From the Visions of Saint Teresa of Jesus to the Voices of Schizophrenia

The life of Saint Teresa of Jesus, the most famous mystic of sixteenth-century Spain, was characterized by recurrent visions and states of ecstasy. In this paper, we examine social components related to Teresa’s personal crises and the historical conditions of her times, factors that must be taken into account to understand these unusual forms of experience and behavior. Many of these factors (e.g., increasing individualism and reflexivity) are precursors of the condition of modern times. Indeed, certain parallels can be observed between Saint Teresa and certain present-day psychopathological disorders. The analogy should not, however, be carried too far. Religion played a particularly crucial role in Teresa’s cultural context; as a result, it would be misleading to view her mystical experiences as resulting from a mental disorder

Variedades de la experiencia de sí mismo: una fenomenología comparativa de la melancolía, la manía y la esquizofrenia. Parte I

Este trabajo ofrece un estudio crítico de algunos trastornos de la experiencia de sí mismo [self experience], sutiles y a menudo pasados por alto, que pueden encontrarse en la esquizofrenia, la melancolía y la manía. El objetivo es mejorar la comprensión de las similitudes y las diferencias entre estos desórdenes. Aquí presentamos estudios clásicos y contemporáneos, en su mayoría de la tradición fenomenológica, que ilustramos con reportes de pacientes. Se consideran cambios experienciales en cinco dominios del “sí mismo” [selfhood] (siguiendo a Parnas et al., 2005): cognición, auto-conciencia, experiencias corporales, demarcación/transitivismo, y reorientación existencial. Vamos a discutir: I, las principales diferencias entre la esquizofrenia y los desordenes afectivos que involucran la experiencia propia; II, experiencias en las cuales estas condiciones, a pesar de las diferencias principales, se parecen entre sí; y III, sugerencias sobre cómo estas experiencias pueden, sin embargo, diferenciarse en un plano fenomenológico más sutil. Mientras que los pacientes afectivos pueden pasar por cambios significativos en su experiencia propia, su sentido subyacente de una individualidad mínima o básica (“ipseidad”) se mantiene intacto. En la esquizofrenia hay un trastorno del sí mismo [self] básico, y esto nos puede ayudar a dar cuenta de muchos de los trastornos característicos de este desorden

Uncertainty of ICESat-2 ATL06- and ATL08-Derived Snow Depths for Glacierized and Vegetated Mountain Regions

Seasonal snow melt dominates the hydrologic budget across a large portion of the globe. Snow accumulation and melt vary over a broad range of spatial scales, preventing accurate extrapolation of sparse in situ observations to watershed scales. The lidar onboard the Ice, Cloud, and land Elevation, Satellite (ICESat-2) was designed for precise mapping of ice sheets and sea ice, and here we assess the feasibility of snow depth-mapping using ICESat-2 data in more complex and rugged mountain landscapes. We explore the utility of ATL08 Land and Vegetation Height and ATL06 Land Ice Height differencing from reference elevation datasets in two end member study sites. We analyze ∼3 years of data for Reynolds Creek Experimental Watershed in Idaho\u27s Owyhee Mountains and Wolverine Glacier in southcentral Alaska\u27s Kenai Mountains. Our analysis reveals decimeter-scale uncertainties in derived snow depth and glacier mass balance at the watershed scale. Both accuracy and precision decrease as slope increases: the magnitudes of the median and median of the absolute deviation of elevation errors (MAD) vary from ∼0.2 m for slopes \u3c 5° to \u3e 1 m for slopes \u3e 20°. For glacierized regions, failure to account for intra- and inter-annual evolution of glacier surface elevations can strongly bias ATL06 elevations, resulting in under-estimation of the mass balance gradient with elevation. Based on these results, we conclude that ATL08 and ATL06 observations are best suited for characterization of watershed-scale snow depth and mass balance gradients over relatively shallow slopes with thick snowpacks. In these regions, ICESat-2 elevation residual-derived snow depth and mass balance transects can provide valuable watershed scale constraints on terrain parameter- and model-derived estimates of snow accumulation and melt

Holocene Deglaciation of Marie Byrd Land, West Antarctica

Surface exposure ages of glacial deposits in the Ford Ranges of western Marie Byrd Land indicate continuous thinning of the West Antarctic Ice Sheet by more than 700 meters near the coast throughout the past 10,000 years. Deglaciation lagged the disappearance of ice sheets in the Northern Hemisphere by thousands of years and may still be under way. These results provide further evidence that parts of the West Antarctic Ice Sheet are on a long-term trajectory of decline. West Antarctic melting contributed water to the oceans in the late Holocene and may continue to do so in the future

The ESCAPE project : Energy-efficient Scalable Algorithms for Weather Prediction at Exascale

In the simulation of complex multi-scale flows arising in weather and climate modelling, one of the biggest challenges is to satisfy strict service requirements in terms of time to solution and to satisfy budgetary constraints in terms of energy to solution, without compromising the accuracy and stability of the application. These simulations require algorithms that minimise the energy footprint along with the time required to produce a solution, maintain the physically required level of accuracy, are numerically stable, and are resilient in case of hardware failure. The European Centre for Medium-Range Weather Forecasts (ECMWF) led the ESCAPE (Energy-efficient Scalable Algorithms for Weather Prediction at Exascale) project, funded by Horizon 2020 (H2020) under the FET-HPC (Future and Emerging Technologies in High Performance Computing) initiative. The goal of ESCAPE was to develop a sustainable strategy to evolve weather and climate prediction models to next-generation computing technologies. The project partners incorporate the expertise of leading European regional forecasting consortia, university research, experienced high-performance computing centres, and hardware vendors. This paper presents an overview of the ESCAPE strategy: (i) identify domain-specific key algorithmic motifs in weather prediction and climate models (which we term Weather & Climate Dwarfs), (ii) categorise them in terms of computational and communication patterns while (iii) adapting them to different hardware architectures with alternative programming models, (iv) analyse the challenges in optimising, and (v) find alternative algorithms for the same scheme. The participating weather prediction models are the following: IFS (Integrated Forecasting System); ALARO, a combination of AROME (Application de la Recherche a l'Operationnel a Meso-Echelle) and ALADIN (Aire Limitee Adaptation Dynamique Developpement International); and COSMO-EULAG, a combination of COSMO (Consortium for Small-scale Modeling) and EULAG (Eulerian and semi-Lagrangian fluid solver). For many of the weather and climate dwarfs ESCAPE provides prototype implementations on different hardware architectures (mainly Intel Skylake CPUs, NVIDIA GPUs, Intel Xeon Phi, Optalysys optical processor) with different programming models. The spectral transform dwarf represents a detailed example of the co-design cycle of an ESCAPE dwarf. The dwarf concept has proven to be extremely useful for the rapid prototyping of alternative algorithms and their interaction with hardware; e.g. the use of a domain-specific language (DSL). Manual adaptations have led to substantial accelerations of key algorithms in numerical weather prediction (NWP) but are not a general recipe for the performance portability of complex NWP models. Existing DSLs are found to require further evolution but are promising tools for achieving the latter. Measurements of energy and time to solution suggest that a future focus needs to be on exploiting the simultaneous use of all available resources in hybrid CPU-GPU arrangements

Modulation of NKT Cell Development by B7-CD28 Interaction: An Expanding Horizon for Costimulation

It has been demonstrated that the development of NKT cells requires CD1d. The contribution of costimulatory molecules in this process has not been studied. Here we show that in mice with targeted mutations of B7-1/2 and CD28, the TCRβ+α-Galcer/CD1d + (iVα14 NKT) subset is significantly reduced in the thymus, spleen and liver. This is mainly due to decreased cell proliferation; although increased cell death in the thymi of CD28-deficient mice was also observed. Moreover, in the B7-1/2- and CD28-deficient mice, we found a decreased percentage of the CD4−NK1.1+ subset and a correspondingly increased portion of the CD4+NK1.1− subset. In addition, the mice with a targeted mutation of either B7 or CD28 had a reduced susceptibility to Con A induced hepatitis, which is known to be mediated by NKT cells. Our results demonstrate that the development, maturation and function of NKT cell are modulated by the costimulatory pathway and thus expand the horizon of costimulation into NKT, which is widely viewed as a bridge between innate and adaptive immunity. As such, costimulation may modulate all major branches of cell-mediated immunity, including T cells, NK cells and NKT cells

Assessment of the performance of CORDEX Regional Climate Models in Simulating Eastern Africa Rainfall

This study evaluates the ability of 10 regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in simulating the characteristics of rainfall patterns over eastern Africa. The seasonal climatology, annual rainfall cycles, and interannual variability of RCM output have been assessed over three homogeneous subregions against a number of observational datasets. The ability of the RCMs in simulating large-scale global climate forcing signals is further assessed by compositing the El Niño–Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events. It is found that most RCMs reasonably simulate the main features of the rainfall climatology over the three subregions and also reproduce the majority of the documented regional responses to ENSO and IOD forcings. At the same time the analysis shows significant biases in individual models depending on subregion and season; however, the ensemble mean has better agreement with observation than individual models. In general, the analysis herein demonstrates that the multimodel ensemble mean simulates eastern Africa rainfall adequately and can therefore be used for the assessment of future climate projections for the region

The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale

Abstract. In the simulation of complex multi-scale flows arising in weather and climate modelling, one of the biggest challenges is to satisfy strict service requirements in terms of time to solution and to satisfy budgetary constraints in terms of energy to solution, without compromising the accuracy and stability of the application. These simulations require algorithms that minimise the energy footprint along with the time required to produce a solution, maintain the physically required level of accuracy, are numerically stable, and are resilient in case of hardware failure. The European Centre for Medium-Range Weather Forecasts (ECMWF) led the ESCAPE (Energy-efficient Scalable Algorithms for Weather Prediction at Exascale) project, funded by Horizon 2020 (H2020) under the FET-HPC (Future and Emerging Technologies in High Performance Computing) initiative. The goal of ESCAPE was to develop a sustainable strategy to evolve weather and climate prediction models to next-generation computing technologies. The project partners incorporate the expertise of leading European regional forecasting consortia, university research, experienced high-performance computing centres, and hardware vendors. This paper presents an overview of the ESCAPE strategy: (i) identify domain-specific key algorithmic motifs in weather prediction and climate models (which we term Weather & Climate Dwarfs), (ii) categorise them in terms of computational and communication patterns while (iii) adapting them to different hardware architectures with alternative programming models, (iv) analyse the challenges in optimising, and (v) find alternative algorithms for the same scheme. The participating weather prediction models are the following: IFS (Integrated Forecasting System); ALARO, a combination of AROME (Application de la Recherche à l'Opérationnel à Meso-Echelle) and ALADIN (Aire Limitée Adaptation Dynamique Développement International); and COSMO–EULAG, a combination of COSMO (Consortium for Small-scale Modeling) and EULAG (Eulerian and semi-Lagrangian fluid solver). For many of the weather and climate dwarfs ESCAPE provides prototype implementations on different hardware architectures (mainly Intel Skylake CPUs, NVIDIA GPUs, Intel Xeon Phi, Optalysys optical processor) with different programming models. The spectral transform dwarf represents a detailed example of the co-design cycle of an ESCAPE dwarf. The dwarf concept has proven to be extremely useful for the rapid prototyping of alternative algorithms and their interaction with hardware; e.g. the use of a domain-specific language (DSL). Manual adaptations have led to substantial accelerations of key algorithms in numerical weather prediction (NWP) but are not a general recipe for the performance portability of complex NWP models. Existing DSLs are found to require further evolution but are promising tools for achieving the latter. Measurements of energy and time to solution suggest that a future focus needs to be on exploiting the simultaneous use of all available resources in hybrid CPU–GPU arrangements

Inward and Outward FDI Country Profiles, Second Edition

This second edition contains a series of 77 standardized country profiles dealing with the inward and outward foreign direct investment (FDI) performance of 40 economies. The profiles have been peer-reviewed by a global network of experts. The publication is intended to contribute to the analysis of trends in foreign direct investment and policy issues related to them. More specifically, the individual profiles discuss FDI trends and developments (country-level developments, the corporate players); effects of the recent global crises; and the policy scene. Each profile contains a standard set of tables, including on FDI stocks and flows, sectoral and geographical FDI distributions, the largest M&As and greenfield investments, the principal foreign affiliates (for inward FDI), and the principal multinational enterprises (for outward FDI). The standardized template used to produce the profiles allows cross-country comparisons. The volume is meant to be a reference tool for anyone interested in foreign direct investment