Intrinsic Mean Square Displacements in Proteins

The thermal mean square displacement (MSD) of hydrogen in proteins and its associated hydration water is measured by neutron scattering experiments and used an indicator of protein function. The observed MSD as currently determined depends on the energy resolution width of the neutron scattering instrument employed. We propose a method for obtaining the intrinsic MSD of H in the proteins, one that is independent of the instrument resolution width. The intrinsic MSD is defined as the infinite time value of that appears in the Debye-Waller factor. The method consists of fitting a model to the resolution broadened elastic incoherent structure factor or to the resolution dependent MSD. The model contains the intrinsic MSD, the instrument resolution width and a rate constant characterizing the motions of H in the protein. The method is illustrated by obtaining the intrinsic MSD of heparan sulphate (HS-0.4), Ribonuclease A and Staphysloccal Nuclase (SNase) from data in the literature

Opinion Mining on Non-English Short Text

As the type and the number of such venues increase, automated analysis of sentiment on textual resources has become an essential data mining task. In this paper, we investigate the problem of mining opinions on the collection of informal short texts. Both positive and negative sentiment strength of texts are detected. We focus on a non-English language that has few resources for text mining. This approach would help enhance the sentiment analysis in languages where a list of opinionated words does not exist. We propose a new method projects the text into dense and low dimensional feature vectors according to the sentiment strength of the words. We detect the mixture of positive and negative sentiments on a multi-variant scale. Empirical evaluation of the proposed framework on Turkish tweets shows that our approach gets good results for opinion mining

The improved diesel-like fuel from upgraded tire pyrolytic oil

Tire pyrolytic oil (TPO) obtained from thermal pyrolysis of scrap tires is not a diesel equivalent fuel which can be used directly in vehicles due to its high density, viscosity, sulfur content, low flash point and low cetane index. It can only be used in a limited way by mixing with diesel fuel (DF) in amounts less than 30 %. In this study, the pyrolysis of scrap tires was carried out at a heating rates of 5 and 10 °C min-1 in the range of 450–600 °C, using a mixture of hierarchical zeolite (HZSM-5), mesoporous silica (MCM-41) and quicklime (CaO) as the catalyst. The obtained TPO and catalytic pyrolytic oil (CPO) were upgraded by pre-treatment, and distillation consisting of a mixture of Cu(I)-loaded mesoporous aluminosilicate (Cu(I)–MAS) and MCM-41, desulfurization and decolourization steps, respectively. To obtain diesel-like fuel, the upgraded catalytic pyrolytic oil (UCPO) and biodiesel (PBD) obtained from palm oil were blended in certain proportions. Density, viscosity, flash point and cetane index of the obtained diesel-like fuels were found within the limit values of diesel fuel. © 2022 Serbian Chemical Society. All rights reserved

Bioinspired Optoelectronic Nose with Nanostructured Wavelength-Scalable Hollow-Core Infrared Fibers

Cataloged from PDF version of article.A digital photonic nose concept based on infrared absorption inside a hollow core infrared-transmitting fi ber array is presented. Wavelength- scalable photonic bandgap fi bers fi lter specifi c energy photons from a blackbody source, where volatile compounds selectively absorb photons depending on their chemical absorption spectrum. The pattern resulting in the detector array is processed as a binary signature

Gold nanoparticle/polymer nanofibrous composites by laser ablation and electrospinning

Cataloged from PDF version of article.Poly(vinylpyrolidone) (PVP) nanofibers incorporating gold nanoparticles (Au-NPs) were produced in combination with laser ablation and electrospinning techniques. The Au-NPs were directly synthesized in PVP solution by laser ablation and then, the electrospinning of PVP/Au-NPs solution was carried out for obtaining nanofibrous composites. The presence of Au-NPs in the PVP nanofibers was confirmed by SEM, TEM and EDX analyses. The SEM imaging elucidated that the electrospun PVP/Au-NPs nanofibers were bead-free having average fiber diameter of 810 ± 480 nm. The TEM imaging indicated that the Au-NPs were in spherical shape having diameters in the range of 5 to 20 nm and the Au-NPs were more or less dispersed homogeneously in the PVP nanofiber matrix. The FTIR study suggested the presence of molecular interactions between PVP matrix and the Au-NPs in the nanofibrous composites. The UV–Vis measurement confirmed the enhancement of the optical properties of the PVP/Au-NPs nanofibers in the solid state due to the surface plasma resonance effect of Au-NPs

Photoluminescent electrospun polymeric nanofibers incorporating germanium nanocrystals

Cataloged from PDF version of article.The photoluminescent germanium nanocrystals (Ge-NCs) were successfully incorporated into electrospun polymeric nanofiber matrix in order to develop photoluminescent nanofibrous composite web. In the first step, the synthesis of Ge-NCs was achieved by nanosecond pulsed laser ablation of bulk germanium wafer immersed in organic liquid. The size, the structural and the chemical characteristics of Ge-NCs investigated by TEM, XPS, XRD and Raman spectroscopy revealed that the Ge-NCs were highly pure and highly crystalline having spherical shape within 3–20 nm particle size distribution. In the second step, Ge-NCs were mixed with polyvinyl alcohol (PVA) polymer solution, and then, Ge-NC/PVA nanofibers were obtained via electrospinning technique. The electrospinning of Ge-NCs/PVA nanoweb composite structure was successful and bead-free Ge-NCs/PVA nanofibers having average fiber diameter of 185 ± 40 nm were obtained. The STEM analysis of the electrospun Ge-NCs/PVA nanofibers elucidated that the Ge-NCs were distributed homogeneously in the polymeric nanofiber matrix. The UV–Vis absorption and photoluminescence spectroscopy studies indicated the quantum confinement effect of Ge-NCs on the optical properties of the electrospun Ge-NCs/PVA nanoweb

MBotCS: A mobile botnet detection system based on machine learning

As the use of mobile devices spreads dramatically, hackers have started making use of mobile botnets to steal user information or perform other malicious attacks. To address this problem, in this paper we propose a mobile botnet detection system, called MBotCS. MBotCS can detect mobile device traffic indicative of the presence of a mobile botnet based on prior training using machine learning techniques. Our approach has been evaluated using real mobile device traffic captured from Android mobile devices, running normal apps and mobile botnets. In the evaluation, we investigated the use of 5 machine learning classifier algorithms and a group of machine learning box algorithms with different validation schemes. We have also evaluated the effect of our approach with respect to its effect on the overall performance and battery consumption of mobile devices

The inner circumstellar disk of the UX Ori star V1026 Sco

The UX Ori type variables (named after the prototype of their class) are intermediate-mass pre-main sequence objects. One of the most likely causes of their variability is the obscuration of the central star by orbiting dust clouds. We investigate the structure of the circumstellar environment of the UX~Ori star V1026 Sco (HD 142666) and test whether the disk inclination is large enough to explain the UX Ori variability. We observed the object in the low-resolution mode of the near-infrared interferometric VLTI/AMBER instrument and derived H- and K-band visibilities and closure phases. We modeled our AMBER observations, published Keck Interferometer observations, archival MIDI/VLTI visibilities, and the spectral energy distribution using geometric and temperature-gradient models. Employing a geometric inclined-ring disk model, we find a ring radius of 0.15 +- 0.06 AU in the H band and 0.18 +- 0.06 AU in the K band. The best-fit temperature-gradient model consists of a star and two concentric, ring-shaped disks. The inner disk has a temperature of 1257^{+133}_{-53} K at the inner rim and extends from 0.19 +- 0.01 AU to 0.23 +- 0.02 AU. The outer disk begins at 1.35^{+0.19}_{-0.20} AU and has an inner temperature of 334^{+35}_{-17} K. The derived inclination of 48.6^{+2.9}_{-3.6}deg approximately agrees with the inclination derived with the geometric model (49 +- 5deg in the K band and 50 +- 11deg in the H band). The position angle of the fitted geometric and temperature-gradient models are 163 +- 9deg (K band; 179 +- 17deg in the H band) and 169.3^{+4.2}_{-6.7}deg, respectively. The narrow width of the inner ring-shaped model disk and the disk gap might be an indication for a puffed-up inner rim shadowing outer parts of the disk. The intermediate inclination of ~50deg is consistent with models of UX Ori objects where dust clouds in the inclined disk obscure the central star