Optimization algorithms for steady state analysis of self excited induction generator

The current publication is directed to evaluate the steady state performance of three-phase self-excited induction generator (SEIG) utilizing particle swarm optimization (PSO), grey wolf optimization (GWO), wale optimization algorithm (WOA), genetic algorithm (GA), and three MATLAB optimization functions (fminimax, fmincon, fminunc). The behavior of the output voltage and frequency under a vast range of variation in the load, rotational speed and excitation capacitance is examined for each optimizer. A comparison made shows that the most accurate results are obtained with GA followed by GWO. Consequently, GA optimizer can be categorized as the best choice to analyze the generator under various conditions

DEVELOPMENT OF NEW AS-PCR BASED ANALYTICAL APPROACH FOR DETECTING THE SINGLE NUCLEOTIDE POLYMORPHISM OF AGTR.1 GENE

Objective: Angiotensin II is a potent vasoactive peptide that causes blood vessels to constrict, resulting in increased blood pressure. It acts through at least two types of receptors. The angiotensin II receptor type 1 gene (AGTR1) encodes the type 1 receptor (AT1). The AT1 receptor mediates the major cardiovascular effects of angiotensin II. A single nucleotide polymorphism (SNP) in the 3'-untranslated region of the AGTR1 gene (A1166C) has been linked in several studies with essential hypertension. A new analytical approach based on allele-specific polymerase chain reaction (AS-PCR) was developed in this study to detect this SNP.Methods: Allele-specific primers were designed by using appropriate software to allow the PCR amplification only if the nucleotide at the 3'-end of the primer complements the base of the wild-type or variant-type DNA sample. The primers were then tested for uniqueness using the Basic Local Alignment Search Tool search engine. The developed method was tested on 21 samples.Results: The developed method accurately detected the genotype of the SNP. Our results were validated using the reference method for detecting A1166C SNP, PCR-restriction fragment length polymorphism (PCR-RFLP). The use of AS-PCR technique reduced both time and cost of the A1166C AGTR1 genotyping. Moreover, the AS-PCR test is more suitable as it reduces the false results due to incompletely digested PCR products, which can be a problem with PCR-RFLP technique. Conclusion: The use of this method will enable researchers to carry out genetic polymorphism studies for the association of A1166C SNP in AGTR1 gene with essential hypertension and other heart diseases without the use of expensive instrumentation and reagents.Keywords: Essential hypertension, SNP, Angiotensin II type 1 receptor gene (AGTR1), Renin-angiotensin system, AS-PC

Market and companies confidence index and their relation with stock return

This paper analyzes the relationship between market confidence and stock return.In addition, it also aims to analyze the relationship between company’s confidence and stock return. Based on principal component analysis (factor analysis), a confidence index will be developed for the Kuala Lumpur stock exchange with data from 2000 to 2010. The sample consisted of companies listed on Kuala Lumpur stock exchange which will be grouped into quartiles, each representing a portfolio.Next, the average return of each portfolio for every quarter is going to be calculated.Finally, the results will indicate a significant and negative or positive relationship between the market as well as company’s confidence index and the stock return

Handling Imbalanced Data through Re-sampling: Systematic Review

Handling imbalanced data is an important issue that can affect the validity and reliability of the results. One common approach to addressing this issue is through re-sampling the data. Re-sampling is a technique that allows researchers to balance the class distribution of their dataset by either over-sampling the minority class or under-sampling the majority class. Over-sampling involves adding more copies of the minority class examples to the dataset in order to balance out the class distribution. On the other hand, under-sampling involves removing some of the majority class examples from the dataset in order to balance out the class distribution. It's also common to combine both techniques, usually called hybrid sampling. It is important to note that re-sampling techniques can have an impact on the model's performance, and it is essential to evaluate the model using different evaluation metrics and to consider other techniques such as cost-sensitive learning and anomaly detection. In addition, it is important to keep in mind that increasing the sample size is always a good idea to improve the performance of the model. In this systematic review, we aim to provide an overview of existing methods for re-sampling imbalanced data. We will focus on methods that have been proposed in the literature and evaluate their effectiveness through a thorough examination of experimental results. The goal of this review is to provide practitioners with a comprehensive understanding of the different re-sampling methods available, as well as their strengths and weaknesses, to help them make informed decisions when dealing with imbalanced data

An approach for matching schemes of heterogeneous relational databases.

Schema matching is a basic problem in many database application domains, such as data integration. The problem of schema matching can be formulated as follows, ldquogiven two schemas, Si and Sj, find the most plausible correspondences between the elements of Si and Sj, exploiting all available information, such as the schemas, instance data, and auxiliary sourcesrdquo. Given the rapidly increasing number of data sources to integrate and due to database heterogeneities, manually identifying schema matches is a tedious, time consuming, error-prone, and therefore expensive process. As systems become able to handle more complex databases and applications, their schemas become large, further increasing the number of matches to be performed. Thus, automating this process, which attempts to achieve faster and less labor-intensive, has been one of the main tasks in data integration. However, it is not possible to determine fully automatically the different correspondences between schemas, primarily because of the differing and often not explicated or documented semantics of the schemas. Several solutions in solving the issues of schema matching have been proposed. Nevertheless, these solutions are still limited, as they do not explore most of the available information related to schemas and thus affect the result of integration. This paper presents an approach for matching schemas of heterogeneous relational databases that utilizes most of the information related to schemas, which indirectly explores the implicit semantics of the schemas, that further improves the results of the integration

Effect of the COVID-19 Pandemic on Radical Prostatectomy: A Turkish Multicenter Study

Objective: The present study examines the effects of the coronavirus disease 2019 pandemic on radical prostatectomy performed as part of localized prostate cancer treatment in Turkey. Material and methods: A retrospective analysis was made of the data of 176 patients from 8 centers in Turkey who underwent radical prostatectomy due to localized prostate cancer over the 2 years spanning March 1, 2019, to February 28, 2021. Within this timeframe, March 1, 2019, to February 28, 2020, was denoted the 1-year pre-coronavirus disease 2019 period, while March 1, 2020, to February 28, 2021, was denoted the 1-year coronavirus disease 2019 period. An analysis was made of whether there was a difference in the number of radical prostatectomies performed for prostate cancer, the time from biopsy to operation, and the biopsy and radical prostatectomy pathology between the 2 periods. Results: It was found that the number of radical prostatectomies performed for localized prostate cancer during the coronavirus disease 2019 pandemic was statistically and highly significantly fewer than in the pre-coronavirus disease 2019 period (P < .001). The patients diagnosed with Gleason 3 + 3 (low risk) prostate cancer were statistically significantly fewer in number in the coronavirus disease 2019 period (P < .001). The pathological Gleason score was upgrading than the biopsy Gleason score in all patients who underwent in both periods (P < .001). When the periods were compared, the pathological involvement determined by lymph node dissection performed during radical prostatectomy was found to be decreased in the coronavirus disease 2019 period, although the difference was not statistically significant (P = .051). Conclusion: As with many diseases, the diagnosis and treatment of prostate cancer have been adversely affected by the coronavirus disease 2019 pandemic. © 2022, AVES. All rights reserved

Adsorption of Ammonia Nitrogen by using Jackfruit (Artocarpus heterophyllus) Seeds: Batch and Fixed-bed Column Studies

The performance of jackfruit (Artocarpus heterophyllus) seed adsorbent for ammonia nitrogen (NH3-N) removal from aqueous solution was examined through batch and continuous bed column experiments. The effects of sodium chloride (NaCl) and lignin concentration on the adsorption process were evaluated. The results revealed that the adsorption performance gradually decreased from 26% upon addition of NaCl and lignin in the solution. Fixed bed column experiments showed that maximum removal of ammonia nitrogen was obtained at an influent concentration of 100 mg/L, bed height of 10 cm and lowest inlet flow rate of 17 mL/min. Meanwhile, desorption studies were carried out at different pH and highest desorption capacity of jackfruit seed adsorbent was 0.42 mg/g. This study suggests that jackfruit seed is a promising adsorbent for the recovery process of ammonia nitrogen

Matching schemas of heterogeneous relational databases

Schema matching is a basic problem in many database application domains, such as data integration. The problem of schema matching can be formulated as follows, "given two schemas, Si and Sj, find the most plausible correspondences between the elements of Si and S j, exploiting all available information, such as the schemas, instance data, and auxiliary sources" [24]. Given the rapidly increasing number of data sources to integrate and due to database heterogeneities, manually identifying schema matches is a tedious, time consuming, error-prone, and therefore expensive process. As systems become able to handle more complex databases and applications, their schemas become large, further increasing the number of matches to be performed. Thus, automating this process, which attempts to achieve faster and less labor-intensive, has been one of the main tasks in data integration. However, it is not possible to determine fully automatically the different correspondences between schemas, primarily because of the differing and often not explicated or documented semantics of the schemas. Several solutions in solving the issues of schema matching have been proposed. Nevertheless, these solutions are still limited, as they do not explore most of the available information related to schemas and thus affect the result of integration. This paper presents an approach for matching schemas of heterogeneous relational databases that utilizes most of the information related to schemas, which indirectly explores the implicit semantics of the schemas, that further improves the results of the integration

Analysis of Gabapentinoids Abuse-Reports in the Middle East and North Africa Region Utilizing the Food and Drug Administration Adverse Event Reporting System

Objectives: The purpose of this study was to identify abuse-related post-marketing reports associated with gabapentinoids use in the Middle East and North Africa (MENA) region countries. Methods: A retrospective cross-sectional analysis of abuse-related adverse drug event (ADE) reports from the Middle East and North Africa (MENA) region. It was performed using the Food and Drug Administration Adverse Event Reporting System (FAERS) database from January 2008 through June 2020. Abuserelated ADE reports for gabapentin and pregabalin were extracted from the FAERS database. Descriptive statistics were performed, and the proportional reporting ratio (PRR) was calculated to detect disproportional attribution of abuse-related ADEs for gabapentin versus pregabalin. Results: We identified 559 all-cause ADE reports for gabapentinoids, including 205 (36.7%) abuse-related ADE reports reported to FAERS in the period of analysis. FAERS included 139 (67.8%) pregabalin and 66 (32.2%) gabapentin abuse-related ADE reports. Among MENA region countries, Turkey (55, 39.6%) and Saudi Arabia (34, 23.7%) had the highest number of abuse-related ADE reports for pregabalin. The most pregabalin abuse-related ADE reports involved adult male patients. The PRR of pregabalin versus gabapentin abuse-related ADE reports was 1.11, indicating that the number of abuse-related events was higher for pregabalin compared to gabapentin. Conclusion: Over 200 cases of abuserelated gabapentinoids events were reported to FEARS from the MENA region in the study period. Further studies should assess risk factors and potential programs to reduce gabapentinoids abuse