Miracle-dz/UniFAR-FTUs huggingface dataset:
Permission Set Mining: Discovering Practical and Useful Roles

Role based access control is an efficient and effective way to manage and govern permissions to a large number of users. However, defining a role infrastructure that accurately reflects the internal functionalities and workings of a large enterprise is a challenging task. Recent research has focused on the theoretical components of automated role identification while practical applications for identifying roles remain unsolved.This research proposes a practical data mining heuristic method that is fast, scalable and capable of identifying comprehensive roles and placing them into a hierarchy. Permission set pattern data mining can be used to identify the roles with partial orderings that cover the largest portion of user permissions within a system. We test the algorithm on real user permission assignments as well as on generated data sets. Roles identified in test sets cover up to 85% of user permissions and analysis show the roles offer significant administrative benefit. We find interesting correlations between roles and their relationships and analyse the tradeoffs between identifying roles with complete coverage to identifying roles that are most effective and offer significant administrative benefit.
Use of random forest to estimate population attributable fractions from a case-control study of Salmonella enterica serotype Enteritidis infections

SUMMARY To design effective food safety programmes we need to estimate how many sporadic foodborne illnesses are caused by specific food sources based on case-control studies. Logistic regression has substantive limitations for analysing structured questionnaire data with numerous exposures and missing values. We adapted random forest to analyse data of a case-control study of Salmonella enterica serotype Enteritidis illness for source attribution. For estimation of summary population attributable fractions (PAFs) of exposures grouped into transmission routes, we devised a counterfactual estimator to predict reductions in illness associated with removing grouped exposures. For the purpose of comparison, we fitted the data using logistic regression models with stepwise forward and backward variable selection. Our results show that the forward and backward variable selection of logistic regression models were not consistent for parameter estimation, with different significant exposures identified. By contrast, the random forest model produced estimated PAFs of grouped exposures consistent in rank order with results obtained from outbreak data, with egg-related exposures having the highest estimated PAF (22·1%, 95% confidence interval 8·5–31·8). Random forest might be structurally more coherent and efficient than logistic regression models for attributing Salmonella illnesses to sources involving many causal pathways.
Mathematical model of electrode positioning hydraulic drive of electric arc steel-making furnace taking into account stochastic disturbances of arcs

The paper describes the process of mathematical model development of the hydraulic drive of electrode positioning in the ultra-high power electric arc furnace (EAF) taking into account random disturbances of the electric arcs. The developed model makes it possible to assess the dynamic performance parameters of the control system of the electrode positioning hydraulic drive, which is especially important in the process of energy reserves identification in the EAF in order to improve a number of important economic and technical characteristics such as specific energy consumption, electrode consumption, time of current-on operation and the heat time. Besides, it should be noted that the algorithms, which form the basis of this model, are universal and can be applied for both low-power and high-power furnaces using different ways of charging.
Evolution of the Northern Rockweed, Fucus distichus, in a Regime of Glacial Cycling: Implications for Benthic Algal Phylogenetics

Northern hemisphere rockweeds (Fucus) are thought to have evolved in the North Pacific and then spread to the North Atlantic following the opening of the Bering Strait. They have dispersed and widely speciated in the North Atlantic and its tributary seas. Fucus distichus is likely near the ancestral member of this genus, and studies have shown that there are several species/subspecies in this complex (i.e. F. evanescens and F. gardneri). We used phylogenetic and haplotype analyses to test the phylogenetic relationships and biogeography of F. distichus. Our data and subsequent analyses demonstrate that, unlike previous studies that lacked samples from an extensive geographical area of the Arctic and Subarctic, there is a distinct Arctic haplotype that is the source of subspecies in both the North Pacific and North Atlantic. Fucus distichus occupies a low tide zone habitat, and in Arctic/Subarctic regions it is adapted to the severe stress of sea ice coverage and disturbance during many months per year. We hypothesize that the very large geographic area of Arctic and Subarctic rocky shores available to this species during interglacials, supported by large Arctic/Subarctic fringe areas as well as unglaciated refugia during glacial cycles, provided a robust population and gene pool (described by the Thermogeographic Model). This gene pool dilutes that of the more fragmented and area-limited Temperate/Boreal area populations when they are brought together during glacial cycles. We suggest that similar subspecies complexes for a variety of Arctic/Subarctic shore biota should be examined further in this context, rather than arbitrarily being split up into numerous species.
Eurographics Symposium on Geometry Processing (2007) a Streaming Algorithm for Surface Reconstruction

We present a streaming algorithm for reconstructing closed surfaces from large non-uniform point sets based on a geometric convection technique. Assuming that the sample points are organized into slices stacked along one coordinate axis, a triangle mesh can be efficiently reconstructed in a streamable layout with a controlled memory footprint. Our algorithm associates a streaming 3D Delaunay triangulation data-structure with a multilayer version of the geometric convection algorithm. Our method can process millions of sample points at the rate of 50k points per minute with 350 MB of main memory.
Aggregated Packet Transmission in Duty-Cycled WSNs: Modeling and Performance Evaluation

Duty cycling (DC) is a popular technique for energy conservation in wireless sensor networks (WSNs) that allows nodes to wake up and sleep periodically. Typically, a single-packet transmission (SPT) occurs per cycle, leading to possibly long delay. With aggregated packet transmission (APT), nodes transmit a batch of packets in a single cycle. The potential benefits brought by an APT scheme include shorter delay, higher throughput, and higher energy efficiency. In the literature, different analytical models have been proposed to evaluate the performance of SPT schemes. However, no analytical models for the APT mode on synchronous DC medium access control (MAC) mechanisms exist. In this paper, we first develop a 3-D discrete-time Markov chain (DTMC) model to evaluate the performance of an APT scheme with packet retransmission enabled. The proposed model captures the dynamics of the state of the queue of nodes and the retransmission status and the evolution of the number of active nodes in the network, i.e., nodes with a nonempty queue. We then study the number of retransmissions needed to transmit a packet successfully. Based on the observations, we develop another less-complex DTMC model with infinite retransmissions, which embodies only two dimensions. Furthermore, we extend the 3-D model into a 4-D model by considering error-prone channel conditions. The proposed models are adopted to determine packet delay, throughput, packet loss, energy consumption, and energy efficiency. Furthermore, the analytical models are validated through discrete-event-based simulations. Numerical results show that an APT scheme achieves substantially better performance than its SPT counterpart in terms of delay, throughput, packet loss, and energy efficiency and that the developed analytical models reveal precisely the behavior of the APT scheme.
Is Omega-3 Fatty Acids Enriched Nutrition Support Safe for Critical Ill Patients? A Systematic Review and Meta-Analysis

Objective: To systematically review the effects of omega-3 poly unsaturated fatty acids (FA) enriched nutrition support on the mortality of critically illness patients. Methods: Databases of Medline, ISI, Cochrane Library, and Chinese Biomedicine Database were searched and randomized controlled trials (RCTs) were identified. We enrolled RCTs that compared fish oil enriched nutrition support and standard nutrition support. Major outcome is mortality. Methodological quality assessment was conducted based on Modified Jadad’s score scale. For control heterogeneity, we developed a method that integrated I2 test, nutritional support route subgroup analysis and clinical condition of severity. RevMan 5.0 software (The Nordic Cochrane Centre, Copenhagen, Denmark) was used for meta-analysis. Results: Twelve trials involving 1208 patients that met all the inclusion criteria. Heterogeneity existed between the trials. A random model was used, there was no significant effect on mortality RR, 0.82, 95% confidence interval (CI) (0.62, 1.09), p = 0.18. Knowing that the route of fish oil administration may affect heterogeneity, we categorized the trials into two sub-groups: parenteral administration (PN) of omega-3 and enteral administration (EN) of omega-3. Six trials administered omega-3 FA through PN. Pooled results indicated that omega-3 FA had no significant effect on mortality, RR 0.76, 95% CI (0.52, 1.10), p = 0.15. Six trials used omega-3 fatty acids enriched EN. After excluded one trial that was identified as source of heterogeneity, pooled data indicated omega-3 FA enriched EN significant reduce mortality, RR=0.69, 95% CI [0.53, 0.91] (p = 0.007). Conclusion: Omega-3 FA enriched nutrition support is safe. Due to the limited sample size of the included trials, further large-scale RCTs are needed.
Fine-Grained Geographical Relation Extraction from Wikipedia

In this paper, we present work on enhancing the basic data resource of a context-aware system. Electronic text offers a wealth of information about geospatial data and can be used to improve the completeness and accuracy of geospatial resources (e.g., gazetteers). First, we introduce a supervised approach to extracting geographical relations on a fine-grained level. Second, we present a novel way of using Wikipedia as a corpus based on self-annotation. A self-annotation is an automatically created high-quality annotation that can be used for training and evaluation. Wikipedia contains two types of different context: (i) unstructured text and (ii) structured data: templates (e.g., infoboxes about cities), lists and tables. We use the structured data to annotate the unstructured text. Finally, the extracted fine-grained relations are used to complete gazetteer data. The precision and recall scores of more than 97 percent confirm that a statistical IE pipeline can be used to improve the data quality of community-based resources.
Similarity-based spectral clustering ensemble selection

Traditional clustering ensemble methods combine all the obtained clustering results at hand. However, we can often achieve a better clustering solution if only a part of all available clustering results is combined. In this paper, SELective Spectral Clustering Ensemble (SELSCE), a novel clustering ensemble method, is proposed. The component clusterings of an ensemble system are generated by Spectral Clustering (SC) capable of engendering diverse committees. The random scaling parameter, Nyström approximation and random initialization of k-means are used to perturb SC for producing the components of an ensemble system. A measure integrating diversity and quality is proposed to evaluate the quality of all the obtained results. Furthermore, a novel selection strategy based on the nearest neighbor rule is introduced to choose from them a part of the promising to build an ensemble committee. The experimental results on UCI datasets demonstrate that the proposed algorithm outperforms the traditional ones in data clustering.
XML processing in DHT networks

We study the scalable management of XML data in P2P networks based on distributed hash tables (DHTs). We identify performance limitations in this context, and propose an array of techniques to lift them. First, we adapt the DHT platform's index store and communication primitives to the needs of massive data processing. Second, we introduce a distributed hierarchical index and associated efficient algorithms to speed up query processing. Third, we present an innovative, XML-specific flavor of Bloom filters, to reduce data transfers entailed by query processing. Our approach is fully implemented in the KadoP system, used in a real-life software manufacturing application. Our experiments demonstrate the benefits of the proposed techniques.
Interactive Graph Layout of a Million Nodes

Sensemaking of large graphs, specifically those with millions of nodes, is a crucial task in many fields. Automatic graph layout algorithms, augmented with real-time human-in-the-loop interaction, can potentially support sensemaking of large graphs. However, designing interactive algorithms to achieve this is challenging. In this paper, we tackle the scalability problem of interactive layout of large graphs, and contribute a new GPU-based force-directed layout algorithm that exploits graph topology. This algorithm can interactively layout graphs with millions of nodes, and support real-time interaction to explore alternative graph layouts. Users can directly manipulate the layout of vertices in a force-directed fashion. The complexity of traditional repulsive force computation is reduced by approximating calculations based on the hierarchical structure of multi-level clustered graphs. We evaluate the algorithm performance, and demonstrate human-in-the-loop layout in two sensemaking case studies. Moreover, we summarize lessons learned for designing interactive large graph layout algorithms on the GPU.
Heat Shock Improves Sca‐1+ Stem Cell Survival and Directs Ischemic Cardiomyocytes Toward a Prosurvival Phenotype Via Exosomal Transfer: A Critical Role for HSF1/miR‐34a/HSP70 Pathway

Stem cell‐based therapy is a promising intervention for ischemic heart diseases. However, the functional integrity of stem cells is impaired in an ischemic environment. Here, we report a novel finding that heat shock significantly improves Sca‐1+stem cell survival in an ischemic environment by the regulation of the triangle: heat shock factor 1 (HSF1), HSF1/miR‐34a, and heat shock protein 70 (HSP70). Initially we prove that HSP70 is the key chaperone‐mediating cytoprotective effect of heat shock in Sca‐1+cells and then we establish miR‐34a as a direct repressor of HSP70. We found that HSP70 was downregulated in heat shocked Sca‐1+ stem cells (HSSca‐1+ cells). Intriguingly, we demonstrate that the downregulation of miR‐34a is attributed to HSF1‐mediated epigenetic repression through histone H3 Lys27 trimethylation (H3K27me3) on miR‐34a promoter. Moreover, we show that heat shock induces exosomal transfer of HSF1 from Sca‐1+ cells, which directs ischemic cardiomyocytes toward a prosurvival phenotype by epigenetic repression of miR‐34a. In addition, our in vivo study demonstrates that transplantation of HSSca‐1+ cells significantly reduces apoptosis, attenuates fibrosis, and improves global heart functions in ischemic myocardium. Hence, our study provides not only novel insights into the effects of heat shock on stem cell survival and paracrine behavior but also may have therapeutic values for stem cell therapy in ischemic heart diseases. Stem Cells 2014;32:462–472
An Update of Wallace’s Zoogeographic Regions of the World

Next-Generation Biogeography In 1876, Alfred Russel Wallace mapped the zoogeographical regions of the world, based on the distributions and taxonomic relationships of broadly defined mammalian families. Wallace's classification of zoogeographical regions became a cornerstone of modern biogeography and a reference for a wide variety of biological disciplines, including global biodiversity and conservation sciences. Holt et al. (p. 74, published online 20 December) present a next-generation map of wallacean zoogeographic regions, incorporating phylogenetic data on >20,000 vertebrate species to discern and characterize their natural biogeographic patterns. Mapping the geographic distribution and phylogenetic relationships of 21,037 vertebrate species yields 11 realms. Modern attempts to produce biogeographic maps focus on the distribution of species, and the maps are typically drawn without phylogenetic considerations. Here, we generate a global map of zoogeographic regions by combining data on the distributions and phylogenetic relationships of 21,037 species of amphibians, birds, and mammals. We identify 20 distinct zoogeographic regions, which are grouped into 11 larger realms. We document the lack of support for several regions previously defined based on distributional data and show that spatial turnover in the phylogenetic composition of vertebrate assemblages is higher in the Southern than in the Northern Hemisphere. We further show that the integration of phylogenetic information provides valuable insight on historical relationships among regions, permitting the identification of evolutionarily unique regions of the world.
ProcessLine: Visualizing time-series data in process industry

In modern process industry, it is often difficult to analyze a manufacture process due to its numerous time-series data. Analysts wish to not only interpret the evolution of data over time in a working procedure, but also examine the changes in the whole production process through time. To meet such analytic requirements, we have developed ProcessLine, an interactive visualization tool for a large amount of time-series data in process industry. The data are displayed in a fisheye timeline. ProcessLine provides good overviews for the whole production process and details for the focused working procedure. A preliminary user study using beer industry production data has shown that the tool is effective.
Topic and Role Discovery in Social Networks

Previous work in social network analysis (SNA) has modeled the existence of links from one entity to another, but not the attributes such as language content or topics on those links. We present the Author-Recipient-Topic (ART) model for social network analysis, which learns topic distributions based on the direction-sensitive messages sent between entities. The model builds on Latent Dirichlet Allocation (LDA) and the Author-Topic (AT) model, adding the key attribute that distribution over topics is conditioned distinctly on both the sender and recipient--steering the discovery of topics according to the relationships between people. We give results on both the Enron email corpus and a researcher's email archive, providing evidence not only that clearly relevant topics are discovered, but that the ART model better predicts people's roles and gives lower perplexity on previously unseen messages. We also present the Role-Author-Recipient-Topic (RART) model, an extension to ART that explicitly represents people's roles.
Deciphering Structural Intermediates and Genotoxic Fibrillar Aggregates of Albumins: A Molecular Mechanism Underlying for Degenerative Diseases

The misfolding and aggregation of proteins is involved in some of the most prevalent neurodegenerative disorders. The importance of human serum albumin (HSA) stems from the fact that it is involved in bio-regulatory and transport phenomena. Here the effect of acetonitrile (ACN) on the conformational stability of HSA and by comparison, ovalbumin (OVA) has been evaluated in the presence and absence of NaCl. The results show the presence of significant amount of secondary structure in HSA at 70% ACN and in OVA at 50% ACN, as evident from far-UV Circular Dichroism (CD) and Attenuated Total Reflection Fourier transformed infra red spectroscopy (ATR-FTIR). Tryptophan and 8-Anilino-1-Naphthalene-Sulphonic acid (ANS) fluorescence indicate altered tryptophan environment and high ANS binding suggesting a compact “molten globule”-like conformation with enhanced exposure of hydrophobic surface area. However, in presence of NaCl no intermediate state was observed. Detection of aggregates in HSA and OVA was possible at 90% ACN. Aggregates possess extensive β-sheet structure as revealed by far-UV CD and ATR-FTIR. These aggregates exhibit increase Thioflavin T (Th T) fluorescence with a red shift of Congo red (CR) absorption spectrum. X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM) analysis confirmed the presence of fibrillar aggregates. Single cell gel electrophoresis (SCGE) assay of these fibrillar aggregates showed the DNA damage resulting in cell necrosis confirming their genotoxic nature. Some proteins not related to any human disease form fibrils in vitro. In the present study ACN gives access to a model system to study the process of aggregation.
GMM Tests for SD Efficiency of a Given Portfolio

We develop empirical tests for Second-order Stochastic Dominance (SSD) efficiency and Third-order Stochastic Dominance (TSD) efficiency of a given investment portfolio relative to all possible portfolios formed from a set of assets. Contrary to existing Linear Programming tests, our tests are embedded in the Generalized Method of Moments (GMM) framework, which results in superior statistical power properties and increases the comparability with existing mean-variance tests. Using these tests, we demonstrate that the mean-variance inefficiency of the CRSP all-share index relative to beta-sorted portfolios can be explained by tail risk not captured by variance.
The effect of cathodic protection on the stress corrosion characteristics of 300M low alloy steel

The objective of this investigation was to determine if stress corrosion failure of 300M steel is accelerated by the applicAtion of cathodic protection. Testing was conducted on notch tensile specimens th8t were coated with vacuum cadmium, electroplated cadmium, and vacuum aluminum. All specimens were stressed and placed in an aqueous sodium chloride environment. The failure times for the specimens were moni to.red and graphs were drawn which characterized the stress corrosion resistance of 300M steel and the cathodic protection systems. Fractography techniques were used to study the failure surfaces to determine the type of failure mechanism. The results of this thesis program indicated that, for 300M low alloy steel: ·1) The hydrogen evolved during cathodic protection of 300M steel by vacuum aluminum and vacuum cadmium embrittles the steel and accelerates failure. 2) Cathodic protection afforded bJ vacuum cadmium accelerates stress corrosion failure of 300M steel at all stress levels and significantly below 60% NTS. 3) Vacuum aluminum does not afford adequate protection to 300M steel and premature failure can be expected at all