We improve on and generalize a 1960 result of Maltsev. For a field F, we denote by $H(F)$ the Heisenberg group with entries in F. Maltsev showed that there is a copy of F defined in $H(F)$ , using existential formulas with an arbitrary non-commuting pair of elements as parameters. We show that F is interpreted in $H(F)$ using computable $\Sigma _1$ formulas with no parameters. We give two proofs. The first is an existence proof, relying on a result of Harrison-Trainor, Melnikov, R. Miller, and Montalbán. This proof allows the possibility that the elements of F are represented by tuples in $H(F)$ of no fixed arity. The second proof is direct, giving explicit finitary existential formulas that define the interpretation, with elements of F represented by triples in $H(F)$ . Looking at what was used to arrive at this parameter-free interpretation of F in $H(F)$ , we give general conditions sufficient to eliminate parameters from interpretations.

Regression modelling involving heavy-tailed response distributions, which have heavier tails than the exponential distribution, has become increasingly popular in many insurance settings including non-life insurance. Mixed Exponential models can be considered as a natural choice for the distribution of heavy-tailed claim sizes since their tails are not exponentially bounded. This paper is concerned with introducing a general family of mixed Exponential regression models with varying dispersion which can efficiently capture the tail behaviour of losses. Our main achievement is that we present an Expectation-Maximization (EM)-type algorithm which can facilitate maximum likelihood (ML) estimation for our class of mixed Exponential models which allows for regression specifications for both the mean and dispersion parameters. Finally, a real data application based on motor insurance data is given to illustrate the versatility of the proposed EM-type algorithm.

Lamb live weight is one of the key drivers of profitability on sheep farms. Previous studies in Ireland have estimated genetic parameters for live weight and carcass composition traits using a multi-breed population rather than on an individual breed basis. The objective of the present study was to undertake genetic analyses of three lamb live weight and two carcass composition traits pertaining to purebred Texel, Suffolk and Charollais lambs born in the Republic of Ireland between 2010 and 2017, inclusive. Traits (with lamb age range in parenthesis) considered in the analyses were: pre-weaning weight (20 to 65 days), weaning weight (66 to 120 days), post-weaning weight (121 to 180 days), muscle depth (121 to 180 days) and fat depth (121 to 180 days). After data edits, 137 402 records from 50 372 lambs across 416 flocks were analysed. Variance components were derived using animal linear mixed models separately for each breed. Fixed effects included for all traits were contemporary group, age at first lambing of the dam, parity of the dam, a gender by age of the lamb interaction and a birth type by rearing type of the lamb interaction. Random effects investigated in the pre-weaning and weaning weight analyses included animal direct additive genetic, dam maternal genetic, litter common environment, dam permanent environment and residual variances. The model of analysis for post-weaning, muscle and fat depth included an animal direct additive genetic and litter common environment effect only. Significant direct additive genetic variation existed in all cases. Direct heritability for pre-weaning weight ranged from 0.14 to 0.30 across the three breeds. Weaning weight had a direct heritability ranging from 0.17 to 0.27 and post-weaning weight had a direct heritability ranging from 0.15 to 0.27. Muscle and fat depth heritability estimates ranged from 0.21 to 0.31 and 0.15 to 0.20, respectively. Positive direct correlations were evident for all traits. Results revealed ample genetic variation among animals for the studied traits and significant differences between breeds to suggest that genetic evaluations could be conducted on a per-breed basis.

This paper provides evidence for a kind of nominal licensing (Vergnaud licensing) in a number of morphologically caseless languages. Recent work on Bantu languages has suggested that abstract Case or nominal licensing should be parameterised (Diercks 2012, Van der Wal 2015a). With this is mind, we critically discuss the status of Vergnaud licensing in six languages lacking morphological case. While Luganda appears to systematically lack a Vergnaud licensing requirement, Makhuwa more consistently displays evidence in favour of it, as do all of the analytic languages that we survey (Mandarin, Yoruba, Jamaican Creole and Thai). We conclude that, while it seems increasingly problematic to characterise nominal licensing in terms of uninterpretable/abstract Case features, we nonetheless need to retain a (possibly universal) notion of nominal licensing, the explanation for which remains opaque.

A vigilance state is characterized by a particular activity state of the motorIautonomic and psychiclcognitive functional systems. S-W screening is possible through poly graphic monitoring of physiological variables and signals. Quantification of these signals introduces a set of parameters allowing the characterisation of the sleep (dys)function. There is no consensus regarding the choice or definition of these parameters. A particular cluster is presented and their informative value with respect to clinical practice and research is discussed.

We present generalized and unified families of (2n)-point and (2n — 1)-point p-ary interpolating subdivision schemes originated from Lagrange polynomial for any integers n ≥ 2 and p ≥ 3. Almost all existing even-point and odd-point interpolating schemes of lower and higher arity belong to this family of schemes. We also present tensor product version of generalized and unified families of schemes. Moreover error bounds between limit curves and control polygons of schemes are also calculated. It has been observed that error bounds decrease when complexity of the scheme decrease and vice versa. Furthermore, error bounds decrease with the increase of arity of the schemes. We also observe that in general the continuity of interpolating scheme do not increase by increasing complexity and arity of the scheme.

The high prevalence of anthelmintic-resistant gastrointestinal nematodes (GINs) throughout the world has led to the need for alternative worm control strategies. One of the possible substitutes to reduce the problems of drug resistance and residue is the evaluation/breeding of small ruminants for greater resistance to the GINs (organically produced), which in turn would be a helpful tool to predict the performance of an animal. At present, the existing diversity in the genetic potential to resist/tolerate GINs infection both within and between breeds has been validated. Successful selection of animals to define the genotype and identified resistance is related to the employed markers. A number of phenotypic traits such as faecal egg count (FEC), worm burden, serum antibodies, peripheral eosinophilia, packed cell volume, live weight, serum protein and albumin concentrations have been used for this purpose both in natural and artificial infections. Relatively resistant/tolerant animals have also been found to have mastocytosis, globule leucocytes, high levels of histamine and immunoglobulin (Ig) A and IgE concentrations. Of these traits, the principal and most practical measurement used to assess resistance status in animals undergoing similar parasite challenges is FEC. FEC has a positive/negative correlation with other biochemical, cellular and immunological parameters; however, the reliability of individual trial is often questioned and valuable information regarding the genetic makeup can be obtained from pooled data of a large number of trials and parameters. This paper covers all the aspects reported in the literature on various parameters considered to evaluate the resistance status of a range of small ruminant breeds.

The paper presents a meta-study of the kinematic, dynamic and electrical parameters for the PUMA 560 robot. Parameter values which have been reported in the literature are transformed into a single system of units and coordinates, and differences in the data and measurement techniques are discussed. New data have been gathered and are presented where the record was incomplete.

In this paper, nine adaptive control algorithms are compared. The best two of them are tested experimentally. It is shown that the Adaptive FeedForward Controller AFFC) is well suited for learning the parameters of the dynamic equation, even in the presence of friction and noise. The resulting control performance is better than with measured parameters for any trajectory in the workspace. When the task consists of repeating the same trajectory, an adaptive look-up-table MEMory, introduced and analyzed in this paper, is simpler to implement and results in even better control performance.

This paper presents a new criterion based on prediction error which allows the estimation of the number of parameters as well as structures in statistical models. The criterion is valid for short and long samples alike. Unlike Akaike's earlier criterion, also based on prediction error, the criterion proposed here appears to produce consistent error estimates in ARMA processes.