Miracle-dz/UniFAR-FTUs huggingface dataset:
An investigation of parallel memetic algorithms for VLSI circuit partitioning on multi-core computers

Circuit-partitioning is one of the most important, but time-consuming steps, in the VLSI design flow. In this paper, we investigate six different parallel Memetic Algorithms for solving the circuit-partitioning problem. Each parallel implementation uses a global shared-memory to exchange information, and seeks to reduce runtime by exploiting the multiple cores available in today's commodity hardware. When tested with the widely used ACM/SIGDA benchmark suite [16], our empirical results show that near-linear speedups for all six MAs can be achieved, while still producing high-quality solutions.
Nonlinear stability analysis for a class of TCP/AQM networks

Recent work has shown the benefit of using proportional feedback in TCP/AQM (transmission control protocol/active queue management) networks. By proportional feedback we mean the marking probability is proportional to the instantaneous queue length. Our earlier work (2001) relied on linearization of nonlinear fluid-flow models of TCP. In this work we address these nonlinearities directly and establish some stability results when the marking is proportional. In the case of delay-free marking, we show the system's equilibrium point to be asymptotically stable for all proportional gains. In the more realistic case of delayed feedback, we establish local asymptotic stability and quantify a region of attraction.
Process Structuring in Electronic Brainstorming

One aspect of brainstorming that has received little research attention is how the brainstorming problem should be presented to the group, whether as one all-encompassing question or as a series of separate questions each focusing on one aspect of the problem. This paper reports the results of two experiments in which subjects (MBAs in the first, senior executives in the second) electronically brainstormed on intact problems (where all parts of the problem were presented simultaneously) or on decomposed problems (where three subcategories of the problem were sequentially posed to the groups). In both experiments, groups using the decomposed process generated 60% more ideas. We attribute these differences to the ability of time constraints to increase the rate of idea generation, and the ability of problem decomposition to refocus members' attention more evenly across the entire problem.
Behavior-based Spyware Detection

Spyware is rapidly becoming a major security issue. Spyware programs are surreptitiously installed on a user's workstation to monitor his/her actions and gather private information about a user's behavior. Current antispyware tools operate in a way similar to traditional antivirus tools, where signatures associated with known spyware programs are checked against newly-installed applications. Unfortunately, these techniques are very easy to evade by using simple obfuscation transformations. This paper presents a novel technique for spyware detection that is based on the characterization of spywarelike behavior. The technique is tailored to a popular class of spyware applications that use Internet Explorer's Browser Helper Object (BHO) and toolbar interfaces to monitor a user's browsing behavior. Our technique uses a composition of static and dynamic analysis to determine whether the behavior of BHOs and toolbars in response to simulated browser events should be considered malicious. The evaluation of our technique on a representative set of spyware samples show that it is possible to reliably identify malicious components using an abstract behavioral characterization.
Systematic Dissection of Coding Exons at Single Nucleotide Resolution Supports an Additional Role in Cell-Specific Transcriptional Regulation

In addition to their protein coding function, exons can also serve as transcriptional enhancers. Mutations in these exonic-enhancers (eExons) could alter both protein function and transcription. However, the functional consequence of eExon mutations is not well known. Here, using massively parallel reporter assays, we dissect the enhancer activity of three liver eExons (SORL1 exon 17, TRAF3IP2 exon 2, PPARG exon 6) at single nucleotide resolution in the mouse liver. We find that both synonymous and non-synonymous mutations have similar effects on enhancer activity and many of the deleterious mutation clusters overlap known liver-associated transcription factor binding sites. Carrying a similar massively parallel reporter assay in HeLa cells with these three eExons found differences in their mutation profiles compared to the liver, suggesting that enhancers could have distinct operating profiles in different tissues. Our results demonstrate that eExon mutations could lead to multiple phenotypes by disrupting both the protein sequence and enhancer activity and that enhancers can have distinct mutation profiles in different cell types.
Unsupervised Lexicon Discovery from Acoustic Input

We present a model of unsupervised phonological lexicon discovery—the problem of simultaneously learning phoneme-like and word-like units from acoustic input. Our model builds on earlier models of unsupervised phone-like unit discovery from acoustic data (Lee and Glass, 2012), and unsupervised symbolic lexicon discovery using the Adaptor Grammar framework (Johnson et al., 2006), integrating these earlier approaches using a probabilistic model of phonological variation. We show that the model is competitive with state-of-the-art spoken term discovery systems, and present analyses exploring the model’s behavior and the kinds of linguistic structures it learns.
CD39-L4 Is a Secreted Human Apyrase, Specific for the Hydrolysis of Nucleoside Diphosphates*

The human ecto-apyrase gene family consists of five reported members (CD39, CD39-L1,CD39-L2, CD39-L3, and CD39-L4). The family can be subdivided into two groups by conservation of proposed structural domains. The CD39, CD39-L1, andCD39-L3 genes all encode hydrophobic portions in their carboxy and amino termini, serving as transmembrane domains for CD39 and potentially for the other two members. CD39-L2 andCD39-L4 genes encode hydrophobic portions in their amino termini, suggesting that they might encode secreted apyrases. We demonstrate that the CD39-L4 gene encodes the first reported human secreted ecto-apyrase. COS-7 cells transfected with a CD39-L4 expression construct utilizing the naturally occurring leader peptide express recombinant protein outside of the cells. This expression can be blocked by brefeldin A, a chemical that inhibits a step in mammalian secretory pathways. We also demonstrate expression of CD39-L4 message in macrophages, suggesting that the protein is present in the circulation. Furthermore, we show that CD39-L4 is an E-type apyrase, is dependent on calcium and magnesium cations, and has high degree of specificity for NDPs over NTPs as enzymatic substrates. A potential physiological role in hemostasis and platelet aggregation is presented.
Selective modulation of type 1 insulin-like growth factor receptor signaling and functions by β1 integrins

We show here that β1 integrins selectively modulate insulin-like growth factor type I receptor (IGF-IR) signaling in response to IGF stimulation. The β1A integrin forms a complex with the IGF-IR and insulin receptor substrate-1 (IRS-1); this complex does not promote IGF-I mediated cell adhesion to laminin (LN), although it does support IGF-mediated cell proliferation. In contrast, β1C, an integrin cytoplasmic variant, increases cell adhesion to LN in response to IGF-I and its down-regulation by a ribozyme prevents IGF-mediated adhesion to LN. Moreover, β1C completely prevents IGF-mediated cell proliferation and tumor growth by inhibiting IGF-IR auto-phosphorylation in response to IGF-I stimulation. Evidence is provided that the β1 cytodomain plays an important role in mediating β1 integrin association with either IRS-1 or Grb2-associated binder1 (Gab1)/SH2-containing protein-tyrosine phosphate 2 (Shp2), downstream effectors of IGF-IR: specifically, β1A associates with IRS-1 and β1C with Gab1/Shp2. This study unravels a novel mechanism mediated by the integrin cytoplasmic domain that differentially regulates cell adhesion to LN and cell proliferation in response to IGF.
Convergence and No-Regret in Multiagent Learning

Learning in a multiagent system is a challenging problem due to two key factors. First, if other agents are simultaneously learning then the environment is no longer stationary, thus undermining convergence guarantees. Second, learning is often susceptible to deception, where the other agents may be able to exploit a learner's particular dynamics. In the worst case, this could result in poorer performance than if the agent was not learning at all. These challenges are identifiable in the two most common evaluation criteria for multiagent learning algorithms: convergence and regret. Algorithms focusing on convergence or regret in isolation are numerous. In this paper, we seek to address both criteria in a single algorithm by introducing GIGA-WoLF, a learning algorithm for normal-form games. We prove the algorithm guarantees at most zero average regret, while demonstrating the algorithm converges in many situations of self-play. We prove convergence in a limited setting and give empirical results in a wider variety of situations. These results also suggest a third new learning criterion combining convergence and regret, which we call negative non-convergence regret (NNR).
An ERF Transcription Factor in Medicago truncatula That Is Essential for Nod Factor Signal Transduction[W]

Rhizobial bacteria activate the formation of nodules on the appropriate host legume plant, and this requires the bacterial signaling molecule Nod factor. Perception of Nod factor in the plant leads to the activation of a number of rhizobial-induced genes. Putative transcriptional regulators in the GRAS family are known to function in Nod factor signaling, but these proteins have not been shown to be capable of direct DNA binding. Here, we identify an ERF transcription factor, ERF Required for Nodulation (ERN), which contains a highly conserved AP2 DNA binding domain, that is necessary for nodulation. Mutations in this gene block the initiation and development of rhizobial invasion structures, termed infection threads, and thus block nodule invasion by the bacteria. We show that ERN is necessary for Nod factor–induced gene expression and for spontaneous nodulation activated by the calcium- and calmodulin-dependent protein kinase, DMI3, which is a component of the Nod factor signaling pathway. We propose that ERN is a component of the Nod factor signal transduction pathway and functions downstream of DMI3 to activate nodulation gene expression.
Fault Detection of Rotation Machinery using Periodic Time-Frequency Sparsity

This paper addresses the problem of extracting periodic oscillatory features in vibration signals for detecting faults in rotation machinery. To extract the feature, we propose an approach in the short-time Fourier transform (STFT) domain, where the periodic oscillatory feature manifests itself as a relatively sparse grid.To estimate the sparse grid, we formulate an optimization problem using customized binary weights in the regularizer, where the weights are formulated to promote periodicity. As examples, the proposed approach is applied to simulated data, and used as a tool for diagnosing faults in bearings and gearboxes for real data, and compared to some to some state-of-the-art methods. The results show the proposed approach can effectively detect and extract the periodical oscillatory features.
Neural pathways of stress integration: relevance to alcohol abuse.

Stress is a critical component in the development, maintenance, and reinstatement of addictive behaviors, including alcohol use. This article reviews the current state of the literature on the brain’s stress response, focusing on the hypothalamic–pituitary–adrenal (HPA) axis. Stress responses can occur as a reaction to physiological (or systemic) challenge or threat; signals from multiple parts of the brain send input to the paraventricular nucleus (PVN) within the hypothalamus. However, responses also occur to stressors that predict potential threats (psychogenic stressors). Psychogenic responses are mediated by a series of nerve cell connections in the limbic–PVN pathway, with amygdalar and infralimbic cortex circuits signaling excitation and prelimbic cortex and hippocampal neurons signaling stress inhibition. Limbic–PVN connections are relayed by predominantly GABAergic neurons in regions such as the bed nucleus of the stria terminalis and preoptic area. Chronic stress affects the structure and function of limbic stress circuitry and results in enhanced PVN excitability, although the exact mechanism is unknown. Of importance, acute and chronic alcohol exposure are known to affect both systemic and psychogenic stress pathways and may be linked to stress dysregulation by precipitating chronic stress–like changes in amygdalar and prefrontal components of the limbic stress control network.
Automatic Generation of Co-Embeddings from Relational Data with Adaptive Shaping

In this paper, we study the co-embedding problem of how to map different types of patterns into one common low-dimensional space, given only the associations (relation values) between samples. We conduct a generic analysis to discover the commonalities between existing co-embedding algorithms and indirectly related approaches and investigate possible factors controlling the shapes and distributions of the co-embeddings. The primary contribution of this work is a novel method for computing co--embeddings, termed the automatic co-embedding with adaptive shaping (ACAS) algorithm, based on an efficient transformation of the co-embedding problem. Its advantages include flexible model adaptation to the given data, an economical set of model variables leading to a parametric co-embedding formulation, and a robust model fitting criterion for model optimization based on a quantization procedure. The secondary contribution of this work is the introduction of a set of generic schemes for the qualitative analysis and quantitative assessment of the output of co-embedding algorithms, using existing labeled benchmark datasets. Experiments with synthetic and real-world datasets show that the proposed algorithm is very competitive compared to existing ones.
Statistical Quality Scale 6 (SQS-6)

Context. The statistical analysis is an important part of the process of assessing the quality of randomized controlled trials, unfortunately it tends to be underestimated or even omitted by editors, in this sense, scales that cover this gap becomes necessary.Objective. To build a definition and a scale for assessing the quality of statistical analysis in randomized controlled trials. Methods. A content analysis on 16 biostatistics texts was considered in the building of the definition and of the scale. The indicators of quality were based on the description and presentation of results of articles.Results. We identify 32 quality indicators grouping in six dimensions: randomization and management of lost; sample size computation; use of mean and median; statistical test; use and interpretation of confidence interval and P-values. The scale range from 0 to 6 and score greater than three identify article with appropriate statistical analysis. Conclusions. The scale presented three dimensions linked to quality of description and three linked to quality of used strategy.
Presence of N-glycosylated transthyretin in plasma of V30M carriers in familial amyloidotic polyneuropathy: an escape from ERAD

Familial amyloid polyneuropathy (FAP) is an autosomal dominant disease characterized by deposition of amyloid related to the presence of mutations in the transthyretin (TTR) gene. TTR is mainly synthesized in liver, choroid plexuses of brain and pancreas and secreted to plasma and cerebrospinal fluid (CSF). Although it possesses a sequon for N‐glycosylation N‐D‐S at position 98, it is not secreted as a glycoprotein. The most common FAP‐associated mutation is TTR V30M. In a screening for monoclonal antibodies developed against an amyloidogenic TTR form, we detected a distinct TTR with slower electrophoretic mobility in Western of plasma from carriers of the V30M mutation, not present in normal plasma. Mass spectrometry analyses of this slower migrating TTR (SMT) identified both wild‐type and mutant V30M; SMT was undetectable upon N‐glycosidase F treatment. Furthermore, SMT readily disappeared in the plasma of V30M ‐ FAP patients after liver transplantation and appeared in plasma of transplanted domino individuals that received a V30M liver. SMT was also detected in plasma, but not in CSF of transgenic mice for the human V30M mutation. A hepatoma cell line transduced to express human V30M did not present the SMT modification in secretion media. Glycosylated TTR was absent in fibrils extracted from human kidney V30M autopsy tissue or in TTR aggregates extracted from the intestine of human TTR transgenic mice. Studies on the metabolism of this novel, glycosylated TTR secreted from FAP liver are warranted to provide new mechanisms in protein quality control and etiopathogenesis of the disease.
Processing top k queries from samples

Top-k queries are desired aggregation operations on data sets. Examples of queries on network data include the top 100 source AS's, top 100 ports, or top Domain names over IP packets or over IP flow records. Since the complete dataset is often not available or not feasible to examine, we are interested in processing top-k queries from samples. If all records can be processed, the top-k items can be obtained by counting the frequency of each item. Even when the full dataset is observed, however, resources are often insufficient for such counting and techniques were developed to overcome this issue. When we can observe only a random sample of the records, an orthogonal complication arises: The top frequencies in the sample are biased estimates of the actual top-k frequencies. This bias as depends on the distribution and must be accounted for when seeking the actual value. We address this by designing and evaluating several schemes that derive rigorous confidence bounds for top-k estimates. Simulations on various data sets that include IP flows data, show that schemes that exploit more of the structure of the sample distribution produce much tight confidence intervals with an order of magnitude fewer samples than simpler schemes that utilize only the sampled top-k frequencies. The simpler schemes, however, are more efficient in terms of computation. Our work is basic and is widely applicable to all applications that process top-k and heavy hitters queries over a random sample of the actual records.
Effect of in ovo feeding of folic acid on the folate metabolism, immune function and epigenetic modification of immune effector molecules of broiler

Abstract This study was conducted to investigate the effect of in ovo feeding (IOF) of folic acid on the folate metabolism, immune function and the involved epigenetic modification of broilers. A total of 400 (Cobb) hatching eggs were randomly divided into four groups (0, 50, 100 and 150 µg injection of folic acid at embryonic age 11 d), and chicks hatched from each treatment were randomly divided into six replicates with 12 broilers/replicate after incubation. The results indicated that, in ovo, 100- and 150-µg folic acid injections improved the hatchability. The average daily gain and feed conversion ratio increased in the 150-µg group during the late growth stage. Simultaneously, in the 100- and 150-µg groups, an increase was observed in hepatic folate content and the expression of methylenetetrahydrofolate reductase (d1 and 42) and methionine synthase reductase (d21). IgG and IgM concentrations, as well as plasma lysozyme activity of broilers, showed a marked increase along with increasing folic acid levels. The splenic expression levels of IL-2 and IL-4 were up-regulated, whereas that of IL-6 was down-regulated, in the 100- and 150-µg folic acid treatment groups. In addition, histone methylation in IL-2 and IL-4 promoters exhibited an enrichment of H3K4m2 but a loss of H3K9me2 with the increased amount of folic acid additive. In contrast, a decrease in H3K4m2 and an increase in H3K9me2 were observed in the IL-6 promoter in folic acid treatments. Furthermore, in ovo, the 150-µg folic acid injection improved the chromatin tightness of the IL-2 and IL-4 promoter regions. Our findings suggest that IOF of 150 µg of folic acid can improve the growth performance and folate metabolism of broilers, and enhance the relationship between immune function and epigenetic regulation of immune genes, which are involved with the alterations in chromatin conformation and histone methylation in their promoters.
Adaptive optimization of least-squares tracking algorithms: with applications to adaptive antenna arrays for randomly time-varying mobile communications systems

Adaptive antenna arrays are used for reducing the effects of interference and increasing capacity in mobile communications systems. Typical algorithms recursively compute the antenna weights that minimize the weighted error function (at discrete times kh, k=1,2,., for a sampling interval h) /spl sigma//sub l=1//sup k//spl alpha//sup k-l/[e/sub l/(W)]/sup 2/, where e/sub l/(W) is a measure of the reception error at time lh with antenna weight vector W, and /spl alpha/<1. The forgetting factor /spl alpha/<1 allows tracking as conditions change and the minimization is used only to get the weights. The average detection error rate depends heavily on the chosen value of /spl alpha/, whose optimal value can change rapidly in time, perhaps significantly in seconds. We add another adaptive loop that tracks the optimal value of /spl alpha/ and greatly improves the operation when the environment is randomly time-varying. The additional adaptive loop is based on an approximation to a natural "gradient descent" method. The algorithm is practical and can improve the performance considerably. In terms of average detection error rates and for all of the scenarios tested, the new system tracks the optimal value of /spl alpha/ well, and always performs better (sometimes much better) than the original algorithm that uses any fixed value of /spl alpha/. Although the initial motivation arises in adaptive antennas, the method can be used to improve algorithms for tracking parameters of time-varying nonlinear systems, where similar issues are involved.
Featured Tweet Search: Modeling Time and Social Influence for Microblog Retrieval

This paper interests in social search over social networking services, typically in microblogging networks. We propose a new approach that integrates, within a Bayesian network model, new relevance factors such as the social importance of microbloggers and the temporal magnitude of tweets. In particular, the social importance of a microblogger is assimilated to his influence on the social network. This property is evaluated by applying PageRank algorithm on the social network of retweets and mentions. The temporal magnitude of microblogs is estimated based on temporal neighbors that present similar query terms. To validate our approach, we conducted a series of experiments on the TREC 2011 Microblog dataset. Results show that the integration of social and temporal features increases the retrieval effectiveness.