Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic workload and cooling management in high-efficiency data centers

Energy efficiency research in data centers has traditionally focused on raised-floor air-cooled facilities. As rack power density increases, traditional cooling is being replaced by close-coupled systems that provide enhanced airflow and cooling capacity. This work presents a model for close-coupled data centers with free cooling, and explores the power consumption trade-offs in these facilities as outdoor temperature changes throughout the year. Using this model, we propose a technique that jointly allocates workload and controls cooling in a power-efficient way. Our technique is tested with configuration parameters, power traces, and weather data collected from real-life data centers, and application profiles obtained from enterprise servers. Results show that our joint workload allocation and cooling policy provides 5% reduction in overall data center energy consumption, and up to 24% peak power reduction, leading to a 6% decrease in the electricity costs without affecting performance.
Epidemiology, Phylogeny, and Evolution of Emerging Enteric Picobirnaviruses of Animal Origin and Their Relationship to Human Strains

Picobirnavirus (PBV) which has been included in the list of viruses causing enteric infection in animals is highly versatile because of its broad host range and genetic diversity. PBVs are among the most recent and emerging small, nonenveloped viruses with a bisegmented double-stranded RNA genome, classified under a new family “Picobirnaviridae. ” PBVs have also been detected from respiratory tract of pigs, but needs further close investigation for their inhabitant behavior. Though, accretion of genomic data of PBVs from different mammalian species resolved some of the ambiguity, quite a few questions and hypotheses regarding pathogenesis, persistence location, and evolution of PBVs remain unreciprocated. Evolutionary analysis reveals association of PBVs with partitiviruses especially fungi partitiviruses. Although, PBVs may have an ambiguous clinical implication, they do pose a potential public health concern in humans and control of PBVs mainly relies on nonvaccinal approach. Based upon the published data, from 1988 to date, generated from animal PBVs across the globe, this review provides information and discussion with respect to genetic analysis as well as evolution of PBVs of animal origin in relation to human strains.
Binocular stereo vision based indoor scene perception

Scene perception aims to build a semantic context for various tasks of visual processing, especially for object recognition. Binocular vision system is now widely equipped with mobile intelligent robots,however, monocular images are currently mostly used for scene perception task. One can obtain lower classification performance by using features extracted from monocular image as the complexity of natural scene. In this paper a binocular stereo vision based approach for scene perception is developed. A feature descriptor of indoor scene is proposed, that is a vector extracted from planes fitting parameters in several specified regions. First step, scene is classified as empty space and close space classes using feature extracted from disparity map with nearest neighbor method. In following step, both empty space and close space scene are classified into some subclasses using Gist and proposed feature descriptor. To test our approach we created a dataset of 4 indoor scenes categories. The experiments show that our approach got excellent classification performance.
Improving accuracy of fuzzy classifiers using swarm intelligence

This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle swarm optimization (PSO). Two different fuzzy classifiers are considered and optimized. The first classifier is based on Mamdani fuzzy inference system (M_PSO fuzzy classifier). The second classifier is based on Takagi-Sugeno fuzzy inference system (TS_PSO fuzzy classifier). The parameters of the proposed fuzzy classifiers including premise (antecedent) parameters, consequent parameters and structure of fuzzy rules are optimized using PSO. Experimental results show that higher classification accuracy can be obtained with a lower number of fuzzy rules by using the proposed PSO fuzzy classifiers. The performances of M_PSO and TS_PSO fuzzy classifiers are compared to other fuzzy based classifiers.
Vectorization past dependent branches through speculation

Modern architectures increasingly rely on SIMD vectorization to improve performance for floating point intensive scientific applications. However, existing compiler optimization techniques for automatic vectorization are inhibited by the presence of unknown control flow surrounding partially vectorizable computations. In this paper, we present a new approach, speculative vectorization, which speculates past dependent branches to aggressively vectorize computational paths that are expected to be taken frequently at runtime, while simply restarting the calculation using scalar instructions when the speculation fails. We have integrated our technique in an iterative optimizing compiler and have employed empirical tuning to select the profitable paths for speculation. When applied to optimize 9 floating-point benchmarks, our optimizing compiler has achieved up to 6.8X speedup for single precision and 3.4X for double precision kernels using AVX, while vectorizing some operations considered not vectorizable by prior techniques.
Similarity matching for uncertain time series: analytical and experimental comparison

In the last years there has been a considerable increase in the availability of continuous sensor measurements in a wide range of application domains, such as Location-Based Services (LBS), medical monitoring systems, manufacturing plants and engineering facilities to ensure efficiency, product quality and safety, hydrologic and geologic observing systems, pollution management, and others. Due to the inherent imprecision of sensor observations, many investigations have recently turned into querying, mining and storing uncertain data. Uncertainty can also be due to data aggregation, privacy-preserving transforms, and error-prone mining algorithms. In this study, we survey the techniques that have been proposed specifically for modeling and processing uncertain time series, an important model for temporal data. We provide both an analytical evaluation of the alternatives that have been proposed in the literature, highlighting the advantages and disadvantages of each approach. We additionally conduct an extensive experimental evaluation with 17 real datasets, and discuss some surprising results. Based on our evaluations, we also provide guidelines useful for practitioners in the field.
Analytical solutions of the potential vorticity invertibility principle

We define the f‐plane, y‐independent, potential vorticity (PV) invertibility principle as a coupled pair of first‐order partial differential equations relating the balanced wind and mass fields to the known PV. Analytical solutions of this invertibility principle are derived for cases in which an isolated PV anomaly is confined within a region of the vertical plane. The solutions aid in understanding the dynamics of low‐latitude PV intrusions whose associated cloud patterns are often referred to as cloud surges, or moisture bursts, and whose flow patterns are often referred to as tropical upper tropospheric troughs. The existence of such tongues of high PV air intruding into the upper troposphere is documented using reanalysis data from the “Year” of Tropical Convection data set. The solutions illustrate the phenomenon of isentropic upglide below an upper tropospheric positive anomaly in PV. They also quantify how the partitioning of PV between absolute vorticity and static stability depends on the shape and strength of the PV anomaly. With slight modifications, the solutions apply to the problem of determining the balanced flow induced by a surface temperature anomaly, which is equivalent to a very thin layer of infinite PV at the surface. Through numerical solutions of the fully nonlinear invertibility principle we provide justification for the anelastic‐type approximation used in the analytical theory.
Bexarotene Reduces Blood-Brain Barrier Permeability in Cerebral Ischemia-Reperfusion Injured Rats

Background Matrix metalloproteinase-9 (MMP-9) over-expression disrupts the blood-brain barrier (BBB) in the ischemic brain. The retinoid X receptor agonist bexarotene suppresses MMP-9 expression in endothelial cells and displays neuroprotective effects. Therefore, we hypothesized that bexarotene may have a beneficial effect on I/R-induced BBB dysfunction. Methods A total of 180 rats were randomized into three groups (n = 60 each): (i) a sham-operation group, (ii) a cerebral ischemia-reperfusion (I/R) group, and (iii) an I/R+bexarotene group. Brain water content was measured by the dry wet weight method. BBB permeability was analyzed by Evans Blue staining and the magnetic resonance imaging contrast agent Omniscan. MMP-9 mRNA expression, protein expression, and activity were assessed by reverse transcription polymerase chain reaction, Western blotting, and gelatin zymography, respectively. Apolipoprotein E (apoE), claudin-5, and occludin expression were analyzed by Western blotting. Results After 24 h, 48 h, and 72 h post-I/R, several effects were observed with bexarotene administration: (i) brain water content and BBB permeability were significantly reduced; (ii) MMP-9 mRNA and protein expression as well as activity were significantly decreased; (iii) claudin-5 and occludin expression were significantly increased; and (iv) apoE expression was significantly increased. Conclusions Bexarotene decreases BBB permeability in rats with cerebral I/R injury. This effect may be due in part to bexarotene’s upregulation of apoE expression, which has been previously shown to reduce BBB permeability through suppressing MMP-9-mediated degradation of the tight junction proteins claudin-5 and occludin. This work offers insight to aid future development of therapeutic agents for cerebral I/R injury in human patients.
Laboratory measurements of the optical properties of sea salt aerosol

Abstract. The extinction spectra of laboratory generated sea salt aerosols have been measured from 1 μm to 20 μm using a Bruker 66v/S FTIR spectrometer. Concomitant measurements include temperature, pressure, relative humidity and the aerosol size distribution. The refractive indices of the sea salt aerosol have been determined using a simple harmonic oscillator band model (Thomas et al., 2004) for aerosol with relative humidities at eight different values between 0.4% to 86%. The resulting refractive index spectra show significant discrepancies when compared to existing sea salt refractive indices calculated using volume mixing rules (Shettle and Fenn, 1979). Specifically, an additional band is found in the refractive indices of dry sea salt aerosol and the new data shows increased values of refractive index at almost all wavelengths. This implies that the volume mixing rules, currently used to calculate the refractive indices of wet sea salt aerosols, are inadequate. Furthermore, the existing data for the real and imaginary parts of the refractive indices of dry sea salt aerosol are found not to display the Kramers-Kronig relationship. This implies that the original data used for the volume mixing calculations is also inaccurate.
Derive: a tool that automatically reverse-engineers instruction encodings

Many binary tools, such as disassemblers, dynamic code generation systems, and executable code rewriters, need to understand how machine instructions are encoded. Unfortunately, specifying such encodings is tedious and error-prone. Users must typically specify thousands of details of instruction layout, such as opcode and field locations values, legal operands, and jump offset encodings. We have built a tool called DERIVE that extracts these details from existing software: the system assembler. Users need only provide the assembly syntax for the instructions for which they want encodings. DERIVE automatically reverse-engineers instruction encoding knowledge from the assembler by feeding it permutations of instructions and doing equation solving on the output. DERIVE is robust and general. It derives instruction encodings for SPARC, MIPS, Alpha, PowerPC, ARM, and x86. In the last case, it handles variable-sized instructions, large instructions, instruction encodings determined by operand size, and other CISC features. DERIVE is also remarkably simple: it is a factor of 6 smaller than equivalent, more traditional systems. Finally, its declarative specifications eliminate the mis-specification errors that plague previous approaches, such as illegal registers used as operands or incorrect field offsets and sizes. This paper discusses our current DERIVE prototype, explains how it computes instruction encodings, and also discusses the more general implications of the ability to extract functionality from installed software.
Spectral and Textural Weighting Using Takagi-Sugeno Fuzzy System for through Wall Image Enhancement

A through wall image enhancement scheme based on Takagi-Sugeno fuzzy system and principal component analysis is proposed. The scheme incorporates spectral properties of image and textural properties of eigen components of image to assign weights. The scheme overcomes the empirical setting of inference engine and output membership functions. Simulation demonstrates the efiectiveness of proposed scheme in terms of accuracy.
A halo model of galaxy colours and clustering in the Sloan Digital Sky Survey

Successful halo-model descriptions of the luminosity dependence of clustering distinguish between the central galaxy in a halo and all the others (satellites). To include colours, we provide a prescription for how the colour–magnitude relation of centrals and satellites depends on halo mass. This follows from two assumptions: (i) the bimodality of the colour distribution at a fixed luminosity is independent of halo mass and (ii) the fraction of satellite galaxies which populate the red sequence increases with luminosity. We show that these two assumptions allow one to build a model of how galaxy clustering depends on colour without any additional free parameters than those required to model the luminosity dependence of galaxy clustering. We then show that the resulting model is in good agreement with the distribution and clustering of colours in the Sloan Digital Sky Survey, both by comparing the predicted correlation functions of red and blue galaxies with measurements and by comparing the predicted colour–mark correlation function with the measured one. Mark correlation functions are powerful tools for identifying and quantifying correlations between galaxy properties and their environments: our results indicate that the correlation between halo mass and environment is the primary driver for correlations between galaxy colours and the environment; additional correlations associated with halo ‘assembly bias’ are relatively small. Our approach shows explicitly how to construct mock catalogues which include both luminosities and colours – thus providing realistic training sets for, e.g., galaxy cluster-finding algorithms. Our prescription is the first step towards incorporating the entire spectral energy distribution into the halo model approach.
Soil warming, carbon–nitrogen interactions, and forest carbon budgets

Soil warming has the potential to alter both soil and plant processes that affect carbon storage in forest ecosystems. We have quantified these effects in a large, long-term (7-y) soil-warming study in a deciduous forest in New England. Soil warming has resulted in carbon losses from the soil and stimulated carbon gains in the woody tissue of trees. The warming-enhanced decay of soil organic matter also released enough additional inorganic nitrogen into the soil solution to support the observed increases in plant carbon storage. Although soil warming has resulted in a cumulative net loss of carbon from a New England forest relative to a control area over the 7-y study, the annual net losses generally decreased over time as plant carbon storage increased. In the seventh year, warming-induced soil carbon losses were almost totally compensated for by plant carbon gains in response to warming. We attribute the plant gains primarily to warming-induced increases in nitrogen availability. This study underscores the importance of incorporating carbon–nitrogen interactions in atmosphere–ocean–land earth system models to accurately simulate land feedbacks to the climate system.
Angel: A proposed multiprocessor operating system kernel

We describe an operating system design for multiprocessor systems called Angel, based on a single, coherent, uniform virtual address space. This uniies naming and interprocess communication in both shared and distributed memory multiprocessors by using distributed shared memory techniques when shared memory is not already provided by the hardware. The design is motivated by analysis of our earlier operating system implementation, based on message passing, and we show how the uniform address space attempts to solve problems with that approach. In particular, we consider the use of client-server cross-mapping to optimise interprocess communications, as used in Bershad et al.'s lightweight RPC. This document describes initial motivations for Angel and subsequent detailed design| we will review and may modify many of the details described as the design progresses.
Realization of Meander Permutations by Boundary Value Problems

Abstract We consider Neumann boundary value problems of the form uxx+f(x, u, ux)=0 on the unit interval 0⩽x⩽1 for a certain class of dissipative nonlinearities f. Associated to these problems we have (i) meanders in the phase space (u, ux)∈ R 2, which are connected oriented simple curves on the plane intersecting a fixed oriented line (the u-axis) in n points corresponding to the solutions; and (ii) meander permutations πf∈S(n) obtained by ordering the intersection points first along the u-axis and then along the meander. The meander permutation πf is the permutation defined by the braid of solutions in the space (x, u, ux). It was recently shown by Fiedler and Rocha that πf determines the global attractor of the dynamical system generated by the semilinear parabolic differential equation ut=uxx+f(x, u, ux), up to C0 orbit equivalence. Therefore, these permutations are of considerable importance in the classification problem of the (Morse–Smale) attractors for these dynamical systems. In this paper we present a purely combinatorial characterization of the set of meander permutations that are realizable by the above boundary value problems.
An Improved Restoration Method for Non-Uniformly Warped Images Using Optical Flow Technique

A high precision and fast image restoration method is proposed to restore a geometrically corrected image from the atmospheric turbulence degraded video sequence of a static scenery. In this approach, we employ an optical flow technique to register all the frames of the distorted video to a reference frame and determine the flow fields. We use the First Register Then Average And Subtract-variant (FRTAASv) method to correct the geometric distortions using the computed flow fields. We present a performance comparison between our proposed restoration method and earlier Minimum Sum of Squared Differences (MSSD) image registration based FRTAASv method in terms of computational time and accuracy. Simulation experiments show that our proposed method provides higher accuracy with quicker processing time.
Employment of voicing information of speech spectra for noise-robust speaker identification

This paper presents a novel method for voicing information estimation of individual frequency-regions of speech spectra and its employment in a text-independent speaker identification system. The voicing information is incorporated to the system in a form of a mask in a marginalization-based missing-feature model. Experiments were performed on speech data from the TIMIT database corrupted by stationary and real-world noises. The obtained results show that using the proposed voicing estimation method provides performance close to using oracle voicing information. The combination of the voicing information mask with a noise-estimate mask showed further improvement in the identification accuracy and achieved performance close to the oracle mask obtained using full a-priori knowledge of noise.
A Gentzen System for Reasoning with Contrary-To-Duty Obligations: A Preliminary Study

In this paper we present a Gentzen system for reasoning with contrary-to-duty obligations. The intuition behind the system is that a contrary-to-duty is a special kind of normative exception. The logical machinery to formalize this idea is taken from substructural logics and it is based on the definition of a new non-classical connective capturing the notion of reparational obligation. Then the system is tested against well-known contrary-to-duty paradoxes
Designing a spoken language interface for a tutorial dialogue system

We describe our work in building a spoken language interface for a tutorial dialogue system. Our goal is to allow natural, unrestricted student interaction with the computer tutor, which has been shown to improve the student’s learning gain, but presents challenges for speech recognition and spoken language understanding. We discuss the choice of system components and present the results of development experiments in both acoustic and language modelling for speech recognition in this domain.
Question Answering with DBpedia Based on the Dependency Parser and Entity-centric Index

The emerging Linked Open Data provides an opportunity to answer the natural language question based on knowledge bases (KB). This study proposes an approach to question answering (QA) on the DBpedia dataset. After parsing the question by a dependency parser, we locate the entity mention and property mention with predefined templates. We propose an entity-centric indexing model to help search referent entities in KB. After obtaining the referent entities, we expand the property mention with WordNet and ConceptNet to find the referent properties of the returned entities. The values of the referent property are then considered the answer to the question. Evaluations are performed on DBpedia version 2015. Results show that our approach reaches 46% precision when the top-10 entities are returned in the final QA stage. The evaluation tests show that our approach is promising in dealing with QA in Linked Data.
PATRIC: a parallel algorithm for counting triangles in massive networks

Massive networks arising in numerous application areas poses significant challenges for network analysts as these networks grow to billions of nodes and are prohibitively large to fit in the main memory. Finding the number of triangles in a network is an important problem in the analysis of complex networks. Several interesting graph mining applications depend on the number of triangles in the graph. In this paper, we present an efficient MPI-based distributed memory parallel algorithm, called PATRIC, for counting triangles in massive networks. PATRIC scales well to networks with billions of nodes and can compute the exact number of triangles in a network with one billion nodes and 10 billion edges in 16 minutes. Balancing computational loads among processors for a graph problem like counting triangles is a challenging issue. We present and analyze several schemes for balancing load among processors for the triangle counting problem. These schemes achieve very good load balancing. We also show how our parallel algorithm can adapt an existing edge sparsification technique to approximate the number of triangles with very high accuracy. This modification allows us to count triangles in even larger networks.