Water Soluble Chitosan Derivatives via the Freeze Concentration Technique

Chitosan has been an attractive biopolymer for decades, but its processability is lowered by its poor solubility, especially in physiological pH values. Freeze concentrated reactions of chitosan with several organic acids including acrylic, citraconic, itaconic, and maleic acid revealed improved solubility and morphological properties. Solubility traits were assessed with a modified ninhydrin test. Chitosan derivatives were characterized by ATR-FTIR and morphological characteristics were determined by SEM. This study is a unique approach to chemically modify chitosan to enhance water solubility.

Antioxidative, Anticholinesterase and Anti-Neuroinflammatory Properties of Malaysian Brown and Green Seaweeds

Diminished antioxidant defense or increased production of reactive oxygen species in the biological system can result in oxidative stress which may lead to various neurodegenerative diseases including Alzheimer’s disease (AD). Microglial activation also contributes to the progression of AD by producing several proinflammatory cytokines, nitric oxide (NO) and prostaglandin E2 (PGE2). Oxidative stress and inflammation have been reported to be possible pathophysiological mechanisms underlying AD. In addition, the cholinergic hypothesis postulates that memory impairment in patient with AD is also associated with the deficit of cholinergic function in the brain. Although a number of drugs have been approved for the treatment of AD, most of these synthetic drugs have diverse side effects and yield relatively modest benefits. Marine algae have great potential in pharmaceutical and biomedical applications as they are valuable sources of bioactive properties such as anticoagulation, antimicrobial, antioxidative, anticancer and anti-inflammatory. Hence, this study aimed to provide an overview of the properties of Malaysian seaweeds (Padina australis, Sargassum polycystum and Caulerpa racemosa) in inhibiting oxidative stress, neuroinflammation and cholinesterase enzymes. These seaweeds significantly exhibited potent DPPH and moderate superoxide anion radical scavenging ability (P

In silico Studies on Selected Drug Targets for Combating Drug Resistance in Plasmodium falcifarum

With drug resistance becoming widespread in Plasmodium falciparum infections, the development of the alternative drugs is the desired strategy for prevention and cure of malaria. Three drug targets were selected to screen promising drug molecules from the GSK library of 13469 molecules. Using an in silico structure-based drug designing approach, the differences in binding energies of the substrate and inhibitor were exploited between target sites of parasite and human to design a drug molecule against Plasmodium. The docking studies have shown several promising molecules from GSK library with more effective binding as compared to the already known inhibitors for the drug targets. Though stronger interaction has been shown by several molecules as compared to the reference, few molecules have shown the potential as drug candidates though in vitro studies are required to validate the results. In case of thymidylate synthase-dihydrofolatereductase (TS-DHFR), three compounds have shown promise for future studies as potential drugs.

The Design and Applied of Learning Management System via Social Media on Internet: Case Study of Operating System for Business Subject

Learning Management System (LMS) is the system which uses to manage the learning in order to grouping the content and learning activity between the lecturer and learner including online examination and evaluation. Nowadays, it is the borderless learning era so the learning activities can be accessed from everywhere in the world and also anytime via the information technology and media. The learner can easily access to the knowledge so the different in time and distance is not a constraint for learning anymore. The learning pattern which was used in this research is the integration of the in-class learning and online learning via internet and will be able to monitor the progress by the Learning management system which will create the fast response and accessible learning process via the social media. In order to increase the capability and freedom of the learner, the system can show the current and history of the learning document, video conference and also has the chat room for the learner and lecturer to interact to each other. So the objectives of the “The Design and Applied of Learning Management System via Social Media on Internet: Case Study of Operating System for Business Subject” are to expand the opportunity of learning and to increase the efficiency of learning as well as increase the communication channel between lecturer and student. The data of this research was collect from 30 users of the system which are students who enroll in the subject. And the result of the research is in the “Very Good” which is conformed to the hypothesis.

Online Monitoring Rheological Property of Polymer Melt during Injection Molding

The detection of the polymer melt state during manufacture process is regarded as an efficient way to control the molded part quality in advance. Online monitoring rheological property of polymer melt during processing procedure provides an approach to understand the melt state immediately. Rheological property reflects the polymer melt state at different processing parameters and is very important in injection molding process especially. An approach that demonstrates how to calculate rheological property of polymer melt through in-process measurement, using injection molding as an example, is proposed in this study. The system consists of two sensors and a data acquisition module can process the measured data, which are used for the calculation of rheological properties of polymer melt. The rheological properties of polymer melt discussed in this study include shear rate and viscosity which are investigated with respect to injection speed and melt temperature. The results show that the effect of injection speed on the rheological properties is apparent, especially for high melt temperature and should be considered for precision molding process.

Annoyance Caused by Air Pollution: A Comparative Study of Two Industrialized Regions

Although there had been a many studies that shows the impact of air pollution on physical health, comparatively less was known of human behavioral responses and annoyance impacts. Annoyance caused by air pollution is a public health problem because it can be an ambient stressor causing stress and disease and can affect quality of life. The objective of this work is to evaluate the annoyance caused by air pollution in two different industrialized urban areas, Dunkirk (France) and Vitoria (Brazil). The populations of these cities often report feeling annoyed by dust. Surveys were conducted, and the collected data were analyzed using statistical analyses. The results show that sociodemographic variables, importance of air quality, perceived industrial risk, perceived air pollution and occurrence of health problems play important roles in the perceived annoyance. These results show the existence of a common problem in geographically distant areas and allow stakeholders to develop prevention strategies.

Comparative in silico and in vitro Study of N-(1- Methyl-2-Oxo-2-N-Methyl Anilino-Ethyl) Benzene Sulfonamide and Its Analogues as an Anticancer Agent

Doxorubicin, also known as Adriamycin, is an anthracycline class of drug used in cancer chemotherapy. It is used in the treatment of non-Hodgkin’s lymphoma, multiple myeloma, acute leukemia, breast cancer, lung cancer, endometrium cancer and ovary cancers. It functions via intercalating DNA and ultimately killing cancer cells. The major side effects of doxorubicin are hair loss, myelosuppression, nausea & vomiting, oesophagitis, diarrhea, heart damage and liver dysfunction. The minor modifications in the structure of compound exhibit large variation in the biological activity, has prompted us to carry out the synthesis of sulfonamide derivatives. Sulfonamide is an important feature with broad spectrum of biological activity such as antiviral, antifungal, diuretics, antiinflammatory, antibacterial and anticancer activities. Structure of the synthesized compound N-(1-methyl-2-oxo-2-N-methyl anilinoethyl) benzene sulfonamide confirmed by proton nuclear magnetic resonance (1H NMR),13C NMR, Mass and FTIR spectroscopic tools to assure the position of all protons and hence stereochemistry of the molecule. Further we have reported the binding potential of synthesized sulfonamide analogues in comparison to doxorubicin drug using Auto Dock 4.2 software. Computational binding energy (B.E.) and inhibitory constant (Ki) has been evaluated for the synthesized compound in comparison of doxorubicin against Poly (dA-dT).Poly (dA-dT) and Poly (dG-dC).Poly (dG-dC) sequences. The in vitro cytotoxic study against human breast cancer cell lines confirms the better anticancer activity of the synthesized compound over currently in use anticancer drug doxorubicin. The IC50 value of the synthesized compound is 7.12 μM whereas for doxorubicin is 7.2 μM.

Robust Fault Diagnosis for Wind Turbine Systems Subjected to Multi-Faults

Operations, maintenance and reliability of wind turbines have received much attention over the years due to the rapid expansion of wind farms. This paper explores early fault diagnosis technique for a 5MW wind turbine system subjected to multiple faults, where genetic optimization algorithm is employed to make the residual sensitive to the faults, but robust against disturbances. The proposed technique has a potential to reduce the downtime mostly caused by the breakdown of components and exploit the productivity consistency by providing timely fault alarms. Simulation results show the effectiveness of the robust fault detection methods used under Matlab/Simulink/Gatool environment.

High Accuracy ESPRIT-TLS Technique for Wind Turbine Fault Discrimination

ESPRIT-TLS method appears a good choice for high resolution fault detection in induction machines. It has a very high effectiveness in the frequency and amplitude identification. Contrariwise, it presents a high computation complexity which affects its implementation in real time fault diagnosis. To avoid this problem, a Fast-ESPRIT algorithm that combined the IIR band-pass filtering technique, the decimation technique and the original ESPRIT-TLS method was employed to enhance extracting accurately frequencies and their magnitudes from the wind stator current with less computation cost. The proposed algorithm has been applied to verify the wind turbine machine need in the implementation of an online, fast, and proactive condition monitoring. This type of remote and periodic maintenance provides an acceptable machine lifetime, minimize its downtimes and maximize its productivity. The developed technique has evaluated by computer simulations under many fault scenarios. Study results prove the performance of Fast- ESPRIT offering rapid and high resolution harmonics recognizing with minimum computation time and less memory cost.

Mapping of Siltations of AlKhod Dam, Muscat, Sultanate of Oman Using Low-Cost Multispectral Satellite Data

Remote sensing plays a vital role in mapping of resources and monitoring of environments of the earth. In the present research study, mapping and monitoring of clay siltations occurred in the Alkhod Dam of Muscat, Sultanate of Oman are carried out using low-cost multispectral Landsat and ASTER data. The dam is constructed across the Wadi Samail catchment for ground water recharge. The occurrence and spatial distribution of siltations in the dam are studied with five years of interval from the year 1987 of construction to 2014. The deposits are mainly due to the clay, sand and silt occurrences derived from the weathering rocks of ophiolite sequences occurred in the Wadi Samail catchment. The occurrences of clays are confirmed by minerals identification using ASTER VNIR-SWIR spectral bands and Spectral Angle Mapper supervised image processing method. The presence of clays and their spatial distribution are verified in the field. The study recommends the technique and the low-cost satellite data to similar region of the world.

An In-Depth Analysis of Open Data Portals as an Emerging Public E-Service

Governments collect and produce large amounts of data. Increasingly, governments worldwide have started to implement open data initiatives and also launch open data portals to enable the release of these data in open and reusable formats. Therefore, a large number of open data repositories, catalogues and portals have been emerging in the world. The greater availability of interoperable and linkable open government data catalyzes secondary use of such data, so they can be used for building useful applications which leverage their value, allow insight, provide access to government services, and support transparency. The efficient development of successful open data portals makes it necessary to evaluate them systematic, in order to understand them better and assess the various types of value they generate, and identify the required improvements for increasing this value. Thus, the attention of this paper is directed particularly to the field of open data portals. The main aim of this paper is to compare the selected open data portals on the national level using content analysis and propose a new evaluation framework, which further improves the quality of these portals. It also establishes a set of considerations for involving businesses and citizens to create eservices and applications that leverage on the datasets available from these portals.

An Extensible Software Infrastructure for Computer Aided Custom Monitoring of Patients in Smart Homes

This paper describes the tradeoffs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The backend consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Wound Healing Dressing and Some Composites Such as Zeolite, TiO2, Chitosan and PLGA: A Review

The development of Drugs Delivery System (DDS) has been widely investigated in the last decades. In this paper, first a general overview of traditional and modern wound dressing is presented. This is followed by a review of what scientists have done in the medical environment, focusing on the possibility to develop a new alternative for DDS through transdermal pathway, aiming to treat melanoma skin cancer.

Excitonic Refractive Index Change in High Purity GaAs Modulator at Room Temperature for Optical Fiber Communication Network

In this paper, we have compared and analyzed the electroabsorption properties between with and without excitonic effect bulk in high purity GaAs spatial light modulator for optical fiber communication network. The eletroabsorption properties such as absorption spectra, change in absorption spectra, change in refractive index and extinction ration has been calculated. We have also compared the result of absorption spectra and change in absorption spectra with the experimental results and found close agreement with experimental results.

GSM Based Smart Patient Monitoring System

In this paper, we propose an intelligent system that is used for monitoring the health conditions of patients. Monitoring the health condition of patients is a complex problem that involves different medical units and requires continuous monitoring especially in rural areas because of inadequate number of available specialized physicians. The proposed system will improve patient care and drive costs down comparing to the existing system in Jordan. The proposed system will be the start point to faster and improve the communication between different units in the health system in Jordan. Connecting patients and their physicians beyond hospital doors regarding their geographical area is an important issue in developing the health system in Jordan. The ability of making medical decisions, the quality of medical is expected to be improved.

Gammarus:Asellus Ratio as an Index of Organic Pollution – (A Case Study in Markeaton, Kedleston Hall, and Allestree Park Lakes Derby) UK

Macro invertebrates have been used to monitor organic pollution in rivers and streams. Several biotic indices based on macro invertebrates have been developed over the years including the Biological Monitoring Working Party (BMWP). A new biotic index, the Gammarus:Asellus ratio has been recently proposed as an index of organic pollution. This study tested the validity of the Gammarus:Asellus ratio as an index of organic pollution, by examining the relationship between the Gammarus:Asellus ratio and physical chemical parameters, and other biotic indices such as BMWP and, Average Score Per Taxon (ASPT) from lakes and streams at Markeaton Park, Allestree Park and Kedleston Hall, Derbyshire. Macro invertebrates were sampled using the standard five minute kick sampling techniques physical and chemical environmental variables were obtained based on standard sampling techniques. Eighteen sites were sampled, six sites from Markeaton Park (three sites across the stream and three sites across the lake). Six sites each were also sampled from Allestree Park and Kedleston Hall lakes. The Gammarus:Asellus ratio showed an opposite significant positive correlations with parameters indicative of organic pollution such as the level of nitrates, phosphates, and calcium and also revealed a negatively significant correlations with other biotic indices (BMWP/ASPT). The BMWP score correlated positively significantly with some water quality parameters such as dissolved oxygen and flow rate, but revealed no correlations with other chemical environmental variables. The BMWP score was significantly higher in the stream than the lake in Markeaton Park, also The ASPT scores appear to be significantly higher in the upper Lakes than the middle and lower lakes. This study has further strengthened the use of BMWP/ASPT score as an index of organic pollution. But additional application is required to validate the use of Gammarus:Asellus as a rapid bio monitoring tool.

Using Reservoir Models for Monitoring Geothermal Surface Features

As the use of geothermal energy grows internationally more effort is required to monitor and protect areas with rare and important geothermal surface features. A number of approaches are presented for developing and calibrating numerical geothermal reservoir models that are capable of accurately representing geothermal surface features. The approaches are discussed in the context of cases studies of the Rotorua geothermal system and the Orakei-korako geothermal system, both of which contain important surface features. The results show that models are able to match the available field data accurately and hence can be used as valuable tools for predicting the future response of the systems to changes in use.

Effect of Pollination on Qualitative Characteristics of Rapeseed (Brassica campestris L. var. toria) Seed in Chitwan, Nepal

An experiment was conducted to determine the effect of pollination on seed quality of rapeseed in Chitwan, Nepal during 2012-2013. The experiment was designed in Randomized Complete Block with four replications and five treatments. The rapeseed plots were caged with mosquito nets at 10% flowering except natural pollination. Two-framed colonies of Apis mellifera L. and Apis cerana F. were introduced separately for pollination, and control plot caged without pollinators. The highest germination percent was observed on Apis cerana F. pollinated plot seeds (90.50% germination) followed by Apis mellifera L. pollinated plots (87.25 %) and lowest on control plots (42.00% germination) seeds. Similarly, seed test weight of Apis cerana F. pollinated plots (3.22 gm/ 1000 seed) and Apis mellifera L. pollinated plots (2.93 gm/1000 seed) were and lowest on control plots (2.26 gm/ 1000 seed) recorded. Likewise, oil content was recorded highest on pollinated by Apis cerana F. (36.1%) followed by pollinated by Apis mellifera L. (35.4%) and lowest on control plots (32.8%). This study clearly indicated pollination increases the seed quality of rapeseed and therefore, management of honeybee is necessary for producing higher quality of rapeseed under Chitwan condition.

Antioxidant Enzymes and Crude Mitochondria ATPases in the Radicle of Germinating Bean (Vigna unguiculata) Exposed to Different Concentrations of Crude Oil

The study examined the effect of Bonny Light whole crude oil (WC) and its water soluble fraction (WSF) on the activities of antioxidant enzymes (catalase (CAT) and superoxide dismutase (SOD)) and crude mitochondria ATPases in the radicle of germinating bean (Vigna unguiculata). The percentage germination, level of lipid peroxidation, antioxidant enzyme and mitochondria Ca2+ and Mg2+ ATPase activities were measured in the radicle of bean after 7, 14 and 21 days post germination. Viable bean seeds were planted in soils contaminated with 10ml, 25ml and 50ml of whole crude oil (WC) and its water soluble fraction (WSF) to obtain 2, 5 and 10% v/w crude oil contamination. There was dose dependent reduction of the number of bean seeds that germinated in the contaminated soils compared with control (p

Urban Growth Prediction in Athens, Greece, Using Artificial Neural Networks

Urban areas have been expanded throughout the globe. Monitoring and modelling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modelling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.