Stimuli-Responsive Dynamic Metaholographic Displays with Designer Liquid Crystal Modulators

Flat optics, realized by the artificially created 2D material platform called optical metasurfaces, is currently undergoing a science-to-technology transition. However, “real-time” active operations of such flat optical devices remain yet unresolved. Here, liquid crystals (LCs)-integrated metaholograms for ultracompact dynamic holographic displays are proposed. The anisotropic nature of the LCs allows facile and repeatable manipulation of the polarization of light. Specifically designed (“designer”) LCs and efficient helicity-encoded metaholograms are combined to realize stimuli-responsive dynamic displays. The designer LC modulators are used as switches that enable a variety of external stimuli (e.g., electric field, heat, surface pressure) to operate holographic images in real-time. Such a dynamic metaholographic platform will provide a path to external stimuli-driven “smart” sensing and display applications such as hologram labels for temperature/pressure/touch monitoring and interactive holographic displays with haptic motion recognition.     

Heat transfer analysis for particle–fluid suspension thermomagnetohydrodynamic peristaltic flow with Darcy–Forchheimer medium

This theoretical analysis explores the effect of heat and mass transfer on particle–fluid suspension for the Rabinowitsch fluid model with the stiffness and dynamic damping effects through Darcy–Brinkman–Forchheimer porous medium. In this study, we also incorporate slip and transverse magnetic field effects. Using low Reynolds number, to neglect inertial forces and to keep the pressure constant during the flow, channel height is used largely as compared with the ratio of length of the wave. A numerical technique is used to solve flow governing system of differential equations. Particular attention is paid to viscous damping force parameter, stiffness parameter, and rigidity parameter; also, the numerical data for thermal profile, momentum, and concentration distribution are presented graphically. Outcomes are deliberated in detail for different fluid models (thinning, thickening, and viscous models). It is found that velocity profile increases for greater values of viscous damping effect and stiffness and rigidity parameter for shear thinning, but conflicting comportment is showed for thickening nature model. Viscous dissipation effects increases the thermal profile for all cases of fluid models. The scope of the present article is valuable in explaining the blood transport dynamics in small vessels while considering the important wall features with chemical reaction characteristics. The current analysis has extensive applications in biomedical engineering field, that is, peristaltic pumps.     

Simplification of genetic programs: a literature survey

Data Mining and Knowledge Discovery - Genetic programming (GP), a widely used evolutionary computing technique, suffers from bloat—the problem of excessive growth in individuals’ sizes....     

Comparison of total ozone column observations from space-borne Ozone Monitoring Instrument with ground-based Dobson Ozone Spectrophotometer measurements at an urban location in Indo-Gangetic Basin

This article presents a comparison analysis of OMIT (Ozone Monitoring Instrument retrieved overpass total ozone column (TOC)), and DOST (Dobson Ozone Spectrophotometer observed TOC) over Delhi during a period from October 2004 to June 2011. Megacity Delhi, located in Indo-Gangetic Basin, is an important site for comparison of ground-based and satellite retrieved TOCs due to significant anthropogenic emissions of ozone precursors, large shift in seasons, and large-scale crop residue burning in the region. DOST and OMIT data show an overall bias of 3.07% and significant correlation with coefficient of determination R² = 0.73. Large seasonal fluctuations in the biases and correlations have been observed ranging from 2.46% (winter) to 3.82% (spring), and R² = 0.84 (winter) to R² = 0.09 (summer), respectively. The large biases are attributed to changes in temperature, cloud cover, pollutants emissions from urban area, and crop-residue burning events. We also find notable variations in correlations between the datasets due to the varying burden of absorbing aerosols from open field crop-residue burning. The R² has changed from 0.67 (for aerosol optical depth, AOD 1.5–3.5) to 0.77 (for AOD 0–0.99). The dependence of the bias on solar zenith angle, cloud fraction, and satellite distance is also discussed. A simple linear regression analysis is applied to check the linkage between DOST and OMIT. The influence of atmospheric air temperature and relative humidity on OMIT at different pressure levels between 1000 and 20 hPa has been discussed.     

An Efficient Mechanism for Product Data Extraction from E-Commerce Websites

A large amount of data is present on the web which can be used for useful purposes like a product recommendation, price comparison and demand forecasting for a particular product. Websites are designed for human understanding and not for machines. Therefore, to make data machine-readable, it requires techniques to grab data from web pages. Researchers have addressed the problem using two approaches, i.e., knowledge engineering and machine learning. State of the art knowledge engineering approaches use the structure of documents, visual cues, clustering of attributes of data records and text processing techniques to identify data records on a web page. Machine learning approaches use annotated pages to learn rules. These rules are used to extract data from unseen web pages. The structure of web documents is continuously evolving. Therefore, new techniques are needed to handle the emerging requirements of web data extraction. In this paper, we have presented a novel, simple and efficient technique to extract data from web pages using visual styles and structure of documents. The proposed technique detects Rich Data Region (RDR) using query and correlative words of the query. RDR is then divided into data records using style similarity. Noisy elements are removed using a Common Tag Sequence (CTS) and formatting entropy. The system is implemented using JAVA and runs on the dataset of real-world working websites. The effectiveness of results is evaluated using precision, recall, and F-measure and compared with five existing systems. A comparison of the proposed technique to existing systems has shown encouraging results.     

Recent Progress of Two-Dimensional Thermoelectric Materials

Thermoelectric generators have attracted a wide research interest owing to their ability to directly convert heat into electrical power.Moreover,the thermoelectric properties of traditional inorganic and organic materials have been significantly improved over the past few decades.Among these compounds,layered two-dimensional(2D)materials,such as graphene,black phosphorus,transition metal dichalcogenides,IVA–VIA compounds,and MXenes,have generated a large research attention as a group of potentially high-performance thermoelectric materials.Due to their unique electronic,mechanical,thermal,and optoelectronic properties,thermoelectric devices based on such materials can be applied in a variety of applications.Herein,a comprehensive review on the development of 2D materials for thermoelectric applications,as well as theoretical simulations and experimental preparation,is presented.In addition,nanodevice and new applications of 2D thermoelectric materials are also introduced.At last,current challenges are discussed and several prospects in this field are proposed.     

Osteoporosis Prediction for Trabecular Bone using Machine Learning: A Review

Trabecular bone holds the utmost importance due to its significance regarding early bone loss. Diseases like osteoporosis greatly affect the structure of the Trabecular bone which results in different outcomes like high risk of fracture. The objective of this paper is to inspect the characteristics of the Trabecular Bone by using the Magnetic Resonance Imaging (MRI) technique. These characteristics prove to be quite helpful in studying different studies related to Trabecular bone such as osteoporosis. The things that were considered before the selection of the articles for the systematic review were language, research field, and electronic sources. Only those articles written in the English language were selected as it is the most prominent language used in scientific, engineering, computer science, and biomedical researches. This literature review was conducted on the articles published between 2006 and 2020. A total of 62 research papers out of 1050 papers were extracted which were according to our topic of review after screening abstract and article content for the title and abstract screening. The findings from those researches were compiled at the end of the result section. This systematic literature review presents a comprehensive report on scientific researches and studies that have been done in the medical area concerning trabecular bone.     

A new hybrid adaptive combination technique for ECG signal enhancement

This paper proposes a new de-noising system technique which is composed of Adaptive line enhancer (ALE) with the discrete wavelet transform (DWT) in order to improve the demerit of the ALE. A new adaptive algorithm which depends mainly on the second order resemblance between a signal and its delayed version is also derived and proposed for the ALE. Unlike the conventional DWT process where an estimation of a specific threshold is taken into account, here the ALE based proposed adaptive algorithm is exploited to enhance the detail coefficients. Therefore, the entire system works well for canceling Gaussian and non-Gaussian noise. Some experiments are carried out on an ECG signal to show the effectiveness of the proposed system. It illustrates from the simulations that the proposed technique demonstrates spectacular results for separating various noise types from the contaminated ECG signal. Finally, the proposed adaptive algorithm is compared with the leaky least mean square algorithm of the bases of mean square error. It is found that the performance of the proposed algorithm provides faster convergence rate and lower steady-state error. Consequently, the overall proposed system model represents a workable solution for ECG signal enhancement.