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Wind load is mostly influenced by the shape and size of the high-rise structure wind load is a horizontal load that also varies based on the shape and modifications provided along the vertical height of the tall building. The present study is investigating the wind effects on hexagonal plan-shaped high-rise structures provided with openings. Wind effects are compared in both isolated as well as in interference conditions at different spacings. Wind-generated effects on high rise structure are explained with the help of pressure contours, streamlines and average external pressure on each surface of the tall building for the wind incidence angle range from 0° to 90° at the interval of 30°. Most of the studies done on the high-rise structure are on different scales as per the range provided in the wind tunnel manual; hence, here the scale of 1:500 is adopted as per the various guidelines available in the wind tunnel manual report no. 67. The investigation is performed using the k-ε turbulence model in ANSYS CFX, a computational fluid dynamics tool. The results indicated an increase in mean pressure as the spacing between the primary building model and the interfering building model increased. Surface pressure coefficients obtained from different conditions on the primary building model were employed to develop an artificial neural network (ANN)-based prediction model. The generated model exhibited a high degree of reliability when compared to the provided data. Notably the maximum permissible error was considerably low, considering the uncertainty associated with wind effects.

During the COVID-19 pandemic, genomics and bioinformatics have emerged as essential public health tools. The genomic data acquired using these methods have supported the global health response, facilitated the development of testing methods and allowed the timely tracking of novel SARS-CoV-2 variants. Yet the virtually unlimited potential for rapid generation and analysis of genomic data is also coupled with unique technical, scientific and organizational challenges. Here, we discuss the application of genomic and computational methods for efficient data-driven COVID-19 response, the advantages of the democratization of viral sequencing around the world and the challenges associated with viral genome data collection and processing.

Objective: Our study aimed to provide an improvised model that classifies the fetal distress using a two-dimensional Convolution neural network (CNN). It also helps in improving the visualization of FHR and UC signals. Background: Hypoxia or Fetal Distress is the main cause of death in the newborns. Cardiotocography is used to detect hypoxia in which fetal heart rate and uterine contraction signals are observed. Setting: Department of Computer Engineering and Technology, Guru Nanak Dev University, India. Subjects: The CTG-UHB database was used for classification purpose and 552 records were analyzed for classification purposes. Methods: Convolutional Neural Network was used for the classification purpose and HoloViz was used for the visualization of data in which HvPlot and HoloViews libraries are used in python. The CTG-UHB database was used for the analysis purpose. A total of 552 records were used for classification purposes. The classification was performed on the Keras software. Results: The accuracy achieved by our model was above 70%. Three classes were obtained named Normal Hypoxia (pH>7.15), Mild Hypoxia (7.05

We live in an incredible information age. We have smartphones more powerful than the computers NASA uses in the rovers and satellites sent into space. Virtually any type of content [...]

The COVID-19 pandemic has introduced a wide range of challenges to numerous institutions around the world. One of these vital programs being affected is Caribbean medical schools. To continue to train future physicians, Caribbean medical schools have been forced to deliver lectures through video chat, delaying clinical training years as well as exams. Reveal current shortcomings in medical education to improve future learning strategies based on student perspectives.

The article discusses the trend towards cloud-based electronic learning (e-learning) in India and mentions topics including the country's aim of 100% literacy with the help of cloud-based e-learning, the benefits of cloud services for educators, and the projected growth of the e-learning industry.

The article discusses the growth of electronic learning (e-Learning) industry, focusing on the significant impact of cloud computing in the creation of a stable and scalable learning environment globally. Topics mentioned include the increase in usage of big data technologies like Hadoop, the potential role of hybrid clouds like Amazon Web Services Inc. (AWS) in managing the transition between public and private clouds with continues innovations, and the benefits of using cloud computing.

An interview with Harman Singh, chief executive officer (CEO) of India's software as a service (SaaS)-based online education platform WizIQ, is presented. He stresses that entire business and product design of WizIQ is based on the underlying belief that quality education is driven by teachers. He mentions the goal of WizIQ to provide teachers with free product demonstrations and help them with the start-up of their online courses.

The article presents a corporate profile for the WizIQ.com, an online education platform for virtual education classroom software company in Mohali, India. Topics discussed include the corporate's personnel team, its contact information and its customer support services. Other topics include the company's services on teaching online education, offers massive open online courses and distance learning programs.

A letter to the editor is presented in response to the article "Online Education Cast as 'Disruptive Innovation,'" by Clayton M. Christensen, from the May 7, 2008 issue.

The article offers information on a new correlation based on boiling point temperature, which calculates water solubility and Henry's law constants for a wide variety of olefins and diolefins in water. It provides reliable solubility values down to low chemical concentrations in water. Data from the correlation and experimental data are discussed.