Miracle-dz/UniFAR-FTUs huggingface dataset:
Customer Opinion Summarization Based on Twitter Conversations

As Twitter gains popularity, millions of messages are generated every day via this platform allowing people to communicate with each other through daily chatter and public conversations. This social content is usually considered more subjective than professional articles involving a lot of opinions and thoughts. This has stimulated many companies to use tweets to keep track and have general overview on their customer opinions about the brand. The conversational element of Twitter is of particular interest to the marketing community. However, most studies on summarizing customer opinions through Twitter, have so far employed single tweets rather than considering the whole conversations. As tweets are limited to 140 characters and usually written in an informal way, it is frequently hard to detect the exact meaning of the tweet when taken separately. In this paper, we propose a new approach for customer opinion summarization based on Twitter conversations named COSTwiC. We employ a new conversation-based method that employs conversation interactions to effectively extract the different product features as well as the polarity of the conversation messages. Experimentations show promising results. In particular, we have proved that incorporating conversation structure in the opinion summarization task contributes to improving system performance.
RNA-binding protein HuR promotes bladder cancer progression by competitively binding to the long noncoding HOTAIR with miR-1

The elevated expressions of RNA-binding protein HuR and long noncoding HOX transcript antisense RNA (HOTAIR) are observed in numerous cancers. And HuR often exerts its promotive effects on tumorigenesis via binding to AU-rich elements in target transcripts and thus regulating the expression of target transcripts. However, the roles and related mechanisms of HuR/HOTAIR in bladder cancer progression have never been formally tested. Here, we found that the expression level of HuR was higher in clinical bladder cancer samples than in normal adjacent samples, mirroring that of HOTAIR, and their expression showed strong correlation. Knockdown of HuR/HOTAIR in bladder cancer inhibited cell proliferation, migration, invasion, and promoted cell apoptosis. Notably, HuR interacted and stabilized HOTAIR mRNA and knockdown of HuR decreased HOTAIR expression. Additionally, HOTAIR was identified as a potential target of miR-1 in bladder cancer cells. Interestingly, overexpression of HOTAIR enhanced HuR expression and increased cytoplasmic accumulation of HuR, thus enhancing HOTAIR expression in turn. But mutation of miR-1 binding site in HOTAIR canceled the effects of HOTAIR on HuR expression. Overall, we identified a regulatory loop between HOTAIR and HuR during the progression of bladder cancer, which could be exploited to curb bladder cancer progression.
Sorting of β1-Adrenergic Receptors Is Mediated by Pathways That Are Either Dependent on or Independent of Type I PDZ, Protein Kinase A (PKA), and SAP97*

Background: β1-AR trafficking is regulated by its PDZ that binds to a complex composed of SAP97, AKAP79, and PKA. Results: Type I PDZ-mediated recycling of the β1-AR was dependent on PKA-mediated phosphorylation of Ser312, whereas trafficking by non-PDZs was PKA-independent. Conclusion: Divergent trafficking pathways were involved in β1-AR recycling by type I PDZs versus non-PDZs. Significance: These results provide a roadmap for GPCR trafficking pathways. The β1-adrenergic receptor (β1-AR) is a target for treatment of major cardiovascular diseases, such as heart failure and hypertension. Recycling of agonist-internalized β1-AR is dependent on type I PSD-95/DLG/ZO1 (PDZ) in the C-tail of the β1-AR and on protein kinase A (PKA) activity (Gardner, L. A., Naren, A. P., and Bahouth, S. W. (2007) J. Biol. Chem. 282, 5085–5099). We explored the effects of point mutations in the PDZ and in the activity of PKA on recycling of the β1-AR and its binding to the PDZ-binding protein SAP97. These studies indicated that β1-AR recycling was inhibited by PKA inhibitors and by mutations in the PDZ that interfered with SAP97 binding. The trafficking effects of short sequences differing in PDZ and SAP97 binding were examined using chimeric mutant β1-AR. β1-AR chimera containing the type I PDZ of the β2-adrenergic receptor that does not bind to SAP97 failed to recycle except when serine 312 was mutated to aspartic acid. β1-AR chimera with type I PDZ sequences from the C-tails of aquaporin-2 or GluR1 recycled in a SAP97- and PKA-dependent manner. Non-PDZ β1-AR chimera derived from μ-opioid, dopamine 1, or GluR2 receptors promoted rapid recycling of chimeric β1-AR in a SAP97- and PKA-independent manner. Moreover, the nature of the residue at position −3 in the PDZ regulated whether the β1-AR was internalized alone or in complex with SAP97. These results indicate that divergent pathways were involved in trafficking the β1-AR and provide a roadmap for its trafficking via type I PDZs versus non-PDZs.
Inconsistent Effects of Parietal α-tACS on Pseudoneglect across Two Experiments: A Failed Internal Replication

Transcranial electrical stimulation (tES) is being investigated as an experimental and clinical interventional technique in human participants. While promising, important limitations have been identified, including weak effect sizes and high inter- and intra-individual variability of outcomes. Here, we compared two “inhibitory” tES-techniques with supposedly different mechanisms of action as to their effects on performance in a visuospatial attention task, and report on a direct replication attempt. In two experiments, 2 × 20 healthy participants underwent tES in three separate sessions testing different protocols (10 min stimulation each) with a montage targeting right parietal cortex (right parietal–left frontal, electrode-sizes: 3cm × 3cm–7 cm × 5 cm), while performing a perceptual line bisection (landmark) task. The tES-protocols were compared as to their ability to modulate pseudoneglect (thought to be under right hemispheric control). In experiment 1, sham-tES was compared to transcranial alternating current stimulation at alpha frequency (10 Hz; α-tACS) (expected to entrain “inhibitory” alpha oscillations) and to cathodal transcranial direct current stimulation (c-tDCS) (shown to suppress neuronal spiking activity). In experiment 2, we attempted to replicate the findings of experiment 1, and establish frequency-specificity by adding a 45 Hz-tACS condition to α-tACS and sham. In experiment 1, right parietal α-tACS led to the expected changes in spatial attention bias, namely a rightward shift in subjective midpoint estimation (relative to sham). However, this was not confirmed in experiment 2 and in the complete sample. Right parietal c-tDCS and 45 Hz-tACS had no effect. These results highlight the importance of replication studies, adequate statistical power and optimizing tES-interventions for establishing the robustness and reliability of electrical stimulation effects, and best practice.
Conflict-Resolution Behavior in Adolescent Boys: Antecedents and Adaptational Correlates

We investigated three self-reported conflict-resolution behaviors (avoid, attack, and compromise) in a longitudinal study of eighty-one 10th-grade boys drawn from a school-based sample. Boys used all three conflict-resolution behaviors. Boys who frequently responded to parent-adolescent conflict with attack were at risk for the widest range of concurrent adaptational deficit, including both externalizing and internalizing problems. Avoidance was associated with internalizing problems, compromise with fewer problems of all types, and better school functioning. Sixth-grade antecedents of 10th-grade conflict-resolution behaviors included (a) child personality; (b) parents' management of their own affect; (c) inconsistent, rejecting, and supportive child rearing; and (d) family structure (intact, separated or divorced, and remarried). Results are interpreted in terms of modeling and arousal theories.
VolvoxDC : A new scalable data center network architecture

To contend with increasing requirement of cloud based applications nowadays, it is becoming very essential for the data center networks (DCN) to expand the network capacity very frequently. A good DCN topology must possess several properties for any dimensions of the network such as low diameter, high bisection bandwidth, low cost of deployment etc. Moreover, a DCN topology must also show efficiency in terms of scalability, failure resiliency, routing and construction. In this paper, we propose a novel DCN topology named VolvoxDC which resembles the structure of the similar named multi-cellular Algae Volvox which consists of thousands of cells within it. VolvoxDC is built up with several modules connected via perfect matchings and each module is constructed from an arbitrary diameter 2 graph. VolvoxDC shows excellent topological properties and it outperforms significant topologies like Fattree and Jellyfish in terms of providing a better cost effective design with more capacity.
Classifier systems and economic modeling

Human economic decisions are characterized by a number of factors which make them difficult to model with standard mathematical tools. Decisions can be more easily described by a set of rules, and some of them may be "rules of thumb". Economic behavior is adaptive, in that people are able to adjust to a changing environment. It is argued in this paper that the classifier system framework is a suitable means of modeling human economic decisions. A case of a simple economic decision of finding an optimal price is discussed, which is later made more complex by introducing an input variable that effects the optimal price. It is shown that classifier systems can be used in both tasks, and their performance is compared to human decisions in the same set of circumstances.
Efficient Rank Reduction of Correlation Matrices

Geometric optimisation algorithms are developed that efficiently find the nearest low-rank correlation matrix. We show, in numerical tests, that our methods compare favourably to the existing methods in the literature. The connection with the Lagrange multiplier method is established, along with an identification of whether a local minimum is a global minimum. An additional benefit of the geometric approach is that any weighted norm can be applied. The problem of finding the nearest low-rank correlation matrix occurs as part of the calibration of multi-factor interest rate market models to correlation.
Sampling Flies or Sampling Flaws? Experimental Design and Inference Strength in Forensic Entomology

ABSTRACT Forensic entomology is an inferential science because postmortem interval estimates are based on the extrapolation of results obtained in field or laboratory settings. Although enormous gains in scientific understanding and methodological practice have been made in forensic entomology over the last few decades, a majority of the field studies we reviewed do not meet the standards for inference, which are 1) adequate replication, 2) independence of experimental units, and 3) experimental conditions that capture a representative range of natural variability. Using a mock case-study approach, we identify design flaws in field and lab experiments and suggest methodological solutions for increasing inference strength that can inform future casework. Suggestions for improving data reporting in future field studies are also proposed.
Modified Particle Filtering for Wireless Tracking in Digital Broadcasting System

Digital broadcasting signal has the unique advantages for wireless location. In this paper, the pseudo-range measurement method based on OFDM signals is introduced. A mathematical model for wireless location and tracking is presented, which exploits the feature of continuous signal transmission at a fixed rate in digital broadcasting systems. After analyzing the disadvantage of classical particle filtering, i.e. sequential important sampling (SIR) filtering, a new particle filtering method using important sampling function based on EKF bank is proposed. Simulation showed that compared with the EKF and SIR particle filtering, the new algorithm can improve the estimation precision, and converge faster.
Consciousness and Free Will: A Critique of the Argument from Introspection

We can call this argument the introspective argument for free will. The introspective argument essentially maintains that, upon introspection, we do not seem to be causally determined—instead, we feel that our actions and decisions are freely decided by us—hence, we must be free. Libertarians, especially agent-causal theorists, take this introspective datum as their main evidence in support of free will.1 This kind of argument only works, however, if we assume the data is veridical. But, as we’ll see, there is reason to doubt the reliability of such introspective evidence. How do we know that our feeling of freedom isn’t an illusion? How do we know that what we introspect is accurate? Libertarians seldom question the “I feel myself free, therefore, I am free” argument. In fact, the introspective argument can be found throughout the literature. Given this, it is important that we investigate both the role of consciousness and the accuracy of introspection. Perhaps a closer examination of these issues will reveal that the nature of consciousness, rather than supporting free will further impugns it.
A Meta-Analysis on the Relationship between Self-Reported Presence and Anxiety in Virtual Reality Exposure Therapy for Anxiety Disorders

In virtual reality exposure therapy (VRET) for anxiety disorders, sense of presence in the virtual environment is considered the principal mechanism that enables anxiety to be felt. Existing studies on the relation between sense of presence and level of anxiety, however, have yielded mixed results on the correlation between the two. In this meta-analysis, we reviewed publications on VRET for anxiety that included self-reported presence and anxiety. The comprehensive search of the literature identified 33 publications with a total of 1196 participants. The correlation between self-reported sense of presence and anxiety was extracted and meta-analyzed. Potential moderators such as technology characteristics, sample characteristics including age, gender and clinical status, disorder characteristics and study design characteristics such as measurements were also examined. The random effects analysis showed a medium effect size for the correlation between sense of presence and anxiety (r = .28; 95% CI: 0.18–0.38). Moderation analyses revealed that the effect size of the correlation differed across different anxiety disorders, with a large effect size for fear of animals (r = .50; 95% CI: 0.30–0.66) and a no to small effect size for social anxiety disorder (r = .001; 95% CI: −0.19–0.19). Further, the correlation between anxiety and presence was stronger in studies with participants who met criteria for an anxiety disorder than in studies with a non-clinical population. Trackers with six degrees of freedom and displays with a larger field of view resulted in higher effect sizes, compared to trackers with three degrees of freedom and displays with a smaller field of view. In addition, no difference in effect size was found for the type of presence measurement and the type of anxiety measurement. This meta-analysis confirms the positive relation between sense of presence and anxiety and demonstrates that this relation can be affected by various moderating factors.
Cross-media Relevance Computation for Multimedia Retrieval

In this paper, we summarize our works for cross-media retrieval where the queries and retrieval content are of different media types. We study cross-media retrieval in the context of two applications, i.e., ~image retrieval by textual queries, and sentence retrieval by visual queries, two popular applications in multimedia retrieval. For image retrieval by textual queries, we proposetext2image which converts computing cross-media relevance between images and textual queries to comparing the visual similarity among images.We also proposecross-media relevance fusion, a conceptual framework that combines multiple cross-media relevance estimators.These two techniques have resulted in a winning entry in the Microsoft Image Retrieval Challenge at ACM MM 2015. For sentence retrieval by visual queries, we propose to compute cross-media relevance in a visual space exclusively. We contributeWord2VisualVec, a deep neural network architecture that learns to predict a visual feature representation from textual input. With proposedWord2VisualVec model, we won the Video to Text Description task at TRECVID 2016.
Remote sensing images matching of decomposed affine model via pixel migration

An approach of the edge feature matching of remote sensing images matching based on parameters decomposition of the affine transformation model is presented. Firstly, the adaptability of the affine transformation model used in the remote sensing images matching is analyzed, and parameters of the affine transformation model are decomposed. Secondly, the sum of squared gradient (SSG) similarity is constructed based on the edge feature in images, and the parameters of the special transformation model between the matching remote sensing images are solved with the Genetic Algorithms (GA) which is used to obtain the global optimum solution of the similarity. Finally, the performance of the approach is analyzed in theory and validated with remote sensing images matching experiments.
Identifying functional modules in protein–protein interaction networks: an integrated exact approach

Motivation: With the exponential growth of expression and protein–protein interaction (PPI) data, the frontier of research in systems biology shifts more and more to the integrated analysis of these large datasets. Of particular interest is the identification of functional modules in PPI networks, sharing common cellular function beyond the scope of classical pathways, by means of detecting differentially expressed regions in PPI networks. This requires on the one hand an adequate scoring of the nodes in the network to be identified and on the other hand the availability of an effective algorithm to find the maximally scoring network regions. Various heuristic approaches have been proposed in the literature. Results: Here we present the first exact solution for this problem, which is based on integer-linear programming and its connection to the well-known prize-collecting Steiner tree problem from Operations Research. Despite the NP-hardness of the underlying combinatorial problem, our method typically computes provably optimal subnetworks in large PPI networks in a few minutes. An essential ingredient of our approach is a scoring function defined on network nodes. We propose a new additive score with two desirable properties: (i) it is scalable by a statistically interpretable parameter and (ii) it allows a smooth integration of data from various sources. We apply our method to a well-established lymphoma microarray dataset in combination with associated survival data and the large interaction network of HPRD to identify functional modules by computing optimal-scoring subnetworks. In particular, we find a functional interaction module associated with proliferation over-expressed in the aggressive ABC subtype as well as modules derived from non-malignant by-stander cells. Availability: Our software is available freely for non-commercial purposes at http://www.planet-lisa.net. Contact: tobias.mueller@biozentrum.uni-wuerzburg.de
Pervasiveness of Dominant General Factors in Organizational Measurement

General factors are found in the measurement of many human traits. The concept of dominant general factors (DGFs) is introduced to represent the magnitude of general factors within numerous content domains. DGFs are defined as coming from the largest sources of reliable variance and influencing every variable measuring the construct. Although these factors are most frequently found in measures of cognitive ability, they are not limited to cognitive abilities. Examples are provided for a variety of construct and content domains along with estimates of their DGF percentages, ranging from 38% to 92%. Several reasons for these results are offered, and a call for concerted research is made. Research that ignores DGFs by treating specific factors or constructs within a domain as if they were distinct and uncorrelated can lead to errors in interpretation.
The complexity of acyclic conjunctive queries

This paper deals with the evaluation of acyclic Booleanconjunctive queries in relational databases. By well-known resultsof Yannakakis[1981], this problem is solvable in polynomial time;its precise complexity, however, has not been pinpointed so far. Weshow that the problem of evaluating acyclic Boolean conjunctivequeries is complete for LOGCFL, the class of decision problems thatare logspace-reducible to a context-free language. Since LOGCFL iscontained in AC1 and NC2, the evaluation problem of acyclic Booleanconjunctive queries is highly parallelizable. We present a paralleldatabase algorithm solving this problem with alogarithmic number ofparallel join operations. The algorithm is generalized to computingthe output of relevant classes of non-Boolean queries. We also showthat the acyclic versions of the following well-known database andAI problems are all LOGCFL-complete: The Query Output Tuple problemfor conjunctive queries, Conjunctive Query Containment, ClauseSubsumption, and Constraint Satisfaction. The LOGCFL-completenessresult is extended to the class of queries of bounded tree widthand to other relevant query classes which are more general than theacyclic queries.
Isolation and characterization of structural components of Bacillus cereus AHU 1356 cell walls.

From lysozyme digests of the N-acetylated cell walls of Bacillus cereus AHU 1356, a polysaccharide fraction and a teichoic acid fraction were isolated by ion-exchange chromatography and gel chromatography. The former fraction, accounting for 50% of the walls, contained N-acetylglucosamine, N-acetylmannosamine, N-acetylgalactosamine and glucose in a molar ratio of 4:1:1:1 together with a small amount of the peptidoglycan constituents. The latter fraction accounted for 5% of the walls and was composed of N-acetylglucosamine, galactose, glycerol and phosphorus in a molar ratio of 1:1.4:1:1 and a small amount of the peptidoglycan constituents. The molecular weight of the polysaccharide fraction was about 33000 as estimated by gel chromatography. After acid hydrolysis of the polysaccharide fraction, a stoichiometric amount of muramic acid 6-phosphate was detected which was probably involved in the linkage between the polysaccharide and peptidoglycan moieties. The polysaccharide moiety detached from the peptidoglycan components by mild acid hydrolysis was isolated as material with an approximate molecular weight of 28000. Structural studies on the polysaccharide, involving Smith degradation, CrO3 oxidation and proton magnetic resonance spectrometry of the polysaccharide fraction together with the analysis of oligosaccharides obtained from partial acid hydrolysis of the polysaccharide fraction, led to the tentative formulation of the most likely structure of the repeating unit as follows: