Furan-Based Bionanocomposites Reinforced with a Hybrid System of Carbon Nanofillers

Bionanocomposites based on poly(trimethylene 2,5-furandicarboxylate)-block-poly(tetramethylene oxide) (PTF-b-F-PTMO) with various contents of carbon nanofibers, graphene nanoplatelets and a hybrid system of these nanoparticles are synthesized via in situ polymerization. The dispersion of nanoparticles in the nanocomposites is determined using a scanning electron microscope and optical microscopy images. The thermal properties are studied employing differential scanning calorimetry, dynamic mechanical thermal analysis, and thermogravimetric analysis. The melt viscosity of the synthesized materials is determined using rheological measurements. Mechanical properties, along with the thermal and electrical conductivity, are also analyzed. The synthesized polymer nanocomposites are processed using injection molding and they display mechanical properties of elastomers during mechanical testing, which indicates that the obtained materials are, in fact, thermoplastic elastomers (TPE). Compared to a neat matrix (PTF-b-F-PTMO 50/50), the incorporation of nanoparticles causes an increase in the value of the degree of crystallinity and the value of the tensile modulus values (E) of the nanocomposites. Such reinforced bionanocomposites are especially interesting from an applicative point of view. They can be used as components of fuel systems, bumpers, or cupholders.     

Speech nonfluency detection using Kohonen networks

This work covers the problem of application of neural networks to recognition and categorization of non-fluent and fluent utterance records. Fifty-five 4-s speech samples where the blockade on plosives (p, b, t, d, k and g) occurred and 55 recordings of speech of fluent speakers containing the same fragments were applied. Two Kohonen networks were used. The purpose of the first network was to reduce the dimension of the vector describing the input signals. A result of the analysis was the output matrix consisting of the neurons winning in a particular time frame. This matrix was taken as an input for the next self-organizing map network. Various types of Kohonen networks were examined with respect to their ability to classify utterances correctly into two, non-fluent and fluent, groups. Good examination results were accomplished and classification correctness exceeded 76%.     

Hierarchical ANN system for stuttering identification

The presented work covers the issue of applying neural networks to the recognition and categorization of non-fluent and fluent utterance records. Speech samples containing three types of stuttering episodes (blocks before words starting with plosives, syllable repetitions, and sound-initial prolongations) were applied. The proposed system, built with hierarchical neural network framework, was used and then evaluated with respect to its ability to recognize and classify disfluency types in stuttered speech. The purpose of the first network was to reduce the dimension of vector describing the input signals. The result of the analysis was the output matrix consisting of neurons winning in a particular time frame. This matrix was taken as an input for the next network. Various types of MLP networks were examined with respect to their ability to classify utterances correctly into two, non-fluent and fluent, groups. Good examination results were accomplished and classification correctness exceeded 84–100% depending on the disfluency type.     

Multimodal processes optimization subject to fuzzy operation time constraints: declarative modeling approach

We present an extension of the resource-constrained multi-product scheduling problem for an automated guided vehicle (AGV) served flow shop, where multiple material handling transport modes provide movement of work pieces between machining centers in the multimodal transportation network (MTN). The multimodal processes behind the multi-product production flow executed in an MTN can be seen as processes realized by using various local periodically functioning processes. The considered network of repetitively acting local transportation modes encompassing MTN’s structure provides a framework for multimodal processes scheduling treated in terms of optimization of the AGVs fleet scheduling problem subject to fuzzy operation time constraints. In the considered case, both production takt and operation execution time are described by imprecise data. The aim of the paper is to present a constraint propagation (CP) driven approach to multi-robot task allocation providing a prompt service to a set of routine queries stated in both direct and reverse way. Illustrative examples taking into account an uncertain specification of robots and workers operation time are provided.     

N-doped carbon nanotubes for liquid-phase CC bond hydrogenation

The introduction of foreign elements inside the channel of carbon nanotubes could lead to a significant modification of the intrinsic properties of these nanomaterials. Nitrogen atoms entering in the graphene sheets as substitute of carbon could modify in a large extend the acido-basic properties and also adsorption of the nanotube itself. Depending on the synthesis conditions, i.e. nature of the N-source, temperature and C-to-N atomic ratio, various N-doped carbon nanotubes can be synthesized with different surface properties. The aim of the present work is to report the synthesis of N-doped CNTs using a common nitrogen source precursor namely ammonia (NH₃) with C₂H₆ as carbon source. The as-synthesized N-CNTs were subsequently employed as catalyst support in the liquid-phase hydrogenation of cinnamaldehyde using palladium as an active phase.     

Mesoporous niobosilicates serving as catalysts for synthesis of fragrances

Niobium-containing siliceous-MSU-X mesoporous molecular sieves have been prepared according to an original pathway by the reaction between low-cost niobium species (ammonium trisoxalate complex of niobium (V)), silica precursor (tetraethyl orthosilicate), and biodegradable surfactant in strong acidic, acidic or almost neutral medium. The selective oxidation of several terpenes and terpenoids (geraniol, limonene, α-terpineol) using hydrogen peroxide as an oxidant agent over novel Nb-catalysts is studied in this work. A variety of (Nb)MSU-X and (Ru,Nb)MSU-X materials prepared under different conditions has been employed (supermicroporous/mesoporous molecular sieves) for this purpose. The structure–function relationships in these catalysts are reported.     

NKT and NKT-like Cells in Autoimmune Neuroinflammatory Diseases—Multiple Sclerosis,Myasthenia Gravis and Guillain-Barre Syndrome

NKT cells comprise three subsets—type I (invariant, iNKT), type II, and NKT-like cells, of which iNKT cells are the most studied subset. They are capable of rapid cytokine production after the initial stimulus, thus they may be important for polarisation of Th cells. Due to this, they may be an important cell subset in autoimmune diseases. In the current review, we are summarising results of NKT-oriented studies in major neurological autoimmune diseases—multiple sclerosis, myasthenia gravis, and Guillain-Barre syndrome and their corresponding animal models.     

Prognostic Impact and Functional Annotations of KIF11 and KIF14 Expression in Patients with Colorectal Cancer

Genomic instability (GIN) has an important contribution to the pathology of colorectal cancer (CRC). Therefore, we selected mitosis and cytokinesis kinesins, KIF11 and KIF14, as factors of potential clinical and functional value in CRC, as their aberrant expression has been suspected to underlie GIN. We examined the expression and the prognostic and biological significance of KIF11 and KIF14 in CRC via in-house immunohistochemistry on tissue microarrays, public mRNA expression datasets, as well as bioinformatics tools. We found that KIF11 and KIF14 expression, at both the protein and mRNA level, was markedly altered in cancer tissues compared to respective controls, which was reflected in the clinical outcome of CRC patients. Specifically, we provide the first evidence that KIF11 protein and mRNA, KIF14 mRNA, as well as both proteins together, can significantly discriminate between CRC patients with better and worse overall survival independently of other relevant clinical risk factors. The negative prognostic factors for OS were high KIF11 protein, high KIF11 protein + low KIF14 protein, low KIF11 mRNA and low KIF14 mRNA. Functional enrichment analysis revealed that the gene sets related to the cell cycle, DNA replication, DNA repair and recombination, among others, were positively associated with KIF11 or KIF14 expression in CRC tissues. In TCGA cohort, the positive correlations between several measures related to GIN and the expression of KIFs were also demonstrated. In conclusion, our results suggest that CRC patients can be stratified into distinct risk categories by biological and molecular determinants, such as KIF11 and KIF14 expression and, mechanistically, this is likely attributable to their role in maintaining genome integrity.     

Possibility of high-pressure transformation during nanoindentation of SiC

High-pressure transformation to the rocksalt structure has been proposed as a mechanism that underlies the ductile wear observed during nanomachining of SiC. However, in contrast to other brittle materials (e.g. Si), no such transformation has been directly observed either during machining or during nanoindentation of SiC. Here, we performed large-scale molecular dynamics simulations of nanoindentation with spherical indenters of various sizes and surface roughness to determine whether SiC can undergo a nanoindentation-induced transformation from the zincblende to the rocksalt structure. The calculations of possible states of stresses under the indenter have been combined with a thermodynamic analysis to estimate the effects of dislocation density, shear stresses and temperature on the phase transformation pressure in SiC. Our analysis shows that the high-pressure transformation is highly unlikely under the conditions of nanomachining. We conclude that the primary response of SiC to nanoindentation is dislocation nucleation and propagation in the low-pressure (zincblende) phase.     

Formation of catalytic active sites in copper and manganese modified SBA-15 mesoporous silica

A series of copper and manganese oxides modified SBA-15 mesoporous silicas with different composition was prepared by incipient wetness impregnation with the corresponding nitrate precursors and compared with the analogous materials supported on conventional SiO₂. Nitrogen physisorption, XDR, FTIR, UV–Vis and temperature programmed reduction with hydrogen were used for samples characterization. Their catalytic activity was tested in ethyl acetate oxidation and methanol decomposition. The ordered porous structure of the support facilitates the interaction between different metal oxide nanoparticles and increases their dispersion due to the formation of mixed oxide phase. The ethyl acetate oxidation on SBA-15 binary materials is suppressed due to the lower accessibility of the metal oxide particles, located deeply into the micro-meso pores of the support. The reaction medium which forms during the methanol decomposition provides the reduction/decomposition transformations with the mixed oxide phase. The final phase composition of finely dispersed Cu/CuO and MnO_x particles stabilizes in a highly dispersed state into the porous matrix of SBA-15 support and increases the catalytic activity in methanol decomposition due to the appearance of synergistic effect between them.