Supervised Competitive Learning Part II: SCL with Fuzzy Logic

Supervised Competitive Learning (SCL) is described in an accompanying paper [1]; SCL assembles a set of learning modules into a supervised learning system to address the stability-plasticity dilemma. That paper reported results using backpropagation networds as the learning modules (SCL/BP). Here (Part II) we report SCL results using learning modules based on fuzzy logic (SCL/FZ). Although its learning algorithm is very different from that of backpropagation networks, fuzzy logic also suffers the stability-plasticity dilemma. A simulator on handwritten digit and gesture recognition was constructed to demonstrate the utility of SCL/FZ; it is recognized 98% of test digits, and 91% of test gestures. In this paper, we also compare SCL/BP with SCL/FZ for recognizing handwritten digits

Supervised Competitive Learning with Backpropagation Network and Fuzzy Logic

SCL assembles a set of learning modules into a supervised learning system to address the stability-plasticity dilemma. Each learning module acts as a similarity detector for a prototype, and includes prototype resetting (akin to that of ART) to respond to new prototypes. Here (Part I) we report SCL results using back-propagation networks as the learning modules. We used two feature extractors: about 30 energy-based features, and a combination of energy-based and graphical features (about 60). ACL recognized 96% (energy) and 99% (energy/graphical) of test digits, and 91% (energy) and 96% (energy/graphical) of test letters. In the accompanying paper (Part II), we report the results of SCL using fuzzy sets as learning moduels for recognizing handwritten digits

Modulus Computational Entropy

The so-called {\em leakage-chain rule} is a very important tool used in many security proofs. It gives an upper bound on the entropy loss of a random variable $X$ in case the adversary who having already learned some random variables $Z_{1},\ldots,Z_{\ell}$ correlated with $X$, obtains some further information $Z_{\ell+1}$ about $X$. Analogously to the information-theoretic case, one might expect that also for the \emph{computational} variants of entropy the loss depends only on the actual leakage, i.e. on $Z_{\ell+1}$. Surprisingly, Krenn et al.\ have shown recently that for the most commonly used definitions of computational entropy this holds only if the computational quality of the entropy deteriorates exponentially in $|(Z_{1},\ldots,Z_{\ell})|$. This means that the current standard definitions of computational entropy do not allow to fully capture leakage that occurred "in the past", which severely limits the applicability of this notion. As a remedy for this problem we propose a slightly stronger definition of the computational entropy, which we call the \emph{modulus computational entropy}, and use it as a technical tool that allows us to prove a desired chain rule that depends only on the actual leakage and not on its history. Moreover, we show that the modulus computational entropy unifies other,sometimes seemingly unrelated, notions already studied in the literature in the context of information leakage and chain rules. Our results indicate that the modulus entropy is, up to now, the weakest restriction that guarantees that the chain rule for the computational entropy works. As an example of application we demonstrate a few interesting cases where our restricted definition is fulfilled and the chain rule holds.Comment: Accepted at ICTS 201

Biomolecular characterization of 3500-year-old ancient Egyptian mummification balms from the Valley of the Kings

Ancient Egyptian mummification was practiced for nearly 4000 years as a key feature of some of the most complex mortuary practices documented in the archaeological record. Embalming, the preservation of the body and organs of the deceased for the afterlife, was a central component of the Egyptian mummification process. Here, we combine GC-MS, HT-GC-MS, and LC-MS/MS analyses to examine mummification balms excavated more than a century ago by Howard Carter from Tomb KV42 in the Valley of the Kings. Balm residues were scraped from now empty canopic jars that once contained the mummified organs of the noble lady Senetnay, dating to the 18th dynasty, ca. 1450 BCE. Our analysis revealed balms consisting of beeswax, plant oil, fats, bitumen, Pinaceae resins, a balsamic substance, and dammar or Pistacia tree resin. These are the richest, most complex balms yet identified for this early time period and they shed light on balm ingredients for which there is limited information in Egyptian textual sources. They highlight both the exceptional status of Senetnay and the myriad trade connections of the Egyptians in the 2nd millennium BCE. They further illustrate the excellent preservation possible even for organic remains long removed from their original archaeological context

A two-year participatory intervention project with owners to reduce lameness and limb abnormalities in working horses in Jaipur, India

Participatory methods are increasingly used in international human development, but scientific evaluation of their efficacy versus a control group is rare. Working horses support families in impoverished communities. Lameness and limb abnormalities are highly prevalent in these animals and a cause for welfare concern. We aimed to stimulate and evaluate improvements in lameness and limb abnormalities in horses whose owners took part in a 2-year participatory intervention project to reduce lameness (PI) versus a control group (C) in Jaipur, India.In total, 439 owners of 862 horses participated in the study. PI group owners from 21 communities were encouraged to meet regularly to discuss management and work practices influencing lameness and poor welfare and to track their own progress in improving these. Lameness examinations (41 parameters) were conducted at the start of the study (Baseline), and after 1 year and 2 years. Results were compared with control horses from a further 21 communities outside the intervention. Of the 149 horses assessed on all three occasions, PI horses showed significantly (P<0.05) greater improvement than C horses in 20 parameters, most notably overall lameness score, measures of sole pain and range of movement on limb flexion. Control horses showed slight but significantly greater improvements in four parameters, including frog quality in fore and hindlimbs.This participatory intervention succeeded in improving lameness and some limb abnormalities in working horses, by encouraging changes in management and work practices which were feasible within owners’ socioeconomic and environmental constraints. Demonstration of the potentially sustainable improvements achieved here should encourage further development of participatory intervention approaches to benefit humans and animals in other contexts

Cooling of Dark-Matter Admixed Neutron Stars with density-dependent Equation of State

We propose a dark-matter (DM) admixed density-dependent equation of state where the fermionic DM interacts with the nucleons via Higgs portal. Presence of DM can hardly influence the particle distribution inside neutron star (NS) but can significantly affect the structure as well as equation of state (EOS) of NS. Introduction of DM inside NS softens the equation of state. We explored the effect of variation of DM mass and DM Fermi momentum on the NS EOS. Moreover, DM-Higgs coupling is constrained using dark matter direct detection experiments. Then, we studied cooling of normal NSs using APR and DD2 EOSs and DM admixed NSs using dark-matter modified DD2 with varying DM mass and Fermi momentum. We have done our analysis by considering different NS masses. Also DM mass and DM Fermi momentum are varied for fixed NS mass and DM-Higgs coupling. We calculated the variations of luminosity and temperature of NS with time for all EOSs considered in our work and then compared our calculations with the observed astronomical cooling data of pulsars namely Cas A, RX J0822-43, 1E 1207-52, RX J0002+62, XMMU J17328, PSR B1706-44, Vela, PSR B2334+61, PSR B0656+14, Geminga, PSR B1055-52 and RX J0720.4-3125. It is found that APR EOS agrees well with the pulsar data for lighter and medium mass NSs but cooling is very fast for heavier NS. For DM admixed DD2 EOS, it is found that for all considered NS masses, all chosen DM masses and Fermi momenta agree well with the observational data of PSR B0656+14, Geminga, Vela, PSR B1706-44 and PSR B2334+61. Cooling becomes faster as compared to normal NSs in case of increasing DM mass and Fermi momenta. It is infered from the calculations that if low mass super cold NSs are observed in future that may support the fact that heavier WIMP can be present inside neutron stars.Comment: 24 Pages, 15 Figures and 2 Tables. Version accepted in The European Physical Journal

A global optimisation approach to range-restricted survey calibration

Survey calibration methods modify minimally unit-level sample weights to fit domain-level benchmark constraints (BC). This allows exploitation of auxiliary information, e.g. census totals, to improve the representativeness of sample data (addressing coverage limitations, non-response) and the quality of estimates of population parameters. Calibration methods may fail with samples presenting small/zero counts for some benchmark groups or when range restrictions (RR), such as positivity, are imposed to avoid unrealistic or extreme weights. User-defined modifications of BC/RR performed after encountering non-convergence allow little control on the solution, and penalization approaches modelling infeasibility may not guarantee convergence. Paradoxically, this has led to underuse in calibration of highly disaggregated information, when available. We present an always-convergent flexible two-step Global Optimisation (GO) survey calibration approach. The feasibility of the calibration problem is assessed, and automatically controlled minimum errors in BC or changes in RR are allowed to guarantee convergence in advance, while preserving the good properties of calibration estimators. Modelling alternatives under different scenarios, using various error/change and distance measures are formulated and discussed. The GO approach is validated by calibrating the weights of the 2012 Health Survey for England to a fine age-gender-region cross-tabulation (378 counts) from the 2011 Census in England and Wales

A global optimisation approach to range-restricted survey calibration

Survey calibration methods modify minimally unit-level sample weights to fit domain-level benchmark constraints (BC). This allows exploitation of auxiliary information, e.g. census totals, to improve the representativeness of sample data (addressing coverage limitations, non-response) and the quality of estimates of population parameters. Calibration methods may fail with samples presenting small/zero counts for some benchmark groups or when range restrictions (RR), such as positivity, are imposed to avoid unrealistic or extreme weights. User-defined modifications of BC/RR performed after encountering non-convergence allow little control on the solution, and penalization approaches modelling infeasibility may not guarantee convergence. Paradoxically, this has led to underuse in calibration of highly disaggregated information, when available. We present an always-convergent flexible two-step Global Optimisation (GO) survey calibration approach. The feasibility of the calibration problem is assessed, and automatically controlled minimum errors in BC or changes in RR are allowed to guarantee convergence in advance, while preserving the good properties of calibration estimators. Modelling alternatives under different scenarios, using various error/change and distance measures are formulated and discussed. The GO approach is validated by calibrating the weights of the 2012 Health Survey for England to a fine age-gender-region cross-tabulation (378 counts) from the 2011 Census in England and Wales

MSH3 polymorphisms and protein levels affect CAG repeat instability in huntington's disease mice

Expansions of trinucleotide CAG/CTG repeats in somatic tissues are thought to contribute to ongoing disease progression through an affected individual's life with Huntington's disease or myotonic dystrophy. Broad ranges of repeat instability arise between individuals with expanded repeats, suggesting the existence of modifiers of repeat instability. Mice with expanded CAG/CTG repeats show variable levels of instability depending upon mouse strain. However, to date the genetic modifiers underlying these differences have not been identified. We show that in liver and striatum the R6/1 Huntington's disease (HD) (CAG)~100 transgene, when present in a congenic C57BL/6J (B6) background, incurred expansion-biased repeat mutations, whereas the repeat was stable in a congenic BALB/cByJ (CBy) background. Reciprocal congenic mice revealed the Msh3 gene as the determinant for the differences in repeat instability. Expansion bias was observed in congenic mice homozygous for the B6 Msh3 gene on a CBy background, while the CAG tract was stabilized in congenics homozygous for the CBy Msh3 gene on a B6 background. The CAG stabilization was as dramatic as genetic deficiency of Msh2. The B6 and CBy Msh3 genes had identical promoters but differed in coding regions and showed strikingly different protein levels. B6 MSH3 variant protein is highly expressed and associated with CAG expansions, while the CBy MSH3 variant protein is expressed at barely detectable levels, associating with CAG stability. The DHFR protein, which is divergently transcribed from a promoter shared by the Msh3 gene, did not show varied levels between mouse strains. Thus, naturally occurring MSH3 protein polymorphisms are modifiers of CAG repeat instability, likely through variable MSH3 protein stability. Since evidence supports that somatic CAG instability is a modifier and predictor of disease, our data are consistent with the hypothesis that variable levels of CAG instability associated with polymorphisms of DNA repair genes may have prognostic implications for various repeat-associated diseases