Amino Acid Patterns of Different Brands of Corn Steep Liquor

The free amino acids as well as the total amino acid content of Russian corn steep liquor (CSL), French CSL, British CSL, Italian CSL, German dried version of CSL, and Egyptian CSL were identified. The free amino acids and those obtained after the acid hydrolysis in each sample were almost the same. Alanine was the predominant free amino acid found. The major amino acids were arginine, aspartic acid, histidine, glutamic acid, glycine, leucine, lysine, serine and valine with the exception of Italian CSL and German dried CSL, while phenylalanine, methionine, tyrosine, proline as well as cystine were present in lesser amounts. The relation between the amino acid constituents of the different brands of CSL and their penicillin activity were discussed.     

Environmentally Friendly Energy Harvesting Using Magnetocaloric Solid-State Nanoparticles as Magnetic Refrigerator

Journal of Low Temperature Physics - A phenomenological model (PM) is applied to simulate the magnetocaloric (MC) effect of iron oxide nanoparticles (IONs). Based on modeling results, MC parameters...     

Analyzing Customer Reviews on Social Media via Applying Association Rule

The rapid growth of the use of social media opens up new challenges and opportunities to analyze various aspects and patterns in communication. In-text mining, several techniques are available such as information clustering, extraction, summarization, classification. In this study, a text mining framework was presented which consists of 4 phases retrieving, processing, indexing, and mine association rule phase. It is applied by using the association rule mining technique to check the associated term with the Huawei P30 Pro phone. Customer reviews are extracted from many websites and Facebook groups, such as re-view.cnet.com, CNET. Facebook and amazon.com technology, where customers from all over the world placed their notes on cell phones. In this analysis, a total of 192 reviews of Huawei P30 Pro were collected to evaluate them by text mining techniques. The findings demonstrate that Huawei P30 Pro, has strong points such as the best safety, high-quality camera, battery that lasts more than 24 hours, and the processor is very fast. This paper aims to prove that text mining decreases human efforts by recognizing significant documents. This will lead to improving the awareness of customers to choose their products and at the same time sales managers also get to know what their products were accepted by customers suspended.     

Machine Learning-based USD/PKR Exchange Rate Forecasting Using Sentiment Analysis of Twitter Data

This study proposes an approach based on machine learning to forecast currency exchange rates by applying sentiment analysis to messages on Twitter (called tweets). A dataset of the exchange rates between the United States Dollar (USD) and the Pakistani Rupee (PKR) was formed by collecting information from a forex website as well as a collection of tweets from the business community in Pakistan containing finance-related words. The dataset was collected in raw form, and was subjected to natural language processing by way of data preprocessing. Response variable labeling was then applied to the standardized dataset, where the response variables were divided into two classes: “1” indicated an increase in the exchange rate and “ −1” indicated a decrease in it. To better represent the dataset, we used linear discriminant analysis and principal component analysis to visualize the data in three-dimensional vector space. Clusters that were obtained using a sampling approach were then used for data optimization. Five machine learning classifiers—the simple logistic classifier, the random forest, bagging, naïve Bayes, and the support vector machine—were applied to the optimized dataset. The results show that the simple logistic classifier yielded the highest accuracy of 82.14% for the USD and the PKR exchange rates forecasting.     

Numerical analysis of optical feedback phenomenon and intensity noise of fibre‐grating semiconductor lasers

This paper demonstrates numerical analysis of the dynamics and intensity noise of fibre‐grating semiconductor lasers (FGSLs). The induced phenomenon of strong optical feedback (OFB) is analysed. The simulations are based on an improved time‐delay rate equations model of a single‐mode laser that takes into account the multiple round‐trips of the lasing field in the fibre cavity. The analyses are performed in terms of the temporal trajectory of the laser intensity, bifurcation diagram and relative intensity noise (RIN). We explore influence of the fibre‐cavity length on the dynamics and RIN. The results show that when the fibre cavity is short, the regime of strong OFB is characterized by either continuous‐wave (CW) operation or periodic pulsation. The pulsation frequency is locked at the frequency separation of either the compound‐cavity modes or the external fibre‐cavity modes. The corresponding RIN level is close to or higher than the level of the solitary laser depending on pulse symmetry. When the fibre cavity is long, the laser exhibits unstable dynamics over wider range of OFB. Moreover, the strong‐OFB pulsation becomes beating quasi‐periodic at the relaxation oscillation frequency and the fibre‐cavity mode‐separation frequency. Copyright © 2007 John Wiley & Sons, Ltd.     

Overview of Factors Affecting the Behavior of Reinforced Concrete Columns with Imperfections at High Temperature

Fire Technology - In this paper, the behavior of initially imperfect reinforced concrete columns with different eccentricity and end restraint conditions at elevated temperatures is studied. By...     

Development of a Fuzzy Multi-Objective Heuristic Model for Optimum Water Allocation

Water Resources Management - A challenging issue in optimal allocating water resources is uncertainty in parameters of a model. In this paper, a fuzzy multi-objective model was proposed to maximize...     

Collaboration networks of arab biomedical researchers

Social networks (SN) consist of a set of actors and connections between them. A collaboration network (ColNet) is a special type of SN, in which the actors represent researchers and the link between them indicate that they have co-authored at least one paper. ColNet analysis reveals how researchers interact and behave. A wide range of applications can be based on such studies. The current works on ColNet usually focus on a specific domain/discipline, country/geographical region or time interval. In our study, we focus on one of the understudied regions (the Arab world), and present a novel study on the ColNet of researchers in this region. The domain of interest in our study is biomedicine. We construct, analyze, and study ColNet of biomedical researchers in the Arab world. We divide the region of interest (the Arab world) into four geographical regions and look into the evolution of ColNet of each region separately over time. Our analysis reveals that there is an increase in the number of both authors and publications over time, and that authors tend to work in increasingly larger groups rather than working individually, which is consistent with what is assumed about the nature of research in this field. Our analysis also reveals that a researcher’s productivity is correlated with the amount of change in his/her circle of collaborators over time. For example, researchers working in stable or fixed groups and researchers who have completely different research group every few years are not necessarily the most productive ones.