Field dependence of Young’s modulus in a gadolinium single crystal

The field dependence of Young’s modulus along the hexagonal c axis is measured in a gadolinium single crystal over a wide range of temperatures and magnitudes of the magnetic field aligned with the c axis. It is found that the isotherms of the field dependence of the ΔE effect in gadolinium are well approximated by a linear dependence on the square of the magnetization in both strong and weak strong magnetic fields, and also above and below the spin reorientation temperature. It is shown that the experimental trends obtained near the ferromagnetic transition can be interpreted within the approach based on the Landau theory of second-order phase transitions. The parameters of such an approach are determined for gadolinium on the basis of the experimental data. Zh. éksp. Teor. Fiz. 114, 2111–2121 (December 1998)     

Monte Carlo simulation of brain sensing by optical diffuse spectroscopy

We report on development of adapted Monte Carlo based algorithm and code for simulation of light propagation in turbid media with complex geometry aimed for simulation of optical diffuse spectroscopy signal in noninvasive brain sensing. Simulation will allow to determine optimal characteristics of a prototype device for optical diffuse brain sensing. The developed Monte Carlo code can be efficiently parallelized both for SMP and distributed memory systems. We show that the speed-up of the developed algorithm almost linearly depends on the number of nodes/threads in a utilized system.     

Unusual Normal and Superconducting State Properties Observed in Hydrothermal Fe_(1-δ)Se Flakes

The electronic and superconducting properties of Fe_(1-δ)Se single-crystal flakes grown hydrothermally are studied by the transport measurements under zero and high magnetic fields up to 38.5 T. The results contrast sharply with those previously reported for nematically ordered Fe Se by chemical-vapor-transport(CVT) growth. No signature of the electronic nematicity, but an evident metal-to-nonmetal crossover with increasing temperature,is detected in the normal state of the present hydrothermal samples. Interestingly, a higher superconducting critical temperature T_c of 13.2 K is observed compared to a suppressed T_c of 9 K in the presence of the nematicity in the CVT Fe Se. Moreover, the upper critical field in the zero-temperature limit is found to be isotropic with respect to the field direction and to reach a higher value of ~42 T, which breaks the Pauli limit by a factor of 1.8.     

Airline pricing and fare product differentiation: A new theoretical framework

A basic premise in the development of yield management has been that the differentiated fare products offered by airlines are targeted to distinct segments of the total demand for air travel in a market, each of which compete for space on a fixed capacity aircraft. Such representations of differential pricing assume that the airline can segment its demand perfectly and without cost to consumers, and further, ignore the dependence of the demand for a given fare product on the price levels and characteristics of the other available fare products. In this paper, we introduce a new ‘generalised cost’ model of fare product differentiation that incorporates the relationships between available airline fare products as well as the cost incurred by consumers of accepting more restrictions. We extend the model to incorporate the diversion of passengers to lower-priced fare products as a result of their ability to meet the additional restrictions imposed by airlines, and then demonstrate how seat inventory control can be used to induce diverting passengers to ‘sell up’ to higher-priced fare products by applying booking limits. An example of how the model can be used for joint fare product price level optimisation is presented, along with a numerical example that illustrates the extent to which the conventional model of price discrimination over-estimates passenger demand and, in turn, total airline revenues.     

Some properties of a simple moving average when applied to forecasting a time series

Simple (equally weighted) moving averages are frequently used to estimate the current level of a time series, with this value being projected as a forecast for future observations. A key measure of the effectiveness of the method is the sampling error of the estimator, which this paper defines in terms of characteristics of the data. This enables the optimal length of the average for any steady state model to be established and the lead time forecast error derived. A comparison of the performance of a simple moving average (SMA) with an exponentially weighted moving average (EWMA) is made. It is shown that, for a steady state model, the variance of the forecast error is typically less than 3% higher than the appropriate EWMA. This relatively small difference may explain the inconclusive results from the empirical studies about the relative predictive performance of the two methods.     

Causal Algebras on Chain Event Graphs with Informed Missingness for System Failure

Graph-based causal inference has recently been successfully applied to explore system reliability and to predict failures in order to improve systems. One popular causal analysis following Pearl and Spirtes et al. to study causal relationships embedded in a system is to use a Bayesian network (BN). However, certain causal constructions that are particularly pertinent to the study of reliability are difficult to express fully through a BN. Our recent work demonstrated the flexibility of using a Chain Event Graph (CEG) instead to capture causal reasoning embedded within engineers’ reports. We demonstrated that an event tree rather than a BN could provide an alternative framework that could capture most of the causal concepts needed within this domain. In particular, a causal calculus for a specific type of intervention, called a remedial intervention, was devised on this tree-like graph. In this paper, we extend the use of this framework to show that not only remedial maintenance interventions but also interventions associated with routine maintenance can be well-defined using this alternative class of graphical model. We also show that the complexity in making inference about the potential relationships between causes and failures in a missing data situation in the domain of system reliability can be elegantly addressed using this new methodology. Causal modelling using a CEG is illustrated through examples drawn from the study of reliability of an energy distribution network.     

Collider search of light dark matter model with dark sector decay

We explore the possibility that the dark matter relic density is not produced by a thermal mechanism directly, but by the decay of other heavier dark-sector particles which themselves can be produced by the thermal freeze-out mechanism. Using a concrete model with light dark matter from dark sector decay, we study the collider signature of the dark sector particles associated with Higgs production processes. We find that future lepton colliders could be a better place to probe the signature of this kind of light dark matter model than hadron colliders such as LHC. Also, we find that a Higgs factory with center-of-mass energy 250 GeV has a better potential to resolve the signature of this kind of light dark matter model than a Higgs factory with center-of-mass energy 350 GeV.     

WORD READING IS A CRYSTAL MORPHISM

We observe that word reading is a crystal morphism. This leads us to prove that for SLn (?) the map from all galleries to Mikovi?–Vilonen cycles is a surjective morphism of crystals. We also compute the fibers of this map in terms of the Littelmann path model.     

A short proof of Gowers’ lower bound for the regularity lemma

A celebrated result of Gowers states that for every ?>0 there is a graph G such that every ?-regular partition of G (in the sense of Szemerédi’s regularity lemma) has order given by a tower of exponents of height polynomial in 1/?. In this note we give a new proof of this result that uses a construction and proof of correctness that are significantly simpler and shorter.     

Information acquisition and disclosure by firms in the presence of additional available information

In this paper we analyze a model which addresses two stylized facts which have received little attention in disclosure theory. (a) Information that is acquired for internal decision-making can subsequently be disclosed to outside investors who can use it to update their assessment of the firm’s prospects. Thus, the decision to gather information in the first place does not only depend on the decision value of information. (b) Information disclosed by firms is only one element of the information environment upon which investors can draw. This setting creates an interaction between firms’ information gathering and disclosure decisions as well as alternative sources of information. We identify an equilibrium structure which we call a Countersignaling equilibrium in which only average firms acquire information whereas good and bad firms do not. We show that while several equilibria can coexist, a Countersignaling equilibrium is often the economically most efficient one.