Deep K_s-near-infrared Surface Photometry of 80 Dwarf Irregular Galaxies in the Local Volume

We present deep near-infrared (K_s) images and surface photometry for 80 dwarf irregular galaxies (dIs) within ~5 Mpc of the Milky Way. The galaxy images were obtained at five different facilities between 2004 and 2006. The image reductions and surface photometry have been performed using methods specifically designed for isolating faint galaxies from the high and varying near-infrared sky level. Fifty-four of the 80 dIs have surface brightness profiles which could be fit to a hyperbolic-secant (sech) function, while the remaining profiles could be fit to the sum of a sech and a Gaussian function. From these fits, we have measured central surface brightnesses, scale lengths, and integrated magnitudes. This survey is part of a larger study of the connection between large-scale structure and the global properties of dIs, the hypothesized building-blocks of more massive galaxies

Unraveling the Historical Economies of Scale and Learning Effects for Desalination Technologies

As a technology develops and matures, both economies of scale and the lessons learned through experience drive down the cost over time. This article analyzes and separates the effects of economies of scale and learning through experience on historical cost reductions for three mature desalination technologies: multi‐effect distillation (MED), multi‐stage flash (MSF) distillation, and reverse osmosis (RO). The analysis suggests that learning has been the dominant driver for cost reductions, with learning rates of 23%, 30%, and 12% for MED, MSF, and RO, respectively, when the effects of scale are removed. The highest influence of economies of scale is found for MED, with an exponential scale coefficient of 0.71 and the largest difference between a traditional or scale‐free estimation of the learning rate. MSF and RO showed smaller differences between the traditional and de‐scaled learning rates (only 3%), pointing at learning as the main factor driving their historical cost reductions. However, a trend break observed over the last 10 years mirrors an exhaustion of the potential for technical improvements, as well as an increasing complexity and nonlinearity of the factors influencing the systems' cost. The findings provide useful data and insights for integrated and economic modeling frameworks, while providing guidance to prevent overestimations of the learning effect due to the confounding influence of economies of scale effects associated to historical unit upscaling processes

Determinación de la capacidad de regulación hídrica de un Typic Hapludands mediante las curvas de retención de humedad y la modelación de sus propiedades hidrofísicas.

(Eng) In the watershed Centella , located in the upper river basin of the Dagua - Valle del Cauca, in nine farms with association coffee - banana, coffee - guamo, cane panelera and pastures, the water regulation capacity of the soil was studied by means of humidity retention curves obtained in the laboratory and by modeling its hydrophysical properties in Hydrus 2D. Properties such as texture, bulk density, porosity, organic matter, hydraulic conductivity, infiltration and humidity were determined. Subsequently, moisture retention curves were simulated using the hydraulic models of Van Genuchten, Brooks and Corey, Van Genuchten modified and Kosugi, evaluating the average errors and the dispersion of the data. Agreed to the results it is possible to point out that the soil under study has a high capacity for moisture retention ( > 18%), consequence of the high content of clays ( > 41%) and organic matter ( > 5%), characteristics of the Andisols of the Valle del Cauca. Finally, the best fitting model was compared statistically with the data of the curves obtained in the laboratory, finding that Van Genuchten and Van Genuchten models modified, are the most appropriate for obtaining the retention curves from the hydrophysical properties since they presented a lower mean error (ME) with a value not higher than -0.11 cm 3 / cm 3 and a value of the square root of the mean square error (RMSE) less than 0.11 cm 3 / cm 3 .(Spa) En la microcuenca Centella, ubicada en la cuenca alta del río Dagua - Valle del Cauca, en nueve fincas con asociación café – pláta - no, café - guamo, caña panelera y pastos, se estudió la capacidad de regulación hídrica del suelo mediante curvas de retención de humedad obtenidas en laboratorio y por modelación de sus propiedades hidrofísicas, en Hydrus 2D. Se determin ó textura, densidad aparente, porosidad, materia orgánica, conductividad hidr áulica, infiltración y humedad del suelo . Posteriormente, se simularon las curvas de retención de humedad mediante los modelos hidráulicos de Van Genuchten, Brooks y Corey, Van Genuchten modificado y Kosugi, evaluando los errores medios y la dispersión de los datos. De acuerdo a los resultados es posible señalar que el suelo en estudio tiene una alta capacidad de retención de humedad ( > 18 % ), debido a los altos contenidos de arcilla ( > 41 %) y materia or - gánica ( > 5%) , característico de los Andisoles presentes en el Valle del Cauca. Finalmente, se comparó estadísticamente el modelo de mejor ajuste con los datos de las curvas obtenidas en laboratorio, encontrando que los modelos Van Genuchten y Van Genuchten modificado, son los más apropiados para la obtención de las curvas de retención a partir de propiedades hidrofísicas dado que pre - sentaron un menor error medio (ME) con un valor no superior a -0.11 cm 3 /cm 3 y un valor de la raíz cuadrada del error cuadrático medio (RMSE) menor de 0.11 cm 3 /cm 3

Knowledge sharing in infection prevention in routine and outbreak situations: a survey of the Society for Healthcare Epidemiology of America Research Network

Abstract In this cross-sectional Society for Healthcare Epidemiology of America Research Network survey on knowledge sharing in infection prevention we identified a rudimentary understanding of how to communicate and share knowledge within healthcare institutions. Our data support the need of further research in this important field

The developmental dynamics of terrorist organizations

We identify robust statistical patterns in the frequency and severity of violent attacks by terrorist organizations as they grow and age. Using group-level static and dynamic analyses of terrorist events worldwide from 1968-2008 and a simulation model of organizational dynamics, we show that the production of violent events tends to accelerate with increasing size and experience. This coupling of frequency, experience and size arises from a fundamental positive feedback loop in which attacks lead to growth which leads to increased production of new attacks. In contrast, event severity is independent of both size and experience. Thus larger, more experienced organizations are more deadly because they attack more frequently, not because their attacks are more deadly, and large events are equally likely to come from large and small organizations. These results hold across political ideologies and time, suggesting that the frequency and severity of terrorism may be constrained by fundamental processes.Comment: 28 pages, 8 figures, 4 tables, supplementary materia

Statistical Basis for Predicting Technological Progress

Forecasting technological progress is of great interest to engineers, policy makers, and private investors. Several models have been proposed for predicting technological improvement, but how well do these models perform? An early hypothesis made by Theodore Wright in 1936 is that cost decreases as a power law of cumulative production. An alternative hypothesis is Moore's law, which can be generalized to say that technologies improve exponentially with time. Other alternatives were proposed by Goddard, Sinclair et al., and Nordhaus. These hypotheses have not previously been rigorously tested. Using a new database on the cost and production of 62 different technologies, which is the most expansive of its kind, we test the ability of six different postulated laws to predict future costs. Our approach involves hindcasting and developing a statistical model to rank the performance of the postulated laws. Wright's law produces the best forecasts, but Moore's law is not far behind. We discover a previously unobserved regularity that production tends to increase exponentially. A combination of an exponential decrease in cost and an exponential increase in production would make Moore's law and Wright's law indistinguishable, as originally pointed out by Sahal. We show for the first time that these regularities are observed in data to such a degree that the performance of these two laws is nearly tied. Our results show that technological progress is forecastable, with the square root of the logarithmic error growing linearly with the forecasting horizon at a typical rate of 2.5% per year. These results have implications for theories of technological change, and assessments of candidate technologies and policies for climate change mitigation

Engineering serendipity: When does knowledge sharing lead to knowledge production?

Research Summary We investigate how knowledge similarity between two individuals is systematically related to the likelihood that a serendipitous encounter results in knowledge production. We conduct a field experiment at a medical research symposium, where we exogenously varied opportunities for face‐to‐face encounters among 15,817 scientist‐pairs. Our data include direct observations of interaction patterns collected using sociometric badges, and detailed, longitudinal data of the scientists\u27 postsymposium publication records over 6 years. We find that interacting scientists acquire more knowledge and coauthor 1.2 more papers when they share some overlapping interests, but cite each other\u27s work between three and seven times less when they are from the same field. Our findings reveal both collaborative and competitive effects of knowledge similarity on knowledge production outcomes. Managerial Summary Managers often try to stimulate innovation by encouraging serendipitous interactions between employees, for example by using office space redesigns, conferences and similar events. Are such interventions effective? This article proposes that an effective encounter depends on the degree of common knowledge shared by the individuals. We find that scientists who attend the same conference are more likely to learn from each other and collaborate effectively when they have some common interests, but may view each other competitively when they work in the same field. Hence, when designing opportunities for face‐to‐face interactions, managers should consider knowledge similarity as a criteria for fostering more productive exchanges

Deep Ks -near-infrared surface photometry of 80 dwarf irregular galaxies in the local volume

We present deep near-infrared (K_s) images and surface photometry for 80 dwarf irregular galaxies (dIs) within ~5 Mpc of the Milky Way. The galaxy images were obtained at five different facilities between 2004 and 2006. The image reductions and surface photometry have been performed using methods specifically designed for isolating faint galaxies from the high and varying near-infrared sky level. Fifty-four of the 80 dIs have surface brightness profiles which could be fit to a hyperbolic-secant (sech) function, while the remaining profiles could be fit to the sum of a sech and a Gaussian function. From these fits, we have measured central surface brightnesses, scale lengths, and integrated magnitudes. This survey is part of a larger study of the connection between large-scale structure and the global properties of dIs, the hypothesized building-blocks of more massive galaxies