Extreme value statistics in Raman fiber lasers

We present the numerical study of the statistical properties of the partially coherent quasi-CW high-Q cavity Raman fiber laser. The statistical properties are different for the radiation generated at the spectrum center or spectral wings. It is found that rare extreme events are generated at the far spectral wings at one pass only. The mechanism of the extreme events generation is a turbulent-like four-wave mixing of numerous longitudinal generation modes. The similar mechanism of extreme waves appearance during the laser generation could be important in other types of fiber lasers. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Extreme value statistics in quasi-CW Raman fiber lasers

It is found that rare extreme events are generated in a Raman fiber laser. The mechanism of the extreme events generation is a turbulent-like four-wave mixing of numerous longitudinal generation modes. © 2012 OSA.

Extreme value statistics in Raman fiber lasers

We present the numerical study of the statistical properties of the partially coherent quasi-CW high-Q cavity Raman fiber laser. The statistical properties are different for the radiation generated at one or many cavity passes. It is found that rare extreme events are generated at the far spectral wings of the spectrum. The mechanism of the extreme events generation is a turbulent-like four-wave mixing of numerous longitudinal generation modes. © 2011 Optical Society of America.

Analytical model for active metamaterials with quantum ingredients

We present an analytical model for describing complex dynamics of a hybrid system consisting of resonantly coupled classical resonator and quantum structures. Classical resonators in our model correspond to plasmonic metamaterials of various geometries, as well as other types of nano- and microstructure, the optical responses of which can be described classically. Quantum resonators are represented by atoms or molecules, or their aggregates (for example, quantum dots, carbon nanotubes, dye molecules, polymer or bio-molecules etc), which can be accurately modelled only with the use of the quantum mechanical approach. Our model is based on the set of equations that combines well established density matrix formalism appropriate for quantum systems, coupled with harmonic-oscillator equations ideal for modelling sub-wavelength plasmonic and optical resonators. As a particular example of application of our model, we show that the saturation nonlinearity of carbon nanotubes increases multifold in the resonantly enhanced near field of a metamaterial. In the framework of our model, we discuss the effect of inhomogeneity of the carbon-nanotube layer (bandgap value distribution) on the nonlinearity enhancement. © 2012 IOP Publishing Ltd.

Optical rogue waves in telecommunication data streams

Large broadening of short optical pulses due to fiber dispersion leads to a strong overlap in information data streams resulting in statistical deviations of the local power from its average. We present a theoretical analysis of rare events of high-intensity fluctuations-optical freak waves-that occur in fiber communication links using bit-overlapping transmission. Although the nature of the large fluctuations examined here is completely linear, as compared to commonly studied freak waves generated by nonlinear effects, the considered deviations inherit from rogue waves the key features of practical interest-random appearance of localized high-intensity pulses. We use the term "rogue wave" in an unusual context mostly to attract attention to both the possibility of purely linear statistical generation of huge amplitude waves and to the fact that in optics the occurrence of such pulses might be observable even with the standard Gaussian or even rarer-than-Gaussian statistics, without imposing the condition of an increased probability of extreme value events. © 2011 American Physical Society.

Statistical distribution, host for encrypted information

The statistical distribution, when determined from an incomplete set of constraints, is shown to be suitable as host for encrypted information. We design an encoding/decoding scheme to embed such a distribution with hidden information. The encryption security is based on the extreme instability of the encoding procedure. The essential feature of the proposed system lies in the fact that the key for retrieving the code is generated by random perturbations of very small value. The security of the proposed encryption relies on the security to interchange the secret key. Hence, it appears as a good complement to the quantum key distribution protocol. © 2005 Elsevier B.V. All rights reserved.

A fuzzy expected value approach under generalized data envelopment analysis

Fuzzy data envelopment analysis (DEA) models emerge as another class of DEA models to account for imprecise inputs and outputs for decision making units (DMUs). Although several approaches for solving fuzzy DEA models have been developed, there are some drawbacks, ranging from the inability to provide satisfactory discrimination power to simplistic numerical examples that handles only triangular fuzzy numbers or symmetrical fuzzy numbers. To address these drawbacks, this paper proposes using the concept of expected value in generalized DEA (GDEA) model. This allows the unification of three models - fuzzy expected CCR, fuzzy expected BCC, and fuzzy expected FDH models - and the ability of these models to handle both symmetrical and asymmetrical fuzzy numbers. We also explored the role of fuzzy GDEA model as a ranking method and compared it to existing super-efficiency evaluation models. Our proposed model is always feasible, while infeasibility problems remain in certain cases under existing super-efficiency models. In order to illustrate the performance of the proposed method, it is first tested using two established numerical examples and compared with the results obtained from alternative methods. A third example on energy dependency among 23 European Union (EU) member countries is further used to validate and describe the efficacy of our approach under asymmetric fuzzy numbers.

An upper bound on the Bayesian error bars for generalized linear regression

In the Bayesian framework, predictions for a regression problem are expressed in terms of a distribution of output values. The mode of this distribution corresponds to the most probable output, while the uncertainty associated with the predictions can conveniently be expressed in terms of error bars. In this paper we consider the evaluation of error bars in the context of the class of generalized linear regression models. We provide insights into the dependence of the error bars on the location of the data points and we derive an upper bound on the true error bars in terms of the contributions from individual data points which are themselves easily evaluated.

Creating and managing value in collaborative networks

This is a theoretical paper that examines the interplay between individual and collective capabilities and competencies and value transactions in collaborative environments. The theory behind value creation is examined and two types of value are identified, internal value (Shareholder value) and external value (Value proposition). The literature on collaborative enterprises/network is also examined with particular emphasis on supply chains, extended/virtual enterprises and clusters as representatives of different forms and maturities of collaboration. The interplay of value transactions and competencies and capabilities are examined and discussed in detail. Finally, a model is presented which consists of value transactions and a table which compares the characteristics of different types of collaborative enterprises/networks. It is proposed that this model presents a platform for further research to develop an in-depth understanding into how value may be created and managed in collaborative enterprises/networks.

Gas distribution in shallow large diameter packed beds

It is important to maintain a uniform distribution of gas and liquid in large diameter packed columns to maintain mass transfer efficiency on scaling up. This work presents measurements and methods of evaluating maldistributed gas flow in packed columns. Little or no previous work has been done in this field. A gas maldistribution number, F, was defined, based on point to point velocity variations in the gas emerging from the top of packed beds. f has a minimum value for a uniformly distributed flow and much larger values for maldistributed flows. A method of testing the quality of vapour distributors is proposed, based on "the variation of f with packed height. A good gas distributor requires a short packed depth to give a good gas distribution. Measurements of gas maldistribution have shown that the principle of dynamic similarity is satisfied if two geometrically similar beds are operated at the same Reynold's number. The validity of f as a good measure of gas maldistribution, and the principle of dynamic similarity are tested statistically by Multi-Factor Analysis of the variance, and visually by the response "surfaces technique. Pressure distribution has been measured in a model of a large diameter packed bed, and shown to be associated with the velocity of the gas in a tangential feed pipe. Two simplified theoretical models are proposed to describe the flow of gases through packed beds and to support the principle of dynamic similarity. These models explain why the packed bed itself causes the flow of gas to become more uniformly distributed. A 1.2m. diameter scaled-down model was constructed geometrically similar to a 7.3m. diameter vacuum crude distillation column. The previously known internal cylinder gas distributor was tested. Three new distributors suitable for use in a large diameter column were developed and tested, these are: Internal Cylinder with Slots and Cross Baffles, Internal Cylinder with Guides in the Annulus, Internal Cylinder with Internal Cross Baffles - It has been shown that this is an excellent distributor.

An assessment of the performance of high density polyethylene copolymers for natural gas distribution pipes

The total thermoplastics pipe market in west Europe is estimated at 900,000 metric tonnes for 1977 and is projected to grow to some 1.3 million tonnes of predominantly PVC and polyolefins pipe by 1985. By that time, polyethylene for gas distribution pipe and fittings will represent some 30% of the total polyethylene pipe market. The performance characteristics of a high density polyethylene are significantly influenced by both molecular weight and type of comonomer; the major influences being in the long-term hoop stress resistance and the environmental stress cracking resistance. Minor amounts of hexene-1 are more effective than comonomers lower in the homologous series, although there is some sacrifice of density related properties. A synergistic improvement is obtained by combining molecular weight increase with copolymerisation. The Long-term design strength of polyethylene copolymers can be determined from hoop stress measurement at elevated temperatures and by means of a separation factor of approximate value 22, extrapolation can be made to room temperature performance for a water environment. A polyethylene of black composition has a sufficiently improved performance over yellow pigmented pipe to cast doubts on the validity of internationally specifying yellow coded pipe for gas distribution service. The chemical environment (condensate formation) that can exist in natural gas distribution networks has a deleterious effect on the pipe performance the reduction amounting to at least two decades in log time. Desorption of such condensate is very slow and the influence of the more aggressive aromatic components is to lead to premature stress cracking. For natural gas distribution purposes, the design stress rating should be 39 Kg/cm2 for polyethylenes in the molecular weight range of 150 - 200,000 and 55 Kg/cm2 for higher molecular weight materials.

Factors determining the size frequency distribution of β-amyloid (Aβ) deposits in Alzheimer's disease

The size frequency distributions of discrete β-amyloid (Aβ) deposits were studied in single sections of the temporal lobe from patients with Alzheimer's disease. The size distributions were unimodal and positively skewed. In 18/25 (72%) tissues examined, a log normal distribution was a good fit to the data. This suggests that the abundances of deposit sizes are distributed randomly on a log scale about a mean value. Three hypotheses were proposed to account for the data: (1) sectioning in a single plane, (2) growth and disappearance of Aβ deposits, and (3) the origin of Aβ deposits from clusters of neuronal cell bodies. Size distributions obtained by serial reconstruction through the tissue were similar to those observed in single sections, which would not support the first hypothesis. The log normal distribution of Aβ deposit size suggests a model in which the rate of growth of a deposit is proportional to its volume. However, mean deposit size and the ratio of large to small deposits were not positively correlated with patient age or disease duration. The frequency distribution of Aβ deposits which were closely associated with 0, 1, 2, 3, or more neuronal cell bodies deviated significantly from a log normal distribution, which would not support the neuronal origin hypothesis. On the basis of the present data, growth and resolution of Aβ deposits would appear to be the most likely explanation for the log normal size distributions.

A quantitative study of abnormally enlarged neurons in cognitively normal brain and neurodegenerative disease

Abnormally enlarged neurons (AEN) occur in many neurodegenerative diseases. To define AEN more objectively, the frequency distribution of the ratio of greatest cell diameter(CD) to greatest nuclear diameter (ND) was studied in populations of cortical neurons in tissue sections of seven cognitively normal brains. The frequency distribution of CD/ND deviated from a normal distribution in 15 out of 18 populations of neurons studied and hence, the 95th percentile (95P) was used to define a limit of the CD/ND ratio excluding the5% most extreme observations. The 95P of the CD/ ND ratio varied from 2.0 to 3.0 in different cases and regions and a value of 95P = 3.0 was chosen to define the limit for normalneurons under non-pathological conditions. Based on the 95P = 3.0 criterion, the proportion of AEN with a CD/ND ≥ 3 varied from 2.6% in Alzheimer's disease (AD) to 20.3% in Pick's disease (PiD). The data suggest: (1) that a CL/ND ≥ 3.0 may be a useful morphological criterion for defining AEN, and (2) AEN were most numerous in PiD and corticobasal degeneration (CBD) and least abundant in AD and in dementia with Lewy bodies (DLB). © 2013 Dustri-Verlag Dr. K. Feistle.

Building up resilience of construction sector SMEs and their supply chains to extreme weather events

Wider scientific community now accept that the threat of climate change as real and thus acknowledge the importance of implementing adaptation measures in a global context. In the UK , the physical effects of climate change are likely to be directly felt in the form of extreme weather events, which are predicted to escalate in number and severity in future under the changing climatic conditions. Construction industry; which consists of supply chains running across various other industries, economies and regions, will also be affected due to these events. Thus, it is important that the construction organisations are well prepared to withstand the effects of extreme weather events not only directly affecting their organisations but also affecting their supply chains which in turn might affect the organisation concerned. Given the fact that more than 99% of construction sector businesses are SMEs, the area can benefit significantly from policy making to improve SME resilience and coping capacity. This paper presents the literature review and synthesis of a doctoral research study undertaken to address the issue of extreme weather resilience of construction sector SMEs and their supply chains. The main contribution of the paper to both academia and practitioners is a synthesis model that conceptualises the factors that enhances resilience of SMEs and their supply chains against extreme weather events. This synthesis model forms the basis of a decision making framework that will enable SMEs to both reduce their vulnerability and enhance their coping capacity against extreme weather. The value of this paper is further extended by the overall research design that is set forth as the way forward.

Improving “last mile” delivery performance to retailers in hub and spoke distribution systems

Purpose – The purpose of this paper is to investigate the “last mile” delivery link between a hub and spoke distribution system and its customers. The proportion of retail, as opposed to non-retail (trade) customers using this type of distribution system has been growing in the UK. The paper shows the applicability of simulation to demonstrate changes in overall delivery policy to these customers. Design/methodology/approach – A case-based research method was chosen with the aim to provide an exemplar of practice and test the proposition that simulation can be used as a tool to investigate changes in delivery policy. Findings – The results indicate the potential improvement in delivery performance, specifically in meeting timed delivery performance, that could be made by having separate retail and non-retail delivery runs from the spoke terminal to the customer. Research limitations/implications – The simulation study does not attempt to generate a vehicle routing schedule but demonstrates the effects of a change on delivery performance when comparing delivery policies. Practical implications – Scheduling and spreadsheet software are widely used and provide useful assistance in the design of delivery runs and the allocation of staff to those delivery runs. This paper demonstrates to managers the usefulness of investigating the efficacy of current design rules and presents simulation as a suitable tool for this analysis. Originality/value – A simulation model is used in a novel application to test a change in delivery policy in response to a changing delivery profile of increased retail deliveries.