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We introduce a new algorithm and software for solving linear equations insymmetric diagonally dominant matrices with non-positive off-diagonal entries(SDDM matrices), including Laplacian matrices. We use pre-conditioned conjugategradient (PCG) to solve the system of linear equations. Our preconditioner is avariant of the Approximate Cholesky factorization of Kyng and Sachdeva (FOCS2016). Our factorization approach is simple: we eliminate matrix rows/columnsone at a time and update the remaining matrix using sampling to approximate theoutcome of complete Cholesky factorization. Unlike earlier approaches, oursampling always maintains a connectivity in the remaining non-zero structure.Our algorithm comes with a tuning parameter that upper bounds the number ofsamples made per original entry. We implement our algorithm in Julia, providingtwo versions, AC and AC2, that respectively use 1 and 2 samples per originalentry. We compare their single-threaded performance to that of currentstate-of-the-art solvers Combinatorial Multigrid (CMG),BoomerAMG-preconditioned Krylov solvers from HyPre and PETSc, Lean AlgebraicMultigrid (LAMG), and MATLAB's with Incomplete Cholesky Factorization (ICC).Our evaluation uses a broad class of problems, including all large SDDMmatrices from the SuiteSparse collection and diverse programmatically generatedinstances. Our experiments suggest that our algorithm attains a level ofrobustness and reliability not seen before in SDDM solvers, while retaininggood performance across all instances. Our code and data are public, and weprovide a tutorial on how to replicate our tests. We hope that others willadopt this suite of tests as a benchmark, which we refer to as SDDM2023. Oursolver code is available at: https://github.com/danspielman/Laplacians.jl/ Ourbenchmarking data and tutorial are available at:https://rjkyng.github.io/SDDM2023/

In agricultural information dissemination campaigns through agricultural advisory services, seemingly small design attributes, such as the way the information is delivered, who delivers the information, or who is targeted by the message, can result in significant differences in effectiveness and inclusiveness of the intervention. In the context of Information & Communication Technology (ICT) mediated knowledge transfer, this study investigates the importance of the gender composition of the person(s) who provide(s) the information and the gender composition of the person(s) who receive(s) the information. In particular, we set up a field experiment among smallholder maize farmers in Uganda to assess if reducing asymmetric information within the household leads to improved outcomes. In addition, we study the effectiveness of promoting a more cooperative approach to household farming. Finally, we test for gender homophily effects, where female farmers learn more from female trainers. Effectiveness is assessed in terms of knowledge gained, adoption of modern inputs and recommend practices, yield, and poverty reduction. Outcomes are dis-aggregated by gender to study changes in intra-household equity and women empowerment. While endline of the study is planned for February 2018, we preview encouraging effects on knowledge transfer as measured immediately after administering the treatments. Acknowledgement : We acknowledge support from USAID's Global Development Lab and Digital Green.

Despite substantial research on the economic impacts of Bt cotton, there is still limited work on the technology s impacts on human health, particularly the impacts associated with reductions in pesticide use. Using household and biophysical survey data collected in 2013-14, this study provides the first evidence of a direct association between Bt expression and farmers health benefits in Pakistan. We employ a cost-of-illness approach and double-hurdle model to estimate the relationship between Bt cotton and health costs incurred by a representative sample of cotton farmers. Double hurdle estimates show that farmers self-reported adoption of Bt technology could not reduce pesticide induced cost of illness due to inconsistencies between their Bt beliefs and levels of Bt expression in a developing country context. Results with more effective Bt gene expression drawn from laboratory tests show that Bt expression is associated with 33 percent reduction in the cost of illness. Extrapolating the results to the entire Bt cotton area in Pakistan reveals that 1 ?g/g increase in Bt expression is associated with health cost savings of US$ 0.82 million. Hence, better seed regulation and monitoring of seed quality would enhance Bt technology s health effects, which could have important implications for farmers overall welfare. Acknowledgement : This study was conducted under the auspices of the Pakistan Strategy Support Program of the International Food Policy Research Institute with funding from the U.S. Agency for International Development and support from the CGIAR Research Program on Policies, Institutions, and Markets. Any and all errors are the sole responsibility of the authors.

During the last several years, a series of important policy changes affecting genetic resource conservation, use, and exchange have entered into force. These policy changes will likely affect investment choices made by the international research-for-development community - choices that influence scientific collaboration and cooperation nationally, regionally and internationally. Specifically, these policy changes may introduce new institutional constraints on the use of genetic resources, with potentially long-lasting influence on research priority-setting and collaboration strategies. This paper provides a novel characterization of the changing landscape governing international germplasm exchanges. Emphasis is placed on culling evidence from historical trends, networks, and econometric analysis to better understand how national regulatory changes associated with the Convention on Biological Diversity (CBD) of 1993 and the International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA) of 2004 affected the movement of genetic resources and lessons to be drawn to understand the potential effects of the Nagoya Protocol which entered into force beginning 2014. Acknowledgement : This paper was prepared with generous funding from the U.S. Agency for International Development and the CGIAR Research Program on Policies, Institutions, and Markets. The authors thank Jennifer Long, M. Lisa Wilson, Eric Welch, Selim Louafi, Federica Fusi, and Fatima Zaidi for their insightful comments. This paper is dedicated to the memory of Eduardo Magalhaes, our colleague and friend. Any and all errors are the sole responsibility of the authors.

We develop fast algorithms for solving regression problems on graphs where one is given the value of a function at some vertices, and must find its smoothest possible extension to all vertices. The extension we compute is the absolutely minimal Lipschitz extension, and is the limit for large $p$ of $p$-Laplacian regularization. We present an algorithm that computes a minimal Lipschitz extension in expected linear time, and an algorithm that computes an absolutely minimal Lipschitz extension in expected time $\widetilde{O} (m n)$. The latter algorithm has variants that seem to run much faster in practice. These extensions are particularly amenable to regularization: we can perform $l_{0}$-regularization on the given values in polynomial time and $l_{1}$-regularization on the initial function values and on graph edge weights in time $\widetilde{O} (m^{3/2})$., Comment: Code used in this work is available at https://github.com/danspielman/YINSlex 30 pages

Metadata only record This paper examines the role of postsecondary agricultural education and training (AET) in Sub-Saharan Africa in the context of the region’s agricultural innovation systems. Specifically, the paper looks at how AET in Sub-Saharan Africa can contribute to agricultural development by strengthening innovative capabilities, or the ability to introduce new products and processes that are socially or economically relevant to smallholder farmers and other agents in the agricultural sector.

Quantification of gray and white matter levels of spectroscopically visible metabolites can provide important insights into brain development and pathological conditions. Chemical shift imaging offers a gain in efficiency for estimation of global gray and white matter metabolite concentrations compared to single voxel methods. In the present study, the optimal voxel size is calculated from segmented human brain data and accompanying field maps. The optimal voxel size is found to be approximately 8 cc, but a wide range of values, 4-64 cc, can be chosen with little increase in estimated concentration error (

Quantification of apoptotic cell death in vivo has become an important area of investigation in patients with acute lymphoblastic leukemia (ALL). We have devised a noninvasive analytical method to estimate the percentage of apoptotic lymphoblasts in doxorubicin-treated Jurkat T-cell ALL cultures, using proton nuclear magnetic resonance spectroscopy (1H NMR). We have found that the ratio of the methylene (CH2) resonance (at 1.3 ppm) to the methyl (CH3) resonance (at 0.9 ppm) signal intensity, as observed by 1H NMR, is directly proportional to the percentage of apoptotic lymphoblasts in vitro. The correlation between the CH2/CH3 signal intensity ratio and the percentage of apoptotic lymphoblasts was optimal 24 to 28 hours after doxorubicin treatment (r2 = .947, N = 27 samples). There was also a direct temporal relationship between an increase in the CH2/CH3 signal intensity ratio and the onset of apoptosis as detected by nuclear morphologic analysis, fluorescein-annexin V flow cytometry, and DNA gel electrophoresis. Thin-layer chromatography confirmed that a dynamic and/or compositional change of the plasma membrane, rather than increases in lipase activity or fatty acid production, appears to account for the increase in the CH2/CH3 signal intensity ratio during apoptosis. 1H NMR may have clinical utility for the early noninvasive assessment of chemotherapeutic efficacy in patients with ALL.