Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent advances in the gene map of inherited eye disorders: primary hereditary diseases of the retina, choroid, and vitreous.

The diagnosis and basic understanding of many genetic ocular disorders have been aided by the identification of the disease causing chromosomal loci. These chromosomal loci have been mapped using the candidate gene or the positional cloning approaches. This review will focus on genetic disorders that primarily affect ocular function with emphasis on the most recent advances in the chromosomal mapping of these disorders. In particular, we will con-centrate on the genetic diseases affecting the posterior segment of the eye including the retina, choroid, and vitreous. The success of linkage analysis has relied heavily on previous clinical classifications and there are numerous reports of distinct ocular diseases mapping to specific chromosomal loci. However, there are also many examples in which a well defined disease maps to any of a number of chromosomal loci. This genetic phenomenon is known as non-allelic or locus heterogeneity and can be viewed as reflecting the eye's limited repertoire of responses to a variety of genetic lesions. Another emerging pattern is that of "gene sharing" in which different mutations within the same gene can cause clinically dis- tinct ocular diseases. Mapping of mendelian genetic disorders has helped refine the clinical classifications and has led to examples of both "lumping" and "splitting".
Importancia del sueño en el rendimiento y la salud del deportista

espanolEl sueno es un determinante fundamental en el rendimiento y la salud del deportista. En la actualidad algunos expertos la definen como la mejor estrategia de recuperacion debido a sus efectos fisiologicos y restaurativos. Los deportistas deben ser alentados a dormir mas horas que la poblacion general, debido a las demandas de recuperacion impuestas por el ejercicio. La presente revision teorica busca esclarecer los factores que afectan al sueno, los efectos de este sobre el rendimiento deportivo y la salud, asi como explicar las estrategias mas determinantes para mejorar la cantidad y calidad del sueno del deportista. Para ello es importante tener en cuenta los horarios de los eventos deportivos, el estres psicosocial del deportista, el uso de dispositivos electronicos, los viajes, el uso de sustancias estimulantes como la cafeina o la ingesta de alcohol, entre otros. Diferentes estrategias como la extension del sueno, las siestas, estrategias de higiene del sueno y nutricionales deben ser consideradas en la mejora del sueno del deportista. EnglishSleep is a fundamental determinant in the performance and health of the athlete. At present, some experts define it as the best recovery strategy due to its physiological and restorative effects. Athletes should be encouraged to sleep longer than the general population, due to the recovery demands imposed by the exercise. The present review looks for to clarify the factors that affect, the effects of these on sports performance and health, as well as describe the most decisive strategies to improve the quantity and quality of the athlete's sleep. Consequently, it is important the schedules of sporting events, the psychosocial stress of the athlete, the use of electronic devices, travel to compete, the use of stimulating substances such as caffeine or alcohol intake, among others. Different strategies such as sleep extension, naps, sleep hygiene and nutritional strategies should be considered in improving the athlete's sleep.
An End-to-End Conversational Second Screen Application for TV Program Discovery

In this article, we report on a multiphase R&D effort to develop a conversational second screen application for TV program discovery. Our goal is to share with the community the breadth of artificial intelligence (AI) and natural language (NL) technologies required to develop such an application along with learnings from target end-users. We first give an overview of our application from the perspective of the end-user. We then present the architecture of our application along with the main AI and NL components, which were developed over multiple phases. The first phase focuses on enabling core functionality such as effectively finding programs matching the user’s intent. The second phase focuses on enabling dialog with the user. Finally, we present two user studies, corresponding to these two phases. The results from both studies demonstrate the effectiveness of our application in the target domain.
ENHANCED FILTERING OF MODIS TIME SERIES DATA FOR THE ANALYSIS OF DESERTIFICATION PROCESSES IN NORTHEAST BRAZIL

Long time series of satellite data provide key input for geographically explicit monitoring and modelling of the environmental condition in the context of land use and land cover change (LUCC) analysis. Within the present study, the quality of vegetation index (VI) time series data was analysed under the assumption that a post-processing filtering algorithm considerably reduces noise and enhances the usability for land cover degradation monitoring purposes. As a prerequisite for data analysis, a filtering workflow for VI time series data was developed that accounts for disturbances in the satellite data time series which are related to atmospheric effects. The filter algorithm includes linear interpolation of cloudy pixels, long-term change trend calculation, iterative filtering and fitting of the new time series based on the Savitzky-Golay filter algorithm. Missing or uncertain values are replaced by long-term trend values and fitted using a polynomial function fitting method The time series filtering results in a new data set of enhanced temporal trajectories of VI values. The filter method was applied to a four year time series of MODIS vegetation index data (MOD13Q1). The results indicate the high potential of the Savitzky-Golay based filtering workflow to minimize noise in lower frequencies while conserving natural peaks of VI values that are related to phenological and seasonal phenomena in vegetation physiology. As a consequence, the filtered time series data provide improved input for the assessment of climate related versus human induced land degradation in semi-humid regions.
Challenging More Updates: Towards Anonymous Re-publication of Fully Dynamic Datasets

Most existing anonymization work has been done on static datasets, which have no update and need only one-time publication. Recent studies consider anonymizing dynamic datasets with external updates: the datasets are updated with record insertions and/or deletions. This paper addresses a new problem: anonymous re-publication of datasets with internal updates, where the attribute values of each record are dynamically updated. This is an important and challenging problem for attribute values of records are updating frequently in practice and existing methods are unable to deal with such a situation. We initiate a formal study of anonymous re-publication of dynamic datasets with internal updates, and show the invalidation of existing methods. We introduce theoretical definition and analysis of dynamic datasets, and present a general privacy disclosure framework that is applicable to all anonymous re-publication problems. We propose a new counterfeited generalization principle alled m-Distinct to effectively anonymize datasets with both external updates and internal updates. We also develop an algorithm to generalize datasets to meet m-Distinct. The experiments conducted on real-world data demonstrate the effectiveness of the proposed solution.
On exploiting hierarchical label structure with pairwise classifiers

The goal of this work was to test whether the performance of a regular pairwise classifier can be improved when additional information about the hierarchical class structure is added to the training sets. Somewhat surprisingly, the additional information seems to hurt the performance. We explain this with the fact that the structure of the class hierarchy is not reflected in the distribution of the instances.
ObjectGlobe: Integrating Data Processing Services on the Internet

Because of the Internet we believe that in the long run there will be alternative providers for all of these three resources for any given application. Data providers will bring more and more data and more and more different kinds of data to the net. Likewise, function providers will develop new methods to process and work with the data; e.g., function providers might develop new algorithms to compress data or to produce thumbnails out of large images and try to sell these on the Internet. It is also conceivable, that some people allow other people to use spare cycles of their idle machines in the Internet (as in the Condor system of the University of Wisconsin [LLM88]) or that some companies (cycle providers) even specialize on selling computing time to businesses that occasionally need to carry out very complex operations for which regular hardware is not sufficient. Unfortunately, we are still a far cry from such an open data processing marketplace. What we can already see today is a growing number of data (content) providers, but we can only see a few function providers and virtually no commercial cycle providers. The reason is that there is an asymmetry in the Internet: due to protocols like http or OLE or CORBA, it is possible to move data around in the Internet, but it is not yet as easily possible to move functionality around in the Internet. The only two ways to provide new functionality is (1) to develop Java applets or browser plug-ins, which can be executed at client machines, or (2) to develop middleware systems—in both ways, the data must be shipped to the functionality, which can be prohibitively expensive, if large amounts of data must be processed, and it is not possible to ship the functionality to the data or to ship both the functionality and the data to machines, which are located near the data and particularly suited to carry out the operations. At the University of Passau, we are currently developing a distributed database system to be used in the Internet. The goal is to ultimately have a system which is able to run on any machine, manage any kind of data, import any kind of data from other systems and import any kind of database operations. The system is entirely written in Java. One of the most important features of the system is that it is capable of dynamically loading (external) query operators, written in Java and supplied by any function provider, and executing these query operators in concert with pre-defined and other external operators in order to evaluate a query. Compared to object-relational database systems, which allow to integrate external data and functionality by the means of extensions (datablades, extenders or cartridges) or heterogeneous database systems such as
Abnormal Behavior Analysis Based on Examination Surveillance Video

It's difficult to review a large number of examination surveillance videos at the same time. To reduce the workload of censors, we propose a method to analyze abnormal behaviors during examinations. This paper mainly includes two parts. Firstly, it employs a two-layer classifier with Histograms of Oriented Gradients feature to detect head-shoulder part of examinees, thus we can report the presence of examinees. Secondly, it exploits a method based on sparse combination algorithm to detect suspicious cheating behaviors. Experiments show that our method can achieve decent performance with high efficiency.
The health of a nation predicts their mate preferences: cross-cultural variation in women's preferences for masculinized male faces

Recent formulations of sexual selection theory emphasize how mate choice can be affected by environmental factors, such as predation risk and resource quality. Women vary greatly in the extent to which they prefer male masculinity and this variation is hypothesized to reflect differences in how women resolve the trade-off between the costs (e.g. low investment) and benefits (e.g. healthy offspring) associated with choosing a masculine partner. A strong prediction of this trade-off theory is that women's masculinity preferences will be stronger in cultures where poor health is particularly harmful to survival. We investigated the relationship between women's preferences for male facial masculinity and a health index derived from World Health Organization statistics for mortality rates, life expectancies and the impact of communicable disease. Across 30 countries, masculinity preference increased as health decreased. This relationship was independent of cross-cultural differences in wealth or women's mating strategies. These findings show non-arbitrary cross-cultural differences in facial attractiveness judgements and demonstrate the use of trade-off theory for investigating cross-cultural variation in women's mate preferences.
Landslide Hazard Zonation Using Quantitative Methods in GIS

Landslides are major natural hazards which not only result in the loss of human life but also cause economic burden on the society. Therefore, it is essential to develop suitable models to evaluate the susceptibility of slope failures and their zonations. This paper scientifically assesses various methods of landslide susceptibility zonation in GIS environment. A comparative study of Weights of Evidence (WOE), Analytical Hierarchy Process (AHP), Artificial Neural Network (ANN), and Generalized Linear Regression (GLR) procedures for landslide susceptibility zonation is presented. Controlling factors such as lithology, landuse, slope angle, slope aspect, curvature, distance to fault, and distance to drainage were considered as explanatory variables. Data of 151 sample points of observed landslides in Mazandaran Province, Iran, were used to train and test the approaches. Small scale maps (1:1,000,000) were used in this study. The estimated accuracy ranges from 80 to 88 percent. It is then inferred that the application of WOE in rating maps' categories and ANN to weight effective factors result in the maximum accuracy.
Adaptive Interfaces for Home Health

Technology for home health applications offers great promise for helping patients and their families manage their health and maintain independence. However, user interface issues are often the greatest barrier to these systems being used. The focus of our research has been to develop methods for measuring cognitive performance through the unobtrusive monitoring of users’ interactions with the computer. This data is useful for both measuring cognitive changes as an important health indicator, but also for dynamically adapting the user interface of the various computer applications based on this information to better meet the needs of individual users.
Automatic Face Detection Using Color Based Segmentation and Computing Eigen face

This paper introduces the face Detection that makes effective image analysis and understanding. Automating the process to a computer requires the use of various image processing techniques. In the present paper, a face detection method based on "color based segmentation" and "Eigen Face" for Color Face detection with detailed experimental results has been given. The algorithm designed uses color based segmentation, and detect a face from an online surveillance system or an offline image. The main component that should be detected is the skin area. This Paper proposes a skin based segmentation algorithm for face detection in color images with detection of multiple faces and skin regions. Skin color has proven to be a useful and robust cue for face detection, localization and tracking.The proposed algorithm has been tested on various real images and its performance is found to be quite satisfactory.
Hindi-to-Urdu Machine Translation through Transliteration

We present a novel approach to integrate transliteration into Hindi-to-Urdu statistical machine translation. We propose two probabilistic models, based on conditional and joint probability formulations, that are novel solutions to the problem. Our models consider both transliteration and translation when translating a particular Hindi word given the context whereas in previous work transliteration is only used for translating OOV (out-of-vocabulary) words. We use transliteration as a tool for disambiguation of Hindi homonyms which can be both translated or transliterated or transliterated differently based on different contexts. We obtain final BLEU scores of 19.35 (conditional probability model) and 19.00 (joint probability model) as compared to 14.30 for a baseline phrase-based system and 16.25 for a system which transliterates OOV words in the baseline system. This indicates that transliteration is useful for more than only translating OOV words for language pairs like Hindi-Urdu.
Characterization of organic matter fractions in the top layer of soils under different land uses in Central‐Eastern Europe

The objective of this study was to investigate differences in organic matter fractions, such as dissolved organic carbon and humic substances, in soils under different land uses. Soil samples were collected from the upper layer of arable lands and grasslands. Humic substances (HS) were chemically fractionated into fulvic acids (FA), humic acids (HA) and humins (HUM), and based on the separated fractions, the humification index (HI) and the degree of HS transformation (DT) were calculated. Dissolved organic carbon (DOC) was determined by cold (CWE) and hot water (HWE) extractions. Regardless of land use, the results indicated significant differences in soil organic carbon (SOC) and HS composition, with HA and HUM as the dominant fractions. Total SOC was higher in grassland (median = 17.51 g kg−1) than arable soils (median = 9.98 g kg−1); the HI and DT indices did not differ significantly between land uses (HI = 0.3–10.3 and DT = 0.2–6.2 for grasslands, p > 0.05; HI = 0.3–3.9 and DT = 0.2–20.1 for arable lands, p > 0.05). This indicates the relatively high stability of organic carbon and efficient humification processes in both land uses. Additionally, in arable soils lower CWE‐C (0.75 g kg−1) and higher HWE‐C (2.59 g kg−1) than in grasslands (CWE‐C = 1.13 g kg−1, HWE‐C = 1.60 g kg−1) can be related to farming practice and application of soil amendments. The results showed that both labile and humified organic matter are better protected in grassland soils and are consequently less vulnerable to mineralization.
Quantum inspired genetic algorithm for community structure detection in social networks

Community detection is a key problem in social network analysis. We propose a two-phase algorithm for detecting community structure in social networks. First phase employs a local-search method to group together nodes that have a high chance of falling in a single community. The second phase is bi-partitioning strategy that optimizes network modularity and deploys a variant of quantum-inspired genetic algorithm. The proposed algorithm does not require any knowledge of the number of communities beforehand and works well for both directed and undirected networks. Experiments on synthetic and real-life networks show that the method is able to successfully reveal community structure with high modularity.
Extending Amdahl's law for energy-efficiency

This paper presents a study about the potential dynamic energy improvement that can be achieved when hardware parallelization is used to increase the energy efficiency of the system rather than to increase performance. We show that it is possible, at early design stages, to know the number of parallel cores that allows a system to achieve the maximum energy improvement for a given throughput. Using Amdahl's law to represent the ratio between the serial and parallel portion of an application, we can derive simple formulas to obtain the optimum frequency, supply voltage and energy improvement while the execution time remains constant.
The Generalized Spherical Radon Transform and Its Application in Texture Analysis

The generalized spherical Radon transform associates the mean values over spherical tori to a function $f$ defined on $\mathbb{S}^3 \subset \mathbb{H}$, where the elements of $\mathbb{S}^3$ are considered as quaternions representing rotations. It is introduced into the analysis of crystallographic preferred orientation and identified with the probability density function corresponding to the angle distribution function $W$. Eventually, this communication suggests a new approach to recover an approximation of $f$ from data sampling $W$. At the same time it provides additional clarification of a recently suggested method applying reproducing kernels and radial basis functions by instructive insight in its involved geometry. The focus is on the correspondence of geometrical and group features but not on the mapping of functions and their spaces.
Distribution of Culicoides sonorensis (Diptera: Ceratopogonidae) in Nebraska, South Dakota, and North Dakota: Clarifying the Epidemiology of Bluetongue Disease in the Northern Great Plains Region of the United States

ABSTRACT The presence or absence of the biting midge Culicoides sonorensis Wirth & Jones (Diptera: Ceratopogonidae), a primary vector of bluetongue viruses (genus Orbivirus, family Reoviridae, BTV) in North America, was assessed on ranches and farms across the Northern Great Plains region of the United States, specifically Nebraska, South Dakota, and North Dakota, as part of a 2-yr regional study of BTV exposure among cattle. Blacklight/suction trap samples totaling 280 2-night intervals were taken at 140 aquatic sites (potential larval habitat for C. sonorensis) on 82 livestock operations (ranches and farms) that span a south-to-north gradient of expected decreasing risk for exposure to BTV. In Nebraska, C. sonorensis populations were common and widespread, present at 15 of 18 operations. Of 32 operations sampled in South Dakota, seven of which were sampled in successive years, 18 were positive for C. sonorensis; 13 of 14 operations located west of the Missouri River were positive, whereas 13 of 18 operations east of the river were negative. Of 32 operations sampled in North Dakota, seven of which were sampled both years, 12 were positive for C. sonorensis. Six of eight operations located west and south of the Missouri River in North Dakota were positive, whereas 18 of 24 operations east and north of the river were negative for C. sonorensis. These data illustrate a well-defined pattern of C. sonorensis spatial distribution, with populations consistently present across Nebraska, western South Dakota, and western North Dakota; western South Dakota, and North Dakota encompass the Northwestern Plains Ecoregion where soils are nonglaciated and evaporation exceeds precipitation. In contrast, C. sonorensis populations were largely absent east of the Missouri River in South Dakota and North Dakota; this area comprises the Northwestern Glaciated Plains Ecoregion and Northern Glaciated Plains Ecoregion where surface soils reflect Wisconsinan glaciation and precipitation exceeds evaporation. In defining a well-demarcated pattern of population presence or absence on a regional scale, the data suggest that biogeographic factors regulate the distribution of C. sonorensis and in turn BTV exposure. These factors, ostensibly climate and soil type as they affect the suitability of larval habitat, may explain the absence of C. sonorensis, hence limited risk for exposure to BTV, across the eastern Northern Plains, upper Midwest, and possibly Northeast, regions of the United States.