Miracle-dz/UniFAR-FTUs huggingface dataset:
Column-Oriented Database Implementation in PostgreSql for Improving Performance of Read-Only

The era of Column-oriented database systems has truly begun with open source database systems like C-Store, MonetDb, LucidDb and commercial ones like Vertica. Column-oriented database stores data column-by-column which means it stores information of single attribute collectively. Row-Store database stores data row-by-row which means it stores all information of an entity together. Hence, when there is a need to access the data at the granularity of an entity, Row-Store performs well. But, in decision making applications, data is accessed in bulk at the granularity of an attribute. The need for Column-oriented database arose from the need of business intelligence needed for efficient decision making where traditional Row-oriented database gives poor performance. PostgreSql is an open source Row-oriented and most widely used relational database management system which does not have facility for storing data in Column-oriented fashion. This work discusses the best method for implementing column-store on top of Row-store in PostgreSql along with successful design and implementation of the same. Performance results of our Column-Store are presented, and compared with that of traditional Row-store results with the help of TPC-H benchmark. We also discuss about the areas in which this new feature could be used so that performance will be very high as compared to Row-Stores.
Link Failure Rate and Speed of Nodes in Wireless Network

In the simulation analysis of wireless network, the speed of nodes is an important property of mobility. The faster the nodes move, the more unstable the network is. Meanwhile, in theoretical analysis, link failure rate is widely used to modeling the stability of a wireless network. This paper presents an analysis of a simplified mobility model and shows that the link failure rate is positively correlated with the average speed of nodes in this model. Though this result is based on a mobility model with many restrictions, a simulation evaluation suggests that the result still holds in the popular random waypoint model and random direction model.
A novel spectral analysis method of EMG feature extraction for wrist motions recognition

This paper presents a new time-dependent spectral analysis, smooth localized complex exponential (SLEX), for extracting the surface EMG features of the wrist motions. Different from conventional Fourier method, SLEX-based spectral analysis applies two special smooth windows on Fourier basis function and can be simultaneously orthogonal and localized. In wrist motions recognition, we conduct SLEX transform on 4 selected channels with dimensionality reduction projection -LDA (linear discriminant analysis) in order to obtain EMG features of wrist motions. Then we evaluate separation of SLEX-based feature vector in LDA-subspace by the use of visualization 3-dimension plot and quantitative measurement, Davies-Boulder clustering Index. Finally, MLP (multiple layers perceptron) classifier is used to evaluate the classification accuracy of the SLEX-based feature extraction. Compared to commonly used methods- AR model and power spectral estimation (PSE), the SLEX-based model has better performance in classifying wrist motions and the classification accuracy is up to 98%.
Structural Property Preservation of a Kind of Petri Net Refinement

A refinement of Petri nets is a transformation by replacing a simple entity of a system with its functional and operational details. In general, the refined system may become incorrect even if the original system is correct because some of its original properties may have been lost or some undesired properties may have been created. For systems specified in ordinary Petri nets, this paper proposes the conditions imposed on a kind of net refinement under which the following structural properties will be preserved: repetitiveness, consistency, T-invariant, structural boundedness, conservativeness and P-invariant.
Treatment of chronic painful diabetic neuropathy with isosorbide dinitrate spray: a double-blind placebo-controlled cross-over study.

OBJECTIVE Considerable evidence implicates impaired nitric oxide (NO) generation in the pathogenesis of diabetic neuropathic pain. We therefore conducted a pilot study to examine the effects of isosorbide dinitrate (ISDN), a NO donor with local vasodilating properties, in spray form in the management of chronic neuropathic pain. RESEARCH DESIGN AND METHODS The study was of double-blind, randomized, placebo-controlled, and two-period cross-over design. After a 2-week run-in period, 22 diabetic patients (13 men, 20 with type 2 diabetes, age [mean +/- SE] 63.7 +/- 1.8 years, duration of diabetes 9.1 +/- 1.5 years, duration of painful neuropathy 2.6 +/- 0.4 years) were randomized to receive ISDN or placebo sprays for 4 weeks, exchanging their treatment for a further 4 weeks after a 2-week wash-out period. The patients administered the spray to both feet before bedtime. Biweekly pain and other sensory symptoms were assessed using a visual analog scale (VAS) and the Lickert scale, respectively. RESULTS ISDN spray reduced overall neuropathic pain (P = 0.02) and burning sensation (P = 0.006). No treatment difference was observed with other sensory modalities (hot/cold sensation, tingling, numbness, hyperesthesia, and jabbing-like sensation). At study completion, 11 patients (50%) reported benefit and wished to continue using the ISDN spray, 4 (18%) preferred the placebo spray, and the remaining 7 (32%) were undecided. CONCLUSIONS ISDN spray offers an alternative and effective pharmacological option in relieving overall pain and burning sensation in the management of painful diabetic neuropathy. The potential of ISDN spray in alleviating other specific sensory symptoms associated with diabetic peripheral neuropathy merits further study.
Betting to deal: coping motives mediate the relationship between urgency and Problem gambling severity

Abstract Background and aims: Elevated impulsivity traits, particularly negative and positive urgency, have been identified as robust predictors of problem gambling. However, the mechanisms that link urgency to problem gambling remain unknown. The present research examined whether self-reported gambling motives (social, coping, enhancement, financial) mediated the association between urgency and problem gambling severity. Methods: The sample consisted of 564 community gamblers (52.1% female; M age =36.10, SD = 11.25) including 156 (27.7%) who were classified as moderate risk gamblers and 141 (25%) as problem gamblers. Results: The mediation analyzes revealed that both negative and positive urgency were associated with problem gambling severity. Coping was the only motive that mediated these associations. The pattern of results remained the same when the analyzes were restricted to problem gamblers and when controlling for days gambled and money spent in the past 30 days. Conclusions: The desire to alleviate strong emotional states (negative or positive) maybe an important determinant of problem gambling. Furthermore, results indicate that treatment initiatives for problem gambling may benefit from including training for clients in alternative and more adaptive coping strategies for the effective management of intense affective states.
RETROTRANSLOCATION OF PRION PROTEINS FROM THE ER

Neurodegeneration in diseases caused by altered metabolism of mammalian prion protein (PrP) can be averted by reducing PrP expression. To identify novel pathways for PrP downregulation, we analyzed cells that had adapted to the negative selection pressure of stable overexpression of a disease-causing PrP mutant. A mutant cell line was isolated that selectively and quantitatively routes wild type and various mutant PrPs for ER retrotranslocation and proteasomal degradation. Biochemical analyses of the mutant cells revealed that a defect in glycosylphosphatidylinositol (GPI) anchor synthesis leads to an unprocessed GPI-anchoring signal sequence that directs both ER retention and efficient retrotranslocation of PrP. An unprocessed GPI signal was sufficient to impart ER retention, but not retrotranslocation, to a heterologous protein, revealing an unexpected role for the mature domain in the metabolism of misprocessed GPI-anchored proteins. Our results provide new insights into the quality control pathways for unprocessed GPI anchored proteins and identify transamidation of the GPI signal sequence as a step in PrP biosynthesis that is absolutely required for its surface expression. As each GPI signal sequence is unique, these results also identify signal recognition by the GPI-transamidase as a potential step for selective small molecule perturbation of PrP expression.
An imaginary friend that connects with the user's emotions

In this paper we present a metaphor of an Imaginary Friend that walks along with the user. Due to a special bond with the user, the Imaginary Friend can see the emotions that the human companion is feeling glowing around her. As the user moves around she leaves behind emotion cookies that the Imaginary Friend will collect and treasure. In order to enable rich and playful interactions in the virtual-real continuum the implementation of the Imaginary Friend responds to motion, to the electrodermal activity and resorts to GPS coordinates. The Imaginary Friend was tested with several users to evaluate the connection between humans and this creature that lives in the border that separates imagination and reality.
Toward A Pragmatic Discourse of Constructivism: Reflections on Lessons from Practice

Quinnipiac UniversityIn the past few decades, a constructivist discourse has emerged as a very powerfulmodel for explaining how knowledge is produced in the world, as well as howstudents learn. ' For constructivists like Joe Kincheloe (2000) and Barbara Thayer-Bacon (1999), knowledge about the world does not simply exist out there, waitingto be discovered, but is rather constructed by human beings in their interaction withthe world. "The angle from which an entity is seen, the values of the researcherthat shape the questions he or she asks about it, and what the researcher considersimportant are all factors in the construction of knowledge about the phenomenonin question" (Kincheloe, 2000, 342). Thayer-Bacon (1999) invoke a quilting beemetaphor to highlight the fact that knowledge is constructed by people who aresocially and culturally embedded, rather than isolated individuals. To assert thatknowledge is constructed, rather than discovered, implies that it is neither indepen-dent of human knowing nor value free. Indeed, constructivists believe that what isdeemed knowledge is always informed by a particular perspective and shaped byvarious implicit value judgments.According to Mark Windschitl (1999), constructivism is based on the assertionthat learners actively create, interpret, and reorganize knowledge in individualways. "These fluid intellectual transformations," he maintain, "occur when stu-dents reconcile formal instructional experiences with their existing knowledge,with the cultural and social contexts in which ideas occur, and with a host ofother influences that serve to mediate understanding" (752). In this view, teach-ing should promote experiences that require students to become active, scholarlyparticipators in the learning process. Windschitl (1999) goes on to note that "suchexperiences include problem-based learning, inquiry activities, dialogues with
Bayesian video matting using learnt image priors

Video matting, or layer extraction, is a classic inverse problem in computer vision that involves the extraction of foreground objects, and the alpha mattes that describe their opacity, from a set of images. Modem approaches that work with natural backgrounds often require user-labelled "trimaps" that segment each image into foreground, background and unknown regions. For long sequences, the production of accurate trimaps can be time consuming. In contrast, another class of approach depends on automatic background extraction to automate the process, but existing techniques do not make use of spatiotemporal consistency, and cannot take account of operator hints such as trimaps. This paper presents a method inspired by natural image statistics that cleanly unifies these approaches. A prior is learnt that models the relationship between the spatiotemporal gradients in the image sequence and those in the alpha mattes. This is used in combination with a learnt foreground colour model and a prior on the alpha distribution to help regularize the solution and greatly improve the automatic performance of such systems. The system is applied to several real image sequences that demonstrate the advantage that the unified approach can afford.
Electrical Remodeling of the Atrium in an Anatomic Model of Atrial Flutter: Relationship Between Substrate and Triggers for Conversion to Atrial Fibrillation

Background—Atrial flutter (AFL) and atrial fibrillation (AF) frequently coexist, yet the specific relationship between these arrhythmias, and particularly whether sustained AFL leads to AF, is unknown. Methods and Results—We investigated the electrophysiological consequences of chronic AFL using an ovine anatomic right atrial Y-lesion model. AFL was induced in 7 animals, and 4 remained in sinus rhythm (controls). Sheep were monitored for spontaneous conversion of AFL to AF. Six of 7 sheep sustained AFL for 28 days. In 1 of 7 sheep, spontaneous conversion of AFL to AF occurred on day 5. AFL produced a highly significant fall in right and left atrial refractoriness (AERP, P <0.001), with 74±10% of the reduction occurring by day 3. Right atrial conduction velocity also fell significantly (baseline 89±9 cm/s versus day 28 64±14 cm/s, P <0.001) but over a slower time course. AERP and conduction velocity changes coincided with a characteristic biphasic decrease and increase in the AFL cycle length. The excitable gap (percent of AFL cycle length) increased from 13±3% at baseline to 46±8% by day 28 (P <0.001). Sustained AF (>30 seconds) was not inducible at baseline but after 28 days of AFL could be induced in 6 of 6 sheep by critically timed single or multiple extrastimuli delivered either in sinus rhythm or AFL. There was no significant change in any parameter in control sheep. Conclusions—In this model, AFL produced electrical remodeling and the substrate for sustained AF. However, spontaneous conversion to AF was uncommon, and the development of AF was dependent on specific triggers.
Divisive Monothetic Clustering for Interval and Histogram-valued Data

In this paper we propose a divisive top-down clustering method designed for interval and histogram-valued data. The method provides a hierarchy on a set of objects together with a monothetic characterization of each formed cluster. At each step, a cluster is split so as to minimize intra-cluster dispersion, which is measured using a distance suitable for the considered variable types. The criterion is minimized across the bipartitions induced by a set of binary questions. Since interval-valued variables may be considered a special case of histogram-valued variables, the method applies to data described by either kind of variables, or by variables of both types. An example illustrates the proposed approach.
INVISIP: Establishment of a Context Repository to Support the Site Planning Process

The EU-funded project INVISIP aims to create a framework to support all involved parties in the site planning process: Municipal authorities and departments, planning offices, data suppliers and citizens. This paper describes the INVISIP approach, global aims and objectives as well as the current state of the project. Here, from the technical point of view first results achieved within the analysis phase of the project have shown different possibilities to enhance data mining and visualization tasks by information visualization techniques using metadata and familiar metaphors. On the other hand, from the applicationdriven point of view the necessity to establish an integrated framework for the site planning process providing not only data handling techniques but also context information concerning the workflow, tasks and objectives within the different site planning phases, is an important result of the case studies within the four INVISIP partner countries (Germany, Italy, Sweden and Poland). Concerning this issue, the establishment of a context repository and its usage within the proposed INVISIP architecture and the application scenario (site planning of a shopping center in a suburban area) will be discussed in detail.
Bio-inspired optimization techniques: a critical comparative study

Despite insistent and breathtaking advances in computing, we continue to be humbled by the variety and adaptability of the natural world around us. Bio-inspired optimization is a term that covers a wide variety of computational approaches that are based on the principles of biological systems. This motivates the application of biology to optimization problems. Biologically inspired computing and optimization is a major subset of natural computation. This paper presents a critical survey of bio-inspired optimization techniques. There are many legacy optimization techniques available. This survey explains almost all important bio-inspired optimization techniques based on their development, intention, performance and application. It provides insight into determining the direction of future optimization techniques research.
Visibility Sorting and Compositing for Image-Based Rendering

We present an efficient algorithm for analyzing synthetic scenes involving a set of moving objects and changing view parameters into a sorted sequence of image layers. The final image is generated by evaluating a 2D image compositing expression on these layers. Unlike previous visibility approaches, we detect and report occlusion cycles rather than splitting to remove them. Such an algorithm has many applications in computer graphics; we demonstrate two: rendering acceleration using image interpolation, and visibility-correct depth of field using image blurring. The algorithm involves an incremental method for identifying mutually occluding sets of objects and computing a visibility sort of these sets. Occlusion queries are accelerated by testing on convex bounding hulls; less conservative tests are also discussed. Kd-trees formed by combinations of directions in object or image space provide an initial cull on potential occluders, and a new incremental algorithm is employed to resolve pairwise occlusions. Mutual occluders are further analyzed to generate an image compositing expression; in the case of nonbinary cycles an expression can always be generated without aggregating the objects into a single layer. Results demonstrate that the algorithm is practical for interactive animation of scenes involving hundreds of objects each comprising hundreds or thousands of polygons.
Facilitating Withdrawer Re-Engagement in Emotionally Focused Couple Therapy: A Modified Task Analysis

A modified, discovery-oriented task analysis was conducted to delineate what therapist interventions and client emotional processes are involved in successful withdrawer re-engagement in Emotionally Focused Couple Therapy (EFT). EFT is an empirically validated approach to treating couples. Withdrawer re-engagement is seen as a key element of the change process in EFT, yet limited research is available as to how the process is facilitated in session. Seven videotaped samples of successful withdrawer re-engagement were critically examined using task analytic methods. Therapist interventions and client emotional processes were assessed using the Emotion-Focused Therapy Coding Scheme and the Experiencing Scale. Implications for future research, clinical practice, and training are discussed.
Young Stars in the Camelopardalis Dust and Molecular Clouds. II. Infrared Objects

Using infrared photometric data extracted from the 2MASS, IRAS and MSX databases, 142 suspected young stellar objects (YSOs) are selected from about 2 million stars in the Camelopardalis segment of the Milky Way limited by Galactic longitude 132-158 deg, latitude pm 12 deg. According to radial velocities of the associated CO clouds, the objects are attributed to three molecular and dust cloud layers at 150--300 pc, 900 pc and 2.2 kpc distances from the Sun. These objects concentrate into dust and molecular clouds and exhibit extremely large reddenings (A_V up to 25 mag) which can be caused by the dust in foreground clouds and circumstellar envelopes or disks. In the J-H vs. H-K diagram these objects lie above the intrinsic line of T Tauri variables, roughly along the black-body line. Among the identified objects, some already known YSOs are present, including the well investigated massive object GL 490. The spectral energy distributions between 700 nm and 100 mum suggest that the objects may be YSOs of classes I, II and III. However, we do not exclude the possibility that a small fraction of the objects, especially those without IRAS and MSX photometry, may be unrecognized heavily reddened OB-stars, late-type AGB stars or even galaxies.
Assessing the Determinants of Renewable Electricity Acceptance Integrating Meta-Analysis Regression and a Local Comprehensive Survey

In dealing with renewable electricity (RE), individuals are involved both as end-consumers on the demand side and as stakeholders (citizens) in the local production process on the supply side. Empirical evidence shows that in many countries, consumers are willing to pay a significant amount to facilitate adoption of RE. By contrast, environmental externalities are often the cause of strong opposition to RE adoption if local communities are involved as stakeholders in wind, solar or biomass investment projects. Looking at the literature on willingness to pay and on willingness to accept, we have investigated RE acceptance mechanisms. First, we have used the meta-analysis to assess the major determinants of RE acceptance on both demand and supply sides. Meta-analysis has provided some insights useful for managing field research on an onshore wind farm enlargement project located in the Umbria region. Meta-analysis and survey results confirm that the local community plays a central role in local RE acceptance. Furthermore, people who have previous experience with windmills require less compensation, or are willing to pay more, for RE development. Results suggest that these attributes should be included in future research to improve understanding of determinants of RE acceptance.
Multicore Based Spatialk-dominant Skyline Computation

We consider k-dominant skyline computation when the underlying dataset is partitioned into geographically distant computing core that are connected to the coordinator (server). The existing k-dominant skyline solutions are not suitable for our problem, because they are restricted to centralized query processors, limiting scalability and imposing a single point of failure. Moreover, k-dominant skyline computation does not follow transitivity property like skyline computation. In this paper, we developed a multicore based spatial k-dominant skyline (MSKS) computation algorithm. MSKS is a feedback-driven mechanism, where the coordinator iteratively transmits data to each computing core. Computing core is able to prune a large amount of local data, which otherwise would need to be sent to the coordinator. Furthermore, it supports a user-friendly progress indicator that allows user to modify (insert, delete, and update) and monitor the progress of long running k-dominant skyline queries. Extensive performance study shows that proposed algorithm is efficient and robust to different data distributions and achieves its progressive goal with a minimal overhead.