Anthracnose fruit rot, caused by Colletotrichum spp. is a major disease of highbush blueberries. The inheritance of fruit rot resistance to C. fioriniae was investigated in crosses of parents with varying levels of susceptibility. Three cultivars with known resistance profiles (Bluecrop, Elliott, and Jersey) and progeny from 16 crosses of parents with varying levels of susceptibility were screened. Fruit of field-grown bushes was inoculated when immature, harvested when ripe, and rated for infection incidence after 5, 8, and 12 days of incubation at 100% RH and 22–23°C. Area under the disease progress curves (AUDPC) values were calculated for 2010 and 2011 and slightly higher disease pressure was observed in 2011. These values were then regressed against actual disease incidences of cultivars and predicted (midparent) values for cross families based on two previous studies in 2010 and 2011 and significant correlations with the proportion of fruit decayed and sporulation capacity were observed. These findings provide strong evidence that anthracnose resistance is heritable in highbush blueberries, which has important implications for anthracnose resistance breeding. Additionally, this research provides benchmark AUDPC values for evaluation of future breeding selections for their resistance to C. fioriniae.
Campylobacter jejuni is a leading cause of gastroenteritis that has been causally linked with development of the autoimmune peripheral neuropathy Guillain Barré Syndrome (GBS). Previously, we showed that C. jejuni isolates from human enteritis patients induced Type1/17-cytokine dependent colitis in interleukin-10 (IL-10)-/- mice, while isolates from GBS patients colonized these mice without colitis but instead induced autoantibodies that cross-reacted with the sialylated oligosaccharide motifs on the LOS of GBS-associated C. jejuni and the peripheral nerve gangliosides. We show here that infection of IL-10-/- mice with the GBS but not the colitis isolate led to sciatic nerve inflammation and abnormal gait and hind limb movements, with character and timing consistent with this syndrome in humans. Autoantibody responses and associated nerve histologic changes were dependent on IL-4 production by CD4 T cells. We further show that Siglec-1 served as a central antigen presenting cell receptor mediating the uptake of the GBS isolates via interaction with the sialylated oligosaccharide motifs found specifically on the LOS of GBS-associated C. jejuni, and the ensuing T cell differentiation and autoantibody elicitation. Sialylated oligosaccharide motifs on the LOS of GBS-associated C. jejuni therefore acted as both the Siglec-1-ligand for phagocytosis, as well as the epitope for autoimmunity. Overall, we present a mouse model of an autoimmune disease induced directly by a bacterium that is dependent upon Siglec-1 and IL-4. We also demonstrate the negative regulatory role of IL-10 in C. jejuni induced autoimmunity and provide IL-4 and Siglec-1 blockade as potential therapeutic interventions against GBS.
Background As a triazole fungicide, triadimefon is widely used around the world. The ubiquitous occurrence of triadimefon in aquatic environments and potential adverse effects on aquatic organisms have resulted in global concerns. In this review, the current state of knowledge on occurrence, environmental behavior, and toxic effects are presented and used to conduct an assessment of risks posed by current concentrations of triadimefon in aquatic environments. Results The key findings from this review are that: (1) triadimefon occurred widely in surface waters, with high rates of detection; (2) abiotic degradation of triadimefon was affected by many factors. Stereoselectivity was found during biotic degradation and metabolism of triadimefon. Different enantiomers can cause various adverse effects, which complicates the assessment and requires enantiomers-specific considerations; (3) triadimefon exposure can affect organisms by causing multiple toxic effects on the thyroid, reproductive system, liver, nervous system as well as carcinogenicity and teratogenicity, and it can also act synergistically with other pesticides. Long-term, low-dose effects were considered to be the main characteristics of toxic effects of triadimefon; (4) results of the risk assessment based on probabilistic relationships represented by joint probability curves (JPCs) indicated that risk of triadimefon was classified as low risk. Conclusion Triadimefon occurred widely in surface waters, with high rates of detection, while the concentration data of triadimefon in surface water is insufficient. Researches about toxic effects and mechanisms of triadimefon on invertebrate are needed. Meanwhile, researches about toxic effects and environmental exposure of chiral monomers are also required. Due to its reproductive toxicity, triadimefon might result in adverse effects on the population level or even on the ecosystem level. Risk assessments for pesticides that cause long-term and low-dose effects on aquatic organisms such as triadimefon need to consider higher-level ecological risk.
The protein corona is a key component controlling biological activity, that develops on foreign materials when introduced to biological environments. This comment discusses the risk of errors from poor methodology that can lead to misinterpretation and poor outcomes.
Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis complex (MTBC) in humans and animals. Numbers of multi drug resistance TB (MDR-TB), extrapulmonary TB (EPTB) and zoonotic TB cases are increasingly being reported every year in Nepal posing a major public health problem. Therefore, the Government of Nepal should act immediately to strengthen the screening facilities across the country to be able to identify and treat the TB infected patients as well as detect zoonotic TB in animal species. Endorsement of One Health Act by the Government of Nepal is an opportunity to initiate the joint programs for TB surveillance among human and animal species using one health approach to reduce the TB burden in Nepal.
The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.
The IceCube Neutrino Observatory is a cubic kilometer neutrino detector located at the geographic South Pole designed to detect high-energy astrophysical neutrinos. To thoroughly understand the detected neutrinos and their properties, the detector response to signal and background has to be modeled using Monte Carlo techniques. An integral part of these studies are the optical properties of the ice the observatory is built into. The simulated propagation of individual photons from particles produced by neutrino interactions in the ice can be greatly accelerated using graphics processing units (GPUs). In this paper, we (a collaboration between NVIDIA and IceCube) reduced the propagation time per photon by a factor of up to 3 on the same GPU. We achieved this by porting the OpenCL parts of the program to CUDA and optimizing the performance. This involved careful analysis and multiple changes to the algorithm. We also ported the code to NVIDIA OptiX to handle the collision detection. The hand-tuned CUDA algorithm turned out to be faster than OptiX. It exploits detector geometry and only a small fraction of photons ever travel close to one of the detectors.
Fungicides reduce fungal pathogen populations and are essential to food security. Understanding the impacts of fungicides on crop microbiomes is vital to minimizing unintended consequences while maintaining their use for plant protection. However, fungicide disturbance of plant microbiomes has received limited attention, and has not been examined in different agricultural management systems. We used amplicon sequencing of fungi and prokaryotes in maize and soybean microbiomes before and after foliar fungicide application in leaves and roots from plots under long-term no-till and conventional tillage management. We examined fungicide disturbance and resilience, which revealed consistent non-target effects and greater resiliency under no-till management. Fungicides lowered pathogen abundance in maize and soybean and decreased the abundance of Tremellomycetes yeasts, especially Bulleribasidiaceae, including core microbiome members. Fungicide application reduced network complexity in the soybean phyllosphere, which revealed altered co-occurrence patterns between yeast species of Bulleribasidiaceae, and Sphingomonas and Hymenobacter in fungicide treated plots. Results indicate that foliar fungicides lower pathogen and non-target fungal abundance and may impact prokaryotes indirectly. Treatment effects were confined to the phyllosphere and did not impact belowground microbial communities. Overall, these results demonstrate the resilience of no-till management to fungicide disturbance, a potential novel ecosystem service provided by no-till agriculture.
Background Cowpea or black-eyed pea ( Vigna unguiculata L.) is one of the preferred food crops in Nigeria, as expressed in land area and production. The popularity of the crop is in part related to the successful development and adoption of improved cowpea varieties. Although the genebank of the International Institute of Tropical Agriculture (IITA) has contributed to cowpea conservation and improvement efforts by breeding programs internationally and in Nigeria, few studies have attempted to link the genebank to the management of cowpea genetic resources (CGRs) on farms. This study explores the linkage between IITA’s genebank and cowpea variety diversity on farms and other measures of farmers’ welfare in Nigeria. Methods A multistage stratified sampling was used to select the sample households. A cross-sectional household survey was conducted to collect data from 1524 cowpea-producing households. In addition, “Helium”, a multi-platform pedigree visualization tool with phenotype display was used to gather information about improved cowpea breeding lines and their pedigrees. For data analysis, ecological indices of spatial diversity were employed, and a conditional recursive mixed-process model and a multinomial endogenous treatment effect model were developed. Results We found that growing an improved variety with genebank ancestry is not significantly associated with lower spatial diversity among cowpea varieties. While they may introduce new traits through ancestry, improved varieties do not displace other cowpea varieties or landraces. We also found that genebank ancestry is positively and significantly associated with cowpea yield and farmers’ welfare. Conclusions These findings show additional benefits from IITA’s genebank in Nigeria and that adoption of improved varieties with genebank ancestry does not contribute to the erosion of CGRs on smallholder farms in Nigeria. Policymakers and practitioners should consider these findings when analyzing the benefits of conserving crop genetic diversity in genebanks and on farms.
Background One of the less known benefits of the CGIAR is the facilitation of international agricultural research for crop improvement by providing a continuous supply of breeding materials for the development of disease resistant varieties. The Germplasm Health Units (GHUs) of the CGIAR are phytosanitary mechanisms put in place to help ensure safe (from pests and diseases) and efficient international transfer of germplasm among genebanks and breeding programs around the world. To date, there is no systematic documentation of the pathways and extent to which GHUs contribute to economic impact in recipient countries. Methods We conducted interviews with key experts and reviewed secondary literature and data to trace the pathways through which the GHU of the International Rice Research Institute (IRRI) contributes to the impact of breeding for rice blast. We applied an ex ante economic surplus framework to the case of rice blast in Bangladesh, considering productivity maintenance and time saving factors from GHU facilitation. Data were drawn from a national panel dataset of farm households (from 2013 to 2016 with about 4490 households) and field surveys of blast incidence and severity (from 2011 to 2012 in 10 agroecological zones). We augmented our model with Monte Carlo sampling to simulate distributions of parameters. Results Our model predicts that, in the most probable scenario (modal values), the IRRI GHU contributed about US$ 5.9 million of the total US$ 295 million net benefits over a 20-year time frame of continuous blast resistance breeding and deployment. In the most optimistic conditions (maximum), the IRRI GHU contributed as much as US$ 62 million of the US$ 1.46 billion benefits. The modal benefit–cost ratio of the GHU in this breeding program alone was estimated at 112. The results are sensitive to the rate of yield savings, which is contingent on yield levels, timing of deployment, effectiveness of resistance, and lifespan of resistance to blast. Conclusions The study reinforces the important, and often overlooked, role of the GHUs in the international agricultural research that aims to enhance genetic gains in crops through efficient and timely access to clean and healthy germplasm.
The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.
Autonomous driving has attracted significant research interests in the past two decades as it offers many potential benefits, including releasing drivers from exhausting driving and mitigating traffic congestion, among others. Despite promising progress, lane-changing remains a great challenge for autonomous vehicles (AV), especially in mixed and dynamic traffic scenarios. Recently, reinforcement learning (RL) has been widely explored for lane-changing decision makings in AVs with encouraging results demonstrated. However, the majority of those studies are focused on a single-vehicle setting, and lane-changing in the context of multiple AVs coexisting with human-driven vehicles (HDVs) have received scarce attention. In this paper, we formulate the lane-changing decision-making of multiple AVs in a mixed-traffic highway environment as a multi-agent reinforcement learning (MARL) problem, where each AV makes lane-changing decisions based on the motions of both neighboring AVs and HDVs. Specifically, a multi-agent advantage actor-critic (MA2C) method is proposed with a novel local reward design and a parameter sharing scheme. In particular, a multi-objective reward function is designed to incorporate fuel efficiency, driving comfort, and the safety of autonomous driving. A comprehensive experimental study is made that our proposed MARL framework consistently outperforms several state-of-the-art benchmarks in terms of efficiency, safety, and driver comfort.
Direct Aid (formerly Africa Muslims Agency), Kuwait's largest charity focused on Africa, carefully mediates between Gulf donor wishes, aid recipient needs, Kuwaiti and African government regulations, and various development priorities. Since the 1980s, Direct Aid has been centralizing religious and development work in complexes that comprise orphanages, schools, clinics, and mosques – a distinctly Kuwaiti model that aims for self‐sufficient communities. The Islamic NGO cannot be confined to narrow Western categorizations of Gulf Salafi da‘wa (proselytizing) institutions. Direct Aid's approach is strategically grounded in comprehensiveness/“holism,” which serves to blur established categories of “charity,” “relief,” and “development” to become da‘wa‐as‐development. “Good Muslims” are envisioned as those who graduate from the international NGO's educational programs and become moral members of society trained to be productive citizens of their countries. This article examines the work of one transnational Islamic charity headquartered in Kuwait in two very different African countries. A comparison of the similarities and variances of Direct Aid's projects in Tanzania and Senegal highlights how the organization adapts its work to local Muslim‐minority and Muslim‐majority settings. What is the cultural and religious impact of Gulf funding in East and West Africa? How do Kuwait headquarters interact with African beneficiaries?
Background Mali’s fertilizer subsidy program aims to reduce food insecurity among the nation’s predominantly rural people by jump-starting productivity gains of major crops. This paper contributes to sparse evidence regarding its effects. Methods Theory predicts that agricultural productivity can affect diet quality directly through two channels. The production channel influences the availability of food for household consumption or sale. The income pathway, resulting from sales, leads to household food expenditure. We test this hypothesis by applying propensity score matching methods to farm household survey data collected from 2400 households in Mali in 2018. Results We find that the overall effect of the fertilizer subsidy on women’s dietary diversity is positive in the Niger Delta and negative on the Koutiala Plateau. Further examination by food supply source reveals no subsidy effects on the dietary diversity provided by on-farm production in either zone. The subsidy negatively influences dietary diversity of foods sourced as gifts in the Niger Delta. Subsidy effects on dietary diversity accessed through food purchases are strong and positive in the Niger Delta, but negative on the Koutiala Plateau. The Koutiala Plateau is found in the region of Sikasso, where rising incomes from cotton production, which is the major export crop of the region and of the nation, have been shown not to alleviate poverty and malnutrition (a dilemma known as the “Sikasso Paradox”). Conclusions Our approach reveals that additional income from increased yields stimulated by subsidized fertilizer can enable off-farm purchases of more nutritious food and thereby improve nutritional outcomes for women.
We introduce multiple parametrized circuit ansätze and present the results of a numerical study comparing their performance with a standard Quantum Alternating Operator Ansatz approach. The ansätze are inspired by mixing and phase separation in the QAOA, and also motivated by compilation considerations with the aim of running on near-term superconducting quantum processors. The methods are tested on random instances of a quadratic binary constrained optimization problem that is fully connected for which the space of feasible solutions has constant Hamming weight. For the parameter setting strategies and evaluation metric used, the average performance achieved by the QAOA is effectively matched by the one obtained by a ”mixer-phaser” ansatz that can be compiled in less than half-depth of standard QAOA on most superconducting qubit processors.
We review the literature on the distribution of farm sizes in sub-Saharan Africa, trends over time, drivers of change in farm structure, and effects on agricultural transformation and present new evidence for seven countries. While it is widely viewed that African agriculture is dominated by small-scale farms, we show that medium-scale farms of 5 to 100 hectares are a nontrivial—and rapidly expanding—force that is influencing the nature and pace of food systems transformation in Africa. The increased prevalence of medium-scale holdings is associated with farm labor productivity growth and underappreciated benefits to smallholder farmers. However, the rise of African investor farmers is also contributing to the commodification of land, escalating land prices, and restricted land access for most local people. A better understanding of these trends and linkages, which requires new data collection activities, could help resolve long-standing policy debates and support strategies that accelerate agricultural transformation. Expected final online publication date for the Annual Review of Resource Economics, Volume 14 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Movement of labor from agriculture to nonagriculture and the associated increase in farm size through structural transformation are at the core of economic development. We conduct a comprehensive review of the literature exploring the causes and consequences of the transformation. We discuss ( a) the size and determinants for the persisting wage gap between agriculture and nonagriculture, ( b) policy-induced barriers to structural changes, ( c) the role of trade costs and technical change in shaping the nature of structural transformation and comparative advantage of regions, and ( d) how the overall development of an economy affects the relationship between farm size and farm productivity and hence changes competitiveness of different scales of farms. We also identify questions for policy and research and the ways in which new sources and interoperability of data can help answer these questions. Expected final online publication date for the Annual Review of Resource Economics, Volume 14 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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