Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Video Feedback to Measure Self-Efficacy.

When a student has a high sense of self-efficacy, foreseeing success and providing positive guides and supports for performing the skill will usually occur. A low self-efficacy tends to predict failure and anticipation of what could go wrong. Videotape feedback provided to students has reported favorable outcomes. Self-efficacy could alter performance in learning a psychomotor competency skill (PCS). The purpose of this study was a) to assess the self-efficacy of athletic training students in learning to perform a PCS; and b) to measure the impact on selfefficacy by implementing an educational intervention of video feedback in learning to perform a PCS. An intact cohort of level I (lower-level) students within a CAATE-accredited entry-level master athletic training educational program learned and performed an upper body neurological screening. Throughout the study students also completed the Self-efficacy questionnaire (n=5 trials/times). Group mean for self-efficacy from baseline (M = 6.14; ± 2.04) to post-intervention (M = 9.51; ± 0.70) increased. One-way ANOVA indicated a significant effect using Wilks’ Lambda post hoc, with alpha set at . 001 (.05/5 = .001). Significant differences of improved selfefficacy between trials one and four, one and five, and two and five were found, all following the educational intervention. The use of video feedback could increase self-efficacy when learning to perform a PCS.
Viral interference ( Interferon ) effects in animals

I would like to thank the Nobel Assembly of the Karolinska Institutet for the opportunity to describe some recent work on RNA-triggered gene silencing. First a few disclaimers, however. Telling the full story of gene silencing would be a mammoth enterprise that would take me many years to write and would take you well into the night to read. So we’ll need to abbreviate the story more than a little. Second (and as you will see) we are only in the dawn of our knowledge; so consider the following to be primer. the best we could do as of December 8th, 2006. And third, please understand that the story that I am telling represents the work of several generations of biologists, chemists, and many shades in between. I’m pleased and proud that work from my laboratory has contributed to the field, and that this has led to my being chosen as one of the messengers to relay the story in this forum. At the same time, I hope that there will be no confusion of equating our modest contributions with those of the much grander RNAi enterprise.
Sibling and friendship relationships of children with attention-deficit/hyperactivity disorder and typical development

ABSTRACT Sibling and friendship relationships are quite similar, in that they are both dyadic and reciprocal, and offer the child feelings of warmth, trust, loyalty and intimacy. Children with Attention Deficit/Hyperactivity Disorder (ADHD) often experience difficulties in their interpersonal relationships. The aim of this study was to evaluate the quality of and to acknowledge possible links between sibling and friendship relationships of children with ADHD and typical development. Participants were 40 ADHD children and 120 typically developing peers, attending Greek primary schools (Mage = 9.51 years, SD = 1.1). The Sibling Relationship Questionnaire, sociometric nominations, and the Friendship Quality Questionnaire were used. The results showed that children with ADHD had greater antagonism with their siblings and fewer reciprocated friendships. Significant differences in friendship quality between the two groups were observed. Sibling relationships were found to influence all children’s number of mutual friends, and the friendship quality of the typically developing children.
I Corrosion Characterisation Using Texture Analysis 1 1 Methods for Texture Analysis 5 3 Classiication of Corrosion Images 35 Characterisation of Corrosion Images Characterisation of Silver Halide Microcrystals

derzoek in de industrie" (IWT). Summary In this thesis, a number of image analysis methods are presented as solutions to two applications concerning the characterisation of materials. The rst application deals with the characterisation of corrosion images, which is handled using a texture analysis approach. The second application is the study of silver halide microcrystals with the aid of light microscopy, for which colour image analysis and shape recognition are being employed. Problem Formulation We investigate methods for the automatic characterisa-tion of surface corrosion using digital image analysis techniques. Two morphologies are being considered: pit formation and cracking. Because the global appearance of the corroded surfaces is a very important factor for the discrimination of the morphologies, they are described as textures. Multiscale Texture Analysis The notion of scale is very important in the decription of textures. Therefore we choose a multiscale texture analysis which is performed with a wavelet transform. With this, an image is represented as a collection of subimages that each contain the information of the details of a speciic scale and orientation. An energy feature is extracted from each subimage. The collection of features form a feature vector that describes the texture. A disadvantage of such a description is that it strongly depends on the orientation. As a solution to this, we propose an extra transformation that converts the features within a scale to orientation independent features. Classiication The feature vectors are being classiied with diierent methods. Successively, we study a Baysian classiication which assumes a normal distribution of the data per class, a k-nearest neighbour classiication that makes a decision based on the k most similar examples, and a neural network method called Learning Vector Quantisation. This last one shows to be best capable to adapt itself to the speciic nature of the data, and at the same time suuciently generalise. Special attention is being given to the estimation of classiication performance and to the statistical validity of results. iii iv Experiments An experiment is being performed on a set of 398 example images that represent the two corrosion morphologies. The wavelet-based texture analysis (in diierent variants) and the classiication methods are being employed. The best result yields 81; 9% correctly classiied images. By combining the outputs of diierent classiications, this can be improved upto 86; 2%. The results show that the approach is useful for the characterisation of corrosion. It is also interesting as …
Toward interoperability in a web of things

In this position paper we explore the challenges and issues around interoperability in the web of things. A key concern is how to increase interoperability while maintaining a high degree of innovation and exploration in the community. To that end we propose a hub- centric approach toward interoperability consisting of four levels or stages. We are working to validate this approach in the context of a large-scale IoT ecosystem project consisting of eight IoT hubs in different domains where a key requirement is hub-to-hub and hub- application interoperability.
Long‐term blood vessel removal with combined laser and topical rapamycin antiangiogenic therapy: Implications for effective port wine stain treatment

Complete blanching of port wine stain (PWS) birthmarks after laser therapy is rarely achieved for most patients. We postulate that the low therapeutic efficacy or treatment failure is caused by regeneration and revascularization of photocoagulated blood vessels due to angiogenesis associated with the skin's normal wound healing response. Rapamycin (RPM), an antiangiogenic agent, has been demonstrated to inhibit growth of pathological blood vessels. Our objectives were to (1) investigate whether topical RPM can inhibit reperfusion of photocoagulated blood vessels in an animal model and (2) determine the effective RPM concentration required to achieve this objective.
DCSim: Design Analysis on Virtualization Data Center

Virtualization has become a core technique to support a data center, which usually consists of hardware, virtual machine(VM), and operating system(OS) etc. With virtualization, users can make good use of resources provided in a data center with resource protection and efficient hardware utilization. However, as data amount has increased very rapidly, many issues such as low power and resource sharing have become very critical. To resolved these issues, this paper presents a novel simulation environment based on a tiny OS, Hard Disk Drive (HDD), and Solid State Drive(SSD) to help users and designers understand a data center via simulation and analysis. Compared with the previous work, our tool can simulate and analyze homogeneous and heterogeneous systems with a multi-layer approach. Although each part of a data center has been studied by researchers, the analysis for data centers with multiple layers or heterogeneous devices is still an important issue. If programmers cannot analyze a data center, they are not easy to handle resources efficiently or understand cross-layer influence. They may encounter unpredictable challenges arising from the integration of various components. To address these challenges, programmer and system designer will be need thorough understanding of multi-layer heterogenous system. We propose a new simulation tool called Data Center Simulator(DCSim). We have used small-scale os and storage simulation to achieve multi-layer system simulation to help us to understand multi-layer heterogenous system. Therefore, programmer can simulate and analysis the system that we will analysis the parallel program and different storage deices on DCSim.
Compressed sensing in spatial MIMO channels

Many wireless channels exhibit sparse multipath feature in practice. In this paper, we analyze the sparsity of sparse MIMO channel and the leakage effect with fixed Fourier basis in the spatial/angular domain. In order to enhance the sparsity of the MIMO angular channels we propose an optimized overcomplete Fourier basis dictionary, which is obtained by a sparsity criterion, to represent the signals with the best basis. By converting the compressed sensing from multiple measurement vectors to a single measurement vector, the reconstruction of the MIMO channel is simplified and makes better use of the sparsity of the MIMO angular channels. Simulations show that with the optimized basis dictionary the leakage effect is reduced and the orthogonal matching pursuit algorithm can reconstruct the MIMO channel effectively with the optimized Fourier basis.
Fuzzy Logic Approach to Represent and Propagate Imprecision in Agri-Environmental Indicator Assessment

The indicator of groundwater contamination devel- oped and used in agriculture is calculated from data available in the field or data estimated by an expert. The modeling of this indica- tor generally requires a large number of parameters whose measure is imprecise. Several information sources provide information about the same imprecise quantities which have to be combined for defining what is called an "indicator of groundwater contamination" (Igro). This indicator estimates the impact of cultivation practices on the groundwater contamination. In this paper, we explore a possibilistic information fusion method by using the notion of maximal coherent subsets to represent the impre- cisions of multisource variables of the indicator. We also calculate the bounds of this indicator, and we propagate imprecision by using an interval analysis. Finally, we present the indicator's results for pesticides applied on different crops.
MySocialTree : Browsing the Facebook feed using hierarchies

Twitter and Facebook share one characteristic in common, they both change rapidly, and every time is more difficult for its users to keep up with all the updates and tweets post in their feeds, and to filter out the most relevant ones. I present MySocialTree a novel tool for navigating users feeds using hierarchical structures. This paper describes the goals of the project and the challenges faced in its development. An initial implementation of the tool was developed and deployed on http:// mysocialtree.appspot. com, and an exploratory user satisfaction survey suggests that the tool can be easy to understand and effective at finding the most relevant posts in the feed.
The relationship between implementation variables and performance improvement of ERP systems

This study explores the relationship between implementation variables and performance improvements of ERP systems. DeLone and McLean's (1992) information systems (IS) success framework is adopted to develop performance measures to evaluate improvements in the performance of ERP systems after implementing ERP systems. The implementation variables investigated in this study are the ERP implementation status, ERP system source and ERP implementation strategy. Structured questionnaires were sent to companies listed in the top 5000 largest corporations of Taiwan. The research findings indicate that the strongest ERP systems performance improvement comes from companies that implement non-packaged ERP systems, using integral planning, and employing all the planned ERP modules.
A review for short-term scheduling of batch processes

Significant progresses in the area of short-term scheduling of batch processes have been achieved in the pass two decades. The main objective of this paper is to present a review in this challenging area. Based on time representation, existing scheduling approaches are classified into discrete and continuous time formulation and their strengths and limitations are also examined. Furthermore, some applications of the scheduling in the real world are described. Finally, we give the perspective of the short-term scheduling.
Summarizing figures, tables, and algorithms in scientific publications to augment search results

Increasingly, special-purpose search engines are being built to enable the retrieval of document-elements like tables, figures, and algorithms [Bhatia et al. 2010; Liu et al. 2007; Hearst et al. 2007]. These search engines present a thumbnail view of document-elements, some document metadata such as the title of the papers and their authors, and the caption of the document-element. While some authors in some disciplines write carefully tailored captions, generally, the author of a document assumes that the caption will be read in the context of the text in the document. When the caption is presented out of context as in a document-element-search-engine result, it may not contain enough information to help the end-user understand what the content of the document-element is. Consequently, end-users examining document-element search results would want a short “synopsis” of this information presented along with the document-element. Having access to the synopsis allows the end-user to quickly understand the content of the document-element without having to download and read the entire document as examining the synopsis takes a shorter time than finding information about a document element by downloading, opening and reading the file. Furthermore, it may allow the end-user to examine more results than they would otherwise. In this paper, we present the first set of methods to extract this useful information (synopsis) related to document-elements automatically. We use Naïve Bayes and support vector machine classifiers to identify relevant sentences from the document text based on the similarity and the proximity of the sentences with the caption and the sentences in the document text that refer to the document-element. We compare the two classification methods and study the effects of different features used. We also investigate the problem of choosing the optimum synopsis-size that strikes a balance between the information content and the size of the generated synopses. A user study is also performed to measure how the synopses generated by our proposed method compare with other state-of-the-art approaches.
The affordances of media spaces for collaboration

ABSTRACT In this paper, I discuss the affordances offered by media spaces for collaboration, contrasting their properties with those of the everyday medium and exploring the implications for perception and interaction. Collaboration is situated in a physical environment which supports or constrains the various forms social interactions might take. An analysis of the affordances of the environment – the properties that offer actions and interactions to those within it – thus complements analyses which emphasize social and cultural factors. Examining the “physics” of media space systems is helpful both in understanding how people use them to collaborate and in suggesting possibilities for design.
How to develop smarter host mixtures to control plant disease

A looming challenge for agriculture is sustainable intensification of food production to feed the growing human population. Current chemical and genetic technologies used to manage plant diseases are highly vulnerable to pathogen evolution and are not sustainable. Pathogen evolution is facilitated by the genetic uniformity underlying modern agroecosystems, suggesting that one path to sustainable disease control lies through increasing genetic diversity at the field scale by using genetically diverse host mixtures. We investigate how host mixtures can improve disease control using a population dynamics model. We find that when a population of crop plants is exposed to host-specialized pathogen species or strains, the overall disease severity is smaller in the mixture of two host varieties than in each of the corresponding pure stands. The disease severity can be minimized over a range of mixing ratios. These findings may help in designing host mixtures that efficiently control diseases of crops. We then generalize the model to describe host mixtures with many components. We find that when pathogens exhibit host specialization, the overall disease severity decreases with the number of components in the mixture. As the degree of specialization increases, the decrease in disease severity becomes larger. Using these model outcomes, we propose ways to optimize the use of host mixtures to decrease disease in agroecosystems.
MEAN-FIELD SPIN GLASS MODELS FROM THE CAVITY-ROST PERSPECTIVE

The Sherrington-Kirkpatrick spin glass model has been studied as a source of insight into the statistical mechanics of systems with hi ghly diversified collections of competing low energy states. The goal of this summary is to present some of the ideas which have emerged in the mathematical study of its free energy. In particular, we high- light the perspective of the cavity dynamics, and the relate d variational principle. These are expressed in terms of Random Overlap Structures (ROSt), which are used to describe the possible states of the reservoir in the cavity step. The P arisi solution is presented as reflecting the ansatz that it suffices to restrict the variati on to hierarchal structures which are discussed here in some detail. While the Parisi solution was proven to be correct, through recent works of F. Guerra and M. Talagrand, the reasons for the effectiveness of the Parisi ansatz still remain to be elucidated. We question whether this could be related to the quasi-stationarity of the special subclass of ROSts giv en by Ruelle's hierarchal 'random probability cascades' (also known as GREM).
Speeding up random walks by choosing unvisited edges or vertices ?

In this paper we use simulations to investigate the vertex cover time of several related random walk related processes. The modifications are as follows: Our first process (E-process) uses unvisited edge whenever possible. Our second process (V -process) uses unvisited vertices whenever possible. Our third process assumes that every vertex has a list with all its neighbours in a random order. Each time a vertex is left during the walk, the next neighbour w.r. t. this permutation is used (modulo degree), in a round-robin fashion. We investigate the performance of these processes on the following regular graphs of constant degree: the two-dimensional torus and random d-regular graphs, RR[d]. In the case of d ≥ 4 even it is known theoretically that (almost surely) the E-process has cover time linear in the number of vertices; but these processes are not generally well understood. Our simulations show that in most settings the E-process has the smallest cover time. We will also see that the E-process is especially fast for RR[d] with constant and even d.
Making the Urban Coast

Submissions from multiple theoretical perspectives, regions, and disciplines that correspond to the journal’s mission are welcome. Submit manuscripts online at www.editorialmanager. com/cssaame/. Manuscripts (text, quotations, and footnotes) should be no longer than 10,000 words. For house style, especially documentation style, consult the journal’s style guide, which follows The Chicago Manual of Style, 16th edition. Transliterations should be provided and should follow the Library of Congress system for romanization, without diacritical marks, except ayn and hamza. See www.loc. gov/catdir/cpso/roman.html. Send correspondence about editorial matters to cssaame @dukeupress.edu.
Optimizing Database Accesses for Parallel Processing of Multikey Range Searches

A multikey search query has many qualified records because it specifies some of the attributes and the rest of them are unspecified. Thus, data distribution among the parallel devices is important to enhance access concurrency for multikey search queries. Though there are some heuristics on data distribution for multikey accesses, range specification in a query has not been considered in those methods. In this paper we investigate optimal data distribution for multiattribute range queries in parallel processing file systems. We show for various-types of multiattribute range queries that there are inherent limitations to achieve optimal distribution. The results show that optimal distribution does not exist in many cases even for files with two fields. We give sufficient conditions for the nonexistence of perfect optimal distribution for certain types of multiattribute range queries. We have also developed data distribution methods for several useful multiattribute range queries. Sufficient conditions for optimal distribution by these proposed data distribution methods are given. It will be shown that the proposed distribution methods are perfect optimal for certain types of multiattribute range queries, and strict optimal for a large class of multiattribute range queries.