From Horndeski action to the Callan-Giddings-Harvey-Strominger model and beyond

The knowledge of what entered black hole (BH) is completely lost as it evaporates. This contradicts the unitarity principle of quantum mechanics and is referred to as the information loss paradox. Understanding the end stages of BH evaporation is key to resolving this paradox. As a first step, we need to have exact models that can mimic 4-D BHs in General relativity in classical limit and have a systematic way to include high-energy corrections. While there are various models in the literature, there is no systematic procedure by which one can study high-energy corrections. In this work, for the first time, we obtain Callan, Giddings, Harvey, and Strominger (CGHS) -- a (1+1)-D -- model from 4-D Horndeski action -- the most general scalar-tensor theory that does not lead to Ostrogradsky ghosts. We then show that 4-D Horndeski action can systematically provide a route to include higher-derivative terms relevant at the end stages of black hole evaporation. We derive the leading order Hawking flux while discussing some intriguing characteristics of the corrected CGHS models. We compare our results with other works and discuss the implications for primordial BHs.Comment: V2: Version accepted in PRD Letters. The title is modified. 34 Pages, 4 figures (including supplementary material

Biolistic transformation of Saccharomyces cerevisiae with β-glucosidase gene from Cellulomonas biazotea

A β-glucosidase genomic DNA from Cellulomonas biazotea NIAB 442 was isolated and coated onto tungsten microprojectiles for direct transformation of the gene into Saccharomyces cerevisiae. Transformation of β-glucosidase into S. cerevisae conferred the ability to hydrolyse esculin and cellobiose, indicated that the gene is expressed in the bombarded yeast. Key Words: Biolistic transformation, β-glucosidase, Cellulomonas biazotea, Saccharomyces cerevisiae. African Journal of Biotechnology Vol.3(1) 2004: 112-11

(R)-Doxylaminium (R,R)-tartrate

In the title compound (systematic name: (R)-dimeth­yl{2-[1-phenyl-1-(pyridin-2-yl)eth­oxy]eth­yl}aza­nium (R,R)-3-carb­oxy-2,3-dihy­droxy­propano­ate), C17H23N2O+·C4H5O6 −, the doxylaminium cation is protonated at the N atom. The tartrate monoanions are linked by short, almost linear O—H⋯O hydrogen bonds into chains extended along [100]. These chains are inter­linked by anion–pyridine O—H⋯N hydrogen bonds into a two-dimensional grid structure. WeakC—H⋯O inter­actions also play a role in the crystal packing. An intra­molecular hy­droxy–carboxyl­ate O—H⋯O hydrogen bond influences the conformation of the anion: the hydrogen-bonded fragment is almost planar, the maximum deviation from the mean plane being 0.059 (14) Å. In the cation, the aromatic rings are almost perpendicular [dihedral angle = 84.94 (8)°] and the conformation of the O—C—C—N chain is gauche(−), the dihedral angle is −76.6 (2)°. The absolute configuration was assigned on the basis of known chirality of the parent compound

Authorship Identification of Source Code Segments Written by Multiple Authors Using Stacking Ensemble Method

Source code segment authorship identification is the task of identifying the author of a source code segment through supervised learning. It has vast importance in plagiarism detection, digital forensics, and several other law enforcement issues. However, when a source code segment is written by multiple authors, typical author identification methods no longer work. Here, an author identification technique, capable of predicting the authorship of source code segments, even in the case of multiple authors, has been proposed which uses a stacking ensemble classifier. This proposed technique is built upon several deep neural networks, random forests and support vector machine classifiers. It has been shown that for identifying the author group, a single classification technique is no longer sufficient and using a deep neural network-based stacking ensemble method can enhance the accuracy significantly. The performance of the proposed technique has been compared with some existing methods which only deal with the source code segments written precisely by a single author. Despite the harder task of authorship identification for source code segments written by multiple authors, our proposed technique has achieved promising results evidenced by the identification accuracy, compared to the related works which only deal with code segments written by a single author.Comment: 2019 22nd International Conference on Computer and Information Technology (ICCIT

Configuration Detection of Grounding Grid: Static Electric Field Based Nondestructive Technique

Grounding grid configuration which, is key to its fault diagnosis, changes continuously with the extension in a substation. Furthermore, older substations grounding grid configurations are unknown. Existing literature regarding configuration detection mainly accounts for the magnetic field that required a gradient to locate the grounding conductor. The gradient of raw measurement in the substation vicinity enhances electromagnetic noise and distorts the results. Therefore, in this paper, we have developed a new algorithm, Configuration Detection of Grounding Grid (CDGG) based on the static electric field and the concept of ordered pairs to draw the configuration of the unknown grounding grid. Unlike, the practiced magnetic field, the electric field does not require a gradient. The maximum electric field value indicates the location of a grounding conductor. The connection between nodes is verified by measuring the electric field on the circle. Furthermore, the proposed algorithm also locates any diagonal conductor in the configuration. Mathematical reasoning and simulation results illustrate that our proposed algorithm is feasible to draw the configuration of the unknown grounding grid

Wdr1 and cofilin are necessary mediators of immune-cell-specific apoptosis triggered by Tecfidera.

Despite the emerging importance of reactive electrophilic drugs, deconvolution of their principal targets remains difficult. The lack of genetic tractability/interventions and reliance on secondary validation using other non-specific compounds frequently complicate the earmarking of individual binders as functionally- or phenotypically-sufficient pathway regulators. Using a redox-targeting approach to interrogate how on-target binding of pleiotropic electrophiles translates to a phenotypic output in vivo, we here systematically track the molecular components attributable to innate immune cell toxicity of the electrophilic-drug dimethyl fumarate (Tecfidera®). In a process largely independent of canonical Keap1/Nrf2-signaling, Keap1-specific modification triggers mitochondrial-targeted neutrophil/macrophage apoptosis. On-target Keap1-ligand-engagement is accompanied by dissociation of Wdr1 from Keap1 and subsequent coordination with cofilin, intercepting Bax. This phagocytic-specific cell-killing program is recapitulated by whole-animal administration of dimethyl fumarate, where individual depletions of the players identified above robustly suppress apoptosis