First principles investigation of chromium carbide, CrC

We have investigated the electronic structure of 14 states of the experimentally unknown diatomic molecule chromium carbide, CrC, using standard multireference configuration interaction methods and high quality basis sets. We report potential curves, binding energies, and a number of spectroscopic parameters. The ground state of CrC, X 3Sigma-, displays triple-bond character with a binding energy of D(e)=89 kcal/mol and an internuclear separation of r(e)=1.63 A. The first excited state (1 5Sigma-) lies 9.2 kcal/mol higher. All the states studied are fairly ionic, featuring an electron transfer of 0.3-0.5e- from the metal atom to the carbon atom.     

Set-theoretic complete intersections on binomials

Let be an affine toric variety of codimension over a field of any characteristic. We completely characterize the affine toric varieties that are set-theoretic complete intersections on binomials. In particular we prove that in the characteristic zero case, is a set-theoretic complete intersection on binomials if and only if is a complete intersection. Moreover, if are binomials such that , then . While in the positive characteristic case, is a set-theoretic complete intersection on binomials if and only if is completely -glued.

These results improve and complete all known results on these topics.

     

H Magnetic resonance imaging of rigid polymeric solids

Implementation of the ¹H magnetic resonance single-point imaging technique has provided new opportunities for the direct imaging of rigid solids, particularly semicrystalline polymers with spin-spin relaxation times, T^*₂, of the order of 10 μs and greater. Potential applications of industrial relevance in the following areas are briefly discussed and illustrated: fabricated/processed parts, photochemical degradation, oxidation, and blend characterization.     

Resonant tau leptogenesis with observable lepton number violation

We consider a minimal extension of the standard model with one singlet neutrino per generation that can realize resonant leptogenesis at the electroweak scale. In particular, the baryon asymmetry in the Universe can be created by lepton-to-baryon conversion of an individual lepton number, for example, that of the tau lepton. The current neutrino data can be explained by a simple CP-violating Yukawa texture. The model has several testable phenomenological implications. It contains heavy Majorana neutrinos at the electroweak scale, which can be probed at e+ e- linear colliders, and predicts e- and mu-lepton-number-violating processes, such as 0nu betabeta decay, mu --> e gamma, and mu-e conversion in nuclei, with rates that are within reach of experimental sensitivity.     

Structural Detail and Thermal Bond Relocation of a Sterically Strained Cyclononatetraene Preliminary Communication

The X-ray crystallographic molecular dimensions and thermal response of the 5, 13-diphenyl-cyclonoa [b]naphthalene 1a , are described.     

Evaluation of Lighting Systems,Carbon Sources,and Bacteria Cultures on Photofermentative Hydrogen Production

Fluorescent and incandescent lighting systems were applied for batch photofermentative hydrogen production by four purple non-sulfur photosynthetic bacteria (PNSB). The hydrogen production efficiency of Rhodopseudomonas palustris, Rhodobacter sphaeroides, Rhodobacter capsulatus, and Rhodospirillum rubrum was evaluated using different carbon sources (acetate, butyrate, lactate, and malate). Incandescent light was found to be more effective for bacteria cell growth and hydrogen production. It was observed that PNSB followed substrate selection criteria for hydrogen production. Only R. palustris was able to produce hydrogen using most carbon sources. Cell density was almost constant, but cell growth rate and hydrogen production were significantly varied under the different lighting systems. The kinetics study suggested that initial substrate concentration had a positive correlation with lag phase duration. Among the PNSB, R. palustris grew faster and had higher hydrogen yields of 1.58, 4.92, and 2.57 mol H₂/mol using acetate, butyrate, and lactate, respectively. In the integrative approach with dark fermentation effluents rich in organic acids, R. palustris should be enriched in the phototrophic microbial consortium of the continuous hydrogen production system.     

Systematic Analysis of Polymer Molecular Weight Influence on the Organic Photovoltaic Performance

The molecular weight of an electron donor‐conjugated polymer is as essential as other well‐known parameters in the chemical structure of the polymer, such as length and the nature of any side groups (alkyl chains) positioned on the polymeric backbone, as well as their placement, relative strength, the ratio of the donor and acceptor moieties in the backbone of donor–acceptor (D–A)‐conjugated polymers, and the arrangement of their energy levels for organic photovoltaic performance. Finding the “optimal” molecular weight for a specific conjugated polymer is an important aspect for the development of novel photovoltaic polymers. Therefore, it is evident that the chemistry of functional conjugated polymers faces major challenges and materials have to adopt a broad range of specifications in order to be established for high photovoltaic performance. In this review, the approaches followed for enhancing the molecular weight of electron‐donor polymers are presented in detail, as well as how this influences the optoelectronic properties, charge transport properties, structural conformation, morphology, and the photovoltaic performance of the active layer.

     

Examining the Capacity of Text Mining and Software Metrics in Vulnerability Prediction

Software security is a very important aspect for software development organizations who wish to provide high-quality and dependable software to their consumers. A crucial part of software security is the early detection of software vulnerabilities. Vulnerability prediction is a mechanism that facilitates the identification (and, in turn, the mitigation) of vulnerabilities early enough during the software development cycle. The scientific community has recently focused a lot of attention on developing Deep Learning models using text mining techniques for predicting the existence of vulnerabilities in software components. However, there are also studies that examine whether the utilization of statically extracted software metrics can lead to adequate Vulnerability Prediction Models. In this paper, both software metrics- and text mining-based Vulnerability Prediction Models are constructed and compared. A combination of software metrics and text tokens using deep-learning models is examined as well in order to investigate if a combined model can lead to more accurate vulnerability prediction. For the purposes of the present study, a vulnerability dataset containing vulnerabilities from real-world software products is utilized and extended. The results of our analysis indicate that text mining-based models outperform software metrics-based models with respect to their F₂-score, whereas enriching the text mining-based models with software metrics was not found to provide any added value to their predictive performance.