Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis for Multi-Entity Summarization

Location-based social networks (LBSNs), exemplified by Foursquare, are fast gaining popularity. One important feature of LBSNs is micro-review. Upon check-in at a particular venue, a user may leave a short review (up to 200 characters long), also known as a tip. These tips are an important source of information for others to know more about various aspects of an entity (e.g., restaurant), such as food, waiting time, or service. However, a user is often interested not in one particular entity, but rather in several entities collectively, for instance within a neighborhood or a category. In this paper, we address the problem of summarizing the tips of multiple entities in a collection, by way of synthesizing new microreviews that pertain to the collection, rather than to the individual entities per se. We formulate this problem in terms of first finding a representation of the collection, by identifying a number of “aspects” that link common threads across two or more entities within the collection. We express these aspects as dense subgraphs in a graph of sentences derived from the multi-entity corpora. This leads to a formulation of maximal multi-entity quasi-cliques, as well as a heuristic algorithm to find K such quasi-cliques maximizing the coverage over the multi-entity corpora. To synthesize a summary tip for each aspect, we select a small number of sentences from the corresponding quasi-clique, balancing conciseness and representativeness in terms of a facility location problem. Our approach performs well on collections of Foursquare entities based on localities and categories, producing more representative and diverse summaries than the baselines.
Measuring Young Men's Expected Effects of Alcohol in Provoking Situations in Bars

A newly-developed measure of the expected effects of alcohol in provoking situations was examined in terms of its factor structure, differences by situation, and associations with barroom aggression in a sample of male postsecondary students. Participants rated the extent that 49 effects of alcohol would affect their reaction to one of three randomly assigned provoking situations (i.e., guy “hits on” your girlfriend, guy punches your friend, or guy shoves you over spilled drink). Principal component analysis identified three dimensions: Cognitive Impairment, Power/Aggression, and Hyper-Emotional effects. One-way analysis of variance revealed significantly lower means on each of the three scales for the “spilled drink” situation than for the other two situations. All three scales were associated with barroom aggression in multivariate logistic regression models. This new measure provides an important tool for understanding how people perceive the effects of alcohol on their own aggression and the extent that these effects differ by situation.
YEH2/YLR020c Encodes a Novel Steryl Ester Hydrolase of the Yeast Saccharomyces cerevisiae*

Previous work from our laboratory (Zinser, E., Paltauf, F., and Daum, G. (1993) J. Bacteriol. 175, 2853–2858) demonstrated steryl ester hydrolase activity in the plasma membrane of the yeast Saccharomyces cerevisiae. Here, we show that the gene product of YEH2/ YLR020c, which is homologous to several known mammalian steryl ester hydrolases, is the enzyme catalyzing this reaction. Deletion of yeast YEH2 led to complete loss of plasma membrane steryl ester hydrolase activity whereas overexpression of the gene resulted in a significant elevation of the activity. Purification of enzymatically active Yeh2p close to homogeneity unambiguously identified this protein as a steryl ester hydrolase and thus as the first enzyme of this kind characterized in S. cerevisiae. In addition to evidence obtained in vitro experiments in vivo contributed to the characterization of this novel enzyme. Sterol analysis of yeh2Δ unveiled a slightly elevated level of zymosterol suggesting that the esterified form of this sterol precursor is a preferred substrate of Yeh2p. However, in strains bearing hybrid proteins with strongly enhanced Yeh2p activity decreased levels of all steryl esters were observed. Thus, it appears that Yeh2p activity is not restricted to distinct steryl esters but rather has broad substrate specificity. The fact that in a yeh2Δ deletion strain bulk steryl ester mobilization occurred at a similar rate as in wild type suggested that Yeh2p is not the only steryl ester hydrolase but that other enzymes with overlapping function exist in the yeast.
A biologically inspired approach for interactive learning of categories

An amazing capability of the human visual system is the ability to learn a large repertoire of visual categories. We propose an architecture for learning visual categories in an interactive and life-long fashion based on complex-shaped objects, which typically belong to several different categories. The fundamental problem of life-long learning with artificial neural networks is the so-called “stability-plasticity dilemma”. This dilemma refers to the incremental incorporation of newly acquired knowledge, while also the earlier learned information should be preserved. To achieve this learning ability we propose biologically inspired modifications to the established learning vector quantization (LVQ) approach and combine it with a category-specific forward feature selection to decouple co-occurring categories. Both parts are optimized together to ensure a compact and efficient category representation, which is necessary for fast and interactive learning.
Structural requirements for adhesion of soluble recombinant murine vascular cell adhesion molecule-1 to alpha 4 beta 1

This study describes the identification of seven amino acid residues of the vascular cell adhesion molecule (VCAM-1) that influence binding to the alpha 4 beta 1 receptor. Using recombinant murine VCAM-1-IgG, which is bound by both mouse (WEHI 231) and human (Ramos) lymphoid cells, two approaches demonstrated the crucial role of the first two NH2-terminal Ig-like domains in binding: (a) blocking monoclonal anti-mouse VCAM-1 antibodies bound to only truncation variants that included the first two domains; (b) site-direct mutagenesis of the first NH2-terminal domain showed that alanine substitution of the amino acid residues R36, D40, K46, S54, N65, T72, and E81 partially or completely reduced adherence by human and/or mouse cells. Of these D40, when mutated to A, N, or K (but not E), showed complete abrogation of adherence by mouse and human cells, as well as inability to bind blocking anti-murine VCAM- 1 antibody MVCAM.A429, while not inducing gross structural perturbations in VCAM-1. By molecular modeling, the D40 residue was located on a beta turn connecting two beta strands defined as C and D. The residues R36, K46, S54, N65, T72, and E81, which perturb cell adherence and caused small changes to gross structure, are conformationally near or adjacent to D40. Although these residues, identified as crucial for cell adhesion, are all located in domain 1, it is evident that there is a structural requirement for domains 1 and 2 to be intact so that cell adhesive function can occur.
High-throughput chromatin motion tracking in living yeast reveals the flexibility of the fiber throughout the genome

Chromosome dynamics are recognized to be intimately linked to genomic transactions, yet the physical principles governing spatial fluctuations of chromatin are still a matter of debate. Using high-throughput single-particle tracking, we recorded the movements of nine fluorescently labeled chromosome loci located on chromosomes III, IV, XII, and XIV of Saccharomyces cerevisiae over an extended temporal range spanning more than four orders of magnitude (10−2–103 sec). Spatial fluctuations appear to be characterized by an anomalous diffusive behavior, which is homogeneous in the time domain, for all sites analyzed. We show that this response is consistent with the Rouse polymer model, and we confirm the relevance of the model with Brownian dynamics simulations and the analysis of the statistical properties of the trajectories. Moreover, the analysis of the amplitude of fluctuations by the Rouse model shows that yeast chromatin is highly flexible, its persistence length being qualitatively estimated to <30 nm. Finally, we show that the Rouse model is also relevant to analyze chromosome motion in mutant cells depleted of proteins that bind to or assemble chromatin, and suggest that it provides a consistent framework to study chromatin dynamics. We discuss the implications of our findings for yeast genome architecture and for target search mechanisms in the nucleus.
Improved Spelling Error Detection and Correction for Arabic

A spelling error detection and correction application is based on three main components: a dictionary (or reference word list), an error model and a language model. While most of the attention in the literature has been directed to the language model, we show how improvements in any of the three components can lead to significant cumulative improvements in the overall performance of the system. We semi-automatically develop a dictionary of 9.3 million fully inflected Arabic words using a morphological transducer and a large corpus. We improve the error model by analysing error types and creating an edit distance based re-ranker. We also improve the language model by analysing the level of noise in different sources of data and selecting the optimal subset to train the system on. Testing and evaluation experiments show that our system significantly outperforms Microsoft Word 2010, OpenOffice Ayaspell and Google Docs.
Optimizing schema-last tuple-store queries in graphd

Current relational databases require that a database schema exist prior to data entry and require manual optimization for best performance. We describe the query optimization techniques used by graphd, the schema-last, automatically indexed tuple-store which supports freebase.com, a large world-writable database. Graphd is a log-structured store with a query optimizer based on a functional operator tree over the domain of sorted integer sets which accumulate naturally as tuples are appended to the store. We demonstrate that a set-based optimizer can deliver performance that is roughly comparable to traditional RDBMS query optimization techniques applied to a fixed schema.
The Family Diagram and Genogram: Comparisons and Contrasts

The family diagram and its derivative the genogram are widely used in marriage and family therapy, other mental health disciplines, and family medicine. After a brief history of the origins of the family diagram and genogram, several different areas are compared in order to help distinguish differences between family diagrams and genograms. The results of these evaluations illustrate some similarities in format and symbols due to a common history, but distinct differences in purpose, theoretical basis, rationale for data collection, and interpretation guidelines. Divergent theoretical perspectives explain the differences between family diagrams and genograms. The family diagram is intertwined with Bowen family systems theory, while the genogram emphasizes how the nuclear family interacts within multiple contextual levels. The family diagram and genogram are not synonymous; rather, they are distinctly different methods of family assessment.
Redescription of two species of Thaparocleidus (Monogenea: Dactylogyridae), with the description of T. armillatus sp. n. from Wallago attu and a phylogenetic analysis based on 18S rDNA sequences

The phylogenetic studies on monogeneans of the genus Thaparocleidus parasitizing W. attu in India was inferred from 18S rDNA gene data. Out of species of Thaparocleidus, one new, T. armillatus sp. n. , is described herein which distinguished from its congener species in the shapes and sizes of sclerotized structures and rest of the two species, T. indicus and T. wallagonius are redescribed morphologically as well as validated and confirmed by molecular means also. Besides the above, T. gangus was also included in the molecular analysis as it is recently described on the basis of morphology only. The phylogenetic tree was also reconstructed in order to elucidate the taxonomic status of Thaparocleidus armillatus sp. n. , T. indicus, T. wallagonius and T. gangus. This research reports for the first time, the molecular phylogenetic analysis of 18S rDNA gene for four species belonging to the genus Thaparocleidus from W. attu collected off the River Ganga in India. In phylogram, all four species of Thapaocleidus come in a single clade that confirmed their monophyletic status. A very low interspecific variability was observed in T. armillatus sp. n. and T. wallagonius suggesting that these species are highly similar in morphology. Correspondingly, T. indicus and T. gangus also showed low interspecific variability which too signifies their morphological similarities in their sclerotized structures. Our result suggested that all four species taken in the present investigation from India are monophyletic and it is also observed that morphological similarities in the sclerotized structures are well correlated with phylogeny.
Pilsner: a compositionally verified compiler for a higher-order imperative language

Compiler verification is essential for the construction of fully verified software, but most prior work (such as CompCert) has focused on verifying whole-program compilers. To support separate compilation and to enable linking of results from different verified compilers, it is important to develop a compositional notion of compiler correctness that is modular (preserved under linking), transitive (supports multi-pass compilation), and flexible (applicable to compilers that use different intermediate languages or employ non-standard program transformations). In this paper, building on prior work of Hur et al., we develop a novel approach to compositional compiler verification based on parametric inter-language simulations (PILS). PILS are modular: they enable compiler verification in a manner that supports separate compilation. PILS are transitive: we use them to verify Pilsner, a simple (but non-trivial) multi-pass optimizing compiler (programmed in Coq) from an ML-like source language S to an assembly-like target language T, going through a CPS-based intermediate language. Pilsner is the first multi-pass compiler for a higher-order imperative language to be compositionally verified. Lastly, PILS are flexible: we use them to additionally verify (1) Zwickel, a direct non-optimizing compiler for S, and (2) a hand-coded self-modifying T module, proven correct w.r. t. an S-level specification. The output of Zwickel and the self-modifying T module can then be safely linked together with the output of Pilsner. All together, this has been a significant undertaking, involving several person-years of work and over 55,000 lines of Coq.
Rapid Classification of Phenotypic Mutants of Arabidopsis via Metabolite Fingerprinting1[W][OA]

We evaluated the application of gas chromatography-mass spectrometry metabolic fingerprinting to classify forward genetic mutants with similar phenotypes. Mutations affecting distinct metabolic or signaling pathways can result in common phenotypic traits that are used to identify mutants in genetic screens. Measurement of a broad range of metabolites provides information about the underlying processes affected in such mutants. Metabolite profiles of Arabidopsis (Arabidopsis thaliana) mutants defective in starch metabolism and uncharacterized mutants displaying a starch-excess phenotype were compared. Each genotype displayed a unique fingerprint. Statistical methods grouped the mutants robustly into distinct classes. Determining the genes mutated in three uncharacterized mutants confirmed that those clustering with known mutants were genuinely defective in starch metabolism. A mutant that clustered away from the known mutants was defective in the circadian clock and had a pleiotropic starch-excess phenotype. These results indicate that metabolic fingerprinting is a powerful tool that can rapidly classify forward genetic mutants and streamline the process of gene discovery.
Improvements in Sub-character HMM Model Based Arabic Text Recognition

Sub-character HMM models for Arabic text recognition allow sharing of common patterns between different position-dependent shape forms of an Arabic character as well as between different characters. The number of HMMs gets reduced considerably while still capturing the variations in shape patterns. This results in a compact, efficient, and robust recognizer with reduced model set. In the current paper we are presenting our recent improvements in sub-character HMM modeling for Arabic text recognition where we use special 'connector' and 'space' models. Additionally we investigated contextual sub-characters HMMs for text recognition. We also present multi-stream contextual sub-character HMMs where the features calculated from a sliding window frame form one stream and its derivative features are part of the second stream. We report state-of-the-art results on the IFN/ENIT (benchmark) database of handwritten Arabic text and the recognition rate of 85.12% on sets outperforms previously published results.
Six contributions to understanding 'gaps between policy and implementation' : an overview and comments

In this issue of Politeia 'gaps between policy and implementation' are explored. The overview opens by presenting 'working conceptions' of policy (and related terms) which are compatible with the six substantive case studies. Those conceptions constitute the backdrop for an outline of selected arguments and conclusions from the six cases. This is followed by a brief critique of the linear model of policy processes which underlies many analyses of policy implementation gaps. The possible salience of an interactive model is mooted and illustrated with reference to the six cases. The conclusions of linear analyses tend to emphasise institutional causes of gaps. The interactive model has the merit of emphasising the 'gap-producing' character of complex and mutable policy processes. Policy improvement requires, in addition to 'improving implementation', conscientious attention to such processes. This is particularly important in transitional societies - where 'gaps' are likely to derive from the pursuit of heavily contested, ideologically loaded, transformation goals.
The impact on career development of learning opportunities and learning behavior at work

This study focuses on the individual career development process of M.B.A.s on the job, in an era emphasizing personal responsibility for learning and development. The impact of learning opportunities and individual learning behavior was analyzed through repeated measures. Hierarchical regressions and difference-of-means tests were performed based on survey data collected from early-career M.B.A.s. Several relationships between the research variables were found to be consistent with current literature. The results provide leads for further research into effects of both context and personal characteristics on the individual's career development process on the job.
Does Mortality Risk of Cigarette Smoking Depend on Serum Concentrations of Persistent Organic Pollutants? Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) Study

Cigarette smoking is an important cause of preventable death globally, but associations between smoking and mortality vary substantially across country and calendar time. Although methodological biases have been discussed, it is biologically plausible that persistent organic pollutants (POPs) like polychlorinated biphenyls (PCBs) and organochlorine (OC) pesticides can affect this association. This study was performed to evaluate if associations of cigarette smoking with mortality were modified by serum concentrations of PCBs and OC pesticides. We evaluated cigarette smoking in 111 total deaths among 986 men and women aged 70 years in the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) with mean follow-up for 7.7 years. The association between cigarette smoking and total mortality depended on serum concentration of PCBs and OC pesticides (P value for interaction = 0.02). Among participants in the highest tertile of the serum POPs summary score, former and current smokers had 3.7 (95% CI, 1.5–9.3) and 6.4 (95% CI, 2.3–17.7) times higher mortality hazard, respectively, than never smokers. In contrast, the association between cigarette smoking and total mortality among participants in the lowest tertile of the serum POPs summary score was much weaker and statistically non-significant. The strong smoking-mortality association observed among elderly people with high POPs was mainly driven by low risk of mortality among never smokers with high POPs. As smoking is increasing in many low-income and middle-income countries and POPs contamination is a continuing problem in these areas, the interactions between these two important health-related issues should be considered in future research.
Middlebox Communication (MIDCOM) Protocol Semantics

This document specifies semantics for a Middlebox Communication (MIDCOM) protocol to be used by MIDCOM agents for interacting with middleboxes such as firewalls and Network Address Translators (NATs). The semantics discussion does not include any specification of a concrete syntax or a transport protocol. However, a concrete protocol is expected to implement the specified semantics or, more likely, a superset of it. The MIDCOM protocol semantics is derived from the MIDCOM requirements, from the MIDCOM framework, and from working group decisions. This document obsoletes RFC 3989.
From Q(λ) to average Q-learning: efficient implementation of an asymptotic approximation

Q(λ) is a reinforcement learning algorithm that combines Q-learning and TD(λ). Online implementations of Q(λ) that use eligibility traces have been shown to speed basic Q-learning. In this paper we present an asymptotic analysis of Watkins' Q(λ) with accumulative eligibility traces. We first introduce an asymptotic approximation of Q(λ) that appears to be a gain matrix variant of basic Q-learning. Using the ODE method, we then determine an optimal gain matrix for Q-learning that maximizes its rate of convergence toward the optimal value function Q*. The similarity between this optimal gain and the asymptotic gain of Q(λ) explains the relative efficiency of the latter for (λ) > 0. Furthermore, by minimizing the difference between these two gains, optimal values for the λ parameter and the decreasing learning rates can be determined. This optimal λ strongly depends on the exploration policy during learning. A robust approximation of these learning parameters leads to the definition of a new efficient algorithm called AQ-learning (Average Q-learning), that shows a close resemblance to Schwartz' R-learning. Our results have been demonstrated through numerical simulations.
MINING TOP-K FREQUENT CLOSED ITEMSETS IN DATA STREAMS USING SLIDING WINDOW

Frequent itemset mining has become a popular research area in data mining community since the last few years. There are two main technical hitches while finding frequent itemsets. First, to provide an appropriate minimum support value to start and user need to tune this minimum support value by running the algorithm again and again. Secondly, generated frequent itemsets are mostly numerous and as a result a number of association rules generated are also very large in numbers. Applications dealing with streaming environment need to process the data received at high rate, therefore, finding frequent itemsets in data streams becomes complex. In this paper, we present an algorithm to mine top-k frequent closed itemsets using sliding window approach from streaming data. We developed a single-pass algorithm to find frequent closed itemsets of length between user‟s defined minimum and maximum-length. To improve the performance of algorithm and to avoid rescanning of data, we have transformed data into bitmap based tree data structure. Keyword: Data stream mining, Closed frequent itemsets, Approximate mining, Sliding window