Mathematical Modelling of Blood Flow through a Tapered Overlapping Stenosed Artery with Variable Viscosity

This paper presents a theoretical study of blood flow through a tapered and overlapping stenosed artery under the action of an externally applied magnetic field. The fluid (blood) medium is assumed to be porous in nature. The variable viscosity of blood depending on hematocrit (percentage volume of erythrocytes) is taken into account in order to improve resemblance to the real situation. The governing equation for laminar, incompressible and Newtonian fluid subject to the boundary conditions is solved by using a well known Frobenius method. The analytical expressions for velocity component, volumetric flow rate, wall shear stress and pressure gradient are obtained. The numerical values are extracted from these analytical expressions and are presented graphically. It is observed that the influence of hematocrit, magnetic field and the shape of artery have important impact on the velocity profile, pressure gradient and wall shear stress. Moreover, the effect of primary stenosis on the secondary one has been significantly observed

FINITE ELEMENT SIMULATION OF LCF BEHAVIOUR OF SA 333 C-MN STEEL

Finite Element simulation to characterize the LCF behavior of Sa 333 C-Mn Steel is studied in this paper. Experiment and Finite Element simulation are done together. LCF parameters of the material are calibrated and tuned from the experimental results. Non linear version of Ziegler kinematic hardening material model is used to address the stable hysteresis cycles of the material. Cyclic hardening phenomenon is addressed by introducing cyclic hardening in the material model. The elastic plastic FE code ABAQUS is used for finite element simulation of LCF behavior. The plastic modulus formulation with zeigler kinematic hardening rule and exponential isotropic hardening rule has been used for simulation. Using the incremental plasticity theories the cyclic plastic stress-strain responses were analyzed and the results obtained from FE simulations have been compared with the experimental results at different strain amplitudes. Variation of cyclic yield stress with strain amplitudes has also been studied in this paper

Development of a miniaturized fixed displacement vane pump

One of the viable technologies to actuate robotic systems such as quadruped or biped is the use of hydraulic energy through centralized electro-hydraulic systems. The use of huge motor-pump assembly resulting increase in the whole system dimension along with the piping arrangements to connect the different components limits its use for autonomous robots. Present research trend is to develop miniaturized integrated electro-hydraulic systems such that each robotic joint will have its own actuation system dimensioned to fulfill the force and the velocity requirements. For such a system the hydraulic pump generates the hydraulic power required for the actuation system. The present work reports the development of a miniaturized vane pump. The conventional version of this is widely used in hydraulic control systems to maintain constant flow rate. However, the analysis of such kind of pump in its miniaturized form is yet to be addressed. A mathematical model has been developed to analyze the performance of the pump. The model has been simulated in Matlab/Simulink environment to obtain the delivery flow and pressure ripples for different operating conditions. It has been found that for the chosen size, the pump can able to develop substantial amount of pressure required for the actuation system

EMERGENCE OF METABOLIC SYNDROME IN POLICE PROFESSIONALS: A LONGITUDINAL OBSERVATIONAL STUDY

Objective: This is a longitudinal observation looking for the emergence of metabolic syndrome (MetS) in a rapid response police unit. Methods: After taking informed consent, measurements were taken of blood pressure, body mass index (BMI), waist circumference, triglycerides, HDL-cholesterol, and fasting blood glucose periodically in 2019, 2021, and 2023 in January. 146 police officers enrolled out of 148 screened and 117 completed the study. Results: In four years, the proportion of individuals with MetS values exceeding the norm increased by 20-30% for each component with 56 new cases of impaired metabolic parameters and 13 new cases of MetS observed among 110 previously unaffected police officers. Conclusion: A significant increase in the number of Metabolic Syndrome was found, particularly via its effects on blood lipid levels in police personnel which a highly stressful for professionals. Future longitudinal studies with continuous stress monitoring and comparing with a control will more in-depth knowledge into it

Peristaltic Transport of a Physiological Fluid in an Asymmetric Porous Channel in the Presence of an External Magnetic Field

The paper deals with a theoretical investigation of the peristaltic transport of a physiological fluid in a porous asymmetric channel under the action of a magnetic field. The stream function, pressure gradient and axial velocity are studied by using appropriate analytical and numerical techniques. Effects of different physical parameters such as permeability, phase difference, wave amplitude and magnetic parameter on the velocity, pumping characteristics, streamline pattern and trapping are investigated with particular emphasis. The computational results are presented in graphical form. The results are found to be in perfect agreement with those of a previous study carried out for a non-porous channel in the absence of a magnetic field

Automated claustrum segmentation in human brain MRI using deep learning

In the last two decades, neuroscience has produced intriguing evidence for a central role of the claustrum in mammalian forebrain structure and function. However, relatively few in vivo studies of the claustrum exist in humans. A reason for this may be the delicate and sheet-like structure of the claustrum lying between the insular cortex and the putamen, which makes it not amenable to conventional segmentation methods. Recently, Deep Learning (DL) based approaches have been successfully introduced for automated segmentation of complex, subcortical brain structures. In the following, we present a multi-view DL-based approach to segment the claustrum in T1-weighted MRI scans. We trained and evaluated the proposed method in 181 individuals, using bilateral manual claustrum annotations by an expert neuroradiologist as reference standard. Cross-validation experiments yielded median volumetric similarity, robust Hausdorff distance, and Dice score of 93.3%, 1.41 mm, and 71.8%, respectively, representing equal or superior segmentation performance compared to human intra-rater reliability. The leave-one-scanner-out evaluation showed good transferability of the algorithm to images from unseen scanners at slightly inferior performance. Furthermore, we found that DL-based claustrum segmentation benefits from multi-view information and requires a sample size of around 75 MRI scans in the training set. We conclude that the developed algorithm allows for robust automated claustrum segmentation and thus yields considerable potential for facilitating MRI-based research of the human claustrum. The software and models of our method are made publicly available

A skeletonization algorithm for gradient-based optimization

The skeleton of a digital image is a compact representation of its topology, geometry, and scale. It has utility in many computer vision applications, such as image description, segmentation, and registration. However, skeletonization has only seen limited use in contemporary deep learning solutions. Most existing skeletonization algorithms are not differentiable, making it impossible to integrate them with gradient-based optimization. Compatible algorithms based on morphological operations and neural networks have been proposed, but their results often deviate from the geometry and topology of the true medial axis. This work introduces the first three-dimensional skeletonization algorithm that is both compatible with gradient-based optimization and preserves an object's topology. Our method is exclusively based on matrix additions and multiplications, convolutional operations, basic non-linear functions, and sampling from a uniform probability distribution, allowing it to be easily implemented in any major deep learning library. In benchmarking experiments, we prove the advantages of our skeletonization algorithm compared to non-differentiable, morphological, and neural-network-based baselines. Finally, we demonstrate the utility of our algorithm by integrating it with two medical image processing applications that use gradient-based optimization: deep-learning-based blood vessel segmentation, and multimodal registration of the mandible in computed tomography and magnetic resonance images.Comment: Accepted at ICCV 202

Navigating Copper-Atom-Pair Structural Effect inside a Porous Organic Polymer Cavity for Selective Hydrogenation of Biomass-Derived 5-Hydroxymethylfurfural

In recent times, selective hydrogenation of biomass-derived 5-hydroxymethylfurfural (5-HMF) to produce the novel difuranic polyol scaffold 2,5-dihydroxymethylfuran (DHMF) has attracted the interest of the many researchers due to its peculiar symmetrical structure and its widespread application as a monomer for the preparation of cross-linked polyesters and polyurethane. Copper-based catalysts have been explored for selective catalytic hydrogenation; however, hurdles are still associated with the strongly reducing H2 atmosphere and oxidizing C–O bond that make the Cu0 and Cux+ surface active species unstable, limiting the rational design of highly efficient integrated catalyst systems. To address this, herein, we built catalytic systems for 5-HMF hydrogenation with stable and balanced Cu0 and Cux+ active surface species inside the nanocage of a catechol-based porous organic polymer (POP) endowed with large surface areas, impressive stabilities, and spatial restriction inhibiting nanoparticle aggregation. Batch reactor screening identified that a superior catalytic performance (DHMF selectivity of 98%) has been achieved with our newly designed Cu@C-POP at 150 °C temperature and 20 bar H2 pressure, which was also higher than that of other reported copper catalysts. Comprehensive characterization understanding with H2-TPR and X-ray photoelectron spectroscopy (XPS) study revealed that substantially boosted activity is induced by the presence of the bulk CuOx phase and atomically dispersed Cu species incorporating isolated Cu ions, which are further confirmed through the positive binding energy shift of Cu 2p3/2 XPS spectra (∼0.4 eV). The Cu environment in our catalytic systems comprises a predominantly square planar geometry (probably Jahn–Teller distorted OH), which we gleaned from the extended X-ray absorption for fine structure (EXAFS) analysis featuring two adjacent copper atoms with the valence state in between of 0 and +2, as validated by XANES absorption edge positions. EXAFS studies further revealed a lowering of the Cu coordination number for the most active Cu@C-POP-B catalyst, suggesting the presence of metal vacancies. Density functional theory calculations showed that the presence of Cu metal vacancies stabilized the reaction intermediates formed during 5-HMF hydrogenation and decreased the hydrogenation barriers, resulting in an enhanced catalytic activity of the Cu@C-POP-B catalyst