Performance analysis of interferometric noise due to unequally powered interferers in optical networks

Interferometric crosstalk has been identified as the cause of performance limits in future transparent all-optical networks. A large number of studies have been conducted on this phenomenon using a vast array of evaluation techniques. However, most major studies have considered that although the interfering terms may differ in number, the power contribution that they all make will be identical for all interfering terms. Although this situation is easy to analyze, it does not necessarily represent the situation that is likely to occur in a real network, which will be constructed of nodes with different degrees of connectivity, quite possibly from different vendors, and therefore with differing crosstalk characteristics. This paper describes a study on the impact of unequally powered interfering terms using a rigorous analysis technique. To validate the use of the chosen technique, the paper begins by bench-marking a number of common evaluation techniques against empirically derived, experimentally verified noise performance formulas

Operational Semantics of Process Monitors

CSPe is a specification language for runtime monitors that can directly express concurrency in a bottom-up manner that composes the system from simpler, interacting components. It includes constructs to explicitly flag failures to the monitor, which unlike deadlocks and livelocks in conventional process algebras, propagate globally and aborts the whole system's execution. Although CSPe has a trace semantics along with an implementation demonstrating acceptable performance, it lacks an operational semantics. An operational semantics is not only more accessible than trace semantics but also indispensable for ensuring the correctness of the implementation. Furthermore, a process algebra like CSPe admits multiple denotational semantics appropriate for different purposes, and an operational semantics is the basis for justifying such semantics' integrity and relevance. In this paper, we develop an SOS-style operational semantics for CSPe, which properly accounts for explicit failures and will serve as a basis for further study of its properties, its optimization, and its use in runtime verification

Reasoning about embedded dependencies using inclusion dependencies

The implication problem for the class of embedded dependencies is undecidable. However, this does not imply lackness of a proof procedure as exemplified by the chase algorithm. In this paper we present a complete axiomatization of embedded dependencies that is based on the chase and uses inclusion dependencies and implicit existential quantification in the intermediate steps of deductions

Informing investment to reduce inequalities: a modelling approach

Background: Reducing health inequalities is an important policy objective but there is limited quantitative information about the impact of specific interventions. Objectives: To provide estimates of the impact of a range of interventions on health and health inequalities. Materials and methods: Literature reviews were conducted to identify the best evidence linking interventions to mortality and hospital admissions. We examined interventions across the determinants of health: a ‘living wage’; changes to benefits, taxation and employment; active travel; tobacco taxation; smoking cessation, alcohol brief interventions, and weight management services. A model was developed to estimate mortality and years of life lost (YLL) in intervention and comparison populations over a 20-year time period following interventions delivered only in the first year. We estimated changes in inequalities using the relative index of inequality (RII). Results: Introduction of a ‘living wage’ generated the largest beneficial health impact, with modest reductions in health inequalities. Benefits increases had modest positive impacts on health and health inequalities. Income tax increases had negative impacts on population health but reduced inequalities, while council tax increases worsened both health and health inequalities. Active travel increases had minimally positive effects on population health but widened health inequalities. Increases in employment reduced inequalities only when targeted to the most deprived groups. Tobacco taxation had modestly positive impacts on health but little impact on health inequalities. Alcohol brief interventions had modestly positive impacts on health and health inequalities only when strongly socially targeted, while smoking cessation and weight-reduction programmes had minimal impacts on health and health inequalities even when socially targeted. Conclusions: Interventions have markedly different effects on mortality, hospitalisations and inequalities. The most effective (and likely cost-effective) interventions for reducing inequalities were regulatory and tax options. Interventions focused on individual agency were much less likely to impact on inequalities, even when targeted at the most deprived communities

Adaptive multiphoton endomicroscopy through a dynamically deformed multicore optical fiber using proximal detection

This paper demonstrates multiphoton excited fluorescence imaging through a polarisation maintaining multicore fiber (PM-MCF) while the fiber is dynamically deformed using all-proximal detection. Single-shot proximal measurement of the relative optical path lengths of all the cores of the PM-MCF in double pass is achieved using a Mach-Zehnder interferometer read out by a scientific CMOS camera operating at 416 Hz. A non-linear least squares fitting procedure is then employed to determine the deformation-induced lateral shift of the excitation spot at the distal tip of the PM-MCF. An experimental validation of this approach is presented that compares the proximally measured deformation-induced lateral shift in focal spot position to an independent distally measured ground truth. The proximal measurement of deformation-induced shift in focal spot position is applied to correct for deformation-induced shifts in focal spot position during raster-scanning multiphoton excited fluorescence imaging

An Overview of the Use of Neural Networks for Data Mining Tasks

In the recent years the area of data mining has experienced a considerable demand for technologies that extract knowledge from large and complex data sources. There is a substantial commercial interest as well as research investigations in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from datasets. Artificial Neural Networks (NN) are popular biologically inspired intelligent methodologies, whose classification, prediction and pattern recognition capabilities have been utilised successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks

Most vital segment barriers

We study continuous analogues of "vitality" for discrete network flows/paths, and consider problems related to placing segment barriers that have highest impact on a flow/path in a polygonal domain. This extends the graph-theoretic notion of "most vital arcs" for flows/paths to geometric environments. We give hardness results and efficient algorithms for various versions of the problem, (almost) completely separating hard and polynomially-solvable cases

Can people guess what happened to others from their reactions?

Are we able to infer what happened to a person from a brief sample of his/her behaviour? It has been proposed that mentalising skills can be used to retrodict as well as predict behaviour, that is, to determine what mental states of a target have already occurred. The current study aimed to develop a paradigm to explore these processes, which takes into account the intricacies of real-life situations in which reasoning about mental states, as embodied in behaviour, may be utilised. A novel task was devised which involved observing subtle and naturalistic reactions of others in order to determine the event that had previously taken place. Thirty-five participants viewed videos of real individuals reacting to the researcher behaving in one of four possible ways, and were asked to judge which of the four ‘scenarios’ they thought the individual was responding to. Their eye movements were recorded to establish the visual strategies used. Participants were able to deduce successfully from a small sample of behaviour which scenario had previously occurred. Surprisingly, looking at the eye region was associated with poorer identification of the scenarios, and eye movement strategy varied depending on the event experienced by the person in the video. This suggests people flexibly deploy their attention using a retrodictive mindreading process to infer events

Super-resolving phase measurements with a multi-photon entangled state

Using a linear optical elements and post-selection, we construct an entangled polarization state of three photons in the same spatial mode. This state is analogous to a ``photon-number path entangled state'' and can be used for super-resolving interferometry. Measuring a birefringent phase shift, we demonstrate two- and three-fold improvements in phase resolution.Comment: 4 pages, 3 figure