Energy loss due to defect formation from \u3csup\u3e206\u3c/sup\u3ePb recoils in SuperCDMS germanium detectors

The Super Cryogenic Dark Matter Search experiment (SuperCDMS) at the Soudan Underground Laboratory studied energy loss associated with Frenkel defect formation in germanium crystals at mK temperatures using in situ 210Pb sources. We examine the spectrum of 206Pb nuclear recoils near its expected 103 keV endpoint energy and determine an energy loss of (6.08±0.18) %, which we attribute to defect formation. From this result and using TRIM simulations, we extract the first experimentally determined average displacement threshold energy of (19.7+0.6−0.5) eV for germanium. This has implications for the analysis thresholds of future germanium-based dark matter searches

Projected sensitivity of the SuperCDMS SNOLAB experiment

SuperCDMS SNOLAB will be a next-generation experiment aimed at directly detecting low-mass (\u3c 10 GeV/c2) particles that may constitute dark matter by using cryogenic detectors of two types (HV and iZIP) and two target materials (germanium and silicon). The experiment is being designed with an initial sensitivity to nuclear recoil cross sections ~ 1 x 10−43 cm2 for a dark matter particle mass of 1 GeV/c2, and with capacity to continue exploration to both smaller masses and better sensitivities. The phonon sensitivity of the HV detectors will be sufficient to detect nuclear recoils from sub-GeV dark matter. A detailed calibration of the detector response to low energy recoils will be needed to optimize running conditions of the HV detectors and to interpret their data for dark matter searches. Low-activity shielding, and the depth of SNOLAB, will reduce most backgrounds, but cosmogenically produced 3H and naturally occurring 32Si will be present in the detectors at some level. Even if these backgrounds are x10 higher than expected, the science reach of the HV detectors would be over three orders of magnitude beyond current results for a dark matter mass of 1 GeV/c2. The iZIP detectors are relatively insensitive to variations in detector response and backgrounds, and will provide better sensitivity for dark matter particle masses (\u3e 5 GeV/c2). The mix of detector types (HV and iZIP), and targets (germanium and silicon), planned for the experiment, as well as flexibility in how the detectors are operated, will allow us to maximize the low-mass reach, and understand the backgrounds that the experiment will encounter. Upgrades to the experiment, perhaps with a variety of ultra-low-background cryogenic detectors, will extend dark matter sensitivity down to the neutrino floor , where coherent scatters of solar neutrinos become a limiting background

First Dark Matter Constraints from a SuperCDMS Single-Charge Sensitive Detector

We present the first limits on inelastic electron-scattering dark matter and dark photon absorption using a prototype SuperCDMS detector having a charge resolution of 0.1 electron-hole pairs (CDMS HVeV, a 0.93 gram CDMS HV device). These electron-recoil limits significantly improve experimental constraints on dark matter particles with masses as low as 1 MeV/c2. We demonstrate a sensitivity to dark photons competitive with other leading approaches but using substantially less exposure (0.49 gram days). These results demonstrate the scientific potential of phonon-mediated semiconductor detectors that are sensitive to single electronic excitations

Search for low-mass dark matter with CDMSlite using a profile likelihood fit

The Cryogenic Dark Matter Search low ionization threshold experiment (CDMSlite) searches for interactions between dark matter particles and germanium nuclei in cryogenic detectors. The experiment has achieved a low energy threshold with improved sensitivity to low-mass (/c2) dark matter particles. We present an analysis of the final CDMSlite data set, taken with a different detector than was used for the two previous CDMSlite data sets. This analysis includes a data salting method to protect against bias, improved noise discrimination, background modeling, and the use of profile likelihood methods to search for a dark matter signal in the presence of backgrounds. We achieve an energy threshold of 70 eV and significantly improve the sensitivity for dark matter particles with masses between 2.5 and 10 GeV/c2 compared to previous analyses. We set an upper limit on the dark matter-nucleon scattering cross section in germanium of 5.4×10−42 cm2 at 5 GeV/c2, a factor of ∼2.5 improvement over the previous CDMSlite result

Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects

Objective: Although lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification of clinically relevant imaging biomarkers. Using pooled data from 14 countries, the authors sought to identify general and substance-specific associations between dependence and regional brain volumes. Method: Brain structure was examined in a mega-analysis of previously published data pooled from 23 laboratories, including 3,240 individuals, 2,140 of whom had substance dependence on one of five substances: alcohol, nicotine, cocaine, methamphetamine, or cannabis. Subcortical volume and cortical thickness in regions defined by FreeSurfer were compared with nondependent control subjects when all sampled substance categories were combined, as well as separately, while controlling for age, sex, imaging site, and total intracranial volume. Because of extensive associations with alcohol dependence, a secondary contrast was also performed for dependence on all substances except alcohol. An optimized split-half strategy was used to assess the reliability of the findings. Results: Lower volume or thickness was observed in many brain regions in individuals with substance dependence. The greatest effects were associated with alcohol use disorder. A set of affected regions related to dependence in general, regardless of the substance, included the insula and the medial orbitofrontal cortex. Furthermore, a support vector machine multivariate classification of regional brain volumes successfully classified individuals with substance dependence on alcohol or nicotine relative to nondependent control subjects. Conclusions: The results indicate that dependence on a range of different substances shares a common neural substrate and that differential patterns of regional volume could serve as useful biomarkers of dependence on alcohol and nicotine

Cohort Profile: The Cohorts Consortium of Latin America and the Caribbean (CC-LAC)

Latin America and the Caribbean (LAC) are characterized by much diversity in terms of socio-economic status, ecol�ogy, environment, access to health care,1,2 as well as the fre�quency of risk factors for and prevalence or incidence of non-communicable diseases;3–7 importantly, these differen�ces are observed both between and within countries in LAC.8,9 LAC countries share a large burden of non�communicable (e.g. diabetes and hypertension) and cardio�vascular (e.g. ischaemic heart disease) diseases, with these conditions standing as the leading causes of morbidity, dis�ability and mortality in most of LAC.10–12 These epidemio�logical estimates—e.g. morbidity—cannot inform about risk factors or risk prediction, which are relevant to identify pre�vention avenues. Cohort studies, on the other hand, could provide this evidence. Pooled analysis, using data from mul�tiple cohort studies, have additional strengths such as in�creased statistical power and decreased statistical uncertainty.13 LAC cohort studies have been under-repre�sented,14 or not included at all,15–17 in international efforts aimed at pooling data from multiple cohort studies. We therefore set out to pool data from LAC cohorts to address research questions that individual cohort studies would not be able to answer. Drawing from previous successful regional enterprises (e.g. Asia Pacific Cohort Studies Collaboration),18,19 we established the Cohorts Consortium of Latin America and the Caribbean (CC-LAC). The main aim of the CC-LAC is to start a collaborative cohort data pooling in LAC to ex�amine the association between cardio-metabolic risk actors (e.g. blood pressure, glucose and lipids) and non�fatal and fatal cardiovascular outcomes (e.g. stroke or myocardial infarction). In so doing, we aim to provide re�gional risk estimates to inform disease burden metrics, as well as other ambitious projects including a cardiovascular risk score to strengthen cardiovascular prevention in LAC. Initial funding has been provided by a fellowship from the Wellcome Trust Centre for Global Health Research at Imperial College London (Strategic Award, Wellcome Trust–Imperial College Centre for Global Health Research, 100693/Z/12/Z). Additional funding is being provided by an International Training Fellowship from the Wellcome Trust (214185/Z/18/Z). At the time of writing, the daily operations and pooled database are hosted at Imperial College London, though a mid-term goal is to transfer this expertise and operations to LAC. The collaboration relies fundamentally on a strong regional network of health researchers and practitioners

Impact of common cardio-metabolic risk factors on fatal and non-fatal cardiovascular disease in Latin America and the Caribbean: an individual-level pooled analysis of 31 cohort studies

Background: Estimates of the burden of cardio-metabolic risk factors in Latin America and the Caribbean (LAC) rely on relative risks (RRs) from non-LAC countries. Whether these RRs apply to LAC remains un- known. Methods: We pooled LAC cohorts. We estimated RRs per unit of exposure to body mass index (BMI), systolic blood pressure (SBP), fasting plasma glucose (FPG), total cholesterol (TC) and non-HDL cholesterol on fatal (31 cohorts, n = 168,287) and non-fatal (13 cohorts, n = 27,554) cardiovascular diseases, adjusting for regression dilution bias. We used these RRs and national data on mean risk factor levels to estimate the number of cardiovascular deaths attributable to non-optimal levels of each risk factor. Results: Our RRs for SBP, FPG and TC were like those observed in cohorts conducted in high-income countries; however, for BMI, our RRs were consistently smaller in people below 75 years of age. Across risk factors, we observed smaller RRs among older ages. Non-optimal SBP was responsible for the largest number of attributable cardiovascular deaths ranging from 38 per 10 0,0 0 0 women and 54 men in Peru, to 261 (Dominica, women) and 282 (Guyana, men). For non-HDL cholesterol, the lowest attributable rate was for women in Peru (21) and men in Guatemala (25), and the largest in men (158) and women (142) from Guyana. Interpretation: RRs for BMI from studies conducted in high-income countries may overestimate disease burden metrics in LAC; conversely, RRs for SBP, FPG and TC from LAC cohorts are similar to those esti- mated from cohorts in high-income countries

Movilidad urbana sostenible

Trabajo presentado como resultado del Curso CELFI. Movilidad Sostenible. Hacia un Cambio de Paradigma. Córdoba, Argentina. 2017Córdoba tiene baja densidad edilicia y poblacional, es una ciudad difusa con una extensión territorial que ocupa aproximadamente el 70% de la superficie municipal. Con polaridades domésticas y sociales fuertemente marcadas y aisladas unas de otras, Córdoba genera áreas mayormente mono-funcionales y segregadas (Figura 1). En paralelo, el deficiente sistema estructural de movilidad se orienta al enfoque de demanda, aunque sin satisfacer la demanda existente. Se desarrollan así vaciamientos de vida de los espacios urbanos (calles, parques, espacios públicos, etc.) lo que genera además inaccesibilidad social, económica, cultural, educativa, físico-natural y de transporte público entre otras.La Ciudad Universitaria (CU) replica en menor escala, en una porción del territorio, los problemas detectados en la ciudad, ya que se trata de otra zona mono-funcional- estacional que funciona ligada a las actividades netamente académicas.En el imaginario colectivo este espacio es un gran núcleo verde urbano que se complementa con dos parques de distintas escalas, y con usos diferenciados. Uno de ellos, el Parque Sarmiento y el otro Parque de Las Tejas. A pesar de ello CU, no conecta estos espacios, y no se relaciona de manera eficiente con ellosFil: Botta, Pablo. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Castro Morales, Betty. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: González Alvo, Inés. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Menini, Sheila E. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Rodas, Ana P. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Schwarz, Yanelle. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Sosa, Beatríz S. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Benito, María A. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Chein, Aylen. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Destefanis Natalia. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Destefanis, Natalia. Universidad nacional de Córdoba. Facultad de Arquitectura, Urbanismo y Diseño; ArgentinaFil: Favaro, Micaela. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Foschiatti, Fabiola. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Santiago, Jaquelin. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Testori, Carla. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Dalvit, Vanina Vanina. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Dalvit, Emilse Vanina. universidad Nacional de Córdoba. Facultad de Arquitectura, Urbanismo y Diseño; ArgentinaFil: Armayor, Eliana. Universidad Nacional de Córdoba. Secretaría de Ciencia y Tecnología; ArgentinaFil: Armayor, Eliana. Universidad Nacional de Córdoba. Facultad de Arquitectura, Urbanismo y Diseño; ArgentinaOtras Ingeniería Civi

Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects.

ObjectiveAlthough lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification of clinically relevant imaging biomarkers. Using pooled data from 14 countries, the authors sought to identify general and substance-specific associations between dependence and regional brain volumes.MethodBrain structure was examined in a mega-analysis of previously published data pooled from 23 laboratories, including 3,240 individuals, 2,140 of whom had substance dependence on one of five substances: alcohol, nicotine, cocaine, methamphetamine, or cannabis. Subcortical volume and cortical thickness in regions defined by FreeSurfer were compared with nondependent control subjects when all sampled substance categories were combined, as well as separately, while controlling for age, sex, imaging site, and total intracranial volume. Because of extensive associations with alcohol dependence, a secondary contrast was also performed for dependence on all substances except alcohol. An optimized split-half strategy was used to assess the reliability of the findings.ResultsLower volume or thickness was observed in many brain regions in individuals with substance dependence. The greatest effects were associated with alcohol use disorder. A set of affected regions related to dependence in general, regardless of the substance, included the insula and the medial orbitofrontal cortex. Furthermore, a support vector machine multivariate classification of regional brain volumes successfully classified individuals with substance dependence on alcohol or nicotine relative to nondependent control subjects.ConclusionsThe results indicate that dependence on a range of different substances shares a common neural substrate and that differential patterns of regional volume could serve as useful biomarkers of dependence on alcohol and nicotine