A neural network to solve quadratic programming problems with fuzzy parameters

In this paper, a representation of a recurrent neural network to solve quadratic programming problems with fuzzy parameters (FQP) is given. The motivation of the paper is to design a new effective one-layer structure neural network model for solving the FQP. As far as we know, there is not a study for the neural network on the FQP. Here, we change the FQP to a bi-objective problem. Furthermore, the bi-objective problem is reduced to a weighting problem and then the Lagrangian dual is constructed. In addition, we consider a neural network model to solve the FQP. Finally, some illustrative examples are given to show the effectiveness of our proposed approach.     

Frequency modules and nonexistence of quasi-periodic solutions of nonlinear evolution equations

This paper gives lower estimates for the frequency modules of almost periodic solutions to equations of the form , where A generates a strongly continuous semigroup in a Banach space , F(t,x) is 2π-periodic in t and continuous in (t,x), and f is almost periodic. We show that the frequency module ℳ(u) of any almost periodic mild solution u of (*) and the frequency module ℳ(f) of f satisfy the estimate e ^{2π iℳ(f)}⊂e ^{2π iℳ(u)}. If F is independent of t, then the estimate can be improved: ℳ(f)⊂ℳ(u). Applications to the nonexistence of quasi-periodic solutions are also given.     

On the Kolmogorov complexity of continuous real functions

Kolmogorov complexity was originally defined for finitely-representable objects. Later, the definition was extended to real numbers based on the asymptotic behaviour of the sequence of the Kolmogorov complexities of the finitely-representable objects—such as rational numbers—used to approximate them.This idea will be taken further here by extending the definition to continuous functions over real numbers, based on the fact that every continuous real function can be represented as the limit of a sequence of finitely-representable enclosures, such as polynomials with rational coefficients.Based on this definition, we will prove that for any growth rate imaginable, there are real functions whose Kolmogorov complexities have higher growth rates. In fact, using the concept of prevalence, we will prove that ‘almost every’ continuous real function has such a high-growth Kolmogorov complexity. An asymptotic bound on the Kolmogorov complexities of total single-valued computable real functions will be presented as well.     

Assessment model of classroom acoustics criteria for enhancing speech intelligibility and learning quality

In this paper, a new classroom acoustics assessment model (CAAM) based on analytic hierarchy process (AHP) for enhancing speech intelligibility and learning quality is proposed. The model is based on five main criteria that affect the learning process and related to classrooms acoustical properties. These include classroom specifications, noise sources inside and outside the classroom, teaching style, and vocal effort. The priority and weights of these major criteria along with their alternatives are identified using the views of students, staff, education consultants, and expertise by using a developed questionnaire, and the AHP methodology. This model can be considered as a helpful framework enabling universities decision makers to take effective decisions on classroom acoustics treatment issues. It also provides colleges’ higher authorities the suitable guidelines that help for determining necessary requirements that help to raise the quality and efficiency of the educational environment; in order to reach an excellent learning environment; and hence increasing students learning outcomes.     

Optical and current transport properties of CuO/ZnO nanocoral p–n heterostructure hydrothermally synthesized at low temperature

We demonstrate the synthesis and investigate the electrical and optical characteristics of ‘nanocorals’ (NCs) composed of CuO/ZnO grown at low temperature through the hydrothermal approach. High-density CuO nanostructures (NSs) were selectively grown on ZnO nanorods (NRs). The synthesized NCs were used to fabricate p–n heterojunctions that were investigated by the current density–voltage (J–V) and the capacitance–voltage (C–V) techniques. It was found that the NC heterojunctions exhibit a well-defined diode behavior with a threshold voltage of about 1.52 V and relatively high rectification factor of ～760. The detailed forward J–V characteristics revealed that the current transport is controlled by an ohmic behavior for V≤0.15 V, whereas at moderate voltages 1.46≤V<1.5 the current follows a J? α?exp(βV) relationship. At higher voltages (≥1.5 V) the current follows the relation J? α? V ², indicating that the space-charge-limited current mechanism is the dominant current transport. The C–V measurement indicated that the NC diode has an abrupt junction. The grown CuO/ZnO NCs exhibited a broad light absorption range that is covering the UV and the entire visible parts of the spectrum.     

Understanding the Mechanocatalytic Conversion of Biomass: A Low‐Energy One‐Step Reaction Mechanism by Applying Mechanical Force

On the way to establishing biomass as a renewable and environmentally friendly source to cover the ever‐increasing global demand on energy and chemicals, one great challenge is the efficient depolymerization of cellulose. Enhanced conversion rates have been discovered in ball‐milling experiments, thus opening a mechanocatalytic approach. However, an understanding of the impact of mechanical forces on the acid‐catalyzed cleavage of glycosidic bonds at the molecular level is still missing. Herein, we contribute such fundamental insight based on atomistic modeling. Mechanically stressing the macromolecular backbone radically changes the depolymerization pathway from a complex high‐barrier reaction upon thermal activation to a low‐energy single‐step mechanocatalytic process. In addition to revealing a regioselective increase in basicity under a mechanical force, our results provide molecular‐level explanations of the experimental findings and might therefore guide rational ways to improve such mechanocatalytic processes.     

Synthesis and characterization of some Schiff-base-containing polyimides

The diamine, 4-aminophenyloxy-N-4-[(4-amiophenyloxy)benzylidene]aniline, was prepared via the nucleophilic substitution reaction and was polymerized with different dianhydrides either by one-step solution polymerization reaction or two-step procedure. The latter includes ring-opening polyaddition to give poly(amic acid), followed by cyclodehydration to polyimides. The inherent viscosity ranges from 0.61–0.79 dl/g. Some of the polymers were soluble in most of the organic solvents such as DMSO, DMF, DMAc, NMP, and m-cresol even at room temperature. The degradation temperature of the resultant polymers falls in the ranges from 240–500 °C in nitrogen with only 10% weight loss. Specific heat capacity at 200 °C ranges from 1.0929–2.6275 J g⁻¹ k⁻¹. The temperature at which the maximum degradation of the polymer occurs ranges from 600–630 °C. The glass transition temperature (Tg) values of the polyimides ranged from 185 to 272 °C. The activation energy and enthalpy of the polyimides ranged from 47.5–55.0 kJ/mole and 45.7–53.0 kJ/mole and the moisture absorption in the range of 0.23–0.72%.     

Phytochemical Profiling,In Vitro Biological Activities,and In Silico Molecular Docking Studies of Dracaena reflexa

Dracaena reflexa, a traditionally significant medicinal plant, has not been extensively explored before for its phytochemical and biological potential. The present study was conducted to evaluate the bioactive phytochemicals and in vitro biological activities of D. reflexa, and perform in silico molecular docking validation of D. reflexa. The bioactive phytochemicals were assessed by preliminary phytochemical testing, total bioactive contents, and GC-MS analysis. For biological evaluation, the antioxidant (DPPH, ABTS, CUPRAC, and ABTS), antibacterial, thrombolytic, and enzyme inhibition (tyrosinase and cholinesterase enzymes) potential were determined. The highest level of total phenolic contents (92.72 ± 0.79 mg GAE/g extract) was found in the n-butanol fraction while the maximum total flavonoid content (110 ± 0.83 mg QE/g extract) was observed in methanolic extract. The results showed that n-butanol fraction exhibited very significant tyrosinase inhibition activity (73.46 ± 0.80) and acetylcholinesterase inhibition activity (64.06 ± 2.65%) as compared to other fractions and comparable to the standard compounds (kojic acid and galantamine). The methanolic extract was considered to have moderate butyrylcholinesterase inhibition activity (50.97 ± 063) as compared to the standard compound galantamine (53.671 ± 0.97%). The GC-MS analysis of the n-hexane fraction resulted in the tentative identification of 120 bioactive phytochemicals. Furthermore, the major compounds as identified by GC-MS were analyzed using in silico molecular docking studies to determine the binding affinity between the ligands and the enzymes (tyrosinase, acetylcholinesterase, and butyrylcholinesterase enzymes). The results of this study suggest that Dracaena reflexa has unquestionable pharmaceutical importance and it should be further explored for the isolation of secondary metabolites that can be employed for the treatment of different diseases.     

Recent Advances in the Chemistry and Therapeutic Evaluation of Naturally Occurring and Synthetic Withanolides

Natural products are a major source of biologically active compounds that make promising lead molecules for developing efficacious drug-like molecules. Natural withanolides are found in many flora and fauna, including plants, algae, and corals, that traditionally have shown multiple health benefits and are known for their anti-cancer, anti-inflammatory, anti-bacterial, anti-leishmaniasis, and many other medicinal properties. Structures of these withanolides possess a few reactive sites that can be exploited to design and synthesize more potent and safe analogs. In this review, we discuss the literature evidence related to the medicinal implications, particularly anticancer properties of natural withanolides and their synthetic analogs, and provide perspectives on the translational potential of these promising compounds.     

Is Genetic Engineering a Route to Enhance Microalgae-Mediated Bioremediation of Heavy Metal-Containing Effluents?

Contamination of the biosphere by heavy metals has been rising, due to accelerated anthropogenic activities, and is nowadays, a matter of serious global concern. Removal of such inorganic pollutants from aquatic environments via biological processes has earned great popularity, for its cost-effectiveness and high efficiency, compared to conventional physicochemical methods. Among candidate organisms, microalgae offer several competitive advantages; phycoremediation has even been claimed as the next generation of wastewater treatment technologies. Furthermore, integration of microalgae-mediated wastewater treatment and bioenergy production adds favorably to the economic feasibility of the former process—with energy security coming along with environmental sustainability. However, poor biomass productivity under abiotic stress conditions has hindered the large-scale deployment of microalgae. Recent advances encompassing molecular tools for genome editing, together with the advent of multiomics technologies and computational approaches, have permitted the design of tailor-made microalgal cell factories, which encompass multiple beneficial traits, while circumventing those associated with the bioaccumulation of unfavorable chemicals. Previous studies unfolded several routes through which genetic engineering-mediated improvements appear feasible (encompassing sequestration/uptake capacity and specificity for heavy metals); they can be categorized as metal transportation, chelation, or biotransformation, with regulation of metal- and oxidative stress response, as well as cell surface engineering playing a crucial role therein. This review covers the state-of-the-art metal stress mitigation mechanisms prevalent in microalgae, and discusses putative and tested metabolic engineering approaches, aimed at further improvement of those biological processes. Finally, current research gaps and future prospects arising from use of transgenic microalgae for heavy metal phycoremediation are reviewed.