Experimental elucidation of templated crystallization and secondary processing of peptides

The crystallization of peptides offers a sustainable and inexpensive alternative to the purification process. In this study, diglycine was crystallised in porous silica, showing the porous templates' positive yet discriminating effect. The diglycine induction time was reduced by five-fold and three-fold upon crystallising in the presence of silica with pore sizes of 6 nm and 10 nm, respectively. The diglycine induction time had a direct relationship with the silica pore size. The stable form (α-form) of diglycine was crystallised in the presence of porous silica, with the diglycine crystals obtained associated with the silica particles. Further, we studied the mechanical properties of diglycine tablets for their tabletability, compactability, and compressibility. The mechanical properties of the diglycine tablets were similar to those of pure MCC, even with the presence of diglycine crystals in the tablets. The diffusion studies of the tablets using the dialysis membrane presented an extended release of diglycine through the dialysis membrane, confirming that the peptide crystal can be used for oral formulation. Hence, the crystallization of peptides preserved their mechanical and pharmacological properties. More data on different peptides can help us produce oral formulation peptides faster than usual

An Empirical Estimation of CSS Cognitive Radio Network Performance under Spectrum Sensing Data Falsification Attack

Cooperative spectrum sensing (CSS) significantly improves the performance of spectrum sensing process in cognitive radio networks (CRNs). Individual spectrum sensing by a cognitive radio (CR) is often inaccurate as the channel often experiences fading and shadowing effects. CSS has been shown to have many advantages in terms of spectrum use and robustness. Despite these facts, a CSS scheme also vulnerable to many security attacks from Malicious users (MUs). In order to get unfair USAge of spectrum band, MUs can generate false spectrum sensing reports to disturb the good secondary users (SUs) decision about presence of primary user (PU). In this paper, we consider the spectrum sensing data falsification attack (SSDF) in CSS and propose the protocol to identify and eliminate the attacker or Malicious user (MU) to improve the network performance. In SSDF attack, MUs send the false spectrum sensing results to fusion center (FC) with the intension that it should make wrong decision about spectrum sensing. In this scenario, FC acts as a data collector to fuse the reports sent by SUs

Detecting Malicious Applications from the cloud by using user feedback method

As in recent period of computers and internets, mobiles devices, Smartphone’s plays a vital role in human day to day activities. Also now a days Smartphone’s & tablets are becoming very popular especially android based Smartphone’s are gaining much more popularity as compared to Apple’s iOS. These Smartphone’s having lot of applications and features based on only internet but these new emerging features of these devices give opportunity to new malwares & threats. Android is comparatively new OS hence its makes very hard to detect and prevent these viruses and malwares attacks by using some basic traditional mechanisms. So security of these Smartphone’s is now becoming very popular issue of researchers. The lack of standard security mechanism in Android applications is very useful to hackers. So to overcome these various pitfalls we use cloud services as a security weapon for providing decent security system for Android applications

Investigating sizing induced surface alterations in crystalline powders using surface energy heterogeneity determination

Particle sizing is the most commonly employed and critical unit operation across powder processing industries. In this work, we show the surface energy changes prompted by the sizing operations like milling and sieving in α-lactose monohydrate powders using Finite Dilution Inverse gas chromatography (FD-IGC) analysis. Three separate sieved fractions of α-lactose monohydrate powder were divided into a top, middle and bottom fraction from the same starting material. Similarly, a custom grade α-lactose monohydrate was milled for a different duration to produce two milled samples with different median particle sizes. Sieved sample results showed that the bottom fraction exhibited higher heterogeneity with higher dispersive (γd) surface energy values ranging from 42.5 mJ/m2 to 45.9 mJ/m2 compared to the top and middle fractions. The finest fraction contains more cleaved surfaces that are exposed during the preparation process, i.e. milling, of the material resulting in different surface properties. Furthermore, the surface energy analysis of the milled samples revealed slight but vital differences in the γd heterogeneity profiles. The site-specific distribution of energies was obtained using the Boltzmann probability distribution model and revealed two distinct regions for crystalline α-lactose monohydrate. Thus, our work confirmed that sizing operations like milling and sieving affect the surface energy of the particulate solids due to the changes in properties like size, shape, exposure of internal cleavage planes, etc. and that the surface energy heterogeneity determination using FD-IGC helped in characterising these changes

A numerical analysis of the influence of material properties on dry powder coating performance

Dry powder coating is a preferable surface modification technique over the traditional aqueous coating technique due to reduced energy waste and less environmental impact. Despite the benefits of dry powder coating, excessive amount of coating powder energy input is often applied to ensure sufficient coating is achieved. In this study, the Discrete Element Method (DEM) is utilised to assess the influence of material properties on dry coating efficiency in a blade-driven system. Granular Bond number is used to predict coating performance based on multiple simulations with varied material properties. This provides insight on the optimal range of material properties (size ratio, density ratio and surface energy) to achieve uniformly distributed coatings, thus providing precise control of the quantity of coating material required and minimising energy consumption

Use of shear sensitive coloured guest component to track powder mixing in adhesive binary mixtures

The mixing performance in binary powder blends with components exhibiting guest and host type interactions was assessed by tracking the colour change of the mixture. The operation parameters like mixing time and speed were studied in compositions containing lactose monohydrate as host and iron oxide nanoparticle as coloured guest components. The mixing characteristics were analysed through visual imaging and colorimetric estimations. Furthermore, surface analytical techniques like scanning electron microscope (SEM) for surface area coverage (SAC) determination and Finite Dilution Inverse Gas chromatography (FD-IGC) for surface energy heterogeneity characterisation were employed. The mixing sensitivity of the coloured tracer and the consequent colour transitions under different conditions helped in validating the mixing performance and operation conditions. The FD-IGC results showed a lowering of the energetic heterogeneity for better quality mixtures. Thus, a shear sensitive coloured nano-tracer can be utilised for a simple, quick and cost-effective estimation of the mixture quality and for the validation of mixing process

Influence of interparticle structuring on the surface energetics of a binary powder system

The structuring of component particles in binary compositions affects the solid-solid interfacial properties. This work reports the effect of interparticle interactions in binary powder compositions of D-Mannitol and glass beads through the heterogeneity data obtained from Finite Dilution Inverse Gas Chromatography (FD-IGC). Three different scenarios viz. structured, random and segregated systems of the binary powder composition were considered for the analysis in the IGC column. Binary mixtures with large size disparity between the components produced structured mixtures exhibiting a guest-host type of interactions and energetic homogeneity irrespective of the energetics of the finer component. Random and segregated systems revealed a heterogeneous trend in the data indicating preferential probing of the active sites of the composition, particularly at the lower probe coverages. The results demonstrate that in the multicomponent binary systems the surface energetics is influenced by the solid-solid interfaces and structuring of the component particles within the mix i.e., the surface energy analysis could reveal a mixing behavior in powders. Furthermore, an adsorption energy distribution model based on Boltzmann statistics and simulation fitting approach was employed to deconvolute the distribution of the changing energy landscape of the binary mixtures

A regime map for dry powder coating: the influence of material properties and process parameters

Copyright \ua9 2023 Khala, Hare, Karde and Heng. A numerical study is carried out to investigate the combined influence of material properties and process parameters on coating quality in a high shear mixer (specifically an FT4 Powder Rheometer) to construct a regime map. The Discrete Element Method (DEM) is employed to simulate a range of material properties (size, density, and surface energy) and process parameters (impeller speed and mixing time) via Design of Experiments (DoE). A robust regime map is proposed for prediction of dry coating performance based on dimensionless Stokes deformation number (Stdef) and granular Bond number (Bo). The regime map provides insight on the optimal range of material properties and process parameters to achieve high coating levels in a high-shear bladed mixer. Furthermore, the minimum energy required to achieve optimal coating performance as well as regions of poor coating quality due to guest detachment exacerbated by excessive energy input can be identified from the regime map, thus reducing wastage of energy and coating material required. The regime map enables the required mixing time for optimal coating to be determined so long as particle size distributions and surface energies are known

COMPREHENSIVE ANALYSIS OF SOME RECENT COMPETITIVE CBIR TECHNIQUES

In today’s real life applications complexity of multimedia contents is significantly increased. This is highly demanding the development of effective retrieval systems to satisfy human desires. Recently, extensive research efforts have been carried out in the field of content-based image retrieval (CBIR). These research efforts are based on various parameters; feature extraction (to find content of image), similarity matching (compare the content of a query image with content of other images), indexing (index images based on their content), and relevance feedback (consider users view to get better output). The efforts result many promising solutions in designing effective and interactive CBIR systems. This paper mainly includes study of some recent CBIR techniques with the goal to design efficient system. Additionally, this study presents a detailed framework of CBIR system. Further it includes improvements achieved in the major areas like feature extraction, indexing, similarity matching, relevance feedback