Angular Resolution of an EAS Array for Gamma Ray Astronomy at Energies Greater Than 5 x 10 (13) Ev

A 24 detector extensive air shower array is being operated at Ootacamund (2300 m altitude, 11.4 deg N latitude) in southern India for a study of arrival directions of showers of energies greater than 5 x 10 to the 13th power eV. Various configurations of the array of detectors have been used to estimate the accuracy in determination of arrival angle of showers with such an array. These studies show that it is possible to achieve an angular resolution of better than 2 deg with the Ooty array for search for point sources of Cosmic gamma rays at energies above 5 x 10 to the 13th power eV

A Bayesian approach to Lagrangian data assimilation

Lagrangian data arise from instruments that are carried by the flow in a fluid field. Assimilation of such data into ocean models presents a challenge due to the potential complexity of Lagrangian trajectories in relatively simple flow fields. We adopt a Bayesian perspective on this problem and thereby take account of the fully non-linear features of the underlying model. In the perfect model scenario, the posterior distribution for the initial state of the system contains all the information that can be extracted from a given realization of observations and the model dynamics. We work in the smoothing context in which the posterior on the initial conditions is determined by future observations. This posterior distribution gives the optimal ensemble to be used in data assimilation. The issue then is sampling this distribution. We develop, implement, and test sampling methods, based on Markov-chain Monte Carlo (MCMC), which are particularly well suited to the low-dimensional, but highly non-linear, nature of Lagrangian data. We compare these methods to the well-established ensemble Kalman filter (EnKF) approach. It is seen that the MCMC based methods correctly sample the desired posterior distribution whereas the EnKF may fail due to infrequent observations or non-linear structures in the underlying flow

Recovering missing data on satellite images

International audienceData Assimilation is commonly used in environmental sciences to improve forecasts, obtained by meteorological, oceanographic or air quality simulation models, with observation data. It aims to solve an evolution equation, describing the dynamics, and an observation equation, measuring the misfit between the state vector and the observations, to get a better knowledge of the actual system's state, named the reference. In this article, we describe how to use this technique to recover missing data and reduce noise on satellite images. The recovering process is based on assumptions on the underlying dynamics displayed by the sequence of images. This is a promising alternative to methods such as space-time interpolation. In order to better evaluate our approach, results are first quantified for an artificial noise applied on the acquisitions and then displayed for real data

Stage 3 N2 lung cancer: A multidisciplinary therapeutic conundrum

The treatment of stage III N2 non-small cell lung cancer (NSCLC) remains debated. There is an absence of a universally agreed definition of resectability for this heterogeneous group and a lack of trial data. We reviewed and compared current international guidelines and evidence surrounding management of stage III N2 NSCLC. The Irish and Australian guidelines advise subcategorising N2 disease into N2a (may be resectable) and N2b (never resectable). On the contrary, American and British guidelines avoid subcategorising N2 disease, emphasising importance of local MDT decisions. It is suggested that evidence for resection of stage III tumours is relatively weak, but that stage IIIA should generally be considered for resection, and stage IIIB is not recommended for resection. For resectable disease, surgery may be combined with neoadjuvant chemoimmunotherapy, or adjuvant chemotherapy followed by immunotherapy and radiotherapy in selected patients. There is some evidence that technically resectable disease can be treated solely with radiotherapy with similar outcomes to resection. In the event of unresectable disease, chemoradiotherapy has been the traditional management option. However, recent studies with chemoradiotherapy alongside immunotherapy appear promising. There are many factors that influence the treatment pathway offered to patients with stage III N2 NSCLC, including patient factors, team expertise, and local resources. Therefore, the role of MDTs in defining resectability and formulating an individualised treatment plan is crucial. [Abstract copyright: © 2024. Crown.

The impact of nonlinearity in Lagrangian data assimilation

The focus of this paper is on how two main manifestations of nonlinearity in low-dimensional systems – shear around a center fixed point (nonlinear center) and the differential divergence of trajectories passing by a saddle (nonlinear saddle) – strongly affect data assimilation. The impact is felt through their leading to non-Gaussian distribution functions. The major factors that control the strength of these effects is time between observations, and covariance of the prior relative to covariance of the observational noise. Both these factors – less frequent observations and larger prior covariance – allow the nonlinearity to take hold. To expose these nonlinear effects, we use the comparison between exact posterior distributions conditioned on observations and the ensemble Kalman filter (EnKF) approximation of these posteriors. We discuss the serious limitations of the EnKF in handling these effects

Self Injection length in La0.7 Ca0.3 Mno3-YBa 2Cu3O7-d ferromagnet- superconductor multi layer thin films

We have carried out extensive studies on the self-injection problem in barrierless heterojunctions between La0.7Ca0.3MnO3 (LCMO) and YBa2Cu3O7-d (YBCO). The heterojunctions were grown in situ by sequentially growing LCMO and YBCO films on LaAlO3 (LAO) substrate using a pulsed laser deposition (PLD) system. YBCO micro-bridges with 64 microns width were patterned both on the LAO (control) and LCMO side of the substrate. Critical current, Ic, was measured at 77K on both the control side as well as the LCMO side for different YBCO film thickness. It was observed that while the control side showed a Jc of ~2 x 10E6 A/ cm2 the LCMO side showed about half the value for the same thickness (1800 A). The difference in Jc indicates that a certain thickness of YBCO has become 'effectively' normal due to self-injection. From the measurement of Jc at two different thickness' (1800 A and 1500 A) of YBCO both on the LAO as well as the LCMO side, the value of self-injection length (at 77K) was estimated to be ~900 A self-injection length has been quantified. A control experiment carried out with LaNiO3 deposited by PLD on YBCO did not show any evidence of self-injection.Comment: 6 pages, one figure in .ps forma

Rank deficiency of Kalman error covariance matrices in linear time-varying system with deterministic evolution

We prove that for-linear, discrete, time-varying, deterministic system (perfect-model) with noisy outputs, the Riccati transformation in the Kalman filter asymptotically bounds the rank of the forecast and the analysis error covariance matrices to be less than or equal to the number of nonnegative Lyapunov exponents of the system. Further, the support of these error covariance matrices is shown to be confined to the space spanned by the unstable-neutral backward Lyapunov vectors, providing the theoretical justification for the methodology of the algorithms that perform assimilation only in the unstable-neutral subspace. The equivalent property of the autonomous system is investigated as a special case

A Bayesian approach to Lagrangian data assimilation

Lagrangian data arise from instruments that are carried by the flow in a fluid field. Assimilation of such data into ocean models presents a challenge due to the potential complexity of Lagrangian trajectories in relatively simple flow fields. We adopt a Bayesian perspective on this problem and thereby take account of the fully non-linear features of the underlying model. In the perfect model scenario, the posterior distribution for the initial state of the system contains all the information that can be extracted from a given realization of observations and the model dynamics. We work in the smoothing context in which the posterior on the initial conditions is determined by future observations. This posterior distribution gives the optimal ensemble to be used in data assimilation. The issue then is sampling this distribution. We develop, implement, and test sampling methods, based on Markov-chain Monte Carlo (MCMC), which are particularly well suited to the low-dimensional, but highly non-linear, nature of Lagrangian data. We compare these methods to the well-established ensemble Kalman filter (EnKF) approach. It is seen that the MCMC based methods correctly sample the desired posterior distribution whereas the EnKF may fail due to infrequent observations or non-linear structures in the underlying flow

Optimization of HALO structure effects in 45nm p-type MOSFETs device using Taguchi Method

In this study, the Taguchi method was used to optimize the effect of HALO structure or halo implant variations on threshold voltage (VTH) and leakage current (ILeak) in 45nm p-type Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) device. Besides halo implant dose, the other process parameters which used were Source/Drain (S/D) implant dose, oxide growth temperature and silicide anneal temperature. This work was done using TCAD simulator, consisting of a process simulator, ATHENA and device simulator, ATLAS. These two simulators were combined with Taguchi method to aid in design and optimize the process parameters. In this research, the most effective process parameters with respect to VTH and ILeak are halo implant dose (40%) and S/D implant dose (52%) respectively. Whereas the second ranking factor affecting VTH and ILeak are oxide growth temperature (32%) and halo implant dose (34%) respectively. The results show that after optimizations approaches is -0.157V at ILeak=0.195mA/μm