Automatised full one-loop renormalisation of the MSSM I: The Higgs sector, the issue of tan(beta) and gauge invariance

We give an extensive description of the renormalisation of the Higgs sector of the minimal supersymmetric model in SloopS. SloopS is an automatised code for the computation of one-loop processes in the MSSM. In this paper, the first in a series, we study in detail the non gauge invariance of some definitions of tan(beta). We rely on a general non-linear gauge fixing constraint to make the gauge parameter dependence of different schemes for tan(beta) at one-loop explicit. In so doing, we update, within these general gauges, an important Ward-Slavnov-Taylor identity on the mixing between the pseudo-scalar Higgs, A^0, and the Z^0. We then compare the tan(beta) scheme dependence of a few observables. We find that the best tan(beta) scheme is the one based on the decay A^0 -> tau^+ tau^- because of its gauge invariance, being unambiguously defined from a physical observable, and because it is numerically stable. The oft used DRbar scheme performs almost as well on the last count, but is usually defined from non-gauge invariant quantities in the Higgs sector. The use of the heavier scalar Higgs mass in lieu of tan(beta) though related to a physical parameter induces too large radiative corrections in many instances and is therefore not recommended.Comment: 34 pages, 1 figure, typos corrected, accepted for publication in Phys. Rev.

Loop-induced photon spectral lines from neutralino annihilation in the NMSSM

We have computed the loop-induced processes of neutralino annihilation into two photons and, for the first time, into a photon and a Z boson in the framework of the NMSSM. The photons produced from these radiative modes are monochromatic and possess a clear "smoking gun" experimental signature. This numerical analysis has been done with the help of the SloopS code, initially developed for automatic one-loop calculation in the MSSM. We have computed the rates for different benchmark points coming from SUGRA and GMSB soft SUSY breaking scenarios and compared them with the MSSM. We comment on how this signal can be enhanced, with respect to the MSSM, especially in the low mass region of the neutralino. We also discuss the possibility of this observable to constrain the NMSSM parameter space, taking into account the latest limits from the FERMI collaboration on these two modes.Comment: 18 pages, 3 figures. Minor clarifications added in the text. Typing mistakes and references corrected. Matches published versio

Organizational and Informational System Factors in Post-Merger Technology Integration

Many corporate mergers fail to achieve their intended objectives. The literature indicates that slow post-merger integrations are partly responsible for such failure and highlights that a successful post-merger integration is essential to a successful merger. Recognizing the fact that information systems (IS) integration is important for effective merger performance and that few IS and merger research has addressed this area, the objective of this article is to focus on organizational and information systems factors that affect post-merger IS integration performance with the eventual aim of identifying ways in which to manage the significant factors post-merger. This research is timely and relevant and will contribute to the body of research that facilitates the understanding and management of merger effectiveness and its associated processes

Experimental Evaluation of Psychophysical Distortion Metrics for JPEG-Encoded Images

Two experiments for evaluating psychophysical distortion metrics for JPEG-encoded images are described. The first is a threshold experiment, in which subjects determined the bit rate or level of distortion at which distortion was just noticeable. The second is a suprathreshold experiment in which subjects ranked image blocks according to perceived distortion. The results of these experiments were used to determine the predictive value of a number of computer image distortion metrics. It was found that mean-square-error is not a good predictor of distortion thresholds or suprathreshold perceived distortion. Some simple pointwise measures were in good agreement with psychophysical data; other more computationally intensive metrics involving spatial properties of the human visual system gave mixed results. It was determined that mean intensity, which is not accounted for in the JPEG algorithm, plays a significant role in perceived distortion

A Novel Detection Refinement Technique for Accurate Identification of Nephrops norvegicus Burrows in Underwater Imagery

With the evolution of the convolutional neural network (CNN), object detection in the underwater environment has gained a lot of attention. However, due to the complex nature of the underwater environment, generic CNN-based object detectors still face challenges in underwater object detection. These challenges include image blurring, texture distortion, color shift, and scale variation, which result in low precision and recall rates. To tackle this challenge, we propose a detection refinement algorithm based on spatial–temporal analysis to improve the performance of generic detectors by suppressing the false positives and recovering the missed detections in underwater videos. In the proposed work, we use state-of-the-art deep neural networks such as Inception, ResNet50, and ResNet101 to automatically classify and detect the Norway lobster Nephrops norvegicus burrows from underwater videos. Nephrops is one of the most important commercial species in Northeast Atlantic waters, and it lives in burrow systems that it builds itself on muddy bottoms. To evaluate the performance of proposed framework, we collected the data from the Gulf of Cadiz. From experiment results, we demonstrate that the proposed framework effectively suppresses false positives and recovers missed detections obtained from generic detectors. The mean average precision (mAP) gained a 10% increase with the proposed refinement technique.Versión del edito

Automatic Detection of Nephrops norvegicus Burrows in Underwater Images Using Deep Learning

Autonomous Underwater Vehicles and Remotely Operated Vehicles equipped with HD cameras are used by the scientist to capture the underwater footages efficiently and accurately. The abundance of the Norway Lobster Nephrops norvegicus stock in the Gulf of Cadiz is assessed based on the identification and counting of the burrows where they live, using underwater videos. The Instituto Espa˜ nol de Oceanograf´ıa (IEO) conducts an annual standard underwater television survey (UWTV) to generate burrow density estimates of Nephrops within a defined area, with a coefficient of variation (CV) or relative standard error of less than 20%. Currently, the identification and counting of the Nephrops burrows are carried out manually by the experts. This is quite hectic and time consuming job. Computer Vision and Deep learning plays a vital role now a days in detection and classification of objects. The proposed system introduces a deep learning based automated way to identify and classify the Nephrops burrows. The proposed work is using current state of the art Faster RCNN models Inception v2 and MobileNet v2 for objects detection and classification. Tensorflow is used to evaluate the Inception and MobileNet performance with different numbers of training images. The average mean precision of Inception is more than 75% as compared to MobileNet which is 64%. The results show the comparison of Inception and MobileNet detections, as well as the calculation of True Positive and False Positive detections along with undetected burrows.Universidad de Málaga, IEEE, Sir SYED University Karachi-Pakistán, Mehran University Jamshoro-Pakistán, Riphah International Universit

Automatic Detection of Nephrops Norvegicus Burrows from Underwater Imagery Using Deep Learning

The Norway lobster, Nephrops norvegicus, is one of the main commercial crustacean fisheries in Europe. The abundance of Nephrops norvegicus stocks is assessed based on identifying and counting the burrows where they live from underwater videos collected by camera systems mounted on sledges. The Spanish Oceanographic Institute (IEO) andMarine Institute Ireland (MIIreland) conducts annual underwater television surveys (UWTV) to estimate the total abundance of Nephrops within the specified area, with a coefficient of variation (CV) or relative standard error of less than 20%. Currently, the identification and counting of the Nephrops burrows are carried out manually by the marine experts. This is quite a time-consuming job. As a solution, we propose an automated system based on deep neural networks that automatically detects and counts the Nephrops burrows in video footage with high precision. The proposed system introduces a deep-learning-based automated way to identify and classify the Nephrops burrows. This research work uses the current state-of-the-art Faster RCNN models Inceptionv2 and MobileNetv2 for object detection and classification. We conduct experiments on two data sets, namely, the Smalls Nephrops survey (FU 22) and Cadiz Nephrops survey (FU 30), collected by Marine Institute Ireland and Spanish Oceanographic Institute, respectively. From the results, we observe that the Inception model achieved a higher precision and recall rate than theMobileNetmodel. The best mean Average Precision (mAP) recorded by the Inception model is 81.61% compared toMobileNet, which achieves the best mAP of 75.12%.Versión del edito

The evaluation of surface diffusion coefficients of gold and platinum atoms at electrochemical interfaces from combined STM-SEM imaging and electrochemical techniques

A simple method is presented for measuring the surface diffusion coefficients of Au and Pt atoms at electrodispersed electrodes of the same metals in contact with 0.5M H2SO4. The technique is based upon the time dependence of the surface roughness factor of electrodispersed metal overlayers. The method requires a model for the surface roughness of the metal structure. The model is deduced from microscopic measurements by a STM integrated into a conventional SEM microscope. This allows the relationship between the roughness factor and the area of the surface structure to be obtained. For Au and Pt in contact with an electrolyte solution, the values of our diffusion coefficients are higher than those reported in vacuum at the same temperature.Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA)Facultad de Ciencias Exacta

Samarium iodide-promoted asymmetric Reformatsky reaction of 3-(2-Haloacyl)-2-oxazolidinones with enals

3-(2-Haloacyl)-2-oxazolidinones were shown to react with enals in an asymmetric SmI2-promoted Reformatsky reaction to give stereochemically well-defined 3-hydroxy-4-alkenyl- and 3-hydroxy-2-methyl-4-alkenyl imides. Chirality transfer of the Evans (S)-oxazolidinone unit via a Zimmerman-Traxler-like transition state resulted in Reformatsky products with a relative syn-configuration. The absolute configuration of compounds obtained is opposite to the corresponding products obtained via aldol addition of boron enolates to enals using the same Evans oxazolidinones