Fienup Algorithm With Sparsity Constraints: Application to Frequency-Domain Optical-Coherence Tomography

We address the problem of reconstructing a sparse signal from its DFT magnitude. We refer to this problem as the sparse phase retrieval (SPR) problem, which finds applications in tomography, digital holography, electron microscopy, etc. We develop a Fienup-type iterative algorithm, referred to as the Max-K algorithm, to enforce sparsity and successively refine the estimate of phase. We show that the Max-K algorithm possesses Cauchy convergence properties under certain conditions, that is, the MSE of reconstruction does not increase with iterations. We also formulate the problem of SPR as a feasibility problem, where the goal is to find a signal that is sparse in a known basis and whose Fourier transform magnitude is consistent with the measurement. Subsequently, we interpret the Max-K algorithm as alternating projections onto the object-domain and measurement-domain constraint sets and generalize it to a parameterized relaxation, known as the relaxed averaged alternating reflections (RAAR) algorithm. On the application front, we work with measurements acquired using a frequency-domain optical-coherence tomography (FDOCT) experimental setup. Experimental results on measured data show that the proposed algorithms exhibit good reconstruction performance compared with the direct inversion technique, homomorphic technique, and the classical Fienup algorithm without sparsity constraint; specifically, the autocorrelation artifacts and background noise are suppressed to a significant extent. We also demonstrate that the RAAR algorithm offers a broader framework for FDOCT reconstruction, of which the direct inversion technique and the proposed Max-K algorithm become special instances corresponding to specific values of the relaxation parameter.

Development and Evaluation of Statistical Downscaling Models for Monthly Precipitation

Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.

Return levels of hydrologic droughts under climate change

Developments in the statistical extreme value theory, which allow non-stationary modeling of changes in the frequency and severity of extremes, are explored to analyze changes in return levels of droughts for the Colorado River. The transient future return levels (conditional quantiles) derived from regional drought projections using appropriate extreme value models, are compared with those from observed naturalized streamflows. The time of detection is computed as the time at which significant differences exist between the observed and future extreme drought levels, accounting for the uncertainties in their estimates. Projections from multiple climate model-scenario combinations are considered; no uniform pattern of changes in drought quantiles is observed across all the projections. While some projections indicate shifting to another stationary regime, for many projections which are found to be non-stationary, detection of change in tail quantiles of droughts occurs within the 21st century with no unanimity in the time of detection. Earlier detection is observed in droughts levels of higher probability of exceedance. (C) 2014 Elsevier Ltd. All rights reserved.

Detection of a quantum particle on a lattice under repeated projective measurements

We consider a quantum particle, moving on a lattice with a tight-binding Hamiltonian, which is subjected to measurements to detect its arrival at a particular chosen set of sites. The projective measurements are made at regular time intervals tau, and we consider the evolution of the wave function until the time a detection occurs. We study the probabilities of its first detection at some time and, conversely, the probability of it not being detected (i.e., surviving) up to that time. We propose a general perturbative approach for understanding the dynamics which maps the evolution operator, which consists of unitary transformations followed by projections, to one described by a non-Hermitian Hamiltonian. For some examples of a particle moving on one-and two-dimensional lattices with one or more detection sites, we use this approach to find exact expressions for the survival probability and find excellent agreement with direct numerical results. A mean-field model with hopping between all pairs of sites and detection at one site is solved exactly. For the one-and two-dimensional systems, the survival probability is shown to have a power-law decay with time, where the power depends on the initial position of the particle. Finally, we show an interesting and nontrivial connection between the dynamics of the particle in our model and the evolution of a particle under a non-Hermitian Hamiltonian with a large absorbing potential at some sites.

Regional hydrological impacts of climate change: implications for water management in India

Climate change is most likely to introduce an additional stress to already stressed water systems in developing countries. Climate change is inherently linked with the hydrological cycle and is expected to cause significant alterations in regional water resources systems necessitating measures for adaptation and mitigation. Increasing temperatures, for example, are likely to change precipitation patterns resulting in alterations of regional water availability, evapotranspirative water demand of crops and vegetation, extremes of floods and droughts, and water quality. A comprehensive assessment of regional hydrological impacts of climate change is thus necessary. Global climate model simulations provide future projections of the climate system taking into consideration changes in external forcings, such as atmospheric carbon-dioxide and aerosols, especially those resulting from anthropogenic emissions. However, such simulations are typically run at a coarse scale, and are not equipped to reproduce regional hydrological processes. This paper summarizes recent research on the assessment of climate change impacts on regional hydrology, addressing the scale and physical processes mismatch issues. Particular attention is given to changes in water availability, irrigation demands and water quality. This paper also includes description of the methodologies developed to address uncertainties in the projections resulting from incomplete knowledge about future evolution of the human-induced emissions and from using multiple climate models. Approaches for investigating possible causes of historically observed changes in regional hydrological variables are also discussed. Illustrations of all the above-mentioned methods are provided for Indian regions with a view to specifically aiding water management in India.

Bioenergy and climate change mitigation: an assessment

Bioenergy deployment offers significant potential for climate change mitigation, but also carries considerable risks. In this review, we bring together perspectives of various communities involved in the research and regulation of bioenergy deployment in the context of climate change mitigation: Land-use and energy experts, land-use and integrated assessment modelers, human geographers, ecosystem researchers, climate scientists and two different strands of life-cycle assessment experts. We summarize technological options, outline the state-of-the-art knowledge on various climate effects, provide an update on estimates of technical resource potential and comprehensively identify sustainability effects. Cellulosic feedstocks, increased end-use efficiency, improved land carbon-stock management and residue use, and, when fully developed, BECCS appear as the most promising options, depending on development costs, implementation, learning, and risk management. Combined heat and power, efficient biomass cookstoves and small-scale power generation for rural areas can help to promote energy access and sustainable development, along with reduced emissions. We estimate the sustainable technical potential as up to 100EJ: high agreement; 100-300EJ: medium agreement; above 300EJ: low agreement. Stabilization scenarios indicate that bioenergy may supply from 10 to 245EJyr(-1) to global primary energy supply by 2050. Models indicate that, if technological and governance preconditions are met, large-scale deployment (>200EJ), together with BECCS, could help to keep global warming below 2 degrees degrees of preindustrial levels; but such high deployment of land-intensive bioenergy feedstocks could also lead to detrimental climate effects, negatively impact ecosystems, biodiversity and livelihoods. The integration of bioenergy systems into agriculture and forest landscapes can improve land and water use efficiency and help address concerns about environmental impacts. We conclude that the high variability in pathways, uncertainties in technological development and ambiguity in political decision render forecasts on deployment levels and climate effects very difficult. However, uncertainty about projections should not preclude pursuing beneficial bioenergy options.

Minimization Problems Based on Relative alpha-Entropy I: Forward Projection

Minimization problems with respect to a one-parameter family of generalized relative entropies are studied. These relative entropies, which we term relative alpha-entropies (denoted I-alpha), arise as redundancies under mismatched compression when cumulants of compressed lengths are considered instead of expected compressed lengths. These parametric relative entropies are a generalization of the usual relative entropy (Kullback-Leibler divergence). Just like relative entropy, these relative alpha-entropies behave like squared Euclidean distance and satisfy the Pythagorean property. Minimizers of these relative alpha-entropies on closed and convex sets are shown to exist. Such minimizations generalize the maximum Renyi or Tsallis entropy principle. The minimizing probability distribution (termed forward I-alpha-projection) for a linear family is shown to obey a power-law. Other results in connection with statistical inference, namely subspace transitivity and iterated projections, are also established. In a companion paper, a related minimization problem of interest in robust statistics that leads to a reverse I-alpha-projection is studied.

Minimization Problems Based on Relative alpha-Entropy II: Reverse Projection

In part I of this two-part work, certain minimization problems based on a parametric family of relative entropies (denoted I-alpha) were studied. Such minimizers were called forward I-alpha-projections. Here, a complementary class of minimization problems leading to the so-called reverse I-alpha-projections are studied. Reverse I-alpha-projections, particularly on log-convex or power-law families, are of interest in robust estimation problems (alpha > 1) and in constrained compression settings (alpha < 1). Orthogonality of the power-law family with an associated linear family is first established and is then exploited to turn a reverse I-alpha-projection into a forward I-alpha-projection. The transformed problem is a simpler quasi-convex minimization subject to linear constraints.

Isolating the impacts of land use and climate change on streamflow

Quantifying the isolated and integrated impacts of land use (LU) and climate change on streamflow is challenging as well as crucial to optimally manage water resources in river basins. This paper presents a simple hydrologic modeling-based approach to segregate the impacts of land use and climate change on the streamflow of a river basin. The upper Ganga basin (UGB) in India is selected as the case study to carry out the analysis. Streamflow in the river basin is modeled using a calibrated variable infiltration capacity (VIC) hydrologic model. The approach involves development of three scenarios to understand the influence of land use and climate on streamflow. The first scenario assesses the sensitivity of streamflow to land use changes under invariant climate. The second scenario determines the change in streamflow due to change in climate assuming constant land use. The third scenario estimates the combined effect of changing land use and climate over the streamflow of the basin. Based on the results obtained from the three scenarios, quantification of isolated impacts of land use and climate change on streamflow is addressed. Future projections of climate are obtained from dynamically downscaled simulations of six general circulation models (GCMs) available from the Coordinated Regional Downscaling Experiment (CORDEX) project. Uncertainties associated with the GCMs and emission scenarios are quantified in the analysis. Results for the case study indicate that streamflow is highly sensitive to change in urban areas and moderately sensitive to change in cropland areas. However, variations in streamflow generally reproduce the variations in precipitation. The combined effect of land use and climate on streamflow is observed to be more pronounced compared to their individual impacts in the basin. It is observed from the isolated effects of land use and climate change that climate has a more dominant impact on streamflow in the region. The approach proposed in this paper is applicable to any river basin to isolate the impacts of land use change and climate change on the streamflow.

Projected climate change impacts on vegetation distribution over Kashmir Himalayas

Despite high vulnerability, the impact of climate change on Himalayan ecosystem has not been properly investigated, primarily due to the inadequacy of observed data and the complex topography. In this study, we mapped the current vegetation distribution in Kashmir Himalayas from NOAA AVHRR and projected it under A1B SRES, RCP-4.5 and RCP-8.5 climate scenarios using the vegetation dynamics model-IBIS at a spatial resolution of 0.5A degrees. The distribution of vegetation under the changing climate was simulated for the 21st century. Climate change projections from the PRECIS experiment using the HADRM3 model, for the Kashmir region, were validated using the observed climate data from two observatories. Both the observed as well as the projected climate data showed statistically significant trends. IBIS was validated for Kashmir Himalayas by comparing the simulated vegetation distribution with the observed distribution. The baseline simulated scenario of vegetation (1960-1990), showed 87.15 % agreement with the observed vegetation distribution, thereby increasing the credibility of the projected vegetation distribution under the changing climate over the region. According to the model projections, grasslands and tropical deciduous forests in the region would be severely affected while as savannah, shrubland, temperate evergreen broadleaf forest, boreal evergreen forest and mixed forest types would colonize the area currently under the cold desert/rock/ice land cover types. The model predicted that a substantial area of land, presently under the permanent snow and ice cover, would disappear by the end of the century which might severely impact stream flows, agriculture productivity and biodiversity in the region.

El Matadero de Esteban Echeverría, o la inauguración de los mataderos

Resumen: En el presente texto retomamos y reconocemos el carácter de ‘texto fundante’ que El Matadero de Esteban Echeverría tiene en nuestra cultura argentina. Analizamos lo enraizado del texto conectándolo hacia atrás, con los orígenes de la gauchesca, y hacia adelante, con su culminación y con sus proyecciones, incluso en diversas disciplinas. Luego podemos centrarnos en el tema de la violencia como recurrente no solo literario, y precisar el sentido en que la tomamos. Sostenemos que la violencia de El Matadero ya estaba presente, de manera velada, en otras obras de Echeverría; no tanto por su tematización, sino porque figurativiza, de manera muy acorde con la ideología románticas, razón y corazón, considerado éste no como exclusiva sede de sentimientos, sino como víscera, y de allí sus equivalentes, como el estómago y el matambre. Esta parte visceral no accede a mayor formulación, porque no entra en el programa de la estética en boga. Desde este punto de vista, releo las quejas debidas al sufrimiento del corazón, y entiendo el llanto y el descontento de otro modo. Hay lamento porque nada, al menos en el terreno literario, brinda salida a ese fondo vivo, no esquemático y que le resulta abyecto, porque encierra un modo y un contenido que no puede reconocer como propios. Asociado con esta cara puesta en sombra, inopinadamente, El matadero vuelve a ser texto fundante, pero de otra parte de la literatura argentina: de lo marginal, que no puede sumarse a proyectos, y que muy pocos dicen.

Las Prophetiae Merlini de Geoffrey de Monmouth en los Baladros castellanos: estado de la cuestión

Resumen: La Historia regum Britanniae (circa 1139) del obispo galés Geoffrey de Monmouth, texto destacado en el corpus latino medieval a causa de sus proyecciones tanto historiográficas como ficcionales, tiene como objeto referir los actos de todos los monarcas célticos de la Gran Bretaña anteriores a la conquista germánica. En este propósito, sus capítulos 112 a 117 obran como una mise en abîme puesto que las Prophetiae Merlini que allí se leen, atribuidas al famoso mago pero inspiradas en la literatura apocalíptica vétero y neotestamentaria, reproducen proféticamente las grandes líneas de contenido de la propia crónica, e incluso anticipan la restauración definitiva de los celtas derrotados. Aunque Wace, Chrétien de Troyes y la tradición romancística francesa posterior, deudora de la Historia en muchos puntos, desecharon el texto a causa de su agudo hermetismo, el mismo sí se difundió por el continente y reapareció asombrosamente interpolado, en versión castellana, dentro de dos tardíos ejemplares del género caballeresco hispánico, el Baladro del sabio Merlín con sus profecías (Burgos, 1498) y la primera parte de la Demanda del santo Grial (Sevilla, 1535). La presente comunicación tiene como objetivos reseñar los actuales conocimientos de la crítica acerca de esta versión castellana de las Prophetiae y señalar los problemas aún pendientes de resolución; serán consideradas las contribuciones fundamentales relativas al original latino y, también, a las versiones francesas conservadas, dada la posibilidad de que nuestra traducción tenga una fuente gala

Body and Grotesque as Self-Disruption in Kerstin Hensel’s Gothic East(ern) German Novel Lärchenau (2008)

[EN] By analysing the novel Lärchenau and its -to a certain point- gothic features, this article interprets the elaboration of body in this novel as a site of the expression of power, but also as an alternative language. The grotesque dimension and the representation of the bodily numbness and pain as projections of historical awareness are key elements for the interpretation of Lärchenau in the context of Post-Unification Germany.

Strategies and options for increasing and sustaining fisheries and aquaculture production to benefit poorer households in Asia

The last three decades have witnessed dramatic changes in the structure of supply and demand for fish, especially in Asia. This WorldFish research study sponsored by the Asian Development Bank focussed on nine developing countries – Bangladesh, China, India, Indonesia, Malaysia, the Philippines, Sri Lanka, Thailand, and Vietnam, all active players in the transformation of global fish supply and demand. The study, broken into five components and reported here, considered: 1) the profile of key aquaculture technologies and fishing practices; 2) analysis of policies, institutions and support services; 3) socioeconomic profile of major stakeholders in the fisheries sector; 4) projections of fish demand and supply in the nine Asian countries; and 5) formulation of national action plans based on the findings and recommendations of the study.

Diagnosis and the management constituency of small-scale fisheries

Diagnosis and adaptive management can help improve the ability of small-scale fisheries (SSF) in the developing world to better cope with and adapt to both external drivers and internal sources of uncertainty. This paper presents a framework for diagnosis and adaptive management and discusses ways of implementing the first two phases of learning: diagnosis and mobilising an appropriate management constituency. The discussion addresses key issues and suggests suitable approaches and tools as well as numerous sources of further information. Diagnosis of a SSF defines the system to be managed, outlines the scope of the management problem in terms of threats and opportunities, and aims to construct realistic and desired future projections for the fishery. These steps can clarify objectives and lead to development of indicators necessary for adaptive management. Before management, however, it is important to mobilize a management constituency to enact change. Ways of identifying stakeholders and understanding both enabling and obstructive interactions and management structures are outlined. These preliminary learning phases for adaptive SSF management are expected to work best if legitimised by collaborative discussion among fishery stakeholders drawing on multiple knowledge systems and participatory approaches to assessment. (PDF contains 33 pages)