Brakes Analysis of BAJA ATV

In the modern day and age where automobiles are an essential part of our day to day life, the requirements of each are different. Some demand for a high-performance machine whereas others require a comfortable ride. The modern engineering helps in achieving all the aspects of a safe, reliable and fast vehicle. With the change in time, the need for an all-terrain vehicle has gradually increased. The research paper includes the optimisation of braking system for minimum stopping distance and locking all four tyres simultaneously. The SolidWorks struct-static analysis and simulation are done to obtain a better braking system which can provide the best in class arrangements for the customer. The research focused on disc, master cylinder position. The designs provide the sturdiness and durability which is the primary requirement for an all-terrain vehicle. The study comprises of braking for BAJA-ATV. The all-terrain conditions require active braking and all wheels locking at the instant time. The research paper includes the parameters for the efficient disc, callipers, master cylinder position for effective braking

Fusion dynamics of spherical and deformed projectiles with hexadecapole deformed target nuclei

The quadrupole ($$\beta _{\lambda =2}$$) deformation and corresponding cold and hot optimum orientations of the nuclei play an important role in the synthesis of new nuclear entity. Consequently, a comprehensive knowledge is required to understand the relevance of higher-order deformed nuclei in the nuclear fusion dynamics. In the present work, the hexadecapole ($$\beta _{\lambda =2,4}$$) deformed nuclei of different shapes, i.e. $$\beta _2^+\beta _4^+$$ ($$^{147-150,152,154}$$Sm), $$\beta _2^+\beta _4^-$$ ($$^{172,174,176,178,180,182}$$Yb), $$\beta _2^-\beta _4^+$$ ($$^{40,43,55,77,82}$$Sc) and $$\beta _2^-\beta _4^-$$ ($$^{70,72-74}$$Ge) are taken into consideration as target of $$^{16}$$O (sph.), $$^{48}$$Ca (sph.), $$^{48}$$Ar ($$\beta _2^-$$) and $$^{62}$$Fe ($$\beta _2^+$$) induced reactions. For these selected choices of projectile-target (p-t) combinations, the impact of ± signs and hot/cold optimum orientations of higher-order deformation (up to $$\beta _4$$) has been investigated, in reference to that $$\beta _2^{\pm }$$ deformation. The above analysis has been discussed in terms of fusion barrier characteristics (barrier height $$V_B$$ and barrier position $$R_B$$), which is sensitive towards the deformation and orientation degree of freedom. Furthermore, the corresponding effects have been analyzed in the calculation of fusion cross-section $$\sigma _{fus}$$, with respect to the center of mass energy ($$E_{c.m.}$$) lying across the Coulomb barrier. Therefore, the nuclear shape for targets $$\beta _2^{\pm }\beta _4^+$$ expands relatively larger, and consequently the radius which enhances the fusion cross-sectional area as compared to that of $$\beta _2^{\pm }$$ deformation. In contrast to the above case, the $$\beta _2^{\pm }\beta _4^-$$ shapes have been found to hinder the fusion, mainly at the below- and near-barrier regions. Subsequently, the present work gives the relevance of the expanded and compressed shapes of hexadecapole deformed nuclei in the nuclear fusion dynamics for the considered choices of p-t combinations at the low-energy regime. Besides, the available experimental data for $$^{16}$$O+$$^{147-150,152,154}$$Sm p-t combinations, here ‘Sm’ isotopes are $$\beta _4^+$$-deformed, has been addressed by integrating $$\sigma _{fus}$$ over all orientations and deformations up to $$\beta _4$$, over a given range of $$E_{c.m.}$$

Functional traits and phylogenetic analysis of top-soil inhabiting rhizobacteria associated with tea rhizospheres in North Bengal, India

Rhizobacteria associated with cultivated crops are known to stimulate plant growth through various indirect or direct mechanisms. In recent years, the host list of plant growth promotion/promoting rhizobacteria has expanded to include bean, barley, cotton, maize, rice, vegetables, peanut, rice, wheat, and several plantation crops. However, interaction of rhizobacteria with tea plants of organic and conventional tea gardens is poorly understood. In the present study, rhizobacterial species associated with tea rhizosphere were isolated from 14 tea gardens located in North Bengal, India. In total, 16 rhizobacterial isolates isolated from collected soil samples were assessed for antagonistic and plant growth promotion/promoting activity under laboratory conditions. Molecular characterization based on sequencing of 16S rRNA gene revealed dominance of Bacillus with five species followed by Pseudomonas with two species. Interestingly, only one isolate was affiliated with actinobacteria, i.e., Microbacterium barkeri. Out of 16 isolates, isolates Bacillus subtilis OKAKP01, B. subtilis BNLG01, B. paramycoides BOK01, M. barkeri BPATH02, and Stenotrophomonas maltophilia BSEY01 showed highest growth inhibition against Fusarium solani (68.2 to 72.8%), Pseudopestalotiopsis theae (71.1 to 85.6%), and Exobasidium vexans (67.4 to 78.3%) causing respective Fusarium dieback, gray blight, and blister blight diseases in tea crop. Further, these five isolates also possessed significantly greater antifungal (siderophore producer, protease, chitinase, and cellulase activity) and plant growth promotion/promoting (indole-3-acetic acid production, ACC deaminase, ammonia, and phosphate solubilization) traits over other eleven rhizobacterial isolates. Therefore, these five isolates of rhizobacteria were chosen for their plant growth promotion/promoting activity on tea plants in nursery conditions. Results from nursery experiments revealed that these five rhizobacteria significantly improved growth rates of tea plants compared with the control. Therefore, this study suggests that these rhizobacteria could be used to formulate biopesticides and biofertilizers, which could be applied to sustainable tea cultivation to improve crop health and reduce disease attack

A Method Noise-Based Convolutional Neural Network Technique for CT Image Denoising

Medical imaging is a complex process that capitulates images created by X-rays, ultrasound imaging, angiography, etc. During the imaging process, it also captures image noise during image acquisition, some of which are extremely corrosive, creating a disturbance that results in image degradation. The proposed work addresses the challenge to eliminate the corrosive Gaussian additive white noise from computed tomography (CT) images while preserving the fine details. The proposed approach is synthesized by amalgamating the concept of method noise with a deep learning-based framework of a convolutional neural network (CNN). The corrupted images are obtained by explicit addition of Gaussian additive white noise at multiple noise variance levels (σ = 10, 15, 20, 25). The denoised images obtained are then evaluated according to their visual quality and quantitative metrics, such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). These metrics for denoised CT images are then compared with their respective values for the reference CT image. The average PSNR value of the proposed method is 25.82, the average SSIM value is 0.85, and the average computational time is 2.8760. To better understand the proposed approach’s effectiveness, an intensity profile of denoised and original medical images is plotted and compared. To further test the performance of the proposed methodology, the results obtained are also compared with that of other non-traditional methods. The critical analysis of the results shows the commendable efficiency of the proposed methodology in denoising the medical CT images corrupted by Gaussian noise. This approach can be utilized in multiple pragmatic areas of application in the field of medical image processing

Finish hard turning: A review of minimum quantity lubrication using paraffin-based nanofluids

A wide range of cooling techniques for hard turning machining continues to be proposed and assessed. In this review, the overall characteristics of cutting tools and stainless steel materials were reviewed in terms of vibration, surface roughness, cutting force, and tool life while using minimum quantity lubrication (MQL) with paraffin-based nanofluids. Nanoparticles are particularly appealing in MQL due to its remarkable improvement in the cutting conditions. Under aggressive machining conditions, the lubricant media tends to evaporate or disintegrate when in contact with the cutting tool. With the addition of high thermal conductivity nanoparticle additives as cutting fluid, the performance of the MQL technique has improved remarkably. This review exposed that a few work has used MQL with nanofluid when machining martensitic stainless steel AISI 420 using TiAlN-coated carbide cutting tool. Furthermore, the application of MQL via paraffin oil, ?-Fe2O3, and xGnP nanofluid when machining hardened stainless steel using coated carbide cutting tools has not yet been examined