56,956 research outputs found
Qubit Data Structures for Analyzing Computing Systems
Qubit models and methods for improving the performance of software and
hardware for analyzing digital devices through increasing the dimension of the
data structures and memory are proposed. The basic concepts, terminology and
definitions necessary for the implementation of quantum computing when
analyzing virtual computers are introduced. The investigation results
concerning design and modeling computer systems in a cyberspace based on the
use of two-component structure are presented.Comment: 9 pages,4 figures, Proceeding of the Third International Conference
on Data Mining & Knowledge Management Process (CDKP 2014
Categorical Ontology of Complex Systems, Meta-Systems and Theory of Levels: The Emergence of Life, Human Consciousness and Society
Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quantum states emerging from complex quantum dynamics of interacting networks of biomolecules, such as proteins and nucleic acids that are now collectively defined as quantum interactomics. On the other hand, the time dependent evolution over several generations of cancer cells --that are generally known to undergo frequent and extensive genetic mutations and, indeed, suffer genomic transformations at the chromosome level (such as extensive chromosomal aberrations found in many colon cancers)-- cannot be correctly represented in the ‘standard’ terms of quantum automaton modules, as the normal somatic cells can. This significant difference at the cancer cell genomic level is therefore reflected in major changes in cancer cell interactomics often from one cancer cell ‘cycle’ to the next, and thus it requires substantial changes in the modeling strategies, mathematical tools and experimental designs aimed at understanding cancer mechanisms. Novel solutions to this important problem in carcinogenesis are proposed and experimental validation procedures are suggested. From a medical research and clinical standpoint, this approach has important consequences for addressing and preventing the development of cancer resistance to medical therapy in ongoing clinical trials involving stage III cancer patients, as well as improving the designs of future clinical trials for cancer treatments.\ud
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KEYWORDS: Emergence of Life and Human Consciousness;\ud
Proteomics; Artificial Intelligence; Complex Systems Dynamics; Quantum Automata models and Quantum Interactomics; quantum-weave dynamic patterns underlying human consciousness; specific molecular processes underlying extensive memory, learning, anticipation mechanisms and human consciousness; emergence of human consciousness during the early brain development in children; Cancer cell ‘cycling’; interacting networks of proteins and nucleic acids; genetic mutations and chromosomal aberrations in cancers, such as colon cancer; development of cancer resistance to therapy; ongoing clinical trials involving stage III cancer patients’ possible improvements of the designs for future clinical trials and cancer treatments. \ud
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A Cost- Effective Design of Reversible Programmable Logic Array
In the recent era, Reversible computing is a growing field having
applications in nanotechnology, optical information processing, quantum
networks etc. In this paper, the authors show the design of a cost effective
reversible programmable logic array using VHDL. It is simulated on xilinx ISE
8.2i and results are shown. The proposed reversible Programming logic array
called RPLA is designed by MUX gate [10] & Feynman gate for 3- inputs, which is
able to perform any reversible 3- input logic function or Boolean function.
Furthermore the quantized analysis with camparitive finding is shown for the
realized RPLA against the existing one. The result shows improvement in the
quantum cost and total logical caculation in proposed RPLA.Comment: 6 Pages, 9 Figure
SciTech News Volume 71, No. 3 (2017)
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Application of Computational Chemical Shift Prediction Techniques to the Cereoanhydride Structure Problem-Carboxylate Complications.
Despite the vast array of techniques available to modern-day chemists, structural misassignments still occur. These misassignments are often only realized upon attempted synthesis, when the spectra of synthesized products do not match previously reported spectra. This was the case with marine natural product cereoanhydride. The originally proposed 7-membered ring anhydride (1) was shown to be incorrect, although a likely precursor to the correct structure (2) in both its laboratory synthesis and biosynthesis. Herein, in addition to showing how NMR computations could have been used to arrive at the correct structure, we show that the conversion of 1 to 2 is indeed energetically viable, and we highlight complications in predicting NMR chemical shifts for molecules with acidic protons
COMPUTER SIMULATION AND COMPUTABILITY OF BIOLOGICAL SYSTEMS
The ability to simulate a biological organism by employing a computer is related to the
ability of the computer to calculate the behavior of such a dynamical system, or the "computability" of the system.* However, the two questions of computability and simulation are not equivalent. Since the question of computability can be given a precise answer in terms of recursive functions, automata theory and dynamical systems, it will be appropriate to consider it first. The more elusive question of adequate simulation of biological systems by a computer will be then addressed and a possible connection between the two answers given will be considered. A conjecture is formulated that suggests the possibility of employing an algebraic-topological, "quantum" computer (Baianu, 1971b)
for analogous and symbolic simulations of biological systems that may include chaotic processes that are not, in genral, either recursively or digitally computable. Depending on the biological network being modelled, such as the Human Genome/Cell Interactome or a trillion-cell Cognitive Neural Network system, the appropriate logical structure for such simulations might be either the Quantum MV-Logic (QMV) discussed in recent publications (Chiara, 2004, and references cited therein)or Lukasiewicz Logic Algebras that were shown to be isomorphic to MV-logic algebras (Georgescu et al, 2001)
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