Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Buyers' Perceptions of Product Quality: From Seller and Product Signals to eWOM

Online transaction environment is full of uncertainties. To reduce online uncertainty, the first stage model examines the effect of extrinsic signals on perceived product quality, and the second stage model employs cue-diagnosticity framework to examine the influence of eWOM attributes (eWOM volume and eWOM consensus) on both perceived product quality and purchase intention. Our research questions are as follows, 1. Do IT-enabled solutions reduce uncertainty about sellers and products? 2. Do seller and product uncertainty affect buyers’ perceptions of product quality? 3. How do eWOM volume and eWOM consensus jointly influence buyers’ perceptions of product quality, and in turn their purchase intention? To answer these questions, this study will conduct two experiments. The first will explore the research model from the perspective of IT-enabled solutions in a laboratory setting, and the second will validate the effect of eWOM on perceived product quality based on the findings of the first experiment.
Integrating Blogging and Microblogging to Foster Learning and Social Interaction in Online Learning Communities

In this paper we explore a combination of social technologies and their use within higher education. Our research builds atop ongoing design science research looking to expand an existing online learning community (OLC) used at our university. Our new design implements the latest version of Elgg, an online social learning platform and integrates it with the popular microblogging site Twitter. The overarching goal of this research is to measure the impact these technologies have on levels of learning and social interaction inside and outside the classroom. We measure this impact across two undergraduate classes taking upper-division information systems courses. Initial findings indicate that while the blogging component of our OLC continues to provide high levels of learning and social interaction in the classroom, microblogging, while effective in bringing new information into the classroom, failed to have a significant impact on learning or interaction.
Towards a Workbench for Acquisition of Domain Knowledge from Natural Language

In this paper we describe an architecture and functionality of main components of a workbench for an acquisition of domain knowledge from large text corpora. The workbench supports an incremental process of corpus analysis starting from a rough automatic extraction and organization of lexico-semantic regularities and ending with a computer supported analysis of extracted data and a semiautomatic refinement of obtained hypotheses. For doing this the workbench employs methods from computational linguistics, information retrieval and knowledge engineering. Although the work-bench is currently under implementation some of its components are already implemented and their performance is illustrated with samples from engineering for a medical domain.
The Caspian Sea – Hindu Kush Index (CasHKI): definition, meteorological influences and Dust activities over southwest Asia

This work introduces for the first time a new meteorology/climatology Index over Asia, the so-called “Caspian Sea – Hindu Kush Index (CasHKI)”, which consists of changes in the mean sea level pressure (MSLP) gradient between two geographical domains over the Caspian Sea (40-50 o N, 50-55 o E) and Hindu Kush (35-40 o N, 70-75 o E). CasHKI is defined as the difference in MSLP anomalies between the Caspian Sea and Hindu Kush (MSLPanom.Casp – MSLPanom.HK) and is examined during the summer months (JuneSeptember) of 2000-2014 in view of modulating the atmospheric and climate dynamics and dust activity over southwest (SW) Asia. The CasHKI intensity and long-term trends are mostly modulated by the evolution in MSLP anomalies over the Caspian Sea, while the respective changes in Hindu Kush contribute to the CasHKI trends. A neutral-to-slight increasing trend (not statistically significant) in CasHKI is shown in all months during 2000-2014. The intensity in CasHKI enhances the MSLP over central Asia and deepens the Indo-Pakistan thermal low associated with the Indian summer monsoon. Larger wind speeds associated with a decrease in visibility, increase in dust emissions and slightly lower temperatures over Zabol are observed for the high CasHKI values. In synopsis, the high CasHKI modes enhance the near-surface and mid-troposphere northerlies over SW Asia, thus increasing the activation of the dust-sources and enhance the Asian continental outflow over the Arabian Sea.
Heap Abstractions for Static Analysis

Heap data is potentially unbounded and seemingly arbitrary. Hence, unlike stack and static data, heap data cannot be abstracted in terms of a fixed set of program variables. This makes it an interesting topic of study and there is an abundance of literature employing heap abstractions. Although most studies have addressed similar concerns, insights gained in one description of heap abstraction may not directly carry over to some other description. In our search of a unified theme, we view heap abstraction as consisting of two steps: (a) heap modelling, which is the process of representing a heap memory (i.e., an unbounded set of concrete locations) as a heap model (i.e., an unbounded set of abstract locations), and (b) summarization, which is the process of bounding the heap model by merging multiple abstract locations into summary locations. We classify the heap models as storeless, store based, and hybrid. We describe various summarization techniques based on k-limiting, allocation sites, patterns, variables, other generic instrumentation predicates, and higher-order logics. This approach allows us to compare the insights of a large number of seemingly dissimilar heap abstractions and also paves the way for creating new abstractions by mix and match of models and summarization techniques.
5 A Partition-Based Suffix Tree Construction and Its Applications

A suffix tree (also called suffix trie, PAT tree or, position tree) is a powerful data structure that presents the suffixes of a given string in a way that allows a fast implementation of important string operations. The idea behind suffix trees is to assign to each symbol of a string an index corresponding to its position in the string. The first symbol in the string will have the index 1, the last symbol in the string will have the index n, where n = number of symbols in the string. These indexes instead of actual objects are used for the suffix tree construction. Suffix trees provide efficient access to all substrings of a string. They are used in string processing (such as string search, the longest repeated substring, the longest common substring, the longest palindrome, etc), text processing (such as editing, free-text search, etc), data compression, data clustering in search machines, etc. Suffix trees are important and popular data structures for processing long DNA sequences. Suffix trees are often used for efficient solving a variety computational biology and/or bioinformatics problems (such as searching for patterns in DNA or protein sequences, exact and approximate sequence matching, repeat finding, anchor finding in genome alignment, etc). A suffix tree displays the internal structure of a string in a deeper way. It can be constructed and represented in time and space proportional to the length of a sequence. A suffix tree requires affordable amount of memory. It can be fitted completely in the main memory of the present desktop computers. The linear construction time and space and the short search time are good features of suffix trees. They increase the importance of suffix trees. A suffix tree construction process is space demanding and may be a fatal in the case of a suffix tree to handle a huge number of long DNA sequences. Increasing the number of sequences to be handled, due to random access, causes degrades of the suffix tree construction process performance that uses suffix links. Thus, some approaches completely abandon the use of suffix link and give up the theoretically superior linear construction time for a quadratic time algorithm with better locality of reference.
Arterial Stiffness, Cognitive Decline, and Risk of Dementia: The Rotterdam Study

Background and Purpose— Arterial stiffness is associated with an increased risk of myocardial infarction and stroke, independent of classical vascular risk factors. Vascular factors and stroke are associated with cognitive function and dementia. We examined whether arterial stiffness was independently associated with cognitive function and dementia. Methods— The present study was based on the Rotterdam Study, a prospective population-based cohort study ongoing since 1990. During the third examination (1997–1999) arterial stiffness was measured by assessment of pulse wave velocity and carotid distensibility. Cognitive function was assessed during the third and fourth examination (2002–2004) with a neuropsychological test battery. We used linear and logistic regression to estimate the association of arterial stiffness with cognitive function and cognitive decline. From the third examination until January 1, 2005, we identified 156 incident dementia cases. Cox proportional hazard models were used to estimate the association between arterial stiffness and the risk of dementia. Results— After adjustment for cardiovascular risk factors we found an association of increased pulse wave velocity with poorer performance on the Stroop test (adjusted &bgr;-coefficient [95% confidence interval] 1.13 [0.26 to 1.99] per standard deviation increase in pulse wave velocity) but not with performance on other cognitive tests. No associations were found between measures of arterial stiffness and cognitive decline or risk of dementia after adjustment for cardiovascular factors. Conclusions— We did not identify arterial stiffness as an independent risk factor of cognitive decline or risk of dementia.
Scattering and Placing Data Replicas to Enhance Long-Term Durability

Distributed storage systems have to ensure data availability and durability despite the occurrence of failures. To do so, many of them rely on replication mechanisms. We show that the layout of the data block copies on the nodes, chiefly the way the copies are scattered, has a major impact on the reparation speed and thus on the data loss ratio. In this paper, we propose an approach that provides the ability: (i) to finely tune the proportion of common content stored by the nodes, and (ii) to control the storage load distribution while creating new data block copies. We propose a simulation model that allows us to present a long-term study of the impact of the data block copies layout and the system's storage load on the data loss ratio.
Enhanced Adsorption of Methylene Blue Dye on Functionalized Multi-Walled Carbon Nanotubes

Carbon nanomaterials are promising adsorbents for dye removal from wastewater also due to their possible surface functionalization that, in principle, can increase the adsorption rate and provide regeneration. To investigate the real advantages of functionalization, we synthesized and characterized through IR, TGA, TEM, XPS and DLS measurements a multi-walled carbon nanotube (MWCNT) derivative bearing benzenesulfonate groups (MWCNT-S). The obtained material demonstrated to have good dispersibility in water and better capability to adsorb methylene blue (MB) compared to the pristine MWCNT adsorbent. Adsorption kinetic studies showed a very fast process, with a constant significantly higher with respect not only to that of the unfunctionalized MWCNT adsorbent but also to those of widely used activated carbons. Moreover, the adsorption capacity of MWCNT-S is more than doubled with respect to that of the insoluble pristine MWCNT adsorbent, thanks to the dispersibility of the derivatives, providing a larger available surface, and to the possible electrostatic interactions between the cationic MB and the anionic sulfonate groups. Additionally, the reversibility of ionic interactions disclosed the possibility to release the adsorbed cationic pollutant through competition with salts, not only regenerating the adsorbent, but also recovering the dye. Indeed, by treating the adsorbed material for 1 h with 1 M NaCl, a regeneration capacity of 75% was obtained, demonstrating the validity of this strategy.
CICBUAPnlp at SemEval-2016 Task 4-A: Discovering Twitter Polarity using Enhanced Embeddings

This paper presents our approach for SemEval 2016 task 4: Sentiment Analysis in Twitter. We participated in Subtask A: Message Polarity Classiﬁcation. The aim is to classify Twitter messages into positive, neutral, and negative polarity. We used a lexical resource for pre-processing of social media data and train a neural network model for feature representation. Our resource includes dictionaries of slang words, contractions, abbreviations
A 2.2-mW Backgate Coupled  $LC$ Quadrature VCO With Current Reused Structure

This letter presents a backgate coupled quadrature voltage-controlled oscillator (QVCO) which consists of a pair of current reused LC-VCOs. The proposed QVCO is designed for 2-GHz operation based on a 0.18-mum triple-well CMOS technology. Measurements show -102 and -124dBc/Hz at 100-kHz and 1-MHz offset, respectively. Compared to the conventional QVCO, the proposed QVCO dissipates significantly lower power (1.74mA from a 1.25-V supply) while showing good 1/f3 close-in phase noise
Protein kinase C-theta (PKCθ) phosphorylates and inhibits the guanine exchange factor, GIV/Girdin

Gα-interacting, vesicle-associated protein (GIV/Girdin) is a multidomain signal transducer that enhances PI3K-Akt signals downstream of both G-protein–coupled receptors and growth factor receptor tyrosine kinases during diverse biological processes and cancer metastasis. Mechanistically, GIV serves as a non-receptor guanine nucleotide exchange factor (GEF) that enhances PI3K signals by activating trimeric G proteins, Gαi1/2/3. Site-directed mutations in GIV’s GEF motif disrupt its ability to bind or activate Gi and abrogate PI3K-Akt signals; however, nothing is known about how GIV’s GEF function is regulated. Here we report that PKCθ, a novel protein kinase C, down-regulates GIV’s GEF function by phosphorylating Ser(S)1689 located within GIV’s GEF motif. We demonstrate that PKCθ specifically binds and phosphorylates GIV at S1689, and this phosphoevent abolishes GIV’s ability to bind and activate Gαi. HeLa cells stably expressing the phosphomimetic mutant of GIV, GIV-S1689→D, are phenotypically identical to those expressing the GEF-deficient F1685A mutant: Actin stress fibers are decreased and cell migration is inhibited whereas cell proliferation is triggered, and Akt (a.k.a. protein kinase B, PKB) activation is impaired downstream of both the lysophosphatidic acid receptor, a G-protein–coupled receptor, and the insulin receptor, a receptor tyrosine kinase. These findings indicate that phosphorylation of GIV by PKCθ inhibits GIV's GEF function and generates a unique negative feedback loop for downregulating the GIV-Gi axis of prometastatic signaling downstream of multiple ligand-activated receptors. This phosphoevent constitutes the only regulatory pathway described for terminating signaling by any of the growing family of nonreceptor GEFs that modulate G-protein activity.
Threshold extraction in metabolite concentration data

MOTIVATION Continued development of analytical techniques based on gas chromatography and mass spectrometry now facilitates the generation of larger sets of metabolite concentration data. An important step towards the understanding of metabolite dynamics is the recognition of stable states where metabolite concentrations exhibit a simple behaviour. Such states can be characterized through the identification of significant thresholds in the concentrations. But general techniques for finding discretization thresholds in continuous data prove to be practically insufficient for detecting states due to the weak conditional dependences in concentration data. RESULTS We introduce a method of recognizing states in the framework of decision tree induction. It is based upon a global analysis of decision forests where stability and quality are evaluated. It leads to the detection of thresholds that are both comprehensible and robust. Applied to metabolite concentration data, this method has led to the discovery of hidden states in the corresponding variables. Some of these reflect known properties of the biological experiments, and others point to putative new states. AVAILABILITY An implementation of this approach can be obtained from the authors upon request.
Verb transitivity bias affects on-line sentence reading in people with aphasia

Background: Studies of sentence comprehension in non-disordered populations have convincingly demonstrated that probabilistic cues influence on-line syntactic processing. One well-studied cue is verb argument structure bias, which refers to the probability that a verb will occur in a particular syntactic frame. According to the Lexical Bias Hypothesis people with aphasia have difficulty understanding sentences in which the verb's argument structure bias conflicts with the sentence structure (e.g., a transitively biased verb in an intransitive sentence). This hypothesis may provide an account of why people with aphasia have difficulty understanding both simple and complex sentences. Aims: The purpose of this study was to test the Lexical Bias Hypothesis using an on-line measure of written sentence comprehension, self-paced reading. Methods & Procedures: The participants were 10 people with aphasia and 10 non-brain-damaged controls. The stimuli were syntactically simple transitive and intransitive sentences that contained transitively or intransitively biased verbs. For example, the transitively biased verb “called” appeared in sentences such as “The agent called (the writer) from overseas to make an offer. ” The intransitively biased verb “danced” appeared in sentences such as “The couple danced (the tango) every Friday night last summer. ” Outcomes & Results: Both groups' reading times for critical segments were longer when the verb's transitivity bias did not match the sentence structure, particularly in intransitive sentences. Conclusions: The results were generally consistent with the Lexical Bias Hypothesis, and demonstrated that lexical biases affect on-line processing of syntactically simple sentences in people with aphasia and controls.
Mechanical properties and fretting behavior of sulfide film

On sliding or fretting contacts, sulfide films may cause many kinds of problems. On some conditions, sulfide films may be removed; and on other conditions, they are very sticky. These phenomena are not fully understood and the characteristics of sulfide films are not very clear. Many papers have been published on electric contact behavior of sulfide films. However, mechanical properties of them are neglected. Nevertheless, the mechanical properties may be very helpful to understand their electric contact behavior. This is the basic requirement of this paper. Wires of copper and silver, copper coupons, and silver plated coupons were exposed in H/sub 2/S gas environment. Wires and coupons after corrosion were cross-sectioned to observe the growth of sulfide films which were identified by X-ray energy dispersive spectroscopy (XES). Tensile strength and Young's modulus of the wires covered by sulfide films were studied by the specific micro-tension testing machine. A tentative calculation was made for the tensile strength of Cu/sub 2/S. The mechanical property probe-Nano Indenter II was also used to measure Young's modulus of sulfide films covered on coupon surfaces. The relationship between electric contact behavior of sulfide films and mechanical properties are discussed.
A QoS Routing Protocol based on Available Bandwidth Estimation for Wireless Ad Hoc Networks

At the same time as the emergence of multimedia in mobile Ad hoc networks, research for the introduction of the quality of service (QoS) has received much attention. However, when designing a QoS solution, the estimation of the available resources still represents one of the main issues. This paper suggests an approach to estimate available resources on a node. This approach is based on the estimation of the busy ratio of the shared canal. We consider in our estimation the several constraints related to the Ad hoc transmission mode such as Interference phenomena. This approach is implemented on the AODV routing protocol. We call AODVwithQOS our new routing protocol. We also performed a performance evaluation by simulations using NS2 simulator. The results confirm that AODVwithQoS provides QoS support in ad hoc wireless networks with good performance and low overhead.
Dance of the SNAREs: Assembly and Rearrangements Detected with FRET at Neuronal Synapses

Soluble N-ethylmaleimide-sensitive fusion protein attachment protein receptors (SNAREs) mediate vesicle fusion with the plasma membrane on activation by calcium binding to synaptotagmin. In the present study, we used fluorescence resonance energy transfer (FRET) and fluorescence lifetime imaging microscopy between fluorescently labeled SNARE proteins expressed in cultured rat hippocampal neurons to detect resting SNARE complexes, their conformational rearrangement on exocytosis, their disassembly before endocytosis of vesicular proteins, and SNARE assembly at newly docked vesicles. Assembled SNAREs are not only present in docked vesicles; unexpected residual “orphan SNARE complexes” also reside in para-active zone regions. Real-time changes in FRET between N-terminally labeled SNAP-25 and VAMP reported a reorientation of the SNARE motif upon exocytosis, SNARE disassembly in the active zone periphery, and SNARE reassembly in newly docked vesicles. With VAMP labeled C-terminally, decreased fluorescence in C-terminally labeled syntaxin (extracellular) reported trans-cis-conformational changes in SNAREs on vesicle fusion. After fusion SNAP-25 and syntaxin disperse along with VAMP, as well as the FRET signal itself, indicating diffusion of intact SNAREs after vesicle fusion but before their peripheral disassembly. Our measurements of spatiotemporal dynamics of SNARE conformational changes and movements refine models of SNARE function. Technical advances required to detect tiny changes in fluorescence in small fractions of labeled proteins in presynaptic boutons on a time scale of seconds permit the detection of rapid intermolecular interactions between small proportions of protein partners in cellular subcompartments.
Exergy and Energy Analysis of Diesel Engine using Karanja Methyl Ester under Varying Compression Ratio

In the present study, there is a need to reduce the consumption of conventional fuel and related fossil fuels. So, in order to promote the use of renewable sources such as biofuels there is a requirement for the effective evaluation of the performance of engines based on the second law of thermodynamic. In this paper, the analysis of energy, exergy, mean gas temperature and exhaust gas temperature of a compression ignition (CI) engine using diesel and Karanja methyl ester blends are done. The results are calculated at various compression ratios under full load and at different engine loads at a compression ratio of 18:1. It is observed that the exergy efficiency, mean gas temperature, brake thermal efficiency increases with increase in compression ratio as well as load. The exhaust gas temperature and destruction of exergy decreases with increase in compression ratio and increases with increase in load for all blends of fuel.