arXiv subjects

Manpreet Kaur

Publications and source records attributed to Manpreet Kaur.

36 records · Page 2Linked to original sources

arXiv2024

Effect of Asymmetric Nuclear Medium on the Valence Quark Structure of the Kaons

The role of asymmetric nuclear medium on the properties of kaon is investigated at zero and finite temperature employing a hybrid approach integrating the light cone quark model (LCQM) and the chiral SU(3) quark mean field (CQMF) model. The in-medium quark masses are calculated within the CQMF model and are used as inputs to study the medium modifications in the kaon properties. In particular, we have analysed the impact of baryonic density, isospin asymmetry and temperature on the weak decay constant, distribution amplitudes (DAs) and parton quark distributions (PDFs) of valence quark structure of kaons. The effects of isospin asymmetry on the kaon doublet $K =\left(\begin{array}{c} K^{+} \\ K^{0} \end{array} \right)$ and antikaon doublet $\bar{K}$= ($K^-, \bar{K}^0$) are also studied. In order to compare with future experiments, we have also evolved the in-medium DAs and PDFs of kaons to $Q^2=16$ GeV$^2$. As compared to the temperature and isospin asymmetry, change in baryonic density of the nuclear medium makes more significant changes to the DAs and PDFs of kaons.

hep-ph↗

arXiv2024

Kaons and antikaons in isospin asymmetric dense resonance matter at finite temperature

We study the in-medium properties of kaons and antikaons in isospin asymmetric hot and dense resonance matter within the chiral SU(3) hadronic mean field model. Along with nucleons and hyperons, the interactions of $K$ and $\bar K$ mesons with all decuplet baryons ($Δ^{++,+,0,-}, Σ^{*\pm,0},Ξ^{*0,-}, Ω^{-}$) are explicitly considered in the dispersion relations. The properties of mesons in the chiral SU(3) model are modified at finite density and temperature of asymmetric resonance matter through the exchange of scalar fields $σ, ζ$ and $δ$ and the vector fields $ω, ρ$ and $ϕ$. The presence of resonance baryons in the medium at finite temperature is observed to modify significantly the effective masses of $K$ and $\bar{K}$ mesons. We also calculated the optical potentials of kaons and antikaons as a function of momentum in resonance matter. The present study of in-medium masses and optical potentials of kaons and antikaons will be important for understanding the experimental observables from the heavy-ion collision experiments where hot and dense matter may be produced. Our results indicate that when resonance baryons are present within the medium at finite baryonic density, the mass reduction of kaons and antikaons becomes more pronounced as the temperature of the medium increases from zero to 100 and 150 MeV. The study of the optical potentials of kaons and antikaons reveals a stronger correlation with strangeness fraction compared to isospin asymmetry.

hep-ph↗

arXiv2024

Nerve Block Target Localization and Needle Guidance for Autonomous Robotic Ultrasound Guided Regional Anesthesia

Visual servoing for the development of autonomous robotic systems capable of administering UltraSound (US) guided regional anesthesia requires real-time segmentation of nerves, needle tip localization and needle trajectory extrapolation. First, we recruited 227 patients to build a large dataset of 41,000 anesthesiologist annotated images from US videos of brachial plexus nerves and developed models to localize nerves in the US images. Generalizability of the best suited model was tested on the datasets constructed from separate US scanners. Using these nerve segmentation predictions, we define automated anesthesia needle targets by fitting an ellipse to the nerve contours. Next, we developed an image analysis tool to guide the needle toward their targets. For the segmentation of the needle, a natural RGB pre-trained neural network was first fine-tuned on a large US dataset for domain transfer and then adapted for the needle using a small dataset. The segmented needle trajectory angle is calculated using Radon transformation and the trajectory is extrapolated from the needle tip. The intersection of the extrapolated trajectory with the needle target guides the needle navigation for drug delivery. The needle trajectory average error was within acceptable range of 5 mm as per experienced anesthesiologists. The entire dataset has been released publicly for further study by the research community at https://github.com/Regional-US/

cs.CV↗

arXiv2024

Enhanced quantum emission from a topological Floquet resonance

Entanglement is a valuable resource in quantum information technologies. The practical implementation of entangled photon sources faces obstacles from imperfections and defects inherent in physical systems, resulting in a loss or degradation of entanglement. The topological photonic insulators, however, have emerged as promising candidates, demonstrating an exceptional capability to resist defect-induced scattering, thus enabling the development of robust entangled sources. Despite their inherent advantages, building programmable topologically protected entangled sources remains challenging due to complex device designs and weak material nonlinearity. Here we present a development in entangled photon pair generation achieved through a non-magnetic and tunable anomalous Floquet insulator, utilizing an optical spontaneous four-wave mixing process. We verify the non-classicality and time-energy entanglement of the photons generated by our topological system. Our experiment demonstrates a substantial enhancement in nonclassical photon pair generation compared to devices reliant only on topological edge states. Our result could lead to the development of resilient quantum sources with potential applications in quantum technology.

quant-ph↗

arXiv2024

On The Effective Rate and Error Rate Analysis over Fluctuating Nakagami-m Fading Channel

This paper provides a detailed analysis of the important performance metrics like effective capacity and symbol error rate over fluctuating Nakagami-m fading channel. This distribution is obtained from the ratio of two random variables, following the Nakagami-m distribution and the uniform distribution. Our study derives exact analytical expressions for the EC and SER under different modulation schemes, considering the effect of channel parameters. Recognising the importance of additive Laplacian noise in today scenario, it has been considered for the error performance analysis of the system. This work may be utilised for the design and optimization of the systems operating in environments characterized by fluctuating Nakagami-m fading.

cs.IT↗

arXiv2023

On the Effective throughput of Shadowed Beaulieu-Xie fading channel

Given the imperative for advanced wireless networks in the next generation and the rise of real-time applications within wireless communication, there is a notable focus on investigating data rate performance across various fading scenarios. This research delved into analyzing the effective throughput of the shadowed Beaulieu-Xie (SBX) composite fading channel using the PDF-based approach. To get the simplified relationship between the performance parameter and channel parameters, the low-SNR and the high-SNR approximation of the effective rate are also provided. The proposed formulations are evaluated for different values of system parameters to study their impact on the effective throughput. Also, the impact of the delay parameter on the EC is investigated. Monte-Carlo simulations are used to verify the facticity of the deduced equations.

cs.IT↗

arXiv2023

A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information

Resection and whole brain radiotherapy (WBRT) are the standards of care for the treatment of patients with brain metastases (BM) but are often associated with cognitive side effects. Stereotactic radiosurgery (SRS) involves a more targeted treatment approach and has been shown to avoid the side effects associated with WBRT. However, SRS requires precise identification and delineation of BM. While many AI algorithms have been developed for this purpose, their clinical adoption has been limited due to poor model performance in the clinical setting. Major reasons for non-generalizable algorithms are the limitations in the datasets used for training the AI network. The purpose of this study was to create a large, heterogenous, annotated BM dataset for training and validation of AI models to improve generalizability. We present a BM dataset of 200 patients with pretreatment T1, T1 post-contrast, T2, and FLAIR MR images. The dataset includes contrast-enhancing and necrotic 3D segmentations on T1 post-contrast and whole tumor (including peritumoral edema) 3D segmentations on FLAIR. Our dataset contains 975 contrast-enhancing lesions, many of which are sub centimeter, along with clinical and imaging feature information. We used a streamlined approach to database-building leveraging a PACS-integrated segmentation workflow.

q-bio.QM↗

arXiv2023

Designing Mixed-Metal Electrocatalyst Systems for Photoelectrochemical Dinitrogen Activation

Efficient artificial photosynthesis systems are currently realized as catalyst- and surfacefunctionalized photovoltaic tandem- and triple-junction devices, enabling photoelectrochemical (PEC) water oxidation while simultaneously recycling CO2 and generating hydrogen as a solar fuel for storable renewable energy. Although PEC systems also bear advantages for the activation of dinitrogen - such as a high system tunability with respect to the electrocatalyst integration and a directly controllable electron flux to the anchoring catalyst through the adjustability of incoming irradiation - only a few PEC devices have been developed and investigated for this purpose. We have developed a series of photoelectrodeposition procedures to deposit mixed-metal electrocatalyst nanostructures directly on the semiconductor surface for light-assisted dinitrogen activation. These electrocatalyst compositions containing Co, Mo and Ru in different atomic ratios follow previously made recommendations of metal compositions for dinitrogen reduction and exhibit different physical properties. XPS studies of the photoelectrode surfaces reveal that our electrocatalyst films are to a large degree nitrogen-free after their fabrication, which is generally difficult to achieve with traditional magnetron sputtering or e-beam evaporation techniques. Initial chronoamperometric measurements of the p-InP photoelectrode coated with the Co-Mo alloy electrocatalyst show higher photocurrent densities in the presence of N2(g) than in the presence of Ar at -0.09 V vs RHE. Indications of successful dinitrogen activation have also been found in consecutive XPS studies, where both, N 1s and Mo 3d spectra, reveal evidence of nitrogen-metal interactions.

cond-mat.mtrl-sci↗

arXiv2023

Quantum ghost imaging of a transparent polarisation sensitive phase pattern

A transparent polarisation sensitive phase pattern exhibits a position and polarisation dependent phase shift of transmitted light and it represents a unitary transformation. A quantum ghost image of this pattern is produced with hyper-entangled photons consisting of Einstein-Podolsky-Rosen (EPR) and polarisation entanglement. In quantum ghost imaging, a single photon interacts with the pattern and is detected by a stationary detector and a non-interacting photon is imaged on a coincidence camera. EPR entanglement manifests spatial correlations between an object plane and a ghost image plane, whereas a polarisation dependent phase shift exhibited by the pattern is detected with polarisation entanglement. In this quantum ghost imaging, the which-position-polarisation information of a photon interacting with the pattern is not present in the experiment. A quantum ghost image is constructed by measuring correlations of the polarisation-momentum of an interacting photon with polarisation-position of a non-interacting photon. The experiment is performed with a coincidence single photon detection camera, where a non-interacting photon travels a long optical path length of 17.83~$m$ from source to camera and a pattern is positioned at an optical distance of 19.16~$m$ from the camera.

quant-ph↗

arXiv2021

Quantum imaging of a polarisation sensitive phase pattern with hyper-entangled photons

A transparent polarisation sensitive phase pattern makes a polarisation dependent transformation of quantum state of photons without absorbing them. Such an invisible pattern can be imaged with quantum entangled photons by making joint quantum measurements on photons. This paper shows a long path experiment to quantum image a transparent polarisation sensitive phase pattern with hyper-entangled photon pairs involving momentum and polarisation degrees of freedom. In the imaging configuration, a single photon interacts with the pattern while the other photon, which has never interacted with the pattern, is measured jointly in a chosen polarisation basis and in a quantum superposition basis of its position which is equivalent to measuring its momentum. Individual photons of each hyper-entangled pair cannot provide a complete image information. The image is constructed by measuring the polarisation state and position of the interacting photon corresponding to a measurement outcome of the non-interacting photon. This paper presents a detailed concept, theory and free space long path experiments on quantum imaging of polarisation sensitive phase patterns.

quant-ph↗

arXiv2021

On the role of Initial Error Growth in the Skill of Extended Range Prediction of Madden-Julian Oscillation (MJO)

The seamless forecast approach of subseasonal to seasonal scale variability has been succeeding in the forecast of multiple meteorological scales in a uniform framework. In this paradigm, it is hypothesized that reduction in initial error in dynamical forecast would help to reduce forecast error in extended lead-time up to 2-3 weeks. This is tested in a version of operational extended range forecasts based on Climate Forecast System version 2 (CFSv2) developed at Indian Institute of Tropical Meteorology (IITM), Pune. Forecast skills are assessed to understand the role of initial errors on the prediction skill for MJO. A set of lowest and highest initial day error (LIDE & HIDE) cases are defined and the error-growth for these categories are analysed for the strong MJO events during May to September (MJJAS). The MJO forecast initial errors are categorized and defined using the well-known multivariate MJO index introduced by Wheeler &Hendon (2004). The probability distribution of bivariate RMSE and error growth evolution (first order difference of index error for each successive lead days) with respect to extended range lead-time are used as metrics in this analysis. The result showed that initial error is not showing any influence in the skill of model after a lead time of 7-10 days and the error growth remains the same for both set of errors. A rapid error growth evolution of same order is seen for both the classified cases. Further the physical attribution of these errors is studied and found that the errors originate from the events with initial phase in Western Pacific and Indian Ocean. The spatial distribution of OLR and the zonal winds also confirms the same. The study emphasises the importance of better representation of MJO phases especially over Indian ocean in the model to improve the MJO prediction rather than focusing primarily on the initial condition

physics.ao-ph↗

arXiv2021

Application of the coherent density fluctuation model to study the nuclear matter properties of finite nuclei within the relativistic mean-field formalism

We obtained a density-dependent analytical expression of binding energy per nucleon for different neutron-proton asymmetry of the nuclear matter (NM) with a polynomial fitting, which manifests the results of effective field theory motivated relativistic mean-field (E-RMF) model. This expression has the edge over the Br$\ddot{u}$ckner energy density functional [Phys. Rev. {\bf 171}, 1188 (1968)] since it resolves the Coster-Band problem. The NM parameters like incompressibility, neutron pressure, symmetry energy, and its derivatives are calculated using the acquired expression of energy per nucleon. Further, the weight function calculated by E-RMF densities are folded with calculated NM parameters within coherent density fluctuation model to find the properties of closed/semi-closed-shell even-even $^{16}$O, $^{40}$Ca, $^{48}$Ca, $^{56}$Ni, $^{90}$Zr, $^{116}$Sn, and $^{208}$Pb nuclei. The values obtained for the neutron pressure $P^{A}$, symmetry energy $S^{A}$ and its derivative $L_{sym}^A$ known as slope parameter, lie within a narrow domain whereas there is a large variation in isoscalar incompressibility $K^{A}$ and surface incompressibility $K_{sym}^{A}$ while moving from light to heavy nuclei. The sizable variation in $K^{A}$ and $K_{sym}^{A}$ for light and heavy nuclei depicts their structural dependence due to the peculiar density distribution of each nucleus. A comparison of surface quantities calculated in the present work has also been made with ones obtained via Br$\ddot{u}$ckner energy density functional.

nucl-th↗

arXiv2020

Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors

This paper investigates the Cyber-Physical behavior of users in a large indoor shopping mall by leveraging anonymized (opt in) Wi-Fi association and browsing logs recorded by the mall operators. Our analysis shows that many users exhibit a high correlation between their cyber activities and their physical context. To find this correlation, we propose a mechanism to semantically label a physical space with rich categorical information from DBPedia concepts and compute a contextual similarity that represents a user's activities with the mall context. We demonstrate the application of cyber-physical contextual similarity in two situations: user visit intent classification and future location prediction. The experimental results demonstrate that exploitation of contextual similarity significantly improves the accuracy of such applications.

cs.IR↗

arXiv2020

On the airborne aspect of COVID-19 coronovirus

It is a widely accepted view that COVID 19 is either transmitted via surface contamination or via close contact of an un-infected person with an infected person. Surface contamination usually happens when infected water droplets from exhalation/sneeze/cough of COVID sick person settle on nearby surfaces. To curb this, social distancing and good hand hygiene advise is advocated by World health Organization (WHO). We argue that COVID 19 coronovirus can also be airborne in a puff cloud loaded with infected droplets generated by COVID sick person. An elementary calculation shows that a $5~μm$ respiratory infected droplet can remain suspended for about 9.0 minutes and a $2~μm$ droplet can remain suspended for about an hour! And social distancing advise of 3 feet by WHO and 6 feet by CDC (Centers for Disease Control and Prevention) may not be sufficient in some circumstances as discussed in the text.

physics.pop-ph↗

arXiv2019

A Comprehensive Performance Evaluation of a DF-Based Multi-Hop System Over $α-κ-μ$ and $α-κ-μ$-Extreme Fading Channels

In this work, an integrated performance evaluation of a decode-and-forward (DF) multi-hop wireless communication system is undertaken over the non-linear generalized $α-κ-μ$ and $α-κ-μ$-Extreme fading models. Analytical formulas for the probability density function (PDF) and the cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) as well as its generalized moments and moment generating function (MGF) are derived. Based on the derived PDFs, novel closed-form expressions for traditional performance metrics such as amount of fading (AF), outage probability (OP), bit error rate (BER) under coherent and non-coherent modulation schemes as well as channel capacity under various adaptive transmission techniques are derived. Additionally, asymptotic analyses of BER based on Poincare series expansions of SNR PDFs are carried out and results show good approximations for low SNR regimes. The correctness of the proposed solutions has been corroborated by comparing them with Monte Carlo simulation results.

cs.IT↗

arXiv2017

Specially designed B4C/SnO2 nanocomposite for photocatalysis: traditional ceramic with unique properties

Boron carbide: A traditional ceramic material shows unique properties when explored in nano-range. Specially designed boron based nanocomposite has been synthesized by reflux method. The addition of SnO2 in base matrix increase the defect states in boron carbide and shows unique catalytic properties. The calculated texture coefficient and Nelson Riley factor shows that the synthesized nanocomposite have very high defect states. Also this composite is explored for the first time for catalysis degradation of industrial used dyes. The industrial pollutants such as Novacron red and methylene blue dye degradation analysis reveal that the composite is an efficient catalyst. Degradation study shows that 1 g/L catalyst concentration of B4C/SnO2 degrade Novacron red Huntsman dye upto 97.38% approximately in 20 minutes under sunlight irradiation time. This water insoluble catalyst can be recovered and reused.

physics.app-ph↗

arXiv2014

Toward Refactoring of DMARF and GIPSY Case Studies -- a Team 9 SOEN6471-S14 Project Report

Software architecture consists of series of decisions taken to give a structural solution that meets all the technical and operational requirements. The paper involves code refactoring. Code refactoring is a process of changing the internal structure of the code without altering its external behavior. This paper focuses over open source systems experimental studies that are DMARF and GIPSY. We have gone through various research papers and analyzed their architectures. Refactoring improves understandability, maintainability, extensibility of the code. Code smells were identified through various tools such as JDeodorant, Logiscope, and CodePro. Reverse engineering of DMARF and GIPSY were done for understanding the system. Tool used for this was Object Aid UML. For better understanding use cases, domain model, design class diagram are built.

cs.SE↗

arXiv2014

Survey on Variants of Distributed Energy efficient Clustering Protocols in heterogeneous Wireless Sensor Network

Wireless sensor networks are composed of low cost and extremely power constrained sensor nodes which are scattered over a region forming self organized networks, making energy consumption a crucial design issue. Thus, finite network lifetime is widely regarded as a fundamental performance bottleneck. These networks are used for various applications such as field monitoring, home automation, medical data collection or surveillance. Research has shown that clustering sensor nodes is an efficient method to manage energy consumption for prolonging the network lifetime. Presence of heterogeneity enhances the lifetime and reliability in network. In this paper, we present the distributed and energy efficient clustering protocols which follow the thoughts of Distributed Energy Efficient Clustering protocol. Objective of our work is to analyze that how these extended routing protocols work in order to optimize network lifetime and how routing protocols are improved. We emphasizes on issues experienced by various protocols and how these issues are tackled by other enhanced protocols. This provides a survey of work done on distributed energy efficient protocols

cs.NI↗