2D Molecular Dynamics Simulation of Solitons Interaction in Dusty Plasma

Molecular Dynamics (MD) method is used to simulate a dusty plasma system as a one component plasma (OCP).  The heavy dust particles are considered as discrete particles interacting with each other through the Yukawa potential. This assumption is justified by the screening effect due to the lighter plasma components (electrons and ions). Solitons excitation at different values of the Coulomb coupling parameter (Γ) is simulated. The formation of solitons in the system using electric field pulse in a narrow region is studied. Different scenarios of the interaction of solitons are studied for: A) Two solitons with the same amplitude and opposite directions.  B) Two solitons with different amplitudes and opposite directions.  C) Two solitons with different amplitudes and propagating in the same direction

COLLISIONAL DRIFT WAVES OF A WEAKLY MAGNETIZED PLASMA

The two-fluid equations are used to derive a model of collisional drift waves for cylindrical magnetized plasmas. Both the radial electron temperature variation and the sheared BE о о× rotation in the plasmas have been taken into account. It is found that the presence of the BE о о× rotation leads to an important modification of the theory of drift waves derived by Sayasov Yu. S. and Aebischer HA (1988). The theory is applied to an experimental data of helium plasma using Runge-Kutta integration method. Our calculation shows that the temperature variation and the BE о о× rotation are important in the predictions of drift wave frequency and radial position of the maximum wave amplitude

Negative Differential Resistance, Memory and Reconfigurable Logic Functions based on Monolayer Devices derived from Gold Nanoparticles Functionalized with Electro-polymerizable Thiophene-EDOT Units

We report on hybrid memristive devices made of a network of gold nanoparticles (10 nm diameter) functionalized by tailored 3,4(ethylenedioxy)thiophene (TEDOT) molecules, deposited between two planar electrodes with nanometer and micrometer gaps (100 nm to 10 um apart), and electropolymerized in situ to form a monolayer film of conjugated polymer with embedded gold nanoparticles (AuNPs). Electrical properties of these films exhibit two interesting behaviors: (i) a NDR (negative differential resistance) behavior with a peak/valley ratio up to 17, and (ii) a memory behavior with an ON/OFF current ratio of about 1E3 to 1E4. A careful study of the switching dynamics and programming voltage window is conducted demonstrating a non-volatile memory. The data retention of the ON and OFF states is stable (tested up to 24h), well controlled by the voltage and preserved when repeating the switching cycles (800 in this study). We demonstrate reconfigurable Boolean functions in multiterminal connected NP molecule devices.Comment: Full manuscript, figures and supporting information, J. Phys. Chem. C, on line, asap (2017

Electron refraction at lateral atomic interfaces

We present theoretical simulations of electron refraction at the lateral atomic interface between a “homogeneous” Cu(111) surface and the “nanostructured” one-monolayer (ML) Ag/Cu(111) dislocation lattice. Calculations are performed for electron binding energies barely below the 1 ML Ag/ Cu(111) M-point gap (binding energy EB ¼53 meV, below the Fermi level) and slightly above its C -point energy (EB ¼160 meV), both characterized by isotropic/circular constant energy surfaces. Using plane-wave-expansion and boundary-element methods, we show that electron refraction occurs at the interface, the Snell law is obeyed, and a total internal reflection occurs beyond the critical angle. Additionally, a weak negative refraction is observed for EB ¼53 meV electron energy at beam incidence higher than the critical angle. Such an interesting observation stems from the interface phase-matching and momentum conservation with the umklapp bands at the second Brillouin zone of the dislocation lattice. The present analysis is not restricted to our Cu-Ag/Cu model system but can be readily extended to technologically relevant interfaces with spinpolarized, highly featured, and anisotropic constant energy contours, such as those characteristic for Rashba systems and topological insulators. Published by AIP Publishing.Peer ReviewedPostprint (published version

Synthesis and biological evaluation of some heterocyclic compounds

Cancer is one of the most striking diseases that has a potential impact on human health with high mortality rate. During the last century many anticancer agents have emerged but unfortunately, these agents could not provide effective solutions for cancer treatment due to side effects and resistance. All over the world, asking for new anticancer agents is still a major goal for medicinal chemists. Pyrrole and pyrrolo[2,3-d]pyrimidine scaffolds are very interesting bioactive core exhibiting several biological activities as anticancer, anti-inflammatory, antimicrobial activities. Herein, we highlighted on the anticancer activity of the pyrrole and pyrrolo[2,3-d]pyrimidine derivatives which are reported to possess anticancer activity and many of them are in market or still in clinical trials. This work deals with design and synthesis of new pyrrole and pyrrolopyrimidine derivatives. The new compounds were screened for their cytotoxic activity against HepG2 and MCF7in vitro. The most active compounds were evaluated for their VEGFR-2 inhibition in vitr

Diffusion and swelling measurements in pharmaceutical powder compacts using terahertz pulsed imaging.

Tablet dissolution is strongly affected by swelling and solvent penetration into its matrix. A terahertz-pulsed imaging (TPI) technique, in reflection mode, is introduced as a new tool to measure one-dimensional swelling and solvent ingress in flat-faced pharmaceutical compacts exposed to dissolution medium from one face of the tablet. The technique was demonstrated on three tableting excipients: hydroxypropylmethyl cellulose (HPMC), Eudragit RSPO, and lactose. Upon contact with water, HPMC initially shrinks to up to 13% of its original thickness before undergoing expansion. HPMC and lactose were shown to expand to up to 20% and 47% of their original size in 24 h and 13 min, respectively, whereas Eudragit does not undergo dimensional change. The TPI technique was used to measure the ingress of water into HPMC tablets over a period of 24 h and it was observed that water penetrates into the tablet by anomalous diffusion. X-ray microtomography was used to measure tablet porosity alongside helium pycnometry and was linked to the results obtained by TPI. Our results highlight a new application area of TPI in the pharmaceutical sciences that could be of interest in the development and quality testing of advanced drug delivery systems as well as immediate release formulations.We would like to thank Huxley Bertram Engineering Ltd.,Cambridge, UK for making time available on the compactionsimulator and Martin Bennett from Huxley Bertram for helppreparing samples. We would also like to acknowledge EvonikIndustries, Germany for providing Eudragit RSPO. S.Y. wouldlike to thank the UK Engineering and Physical Sciences Re-search Council for financial support.This is the final version of the article. It was originally published online in the Journal of Pharmaceutical Sciences, 2015, doi: 10.1002/jps.24376

Transformer Faults Classification Based on Convolution Neural Network

This paper studies the latest advances made in Deep Learning (DL) methods utilized for transformer inrush and fault currents classification. Inrush and fault currents at different operating conditions, initial flux and fault type are simulated. This paper presents a technique for the classification of power transformer faults which is based on a DL method called convolutional neural network (CNN) and compares it with traditional artificial neural network (ANN) and other techniques. The inrush and fault current signals of the transformer are simulated within MATLAB by using Fourier analyzers that provides the 2nd harmonic signal. The 2nd harmonic peak and variance statistic values of input signals of the three phases of transformer are used at different operating conditions. The resulted values are aggregated into a dataset to be used as an input for the CNN model, then training and testing the CNN model is performed. Consequently, it is obvious that the CNN algorithm achieves a better performance compared to other algorithms. This study helps with easy discrimination between normal signals and faulty signals and to determine the type of the fault to clear it easily

Pengembangan Sistem Penyediaan Air Bersih Untuk Zona Pelayanan IPA Pilolodaa Kota Gorontalo

Sistem jaringan air bersih adalah suatu sistem suplai air bersih yang meliputi sistem transmisi dan reservoar. Sistem distribusi atau perpipaan dioperasikan sedemikian rupa sehingga dapat memenuhi kebutuhan air bersih.Zona pelayanan IPA Pilolodaa terletak di Kota Barat, Kota Gorontalo. Saat ini sebagian wilayah pelayanan tersebut telah mendapat pelayanan air bersih dari PDAM, namun sebagian wilayah pelayanan tidak mendapatkan air bersih. Penyebabnya adalah wilayah tersebut berada pada dataran yang lebih tinggi dari PDAM, sehingga tekanan air untuk distribusinya terbatas.Dengan menggunakan analisa eksponensial, hasil proyeksi jumlah penduduk zona pelayanan IPA Pilolodaa pada tahun 2032 yakni berjumlah 18.537 jiwa dengan total kebutuhan air bersih mencapai 40,164 liter/detik. Agar kebutuhan air bersih terpenuhi maka dibangun 2 reservoir, masing-masing bertipe ground reservoir dengan ukuran 11m x 11m x 3m dan 15m x 15m x 3m. Sistem distribusi menggunakan sistem kombinasi antara sistem pompa dan gravitasi, dengan hasil perhitungan diameter pipa transmisi ke masing-masing reservoar adalah 175 mm dan 200 mm, untuk pipa distribusi bervariasi antara 50 mm - 200 mm. Untuk mendesain sistem penyediaan air bersih digunakan software EPANET 2.0

Increasing the “region of interest” and “time of interest”, both reduce the variability of blood flow measurements using laser speckle contrast imaging

ObjectiveBoth spatial variability and temporal variability of skin blood flow are high. Laser speckle contrast imagers (LSCI) allow non-contact, real-time recording of cutaneous blood flow on large skin surfaces. Thereafter, the observer can define different sizes for the region of interest (ROI) in the images to decrease spatial variability and different durations over which the blood flow values are averaged (time of interest, TOI) to decrease temporal variability. We aimed to evaluate the impact of the choices of ROI and TOI on the analysis of rest blood flow and post occlusive reactive hyperemia (PORH). Methods Cutaneous blood flow (CBF) was assessed at rest and during PORH. Three different sizes of ROI (1 mm2, 10 mm2 and 100 mm2), and three different TOI (CBF averaged over 1 s, 15 s, and 30 s for rest, and over 1 s, 5 s and 10 s for PORH peak) were evaluated. Inter-subjects and intra-subjects coefficient of variations (inter-CV and intra-CV) were studied. Results The inter-subject variability of CBF is about 25% at rest and is moderately improved when the size of the ROI increases (inter-CV = 31%, for 1 s and 1 mm2 versus inter-CV = 23%, for 15 s and 100 mm2). However, increasing the TOI does not improve the results. The variability of the PORH peak is lower with an inter-CV varying between 11.4% (10 s and 100 mm2) and 21.6% (5 s and 1 mm2). The lowest intra-CV for the CBF at rest was 7.3% (TOI of 15 s on a ROI of 100 mm2) and was 3.1% for the PORH peak (TOI of 10 s on a ROI of 100 mm2). Conclusion We suggest that a size of ROI larger than 10 mm2 and a TOI longer than 1 s are required to reduce the variability of CBF measurements both at rest and during PORH peak evaluations at the forearm level. Many technical aspects such as comparison of laser speckle contrast imaging and laser Doppler imaging or the effect of skin to head distance on recorded values with LCSI are required to improve future studies using this fascinating clinical tool

Multi-Layer Perceptron (MLP)-Based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) Stock Forecasting Model

The prediction of stocks in the stock market is important in investment as it would help the investor to time buy and sell transactions to maximize profits. In this paper, a Multi-Layer Perceptron (MLP)-based Nonlinear Auto-Regressive with Exogenous Inputs (NARX) model was used to predict the prices of the Apple Inc. weekly stock prices over a time horizon of 1995 to 2013. The NARX model belongs is a system identification model that constructs a mathematical model from the dynamic input/output readings of the system, and predicts the future behaviour of the system based on the constructed mathematical model. The One Step Ahead (OSA) and correlation tests were used to test validate the model. Results demonstrate the predictive ability of the model while producing Gaussian residuals (indicating the validity of the model)