Casein Grafted Maleic Anhydride Copolymer and Substituted With Procaine

In this work, Casein as a natural polymer was modified with Maleic anhydride a grafted copolymer (A1) ,then the substitution reaction was undergo between grafted maleic anhydride and procaine as amino drug, producing Casein grafted N- procienyl meleamic acid copolymer (A2) as biodegradable polymers a suitable design of drug carrier for  controlled delivery of therapeutic agent to extend period of time and increase the residence time of drug in the system . The prepare new drug copolymer was characterized by FTIR spectroscopy and controlled release was studied in different pH values 1.1and 7.4 at 37C0 .Thermo gravemetric analysis was carried out, which indicated the thermal stability of (A1) and (A2). Keywords:Casein ,Natural polymer ,Grafted copolymer

An investigation of cryptographically generated address (CGA)-based authentication for mobile IPv6

It is well known that the most promising approach to solving the problem of authentication in a mobile IPv6 network is to use CGA-based authentication. The only drawback is that CGA algorithms can be computationally expensive. This study analyses the performance of the CGA generation algorithm and proposes changes to impose a minimal computational security while maintaining reasonable performance. This study also compares the use of Rivest Shamir Adleman (RSA) signatures with the Merkle Signature Scheme (MSS) for generating CGA Signatures. It finds that using MSS significantly improves the key generation time. However, more work needs to be done to improve both the CGA generation algorithm and MSS in order to make CGA-based authentication an attractive option in MIPv6 setups

Bayesian estimation using Lindley’s approximation of Inverted Kumaraswamy distribution based on lower record values

In this paper, we have considered estimation of unknown parameters based on lower record values for Inverted Kumaraswamy distribution. Maximum likelihood and approximate Bayes estimators based on lower record values for unknown parameters of this distribution are obtained. Lindley’s approximation (L-approximation) is used to obtain approximate Bayes estimators under DeGroot loss function based on lower record values. A Simulation study and a real data analysis are presented to illustrate the results.Publisher's Versio

Local pre-processing for node classification in networks : application in protein-protein interaction

Network modelling provides an increasingly popular conceptualisation in a wide range of domains, including the analysis of protein structure. Typical approaches to analysis model parameter values at nodes within the network. The spherical locality around a node provides a microenvironment that can be used to characterise an area of a network rather than a particular point within it. Microenvironments that centre on the nodes in a protein chain can be used to quantify parameters that are related to protein functionality. They also permit particular patterns of such parameters in node-centred microenvironments to be used to locate sites of particular interest. This paper evaluates an approach to index generation that seeks to rapidly construct microenvironment data. The results show that index generation performs best when the radius of microenvironments matches the granularity of the index. Results are presented to show that such microenvironments improve the utility of protein chain parameters in classifying the structural characteristics of nodes using both support vector machines and neural networks

Analyzing Facebook Mobile Usage: Efficacy and ESL Learners’ Writing Proficiency

Facebook has leveraged rapid technological and societal changes over the past decade and has emerged as the largest social networking platform. However, research on Facebook has been limited, particularly when examining its potential to improve English as a second language (ESL) writing in comparison to a control group. The study aims to explore the morphological, syntactic, and orthographical aspects of ESL writing through an experimental group [N = 30] using Facebook on mobile and a control group [N = 30] with a traditional teaching approach. The experimental and control groups undergo observation through twice-weekly, in-class-focused free writing sessions for 10 weeks. The progress of the learners’ writing was tracked using pre- and post-tests to assess its impact. The analysis of variance (ANOVA) test revealed that the experimental group made more significant advancements in writing by reducing morphological, syntactic, and orthographical errors compared to the control group. These results validate previous studies that support the use of Facebook on mobile devices in ESL courses and emphasize the need for further research comparing Facebook with other writing platforms

A Potential Bio-sorbent for Heavy Metals in the Remediation of Waste Water

Bay leaves are used for flavoring in cold drinks production, in bakery goods, sauces, confectionary products and liquors. The waste generated from these sources has been valorized by attempting the remediation of waste water. Hence, adsorption of toxic metals onto Bay leaves has been investigated after optimizing the experimental parameters, namely the pH, contact time, adsorbent and Zn(II) concentrations as well as the temperature of the equilibrium mixture (consisting of the metal solution in contact with the adsorbent). The participation of the constituent functional groups, of the adsorbent, was ascertained with Fourier transform spectroscopic studies. The mode of adsorption was examined by employing important isotherm models, namely Langmuir, Freundlich and Dubinin-Radushkevich models. The adsorption process was found to follow pseudo-first order kinetic model and also followed the intraparticle diffusion up to 60 minutes of contact time. The thermodynamic parameters suggest the spontaneous nature of adsorption

A Simple and Cost-Effective EPON-Based Next Generation Mobile Backhaul RAN Architecture

This study proposes a novel, simple and cost-effective PON-based next generation mobile backhaul RAN architecture that enables redistribution of some of the intelligence currently centralized in the Mobile Packet Core (MPC) platform out into the access nodes of the RAN. Specifically, this work proposes a fully distributed ring-based EPON architecture that enables the support of a converged PON-4G/5G mobile WiMAX/LTE access networking transport infrastructure to seamlessly backhaul both mobile and wireline multimedia traffic and services

Iranian Authors\u27 Contributions to the Library Philosophy and Practice

Objective: This study aimed to conduct a bibliometric analysis and scientific visualization of the contribution made by Iranians\u27 authors in the Library Philosophy and Practice (LPP) from 2006 to 2019. Material and Methods: This bibliometric analysis used Scopus database for retrieving data on all papers published by Iranians in LPP during the study time span. VOSviewer and Microsoft Excel software packages were used for data analysis. Findings: Out of 139 papers authored by Iranians in LPP, the first published paper belonged to 2006. An increasing trend can be seen in annual publication number, with 1 and 64 papers in 2007 and 2019, respectively. The first ranked active author was Khasseh A.A. with 9 papers. Shahid Beheshti University of Medical Sciences and Payame Noor University were in the top of the contributing institutes, each with authoring 20 papers followed by Islamic Azad University, Central with 13 papers. Iranian more collaborated with Indians. The mean rate of received citations per paper was 0.62. The top three highly-cited authors were Isfandyiari-Moghaddam, A. (with 13), Khasseh A.A. and Saberi M.K. (each with 11) and Biranvand (with 10), respectively. Citing some known journals in their papers, Iranian researchers considered main topics in LIS field, including bibliometrics, altmetrics and library management and technologies. Conclusion: This study is a relatively comprehensive bibliometric analysis of Iranians\u27 contributions to LPP. The result can be helpful as a road map for researchers and readers countrywide as well as the editorial team of the journal

Chatbot Design Challenges and the Effect on User Behavior

Chatbots are efficient artificial intelligence tools employed frequently across various industries such as healthcare, tourism, entertainment, and education, to assist in performing repetitive activities requiring a conversation, thereby facilitating humans to focus on more innovative tasks. This chapter reviews the design challenges of two types of chatbots classified based on their interaction modes: dyadic chatbots interacting with one individual at a time; and polyadic chatbots interacting with multiple individuals simultaneously. Further, the chapter identified the associated challenges in the chatbots, namely: engagement, trust, and human likeliness based on personality types - at a higher level in the chatbot design, together with the impact of each challenge on the user behavior. The authors review the literature in the relevant areas to pinpoint the research gaps requiring more focus within each area of challenge. The research community can address these identified research areas, which will eventually promote a more efficient human-machine collaboration