Influence of phase transformations on the mechanical properties of high-strength austenitic Fe-Mn-Cr steel

The influence of Cr and N additions on the mechanical properties of a Fe-Mn-C steel was investigated. The chemical composition was found to have a pronounced effect on the strain-hardening behavior, due to the strain-induced sequence of the γ → ▓ → α′ martensitic transformations. It was found that Cr and N suppress this transformation sequence. At Cr levels higher than 7.5 mass pct, no α′ martensite was formed, which led to a pronounced improvement of the ductility. The differences in transformation behavior can be attributed to the change in the intrinsic stacking-facult energy (ISFE): in the compositional range studied, Cr and N additions cause an increase of the ISFE.     

Variability of operator performance in remote-sensing image interpretation: the importance of human and external factors

This study tackles a common, yet underrated problem in remote-sensing image analysis: the fact that human interpretation is highly variable among different operators. Despite current technological advancements, human perception and interpretation are still vital components of the map-making process. Consequently, human errors can considerably bias both mapping and modelling results. In our study, we present a web-based tool to quantify operator variability and to identify the human and external factors affecting this variability. Human operators were given a series of images and were asked to hand-digitize different point, line, and polygon objects. The quantification of performance variability was achieved using both thematic and positional accuracy measures. Subsequently, a series of questions related to demographics, experience, and personality were asked, and the answers were also quantified. Correlation and regression analysis was then used to explain the variability in operator performance. From our study, we conclude that: (1) humans were seldom perfect in visual interpretation; (2) some geographic objects were more complex to accurately digitize than others; (3) there was a high degree of variability among image interpreters when hand-digitizing the same objects; and (4) operator performance was mainly determined by demographic, non-cognitive, and cognitive personality factors, whereas external and technical factors influenced operator performance to a lesser extent. Finally, the results also indicated a gradual decline in performance over time, mimicking classical mental fatigue effects.     

Normal State Resistivity of Underdoped YBa2Cu3Ox Thin Films and La2-xSrxCuO4 Ultra-Thin Films under Epitaxial Strain

The normal state resistivity of high temperature superconductors can be probed in the region below T _c by suppressing the superconducting state in high magnetic fields. Here we present the normal state properties of YBa ₂ Cu ₃ O _x thin films in the underdoped regime and the normal state resistance of La _2-x Sr _x CuO ₄ thin films under epitaxial strain, measured below T _c by applying pulsed fields up to 60 T. We interpret these data in terms of the recently proposed 1D quantum transport model with the 1D paths corresponding to the charge stripes.     

Learning with tensors: a framework based on convex optimization and spectral regularization

We present a framework based on convex optimization and spectral regularization to perform learning when feature observations are multidimensional arrays (tensors). We give a mathematical characterization of spectral penalties for tensors and analyze a unifying class of convex optimization problems for which we present a provably convergent and scalable template algorithm. We then specialize this class of problems to perform learning both in a transductive as well as in an inductive setting. In the transductive case one has an input data tensor with missing features and, possibly, a partially observed matrix of labels. The goal is to both infer the missing input features as well as predict the missing labels. For induction, the goal is to determine a model for each learning task to be used for out of sample prediction. Each training pair consists of a multidimensional array and a set of labels each of which corresponding to related but distinct tasks. In either case the proposed technique exploits precise low multilinear rank assumptions over unknown multidimensional arrays; regularization is based on composite spectral penalties and connects to the concept of Multilinear Singular Value Decomposition. As a by-product of using a tensor-based formalism, our approach allows one to tackle the multi-task case in a natural way. Empirical studies demonstrate the merits of the proposed methods.     

Doped CuO 2 Planes in High T c Cuprates: 2D Or Not 2D ?

The key problem in physics of underdoped cuprates is whether the doping is inhomogeneous and holes are expelled into the 1D domains (stripes). Direct comparison of the resistivity vs T curves of the recently discovered 1D spin-ladder cuprates and underdoped cuprates below the pseudogap temperature T* shows a remarkable similarity which implies that the main scattering mechanism is the same for these two classes of cuprates and therefore in the pseudogap regime the transport in underdoped cuprates is essentially 1D. All the resistivity curves in underdoped cuprates can then be fitted by the model of the 1D quantum transport with the inelastic length in charge stripes being fully controlled by the magnetic spin correlation length in even-chain spin-ladders formed in the Cu-O plane as a result of inhomogeneous doping. Knight shift data are also successfully interpreted by taking the same spin-gap value as the one found from resistivity data.     

Access to premium content on mobile television platforms: The case of mobile sports

As broadcasting sports content has proved to be a popular strategy for driving the growth of the digital premium content marketplace in the past, mobile service operators aim to enter the sports rights market. However, as the markets for live sports broadcasting are still dominated by established broadcasters, mobile network operators are facing significant barriers to access premium content creating bottlenecks in the construction of business models. Therefore, content regulation is seen as essential for the development of mobile television platforms. This article aims to stress the strategic importance of content in the development of sustainable business models for mobile broadcasting services and will discuss the implications of bundling strategies and regulations for the viability of these emerging platforms.     

Lattice expansion in seamless bilayer graphene constrictions at high bias

Our understanding of sp(2) carbon nanostructures is still emerging and is important for the development of high performance all carbon devices. For example, in terms of the structural behavior of graphene or bilayer graphene at high bias, little to nothing is known. To this end, we investigated bilayer graphene constrictions with closed edges (seamless) at high bias using in situ atomic resolution transmission electron microscopy. We directly observe a highly localized anomalously large lattice expansion inside the constriction. Both the current density and lattice expansion increase as the bilayer graphene constriction narrows. As the constriction width decreases below 10 nm, shortly before failure, the current density rises to 4 × 10(9) A cm(-2) and the constriction exhibits a lattice expansion with a uniaxial component showing an expansion approaching 5% and an isotropic component showing an expansion exceeding 1%. The origin of the lattice expansion is hard to fully ascribe to thermal expansion. Impact ionization is a process in which charge carriers transfer from bonding states to antibonding states, thus weakening bonds. The altered character of C-C bonds by impact ionization could explain the anomalously large lattice expansion we observe in seamless bilayer graphene constrictions. Moreover, impact ionization might also contribute to the observed anisotropy in the lattice expansion, although strain is probably the predominant factor.     

Frequency response function shape-based methods for structural damage localisation

The ultilisation of structural shape signals for damage localisation has shown some promise, especially in the applications where an accurate finite element model of the structure is not available. For this purpose, traditional shape signals, like mode shapes, flexibility matrices, uniform load surface (ULS) and operational deflection shapes (ODS) have been widely used. Using frequency response function (FRF) shapes for structural damage localisation is however, a relatively new but promising technique. Unlike mode shapes, ULS and ODS, FRF shapes are defined on broadband data and so have potential to reveal damage location more clearly. Another advantage of using FRF shapes is that the test data can be directly used without the necessity of conducting modal identification. Nevertheless, some problems associated with this approach still remain to be solved. No solid foundation or deduction about the use of FRF shapes for damage localisation has been given in any literature so far. In addition, it has been observed that this method only works for a low-frequency range. This limitation of FRF shapes has not been explained or well treated so far. In this study, a scheme of using FRF shapes for structural damage localisation is proposed. Methods within this scheme include some important modifications like using the imaginary parts of FRF shapes and normalising FRF shapes before comparison. The theoretical explanation of using FRF shapes for damage localisation is presented and the limitations of the previous FRF shape methods have been overcome. The proposed methods have shown great potential in structural damage localisation.     

Occurrence and distribution of Arcobacter species in poultry processing

A total of 16 broiler flocks slaughtered in the morning in eight Belgian poultry slaughterhouses were examined for the presence of Campylobacteraceae. In samples collected before and after chilling, the prevalence of arcobacters was found to be higher than the prevalence of thermophilic campylobacters, with the slaughter procedure used having no clear effect. Two slaughterhouses were selected for a detailed investigation of the occurrence and distribution of arcobacters. Sampling carried out before slaughter revealed that both Arcobacter butzleri and Arcobacter cryaerophilus were commonly present on the slaughter equipment in both plants. These findings indicate inadequate decontamination of the slaughterhouse environment and suggest potential Arcobacter contamination of broiler carcasses through the slaughter equipment. Even before evisceration, contamination levels of hundreds to several thousands of arcobacters per gram of neck skin were detected. It appears unlikely that contamination through slaughter equipment alone explains the high contamination levels found for poultry products. Arcobacters were not isolated from the 30 intestinal tracts sampled for each broiler flock examined. A. cryaerophilus was the only Arcobacter species recovered from the transport crate samples collected before and after washing. Arcobacter contamination during slaughter, either direct (from chicken intestinal content or feces) or indirect (from equipment), was not confirmed. The origin and the precise routes of contamination remain to be determined.     

Preliminary experience with a new double-echo half-Fourier single-shot turbo spin echo acquisition in the characterization of liver lesions

A new double-echo half-Fourier single-shot turbo spin echo technique has been implemented in which two images are obtained per excitation pulse, one with an echo time (TE) of 60 ms and another with a TE of 438 ms. The acquisition window per image is 380 ms and is determined by the echo spacing of 4.3 ms and the echo train length of 88 for images with resolution of 160×256. No breath holding was performed. The aim of the study was to test whether the additional information of the late TE image improves the characterization of liver lesions. Twenty-eight patients with 39 focal liver lesions (9 cysts, 11 hemangiomas, and 19 solid lesions) were imaged with the new technique, and signal intensity (SI) ratios of lesion and liver were obtained. At-test analysis showed that in the TE 60 ms image, SI ratios of cysts and hemangiomas were not significantly different, whereas in the TE 438 ms images the two types of lesions can be classified. Signal intensity ratios of solid lesions were in both images clearly lower than those of cysts and hemangiomas. The technique, therefore, seems a promising and straightforward new tool for the characterization of liver lesions.