52 research outputs found
Influence of radiation and thermal slip on electrically conductive dusty Walter’s B fluid moving peristaltically through an asymmetric channel
No full textMotivation: The motivation of this recent article is to study dusty Walter’s B fluid flow due to its wide range of applications in biology and polymer industry. The fluid is traveling peristaltically through an asymmetric channel with wall slip. A discussion is also presented to examine heat transfer effects with thermal radiation and slip. Methodology: The regular perturbation technique is employed to evaluate the mathematical model of the problem, which is first simplified by using stream functions. Mathematical results are simulated to illustrate flow characteristics of fluid and solid particles in salient quantities. Also, graphs of temperature distribution of fluid and dust particles have been discussed to study the impacts of various parameters. Outcomes: Walter’s B fluid parameter reduces speed of both fluid and dust particles. By increasing thermal slip parameter, temperature transference becomes slower through the fluid, while Brinkman number significantly raises the temperature profile of both fluid and particles. This article presents a theoretical analysis of the problem. Moreover, the characteristics of liquids involved in the plastic industry and medical science can also be understood using the current analysis. Originality/Value: Walter’s B fluid with dust particle suspension has not been investigated for slip and thermal radiation effects
All organic memory devices utilizing C60 molecules and insulating polymers
No full textThe convergence of mobile technologies combined with stricter power requirements and increasing demands have strained the current memory technology. Newer technologies such as phase changing, ferroelectric, and magnetic random access memories are unsatisfactory in meeting the new requirements. We propose a new memory technology based on our initial discovery of charge storage in C60 molecules within poly (4-vinyl phenol) (PVP). To understand the memory potential, we created single-layer devices consisting of ~30nm films of PVP+C60 sandwiched between aluminum (Al) electrodes. Current versus voltage (I-V) sweeps showed a significant hysteresis of 75nA, with distinguishable memory states. Room temperature charging of C60 was confirmed indirectly through capacitance versus voltage measurements and directly by monitoring the A1g characteristic peak of C60 during Raman measurements. We demonstrated memory operations by applying read-write-erase (RWE) pulses. The PVP+C60 devices exhibited memory retention for over 1 hour and response times of around 10ns. Characteristic hysteresis was demonstrated at the nanoscale. Conduction models were fitted at room temperature to the I-V curves. It was found that combination of direct and Fowler-Nordheim tunneling were the principle conduction mechanisms.
For a more technologically viable memory device, we developed a multi-layer device structure, consisting of a polystyrene (PS) capping layer. The resulting asymmetrical I-V curve exhibited a hysteresis ratio of 103. RWE cycles were measured with clearly distinguishable states. The memory retentions were measured over 2 hours and the response time around 10ns. The stability of the multi-layer devices was improved. I-V measurements at temperatures varying from 4.2 K to 298 K were performed to construct a theoretical model. The I-V curves were found to be temperature independent and exhibited similar tunneling behaviors as the single-layer devices. A simple model for conduction and memory operation is proposed based on the I-V fits.
These devices exhibit the characteristics needed to satisfy the new demands for memory application and have the potential of becoming the first universal memory technology. They possess the high speed, non-volatility, thermal stability, and potentially high memory densities to make them ideal for use in laptops, iPhones, mp3 players, portable video players, GPS systems, and other mobile devices.Ph.D.Includes bibliographical references
A comprehensive study of Hilbert spaces, 1972
No full textA Hilbert Space H is an inner product space which as a metric space is complete. The most important theorems proved are Riesz's Representation Theorem, theorems of Adjoints and operators. Measure of Spectrum and spectral integrals are briefly discussed
Copyright in software
No full textThe author looks at the various legal approaches to protecting computer software in the existing legal environment in New Zealand. The author argues that object code both is and should be protected by copyright law and that the Copyright Act, 1962 does provide protection to object form software. The author argues that depending on the circumstances, various approaches may be combined to achieve the optimal result. Usually this is a combination strategy of contract law and copyright law, where the former binds parties and the latter provides protection in the absence of any legal relationship. (Editor’s abstract.
Label-free electrochemical aptasensor for the detection of SARS-CoV-2 spike protein based on carbon cloth sputtered gold nanoparticles
No full textThe proliferation and transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or the (COVID-19) disease, has become a threat to worldwide biosecurity. Therefore, early diagnosis of COVID-19 is crucial to combat the ongoing infection spread. In this study we propose a flexible aptamer-based electrochemical sensor for the rapid, label-free detection of SARS-CoV-2 spike protein (SP). A platform made of a porous and flexible carbon cloth, coated with gold nanoparticles, to increase the conductivity and electrochemical performance of the material, was assembled with a thiol functionalized DNA aptamer via S–Au bonds, for the selective recognition of the SARS-CoV-2 SP. The various steps for the sensor preparation were followed by using scanning electron microscopy, cyclic voltammetry and differential pulse voltammetry (DPV). The proposed platform displayed good mechanical stability, revealing negligible changes on voltammetric responses to bending at various angles. Quantification of SARS-CoV-2 SP was performed by DPV and chronopotentiometry (CP), exploiting the changes of the electrical signals due the [Fe(CN)6]3-/4- redox probe, when SARS-CoV-2 SP binds to the aptamer immobilized on the electrode surface. Current density, in DPV, and square root of the transition time, in CP, varied linearly with the log[ SARS-CoV-2 SP], providing lower limits of detection (LOD) of 0.11 ng/mL and 37.8 ng/mL, respectively. The sensor displayed good selectivity, repeatability, and was tested in diluted human saliva, spiked with different SARS-CoV-2 SP concentrations, providing LODs of 0.167 ng/mL and 46.2 ng/mL for DPV and CP, respectively
Rethinking Identities in Contemporary Pakistani Fiction : Beyond 9/11
No full textDefinitions of home and identity have changed for Muslims as a result of international “war on terror” rhetoric. This book uniquely links the post-9/11 stereotyping of Muslims and Islam in the West to the roots of current jihadism, the resurgence of different forms of Islam and ethnocentrism within the subcontinent and beyond, and to US realpolitik in order to foreground the effects of terrorism debates on Pakistanis at home and in the diaspora. Through close readings of fiction by Nadeem Aslam, Kamila Shamsie, Uzma Aslam Khan, Mohsin Hamid, Mohammed Hanif, H.M. Naqvi, Ali Sethi, Maha Khan Phillips and Feryal Gauhar, who confront negative attitudes towards Muslims and Islam in the twenty-first century, this book not only challenges the centrality of Western narratives but also foregrounds Anglo-American foreign policy in the Muslim world as a form of terrorism. The author proposes an articulation of a flexible identity among Muslims that is termed a “global ummah” after 9/11
Feasibility of a Carbon Consumption Tax for sustainable development – A case study of India
No full textGlobal climate change is a major issue confronting policymakers worldwide, and there is widespread scientific acceptance of the reality of climate change and its adverse consequences In terms of economic analysis, greenhouse gas emissions (GHG), which cause planetary climate changes, represent both an environmental externality and the overuse of a common property resource. The paper is premised around the hypothesis that tax policy can be used to address climate concerns by making less Green House Gas intensive purchases and investments more financially attractive. However, in the absence of an international framework capping GHG emissions, countries adopting mitigation policies incur costs that would not exist under global cooperation such as the loss of competitiveness and emissions leakage. A consumption tax based on the carbon footprint of a product levied on all products at the point of purchase by the final end-user, regardless of where the goods are produced using a Credit-method would be capable of addressing these concerns of emissions leakage and loss of competitiveness, while being WTO compliant. The author intends to test the feasibility and effectiveness of such a carbon consumption tax in the Indian Context. The author shall test the feasibility of levy of such a consumption tax in the context of India and evaluate the effectiveness in mitigating climate change and catering to the goal of sustainable development.</jats:p
Enhancing Deep Networks through Customized Iterative Hierarchical Data Augmentation: A Study utilizing the Sussex-Huawei-Locomotion Dataset
No full textArtificial Neural Networks (ANNs) have emerged as a powerful tool for classification tasks due to their ability to outperform traditional methods. Nevertheless, their effectiveness relies heavily on the availability of large, varied, and labeled datasets, which are often not available. To counter this constraint, data augmentation techniques have emerged, leveraging existing data to generate additional, variant data. Extending these techniques to multi-dimensional time series data, such as the transportation mode detection data considered in this thesis, however, introduces challenges. In response, generative models such as Variational Autoencoders (VAEs) have shown promising advancements.In this context, this thesis investigates the application of the Iterative Hierarchical Data Aug- mentation (IHDA) algorithm for ANNs, which represents a VAE-based data augmentation technique. The IHDA method utilizes VAEs not only to generate new data samples but also to map existing data to a lower-dimensional latent space, which is then utilized for identifying samples that might require additional training. The proponents of this method, Khan and Fraz, reported an accuracy elevation for the considered transportation mode detection classifier from 83% to 92%. However, due to the absence of publicly accessible code for this algorithm, the initial step of this thesis involved implementing the IHDA algorithm. Further, this research proposed and incorporated advancements like the σ-VAE, aimed to improve the generative capacity of the VAE and to refine its latent space mapping. Additionally, the Kullback-Leibler (KL) divergence was introduced as a similarity metric, aiming to optimize the identification process of samples that require retraining.Unfortunately, the results reported by Khan and Fraz could not be reproduced in this study. Furthermore, despite the potential shown by the σ-VAE to improve the generative capacity and refine the latent space mapping, along with the enhanced sample identification through the KL divergence, these enhancements did not lead to an overall improvement in the IHDA algorithm. This was primarily attributed to the low generative performance of the VAEs utilized, which also hindered a thorough evaluation of the effectiveness of the IHDA algorithm.Given these outcomes, it is suggested that future work should focus on employing more complex VAE models with the potential to enhance their generative performance, which, in turn, could improve the IHDA algorithm’s overall effectiveness.Mechanical Engineering | Systems and Contro
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