This work presents a novel framework for spherical mesh parameterization. An efficient angle-preserving spherical parameterization algorithm is introduced, which is based on dynamic Yamabe flow and ...the conformal welding method with solid theoretic foundation. An area-preserving spherical parameterization is also discussed, which is based on discrete optimal mass transport theory. Furthermore, a spherical parameterization algorithm, which is based on the polar decomposition method, balancing angle distortion and area distortion is presented. The algorithms are tested on 3D geometric data and the experiments demonstrate the efficiency and efficacy of the proposed methods.
Worldwide, the broad usage of plastic has resulted in the massive production of plastic pollution. In this work, it was demonstrated that municipal plastic waste could be converted into valuable ...liquid products. This study shows the catalytic and non-catalytic pyrolysis of low-density polyethylene (LDPE), polypropylene (PP), and high-density polyethylene (HDPE). Pyrolysis was carried out in the absence of Oxygen, and three types of fractions: gas, liquid, and solid residues were obtained. The proportions of liquid or gas residue depend on the operating conditions such as temperature and the type of catalyst. The product obtained was then characterized through ASTM D-97, ASTM D-86, ASTM D-4294, Cloud Point, Conradson Carbon Residue, FTIR Analysis, ASTM D-611, Density and Specific Gravity. The use of catalysts showed more quantity of lower boiling points products due to further cracking of carbon chains and pour points decrease was also observed generally with the use of catalyst specially by using bentonite. A decrease in Pour Point indicated a decrease in paraffin content, therefore, reducing wax content, and so it indicated better flow properties at lower temperatures. Pour point and viscosity observed were interconnected with each other, sample having high pour points had high viscosity, hence showing the flowing ability of the liquid. Also, the Sulphur contents of all the samples falling under Euro II and Euro II category. C-Stretching, C=Stretching and C-Bending bonds were noted using the FTIR analysis. One of the important purposes of this study was to convert the waxes obtained from thermal pyrolysis of HDPE and LDPE to higher chain hydrocarbons, which was achieved by using bentonite as the catalyst and also flowing properties of the liquid improved by using the catalyst. HDPE with bentonite gave the highest percent of liquid fuel (75.15%) obtained which in turn shows the best result obtained through all our experiments.
The glymphatic system (GS) hypothesis states that advective driven cerebrospinal fluid (CSF) influx from the perivascular spaces into the interstitial fluid space rapidly transport solutes and clear ...waste from brain. However, the presence of advection in neuropil is contested and solutes are claimed to be transported by diffusion only. To address this controversy, we implemented a regularized version of the optimal mass transport (rOMT) problem, wherein the advection/diffusion equation is the only a priori assumption required. rOMT analysis with a Lagrangian perspective of GS transport revealed that solute speed was faster in CSF compared to grey and white matter. Further, rOMT analysis also demonstrated 2-fold differences in regional solute speed within the brain. Collectively, these results imply that advective transport dominates in CSF while diffusion and advection both contribute to GS transport in parenchyma. In a rat model of cerebral small vessel disease (cSVD), solute transport in the perivascular spaces (PVS) and PVS-to-tissue transfer was slower compared to normal rats. Thus, the analytical framework of rOMT provides novel insights in the local dynamics of GS transport that may have implications for neurodegenerative diseases. Future studies should apply the rOMT analysis approach to confirm GS transport reductions in humans with cSVD.
In this work the effect of different coupling ratios of ZnFe2O4 and TiO2 on the band gap was investigated, to convert TiO2 as a visible light driven photocatalyst ZnFe2O4. In this work, ZnFe2O4 was ...synthesized utilizing sol-gel technique and calcining under normal atmosphere at 900 and#176;C. Thereafter, ZnFe2O4 was coupled with TiO2 by mixing in 50 ml water in three different coupling w/w ratios (1:1, 1:2 and 2:1) followed by the calcination of coupled catalyst under nitrogen environment at 500 and#176;C. XRD, XPS, FESEM-EDS imaging, TGA, UV-Vis, and FTIR were performed to characterize the catalyst. Crystal phase identification could be confirmed through XRD analysis with homogenous distribution of metal constituents through color mapping and surface charge transitions from XPS analysis for a better electron hole generation. Thermogravimetric analysis (TGA) confirmed that the pure ZnFe2O4 obtained at 900 and#176;C, while FTIR verified the presence of desired functional group in ZnFe2O4. Moreover, Fourier Transformation Infrared Spectroscopy (FTIR) illustrated two major peaks and no extra major impurity was detected. ZnFe2O4 is visible light driven photocatalyst and TiO2 can work only under UV light. So, the effect of different coupling ratios of ZnFe2O4 with TiO2 was examined by UV-Vis characterization. The band gap is given by 1:1 was 2.8, 2:1 was 3.17 and 1:2 was 3.02. It was observed that the most optimum coupling ratio is 1:1 and the band-gap fall under visible region. The findings of this work could be supportive significantly for the selection of suitable coupling ratio to convert UV-driven photocatalyst into visible region active photocatalyst.
Cu and Mn based tetraphenyl porphyrin namely CuTPP and MnTPP were synthesized through a one pot route with a modified procedure and the reaction conditions (Temperature and time) were optimized based ...on the energy consumption during the synthesis of the target macrocyclic ligands. The temperature (145oC and 160oC) and time (3, 4, 8 hr) were used to study the effect on the product yield. The optimized values obtained using MATLAB routines are 3.7 hr and 145oC.
We present a method for registration and visualization of corresponding supine and prone virtual colonoscopy scans based on eigenfunction analysis and fold modeling. In virtual colonoscopy, CT scans ...are acquired with the patient in two positions, and their registration is desirable so that physicians can corroborate findings between scans. Our algorithm performs this registration efficiently through the use of Fiedler vector representation (the second eigenfunction of the Laplace-Beltrami operator). This representation is employed to first perform global registration of the two colon positions. The registration is then locally refined using the haustral folds, which are automatically segmented using the 3D level sets of the Fiedler vector. The use of Fiedler vectors and the segmented folds presents a precise way of visualizing corresponding regions across datasets and visual modalities. We present multiple methods of visualizing the results, including 2D flattened rendering and the corresponding 3D endoluminal views. The precise fold modeling is used to automatically find a suitable cut for the 2D flattening, which provides a less distorted visualization. Our approach is robust, and we demonstrate its efficiency and efficacy by showing matched views on both the 2D flattened colons and in the 3D endoluminal view. We analytically evaluate the results by measuring the distance between features on the registered colons, and we also assess our fold segmentation against 20 manually labeled datasets. We have compared our results analytically to previous methods, and have found our method to achieve superior results. We also prove the hot spots conjecture for modeling cylindrical topology using Fiedler vector representation, which allows our approach to be used for general cylindrical geometry modeling and feature extraction.
Extracting the trapped oil in the pores and channels of rock reservoirs, after secondary recovery, using traditional enhanced oil recovery (EOR) techniques is still a challenging task. Nano-materials ...offer novel pathways to address these unsolved challenges as EOR agents due to their unique characteristics. This study aimed to investigate the novel use of zinc oxide nanocrystals (ZnO-NCs) in EOR and, investigate the influence of the combination of ZnO-NCs with EM energy irradiation on the recovery efficiency. For this purpose, different nanofluid concentrations and flow rates, as well as brine salinity was injected into the porous medium, in the absence of EM energy, to obtain the optimum experimental conditions with the highest recovery efficiency. The injected nanofluid in the porous medium, under the optimum conditions, was subjected to EM energy. The Zinc oxide nanofluid (ZnO-NF) showed a significant rise in recovery efficiency in the absence of EM energy by 50% ROIP due to the self-assembling of the ZnO-NCs which resulted in an increment in the local viscosity of the nanofluid at the water–oil interface. This study proved the capability of EM energy to enhance the viscosity of the injected ZnO-NF in the porous medium, which consequently increased the recovery efficiency by 23.3% ROIP through the electrorheological effect of the activated dielectric ZnO-NCs.
Reporting biomarkers assessed by routine immunohistochemical (IHC) staining of tissue is broadly used in diagnostic pathology laboratories for patient care. So far, however, clinical reporting is ...predominantly qualitative or semi-quantitative. By creating a multitask deep learning framework, DeepLIIF, we present a single-step solution to stain deconvolution/separation, cell segmentation and quantitative single-cell IHC scoring. Leveraging a unique de novo dataset of co-registered IHC and multiplex immunofluorescence (mpIF) staining of the same slides, we segment and translate low-cost and prevalent IHC slides to more informative, but also more expensive, mpIF images, while simultaneously providing the essential ground truth for the superimposed brightfield IHC channels. A new nuclear-envelope stain, LAP2beta, with high (>95%) cell coverage is also introduced to improve cell delineation/segmentation and protein expression quantification on IHC slides. We show that DeepLIIF trained on clean IHC Ki67 data can generalize to noisy images as well as other nuclear and non-nuclear markers.Multiplex immunofluorescence imaging can provide a wealth of data compared to immunohistochemical staining, which is cheaper and more widely available. Ghahremani et al. present DeepLIIF, a GAN-based cell segmentation and classification approach, which is trained on co-registered images of these two modalities to provide the insights from the more data-rich muliplex data from simpler IHC images.
Visualization of medical organs and biological structures is a challenging task because of their complex geometry and the resultant occlusions. Global spherical and planar mapping techniques simplify ...the complex geometry and resolve the occlusions to aid in visualization. However, while resolving the occlusions these techniques do not preserve the geometric context, making them less suitable for mission-critical biomedical visualization tasks. In this paper, we present a shape-preserving local mapping technique for resolving occlusions locally while preserving the overall geometric context. More specifically, we present a novel visualization algorithm, LMap, for conformally parameterizing and deforming a selected local region-of-interest (ROI) on an arbitrary surface. The resultant shape-preserving local mappings help to visualize complex surfaces while preserving the overall geometric context. The algorithm is based on the robust and efficient extrinsic Ricci flow technique, and uses the dynamic Ricci flow algorithm to guarantee the existence of a local map for a selected ROI on an arbitrary surface. We show the effectiveness and efficacy of our method in three challenging use cases: (1) multimodal brain visualization, (2) optimal coverage of virtual colonoscopy centerline flythrough, and (3) molecular surface visualization.
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