Miracle-dz/UniFAR-FTUs huggingface dataset:
Preventing the explosion of exascale profile data with smart thread-level aggregation

State of the art performance analysis tools, such as Score-P, record performance profiles on a per-thread basis. However, for exascale systems the number of threads is expected to be in the order of a billion threads, and this would result in extremely large performance profiles. In most cases the user almost never inspects the individual per-thread data. In this paper, we propose to aggregate per-thread performance data in each process to reduce its amount to a reasonable size. Our goal is to aggregate the threads such that the thread-level performance issues are still visible and analyzable. Therefore, we implemented four aggregation strategies in Score-P: (i) SUM -- aggregates all threads of a process into a process profile; (ii) SET -- calculates statistical key data as well as the sum; (iii) KEY -- identifies three threads (i.e., key threads) of particular interest for performance analysis and aggregates the rest of the threads; (iv) CALLTREE -- clusters threads that have the same call-tree structure. For each one of these strategies we evaluate the compression ratio and how they maintain thread-level performance behavior information. The aggregation does not incur any additional performance overhead at application run-time.
Correlations among subjective performance qualities and objective acoustical parameters of the didjeridu

Traditional didjeridus have a broad range of unknown bore geometries, and consequently have advantages for examining relationships between subjective and physical parameters. This study involved 7 experienced players assessing each of 38 traditionally made didjeridus in terms of 8 subjective parameters. Their assessments were then correlated with detailed measurements of acoustic input impedance spectra and geometry. There was a small, but useful, consistency in the rankings of the 7 players, although it was surprising that backpressure was the least consistent term, because this term is widely used by both didjeridu and brass players. A high degree of positive correlation existed between most of the parameters (clarity, resonance, loudness, vocals, overtones and overall quality). The other two parameters studied (backpressure and speed) were correlated with each other, although not significantly correlated with the other parameters. The parameters clarity, resonance and backpressure made the most important contributions to the overall quality of an instrument. In general there was a strong negative correlation with the characteristic impedance of the instrument for overtones, vocals, resonance, loudness and overall quality. The parameter speed was found to be positively correlated with the frequency of the first (or lowest) frequency resonance. Assessments of PVC pipes were consistent with these results. The overwhelming preference of the assessors was for instruments with a low magnitude of impedance across the spectrum, particularly in the 1 to 2 kHz region; a feature that allows time-varying resonances of a player's vocal tract to have a dominant influence over the spectral envelope of the sound.
ANALYZING BIOLOGICAL PROCESS ON GENE EXPRESSION DATASETS USING HEURISTIC SEARCH 1

Mining micro-array gene expression data is an imperative subject matter in bioinformatics with extensive applications. Bio informative knowledge discovery from DNA microarrays become more essential in various disease diagnosis, drug development, genetic functional interpretation, gene metamorphisms etc., Recently biological information mining using clustering techniques were used for the analytical evaluation of gene expression. The expression of Nnumerous genes can be scrutinized concurrently using DNA microarray technology. To develop the massive quantity of information enclosed in gene expression data, revision of existing work presented a biclustering algorithm, which presents local structures from gene expression data set. However, traditional single cluster model unable to mine precise information from large, and heterogeneous collection gene expression data. So the development of a new computational method is presented in this work to improve the analysis of gene expression data sets. In this work we first introduce the heuristic search for the standard biological process on physiological data of the gene expression. The physiological data consists of both physical and logical patterns of the gene expression datasets and the biological process of physical and logical pattern of gene expression datasets are analyzed through Heuristic search. Experimental evaluations are conducted for our heuristic search based analysis of biological process on physiological data with standard benchmark gene expression data sets from research repositories such as UCI in terms of size of gene expression datasets.
Identification of Commensal Escherichia coli Genes Involved in Biofilm Resistance to Pathogen Colonization

Protection provided by host bacterial microbiota against microbial pathogens is a well known but ill-understood property referred to as the barrier effect, or colonization resistance. Despite recent genome-wide analyses of host microbiota and increasing therapeutic interest, molecular analysis of colonization resistance is hampered by the complexity of direct in vivo experiments. Here we developed an in vitro-to-in vivo approach to identification of genes involved in resistance of commensal bacteria to exogenous pathogens. We analyzed genetic responses induced in commensal Escherichia coli upon entry of a diarrheagenic enteroaggregative E. coli or an unrelated Klebsiella pneumoniae pathogen into a biofilm community. We showed that pathogens trigger specific responses in commensal bacteria and we identified genes involved in limiting colonization of incoming pathogens within commensal biofilm. We tested the in vivo relevance of our findings by comparing the extent of intestinal colonization by enteroaggregative E. coli and K. pneumoniae pathogens in mice pre-colonized with E. coli wild type commensal strain, or mutants corresponding to identified colonization resistance genes. We demonstrated that the absence of yiaF and bssS (yceP) differentially alters pathogen colonization in the mouse gut. This study therefore identifies previously uncharacterized colonization resistance genes and provides new approaches to unravelling molecular aspects of commensal/pathogen competitive interactions.
A Multi-class Image Classification System Using Salient Features and Support Vector Machines

This paper addresses the problem of automatic image annotation for semantic retrieval of images. We propose an image classification system that is capable of recognizing several image categories. The system is based on the support vector machine and a set of image features that includes MPEG-7 visual descriptors and a custom feature. The system is evaluated on a large dataset consisting of 14400 images in four categories - landscape, cityscape, vehicle and portrait. We find that the proposed edge direction histogram and the MPEG-7 edge histogram perform better than other features in this application. Experiment results indicate that the pair- wise SVM approach performs better than the one-versus-all SVM approach. The pair-wise method with confidence score voting has better classification rates compared to the pair-wise method with majority voting.
Finding the evidence for protein-protein interactions from PubMed abstracts

MOTIVATION Protein-protein interactions play critical roles in biological processes, and many biologists try to find or to predict crucial information concerning these interactions. Before verifying interactions in biological laboratory work, validating them from previous research is necessary. Although many efforts have been made to create databases that store verified information in a structured form, much interaction information still remains as unstructured text. As the amount of new publications has increased rapidly, a large amount of research has sought to extract interactions from the text automatically. However, there remain various difficulties associated with the process of applying automatically generated results into manually annotated databases. For interactions that are not found in manually stored databases, researchers attempt to search for abstracts or full papers. RESULTS As a result of a search for two proteins, PubMed frequently returns hundreds of abstracts. In this paper, a method is introduced that validates protein-protein interactions from PubMed abstracts. A query is generated from two given proteins automatically and abstracts are then collected from PubMed. Following this, target proteins and their synonyms are recognized and their interaction information is extracted from the collection. It was found that 67.37% of the interactions from DIP-PPI corpus were found from the PubMed abstracts and 87.37% of interactions were found from the given full texts. AVAILABILITY Contact authors.
Efficient Burst Error Correction by Hermitian Codes

Hermitian codes belong to a powerful class of algebraic geometry codes, which allow to correct many independent errors. We show that Hermitian codes can correct many bursts of errors as well. Decoding of a Hermitian (N,K) code over q2 can be reduced to decoding of interleaved extended Reed-Solomon codes. Using this fact, we propose an efficient unique decoding algorithm correcting up to (N −K)/(q + 1) phased bursts of length q. Decoding failure probability is upper bounded by 1/q and exponentially decreases with the number of bursts. It is also shown that low rate Hermitian codes can correct even more bursts of errors using “power” and “mixed” decoding. Time complexity of the algorithms is O(N) field operations.
Why Should an Economy Be Competitive?

Is a competitive free market the most efficient way to maximize welfare and to equally allocate rare resources among economic agents? Economists usually tend to think this is the case. This paper presents a preliminary attempt through an object-oriented multi-agent model to address this question. Agents which are alternatively producers, sellers, buyers and consumers participate in a market to increase their welfare. Two market models are compared: the competitive market, which is a double auction market in which agents attempt to outbid each other in order to buy and sell products, and the random market, in which products are allocated in a random manner. The comparison focuses on wealth creation (a common study) and above all on inequalities in resources allocation (much less frequently addressed). We compute and compare in both cases the money and utility generated within the markets as well as a Gini index that characterizes the degree of inequality in the allocation of these values among agents. In contrast with earlier works, we also compare welfare creation and distribution with more or less intelligent agents who use more or less information provided by the market. The results of hundreds of simulations are analyzed to find that, as is well known, the competitive market creates more value overall but, and generally less accepted and discussed by economists, at the expense of a much greater inequality. We further find that whereas the use of market information by the producers leads to less inequality in both types of markets, the inequality induced by the competitive market depends on the behavior of the agents, suggesting that it is both the institutions and the agents that foster inequality in competitive market structures.
Development of the MIMO system for future mobile communications

From 2001, a high-tech program named "FuTure" has been launched for developing the future mobile communications systems in China. The State Key Lab. of Millimeter Waves (SKLMMW) in Southeast University was supported by the "FuTure" program to develop a MIMO system which has been considered as one of the most potential technology for 4G mobile communications (GJ Foschini, 1996) (ZD Wang and GB Giannakis, 2000) (A Paulraj, 1997, 1999) (M Shafi, et al, 2003) In this paper we give a brief introduction to the research progress on the MIMO technology in SKLMMW.
Improvisation Planning and Jam Session Design using concepts of Sequence Variation and Flow Experience

We describe a model for improvisation design based on Factor Oracle automation, which is extended to perform learning and analysis of incoming sequences in terms of sequence variation parameters, namely replication, recombination and innovation. These parameters describe the improvisation plan and allow the design of new improvisations or analysis and modification of plans of existing improvisations. We further introduce an idea of flow experience that represents the various improvisation situations in a mental space that allows defining interactions between improvisers in terms of mental states and behavioural scripts.
Implicit and Explicit Timing in Oculomotor Control

The passage of time can be estimated either explicitly, e.g. before leaving home in the morning, or implicitly, e.g. when catching a flying ball. In the present study, the latency of saccadic eye movements was used to evaluate differences between implicit and explicit timing. Humans were required to make a saccade between a central and a peripheral position on a computer screen. The delay between the extinction of a central target and the appearance of an eccentric target was the independent variable that could take one out of four different values (400, 900, 1400 or 1900 ms). In target trials, the delay period lasted for one of the four durations randomly. At the end of the delay, a saccade was initiated by the appearance of an eccentric target. Cue&target trials were similar to target trials but the duration of the delay was visually cued. In probe trials, the duration of the upcoming delay was cued, but there was no eccentric target and subjects had to internally generate a saccade at the estimated end of the delay. In target and cue&target trials, the mean and variance of latency distributions decreased as delay duration increased. In cue&target trials latencies were shorter. In probe trials, the variance increased with increasing delay duration and scalar variability was observed. The major differences in saccadic latency distributions were observed between visually-guided (target and cue&target trials) and internally-generated saccades (probe trials). In target and cue&target trials the timing of the response was implicit. In probe trials, the timing of the response was internally-generated and explicitly based on the duration of the visual cue. Scalar timing was observed only during probe trials. This study supports the hypothesis that there is no ubiquitous timing system in the brain but independent timing processes active depending on task demands.
Collaborative Spectrum Sensing Algorithm Based on Exponential Entropy in Cognitive Radio Networks

Traditional detectors for spectrum sensing in cognitive radio networks always become disabled when noise uncertainty is severe. Shannon entropy-based detection methods have aroused widespread attention in recent years due to the characteristics of effective anti-noise uncertainty. However, in existing entropy-based sensing schemes, the uniform quantization method cannot guarantee the maximum entropy distribution when primary users do not exist, and cannot effectively distinguish between two hypotheses, which severely limits the promotion of detection performance. Moreover, the Shannon entropy-based sensing schemes are prone to misconvergence occurring when estimating entropy values, thus causing failure detection, which leads to system detection inefficiency and resource waste. These are the two major serious defects in Shannon entropy-based detectors, which restrict the performance improvement. In this paper, a novel non-uniform quantized exponential entropy-based (NQEE) detector is proposed for local sensing to deal with the problems of maximum entropy distribution and detection failure. To further improve the reliability of the detection, a collaborative spectrum sensing algorithm based on an NQEE detector with multiple fusion rules is presented. Simulation results verify that the detection performance of the improved local entropy-based detector is superior to the existing Shannon entropy-based detectors and is proved to be robust to noise power uncertainty. In addition, the novel collaborative detection algorithm outperforms the traditional collaborative spectrum detection method to a great degree.
N6-(2-Hydroxyethyl)-Adenosine Exhibits Insecticidal Activity against Plutella xylostella via Adenosine Receptors

The diamondback moth, Plutella xylostella, is one of the most important pests of cruciferous crops. We have earlier shown that N6-(2-hydroxyethyl)-adenosine (HEA) exhibits insecticidal activity against P. xylostella. In the present study we investigated the possible mechanism of insecticidal action of HEA on P. xylostella. HEA is a derivative of adenosine, therefore, we speculated whether it acts via P. xylostella adenosine receptor (PxAdoR). We used RNAi approach to silence PxAdoR gene and used antagonist of denosine receptor (AdoR) to study the insecticidal effect of HEA. We cloned the whole sequence of PxAdoR gene. A BLAST search using NCBI protein database showed a 61% identity with the Drosophila adenosine receptor (DmAdoR) and a 32–35% identity with human AdoR. Though the amino acids sequence of PxAdoR was different compared to other adenosine receptors, most of the amino acids that are known to be important for adenosine receptor ligand binding and signaling were present. However, only 30% binding sites key residues was similar between PxAdoR and A1R. HEA, at a dose of 1 mg/mL, was found to be lethal to the second-instar larvae of P. xylostella, and a significant reduction of mortality and growth inhibition ratio were obtained when HEA was administered to the larvae along with PxAdoR-dsRNA or antagonist of AdoR (SCH58261) for 36, 48, or 60 h. Especially at 48 h, the rate of growth inhibition of the PxAdoR knockdown group was 3.5-fold less than that of the HEA group, and the corrected mortality of SCH58261 group was reduced almost 2-fold compared with the HEA group. Our findings show that HEA may exert its insecticidal activity against P. xylostella larvae via acting on PxAdoR.
Voltage island design in multi-core SIMD processors

Today, power management is a key design objective in chip fabrication. In this paper, we present a novel approach to reduce power consumption in SIMD based multi-core architectures. Voltage scaling technique is used, by implementing voltage islands, to optimize power and performance tradeoff for the cores. The number of islands and their respective voltage are selected based on the power-delay characteristics of each instruction: slow instructions run at the nominal voltage while fast instructions run at a lower voltage to save power. An image compression algorithm is mapped into the hardware to demonstrate the power reduction. The results show energy savings of 2.0X for the specified application.
Input-Specific Intrasynaptic Arrangements of Ionotropic Glutamate Receptors and Their Impact on Postsynaptic Responses

To examine the intrasynaptic arrangement of postsynaptic receptors in relation to the functional role of the synapse, we quantitatively analyzed the two-dimensional distribution of AMPA and NMDA receptors (AMPARs and NMDARs, respectively) using SDS-digested freeze-fracture replica labeling (SDS-FRL) and assessed the implication of distribution differences on the postsynaptic responses by simulation. In the dorsal lateral geniculate nucleus, corticogeniculate (CG) synapses were twice as large as retinogeniculate (RG) synapses but expressed similar numbers of AMPARs. Two-dimensional views of replicas revealed that AMPARs form microclusters in both synapses to a similar extent, resulting in larger AMPAR-lacking areas in the CG synapses. Despite the broad difference in the AMPAR distribution within a synapse, our simulations based on the actual receptor distributions suggested that the AMPAR quantal response at individual RG synapses is only slightly larger in amplitude, less variable, and faster in kinetics than that at CG synapses having a similar number of the receptors. NMDARs at the CG synapses were expressed twice as many as those in the RG synapses. Electrophysiological recordings confirmed a larger contribution of NMDAR relative to AMPAR-mediated responses in CG synapses. We conclude that synapse size and the density and distribution of receptors have minor influences on quantal responses and that the number of receptors acts as a predominant postsynaptic determinant of the synaptic strength mediated by both the AMPARs and NMDARs.
Design and experimental evaluation of market mechanisms for participatory sensing environments

Participatory Sensing concerns the sharing of sensor information within user communities, forming a body of knowledge that can be beneficial to the community itself, either directly or through specialized applications. We introduce a framework for a marketplace where such applications can sell and buy sensor information. We focus on the buyers' side and we use various ideas from the cost-sharing literature, to propose three classes of mechanisms. We evaluate them experimentally, comparing their performance according to metrics such as social efficiency, cost coverage and budget deficit, as well as metrics related to encouraging participation.
Testing Environments for Assessing Conformance and Interoperability

We present a classification framework of testing environments that supports conformance and interoperability testing of distributed systems. We describe each testing environment and state the applicability and requirements placed on a realization of a testing tool. The broad categories identified include data instance validation, isolated systems testing, and peer-to-peer systems testing. Our targeted systems include those that support data exchange standards. We list and define the types of conformance and interoperability testing that can be conducted and associate the types that can be performed in a given testing environment. We describe and illustrate a conceptual test tool design for each testing environment. The delineation of environments and their testing capacity is intended to facilitate a more structured approach to testing in which the relationship between testing and test requirements is more clearly defined and the capabilities and limitations of testing tools are better understood. In broader terms, this approach should help industry and testing bodies identify and describe the depth and scope of their testing endeavors.
Drawing Feynman Diagrams with L A TEX and METAFONT . Part 2 : Immediate Mode

In addition to the graph mode discussed earlier, which corresponds to display list mode, feynMF offers an immediate mode in which drawing operations are performed immediately. There is another distinction that should be kept in mind: graph mode operates on abstract vertices and how they are connected, while immediate mode works directly with the coordinates of vertices and the arcs (called paths in [3]) connecting them. With minor exceptions, feynMF’s graph mode will produce straight lines only. Therefore one of immediate mode’s most important applications is the drawing of diagrams with unusually curved arcs. These curved arcs can be drawn in the same line styles as the arcs in graph mode. This feature allows us to combine the two modes for maximizing the expressive power and convenience of feynMF. A comprehensive discussion of METAFONT’s facilities for constructing curves is far beyond the scope of this tutorial. Interested readers should consult the first chapters of [3] for the definitive guide.