Exploration in red knots:The role of personality in the expression of individual behaviour across contexts

All individuals show behavioural traits that are consistent over time, but differ across individuals, and affect the expression of behaviours in different situations (personality traits). This personality traits have been shown to have consistent ecological and evolutionary consequences thus, studying the variation in personality traits is important. The aim of this thesis was to identify the variation in exploratory behaviour in red knots, understand the origin of this variation, understand how variation in exploration maintained in natural populations, and whether exploration measured in experimental setups could be extrapolated to ecological contexts. We found that experience during ontogeny (i.e., exposure to a certain physical or social environment) can be important for the development of personalities in juvenile red knots. For adults, exploratory behaviour assayed in experimental setups is highly consistent within individuals and can predict other behaviours in different contexts. That is, variation in exploratory personality (i.e., slow vs. fast explorer) predicts foraging tactics and dietary choice in the wild. Exploratory behaviour also relates to variation in movement across different temporal and spatial scales in previously unforeseen ways. Specifically, slow and fast explorers show divergent movement patterns during the day and night and differ in arrival times from migration. This thesis fills a gap in the literature to link an experimentally measured personality trait to real-world behavioural strategies and demonstrates the importance of studying personality across contexts. Understanding the causes, maintenance, and consequences of animal personalities should further our understanding of population responses to environmental change, population and community dynamics, and speciation

Nonzero macroscopic magnetization in half-metallic antiferromagnets at finite temperatures

Combining density-functional theory calculations with many-body Green's-function technique, we reveal that the macroscopic magnetization in half-metallic antiferromagnets does not vanish at finite temperature as for the T=0 limit. This anomalous behavior stems from the inequivalent magnetic sublattices which lead to different intrasublattice exchange interactions. As a consequence, the spin fluctuations suppress the magnetic order of the sublattices in a different way leading to a ferrimagnetic state at finite temperatures. Computational results are presented for the half-metallic antiferromagnetic CrMnZ (Z=P,As,Sb) semi-Heusler compounds.Comment: 4 pages, 2 figure

Electroweak Interactions: Experimental Facts and Theoretical Foundation

Although intimate partner violence (IPV) is an important problem that threatens women’s health, very few studies focus on the victim—perpetrator relationship or examine this relationship across Turkey. The aim of this study is to contribute to a better understanding of femicide cases in Turkey and to describe the socio-demographic, clinical, forensic, and criminological characteristics of femicide victims and offenders. This study analysed 162 femicide cases that occurred in 12 cities in Turkey from 1 January 2000 to 31 December 2010. Eighty women were killed by their partners (classified as intimate partner femicide, IPF), and 81 women were killed by one of their relatives, friends, or strangers (classified as non-intimate partner femicide, non-IPF). According to our results, the typical IPF victim is of child-bearing age, does not have a paid job, is married or divorced, is killed in a domestic setting due to injuries to the thorax or abdomen produced by an edged/pointed weapon or firearm, and is possibly a victim of overkill. The typical IPF perpetrator is close to his victim’s age, has a paid job, has no mental disability, owns a gun, and has threatened his partner or ex-partner previously because of jealousy/infidelity/honour or separation. The typical non-IPF victim is very similar to the IPF victim; however, her marital status can be single, married or divorced, and she is commonly killed by a relative. The surveillance and screening of femicide and IPV is an important step when analysing and attempting to prevent femicide. Second, the training and sensitization of health professionals are important. Moreover, health staff should be encouraged to participate in advocacy interventions. Third, gun ownership must be brought under control. © 2017 Toprak, Ersoy. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Investigation of Sound Properties of High Density Polyethylene / Styrene Butadiene Rubber Polymer Composites

Polymers are used in many areas today and able to produce specially with enhanced features. For this reason, Polymer Industry has developed several polymers composite. Some features of polymer composites are examined in determining areas and to improve these properties such as mechanical, thermal, electricity and morphological. One of the important features of the sound characteristics of a material that can help identifies the areas where the material is used. Provide strength and comforts of used materials are very important in transportation technologies such as rail vehicles, automotive and aircraft. In this study High Density Poly Ethylene (HDPE) with Styrene Butadiene Rubber (SBR) polymer with elastomeric composites with properties were determined of the sound. Firstly, a sound absorption material composed of blends of HDPE with SBR developed. After then HDPE/SBR composite’s sound absorbing characteristics were investigated in an impedance tube, according to transfer function method. Measurements show that HDPE ratios have a significant effect on the acoustic absorption performance of the blend due to their microstructures and physical features. Furthermore, a polymer blend of High Density Poly Ethylene and Styrene Butadiene Rubber was tested in order to quantify its sound properties such as sound absorption and impedance ratio. There was sound absorption in the frequency range between 100 and 6400 where is high frequency range. All the data was filtered via MATLAB numeric analyses program. In the light of all these data, it was seen that SBR contribution leads to property of acoustics behaviors

NONLINEAR ADAPTIVE SIGNAL PROCESSING

Nonlinear techniques for signal processing and recognition have the promise of achieving systems which are superior to linear systems in a number of ways such as better performance in terms of accuracy, fault tolerance, resolution, highly parallel architectures and cloker similarity to biological intelligent systems. The nonlinear techniques proposed are in the form of multistage neural networks in which each stage can be a particular neural network and all the stages operate in parallel. The specific approach focused upon is the parallel, self-organizing, hierarchical neural networks (PSHNN\u27s). A new type of PSHNN is discussed such that the outputs are allowed to be continuous-valued. The perfo:rmance of the resulting networks is tested in problems of prediction of speech and of chaotic time-series. Three types of networks in which the stages are learned by the delta rule, sequential least-squares, and the backpropagation (BP) algolrithm, respectively, are described. In all cases studied, the new networks achieve better performarnce than linear prediction. This is shown both theoretically and experimentally. A revised BP algorithm is discussed for learning input nonlinearities. The advantage of the revised BP algorithm is that the PSHNN with revised BP stages can be extended to use the sequential leastsquares (SLS) or the least mean absolule value rule (LMAV) in the last stage. A forward-backward training algorithm for parallel, self-organizing hierarchical neural networks is described. Using linear algebra, it is shown that the forward-backward training of an n-stage PSHNN until convergence is equivalent to the pseudo-inverse solution for a single, total network designed in the leastsquares sense with the total input vector consisting of the actual input vector and its additional nonlinear transformations. These results are also valid when a single long input vector is partitioned into smaller length vectors. A number of advantages achieved are small modules for easy and fast learning, parallel implementation of small modules during testing, faster convergence rate, better numerical error-reduction, and suitability for learning input nonlinear transformations by the backpropagation algorithm. Better performance in terms of deeper minimum of the error function and faster convergence rate is achieved when a single BP network is replaced by a PSHNN of equal complexity in which each stage is a BP network of smaller complexity than the single BP network

Weighted Chebyshev Distance Algorithms for Hyperspectral Target Detection and Classification Applications

In this study, an efficient spectral similarity method referred to as Weighted Chebyshev Distance (WCD) is introduced for supervised classification of hyperspectral imagery (HSI) and target detection applications. The WCD is based on a simple spectral similarity based decision rule using limited amount of reference data. The estimation of upper and lower spectral boundaries of spectral signatures for all classes across spectral bands is referred to as a vector tunnel (VT). To obtain the reference information, the training signatures are provided randomly from existing data for a known class. After determination of the parameters of the WCD algorithm with the training set, classification or detection procedures are accomplished at each pixel. The comparative performances of the algorithms are tested under various cases. The decision criterion for classification of an input vector is based on choosing its class corresponding to the narrowest VT that the input vector fits in to. This is also shown to be approximated by the WCD in which the weights are chosen as an inverse power of the generalized standard deviation per spectral band. In computer experiments, the WCD classifier is compared with the Euclidian Distance (ED) classifier and the Spectral Angle Map (SAM) classifier. The WCD algorithm is also used for HSI target detection purpose. Target detection problem is considered as a two-class classification problem. The WCD is characterized only by the target class spectral information. Then, this method is compared with ED, SAM, Spectral Matched Filter (SMF), Adaptive Cosine Estimator (ACE) and Support Vector Machine (SVM) algorithms. During these studies, threshold levels are evaluated based on the Receiver Operating Characteristic Curves (ROC)

Bicarbonate Resensitization of Methicillin-Resistant Staphylococcus aureus to β-Lactam Antibiotics.

Endovascular infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are a major health care concern, especially infective endocarditis (IE). Standard antimicrobial susceptibility testing (AST) defines most MRSA strains as "resistant" to β-lactams, often leading to the use of costly and/or toxic treatment regimens. In this investigation, five prototype MRSA strains, representing the range of genotypes in current clinical circulation, were studied. We identified two distinct MRSA phenotypes upon AST using standard media, with or without sodium bicarbonate (NaHCO3) supplementation: one highly susceptible to the antistaphylococcal β-lactams oxacillin and cefazolin (NaHCO3 responsive) and one resistant to such agents (NaHCO3 nonresponsive). These phenotypes accurately predicted clearance profiles of MRSA from target tissues in experimental MRSA IE treated with each β-lactam. Mechanistically, NaHCO3 reduced the expression of two key genes involved in the MRSA phenotype, mecA and sarA, leading to decreased production of penicillin-binding protein 2a (that mediates methicillin resistance), in NaHCO3-responsive (but not in NaHCO3-nonresponsive) strains. Moreover, both cefazolin and oxacillin synergistically killed NaHCO3-responsive strains in the presence of the host defense antimicrobial peptide (LL-37) in NaHCO3-supplemented media. These findings suggest that AST of MRSA strains in NaHCO3-containing media may potentially identify infections caused by NaHCO3-responsive strains that are appropriate for β-lactam therapy

Identification of viscoelastic material properties based on Big Bang-Big Crunch optimization method

An efficient identification method of the dynamic properties of viscoelastic damping materials using an optimization technique is proposed. A Zener fractional derivative model is used to describe the frequency-dependent dynamic characteristics of materials. In this study, the viscoelastic material is used in a Passive Constrained Layer Damping (PCLD) configuration in order to increase the shear deformation in the material. Mean Square Velocities (MSVs) of a clamped-free beam covered with a PCLD patch are measured in an environmental chamber at different frequencies and used as reference MSVs. The excitation force is performed thinks to a low mass magnet fixed on the beam and placed inside a coil subjected to an electrical current. Numerical MSVs are calculated using an equivalent single layer plate model with warping functions chosen to ensure continuity of transverse shear stresses and displacements layer's interfaces