State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth

It has been well documented that the consensus forecast from surveys of professional forecasters shows a bias that varies over time. In this paper, we examine whether this bias may be due to forecasters having an asymmetric loss function. In contrast to previous research, we account for the time variation in the bias by making the loss function depend on the state of the economy. The asymmetry parameter in the loss function is specified to depend on set state variables which may cause forecaster to intentionally bias their forecasts. We consider both the Lin–Ex and asymmetric power loss functions. For the commonly used Lin–Ex and Lin–Lin loss functions, we show the model can be easily estimated by least squares. We apply our methodology to the consensus forecast of real U.S. GDP growth from the Survey of Professional Forecasters. We find that forecast uncertainty has an asymmetric effect on the asymmetry parameter in the loss function dependent upon whether the economy is in expansion or contraction. When the economy is in expansion, forecaster uncertainty is related to an overprediction in the median forecast of real GDP growth. In contrast, when the economy is in contraction, forecaster uncertainty is related to an underprediction in the median forecast of real GDP growth. Our results are robust to the particular loss function that is employed in the analysis.

State and input simultaneous estimation for a class of nonlinear systems

This paper addresses the problem of estimating simultaneously the state and input of a class of nonlinear systems. Here, the systems nonlinear part comprises a Lipschitz nonlinear function with respect to the state and input, and a state-dependent unknown function including additive disturbance as well as uncertain/nonlinear/time-varying terms. Upon satisfying some conditions, the observer design problem can be solved via a Riccati inequality or a LMI-based technique with asymptotic estimation guaranteed. A numerical example is included for illustration.

Recognising and monitoring high-level behaviours in complex spatial environments

The recognition of activities from sensory data is important in advanced surveillance systems to enable prediction of high-level goals and intentions of the target under surveillance. The problem is complicated by sensory noise and complex activity spanning large spatial and temporal extents. This paper presents a system for recognising high-level human activities from multi-camera video data in complex spatial environments. The Abstract Hidden Markov mEmory Model (AHMEM) is used to deal with noise and scalability The AHMEM is an extension of the Abstract Hidden Markov Model (AHMM) that allows us to represent a richer class of both state-dependent and context-free behaviours. The model also supports integration with low-level sensory models and efficient probabilistic inference. We present experimental results showing the ability of the system to perform real-time monitoring and recognition of complex behaviours of people from observing their trajectories within a real, complex indoor environment.

State and input simultaneous estimation for a class of time-delay systems with uncertainties

This brief addresses the problem of estimation of both the states and the unknown inputs of a class of systems that are subject to a time-varying delay in their state variables, to an unknown input, and also to an additive uncertain, nonlinear disturbance. Conditions are derived for the solvability of the design matrices of a reduced-order observer for state and input estimation, and for the stability of its dynamics. To improve computational efficiency, a delay-dependent asymptotic stability condition is then developed using the linear matrix inequality formulation. A design procedure is proposed and illustrated by a numerical example.

Structural characterization of conducting polypyrrole using 13C cross-polarization/magic-angle spinning solid-state nuclear magnetic resonance spectroscopy

¹³C nuclear magnetic resonance (n.m.r.) has been used to study polypyrrole and N-substituted polypyrrole in the solid state. The extent of oxidation appears to be counterion-dependent; in particular, the quinoid structure appears favoured in the films prepared with dodecyl sulfate. Resonances associated with the quinoid unit are lost upon reduction of the polypyrrole film, which supports the idea that the quinoid structure is associated with the oxidized form of polypyrrole. N-substituted polypyrroles have a more distinct resonance at 110 ppm, which is linked to lower degrees of oxidation or charge delocalization in these systems. The decrease in conductivity of polypyrrole upon thermal ageing in air is associated with both the loss of counterion (‘thermal dedoping’) and the decomposition of the quinoid structure in the polymer backbone. There is no indication of carbonyl formation in the solid-state n.m.r. spectra obtained in the present study.

Angiotensin I-converting enzyme transition state stabilization by HIS1089 : evidence for a catalytic mechanism distinct from other gluzincin metalloproteinases

Angiotensin (Ang) I-converting enzyme (ACE) is a member of the gluzincin family of zinc metalloproteinases that contains two homologous catalytic domains. Both the N- and C-terminal domains are peptidyl-dipeptidases that catalyze Ang II formation and bradykinin degradation. Multiple sequence alignment was used to predict His¹⁰⁸⁹ as the catalytic residue in human ACE C-domain that, by analogy with the prototypical gluzincin, thermolysin, stabilizes the scissile carbonyl bond through a hydrogen bond during transition state binding. Site-directed mutagenesis was used to change His¹⁰⁸⁹ to Ala or Leu. At pH 7.5, with Ang I as substrate, k_cat/K_m values for these Ala and Leu mutants were 430 and 4,000-fold lower, respectively, compared with wild-type enzyme and were mainly due to a decrease in catalytic rate (k_cat) with minor effects on ground state substrate binding (K_m). A 120,000-fold decrease in the binding of lisinopril, a proposed transition state mimic, was also observed with the His¹⁰⁸⁹ --> Ala mutation. ACE C-domain-dependent cleavage of AcAFAA showed a pH optimum of 8.2. H1089A has a pH optimum of 5.5 with no pH dependence of its catalytic activity in the range 6.5-10.5, indicating that the His¹⁰⁸⁹ side chain allows ACE to function as an alkaline peptidyl-dipeptidase. Since transition state mutants of other gluzincins show pH optima shifts toward the alkaline, this effect of His¹⁰⁸⁹ on the ACE pH optimum and its ability to influence transition state binding of the sulfhydryl inhibitor captopril indicate that the catalytic mechanism of ACE is distinct from that of other gluzincins.

Credit cycle dependent spread determinants in emerging sovereign debt markets

We address credit cycle dependent sovereign credit risk determinants. In our model, the spread determinants' magnitude is conditional on an unobservable endogenous sovereign credit cycle as represented by the underlying state of a Markov regime switching process. Our explanatory variables are motivated in the tradition of structural credit risk models and include changes in asset prices, interest rates, implied market volatility, gold price changes and foreign exchange rates. We examine daily frequency variations of U.S. dollar denominated Eurobond credit spreads of four major Latin American sovereign bond issuers (Brazil, Colombia, Mexico and Venezuela) with liquid bond markets during March 2000 to June 2011. We find that spread determinants are statistically significant and consistent with theory, while their magnitude remarkably varies with the state of the credit cycle. Crisis states are characterized by high spread change uncertainty and high sensitivities with respect to the spread change determinants. We further document that not only changes of local currencies, but also changes of the Euro with respect to the U.S. dollar are significant spread drivers and argue that this is consistent with the sovereigns' ability to pay.

Analyses and comparison of counter-movement jump performance and self-rated recovery in state under-18s Australian Rules Football players during a national championship

Recovery of team sport athletes during multiple competitive games is an important area for strength and conditioning coaches to monitor as it facilitates for athletes to be ready to perform (11,13). Utilising athletic performance data in conjunction with self-rated reporting measures can help determine if in fact a player or team has recovered sufficiently or shown a trend towards recovery prior to a competitive match (11). Positive improvement in recovery variables can provide confidence in the effectiveness of recovery methods used and assist in determining the training schedule in order to positively manipulate the fitness-fatigue relationship (3).

Various methods of analysing the recovery of athletes have been reported in the literature and are available to the strength and conditioning coach. These include subjective, self-rated scales and perceived level of recovery questionnaires (11,12,13). Athletic performance measures during exercises such as the counter movement jump (CMJ) have also been analysed, predominantly utilising force plates to obtain kinetic data. (5,13,14). However, such equipment can be difficult to transport, requires continual calibration and is costly to purchase. A linear transducer can provide important information on CMJ variables in the assessment of athletic movements and due to its size and portability could serve as a valuable tool to assist strength and conditioning coaches, (8,10), and potentially enable the monitoring of recovery.

Previous studies have investigated the fatigue effects of competitive games in various sports (11,13,14) including Australian Rules Football (AFL) at the senior elite league level (5, 6). To the authors’ knowledge, however, there is yet to be a study investigating the recovery response in AFL players, specifically in players 18 years and under competing in the National Under 18s Championships. Australian Rules football is an extremely physically demanding and fatiguing sport where players participate in games time exceeding 120 minutes duration, covering large distances (~12-18km, position dependent) with many high intensity efforts performed at random times throughout the game (2,6,16). Hence, it would seem pertinent to analyse the fatigue effects of competitive matches in an Australian Rules Under-18’s National Championship and the subsequent recovery from these games.

The aim of this study was to analyse and compare two self-rated subjective measures of recovery; they being muscle soreness (MS) of the lower body, overall perceived total recovery (TR), and the performance measure of peak velocity (PV) obtained from a CMJ analysed with a linear transducer. Data collection occurred between rounds four and five of the Australian Football League Under-18’s National Championship, representing a four-day recovery analysis period between matches.

Reduced order functional observers with application to partial state estimation of linear systems with input delay

Reduced order multi-functional observer design for multi-input multi-utput (MIMO) linear time-invariant (LTI) systems with constant delayed inputs is studied. This research is useful in the input estimation of LTI systems with actuator delay, as well as system monitoring and fault detection of these systems. Two approaches for designing an asymptotically stable functional observer for the system are proposed: delay-dependent and delay-free. The delay-dependent observer is infinite-dimensional, while the delay-free structure is finite-dimensional. Moreover, since the delay-free observer does not require any information on the time delay, it is more practical in real applications. However, the delay-dependent observer contains less restrictive assumptions and covers more variety of systems. The proposed observer design schemes are novel, simple to implement, and have improved numerical features compared to some of the other available approaches to design (unknown-input) functional observers. In addition, the proposed observers usually possess lower order than ordinary Luenberger observers, and the design schemes do not need the observability or detectability requirements of the system. The necessary and sufficient conditions of the existence of an asymptoticobserver in each scenario are explored. The extensions of the proposed observers to systems with multiple delayed-inputs are also discussed. Several numerical examples and simulation results are employed to support our theories.

New H∞ control design for polytopic systems with mixed time-varying delays in state and input

This paper concerns with the problem of state-feedback H∞ control design for a class of linear systems with polytopic uncertainties and mixed time-varying delays in state and input. Our approach can be described as follows. We first construct a state-feedback controller based on the idea of parameter-dependent controller design. By constructing a new parameter-dependent Lyapunov-Krasovskii functional (LKF), we then derive new delay-dependent conditions in terms of linear matrix inequalities ensuring the exponential stability of the corresponding closed-loop system with a H∞ disturbance attenuation level. The effectiveness and applicability of the obtained results are demonstrated by practical examples.

Data clustering using side information dependent Chinese restaurant processes

Side information, or auxiliary information associated with documents or image content, provides hints for clustering. We propose a new model, side information dependent Chinese restaurant process, which exploits side information in a Bayesian nonparametric model to improve data clustering. We introduce side information into the framework of distance dependent Chinese restaurant process using a robust decay function to handle noisy side information. The threshold parameter of the decay function is updated automatically in the Gibbs sampling process. A fast inference algorithm is proposed. We evaluate our approach on four datasets: Cora, 20 Newsgroups, NUS-WIDE and one medical dataset. Types of side information explored in this paper include citations, authors, tags, keywords and auxiliary clinical information. The comparison with the state-of-the-art approaches based on standard performance measures (NMI, F1) clearly shows the superiority of our approach.

Brief reminiscence activities improve state well-being and self-concept in young adults: a randomised controlled experiment

Reminiscence-based psychotherapies have been demonstrated to have robust effects on a range of therapeutic outcomes. However, little research has been conducted on the immediate effects of guided activities they are composed of, or how these might differ dependent on the type of reminiscence. The current study utilised a controlled experimental design, whereby 321 young adults (mean age = 25.5 years, SD = 3.0) were randomised to one of four conditions of online reminiscence activity: problem-solving (successful coping experiences), identity (self-defining events contributing to a meaningful and continuous personal identity), bitterness revival (negative or adverse events), or a control condition (any memory from their past). Participants recalled autobiographical memories congruent with the condition, and answered questions to facilitate reflection on the memories. The results indicated that problem-solving and identity reminiscence activities caused significant improvements in self-esteem, meaning in life, self-efficacy and affect, whereas no effects were found in the bitterness revival and control conditions. Problem-solving reminiscence also caused a small effect in increasing perceptions of a life narrative/s. Differences between the conditions did not appear to be explained by the positive-valence of memories. These results provide evidence for the specific effects of adaptive types of problem-solving and identity reminiscence in young adults.

Partial state estimation of LTI systems with multiple constant time-delays

Functional observer design for Multi-Input Multi-Output (MIMO) Linear Time-Invariant (LTI) systems with multiple mixed time delays in the states of the system is addressed. Two structures for the design of a minimum-order observer are considered: 1 - delay-dependent, and 2 - internal-delay independent. The parameters of the delay-dependent observer are designed using the Lyapunov Krasovskii approach. The delay-dependent exponential stability of the observer for a specified convergence rate and delay values is guaranteed upon the feasibility of a set of Linear Matrix Inequalities (LMIs) together with a rank condition. Using the descriptor transformation, a modified Jensen's inequality, and improved Park's inequality, the results can be less conservative than the available functional observer design methods that address LTI systems with single state delay. Furthermore, the necessary and sufficient conditions of the asymptotic stability of the internal-delay independent observer are obtained, which are shown to be independent of delay. Two illustrative numerical examples and simulation studies confirm the validity and highlight the performance of the proposed theoretical achievements.

Stability analysis of two-dimensional Markovian jump state-delayed systems in the Roesser model with uncertain transition probabilities

This paper is concerned with the problem of stochastic stability analysis of discrete-time two-dimensional (2-D) Markovian jump systems (MJSs) described by the Roesser model with interval time-varying delays. The transition probabilities of the jumping process/Markov chain are assumed to be uncertain, that is, they are not exactly known but can be estimated. A Lyapunov-like scheme is first extended to 2-D MJSs with delays. Based on some novel 2-D summation inequalities proposed in this paper, delay-dependent stochastic stability conditions are derived in terms of linear matrix inequalities (LMIs) which can be computationally solved by various convex optimization algorithms. Finally, two numerical examples are given to illustrate the effectiveness of the obtained results.

Minimum-order filter design for partial state estimation of linear systems with multiple time-varying state delays and unknown input delays

Designing delay-dependent functional observers for LTI systems with multiple known time-varying state delays and unknown time-varying input delays is studied. The input delays are arbitrary, but the state delays should be upper-bounded. In addition, two scenarios of slow-varying and fast-varying state delays are investigated. The results of the paper can also be considered as one of the first contributions considering unknown-input functional observer design for linear systems with multiple time-varying state delays. Based on the Lyapunov Krasovskii approach, delay-dependent sufficient conditions of the exponential stability of the observer in each scenario are established in terms of linear matrix inequalities. Because of using effective techniques, such as the descriptor transformation and an advanced weighted integral inequality, the proposed stability criteria can result in larger stability regions compared with the other papers that study functional observers for time-varying delay systems. Furthermore, to help with the design procedure, a genetic algorithm-based scheme is proposed to adjust a weighting matrix in the established linear matrix inequalities. Two numerical examples illustrate the design procedure and demonstrate the efficacy of the proposed observer in each scenario.