Blockchain for Collaborative Businesses

Mobile Networks and Applications - Blockchain applications have continuously improved ever since its first debut on cryptocurrency. From then on, its uses have branched out from the financial...     

Lipidomic Analysis of Plasma from Healthy Men and Women Shows Phospholipid Class and Molecular Species Differences between Sexes

The phospholipid composition of lipoproteins is determined by the specificity of hepatic phospholipid biosynthesis. Plasma phospholipid 20:4n-6 and 22:6n-3 concentrations are higher in women than in men. We used this sex difference in a lipidomics analysis of the impact of endocrine factors on the phospholipid class and molecular species composition of fasting plasma from young men and women. Diester species predominated in all lipid classes measured. 20/54 Phosphatidylcholine (PtdCho) species were alkyl ester, 15/48 phosphatidylethanolamine (PtdEtn) species were alkyl ester, and 12/48 PtdEtn species were alkenyl ester. There were no significant differences between sexes in the proportions of alkyl PtdCho species. The proportion of alkyl ester PtdEtn species was greater in women than men, while the proportion of alkenyl ester PtdEtn species was greater in men than women. None of the phosphatidylinositol (PtdIns) or phosphatidylserine (PtdSer) molecular species contained ether-linked fatty acids. The proportion of PtdCho16:0_22:6, and the proportions of PtdEtn O-16:0_20:4 and PtdEtn O-18:2_20:4 were greater in women than men. There were no sex differences in PtdIns and PtdSer molecular species compositions. These findings show that plasma phospholipids can be modified by sex. Such differences in lipoprotein phospholipid composition could contribute to sexual dimorphism in patterns of health and disease.     

κ-Opioid Signaling in the Lateral Hypothalamic Area Modulates Nicotine-Induced Negative Energy Balance

Several studies have reported that nicotine, the main bioactive component of tobacco, exerts a marked negative energy balance. Apart from its anorectic action, nicotine also modulates energy expenditure, by regulating brown adipose tissue (BAT) thermogenesis and white adipose tissue (WAT) browning. These effects are mainly controlled at the central level by modulation of hypothalamic neuropeptide systems and energy sensors, such as AMP-activated protein kinase (AMPK). In this study, we aimed to investigate the kappa opioid receptor (κOR)/dynorphin signaling in the modulation of nicotine’s effects on energy balance. We found that body weight loss after nicotine treatment is associated with a down-regulation of the κOR endogenous ligand dynorphin precursor and with a marked reduction in κOR signaling and the p70 S6 kinase/ribosomal protein S6 (S6K/rpS6) pathway in the lateral hypothalamic area (LHA). The inhibition of these pathways by nicotine was completely blunted in κOR deficient mice, after central pharmacological blockade of κOR, and in rodents where κOR was genetically knocked down specifically in the LHA. Moreover, κOR-mediated nicotine effects on body weight do not depend on orexin. These data unravel a new central regulatory pathway modulating nicotine’s effects on energy balance.     

Phase locked loop-based clock synthesizer for reconfigurable analog-to-digital converters

Analog Integrated Circuits and Signal Processing - This paper presents the complete design of a phase locked loop-based clock synthesizer for reconfigurable analog-to-digital converters. The...     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

Alumina-Periclase-Carbon Refractories Produced by OOO Ogneupor

Refractories and Industrial Ceramics - Technology for producing alumina-periclase-carbon refractories of the brands APUK-D and APU-D is developed and implemented. Use of complex antioxidant and...     

Properties of High-Strength Aramid Fiber Textile Materials for Protective Clothing

Fibre Chemistry - An analysis of the aramid fiber market including the range of industrial textile materials containing chemical fibers for specialized protective clothing of metallurgical workers,...     

Dielectric performance of pyrochlore-type Bi2MgNb2-xTaxO9 ceramics: The effects of tantalum doping

The solid solutions based on the pyrochlore-type system Bi₂MgNb_2-xTa_xO₉ were formed in the compositional range х = 0–2.0 (Bi_1·6Mg_0·8Nb_1.6-tTa_tO_7.2, t = 0–1.6). The Rietveld method was used to refine the structure for Bi₂MgNb_2-xTa_xO₉ (x = 0, 1.0, 2.0). The increasing tantalum content led to the slight decrease in the cubic unit cell parameters from 10.56934 (4) Å for x = 0 and 10.54607 (3) Å for x = 2 (sp.gr. Fd-3m:2). At the same time, tantalum additions suppressed grain growth in the pyrochlore ceramics during sintering and made it possible to obtain materials with an average grain size of 1–2 μm (Bi_1·6Mg_0·8Ta_1·6O_7.2). The increase in the Ta⁵⁺ concentration led to the decrease in the dielectric permeability from 104 (Bi_1·6Mg_0·8Nb_1·6O_7.2) to 20 (Bi_1·6Mg_0·8Ta_1·6O_7.2) at room temperature, while the dielectric loss tangent remained lower than 0.002, which is due to the small grain size and the high porosity of the samples. An increase in temperature has practically no effect on the values of the dielectric permittivity in the entire frequency range. The samples have weak through conductivity. The activation energies of electrical conductivity varied in the range of 0.84–1.00 eV, and the less tantalum, the lower the activation energy. The electrical properties of the samples at 200 Hz to 1 MHz are described by the simplest parallel scheme.     

Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.