Design of Deep Convolution Neural Networks for categorical signature classification of raw panchromatic satellite images

Multimedia Tools and Applications - Remote Sensing categorical signature classification has gained significant implications on spatial resolution image analysis due to differences in the...     

Modulation of electrical transport in calcium cobaltite ceramics and thick films through microstructure control and doping

Ca₃Co₄O₉ is a promising p-type thermoelectric oxide material having intrinsically low thermal conductivity. With low cost and opportunities for automatic large scale production, thick film technologies offer considerable potential for a new generation of micro-sized thermoelectric coolers or generators. Here, based on the chemical composition optimized by traditional solid state reaction for bulk samples, we present a viable approach to modulating the electrical transport properties of screen-printed calcium cobaltite thick films through control of the microstructural evolution by optimized heat-treatment. XRD and TEM analysis confirmed the formation of high-quality calcium cobaltite grains. By creating 2.0 at% cobalt deficiency in Ca_2.7Bi_0.3Co₄O_9+δ, the pressureless sintered ceramics reached the highest power factor of 98.0 μWm^?1 K^-2 at 823 K, through enhancement of electrical conductivity by reduction of poorly conducting secondary phases. Subsequently, textured thick films of Ca_2.7Bi_0.3Co_3.92O_9+δ were efficiently tailored by controlling the sintering temperature and holding time. Optimized Ca_2.7Bi_0.3Co_3.92O_9+δ thick films sintered at 1203 K for 8 h exhibited the maximum power factor of 55.5 μWm^?1 K^-2 at 673 K through microstructure control.     

Influence of Titanium Excess in a Ti–Si Reaction Mixture on the Synthesis of a Composite in a Combustion Wave

Theoretical Foundations of Chemical Engineering - On the basis of the classic concepts of the theory of solid-phase combustion, for the first time, a model with a detailed scheme of chemical...     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Effect of Drosophila suzukii on Blueberry VOCs: Chemical Cues for a Pupal Parasitoid,Trichopria anastrephae

Journal of Chemical Ecology - Biocontrol agents such as parasitic wasps use long-range volatiles and host-associated cues from lower trophic levels to find their hosts. However, this chemical...     

Organofluorine Hydrazone Derivatives as Multifunctional Anti-Alzheimer's Agents with CK2 Inhibitory and Antioxidant Features

A set of novel hydrazone derivatives were synthesized and analyzed for their biological activities. The compounds were tested for their inhibitory effect on the phosphorylating activity of the protein kinase CK2, and their antioxidant activity was also determined in three commonly used assays. The hydrazones were evaluated for their radical scavenging against the DPPH, ABTS and peroxyl radicals. Several compounds have been identified as good antioxidants as well as potent protein kinase CK2 inhibitors. Most hydrazones containing a 4-N(CH₃)₂ residue or perfluorinated phenyl rings showed high activity in the radical-scavenging assays and possess nanomolar IC₅₀ values in the kinase assays.     

Combinations of Piperine with Hydroxypropyl-β-Cyclodextrin as a Multifunctional System

Piperine is an alkaloid that has extensive pharmacological activity and impacts other active substances bioavailability due to inhibition of CYP450 enzymes, stimulation of amino acid transporters and P-glycoprotein inhibition. Low solubility and the associated low bioavailability of piperine limit its potential. The combination of piperine with 2-hydroxypropyl-β-cyclodextrin (HP-β-CD) causes a significant increase in its solubility and, consequently, an increase in permeability through gastrointestinal tract membranes and the blood–brain barrier. X-ray powder diffraction (XRPD), differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FT-IR), nuclear magnetic resonance (NMR) were used to characterize interactions between piperine and HP-β-CD. The observed physicochemical changes should be combined with the process of piperine and CD system formation. Importantly, with an increase in solubility and permeability of piperine as a result of interaction with CD, it was proven to maintain its biological activity concerning the antioxidant potential (2,2-diphenyl-1-picryl-hydrazyl-hydrate assay), inhibition of enzymes essential for the inflammatory process and for neurodegenerative changes (hyaluronidase, acetylcholinesterase, butyrylcholinesterase).     

Influence of Continuous Wave Interference on the Efficiency of the Non-Threshold Search Procedure for a Noise-Like Signal by Delay Time with Transition to the Frequency Domain

Journal of Communications Technology and Electronics - A statistical study of the effectiveness of the non-threshold search procedure for a noise-like phase-shift keyed signal by the delay time is...     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.     

Sirtuins as Important Factors in Pathological States and the Role of Their Molecular Activity Modulators

Sirtuins (SIRTs), enzymes from the family of NAD⁺-dependent histone deacetylases, play an important role in the functioning of the body at the cellular level and participate in many biochemical processes. The multi-directionality of SIRTs encourages scientists to undertake research aimed at understanding the mechanisms of their action and the influence that SIRTs have on the organism. At the same time, new substances are constantly being sought that can modulate the action of SIRTs. Extensive research on the expression of SIRTs in various pathological conditions suggests that regulation of their activity may have positive results in supporting the treatment of certain metabolic, neurodegenerative or cancer diseases or this connected with oxidative stress. Due to such a wide spectrum of activity, SIRTs may also be a prognostic markers of selected pathological conditions and prove helpful in assessing their progression, especially by modulating their activity. The article presents and discusses the activating or inhibiting impact of individual SIRTs modulators. The review also gathered selected currently available information on the expression of SIRTs in individual disease cases as well as the biological role that SIRTs play in the human organism, also in connection with oxidative stress condition, taking into account the progress of knowledge about SIRTs over the years, with particular reference to the latest research results.