Validation and analysis of MOPITT CO observations of the Amazon Basin

We analyze satellite retrievals of carbon monoxide from the MOPITT (Measurements of Pollution in the Troposphere) instrument over the Amazon Basin, focusing on the MOPITT Version 6 "multispectral" retrieval product (exploiting both thermal-infrared and near-infrared channels). Validation results based on in situ vertical profiles measured between 2010 and 2013 are presented for four sites in the Amazon Basin. Results indicate a significant negative bias in retrieved lower-tropospheric CO concentrations. The possible influence of smoke aerosol as a source of retrieval bias is investigated using collocated Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) measurements at two sites but does not appear to be significant. Finally, we exploit the MOPITT record to analyze both the mean annual cycle and the interannual variability of CO over the Amazon Basin since 2002

Determination of Region of Influence Obtained by Aircraft Vertical Profiles Using the Density of Trajectories from the HYSPLIT Model

Aircraft atmospheric profiling is a valuable technique for determining greenhouse gas fluxes at regional scales (104–106 km2). Here, we describe a new, simple method for estimating the surface influence of air samples that uses backward trajectories based on the Lagrangian model Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT). We determined “regions of influence” on a quarterly basis between 2010 and 2018 for four aircraft vertical profile sites: SAN and ALF in the eastern Amazon, and RBA and TAB or TEF in the western Amazon. We evaluated regions of influence in terms of their relative sensitivity to areas inside and outside the Amazon and their total area inside the Amazon. Regions of influence varied by quarter and less so by year. In the first and fourth quarters, the contribution of the region of influence inside the Amazon was 83–93% for all sites, while in the second and third quarters, it was 57–75%. The interquarter differences are more evident in the eastern than in the western Amazon. Our analysis indicates that atmospheric profiles from the western sites are sensitive to 42–52.2% of the Amazon. In contrast, eastern Amazon sites are sensitive to only 10.9–25.3%. These results may help to spatially resolve the response of greenhouse gas emissions to climate variability over Amazon

A Randomized Double-Blind Study Comparing the Efficacy and Safety of Orlistat Versus Placebo in Obese Patients with Mild to Moderate Hypercholesterolemia

INTRODUCTION: Obesity is a chronic disease and a serious health problem that leads to increased prevalence of diabetes, hypertension, dyslipidemia and gallbladder disease. OBJECTIVE: To evaluate the efficacy of orlistat for weight loss and improved lipid profile compared to placebo in obese patients with hypercholesterolemia, treated over a period of 6 months. METHODOLOGY: In a 6-month, multicenter (10 centers in Portugal), double-blind, parallel, placebo-controlled study, 166 patients, aged 18-65 years, body mass index (BMI) > or = 27 kg/m2, LDL cholesterol > 155 mg/dl, were randomized to a reduced calorie diet (600 kcal/day deficit) plus orlistat three times a day or placebo. Exclusion criteria included triglycerides > 400 mg/dl, severe cardiovascular disease, uncontrolled hypertension, type 1 or 2 diabetes under pharmacological treatment, and gastrointestinal or pancreatic disease. RESULTS: The mean difference in weight from baseline was 5.9% (5.6 kg) in the orlistat group vs. 2.3% (2.2 kg) in the placebo group. In the orlistat group 49% of patients achieved 5-10% weight loss and 8.8% achieved > 10%. The orlistat group showed a significant reduction in total and LDL cholesterol, with similar changes for HDL in both treatment groups. The frequency of gastrointestinal adverse events was slightly higher in the orlistat group than in the placebo group, leading to discontinuation in 7 patients. CONCLUSION: Treatment with orlistat plus a reduced calorie diet for 6 months achieved significant reductions in weight, BMI and lipid parameters

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.This work was co-financed by FCT/MEC and FEDER under Program PT2020 (Project UID/EQU/50020/2013); by Fundacao para a Ciencia e Tecnologia under the strategic funding of UID/BIO/04469/2013 unit; and by Project POCTEP through Project RED/AGROTEC-Experimentation network and transfer for development of agricultural and agro industrial sectors between Spain and Portugal

Developing nanotechnology in Latin America

This article investigates the development of nanotechnology in Latin America with a particular focus on Argentina, Brazil, Chile, and Uruguay. Based on data for nanotechnology research publications and patents and suggesting a framework for analyzing the development of R&D networks, we identify three potential strategies of nanotechnology research collaboration. Then, we seek to identify the balance of emphasis upon each of the three strategies by mapping the current research profile of those four countries. In general, we find that they are implementing policies and programs to develop nanotechnologies but differ in their collaboration strategies, institutional involvement, and level of development. On the other hand, we find that they coincide in having a modest industry participation in research and a low level of commercialization of nanotechnologies

Sixteen years of MOPITT satellite data strongly constrain Amazon CO fire emissions

Despite the consensus on the overall downward trend in Amazon forest loss in the previous decade, estimates of yearly carbon emissions from deforestation still vary widely. Estimated carbon emissions are currently often based on data from local logging activity reports, changes in remotely sensed biomass, and remote detection of fire hotspots and burned area. Here, we use 16 years of satellite-derived carbon monoxide (CO) columns to constrain fire CO emissions from the Amazon Basin between 2003 and 2018. Through data assimilation, we produce 3 d average maps of fire CO emissions over the Amazon, which we verified to be consistent with a long-term monitoring programme of aircraft CO profiles over five sites in the Amazon. Our new product independently confirms a long-term decrease of 54 % in deforestation-related CO emissions over the study period. Interannual variability is large, with known anomalously dry years showing a more than 4-fold increase in basin-wide fire emissions relative to wet years. At the level of individual Brazilian states, we find that both soil moisture anomalies and human ignitions determine fire activity, suggesting that future carbon release from fires depends on drought intensity as much as on continued forest protection. Our study shows that the atmospheric composition perspective on deforestation is a valuable additional monitoring instrument that complements existing bottom-up and remote sensing methods for land-use change. Extension of such a perspective to an operational framework is timely considering the observed increased fire intensity in the Amazon Basin between 2019 and 2021

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration