Composite 2HDM with singlets: a viable dark matter scenario

We study the non-minimal composite Higgs model with global symmetry SO(7) broken to SO(5) x SO(2). The model results in a composite Two-Higgs doublet model (2HDM) equipped with two extra singlets, the lightest of which can be a viable dark matter candidate. The model is able to reproduce the correct dark matter relic density both via the usual thermal freeze-out and through late time decay of the heavier singlet. In the case of thermal freeze-out, it is possible to evade current experimental constraints even with the minimum fine tuning allowed by electroweak precision tests

A modular modelling approach to stochastic simulation of production – logistic systems

The economic scenario today is highly competitive in terms of costs and number of competitors, so it isnecessary to adopt strategies that allow the constant improvement of manufacturing processes withinthe spending constrains. Simulation models are useful to support and drive company management inimproving the performances of production and logistic systems. The costs of simulation modeldevelopment could be reduced by the reuse of some of its parts. This work presents a case studyconcerning stochastic modeling of a small manufacture operating into the wood products field. Amodular simulation model composed of reusable sub-models has been developed using AutoMod™software package. The aim of the modular architecture is to allow the use of sub-models in differentproduction systems with little changes, decreasing the costs of development in order to became moreaffordable in a SME (small medium enterprise) contest

Polymorphisms of beta-lactoglobulin promoter region in three Sicilian goat breeds

Several beta-lactoglobulin (BLG) polymorphisms have been described within the proximal promoter region and coding region of the caprine gene, although no genetic variants affecting the protein amino acid composition and/or expression level have been characterized so far. Binding sites for several transcription factors (TFs) are present in the BLG promoter region. The aims of this work were to sequence the full-length promoter region of three Sicilian goat breeds in order to identify polymorphisms, analyze the identified haplotypes, search for differences between breeds for the presence of polymorphisms in this gene region, search for putative TFs binding sites, and check if polymorphisms lay within the identified TFs binding sites. The promoter region of BLG gene in Sicilian goat breeds showed high level of polymorphism due to the presence of 36 single nucleotide polymorphisms (SNPs). Association between polymorphic sites was computed within the whole sample analyzed and 18 haplotypes were inferred. Binding sites for three milk protein binding factors (MPBFs) and four nuclear factor-I (NF-I) were found within BLG promoter region based on the ovine sequence. The identification of some SNPs within TFs binding sites allowed hypothesizing the loss of TFs. Further studies are in progress to evaluate the effect of these mutations on binding affinity of TFs, the functional interaction of the TFs with the goat BLG promoter, and the relationship of the polymorphisms with BLG gene expression and milk production and composition

Research Notes : United States : A greenhouse method of screening soybeans for resistance to Fusarium wilt

Fusarium wilt of soybean (causal organism: Fusarium oxysporum Schlecht. emend. Snyd. & Hans.) has become an increasingly severe disease in the breed-ing plots at Gainesville and may be an undiagnosed or misdiagnosed problem in soybean production fields. At Gainesville, severity of Fusarium wilt, or a complex which includes F. oxysporum, has reduced yields in some plots to near-ly zero

The Effects of Milk Protein Polymorphisms on Milk Components and Cheese-Producing Ability

Abstract A Total of 2005 first lactation Holstein-Friesian cows with known 305-d lactation yield for milk, fat, and protein were available. For each cow, genotypes for α s1 -casein, β-casein, κ-casein, and β-lactoglobulin were known. It appears that the milk protein variants α s1 -casein, β-casein, and κ-casein may not be segregating independently. Effects of genetic variants of milk proteins on estimated individual Parmesan cheese yields were investigated. The relationships of the genetic variants of milk proteins to total lactation milk yield, fat yield, protein yield, fat percentage, and protein percentage were also investigated. Least squares analysis of the data indicated that α s1 -casein genotype significantly influenced milk yield, fat yield, and protein yield with the highest yields obtained for the genotype BB . Cheese yield on a fixed amount of milk and fat percentage were significantly related to β-lactoglobulin genotype with the highest estimates obtained for BB . Protein percentage was influenced by α s1 -casein and κ-casein, with the genotypes BC and BB , respectively, having the highest percentages. Significantly higher lactation cheese yields were estimated with α s1 -casein genotype BB . Using the prediction equation to estimate cheese yield (on data from another study), it was found that differences in Parmesan cheese yield from milk of either κ-casein genotype AA or BB were greater than expected based on composition. Differences in salted curd yield from another study using milk of either β-lactoglobulin genotype AA or BB were also greater than expected

An Approximate Maximum Likelihood Method for the Joint Estimation of Range and Doppler of Multiple Targets in OFDM-Based Radar Systems

In this manuscript, an innovative method for the detection and the estimation of multiple targets in a radar system employing orthogonal frequency division multiplexing is illustrated. The core of this method is represented by a novel algorithm for detecting multiple superimposed two-dimensional complex tones in the presence of noise and estimating their parameters. This algorithm is based on a maximum likelihood approach and combines a single tone estimator with a serial cancellation procedure. Our numerical results lead to the conclusion that the developed method can achieve a substantially better accuracy-complexity trade-off than various related techniques in the presence of closely spaced targets

Deterministic Signal Processing Techniques for OFDM-Based Radar Sensing: An Overview

In this manuscript, we analyze the most relevant classes of deterministic signal processing methods currently available for the detection and the estimation of multiple targets in a joint communication and sensing system employing orthogonal frequency division multiplexing. Our objective is offering a fair comparison of the available technical options in terms of required computational complexity and accuracy in both range and Doppler estimation. Our numerical results, obtained in various scenarios, evidence that distinct algorithms can achieve a substantially different accuracy-complexity trade-off

Novel Deterministic Detection and Estimation Algorithms for Colocated Multiple-Input Multiple-Output Radars

In this manuscript, the problem of detecting multiple targets and estimating their spatial coordinates (namely, their range and the direction of arrival of their electromagnetic echoes) in a colocated multiple-input multiple-output radar system operating in a static or slowly changing two-dimensional or three-dimensional propagation scenario is investigated. Various solutions, collectively called range & angle serial cancellation algorithms, are developed for both frequency modulated continuous wave radars and stepped frequency continuous wave radars. Moreover, specific technical problems experienced in their implementation are discussed. Finally, the accuracy achieved by these algorithms in the presence of multiple targets is assessed on the basis of both synthetically generated data and of the measurements acquired through three different multiple-input multiple-output radars and is compared with that provided by other methods based on multidimensional Fourier analysis and multiple signal classification