Molecular-dynamics simulations of nickel clusters

Structural stability and energetics of nickel clusters, Nih (N = 3 - 459), have been inves tigated by molecular-dynamics simulations, A size-dependent empirical model potential energy function has been used in the simulations. Stable structures of the microclusters with sizes N = 3 - 55 and clusters generated from fee crystal structure with sizes N = 79 - 459 have been determined by molecular-dynamics simulations. It has been found that the fivefold symmetry appears on the surface of the spherical clusters. The average coordination number shows a size-dependent characteristic, on the other hand the average nearest-neighbor distance does not show a size-dependence

Personality perception of robot avatar tele-operators

© 2016 IEEE. Nowadays a significant part of human-human interaction takes place over distance. Tele-operated robot avatars, in which an operator's behaviours are portrayed by a robot proxy, have the potential to improve distance interaction, e.g., improving social presence and trust. However, having communication mediated by a robot changes the perception of the operator's appearance and behaviour, which have been shown to be used alongside vocal cues in judging personality. In this paper we present a study that investigates how robot mediation affects the way the personality of the operator is perceived. More specifically, we aim to investigate if judges of personality can be consistent in assessing personality traits, can agree with one another, can agree with operators' self-assessed personality, and shift their perceptions to incorporate characteristics associated with the robot's appearance. Our experiments show that (i) judges utilise robot appearance cues along with operator vocal cues to make their judgements, (ii) operators' arm gestures reproduced on the robot aid personality judgements, and (iii) how personality cues are perceived and evaluated through speech, gesture and robot appearance is highly operator-dependent. We discuss the implications of these results for both tele-operated and autonomous robots that aim to portray personality.This work was funded by the EPSRC under its IDEAS Factory Sandpits call on Digital Personhood (Grant Ref: EP/L00416X/1).This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/ 10.1109/HRI.2016.745174

Site-specific C-terminal and internal loop labeling of proteins using sortase-mediated reactions

Methods for site-specific modification of proteins should be quantitative and versatile with respect to the nature and size of the biological or chemical targets involved. They should require minimal modification of the target, and the underlying reactions should be completed in a reasonable amount of time under physiological conditions. Sortase-mediated transpeptidation reactions meet these criteria and are compatible with other labeling methods. Here we describe the expression and purification conditions for two sortase A enzymes that have different recognition sequences. We also provide a protocol that allows the functionalization of any given protein at its C terminus, or, for select proteins, at an internal site. The target protein is engineered with a sortase-recognition motif (LPXTG) at the place where modification is desired. Upon recognition, sortase cleaves the protein between the threonine and glycine residues, facilitating the attachment of an exogenously added oligoglycine peptide modified with the functional group of choice (e.g., fluorophore, biotin, protein or lipid). Expression and purification of sortase takes ∼3 d, and sortase-mediated reactions take only a few minutes, but reaction times can be extended to increase yields.National Institutes of Health (U.S.) (Grant RO1 AI08787

Computational identification of disease models through cross-species phenotype comparison.

The use of standardised phenotyping screens to identify abnormal phenotypes in mouse knockouts, together with the use of ontologies to describe such phenotypic features, allows the implementation of an automated and unbiased pipeline to identify new models of disease by performing phenotype comparisons across species. Using data from the International Mouse Phenotyping Consortium (IMPC), approximately half of mouse mutants are able to mimic, at least partially, the human ortholog disease phenotypes as computed by the PhenoDigm algorithm. We found the number of phenotypic abnormalities in the mouse and the corresponding Mendelian disorder, the pleiotropy and severity of the disease, and the viability and zygosity status of the mouse knockout to be associated with the ability of mouse models to recapitulate the human disorder. An analysis of the IMPC impact on disease gene discovery through a publication-tracking system revealed that the resource has been implicated in at least 109 validated rare disease-gene associations over the last decade

Signal and Noise Modeling of Microwave Transistors Using Characteristic Support Vector-based Sparse Regression

In this work, an accurate and reliable S- and Noise (N) - parameter black-box models for a microwave transistor are constructed based on the sparse regression using the Support Vector Regression Machine (SVRM) as a nonlinear extrapolator trained by the data measured at the typical bias currents belonging to only a single bias voltage in the middle region of the device operation domain of (VDS/VCE, IDS/IC, f). SVRMs are novel learning machines combining the convex optimization theory with the generalization and therefore they guarantee the global minimum and the sparse solution which can be expressed as a continuous function of the input variables using a subset of the training data so called Support Vector (SV)s. Thus magnitude and phase of each S- or N- parameter are expressed analytically valid in the wide range of device operation domain in terms of the Characteristic SVs obtained from the substantially reduced measured data. The proposed method is implemented successfully to modelling of the two LNA transistors ATF-551M4 and VMMK 1225 with their large operation domains and the comparative error-metric analysis is given in details with the counterpart method Generalized Regression Neural Network GRNN. It can be concluded that the Characteristic Support Vector based-sparse regression is an accurate and reliable method for the black-box signal and noise modelling of microwave transistors that extrapolates a reduced amount of training data consisting of the S- and N- data measured at the typical bias currents belonging to only a middle bias voltage in the form of continuous functions into the wide operation range

Severe renal bleeding caused by a ruptured renal sheath: case report of a rare complication of percutaneous nephrolithotomy

BACKGROUND: Percutaneous nephrolithotomy is a minimally invasive intervention for renal stone disease. Complications, which are rare and usually presented as case reports, are diversified as the utilization of the procedure is expanded. The procedure causes less blood loss and less morbidity when compared to open surgical procedures. Yet, there are some reports involving severe bleeding and relevant morbidity during surgery. These are usually related with the surgical technique or experience of the surgeon. Renal sheaths are designed to cause minimal trauma inside the kidney and, to our knowledge, there are no reports presenting the rupture of a sheath causing severe bleeding during the procedure. CASE REPORT: We present an adult patient who had severe bleeding during percutaneous nephrolithotomy due to parenchymal injury caused by a ruptured renal sheath. During retrieval, due probably to rough handling of the equipment, a piece of stone with serrated edges ruptured the tip of the sheath, and this tip caused damage inside the kidney. The operation was terminated and measures were taken to control bleeding. The patient was transfused with a total of 1600 ml of blood, and the stones were cleared in a second look operation. CONCLUSION: Although considered to be a minimally invasive procedure, some unexpected complications may arise during percutaneous nephrolithotomy. After being fragmanted, stone pieces may damage surgical equipment, causing acute and severe harm to the kidney. Surgeons must manipulate the equipment with fine and careful movements in order to prevent this situation

Automatic detection of a driver’s complex mental states

Automatic classification of drivers’ mental states is an important yet relatively unexplored topic. In this paper, we define a taxonomy of a set of complex mental states that are relevant to driving, namely: Happy, Bothered, Concentrated and Confused. We present our video segmentation and annotation methodology of a spontaneous dataset of natural driving videos from 10 different drivers. We also present our real-time annotation tool used for labelling the dataset via an emotion perception experiment and discuss the challenges faced in obtaining the ground truth labels. Finally, we present a methodology for automatic classification of drivers’ mental states. We compare SVM models trained on our dataset with an existing nearest neighbour model pre-trained on posed dataset, using facial Action Units as input features. We demonstrate that our temporal SVM approach yields better results. The dataset’s extracted features and validated emotion labels, together with the annotation tool, will be made available to the research community

Effect of arsenic-phosphorus interaction on arsenic-induced oxidative stress in chickpea plants

Arsenic-induced oxidative stress in chickpea was investigated under glasshouse conditions in response to application of arsenic and phosphorus. Three levels of arsenic (0, 30 and 60 mg kg−1) and four levels of P (50, 100, 200, and 400 mg kg−1) were applied to soil-grown plants. Increasing levels of both arsenic and P significantly increased arsenic concentrations in the plants. Shoot growth was reduced with increased arsenic supply regardless of applied P levels. Applied arsenic induced oxidative stress in the plants, and the concentrations of H2O2 and lipid peroxidation were increased. Activity of superoxide dismutase (SOD) and concentrations of non-enzymatic antioxidants decreased in these plants, but activities of catalase (CAT) and ascorbate peroxidase (APX) were significantly increased under arsenic phytotoxicity. Increased supply of P decreased activities of CAT and APX, and decreased concentrations of non-enzymatic antioxidants, but the high-P plants had lowered lipid peroxidation. It can be concluded that P increased uptake of arsenic from the soil, probably by making it more available, but although plant growth was inhibited by arsenic the P may have partially protected the membranes from arsenic-induced oxidative stress

The analysis of facial beauty: an emerging area of research in pattern analysis

Much research presented recently supports the idea that the human perception of attractiveness is data-driven and largely irrespective of the perceiver. This suggests using pattern analysis techniques for beauty analysis. Several scientific papers on this subject are appearing in image processing, computer vision and pattern analysis contexts, or use techniques of these areas. In this paper, we will survey the recent studies on automatic analysis of facial beauty, and discuss research lines and practical application

GaInNAs-based Hellish-vertical cavity semiconductor optical amplifier for 1.3 μm operation

Hot electron light emission and lasing in semiconductor heterostructure (Hellish) devices are surface emitters the operation of which is based on the longitudinal injection of electrons and holes in the active region. These devices can be designed to be used as vertical cavity surface emitting laser or, as in this study, as a vertical cavity semiconductor optical amplifier (VCSOA). This study investigates the prospects for a Hellish VCSOA based on GaInNAs/GaAs material for operation in the 1.3-μm wavelength range. Hellish VCSOAs have increased functionality, and use undoped distributed Bragg reflectors; and this coupled with direct injection into the active region is expected to yield improvements in the gain and bandwidth. The design of the Hellish VCSOA is based on the transfer matrix method and the optical field distribution within the structure, where the determination of the position of quantum wells is crucial. A full assessment of Hellish VCSOAs has been performed in a device with eleven layers of Ga0.35In0.65N0.02As0.08/GaAs quantum wells (QWs) in the active region. It was characterised through I-V, L-V and by spectral photoluminescence, electroluminescence and electro-photoluminescence as a function of temperature and applied bias. Cavity resonance and gain peak curves have been calculated at different temperatures. Good agreement between experimental and theoretical results has been obtained