Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Social Capital in Organizations: The Precursors and Effects of Social Capital among Certified Nurse Aides in Nursing Homes

The role of social capital in forming organizational commitment is the focus of this research. Organizational social capital is the idea that social relationships have value in the organization. The theoretical framework is based on Kanter's (1993) structure of organizational commitment. This research views the structure within organizations based on global empowerment, job satisfaction, organizational commitment, and social capital. In addition, the role that race, income, and education affect the organizational structure is also taken into account. The organizational configuration was assembled using a structural equation model with latent variables employing a sample of 235 certified nurse aides. The sample was collected from 10 nursing homes in the Dallas-Ft.Worth metropolitan area. It was expected that Kanter's general format is reestablished within the sample. In fact, the study found that empowerment significantly influences job satisfaction. In turn, job satisfaction does foster organizational commitment. Although Kanter's original thesis was supported in this analysis, it was also determined that social capital plays a significant mediating role in creating organizational commitment. Furthermore, this research indicates that social capital alone can create organizational commitment. Thus, in conclusion, this research builds on Kanter's original idea and argues that organizational commitment is based on job satisfaction, global empowerment, and social capital.
Environment Map Morphing

The techniques of static and dynamic view morphing [19, 12] are extended to allow for (1) interpolation between arbitrary, uncalibrated environment maps (complete or partial), (2) camera motion directly towards or away from the scene (so that the epipole is visible), and (3) views of dynamic scenes in which an object’s vanishing point is visible inside the object. It is shown that, by using an image cylinder instead of an image plane, the scanline property [18] can be preserved and the morphing process can be made continuous for environment maps. Environment map interpolation together with layering provides an uncalibrated, sprite-like graphics primitive similar to “billboarding” techniques. This work is sponsored by the National Science Foundation under Grant No. IIS-9530985 and by the Defense Advanced Research Projects Agency (DARPA) and Rome Laboratory, Air Force Materiel Command, USAF, under agreement number F30602-97-1-0138. Figure 1: View interpolation involves synthesizing the view from the camera in the middle frame starting with only the two reference views from the cameras in the left and right frames. In this case, the epipole will be visible in the first view.
Filopodia and Viruses: An Analysis of Membrane Processes in Entry Mechanisms

Filopodia are thin, actin rich bundles protruding from cell plasma membranes, serving physiological purposes, such as probing the environment and facilitating cell-to-cell adhesion. Recent studies have highlighted that actively polymerized filopodial-protrusions are exploited during virus entry, trafficking, spread, and the development of clinical pathology of viral diseases. These observations have caused a surge in investigation of the key determinants of filopodial induction and their influence on cell topography including receptor expression for viral entry. It is now very clear that filopodia can provide unique opportunities for many viruses to invade host cells vertically during primary infection, or horizontally during virus spread from cell-to-cell. These emerging concepts can explain the unprecedented ability of viruses to invade both nearby and long-distant host cells, a feature that may directly contribute to viral tropism. In this review, we summarize the significance of filopodia in viral diseases and discuss future therapeutic possibilities to precisely target filopodial-flyovers to prevent or control infectious diseases.
Stable Matching Based on Disparity Components

In this paper, we demonstrate how disparity maps could be improved by applying adaptive windows (varying in their shape). In our approach, windows adapt to high-correlation structures in disparity space, which we call disparity components . The method is straightforward and it is applicable to any stereo algorithm. This helps us in solving standard stereo problems such as: (1) to enforce the inter-line continuity constraint, (2) to improve disparity map accuracy. To show the proposed method properties, we measure the improvement of stereo matching failure due to adaptive windows in a rigorous ground-truth evaluation experiment. We demonstrate that adaptive windows account for 15× improvement in false positive rate and5× improvement in mismatch rate. All other measured types of error improve only marginally. Our results on standard stereo pairs are also presented.
A Study on the Efficiency Aspect of Data Race Detection: A Compiler Optimization Level Perspective

Dynamically detecting data races in multithreaded programs incurs significant slowdown and memory overheads. Many existing techniques have been put forward to improve the performance slowdown through different dimensions such as sampling, detection precision, and data structures to track the happened-before relations among events in execution traces. Compiling the program source code with different compiler optimization options, such as reducing the object code size as the selected optimization objective, may produce different versions of the object code. Does optimizing the object code with a standard optimization option help improve the performance of the precise online race detection? To study this question and a family of related questions, this paper reports a pilot study based on four benchmarks from the PARSEC 3.0 suite compiled with six GCC compiler optimization options. We observe from the empirical data that in terms of performance slowdown, the standard optimization options behave comparably to the optimization options for speed and code size, but behave quite different from the baseline option. Moreover, in terms of memory cost, the standard optimization options incur similar memory costs as the baseline option and the option for speed, and consume less memory than the option for code size.
Protein dynamics with off-lattice Monte Carlo moves.

A Monte Carlo method for dynamics simulation of all-atom protein models is introduced, to reach long times not accessible to conventional molecular dynamics. The considered degrees of freedom are the dihedrals at C$_\alpha$-atoms. Two Monte Carlo moves are used: single rotations about torsion axes, and cooperative rotations in windows of amide planes, changing the conformation globally and locally, respectively. For local moves Jacobians are used to obtain an unbiased distribution of dihedrals. A molecular dynamics energy function adapted to the protein model is employed. A polypeptide is folded into native-like structures by local but not by global moves.
On the solvability of homogeneous two-sided systems in max-algebra

Let a b = max(a;b) and a b = a+b for a;b2 R and extend the pair of operations to matrices and vectors in the same way as in linear algebra. The homogeneous twosided system in max-algebra is of the form A x = B x. No polynomial method for solving homogeneous system is known. In this paper, we consider homogeneous twosided linear systems in max-algebra in a special case. We show that it can be checked in O(n 3 ) time whether a given two-sided homogeneous system belongs to this special case. Solvability can be decided in O(n 3 ) time and in the positive case a solution can be found in O(n 3 ).
On the Relation between Linear Dispersion and Generic Network Code

Four classes of linear network codes have been introduced in the recent work of Yeung et al., namely linear multicast, linear broadcast, linear dispersion and generic linear network code, where each of these four classes of codes is strictly stronger than the preceding one. In this paper, we establish a nontrivial relation between linear dispersion and generic linear network code
0 00 10 22 v 2 2 4 Ja n 20 00 1 Strings and Branes in Nonabelian Gauge Theory CERN-TH / 99-198

It is an old speculation that SU(N) gauge theory can alternatively be formulated as a string theory. Recently this subject has been revived, in the wake of the discovery of D-branes. In particular, it has been argued that at least some conformally invariant cousins of the theory have such a string representation. This is a pedagogical introduction to these developments for non-string theorists. Some of the existing arguments are simplified.
Laccase: Microbial Sources, Production, Purification, and Potential Biotechnological Applications

Laccase belongs to the blue multicopper oxidases and participates in cross-linking of monomers, degradation of polymers, and ring cleavage of aromatic compounds. It is widely distributed in higher plants and fungi. It is present in Ascomycetes, Deuteromycetes and Basidiomycetes and abundant in lignin-degrading white-rot fungi. It is also used in the synthesis of organic substance, where typical substrates are amines and phenols, the reaction products are dimers and oligomers derived from the coupling of reactive radical intermediates. In the recent years, these enzymes have gained application in the field of textile, pulp and paper, and food industry. Recently, it is also used in the design of biosensors, biofuel cells, as a medical diagnostics tool and bioremediation agent to clean up herbicides, pesticides and certain explosives in soil. Laccases have received attention of researchers in the last few decades due to their ability to oxidize both phenolic and nonphenolic lignin-related compounds as well as highly recalcitrant environmental pollutants. It has been identified as the principal enzyme associated with cuticular hardening in insects. Two main forms have been found: laccase-1 and laccase-2. This paper reviews the occurrence, mode of action, general properties, production, applications, and immobilization of laccases within different industrial fields.
Vesicular Monoamine Transporter-2 and Aromaticl-Amino Acid Decarboxylase Enhance Dopamine Delivery afterl-3,4-Dihydroxyphenylalanine Administration in Parkinsonian Rats

Medical therapy in Parkinson’s disease (PD) is limited by the short-duration response and development of dyskinesia that result from chronic l-3,4-dihydroxyphenylalanine (l-DOPA) therapy. These problems occur partly because the loss of dopamine storage sites leads to erratic dopamine delivery. Vesicular monoamine transporter-2 (VMAT-2) plays a critical role in dopamine storage by packaging dopamine into synaptic vesicles and regulating sustained release of dopamine. To restore the capacity to produce and store dopamine in parkinsonian rats, primary skin fibroblast cells (PF) were genetically modified with aromatic l-amino acid decarboxylase (AADC) and VMAT-2 genes. After incubation withl-DOPA in culture, the doubly transduced fibroblast cells (PFVMAA) produced and stored dopamine at a much higher level than the cells with either gene alone. PFVMAA cells in culture released dopamine gradually in a constitutive manner. Genetically modified fibroblast cells were grafted in parkinsonian rat striata, and l-DOPA was systemically administered. Higher dopamine levels were sustained for a longer duration in rats grafted with PFVMAA cells than in those grafted with either control cells or cells with AADC alone. These findings underscore the importance of dopamine storage capacity in determining the efficacy of l-DOPA therapy and illustrate a novel method of gene therapy combined with precursor administration to overcome the major obstacles of PD treatment.
Integrating a network IDS into an open source Cloud Computing environment

The success of the Cloud Computing paradigm may be jeopardized by concerns about the risk of misuse of this model aimed at conducting illegal activities. In this paper we address the issue of detecting Denial of Service attacks performed by means of resources acquired on-demand on a Cloud Computing platform. To this purpose, we propose to investigate the consequences of the use of a distributed strategy to detect and block attacks, or other malicious activities, originated by misbehaving customers of a Cloud Computing provider. In order to check the viability of our approach, we also evaluate the impact on performance of our proposed solution. This paper presents the installation and deployment experience of a distributed defence strategy and illustrates the preliminary results of the performance evaluation.
Intersections of Quadrics, Moment-angle Manifolds and Connected Sums

The topology of the intersection of two real homogeneous coaxial quadrics was studied by the second author who showed that its intersection with the unit sphere is in most cases diffeomorphic to a connected sum of sphere products. Combining that approach with a recent one (due to Antony Bahri, Martin Bendersky, Fred Cohen and the first author) we study here the intersections of k>2 quadrics and we identify very general families of such manifolds that are diffeomorphic to connected sums of sphere products. These include those moment-angle manifolds for which the result was conjectured by Frederic Bosio and Laurent Meersseman. As a byproduct, a simpler and neater proof of the result for the case k=2 is obtained. Two new sections contain results not included in the first version of this article: Section 2 describes the topological change on the manifolds after the operations of cutting off a vertex or an edge of the associated polytope, which can be combined in a special way with the previos results to produce new infinite families of manifolds that are connected sums of sphere products. In other cases we get slightly more complicated manifolds: with this we solve another question by Bosio-Meersseman about the manifold associated to the truncated cube. In Section 3 we use this to show that the known rules for the cohomology product of a moment-angle manifold have to be drastically modified in the general situation. We state the modified rule, but leave the details of this for another publication. Section 0 recalls known definitions and results and in section 2.1 some elementary topological constructions are defined and explored. In the Appendix we state and prove some results about specific differentiable manifolds, which are used in sections 1 and 2.
Magnetic Resonance Imaging to Visualize Stroke and Characterize Stroke Recovery: A Review

The global burden of stroke continues to grow. Although stroke prevention strategies (e.g., medications, diet, and exercise) can contribute to risk reduction, options for acute interventions (e.g., thrombolytic therapy for ischemic stroke) are limited to the minority of patients. The remaining patients are often left with profound neurological disabilities that substantially impact quality of life, economic productivity, and increase caregiver burden. In the last decade, however, the future outlook for such patients has been tempered by movement toward the view that the brain is capable of reorganizing after injury. Many now view brain recovery after stroke as an area of scientific research with large potential for therapeutic advances, far into the future (Broderick and William, 2004). As a probe of brain anatomy, function and physiology, magnetic resonance imaging (MRI) is a non-invasive and highly versatile modality that promises to play a particularly important role in such research. Here we provide a basic review of MRI physical principles and applications for assessing stroke, looking toward the future role MRI may play in improving stroke rehabilitation methods and stroke recovery.
omputational structure analysis of biomacromolecule complexes by nterface geometry

The ability to analyze and compare protein–nucleic acid and protein–protein interaction interface has critical importance in understanding the biological function and essential processes occurring in the cells. Since high-resolution three-dimensional (3D) structures of biomacromolecule complexes are available, computational characterizing of the interface geometry become an important research topic in the field of molecular biology. In this study, the interfaces of a set of 180 protein–nucleic acid and protein–protein complexes are computed to understand the principles of their interactions. The weighted Voronoi diaomputational geometry rotein–nucleic acid complexes rotein–protein complexes oronoi diagram gram of the atoms and the Alpha complex has provided an accurate description of the interface atoms. Our method is implemented in the presence and absence of water molecules. A comparison among the three types of interaction interfaces show that RNA–protein complexes have the largest size of an interface. The results show a high correlation coefficient between our method and the PISA server in the presence and absence of water molecules in the Voronoi model and the traditional model based on solvent accessibility and the high validation parameters in comparison to the classical model.
Correcting sample selection bias for image classification

One of the basic assumptions in traditional machine learning is that it requires training and test data be under the same distribution. However, in image classification, this assumption often does not hold, since image labels are not as sufficient as text ones. In this paper, we propose to use labeled images from relevant but different categories to take the role of training data for estimating a prediction model. Correcting sample selection bias, the 2000 Nobel Prize work in Economic, is applied to our problem. We assume that the difference between training and test data is that they are governed by different distributions. By eliminative sample selection bias in the training data, the supervisory knowledge in the training data can be effectively learned for classifying images in the test set. We present theoretical and empirical analysis to demonstrate the effectiveness of our algorithm. The experimental results on two image corpora show that our algorithm can greatly improve several state-of-the-art classifiers when the training and test images come from similar but different categories.
Localization of epileptic focus using SVM and PSVM

Localization of epileptic focus and motor regions, is presented in the paper using raw referential EEG data from database http://eeg.pl/epi of Warsaw Memorial Child Hospital. The study is carried out on two patients named CHIMIC and JANPRZ who were diagnosed with drug-resistant epilepsy and were subsequently operated. Along with EEG recordings, inter-ictal discharges, magnetic resonance imaging (MRI) scans, structural placement of the epileptogenic zone and clinical description, are used in the study. The key step involved in the analysis, is to create an algorithm that shapes the problem into an appropriate machine learning framework, identifying the features, forward modeling of the extracted features and finally classifying them as epileptic seizures arising from the location on the right or left region of the brain. The feature extraction is done by independent component analysis (ICA) with spatially filtered eight spectral features per components. These features are classified using Support Vector Machines with radial basis function kernels (SVM) and Proximal SVM. A comparative study is done for evaluating specificity and sensitivity using segments of ICA data. The analysis and results of both patients indicates that the specificity and sensitivity ratios are higher for ICA with SVM rather than those obtained from PSVM. Localization of epileptic focuses from the classified results showed that they matched with the marked epileptic regions in the MRI scans.
Energy Detection Algorithm Based on Wavelet Packet Transform under Uncertain Noise for Spectrum Sensing

Spectrum sensing is a key technology in cognitive radio technology and has attracted lots of attention in both academia and industry. This paper addresses the spectrum sensing under uncertain noise power and proposes an energy detection algorithm, which is based on the wavelet packet transform. By means of wavelet packet transform, noise power and signal power are estimated, and the threshold for spectrum sensing is obtained. The simulations show that the proposed algorithm has the robustness to the noise uncertainty and is a quite promising technology for CR applications.
Randomized Wait-free Naming Randomized Wait-free Naming

We present new distributed randomized naming protocols improving previous results in renaming and unique processor identity protocols. They are wait-free (which implies maximal fault-tolerance) and allow stronger adversaries. They also have low complexity. We give the rst wait-free protocol achieving optimal key space range. (This is impossible for deterministic wait-free methods, so we use randomization.) We also introduce a novel wait-free object, a test-and-set object which upon invocation succeeds with probability less than 1, and we give a low complexity implementation of such objects.
Towards an understanding of the factors that influence teacher engagement in continuimng professional development

The aim of the research reported in this thesis is to examine the factors that Irish post-primary teachers report as influencing their decision making regarding engagement in continuing professional development (CPD) and to present a conceptualisation of what I call engagement. The study examines the current research and theorising about CPD and from this develops an analysis and argument about how there is a need, within the context of CPD, to examine the relationship between the agency of the professional and the structuring context in which they are located. The study offers, through case study work with teachers in six post-primary schools in Ireland, new understandings of teachers' personal views, opinions and reflections with regard to the factors that influence their decision making regarding engagement in CPD. The analysis of the data leads to a number of outcomes, firstly, it offers a conceptualisation of these factors as a contribution towards a refinement of understanding of a model of engagement in CPD, secondly, consideration is given to what engagement means for professionalism and professionality and the implications that arise for both the policy makers and for post-primary teachers in Ireland. In pursuit of these aims the following research questions are addressed:1. What are the factors that influence teacher decision making regarding engagement in CPD? 2. What does this mean for CPD and professional practice? The findings presented in this study are twofold. Firstly, in general, Irish post-primary teachers recognise the need for, and appreciate the potential value and benefit of professional learning in developing their understanding of the learning processes and its potential to improve the student experience and learning outcomes. Secondly, within the current Irish context individual teachers? decision making with regard to engagement in CPD is influenced by a variety of factors but none more so than that of the impact of their decision to engage on their own personal lives. Consequently, it shows that there are emerging tensions between teachers and the Government in light of recent Government policy to locate more and more CPD events in an after school-time elective context. These issues combine to an examination of how teachers are being positioned and are positioning themselves for the reform process and what this means for the professionalism and professionality of Irish post-primary teachers.