Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient and Scalable Graph Similarity Joins in MapReduce

Along with the emergence of massive graph-modeled data, it is of great importance to investigate graph similarity joins due to their wide applications for multiple purposes, including data cleaning, and near duplicate detection. This paper considers graph similarity joins with edit distance constraints, which return pairs of graphs such that their edit distances are no larger than a given threshold. Leveraging the MapReduce programming model, we propose MGSJoin, a scalable algorithm following the filtering-verification framework for efficient graph similarity joins. It relies on counting overlapping graph signatures for filtering out nonpromising candidates. With the potential issue of too many key-value pairs in the filtering phase, spectral Bloom filters are introduced to reduce the number of key-value pairs. Furthermore, we integrate the multiway join strategy to boost the verification, where a MapReduce-based method is proposed for GED calculation. The superior efficiency and scalability of the proposed algorithms are demonstrated by extensive experimental results.
Rapid Loss of Dendritic Spines after Stress Involves Derangement of Spine Dynamics by Corticotropin-Releasing Hormone

Chronic stress causes dendritic regression and loss of dendritic spines in hippocampal neurons that is accompanied by deficits in synaptic plasticity and memory. However, the responsible mechanisms remain unresolved. Here, we found that within hours of the onset of stress, the density of dendritic spines declined in vulnerable dendritic domains. This rapid, stress-induced spine loss was abolished by blocking the receptor (CRFR1) of corticotropin-releasing hormone (CRH), a hippocampal neuropeptide released during stress. Exposure to CRH provoked spine loss and dendritic regression in hippocampal organotypic cultures, and selective blockade of the CRFR1 receptor had the opposite effect. Live, time-lapse imaging revealed that CRH reduced spine density by altering dendritic spine dynamics: the peptide selectively and reversibly accelerated spine retraction, and this mechanism involved destabilization of spine F-actin. In addition, mice lacking the CRFR1 receptor had augmented spine density. These findings support a mechanistic role for CRH–CRFR1 signaling in stress-evoked spine loss and dendritic remodeling.
2 . WHY DO WE NEED BETTER LOGGING ?

Interactive data analysis applications have become critical tools for making sense of our world. We present a set of recommendations to improve the quality and quantity of user activity data logged from interactive data analysis systems. Such data is invaluable for improving our understanding of the data exploration process, for implementing intelligent user interfaces, for evaluating data mining and visualization techniques, and for characterizing how the broader ecosystem of data analysis tools are used in practice. Currently, much of the data logged by data analysis systems is intended for the purpose of debugging and system performance monitoring, not for understanding user behavior. As a result, researchers have to rely on labor-intensive techniques for extracting useful information from low-level event streams, or on collecting data through observation, interviews, experiments, and case studies. We present recommendations – derived from personal experience as well as examples from the literature – for logging user activity in interactive data analysis tools, to ensure that better information is collected, and ultimately, to enhance human problem-solving abilities and speed the pace of discovery. We illustrate these recommendations using examples from three widely-used but distinct systems for analyzing data: Tableau, an interactive visualization product, Excel, a spreadsheet application, and Splunk, an enterprise log management and analysis platform.
Saitohin, Which Is Nested in the tau Locus and Confers Allele-specific Susceptibility to Several Neurodegenerative Diseases, Interacts with Peroxiredoxin 6*

Saitohin is a gene unique to humans and their closest relatives, the function of which is not yet known. Saitohin contains a single polymorphism (Q7R), and its Q and R alleles belong to the H1 and H2 tau haplotype, respectively. The Saitohin Q allele confers susceptibility to several neurodegenerative diseases. To get a handle on Saitohin function, we used it as a bait in a yeast two-hybrid screen. By this assay and subsequent co-immunoprecipitation and glutathione S-transferase pull-down assays, we discovered and confirmed that Saitohin interacts with peroxiredoxin 6, a unique member of that family that is bifunctional and the levels of which increase in Pick disease. The strength of the interaction appeared to be allele-specific, giving the first distinction between the two forms of Saitohin.
Overview of the First SMOS Sea Surface Salinity Products. Part I: Quality Assessment for the Second Half of 2010

Multi-angular images of the brightness temperature (TB) of the Earth at 1.4 GHz are reconstructed from the Soil Moisture and Ocean Salinity (SMOS) satellite sensor data since end 2009. Sea surface salinity (SSS) products remote sensing from space is being attempted using these data over the world oceans. The quality of the first version of the European Space Agency operational Level 2 (L2) SSS swath products is assessed in this paper, using satellite/in situ SSS data match-ups that were collected over the second half of 2010. This database reveals that 95% of the SMOS L2 products show a global error standard deviation on the order of ~ 1.3 practical salinity scale. Simple spatiotemporal aggregation of the L2 products to generate monthly SSS maps at 1° ×1° spatial resolution reduces the error down to about 0.6 globally and 0.4 in the tropics for 90% of the data. Several major problems are, however, detected in the products. Systematically, SMOS SSS data are biased within a ~ 1500 km wide belt along the world coasts and sea ice edges, with a contamination intensity and spread varying from ascending to descending passes. Numerous world ocean areas are permanently or intermittently contaminated by radio-frequency interferences, particularly in the northern high latitudes and following Asia coastlines. Moreover, temporal drifts in the retrieved SSS fields are found with varying signatures in ascending and descending passes. In descending passes, a time-dependent strong latitudinal bias is found, with maximum amplitude reached at the end of the year. Errors in the forward modeling of the wind-induced emissivity and of the sea surface scattered galactic sources are as well identified, biasing the sss retrievals at high and low winds and when the galactic equator sources are reflected toward the sensor.
Validity of the Severity of Dependence Scale (SDS) Construct Applying the Item Response Theory to a Non-Clinical Sample of Heroin Users

Aims: The purpose of this work is to study the validity of the Severity of Dependence Scale (SDS) construct by applying Rasch models to a non-clinical sample of heroin abusers. Subjects: 982 (73% men) young people 30 years old or under (mean age 25.9 years) participated. All of them were captured from the community in the metropolitan areas of Madrid, Barcelona and Seville, between April 2002 and December 2003. Analysis: Dimensionality of the scale and calibration of items were studied using the Rating Scale model, which is a Rasch-type model. A factorial analysis was also performed to check the dimensionality of the scale. Results: The analysis of fit shows that all the items have infit and outfit values between ± 2 logits, indicating that the data fit the model and that it may be assumed to be unidimensional. The principal components analysis also showed the existence of a principal factor that explains 52.5% of the variance observed. Item calibration found that they are between +0.89 and −1.04 logits on the scale. Conclusion: The results show unidimensional structure of the SDS scale. Item calibration shows they are distributed along the continuum, which must be taken into account when calculating total scores. The study's limitations are noted.
Axiomatization of trace semantics for stochastic nondeterministic processes

We give a complete axiomatization of trace distribution precongruence for probabilistic nondeterministic processes based on a process algebra that includes internal behavior and recursion. The axiomatization is given for two different semantics of the process algebra that are consistent with the alternating model of Hansson and the nonalternating model of Segala, respectively. It is shown that the two semantics coincide up to trace distribution precongruence.
Computer assisted early detection of liver metastases from fMRI maps

We present a new method for computer-aided early detection of liver metastases tumors. The method characterized colorectal hepatic metastases and follows their early hemodynamical changes using an fMRI-based statistical model. The changes in hepatic hemodynamics are evaluated from T2W fMRI images acquired during breathing of air, air-CO2, and carbogen. A classification model is build to help radiologists differentiate tumor from healthy tissue. The model is built from 132 wellvalidated fMRI samples of tumors and healthy tissue. For each sample, a histogrambased features-vector is constructed. The model is then generated from the data with an SVM classifier. To test the model, 32 non-validated fMRI samples were used. 22 samples proved to be healthy tissue and 11 samples proved to be tumors. 9 samples were judged as tumors by the naked eye, but proved to be healthy tissue later. Our classification model yields accuracy of 78.12% with 66.67% precision on the test set.
A new pedestrian detection algorithm used for Advanced Driver-Assistance System with one cheap camera

This paper presents a new pedestrian detection algorithm used in Advanced Driver-Assistance System with only one camera aiming to improving traffic safety. The new pedestrian detection algorithm differs from traditional pedestrian detection algorithm, which only focuses on pedestrian detection rate or pedestrian detection accuracy. Conversely, the proposed algorithm focuses on both the accuracy and the rate. Some new features are proposed to improve pedestrian detection rate of the system. Also we use color difference to decrease the false detecting rate. The experimental results show that the pedestrian detection rate can be around 90% and the false detecting rate is 3%. Moreover, the new algorithm has been proved that it's available in real ADASs.
Cache node determination, allocation and distribution in cognitive networks using game theory

In cognitive networks, unlicensed users can use underutilized licensed spectrum when it is not in use by the licensed user. To avoid interference, unlicensed (secondary) user must leave the spectrum when it is accessed by the licensed (primary) user. Since it takes some time to sense the nearby free channels for the secondary user and switch to them, interruption in the ongoing data transmission is inevitable. Hence, the delay constraints of many applications cannot be met. So a cache generation approach is discussed in this paper, which reduces the time lag of delay by systematically generating cache of the signal at appropriate places. Since, every secondary users' cache must be placed in such a way that the time lag of delay is reduced to bare minimum, a game theoretic approach is used for smart distribution and allocation of cache nodes for unlicensed users.
Interaction of the Postsynaptic Density-95/Guanylate Kinase Domain-Associated Protein Complex with a Light Chain of Myosin-V and Dynein

NMDA receptors interact directly with postsynaptic density-95 (PSD-95), a scaffold protein that organizes a cytoskeletal– signaling complex at the postsynaptic membrane. The molecular mechanism by which the PSD-95-based protein complex is trafficked to the postsynaptic site is unknown but presumably involves specific motor proteins. Here we demonstrate a direct interaction between the PSD-95-associated protein guanylate kinase domain-associated protein (GKAP) and dynein light chain (DLC), a light chain subunit shared by myosin-V (an actin-based motor) and cytoplasmic dynein (a microtubule-based motor). A yeast two-hybrid screen with GKAP isolated DLC2, a novel protein 93% identical to the previously cloned 8 kDa dynein light chain (DLC1). A complex containing PSD-95, GKAP, DLC, and myosin-V can be immunoprecipitated from rat brain extracts. DLC colocalizes with PSD-95 and F-actin in dendritic spines of cultured neurons and is enriched in biochemical purifications of PSD. Immunogold electron microscopy reveals a concentration of DLC in the postsynaptic compartment of asymmetric synapses of brain in which it is associated with the PSD and the spine apparatus. We discuss the possibility that the GKAP/DLC interaction may be involved in trafficking of the PSD-95 complex by motor proteins.
SECURE KEY SHARING FOR GROUP COMMUNICATION UNDER COMMUNITY CLOUD

The cloud is one of the most discussed topics among IT professionals today, and organizations are increasingly exploring the potential benefits of using cloud computing or solutions for their businesses. In our modern world people join hands together to form groups and that forms communities through which the ability of one can enhance by communicating with others. In order to satisfy these people over cloud, transformed itself as community cloud. As a cloud infrastructure that is shared by several organization’s and supports a specific community, such as healthcare, telecommunication, education and businesses that has shared concerns around mission, policy and compliance considerations. The goal of a community cloud is to have participating organizations realize the benefits of a public cloud -- such as multi-tenancy and a pay-as-you-go billing structure but with the added level of privacy, security and policy compliance usually associated with a private cloud. The community cloud can be either on-premises or off-premises, and can be governed by the participating organizations or by a third-party managed service provider (MSP). In this community cloud large number of groups which were formed by huge number users. At this situation in order to have secure communication and data storage in cloud, consumers use keys. Though these keys were kept private in many cases they are in need to be shared at least once for the sake of security. So, in this paper we are going to discuss a secured protocol through which a community cloud users can share keys among themselves in a secured manner.
Small‐scale oxygen fluxes and remineralization in sinking aggregates

Sinking aggregates are the major component of the vertical particulate flux in most regions of the ocean. Controlling factors for aggregate remineralization rates and solute exchange with the surrounding water, however, are poorly quantified because of few empirical data. To study the role of flow and diffusion on aggregate remineralization rates, oxygen distributions were mapped within and around aggregates by use of microelectrodes in a flow field similar to that experienced by sinking aggregates. The oxygen distribution was asymmetrical with a wake of undersaturated water at the rear (downstream) of the aggregates. Oxygen concentrations within the aggregates were >80% of air saturation. The diffusive fluxes of oxygen at the aggregate‐water interface were similar along the equator and at the downstream pole for a wide range of different aggregate sources (field‐sampled diatom aggregates, lab‐made diatom aggregates, aggregates formed from freeze‐thawed diatoms, and zooplankton detritus aggregates) measured at various temperatures. Remineralization rates were reaction limited and, hence, determined by substrate quality and quantity rather than by transport‐limited oxygen supply during sedimentation at ambient oxygen concentrations above ~25 µM.
Rescue and Digitization of Climate Data by Extraction from Autographic Weather Charts

Data Rescue is the ongoing process of preserving alldata at risk of being lost due to deterioration of the medium and digitizing current and past data into computer compatible form for easy access. IMD has conscientiously taken observations of the weather, recorded them either manually or automatically, transcribed them onto preset paper forms called autographic charts. Most of the charts are now at risk of being lost due to rapid deterioration of the medium. This paper presents algorithms for automatic extraction and storage of the atmospheric data using image processing tools. The key factors that influence the methods are speed, accuracy and space. Wehave tested the algorithms on scanned images of theautographic charts available at IMD and present the results.
DESIGN OF A DYNAMIC FOCUSING MICROSCOPE OBJECTIVE FOR OCT IMAGING by

Optical Coherence Tomography (OCT) is a novel optical imaging technique that has assumed significant importance in bio-medical imaging in the last two decades because it is non-invasive and provides accurate, high resolution images of three dimensional crosssections of body tissue, exceeding the capabilities of the current predominant imaging technique –ultrasound. In this thesis, high resolution OCT is investigated for in vivo detection of abnormal skin pathology for the early diagnosis of cancer. The technology presented is based on a dynamic focusing microscopic imaging probe conceived for skin imaging and the detection of abnormalities in the epithelium. A novel method for dynamic focusing in the biological sample using liquid crystal (LC) lens technology to obtain three dimensional images with invariant resolution throughout the cross-section and depth of the sample is presented and discussed. Two different skin probe configurations that incorporate dynamic focusing with LC lenses, one involving a reflective microscope objective sub-system, and the other involving an all-refractive immersion microscope objective sub-system are investigated. In order to ensure high resolution imaging, a low coherence broadband source, namely a femtosecond modelocked Ti: sapphire laser centered at a wavelength of approximately 800nm is used to illuminate the sample. An in-depth description and analysis of the optical design and predicted performance of the two microscope objectives designed for dynamic three dimensional imaging at 5μm resolution for the chosen broadband spectrum is presented.
AP-2-containing clathrin coats assemble on mature lysosomes

Coat proteins appear to play a general role in intracellular protein trafficking by coordinating a membrane budding event with cargo selection. Here we show that the AP-2 adaptor, a clathrin-associated coat-protein complex that nucleates clathrin-coated vesicle formation at the cell surface, can also initiate the assembly of normal polyhedral clathrin coats on dense lysosomes under physiological conditions in vitro. Clathrin coat formation on lysosomes is temperature dependent, displays an absolute requirement for ATP, and occurs in both semi-intact cells and on purified lysosomes, suggesting that clathrin-coated vesicles might regulate retrograde membrane traffic out of the lysosomal compartment.
Submodular structure and optimal quantization in Gaussian multiple access relay networks

We discuss noisy network coding bounds on the capacity region of Gaussian multiple access relay networks. These networks feature a single destination node and multiple nodes that can be either sources or relays or both. We show that simple inner and outer bounds on the capacity region obtained from noisy network coding exhibit a submodular structure and differ only in a constant, which is independent of the channel parameters and grows linearly only in the number of dedicated relay nodes. This tightens previous results where the gap grows linear in the total network size. Furthermore, the combination of submodularity with convexity of the bound expressions with respect to the optimal quantization noise parameters leads to an efficient characterization of a noisy network coding achievable rate region for multiple access relay networks via Lagrangian duality.
Energy dissipation in microfluidic beam resonators

The fluid–structure interaction of resonating microcantilevers immersed in fluid has been widely studied and is a cornerstone in nanomechanical sensor development. In many applications, fluid damping imposes severe limitations by strongly degrading the signal-to-noise ratio of measurements. Recently, Burg et al. (Nature, vol. 446, 2007, pp. 1066–1069) proposed an alternative type of microcantilever device whereby a microfluidic channel was embedded inside the cantilever with vacuum outside. Remarkably, it was observed that energy dissipation in these systems was almost identical when air or liquid was passed through the channel and was 4 orders of magnitude lower than that in conventional microcantilever systems. Here, we study the fluid dynamics of these devices and present a rigorous theoretical model corroborated by experimental measurements to explain these observations. In so doing, we elucidate the dominant physical mechanisms giving rise to the unique features of these devices. Significantly, it is found that energy dissipation is not a monotonic function of fluid viscosity, but exhibits oscillatory behaviour, as fluid viscosity is increased/decreased. In the regime of low viscosity, inertia dominates the fluid motion inside the cantilever, resulting in thin viscous boundary layers – this leads to an increase in energy dissipation with increasing viscosity. In the high-viscosity regime, the boundary layers on all surfaces merge, leading to a decrease in dissipation with increasing viscosity. Effects of fluid compressibility also become significant in this latter regime and lead to rich flow behaviour. A direct consequence of these findings is that miniaturization does not necessarily result in degradation in the quality factor, which may indeed be enhanced. This highly desirable feature is unprecedented in current nanomechanical devices and permits direct miniaturization to enhance sensitivity to environmental changes, such as mass variations, in liquid.
Fingerprint Registration Using Composite Features Consensus

The paper presents a fingerprint registration approach based on the decomposition of registration process into elementary stages. In each stage a single transformation parameter is elim- inated. The algorithm uses composite features, i.e., lines connecting two minutiae instead of fin- gerprint minutiae. These features have rotation and translation-invariant attributes allowing feature filtering with significantly enhanced signal-to-noise ratio in feature consensus scheme. Experimen- tal results of goal-directed performance evaluation with live-captured fingerprint image database are presented.
The universal Khovanov link homology theory

We determine the algebraic structure underlying the geometric complex associated to a link in Bar-Natan’s geometric formalism of Khovanov’s link homology theory (nD 2). We find an isomorphism of complexes which reduces the complex to one in a simpler category. This reduction enables us to specify exactly the amount of information held within the geometric complex and thus state precisely its universality properties for link homology theories. We also determine its strength as a link invariant relative to the different topological quantum field theories (TQFTs) used to create link homology. We identify the most general (universal) TQFT that can be used to create link homology and find that it is “smaller” than the TQFT previously reported by Khovanov as the universal link homology theory. We give a new method of extracting all other link homology theories (including Khovanov’s universal TQFT) directly from the universal geometric complex, along with new homology theories that hold a controlled amount of information. We achieve these goals by making a classification of surfaces (with boundaries) modulo the 4TU/S/T relations, a process involving the introduction of genus generating operators. These operators enable us to explore the relation between the geometric complex and its algebraic structure.