Miracle-dz/UniFAR-FTUs huggingface dataset:
Ontoolcole: Supporting Educators in the Semantic Search of CSCL Tools

Collaborative learning systems can be constructed following the service- oriented computing paradigm. This allows educators to integrate external tools, offered as services by software providers, in order to support the realization of collaborative learning situations. Discovering appropriate services is a challenging task that requires the description of their capabilities. This can be accomplished with Ontoolcole, an on- tology of collaborative learning tools designed with the aim of supporting educators in the search of CSCL tools. Ontoolcole is depicted here and some new, relevant features are discussed. Namely, Ontoolcole incorporates an artifact module, a task-level coordi- nation module and the description of static information resources, further improving the capabilities to describe complex CSCL tools. As a proof of concept, we also present a preliminary prototype of the intended target application of Ontoolcole, an interac- tive system for the search of CSCL tools, named Ontoolsearch. A case study with practitioners has been carried out to evaluate whether Ontoolcole can be employed by educators to search CSCL tools. Evaluation results show that Ontoolcole abstractions fit educators' questions based on their real practice while retrieving useful tools for their educational needs.
Expert dictionaries: knowledge based tools for explanation and maintenance of complex application environments

The paper describes a new type of tool, which has been defined to support complex applications (such as the ones typically found in office environments). The relevant features of this tool are the following:it collects “domain” (also called “deep”) knowledge (relevant for the application domain), and uses it to explain the application “behaviour”, either automated or not it makes use of an extensional representation of the domain knowledge based on Hypertexts it can support the activity of maintenance (of the application) and of training (to understand how the application works). We have chosen for the tool the name “Expert Dictionary”. A first implementation of this tool for a specific application target (document generation) has been carried on with Hypertalk, the programming language of Hypercard.
Stability and performance analysis of HIPERLAN

This paper thoroughly analyses the HIPERLAN MAC protocol, which is a standard for wireless local area networks (WLANs) defined by the European Telecommunications Standards Institute (ETSI). Since the HIPERLAN MAC protocol belongs to the class of carrier sensing multiple access with collision avoidance (CSMA/CA), we analyze the HIPERLAN stability problem. We also present an in depth performance analysis, by simulation, of the HIPERLAN MAC protocol. The analysis is performed by considering data traffic patterns (advanced data traffic) which have a very similar shape to traffic generated by WWW applications. Furthermore, in the analysis we consider Poissonian data traffic too. Our conclusion is that the HIPERLAN MAC protocol performs satisfactorily, although performance measures with advanced traffic are worse than the corresponding performance measures with Poissonian traffic. Furthermore, we broadened our analysis to include the influence of the packet lifetime and channel access priority mechanism on the performance measures provided by HIPERLAN.
The Tomato Pip's Story: Creative Narratives as Bridging Cultural and Science Discourses for Indigenous Students

This article reports on what happened when a Rumaki pūtaiao kaiako (Science) teacher at a New Zealand high school trialled the use of creative narratives with her Year-10 students as a way of developing their understanding of the human digestive system. These students were members of the school's Māori immersion unit, and creative narratives were in part utilised as a bridge between science discourse and the cultural knowledges these students brought to their learning. In this case study, students developed ‘Tomato Pip’ narratives through four versions, which told the story of a tomato pip travelling through the human digestive system. Word-count data based on these versions and from a summative test were analysed and correlations found between test scores and three categories of word-count total (total words, total science words and total discrete science words). A discourse analysis of one student's narratives identified two distinct voices in these texts: the personal narrator and the emerging biologist. Questionnaire and focus-group data indicated that the use of creative narratives was both motivational to these students and effective as a bridge into science discourse mastery. It is argued that the findings have implications for disciplinary literacy theory, Indigenous education and science instruction.
Operationalizing Economic Theory for Use in IT Evaluation: A Principal-Agent Based Framework for Assessing Collective IT Investments

Frameworks for IT evaluation have been extensively discussed in the past. Until recently, research had concentrated on advancing classic approaches such as monetary cost/benefit considerations or strategic management matrices, but that constriction to known methods has considerably softened. More researchers now use economic models in IT evaluation. Their contributions open exciting new perspectives but unfortunately the models put forward cannot reach wide in practice as they are highly formalized. Addressing the use of economic theory in IS research, this paper attempts to fully operationalize an economic theory into a framework apt for management. Exemplarily, in a “research method case study”, we operationalize Principal-Agent theory for a specific organizational setting. The particular situation we develop the framework for is collective investment into Information Technology (such as collaborative Supply Chain Management systems or collective reservation systems for airline networks). The four steps we conduct in our operationalization are translation, scenario building, structured qualitative analysis and aggregation. Along with presenting the complete operationalization process, the final framework demonstrates that a complex Principal-Agent problem can be transcribed into an easy to use IS management framework.
A symmetric approach to understand the dynamics of scientiﬁc collaborations and knowledge production

How are social and epistemic structures of a research community driving future research dynamics ? We analyzed a very large data set of scientific publications (APS dataset) covering more than 20 years to investigate the social dynamics of collaboration network and the epistemic network of PACS codes co-occurrences network. In particular we show that the epistemic network built through concepts co-occurrences in articles has a non trivial structure characterized by an heterogeneous degree distribution and a high value of modularity, produced by local mechanisms that depend on similarity factors. We empirically show that those local epistemic dynamics are both linked to past social and epistemic structures. Moreover we show that the evolution of the social network depends also on epistemic factors, indicating that the two networks mutually influence their evolution and are thus co-evolving over time.
Cross-domain processing of musical and vocal emotions in cochlear implant users

Music and voice bear many similarities and share neural resources to some extent. Experience dependent plasticity provides a window into the neural overlap between these two domains. Here, we suggest that research on auditory deprived individuals whose hearing has been bionically restored offers a unique insight into the functional and structural overlap between music and voice. Studying how basic emotions (happiness, sadness, and fear) are perceived in auditory stimuli constitutes a favorable terrain for such an endeavor. We outline a possible neuro-behavioral approach to study the effect of plasticity on cross-domain processing of musical and vocal emotions, using cochlear implant users as a model of reversible sensory deprivation and comparing them to normal-hearing individuals. We discuss the implications of such developments on the current understanding of cross-domain neural overlap.
Molecular dynamics simulation of α-syn12 peptide and synphilin-1 protein complex

The dynamics and structural character of a-syn12 peptide complex with synphilin-1 protein in aqueous solution has been investigated through molecular dynamics simulations by using GROMOS 43A1 force field. The structural character of a-syn12 peptide complex with synphilin-1 protein adopts in water a loop structure.
RELEVANCE OF SOCIAL MEDIA ANALYSIS FOR OPERATIONAL MANAGEMENT IN HEALTH INSURANCE

This master’s thesis illustrates the future trend of insurance companies using social media data for improvement of business management in various fields of operation. Using the example of Facebook data for product development, the research question, how external data can be structured and combined with internal data and how the resulting database can be used in order to improve the product development process in health insurance, is analyzed. Here for, two comprehensive approaches exist, whereby this master’s thesis will focus on the first proceeding. On the one hand, new products can be determined beforehand and it is considered, that the suggested products do not yet exist in this compilation and they also represent a market and client need. Thereby, the task is to find potential customers whom those products can be offered to. On the other hand, however, it can also be of interest to find new, not yet existing products according to demands of the market and of the existing clients derived from social media data. To begin with, the term Big Data as the global source of external data, as well as its challenges are introduced. As social media is a substantial and very promising part of Big Data, it is illustrated what different sources and types of social media data there are and how such data can easily be extracted. Only a small amount of social media data is structured or semi-structured data, from which information content is easily extractable. Unstructured data represents the largest share of social media data, which has to be structured first in order to be able to obtain information on an automated basis. In the next step, therefore, important text analytics tools and techniques for structuring of unstructured data are introduced and described step by step. The combination of the then structured external data and the existing internal data warehouse, afterwards, creates a Big Data warehouse, which allows the evaluation and intelligence gathering from versatile, innovative and information-rich data. Here for, suitable matching techniques are illustrated. To conclude this master’s thesis, such a combined dataset is simulated and analyzed with regard to product development by finding potential clients for new products. One possible approach here for is to score existing clients according to their externally matched information regarding their affinity towards the offered product. The alternative is to assign existing clients into so called lifestyle clusters according to their externally matched information and intuitively choose clusters, which contain potential new clients for the offered products.
Reduction in Thrombus Extension and Clinical End Points in Patients after Initial Treatment for Deep Vein Thrombosis with the Fixed-Dose Body Weight-Independent Low Molecular Weight Heparin Certoparin

Low molecular weight heparin (LMWH) is effective in the treatment of acute deep vein thrombosis (DVT) in adults. This has not been demonstrated for one LMWH alone. The relationship between venographic changes due to LMWH therapy and clinical outcome in the initial treatment period has not been reported. A pooled analysis of two clinical trials was performed. The trials compared a fixed-dose, body weight-independent, subcutaneous LMWH, certoparin (8000 antifactor Xa [aXa] U twice a day [b.i.d.]), with an adjusted-dose intravenous unfractionated heparin (UFH) with respect to venographic changes expressed as Marder score and occurrence of recurrent venous thromboembolism, major bleeding, and mortality. The Marder score was 23.2 +/- 8.4 in patients randomized to LMWH (n = 299 paired phlebograms) and 23.9 +/- 8.9 in patients allocated to UFH (n = 297 paired phlebograms) at entry (2p = 0.23) and 18.9 +/- 9.7 and 20.5 +/- 9.9 at the end of the initial therapy (2p = 0.04), respectively. The composite outcome of recurrent venous thromboembolism, major bleeding, and mortality occurred less frequently during treatment with LMWH (n = 393) than it did with UFH (n = 404, 1.3% versus 5.0%, risk reduction [RR] 0.26, 95% confidence interval [CI] 0.11 to 0.63, 2p = 0.004). Single events of recurrent thromboembolism (2p = 0.12), major bleeding (2p = 0.03), and mortality (2p = 0.12) were observed less frequently with LMWH. A trend toward a lack of regression of thrombus size was observed in recurrent venous thromboembolism (2p = 0.08). Body weight-independent LMWH significantly reduces thrombus size and the incidence of composite outcome during the initial treatment of acute proximal venous thrombosis compared with adjusted dose intravenous UFH. The data indicate a relation between an unimproved Marder score and a recurrent venous thromboembolism.
Genetic Risk Assessment of Type 2 Diabetes–Associated Polymorphisms in African Americans

OBJECTIVE Multiple single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D) susceptibility have been identified in predominantly European-derived populations. These SNPs have not been extensively investigated for individual and cumulative effects on T2D risk in African Americans. RESEARCH DESIGN AND METHODS Seventeen index T2D risk variants were genotyped in 2,652 African American case subjects with T2D and 1,393 nondiabetic control subjects. Individual SNPs and cumulative risk allele loads were assessed for association with risk for T2D. Cumulative risk was assessed by counting risk alleles and evaluating the difference in cumulative risk scores between case subjects and control subjects. A second analysis weighted risk scores (ln [OR]) based on previously reported European-derived effect sizes. RESULTS Frequencies of risk alleles ranged from 8.6 to 99.9%. Eleven SNPs had ORs >1, and 5 from ADAMTS9, WFS1, CDKAL1, JAZF1, and TCF7L2 trended or had nominally significant evidence of T2D association (P < 0.05). Individuals carried between 13 and 29 risk alleles. Association was observed between T2D and increase in risk allele load (unweighted OR 1.04 [95% CI 1.01–1.08], P = 0.010; weighted 1.06 [1.03–1.10], P = 8.10 × 10−5). When TCF7L2 SNP rs7903146 was included as a covariate, the risk score was no longer associated with T2D in either model (unweighted 1.02 [0.98–1.05], P = 0.33; weighted 1.02 [0.98–1.06], P = 0.40). CONCLUSIONS The trend of increase in risk for T2D with increasing risk allele load is similar to observations in European-derived populations; however, these analyses indicate that T2D genetic risk is primarily mediated through the effect of TCF7L2 in African Americans.
GLRT Based Active Spectrum Sensing for Cognitive Radio Systems

In this paper, we have proposed an active spectrum sensing method which benefits from primary user's closed loop power control. The idea of active sensing let the cognitive transmitter to use the spectrum by estimating the maximum power of cognitive Radio transmitter that doesn't lead to harmful interference to primary receiver in the range of primary transmitter. So a cognitive radio can communicate through spatial holes of spectrum. Our work is based on generalized likelihood ratio test (GLRT) model. Using a probabilistic modeling of power profile of primary transmitter and employing energy detection as a channel measurement metric for power statistics, we have developed a GLRT based decision metric for spectrum decision process.
Genome-Wide Association Scan for Variants Associated with Early-Onset Prostate Cancer

Prostate cancer is the most common non-skin cancer and the second leading cause of cancer related mortality for men in the United States. There is strong empirical and epidemiological evidence supporting a stronger role of genetics in early-onset prostate cancer. We performed a genome-wide association scan for early-onset prostate cancer. Novel aspects of this study include the focus on early-onset disease (defined as men with prostate cancer diagnosed before age 56 years) and use of publically available control genotype data from previous genome-wide association studies. We found genome-wide significant (p<5×10−8) evidence for variants at 8q24 and 11p15 and strong supportive evidence for a number of previously reported loci. We found little evidence for individual or systematic inflated association findings resulting from using public controls, demonstrating the utility of using public control data in large-scale genetic association studies of common variants. Taken together, these results demonstrate the importance of established common genetic variants for early-onset prostate cancer and the power of including early-onset prostate cancer cases in genetic association studies.
Intracellular calcium-dependent regulation of the sperm-specific calcium-activated potassium channel, hSlo3, by the BKCa activator LDD175

Plasma membrane hyperpolarization associated with activation of Ca2+-activated K+ channels plays an important role in sperm capacitation during fertilization. Although Slo3 (slowpoke homologue 3), together with the auxiliary γ2-subunit, LRRC52 (leucine-rich-repeat–containing 52), is known to mediate the pH-sensitive, sperm-specific K+ current KSper in mice, the molecular identity of this channel in human sperm remains controversial. In this study, we tested the classical BKCa activators, NS1619 and LDD175, on human Slo3, heterologously expressed in HEK293 cells together with its functional interacting γ2 subunit, hLRRC52. As previously reported, Slo3 K+ current was unaffected by iberiotoxin or 4-aminopyridine, but was inhibited by ~50% by 20 mM TEA. Extracellular alkalinization potentiated hSlo3 K+ current, and internal alkalinization and Ca2+ elevation induced a leftward shift its activation voltage. NS1619, which acts intracellularly to modulate hSlo1 gating, attenuated hSlo3 K+ currents, whereas LDD175 increased this current and induced membrane potential hyperpolarization. LDD175-induced potentiation was not associated with a change in the half-activation voltage at different intracellular pHs (pH 7.3 and pH 8.0) in the absence of intracellular Ca2+. In contrast, elevation of intracellular Ca2+ dramatically enhanced the LDD175-induced leftward shift in the half-activation potential of hSlo3. Therefore, the mechanism of action does not involve pH-dependent modulation of hSlo3 gating; instead, LDD175 may modulate Ca2+-dependent activation of hSlo3. Thus, LDD175 potentially activates native KSper and may induce membrane hyperpolarization-associated hyperactivation in human sperm.
Shape from Silhouette Under Varying Lighting and Multi-viewpoints

We present a new segmentation method for visual hull (VH) reconstruction from an image sequence. The camera moves on a hemisphere around an object set on a turntable with complex and unknown background. Even though the background is assumed to be constant, it cannot be modeled from all possible viewpoints. A series of images of a moving object under different lighting conditions are captured and analyzed. In this analysis, information from space, time and light domains are fused into an MRF framework. The method is validated by VH reconstruction of challenging objects with different optical properties.
On improving the extrapolation capability of task-parameterized movement models

Gestures are characterized by intermediary or final landmarks (real or virtual) in task space or joint space that can change during the course of the motion, and that are described by varying accuracy and correlation constraints. Generalizing these trajectories in robot learning by imitation is challenging, because of the small number of demonstrations provided by the user. We present an approach to statistically encode movements in a task-parameterized mixture model, and derive an expectation-maximization (EM) algorithm to train it. The model automatically extracts the relevance of candidate coordinate systems during the task, and exploits this information during reproduction to adapt the movement in real-time to changing position and orientation of landmarks or objects. The approach is tested with a robotic arm learning to roll out a pizza dough. It is compared to three categories of task-parameterized models: 1) Gaussian process regression (GPR) with a trajectory models database; 2) Multi-streams approach with models trained in several frames of reference; and 3) Parametric Gaussian mixture model (PGMM) modulating the Gaussian centers with the task parameters. We show that the extrapolation capability of the proposed approach outperforms existing methods, by extracting the local structures of the task instead of relying on interpolation principles.
Homogeneous Crystallization of Micro-DispensedTIPS-Pentacene Using a Two-Solvent System toEnable Printed Inverters on Foil Substrates

We report on a micro-dispensing system for 6,13-Bis(triisopropylsilylethynyl)pentacene (TIPS-pentacene) to enable homogenous crystallization and uniform filmmorphology of the dispensed droplets using a two-solvent mixture along with the use of aninsulating binder. This solution composition results in a controlled evaporation of the dropletin ambient air such that the Marangoni flow counteracts the outward convective flow toenable uniform radial crystal growth from the edge towards the center of the drops.The consequence of this process is the high degree of uniformity in the crystallization of thedrops, which results in a reduction in the performance spread of the organic field effecttransistors (OFET) created using this process. The addition of the insulating binder furtherimproves the reduction in the spread of the results as a trade-off to the reduction in mobilityof the transistors. The transfer curves of the OFETs show a tight grouping due to thecontrolled self-alignment of the TIPS-pentacene crystals; this repeatability was furtherhighlighted by fabricating p-type inverters with driver to load ratios of 8:1, wherein theoutput inverter curves were also grouped tightly while exhibiting a gain of greater than 4 inthe switching region. Therefore, the reliability and repeatability of this process justifies itsuse to enable large area solution-processed printed circuits at the cost of reduced mobility.