Miracle-dz/UniFAR-FTUs huggingface dataset:
Information-geometric measures estimate neural interactions during oscillatory brain states

The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.
A 60-GHz sub-harmonic IQ modulator and demodulator using drain-body feedback technique

A 50-to-62 GHz sub-harmonic IQ de/modulator using 90-nm CMOS technology is presented in this paper. A passive sub-harmonic gate mixer for both up-conversion and down-conversion simultaneously is used as the sub-circuit of this IQ de/modulator, which can achieve high isolation without baluns and quadrature phase dividers, therefore the required LO power is lower than those of other passive modulators. The modulator exhibits an up-conversion gain of -13 dB and a down-conversion gain of -15 dB from 50 to 62 GHz with LO power of 4 dBm. The 2LO-to-RF isolation is better than 40 dB. The sideband suppression is better than -20 dBc from 50 to 62 GHz.
Automatically learning gazetteers from the deep web

Wrapper induction faces a dilemma: To reach web scale, it requires automatically generated examples, but to produce accurate results, these examples must have the quality of human annotations. We resolve this conflict with AMBER, a system for fully automated data extraction from result pages. In contrast to previous approaches, AMBER employs domain specific gazetteers to discern basic domain attributes on a page, and leverages repeated occurrences of similar attributes to group related attributes into records rather than relying on the noisy structure of the DOM. With this approach AMBER is able to identify records and their attributes with almost perfect accuracy (>98%) on a large sample of websites. To make such an approach feasible at scale, AMBER automatically learns domain gazetteers from a small seed set. In this demonstration, we show how AMBER uses the repeated structure of records on deep web result pages to learn such gazetteers. This is only possible with a highly accurate extraction system. Depending on its parametrization, this learning process runs either fully automatically or with human interaction. We show how AMBER bootstraps a gazetteer for UK locations in 4 iterations: From a small seed sample we achieve 94.4% accuracy in recognizing UK locations in the $4th$ iteration.
Using Statistical Information to Communicate Android Permission Risks to Users

The Android OS has a permission-based security system that controls the third party applications' access to sensitive information on the smartphone. The risk evaluation is left to the user who has to evaluate whether or not the requested permissions are appropriate. However, former work has shown that users lack attention to and understanding of the permissions which makes it difficult for them to make appropriate decisions. To support users with better understandable information we provide statistical information about permissions, grouped by functionality. We use methods from health risk communication to communicate this information to the users. In a lab experiment with 48 participants we find that users tend to choose more often the app with a lower number of permissions when statistical information is provided together with graphics. We also find that the privacy-intrusiveness and trustworthiness of apps is perceived differently when statistical information is given.
Sex Differences in the Neural Processing of Aversive Interoceptive Events: The Benefit of Relief

Do men and women process and experience unpleasant bodily states differently? We used fMRI to determine brain processing before, during and after an aversive respiratory stimulation. No sex difference emerged during anticipation or stimulation. However, after the offset of the stimulation, men but not women showed enhanced activation of brain regions that are important for interoception and reward processing. Moreover, this activation was highest in those males who rated the preceding stimulation as most unpleasant. These results indicate that men are particularly sensitive to reward associated with the termination of an aversive event, which may signal relief.
Benefit of an Extended Stroke Unit Service With Early Supported Discharge: A Randomized, Controlled Trial

Background and Purpose Several trials have shown that stroke unit care improves outcome for stroke patients. The aim of the present trial was to evaluate the effects of an extended stroke unit service (ESUS), with early supported discharge, cooperation with the primary healthcare system, and more emphasis on rehabilitation at home as essential elements. Methods In a randomized, controlled trial, 160 patients with acute stroke were allocated to the ESUS and 160 to the ordinary stroke unit service (OSUS). The primary outcome was the proportion of patients who were independent as assessed by the modified Rankin Scale (RS) (RS ≤2=global independence) and independent in activities of daily living (ADL) as assessed by Barthel Index (BI) (BI ≥95=independent in ADL) after 26 weeks. Secondary outcomes were RS and BI scores after 6 weeks; the proportion of patients at home, in institutions, and deceased after 6 and 26 weeks; and the length of stay in institutions. Results After 26 weeks, 65.0% in the ESUS versus 51.9% in the OSUS group showed global independence (RS ≤2) (P= 0.017) , while 60.0% in the ESUS versus 49.4% in the OSUS group were independent in ADL (BI ≥95) (P =0.056). The odds ratios for independence (ESUS versus OSUS) were as follows: RS, 1.72 (95% CI, 1.10 to 2.70); BI, 1.54 (95% CI, 0.99 to 2.39). At 6 weeks, 54.4% of the ESUS group and 45.6% of the OSUS group were independent according to RS (P =0.118), and 56.3% versus 48.8% were independent according to BI (P =0.179). The proportion of patients at home after 6 weeks was 74.4% for ESUS and 55.6% for OSUS (P =0.0004), and the proportion in institutions was 23.1% versus 40.0%, respectively (P =0.001). After 26 weeks, 78.8% in the ESUS group versus 73.1% in the OSUS were at home (P =0.239), while 13.1% versus 17.5% were in institutions (P =0.277). The mortality in the 2 groups did not differ. Average lengths of stay in an institution were 18.6 days in the ESUS and 31.1 days in the OSUS group (P =0.0324). Conclusions An ESUS with early supported discharge seems to improve functional outcome and to reduce the length of stay in institutions compared with traditional stroke unit care.
Shape Retrieval Using Hierarchical Total Bregman Soft Clustering

In this paper, we consider the family of total Bregman divergences (tBDs) as an efficient and robust “distance” measure to quantify the dissimilarity between shapes. We use the tBD-based l1-norm center as the representative of a set of shapes, and call it the t-center. First, we briefly present and analyze the properties of the tBDs and t-centers following our previous work in [1]. Then, we prove that for any tBD, there exists a distribution which belongs to the lifted exponential family (lEF) of statistical distributions. Further, we show that finding the maximum a posteriori (MAP) estimate of the parameters of the lifted exponential family distribution is equivalent to minimizing the tBD to find the t-centers. This leads to a new clustering technique, namely, the total Bregman soft clustering algorithm. We evaluate the tBD, t-center, and the soft clustering algorithm on shape retrieval applications. Our shape retrieval framework is composed of three steps: 1) extraction of the shape boundary points, 2) affine alignment of the shapes and use of a Gaussian mixture model (GMM) [2], [3], [4] to represent the aligned boundaries, and 3) comparison of the GMMs using tBD to find the best matches given a query shape. To further speed up the shape retrieval algorithm, we perform hierarchical clustering of the shapes using our total Bregman soft clustering algorithm. This enables us to compare the query with a small subset of shapes which are chosen to be the cluster t-centers. We evaluate our method on various public domain 2D and 3D databases, and demonstrate comparable or better results than state-of-the-art retrieval techniques.
Characterizing Web Censorship Worldwide: Another Look at the OpenNet Initiative Data

In this study, we take another look at 5 years of web censorship data gathered by the OpenNet Initiative in 77 countries using user-based testing with locally relevant content. Prior to our work, this data had been analyzed with little automation, focusing on what content had been blocked, rather than how blocking was carried out. In this study, we use more rigorous automation to obtain a longitudinal, global view of the technical means used for web censorship. We also identify blocking that had been missed in prior analyses. Our results point to considerable variability in the technologies used for web censorship, across countries, time, and types of content, and even across ISPs in the same country. In addition to characterizing web censorship in countries that, thus far, have eluded technical analysis, we also discuss the implications of our observations on the design of future network measurement platforms and circumvention technologies.
A brief survey on power gating design

With the process scaling down to 65nm, leakage power begin to dominate the power consumption. Power gating as one of the most effective techniques to reduce leakage power has become the research hot spot in the past ten years, and will be applicable in all the future low power design. This paper give a brief summary of the concept of power gating design, the problems when implementing it as well as techniques to deal with them.
An Integrated Approach toward Retrieving Physically Consistent Profiles of Temperature, Humidity, and Cloud Liquid Water

Abstract A method is presented for deriving physically consistent profiles of temperature, humidity, and cloud liquid water content. This approach combines a ground-based multichannel microwave radiometer, a cloud radar, a lidar-ceilometer, the nearest operational radiosonde measurement, and ground-level measurements of standard meteorological properties with statistics derived from results of a microphysical cloud model. All measurements are integrated within the framework of optimal estimation to guarantee a retrieved profile with maximum information content. The developed integrated profiling technique (IPT) is applied to synthetic cloud model output as a test of accuracy. It is shown that the liquid water content profiles obtained with the IPT are significantly more accurate than common methods that use the microwave-derived liquid water path to scale the radar reflectivity profile. The IPT is also applied to 2 months of the European Cloud Liquid Water Network (CLIWA-NET) Baltic Sea Experiment (BALTEX.
Patent classification of the new invention using PLSA

In the current scenario of the world for Research and Development leading to patenting, content classification in accordance with the subject areas to which it belongs to is a challenging task. This is because today's R&D draws its novelty/newness not in one technical area but a unique combination of different technical areas. For example, a Typical ICT patent may be a composite effect for advancing the knowledge in some combination of Control Engg, Electronic Components, Databases Technology, Information retrieval methodology, Internet and Wireless technology, Speech, Signal, and Image Processing etc. In this paper, the work has been reported for the content classification for a newly drafted patent document using Probabilistic Latent Semantic Analysis technique. The probabilistic latent semantic analysis (PLSA) is used for automated indexing of the document by creating an indexer which tokenizes the documents and creates a proper generative model. Herein a singular value decomposition model is used for compacting the size of term document matrix and their co-occurrences in the matrix. The objective is to take up the large document corpora generated from the past patent document to categorize documents based on the concept generated model. The approach is illustrated and has been tested for by an example classification of the content for two typical US Patent Classes, and has been found to work well for them.
Combining Multiple Feature Extraction Technique and Classifiers for Increasing Accuracy for Devanagari OCR

In this paper we combining statistical, structural Global transformation and moments features to form hybrid feature vector . We are combining Classifiers for ach ieving high accuracy for Devanagari Script. To abolish the hitc h of misclassification and increase the classifier accur ac combining SVM and KNN together. The dataset used for experiment are created by us.
Image editing based on Sparse Matrix-Vector multiplication

This paper presents a unified model for image editing in terms of Sparse Matrix-Vector (SpMV) multiplication. In our framework, we cast image editing as a linear energy minimization problem and address it by solving a sparse linear system, which is able to yield a globally optimal solution. First, three classical image editing operations, including linear filtering, resizing and selecting, are reformulated in the SpMV multiplication form. The SpMV form helps us set up a straightforward mechanism to flexibly and naturally combine various image features (low-level visual features or geometrical features) and constraints together into an integrated energy minimization function under the L2 norm. Then, we apply our model to implement the tasks of pan-sharpening, image cloning, image mixed editing and texture transfer, which are now popularly used in the field of digital art. Comparative experiments are reported to validate the effectiveness and efficiency of our model.
Social Policy and Productivity Growth: What are the Linkages?

In this chapter, Richard Harris points out that a traditional view has been that there is an inherent conflict between economic efficiency and social equality, a view neatly summarized in the title of Okun's famous book, Equality and Efficiency: The Big Trade-off (1975). This view gained renewed currency in the policy debates of the 1990s, as commentators contrasted the economic performance of Europe and the U.S. in that decade. This view has been challenged both by cross-national empirical studies and by theoretical advances. Recent research seems to suggest that there is no efficiency-equity trade-off and that social policy and greater equality may actually contribute to higher productivity growth. Richard Harris surveys two streams of recent research that point in this direction. The chapter also examines new theoretical literature, especially the new endogenous growth theory that suggests that increases in inequality can hurt growth.
Targeted Overexpression of the Neurite Growth-Associated Protein B-50/GAP-43 in Cerebellar Purkinje Cells Induces Sprouting after Axotomy But Not Axon Regeneration into Growth-Permissive Transplants

B-50/GAP-43 is a nervous tissue-specific protein, the expression of which is associated with axon growth and regeneration. Its overexpression in transgenic mice produces spontaneous axonal sprouting and enhances induced remodeling in several neuron populations (Aigner et al., 1995; Holtmaat et al., 1995). We examined the capacity of this protein to increase the regenerative potential of injured adult central axons, by inducing targeted B-50/GAP-43 overexpression in Purkinje cells, which normally show poor regenerative capabilities. Thus, transgenic mice were produced in which B-50/GAP-43 overexpression was driven by the Purkinje cell-specific L7 promoter. Uninjured transgenic Purkinje cells displayed normal morphology, indicating that transgene expression does not modify the normal phenotype of these neurons. By contrast, after axotomy numerous transgenic Purkinje cells exhibited profuse sprouting along the axon and at its severed end. Nevertheless, despite these growth phenomena, which never occurred in wild-type mice, the severed transgenic axons were not able to regenerate, either spontaneously or into embryonic neural or Schwann cell grafts placed into the lesion site. Finally, although only a moderate Purkinje cell loss occurred in wild-type cerebella after axotomy, a considerable number of injured transgenic neurons degenerated, but they could be partially rescued by the different transplants placed into the lesion site. Thus, B-50/GAP-43 overexpression substantially modifies Purkinje cell response to axotomy, by inducing growth processes and decreasing their resistance to injury. However, the presence of this protein is not sufficient to enable these neurons to accomplish a full program of axon regeneration.
Vaporization of perfluorocarbon droplets using optical irradiation

Micron-sized liquid perfluorocarbon (PFC) droplets are currently being investigated as activatable agents for medical imaging and cancer therapy. After injection into the bloodstream, superheated PFC droplets can be vaporized to a gas phase for ultrasound imaging, or for cancer therapy via targeted drug delivery and vessel occlusion. Droplet vaporization has been previously demonstrated using acoustic methods. We propose using laser irradiation as a means to induce PFC droplet vaporization using a method we term optical droplet vaporization (ODV). In order to facilitate ODV of PFC droplets which have negligible absorption in the infrared spectrum, optical absorbing nanoparticles were incorporated into the droplet. In this study, micron-sized PFC droplets loaded with silica-coated lead sulfide (PbS) nanoparticles were evaluated using a 1064 nm laser and ultra-high frequency photoacoustic ultrasound (at 200 and 375 MHz). The photoacoustic response was proportional to nanoparticle loading and successful optical droplet vaporization of individual PFC droplets was confirmed using photoacoustic, acoustic, and optical measurements. A minimum laser fluence of 1.4 J/cm(2) was required to vaporize the droplets. The vaporization of PFC droplets via laser irradiation can lead to the activation of PFC agents in tissues previously not accessible using standard ultrasound-based techniques.
Evaluation of brief screening tools for neurocognitive impairment in HIV/AIDS: a systematic review of the literature

Objective(s):To systematically review literature on brief screening tools used to detect and differentiate between normal cognition and neurocognitive impairment and HIV-associated neurocognitive disorders (HANDs) in adult populations of persons with HIV. Design:A formal systematic review. Methods:We searched six electronic databases in 2011 and contacted experts to identify relevant studies published through May 2012. We selected empirical studies that focused on evaluating brief screening tools (<20 min) for neurocognitive impairment in persons with HIV. Two reviewers independently reviewed retrieved literature for potential relevance and methodological quality. Meta-analyses were completed on screening tools that had sufficient data. Results:Fifty-one studies met inclusion criteria; we focused on 31 studies that compared brief screening tools with reference tests. Within these 31 studies, 39 tools were evaluated and 67% used a comprehensive neuropsychological battery as a reference. The majority of these studies evaluated HIV-associated dementia (HAD). Meta-analyses demonstrated that the HIV Dementia Scale (HDS) has poor pooled sensitivity (0.48) and the International HIV Dementia Scale (IHDS) has moderate pooled sensitivity (0.62) in detecting a range of cognitive impairment. Five newer screening tools had relatively good sensitivities (>0.70); however, none of the tools differentiated HAND conditions well enough to suggest broader use. There were significant methodological shortcomings noted in most studies. Conclusion:HDS and IHDS perform well to screen for HAD but poorly for milder HAND conditions. Further investigation, with improved methodology, is required to understand the utility of newer screening tools for HAND; further tools may need to be developed for milder HAND conditions.
Restart-able Tight-coupled Algorithms for SMP Cluster Architectures

The current variety of parallel programming model (MPI, OpenMP,.) and the growing performance requirements for scientific applications (weather forecast, nuclear, etc.) require numerical analysis research to explore hybrid techniques. This later is a combination of several numerical techniques, or several copies of the same method parameterized differently in order to accelerate the convergence and/or to improve the accuracy of the solution of some large linear algebra problems. This paper shows how parallel collaborative computations, can outperform traditional ones by solving the communication challenge between the involved methods. Our work focuses on the hybrid computation of Krylov subspace methods, involved in solving most linear algebra problems underlying the previously mentioned large-scale applications. This paper proposes a strategy to realize an efficient hybrid computation, based on asynchronous non-blocking communication among the co-methods, and paves the way to a new approach to parallelize the tight-coupled algorithms on architecture made of cluster of shared memory nodes. By evaluating the performance of the hybrid Multiple Explicitly Restarted Arnoldi method [11] on IBM SP3 and SP4 platforms, we illustrate the effectiveness of our solution.
SPLUNC1 Regulates Cell Progression and Apoptosis through the miR-141-PTEN/p27 Pathway, but Is Hindered by LMP1

Little is known about the role of the host defensive protein short palate, lung and nasal epithelium clone 1 (SPLUNC1) in the carcinogenesis of nasopharyngeal carcinoma (NPC). Here we report that SPLUNC1 plays a role at a very early stage of NPC carcinogenesis. SPLUNC1 regulates NPC cell proliferation, differentiation and apoptosis through miR-141, which in turn regulates PTEN and p27 expression. This signaling axis is negatively regulated by the EBV-coded gene LMP1. Therefore we propose that SPLUNC1 suppresses NPC tumor formation and its inhibition by LMP1 provides a route for NPC tumorigenesis.