Market impact on cassava's development potential in the Atlantic Coast region of Colombia

The impact of markets on agricultural development was analyzed by means of a case study on cassava in the Atlantic Coast region of Colombia. In the development process, the demand for agricultural products changes considerably. Traditional food products, such as roots and tubers, face a decreasing demand in the course of urbanization and income growth. Feed grains and animal products face a growing demand. The agricultural sector is often not able to adapt to these demand changes and imports result. In case the structure of agriculture is dualistic, small farmers might be harmed and large farmers benefitted by these changes. This leads to unbalanced agricultural development. Market improvement strategies directed to small farm products might correct part of the unbalanced development.Cassava in the Atlantic Coast region is a small farm crop which faces severe market(ing) problems in the development process. Fresh cassava consumption, the traditional utilization, decreases because it has a high marketing margin, because it has to be bought on the day of consumption and because other products become more widely available.Two market improvement strategies for cassava are evaluated: improvement of the traditional fresh cassava market by means of improved storage; opening the market for dried cassava as an animal feed in order to replace sorghum. To study the impact of these strategies the role of cassava in the Atlantic Coast region is analyzed within a systems framework. The interactions that are found between production, marketing and consumption are strong. Cassava production will be stimulated by the price stabilization that the establishment of a cassava drying industry will cause. The improvement of cassava's storage characteristics will decrease marketing costs, increase consumer convenience and, therefore, stimulate cassava consumption.Because of the interactions encountered, the impact of cassava market improvements cannot be measured in the market alone. An analysis of the cassava system that integrates production, marketing and consumption is needed. The integrated analysis is made by means of a multi-market, multi-farm type simulation model. The model forecasts the impact of market improvement strategies given different assumptions on the development of the Atlantic Coast economy and on the cassava systems behavior. Cassava drying for animal feed is a strategy, which explicitly benefits cassava producers. Additionally Colombia could save on sorghum imports. Improvement of the fresh market would most benefit urban consumers. Considering the rural-urban migration problems of Latin America, cassava drying appears the most attractive strategy.Both market improvement strategies have very favorable rates of return. Market improvement projects might serve additionally as a diving board for further rural development efforts. Increased attention to the role of markets could contribute to fulfilling the goals of agricultural development and to balancing overall economic growth

Deep compartment models: A deep learning approach for the reliable prediction of time-series data in pharmacokinetic modeling

Nonlinear mixed effect (NLME) models are the gold standard for the analysis of patient response following drug exposure. However, these types of models are complex and time-consuming to develop. There is great interest in the adoption of machine-learning methods, but most implementations cannot be reliably extrapolated to treatment strategies outside of the training data. In order to solve this problem, we propose the deep compartment model (DCM), a combination of neural networks and ordinary differential equations. Using simulated datasets of different sizes, we show that our model remains accurate when training on small data sets. Furthermore, using a real-world data set of patients with hemophilia A receiving factor VIII concentrate while undergoing surgery, we show that our model more accurately predicts a priori drug concentrations compared to a previous NLME model. In addition, we show that our model correctly describes the changing drug concentration over time. By adopting pharmacokinetic principles, the DCM allows for simulation of different treatment strategies and enables therapeutic drug monitoring

Effects of Ambient Air Pollution on Hemostasis and Inflammation

BACKGROUND: Air pollution has consistently been associated with increased morbidity and mortality due to respiratory and cardiovascular disease. Underlying biological mechanisms are not entirely clear, and hemostasis and inflammation are suggested to be involved. OBJECTIVES: Our aim was to study the association of the variation in local concentrations of airborne particulate matter (PM) with aerodynamic diameter < 10 mu m, carbon monoxide, nitrogen monoxide, nitrogen dioxide, and ozone with platelet aggregation, thrombin generation, fibrinogen, and C-reactive protein (CRP) levels in healthy individuals. METHODS: From 40 healthy volunteers, we collected 13 consecutive blood samples within a 1-year period and measured light-transmittance platelet aggregometry, thrombin generation, fibrinogen, and CRP. We performed regression analysis using generalized additive models to study the association between the hemostatic and inflammatory variables, and local environmental concentrations 0 air pollutants for time lags within 24 hr before blood sampling or 24-96 hr before blood sampling. RESULTS: In general, air pollutants were associated with platelet aggregation [average, +8% per interquartile range (IQR), p < 0.01] and thrombin generation (average, +1% per IQR, p < 0.015). Platelet aggregation was not affected by in vitro incubation of plasma with PM. We observed no relationship between any of the air pollutants and fibrinogen or CRP levels. CONCLUSIONS:. Air pollution increased platelet aggregation as well as coagulation activity but had no clear effect on systemic inflammation. These prothrombotic effects may partly explain the relationship between air pollution and the risk of ischemic cardiovascular disease

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Galaxy Clusters Associated with Short GRBs. II. Predictions for the Rate of Short GRBs in Field and Cluster Early-Type Galaxies

We determine the relative rates of short GRBs in cluster and field early-type galaxies as a function of the age probability distribution of their progenitors, P(\tau) \propto \tau^n. This analysis takes advantage of the difference in the growth of stellar mass in clusters and in the field, which arises from the combined effects of the galaxy stellar mass function, the early-type fraction, and the dependence of star formation history on mass and environment. This approach complements the use of the early- to late-type host galaxy ratio, with the added benefit that the star formation histories of early-type galaxies are simpler than those of late-type galaxies, and any systematic differences between progenitors in early- and late-type galaxies are removed. We find that the ratio varies from R(cluster)/R(field) ~ 0.5 for n = -2 to ~ 3 for n = 2. Current observations indicate a ratio of about 2, corresponding to n ~ 0 - 1. This is similar to the value inferred from the ratio of short GRBs in early- and late-type hosts, but it differs from the value of n ~ -1 for NS binaries in the Milky Way. We stress that this general approach can be easily modified with improved knowledge of the effects of environment and mass on the build-up of stellar mass, as well as the effect of globular clusters on the short GRB rate. It can also be used to assess the age distribution of Type Ia supernova progenitors.Comment: ApJ accepted versio

Search for H→γγ produced in association with top quarks and constraints on the Yukawa coupling between the top quark and the Higgs boson using data taken at 7 TeV and 8 TeV with the ATLAS detector

A search is performed for Higgs bosons produced in association with top quarks using the diphoton decay mode of the Higgs boson. Selection requirements are optimized separately for leptonic and fully hadronic final states from the top quark decays. The dataset used corresponds to an integrated luminosity of 4.5 fb−14.5 fb−1 of proton–proton collisions at a center-of-mass energy of 7 TeV and 20.3 fb−1 at 8 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. No significant excess over the background prediction is observed and upper limits are set on the tt¯H production cross section. The observed exclusion upper limit at 95% confidence level is 6.7 times the predicted Standard Model cross section value. In addition, limits are set on the strength of the Yukawa coupling between the top quark and the Higgs boson, taking into account the dependence of the tt¯H and tH cross sections as well as the H→γγ branching fraction on the Yukawa coupling. Lower and upper limits at 95% confidence level are set at −1.3 and +8.0 times the Yukawa coupling strength in the Standard Model

Operation and performance of the ATLAS semiconductor tracker

The semiconductor tracker is a silicon microstrip detector forming part of the inner tracking system of the ATLAS experiment at the LHC. The operation and performance of the semiconductor tracker during the first years of LHC running are described. More than 99% of the detector modules were operational during this period, with an average intrinsic hit efficiency of (99.74±0.04)%. The evolution of the noise occupancy is discussed, and measurements of the Lorentz angle, δ-ray production and energy loss presented. The alignment of the detector is found to be stable at the few-micron level over long periods of time. Radiation damage measurements, which include the evolution of detector leakage currents, are found to be consistent with predictions and are used in the verification of radiation background simulations

Fiducial and differential cross sections of Higgs boson production measured in the four-lepton decay channel in pp collisions at √s = 8 TeV with the ATLAS detector

Measurements of fiducial and differential cross sections of Higgs boson production in the H→ZZ∗ → 4ℓ decay channel are presented. The cross sections are determined within a fiducial phase space and corrected for detection efficiency and resolution effects. They are based on 20.3 fb−¹ of pp collision data, produced at √s = 8 TeV centre-of-mass energy at the LHC and recorded by the ATLAS detector. The differential measurements are performed in bins of transverse momentum and rapidity of the four-lepton system, the invariant mass of the subleading lepton pair and the decay angle of the leading lepton pair with respect to the beam line in the four-lepton rest frame, as well as the number of jets and the transverse momentum of the leading jet. The measured cross sections are compared to selected theoretical calculations of the Standard Model expectations. No significant deviation from any of the tested predictions is found

Measurement of the cross section of high transverse momentum Z→bb̄ production in proton–proton collisions at √s = 8 TeV with the ATLAS detector

This Letter reports the observation of a high transverse momentum Z→bb̄ signal in proton–proton collisions at √s=8 TeV and the measurement of its production cross section. The data analysed were collected in 2012 with the ATLAS detector at the LHC and correspond to an integrated luminosity of 19.5 fb−¹. The Z→bb̄ decay is reconstructed from a pair of b -tagged jets, clustered with the anti-ktkt jet algorithm with R=0.4R=0.4, that have low angular separation and form a dijet with pT>200 GeVpT>200 GeV. The signal yield is extracted from a fit to the dijet invariant mass distribution, with the dominant, multi-jet background mass shape estimated by employing a fully data-driven technique that reduces the dependence of the analysis on simulation. The fiducial cross section is determined to be σZ→bb¯fid=2.02±0.20 (stat.) ±0.25 (syst.)±0.06 (lumi.) pb=2.02±0.33 pb, in good agreement with next-to-leading-order theoretical predictions