Adaptive resource allocation for efficient patient scheduling

Objective Efficient scheduling of patient appointments on expensive resources is a complex and dynamic task. A resource is typically used by several patient groups. To service these groups, resource capacity is often allocated per group, explicitly or implicitly. Importantly, due to fluctuations in demand, for the most efficient use of resources this allocation must be flexible. Methods We present an adaptive approach to automatic optimization of resource calendars. In our approach, the allocation of capacity to different patient groups is flexible and adaptive to the current and expected future situation. We additionally present an approach to determine optimal resource openings hours on a larger time frame. Our model and its parameter values are based on extensive case analysis at the Academic Medical Hospital Amsterdam. Results and conclusion We have implemented a comprehensive computer simulation of the application case. Simulation experiments show that our approach of adaptive capacity allocation improves the performance of scheduling patients groups with different attributes and makes efficient use of resource capacity

String pattern recognition using evolving spiking neural networks and quantum inspired particle swarm optimization

This paper proposes a novel method for string pattern recognition using an Evolving Spiking Neural Network (ESNN) with Quantum-inspired Particle Swarm Optimization (QiPSO). This study reveals an interesting concept of QiPSO by representing information as binary structures. The mechanism optimizes the ESNN parameters and relevant features using the wrapper approach simultaneously. The N-gram kernel is used to map Reuters string datasets into high dimensional feature matrix which acts as an input to the proposed method. The results show promising string classification results as well as satisfactory QiPSO performance in obtaining the best combination of ESNN parameters and in identifying the most relevant features

An early diagnostic tool for diabetic peripheral neuropathy in rats

The skin's rewarming rate of diabetic patients is used as a diagnostic tool for early diagnosis of diabetic neuropathy. At present, the relationship between microvascular changes in the skin and diabetic neuropathy is unclear in streptozotocin (STZ) diabetic rats. The aim of this study was to investigate whether the skin rewarming rate in diabetic rats is related to microvascular changes and whether this is accompanied by changes observed in classical diagnostic methods for diabetic peripheral neuropathy. Computer-assisted infrared thermography was used to assess the rewarming rate after cold exposure on the plantar skin of STZ diabetic rats' hind paws. Peripheral neuropathy was determined by the density of intra-epidermal nerve fibers (IENFs), mechanical sensitivity, and electrophysiological recordings. Data were obtained in diabetic rats at four, six, and eight weeks after the induction of diabetes and in controls. Four weeks after the induction of diabetes, a delayed rewarming rate, decreased skin blood flow and decreased density of IENFs were observed. However, the mechanical hyposensitivity and decreased motor nerve conduction velocity (MNCV) developed 6 and 8 weeks after the induction of diabetes. Our study shows that the skin rewarming rate is related to microvascular changes in diabetic rats. Moreover, the skin rewarming rate is a non-invasive method that provides more information for an earlier diagnosis of peripheral neuropathy than the classical monofilament test and MNCV in STZ induced diabetic rats

Exclusive Higgs Boson Production with bottom quarks at Hadron Colliders

We present the next-to-leading order QCD corrected rate for the production of a scalar Higgs boson with a pair of high p_T bottom and anti-bottom quarks at the Tevatron and at the Large Hadron Collider. Results are given for both the Standard Model and the Minimal Supersymmetric Standard Model. The exclusive b-bbar-h production rate is small in the Standard Model, but it can be greatly enhanced in the Minimal Supersymmetric Standard Model for large tan(beta), making b-bbar-h an important discovery mode. We find that the next-to-leading order QCD results are much less sensitive to the renormalization and factorization scales than the lowest order results, but have a significant dependence on the choice of the renormalization scheme for the bottom quark Yukawa coupling.Comment: 27 pages, 17 figures, RevTeX

Coherence Resonance and Noise-Induced Synchronization in Globally Coupled Hodgkin-Huxley Neurons

The coherence resonance (CR) of globally coupled Hodgkin-Huxley neurons is studied. When the neurons are set in the subthreshold regime near the firing threshold, the additive noise induces limit cycles. The coherence of the system is optimized by the noise. A bell-shaped curve is found for the peak height of power spectra of the spike train, being significantly different from a monotonic behavior for the single neuron. The coupling of the network can enhance CR in two different ways. In particular, when the coupling is strong enough, the synchronization of the system is induced and optimized by the noise. This synchronization leads to a high and wide plateau in the local measure of coherence curve. The local-noise-induced limit cycle can evolve to a refined spatiotemporal order through the dynamical optimization among the autonomous oscillation of an individual neuron, the coupling of the network, and the local noise.Comment: five pages, five figure

A search for ferromagnetism in transition-metal-doped piezoelectric ZnO

We present the results of a computational study of ZnO in the presence of Co and Mn substitutional impurities. The goal of our work is to identify potential ferromagnetic ground states within the (Zn,Co)O or (Zn,Mn)O material systems that are also good candidates for piezoelectricity. We find that, in contrast to previous results, robust ferromagnetism is not obtained by substitution of Co or Mn on the Zn site, unless additional carriers (holes) are also incorporated. We propose a practical scheme for achieving such $p$-type doping in ZnO

Gain-of-function Nav1.8 mutations in painful neuropathy

Painful peripheral neuropathy often occurs without apparent underlying cause. Gain-of-function variants of sodium channel Nav1.7 have recently been found in ~30% of cases of idiopathic painful small-fiber neuropathy. Here, we describe mutations in Nav1.8, another sodium channel that is specifically expressed in dorsal root ganglion (DRG) neurons and peripheral nerve axons, in patients with painful neuropathy. Seven Nav1.8 mutations were identified in 9 subjects within a series of 104 patients with painful predominantly small-fiber neuropathy. Three mutations met criteria for potential pathogenicity based on predictive algorithms and were assessed by voltage and current clamp. Functional profiling showed that two of these three Na v1.8 mutations enhance the channel's response to depolarization and produce hyperexcitability in DRG neurons. These observations suggest that mutations of Nav1.8 contribute to painful peripheral neuropathy

Comparison of s- and d-wave gap symmetry in nonequilibrium superconductivity

Recent application of ultrafast pump/probe optical techniques to superconductors has renewed interest in nonequilibrium superconductivity and the predictions that would be available for novel superconductors, such as the high-Tc cuprates. We have reexamined two of the classical models which have been used in the past to interpret nonequilibrium experiments with some success: the mu* model of Owen and Scalapino and the T* model of Parker. Predictions depend on pairing symmetry. For instance, the gap suppression due to excess quasiparticle density n in the mu* model, varies as n^{3/2} in d-wave as opposed to n for s-wave. Finally, we consider these models in the context of S-I-N tunneling and optical excitation experiments. While we confirm that recent pump/probe experiments in YBCO, as presently interpreted, are in conflict with d-wave pairing, we refute the further claim that they agree with s-wave.Comment: 14 pages, 11 figure

Three-dimensional random Voronoi tessellations: From cubic crystal lattices to Poisson point processes

We perturb the SC, BCC, and FCC crystal structures with a spatial Gaussian noise whose adimensional strength is controlled by the parameter a, and analyze the topological and metrical properties of the resulting Voronoi Tessellations (VT). The topological properties of the VT of the SC and FCC crystals are unstable with respect to the introduction of noise, because the corresponding polyhedra are geometrically degenerate, whereas the tessellation of the BCC crystal is topologically stable even against noise of small but finite intensity. For weak noise, the mean area of the perturbed BCC and FCC crystals VT increases quadratically with a. In the case of perturbed SCC crystals, there is an optimal amount of noise that minimizes the mean area of the cells. Already for a moderate noise (a>0.5), the properties of the three perturbed VT are indistinguishable, and for intense noise (a>2), results converge to the Poisson-VT limit. Notably, 2-parameter gamma distributions are an excellent model for the empirical of of all considered properties. The VT of the perturbed BCC and FCC structures are local maxima for the isoperimetric quotient, which measures the degre of sphericity of the cells, among space filling VT. In the BCC case, this suggests a weaker form of the recentluy disproved Kelvin conjecture. Due to the fluctuations of the shape of the cells, anomalous scalings with exponents >3/2 is observed between the area and the volumes of the cells, and, except for the FCC case, also for a->0. In the Poisson-VT limit, the exponent is about 1.67. As the number of faces is positively correlated with the sphericity of the cells, the anomalous scaling is heavily reduced when we perform powerlaw fits separately on cells with a specific number of faces