Integrating biopharmaceutics risk assessment and in vivo absorption model in formulation development of BCS class I drug using the QbD approach

Objective: Clinically relevant critical quality attributes (CQA’s) were identified for the development of generic drug products containing fluconazole and potential design spaces relevant to the clinical application of the drug candidate was explored.

Significance: A simplified scoring system for the biopharmaceutics risk assessment roadmap (BioRAM) is proposed to guide product development.

Methods: Factorial design of experiments was employed to study the effect of formulation and process variables on CQA’s. The in vivo model was developed for predicting the fraction of drug absorbed and to identify the effect of formulation components on drug absorption.

Results: BioRAM yielded low scores for fluconazole absorption with respect to severity (risks of sub and supra-bioavailable drug products), probability of incidence of bioinequivalent results and capacity of detection. The results demonstrated that dissolution was highly influenced by the active pharmaceutical ingredient (API) polymorphism and the ratio of diluents. Process variables (mixing time, lubricant concentration, lubrication time and filling speed) did not impact the clinical outcome of the formulation with respect to dissolution and content uniformity.

Conclusions: Understanding the clinical implications of the adopted formulation approach led to the construction of purposeful design space and control strategy.     

A Secure Method for Data Storage and Transmission in Sustainable Cloud Computing

Cloud computing is a technology that provides secure storage space for the customer’s massive data and gives them the facility to retrieve and transmit their data efficiently through a secure network in which encryption and decryption algorithms are being deployed. In cloud computation, data processing, storage, and transmission can be done through laptops and mobile devices. Data Storing in cloud facilities is expanding each day and data is the most significant asset of clients. The important concern with the transmission of information to the cloud is security because there is no perceivability of the client’s data. They have to be dependent on cloud service providers for assurance of the platform’s security. Data security and privacy issues reduce the progression of cloud computing and add complexity. Nowadays; most of the data that is stored on cloud servers is in the form of images and photographs, which is a very confidential form of data that requires secured transmission. In this research work, a public key cryptosystem is being implemented to store, retrieve and transmit information in cloud computation through a modified Rivest-Shamir-Adleman (RSA) algorithm for the encryption and decryption of data. The implementation of a modified RSA algorithm results guaranteed the security of data in the cloud environment. To enhance the user data security level, a neural network is used for user authentication and recognition. Moreover; the proposed technique develops the performance of detection as a loss function of the bounding box. The Faster Region-Based Convolutional Neural Network (Faster R-CNN) gets trained on images to identify authorized users with an accuracy of 99.9% on training.     

Prediction of COVID-19 Cases Using Machine Learning for Effective Public Health Management

COVID-19 is a pandemic that has affected nearly every country in the world. At present, sustainable development in the area of public health is considered vital to securing a promising and prosperous future for humans. However, widespread diseases, such as COVID-19, create numerous challenges to this goal, and some of those challenges are not yet defined. In this study, a Shallow Single-Layer Perceptron Neural Network (SSLPNN) and Gaussian Process Regression (GPR) model were used for the classification and prediction of confirmed COVID-19 cases in five geographically distributed regions of Asia with diverse settings and environmental conditions: namely, China, South Korea, Japan, Saudi Arabia, and Pakistan. Significant environmental and non-environmental features were taken as the input dataset, and confirmed COVID-19 cases were taken as the output dataset. A correlation analysis was done to identify patterns in the cases related to fluctuations in the associated variables. The results of this study established that the population and air quality index of a region had a statistically significant influence on the cases. However, age and the human development index had a negative influence on the cases. The proposed SSLPNN-based classification model performed well when predicting the classes of confirmed cases. During training, the binary classification model was highly accurate, with a Root Mean Square Error (RMSE) of 0.91. Likewise, the results of the regression analysis using the GPR technique with Matern 5/2 were highly accurate (RMSE = 0.95239) when predicting the number of confirmed COVID-19 cases in an area. However, dynamic management has occupied a core place in studies on the sustainable development of public health but dynamic management depends on proactive strategies based on statistically verified approaches, like Artificial Intelligence (AI). In this study, an SSLPNN model has been trained to fit public health associated data into an appropriate class, allowing GPR to predict the number of confirmed COVID-19 cases in an area based on the given values of selected parameters. Therefore, this tool can help authorities in different ecological settings effectively manage COVID-19.     

A hybrid genetic algorithm and tabu search approach for post enrolment course timetabling

The post enrolment course timetabling problem (PECTP) is one type of university course timetabling problems, in which a set of events has to be scheduled in time slots and located in suitable rooms according to the student enrolment data. The PECTP is an NP-hard combinatorial optimisation problem and hence is very difficult to solve to optimality. This paper proposes a hybrid approach to solve the PECTP in two phases. In the first phase, a guided search genetic algorithm is applied to solve the PECTP. This guided search genetic algorithm, integrates a guided search strategy and some local search techniques, where the guided search strategy uses a data structure that stores useful information extracted from previous good individuals to guide the generation of offspring into the population and the local search techniques are used to improve the quality of individuals. In the second phase, a tabu search heuristic is further used on the best solution obtained by the first phase to improve the optimality of the solution if possible. The proposed hybrid approach is tested on a set of benchmark PECTPs taken from the international timetabling competition in comparison with a set of state-of-the-art methods from the literature. The experimental results show that the proposed hybrid approach is able to produce promising results for the test PECTPs.     

Some constructions of the join of fuzzy subgroups and certain lattices of fuzzy subgroups with sup property

In this paper, some new lattices of fuzzy substructures are constructed. For a given fuzzy set μ in a group G, a fuzzy subgroup S(μ) generated by μ is defined which helps to establish that the set L_s of all fuzzy subgroups with sup property constitutes a lattice. Consequently, many other sublattices of the lattice L of all fuzzy subgroups of G like , etc. are also obtained. The notion of infimum is used to construct a fuzzy subgroup i(μ) generated by a given fuzzy set μ, in contrast to the usual practice of using supremum. In the process a new fuzzy subgroup i(μ)^∗ is defined which we shall call a shadow fuzzy subgroup of μ. It is established that if μ has inf property, then i(μ)^∗ also has this property.     

The thematic structure of passenger comfort experience and its relationship to the context features in the aircraft cabin

This paper describes passenger comfort as an experience generated by the cabin interior features. The findings of previous studies are affirmed regarding a set of 22 context features. Passengers experience a certain level of comfort when these features impact their body and elicit subjective perceptions. New findings characterise these perceptions in the form of eight themes and outline their particular eliciting features. Comfort is depicted as a complex construct derived by passengers' perceptions beyond the psychological (i.e. peace of mind) and physical (i.e. physical well-being) aspects, and includes perceptual (e.g. proxemics) and semantic (e.g. association) aspects. The seat was shown to have a focal role in eliciting seven of those themes and impacting comfort through its diverse characteristics. In a subsequent study, a group of aircraft cabin interior designers highlighted the possibility of employing the eight themes and their eliciting features as a framework for design and evaluation of new aircraft interiors.     

Deposition of titanium nitride on Si(1 0 0) wafers using plasma focus

Titanium nitride thin films were deposited on Si(1 0 0) substrates by using a low energy (2.3 KJ) Mather-type plasma focus device. The composition of the deposited films was characterized by X-ray diffraction (XRD). The crystallite size has strong dependence on the numbers of focus shots. The crystallinity of TiN thin films is found to increase with increasing the number of focus shots. The effect of different number of focus shots on micro structural changes of thin films was characterized by Scanning Electron Microscope (SEM) and Atomic Force Microscope (AFM). SEM results showed net-like structure for film deposited for 15 numbers of shots, which are elongated grains of Si₃N₄ in amorphous form embedded into TiN crystals. The average surface roughness was calculated from AFM images of the thin films. These results indicated that the average surface roughness increased for films deposited with increased number of focus shots. The least crystallite size and roughness are observed for film deposited with 25 focus shots.     

Inhibitory effect of antioxidant peptides derived from Pinctada fucata protein on ultraviolet-induced photoaging in mice

The superposition of ultraviolet radiation induced (photodamage) aging process is photoaging. Antioxidant peptides derived from Pinctada fucata protein as raw materials were smeared the back of light-aging. The effect of antioxidant peptides on wrinkle generating, skin restoration capacity after pulled up and measure the active of the superoxide dismutase (SOD), catalase (CAT), hydroxyproline, and glutathione peroxidase (GSH-Px) and lipid peroxidation by kit and histological examination of UVB-irradiated skin that the mitotic index of basal cells, the thickness ratio of the epidermis and dermis, fibroblast count, density of collagen fibers and volume density of dermal microvasculature were studied. The result showed that antioxidant peptides had slowed down the progress of wrinkles formation and skin elasticity deceasing induced by acute irradiation of UVB. It also significantly controlled the speed of lipid peroxidation and the reduction of the activity of SOD, GSH-Px, hydroxyprodline and CAT. Histopathological studies showed that the derived antioxidant peptides could reduce the thickness ratio of the dermis and epidermis and increase the mitotic index of basal cells, fibroblast count, density of collagen fibers and volume density of dermal microvascular, these outcomes confirmed the protective role of antioxidant peptides in the process of photoaging.     

Enhanced non-linear optical properties of Eu3+ activated glasses by embedding silver nanoparticles

Tri-positive lanthanide ion (Eu³⁺) activated glasses doped with different concentrations of silver (Ag0₎ nanoparticles obtained using thermal reducing agent were fabricated by applying the method of melt quench. The formation of Ag⁰ nanoparticles in glasses was revealed by the surface plasmon resonance (SPR) peak in the absorption spectra. Transmission electron microscopic measurements confirmed the presence of spherically shaped Ag⁰ nanoparticles of different size distribution. The absorption spectra showed a red–shift of the SPR peak with an increase in AgNO₃ concentration occurring through Ostwald's ripening process because of the growth of particle size (as evidenced from microscope images). The non-linear optical (NLO) and optical limiting measurements were performed in the near infrared spectral region and femtosecond pulse excitation. The non-linear parameters were found to increase as the AgNO₃ concentration increased to 0.6 mol %, however, the parameters subsequently decreased at higher doping level. The optical limiting threshold values demonstrated a reverse trend. The increase in non-linear optical properties regarding Ag nanoparticles concentration attributed to the enhancement of polarizabilities of glasses that occurred through local field stimulated by SPR of Ag nanoparticles when exposed to laser radiation of high energy. The increase in NLO coefficients (particularly the non-linear absorption coefficient) and the decrease in optical limiting threshold values with AgNO₃ concentration (up to 0.6 mol %) indicated that these glasses containing 0.6 mol % AgNO₃ are useful for the construction of the power optical limiters that function at the infrared region in the femtosecond pulse regime.     

A Comparison between Different Ohmic Contacts for ZnO Thin Films

There are several metals that form ohmic contacts for ZnO thin films, such as copper, aluminum and silver. The aim of this work is to make a comparison between these ohmic contacts. To achieve this purpose,polycrystalline ZnO thin films were prepared by the spray pyrolysis technique, and characterized by the I–V measurements at room temperature. Two strips of each metal were thermally evaporated on the surface of the film and measurements were first recorded in the dark and room light, then in the dark before and after annealing for Al,which was found to be the best in the set. Films with aluminum contacts gave the smallest resistivity, best ohmicity and they are slightly affected by light as required. On the other hand, copper was found to be the worst, and films with copper contacts gave the largest resistivity, worst ohmicity and they are the most affected by light. Annealing improved the aluminum contacts due to alloying and doping.