Bimaximal Mixings from the Texture of the Right-handed Majorana Neutrino Mass Matrix

We study the origin of neutrino masses and mixing angles which can accomodate the LMA MSW solutions of the solar neutrino anomaly as well as the solution of the atmospheric neutrino problem, within the framework of the see-saw mechanism. We employ the diagonal form of the Dirac neutrino mass matrices with the physical masses as diagonal elements in the hierarchical order. Such choice has been motivated from the fact that the known CKM angles for the quark sector, are relatively small. We consider both possibilities where the Dirac neutrino mass matrix is either the charged lepton or the up-quark mass matrix within the framework of SO(10) GUT with or without supersymmetry. The non-zero texture of the right-handed Majorana neutrino mass matrix $M_{R}$ is used for the generation of the desired bimaximal mixings in a model independent way. Both hierarchical and inverted hierarchical models of the left-handed Majorana neutrino mass matrices are generated and then discussed with examples

Network Evolution Based on Centrality

We study the evolution of networks when the creation and decay of links are based on the position of nodes in the network measured by their centrality. We show that the same network dynamics arises under various centrality measures, and solve analytically the network evolution. During the complete evolution, the network is characterized by nestedness: the neighbourhood of a node is contained in the neighbourhood of the nodes with larger degree. We find a discontinuous transition in the network density between hierarchical and homogeneous networks, depending on the rate of link decay. We also show that this evolution mechanism leads to double power-law degree distributions, with interrelated exponents.Comment: 6 pages, 3 figure

Numerical consistency check between two approaches to radiative corrections for neutrino masses and mixings

We briefly outline the two popular approaches on radiative corrections to neutrino masses and mixing angles, and then carry out a detailed numerical analysis for a consistency check between them in MSSM. We find that the two approaches are nearly consistent with a small discrepancy of a factor of 13 percent in mass eigenvalues at low energy scale, but the predictions on mixing angles are almost consistent. We check the stability of the three types of neutrino models, i.e., hierarchical, inverted hierarchical and degenerate models, under radiative corrections, using both approaches, and find consistent conclusions. The neutrino mass models which are found to be stable under radiative corrections in MSSM are the normal hierarchical model and the inverted hierarchical model with opposite CP parity. We also carry out numerical analysis on some important conjectures related to radiative corrections in MSSM, viz., radiative magnification of solar and atmospheric mixings in case of nearly degenerate model having same CP parity (MPR conjecture) and radiative generation of solar mass scale in exactly two-fold degenerate model with opposite CP parity and non-zero reactor angle (JM conjecture). We observe certain exceptions to these conjectures. Finally the effect of scale-dependent vacuum expectation value in neutrino mass renormalisation is discussed.Comment: 26 pages, 5 figures,references added, typos corrected and text modifie

The NAD(P)H oxidase homolog Nox4 modulates insulin-stimulated generation of H\u3csub\u3e2\u3c/sub\u3e0\u3csub\u3e2\u3c/sub\u3e and plays an integral role in insulin signal transduction

Insulin stimulation of target cells elicits a burst of H2O2 that enhances tyrosine phosphorylation of the insulin receptor and its cellular substrate proteins as well as distal signaling events in the insulin action cascade. The molecular mechanism coupling the insulin receptor with the cellular oxidant-generating apparatus has not been elucidated. Using reverse transcription-PCR and Northern blot analyses, we found that Nox4, a homolog of gp91phox, the phagocytic NAD(P)H oxidase catalytic subunit, is prominently expressed in insulin-sensitive adipose cells. Adenovirus-mediated expression of Nox4 deletion constructs lacking NAD(P)H or FAD/NAD(P)H cofactor binding domains acted in a dominant-negative fashion in differentiated 3T3-L1 adipocytes and attenuated insulin-stimulated H2O2 generation, insulin receptor (IR) and IRS-1 tyrosine phosphorylation, activation of downstream serine kinases, and glucose uptake. Transfection of specific small interfering RNA oligonucleotides reduced Nox4 protein abundance and also inhibited the insulin signaling cascade. Overexpression of Nox4 also significantly reversed the inhibition of insulin-stimulated IR tyrosine phosphorylation induced by coexpression of PTP1B by inhibiting PTP1B catalytic activity. These data suggest that Nox4 provides a novel link between the IR and the generation of cellular reactive oxygen species that enhance insulin signal transduction, at least in part via the oxidative inhibition of cellular protein-tyrosine phosphatases (PTPases), including PTP1B, a PTPase that has been previously implicated in the regulation of insulin action

New Uncertainties in QCD-QED Rescaling Factors using Quadrature Method

In this paper we briefly outline the quadrature method for estimating uncertainties in a function of several variables and apply it to estimate the numerical uncertainties in QCD-QED rescaling factors. We employ here the one-loop order in QED and three-loop order in QCD evolution equations of fermion mass renormalization. Our present calculations are found to be new and also reliable compared to the earlier values employed by various authors.Comment: 14 page

Discriminating neutrino mass models using Type II seesaw formula

In this paper we propose a kind of natural selection which can discriminate the three possible neutrino mass models, namely the degenerate, inverted hierarchical and normal hierarchical models, using the framework of Type II seesaw formula. We arrive at a conclusion that the inverted hierarchical model appears to be most favourable whereas the normal hierarchical model follows next to it. The degenerate model is found to be most unfavourable. We use the hypothesis that those neutrino mass models in which Type I seesaw term dominates over the Type II left-handed Higgs triplet term are favoured to survive in nature.Comment: No change in the results, a few references added, some changes in Type[IIB] calculation

Optimizing IoT Protocol Coexistence and Security using Software Defined Network and Intelligent Machine Learning Detection

The rapid growth of heterogeneous IoT environments has made seamless communication across protocols like MQTT and CoAP increasingly difficult, leading to interoperability gaps, latency issues, and security vulnerabilities. This paper proposes a Software-Defined Networking (SDN)-based architecture that integrates MQTT and CoAP through a bidirectional translation layer, while embedding machine learning (ML) intelligence for real-time flag status monitoring and Denial-of-Service (DoS) attack detection. The system leverages classifiers such as SVM, DT, NB, RF, and KNN within the SDN controller to dynamically predict operational states and mitigate malicious traffic. To evaluate performance, a Mininet-based IoT testbed with 50 heterogeneous nodes was deployed. Simulation results demonstrate that the proposed system achieves up to 95% message delivery success, reduces average latency by 18% compared to baseline translation methods, and saves 12–15% residual energy when using SVM-based classification. While the system improves interoperability and security, it also introduces computational overheads at the SDN controller due to ML inference, which may impact CPU and memory utilization in resourceconstrained environments. The proposed solution is highly relevant for smart city, industrial IoT, and healthcare applications, where interoperability and real-time resilience against attacks are critical. By unifying heterogeneous devices and enhancing security, this approach provides a scalable and practical pathway for next-generation IoT networks

Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases.

Inflammatory bowel diseases, which include Crohn's disease and ulcerative colitis, affect several million individuals worldwide. Crohn's disease and ulcerative colitis are complex diseases that are heterogeneous at the clinical, immunological, molecular, genetic, and microbial levels. Individual contributing factors have been the focus of extensive research. As part of the Integrative Human Microbiome Project (HMP2 or iHMP), we followed 132 subjects for one year each to generate integrated longitudinal molecular profiles of host and microbial activity during disease (up to 24 time points each; in total 2,965 stool, biopsy, and blood specimens). Here we present the results, which provide a comprehensive view of functional dysbiosis in the gut microbiome during inflammatory bowel disease activity. We demonstrate a characteristic increase in facultative anaerobes at the expense of obligate anaerobes, as well as molecular disruptions in microbial transcription (for example, among clostridia), metabolite pools (acylcarnitines, bile acids, and short-chain fatty acids), and levels of antibodies in host serum. Periods of disease activity were also marked by increases in temporal variability, with characteristic taxonomic, functional, and biochemical shifts. Finally, integrative analysis identified microbial, biochemical, and host factors central to this dysregulation. The study's infrastructure resources, results, and data, which are available through the Inflammatory Bowel Disease Multi'omics Database ( http://ibdmdb.org ), provide the most comprehensive description to date of host and microbial activities in inflammatory bowel diseases