Effect of Wiggler Magnetic Field on Second Harmonic Generation in Quantum Plasma

Second harmonic generation due to linearly polarized laser pulse propagating through quantum plasma immersed in a transverse wiggler magnetic field is studied using the quantum hydrodynamic (QHD) model. The effects associated with the Fermi pressure, the Bohm potential and the electron spin have been taken into account. Wiggler magnetic field plays both a dynamic role in producing the traverse harmonic current as well as kinematical role in ensuring phase-matching. The quantum dispersive effects also contribute to the intensity of second harmonics. Keywords: Quantum plasma, Harmonic generation, Phase matchin

Investigation of Microstructural and Carbon Deposition Effects in SOFC Anodes Through Modelling and Experiments

The investigation of the SOFC anode microstructural properties affected by microstructural parameters and degradation is the focus of this research. Imaging and image processing techniques are developed to achieve quantification of the anode microstructural information. The analytical and Computational Fluid Dynamics based modelling of the microstructure including the degradation effects developed in this work will enable the microstructure optimisation for achieving performance enhancements

Novel Tools to Investigate Cortical Activity in Paroxysmal Disorders

This PhD project is at the interface between academic research and industry, and is jointly sponsored by the BBSRC and the industrial partner– Scientifica UK. The goal of this research is the development of new instruments and approaches to monitor and manipulate neuronal network activity in disease states. Firstly, (I) I collaborated with Scientifica to develop and utilise the newly developed Laser Applied Stimulation and Uncaging (LASU) system. The combined usage of the LASU system, alongside novel spatially-targeted channelrhodopsin variants, has al- lowed me to test the limits of single-photon optogenetic stimulation in achieving specific activation of targeted neurons. The presented findings demonstrate that, al- though high-resolution stimulation is achievable in the rodent cortex, single-photon stimulation is insufficient to achieve single-cell resolution stimulation. Secondly, (II) I have combined the high temporal resolution of novel, transparent 16-channel epicortical graphene solution-gated field effect transistor (gSGFET) arrays with the large spatial coverage of bilateral widefield Ca2+ fluorescence imaging; to per- form investigations of the relationship between spreading depolarisation (SD) and cortical seizures in awake head-fixed mouse models of epilepsy. To analyse these complex datasets, I developed a bespoke, semi-automated analysis pipeline to pro- cess the data and probe the seizure-SD relationship. I present the advantages of this dual-modality approach by demonstrating the strengths and weaknesses of each recording method, and how a synergistic approach overcomes the limitations of each technique alone. I utilise widefield imaging to perform systematic classification of SD and seizures both temporally and spatially. Detailed electrophysiological anal- ysis of gSGFET data is then performed on extracted time periods of interest. This work demonstrates the complex interaction between seizures and SD, and proposes several mechanisms describing these interactions. The technological and analytical tools presented here lay the groundwork for insightful and flexible experimental paradigms; altogether, able to probe paroxysmal activity in profound detail

Effect of allopurinol and hemin on some biological markers of aging in broiler chickens

Uric acid has been hypothesized as one of the most important antioxidants in limiting the accumulation of advanced glycolated endproducts in broiler breeder hens. This study was designed to quantitatively manipulate the plasma uric acid concentrations using hemin and allopurinol and determine its effect on skin pentosidine, shear force value of Pectoralis major muscle, plasma glucose, body and breast weight, and chemiluminescence induced oxidative stress in broiler chickens. Allopurinol decreased plasma uric acid, ranging from 26% to 74%, with the most pronounced effect at wk 22. Hemin increased plasma uric acid concentrations between 11 and 14%. Skin pentosidine levels increased (P \u3c 0.05) in the allopurinol fed birds, in both ad libitum and diet restricted, at 22 wk of age and in hemin fed birds at wk 22. The reduction in uric acid concentration was associated with an increase in the level of oxidative stress, which can be linked to the increase in tissue skin pentosidine, thus advancing the decline in meat tenderness

EBA's Capital Exercise and Technical Efficiency of the Banks

This study uses a sample of 194 banks from 15 EU countries and two-stage data envelopment analysis (DEA) to provide evidence on the impact of the European Banking Authority (EBA)'s capital exercise on banks' efficiency. In the first stage of the analysis, we measure the efficiency by employing DEA. We then use Tobit regression to investigate the impact of the capital exercise on banks' technical efficiency. We estimate several specifications while controlling for bank-specific attributes and country-level characteristics accounting for macroeconomic conditions, financial development and market structure. The results indicate that EBA's capital exercise came, as a shock for the banks would be contributing towards making the banks more stable. It would be preventing banks from excessive risk-taking activities. Furthermore, it would be allowing the banks to withstand the financial distress and contributing in banks be- coming less prone to the systemic risk. The study finds that the capital requirements would be creating favourable economic conditions, which would be, affect the extent, depth and quality of financial intermediation and banking services

QWID: Quantized Weed Identification Deep neural network

In this paper, we present an efficient solution for weed classification in agriculture. We focus on optimizing model performance at inference while respecting the constraints of the agricultural domain. We propose a Quantized Deep Neural Network model that classifies a dataset of 9 weed classes using 8-bit integer (int8) quantization, a departure from standard 32-bit floating point (fp32) models. Recognizing the hardware resource limitations in agriculture, our model balances model size, inference time, and accuracy, aligning with practical requirements. We evaluate the approach on ResNet-50 and InceptionV3 architectures, comparing their performance against their int8 quantized versions. Transfer learning and fine-tuning are applied using the DeepWeeds dataset. The results show staggering model size and inference time reductions while maintaining accuracy in real-world production scenarios like Desktop, Mobile and Raspberry Pi. Our work sheds light on a promising direction for efficient AI in agriculture, holding potential for broader applications. Code: https://github.com/parikshit14/QNN-for-weedComment: 6 pages, 6 figures, 4 table