Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing the Commitment to Virtual Community: A Belief and Feeling Based Approach

Web-based virtual communities are regarded as potential channels for conducting e-commerce because of their capabilities in building long-term relationships between the vendor and the members. A virtual community (VC) provides repeat points of contact to the customer, thus increasing the stickiness of the Web site. This ability of a VC to retain people or customers to the Website of an online vendor is useful for relationship management, central to which is the relationship commitment of the customers to the VC. By having a community of committed customers, a vendor can obtain numerous benefits especially relevant to relationship marketing (like enhanced store image and loyalty). This study examines the factors which enhance online customers’ relationship commitment to the VC from the balanced beliefs and feelings perspective. By adapting the behavior model developed by Fazio et al. (1978), this study examines the roles of beliefs and feelings of the customer in the formation of commitment to a VC. This study then offers theoretical reasoning for the balanced effects of customers’ beliefs and feelings on enhancing the commitment to the VC and discusses the theoretical and practical implications of this study.
Resilience of the internet to random breakdowns

A common property of many large networks, including the Internet, is that the connectivity of the various nodes follows a scale-free power-law distribution, P(k) = ck(-alpha). We study the stability of such networks with respect to crashes, such as random removal of sites. Our approach, based on percolation theory, leads to a general condition for the critical fraction of nodes, p(c), that needs to be removed before the network disintegrates. We show analytically and numerically that for alpha</=3 the transition never takes place, unless the network is finite. In the special case of the physical structure of the Internet (alpha approximately 2.5), we find that it is impressively robust, with p(c)>0.99.
Bank Characteristics and Cyclical Variations in Bank Stock Returns

This paper investigates whether the stock returns of banks with different risk profiles exhibit different risk factor sensitivities over the business cycle. More specifically, we investigate whether or not capitalization, functional diversification, and geographical diversification provide banks with a structural hedge against a deterioration in the prevailing credit conditions. First, based on recent imperfect capital market theories, we offer some theoretical ground for the existence of asymmetries in systematic risk across various types of banks. Second, a regime-switching model is used to test the theoretical hypotheses empirically. We find that bank stock returns are strongly asymmetric: both the size of shocks and the conditional volatility is higher during business cycle troughs. Relatively poorly capitalized banks have a lower volatility than relatively highly capitalized banks, but react nevertheless stronger to bad news. JEL: G12, G21, F34
Intentradar: search user interface that anticipates user's search intents

We introduce IntentRadar, an interactive search user interface that anticipates user's search intents by estimating them from user interaction. The estimated intents are represented as keywords and visualized on a radial layout that organizes the keywords as directions in the information space. IntentRadar assists users to direct their search by allowing to target relevance feedback on keywords by manipulating the position of the keywords on the radar. The system then learns and visualizes improved estimates of intents and retrieves documents corresponding to the present search intent estimate. IntentRadar has been shown to significantly improve users' task performance and the quality of retrieved information without compromising task execution time.
Comparative Study of Reproductive Development in Wild and Captive-Reared Greater Amberjack Seriola dumerili (Risso, 1810)

The greater amberjack Seriola dumerili is a large teleost fish with rapid growth and excellent flesh quality, whose domestication represents an ambitious challenge for aquaculture. The occurrence of reproductive dysfunctions in greater amberjack reared in captivity was investigated by comparing reproductive development of wild and captive-reared individuals. Wild and captive-reared breeders were sampled in the Mediterranean Sea during three different phases of the reproductive cycle: early gametogenesis (EARLY, late April-early May), advanced gametogenesis (ADVANCED, late May-early June) and spawning (SPAWNING, late June-July). Fish reproductive state was evaluated using the gonado-somatic index (GSI), histological analysis of the gonads and determination of sex steroid levels in the plasma, and correlated with leptin expression in the liver and gonad biochemical composition. The GSI and sex steroid levels were lower in captive-reared than in wild fish. During the ADVANCED period, when the wild greater amberjack breeders were already in spawning condition, ovaries of captive-reared breeders showed extensive atresia of late vitellogenic oocytes and spermatogenic activity ceased in the testes of half of the examined males. During the SPAWNING period, all captive-reared fish had regressed gonads, while wild breeders still displayed reproductive activity. Liver leptin expression and gonad proximate composition of wild and captive greater amberjack were similar. However, the gonads of captive-reared fish showed different total polar lipid contents, as well as specific lipid classes and fatty acid profiles with respect to wild individuals. This study underlines the need for an improvement in rearing technology for this species, which should include minimum handling during the reproductive season and the formulation of a specific diet to overcome the observed gonadal decrements of phospholipids, DHA (22:6n-3) and ARA (20:4n-6), compared to wild breeders.
Exploiting group recommendation functions for flexible preferences

We examine the problem of enabling the flexibility of updating one's preferences in group recommendation. In our setting, any group member can provide a vector of preferences that, in addition to past preferences and other group members' preferences, will be accounted for in computing group recommendation. This functionality is essential in many group recommendation applications, such as travel planning, online games, book clubs, or strategic voting, as it has been previously shown that user preferences may vary depending on mood, context, and company (i.e., other people in the group). Preferences are enforced in an feedback box that replaces preferences provided by the users by a potentially different feedback vector that is better suited for maximizing the individual satisfaction when computing the group recommendation. The feedback box interacts with a traditional recommendation box that implements a group consensus semantics in the form of Aggregated Voting or Least Misery, two popular aggregation functions for group recommendation. We develop efficient algorithms to compute robust group recommendations that are appropriate in situations where users have changing preferences. Our extensive empirical study on real world data-sets validates our findings.
Low-Rank Matrix Factorization With Adaptive Graph Regularizer

In this paper, we present a novel low-rank matrix factorization algorithm with adaptive graph regularizer (LMFAGR). We extend the recently proposed low-rank matrix with manifold regularization (MMF) method with an adaptive regularizer. Different from MMF, which constructs an affinity graph in advance, LMFAGR can simultaneously seek graph weight matrix and low-dimensional representations of data. That is, graph construction and low-rank matrix factorization are incorporated into a unified framework, which results in an automatically updated graph rather than a predefined one. The experimental results on some data sets demonstrate that the proposed algorithm outperforms the state-of-the-art low-rank matrix factorization methods.
An Improved DSSS-Based Flow Marking Technique for Anonymous Communication Traceback

The widely use of anonymous communication systems, which aim at protecting the privacy of Internet users, has posed significant challenges to the capability of tracing cyber crimes. To address the problems of anonymous abuse, Yu et al. recently developed a new class of flow marking technique for invisible traceback based on Direct Sequence Spread Spectrum (DSSS), utilizing a Pseudo-Noise (PN) code. However, there exists one limitation in this technique that the suspect flow to embed flow mark into must have a fixed traffic rate, while it’s not the case for most use of anonymous communication systems, such as web browse, instant communication and remote login. In this paper, an improved approach is proposed, which embeds signal by modulating the statistical character of packets arriving time instead of traffic rate. The experiment results show that this new technique is effective and efficient in detecting interactive traffic through anonymous communication systems and has wider applicability compared with the original DSSS-based flow marking technique.
Tropical Cyclogenesis Associated with Rossby Wave Energy Dispersion of a Preexisting Typhoon. Part I: Satellite Data Analyses*

Abstract The structure and evolution characteristics of Rossby wave trains induced by tropical cyclone (TC) energy dispersion are revealed based on the Quick Scatterometer (QuikSCAT) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) data. Among 34 cyclogenesis cases analyzed in the western North Pacific during 2000–01 typhoon seasons, six cases are associated with the Rossby wave energy dispersion of a preexisting TC. The wave trains are oriented in a northwest–southeast direction, with alternating cyclonic and anticyclonic vorticity circulation. A typical wavelength of the wave train is about 2500 km. The TC genesis is observed in the cyclonic circulation region of the wave train, possibly through a scale contraction process. The satellite data analyses reveal that not all TCs have a Rossby wave train in their wakes. The occurrence of the Rossby wave train depends to a certain extent on the TC intensity and the background flow. Whether or not a Rossby wave train can finally lead to cy.
An RF-Based System for Tracking Transceiver-Free Objects

In traditional radio-based localization methods, the target object has to carry a transmitter (e.g., active RFID), a receiver (e.g., 802.11x detector), or a transceiver (e.g., sensor node). However, in some applications, such as safe guard systems, it is not possible to meet this precondition. In this paper, we propose a model of signal dynamics to allow tracking of transceiver-free objects. Based on radio signal strength indicator (RSSI), which is readily available in wireless communication, three tracking algorithms are proposed to eliminate noise behaviors and improve accuracy. The midpoint and intersection algorithms can be applied to track a single object without calibration, while the best-cover algorithm has potential to track multiple objects but requires calibration. Our experimental test-bed is a grid sensor array based on MICA2 sensor nodes. The experimental results show that the best side length between sensor nodes in the grid is 2 meters and the best-cover algorithm can reach localization accuracy to 0.99 m
Identification of Reproduction-Related Gene Polymorphisms Using Whole Transcriptome Sequencing in the Large White Pig Population

Recent developments in high-throughput sequencing techniques have enabled large-scale analysis of genetic variations and gene expression in different tissues and species, but gene expression patterns and genetic variations in livestock are not well-characterized. In this study, we have used high-throughput transcriptomic sequencing of the Finnish Large White to identify gene expression patterns and coding polymorphisms within the breed in the testis and oviduct. The main objective of this study was to identify polymorphisms within genes that are highly and specifically expressed in male and/or female reproductive organs. The differential expression (DE) analysis underlined 1234 genes highly expressed in the testis and 1501 in the oviduct. Furthermore, we used a novel in-house R-package hoardeR for the identification of novel genes and their orthologs, which underlined 55 additional DE genes based on orthologs in the human, cow, and sheep. Identification of polymorphisms in the dataset resulted in a total of 29,973 variants, of which 10,704 were known coding variants. Fifty-seven nonsynonymous SNPs were present among genes with high expression in the testis and 67 were present in the oviduct, underlining possible influential genes for reproduction traits. Seven genes (PGR, FRAS1, TCF4, ADAT1, SPAG6, PIWIL2, and DNAH8) with polymorphisms were highlighted as reproduction-related based on their biological function. The expression and SNPs of these genes were confirmed using RT-PCR and Sanger sequencing. The identified nonsynonymous mutations within genes highly expressed in the testis or oviduct provide a list of candidate genes for reproduction traits within the pig population and enable identification of biomarkers for sow and boar fertility.
Towards Fish Lipid Nutrigenomics: Current State and Prospects for Fin-Fish Aquaculture

Lipids are the predominant source of energy for fish. The mechanisms by which fish allocate energy from lipids for metabolism, development, growth, and reproduction are critical for understanding key life-history strategies and transitions. Currently, the major lipid component in aquaculture diets is fish oil (FO), derived from wild capture fisheries that are exploited at their maximum sustainable limit. The increasing demand from aquaculture for FO will soon exceed supply and threaten the viability of aquaculture. Thus, it is essential to minimize FO use in aquaculture diets. This might be achieved by a greater understanding of lipid storage and muscle growth, or the identification of alternatives to FO in feeds. This review focuses on recent research applying molecular and genomic techniques to the study of fin-fish lipid metabolism from an aquaculture perspective. Accordingly, particular emphasis will be given to fatty acid metabolism and to highly unsaturated fatty acid (HUFA) biosynthesis and to the transcriptional mechanisms and endocrine factors that regulate these processes in fish. Comparative studies of gene function and distribution are described, which, when integrated with recent fish genome sequence information, provide insights into lipid homeostasis and the outcomes associated with the replacement of FO in fish diets.
A street reference model of MIMO vehicle-to-vehicle fading channel

In future, cars will form a network with other cars and roadside data systems to exchange information that alerts the driver on traffic congestion, road conditions, and accidents. It is expected that vehicle-to-vehicle communication systems will play an important role in intelligent transportation systems. MIMO systems employ multiple transmit and multiple receive antennas, combined with the opportunities opened by large vehicle surfaces on which multielement antennas can be placed, makes MIMO techniques very attractive for vehicle-to-vehicle communications. In this paper, we propose an original street model for MIMO vehicle-to-vehicle fading channels, derived from this model, the analysis of statistical properties of transmit and the receive correlation functions is given, and some numerical results for the special case of isotropic scattering are presented. Our procedure provides also an important framework for studying the channel capacity of MIMO vehicle-to-vehicle channels, channel coding and wireless intelligent transportation systems planning.
Repertoire of Protein Kinases Encoded in the Genome of Takifugu rubripes

Takifugu rubripes is teleost fish widely used in comparative genomics to understand the human system better due to its similarities both in number of genes and structure of genes. In this work we survey the fugu genome, and, using sensitive computational approaches, we identify the repertoire of putative protein kinases and classify them into groups and subfamilies. The fugu genome encodes 519 protein kinase-like sequences and this number of putative protein kinases is comparable closely to that of human. However, in spite of its similarities to human kinases at the group level, there are differences at the subfamily level as noted in the case of KIS and DYRK subfamilies which contribute to differences which are specific to the adaptation of the organism. Also, certain unique domain combination of galectin domain and YkA domain suggests alternate mechanisms for immune response and binding to lipoproteins. Lastly, an overall similarity with the MAPK pathway of humans suggests its importance to understand signaling mechanisms in humans. Overall the fugu serves as a good model organism to understand roles of human kinases as far as kinases such as LRRK and IRAK and their associated pathways are concerned.
Evaluating Natural Language Processing Techniques in Information Retrieval : a Trec Perspective

Natural language processing techniques may hold a tremendous potential for overcoming the inadequacies of purely quantitative methods of text information retrieval, but the empirical evidence to support such predictions has thus far been inadequate, and appropriate scale evaluations have been slow to emerge. In this chapter, we report on the progress of the Natural Language Information Retrieval project, a joint effort of several sites led by GE Research, and its evaluation in a series of Text Retrieval Conferences (TREC) conducted since 1992 under the auspices of the National Institute of Standards and Technology (NIST) and the Defense Advanced Research Projects Agency (DARPA).
Towards a collaborative framework to improve urban grid resilience

Two trends will help to ensure resilient electricity supply in Smart Cities: a) the ongoing deployment of Smart Grid technology and b) the adoption of distributed energy resources. Unfortunately, the increased reliance on ICT in the Smart Grid will expose new threats that could result in incidents that might affect urban electricity distribution networks by causing power outages. Diverse specialists will need to cooperate to address these threats. This position paper outlines a methodology for establishing a collaborative framework that supports the definition of response strategies to threats. We consider the ongoing evolution of the electricity grids and the threats emerging while the grid evolves. After outlining possible scenarios of urban grid development, we highlight several threats and the strategies of attackers. Finally, we introduce a framework that aims to foster the collaboration of stakeholders involved in city resilience planning taking into account grid vulnerability and criticality from a city's perspective.
Learning Signals from the Superior Colliculus for Adaptation of Saccadic Eye Movements in the Monkey

Vital to motor learning is information about movement error. Using this information, the brain creates neural learning signals that instruct a plasticity mechanism to produce appropriate behavioral learning. Little is known, however, about brain structures that generate learning signals for voluntary movements. Here we show that signals from the superior colliculus (SC) can drive learning in saccadic eye movements in the monkey. Electrical stimulation of the SC deeper layers, subthreshold for evoking saccades, was applied immediately (∼60 ms) after the end of horizontal saccades in one or both directions. The target disappeared during saccades and remained invisible for 1 s to eliminate effects of postsaccadic visual information. Repetitive pairing of saccades with SC stimulation produced a marked, two-dimensional shift in movement endpoint relative to the target location. The elicited endpoint shift took a gradual, approximately exponential course over several hundred saccades as in visually induced saccade adaptation. The shift in movement endpoint remained nearly unchanged after stimulation was discontinued, indicating involvement of neuronal plasticity. When both rightward and leftward saccades were paired with stimulation, their endpoints shifted in similar directions. The endpoint shift was directed contralaterally to the stimulated SC. The direction and size of the endpoint shift depended on the stimulation site in the SC. We propose that the SC, a brainstem structure long known to be crucial for saccade execution, is involved in motor learning and sends signals that dictate the direction of adaptive shift in saccade endpoint.
Factors Affecting Consumer Satisfaction of Online Purchase

Consumers frequently engage in pre-purchase search to extract up-to-date information for their purchase decisions. Search is an essential part of online comparison-shopping and decision-making process as it reduces purchase related uncertainty and increases the likelihood of purchase satisfaction. In this paper, we study how determinants of pre-purchase search, purchase related uncertainty and the type of the search process, influence consumers' perceived satisfaction with the online purchase. Our analysis of 351 consumers show that the classic determinants such as product class knowledge, time availability, attitudes toward shopping, and search effort do not significantly affect perceived purchase satisfaction. Instead, we find that involvement and purchase related uncertainties have stronger effect on satisfaction. However, the type of the search process turned out to be the most important factor behind perceived purchase satisfaction.
MagiXen: Combining Binary Translation and Virtualization

Virtualization is emerging as an important technology in future systems, providing an extra layer of abstraction between the hardware and operating system. Previous work on virtualization has focused on the partitioning, isolation, and encapsulation features of virtual machines and their use for different applications, but mainly in the context of a speciﬁc processor architecture. In this paper, we argue for integrating an interface transformation layer to virtualization, speciﬁcally combining virtualization with a dynamic binary translator. This feature signiﬁcantly increases the beneﬁts from current applications of virtualization (e.g., for server consolidation and resource provisioning) while potentially enabling additional new uses of virtualization matched with emerging trends (e.g., virtual appliances and heterogeneous hardware). We have built MagiXen — pronounced “magi-cian” — a prototype implementation of a Xen virtual machine monitor with integrated binary translation that can run IA-32 virtual machines on Itanium platforms. We present performance results for several typical benchmarks and discuss insights from our experiences with building the prototype.
Multiple linear regression modelling of parcels' distribution design factors and online shopping customer satisfaction

In this era of technology, online shopping for goods and services has become more common and user-friendly due to the majority of the population owning gadgets that enable them to connect to the internet. Thus, parcels deliveries exist when the online shoppers purchase goods from online shops. The purpose of this paper is to examine the relationship between parcels' distribution design factors and online shopping customer satisfaction. A questionnaire survey was carried out among 384 respondents from Cheras, Kuala Lumpur. Based on the survey, response time and returnability have an impact on online shopping customer's satisfaction. Meanwhile, service variety, service availability and order visibility has no significant impact on the customer's satisfaction. This paper emphasise the importance of current and future courier service's to focus on the response time and returnability in order to meet the online shopper's satisfaction. Recommendations and limitations of this study are also discussed.