A Clustering Approach Based on Charged Particles

In pattern recognition, clustering is a powerful technique that can be used to find the identical group of objects from a given dataset. It has proven its importance in various domains such as bioinformatics, machine learning, pattern recognition, document clustering, and so on. But, in clustering, it is difficult to determine the optimal cluster centers in a given set of data. So, in this paper, a new method called magnetic charged system search (MCSS) is applied to determine the optimal cluster centers. This method is based on the behavior of charged particles. The proposed method employs the electric force and magnetic force to initiate the local search while Newton second law of motion is employed for global search. The performance of the proposed algorithm is tested on several datasets which are taken from UCI repository and compared with the other existing methods like K-Means, GA, PSO, ACO, and CSS. The experimental results prove the applicability of the proposed method in clustering domain

Potential use of the Asteraceae family as a cure for diabetes: A review of ethnopharmacology to modern day drug and nutraceuticals developments

The diabetes-associated mortality rate is increasing annually, along with the severity of its accompanying disorders that impair human health. Worldwide, several medicinal plants are frequently urged for the management of diabetes. Reports are available on the use of medicinal plants by traditional healers for their blood-sugar-lowering effects, along with scientific evidence to support such claims. The Asteraceae family is one of the most diverse flowering plants, with about 1,690 genera and 32,000 species. Since ancient times, people have consumed various herbs of the Asteraceae family as food and employed them as medicine. Despite the wide variety of members within the family, most of them are rich in naturally occurring polysaccharides that possess potent prebiotic effects, which trigger their use as potential nutraceuticals. This review provides detailed information on the reported Asteraceae plants traditionally used as antidiabetic agents, with a major focus on the plants of this family that are known to exert antioxidant, hepatoprotective, vasodilation, and wound healing effects, which further action for the prevention of major diseases like cardiovascular disease (CVD), liver cirrhosis, and diabetes mellitus (DM). Moreover, this review highlights the potential of Asteraceae plants to counteract diabetic conditions when used as food and nutraceuticals. The information documented in this review article can serve as a pioneer for developing research initiatives directed at the exploration of Asteraceae and, at the forefront, the development of a botanical drug for the treatment of DM

Laparoscopic Cholecystectomy in Situs Inversus Totalis with Stage 5 Chronic Kidney Disease: A Case Report

Situs inversus totalis is a rare congenital anomaly in which the abdominal and thoracic organs are transposed in a mirror image. Diagnosis and management of cholelithiasis in patients with situs inversus totalis pose a challenge due to the anatomical variation. A laparoscopic cholecystectomy in such a case can be technically challenging, especially for a right-handed surgeon. In this case report, we present a case of a 38-year-old male with symptomatic cholelithiasis in a chronic kidney disease stage five patient under maintenance hemodialysis planned for recipient renal transplant. A laparoscopic cholecystectomy considered the gold standard for symptomatic cholelithiasis was performed with a three-port technique. The technical challenges anticipated due to anatomical variation were managed by intraoperative modifications. In conclusion, laparoscopic cholecystectomy in patients with situs inversus totalis can be done with technical modifications and re-orientation of visual motor skills

The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

Background: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. Methods: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. Results and Conclusion: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events

Creating a strategic business plan for a Nepalese construction company: a case study of Jhapali International Engineering and Builders

Developing an effective strategy is a vital aspect of business management, which is necessary to survive in the market and achieve the corporate mission and vision. In order to succeed a company must develop a plan of action in their business plan. The formulation of the strategy is central to any business plan. Constructing a detailed business plan will guide the company’s owner to envision the future shape of the company and make the best decisions regarding the company’s business. The research conducted for this thesis examines this subject in the case of a construction company located in Nepal. The objective of the thesis project is to develop a strategic business plan for the case company Jhapali International Engineering and Builders (JIEB) based on an analysis of the company’s current situation. JIEB is a construction company located in the southeast of Nepal that is specialized in public civil engineering projects such as the construction of roads, bridges, dams, and canals. Developing a clear strategy will help the company improve its growth by detailing the activities it should follow respond to challenges. The thesis is a case study and the main research approach is qualitative. In addition, information was collected through literature analysis, documentation, and observation. Triangulation was used in the data collection in order to increase validity. Analysis of the collected data was made to develop an effective strategic plan for the case company to achieve their mission and vision. The outcomes of the thesis were an analysis of the case company’s current situation in the construction market of Nepal, the development of a business plan as an effective strategy, and suggestions concerning the use of the strategic business plan in the case company’s corporate strategy

Healthcare Data Analysis Using Water Wave Optimization-Based Diagnostic Model

This paper presents a new diagnostic model for various diseases. In the proposed diagnostic model, a water wave optimization (WWO) algorithm was implemented for improving the diagnosis accuracy. It was observed that the WWO algorithm suffered from the absence of global best information and premature convergence problems. Therefore in this work, some improvements were proposed to formulate the WWO algorithm as more promising and efficient. The global best information issue was addressed by using an improved solution search equation and the aim of this was to explore the global best optimal solution. Furthermore, a premature convergence problem was rectified by using a decay operator. These improvements were incorporated in the propagation and refraction phases of the WWO algorithm. The proposed algorithm was integrated into a diagnostic model for the analysis of healthcare data. The proposed algorithm aimed to improve the diagnosis accuracy of various diseases. The diverse disease datasets were considered for implementing the performance of the proposed diagnostic model based on accuracy and F-score performance indicators, while the existing techniques were regarded to compare the simulation results. The results confirmed that the WWO-based diagnostic model achieved a higher accuracy rate as compared to existing models/techniques with most disease/healthcare datasets. Therefore, it stated that the proposed diagnostic model is more promising and efficient for the diagnosis of different diseases