Polyamic acid: nanoprecipitation and electrophoretic deposition on porous supports

Polyamic acid (PAA, a precursor of polyimide) was synthesized from 4,4′-oxydiphthalic anhydride and 4,4′-oxydianiline. PAA, dissolved in dimethylsulfoxide (DMSO), was precipitated into colloidal particles after its injection into acetone. The resulting particle size distribution was found to depend on aging time of PAA solutions, their concentration, and the manner in which the solutions were mixed with acetone. PAA particles of any size down to 10 nm appeared to be achievable by decreasing the acetone/DMSO ratio. Particles in DMSO/acetone suspensions were found to have a significant negative zeta potential. Therefore, there was no need to add organic bases to form PAA anions, in contrast to all previously published studies on the PAA electrodeposition. EPD was performed onto porous stainless-steel or alumina disks, which are suitable supports (reinforcements) for membranes. The slow evaporation of DMSO residue yielded dried polymer layers, comprised of 50–100 nm PAA globules. The outer surface of layers was usually covered with a very thin, continuous PAA skin. Such supported PAA layers—after a simple imidization step via a heat treatment—could be applied as thermally resistant membranes for gas separation.     

Synthesis of DNA-Encoded Disulfide- and Thioether-Cyclized Peptides

DNA-encoded chemical library technologies enable the screening of large combinatorial libraries of chemically and structurally diverse molecules, including short cyclic peptides. A challenge in the combinatorial synthesis of cyclic peptides is the final step, the cyclization of linear peptides that typically suffers from incomplete reactions and large variability between substrates. Several efficient peptide cyclization strategies rely on the modification of thiol groups, such as the formation of disulfide or thioether bonds between cysteines. In this work, we established a strategy and reaction conditions for the efficient chemical synthesis of cyclic peptide–DNA conjugates based on linking the side chains of cysteines. We tested two different thiol-protecting groups and found that tert-butylthio (S-tBu) works best for incorporating a pair of cysteines, and we show that the DNA-linked peptides can be efficiently cyclized through disulfide and thioether bond formation. In combination with established procedures for DNA encoding, the strategy for incorporation of cysteines may be readily applied for the generation and screening of disulfide- and thioether-cyclized peptide libraries.     

Influence of salt concentration on solubility and tie-line data for the system: Formic acid + n-butanol + water

The tie-line and solubility data, i.e. formic acid (FA) + n-butanol + water + NaCl, were resolved at T = 298.15 K and under ambient pressure. The Othmer–Tobias equation was applied in this study. The experimental data were correlated and all linear correlation coefficients were found to be approximately equal to 1. Both the Universal Quasi-chemical Theory (UNIQUAC) and Nonrandom Two Liquid Theory (NRTL) and NRTL models were employed in order to compare the experimental liquid–liquid equilibrium (LLE) and tie-line data. Consequently, the calculated and experimental data proved to be a good fit. Results show that adding salt to the system proved beneficial by increasing the separation of FA from water.     

Semantic integration of enterprise information systems using meta-metadata ontology

This paper proposes a non-domain-specific metadata ontology as a core component in a semantic model-based document management system (DMS), a potential contender towards the enterprise information systems of the next generation. What we developed is the core semantic component of an ontology-driven DMS, providing a robust semantic base for describing documents’ metadata. We also enabled semantic services such as automated semantic translation of metadata from one domain to another. The core semantic base consists of three semantic layers, each one serving a different view of documents’ metadata. The core semantic component’s base layer represents a non-domain-specific metadata ontology founded on ebRIM specification. The main purpose of this ontology is to serve as a meta-metadata ontology for other domain-specific metadata ontologies. The base semantic layer provides a generic metadata view. For the sake of enabling domain-specific views of documents’ metadata, we implemented two domain-specific metadata ontologies, semantically layered on top of ebRIM, serving domain-specific views of the metadata. In order to enable semantic translation of metadata from one domain to another, we established model-to-model mappings between these semantic layers by introducing SWRL rules. Having the semantic translation of metadata automated not only allows for effortless switching between different metadata views, but also opens the door for automating the process of documents long-term archiving. For the case study, we chose judicial domain as a promising ground for improving the efficiency of the judiciary by introducing the semantics in this field.     

A novel split-and-merge algorithm for hierarchical clustering of Gaussian mixture models

The paper presents a novel split-and-merge algorithm for hierarchical clustering of Gaussian mixture models, which tends to improve on the local optimal solution determined by the initial constellation. It is initialized by local optimal parameters obtained by using a baseline approach similar to k-means, and it tends to approach more closely to the global optimum of the target clustering function, by iteratively splitting and merging the clusters of Gaussian components obtained as the output of the baseline algorithm. The algorithm is further improved by introducing model selection in order to obtain the best possible trade-off between recognition accuracy and computational load in a Gaussian selection task applied within an actual recognition system. The proposed method is tested both on artificial data and in the framework of Gaussian selection performed within a real continuous speech recognition system, and in both cases an improvement over the baseline method has been observed.     

A case of using the Semantic Interoperability Framework for custom orthopedic implants manufacturing

The efficiency and effectiveness of the daily practice in orthopedic surgery depend on the availability, interoperability and unique access to a wide set of information, related to the patient’s medical record and diagnosis, domain knowledge and available resources and staff. The most important of the tangible resources, needed for the therapeutic or preventive actions are orthopedic implants. In some cases, the implants may be highly complex and customized products, which need to be manufactured (assembled) on basis of the above information in a shortest possible timeframe. In this paper, the case of the custom orthopedic implants manufacturing is described from the perspective of the collaborative enterprising, with special consideration of the interoperability issues of the involved enterprise collaboration. It is shown how the previously developed Semantic Interoperability Framework can be used to improve the efficiency of the manufacturing and other relevant processes.     

Image coding algorithm based on Hadamard transform and simple vector quantization

Transform coding is commonly used in image processing algorithms to provide high compression ratios, often at the expense of processing time and simplicity of the system. We have recently proposed a pixel value prediction scheme in order to exploit adjacent pixel correlation, providing a low-complexity model for image coding. However, the proposed model was unable to reach high compression ratios retaining high quality of reconstructed image at the same time. In this paper we propose a new segmentation algorithm which further utilizes adjacent pixel correlation, provides higher compression ratios and it is based on application of Hadamard transform coding. Additional compression is provided by using vector quantization for a low number of quantization levels and by simplifying generalized Lloyd’s algorithm where the special attention is paid to determination of optimal partitions for vector quantization, making a fixed quantizer. The proposed method is quite simple and experimental results show that it ensures better or similar rate-distortion ratio for very low bit-rates, comparing to the other similar methods that are based on wavelet or curvelet transform coding and support or core vector machine application. Furthermore, the proposed method requires very low processing time since the proposed quantizers are fixed, much less than the required time for the aforementioned methods that we compare with as well as much less than the time required for fractal image coding. In the end, the appropriate discussion is provided comparing the results with a scheme based on linear prediction and dual-mode quantization.

     

Developing a model to assess the success of e-learning systems: evidence from a manufacturing company in transitional economy

This paper examines the success of an e-learning system in a company from the perspective of employees by using a multimethod approach. For this purpose Moodle learning management system was used. The success of e-learning as an information system was evaluated using four constructs of the updated DeLone and McLean IS success model—system quality, use, user satisfaction and net benefits, and adding one more construct—user performance. In this research a combination of observation and survey as two different research methods was used, which allowed the new measure to be incorporated into the model. Empirical assessment was carried out by exploratory factor analysis, confirmatory factor analysis and structural equation modeling. The research model was found to be valid and reliable. The results provide an expanded understanding of the constructs that measure the success of an e-learning system, helping to more deeply understand the key success dimensions and their interrelationships. The implications of our work were discussed. The DeLone and McLean IS success model applied equally well. However, the use of observation as a method of data collection revealed the weaknesses of the original model.     

Demonstration and characterization of biomolecular enrichment on microfluidic aptamer-functionalized surfaces

This paper demonstrates and systematically characterizes the enrichment of biomolecular compounds using aptamer-functionalized surfaces within a microfluidic device. The device consists of a microchamber packed with aptamer-functionalized microbeads and integrated with a microheater and temperature sensor to enable thermally controlled binding and release of biomolecules by the aptamer. We first present an equilibrium binding-based analytical model to understand the enrichment process. The characteristics of the aptamer-analyte binding and enrichment are then experimentally studied, using adenosine monophosphate (AMP) and a specific RNA aptamer as a model system. The temporal process of AMP binding to the aptamer is found to be primarily determined by the aptamer-AMP binding kinetics. The temporal process of aptamer-AMP dissociation at varying temperatures is also obtained and observed to occur relatively rapidly (<2 s). The specificity of the enrichment is next confirmed by performing selective enrichment of AMP from a sample containing biomolecular impurities. Finally, we investigate the enrichment of AMP by either discrete or continuous introduction of a dilute sample into the microchamber, demonstrating enrichment factors ranging from 566 to 686×, which agree with predictions of the analytical model.