Modified Higgs couplings and unitarity violation

Prompted by the recent observation of a Higgs-like particle at the CERN Large Hadron Collider (LHC), we investigate a quantitative correlation between possible departures of the gauge and Yukawa couplings of this particle from their Standard Model expectations and the scale of unitarity violation in the processes $WW \to WW$ and $t\bar t \to WW$.Comment: 6 pages, 6 eps figures, Arrayeq.sty attached; v2: minor updates, version published: PRD 87 (2013) 011702(R), Rapid Communicatio

Scalar sector properties of two-Higgs-doublet models with a global U(1) symmetry

We analyze the scalar sector properties of a general class of two-Higgs-doublet models which has a global U(1) symmetry in the quartic terms. We find constraints on the parameters of the potential from the considerations of unitarity of scattering amplitudes, the global stability of the potential and the $\rho$-parameter. We concentrate on the spectrum of the non-standard scalar masses in the decoupling limit which is preferred by the Higgs data at the LHC. We exhibit charged-Higgs induced contributions to the diphoton decay width of the 125\,GeV Higgs boson and its correlation with the corresponding $Z\gamma$ width.Comment: 12 pages, 15 eps figure files; minor modifications made and a few references adde

New constraints on R-parity violation from proton stability

We derive stringent upper bounds on all the $(\lambda''_{ijk} \mu_l)$-type combinations from the consideration of proton stability, where $\lambda''_{ijk}$ are baryon-number-violating trilinear couplings and $\mu_l$ are lepton-number-violating bilinear mass parameters in a R-parity-violating supersymmetric theory.Comment: 4 pages, Latex, uses axodraw.sty (in the revised version all combinations of the form $\lambda"_{ijk}\mu_l$ have been constrained, using one-loop graphs) To appear in Phys. Lett.

SO(10) unification with horizontal symmetry

We extend the nonsupersymmetric SO(10) grand unification theories by adding a horizontal symmetry, which connects the three generations of fermions. Without committing to any specific symmetry group, we investigate the 1-loop renormalization group evolutions of the gauge couplings with one and two intermediate breaking scales. We find that depending on the SO(10) breaking chains, gauge coupling unification is compatible with only a handful of choices of representations of the Higgs bosons under the horizontal symmetry.Comment: 21 pages, 6 tables. v2: Further clarifications added primarily in Discussions Section, References updated, to be published in PR

Risk correlates of acute respiratory infections in children under five years of age in slums of Bankura, West Bengal

Background: Acute respiratory infections (ARI) are the leading cause of mortality and morbidity globally inchildren under five years of age. Objective: To find out prevalence and risk factors of ARI among under fivechildren. Methods: A population based analytical cross-sectional study was conducted in the urban slums ofBankura, West Bengal on the prevalence of ARI and feeding practices, nutrition and immunization among 152children under five years of age. Results: Overall prevalence of ARI was 44.73 percent; 43.47 percent male and45.78 percent female were affected with ARI; half of the infants suffered from ARI (51.21%), it was 45.71percent in 13- 24 months age groups; with increasing age, prevalence of ARI gradually decreased. ARI was seenin 45.76 percent of exclusively breast fed children and 57.89 percent in children with breast feeding less than sixmonths; in bottle fed children ARI prevalence was 47.82 compared to 44.18 percent in breast-fed. Risk of ARIis almost equal in normal participants and undernourished children. ARI cases were seen among 38.73 percentof completely immunization in comparison to 80.00 percent of partially-immunized children (X2=4.97,p=0.026). Conclusion: The present study had identified a high prevalence of ARI in children less than fiveyears of age. In our study population, ARI was significantly associated with immunization status, but not withfeeding practices and nutritional status of the child

Multimodal Approach for Big Data Analytics and Applications

The thesis presents multimodal conceptual frameworks and their applications in improving the robustness and the performance of big data analytics through cross-modal interaction or integration. A joint interpretation of several knowledge renderings such as stream, batch, linguistics, visuals and metadata creates a unified view that can provide a more accurate and holistic approach to data analytics compared to a single standalone knowledge base. Novel approaches in the thesis involve integrating multimodal framework with state-of-the-art computational models for big data, cloud computing, natural language processing, image processing, video processing, and contextual metadata. The integration of these disparate fields has the potential to improve computational tools and techniques dramatically. Thus, the contributions place multimodality at the forefront of big data analytics; the research aims at mapping and under- standing multimodal correspondence between different modalities. The primary contribution of the thesis is the Multimodal Analytics Framework (MAF), a collaborative ensemble framework for stream and batch processing along with cues from multiple input modalities like language, visuals and metadata to combine benefits from both low-latency and high-throughput. The framework is a five-step process: Data ingestion. As a first step towards Big Data analytics, a high velocity, fault-tolerant streaming data acquisition pipeline is proposed through a distributed big data setup, followed by mining and searching patterns in it while data is still in transit. The data ingestion methods are demonstrated using Hadoop ecosystem tools like Kafka and Flume as sample implementations. Decision making on the ingested data to use the best-fit tools and methods. In Big Data Analytics, the primary challenges often remain in processing heterogeneous data pools with a one-method-fits all approach. The research introduces a decision-making system to select the best-fit solutions for the incoming data stream. This is the second step towards building a data processing pipeline presented in the thesis. The decision-making system introduces a Fuzzy Graph-based method to provide real-time and offline decision-making. Lifelong incremental machine learning. In the third step, the thesis describes a Lifelong Learning model at the processing layer of the analytical pipeline, following the data acquisition and decision making at step two for downstream processing. Lifelong learning iteratively increments the training model using a proposed Multi-agent Lambda Architecture (MALA), a collaborative ensemble architecture between the stream and batch data. As part of the proposed MAF, MALA is one of the primary contributions of the research.The work introduces a general-purpose and comprehensive approach in hybrid learning of batch and stream processing to achieve lifelong learning objectives. Improving machine learning results through ensemble learning. As an extension of the Lifelong Learning model, the thesis proposes a boosting based Ensemble method as the fourth step of the framework, improving lifelong learning results by reducing the learning error in each iteration of a streaming window. The strategy is to incrementally boost the learning accuracy on each iterating mini-batch, enabling the model to accumulate knowledge faster. The base learners adapt more quickly in smaller intervals of a sliding window, improving the machine learning accuracy rate by countering the concept drift. Cross-modal integration between text, image, video and metadata for more comprehensive data coverage than a text-only dataset. The final contribution of this thesis is a new multimodal method where three different modalities: text, visuals (image and video) and metadata, are intertwined along with real-time and batch data for more comprehensive input data coverage than text-only data. The model is validated through a detailed case study on the contemporary and relevant topic of the COVID-19 pandemic. While the remainder of the thesis deals with text-only input, the COVID-19 dataset analyzes both textual and visual information in integration. Post completion of this research work, as an extension to the current framework, multimodal machine learning is investigated as a future research direction

Radiative neutrino decay and CP-violation in R-parity violating supersymmetry

We calculate the radiative decay amplitude for Majorana neutrinos in trilinear R-parity violating supersymmetric framework. Our results make no assumption regarding the masses and mixings of fermions and sfermions. The results obtained are exemplary for generic models with loop-generated neutrino masses. Comparison of this amplitude with the neutrino mass matrix shows that the two provide independent probes of CP-violating phases.Comment: Latex, uses axodraw, 14 pages (small changes implemented