On smoothed probability density estimation for stationary processes

Aspects of estimation of the (marginal) probability density for a stationary sequence or continuous parameter process, are considered in this paper. Consistency and asymptotic distributional results are obtained using a class of smoothed function estimators including those of kernel type, under various decay of dependence conditions for the process. Some of the consistency results contain convergence rates which appear to be more delicate than those previously available, even for i.i.d. sequences

Role of the Tracy-Widom distribution in the finite-size fluctuations of the critical temperature of the Sherrington-Kirkpatrick spin glass

We investigate the finite-size fluctuations due to quenched disorder of the critical temperature of the Sherrington-Kirkpatrick spin glass. In order to accomplish this task, we perform a finite-size analysis of the spectrum of the susceptibility matrix obtained via the Plefka expansion. By exploiting results from random matrix theory, we obtain that the fluctuations of the critical temperature are described by the Tracy-Widom distribution with a non-trivial scaling exponent 2/3

Possible seismo-ionosphere perturbations revealed by VLF signals collected on ground and on a satellite

The results of the monitoring of three VLF/LF signals collected in Petropavlovsk station (Kamchatka, Russia) and one VLF signal collected on board of the DEMETER French satellite are presented. Two periods of the seismic activity occurred in the Japan-Kamchatka area during November–December 2004 and July–September 2005 were investigated and the earthquakes with M≥6.0 in the Japan-Kamchatka area, located inside one or more of the third Fresnel zones of the three radio paths were considered. The ground data were analysed using residual signal of phase <i>dP</i> or of amplitude <i>dA</i>, defined as the difference between the signal and the average of few quiet days (±5 days) immediately preceding or following the current day. Also the satellite data were processed by a method based on the difference between the real signal and the reference one, but in order to obtain this last signal it was necessary to construct previously a model of the signal distribution over the selected area. The method consists: (a) in averaging all the data available in the considered region over a period characterized by low level seismicity, regardless of the global disturbances, in particular, of the magnetic activity; (b) in computing a polynomial expression for the surface as a function of the longitude and the latitude. The model well describes the real data in condition of their completeness and in absence of magnetic storms or seismic forcing. In the quoted periods of seismic activity clear anomalies both in the ground and in satellite data were revealed. The influence of the geomagnetic activity cannot to be excluded, but the seismic forcing seems more probable

Finite-size scaling analysis of the distributions of pseudo-critical temperatures in spin glasses

Using the results of large scale numerical simulations we study the probability distribution of the pseudo critical temperature for the three-dimensional Edwards-Anderson Ising spin glass and for the fully connected Sherrington-Kirkpatrick model. We find that the behavior of our data is nicely described by straightforward finite-size scaling relations.Comment: 23 pages, 9 figures. Version accepted for publication in J. Stat. Mec

Bridging Python to Silicon: The SODA Toolchain

Systems performing scientific computing, data analysis, and machine learning tasks have a growing demand for application-specific accelerators that can provide high computational performance while meeting strict size and power requirements. However, the algorithms and applications that need to be accelerated are evolving at a rate that is incompatible with manual design processes based on hardware description languages. Agile hardware design tools based on compiler techniques can help by quickly producing an application specific integrated circuit (ASIC) accelerator starting from a high-level algorithmic description. We present the SODA Synthesizer, a modular and open-source hardware compiler that provides automated end-to-end synthesis from high-level software frameworks to ASIC implementation, relying on multi-level representations to progressively lower and optimize the input code. Our approach does not require the application developer to write register-transfer level code, and it is able to reach up to 364 GFLOPS/W efficiency (32-bit precision) on typical convolutional neural network operators

Addressing statistical biases in nucleotide-derived protein databases for proteogenomic search strategies

[Image: see text] Proteogenomics has the potential to advance genome annotation through high quality peptide identifications derived from mass spectrometry experiments, which demonstrate a given gene or isoform is expressed and translated at the protein level. This can advance our understanding of genome function, discovering novel genes and gene structure that have not yet been identified or validated. Because of the high-throughput shotgun nature of most proteomics experiments, it is essential to carefully control for false positives and prevent any potential misannotation. A number of statistical procedures to deal with this are in wide use in proteomics, calculating false discovery rate (FDR) and posterior error probability (PEP) values for groups and individual peptide spectrum matches (PSMs). These methods control for multiple testing and exploit decoy databases to estimate statistical significance. Here, we show that database choice has a major effect on these confidence estimates leading to significant differences in the number of PSMs reported. We note that standard target:decoy approaches using six-frame translations of nucleotide sequences, such as assembled transcriptome data, apparently underestimate the confidence assigned to the PSMs. The source of this error stems from the inflated and unusual nature of the six-frame database, where for every target sequence there exists five “incorrect” targets that are unlikely to code for protein. The attendant FDR and PEP estimates lead to fewer accepted PSMs at fixed thresholds, and we show that this effect is a product of the database and statistical modeling and not the search engine. A variety of approaches to limit database size and remove noncoding target sequences are examined and discussed in terms of the altered statistical estimates generated and PSMs reported. These results are of importance to groups carrying out proteogenomics, aiming to maximize the validation and discovery of gene structure in sequenced genomes, while still controlling for false positives

Tumor-Derived Microvesicles Induce, Expand and Up-Regulate Biological Activities of Human Regulatory T Cells (Treg)

Background: Tumor-derived microvesicles (TMV) or exosomes are present in body fluids of patients with cancer and might be involved in tumor progression. The frequency and suppressor functions of peripheral blood CD4 + CD25 high FOXP3 + Treg are higher in patients with cancer than normal controls. The hypothesis is tested that TMV contribute to induction/ expansion/and activation of human Treg. Methodology/Principal Findings: TMV isolated from supernatants of tumor cells but not normal cells induced the generation and enhanced expansion of human Treg. TMV also mediated conversion of CD4 + CD25 neg T cells into CD4 + CD25 high FOXP3 + Treg. Upon co-incubation with TMV, Treg showed an increased FasL, IL-10, TGF-b1, CTLA-4, granzyme B and perforin expression (p,0.05) and mediated stronger suppression of responder cell (RC) proliferation (p,0.01). Purified Treg were resistant to TMV-mediated apoptosis relative to other T cells. TMV also increased phospho-SMAD2/3 and phospho-STAT3 expression in Treg. Neutralizing Abs specific for TGF-b1 and/or IL-10 significantly inhibited TMV ability to expand Treg. Conclusions/Significance: This study suggests that TMV have immunoregulatory properties. They induce Treg, promote Treg expansion, up-regulate Treg suppressor function and enhance Treg resistance to apoptosis. Interactions of TMV wit

Neuropeptidomic Components Generated by Proteomic Functions in Secretory Vesicles for Cell–Cell Communication

Diverse neuropeptides participate in cell–cell communication to coordinate neuronal and endocrine regulation of physiological processes in health and disease. Neuropeptides are short peptides ranging in length from ~3 to 40 amino acid residues that are involved in biological functions of pain, stress, obesity, hypertension, mental disorders, cancer, and numerous health conditions. The unique neuropeptide sequences define their specific biological actions. Significantly, this review article discusses how the neuropeptide field is at the crest of expanding knowledge gained from mass-spectrometry-based neuropeptidomic studies, combined with proteomic analyses for understanding the biosynthesis of neuropeptidomes. The ongoing expansion in neuropeptide diversity lies in the unbiased and global mass-spectrometry-based approaches for identification and quantitation of peptides. Current mass spectrometry technology allows definition of neuropeptide amino acid sequence structures, profiling of multiple neuropeptides in normal and disease conditions, and quantitative peptide measures in biomarker applications to monitor therapeutic drug efficacies. Complementary proteomic studies of neuropeptide secretory vesicles provide valuable insight into the protein processes utilized for neuropeptide production, storage, and secretion. Furthermore, ongoing research in developing new computational tools will facilitate advancements in mass-spectrometry-based identification of small peptides. Knowledge of the entire repertoire of neuropeptides that regulate physiological systems will provide novel insight into regulatory mechanisms in health, disease, and therapeutics