Methods of sequential estimation for determining initial data in numerical weather prediction

Numerical weather prediction (NWP) is an initial-value problem for a system of nonlinear differential equations, in which initial values are known incompletely and inaccurately. Observational data available at the initial time must therefore be supplemented by data available prior to the initial time, a problem known as meteorological data assimilation. A further complication in NWP is that solutions of the governing equations evolve on two different time scales, a fast one and a slow one, whereas fast scale motions in the atmosphere are not reliably observed. This leads to the so called initialization problem: initial values must be constrained to result in a slowly evolving forecast. The theory of estimation of stochastic dynamic systems provides a natural approach to such problems. For linear stochastic dynamic models, the Kalman-Bucy (KB) sequential filter is the optimal data assimilation method, for linear models, the optimal combined data assimilation-initialization method is a modified version of the KB filter

Acute complete heart block in dogs

A study has been conducted immediately and up to 18 days after the surgical production of complete heart block in dogs. Immediately after surgery cardiac output, coronary flow, and mean arterial pressure were reduced in rough proportion to the degree of bradycardia. In time, these measures began to return toward preoperative levels. Paralleling the diminished left ventricular work was a diminished left ventricular oxygen consumption with little consequent change in myocardial efficiency. Small rises were detected in central venous pressure. At autopsy, the only unequivocal abnormality was myocardial hypertrophy which became measurable between 2 and 18 days after operation

Dimers on two-dimensional lattices

We consider close-packed dimers, or perfect matchings, on two-dimensional regular lattices. We review known results and derive new expressions for the free energy, entropy, and the molecular freedom of dimers for a number of lattices including the simple-quartic (4^4), honeycomb (6^3), triangular (3^6), kagome (3.6.3.6), 3-12 (3.12^2) and its dual [3.12^2], and 4-8 (4.8^2) and its dual Union Jack [4.8^2] Archimedean tilings. The occurrence and nature of phase transitions are also analyzed and discussed.Comment: Typos corrections in Eqs. (28), (32) and (43

Ground states and formal duality relations in the Gaussian core model

We study dimensional trends in ground states for soft-matter systems. Specifically, using a high-dimensional version of Parrinello-Rahman dynamics, we investigate the behavior of the Gaussian core model in up to eight dimensions. The results include unexpected geometric structures, with surprising anisotropy as well as formal duality relations. These duality relations suggest that the Gaussian core model possesses unexplored symmetries, and they have implications for a broad range of soft-core potentials.Comment: 7 pages, 1 figure, appeared in Physical Review E (http://pre.aps.org

Big brother is watching - using digital disease surveillance tools for near real-time forecasting

Abstract for the International Journal of Infectious Diseases 79 (S1) (2019).https://www.ijidonline.com/article/S1201-9712(18)34659-9/abstractPublished versio

Multidisciplinary team meetings in palliative care: an ethnographic study

OBJECTIVES: Multidisciplinary team meetings are a regular feature in the provision of palliative care, involving a range of professionals. Yet, their purpose and best format are not necessarily well understood or documented. This article describes how hospital and community-based palliative care multidisciplinary team meetings operate to elucidate some of their main values and offer an opportunity to share examples of good practice. METHODS: Ethnographic observations of over 70 multidisciplinary team meetings between May 2018 and January 2020 in hospital and community palliative care settings in intercity London. These observations were part of a larger study examining palliative care processes. Fieldnotes were thematically analysed. RESULTS: This article analyses how the meetings operated in terms of their setup, participants and general order of business. Meetings provided a space where patients, families and professionals could be cared for through regular discussions of service provision. CONCLUSIONS: Meetings served a variety of functions. Alongside discussing the more technical, clinical and practical aspects that are formally recognised aspects of the meetings, an additional core value was enabling affectual aspects of dealing with people who are dying to be acknowledged and processed collectively. Insight into how the meetings are structured and operate offer input for future practice

Heat Conduction and Magnetic Phase Behavior in Electron-Doped Ca_{1-x} La_x MnO_3(0 <= x <= 0.2)

Measurements of thermal conductivity (kappa) vs temperature are reported for a series of Ca_{1-x} La_x MnO_3(0 <= x <= 0.2) specimens. For the undoped (x=0), G-type antiferromagnetic compound a large enhancement of kappa below the Neel temperature (T_N ~ 125 K) indicates a strong coupling of heat-carrying phonons to the spin system. This enhancement exhibits a nonmonotonic behavior with increasing x and correlates remarkably well with the small ferromagnetic component of the magnetization reported previously [Neumeier and Cohn, Phys. Rev. B 61 14319 (2000).] Magnetoelastic polaron formation appears to underly the behavior of kappa and the magnetization at x <= 0.02.Comment: submitted to PRB; 4 pp., 4 Fig.'s, RevTex

ViTac: Feature Sharing between Vision and Tactile Sensing for Cloth Texture Recognition

Vision and touch are two of the important sensing modalities for humans and they offer complementary information for sensing the environment. Robots could also benefit from such multi-modal sensing ability. In this paper, addressing for the first time (to the best of our knowledge) texture recognition from tactile images and vision, we propose a new fusion method named Deep Maximum Covariance Analysis (DMCA) to learn a joint latent space for sharing features through vision and tactile sensing. The features of camera images and tactile data acquired from a GelSight sensor are learned by deep neural networks. But the learned features are of a high dimensionality and are redundant due to the differences between the two sensing modalities, which deteriorates the perception performance. To address this, the learned features are paired using maximum covariance analysis. Results of the algorithm on a newly collected dataset of paired visual and tactile data relating to cloth textures show that a good recognition performance of greater than 90% can be achieved by using the proposed DMCA framework. In addition, we find that the perception performance of either vision or tactile sensing can be improved by employing the shared representation space, compared to learning from unimodal data