Perspectives on using remotely-sensed imagery in predictive veterinary epidemiology and global early warning systems

Recent disease epidemics and their spread around the world have illustrated the weaknesses of disease surveillance and early warning systems (EWS), both at national and international levels. These diseases continuously threaten the livestock sector on a worldwide basis, some with major public health impact. EWS and accurate forecasting of new outbreaks of epidemic livestock diseases that may also affect wildlife, and the capacity for spread of such diseases to new areas is an essential pre-requisite to their effective containment and control. Because both the geographical and seasonal distribution of many infectious diseases are linked to climate, the possibility of using climaterelated environmental factors as predictive indicators, in association with regular disease surveillance activities, has proven to be relevant when establishing EWS for climate-related diseases. This article reviews the growing importance of using geographical information systems in predictive veterinary epidemiology and its integration into EWS, with a special focus on Rift Valley fever. It shows that, once fully validated in a country or region, this technology appears highly valuable and could play an increasing role in forecasting major epidemics, providing lead time to national veterinary services to take action to mitigate the impact of the disease in a cost-effective manner

Perspectives on using remotely-sensed imagery in predictive veterinary epidemiology and global early warning systems

Recent disease epidemics and their spread around the world have illustrated the weaknesses of disease surveillance and early warning systems (EWS), both at national and international levels. These diseases continuously threaten the livestock sector on a worldwide basis, some with major public health impact. EWS and accurate forecasting of new outbreaks of epidemic livestock diseases that may also affect wildlife, and the capacity for spread of such diseases to new areas is an essential pre-requisite to their effective containment and control. Because both the geographical and seasonal distribution of many infectious diseases are linked to climate, the possibility of using climaterelated environmental factors as predictive indicators, in association with regular disease surveillance activities, has proven to be relevant when establishing EWS for climate-related diseases. This article reviews the growing importance of using geographical information systems in predictive veterinary epidemiology and its integration into EWS, with a special focus on Rift Valley fever. It shows that, once fully validated in a country or region, this technology appears highly valuable and could play an increasing role in forecasting major epidemics, providing lead time to national veterinary services to take action to mitigate the impact of the disease in a cost-effective manner

The impact of climate change on the epidemiology and control of Rift Valley fever

Climate change is likely to change the frequency of extreme weather events, such as tropical cyclones, floods, droughts and hurricanes, and may destabilize and weaken the ecosystem services upon which human society depends. Climate change is also expected to affect animal, human and plant health via indirect pathways: it is likely that the geography of infectious diseases and pests will be altered, including the distribution of vector-borne diseases, such as Rift Valley fever, yellow fever, malaria and dengue, which are highly sensitive to climatic conditions. Extreme weather events might then create the necessary conditions for Rift Valley fever to expand its geographical range northwards and cross the Mediterranean and Arabian seas, with an unexpected impact on the animal and human health of newly affected countries. Strengthening global, regional and national early warning systems is crucial, as are co-ordinated research programmes and subsequent prevention and intervention measures

The impact of climate change on the epidemiology and control of Rift Valley fever

Climate change is likely to change the frequency of extreme weather events, such as tropical cyclones, floods, droughts and hurricanes, and may destabilize and weaken the ecosystem services upon which human society depends. Climate change is also expected to affect animal, human and plant health via indirect pathways: it is likely that the geography of infectious diseases and pests will be altered, including the distribution of vector-borne diseases, such as Rift Valley fever, yellow fever, malaria and dengue, which are highly sensitive to climatic conditions. Extreme weather events might then create the necessary conditions for Rift Valley fever to expand its geographical range northwards and cross the Mediterranean and Arabian seas, with an unexpected impact on the animal and human health of newly affected countries. Strengthening global, regional and national early warning systems is crucial, as are co-ordinated research programmes and subsequent prevention and intervention measures

Dust Formation and Survival in Supernova Ejecta

The presence of dust at high redshift requires efficient condensation of grains in SN ejecta, in accordance with current theoretical models. Yet, observations of the few well studied SNe and SN remnants imply condensation efficiencies which are about two orders of magnitude smaller. Motivated by this tension, we have (i) revisited the model of Todini & Ferrara (2001) for dust formation in the ejecta of core collapse SNe and (ii) followed, for the first time, the evolution of newly condensed grains from the time of formation to their survival - through the passage of the reverse shock - in the SN remnant. We find that 0.1 - 0.6 M_sun of dust form in the ejecta of 12 - 40 M_sun stellar progenitors. Depending on the density of the surrounding ISM, between 2-20% of the initial dust mass survives the passage of the reverse shock, on time-scales of about 4-8 x 10^4 yr from the stellar explosion. Sputtering by the hot gas induces a shift of the dust size distribution towards smaller grains. The resulting dust extinction curve shows a good agreement with that derived by observations of a reddened QSO at z =6.2. Stochastic heating of small grains leads to a wide distribution of dust temperatures. This supports the idea that large amounts (~ 0.1 M_sun) of cold dust (T ~ 40K) can be present in SN remnants, without being in conflict with the observed IR emission.Comment: MNRAS accepte

Metacognitive training

Metacognition is usually defined as “thinking about thinking,” and it refers to knowledge about factors that influence task performance and knowledge about strategies. Moreover, it includes metacognitive regulation processes such as planning and monitoring task performance as well as evaluating the efficiency of these planning and monitoring processes. Good metacognitive abilities are essential for academic success, and good metacognitive skills support a number of other cognitive processes that are necessary to perform a specific task. Thus, training of metacognitive skills has become an important element of different training programs in various domains. In the present chapter, we will give an overview of recent advancements in the knowledge about metacognitive training in the context of mathematical skills, reading abilities, and regarding executive function training. Research from all three domains reveals promising results, indicating that the integration of metacognitive training into more conventional training programs leads to greater improvements than conventional training alone. Metacognitive training is effective for many different age groups, via different methods, and in different contexts. At the same time, however, there are still a number of open questions like the question of interindividual differences or the question of long-term effects, indicating that the field of metacognitive training research is likely to keep in the future

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Inclusive search for same-sign dilepton signatures in pp collisions at root s=7 TeV with the ATLAS detector

An inclusive search is presented for new physics in events with two isolated leptons (e or mu) having the same electric charge. The data are selected from events collected from p p collisions at root s = 7 TeV by the ATLAS detector and correspond to an integrated luminosity of 34 pb(-1). The spectra in dilepton invariant mass, missing transverse momentum and jet multiplicity are presented and compared to Standard Model predictions. In this event sample, no evidence is found for contributions beyond those of the Standard Model. Limits are set on the cross-section in a fiducial region for new sources of same-sign high-mass dilepton events in the ee, e mu and mu mu channels. Four models predicting same-sign dilepton signals are constrained: two descriptions of Majorana neutrinos, a cascade topology similar to supersymmetry or universal extra dimensions, and fourth generation d-type quarks. Assuming a new physics scale of 1 TeV, Majorana neutrinos produced by an effective operator V with masses below 460 GeV are excluded at 95% confidence level. A lower limit of 290 GeV is set at 95% confidence level on the mass of fourth generation d-type quarks

Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results