Miracle-dz/UniFAR-FTUs huggingface dataset:
E-COMMERCE ENTREPRENEURSHIP: EMERGING PRACTICES, KEY CHALLENGES AND FUTURE DIRECTIONS

Introduction The rise of the World Wide Web and electronic commerce has created one of the most challenging environments for entrepreneurship in recent history. Market needs and the technology required to meet those needs can change even while the product or service is still being developed (Iansiti and MacCormak, 1997). This framework demands that founders of organizations strive for "relentless innovation," leading their firms through the continual infusion of new ideas, and emphasizing constant innovation, experimentation, and rapid change (Cohen and Jordan, 1999). The environment of e-commerce enables entrepreneurs to rapidly try new approaches, quickly share successes and failures, and monitor what is new and useful (Oliva, 1998). E-commerce permits managers to become quicker in how they gather, synthesize, utilize, and disseminate information. Those who are willing to experiment with new product and service offerings will be positioned to compete most effectively (Hodgetts, Luthans, and Slocum, 1999). The extent to which entrepreneurs capitalize on the conditions presented by e-commerce and engage in experimentation and innovation is of major interest in contemporary research. Because of the demand for innovative organizational behavior present in e-business, this is an important domain in which to study entrepreneurship. However, because it is so recent, very little is known about the role attributes or innovative activities of entrepreneurs in Internet organizations. What enables emerging organizations to achieve effective performance? What are the opportunities and constraints in operating within this environment? These and many others questions are arising as the field of Internet entrepreneurship grows and develops. The answers 3 will inform the development of the growing research base in this area and will facilitate the subsequent comparison of key variables and relationships found in firms engaging in e-commerce with those in traditional brick and mortar firms. This paper presents the emergent practices and processes of e-commerce entrepreneurship, explores the key challenges facing the new ventures, and offers a research agenda to guide future work in this area. The paper draws on recent research findings and focuses on founders and organizations whose activities encompass the Internet, conducting multiple transactions on the Web, rather than on organizations that use the Web only for customer advertising and information gathering purposes. It is the premise of this paper that the first major step in developing a model of e-commerce entrepreneurship is to examine the processes and behaviors found within the ventures. The examination is conducted along several dimensions and contributes …
Multi Class Support Vector Machines for Disruption Classification in Tokamak Reactors

The paper addresses the problem of predicting the one set of a disruption on the basis of some known precursors possibly announcing the event. The availability in real time of a set of diagnostic signals allows us to collectively interpret the data in order to decide whether we are near a disruption or during a normal operation scenario. A database of disruptive discharges in JET-Team has been analyzed in this work, as a relevant experimental example. Multi-Class Support Vector Machines have been investigated aiming to gain information about the mechanism which drive to a disruption. The proposed processor will operate by implementing a classification of the shot type, and outputting an integer number that indicates the category of disruption. Keywords— Support Vector Machines; classification of disruption; nuclear fusion.
LIGHT/TNFSF14 as a New Biomarker of Bone Disease in Multiple Myeloma Patients Experiencing Therapeutic Regimens

We have previously shown that through the production of high LIGHT levels, immune cells contribute to both osteoclastogenesis and bone destruction in Multiple Myeloma (MM)-related bone disease. With the aim of further exploring the mechanisms underlying the development of MM-related bone disease, here we focused on a possible role of LIGHT in MM patients with active bone disease despite the treatment received. We detected LIGHT over-expression by circulating CD14+ monocytes from MM patients still showing active bone disease, despite the treatment. In addition, we found over-expression of receptor activator of nuclear factor kappa-B ligand (RANKL), whose pro-osteoclastogenic role is well-known, in T-lymphocytes isolated from the same patients. Although the percentages of circulating osteoclast progenitors, CD14+CD16+ monocytes, were higher in all the MM patients than in the controls spontaneous osteoclastogenesis occurred only in the cultures derived from PBMCs of MM patients with unresponsive bone disease. Of note, in the same cultures osteoclastogenesis was partially or completely inhibited, in a dose-dependent manner, by the addition of RANK-Fc or anti-LIGHT neutralizing antibody, demonstrating the contribution of both LIGHT and RANKL to the enhanced osteoclast formation observed. In addition, high serum levels of TRAP5b and CTX, the two markers of osteoclast activity, were detected in MM patients with bone disease not responsive to treatment. In conclusion, our study indicates a prominent role of LIGHT in the crosstalk among osteoclasts and immune cells, co-involved together with RANKL in the pathophysiological mechanisms leading to MM-related bone disease. This TNF superfamily member may thus be a possible new therapeutic target in MM-related bone disease.
Using Semantics to Discover Web Services Based on Partial Data: An Update of Previous Research

The authors developed an algorithm and a proof-of-concept tool to help business analysts search a pool of hundreds or thousands of services to find the closest ones to their needs when they are composing business processes, even when an exact match does not exist. The authors achieve this by semantically annotating the services with properties from an ontology, while, traditionally, only the concepts are used. This enables them to generate finer-grained partial semantic mappings between a query and the signature of the services published in a registry, despite potentially different parameter cardinalities and types. Their searches return a ranked list of those services available in the registry that most closely match the query specification. The analyst can then study the hits to see which of the suggested alternatives is more convenient. Such an approach is fundamental to effectively manage reuse in large service-oriented deployments, where the number of services in the registry becomes too voluminous for browsing individually or even syntactic searches that rely on some degree of memorization by the analyst.
WIDIT in TREC 2008 Blog Track: Leveraging Multiple Sources of Opinion Evidence

Indiana University‟s WIDIT Lab 1 participated in the Blog track‟s opinion task and the polarity subtask, where we combined multiple opinion detection methods to leverage a variety of complementary evidences rather than trying to optimize the utilization of a single source of evidence. To address the weakness of our past topical retrieval strategy, which generated mediocre baseline results with short queries (i.e., title only queries), we explored Web-based query expansion (WebX) methods to increase the initial retrieval performance for the short query. Our WebX methods consisted of the Google module, which harvests expansion terms from Google search results using various term selection methods, and Wikipedia module, which extracts noun phrases and related terms from Wikipedia articles and Wikipedia thesaurus. Web-expanded queries were combined using ad-hoc heuristics based on observation, trial and error, and some basic assumptions regarding quality of individual WebX methods. For opinion detection, we leveraged the complementary opinion evidences of Opinion Lexicon (e.g., suck, cool), Opinion Collocation (e.g., I believe, to me), and Opinion Morphology (e.g., sooooo, metacool) in the form of semi-automatically constructed opinion lexicons. In creating the opinion lexicons, we extracted terms from external sources (e.g., IMDb movie reviews and plot summaries) as well as the blog collection. Opinion lexicons were utilized by opinion scoring modules to compute opinion scores of documents, and the combined opinion score in conjunction with the on-topic retrieval score was used to boost the ranks of opinionated documents. To optimize the fusion formula for combining opinion and polarity scores, WIDIT used the “Dynamic Tuning Interface”, an interactive system optimization mechanism that displays the effects of tuning parameter changes in real time so as to guide its user towards the discovery of a system optimization state.
Performance predictions of bridge structures based on damage pattern detection and extreme value methods

Recently, novel numeric and monitoring techniques, such as fibre optic sensor systems and inverse damage detection analysis among others, are becoming more and more attractive for the long term reliability and performance assessment of engineering structures. These techniques combined with advanced software systems (SARA) and monitoring techniques, allow the continuously or discrete determination of the global reliability level of structures or structural components in time. Nevertheless, beyond these developments there are intentions to detect the structural performance by scanning the time dependent surface behavior, such as the pavement of bridges, and the associated stressors, by monitoring vehicles. In generally, these vehicles are equipped with laser sensor systems and high frequency cameras recording several properties of the surface. However, there is the requirement to supplement (a) the image recognition systems with the sensor readings, and (b) the performance level of a structure by means of a monitored surface degradation process. Therefore, the objectives of this paper are the presentation: (a) of methods for the incorporation of sensor readings in image recognition systems, (b) of inverse methods for the incorporation of surface damage processes in the performance level of structures, and (c) of extreme value based methods for the prediction of surface damage processes. The approaches will be applied to the existing Gossensass Bridge in Südtirol (IT).
On the Design of 2-DOF Robot

The gripper constitutes the end of the kinematic chain of an industrial robot and makes possible the interactions with the work environment. Although universal grippers with wide clamping ranges can be used for varied object shapes, in many cases they must be adapted to specific work-pieces shapes. The mechanical two-finger grippers with a single degree of freedom are the most usual device used in industry today. The fingers have symmetrical motions with respect to the gripper axis. In some applications, the position of the work piece with respect to the gripper frame may not be very precisely. It is the case of the unmachined or semi-finished parts in the interoperations transfer. A particular category of grippers for industrial robots has two degrees of freedom and a single driving motor. The relative positions of the component elements depend on the frictional coefficients between work piece and fingers and on the initial position of the work piece with respect to the gripper’s frame. The paper presents some considerations on the design of the 2-DOF robot grippers. Key-Words: robot gripper, 2-DOF gripper, optimum synthesis of gripper
STOCHASTICS AND THE PROFESSIONAL KNOWLEDGE OF TEACH ERS

Teachers widen their professional knowledge and the ir pedagogical practice by writing and publishing about their experiences in preparing and developing activities in statistics and probability. In this study data were collected and then analysed by triangulation. The role of reflection in teacher development, the relation wit h the curriculum and the relation with the collaborative work emerged. The results promote the development of the teacher’s professional role to create the teaching and learning process in terms of children’s cognitive development. Teachers worked within many constraints but still cvery sensible solutions for practical situations and are active innovators of the curricu lum
Face Detection Using Color Based Segmentation and Morphological Processing – A Case Study

Face is our primary focus of attention for conveying identity. Human face detection by computer systems has become a major field of interest. Detection of faces in a digital image has gained much importance in the last decade, with application in many fields. Automating the process to a computer requires the use of various image processing techniques. In the present paper, a face detection method based on color based segmentation and morphological processing is proposed with detailed experimental results. The algorithm designed uses color based segmentation and some morphological processing like open, closed and connected operation. The color based segmentation takes the advantage of patterns developed in only two color spaces i.e HSI and YCrCb, instead of three color spaces, followed by the morphological operations and a template matching. The present algorithm is applied to Indian faces. Experimental results show that the proposed algorithm is good enough to detect the human face taken through video with an accuracy of 90% and recognition of the detected face with an accuracy of 86-90%.
The Association between Cardiac Energy Metabolism and Physical Activity during Adolescence and Early Adulthood

A greater understanding of the mechanistic associations among subclinical cardiac dysfunction, metabolism, and physical activity may facilitate the early identification and treatment of premature cardiovascular disease originating during late adolescence, thereby preventing the progression of cardiovascular disease in adulthood. The present set of studies involved the implementation of novel cardiac Phosphorus Magnetic Resonance Spectroscopy in adolescents and young adults at The Hospital for Sick Children. These pilot studies are the first to characterize cardiac energy metabolism in both healthy and overweight cohorts during adolescence and early adulthood, as well as the first to explore the relationships among physical activity, cardiac and skeletal muscle energy metabolism, and cardiac function. Notably, reproducibility of primary study measures, including cardiac (i.e., PCr/ATPβ) and skeletal muscle energy metabolism (i.e., PCr recovery half-time), was explored (Study A). A positive association was demonstrated between cardiac energy metabolism and skeletal muscle energy metabolism, independent of moderate-to-vigorous physical activity levels and peak exercise performance (Study B). A positive association was also observed between novel measures of cardiac energy metabolism (resting cardiac
Stereoscopic Seam Carving with Temporal Consistency

In this paper, we present a novel technique for seam carving of stereoscopic video. It removes seams of pixels in areas that are most likely not noticed by the viewer. When applying seam carving to stereoscopic video rather than monoscopic still images, new challenges arise. The detected seams must be consistent between the left and the right view, so that no depth information is destroyed. When removing seams in two consecutive frames, temporal consistency between the removed seams must be established to avoid flicker in the resulting video. By making certain assumptions, the available depth information can be harnessed to improve the quality achieved by seam carving. Assuming that closer pixels are more important, the algorithm can focus on removing distant pixels first. Furthermore, we assume that coherent pixels belonging to the same object have similar depth. By avoiding to cut through edges in the depth map, we can thus avoid cutting through object boundaries.
Visualizing the First World War Using StreamGraphs and Information Extraction

In this paper, we develop a visualization tool that applies unsupervised named entity recognition and streamgraphs in order to visualize massive amounts of unstructured textual stream data, namely, French newspapers (e.g. Le Figaro, La presse, L'humanité) from the first world war period. Such a visualization allows us to identify main characters, events and locations involved in or relevant to the first world war, according to the French press. Furthermore, our visualization technique can help visually identify correlations between major people (e.g. presidents, generals, public figures.), locations (e.g. countries, cities, towns.) and organizations and events (e.g. corporations, battles.) on multiple aligned streamgraphs. We discuss the streamgraph method and compare it to alternative methods while drawing some examples from the visualization of the first world war. Our method helps users identify named entities and visualise them highlighting significant ones at specific time periods. Furthermore, it can be applied to unstructured data streams of any domain or time period.
A taskonomy for the Semantic Web

The modalities of search and browse dominate current thinking about interaction with the Web. Given the Web's origins as a global hypertext system, it is understandable that these document-centric interaction patterns prevail. However, these modalities alone are inadequate as a conceptual model of interaction with the global Linked Data space that is the Semantic Web. Realising the full potential of the Semantic Web requires a fundamental reconsideration of Web interaction patterns in the light of Linked Data, and this renewed conceptualisation must drive the research agenda related to user interaction and the Semantic Web. This paper argues that a fundamental understanding of user goals and tasks is the appropriate perspective from which to approach the research and development of Semantic Web applications. However, the Web in Semantic Web should not detract from the potential for cross-platform data interoperability enabled by the Semantic Web technology stack. In this context we propose a taskonomy of data- and object-centric user tasks derived from an analytical abstraction of existing research, not simply in the fields of Web search and browse but also email and Instant Messaging, that can help shape the direction of research and application development in the Semantic Web field.
Parallel Characterization of Anaerobic Toluene- and Ethylbenzene-Degrading Microbial Consortia by PCR-Denaturing Gradient Gel Electrophoresis, RNA-DNA Membrane Hybridization, and DNA Microarray Technology

ABSTRACT A mesophilic toluene-degrading consortium (TDC) and an ethylbenzene-degrading consortium (EDC) were established under sulfate-reducing conditions. These consortia were first characterized by denaturing gradient gel electrophoresis (DGGE) fingerprinting of PCR-amplified 16S rRNA gene fragments, followed by sequencing. The sequences of the major bands (T-1 and E-2) belonging to TDC and EDC, respectively, were affiliated with the family Desulfobacteriaceae. Another major band from EDC (E-1) was related to an uncultured non-sulfate-reducing soil bacterium. Oligonucleotide probes specific for the 16S rRNAs of target organisms corresponding to T-1, E-1, and E-2 were designed, and hybridization conditions were optimized for two analytical formats, membrane and DNA microarray hybridization. Both formats were used to characterize the TDC and EDC, and the results of both were consistent with DGGE analysis. In order to assess the utility of the microarray format for analysis of environmental samples, oil-contaminated sediments from the coast of Kuwait were analyzed. The DNA microarray successfully detected bacterial nucleic acids from these samples, but probes targeting specific groups of sulfate-reducing bacteria did not give positive signals. The results of this study demonstrate the limitations and the potential utility of DNA microarrays for microbial community analysis.
OptiType: precision HLA typing from next-generation sequencing data

Motivation: The human leukocyte antigen (HLA) gene cluster plays a crucial role in adaptive immunity and is thus relevant in many biomedical applications. While next-generation sequencing data are often available for a patient, deducing the HLA genotype is difficult because of substantial sequence similarity within the cluster and exceptionally high variability of the loci. Established approaches, therefore, rely on specific HLA enrichment and sequencing techniques, coming at an additional cost and extra turnaround time. Result: We present OptiType, a novel HLA genotyping algorithm based on integer linear programming, capable of producing accurate predictions from NGS data not specifically enriched for the HLA cluster. We also present a comprehensive benchmark dataset consisting of RNA, exome and whole-genome sequencing data. OptiType significantly outperformed previously published in silico approaches with an overall accuracy of 97% enabling its use in a broad range of applications. Contact: szolek@informatik.uni-tuebingen.de Supplementary information: Supplementary data are available at Bioinformatics online.
Virtual Telescope : A Mobile Augmented Reality System EE 368 Digital Image Processing Final Project Report 2012

We present a mobile image matching application for Android mobile phone called Virtual Telescope to assist users in viewing distant buildings. The application automatically augments photo's field of view by retrieving replacement images and satellite images from the Internet. The application adopts content based image retrieval method and allow user two choices of feature descriptor, namely Scale-invariant feature transform (SIFT) [1] and Affine-SIFT (ASIFT) [2]. The proposed application can also work as a general image retrieval system. Keywords-content based image retrieval; SIFT; ASIFT; Android application
Investigating the Use and Design of Immersive Simulation to Improve Self-Efficacy for Aspiring Principals

Aim/Purpose Improving public schools is a focus of federal legislation in the United States with much of the burden placed on principals. However, preparing principals for this task has proven elusive despite many changes in programming by institutions of higher learning. Emerging technologies that rely on augmented and virtual realities are posited to be powerful pedagogical tools for closing this gap. Background This study investigated the effects of immersive simulation technologies on principals’ self-efficacy after treatment and the perceived significance of the design of the immersive simulation experience as an effective tool for adult learners. Methodology The investigator employed a multiple-methods study that relied on a purposive sample of graduate students enrolled in educational leadership programs at two small universities in the southeastern United States. Participants completed a two-hour module of immersive simulation designed to facilitate transfer of knowledge to skills thereby increasing their self-efficacy. Contribution This paper contributes to a small body of literature that examines the use of immersive simulation to prepare aspiring principals. Findings The findings indicate moderate effect sizes in changes in self-efficacy, positive attitudes toward immersive simulation as a pedagogical tool, and significance in the design of immersive simulation modules. This suggests that immersive simulation, when properly designed, aids principals in taking action to improve schools. Recommendations for Practitioners Educational leadership programs might consider the use of immersive simulations to enhance principals’ ability to meet the complex demands of leading in the 21st century. Impact on Society Principals may be more adept at improving schools if preparation programs provided consistent opportunities to engage in immersive simulations. Use and Design of Immersive Simulation 128 Future Research Future research should be conducted with larger sample sizes and longitudinally to determine the effectiveness of this treatment.