Clustering clinical departments for wards to achieve a prespecified blocking probability

When the number of available beds in a hospital is limited and fixed, it can be beneficial to cluster several clinical departments such that the probability of not being able to admit a patient is acceptably small. The clusters are then assigned to the available wards such that enough beds are available to guarantee a blocking probability below a prespecified value. We first give an exact formulation of the problem to be able to achieve optimal solutions. To reduce computation times, we also introduce two heuristic solution methods. The first heuristic is similar to the exact solution method, however, the number of beds needed is approximated by a linear function. The second heuristic uses a local search approach to determine the assignment of clinical departments to clusters and a restricted version of the exact solution method to determine the assignment of clusters to wards

Improve OR-schedule to reduce number of required beds

After surgery most of the surgical patients have to be admitted in a ward in the hospital. Due to financial reasons and an decreasing number of available nurses in the Netherlands over the years, it is important to reduce the bed usage as much as possible. One possible way to achieve this is to create an operating room (OR) schedule that spreads the usage of beds nicely over time, and thereby minimizes the number of required beds. An OR-schedule is given by an assignment of OR-blocks to specific days in the planning horizon and has to fulfill several resource constraints. Due to the stochastic nature of the length of stay of patients, the analytic calculation of the number of required beds for a given OR-schedule is a complex task involving the convolution of discrete distributions. In this paper, two approaches to deal with this complexity are presented. First, a heuristic approach based on local search is given, which takes into account the detailed formulation of the objective. A second approach reduces the complexity by simplifying the objective function. This allows modeling and solving the resulting problem as an ILP. Both approaches are tested on data provided by Hagaziekenhuis in the Netherlands. Furthermore, several what-if scenarios are evaluated. The computational results show that the approach that uses the simplified objective function provides better solutions to the original problem. By using this approach, the number of required beds for the considered instance of HagaZiekenhuis can be reduced by almost 20%

Long Range Magnetic Order and the Darwin Lagrangian

We simulate a finite system of $N$ confined electrons with inclusion of the Darwin magnetic interaction in two- and three-dimensions. The lowest energy states are located using the steepest descent quenching adapted for velocity dependent potentials. Below a critical density the ground state is a static Wigner lattice. For supercritical density the ground state has a non-zero kinetic energy. The critical density decreases with $N$ for exponential confinement but not for harmonic confinement. The lowest energy state also depends on the confinement and dimension: an antiferromagnetic cluster forms for harmonic confinement in two dimensions.Comment: 5 figure

Vector Theory of Gravity

We proposed a gravitation theory based on an analogy with electrodynamics on the basis of a vector field. For the first time, to calculate the basic gravitational effects in the framework of a vector theory of gravity, we use a Lagrangian written with gravitational radiation neglected and generalized to the case of ultra-relativistic speeds. This allows us to accurately calculate the values of all three major gravity experiments: the values of the perihelion shift of Mercury, the light deflection angle in the gravity field of the Sun and the value of radar echo delay. The calculated values coincide with the observed ones. It is shown that, in this theory, there exists a model of an expanding Universe.Comment: 9 page

Exploring the action landscape with trial world-lines

The Hamilton action principle, also known as the principle of least action, and Lagrange equations are an integral part of advanced undergraduate mechanics. At present, substantial efforts are ongoing to suitably incorporate the action principle in introductory physics courses. Although the Hamilton principle is oft stated as "the action for any nearby trial world-line is greater than the action for the classical world-line", the landscape of action in the space of world-lines is rarely explored. Here, for three common problems in introductory physics - a free particle, a uniformly accelerating particle, and a simple harmonic oscillator - we present families of trial world-lines, characterized by a few parameters, that evolve continuously from their respective classical world-lines. With explicit analytical expressions available for the action, they permit a graphical visualization of the action landscape in the space of nearby world-lines. Although these trial world-lines form only a subset of the space of all nearby world-lines, they provide a pedagogical tool that complements the traditional Lagrange equation approach and is well-suited for advanced undergraduate students.Comment: 9 pages, 6 figures, significant structural revisio

Models for ambulance planning on the strategic and the tactical level

Ambulance planning involves decisions to be made on different levels. The decision for choosing base locations is usually made for a very long time (strategic level), but the number and location of used ambulances can be changed within a shorter time period (tactical level). We present possible formulations for the planning problems on these two levels and discuss solution approaches that solve both levels either simultaneously or separately. The models are set up such that different types of coverage constraints can be incorporated. Therefore, the models and approaches can be applied to different emergency medical services systems occurring all over the world. The approaches are tested on data based on the situation in the Netherlands and compared based on computation time and solution quality. The results show that the solution approach that solves both levels separately performs better when considering minimizing the number of bases. However, the solution approach that solves both levels simultaneously performs better when considering minimizing the number of ambulances. In addition, with the latter solution approach it is easier to make a good trade-off between minimizing the number of bases and ambulances because it considers a weighted objective function. However, the computation time of this approach increases exponentially with the input size whereas the computation time of the approach that solves both levels separately follows a more linear trend

Pattern recognition, attention, and information bottlenecks in the primate visual system

In its evolution, the primate visual system has developed impressive capabilities for recognizing complex patterns in natural images. This process involves many stages of analysis and a variety of information processing strategies. This paper concentrates on the importance of 'information bottlenecks,' which restrict the amount of information that can be handled at different stages of analysis. These steps are crucial for reducing the overwhelming computational complexity associated with recognizing countless objects from arbitrary viewing angles, distances, and perspectives. The process of directed visual attention is an especially important information bottleneck because of its flexibility in determining how information is routed to high-level pattern recognition centers