Lysosomal Hydrolase Mannose 6-Phosphate Uncovering Enzyme Resides in the trans-Golgi Network

A crucial step in lysosomal biogenesis is catalyzed by “uncovering” enzyme (UCE), which removes a covering N-acetylglucosamine from the mannose 6-phosphate (Man-6-P) recognition marker on lysosomal hydrolases. This study shows that UCE resides in the trans-Golgi network (TGN) and cycles between the TGN and plasma membrane. The cytosolic domain of UCE contains two potential endocytosis motifs: 488YHPL and C-terminal 511NPFKD. YHPL is shown to be the more potent of the two in retrieval of UCE from the plasma membrane. A green-fluorescent protein-UCE transmembrane-cytosolic domain fusion protein colocalizes with TGN 46, as does endogenous UCE in HeLa cells, showing that the transmembrane and cytosolic domains determine intracellular location. These data imply that the Man-6-P recognition marker is formed in the TGN, the compartment where Man-6-P receptors bind cargo and are packaged into clathrin-coated vesicles.

LocLess: Do You Really Care Where Your Cloud Files Are?

Physical location of data in cloud storage is a problem that gains a lot of attention not only from the actual cloud providers but also from the end users' who lately raise many concerns regarding the privacy of their data. It is a common practice that cloud service providers create replicate users' data across multiple physical locations. However, moving data in different countries means that basically the access rights are transferred based on the local laws of the corresponding country. In other words, when a cloud service provider stores users' data in a different country then the transferred data is subject to the data protection laws of the country where the servers are located. In this paper, we propose LocLess, a protocol which is based on a symmetric searchable encryption scheme for protecting users' data from unauthorized access even if the data is transferred to different locations. The idea behind LocLess is that "Once data is placed on the cloud in an unencrypted form or encrypted with a key that is known to the cloud service provider, data privacy becomes an illusion". Hence, the proposed solution is solely based on encrypting data with a key that is only known to the data owner.

Biobutanol as Fuel for Direct Alcohol Fuel Cells-Investigation of Sn-Modified Pt Catalyst for Butanol Electro-oxidation

Direct alcohol fuel cells (DAFCs) mostly use low molecular weight alcohols such as methanol and ethanol as fuels. However, short-chain alcohol molecules have a relative high membrane crossover rate in DAFCs and a low energy density. Long chain alcohols such as butanol have a higher energy density, as well as a lower membrane crossover rate compared to methanol and ethanol. Although a significant number of studies have been dedicated to low molecular weight alcohols in DAFCs, very few studies are available for longer chain alcohols such as butanol. A significant development in the production of biobutanol and its proposed application as an alternative fuel to gasoline in the past decade makes butanol an interesting candidate fuel for fuel cells. Different butanol isomers were compared in this study on various Pt and PtSn bimetallic catalysts for their electro-oxidation activities in acidic media. Clear distinctive behaviors were observed for each of the different butanol isomers using cyclic voltammetry (CV), indicating a difference in activity and the mechanism of oxidation. The voltammograms of both n-butanol and iso-butanol showed similar characteristic features, indicating a similar reaction mechanism, whereas 2-butanol showed completely different features; for example, it did not show any indication of poisoning. Ter-butanol was found to be inactive for oxidation on Pt. In situ FTIR and CV analysis showed that OHads was essential for the oxidation of primary butanol isomers which only forms at high potentials on Pt. In order to enhance the water oxidation and produce OHads at lower potentials, Pt was modified by the oxophilic metal Sn and the bimetallic PtSn was studied for the oxidation of butanol isomers. A significant enhancement in the oxidation of the 1° butanol isomers was observed on addition of Sn to the Pt, resulting in an oxidation peak at a potential ∼520 mV lower than that found on pure Pt. The higher activity of PtSn was attributed to the bifunctional mechanism on PtSn catalyst. The positive influence of Sn was also confirmed in the PtSn nanoparticle catalyst prepared by the modification of commercial Pt/C nanoparticle and a higher activity was observed for PtSn (3:1) composition. The temperature-dependent data showed that the activation energy for butanol oxidation reaction over PtSn/C is lower than that over Pt/C.

CABSYS BASE DE DATOS BIBLIOGRÁFICA SOBRE RELIGIÓN EN COSTA RICA, NORMALIZACIÓN Y VALORACIÓN DE CONTENIDOS

Esta base de datos contiene 30738 registros referenciales de la prensa religiosa costarricense, en formato CEPAL, elaborados utilizando el programa Microisis, en la Escuela Ecuménica de la Religión de la Universidad Nacional.Se presenta la experiencia y los procedimientos utilizados para la normalización de la base de datos Cabsys, desde la identificación y verificación de los artículos ingresados desde 1986, directamente de las fuentes originales: los periódicos religiosos, la complementación de los títulos, la elaboración de un archivo de autoridad de autor, la corroboración de los datos referenciales de ubicación; la normalización de los descriptores y la elaboración de un archivo de autoridad de materia.Se presentan cuadros ilustrativos sobre los artículos incluidos, por ejemplo: distribución de trabajos por autor, distribución por género, distribución por año de publicación, temas más representativos según descriptores asignados y correlación entre estos y las palabras del título de los artículos.

Análisis de viajes con la aplicación de teléfonos inteligentes

Se han desarrollado varios modelos prometedores para la captura digital de datos de movilidad, que pueden ser aplicados en la planificación urbana, de transporte y de ordenamiento territorial. Por ello el objetivo de este trabajo es desarrollar una metodología que recolecte información de movilidad con la cual se generen matrices Origen-Destino (OD) y de tiempos de viajes, además que identifique puntos de interés, modos y rutas frecuentes de viaje mediante el desarrollo e implementación de una aplicación para dispositivos móviles Android. Metodología: Se produjo una aplicación para dispositivos móviles con sistema operativo Android, en base a modelos existentes. Esta aplicación obtuvo datos de movilidad a partir de los sensores de localización incorporados en los móviles (GPS), para su posterior migración a una base de datos en la nube y consiguiente post proceso con herramientas de análisis como KNIME, Python y QuantumGis. La aplicación fue probada por 68 estudiantes voluntarios de la Universidad de Cuenca, durante 14 días del mes de enero de 2016. Resultados: Con la información completa de 44 participantes se obtuvieron matrices OD y de tiempos de viajes para diferentes períodos del día, las cuales permitieron identificar variaciones de interacción entre zonas, variaciones de número y tiempo de viajes. Fueron reconocidos también modos de transporte como caminata, bicicleta y motorizados para una sub muestra (n=6). Se detectaron los POIs Residencia (91%), Trabajo/Estudio (74%) y puntos intermedios (20% del total de POIs) y se logró observar comportamientos de movilidad atípico. Finalmente se compararon las rutas más frecuentadas por los usuarios con las rutas óptimas teóricas calculadas, encontrando que el 63.6% de los usuarios coincidían con el recorrido de estas últimas. Conclusiones: El método planteado presenta coherencia con trabajos previos, mostrando niveles de confianza equiparables. El mayor reto es la implementación masiva del modelo creado para la recolección de datos útiles para planes de movilidad.

Ravines in Angola. Causes and restraint methods

The Earth we know today was not always so. Over millions of years have undergone significant ch an g e s brought about by numerous geological phenomena aimed at your balance, some internal order, creating new geological formations and other external order smoothing formations previously created. From t h e tectonic standpoint, Angola is located in a relatively stable area which gives it a certain p ri v i l e g e w h e n compared with some Asian countries or even Americans where quite often occur earthquakes and volcanic eruptions. However, the same cannot be said in relation to the occurrence of an external geodynamics phenomena, such as the ravines, which in recent years has taken shape in many provinces, especially due to anthropogenic activity, giving rise to geological hazards, increasing the risk of damage in buildings and others infrastructures, losses direct or indirect in economic activities and loss of human lives. We understand that the reducing of these risks starts, in particular, by their identification, for later take preventive measures. This work is the result of some research work carried out by the authors through erosion courses of s o i l and stabilization of soils subject to erosion phenomena, carried out by Engineering Laboratory of Angola (LEA). For the realization of this work, we resorted to cartographic data query, literature, listening to s o m e o f the provincial representatives and local residents, as well as the observation in lo co o f s o m e af f e ct ed areas. The results allow us to infer that the main provinces affected by ravine phenomenon are located in Central and Northern highlands, as well as in the eastern region, and more recently in Cuando-Cub an go province. Not ruling out, however, other regions, such as in Luanda and Cabinda [1]. Relatively the causes, we can say that the ravines in Angola are primarily due to the combination of three natural factors: climate, topography and type of soil [2]. When we add the anthropogenic activit y , namely the execution of construction works, the drainage system obstructio n, exploration of m i n e ral s, agriculture and fires, it is verified an increasing of the phenomenon, often requiring immedi at e act i o n . These interventions can be done through structural or engineering measures and by the stabilization measures on the degraded soil cover [3]. We present an example of stabilization measures throu g h t h e deployment of a local vegetation called Pennisetum purpureum. It is expected that the results may contribute to a better understanding of the causes of the ravine phenomenon in Angola and that the adopted stabilization method can be adapted in other affected provinces in order to prevent and making the contention of the ravines.

Robust estimation using the Huber function with a data-dependent tuning constant

Robust estimation often relies on a dispersion function that is more slowly varying at large values than the square function. However, the choice of tuning constant in dispersion functions may impact the estimation efficiency to a great extent. For a given family of dispersion functions such as the Huber family, we suggest obtaining the "best" tuning constant from the data so that the asymptotic efficiency is maximized. This data-driven approach can automatically adjust the value of the tuning constant to provide the necessary resistance against outliers. Simulation studies show that substantial efficiency can be gained by this data-dependent approach compared with the traditional approach in which the tuning constant is fixed. We briefly illustrate the proposed method using two datasets.

Geoadditive models for regional count data: an application to industrial location

We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 2003–2007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.

A context sensitive model for querying linked scientific data

This thesis provides a query model suitable for context sensitive access to a wide range of distributed linked datasets which are available to scientists using the Internet. The model is designed based on scientific research standards which require scientists to provide replicable methods in their publications. Although there are query models available that provide limited replicability, they do not contextualise the process whereby different scientists select dataset locations based on their trust and physical location. In different contexts, scientists need to perform different data cleaning actions, independent of the overall query, and the model was designed to accommodate this function. The query model was implemented as a prototype web application and its features were verified through its use as the engine behind a major scientific data access site, Bio2RDF.org. The prototype showed that it was possible to have context sensitive behaviour for each of the three mirrors of Bio2RDF.org using a single set of configuration settings. The prototype provided executable query provenance that could be attached to scientific publications to fulfil replicability requirements. The model was designed to make it simple to independently interpret and execute the query provenance documents using context specific profiles, without modifying the original provenance documents. Experiments using the prototype as the data access tool in workflow management systems confirmed that the design of the model made it possible to replicate results in different contexts with minimal additions, and no deletions, to query provenance documents.

Optical data encryption using time-dependent dynamics of refractive index changes in LiNbO3

We present a method for optical encryption of information, based on the time-dependent dynamics of writing and erasure of refractive index changes in a bulk lithium niobate medium. Information is written into the photorefractive crystal with a spatially amplitude modulated laser beam which when overexposed significantly degrades the stored data making it unrecognizable. We show that the degradation can be reversed and that a one-to-one relationship exists between the degradation and recovery rates. It is shown that this simple relationship can be used to determine the erasure time required for decrypting the scrambled index patterns. In addition, this method could be used as a straightforward general technique for determining characteristic writing and erasure rates in photorefractive media.

Non-Gaussianity and direction-dependent systematics in HST Key Project data

Two new statistics, namely Delta(chi 2) and Delta(chi), based on the extreme value theory, were derived by Gupta et al. We use these statistics to study the direction dependence in the HST Key Project data, which provides one of the most precise measurements of the Hubble constant. We also study the non-Gaussianity in this data set using these statistics. Our results for Delta(chi 2) show that the significance of direction-dependent systematics is restricted to well below the 1 sigma confidence limit; however, the presence of non-Gaussian features is subtle. On the other hand, the Delta(chi). statistic, which is more sensitive to direction dependence, shows direction dependence systematics to be at a slightly higher confidence level, and the presence of non-Gaussian features at a level similar to the Delta(chi 2) statistic.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Generalized Partial Response Equalization and Data-Dependent Noise Predictive Signal Detection Over Media Models for TDMR

Two-dimensional magnetic recording (2-D TDMR) is an emerging technology that aims to achieve areal densities as high as 10 Tb/in(2) using sophisticated 2-D signal-processing algorithms. High areal densities are achieved by reducing the size of a bit to the order of the size of magnetic grains, resulting in severe 2-D intersymbol interference (ISI). Jitter noise due to irregular grain positions on the magnetic medium is more pronounced at these areal densities. Therefore, a viable read-channel architecture for TDMR requires 2-D signal-detection algorithms that can mitigate 2-D ISI and combat noise comprising jitter and electronic components. Partial response maximum likelihood (PRML) detection scheme allows controlled ISI as seen by the detector. With the controlled and reduced span of 2-D ISI, the PRML scheme overcomes practical difficulties such as Nyquist rate signaling required for full response 2-D equalization. As in the case of 1-D magnetic recording, jitter noise can be handled using a data-dependent noise-prediction (DDNP) filter bank within a 2-D signal-detection engine. The contributions of this paper are threefold: 1) we empirically study the jitter noise characteristics in TDMR as a function of grain density using a Voronoi-based granular media model; 2) we develop a 2-D DDNP algorithm to handle the media noise seen in TDMR; and 3) we also develop techniques to design 2-D separable and nonseparable targets for generalized partial response equalization for TDMR. This can be used along with a 2-D signal-detection algorithm. The DDNP algorithm is observed to give a 2.5 dB gain in SNR over uncoded data compared with the noise predictive maximum likelihood detection for the same choice of channel model parameters to achieve a channel bit density of 1.3 Tb/in(2) with media grain center-to-center distance of 10 nm. The DDNP algorithm is observed to give similar to 10% gain in areal density near 5 grains/bit. The proposed signal-processing framework can broadly scale to various TDMR realizations and areal density points.