Coupling orientation diffusion with coherence-enhancing diffusion: a fingerprint case

The enhancement of coherent flow-like structures is desired for many image processing tasks, such as segmentation and feature detection. This task can be accomplished in a natural way by adopting anisotropic diffusion filtering using a diffusion matrix adapted to the local structure. This method is referred to as coherence-enhancing diffusion (CED). The performance of CED can be analyzed by observing the evolution of the orientation field (OF) associated with an evolving diffusion matrix. It was revealed from a series of experiments that the final OF from a CED-enhanced image sometimes strays from its true underlying OF (marked by a human expert), degrading its performance. In this paper, a strategy is proposed which repeatedly cleans the OF associated with a diffusion matrix. Thus, for every iteration of CED, its OF is diffused separately until it converges and is then fed back to the CED process to move forward. This hypothesis is tested with the motive of getting an enhanced CED performance. The proposed scheme is validated using fingerprint data, and their numerical results are displayed.     

Searching surface orientation of microscopic objects for accurate 3D shape recovery

In this article, we propose a new shape from focus (SFF) method to estimate 3D shape of microscopic objects using surface orientation cue of each object patch. Most of the SFF algorithms compute the focus value of a pixel from the information of neighboring pixels lying on the same image frame based on an assumption that the small object patch corresponding to the small neighborhood of a pixel is a plane parallel to the focal plane. However, this assumption fails in the optics with limited depth of field where the neighboring pixels of an image have different degree of focus. To overcome this problem, we try to search the surface orientation of the small object patch corresponding to each pixel in the image sequence. Searching of the surface orientation is done indirectly by principal component analysis. Then, the focus value of each pixel is computed from the neighboring pixels lying on the surface perpendicular to the corresponding surface orientation. Experimental results on synthetic and real microscopic objects show that the proposed method produces more accurate 3D shape in comparison to the existing techniques.     

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.     

Synthesis of surface imprinted polymers based on wrinkled flower-like magnetic graphene microspheres with favorable recognition ability for BSA

Nowadays,the employing of molecular imprinting technique in the analysis and separation of proteins from complex biological samples has been widely favored by researchers.To enrich the types of surface protein imprinted materials and expand the application fields of graphene materials,novel surface molecular imprinted polymers (MIPs) based on magnetic graphene microspheres Fe304@rGO@MIPs are first synthesized in this paper.Fe304@rGO@MIPs are prepared by oxidative self-polymerization of dopamine on the surface of magnetic graphene (Fe304@rGO) composite microspheres.Bovine serum albumin (BSA) is selected as protein template.Fe3O4@rGO microspheres with wrinkled flower-like structure are obtained by compounding Fe3O4 and graphene oxide in an appropriate ratio via the method of high-temperature reduction self-assembly.The microspheres exhibit promising dispersibility,high external surface area,rich pore structure,and sufficient magnetic properties.These advantages not only prevent the agglomeration of imprinted microspheres in the aqueous phase,which is conducive to contact and static adsorption,but also increase the amount of protein imprinting.Additionally,sufficient magnetic properties ensure fast and effective separation of the adsorbents.While the adsorption capacity is increased,the separation procedure becomes simple.The binding capacity of Fe304@rGO@MIPs for BSA can reach 317.58 mg/g within 60 min,and the imprinting factor (IF) is 4.24.More importantly,Fe3O4@rGO@MIPs can specifically recognize the target BSA from the mixed proteins and the actual sample.There is no significant decrease in the adsorption amount,IF,and magnetic properties after eight runs.It is promising to be used in the separation of proteins from the actual biological samples.     

Aluminum‐Tailored Energy Level and Morphology of Co3−xAlxO4 Porous Nanosheets toward Highly Efficient Electrocatalysts for Water Oxidation

Tuning energy levels plays a crucial role in developing cost‐effective, earth‐abundant, and highly active oxygen evolution catalysts. However, to date, little attention has been paid to the effect of using heteroatom‐occupied lattice sites on the energy level to engineer electrocatalytic activity. In order to explore heteroatom‐engineered energy levels of spinel Co₃O₄ for highly‐effective oxygen electrocatalysts, herein Al atoms are directly introduced into the crystal lattice by occupying the Co²⁺ ions in the tetrahedral sites and Co³⁺ ions in the octahedral sites (denoted as Co²⁺_Td and Co³⁺_Oh, respectively). Experimental and theoretical simulations demonstrate that Al³⁺ ions substituting Co²⁺_Td and Co³⁺_Oh active sites, especially Al³⁺ ions occupying the Co²⁺_Td sites, optimizes the adsorption, activation, and desorption features of intermediate species during oxygen evolution reaction (OER) processes. As a result, the optimized Co_1.75Al_1.25O₄ nanosheet exhibit unprecedented OER activity with an ultralow overpotential of 248 mV to deliver a current of 10 mA cm^–2, among the best Co‐based OER electrocatalysts. This work should not only provide fundamental understanding of the effect of Al‐occupied different Co sites in Co_3–xAl_xO₄ composites on OER performance, but also inspire the design of low‐cost, earth‐abundant, and high‐active electrocatalysts toward water oxidation.     

A First-Principles Calculation of Electronic Structure and dHvA Simulation of the Novel Superconductor Re<Subscript>6</Subscript>Hf

In this paper, we performed a density functional theory calculation study on the newly discovered superconductor Re₆Hf containing anti-symmetric spin-orbit coupling (ASOC) properties. The calculated densities of electronic states demonstrate that the d–d interaction of Re₆Hf is much stronger than that in Re₆Zr. A fully relativistic DFT study shows a special performance of densities of states for the spin-up and spin-down electrons. Band structure calculations indicate that the lifting at several high symmetric k points and plenty of splits in band structures yield significant topological transitions in the Fermi surfaces of Re₆Hf. The energy splitting of bands caused by ASOC are estimated to be 34 and 44 meV, respectively. The de Hass-van Alphen effect simulation is demonstrated and analyzed.     

Application of moisture activated dry granulation (MADG) process to develop high dose immediate release (IR) formulations

Moisture activated dry granulation (MADG) method was used to develop IR tablets with cohesive, fluffy and high dose drugs. To evaluate this approach, three drugs: metformin hydrochloride, acetaminophen and ferrous ascorbate were selected as model compound along with three binders: maltodextrin DE16, PVP K 12 and HPC. The granules were generated using MADG method and tablets were prepared using rotary tablet press. The granules and tablets were characterized for particle size analysis, flow properties, tablet hardness, friability, moisture content, dissolution study, disintegration time and stability study. All results were found to be within acceptable limits. Development of all formulation tablets were found as best fitted for an immediate release of Metformin hydrochloride, acetaminophen and ferrous ascorbate. MADG delivered a robust manufacturing process for generation of granules with excellent flowability. The tablets prepared using this method were found to show better content uniformity, good compactability and low friability. Use of this approach aids to lower the amount of excipients used to overcome physiochemical limitation of the drug substances and there side effects. Both drying and milling steps in wet granulation were not required for MADG process. MADG became a cost effective process which could lead to reduced total tablet size and also save time.     

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.