A Boltzmann machine for the organization of intelligent machines

In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved to converge to the minimum of a cost function. Finally, simulations will show the effectiveness of a variety of search techniques for the intelligent machine

Occupational exposure to gases/fumes and mineral dust affect DNA methylation levels of genes regulating expression

Many workers are daily exposed to occupational agents like gases/fumes, mineral dust or biological dust, which could induce adverse health effects. Epigenetic mechanisms, such as DNA methylation, have been suggested to play a role. We therefore aimed to identify differentially methylated regions (DMRs) upon occupational exposures in never-smokers and investigated if these DMRs associated with gene expression levels. To determine the effects of occupational exposures independent of smoking, 903 never-smokers of the LifeLines cohort study were included. We performed three genome-wide methylation analyses (Illumina 450 K), one per occupational exposure being gases/fumes, mineral dust and biological dust, using robust linear regression adjusted for appropriate confounders. DMRs were identified using comb-p in Python. Results were validated in the Rotterdam Study (233 never-smokers) and methylation-expression associations were assessed using Biobank-based Integrative Omics Study data (n = 2802). Of the total 21 significant DMRs, 14 DMRs were associated with gases/fumes and 7 with mineral dust. Three of these DMRs were associated with both exposures (RPLP1 and LINC02169 (2x)) and 11 DMRs were located within transcript start sites of gene expression regulating genes. We replicated two DMRs with gases/fumes (VTRNA2-1 and GNAS) and one with mineral dust (CCDC144NL). In addition, nine gases/fumes DMRs and six mineral dust DMRs significantly associated with gene expression levels. Our data suggest that occupational exposures may induce differential methylation of gene expression regulating genes and thereby may induce adverse health effects. Given the millions of workers that are exposed daily to occupational exposures, further studies on this epigenetic mechanism and health outcomes are warranted

Effectiveness of Journal Ranking Schemes as a Tool for Locating Information

BACKGROUND: The rise of electronic publishing, preprint archives, blogs, and wikis is raising concerns among publishers, editors, and scientists about the present day relevance of academic journals and traditional peer review. These concerns are especially fuelled by the ability of search engines to automatically identify and sort information. It appears that academic journals can only remain relevant if acceptance of research for publication within a journal allows readers to infer immediate, reliable information on the value of that research. METHODOLOGY/PRINCIPAL FINDINGS: Here, we systematically evaluate the effectiveness of journals, through the work of editors and reviewers, at evaluating unpublished research. We find that the distribution of the number of citations to a paper published in a given journal in a specific year converges to a steady state after a journal-specific transient time, and demonstrate that in the steady state the logarithm of the number of citations has a journal-specific typical value. We then develop a model for the asymptotic number of citations accrued by papers published in a journal that closely matches the data. CONCLUSIONS/SIGNIFICANCE: Our model enables us to quantify both the typical impact and the range of impacts of papers published in a journal. Finally, we propose a journal-ranking scheme that maximizes the efficiency of locating high impact research

Continued Neurogenesis in Adult Drosophila as a Mechanism for Recruiting Environmental Cue-Dependent Variants

Background The skills used by winged insects to explore their environment are strongly dependent upon the integration of neurosensory information comprising visual, acoustic and olfactory signals. The neuronal architecture of the wing contains a vast array of different sensors which might convey information to the brain in order to guide the trajectories during flight. In Drosophila, the wing sensory cells are either chemoreceptors or mechanoreceptors and some of these sensors have as yet unknown functions. The axons of these two functionally distinct types of neurons are entangled, generating a single nerve. This simple and accessible coincidental signaling circuitry in Drosophila constitutes an excellent model system to investigate the developmental variability in relation to natural behavioral polymorphisms. Methodology/Principal Findings A fluorescent marker was generated in neurons at all stages of the Drosophila life cycle using a highly efficient and controlled genetic recombination system that can be induced in dividing precursor cells (MARCM system, flybase web site). It allows fluorescent signals in axons only when the neuroblasts and/or neuronal cell precursors like SOP (sensory organ precursors) undergo division during the precedent steps. We first show that a robust neurogenesis continues in the wing after the adults emerge from the pupae followed by an extensive axonal growth. Arguments are presented to suggest that this wing neurogenesis in the newborn adult flies was influenced by genetic determinants such as the frequency dependent for gene and by environmental cues such as population density. Conclusions We demonstrate that the neuronal architecture in the adult Drosophila wing is unfinished when the flies emerge from their pupae. This unexpected developmental step might be crucial for generating non-heritable variants and phenotypic plasticity. This might therefore constitute an advantage in an unstable ecological system and explain much regarding the ability of Drosophila to robustly adapt to their environment

Environmental Stress-Dependent Effects of Deletions Encompassing Hsp70Ba on Canalization and Quantitative Trait Asymmetry in Drosophila melanogaster

Hsp70 genes may influence the expression of wing abnormalities in Drosophila melanogaster but their effects on variability in quantitative characters and developmental instability are unclear. In this study, we focused on one of the six Hsp70 genes, Hsp70Ba, and investigated its effects on within-and among-individual variability in orbital bristle number, sternopleural bristle number, wing size and wing shape under different environmental conditions. To do this, we studied a newly constructed deletion, Df(3R)ED5579, which encompasses Hsp70Ba and nine non-Hsp genes, in the heterozygous condition and another, Hsp70Ba304, which deletes only Hsp70Ba, in the homozygous condition. We found no significant effect of both deletions on within-individual variation quantified by fluctuating asymmetry (FA) of morphological traits. On the other hand, the Hsp70Ba304/Hsp70Ba304 genotype significantly increased among-individual variation quantified by coefficient of variation (CV) of bristle number and wing size in female, while the Df(3R)ED5579 heterozygote showed no significant effect. The expression level of Hsp70Ba in the deletion heterozygote was 6 to 20 times higher than in control homozygotes, suggesting that the overexpression of Hsp70Ba did not influence developmental stability or canalization significantly. These findings suggest that the absence of expression of Hsp70Ba increases CV of some morphological traits and that HSP70Ba may buffer against environmental perturbations on some quantitative traits

Combined analysis of νμ disappearance and νμ → νe appearance in MINOS using accelerator and atmospheric neutrinos

We report on a new analysis of neutrino oscillations in MINOS using the complete set of accelerator and atmospheric data. The analysis combines the νμ disappearance and νe appearance data using the three-flavor formalism. We measure |Δm^2 32| = [2.28–2.46] × 10−3 eV^2 (68% C.L.) and sin^2 θ23 = 0.35–0.65 (90% C.L.) in the normal hierarchy, and |Δm^2 32| = [2.32–2.53] × 10−3 eV^2 (68% C.L.) and sin^2 θ23 = 0.34–0.67 (90% C.L.) in the inverted hierarchy. The data also constrain δCP, the θ23 octant degeneracy and the mass hierarchy; we disfavor 36% (11%) of this three-parameter space at 68% (90%) C.L

Combined Analysis Of νμ Disappearance And νμ→νe Appearance In Minos Using Accelerator And Atmospheric Neutrinos.

We report on a new analysis of neutrino oscillations in MINOS using the complete set of accelerator and atmospheric data. The analysis combines the ν(μ) disappearance and ν(e) appearance data using the three-flavor formalism. We measure |Δm(32)(2)| = [2.28-2.46] × 10(-3) eV(2) (68% C.L.) and sin(2)θ(23) = 0.35-0.65 (90% C.L.) in the normal hierarchy, and |Δm(32)(2)| = [2.32-2.53] × 10(-3) eV(2) (68% C.L.) and sin(2)θ(23) = 0.34-0.67 (90% C.L.) in the inverted hierarchy. The data also constrain δ(CP), the θ(23} octant degeneracy and the mass hierarchy; we disfavor 36% (11%) of this three-parameter space at 68% (90%) C.L.11219180

Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution

We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious findings if left unaddressed. Neither GWAS-based methodology nor state-of-the-art confounder adjustment methods completely remove bias and inflation. We propose a Bayesian method to control bias and inflation in EWAS and TWAS based on estimation of the empirical null distribution. Using simulations and real data, we demonstrate that our method maximizes power while properly controlling the false positive rate. We illustrate the utility of our method in large-scale EWAS and TWAS meta-analyses of age and smoking

Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits

DNA methylation signatures of aggression and closely related constructs : A meta-analysis of epigenome-wide studies across the lifespan

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 x 10(-7); Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.Peer reviewe