Inflation in minimal left-right symmetric model with spontaneous D-parity breaking

We present a simplest inflationary scenario in the minimal left-right symmetric model with spontaneous D-parity breaking, which is a well motivated particle physics model for neutrino masses. This leads us to connect the observed anisotropies in the cosmic microwave background to the sub-eV neutrino masses. The baryon asymmetry via the leptogenesis route is also discussed briefly.Comment: (v1) 4 pages, 1 figure; (v2) typos corrected; (v3) title and abstract changed, numerical estimates given, minor changes; (v4) 5 pages, relations between the neutrino masses and the CMB fluctuations become more explicit, miscellaneous changes, to appear in Physical Review

Studies on atmospheric gravity wave activity in the troposphere and lower stratosphere over a tropical station at Gadanki

MST radars are powerful tools to study the mesosphere, stratosphere and troposphere and have made considerable contributions to the studies of the dynamics of the upper, middle and lower atmosphere. Atmospheric gravity waves play a significant role in controlling middle and upper atmospheric dynamics. To date, frontal systems, convection, wind shear and topography have been thought to be the sources of gravity waves in the troposphere. All these studies pointed out that it is very essential to understand the generation, propagation and climatology of gravity waves. In this regard, several campaigns using Indian MST Radar observations have been carried out to explore the gravity wave activity over Gadanki in the troposphere and the lower stratosphere. The signatures of the gravity waves in the wind fields have been studied in four seasons viz., summer, monsoon, post-monsoon and winter. The large wind fluctuations were more prominent above 10 km during the summer and monsoon seasons. The wave periods are ranging from 10 min-175 min. The power spectral densities of gravity waves are found to be maximum in the stratospheric region. The vertical wavelength and the propagation direction of gravity waves were determined using hodograph analysis. The results show both down ward and upward propagating waves with a maximum vertical wave length of 3.3 km. The gravity wave associated momentum fluxes show that long period gravity waves carry more momentum flux than the short period waves and this is presented

AMBRA1 is able to induce mitophagy via LC3 binding, regardless of PARKIN and p62/SQSTM1

Damaged mitochondria are eliminated by mitophagy, a selective form of autophagy whose dysfunction associates with neurodegenerative diseases. PINK1, PARKIN and p62/SQTMS1 have been shown to regulate mitophagy, leaving hitherto ill-defined the contribution by key players in 'general' autophagy. In basal conditions, a pool of AMBRA1 - an upstream autophagy regulator and a PARKIN interactor - is present at the mitochondria, where its pro-autophagic activity is inhibited by Bcl-2. Here we show that, upon mitophagy induction, AMBRA1 binds the autophagosome adapter LC3 through a LIR (LC3 interacting region) motif, this interaction being crucial for regulating both canonical PARKIN-dependent and -independent mitochondrial clearance. Moreover, forcing AMBRA1 localization to the outer mitochondrial membrane unleashes a massive PARKIN- and p62-independent but LC3-dependent mitophagy. These results highlight a novel role for AMBRA1 as a powerful mitophagy regulator, through both canonical or noncanonical pathways

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics

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

Adaptive Workflow Design Based on Blockchain

Increasingly, organizational processes have become more complex. There is a need for the design of workflows to focus on how organizations adapt to emergent processes while balancing the need for decentralization and centralization goal. The advancement in new technologies especially blockchain provides organizations with the opportunity to achieve the goal. Using blockchain technology (i.e. smart contract and blocks of specified consensus for deferred action), we leverage the theory of deferred action and a coordination framework to conceptually design a workflow management system that addresses organizational emergence (e-WfMS). Our artifact helps managers to predict and store the impact of deferred actions. We evaluated the effectiveness of our system against a complex adaptive system for utility assessment

Assessment of immunogenicity of romiplostim in clinical studies with ITP subjects

Romiplostim is an Fc-peptide fusion protein that activates intracellular transcriptional pathways via the thrombopoietin (TPO) receptor leading to increased platelet production. Romiplostim has been engineered to have no amino acid sequence homology to endogenous TPO. Recombinant protein therapeutics can be at a risk of development of an antibody response that can impact efficacy and safety. Hence, a strategy to detect potential antibody formation to the drug and to related endogenous molecules can be useful. The immunogenicity assessment strategy involved both the detection and characterization of binding and neutralizing antibodies. The method for detection was based on a surface plasmon resonance biosensor platform using the Biacore 3000. Samples that tested positive for binding antibodies in the Biacore immunoassay were then tested in a neutralization assay. Serum samples from 225 subjects with immune thrombocytopenic purpura (ITP) dosed with romiplostim and 45 ITP subjects dosed with placebo were tested for romiplostim and TPO antibodies. Prior to romiplostim treatment, 17 subjects (7%) tested romiplostim antibody positive and 12 subjects (5%) tested TPO antibody positive for pre-existing binding antibodies. After romiplostim exposure, 11% of the subjects exhibited binding antibodies against romiplostim and 5% of the subjects with ITP showed binding antibodies against TPO. The antibodies against romiplostim did not cross-react with TPO and vice versa. No cases of anti-TPO neutralizing antibodies were detected in romiplostim-treated subjects. The incidence of anti-romiplostim neutralizing antibodies to romiplostim was 0.4% (one subject); this subject tested negative at the time of follow-up 4 months later. No impact on platelet profiles were apparent in subjects that had antibodies to romiplostim to date. In summary, administration of romiplostim in ITP subjects resulted in the development of a binding antibody response against romiplostim and TPO ligand. One subject developed a neutralizing antibody response to romiplostim that impacted the platelet counts of this subject. No neutralizing antibodies to endogenous TPO were observed