Influence of Different Additives on the Interaction of Quinolone Antibiotic Drug with Surfactant: Conductivity and Cloud Point Measurement Study

Conductometric and cloud point (CP) measurement studies have been performed to investigate the interaction of tetradecyltrimethylammonium bromide (TTAB) and Triton® X-100 (TX-100) with ciprofloxacin hydrochloride (CFH) in different solvents over the temperature range of 295.15–315.15 K. CFH is used for the treatment of various bacterial infections. The observed critical micelle concentration (CMC) values of TTAB were found to be reduced in the presence of electrolytes (Na₂SO₄/Na₃PO₄), and this reduction proceeds with the elevation of salt concentration. The order of the CMC of TTAB follows the trend: > >. The observed CMC values of TTAB were found to increase with increasing temperature and decrease with increasing concentration of CFH in aqueous medium. The values of Gibbs free energy of micellization () for the TTAB/TTAB + CFH mixture were found to be negative, implying spontaneous micellization. The estimated CP of TX-100 decreases with increasing concentration of TX-100 in aqueous medium. The CP values first decrease with increasing concentration of CFH and then increase at higher concentration of CFH almost in all cases investigated. The values of free energy of clouding were found to be positive in all cases studied implying that phase separation of TX-100 was nonspontaneous. The other thermodynamic parameters associated with the micellization of TTAB and the phase separation of TX-100 were estimated and explained.     

Synthesis of amino-cosubstituted polyorganophosphazenes and fabrication of their nanoparticles for anticancer drug delivery

The development of safe drug carriers is cardinal in cancer therapy, which can target the cancer cells and release the loaded drug on-demand without damaging the healthy cells of the body. In our work, we synthesized three different biodegradable polymers, poly[(ethyl aminobezoate) (ethyl glycinato) phosphazenes] (PABGPs), in different mole ratio of side groups. The successful synthesis of these PABGPs was confirmed by ¹H NMR, ³¹P NMR, FT-IR, and gel permeation chromatography. These PABGPs were fabricated into drug (camptothecin, CPT, a hydrophobic anticancer drug) loaded nanoparticles. These drug-loaded nanoparticles showed good drug release behaviors under normal physiological conditions (pH 7.4 and temperature 37°C). These PABGPs-based nanoparticles may find their application as effective drug carriers for cancer therapy.     

A panoramic view of Li7P3S11 solid electrolytes synthesis,structural aspects and practical challenges for all-solid-state lithium batteries

The development of an inorganic electrochemical stable solid-state electrolyte is essentially responsible for future state-of-the-art all-solid-state lithium batteries (ASSLBs). Because of their advantages in safety, working temperature, high energy density, and packaging, ASSLBs can develop an ideal energy storage system for modern electric vehicles (EVs). A solid electrolyte (SE) model must have an economical synthesis approach, exhibit electrochemical and chemical stability, high ionic conductivity, and low interfacial resistance. Owing to its highest conductivity of 17 mS·cm^-1, and deformability, the sulfide-based Li₇P₃S₁₁ solid electrolyte is a promising contender for the high-performance bulk type of ASSLBs. Herein, we present a current glimpse of the progress of synthetic procedures, structural aspects, and ionic conductivity improvement strategies. Structural elucidation and mechanistic approaches have been extensively discussed by using various characterization techniques. The chemical stability of Li₇P₃S₁₁ could be enhanced via oxide doping, and hard and soft acid/base (HSAB) concepts are also discussed. The issues to be undertaken for designing the ideal solid electrolytes, interfacial challenges, and high energy density have been discoursed. This review aims to provide a bird's eye view of the recent development of Li₇P₃S₁₁-based solid-state electrolyte applications and explore the strategies for designing new solid electrolytes with a target-oriented approach to enhance the efficiency of high energy density all-solid-state lithium batteries.     

An improved remote user authentication scheme with key agreement

In distributed systems, user authentication schemes based on password and smart card are widely used to ensure only authorized access to the protected services. Recently, Chang et al. presented an untraceable dynamic-identity-based user authentication scheme with verifiable-password-update. In this research, we illustrate that Chang et al.’s scheme violates the purpose of dynamic-identity contrary to authors’ claim. We show that once the smart card of an arbitrary user is lost, passwords of all registered users are at risk. Using information from an arbitrary smart card, an adversary can impersonate any user of the system. In addition, its password change phase has loopholes and is misguiding. The scheme has no provision for session key agreement and the smart card lacks any verification mechanism. Then we come-up with an improved remote user authentication scheme with the session key agreement, and show its robustness over related schemes.     

An adaptive watermarking scheme for e-government document images

This paper proposes an adaptive watermarking scheme for e-government document images. The adaptive scheme combines the discrete cosine transform (DCT) and the singular value decomposition (SVD) using luminance masking. As a core of masking model in the human visual system (HVS), luminance masking is implemented to improve noise sensitivity. Genetic algorithm (GA), subsequently, is employed for the optimization of the scaling factor of the masking. Involving a number of steps, the scheme proposed through this study begins by calculating the mask of the host image using luminance masking. It is then continued by transforming the mask on each area into all frequencies domain. The watermark image, following this, is embedded by modifying the singular values of DCT-transformed host image with singular values of mask coefficient of host image and the control parameter of DCT-transformed watermark image using Genetic Algorithm (GA). The use of both the singular values and the control parameter respectively, in this case, is not only to improve the sensitivity of the watermark performance but also to avoid the false positive problem. The watermark image, afterwards, is extracted from the distorted images. The experiment results show the improved adaptive performance of the proposed scheme is in resistant to several types of attacks in comparison with the previous schemes; the adaptive performance refers to the adaptive parameter of the luminance masking functioned to improve the performance or robustness of an image from any attacks.     

An architecture modeling framework for probabilistic prediction

In the design phase of business and IT system development, it is desirable to predict the properties of the system-to-be. A number of formalisms to assess qualities such as performance, reliability and security have therefore previously been proposed. However, existing prediction systems do not allow the modeler to express uncertainty with respect to the design of the considered system. Yet, in contemporary business, the high rate of change in the environment leads to uncertainties about present and future characteristics of the system, so significant that ignoring them becomes problematic. In this paper, we propose a formalism, the Predictive, Probabilistic Architecture Modeling Framework (P²AMF), capable of advanced and probabilistically sound reasoning about business and IT architecture models, given in the form of Unified Modeling Language class and object diagrams. The proposed formalism is based on the Object Constraint Language (OCL). To OCL, P²AMF adds a probabilistic inference mechanism. The paper introduces P²AMF, describes its use for system property prediction and assessment and proposes an algorithm for probabilistic inference.     

Wear failure of a leaded bronze bearing: Correlation between plant experience and laboratory wear test data

This paper describes an investigation on the failure of a large leaded bronze bearing that supports a nine-ton roller of a plastic calendering machine. At the end of the normal service life of a good bearing, which lasted for seven years, a new bearing was installed. However the new one failed catastrophically within a few days, generating a huge amount of metallic wear debris and causing pitting on the surface of the cast iron roller. Following the failure, samples were collected from both good and failed bearings. The samples were analyzed chemically and their microstructures examined. Both samples were subjected to accelerated wear tests in a laboratory type pin-on-disk apparatus. During the tests, the bearing materials acted as pins, which were pressed against a rotating cast iron disk. The wear behaviors of both bearing materials were studied using weight loss measurement. The worn surfaces of samples and the wear debris were examined by light optical microscope, scanning electron microscope, and energy-dispersive x-ray microanalyzer. It was found that the laboratory pin-on-disk wear data correlated well with the plant experience. It is suggested that the higher lead content (∼18%) of the good bearing compared with 7% lead of the failed bearing helped to establish a protective transfer layer on the worn surface. This transfer layer reduced metal-to-metal contact between the bearing and the roller and resulted in a lower wear rate. The lower lead content of the failed bearing does not allow the establishment of a well-protected transfer layer and leads to rapid wear.     

Adaptive image denoising using cuckoo algorithm

This paper presents a novel denoising approach based on smoothing linear and nonlinear filters combined with an optimization algorithm. The optimization algorithm used was cuckoo search algorithm and is employed to determine the optimal sequence of filters for each kind of noise. Noises that would be eliminated form images using the proposed approach including Gaussian, speckle, and salt and pepper noise. The denoising behaviour of nonlinear filters and wavelet shrinkage threshold methods have also been analysed and compared with the proposed approach. Results show the robustness of the proposed filter when compared with the state-of-the-art methods in terms of peak signal-to-noise ratio and image quality index. Furthermore, a comparative analysis is provided between the said optimization algorithm and the genetic algorithm.     

Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

Meteorological changes urge engineering communities to look for sustainable and clean energy technologies to keep the environment safe by reducing CO2 emissions. The structure of these technologies relies on the deep integration of advanced data-driven techniques which can ensure efcient energy generation, transmission, and distribution. After conducting thorough research for more than a decade, the concept of the smart grid (SG) has emerged, and its practice around the world paves the ways for efcient use of reliable energy technology. However, many developing features evoke keen interest and their improvements can be regarded as the next-generation smart grid (NGSG). Also, to deal with the non-linearity and uncertainty, the emergence of data-driven NGSG technology can become a great initiative to reduce the diverse impact of non-linearity. This paper exhibits the conceptual framework of NGSG by enabling some intelligent technical features to ensure its reliable operation, including intelligent control, agent-based energy conversion, edge computing for energy management, internet of things (IoT) enabled inverter, agent-oriented demand side management, etc. Also, a study on the development of data-driven NGSG is discussed to facilitate the use of emerging data-driven techniques (DDTs) for the sustainable operation of the SG. The prospects of DDTs in the NGSG and their adaptation challenges in real-time are also explored in this paper from various points of view including engineering, technology, et al. Finally, the trends of DDTs towards securing sustainable and clean energy evolution from the NGSG technology in order to keep the environment safe is also studied, while some major future issues are highlighted. This paper can ofer extended support for engineers and researchers in the context of data-driven technology and the SG.