Miracle-dz/UniFAR-FTUs huggingface dataset:
Near-ellipsoidal Voronoi coding

We consider a special case of Voronoi coding, where a lattice /spl Lambda/ in /spl Ropf//sup n/ is shaped (or truncated) using a lattice /spl Lambda/'={(m/sub 1/x/sub 1/,.,m/sub n/x/sub n/)|(x/sub 1/,.,x/sub n/)/spl isin//spl Lambda/} for a fixed m_=(m/sub 1/,.,m/sub n/)/spl isin/(/spl Nopf//spl bsol/{0,1})/sup n/. Using this technique, the shaping boundary is near-ellipsoidal. It is shown that the resulting codes can be indexed by standard Voronoi indexing algorithms plus a conditional modification step, as far as /spl Lambda/' is a sublattice of /spl Lambda/. We derive the underlying conditions on m_ and present generic near-ellipsoidal Voronoi indexing algorithms. Examples of constraints on m_ and conditional modification are provided for the lattices A/sub 2/, D/sub n/ (n/spl ges/2) and 2D/sub n//sup +/ (n even /spl ges/4).
A High Dimensional Data Indexing Technique Based on Max Gap Space Mapping

In the similarity query processing based on high dimensional indexing, the searching space is usually narrowed down by pruning the inactive subspaces which do not contain any query results. However, among the active subspaces, some of them do not contain any query results at all, those are called false active subspaces. It is obvious that the performance of query processing degrades in the presence of false active subspaces. The problem becomes seriously in the case of high dimensional data. The experiment in this paper shows that the number of accesses to false active subspaces increases as the dimensionality increases. In order to overcome the problem, a space mapping approach is proposed to reduce such unnecessary accesses. For a given query, it can be refined by filtering within its mapped space. A maximal gap space mapping strategy, MaxGapMapping, is proposed to improve the efficiency of the refinement processing. An index structure——MS-tree, the algorithms of construction, and query processing based on this refining method are designed and implemented. Finally, the performance of MS-tree is systemically compared with that of other competitors in terms of range queries based on a real data set.
Linear fractional LPV model identification from local experiments: An H∞-based optimization technique

In this paper, a new identification technique is introduced to estimate a linear fractional representation of a linear parameter-varying (LPV) system from local experiments by using a dedicated non-smooth optimization procedure. More precisely, the developed approach consists in estimating the parameters of an LPV state-space model from local fully-parameterized identified state-space models through the non-smooth optimization of a specific H∞-based criterion. The method presented in this paper results directly in an LPV model whose parametric matrices can be rational functions of the scheduling variables without any interpolation step (required usually by the local approach) and without writing the local fully-parameterized LTI state-space models with respect to a coherent basis. A numerical example is used to illustrate the performance of the suggested technique.
VALIDATION OF A SCALE MEASURING THE RELATIONSHIPS BETWEEN LONG-TERM ORIENTATION, POLITICAL ORIENTATION, ENVIRONMENTAL PURCHASE INTENTIONS AND GREEN PURCHASE BEHAVIOUR

This paper outlines the procedure undertaken to validate a scale measuring the relationships between long-term and political orientation, and environmental intentions and behaviour as a four dimensional structure in the South African context. The data was gathered using a self-administered questionnaire from a convenience sample of 329 students registered at four public higher education institutions in South Africa. The four higher public institutions comprised one university of technology, one comprehensive university and two traditional universities. The questionnaire consisted of scales intended to measure long-term orientation, political orientation, environmental purchase intentions and green purchase behaviour. Pearson’s Product-Movement correlation and structural equation modelling were the methods of analysis of the captured data. The proposed measurement model of long-term and political orientation, and environmental intentions and behaviour being a four dimensional structure revealed good internal-consistency reliability, composite reliability and construct validity. Furthermore, AMOS produced a well-fitting model represented by acceptable goodness-of-fit indices. The results of the measurement model suggest that long-term orientation, political orientation, environmental purchase intention and green purchase behaviour are four suitable dimensions for the use of path analysis in structural equation modelling
The Generalized Switched Accounting or Conduction

The method of average modeling and simulation of PWM converters was extended to include conduction losses. The method covers losses due to the inductor's resistance and due to the voltage drops across the switch and the diode. The same model is applicable to both CCM and DCM operations, and the switching from one to the other is automatic. The large-signal model is SPICE compatible and as such can be used to run DC (steady state), TRAN (large signal, time domain) and AC (small signal, frequency domain) analyses.
Does the Age of Exposure of Serpentine Explain Variation in Endemic Plant Diversity in California?

We analyzed botanical, geologic, and climatic data in an effort to understand why there are many more serpentine endemics—i.e., plant species restricted to ultramafic substrates—in some regions of California than in others. We found that, in addition to elevational range (which subsumed the effect of serpentine area) and annual rainfall, the age of exposure of serpentine explained significant geographic variation in the diversity of endemic plant species. Estimated ages of subaerial exposure are generally higher in the Klamath and northern Coast Range serpentines than in Sierra Nevadan and southern Coast Range analogues, paralleling the trends in endemic plant diversity. However, the fit of the relationship is weakened by the southern Sierran serpentines, which are apparently long-exposed yet poor in endemic plant species. These results have significance for understanding local ecological processes, because we have also found that the diversity of endemic species within 50 x 10 m field plots is best predicted by the diversity of endemics in the surrounding region, which in turn is a function of the age of subaerial exposure.
Virtual communities of practice: The role of content quality and technical features to increase health care professionals' satisfaction

Knowledge management in health care sector poses a challenge for policy makers and international health organizations. Nowadays, virtual communities of practice (VCoPs) resolve many problems, which arise from geographical distance and expensive learning process in health care sector. It is used by health professionals and researchers, for improving health care services quality, by enhancing the knowledge of health practitioners. Whereby, satisfaction of using VCoPs is the nucleus its success, since, pleasant experience with VCoPs will lead to better “user satisfaction”, which in turn leads to increase the number of users. This study aims to identify the determinants of member’s satisfaction with VCoPs. We have also developed a VCoPs satisfaction model, based on the information systems (IS) success theories: the technology acceptance model (TAM) and DeLone and McLean IS success model. The proposed model can be used to evaluate and measure the satisfaction of VCoPs in health care sector.
Classification applications of sparse signal processing and kernel based methods

Sparsity based signal processing is a relatively new research area which has attracted tremendous interest from researchers. Application areas for sparse signal processing include but are not limited to image processing, pattern recognition and computer vision. This work considers the joint application of sparsity and kernel methods to classification problems. Novel sparsity based classifiers have been effectively utilized in classification. Variants of sparse classifiers utilizing kernel functions on the other hand have garnered limited interest. Here we will examine the combination of non-dictionary learning sparse classifiers with kernel based methods. Simulations in face and digit recognition applications demonstrate competitive performance for classifiers utilizing sparsity and kernel methods concurrently.
Using Queuing Theory to Model Streaming Applications

Queuing theory provides a theoretical framework for quantitative understanding of the performance of streaming applications. There are questions, however, as to the suitability of queuing models to real applications. Here, we investigate the correspondence between a relatively simple queuing model of an FPGA-accelerated BLAST implementation and empirical measurements taken from executions of the actual application.
Note on anomalies in the AdS-CFT correspondence

We test the AdS-CFT correspondence in the case of a d=4 N=2 superconformal field theory by comparing chiral anomalies which are of order [ital N] in the [close quote]t Hooft large [ital N] limit. These include corrections of order 1/N to the conformal anomaly, thus testing the correspondence beyond the extreme large [ital N] limit. The field theory anomalies are reproduced by terms in the 7-brane effective action in the bulk. [copyright] [ital 1999] [ital The American Physical Society]
Investigating the Effects of Negative Affect on Creativity

Prominent research of creativity and affect has historically illuminated the relationship between positive affect and creativity, whereas little is known about the effects- influence of negative affect on creativity. The present study aimed to investigate how negative affect influenced creativity by using a divergent and convergent creativity task. A sample of 54 participants was recruited and randomly assigned to a negative or positive affect condition. Before performing the creativity tasks, participants were exposed to a stimulus which were meant to induce either positive or negative affect. Results shows no significant differences between the participants’ performance on either of the tasks. The limitations of the study, it’s contributions and the potential cause for the non-significant results are discussed thoroughly. (Less)
ScaleMT: a Free/Open-Source Framework for Building Scalable Machine Translation Web Services

ScaleMT: a Free/Open-Source Framework for Building Scalable Machine Translation Web Services Machine translation web services usage is growing amazingly mainly because of the translation quality and reliability of the service provided by the Google Ajax Language API. To allow the open-source machine translation projects to compete with Google's one and gain visibility on the internet, we have developed ScaleMT: a free/open-source framework that exposes existing machine translation engines as public web services. This framework is highly scalable as it can run coordinately on many servers, efficiently managing the resources needed by the engines, and its API is compatible with Google's one. ScaleMT is based on previous efforts to build a web service for the Apertium machine translation toolbox, but we have also tested it with Matxin, another free/open-source transfer-based machine translation engine. Additionally, we have compared ScaleMT to an alternative web service implementation for Apertium, obtaining satisfactory results.
Finite-time cluster synchronization of nonlinearly coupled reaction-diffusion neural networks via spatial coupling and control

The finite-time cluster synchronization (FTCS) problem of nonlinearly coupled (NC) reaction-diffusion neural networks (RDNNs) with hybrid coupling via control is investigated. The coupling matrix for the network can be asymmetric. We design a control strategy only depending on initial states of the network, which can not only help the network achieve the cluster synchronization, and even the FTCS. This can be regarded as the main contribution of this paper. Some criteria for FTCS are obtained from rigorous proof. Finally, we also present the results of numerical simulations.
Tall tales from de Sitter space I: Renormalization group flows

We study solutions of Einstein gravity coupled to a positive cosmological constant and matter which are asymptotically de Sitter and homogeneous. Regarded as perturbations of de Sitter space, a theorem of Gao and Wald implies that generically these solutions are `tall', meaning that the perturbed universe lives through enough conformal time for an entire spherical Cauchy surface to enter any observer's past light cone. Such observers will realize that their universe is spatially compact. An interesting fact, which we demonstrate with an explicit example, is that this Cauchy surface can have arbitrarily large volume for fixed asymptotically de Sitter behavior. Our main focus is on the implications of tall universes for the proposed dS/CFT correspondence. Particular attention is given to the associated renormalization group flows, leading to a more general de Sitter `c-theorem'. We find, as expected, that a contracting phase always represents a flow toward the infrared, while an expanding phase represents a `reverse' flow toward the ultraviolet. We also discuss the conformal diagrams for various classes of homogeneous flows.
Fabric Defects' Automatic Inspection Based on Computer Vision

In the textile production, there may appear many fabric defects. To fabric defects, there are a lot of image-based inspection techniques: Fourier transform, Sobel algorithm of edge inspection, fast Fourier transform (FFT) et. However, Wavelet transform is a kind of multiresolution algorithm, and its multiresolution character corresponds to time-frequency multiresolution of human vision. The result of the research indicates that wavelet transform gives better results than the other traditional methods. So in this article, we use wavelet transform and BP neural network together to inspect and classify the fabric defects. A plain white fabric is adopted as the sample, and the distinguishing defects are oil stains, warp-lacking, and weft-lacking. An area camera with 256×256 resolution is used in the scheme, a grabbed image is transmitted to a computer for wavelet transform, and then the corresponding image data are then used in BP neural network as input. The result shows that the fabric defects’ classification rate can be up to 95% with above method. Keywordsfabric defects; wavelet; inspection;computer vision
Intestinal Epithelial Cells Synthesize Glucocorticoids and Regulate T Cell Activation

Glucocorticoids (GCs) are important steroid hormones with widespread activities in metabolism, development, and immune regulation. The adrenal glands are the major source of GCs and release these hormones in response to psychological and immunological stress. However, there is increasing evidence that GCs may also be synthesized by nonadrenal tissues. Here, we report that the intestinal mucosa expresses steroidogenic enzymes and releases the GC corticosterone in response to T cell activation. T cell activation causes an increase in the intestinal expression of the steroidogenic enzymes required for GC synthesis. In situ hybridization analysis revealed that these enzymes are confined to the crypt region of the intestinal epithelial layer. Surprisingly, in situ–produced GCs exhibit both an inhibitory and a costimulatory role on intestinal T cell activation. In the absence of intestinal GCs in vivo, activation by anti-CD3 injection resulted in reduced CD69 expression and interferon-γ production by intestinal T cells, whereas activation by viral infection led to increased T cell activation. We conclude that the intestinal mucosa is a potent source of immunoregulatory GCs.
Thermographic Decision Support – Detecting and Classifying Faults in Infrared Images

Thermography is the process of using a camera capable of detecting infrared radiation to determine the temperature of an object. There is a multitude of possible uses for the technique, although traditionally the use of thermography has been limited to industrial inspections, due to the high costs of the necessary equipment. However, lately, due to development in the field, the cameras have become much cheaper and therefore the different uses, and users, of the technique has increased. With the lowered costs of the cameras comes new inexperienced users that may need help in interpreting the results produced by the cameras. For these users, a decision support system, that could guide them in their use of the camera, would be of great importance. This thesis discusses how such a system could be implemented and also presents a proposed system that can be used to identify faults in infrared images of electrical installations. The proposed system works in two layers, Identification of regions of interest (ROIs), and Classification of ROIs. The identification is conducted using an algorithm that detects repeating objects in an image by extracting SIFT features and determines the most probable translation between these features. The classification of the identified regions is done using a feed-forward neural network. This is a novel field of research, and to the best of my knowledge, this is the first work done on decision systems based on infrared images of electrical installations. Termografibeslutsstöd: Att finna och klassificera fel i infraröda bilder Examensarbete vid CSC
Activation of RuvC Holliday junction resolvase in vitro

The Escherichia coli RuvC protein is an endonuclease that resolves Holliday junctions. In vitro, the protein shows efficient structure-specific binding of Holliday junctions, yet the rate of junction resolution is remarkably low. We have mapped the sites of cleavage on a synthetic junction through which a crossover can branch migrate through 26 bp and find that > or = 90% of the junctions were cleaved at one site. This observation of sequence-specific cleavage suggests that inefficient resolution may be due to DNA binding events which occur away from the cleavage site and are therefore non-productive. Holliday junction resolution by RuvC protein can be stimulated by a number of factors including: (i) the presence of Mn2+ (rather than Mg2+) as the divalent metal cofactor, (ii) alkaline pH (< or = 10), and (iii) elevated temperature. These observations may indicate that other proteins are required for efficient RuvC-mediated resolution.
Molecular paleoecology: using gene regulatory analysis to address the origins of complex life cycles in the late Precambrian

SUMMARY Molecular paleoecology is the application of molecular data to test hypotheses made by paleoecological scenarios. Here, we use gene regulatory analysis to test between two competing paleoecological scenarios put forth to explain the evolution of complex life cycles. The first posits that early bilaterians were holobenthic, and the evolution of macrophagous grazing drove the exploitation of the pelagos by metazoan eggs and embryos, and eventually larvae. The alternative hypothesis predicts that early bilaterians were holopelagic, and new adult stages were added on when these holopelagic forms began to feed on the benthos. The former hypothesis predicts that the larvae of protostomes and deuterostomes are not homologous, with the implication that larval‐specific structures, including the apical organ, are the products of convergent evolution, whereas the latter hypothesis predicts homology of larvae, specifically homology of the apical organ. We show that in the sea urchin, Strongylocentrotus purpuratus, the transcription factors NK2.1 and HNF6 are necessary for the correct spatial expression profiles of five different cilia genes. All of these genes are expressed exclusively in the apical plate after the mesenchyme‐blastula stage in cells that also express NK2.1 and HNF6. In addition, abrogation of SpNK2.1 results in embryos that lack the apical tuft. However, in the red abalone, Haliotis rufescens, NK2.1 and HNF6 are not expressed in any cells that also express these same five cilia genes. Nonetheless, like the sea urchin, the gastropod expresses both NK2.1 and FoxA around the stomodeum and foregut, and FoxA around the proctodeum. As we detected no similarity in the development of the apical tuft between the sea urchin and the abalone, these molecular data are consistent with the hypothesis that the evolution of mobile, macrophagous metazoans drove the evolution of complex life cycles multiple times independently in the late Precambrian.
Integrative Genomics and Functional Explanation

In this paper we present a conceptual framework common to all studies of global biological variation. It comprises of three components; data, concepts, and analyses. Most studies are still founded on the collection of one or two data types, but with the recent emergence and deployment of affordable high-throughput biological technologies, an increasing number of studies are reporting integrative approaches. We evaluate the contributions of these studies to biological understanding and conclude with discussion about integrative functional studies as a necessary follow-up to global discovery driven approaches.
Adaptive Modulation for a Downlink Multicast Channel in OFDMA systems

In this paper we focus on adaptive modulation strategies for multicast service in orthogonal frequency division multiple access systems. A reward function has been defined as the optimization target, which includes both the average user throughput and bit error rate. We also developed an adaptive modulation strategy, namely local best reward strategy, to maximize this reward function. The performance of different modulation strategies are compared in different SNR distribution scenarios, and the optimum strategy in each scenario is suggested.
ICST Math Retrieval System for NTCIR-11 Math-2 Task

In NTCIR-11, the NTCIR-Math-2 Task is organized for mathematical information retrieval. This paper proposes an innovative system for ecient formula index and retrieval. We build a novel indexing and matching model, taking both textual and spatial similarities into consideration. Besides, a hierarchical technique is introduced to generate sub-trees from the semi-operator trees of formulae. The experimental results demonstrate that the method of our system is eective and promising in practical application.
A new method of network bottleneck diagnosis

We suggest a method of bottleneck diagnosis with more excellent performance. There are some problems with current diagnosis methods, such as extra network packets and sensitivity to time changes. In this paper, for UDP network, we propose a new method of bottleneck diagnosis based on the concept of network utility maximization. This bottleneck diagnosis method overcomes the disadvantages of current methods, since it totally depends on mathematic models and method, instead of sending and processing large numbers of packets. The problem is modeled as a geometric program problem and the link loss rates are computed by solving the maximization problem. In addition, the method is expanded to random input rates, allowing network managers to control the network performance more flexibly. At last, experiments are carried out to compare the new method with the method proposed by Shetty et al [1]. The results indicate that our method has better performance in both networks with fixed rates and with random rates.
Incidental pelvic lesions in the oncology patient

Abstract The identification of an incidental (i.e. unexpected and asymptomatic) lesion can create a dilemma for the clinician and radiologist. The incidental abnormality may represent metastatic disease, a second primary malignancy or a benign lesion. The diagnosis and management of such incidental findings will depend in part on the clinical setting, the pathology and stage of underlying primary malignancy and the imaging features of the incidental abnormality. This article reviews the diagnosis and management of incidental pelvic lesions in the oncology patient.