Miracle-dz/UniFAR-FTUs huggingface dataset:
User Motivation to Explore Enterprise System Features: An Exploratory Study of Its Organizational Antecedents and Consequences

To attain the strategic goal of deriving competitive advantage from Enterprise System (ES) adoption, organizations rely on users’ exploration of the system features and eventually integrating the system application tightly with job tasks. Research on how to align users’ interest with the organization’s strategic goal and enhance user motivation to explore ES features is of great significance but lacking. Drawing upon organizational psychology and information systems theories, this paper investigates the organizational mechanisms (i.e., reward system, autonomy job design, and socialization tactics) enhancing user motivation (i.e., extrinsic, intrinsic and normative motivation) to explore ES features, the moderating effect of individual motivational system (prevention focus in particular) on the association between organizational mechanisms and motivation, and how different types of motivation affect cognitive and affective exploration outcomes. Our research model is tested by data collected from individual users through a longitudinal two-wave survey. Theoretical contributions and managerial implication of this study are discussed.
Towards Secure and Privacy-Preserving Online Social Networking Services

Online social networking services (e.g., Facebook, Twitter, and Blogger) bring new benefits to almost all aspects of our lives. They have completely transformed how we communicate with each other, how we process information, and how we diffuse social influence. However, these social networking services are also plagued by both conventional and emerging threats to security and privacy. For instance, two fundamental security risks are 1) users’ accounts are compromised by attackers or get lost and 2) attackers create massive fake (or Sybil) accounts to launch various malicious activities. In this thesis, we first design secure and usable account recovery methods based on users’ trusted friends to recover compromised or lost user accounts. Second, we construct a scalable semi-supervised learning framework, which is based on probabilistic graphical model techniques, to detect Sybil accounts. Third, we demonstrate that diverse private information (e.g., private user demographics and hidden social connections) can be inferred with high accuracies from data that is publicly available on social networking sites, which has implications for the design of privacy-preserving online social networking services.
Classifying tags using open content resources

Tagging has emerged as a popular means to annotate on-line objects such as bookmarks, photos and videos. Tags vary in semantic meaning and can describe different aspects of a media object. Tags describe the content of the media as well as locations, dates, people and other associated meta-data. Being able to automatically classify tags into semantic categories allows us to understand better the way users annotate media objects and to build tools for viewing and browsing the media objects. In this paper we present a generic method for classifying tags using third party open content resources, such as Wikipedia and the Open Directory. Our method uses structural patterns that can be extracted from resource meta-data. We describe the implementation of our method on Wikipedia using WordNet categories as our classification schema and ground truth. Two structural patterns found in Wikipedia are used for training and classification: categories and templates. We apply our system to classifying Flickr tags. Compared to a WordNet baseline our method increases the coverage of the Flickr vocabulary by 115%. We can classify many important entities that are not covered by WordNet, such as, London Eye, Big Island, Ronaldinho, geocaching and wii.
Investigating and exploiting the bias of the weighted hypervolume to articulate user preferences

Optimizing the hypervolume indicator within evolutionary multiobjective optimizers has become popular in the last years. Recently, the indicator has been generalized to the weighted case to incorporate various user preferences into hypervolume-based search algorithms. There are two main open questions in this context: (i) how does the specified weight influence the distribution of a fixed number of points that maximize the weighted hypervolume indicator? (ii) how can the user articulate her preferences easily without specifying a certain weight distribution function? In this paper, we tackle both questions. First, we theoretically investigate optimal distributions of μ points that maximize the weighted hypervolume indicator. Second, based on the obtained theoretical results, we propose a new approach to articulate user preferences within biobjective hypervolume-based optimization in terms of specifying a desired density of points on a predefined (imaginary) Pareto front. Within this approach, a new exact algorithm based on dynamic programming is proposed which selects the set of μ points that maximizes the (weighted) hypervolume indicator. Experiments on various test functions show the usefulness of this new preference articulation approach and the agreement between theory and practice.
LINCRNA00273 promotes cancer metastasis and its G-Quadruplex promoter can serve as a novel target to inhibit cancer invasiveness

Discovery of anti-metastatic drugs is of immense clinical significance as metastasis is responsible for 90% of all cancer deaths. Here we report the inhibitory effect of a bis schiff base (M2) on cancer cell migration and invasion in vitro and in vivo. M2 has shown good solubility and permeability across the intestinal cell wall and hence can be classified as BCS (Biopharmaceutical classification system) class I. Microarray studies identified a long non coding intergenic RNA, LINC00273 as a novel molecular target of M2. We report that LINC00273 harbors a unique (4n-1) parallel G-Quadruplex structure in its promoter as validated by DMS footprint. M2 is proposed to stabilize this G-quadruplex structure resulting in the down-regulation of LINC00273 expression. Dual Luciferase reporter assay also suggests inhibition of LINC00273 promoter activity by M2. Involvement of this linc in metastasis is proven by siRNA and shRNA mediated knock down of LINC00273 in vitro and in vivo in nude mice which significantly decelerates cancer cell migration and invasion and also makes the cells unresponsive to TGF-β's pro-metastatic effects. Furthermore, the real time expression of LINC00273 in thirty seven human clinical samples is found to be positively correlated with the histopathological staging of metastasis.
Coordination and productivity issues in free software: The role of brooks' law

Proponents of the Free Software paradigm have argued that some of the most established software engineering principles do not fully apply when considered in an open, distributed approach found in Free Software development. The objective of this research is to empirically examine the Brooks' Law in a Free Software context. The principle is separated out into its two primary premises: the first is based on a developer's ability to become productive when joining a new team; the second premise relates to the quality of coordination as the team grows. Three large projects are studied for this purpose: KDE, Plone and Evince. Based on empirical evidence, the paper provides two main contributions: based on the first premise of Brooks' Law, it claims that coordination costs increase only in a very specific phase for Free Software projects. After that, these costs become quasi-constant. Secondly, it shows that a ramp up period exists in Free Software projects, and this period marks the divide between projects that are successful at engaging new contributors from others that only benefit from occasional new contributors.
A comparative analysis of iterative MapReduce systems

Since the development of MapReduce, there have been several efforts to extend data mining and machine learning algorithms for MapReduce. Many of those algorithms are iterative by nature. In order to process them efficiently, Spark as well as research prototypes such as HaLoop, iMapReduce, and Twister are proposed with solutions to iterative computation. In this paper, we thoroughly examine the pros and cons of each system.
Variable Selection for Efficient Nonnegative Tensor Factorization

Nonnegative Tensor Factorization (NTF) has become a popular tool for extracting informative patterns from tensor data. However, NTF has high computational cost both in space and in time, mostly in iterative calculation of the gradient. In this paper, we consider variable selection to reduce the cost, assuming sparsity of the factor matrices. In fact, it is known that the factor matrices are often very sparse in many applications such as network analysis, text analysis and image analysis. We update only a small subset of important variables in each iterative step. We show the effectiveness of the algorithm analytically and experimentally in comparison with conventional NTF algorithms. The algorithm was five times faster than the naive algorithm in the best case and required one to five hundred times less memory while keeping the approximation accuracy as the same.
FACS-purified myoblasts producing controlled VEGF levels induce safe and stable angiogenesis in chronic hind limb ischemia

We recently developed a method to control the in vivo distribution of vascular endothelial growth factor (VEGF) by high throughput Fluorescence‐Activated Cell Sorting (FACS) purification of transduced progenitors such that they homogeneously express specific VEGF levels. Here we investigated the long‐term safety of this method in chronic hind limb ischemia in nude rats. Primary myoblasts were transduced to co‐express rat VEGF‐A164 (rVEGF) and truncated ratCD8a, the latter serving as a FACS‐quantifiable surface marker. Based on the CD8 fluorescence of a reference clonal population, which expressed the desired VEGF level, cells producing similar VEGF levels were sorted from the primary population, which contained cells with very heterogeneous VEGF levels. One week after ischemia induction, 12 × 106 cells were implanted in the thigh muscles. Unsorted myoblasts caused angioma‐like structures, whereas purified cells only induced normal capillaries that were stable after 3 months. Vessel density was doubled in engrafted areas, but only approximately 0.1% of muscle volume showed cell engraftment, explaining why no increase in total blood flow was observed. In conclusion, the use of FACS‐purified myoblasts granted the cell‐by‐cell control of VEGF expression levels, which ensured long‐term safety in a model of chronic ischemia. Based on these results, the total number of implanted cells required to achieve efficacy will need to be determined before a clinical application.
Ant colony optimization of clustering models

The original ant system algorithm is simplified leading to a generalized ant colony optimization algorithm that can be used to solve a wide variety of discrete optimization problems. It is shown how objective function based clustering models such as hard and fuzzy c‐means can be optimized using particular extensions of this simplified ant optimization algorithm. Experiments with artificial and real datasets show that ant clustering produces better results than alternating optimization because it is less sensitive to local extrema. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 1233–1251, 2005.
Improved Multiplex PCR Using Conserved and Species-Specific 16S rRNA Gene Primers for Simultaneous Detection ofActinobacillus actinomycetemcomitans, Bacteroides forsythus, and Porphyromonas gingivalis

ABSTRACT Among putative periodontal pathogens, Actinobacillus actinomycetemcomitans, Bacteroides forsythus, andPorphyromonas gingivalis are most convincingly implicated as etiological agents in periodontitis. Therefore, techniques for detection of those three species would be of value. We previously published a description of a multiplex PCR that detects A. actinomycetemcomitans and P. gingivalis. The present paper presents an improvement on that technique, which now allows more sensitive detection of all three periodontal pathogens. Sensitivity was determined by testing serial dilutions of A. actinomycetemcomitans, B. forsythus, and P. gingivalis cells. Primer specificity was tested against (i) all gene sequences from the GenBank-EMBL database, (ii) six A. actinomycetemcomitans, one B. forsythus, and fourP. gingivalis strains, (iii) eight different species of oral bacteria, and (iv) supra- and subgingival plaque samples from 20 healthy subjects and subgingival plaque samples from 10 patients with periodontitis. The multiplex PCR had a detection limit of 10 A. actinomycetemcomitans, 10 P. gingivalis, and 100B. forsythus cells. Specificity was confirmed by the fact that (i) none of our forward primers were homologous to the 16S rRNA genes of other oral species, (ii) amplicons of predicted size were detected for all A. actinomycetemcomitans, B. forsythus, and P. gingivalis strains tested, and (iii) no amplicons were detected for the eight other bacterial species.A. actinomycetemcomitans, B. forsythus, andP. gingivalis were detected in 6 of 20, 1 of 20, and 11 of 20 of supragingival plaque samples, respectively, and 4 of 20, 7 of 20, and 13 of 20 of subgingival plaque samples, respectively, from periodontally healthy subjects. Among patients with periodontitis, the organisms were detected in 7 of 10, 10 of 10, and 7 of 10 samples, respectively. The simultaneous detection of three periodontal pathogens is an advantage of this technique over conventional PCR assays.
2D Gaussian Filter for Image Processing: A Study

This paper presents the study of 2D Gaussian filter and its vitality in image processing domain. The smoothing of images using 2D Gaussian filter brings out the best outcomes as compared to the conventional filters used to the date. Furthermore, when it comes to real time implementation of filter used for the image processing; it becomes a quite daunting task for the designers as it requires high computational resources. The purpose of this study is to present the FPGA resource usage for different sizes of Gaussian Kernel; to provide a comparison between fixed-point and floating point implementations
Pollen Viability, Pistil Receptivity, and Embryo Development in Hybridization of Nelumbo nucifera Gaertn

Seed set is usually low and differs for different crosses of flower lotus (Nelumbo nucifera Gaertn.). The reasons remain unknown, and this has a negative impact on lotus breeding. To determine the causes, we carried out two crosses of flower lotus, that is, “Jinsenianhua” × “Qinhuaihuadeng” and “Qinhuaihuadeng” × “Jinsenianhua” and pollen viability, pistil receptivity, and embryo development were investigated. The pollen grains collected at 05:00-06:00 hrs had the highest viability, and the viabilities of “Jinsenianhua” and “Qinhuaihuadeng” were 20.6 and 15.7%, respectively. At 4 h after artificial pollination, the number of pollen grains germinating on each stigma reached a peak: 63.0 and 17.2 per stigma in “Jinsenianhua” × “Qinhuaihuadeng” and “Qinhuaihuadeng” × “Jinsenianhua”, respectively. At 1 d after artificial pollination, the percentages of normal embryos in the two crosses were 55.0 and 21.9%, respectively; however, at 11 d after pollination, the corresponding percentages were 20.8 and 11.2%. Seed sets of the two crosses were 17.9 and 8.0%, respectively. The results suggested that low pistil receptivity and embryo abortion caused low seed set in “Qinhuaihuadeng” × “Jinsenianhua”, whereas low fecundity of “Jinsenianhua” × “Qinhuaihuadeng” was mainly attributable to embryo abortion.
Emerging semantic communities in peer web search

Peer network systems are becoming an increasingly important development in Web search technology. Many studies show that peer search systems perform better when a query is sent to a group of peers semantically similar to the query. This suggests that semantic communities should form so that a query can quickly propagate to many appropriate peers. For the network to be functional, its dynamic communication topology must match the semantic clustering of peers. We introduce two criteria to evaluate a peer search network based on the concept of semantic locality: first, the "small-world" topology of the network; second, we use topical semantic similarity to monitor the quality of a peer's neighbors over time by looking at whether a peer chooses semantically appropriate neighbors to route its queries. We present several simulation experiments conducted with different peer search algorithms on our peer Web search system, 6S. The results suggest that 6S, despite its use of an unstructured overlay network; can effectively foster the spontaneous formation of semantic communities through local peer interactions alone.
Selecting Input Models and Random Variate Generation

Discrete-event simulation almost invariably makes uses of random quantities drawn from given probability distributions to model chance fluctuations. This introductory tutorial discusses the basic ideas and techniques used to obtain such random variates. The two main points addressed are how appropriate distributions should be selected to model different quantities like arrival and service times, and how the variate values should actually be generated from the selected distributions.
One dimension dynamic ablation of bovine shank bone with pulse CO2 laser

The goal of this study was an in vitro evaluation of one dimension dynamic ablation of hard bone tissue with pulse CO2 laser. The tissue model was bovine shank bone which was put on a PC-controlled motorized linear drive stage and move repeatedly through the focused beam. Pulse CO2 laser wavelength 10. 6μm was focused down to a spot size of 510μm on the tissue sample surface. radiant exposure ranged from 5J/cm2 to 45J/cm2, repetition rates was 60Hz. After irradiation, the groove morphology produced by laser ablation were examined by optical coherent tomography (OCT) and light microscope following standard histological processing. Quantitative measurement of geometry and thermal damage of ablation groove was presented. It was shown that the width and depth of ablation groove and the zone of collateral thermal damage created in hard bone sample increased steadily with laser fluence. The results suggest that pulse CO2 laser can be a suitable candidate to cut hard bone tissue, and laser radiant exposure has an important effect on ablation rate and collateral thermal damage.
The Joint Manifold Model for Semi-supervised Multi-valued Regression

Many computer vision tasks may be expressed as the problem of learning a mapping between image space and a parameter space. For example, in human body pose estimation, recent research has directly modelled the mapping from image features (z) to joint angles (thetas). Fitting such models requires training data in the form of labelled (z, thetas) pairs, from which are learned the conditional densities p(thetas\z). Inference is then simple: given test image features z, the conditional p(thetas\z) is immediately computed. However large amounts of training data are required to fit the models, particularly in the case where the spaces are high dimensional. We show how the use of unlabelled data-samples from the marginal distributions p(z) and p(thetas)-may be used to improve fitting. This is valuable because it is often significantly easier to obtain unlabelled than labelled samples. We use a Gaussian process latent variable model to learn the mapping from a shared latent low-dimensional manifold to the feature and parameter spaces. This extends existing approaches to (a) use unlabelled data, and (b) represent one-to-many mappings. Experiments on synthetic and real problems demonstrate how the use of unlabelled data improves over existing techniques. In our comparisons, we include existing approaches that are explicitly semi-supervised as well as those which implicitly make use of unlabelled examples.
Thrombo-prophylaxis in acutely ill medical and critically ill patients

Thrombo-prophylaxis has been shown to reduce the incidence of pulmonary embolism (PE) and mortality in surgical patients. The purpose of this review is to find out the evidence-based clinical practice criteria of deep vein thrombosis (DVT) prophylaxis in acutely ill medical and critically ill patients. English-language randomized controlled trials, systematic reviews, and meta-analysis were included if they provided clinical outcomes and evaluated therapy with low-dose heparin or related agents compared with placebo, no treatment, or other active prophylaxis in the critically ill and medically ill population. For the same, we searched MEDLINE, PUBMED, Cochrane Library, and Google Scholar. In acutely ill medical patients on the basis of meta-analysis by Lederle et al. (40 trials) and LIFENOX study, heparin prophylaxis had no significant effect on mortality. The prophylaxis may have reduced PE in acutely ill medical patients, but led to more bleeding events, thus resulting in no net benefit. In critically ill patients, results of meta-analysis by Alhazzani et al. and PROTECT Trial indicate that any heparin prophylaxis compared with placebo reduces the rate of DVT and PE, but not symptomatic DVT. Major bleeding risk and mortality rates were similar. On the basis of MAGELLAN trial and EINSTEIN program, rivaroxaban offers a single-drug approach to the short-term and continued treatment of venous thrombosis. Aspirin has been used as antiplatelet agent, but when the data from two trials the ASPIRE and WARFASA study were pooled, there was a 32% reduction in the rate of recurrence of venous thrombo-embolism and a 34% reduction in the rate of major vascular events.
The case for electro-optic waveguide devices from ferroelectric (Pb,La)(Zr,Ti)O3 thin film epilayers

(Pb,La)(Zr,Ti)O3 (PLZT) thin films were grown epitaxially on MgO(001) substrate by radio frequency magnetron sputtering. Different ridge-type waveguides, including a Mach-Zehnder interferometer with co-planar metal electrodes, were defined in the PLZT epilayer using standard photolithographic techniques. The propagation losses for transverse electric polarized infrared light (λ0 = 1550 nm) in these ridge-type channel waveguides were measured at ~10 dB/cm. Electro-optic modulation was demonstrated with a half-wave voltage Vπ ≈ 150 V for a 3 mm interaction length, corresponding to a Pockels coefficient r51 ≈ 8.3 pm/V. Photonic crystal slabs (PCSs) were defined by etching a hexagonal two-dimensional lattice of holes in prepatterned ridge-type waveguides, using a focused ion beam. The sidewalls of the etched holes were inclined by an angle of ~10°. The impact on the transmission properties of these PCSs caused by out-of-plane structural asymmetries, such as deviation from a cylindrical shape of the FIB-etched air holes and the presence of a substrate with refractive index different from that of air, was investigated by numerical simulation. Auger depth profiling was used to investigate Ga+ ion implantation into the PLZT epilayer during FIB processing. The measurements suggest that such implantation of Ga+ is confined to the uppermost ~50 nm of the sample surface.