3,447 research outputs found
Higgs boson decays into {\gamma}{\gamma} and Z{\gamma} in the MSSM and BLSSM
We calculate Higgs decay rates into {\gamma}{\gamma} and Z{\gamma} in the
Minimal Supersymmetric Standard Model (MSSM) and (B-L) Supersymmetric Standard
Model (BLSSM) by allowing for contributions from light staus and charginos. We
show that sizable departures are possible from the SM predictions for the 125
GeV state and that they are testable during run 2 at the Large Hadron Collider.
Furthermore, we illustrate how a second light scalar Higgs signal in either or
both these decay modes can be accessed at the CERN machine rather promptly
within the BLSSM, a possibility instead precluded to the MSSM owing to the much
larger mass of its heavy scalar state.Comment: Plots slightly modified, no significant chang
The Compliance Chronic Renal Failure Patient on Restrictions Liquids in Hemodialysis Therapy
Introduction: Nonadherence is a rampant problem among patients undergoing dialysis and can impact multiple aspects of patient care, including medications, and treatment regimens as well as dietary and fluid restriction. The purpose of this descriptive correlative research, on hemodyalysa patient with chronic renal failure was to know the influencing factors of compliance patient to fluid restriction. Method: This study used descriptive correlative design, Data was analysed by using distibution frequency and chi square for analysys relation between variable. Result: The result revealed there were nor significant statistic difference at p > 0.05 between age, gender, education level, frequency of hemodyalysa and health education from nurse to compliance patient to fluid restriction (p = 0.647; p = 0.717; p = 0.345; p = 0.774; p = 0.273). Discussion: Level of patient adherence to therapy not influenced by demographi factor but by the quality of interaction health workers and other factors. This study recommended for further analysis of the factors that influence the level of compliance of the patient as psychological factors (belieft , motivation), socio-economic, and social support
Search for Mono-Higgs Signals in Final States Using Deep Neural Networks
We study mono-Higgs signatures emerging in an illustrative new physics
scenario involving Standard Model Higgs boson decays to bottom quark pairs
using Hybrid Deep Neural Networks. We use a Multi-Layer Perceptron to analyze
the kinematic observables and optimize the signal-to-background discrimination.
The global color flow structure of hard jets emerging from the decay of heavy
particles with different color charges is crucial to single out the mono-Higgs
signature. Upon embedding the different color flow structures for signal and
backgrounds into constructed images, we use a Convolution Neural Network to
analyze the latter. Specifically, the approach takes initially a mono-type data
as input, frittering away invaluable multi-source and multi-scale information.
We then discuss a general architecture of Hybrid Deep Neural Networks that
supports instead mixed input data. In comparison with single input Deep Neural
Networks, like MultiLayers Perceptron or Convolution Neural Network, the Hybrid
Deep Neural Networks provide higher capacity in feature extraction and thus in
signal vs background classification performance. We provide reference results
for the case of the High-Luminosity Large Hadron Collider.Comment: published versio
Titanium Dioxide Modifications for Energy Conversion: Learnings from Dye-Sensitized Solar Cells
During the last two and half decade modifying anatase TiO2 has appreciably enhanced our understanding and application of this semiconducting, non-toxic material. In the domain of DSCs, the main focus has been to achieve band adjustment to facilitate electron injection from anchored dyes, and high electronic mobility for photo-generated electron collection. In retrospection, there is a dire need to assimilate and summarize the findings of these studies to further catalyze the research, better understanding and comparison of the structure–property relationships in modifying TiO2 efficiently for crucial photocatalytic, electrochemical and nanostructured applications. This chapter aims at categorizing the typical approaches used to modify TiO2 in the domain of DSCs such as through TiO2 paste additives, TiO2 doping, metal oxides inclusion, dye solution co-adsorbing additives, post staining surface treatment additives and electrolyte additives. A summary of the consequences of these modifications on electron injection, charge extraction, electronic mobility, conduction band shift and surface states has been presented. This chapter is expected to hugely benefit the researchers employing TiO2 in energy, catalysis and battery applications
Mapping SysML to modelica to validate wireless sensor networks non-functional requirements
International audienceWireless Sensor Networks (WSN) have registered a large success in the scientific and industrial communities for their broad application domains. Furthermore, the WSN specification is a complex task considering to their distributed and embedded nature and the strong interactions between their hardware and software parts. Moreover, most of approaches use semi-formal methods to design systems and generally simulation to validate their properties in order to produce models without errors and conform to the system specifications. In this context, we propose a Model Driven Architecture (MDA) approach to improve the verification of the WSN properties. This approach combines the advantages of the System Modeling Language (SysML) and the Modelica language which promote the reusability and improve the development process. In this work, we specify a model transformation from SysML static, dynamic and requirement diagrams to their corresponding elements in Modelica. Thanks to the SysML requirement diagram which is transformed into Modelica properties (constraints), we propose a technique using dynamic tests to verify WSN properties. We have used the Topcased platform to implement our approach 1 and chosen a crossroads monitoring system which is based on wireless sensors to illustrate it. Besides, we have verified and validated some wireless sensors properties of the studied system
Sharpening the Signature of the Type-II 2HDM at the LHC through Advanced Machine Learning
The decay signature has been highlighted as possibly being
the first testable probe of the Standard Model (SM) Higgs boson discovered in
2012 () interacting with Higgs companion states, such as those existing in a
2-Higgs Doublet Model (2HDM), chiefly, a CP-odd one (). The production
mechanism of the latter at the Large Hadron Collider (LHC) takes place via
-annihilation and/or -fusion, depending on the 2HDM parameters, in
turn dictated by the Yukawa structure of this Beyond the SM (BSM) scenario.
Among the possible incarnations of the 2HDM, we test here the so-called
Type-II, for a twofold reason. On the one hand, it intriguingly offers two very
distinct parameter regions compliant with the SM-like Higgs measurements, i.e.,
where the so-called `SM limit' of the 2HDM can be achieved. On the other hand,
in both configurations, the coupling is generally small, hence the signal
is strongly polluted by backgrounds, so that the exploitation of Machine
Learning (ML) techniques becomes extremely useful. In this paper, we show that
the application of advanced ML implementations can be decisive in establishing
such a signal.
This is true for all distinctive kinematical configurations involving the
decay, i.e., below threshold (), at its maximum
() and near the onset of pair production (), for which we propose Benchmark Points (BPs) for future
phenomenological analyses.Comment: JHEP accepted version., 33 pages, 15 figures, 2 table
Acinetobacterlwoffii Induced Cellulitis with Allergy-like Symptoms
Few reports document the misdiagnosis of Acinetobacterlwoffii skin infections for allergic reactions. In addition, A. lwoffii is
frequently misidentified when applying conventional diagnostic methods. The bacterium has been reported to cause a multitude
of diseases including skin and wound infections. The application of the newly established method “The Universal Method”
allowed definite identification of the bacterium isolated from a leg and foot cellulitis case (Isolate QUBC mk1) that was
misdiagnosed as an allergic reaction and was treated with intramuscular injections of diclofeneac sodium, anonsteroidal antiinflammatory
drug.The isolate was identified as A. lwoffii, it failed to grow on MacConkey agar, and it was sensitive to
ciprofloxacin but resistant to cefazolin. The 51-year old male patient was successfully treated with intravenous administration of
ciprofloxacin, doxacillin, and cefazolin. He was released in good health after ten days.This work emphasizes the importance of
distinguishing between skin infections and allergies. It also stresses the importance of prompt and accurate identification of A.
Lwoffii and its possible relationship to allergic reactions. Misdiagnosis isdiscussed in the context of “The Hygiene Hypothesis”
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