Antidiarrheal activity of methanol extract of Piper sylvaticum (roxb.) stem in mice and in silico molecular docking of its isolated compounds

Background: Piper sylvaticum (Roxb.), is commonly used in traditional medicine to treat a number of disease like in asthma, diarrhea, chronic cough, cold, piles, tuberculosis, and wounds. In this study, we investigated the antidiarrheal activity of methanol extract of P. sylvaticum stem (Met.PSS) in animal models. Later, molecular docking study was performed to better understand its molecular mechanism and to determine the potent phytocompounds of this plant for the antidiarrheal property.Methods: The stems were extracted with methanol and subjected to in vivo antidiarrheal study using the castor oil-induced diarrhea and castor oil induced enteropooling tests in animal models. And then, in silico molecular docking study was performed using Schrödinger suite Maestro v10.1.Results: Met.PSS exhibited a dose-dependent and statistically significant antidiarrheal activity in both castor oil-induced diarrhea and enteropooling tests at the doses of 200 and 400 mg/kg. Additionally, our molecular docking analysis exhibited that four compounds viz. piperine, piperlonguminine, sylvamide, and sylvatine have the best binding affinity against the target enzyme (M3 muscarinic acetylcholine receptor) in comparison to reference drug Loperamide.Conclusions: The present study suggests that Met.PSS possess significant antidiarrheal activity which could be related to the presence of various secondary plant metabolites or phytochemicals. Additionally, the phytocompounds, i.e., piperine, piperlonguminine, sylvamide, and sylvatine were found to be most effective in molecular docking study

BaDLAD: A Large Multi-Domain Bengali Document Layout Analysis Dataset

While strides have been made in deep learning based Bengali Optical Character Recognition (OCR) in the past decade, the absence of large Document Layout Analysis (DLA) datasets has hindered the application of OCR in document transcription, e.g., transcribing historical documents and newspapers. Moreover, rule-based DLA systems that are currently being employed in practice are not robust to domain variations and out-of-distribution layouts. To this end, we present the first multidomain large Bengali Document Layout Analysis Dataset: BaDLAD. This dataset contains 33,695 human annotated document samples from six domains - i) books and magazines, ii) public domain govt. documents, iii) liberation war documents, iv) newspapers, v) historical newspapers, and vi) property deeds, with 710K polygon annotations for four unit types: text-box, paragraph, image, and table. Through preliminary experiments benchmarking the performance of existing state-of-the-art deep learning architectures for English DLA, we demonstrate the efficacy of our dataset in training deep learning based Bengali document digitization models

Conductive textiles for signal sensing and technical applications

Conductive textiles have found notable applications as electrodes and sensors capable of detecting biosignals like the electrocardiogram (ECG), electrogastrogram (EGG), electroencephalogram (EEG), and electromyogram (EMG), etc; other applications include electromagnetic shielding, supercapacitors, and soft robotics. There are several classes of materials that impart conductivity, including polymers, metals, and non-metals. The most significant materials are Polypyrrole (PPy), Polyaniline (PANI), Poly(3,4-ethylenedioxythiophene) (PEDOT), carbon, and metallic nanoparticles. The processes of making conductive textiles include various deposition methods, polymerization, coating, and printing. The parameters, such as conductivity and electromagnetic shielding, are prerequisites that set the benchmark for the performance of conductive textile materials. This review paper focuses on the raw materials that are used for conductive textiles, various approaches that impart conductivity, the fabrication of conductive materials, testing methods of electrical parameters, and key technical applications, challenges, and future potential

Drag-based aerodynamic braking system for the Hyperloop: a numerical study

The Hyperloop promises to revolutionize the transport infrastructure of the 21st century by reducing travel time and allowing people to reach transonic speed on land. It carries with it the hope of a sustainable transportation system during an era of global energy crisis. Overall passenger safety in a high-speed pod necessitates a reliable braking system. This paper introduces the possibility of utilizing aerodynamic drag in the Hyperloop, anticipated to operate at high Mach and low Reynolds flow regime, to attenuate the speed of the pod. Numerical analysis was conducted to investigate the effect of incorporating an aerodynamic brake at different pod velocities (100, 135, and 150 m/s) and deployment angles (30°, 45°, 60°, and 90°). A detailed comparison between the proposed aerodynamic braking system (AeBS) and existing braking systems for the Hyperloop has been presented in this paper. The results demonstrate an increase in drag value of the pod by 3.4 times using a single 0.15 m2 brake plate. When the brake plate was fully deployed at a pod velocity in excess of 112 m/s, the aerodynamic drag-based braking systems was shown to be more effective than the contemporary eddy current braking system.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Impact of Customer Relationship Management (CRM) on Organizational Performance: A Study from the Perspective of Bangladesh

Customer relationship management is recognizing, attracting, obtaining, maintaining, and keeping profitable and faithful customers as the success of a business highly depends on them. The current study’s purpose is to measure the impact of customer relationship management on organizational performance. The study used Yamane’s (1967) formula to calculate the sample, and it has got 90 sample sizes and used semi-structured questionnaires containing pre-coded and open-ended questions. Descriptive statistics like frequency, percentages, and means have been performed. Besides, inferential statistics like correlation and regression analysis have been used to determine the relationship. The result showed that customer relationship management significantly and positively impacts organizational performance. The study will help the policy maker of any organization to rethink and give much more emphasis to customer relationship management

Online Judging Platform Utilizing Dynamic Plagiarism Detection Facilities

A programming contest generally involves the host presenting a set of logical and mathematical problems to the contestants. The contestants are required to write computer programs that are capable of solving these problems. An online judge system is used to automate the judging procedure of the programs that are submitted by the users. Online judges are systems designed for the reliable evaluation of the source codes submitted by the users. Traditional online judging platforms are not ideally suitable for programming labs, as they do not support partial scoring and efficient detection of plagiarized codes. When considering this fact, in this paper, we present an online judging framework that is capable of automatic scoring of codes by detecting plagiarized contents and the level of accuracy of codes efficiently. Our system performs the detection of plagiarism by detecting fingerprints of programs and using the fingerprints to compare them instead of using the whole file. We used winnowing to select fingerprints among k-gram hash values of a source code, which was generated by the Rabin–Karp Algorithm. The proposed system is compared with the existing online judging platforms to show the superiority in terms of time efficiency, correctness, and feature availability. In addition, we evaluated our system by using large data sets and comparing the run time with MOSS, which is the widely used plagiarism detection technique