Community-Based Climate Change Adaptation Action Plans to Support Climate-Resilient Development in the Eastern African Highlands

Smallholder farmers in the Eastern African Highlands depend on rain-fed agriculture for their livelihoods. Climate adaptation and sustainable development goals must be targeted in an integrated way to better match farmers’ realities and address local priorities and vulnerabilities in these areas. To support climate-resilient development in the Eastern African Highlands, 224 local stakeholders were engaged in the development of community-based climate change adaptation action plans for the Jimma Highlands in Ethiopia, Taita Hills in Kenya and Mount Kilimanjaro in Tanzania. Participatory methods, high-resolution climate projections and the United Nations Development Programme’s (UNDP’s) guidelines were used in the design of these climate action plans with specific objectives to: 1) engage stakeholders to increase understanding of climate change impacts, adaptation options and their potential trade-offs, 2) build their capacities to design climate change adaptation projects, 3) empower stakeholders to identify existing vulnerabilities and enhance climate resilience and 4) strengthen networks to facilitate information access and sharing. Increased risk of water stress and reduction of agricultural productivity were the most frequently identified climate-change-induced problems in the three areas. The developed action plans target the underlying causes of these problems and describe sector-specific responses, activities, critical barriers and opportunities and support the National Adaptation Programmes of Action.Peer reviewe

International study to evaluate PCR methods for detection of Trypanosoma cruzi DNA in blood samples from Chagas disease patients

A century after its discovery, Chagas disease, caused by the parasite Trypanosoma cruzi, still represents a major neglected tropical threat. Accurate diagnostics tools as well as surrogate markers of parasitological response to treatment are research priorities in the field. The polymerase chain reaction (PCR) has been proposed as a sensitive laboratory tool for detection of T. cruzi infection and monitoring of parasitological treatment outcome. However, high variation in accuracy and lack of international quality controls has precluded reliable applications in the clinical practice and comparisons of data among cohorts and geographical regions. In an effort towards harmonization of PCR strategies, 26 expert laboratories from 16 countries evaluated their current PCR procedures against sets of control samples, composed by serial dilutions of T.cruzi DNA from culture stocks belonging to different lineages, human blood spiked with parasite cells and blood samples from Chagas disease patients. A high variability in sensitivities and specificities was found among the 48 reported PCR tests. Out of them, four tests with best performance were selected and further evaluated. This study represents a crucial first step towards device of a standardized operative procedure for T. cruzi PCR.Fil: Schijman, Alejandro G. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI-CONICET). Laboratorio de Biología Molecular de la Enfermedad de Chagas (LabMECh); Argentina.Fil: Bisio, Margarita. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI-CONICET). Laboratorio de Biología Molecular de la Enfermedad de Chagas (LabMECh); Argentina.Fil: Orellana, Liliana. Universidad de Buenos Aires. Instituto de Cálculo; Argentina.Fil: Sued, Mariela. Universidad de Buenos Aires. Instituto de Cálculo; Argentina.Fil: Duffy, Tomás. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI-CONICET). Laboratorio de Biología Molecular de la Enfermedad de Chagas (LabMECh); Argentina.Fil: Mejia Jaramillo, Ana M. Universidad de Antioquia. Grupo Chagas; Colombia.Fil: Cura, Carolina. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI-CONICET). Laboratorio de Biología Molecular de la Enfermedad de Chagas (LabMECh); Argentina.Fil: Auter, Frederic. French Blood Services; Francia.Fil: Veron, Vincent. Universidad de Parasitología. Laboratorio Hospitalario; Guayana Francesa.Fil: Qvarnstrom, Yvonne. Centers for Disease Control. Department of Parasitic Diseases; Estados Unidos.Fil: Deborggraeve, Stijn. Institute of Tropical Medicine; Bélgica.Fil: Hijar, Gisely. Instituto Nacional de Salud; Perú.Fil: Zulantay, Inés. Facultad de Medicina; Chile.Fil: Lucero, Raúl Horacio. Universidad Nacional del Nordeste; Argentina.Fil: Velázquez, Elsa. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Parasitología Dr. Mario Fatala Chaben; Argentina.Fil: Tellez, Tatiana. Universidad Mayor de San Simon. Centro Universitario de Medicina Tropical; Bolivia.Fil: Sanchez Leon, Zunilda. Universidad Nacional de Asunción. Instituto de Investigaciones en Ciencias de la Salud; Paraguay.Fil: Galvão, Lucia. Faculdade de Farmácia; Brasil.Fil: Nolder, Debbie. Hospital for Tropical Diseases. London School of Tropical Medicine and Hygiene Department of Clinical Parasitology; Reino Unido.Fil: Monje Rumi, María. Universidad Nacional de Salta. Laboratorio de Patología Experimental; Argentina.Fil: Levi, José E. Hospital Sirio Libanês. Blood Bank; Brasil.Fil: Ramirez, Juan D. Universidad de los Andes. Centro de Investigaciones en Microbiología y Parasitología Tropical; Colombia.Fil: Zorrilla, Pilar. Instituto Pasteur; Uruguay.Fil: Flores, María. Instituto de Salud Carlos III. Centro de Mahahonda; España.Fil: Jercic, Maria I. Instituto Nacional De Salud. Sección Parasitología; Chile.Fil: Crisante, Gladys. Universidad de los Andes. Centro de Investigaciones Parasitológicas J.F. Torrealba; Venezuela.Fil: Añez, Néstor. Universidad de los Andes. Centro de Investigaciones Parasitológicas J.F. Torrealba; Venezuela.Fil: De Castro, Ana M. Universidade Federal de Goiás. Instituto de Patologia Tropical e Saúde Pública (IPTSP); Brasil.Fil: Gonzalez, Clara I. Universidad Industrial de Santander. Grupo de Inmunología y Epidemiología Molecular (GIEM); Colombia.Fil: Acosta Viana, Karla. Universidad Autónoma de Yucatán. Departamento de Biomedicina de Enfermedades Infecciosas y Parasitarias Laboratorio de Biología Celular; México.Fil: Yachelini, Pedro. Universidad Católica de Santiago del Estero. Instituto de Biomedicina; Argentina.Fil: Torrico, Faustino. Universidad Mayor de San Simon. Centro Universitario de Medicina Tropical; Bolivia.Fil: Robello, Carlos. Instituto Pasteur; Uruguay.Fil: Diosque, Patricio. Universidad Nacional de Salta. Laboratorio de Patología Experimental; Argentina.Fil: Triana Chavez, Omar. Universidad de Antioquia. Grupo Chagas; Colombia.Fil: Aznar, Christine. Universidad de Parasitología. Laboratorio Hospitalario; Guayana Francesa.Fil: Russomando, Graciela. Universidad Nacional de Asunción. Instituto de Investigaciones en Ciencias de la Salud; Paraguay.Fil: Büscher, Philippe. Institute of Tropical Medicine; Bélgica.Fil: Assal, Azzedine. French Blood Services; Francia.Fil: Guhl, Felipe. Universidad de los Andes. Centro de Investigaciones en Microbiología y Parasitología Tropical; Colombia.Fil: Sosa Estani, Sergio. ANLIS Dr.C.G.Malbrán. Centro Nacional de Diagnóstico e Investigación en Endemo-Epidemias; Argentina.Fil: DaSilva, Alexandre. Centers for Disease Control. Department of Parasitic Diseases; Estados Unidos.Fil: Britto, Constança. Instituto Oswaldo Cruz/FIOCRUZ. Laboratório de Biologia Molecular e Doenças Endêmicas; Brasil.Fil: Luquetti, Alejandro. Laboratório de Pesquisa de Doença de Chagas; Brasil.Fil: Ladzins, Janis. World Health Organization (WHO). Special Programme for Research and Training in Tropical Diseases (TDR); Suiza

International Study to Evaluate PCR Methods for Detection of Trypanosoma cruzi DNA in Blood Samples from Chagas Disease Patients

A century after its discovery, Chagas disease, caused by the parasite Trypanosoma cruzi, still represents a major neglected tropical threat. Accurate diagnostics tools as well as surrogate markers of parasitological response to treatment are research priorities in the field. The polymerase chain reaction (PCR) has been proposed as a sensitive laboratory tool for detection of T. cruzi infection and monitoring of parasitological treatment outcome. However, high variation in accuracy and lack of international quality controls has precluded reliable applications in the clinical practice and comparisons of data among cohorts and geographical regions. In an effort towards harmonization of PCR strategies, 26 expert laboratories from 16 countries evaluated their current PCR procedures against sets of control samples, composed by serial dilutions of T.cruzi DNA from culture stocks belonging to different lineages, human blood spiked with parasite cells and blood samples from Chagas disease patients. A high variability in sensitivities and specificities was found among the 48 reported PCR tests. Out of them, four tests with best performance were selected and further evaluated. This study represents a crucial first step towards device of a standardized operative procedure for T. cruzi PCR

Benchmarking LHC background particle simulation with the CMS triple-GEM detector

In 2018, a system of large-size triple-GEM demonstrator chambers was installed in the CMS experiment at CERN\u27s Large Hadron Collider (LHC). The demonstrator\u27s design mimicks that of the final detector, installed for Run-3. A successful Monte Carlo (MC) simulation of the collision-induced background hit rate in this system in proton-proton collisions at 13 TeV is presented. The MC predictions are compared to CMS measurements recorded at an instantaneous luminosity of 1.5 ×10$^{34}$ cm$^{-2}$ s$^{-1}$. The simulation framework uses a combination of the FLUKA and GEANT4 packages. FLUKA simulates the radiation environment around the GE1/1 chambers. The particle flux by FLUKA covers energy spectra ranging from 10$^{-11}$ to 10$^{4}$ MeV for neutrons, 10$^{-3}$ to 10$^{4}$ MeV for γ\u27s, 10$^{-2}$ to 10$^{4}$ MeV for e$^{±}$, and 10$^{-1}$ to 10$^{4}$ MeV for charged hadrons. GEANT4 provides an estimate of the detector response (sensitivity) based on an accurate description of the detector geometry, the material composition, and the interaction of particles with the detector layers. The detector hit rate, as obtained from the simulation using FLUKA and GEANT4, is estimated as a function of the perpendicular distance from the beam line and agrees with data within the assigned uncertainties in the range 13.7-14.5%. This simulation framework can be used to obtain a reliable estimate of the background rates expected at the High Luminosity LHC

Triple-GEM discharge probability studies at CHARM: Simulations and experimental results

The CMS muon system in the region with 2.03<|η|<2.82 is characterized by a very harsh radiation environment which can generate hit rates up to 144 kHz/cm$^{2}$ and an integrated charge of 8 C/cm$^{2}$ over ten years of operation. In order to increase the detector performance and acceptance for physics events including muons, a new muon station (ME0) has been proposed for installation in that region. The technology proposed is Triple—Gas Electron Multiplier (Triple-GEM), which has already been qualified for the operation in the CMS muon system. However, an additional set of studies focused on the discharge probability is necessary for the ME0 station, because of the large radiation environment mentioned above. A test was carried out in 2017 at the Cern High energy AcceleRator Mixed (CHARM) facility, with the aim of giving an estimation of the discharge probability of Triple-GEM detectors in a very intense radiation field environment, similar to the one of the CMS muon system. A dedicated standalone Geant4 simulation was performed simultaneously, to evaluate the behavior expected in the detector exposed to the CHARM field. The geometry of the detector has been carefully reproduced, as well as the background field present in the facility. This paper presents the results obtained from the Geant4 simulation, in terms of sensitivity of the detector to the CHARM environment, together with the analysis of the energy deposited in the gaps and of the processes developed inside the detector. The discharge probability test performed at CHARM will be presented, with a complete discussion of the results obtained, which turn out to be consistent with measurements performed by other groups

Impact of magnetic field on the stability of the CMS GE1/1 GEM detector operation

The Gas Electron Multiplier (GEM) detectors of the GE1/1 station of the CMS experiment have been operated in the CMS magnetic field for the first time on the 7$^{th}$ of October 2021. During the magnetic field ramps, several discharge phenomena were observed, leading to instability in the GEM High Voltage (HV) power system. In order to reproduce the behavior, it was decided to conduct a dedicated test at the CERN North Area with the Goliath magnet, using four GE1/1 spare chambers. The test consisted in studying the characteristics of discharge events that occurred in different detector configurations and external conditions. Multiple magnetic field ramps were performed in sequence: patterns in the evolution of the discharge rates were observed with these data. The goal of this test is the understanding of the experimental conditions inducing discharges and short circuits in a GEM foil. The results of this test lead to the development of procedure for the optimal operation and performance of GEM detectors in the CMS experiment during the magnet ramps. Another important result is the estimation of the probability of short circuit generation, at 68 % confidence level, p$_{short}$$^{HV}$ $^{OFF}$ = 0.42$^{-0.35+0.94}$% with detector HV OFF and p$_{short}$$^{HV}$ $^{OFF}$ < 0.49% with the HV ON. These numbers are specific for the detectors used during this test, but they provide a first quantitative indication on the phenomenon, and a point of comparison for future studies adopting the same procedure

Detector Control System for the GE1/1 slice test

Gas Electron Multiplier (GEM) technology, in particular triple-GEM, was selected for the upgrade of the CMS endcap muon system following several years of intense effort on R&D. The triple-GEM chambers (GE1/1) are being installed at station 1 during the second long shutdown with the goal of reducing the Level-1 muon trigger rate and improving the tracking performance in the harsh radiation environment foreseen in the future LHC operation [1]. A first installation of a demonstrator system started at the beginning of 2017: 10 triple-GEM detectors were installed in the CMS muon system with the aim of gaining operational experience and demonstrating the integration of the GE1/1 system into the trigger. In this context, a dedicated Detector Control System (DCS) has been developed, to control and monitor the detectors installed and integrating them into the CMS operation. This paper presents the slice test DCS, describing in detail the different parts of the system and their implementation

Modeling the triple-GEM detector response to background particles for the CMS Experiment

An estimate of environmental background hit rate on triple-GEM chambers is performed using Monte Carlo (MC) simulation and compared to data taken by test chambers installed in the CMS experiment (GE1/1) during Run-2 at the Large Hadron Collider (LHC). The hit rate is measured using data collected with proton-proton collisions at 13 TeV and a luminosity of 1.5$\times10^{34}$ cm$^{-2}$ s$^{-1}$. The simulation framework uses a combination of the FLUKA and Geant4 packages to obtain the hit rate. FLUKA provides the radiation environment around the GE1/1 chambers, which is comprised of the particle flux with momentum direction and energy spectra ranging from $10^{-11}$ to $10^{4}$ MeV for neutrons, $10^{-3}$ to $10^{4}$ MeV for $\gamma$'s, $10^{-2}$ to $10^{4}$ MeV for $e^{\pm}$, and $10^{-1}$ to $10^{4}$ MeV for charged hadrons. Geant4 provides an estimate of detector response (sensitivity) based on an accurate description of detector geometry, material composition and interaction of particles with the various detector layers. The MC simulated hit rate is estimated as a function of the perpendicular distance from the beam line and agrees with data within the assigned uncertainties of 10-14.5%. This simulation framework can be used to obtain a reliable estimate of background rates expected at the High Luminosity LHC.Comment: 16 pages, 9 figures, 6 table

Molecular characterization of occult hepatitis B virus infection in patients with end-stage liver disease in Colombia.

ABSTARCT: Hepatitis B virus (HBV) occult infection (OBI) is a risk factor to be taken into account in transfusion, hemodialysis and organ transplantation. The aim of this study was to identify and characterize at the molecular level OBI cases in patients with end-stage liver disease. METHODS: Sixty-six liver samples were obtained from patients with diagnosis of end-stage liver disease submitted to liver transplantation in Medellin (North West, Colombia). Samples obtained from patients who were negative for the surface antigen of HBV (n = 50) were tested for viral DNA detection by nested PCR for ORFs S, C, and X and confirmed by Southern-Blot. OBI cases were analyzed by sequencing the viral genome to determine the genotype and mutations; additionally, viral genome integration events were examined by the Alu-PCR technique. RESULTS: In five cases out of 50 patients (10%) the criteria for OBI was confirmed. HBV genotype F (subgenotypes F1 and F3), genotype A and genotype D were characterized in liver samples. Three integration events in chromosomes 5q14.1, 16p13 and 20q12 affecting Receptor-type tyrosine-protein phosphatase T, Ras Protein Specific Guanine Nucleotide Releasing Factor 2, and the zinc finger 263 genes were identified in two OBI cases. Sequence analysis of the viral genome of the 5 OBI cases showed several punctual missense and nonsense mutations affecting ORFs S, P, Core and X. CONCLUSIONS: This is the first characterization of OBI in patients with end-stage liver disease in Colombia. The OBI cases were identified in patients with HCV infection or cryptogenic cirrhosis. The integration events (5q14.1, 16p13 and 20q12) described in this study have not been previously reported. Further studies are required to validate the role of mutations and integration events in OBI pathogenesis

CAD-based computer vision: the automatic generation of recognition stragtegies

Journal ArticleThree-dimensional model-based computer vision uses geometric models of objects and sensed data to recognize objects in a scene. Likewise, Computer Aided Design (CAD) systems are used to interactively generate three-dimensional models during these fields. Recently, the unification of CAD and vision systems has become the focus of research in the context of manufacturing automation. This paper explores the connection between CAD and computer vision. A method for the automatic generation of recognition strategies based on the geometric properties of shape has been devised and implemented. This uses a novel technique developed for quantifying the following properties of features which compose models used in computer vision: robustness, completeness, consistency, cost, and uniqueness. By utilizing this information, the automatic synthesis of a specialized recognition scheme, called a Strategy Tree, is accomplished. Strategy Trees describe, in a systematic and robust manner. the search process used for recognition and localization of particular objects in the given scene. They consist of selected features which satisfy system constraints and Corroborating Evidence Subtrees which are used in the formation of hypotheses. Verification techniques, used to substantiate or refute these hypotheses, are explored. Experiments utilizing 3-D data are presented