Progress of transition metal chalcogenides as efficient electrocatalysts for energy conversion

The continuous excessive usage of fossil fuels has resulted in its fast depletion, leading to an escalating energy crisis as well as several environmental issues leading to increased research towards sustainable energy conversion. Electrocatalysts play crucial role in the development of numerous novel energy conversion devices, including fuel cells and solar fuel generators. In particular, high-efficiency and cost-effective catalysts are required for large-scale implementation of these new devices. Over the last few years, transition metal chalcogenides have emerged as highly efficient electrocatalysts for several electrochemical devices such as water splitting, carbon dioxide electroreduction, and, solar energy converters. These transition metal chalcogenides exhibit high electrochemical tunability, abundant active sites, and superior electrical conductivity. Hence, they have been actively explored for various electrocatalytic activities. Herein, we have provided comprehensive review of transition-metal chalcogenide electrocatalysts for hydrogen evolution, oxygen evolution, and carbon dioxide reduction and illustrated structure–property correlation that increases their catalytic activity.     

Stability Indicating RP-LC Method for the Determination of Gemifloxacin Mesylate

The present study describes the degradation of gemifloxacin mesylate under different International Conference on Harmonization prescribed stress conditions (hydrolysis, oxidation, dry and wet heat and photolysis) and application of a specific and selective stability-indicating reversed-phase liquid chromatography assay. Separation of drug and degradation products was successfully achieved on a HiQ-SiL C₈ column using 10 mM potassium dihydrogen orthophosphate (pH adjusted to 3.0 with o-phosphoric acid)–acetonitrile (65:35, v/v) at a flow rate of 1 mL min⁻¹ and detection at 273 nm.

     

Significance of Satellite DNA Revealed by Conservation of a Widespread Repeat DNA Sequence Among Angiosperms

The analysis of plant genome structure and evolution requires comprehensive characterization of repetitive sequences that make up the majority of plant nuclear DNA. In the present study, we analyzed the nature of pCtKpnI-I and pCtKpnI-II tandem repeated sequences, reported earlier in Carthamus tinctorius. Interestingly, homolog of pCtKpnI-I repeat sequence was also found to be present in widely divergent families of angiosperms. pCtKpnI-I showed high sequence similarity but low copy number among various taxa of different families of angiosperms analyzed. In comparison, pCtKpnI-II was specific to the genus Carthamus and was not present in any other taxa analyzed. The molecular structure of pCtKpnI-I was analyzed in various unrelated taxa of angiosperms to decipher the evolutionary conserved nature of the sequence and its possible functional role.     

Cholesterol-based dimeric liquid crystals: synthesis,mesomorphic behaviour of frustrated phases and DFT study

Chiral unsymmetrical dimeric liquid crystals consisting of a cholesterol moiety as chiral entity and a substituted salicylidene imine core (with the substituent being butyl or fluoro or chloro group) interconnected through an even methylene spacer have been synthesised and their mesomorphic properties are characterised. All the dimers exhibit enantiotropic mesophases. The butyl homologue exhibited N* phase only, the fluoro- and chloro-substituted compound exhibited frustrated blue phases (BPs), N* phase and SmC* or twisted grain boundary (TGB) phases. The occurrence of a fluid frustrated phase, the BP, in particular, observed in compounds with a polar moiety and bent optimised conformation by density functional theory (DFT) study, indicates the importance of polar structures and bent shape of the compounds. Theoretical calculation was performed in order to study the optimised conformation, polarity and electron density distribution of the synthesised cholesterol derivatives using DFT. Time-dependent density functional theory (TD-DFT) calculation also had been carried out to investigate the absorption spectra and HOMO–LUMO energies. The experimental and theoretical absorption spectra are also presented.     

New algorithms and complexity status of the reducibility problem of sequences in open shop scheduling minimizing the makespan

We consider the problem of minimizing the makespan in open shop scheduling. The decision problem whether a given sequence in open shop scheduling is irreducible has already been considered, however, has not been solved yet. A sequence is an acyclic orientation of the Hamming graph K _n ×K _m . Irreducible sequences in open shop are the local optimal elements. We present two variants of algorithms based on the specific properties of the H-comparability graph. The first is polynomial whereas the second is exponential. The irreducibility is co-NP. The stated properties argue whether it belongs to P. The complexity status of the considered decision problem is updated.     

Lamivudine hemihydrate

A new lamivudine hydrate, namely, cis‐4‐amino‐1‐(2‐hydroxymethyl‐1,3‐oxathiolan‐5‐yl)pyrimidin‐2(1H)‐one hemihydrate, C₈H₁₁N₃O₃S·0.5H₂O, has been synthesized and structurally characterized by both powder and single‐crystal X‐ray diffraction studies. The hemihydrate crystallizes in the Sohnke space group P2₁, with the asymmetric unit comprising four lamivudine and two water molecules. An extensive network of intermolecular hydrogen bonds involving both lamivudine and solvent water molecules generates a three‐dimensional supramolecular architecture. The structural data and crystal packing of the present lamivudine hemihydrate are compared with those of other hydrated and anhydrous forms of lamivudine.     

Chance constrained uncertain classification via robust optimization

This paper studies the problem of constructing robust classifiers when the training is plagued with uncertainty. The problem is posed as a Chance-Constrained Program (CCP) which ensures that the uncertain data points are classified correctly with high probability. Unfortunately such a CCP turns out to be intractable. The key novelty is in employing Bernstein bounding schemes to relax the CCP as a convex second order cone program whose solution is guaranteed to satisfy the probabilistic constraint. Prior to this work, only the Chebyshev based relaxations were exploited in learning algorithms. Bernstein bounds employ richer partial information and hence can be far less conservative than Chebyshev bounds. Due to this efficient modeling of uncertainty, the resulting classifiers achieve higher classification margins and hence better generalization. Methodologies for classifying uncertain test data points and error measures for evaluating classifiers robust to uncertain data are discussed. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle data uncertainty and outperform state-of-the-art in many cases.     

On a sum form functional equation and its applications in information theory and statistics

The general solutions of a sum form functional equation containing five unknown mappings have been obtained. The importance of these solutions in information theory and statistics has also been discussed.