Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparse signal reconstruction on the sphere: implications of a new sampling theorem

A new sampling theorem on the sphere has been developed recently, reducing the number of samples required to represent a band-limited signal by a factor of two for equiangular sampling schemes. For signals sparse in a spatially localised measure, such as in a wavelet basis, overcomplete dictionary, or in the magnitude of their gradient, for example, a reduction in the number of samples required to represent a band-limited signal has important implications for sparse signal reconstruction on the sphere. A more efficient sampling of the sphere improves the fidelity of sparse signal reconstruction through both the dimensionality and spatial sparsity of signals. To demonstrate this result we consider a simple inpainting problem on the sphere and consider signals sparse in the magnitude of their gradient. We develop a framework for total variation (TV) inpainting, which relies on a sampling theorem to define a discrete TV norm on the sphere. Solving these problems is computationally challenging; hence we develop fast methods for this purpose. Numerical simulations are performed, verifying the enhanced fidelity of sparse signal reconstruction due to the more efficient sampling of the sphere provided by the new sampling theorem.
Using regression splines for software performance analysis

To make software performance prediction more powerful, execution demand functions must be measured over ranges of system parameters, preferably using scripts to automate the collection of large numbers of cases. Once data is collected it is natural to represent it by a regression function, and to interpolate using the function, to obtain parameters for models as they are needed. Although some practitioners have used linear functions, recent experience has shown that simple polynomial regression functions are often inadequate for these “resource functions”. They may be very irregular, even jagged. Regression splines offer a simple representation that can adapt to very irregular functions, and which can be fitted automatically. Resource functions offer an opportunity to gather enough data to provide whatever accuracy we require, by going back for more data after doing a partial fit. However regression splines do not have a strong theory of prediction errors. This research has addressed the estimation of accuracy of fit, and the control of the additional data gathering, to provide a controlled degree of error in the fitted function. A typical example shows the power of the technique.
Application of improved core vector machine in the prediction of algal blooms in Tolo Harbour

Support vector machine (SVM) and its derivative algorithms have been increasingly used to predict algal blooms recently. However, its computation complexity remains an annoying problem. To improve the time cost of SVM, a hybrid approach is proposed in this paper based on Partial Least Square (PLS) feature extraction and Core Vector Machine Regression (CVR) algorithm. We describe the principle of our algorithm and the implementation steps in detail. Based on the biweekly data gathered from Tolo Harbour, Hong Kong, some comparative analysis of the performance of PLS-CVR and other algorithms are presented. We develop these prediction models with different lead time (7-day and 14-day) to study further. The results indicate that the use of biweekly data can simulate the general trend of algal biomass reasonably. The experimental results show that our algorithm can reduce the time cost significantly compared to conventional SVM algorithm while maintaining a satisfactory accuracy.
Cholesterol lowering for secondary prevention: What statin dose should we use?

Over the past decade, 17 large placebo-controlled trials have established that statin therapy lowers LDL cholesterol and prevents cardiovascular events and death in patients with coronary disease or at high risk for atherosclerotic events. Nine trials of higher dose vs. lower dose statins (reporting data from 29,853 patients with coronary artery disease and 486 patients with other indications for statin therapy) have established that higher dose statin therapy is more efficacious than lower dose therapy in reducing myocardial infarctions/coronary death (by 16%) and stroke (by 18%) in patients with coronary disease but only reduces all-cause mortality in patients at high risk for coronary death (such as patients immediately after acute coronary syndrome). Higher dose statins are associated with statistically significantly increased risks of myopathy and elevated transaminases compared to lower dose statins; while relative risks for these outcomes are 1.2 and 4.0, the absolute increases are small (0.5% and 1%). Secondary analyses of these trials using individual patient data and multivariate adjustment will be needed to appropriately examine the incremental benefits of different LDL targets, and trials are needed to determine whether combinations of low dose statins plus other lipid lowering agents may achieve better clinical outcomes than higher dose statin therapy alone.
A complex intronic enhancer regulates expression of the CFTR gene by direct interaction with the promoter

Genes can maintain spatiotemporal expression patterns by long‐range interactions between cis‐acting elements. The cystic fibrosis transmembrane conductance regulator gene (CFTR) is expressed primarily in epithelial cells. An element located within a DNase I‐hyper‐sensitive site (DHS) 10 kb into the first intron was previously shown to augment CFTR promoter activity in a tissue‐specific manner. Here, we reveal the mechanism by which this element influences CFTR transcription. We employed a high‐resolution method of mapping DHS using tiled microarrays to accurately locate the intron 1 DHS. Transfection of promoter‐reporter constructs demonstrated that the element displays classical tissue‐specific enhancer properties and can independently recruit factors necessary for transcription initiation. In vitro DNase I footprinting analysis identified a protected region that corresponds to a conserved, predicted binding site for hepatocyte nuclear factor 1 (HNF1). We demonstrate by electromobility shift assays (EMSA) and chromatin immunoprecipitation (ChIP) that HNF1 binds to this element both in vitro and in vivo. Moreover, using chromosome conformation capture (3C) analysis, we show that this element interacts with the CFTR promoter in CFTR‐expressing cells. These data provide the first insight into the three‐ dimensional (3D) structure of the CFTR locus and confirm the contribution of intronic cis‐acting elements to the regulation of CFTR gene expression.
Resource Scheduling Optimization Algorithm of Energy Consumption for Cloud Computing Based on Task Tolerance

In order to solve that the energy was seriously wasted in cloud computing, an algorithm of energy consumption optimization for cloud computing based on the task tolerance (ECCT) was proposed. The concept of the task tolerance was put forward in the algorithm. The resource utilization of cloud computing node was maximized through increasing the task tolerance. At the same time, the parallelism degree of tasks were increased so that the task waiting time was reduced, which led to a reduction of energy consumption in cloud computing. Parameters were estimated and experiments on actual cloud computing sets were illustrated. The results showed that the total energy consumption and executive time were reduced more in the proposed algorithm than sequential executive algorithm (SEA). In addition, the advantage would be increasingly apparent with the increasing in assignments.
Best Practices for Running VMware vSphere® on Network-Attached Storage (NAS)

Introduction The significant presence of network-attached storage (NAS) in the datacenter today has enabled many people to deploy virtualization environments with NAS-based shared storage resources. For clarity, both Network File Systems (NFS) and NAS refer to the same type of storage protocol and are used interchangeably throughout this paper. The capabilities of VMware vSphere® on NFS are very similar to those of vSphere on block-based storage. VMware offers support for all vSphere features and functions on NFS, as it does for vSphere on block storage. Running vSphere on NFS is a viable option for many virtualization deployments, because it offers strong performance and stability when configured correctly. This paper provides an overview of the considerations and best practices for deployment of vSphere on NFS-based storage.
3D IMAGE BASED GEOMETRIC DOCUMENTATION OF A MEDIEVAL FORTRESS

Abstract. The detailed and thorough documentation of monuments is a rather complex process that requires the application of the best available state of the art techniques in order to preserve, restore, promote and make cultural heritage accessible to the public. This paper presents the 3D Geometric Documentation of a part of the medieval fortress of Chios, focussing in particular on the practical challenges which the object presented. The case study is a part of the fortified construction, consisting of a bastion, a watch tower on top of this bastion and a significant part of its walls with a surface of about 1053 m2 in total. The goal of the survey was to produce an accurate 3D detailed textured model and a series of coloured orthophotos and 2D vector drawings. The documentation methods employed included close-range automated photogrammetry and image-based modelling, terrestrial laser scanning and topographic surveys, an ideal combination of methods.
Improved cost-based algorithm for task scheduling in cloud computing

Cloud computing has been build upon the development of distributed computing, grid computing and virtualization. Since cost of each task in cloud resources is different with one another, scheduling of user tasks in cloud is not the same as in traditional scheduling methods. The objective of this paper is to schedule task groups in cloud computing platform, where resources have different resource costs and computation performance. Due to job grouping, communication of coarse-grained jobs and resources optimizes computation/communication ratio. For this purpose, an algorithm based on both costs with user task grouping is proposed. The proposed scheduling approach in cloud employs an improved cost-based scheduling algorithm for making efficient mapping of tasks to available resources in cloud. This scheduling algorithm measures both resource cost and computation performance, it also improves the computation/communication ratio by grouping the user tasks according to a particular cloud resource's processing capability and sends the grouped jobs to the resource.
Enabling high-performance LPDDRx-compatible MRAM

DRAM consumes a significant amount of energy in mobile computing devices today. Emerging non-volatile memory such as magnetoresistive memory (MRAM) offers a DRAM alternative and can potentially lead to a more energy-efficient memory system. The MRAM technology is already mature, but considering the memory industry is highly standardized, we are still unable to see any MRAM used in mainstream products. To tackle this problem, we design an LPDDRx-compatible MRAM interface by considering both MRAM pros and cons. Our design solves the pin-compatibility and the performance issues caused by MRAM small page size, and it optimizes the interface protocol by leveraging the MRAM unique feature of non-destructive reads. Combining our techniques, we boost the MRAM performance by 14% and provide a DRAM-swappable MRAM solution with 20% less energy.
Characterizing Intransitive Non-Interference in Security Policies with Observability

This paper introduces a new algorithmic approach to the problem of checking the intransitive non-interference (INI) using discrete event systems (DES) tools and concepts. This information flow property is widely used in formal verification of computer systems and security protocols. First a new property called iP -observability (observability based on a purge function) is introduced to capture INI. An equivalence between iP -observability and P -observability (observability as used in DES) is then established. This paper also presents an algorithm to transform the automaton modeling the system/protocol into an automaton where P -observability can be checked, which is equivalent to verifying INI for the original system.
Emoções acadêmicas, autorregulação e seu impacto sobre motivação e aprendizagem

O texto se constitui em revisão da literatura mais recente sobre emoções acadêmicas e sua autorregulação. Com base em dados de pesquisa, são descritas emoções positivas e negativas, suas origens e seus efeitos sobre a motivação e o desempenho, à luz das teorias de atribuição de causalidade, de Weiner e de controle-valorização, de Pekrun. Foram selecionadas as emoções negativas de vergonha, tédio e ansiedade, mais frequentemente focalizadas nos estudos, sobre as quais foram descritas diversas estratégias de autorregulação que os alunos podem usar nos contextos de aprendizagem. Foi discutida a relevância da teoria social cognitiva para explicar os processos de autorregulação, bem como para ajudar alunos a se tornarem capazes de regular emoções negativas. Por último, foram dadas sugestões de pesquisa futuras em nosso meio.
Handling heteroskedasticity in labour demand functions of athletes

Abstract Based on previous research it can be stated that modelling sport economics related demand curves (e.g. demand for sport events and athletes) is different from other types of modelling. The difference lies in the fact that some parts of the demand curves are nearly horizontal in case of sport goods and nearly vertical in case of athletes, because the price of sport events is inflexible and at the same time, salaries of top athletes are extremely flexible. This study investigates parameter estimation methods appropriate for the relevant demand functions of sport economics. In this cases the generally used ordinary least squares estimator is less robust, so the weighted least squares estimators are able to handle heteroskedasticity. If the distribution of the variables is known, the Newey-West heteroscedasticity corrected estimates give even stronger results. The empirical study analyses footballer transfer fees in top European leagues and identifies a threshold at which the traditional supply-demand functions are not appropriate. According to the results, word class athletes, in a way, can be considered prestige goods for which demand may be irrational.
Automatic Construction of a Heuristic Search Function for General Game Playing

General Game Playing (GGP) is the art of designing programs that are capable of playing previously unknown games of a wide variety by being told nothing but the rules of the game. This is in contrast to traditional computer game players like Deep Blue, which are designed for a particular game and can’t adapt automatically to modifications of the rules, let alone play completely different games. General Game Playing is intended to foster the development of integrated cognitive information processing technology. In this article we present an approach to General Game Playing using a novel way of automatically constructing a search heuristics from a formal game description. Our system is being tested with a wide range of different games. Most notably, it is the winner of the AAAI GGP Competition 2006.
Implementation and evaluation of spatio-spectral reconstruction for spatial coding compressive spectral imaging

Compressive spectral imaging combines traditional spectral imaging technique with compressive sensing and its preliminary application ability has been early explored by the usage on the occasions such as machine-vision and biomedical imaging. In this paper, spatio-spectral reconstruction based on sparse recovery method is presented and its performance is estimated. Simulating imaging experiment is carried out by using AVIRIS visible band data and specific module based on two-step iterative shrinkage/thresholding algorithm is built so as to execute reconstruction for the data cube. Statistical index is adopted so as to judge data fidelity quantitatively so that the effect of the regularizer index optimization and frame shooting number increasing on the improvement of reconstructed data fidelity can be distinctly revealed. The spatio-spectral featuring of different ground species are also evaluated by visual judgment on restored images and spectral curves.
Linearized Reference Tissue Parametric Imaging Methods: Application to [11C]DASB Positron Emission Tomography Studies of the Serotonin Transporter in Human Brain

The authors developed and applied two new linearized reference tissue models for parametric images of binding potential (BP) and relative delivery (R1) for [11C]DASB positron emission tomography imaging of serotonin transporters in human brain. The original multilinear reference tissue model (MRTMO) was modified (MRTM) and used to estimate a clearance rate (k′2) from the cerebellum (reference). Then, the number of parameters was reduced from three (MRTM) to two (MRTM2) by fixing k′2. The resulting BP and R1 estimates were compared with the corresponding nonlinear reference tissue models, SRTM and SRTM2, and one-tissue kinetic analysis (1TKA), for simulated and actual [11C]DASB data. MRTM gave k′2 estimates with little bias (<1%) and small variability (<6%). MRTM2 was effectively identical to SRTM2 and 1TKA, reducing BP bias markedly over MRTMO from 12–70% to 1–4% at the expense of somewhat increased variability. MRTM2 substantially reduced BP variability by a factor of two or three over MRTM or SRTM. MRTM2, SRTM2, and 1TKA had R1 bias <0.3% and variability at least a factor of two lower than MRTM or SRTM. MRTM2 allowed rapid generation of parametric images with the noise reductions consistent with the simulations. Rapid parametric imaging by MRTM2 should be a useful method for human [11C]DASB positron emission tomography studies.
An exercise in "anhomomorphic logic"

A classical logic exhibits a threefold inner structure comprising an algebra of propositions , a space of "truth values" V, and a distinguished family of mappings from propositions to truth values. Classically is a Boolean algebra, V = 2, and the admissible maps : 2 are homomorphisms. If one admits a larger set of maps, one obtains an anhomomorphic logic that seems better suited to quantal reality (and the needs of quantum gravity). I explain these ideas and illustrate them with three simple examples.
Debate, Division, and Diversity: Political Discourse Networks in USENET Newsgroups

type newsgroups Posts Replies XPosts Posters Repliers coded codemsg %codedideology 1alt.politics. bush 56216 48923 51222 3873 3384 40 9448 19.3%2alt.politics. democrats . d 20314 18256 19951 1590 1469 40 4874 26.7%3alt.fan. noam- chomsky 2777 2523 2633 463 425 29 1107 43.9%issue 4talk.politics. mideast 10678 9222 10370 1101 992 25 2521 27.3%5talk.abortion 9825 9603 5758 340 301 26 5186 54.0%6alt.politics. immigration 3504 2984 1833 443 394 21 1209 40.5%small 7soc.politics. marxism 223 189 0 45 30 27 156 82.5%8 hsv.politics 218 174 1 32 25 21 150 86.2%
SVM Enhancement with Application to SAR Imagery Classification

This paper investigates enhancing the performance of support vector machines (SVMs) in the application of synthetic aperture radar (SAR) imagery classification. The approach is to replace the conventional Euclidean distance in the SVM kernel with a new similarity measure that is less sensitive to perturbations. Same-target SAR images show perturbations, in part due to the presence of speckle and in part due to small variations in radar depression angle and target orientation. It is expected that SVMs with the proposed new kernel will outperform those with the conventional Euclidean kernel. Experimental results are presented to validate this expectation for both batch and iterative implementations of SVMs. The paper also argues that the proposed approach is well-founded theoretically by demonstrating that the new kernel is still a Mercer kernel
Operator Algebras and Conformal Field Theory

We define and study two-dimensional, chiral conformal field theory by the methods of algebraic field theory. We start by characterizing the vacuum sectors of such theories and show that, under very general hypotheses, their algebras of local observables are isomorphic to the unique hyperfinite type III1 factor. The conformal net determined by the algebras of local observables is proven to satisfy Haag duality. The representation of the Moebius group (and presumably of the entire Virasoro algebra) on the vacuum sector of a conformal field theory is uniquely determined by the Tomita-Takesaki modular operators associated with its vacuum state and its conformal net. We then develop the theory of Moebius covariant representations of a conformal net, using methods of Doplicher, Haag and Roberts. We apply our results to the representation theory of loop groups. Our analysis is motivated by the desire to find a "background-independent" formulation of conformal field theories.
Influence of environmental variability on phylogenetic diversity and trait diversity within Calligonum communities

Since phylogenetic data provide the evolutionary history of the species and traits are the result of adaptation to the environmental conditions, joint analysis of these two aspects and ecological data may illuminate that how ecological processes affect the evolution of species and assembly of communities. In this study, we compared the community structure of sibling communities in order to illuminate the influence of environmental variability. We chose different Calligonum communities as research subjects which grow in active sand dunes and stabilized sand fields. Our results show that species which co-occurred in C. rubicundum community have greater phylogenetic evenness compared to species in other communities where co-occurring plants had similar traits. Soil variability might legitimately explain this result. Based on the similarity between the pattern of trait diversity and the pattern of phylogenetic diversity, we inferred that the evolution of traits is conservative and species of all but C. rubicundum communities are under more intense selection pressure.