Study the effect of thin film thickness on the optical features of (IR5 laser dye/CdSe nanoparticles) samples

The linear optical features such as (transmittance T, absorbance A, the effective length , absorption coefficient and refractive index ) for the thin films samples of (3x10-3 mol/l of (IR5) laser dye, 0.02 gm of (CdS) nanoparticles and 0.04 gm of pp polymer) had been studied at different values of film thickness in one time and at different number of Yb:GdVO4 laser pulses. The non-linear optical features in terms of transmittance difference Δ−, non-linear refractive index 2, non–linear phase shift Δ non-linear absorption coefficient and minimum normalized transmittance () have been computed in relation to obtained normalized transmittance data from setup of Z-scan with open and closed apertures, calculated for (3x10-3 mol/l of (IR5) laser dye, 0.02 gm of (CdSe) nanoparticles and 0.04 gm of (pp) polymer) thin films at different values of film thickness at in one time and at different Yb:GdVO4 laser pulses. Thick films causes in deleting the non-linear effects generated by different layers. The (CdSe) nanoparticles leads to an absorption shifting of the wavelengths to lengthier wavelengths of red shift. So, this can be used in selecting the nanoparticles and medium with applicable exciting wavelengths. The film thickness and the laser pulses have the main effects in consolidating the Non-linear optical features

A User-Centric and Sentiment Aware Privacy-Disclosure Detection Framework Based on Multi-Input Neural Network

Data and information privacy is a major concern of today’s world. More specifically, users’ digital privacy has become one of the most important issues to deal with, as advancements are being made in information sharing technology. An increasing number of users are sharing information through text messages, emails, and social media without proper awareness of privacy threats and their consequences. One approach to prevent the disclosure of private information is to identify them in a conversation and warn the dispatcher before the conveyance happens between the sender and the receiver. Another way of preventing information (sensitive) loss might be to analyze and sanitize a batch of offline documents when the data is already accumulated somewhere. However, automating the process of identifying user-centric privacy disclosure in textual data is challenging. This is because the natural language has an extremely rich form and structure with different levels of ambiguities. Therefore, we inquire after a potential framework that could bring this challenge within reach by precisely recognizing users’ privacy disclosures in a piece of text by taking into account - the authorship and sentiment (tone) of the content alongside the linguistic features and techniques. The proposed framework is considered as the supporting plugin to help text classification systems more accurately identify text that might disclose the author’s personal or private information

Modeling of Personalized Privacy Disclosure Behavior: A Formal Method Approach

In order to create user-centric and personalized privacy management tools, the underlying models must account for individual users' privacy expectations, preferences, and their ability to control their information sharing activities. Existing studies of users' privacy behavior modeling attempt to frame the problem from a request's perspective, which lack the crucial involvement of the information owner, resulting in limited or no control of policy management. Moreover, very few of them take into the consideration the aspect of correctness, explainability, usability, and acceptance of the methodologies for each user of the system. In this paper, we present a methodology to formally model, validate, and verify personalized privacy disclosure behavior based on the analysis of the user's situational decision-making process. We use a model checking tool named UPPAAL to represent users' self-reported privacy disclosure behavior by an extended form of finite state automata (FSA), and perform reachability analysis for the verification of privacy properties through computation tree logic (CTL) formulas. We also describe the practical use cases of the methodology depicting the potential of formal technique towards the design and development of user-centric behavioral modeling. This paper, through extensive amounts of experimental outcomes, contributes several insights to the area of formal methods and user-tailored privacy behavior modeling

High-Porosity Metal Foams: Potentials, Applications, and Formulations

This chapter is aimed as a concise review, but well-focused on the potentials of what is known as “High-porosity metal foams,” and hence, the practical applications where such promising media have been/can be employed successfully, particularly in the field of managing, recovering, dissipating, or enhancing heat transfer. Furthermore, an extensive comparison is conducted between the formulations presented so far for the geometrical and thermal characteristics concerning the heat and fluid flow in open-cell metal foams

A hard look at the X-ray spectral variability of NGC 7582

NGC 7582 (z = 0.005264; D = 22.5 Mpc) is a highly variable, changing-look AGN. In this work, we explore the X-ray properties of this source using XMM-Newton and NuSTAR archival observations in the 3-40 keV range, from 2001 to 2016. NGC 7582 exhibits a long-term variability between observations but also a short-term variability in two observations that has not been studied before. To study the variability, we perform a time-resolved spectral analysis using a phenomenological model and a physically-motivated model (uxclumpy). The spectral fitting is achieved using a nested sampling Monte Carlo method. uxclumpy enables testing various geometries of the absorber that may fit AGN spectra. We find that the best model is composed of a fully covering clumpy absorber. From this geometry, we estimate the velocity, size and distance of the clumps. The column density of the absorber in the line of sight varies from Compton-thin to Compton-thick between observations. Variability over the timescale of a few tens of kilo-seconds is also observed within two observations. The obscuring clouds are consistent with being located at a distance not larger than 0.6 pc, moving with a transverse velocity exceeding $\sim 700$ km s$^{-1}$. We could put only a lower limit on the size of the obscuring cloud being larger than $10^{13}$ cm. Given the sparsity of the observations, and the limited exposure time per observation available, we cannot determine the exact structure of the obscuring clouds. The results are broadly consistent with comet-like obscuring clouds or spherical clouds with a non-uniform density profile.Comment: 14 pages, 12 figures, accepted for publication in MNRA

Adaptive control of four-quadrant DC-DC converters in both discontinuous and continuous conduction modes

The inherently different dynamics of a DC-DC converter while operating in both continuous conduction mode (CCM) and discontinuous conduction mode (DCM) necessitate an advanced controller to control the inductor current. A conventional PI controller cannot be used across both modes since it does not guarantee a smooth transition between both modes. Furthermore, in time-varying input-output voltage applications of the four-quadrant converter such as in battery charging applications, the location of the boundary between the CCM and the DCM changes dynamically, creating an uncertainty. Therefore, a robust controller is required to accurately track the inductor current in the presence of uncertainties. Thus, an adaptive controller is proposed in this work, which is based on the general inverse model of the four-quadrant converter in both modes. Moreover, gain scheduling is used to switch the parameters of the controller as the converter transits between the DCM and the CCM. The adaptability and effectiveness of the controller in ensuring a smooth transition is validated by numerical simulations conducted on various converter topologies. Experimental results are also presented for a buck converter

Selected reactive oxygen species and antioxidant enzymes in common bean after Pseudomonas syringae pv. phaseolicola and Botrytis cinerea infection

Phaseolus vulgaris cv. Korona plants were inoculated with the bacteria Pseudomonas syringae pv. phaseolicola (Psp), necrotrophic fungus Botrytis cinerea (Bc) or with both pathogens sequentially. The aim of the experiment was to determine how plants cope with multiple infection with pathogens having different attack strategy. Possible suppression of the non-specific infection with the necrotrophic fungus Bc by earlier Psp inoculation was examined. Concentration of reactive oxygen species (ROS), such as superoxide anion (O2 -) and H2O2 and activities of antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD) were determined 6, 12, 24 and 48 h after inoculation. The measurements were done for ROS cytosolic fraction and enzymatic cytosolic or apoplastic fraction. Infection with Psp caused significant increase in ROS levels since the beginning of experiment. Activity of the apoplastic enzymes also increased remarkably at the beginning of experiment in contrast to the cytosolic ones. Cytosolic SOD and guaiacol peroxidase (GPOD) activities achieved the maximum values 48 h after treatment. Additional forms of the examined enzymes after specific Psp infection were identified; however, they were not present after single Bc inoculation. Subsequent Bc infection resulted only in changes of H2O2 and SOD that occurred to be especially important during plant–pathogen interaction. Cultivar Korona of common bean is considered to be resistant to Psp and mobilises its system upon infection with these bacteria. We put forward a hypothesis that the extent of defence reaction was so great that subsequent infection did not trigger significant additional response