Miracle-dz/UniFAR-FTUs huggingface dataset:
5-HTT Deficiency Affects Neuroplasticity and Increases Stress Sensitivity Resulting in Altered Spatial Learning Performance in the Morris Water Maze but Not in the Barnes Maze

The purpose of this study was to evaluate whether spatial hippocampus-dependent learning is affected by the serotonergic system and stress. Therefore, 5-HTT knockout (-/-), heterozygous (+/-) and wildtype (+/+) mice were subjected to the Barnes maze (BM) and the Morris water maze (WM), the latter being discussed as more aversive. Additionally, immediate early gene (IEG) expression, hippocampal adult neurogenesis (aN), and blood plasma corticosterone were analyzed. While the performance of 5-HTT-/- mice in the BM was undistinguishable from both other genotypes, they performed worse in the WM. However, in the course of the repeated WM trials 5-HTT-/- mice advanced to wildtype level. The experience of a single trial of either the WM or the BM resulted in increased plasma corticosterone levels in all genotypes. After several trials 5-HTT-/- mice exhibited higher corticosterone concentrations compared with both other genotypes in both tests. Corticosterone levels were highest in 5-HTT-/- mice tested in the WM indicating greater aversiveness of the WM and a greater stress sensitivity of 5-HTT deficient mice. Quantitative immunohistochemistry in the hippocampus revealed increased cell counts positive for the IEG products cFos and Arc as well as for proliferation marker Ki67 and immature neuron marker NeuroD in 5-HTT-/- mice compared to 5-HTT+/+ mice, irrespective of the test. Most differences were found in the suprapyramidal blade of the dentate gyrus of the septal hippocampus. Ki67-immunohistochemistry revealed a genotype x environment interaction with 5-HTT genotype differences in naïve controls and WM experience exclusively yielding more Ki67-positive cells in 5-HTT+/+ mice. Moreover, in 5-HTT-/- mice we demonstrate that learning performance correlates with the extent of aN. Overall, higher baseline IEG expression and increased an in the hippocampus of 5-HTT-/- mice together with increased stress sensitivity may constitute the neurobiological correlate of raised alertness, possibly impeding optimal learning performance in the more stressful WM.
Ieee Computer Graphics and Applications 33 the Reality Deck—an Immersive Gigapixel Display Immersive Virtual Environments the Reality Deck Is a Visualization Facility Offering State-of-the-art Aggregate Resolution and Immersion. It's a 1.5-gpixel Immersive Tiled Display with a Full 360-degree Horizo

A vast number of data sources, such as su-percomputers and sensors, have become " fire hoses, " generating information far more quickly than it can be digested. For example , the AWARE-2 camera system can capture a 1.47-Gpixel photograph. 1 (AWARE stands for Advanced Wide Field of View Architectures for Image Reconstruction and Exploitation.) In cosmology, the Large Synoptic Survey Telescope (www.lsst. org) will feature a 3.2-Gpixel sensor and capture approximately 200,000 images annually. One approach to visualization is to fit vast quantities of data on a single display. Various sum-marization, abstraction, and focus-plus-context techniques aim to accomplish that while providing users with the data's overall patterns and structure. Maximizing the available screen real estate demonstrably affects visualization. 2 Tiled display arrays (powerwalls) embody this concept, offering a large, high-resolution, collaborative work-space. For applications that benefit from physical immersion (for example, surrounding the user with visuals), CAVEs (Cave Automatic Visual Environments) are suitable, potentially offering a fully im-mersive field of view (FOV) and stereoscopic 3D. 3 Immersive virtual environments (IVEs), however , present a fundamental dichotomy. For visualizing large-scale datasets, the total screen real estate and resolution must be maximized, making powerwalls more appropriate. However, pow-erwalls lack immersion, and physical constraints can limit their resolution (for example, a 100 ft. planar powerwall is unwieldy to construct and use). Conversely, CAVEs offer immersion, but their maximum resolution is roughly 100 Mpixels per eye for state-of-the-art systems. Furthermore, their total workspace can be somewhat constrained (approximately 9 × 9 ft. for typical setups). Motivated by this situation, we designed and built the Reality Deck, the world's first gigapixel-resolution display in a fully enclosed setting. Figure 1 depicts a synthetic, to-scale rendering of the facility; Figures 2 and 3 (and other figures in this article) show applications. The Reality Deck offers more than 1.5 Gpixel of resolution, a 360-degree horizontal FOV, and a workspace of approximately 33 × 19 × 11 ft. This configuration lets multiple users naturally explore data at different scales by approaching or distancing themselves from the displays while maintaining the panoramic context. This display real estate can be abstracted in planar or im-mersive configurations. IVE design is driven largely by two factors: the visual acuity (VA) and degree of immersion. VA is a metric that quantifies the quality of the visuals a display can deliver. Maximizing VA lets users approach the display surfaces and naturally perform multiscale exploration (rather …
An Integrated Approach for Question Classification in Chinese Cuisine Question Answering System

This paper presents an integrated method on question classification of Chinese Sichuan cuisine QA system. Classified features are extracted by means of domain attributes and the rule based classifier is constructed. SVM classifier is used for secondary classification to the questions which cannot be matched with rules. Experimental results show that the proposed method can achieve an accuracy of 96.22%.
Genetic stock composition analysis of Chinook salmon bycatch samples from the 2011 Bering Sea and Gulf of Alaska trawl fisheries

A genetic analysis of samples from the Chinook salmon (Oncorhynchus tshawytscha) bycatch of the 2011 Bering Sea-Aleutian Island (BSAI) and Gulf of Alaska (GOA) pollock trawl fisheries was undertaken to determine the stock composition of the sample set. Samples were genotyped for 43 single nucleotide polymorphism (SNP) DNA markers and results were estimated using the Alaska Department of Fish and Game (ADF&G) SNP baseline. In 2011, genetic samples from the Bering Sea were collected using a systematic random sampling protocol from one out of every 10 Chinook salmon encountered. Based on the analysis of 2,473 Chinook salmon bycatch samples collected throughout the 2011 BSAI walleye pollock (Theragra chalcogramma) trawl fishery, Coastal Western Alaska stocks dominated the sample set (68%) with smaller contributions from North Alaska Peninsula (9%), British Columbia (8%), and U.S. west coast (6%) stocks. Analysis of temporal groupings within the pollock “A” and “B” seasons revealed changes in stock composition during the course of the year with lower contributions of North Alaska Peninsula and Yukon River stocks during the “B” season. Genetic samples were also collected from Chinook salmon taken in the bycatch of the 2011 Gulf of Alaska (GOA) pollock trawl fisheries. In contrast with the Bering Sea, genetic samples were collected opportunistically in the GOA during 2011; consequently, the resulting stock composition estimates should be considered as stock compositions of the sample set rather than a representative composition of the entire GOA Chinook salmon bycatch. Based on the analysis of 240 Chinook salmon bycatch samples, British Columbia (40%) and U.S. west coast (26%) stocks comprised the largest stock groups with smaller contributions from Northwest GOA (15%) and Coastal Southeast Alaska (14%) stocks.
Reliability performance of shuffle exchange omega network

Multistage Interconnection Networks (MINs) are design to provide an effective communication in switching. In optical MIN, optical signal are routed through the connecting path by electronically controlled switching element using directional coupler. Shuffle-exchange networks (SENs) have been widely considered as practical interconnection systems due to their size of it switching elements (SEs) and uncomplicated configuration. In this paper, the relationship between reliability performance and number of network size are compared in shuffle exchange network (SEN), SEN with minus one stages (SEN-) and SEN with additional stage (SEN+). There are three parameters used to measure the reliability performance on these networks which is terminal reliability, broadcast reliability and network reliability. From the results the proposed SEN- have a better reliability performance compared to SEN and SEN+.
Survey: Image Mosaicing based on Feature Extraction

Image Mosaicing is as an consider in and personal digital assistant graphics. Image stitching is by the whole of two or images of the close study which is called panoramic image. Image stitching techniques are categorized two approaches: Direct and feature based techniques. Direct techniques link the pixel intensities of the images by all of each whereas based techniques to a mid the images all manner of features extracted from the images. The be has the of preferably at variance with scene life, faster, and has the to automatically the overlapping relationships an unordered of images. The about is to a scan the based stitching. The components of stitching will be described. A of a stitching based on based approaches will be introduced. Finally, the challenges of brain wave stitching will be discussed.
Computing semantic relatedness of words and texts in Wikipedia-derived semantic space

Adequate representation of natural language semantics requires access to vast amounts of common sense and domain-specific world knowledge. Prior work in the field was either based on purely statistical techniques that did not make use of background knowledge or on huge manual efforts, such as the CYC projects. Here we propose a novel method, called Explicit Semantic Analysis (ESA), for finegrained semantic interpretation of unrestricted natural language texts. Our method represents meaning in a high-dimensional space of concepts derived from Wikipedia, the largest encyclopedia in existence. We use machine learning techniques that allow us to explicitly represent the meaning of any text in terms of Wikipedia-based concepts. We evaluate the effectiveness of our method on automatically computing the degree of semantic relatedness between fragments of natural language text. Compared with the previous state of the art, using ESA results in substantial improvements in correlation of computed relatedness scores with human judgments: from r = 0.56 to 0.75 for individual words and from r = 0.60 to 0.72 for texts. Consequently, we anticipate ESA to give rise to the next generation of natural language processing tools. Importantly, due to the use of natural concepts, the ESA model is easy to explain to human users.
Dynamic Construction and Administration of the Workload Graph for Materialized Views Selection

To offer the best performance to each application (e.g., decision support systems) administration and optimization of database management systems is needed. In order to reduce administration costs and to provide continuous adaptation to changing workload patterns, selfmanagement techniques have been in the focus of researchers and DBMS vendors for recent years. One important topic in this area is the selection of materialized views, i.e., complex queries of OLAP systems benefit from pre-computed results. In this work, we present an automatic selection of materialized views using statistics of a workload which is represented in the query graph model. We propose merging of queries of a workload into a workload graph and the computation of merged views. Hence, we introduce a cost model to select the views to be materialized. The proposed techniques are evaluated using the TPC-H benchmark and compared to an industrial design advisor. Furthermore, our approach can be used in static as well as in on-line self-tuning.
StreamKM++: A clustering algorithm for data streams

We develop a new <it>k</it>-means clustering algorithm for data streams of points from a Euclidean space. We call this algorithm StreamKM++. Our algorithm computes a small weighted sample of the data stream and solves the problem on the sample using the <it>k</it>-means++ algorithm of Arthur and Vassilvitskii (SODA '07). To compute the small sample, we propose two new techniques. First, we use an adaptive, nonuniform sampling approach similar to the <it>k</it>-means++ seeding procedure to obtain small coresets from the data stream. This construction is rather easy to implement and, unlike other coreset constructions, its running time has only a small dependency on the dimensionality of the data. Second, we propose a new data structure, which we call coreset tree. The use of these coreset trees significantly speeds up the time necessary for the adaptive, nonuniform sampling during our coreset construction. We compare our algorithm experimentally with two well-known streaming implementations: BIRCH [Zhang et al. 1997] and StreamLS [Guha et al. 2003]. In terms of quality (sum of squared errors), our algorithm is comparable with StreamLS and significantly better than BIRCH (up to a factor of 2). Besides, BIRCH requires significant effort to tune its parameters. In terms of running time, our algorithm is slower than BIRCH. Comparing the running time with StreamLS, it turns out that our algorithm scalesmuch better with increasing number of centers. We conclude that, if the first priority is the quality of the clustering, then our algorithm provides a good alternative to BIRCH and StreamLS, in particular, if the number of cluster centers is large. We also give a theoretical justification of our approach by proving that our sample set is a small coreset in low-dimensional spaces.
Tamper-resistant storage techniques for multimedia systems

Tamper-resistant storage techniques provide varying degrees of authenticity and integrity for data. This paper surveys five implemented tamper-resistant storage systems that use encryption, cryptographic hashes, digital signatures and error-correction primitives to provide varying levels of data protection. Five key evaluation points for such systems are: (1) authenticity guarantees, (2) integrity guarantees, (3) confidentiality guarantees, (4) performance overhead attributed to security, and (5) scalability concerns. Immutable storage techniques can enhance tamper-resistant techniques. Digital watermarking is not appropriate for tamper-resistance implemented in the storage system rather than at the application level.
A New Intelligent Algorithm for Designing Digital Filter

Noise reduction is one of the core issues in signal processing, because the noise exists throughout the channel as well as other communication system. And the filtering technology is a conventional technology of noise cancellation. Traditional filtering techniques require some priori statistical knowledge of signal and noise. In this paper, optimal adaptive filters are implemented by using evolutionary algorithm, which don’t need any priori statistical knowledge of signal and noise, and the parameters of these adaptive filters can be automatically adjusted to the best in accordance with certain criteria. Theoretical analysis and simulation results show that it can not only quickly design effective optimal adaptive filters by using evolutionary algorithm, but also can achieve minimal error.
Variability-Driven Formulation for Simultaneous Gate Sizing and Postsilicon Tunability Allocation

Process variations cause design performance to become unpredictable in deep submicrometer technologies. Several statistical techniques (timing analysis, gate sizing, and buffer insertion) have been proposed to counter these variations during the optimization phase of the design flow to get a better timing yield. Another interesting approach to improve the timing yield is postsilicon-tunable (PST) clock tree. In this paper, we propose such an integrated framework that performs simultaneous statistical gate sizing in the presence of PST clock-tree buffers for minimizing binning yield loss (YL) and tunability costs by determining the ranges of delay tuning to be provided at each buffer. The simultaneous gate sizing and PST-buffer range determination problem is proved to be a convex-stochastic programming formulation under longest path-delay constraints and, hence, solved optimally. We further extend the formulation into a heuristic to additionally consider shortest path-delay constraints. We make experimental comparisons using nominal gate sizing followed by PST-buffer management using the work of Tsai as a base case. We take the solution obtained from this approach and perform the following: 1) sensitivity-based statistical gate sizing while retaining the PST clock tree and 2) simultaneous gate sizing and PST-buffer range determination as proposed in this paper. On an average, the base-case approach gave 23% timing YL, the sensitivity approach gave 15% YL, whereas our proposed algorithm gave only 4% YL.
A frame tampering detection algorithm for MPEG videos

Frame tampering is one of the common video forgery operations, which can change the video content and confuse the viewers by removing or inserting some special frames in the video streams. In this paper, a new method is proposed to detect this kind of tampering based on the features of the power of high frequency area in the doctored sequences. Experiment results demonstrate that our proposed method can effectively detect frame tampering in the MPEG-2 streams.
Recognition of Human Iris Patterns for Biometric Identification

Iris recognition is an efficient method for identification of persons. This paper provides a technique for the iris recognition. A biometric system provides automatic identification of individuals. Iris is an unique feature which is applicable for identification. Unlike face recognition or finger prints, iris recognition comes from randomly distributed features. It is most reliable and accurate method of identification. This paper proposes a personal identification using iris recognition system with the help of six major steps i.e. image acquisition,localization, Isolation, normalization, feature extraction and matching and also these six steps consists a numbers of minor steps to complete each step. The boundaries of the iris, as papillary and limbic boundary, are detected by using Canny Edge Detector. We can use masking technique to isolate the iris image form the given eye image, this isolated iris image is transformed from Cartesian to polar co-ordinate. Now finally extract the unique features (feature vector) of the iris after enhancing the iris image and then perform matching process on iris code using Hamming Distance for acceptance and rejectance process. Keywords: Canny edge detection , Hamming distance , Hough transform, Masking, Histogram equalization, Haar wavelet.
Autonomous Biogeochemical Floats Detect Significant Carbon Dioxide Outgassing in the High‐Latitude Southern Ocean

Although the Southern Ocean is thought to account for a significant portion of the contemporary oceanic uptake of carbon dioxide (CO2), flux estimates in this region are based on sparse observations that are strongly biased toward summer. Here we present new estimates of Southern Ocean air‐sea CO2 fluxes calculated with measurements from biogeochemical profiling floats deployed by the Southern Ocean Carbon and Climate Observations and Modeling project during 2014–2017. Compared to ship‐based CO2 flux estimates, the float‐based fluxes find significantly stronger outgassing in the zone around Antarctica where carbon‐rich deep waters upwell to the surface ocean. Although interannual variability contributes, this difference principally stems from the lack of autumn and winter ship‐based observations in this high‐latitude region. These results suggest that our current understanding of the distribution of oceanic CO2 sources and sinks may need revision and underscore the need for sustained year‐round biogeochemical observations in the Southern Ocean.
Statistical and Probability Quantification of Hydrologic Dynamics in the Lake Tuscaloosa Watershed, Alabama, USA

Interconnected components of water cycle, including surface water, groundwater, and precipitation, can exhibit complex hydrologic dynamics. This study investigates dynamics embedded in surface water, groundwater, and precipitation time series data in the Lake Tuscaloosa watershed located in northern Alabama, using standard statistics and non-stationarity analysis. Standard statistics analysis shows that less water is available in this watershed over time. A significant correlation between different data sets is found, and groundwater is found to be slower evolving than its nearby surface systems. Non-stationarity analysis based on time scale-local Hurst exponents calculated by the multifractal detrended fluctuation approach shows that, on one hand, the stream system exhibits non-stationarity properties similar to precipitation, as expected. On the other hand, groundwater and lake stage non-stationarity is found to be influenced by the seasonal variation in rainfall and the long-term anthropogenic factors. Therefore, sustainability of surface water and aquifer may be affected by natural input and/or anthropogenic activity, both of which can evolve non-stationary in different time scales.
Discovery of principles of nature from mathematical modeling of DNA microarray data

Recent advances in DNA microarray hybridization technology make it possible to record the molecular biological signals, e.g., mRNA expression levels and proteins' DNA-binding occupancy levels, that guide the progression of cellular processes on genomic scales (1, 2). Biology and medicine today may be at a point similar to where physics was after the advent of the telescope (3). The rapidly growing number of DNA microarray data sets holds the key to the discovery of previously unknown molecular biological principles, just as the astronomical tables compiled by Galileo and Brahe (Fig. 1 A ) enabled accurate predictions of planetary motions and, later, the discovery of universal gravitation. Just as Kepler and Newton made these predictions and discoveries by using mathematical frameworks to describe trends in astronomical data (Fig. 1 B ), so future predictive power, discovery, and control in biology and medicine will come from the mathematical modeling of DNA microarray data, where the mathematical variables and operations represent biological reality: The variables, patterns uncovered in the data, might correlate with activities of cellular elements, such as regulators or transcription factors, that drive the measured signals. The operations, such as data classification and reconstruction in subspaces of selected patterns, might simulate experimental observation of the correlations and possibly also causal coordination of these activities. Such models were recently created from DNA microarray data by using singular value decomposition (SVD) (4) and generalized SVD (GSVD) (5), and their ability to predict previously unknown biological as well as physical principles was demonstrated (6, 7). Fig. 1. Kepler' discovery of his first law of planetary motion from mathematical modeling of Brahe's astronomical data. ( A ) Astronomical table of positions of the sun, Earth, and Mars at different times. ( B ) Geometrical reconstruction of the orbit of Mars from these data reveals an ellipse with the sun located … *E-mail: orlyal{at}mail.utexas. edu