A taxonomy for classifying runtime verification tools

International Journal on Software Tools for Technology Transfer - Over the last 20 years, runtime verification (RV) has grown into a diverse and active field, which has stimulated the development...     

Development and Application of a Label-Free Fluorescence Method for Determining the Composition of Gold Nanoparticle–Protein Conjugates

A method was developed for determining the composition of the conjugates between gold nanoparticles and proteins based on the intrinsic fluorescence of unbound protein molecules. The fluorescence was evaluated after separation of the conjugates from the reaction mixture by centrifugation. Gold nanoparticles obtained using the citrate technique (average diameter 24 nm) were conjugated at pH 5.4 with the following four proteins: human immunoglobulin G (IgG), bovine serum albumin (BSA), recombinant streptococcal protein G (protein G), and Kunitz-type soybean trypsin inhibitor (STI). The compositions of these conjugates were determined using the developed method. The conjugate compositions were dependent on the concentration of the added protein, and in all cases reached saturation. The equilibrium dissociation constants of the gold nanoparticle conjugates with IgG, BSA, protein G, STI in the initial section of the concentration dependence curve were 4, 6, 10, and 15 nM, respectively. Close to saturation, the corresponding values were 25, 76, 175, and 100 nM, respectively. The maximal binding capacities of a single gold nanoparticle for IgG, BSA, Protein G, and STI were 52, 90, 500, and 550, respectively, which agrees well with the hypothesis of monolayer immobilization.     

Deep Learning Based Prediction of Gas Chromatographic Retention Indices for a Wide Variety of Polar and Mid-Polar Liquid Stationary Phases

Prediction of gas chromatographic retention indices based on compound structure is an important task for analytical chemistry. The predicted retention indices can be used as a reference in a mass spectrometry library search despite the fact that their accuracy is worse in comparison with the experimental reference ones. In the last few years, deep learning was applied for this task. The use of deep learning drastically improved the accuracy of retention index prediction for non-polar stationary phases. In this work, we demonstrate for the first time the use of deep learning for retention index prediction on polar (e.g., polyethylene glycol, DB-WAX) and mid-polar (e.g., DB-624, DB-210, DB-1701, OV-17) stationary phases. The achieved accuracy lies in the range of 16–50 in terms of the mean absolute error for several stationary phases and test data sets. We also demonstrate that our approach can be directly applied to the prediction of the second dimension retention times (GC × GC) if a large enough data set is available. The achieved accuracy is considerably better compared with the previous results obtained using linear quantitative structure-retention relationships and ACD ChromGenius software. The source code and pre-trained models are available online.     

Design and Synthesis of Polycyclic Imidazole‐Containing N‐ Heterocycles based on C?H Activation/Cyclization Reactions

A new strategy for the synthesis of polycyclic imidazole‐containing N‐heterocycles, based on the two general synthetic ways, namely the Pd(II)‐catalyzed intramolecular arylation via CH/C Hal and CH/CH coupling reactions, was developed. The method proposed here enables the synthesis of many fused N‐heterocycles containing purine, 1‐deazapurines and benzimidazole structural units.     

Diaminofuroxan: Synthetic Approaches and Computer‐Aided Study of Thermodynamic Stability

Different approaches to synthesize diaminofuroxan are presented herein. Mathematical and quantum chemical methods were used to study the possible reasons for failures in the syntheses of diaminofuroxan. Additionally, structural isomers of this compound were generated. With the help of the results of quantum chemical calculations at levels of DFT B3LYP 6‐31G(d) and MP2 6‐31G(d), screening of the most stable isomeric forms in the gaseous phase and in water was performed. It was shown that diaminofuroxan is not the thermodynamically most stable isomer among its structural analogues.     

Computer Simulation of Decomposition Mechanisms for CL‐20, Hydrazine,and Their Binary System

An approach to simulate thermal destruction processes of energetic materials has been developed. It is based on the classification of structural features for nitro compounds and the experimental data regarding their decomposition mechanisms. This approach consists of the mathematical simulation of thermal decomposition mechanisms to predict the likely reactions that may occur during the destruction of organic compounds. On the basis of contemporary experimental data on the decomposition of energetic materials from various chemical classes, a set of semi‐empirical rules for modeling possible reaction pathways has been formulated. These rules allow the generation of a whole set of possible decomposition mechanisms for substances at different steps of their destruction. In this study, the suggested methodology is applied to 2,4,6,8,10,12‐hexanitro‐2,4,6,8,10,12‐hexaazaisowurtzitane (CL‐20) and hydrazine and to their binary energetic mixture. It has been shown that thermal decomposition of the binary system consists in decompositions of the separate compounds at the initial stage with subsequent collisions and interactions of the resultant intermediates and decomposition products at different stages. In addition to some experimentally found decomposition products, our simulation showed some other possible compounds among the final products.     

Graphene oxide windows for in situ environmental cell photoelectron spectroscopy

The performance of new materials and devices often depends on processes taking place at the interface between an active solid element and the environment (such as air, water or other fluids). Understanding and controlling such interfacial processes require surface-specific spectroscopic information acquired under real-world operating conditions, which can be challenging because standard approaches such as X-ray photoelectron spectroscopy generally require high-vacuum conditions. The state-of-the-art approach to this problem relies on unique and expensive apparatus including electron analysers coupled with sophisticated differentially pumped lenses. Here, we develop a simple environmental cell with graphene oxide windows that are transparent to low-energy electrons (down to 400 eV), and demonstrate the feasibility of X-ray photoelectron spectroscopy measurements on model samples such as gold nanoparticles and aqueous salt solution placed on the back side of a window. These proof-of-principle results show the potential of using graphene oxide, graphene and other emerging ultrathin membrane windows for the fabrication of low-cost, single-use environmental cells compatible with commercial X-ray and Auger microprobes as well as scanning or transmission electron microscopes.     

3D Printing to Increase the Flexibility of the Chemical Synthesis of Biologically Active Molecules: Design of On-Demand Gas Generation Reactors

The development of new drugs is accelerated by rapid access to functionalized and D-labeled molecules with improved activity and pharmacokinetic profiles. Diverse synthetic procedures often involve the usage of gaseous reagents, which can be a difficult task due to the requirement of a dedicated laboratory setup. Here, we developed a special reactor for the on-demand production of gases actively utilized in organic synthesis (C₂H₂, H₂, C₂D₂, D₂, and CO₂) that completely eliminates the need for high-pressure equipment and allows for integrating gas generation into advanced laboratory practice. The reactor was developed by computer-aided design and manufactured using a conventional 3D printer with polypropylene and nylon filled with carbon fibers as materials. The implementation of the reactor was demonstrated in representative reactions with acetylene, such as atom-economic nucleophilic addition (conversions of 19–99%) and nickel-catalyzed S-functionalization (yields 74–99%). One of the most important advantages of the reactor is the ability to generate deuterated acetylene (C₂D₂) and deuterium gas (D₂), which was used for highly significant, atom-economic and cost-efficient deuterium labeling of S,O-vinyl derivatives (yield 68–94%). Successful examples of their use in organic synthesis are provided to synthesize building blocks of heteroatom-functionalized and D-labeled biologically active organic molecules.