Effect of Repeated Sorption and Desorption of Uranium to Properties of Anion Exchangers

Water contaminated with uranium can be purified by ion exchangers that can be regenerated and reused. The study investigated how the mechanical and chemical properties of selected anion exchangers change under the simulated operational conditions. Batch and dynamic column experiments were carried out to estimate the change of total capacity, breakthrough capacity, volume of purified water, pressure drop across the column, and the regeneration efficiency. Observed changes include lowering of total capacity and increasing pressure drop because of the mechanical degradation of beads of anion exchangers. The latter was confirmed by the measurement of particle size distribution.     

Adaptive neural network control based on neural observer for quadrotor unmanned aerial vehicle

This paper proposes an adaptive neural network control with neural state’s observer for quadrotor. The adaptive approach is used to solve the dynamics uncertainty problem of the controller. To perform the control, a Single Hidden Layer Neural Network (SHLNN) is used. Based on the structure of Sliding Mode Observer (SMO), a new neural observer is proposed to estimate the states. The aim of this work is to propose an observer insensitive to the measurement noise. The stability proof of global system is made by Lyapunov direct method. The adaptation laws of both artificial neural networks (ANNs) are derived from Lyapunov theory. The proposed controller is validated by simulation on the quadrotor under measurement noise conditions. A comparative study with SMO is made to highlight the performances of the proposed neural observer.     

β‐Polypropylene/wood flour composites: Effects of specific β‐nucleation and coupling agent on mechanical behavior

Polypropylene/wood flour composites were prepared by melt compounding. To improve their mechanical performance, the matrix polypropylene was modified with a specific nucleation agent based on an amide of dicarboxylic acid, which promotes crystallization predominantly in the β‐phase. The resulting material was used as a matrix for composites containing 10%, 20%, and 30% of wood flour. Uniform dispersion of the filler and improved interfacial adhesion was ensured by compatibilization with a small amount of maleic anhydride‐grafted polypropylene. A beneficial effect of application of the nucleation agent together with a compatibilizer on the resulting mechanical behavior was shown. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 506–511, 2007     

An auto-framing method for stochastic process signal by using a hidden Markov model based approach

In this paper, an “auto-framing” method, an algorithmic method to divide stochastic time-series process data into appropriate intervals, is developed based on the approach of hidden Markov model (HMM). While enormous amounts of process time-series data are being measured and collected today, their use is limited by the high costs to gather, store, and analyze them. “Data-framing” refers to the task of dividing stochastic signal data into time frames of distinct patterns so that the data can be stored and analyzed in an efficient manner. Data-framing is typically carried out manually, but doing so can be both laborious and ineffective. For the purpose of automating the data-framing task, stochastic signals of switching patterns are modeled using a hidden Markov model (HMM) based jump linear system (JLS), which switches the stochastic model probabilistically in accordance with the underlying Markov chain. Based on the model, an estimator is constructed to estimate from the collected signal data the state sequence of the underlying Markov chain, which is subsequently used to decide on the framing points. An Expectation Maximization (EM) algorithm, which is composed of two optimal estimators, fixed interval Kalman smoother and Viterbi algorithm, is used to estimate for the state estimation. We demonstrate the effectiveness of the HMM-based approach for auto-framing using simulated data constructed based on real industrial data.     

Micro-Current Stimulation Suppresses Inflammatory Responses in Peptidoglycan-Treated Raw 264.7 Macrophages and Propionibacterium acnes-Induced Skin Inflammation via TLR2/NF-κB Signaling Pathway

Acne is a common inflammatory disorder of the human skin and a multifactorial disease caused by the sebaceous gland and Propionibacterium acnes (P. acnes). This study aimed to evaluate the anti-inflammatory effect of micro-current stimulation (MC) on peptidoglycan (PGN)-treated raw 264.7 macrophages and P. acnes-induced skin inflammation. To specify the intensity with anti-inflammatory effects, nitric oxide (NO) production was compared according to various levels of MC. As the lowest NO production was shown at an intensity of 50 μA, subsequent experiments used this intensity. The changes of expression of the proteins related to TLR2/NF-κB signaling were examined by immunoblotting. Also, immunofluorescence analysis was performed for observing NF-κB p65 localization. All of the expression levels of proteins regarding TLR2/NF-κB signaling were decreased by the application of MC. Moreover, the application of MC to PGN-treated raw 264.7 cells showed a significant decrease in the amount of nuclear p65-protein. In the case of animal models with P. acnes-induced skin inflammation, various pro-inflammatory cytokines and mediators significantly decreased in MC-applied mice. In particular, the concentration of IL-1β in serum decreased, and the area of acne lesions, decreased from the histological analysis. We suggest for the first time that MC can be a novel treatment for acne.     

Study of Biological Activities and ADMET-Related Properties of Novel Chlorinated N-arylcinnamamides

A series of eighteen 4-chlorocinnamanilides and eighteen 3,4-dichlorocinnamanilides were designed, prepared and characterized. All compounds were evaluated for their activity against gram-positive bacteria and against two mycobacterial strains. Viability on both cancer and primary mammalian cell lines was also assessed. The lipophilicity of the compounds was experimentally determined and correlated together with other physicochemical properties of the prepared derivatives with biological activity. 3,4-Dichlorocinnamanilides showed a broader spectrum of action and higher antibacterial efficacy than 4-chlorocinnamanilides; however, all compounds were more effective or comparable to clinically used drugs (ampicillin, isoniazid, rifampicin). Of the thirty-six compounds, six derivatives showed submicromolar activity against Staphylococcus aureus and clinical isolates of methicillin-resistant S. aureus (MRSA). (2E)-N-[3,5-bis(trifluoromethyl)phenyl]- 3-(4-chlorophenyl)prop-2-enamide was the most potent in series 1. (2E)-N-[3,5-bis(Trifluoromethyl)phenyl]-3-(3,4-dichlorophenyl)prop-2-enamide, (2E)-3-(3,4-dichlorophenyl)-N-[3-(trifluoromethyl)phenyl]prop-2-enamide, (2E)-3-(3,4-dichloro- phenyl)-N-[4-(trifluoromethyl)phenyl]prop-2-enamide and (2E)-3-(3,4-dichlorophenyl)- N-[4-(trifluoromethoxy)phenyl]prop-2-enamide were the most active in series 2 and in addition to activity against S. aureus and MRSA were highly active against Enterococcus faecalis and vancomycin-resistant E. faecalis isolates and against fast-growing Mycobacterium smegmatis and against slow-growing M. marinum, M. tuberculosis non-hazardous test models. In addition, the last three compounds of the above-mentioned showed insignificant cytotoxicity to primary porcine monocyte-derived macrophages.     

The effect of online platform maturity on the efficiency of offline industry

The role of platform as an information mediator has been becoming more vital by satisfying buyers’ needs for a reasonable purchase and sellers’ need for more exposure to buyers within the copious information flood. For the platform service provider, increasing the network externality is important to induce both sides while platforms can cause sellers to invest more and create severe competition among sellers, which take a toll on sellers’ surplus. Therefore, this study investigates whether platforms yield benefits for sellers as the platform matures, securing the network externality. Thus, this study divides the seller side industry into 3 periods based on the level of platform maturation. The efficiency in each period is measured using stochastic frontier analysis and efficiencies of each period are compared using meta-frontier analysis. The results show the overall industry efficiency improves with securing the network externality as the platform matures. However, if the individual firm is resistant to innovation, the firm’s efficiency might not be far behind compared to the firm which led the innovation.     

Induction of apoptosis by ethanolic extract of mango peel and comparative analysis of the chemical constitutes of mango peel and flesh

The underlying mechanisms of the anticancer activity of the ethanolic extract of mango peel (EEMP) and its constituents were investigated. EEMP induced death of human cervical carcinoma HeLa cells through apoptosis, as evidenced by the increased cell population in the sub-G1 phase and the appearance of fragmented nuclei. Treatment of the cells with EEMP also downregulated anti-apoptotic Bcl-2 expression, resulting in the proteolytic activation of caspase-3, 7, 8, and 9 and the degradation of poly (ADP-ribose) polymerase (PARP) protein. The major components of mango peel were identified by liquid chromatography–electrospray ionisation tandem mass spectrometry and gas chromatography–mass spectrometry. Our data suggest that EEMP is an excellent source of quercetin 3-O-galactoside, mangiferin gallate, isomangiferin gallate, quercetin-3-O-arabinopyranoside, and mangiferin along with unsaturated fatty acids oleic acid, linoleic acid, and ethyl linoleate, which may help to prevent cervical cancer and may be a useful agent for the treatment of some other malignancies.