The present study experimentally investigates the shock wave attenuation performance of various sandwiched structures made up of different polymer foams (expanded polystyrene and polyurethane foam) ...with and without shear thickening fluid (STF). STF is a non-Newtonian fluid whose viscosity increases with increase in shear rate due to the formation of hydro clusters produced by the increased hydrodynamic forces acting between the interstitial spaces. Two layers of polymer foams have been considered for the shock protective material and the space between the layers is filled with shear thickening fluid. The shock wave is experimentally generated from a shock tube facility and is allowed to impinge on a target plate kept at 10 mm downstream to the shock tube end. It is seen that the protective material with polyurethane foam and shear thickening fluid (polyethylene glycol+silica nanoparticles) reduces the shock overpressure by nearly 35.51 %, whereas the protective material with only polyurethane foam (with the same thickness) reduces the shock overpressure by only 13.17 %. Similarly, the protective material with expanded polystyrene and shear thickening fluid reduces the shock overpressure by nearly 32.16 %, whereas the protective material with only expanded polystyrene (with the same thickness) reduces the shock overpressure by only 10.49 %. Hence, it is evident that the shear thickening fluid between the polymer foam layers greatly helps in shock wave attenuation.
The present study investigates the shock wave propagation and diffraction characteristics in a micro-shock tube with sudden expansion and compares with the well-established classical shock wave ...diffraction in macro-length scale sudden expansions using computational techniques. The Knudsen number for the present micro-shock tube falls in the slip regime and therefore the fluid flow is simulated using the continuum-based Navier–Stokes equation with Maxwell’s slip jump boundary condition. It is found that the shock wave attenuates rapidly in micro-shock tube compared to the shock wave propagation in macro-shock tube. The shock wave diffraction in micro-steps shows similar characteristics compared to macro-steps, such as reflection of the diffracted shock wave from the outer wall and the subsequent transition from regular reflection to Mach reflection, the vortex formation at the step corner, Mach reflection shock structure in the shock-processed gas exiting from the shock tube. However, the secondary shock wave formed due to the interaction of the reflected shock wave with the corner vortex is not seen for the micro-step case compared to the macro-step case. This can be attributed to the reduction in shock strength produced by the thick boundary layer in micro-shock tubes. Different step sizes have been compared for the micro-shock tube with sudden expansion ranging from the step size 1.5 to 3. Also, a detailed comparison has been done between micro- and macro-shock tube with sudden expansion. It is also found that the use of slip velocity increases the shock wave propagation speed compared to the no-slip boundary condition.
Convolutional neural networks (CNN) due to their excellent accuracy, have emerged as the leading machine learning method. However, it becomes difficult to deploy CNN algorithms on hardware platforms ...because of their high memory bandwidth, computational complexity, and power consumption. Hardware accelerators such as Field Programmable Gate Arrays (FPGA), Graphics Processing Unit (GPU), etc. are excellent platforms for modelling CNN algorithms. The purpose of the paper is to run a standard software process in hardware and exploit natural parallelism in hardware to speed up neural network prediction. The paper presents a rule-based synthesizable Advanced Microcontroller Bus Architecture (AMBA) Advanced eXtensible Interface (AXI) protocol for high-speed data transmission. The paper develops a computer vision system on an FPGA that could recognize the numbers 0 through 9 written by hand for the capstone design project. The findings show that 91% accuracy is achieved through Rectified linear activation unit (ReLU) which can be increased to 98% by implementing the Sigmoid activation function with a depth of 10 bits. The method provides good accuracy and clock performance while using few resources.
The ever-increasing integration of renewable energy sources in the power grid necessitates the development of efficient and reliable microgrid systems. Photovoltaic (PV) systems coupled with energy ...storage technologies, such as batteries, offer promising solutions for sustainable and resilient power generation. This paper proposes an adaptive power control topology for a PV-battery microgrid system, aiming to optimize the utilization of available solar energy and enhance the overall system performance. In order to provide a smooth transition between the OFF-GRID and ON-GRID modes of operation with proportionate power sharing, a self-adaptive control method for a microgrid is proposed. Three different modes of operation are discussed in his paper i.e. GRID connected, the transition between Grid-connected and Islanded State and by changing the irradiance of PVs and doing the transitioning. The simulation results show Total harmonic distortion to be 0.08, 1.43 and 2.17 for distribution generation-1 and 4.22,3.92 and 2.10 for distribution generation-2 in the three modes respectively which helps to maintain good power quality. The simulation results demonstrate the superiority of the adaptive power control topology in terms of maximizing renewable energy utilization, improving system stability, and ensuring a seamless transition between grid-connected and islanded modes.
Due to the growing amount of online content, automated article summarization using artificial intelligence (AI) has received a lot of interest lately.This study proposes a novel method to automate ...the process of article summarization by combining Generative AI approaches with React JS, a well-liked JavaScript toolkit for creating user interfaces. React JS integration offers a user- friendly and interactive platform that allows user to submit articles and instantly receive succinct summaries. Neural networks and deep learning architectures are two examples of generative AI models that are used to extract important information and produce cogent summaries that encapsulate the main ideas of the original articles.The system's technological implementation— which includes data preparation, model training, and the creation of real-time summaries—is covered in this paper. The proposed method has a number of benefits, such as a faster summarizing process, better information accessibility, and an improved user experience. ReactJS and Generative AI.summarization system, making it possible to effectively extract important information from articles in a variety of domains. Index Terms - React JS, Generative AI, Neural Networks, RTK Query .
In the last several years, air pollution has risen steadily in urban environments. Cities like Gurugram, Faisalabad, Delhi, Beijing are few of the world's most polluted cities and have seen a ...dangerous rise in air pollution levels. Forecasting is important because of the human, ecologic and economic toll of pollution, and is a useful investment at individual and community levels. Accurate forecasting will help us plan in advance, decreasing the effects on health and the costs associated. Local weather conditions strongly affect air pollution levels. Generating deterministic models to study air pollutant behavior in environmental science research is often not very accurate because they are complex and need simulation at the molecular interaction level. Here comes machine learning to the rescue with high computing facilities to predict air pollution. This paper investigates how effective some available prediction models are in predicting the Air Quality Index(AQI) values given some input data, based on the pollution and meteorological information in New Delhi, India. We perform regression analysis on the dataset, and our results show which meteorological factors affect the AQI values more and how useful the predictive models are to help in air quality forecasting.
This paper presents an effective and intelligent methodology for the recognition of several underlying causes responsible for power quality (PQ) disturbances. The disturbance signals at a 40-dB ...signal-to-noise ratio (SNR) from various locations of the power distribution system have been analyzed with computationally efficient Stockwell transform (ST). Besides the residual voltage and the duration, characteristics like automatic segmented phase angle jump (PAJ) have been extracted and proposed for linking the PQ disturbance with the respective underlying cause. PQ disturbances have been simulated in a MATLAB environment as per the IEEE-1159 standard with five causes, namely symmetrical fault, unsymmetrical fault, induction motor starting, capacitor bank energizing, and transformer energizing. A block scheme has been devised and presented here for the effective recognition of the underlying cause in a power distribution network so that corrective measures can be proposed for the trouble-free operation of the equipment. The performance of the proposed method has also been evaluated with the real-time PQ data to judge the effectiveness of the algorithm in the real environment.
This systematic review aimed to determine the antimicrobial resistance pattern of the extended-spectrum β-lactamases producing Escherichia coli (ESBL-EC) in urine samples in Nepal.
Systematic ...literature review was conducted to locate all articles reporting ESBL-EC in urine samples published between January 2012 to December 2022. The Egger's weighted regression analysis was done to assess the publication bias. A random-effects model was used to calculate the pooled prevalence and corresponding 95% confidence interval due to significant between-study heterogeneity. The strength of correlation between multidrug resistance and ESBL production in E.coli strains was determined using Pearson's correlation coefficient. The data were analyzed using R-language 4.2.2. software.
The combined prevalence of E.coli in urine samples was found to be 14 % (95% CI, 11-18), while the overall pooled prevalence of ESBL E.coli and MDR E.coli were 30% (95% CI, 20-42) and 70% (95% CI, 38-90) respectively. A strong positive correlation of 0.99 (95% CI, 0.89-1.0) was found between ESBL production and MDR among E.coli isolates. Imipenem was the drug of choice against ESBL-E.coli in urine specimens.
Our analyses showed the overall ESBL-EC and MDR-EC burden in Nepal is considerably high. Likewise, the study also infers an increasing trend of antibiotic resistance pattern of ESBL-EC in urine samples.
The phylum Apicomplexa includes serious pathogens of humans and animals. Understanding the distribution and population structure of these protozoan parasites is of fundamental importance to explain ...disease epidemiology and develop sustainable controls. Predicting the likely efficacy and longevity of subunit vaccines in field populations relies on knowledge of relevant preexisting antigenic diversity, population structure, the likelihood of coinfection by genetically distinct strains, and the efficiency of cross-fertilization. All four of these factors have been investigated for Plasmodium species parasites, revealing both clonal and panmictic population structures with exceptional polymorphism associated with immunoprotective antigens such as apical membrane antigen 1 (AMA1). For the coccidian Toxoplasma gondii only genomic diversity and population structure have been defined in depth so far; for the closely related Eimeria species, all four variables are currently unknown. Using Eimeria tenella, a major cause of the enteric disease coccidiosis, which exerts a profound effect on chicken productivity and welfare, we determined population structure, genotype distribution, and likelihood of cross-fertilization during coinfection and also investigated the extent of naturally occurring antigenic diversity for the E. tenella AMA1 homolog. Using genome-wide Sequenom SNP-based haplotyping, targeted sequencing, and single-cell genotyping, we show that in this coccidian the functionality of EtAMA1 appears to outweigh immune evasion. This result is in direct contrast to the situation in Plasmodium and most likely is underpinned by the biology of the direct and acute coccidian life cycle in the definitive host.
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