Sticker systems over monoids

Molecular computing has gained many interests among researchers since Head introduced the first theoretical model for DNA based computation using the splicing operation in 1987. Another model for DNA computing was proposed by using the sticker operation which Adlemanused in his successful experiment for the computation of Hamiltonian paths in a graph: a double stranded DNA sequence is composed by prolonging to the left and to the right a sequence of (single or double) symbols by using given single stranded strings or even more complex dominoes with sticky ends, gluing these ends together with the sticky ends of the current sequence according to a complementarity relation. According to this sticker operation, a language generative mechanism, called a sticker system, can be defined: a set of (incomplete) double-stranded sequences (axioms) and a set of pairs of single or double-stranded complementary sequences are given. The initial sequences are prolonged to the left and to the right by using sequences from the latter set, respectively. The iterations of these prolongations produce “computations” of possibly arbitrary length. These processes stop when a complete double stranded sequence is obtained. Sticker systems will generate only regular languages without restrictions. Additional restrictions can be imposed on the matching pairs of strands to obtain more powerful languages. Several types of sticker systems are shown to have the same power as regular grammars; one type is found to represent all linear languages whereas another one is proved to be able to represent any recursively enumerable language. The main aim of this research is to introduce and study sticker systems over monoids in which with each sticker operation, an element of a monoid is associated and a complete double stranded sequence is considered to be valid if the computation of the associated elements of the monoid produces the neutral element. Moreover, the sticker system over monoids is defined in this study

Semi-nonparametric Estimation of Operational Risk Capital with Extreme Loss Events

Bank operational risk capital modeling using the Basel II advanced measurement approach (AMA) often lead to a counter-intuitive capital estimate of value at risk at 99.9% due to extreme loss events. To address this issue, a flexible semi-nonparametric (SNP) model is introduced using the change of variables technique to enrich the family of distributions to handle extreme loss events. The SNP models are proved to have the same maximum domain of attraction (MDA) as the parametric kernels, and it follows that the SNP models are consistent with the extreme value theory peaks over threshold method but with different shape and scale parameters from the kernels. By using the simulation dataset generated from a mixture of distributions with both light and heavy tails, the SNP models in the Frechet and Gumbel MDAs are shown to fit the tail dataset satisfactorily through increasing the number of model parameters. The SNP model quantile estimates at 99.9 percent are not overly sensitive towards the body-tail threshold change, which is in sharp contrast to the parametric models. When applied to a bank operational risk dataset with three Basel event types, the SNP model provides a significant improvement in the goodness of fit to the two event types with heavy tails, yielding an intuitive capital estimate that is in the same magnitude as the event type total loss. Since the third event type does not have a heavy tail, the parametric model yields an intuitive capital estimate, and the SNP model cannot provide additional improvement. This research suggests that the SNP model may enable banks to continue with the AMA or its partial use to obtain an intuitive operational risk capital estimate when the simple non-model based Basic Indicator Approach or Standardized Approach are not suitable per Basel Committee Banking Supervision OPE10 (2019).Comment: There are 32 pages, including tables, figures, appendix and reference. The research was presented at the MATLAB Annual Computational Finance Conference, September 27-30, 202

GLADE: A galaxy catalogue for multimessenger searches in the advanced gravitational-wave detector era

We introduce a value-added full-sky catalogue of galaxies, named as Galaxy List for the Advanced Detector Era, or GLADE. The purpose of this catalogue is to (i) help identifications of host candidates for gravitational-wave events, (ii) support target selections for electromagnetic follow-up observations of gravitational-wave candidates, (iii) provide input data on the matter distribution of the local Universe for astrophysical or cosmological simulations, and (iv) help identifications of host candidates for poorly localized electromagnetic transients, such as gamma-ray bursts observed with the InterPlanetary Network. Both being potential hosts of astrophysical sources of gravitational waves, GLADE includes inactive and active galaxies as well. GLADE was constructed by cross-matching and combining data from five separate (but not independent) astronomical catalogues: GWGC, 2MPZ, 2MASS XSC, HyperLEDA, and SDSS-DR12Q. GLADE is complete up to dL=37+3−4Mpc in terms of the cumulative B-band luminosity of galaxies within luminosity distance dL, and contains all of the brightest galaxies giving half of the total B-band luminosity up to dL=91Mpc. As B-band luminosity is expected to be a tracer of binary neutron star mergers (currently the prime targets of joint GW+EM detections), our completeness measures can be used as estimations of completeness for containing all binary neutron star merger hosts in the local Universe

Site-directed mutagenesis of structural hot spots for enhanced solubility of deoxyxylulose phosphate pathway enzymes

Increasing the metabolic flux through a biochemical pathway is highly desirable for metabolic engineering. One strategy is to enhance the solubility of overexpressed pace-making enzymes. Accurate theoretical prediction of target mutation sites is instrumental to reduce the experimental efforts and speed up the optimization process. In this study, the rate-limiting steps along the non-mevalonate (DXP) pathway, namely E. coli Dxs and IspG, were used as the model enzymes to learn and develop a set of bioinformatics tools that would enable rational optimization of enzyme solubility. TANGO prediction was first used to identify the aggregation-prone regions (APRs), and then SIFT analysis was carried out to eliminate the non-tolerable amino acids in the APRs. Preliminary results have shown that 5 out of 8 tested mutations have resulted in an increase in Dxs solubility. Similarly, 7 out of 12 IspG mutants have displayed enhanced solubility. Importantly, the in vivo activities of the more soluble mutants were improved. Taken together, the solubility of both Dxs and IspG were enhanced by ~2-fold, by targeted single amino acid mutation. The study demonstrated rapid improvement of enzyme solubility by combinations of computational tools. The information gained would be useful for rational engineering of over-expressed pathway enzymes and improve pathway efficiencies

Thermoelectric property studies on thallium-doped lead telluride prepared by ball milling and hot pressing

Thallium doping into lead telluride has been demonstrated to increase the dimensionless thermoelectric figure-of-merit (ZT) by enhancing Seebeck coefficient due to the creation of resonant states close to Fermi level without affecting the thermal conductivity. However, the process is tedious, energy consuming, and small in quantities since it involves melting, slow cooling for crystal growth, long time annealing, post-crushing and hot pressing. Here we show that a similar ZT value about 1.3 at 400 °C is achieved on bulk samples with grain sizes of 3–7 μm by ball milling a mixture of elemental thallium, lead, and tellurium and then hot pressing the ball milled nanopowders

Solvent-Free Manufacturing of Electrodes for Lithium-Ion Batteries

Lithium ion battery electrodes were manufactured using a new, completely dry powder painting process. The solvents used for conventional slurry-cast electrodes have been completely removed. Thermal activation time has been greatly reduced due to the time and resource demanding solvent evaporation process needed with slurry-cast electrode manufacturing being replaced by a hot rolling process. It has been found that thermal activation time to induce mechanical bonding of the thermoplastic polymer to the remaining active electrode particles is only a few seconds. Removing the solvent and drying process allows large-scale Li-ion battery production to be more economically viable in markets such as automotive energy storage systems. By understanding the surface energies of various powders which govern the powder mixing and binder distribution, bonding tests of the dry-deposited particles onto the current collector show that the bonding strength is greater than slurry-cast electrodes, 148.8 kPa as compared to 84.3 kPa. Electrochemical tests show that the new electrodes outperform conventional slurry processed electrodes, which is due to different binder distribution