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 bbˉb\bar b 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 A→Z(∗)hA\to Z^{(*)}h Signature of the Type-II 2HDM at the LHC through Advanced Machine Learning

The $A\to Z^{(*)}h$ decay signature has been highlighted as possibly being the first testable probe of the Standard Model (SM) Higgs boson discovered in 2012 ($h$) interacting with Higgs companion states, such as those existing in a 2-Higgs Doublet Model (2HDM), chiefly, a CP-odd one ($A$). The production mechanism of the latter at the Large Hadron Collider (LHC) takes place via $b\bar b$-annihilation and/or $gg$-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 $AZh$ 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 $A\to Z^{(*)}h$ decay, i.e., below threshold ($m_A<m_Z+m_h$), at its maximum ($m_Z+m_h<m_A<2m_t$) and near the onset of $t\bar t$ pair production ($m_A \approx 2m_t$), for which we propose Benchmark Points (BPs) for future phenomenological analyses.Comment: JHEP accepted version., 33 pages, 15 figures, 2 table

Reflections on the potential (and limits) of action research as ethos, methodology and practice: A case study of a women's empowerment programme in the Middle East

This paper argues that an evidence-based approach to advocacy led by and targeting women could amplify women's positioning in the political and economic realms. Participatory Action Research is examined as a process for mobilisation, coalition-building and evidence-based advocacy and action, through a case study of a multi-country British Council supported programme that incorporated an action research approach.1 Drawing from the experiences and perceptions of its participants, it offers reflective insights into the theory and practice of action research and its empowerment potential. The findings confirm a widespread support for the use of Participatory Action Research as a starting point for stronger advocacy work, showing its positive transformative effects on individuals, groups and coalition. Participatory Action Research contributes to evidence-based advocacy that is more relevant and inclusive, and arguably empowering for women advocates.Practitioners learned by doing with coaching support from INTRAC both virtual and face-to-face, while the British Council coordinated and supported the country teams. This included country-based as well as regional training and mentoring sessions across all stages of the research and advocacy.Scopu