and maturation) as main plot, and three deficit irrigation levels (80%, 60% and 40% of evapotranspiration of crop (ETc)), and one control irrigation of 100% ETc as a subplot. Crop water requirement was estimated using actual daily climatic data. The result showed that deficit irrigation levels, time of deficit irrigation and their interaction had a significant (p< 0.01) effect on bulb yield and yield components. The treatment received 100% ETc at the time of development stage gave the highest total bulb yield of 30.67 t/ha with no significant difference from 60% deficit treatments during initial and maturation stages. The result showed that initial and maturation stages were the right time to practicing deficit irrigation without significant yield reduction. Water productivity was the highest with 60% deficit irrigation at the maturation stage (8.96 kg/m3), and 0.17ha additional area to be irrigated by saved water. The yield response factor (Ky) was higher (1.98) when 40% deficit occurred at the development stage. The result revealed that onion bulb yield was most sensitive to water deficit that occurred at development and bulb formation stages. While maximum yield was obtained when the whole crop water requirement was applied, implementing deficit irrigation at appropriate stage could increase the irrigated area as a result of high water productivity

Sparse relative risk regression models

Clinical studies where patients are routinely screened for many genomic features are becoming more routine. In principle, this holds the promise of being able to find genomic signatures for a particular disease. In particular, cancer survival is thought to be closely linked to the genomic constitution of the tumor. Discovering such signatures will be useful in the diagnosis of the patient, may be used for treatment decisions and, perhaps, even the development of new treatments. However, genomic data are typically noisy and high-dimensional, not rarely outstripping the number of patients included in the study. Regularized survival models have been proposed to deal with such scenarios. These methods typically induce sparsity by means of a coincidental match of the geometry of the convex likelihood and a (near) non-convex regularizer. The disadvantages of such methods are that they are typically non-invariant to scale changes of the covariates, they struggle with highly correlated covariates, and they have a practical problem of determining the amount of regularization. In this article, we propose an extension of the differential geometric least angle regression method for sparse inference in relative risk regression models. A software implementation of our met

Bistability in fatty-acid oxidation resulting from substrate inhibition

In this study we demonstrated through analytic considerations and numerical studies that the mitochondrial fatty-acid β-oxidation can exhibit bistable-hysteresis behavior. In an experimentally validated computational model we identified a specific region in the parameter space in which two distinct stable and one unstable steady state could be attained with different fluxes. The two stable states were referred to as low-flux (disease) and high-flux (healthy) state. By a modular kinetic approach we traced the origin and causes of the bistability back to the distributive kinetics and the conservation of CoA, in particular in the last rounds of the β-oxidation. We then extended the model to investigate various interventions that may confer health benefits by activating the pathway, including (i) activation of the last enzyme MCKAT via its endogenous regulator p46-SHC protein, (ii) addition of a thioesterase (an acyl-CoA hydrolysing enzyme) as a safety valve, and (iii) concomitant activation of a number of upstream and downstream enzymes by short-chain fatty-acids (SCFA), metabolites that are produced from nutritional fibers in the gut. A high concentration of SCFAs, thioesterase activity, and inhibition of the p46Shc protein led to a disappearance of the bistability, leaving only the high-flux state. A better understanding of the switch behavior of the mitochondrial fatty-acid oxidation process between a low- and a high-flux state may lead to dietary and pharmacological intervention in the treatment or prevention of obesity and or non-alcoholic fatty-liver disease

Performance of model-based multifactor dimensionality reduction methods for epistasis detection by controlling population structure

peer reviewe

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

A Production Function Analysis for Private Peasant Holdings Crop Farms in Ethiopia: An Application of Robust Regression *For Correspondence

ABSTRACT Four major crop producing regions in Ethiopia, i.e., Tigray, Amhara, Oromia and SNNP were included in the study. Three models for production function: linear, exponential and Cobb Douglas were considered and assessed for statistical model diagnostics. The statistical model diagnostics suggested that crop production function was found to be represented by the Cobb-Douglas function based on data from 2007/2008 agricultural sample survey. The Cobb-Douglas production function was first fitted using ordinary least squares (OLS). As expected, the parameter estimates using OLS were misleading due to occurrence of outliers; hence robust regression was taken as an alternative. Then many of the parameter estimates received the expected signs, R2 values increased and standard errors of parameter estimates decreased. In general, farm size, fertilizer, seed, oxen power and human labor were important to maximize crop yield. The great contribution was found to be due to farm size in each of the regions except in SNNP where it was due to human labor. Education variable was found to be statistically insignificant and received negative sign in Tigray and Amhara. Production elasticities for each of the inputs except farm size in Tigray, Amhara and Oromia suggested that the relation between inputs and output was inelastic

Multi-spectral remote sensing for current irrigated area mapping of the Rift Valley Lakes Basin in Ethiopia

The study was conducted in the Rift Valley Basin in 2020–2022, with the objective of evaluating the newly developed techniques for irrigated area mapping of spatially large areas and assessing the current irrigated area in the basin. Methods used for irrigated area mapping are imagery analysis using the NDVI and EVI methods and land use classification. All results were verified with ground-truthing data using the sample locations selected. A 10 m × 10 m spatial resolution image derived from the European Space Agency Sentinel-2 satellite was used to create a time series spanning 2020, 2021, and 2022. Irrigated area maps from all three techniques were obtained and evaluated. Metric indicators were used to evaluate the performance of the irrigated area mapping techniques, the mean overall accuracy was 0.82, with a kappa coefficient of 0.76 and an F1-score of 0.86 with the highest and lowest overall accuracy observed in 2020 (0.86) and 2022 (0.76), respectively. Coefficient of determination was used to quantify the correlation of geospatial information and the multispectral remote sensing data analysis results maps agreed with irrigated area mapping with respect to ground truthing with R2 mean value of 0.87 which suggests a strong agreement. HIGHLIGHTS No previous study has been done for the basin.; The study will have an impact on managing water resources, strategic water allocation planning and climate change mitigation options.; Appropriate references are used.