TensorFlow Enabled Genetic Programming

Genetic Programming, a kind of evolutionary computation and machine learning algorithm, is shown to benefit significantly from the application of vectorized data and the TensorFlow numerical computation library on both CPU and GPU architectures. The open source, Python Karoo GP is employed for a series of 190 tests across 6 platforms, with real-world datasets ranging from 18 to 5.5M data points. This body of tests demonstrates that datasets measured in tens and hundreds of data points see 2-15x improvement when moving from the scalar/SymPy configuration to the vector/TensorFlow configuration, with a single core performing on par or better than multiple CPU cores and GPUs. A dataset composed of 90,000 data points demonstrates a single vector/TensorFlow CPU core performing 875x better than 40 scalar/Sympy CPU cores. And a dataset containing 5.5M data points sees GPU configurations out-performing CPU configurations on average by 1.3x.Comment: 8 pages, 5 figures; presented at GECCO 2017, Berlin, German

Origin of the p-process radionuclides ⁹²Nb and ¹⁴⁶Sm in the early solar system and inferences on the birth of the Sun

The abundances of ⁹²Nb and ¹⁴⁶Sm in the early solar system are determined from meteoritic analysis, and their stellar production is attributed to the p process. We investigate if their origin from thermonuclear supernovae deriving from the explosion of white dwarfs with mass above the Chandrasekhar limit is in agreement with the abundance of ⁵³Mn, another radionuclide present in the early solar system and produced in the same events. A consistent solution for ⁹²Nb and ⁵³Mn cannot be found within the current uncertainties and requires the ⁹²Nb/⁹²Mo ratio in the early solar system to be at least 50% lower than the current nominal value, which is outside its present error bars. A different solution is to invoke another production site for ⁹²Nb, which we find in the α-rich freezeout during core-collapse supernovae from massive stars. Whichever scenario we consider, we find that a relatively long time interval of at least ∼10 My must have elapsed from when the star-forming region where the Sun was born was isolated from the interstellar medium and the birth of the Sun. This is in agreement with results obtained from radionuclides heavier than iron produced by neutron captures and lends further support to the idea that the Sun was born in a massive star-forming region together with many thousands of stellar siblings

Investigating the Mechanism by which Bcl-xL Regulates Ceramide Channels

Digitalitzat per Artypla

Phosphomannosylation and the functional analysis of the extended Candida albicans MNN4-like gene family

We thank Luz A. López-Ramírez (Universidad de Guanajuato) for technical assistance. This work was supported by Consejo Nacional de Ciencia y Tecnología (ref. CB2011/166860; PDCPN2014-247109, and FC 2015-02-834), Universidad de Guanajuato (ref. 000025/11; 0087/13; ref. 1025/2016; Convocatoria Institucional para Fortalecer la Excelencia Académica 2015; CIFOREA 89/2016), Programa de Mejoramiento de Profesorado (ref. UGTO-PTC-261), and Red Temática Glicociencia en Salud (CONACYT-México). NG acknowledges the Wellcome Trust (086827, 075470, 101873, and 200208) and MRC Centre for Medical Mycology for funding (N006364/1). KJ was supported by a research visitor grant to Aberdeen from China Scholarship Council (CSC No. 201406055024). The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2017.02156/full#supplementary-materialPeer reviewedPublisher PD

Exploiting Machine Learning to Subvert Your Spam Filter

Using statistical machine learning for making security decisions introduces new vulnerabilities in large scale systems. This paper shows how an adversary can exploit statistical machine learning, as used in the SpamBayes spam filter, to render it useless—even if the adversary’s access is limited to only 1 % of the training messages. We further demonstrate a new class of focused attacks that successfully prevent victims from receiving specific email messages. Finally, we introduce two new types of defenses against these attacks.

Glueballs amass at RHIC and LHC Colliders! - The early quarkless 1st order phase transition at T=270T=270 MeV - from pure Yang-Mills glue plasma to GlueBall-Hagedorn states

The early stage of high multiplicity pp, pA and AA collider is represented by a nearly quarkless, hot, deconfined pure gluon plasma. According to pure Yang-Mills Lattice Gauge Theory, this hot pure glue matter undergoes, at a high temperature, $T_c = 270$ MeV, a first order phase transition into a confined Hagedorn-GlueBall fluid. These new scenario should be characterized by a suppression of high $p_T$ photons and dileptons, baryon suppression and enhanced strange meson production. We propose to observe this newly predicted class of events at LHC and RHIC.Comment: 7 pages, 6 figures