Time-variant reliability profiles for steel girder bridges

Evaluation of existing steel bridges becomes more important due to natural aging, increasing load spectra, deterioration caused by corrosion, and other problems. In the result, bridge structures exposed to aggressive environmental conditions are subjected to time-variant changes of resistance. Therefore, there is a need for evaluation procedures for an accurate prediction of the load carrying capacity and reliability of bridge structures, in order to make rational decisions about repair, rehabilitation, and expected life-cycle costs. The objective of this paper is to develop time-variant reliability models for steel girder bridges. Traditional methods based on deterministic analysis do not reveal the actual load carrying capacity of the structure. The proposed approach is based on reliability analysis of components and structural systems. The study involves the selection of representative structures, formulation of limit state functions, development of load models, development of resistance models for corroded steel girders, development of the reliability analysis method, reliability analysis of selected bridges, and development of the time-dependant reliability profiles including deterioration due to corrosion. The results of the study can be used for a better prediction of the service life of deteriorating steel girder bridges, and development of optimal reliability-based maintenance strategies.     

Generation of a Multicomponent Library of Disulfide Donor-Acceptor Architectures Using Dynamic Combinatorial Chemistry

We describe here the generation of new donor-acceptor disulfide architectures obtained in aqueous solution at physiological pH. The application of a dynamic combinatorial chemistry approach allowed us to generate a large number of new disulfide macrocyclic architectures together with a new type of [2]catenanes consisting of four distinct components. Up to fifteen types of structurally-distinct dynamic architectures have been generated through one-pot disulfide exchange reactions between four thiol-functionalized aqueous components. The distribution of disulfide products formed was found to be strongly dependent on the structural features of the thiol components employed. This work not only constitutes a success in the synthesis of topologically- and morphologically-complex targets, but it may also open new horizons for the use of this methodology in the construction of molecular machines.     

Supramolecular assembly/reassembly processes: molecular motors and dynamers operating at surfaces

Among the many significant advances within the field of supramolecular chemistry over the past decades, the development of the so-called "dynamers" features a direct relevance to materials science. Defined as "combinatorial dynamic polymers", dynamers are constitutional dynamic systems and materials resulting from the application of the principles of supramolecular chemistry to polymer science. Like supramolecular materials in general, dynamers are reversible dynamic multifunctional architectures, capable of modifying their constitution by exchanging, recombining, incorporating components. They may exhibit a variety of novel properties and behave as adaptive materials. In this review we focus on the design of responsive switchable monolayers, i.e. monolayers capable to undergo significant changes in their physical or chemical properties as a result of external stimuli. Scanning tunneling microscopy studies provide direct evidence with a sub-nanometre resolution, on the formation and dynamic response of these self-assembled systems featuring controlled geometries and properties.     

Nanomaterial Shape Influence on Cell Behavior

Nanomaterials are proven to affect the biological activity of mammalian and microbial cells profoundly. Despite this fact, only surface chemistry, charge, and area are often linked to these phenomena. Moreover, most attention in this field is directed exclusively at nanomaterial cytotoxicity. At the same time, there is a large body of studies showing the influence of nanomaterials on cellular metabolism, proliferation, differentiation, reprogramming, gene transfer, and many other processes. Furthermore, it has been revealed that in all these cases, the shape of the nanomaterial plays a crucial role. In this paper, the mechanisms of nanomaterials shape control, approaches toward its synthesis, and the influence of nanomaterial shape on various biological activities of mammalian and microbial cells, such as proliferation, differentiation, and metabolism, as well as the prospects of this emerging field, are reviewed.     

Tumor Resection Induces Alterations on Serum Phospholipidome of Liver Cancer Patients

Hepatocellular carcinoma and cholangiocarcinoma are the most common primary malignant liver tumors. Since the liver plays a key role in lipid metabolism, the study of serum phospholipid (PL) profiles may provide a better understanding of alterations in hepatic lipid metabolism. In this study, we used a high-resolution HILIC-LC–MS lipidomic approach to establish the serum phospholipidome profile of patients with liver cancer before (T0) and after tumor resection (T1) and a control group (CT) of healthy individuals. After the analysis of PL profiles, we observed that the phospholipidome of patients with liver cancer was significantly modified after the tumor resection procedure. We observed an upregulation of some phosphatidylcholine (PtdCho) species, namely, PtdCho(36:6), PtdCho(42:6), PtdCho(38:5), PtdCho(36:5), PtdCho(38:6) and choline plasmalogens (PlsCho), and/or 1-O-alkyl-2-acyl-glycerophosphocholine (PakCho) in patients with liver cancer at T0 compared to the CT group, and a downregulation after tumor resection (T1) when compared to T0. These results show that LC–MS can detect different serum PL profiles in patients with liver cancer, before and after tumor resection, by defining a specific PL fingerprint that was used to determine the effect of tumor and tumor resection on lipid metabolism.     

Thermal properties of poly(ethylene terephthalate) recovered from municipal solid waste by steam autoclaving

The steam autoclaving of municipal solid waste followed by size separation was shown to be a way to recover virtually 100% of recyclable poly(ethylene terephthalate) (PET); this is a yield not attainable by a typical material recovery facility. The polymer properties of the recovered PET, which had undergone various degrees of thermal processing, were evaluated by thermogravimetric analysis, differential scanning calorimetry, gel permeation chromatography, viscometry, and solid‐state NMR to assess the commercial viability of polymer reuse. The weight‐average molecular weight (M_w) decreased as a result of autoclaving from 61,700 g/mol for postconsumer poly(ethylene terephthalate) (pcPET) to 59,700 g/mol for autoclaved postconsumer poly(ethylene terephthalate) [(apcPET)]. M_w for the reclaimed poly(ethylene terephthalate) (rPET) was slightly lower, at 57,400 g/mol. The melting temperature increased with two heat cycles from 236°C for the heat‐crystallized virgin poly(ethylene terephthalate) (vPET) pellets to 248°C for apcPET and up to 253°C for rPET. Correspondingly, the cold crystallization temperature decreased with increased processing from 134°C for vPET to 120°C for apcPET. The intrinsic viscosity varied from 0.773 dL/g for the vPET to 0.709 dL/g for rPET. Extruded samples were created to assess the potential commercial applications of the recovered rPET samples. The M_w values of the extruded apcPET and rPET samples dropped to 37,000 and 34,000 g/mol, respectively, after extrusion (three heat cycles); this indicated that exposure to heat dictated that these materials would be better suited for downcycled products, such as fibers and injected‐molded products. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2012     

Fusing two cytochromes b of Rhodobacter capsulatus cytochrome bc1 using various linkers defines a set of protein templates for asymmetric mutagenesis

Cytochrome bc(1) (mitochondrial complex III), one of the key enzymes of biological energy conversion, is a functional homodimer in which each monomer contains three catalytic subunits: cytochrome c(1), the iron-sulfur subunit and cytochrome b. The latter is composed of eight transmembrane α-helices which, in duplicate, form a hydrophobic core of a dimer. We show that two cytochromes b can be fused into one 16-helical subunit using a number of different peptide linkers that vary in length but all connect the C-terminus of one cytochrome with the N-terminus of the other. The fusion proteins replace two cytochromes b in the dimer defining a set of available protein templates for introducing mutations that allow breaking symmetry of a dimer. A more detailed comparison of the form with the shortest, 3 amino acid, linker to the form with 12 amino acid linker established that both forms display similar level of structural plasticity to accommodate several, but not all, asymmetric patterns of mutations that knock out individual segments of cofactor chains. While the system based on a fused gene does not allow for the assessments of the functionality of electron-transfer paths in vivo, the family of proteins with fused cytochrome b offers attractive model for detailed investigations of molecular mechanism of catalysis at in vitro/reconstitution level.     

Monte Carlo simulation of terpolymerization: Optimizing the simulation and post-processing times

Monte Carlo simulations are a useful and easy way to understand a polymerization reaction process properly. However, achieving reliable results with Monte Carlo simulations can also lead to prohibitive computational times and a considerable amount of data to be processed afterward. The present study analyses the Monte Carlo simulation of a steady-state terpolymerization process to reduce the overall computational time of the simulation and the post-processing of its results. Different sorting algorithms (Bubble, Insertion, Selection, and Tim) and Python libraries (Joblib and Numba) were used. The chain composition distribution and the micro-structures resultant of different scenarios were assessed by processing the simulated mechanism results. The simulation time results indicate the Tim sorting algorithm as the best to use in the post-processing step and the Numba library as the best suited for both the simulation and the post-processing step.     

Graph machine learning for design of high-octane fuels

Fuels with high-knock resistance enable modern spark-ignition engines to achieve high efficiency and thus low CO₂ emissions. Identification of molecules with desired autoignition properties indicated by a high research octane number and a high octane sensitivity is therefore of great practical relevance and can be supported by computer-aided molecular design (CAMD). Recent developments in the field of graph machine learning (graph-ML) provide novel, promising tools for CAMD. We propose a modular graph-ML CAMD framework that integrates generative graph-ML models with graph neural networks and optimization, enabling the design of molecules with desired ignition properties in a continuous molecular space. In particular, we explore the potential of Bayesian optimization and genetic algorithms in combination with generative graph-ML models. The graph-ML CAMD framework successfully identifies well-established high-octane components. It also suggests new candidates, one of which we experimentally investigate and use to illustrate the need for further autoignition training data.