Generating Einstein gravity, cosmological constant and Higgs mass from restricted Weyl invariance

Recently, it has been pointed out that dimensionless actions in four dimensional curved spacetime possess a symmetry which goes beyond scale invariance but is smaller than full Weyl invariance. This symmetry was dubbed {\it restricted Weyl invariance}. We show that starting with a restricted Weyl invariant action that includes a Higgs sector with no explicit mass, one can generate the Einstein-Hilbert action with cosmological constant and a Higgs mass. The model also contains an extra massless scalar field which couples to the Higgs field (and gravity). If the coupling of this extra scalar field to the Higgs field is negligibly small, this fixes the coefficient of the nonminimal coupling $R \Phi^2$ between the Higgs field and gravity. Besides the Higgs sector, all the other fields of the standard model can be incorporated into the original restricted Weyl invariant action.Comment: 7 pages, no figure

Artificial Itelligence Teaches Drugs to Target Proteins by Tackling the Induced Folding Problem

We explore the possibility of a deep learning (DL) platform that steers drug design to target proteins by inducing binding-competent conformations. We deal with the fact that target proteins are usually not fixed targets but structurally adapt to the ligand in ways that need to be predicted to enable pharmaceutical discovery. In contrast with protein folding predictors, the proposed DL system integrates signals for structural disorder to predict conformations in floppy regions of the target protein that rely on associations with the purposely designed drug to maintain their structural integrity. This is tantamount to solve the drug-induced folding problem within an AI-empowered drug discovery platform. Preliminary testing of the proposed DL platform reveals that it is possible to infer the induced folding ensemble from which a therapeutically targetable conformation gets selected by DL-instructed drug design.Fil: Fernandez, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentin

The logistic map and the birth of period-3 cycle

The goal of this paper is to present a proof that for the logistic map the period-3 begins at . The third-iterate map is the key for understanding the birth of the period-3 cycle. Any point in a period-3 cycle repeats every three iterates by definition. Such points satisfy the condition ,and they are therefore fixed points of the third-iterate map. This fact and the so called tangent bifurcation for the logistic map, as well as the fixed points definition, are used for finding the value. The algebraic treatment utilizes some properties of symmetric polynomials in three variables. For the purposes of this paper, the bifurcation diagram for the logistic map is also presented, as well as a program in Mathematica for its construction

Targeted Deletion of PTEN in Kisspeptin Cells Results in Brain Region- and Sex-Specific Effects on Kisspeptin Expression and Gonadotropin Release

Kisspeptin-expressing neurons in the anteroventral periventricular nucleus (AVPV) and the arcuate nucleus (ARC) of the hypothalamus relay hormonal and metabolic information to gonadotropin-releasing hormone neurons, which in turn regulate pituitary and gonadal function. Phosphatase and tensin homolog (PTEN) blocks phosphatidylinositol 3-kinase (PI3K), a signaling pathway utilized by peripheral factors to transmit their signals. However, whether PTEN signaling in kisspeptin neurons helps to integrate peripheral hormonal cues to regulate gonadotropin release is unknown. To address this question, we generated mice with a kisspeptin cell-specific deletion of Pten (Kiss-PTEN KO), and first assessed kisspeptin protein expression and gonadotropin release in these animals. Kiss-PTEN KO mice displayed a profound sex and region-specific kisspeptin neuron hyperthrophy. We detected both kisspeptin neuron hyperthrophy as well as increased kisspeptin fiber densities in the AVPV and ARC of Kiss-PTEN KO females and in the ARC of Kiss-PTEN KO males. Moreover, Kiss-PTEN KO mice showed a reduced gonadotropin release in response to gonadectomy. We also found a hyperactivation of mTOR, a downstream PI3K target and central regulator of cell metabolism, in the AVPV and ARC of Kiss-PTEN KO females but not males. Fasting, known to inhibit hypothalamic kisspeptin expression and luteinizing hormone levels, failed to induce these changes in Kiss-PTEN KO females. We conclude that PTEN signaling regulates kisspeptin protein synthesis in both sexes and that its role as a metabolic signaling molecule in kisspeptin neurons is sex-specific

Conclave: secure multi-party computation on big data (extended TR)

Secure Multi-Party Computation (MPC) allows mutually distrusting parties to run joint computations without revealing private data. Current MPC algorithms scale poorly with data size, which makes MPC on "big data" prohibitively slow and inhibits its practical use. Many relational analytics queries can maintain MPC's end-to-end security guarantee without using cryptographic MPC techniques for all operations. Conclave is a query compiler that accelerates such queries by transforming them into a combination of data-parallel, local cleartext processing and small MPC steps. When parties trust others with specific subsets of the data, Conclave applies new hybrid MPC-cleartext protocols to run additional steps outside of MPC and improve scalability further. Our Conclave prototype generates code for cleartext processing in Python and Spark, and for secure MPC using the Sharemind and Obliv-C frameworks. Conclave scales to data sets between three and six orders of magnitude larger than state-of-the-art MPC frameworks support on their own. Thanks to its hybrid protocols, Conclave also substantially outperforms SMCQL, the most similar existing system.Comment: Extended technical report for EuroSys 2019 pape