A new approach to forecasting intermittent demand based on the mixed zero-truncated Poisson model

This paper proposes a new approach to forecasting intermittent demand by considering the effects of external factors. We classify intermittent demand data into two parts—zero value and nonzero value—and fit nonzero values into a mixed zero-truncated Poisson model. All the parameters in this model are obtained by an EM algorithm, which regards external factors as independent variables of a logistic regression model and log-linear regression model. We then calculate the probability of occurrence of zero value at each period and predict demand occurrence by comparing it with critical value. When demand occurs, we use the weighted average of the mixed zero-truncated Poisson model as predicted nonzero demands, which are combined with predicted demand occurrences to form the final forecasting demand series. Two performance measures are developed to assess the forecasting methods. By presenting a case study of electric power material from the State Grid Shanghai Electric Power Company in China, we show that our approach provides greater accuracy in forecasting than the Poisson model, the hurdle shifted Poisson model, the hurdle Poisson model, and Croston's method.     

Evaluation of brood detection techniques: recommendations for estimating Greater Sage-Grouse productivity

Obtaining timely and accurate assessment of sage-grouse ( Centrocercus spp.) chick survival and recruitment is an important component of species management and conservation. We compared the effectiveness of walking, spotlight, and pointing-dog surveys to detect radio-marked and unmarked chicks within broods of radio-marked hens in Utah. Walking surveys detected 72% of marked chicks, while spotlight and pointing-dog surveys detected 100% and 96%, respectively. We found no difference between spotlight and pointing-dog counts in number of marked and unmarked chicks detected ( P = 0.57). Spotlight counts were slightly more time efficient than pointing-dog surveys. However, spotlight surveys were nocturnal searches and perceived to be more technically arduous than diurnal pointing-dog surveys. Pointing-dog surveys may offer greater utility in terms of area searched per unit effort and an increased ability to detect unmarked hens and broods.     

Mast cells are essential intermediaries in regulatory T-cell tolerance

Contrary to the proinflammatory role of mast cells in allergic disorders, the results obtained in this study establish that mast cells are essential in CD4+CD25+Foxp3+ regulatory T (T(Reg))-cell-dependent peripheral tolerance. Here we confirm that tolerant allografts, which are sustained owing to the immunosuppressive effects of T(Reg) cells, acquire a unique genetic signature dominated by the expression of mast-cell-gene products. We also show that mast cells are crucial for allograft tolerance, through the inability to induce tolerance in mast-cell-deficient mice. High levels of interleukin (IL)-9--a mast cell growth and activation factor--are produced by activated T(Reg) cells, and IL-9 production seems important in mast cell recruitment to, and activation in, tolerant tissue. Our data indicate that IL-9 represents the functional link through which activated T(Reg) cells recruit and activate mast cells to mediate regional immune suppression, because neutralization of IL-9 greatly accelerates allograft rejection in tolerant mice. Finally, immunohistochemical analysis clearly demonstrates the existence of this novel T(Reg)-IL-9-mast cell relationship within tolerant allografts.     

Reciprocal developmental pathways for the generation of pathogenic effector TH17 and regulatory T cells

On activation, T cells undergo distinct developmental pathways, attaining specialized properties and effector functions. T-helper (T(H)) cells are traditionally thought to differentiate into T(H)1 and T(H)2 cell subsets. T(H)1 cells are necessary to clear intracellular pathogens and T(H)2 cells are important for clearing extracellular organisms. Recently, a subset of interleukin (IL)-17-producing T (T(H)17) cells distinct from T(H)1 or T(H)2 cells has been described and shown to have a crucial role in the induction of autoimmune tissue injury. In contrast, CD4+CD25+Foxp3+ regulatory T (T(reg)) cells inhibit autoimmunity and protect against tissue injury. Transforming growth factor-beta (TGF-beta) is a critical differentiation factor for the generation of T(reg) cells. Here we show, using mice with a reporter introduced into the endogenous Foxp3 locus, that IL-6, an acute phase protein induced during inflammation, completely inhibits the generation of Foxp3+ T(reg) cells induced by TGF-beta. We also demonstrate that IL-23 is not the differentiation factor for the generation of T(H)17 cells. Instead, IL-6 and TGF-beta together induce the differentiation of pathogenic T(H)17 cells from naive T cells. Our data demonstrate a dichotomy in the generation of pathogenic (T(H)17) T cells that induce autoimmunity and regulatory (Foxp3+) T cells that inhibit autoimmune tissue injury.     

A comparison of forecasts from least absolute value and least squares regression

A Monte Carlo simulation is used to compare forecasts from least absolute value and least squares estimated regression equations. When outliers are present, the least absolute value forecasts are shown to be superior to least squares forecasts. The results emphasize the importance of exercising caution when using forecasts from least squares estimated regressions. Use of least absolute value regression (or some other robust regression method) instead of, or as an adjunct to, least squares is recommended. The comparison of forecasts from the two methods provides one way of assessing whether the least squares forecasts have been adversely affected by outliers. If outliers are present, the least absolute value regression forecasts can be used.     

An unusual phase transition to a second liquid vortex phase in the superconductor YBa2Cu3O7

A magnetic field penetrates a superconductor through an array of 'vortices', each of which carries one quantum of flux that is surrounded by a circulating supercurrent. In this vortex state, the resistivity is determined by the dynamical properties of the vortex 'matter'. For the high-temperature copper oxide superconductors (see ref.1 for a theoretical review), the vortex phase can be a 'solid', in which the vortices are pinned, but the solid can 'melt' into a 'liquid' phase, in which their mobility gives rise to a finite resistance. (This melting phenomenon is also believed to occur in conventional superconductors, but in an experimentally inaccessible part of the phase diagram.) For the case of YBa2Cu3O7, there are indications of the existence of a critical point, at which the character of the melting changes. But neither the thermodynamic nature of the melting, nor the phase diagram in the vicinity of the critical point, has been well established. Here we report measurements of specific heat and magnetization that determine the phase diagram in this material to 26 T, well above the critical point. Our results reveal the presence of a reversible second-order transition above the critical point. An unusual feature of this transition-namely, that the high-temperature phase is the less symmetric in the sense of the Landau theory-is in accord with theoretical predictions of a transition to a second vortex-liquid phase.     

Advances in simulated modeling of vibration systems based on computational intelligence

Computational intelligence is the computational simulation of the bio-intelligence, which includes artificial neural networks, fuzzy systems and evolutionary computations. This article summarizes the state of the art in the field of simulated modeling of vibration systems using methods of computational intelligence, based on some relevant subjects and the authors' own research work. First, contributions to the applications of computational intelligence to the identification of nonlinear characteristics of packaging are reviewed. Subsequently, applications of the newly developed training algorithms for feedforward neural networks to the identification of restoring forces in multi-degree-of-freedom nonlinear systems are discussed. Finally, the neural-network-based method of model reduction for the dynamic simulation of microelectromechanical systems (MEMS) using generalized Hebbian algorithm (GHA) and robust GHA is outlined. The prospects of the simulated modeling of vibration systems using techniques of computational intelligence are also indicated.     

Ankyrin-B mutation causes type 4 long-QT cardiac arrhythmia and sudden cardiac death

Mutations in ion channels involved in the generation and termination of action potentials constitute a family of molecular defects that underlie fatal cardiac arrhythmias in inherited long-QT syndrome. We report here that a loss-of-function (E1425G) mutation in ankyrin-B (also known as ankyrin 2), a member of a family of versatile membrane adapters, causes dominantly inherited type 4 long-QT cardiac arrhythmia in humans. Mice heterozygous for a null mutation in ankyrin-B are haploinsufficient and display arrhythmia similar to humans. Mutation of ankyrin-B results in disruption in the cellular organization of the sodium pump, the sodium/calcium exchanger, and inositol-1,4,5-trisphosphate receptors (all ankyrin-B-binding proteins), which reduces the targeting of these proteins to the transverse tubules as well as reducing overall protein level. Ankyrin-B mutation also leads to altered Ca2+ signalling in adult cardiomyocytes that results in extrasystoles, and provides a rationale for the arrhythmia. Thus, we identify a new mechanism for cardiac arrhythmia due to abnormal coordination of multiple functionally related ion channels and transporters.