On Fast and Robust Information Spreading in the Vertex-Congest Model

This paper initiates the study of the impact of failures on the fundamental problem of \emph{information spreading} in the Vertex-Congest model, in which in every round, each of the $n$ nodes sends the same $O(\log{n})$-bit message to all of its neighbors. Our contribution to coping with failures is twofold. First, we prove that the randomized algorithm which chooses uniformly at random the next message to forward is slow, requiring $\Omega(n/\sqrt{k})$ rounds on some graphs, which we denote by $G_{n,k}$, where $k$ is the vertex-connectivity. Second, we design a randomized algorithm that makes dynamic message choices, with probabilities that change over the execution. We prove that for $G_{n,k}$ it requires only a near-optimal number of $O(n\log^3{n}/k)$ rounds, despite a rate of $q=O(k/n\log^3{n})$ failures per round. Our technique of choosing probabilities that change according to the execution is of independent interest.Comment: Appears in SIROCCO 2015 conferenc

Rainfall insurance in India: does it deal with risks in dryland farming?

Rainfall continues to be a major risk confronted by the dryland farmers in semi-arid tropics of India. Through the years, dryland farmers experience an increasingly erratic rainfall and frequent occurrence of droughts. Crop yield and farm income are highly correlated with quantum and distribution of rainfall thereby livelihoods of resource poor farmer are at risk. Rainfall insurance, a type of Weather Based Crop Insurance Scheme (WBCIS), was introduced as a risk covering mechanism to extreme rainfall events and to reduce hassles in operationalization of other crop insurance schemes. This study documents rainfall insurance scheme and its operational modalities such as eligibility criteria, payment of premium, benefit structure and payouts, and technical hassles. It examined the hypothesis that low spread of rainfall insurance was linked with the situation where prospective buyers were unable to relate the product to their regular exposure. This study also underlines incongruity comparing the variation in longitudinal actual village data and reference weather data (mandal level3 ) that were used to calculate strike, exit and payouts to the farmers across six villages of semi-arid tropics (SAT) region. It identified several challenges on the ground in its capacity to cover risk among the farmers. The challenges include lack of proper awareness among farmers, absence of reliable weather datasets, misinformation on insurance contract and processes, exclusion of high risky crops from the rainfall insurance coverage. Real time calculation of risk benefits with existing policy found that existing design cannot appropriate to meet the loss, if incurred during the climate extremes. Hence, there is a need to relook at the insurance policy design in terms of efficiency. The study also argued that with continuous government support and by drawing on both quasi government and private players into the process for greater transparency and design to improve effectiveness of this initiativ

Impacts of genetic enhancement in pearl millet

This chapter documents the benefits from pearl millet genetic enhancement research conducted by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in partnership with national agricultural research systems (NARS). ICRISAT-NARS research efforts and the resultant impacts are summarized, recognizing that many improved pearl millet cultivars and hybrids are the joint products of the partnership. An example of South-South research spillover, where research products developed at ICRISAT found applicability and adaptability across India and sub-Saharan Africa, is presented

Spillover impacts of agricultural research: a review of studies. Working Paper Series no. 8

The spillover impacts of agricultural research are very important for research policy formulation. This paper reviews the existing literature on the policy effects of research and summarizes the methodologies used for quantifying the spillover impacts. Three types of spillover effects have been identified on the basis of the existing literature: across-location spillover, across-commodity spillover, and price spillover effects. The former two are direct effects, and the latter indirect. Acrosslocation or across-environment spillover effects relate to a situation in which a technology developed for one crop at a specific location can be adopted to improve the production efficiency of the same crop at other locations. Across-commodity spillover effects occur when the technology developed has applicability for other commodities. Price spillover effects occur when the technological change for a particular commodity at a specific location increases supply and changes the price of the commodity at other locations through trade. Two types of measurement techniques, subjective and objective, have been used to assess spillover effects in agriculture. Subjective estimates are based on value judgments rather than experimental or onfarm yield and cost data, and are often arrived at through elicitation from experts. Objective estimates on the other hand are based on hard data and evidence reflecting the extent of applicability of a new technology across environments or commodities beyond the designed research target. Both subjective and objective estimates are used in the empirical quantification of across-location spillover impacts. However, only a theoretical model (no empirical quantification) is available for the estimation of across-commodity spillover. Price spillover effects are estimated in conjunction with the across-environment technology spillover. Studies have quantified across-location spillover impacts using economic surplus models, subjectively and objectively. Quantification of spillover benefits from germplasm research conducted at ICRISAT would be very useful in research evaluation and policy planning

Spillover Impacts of Agricultural Research: A Review of Studies

Measurement of the spillover effects of research has drawn significant attention in recent years. Three aspects of spillover effects — spillover as an input in the research policy debate, as an input to support research management decisionmakers, and as an input in the fine-tuning of research evaluation methodology — are very important to understand (Davis 1991). Consideration of the spillover effects has significant implications for research policy design and evaluation of research benefits. Research systems generate technologies for target environments and commodities. However, the outcome of a research effort often impacts an area wider than the target. Thus, research systems generate two types of benefits for their investors: direct and spillover effects. Conventional research evaluation considers only the direct benefits and ignores the spillover. As a result, output from research is underestimated. So when policymakers decide on the level of investment to be made in research, they are likely to do so on the basis of such underestimated benefits. Therefore, the investment is likely to be less than optimum. If, however, spillover effects were quantified, they would help in making research investment decisions more attuned with the needs. Incorporation of spillover effects in the research policy design would also enhance the transparency of the decision-making process. Research spillover effects also have an impact on the competitiveness of farmers in different regions and countries. National research planning tends to underestimate returns to research by not considering spillover effects and, therefore, tends to underinvest in research. International research support, whether bilateral, regional or multilateral, is normally designed to complement national research activities and to generate maximum international rather than national research benefits. It selects research portfolios with an explicit consideration of the likely spillover benefits for countries with similar agroclimatic and socioeconomic environments

Impacts of Improved Pearl Millet Cultivars in India

Pearl millet (Pennisetum glaucum) is the fourth most important cereal in India in terms of area cultivated after rice, wheat, and sorghum. It provides grain and fodder to milch animals and is usually grown under harsh environments and on poor soils. India grows about 7 Mt of pearl millet grain from 10 Mha of land. The major pearl millet-growing states in India are Rajasthan, Maharashtra, Gujarat, Uttar Pradesh, Haryana, Karnataka, Tamil Nadu, Madhya Pradesh and Andhra Pradesh (Table 1). In terms of yield in 1995-98, Uttar Pradesh stood first, followed by Gujarat, Tamil Nadu, Haryana, Madhya Pradesh, Andhra Pradesh, Maharashtra, Karnataka, and Rajasthan. These nine states covered more than 99% of the total pearl millet area and production in 1995-98. While the area under pearl millet has been declining over time in all the states, except Maharashtra, production has gone up in all the states, except Andhra Pradesh and Tamil Nadu (Table 1). Pearl millet yield increased in all the states and more than doubled in a majority of them in the late 1990s compared to the early 1960s. Increase in yield was associated with increase in area under improved pearl millet cultivars..

Impact of modern cultivars on growth and relative variability in sorghum yields in India

The nature and extent of growth and variability in sorghum yield is measured in this study to test the hypothesis that rapid technological change increased yield and also instability in sorghum production. Analysis is being based on 146 major sorghum producing districts of India. Annual compound growth rate of sorghum yields for different districts were computed for various periods between 1966 and 1993. Expansion of modern sorghum cultivars positively contributed to the sorghum yield. The coefficient of variation of sorghum yields was estimated for the same districts and from the same set of data after detrending. Analysis showed a general decline in yield variability over time. The coefficient of variation in sorghum yield decreases with the increase in proportion of modern sorghum cultivars. Relative variability of sorghum yield of modern sorghum cultivars, estimated from the experimental data for the period 1982–96, is less than the relative variability of other sorghum cultivars. The study concludes that modern sorghum cultivars contrihuted to the increase in yield and reduction in relative variability in yield and thereby, enhanced food security in India. It also suggests that future sorghum research in India should be emphasized on yield enhancement rather than on yield stabilizatio

Time-dependent density functional theory beyond the adiabatic local density approximation

In the current density functional theory of linear and nonlinear time-dependent phenomena, the treatment of exchange and correlation beyond the level of the adiabatic local density approximation is shown to lead to the appearance of viscoelastic stresses in the electron fluid. Complex and frequency-dependent viscosity/elasticity coefficients are microscopically derived and expressed in terms of properties of the homogeneous electron gas. As a first consequence of this formalism, we provide an explicit formula for the linewidths of collective excitations in electronic systems.Comment: RevTeX, 4 page

Impacts of Improved Groundnut Varieties in India

India is the largest producer of groundnut in the world. About 88% of the groundnut area and production in India is concentrated in five states: Andhra Pradesh, Gujarat, Karnataka, Tamil Nadu, and Maharashtra. Nearly 83% of the total area is under rainy-season groundnut and the other 17% is cultivated during the postrainy season. During 1995-98, groundnut was grown in India over 7.47 Mha with a total production of 8.02 Mt (CMIE 2000). However, the past three decades have............