Optimal Probabilistic Forecasts for Counts

Optimal probabilistic forecasts of integer-valued random variables are derived. The optimality is achieved by estimating the forecast distribution nonparametrically over a given broad model class and proving asymptotic efficiency in that setting. The ideas are demonstrated within the context of the integer autoregressive class of models, which is a suitable class for any count data that can be interpreted as a queue, stock, birth and death process or branching process. The theoretical proofs of asymptotic optimality are supplemented by simulation results which demonstrate the overall superiority of the nonparametric method relative to a misspecified parametric maximum likelihood estimator, in large but .nite samples. The method is applied to counts of wage claim benefits, stock market iceberg orders and civilian deaths in Iraq, with bootstrap methods used to quantify sampling variation in the estimated forecast distributions.Nonparametric Inference; Asymptotic Efficiency; Count Time Series; INAR Model Class; Bootstrap Distributions; Iceberg Stock Market Orders.

Scoping biological indicators of soil quality Phase II. Defra Final Contract Report SP0534

This report presents results from a field assessment of a limited suite of potential biological indicators of soil quality to investigate their suitability for national-scale soil monitoring

Hair follicle dermal cells repopulate the mouse haematopoietic system

Skin and hair follicle stem cell biology is the focus of increasing interest, not least because the adult hair follicle has well defined dermal and epithelial populations that display distinct developmental properties. Recent evidence suggests that a number of adult cell populations have much broader stem cell capabilities than previously thought. To examine whether this applied to the hair follicle, and with a view to developing the follicle as a stem cell model system we investigated whether adult hair follicles were capable of demonstrating haematopoietic stem cell activity. To investigate haematopoietic activity in hair follicles we first used in vitro haematopoietic colony assays. This demonstrated that rodent hair follicle end bulbs as well as micro-dissected dermal papilla and dermal sheath cells actively produced cells of erythroid and myeloid lineages but that follicle epithelial cells did not. As a more stringent test, we then transplanted cultured dermal papilla or dermal sheath cells from transgenically marked donor mice into lethally irradiated recipient mice and observed multi-lineage haematopoietic reconstitution when assayed at intervals of up to one year. Colony assays from bone marrow of primary recipients revealed that over 70% of clonogenic precursors were derived from donor hair follicle cells. When bone marrow from primary mice was harvested and used to repopulate secondary myeloablated recipients, multi-lineage haematopoietic engraftment was observed. Our data show that dermal but not epidermal compartments of the adult hair follicle have much broader stem cell activities than previously described. Although the treatment for many forms of blood disorder, such as leukemia, often requires transplantation of haematopoietic stem cells (HSC), their availability can be rate limiting. Given its easy accessibility, our identification of the hair follicle as a source of extramedullary haematopoietic stem cell activity makes it an attractive potential source for blood stem cell therapeutics and highlights its value as a model system in adult stem cell biology

Understanding service demand for mental health among Australians aged 16 to 64 years according to their possible need for treatment

Background: To inform decisions about mental health resource allocation, planners require reliable estimates of people who report service demand (i.e. people who use or want mental health services) according to their level of possible need. Methods: Using data on 6915 adults aged 16-64 years in Australia's 2007 National Survey of Mental Health and Wellbeing, we examined past-year service demand among respondents grouped into four levels of possible need: (a) 12-month mental disorder; (b) lifetime but no 12-month mental disorder; (c) any other indicator of possible need (12-month symptoms or reaction to stressful event, or lifetime hospitalisation); (d) no indicator of possible need. Multivariate logistic regression analyses examined correlates of service demand, separately for respondents in each of levels 1-3. Results: Sixteen per cent of Australian adults reported service demand, of whom one-third did not meet criteria for a 12-month mental disorder (equivalent to 5.7% of the adult population). Treatment patterns tended to follow a gradient defined by level of possible need. For example, service users with a 12-month disorder received, on average, 1.6-3.9 times more consultations than their counterparts in other levels of possible need, and had 1.9-2.2 times higher rates of psychologist consultation. Service users with a lifetime but not 12-month disorder or any other indicator of need consumed a similar average number of services to people with mild 12-month mental disorders, but received relatively fewer services involving the mental health sector. Service demand was associated with increased suicidality and psychological distress in all levels of possible need examined, and with poorer clinical and functional status for those with 12-month or lifetime disorders. Conclusions: Many Australians reporting service demand do not meet criteria for a current mental disorder, but may require services to maintain recovery following a past episode or because they are experiencing symptoms and significant psychological distress

Efficiency of the Incomplete Enumeration algorithm for Monte-Carlo simulation of linear and branched polymers

We study the efficiency of the incomplete enumeration algorithm for linear and branched polymers. There is a qualitative difference in the efficiency in these two cases. The average time to generate an independent sample of $n$ sites for large $n$ varies as $n^2$ for linear polymers, but as $exp(c n^{\alpha})$ for branched (undirected and directed) polymers, where $0<\alpha<1$. On the binary tree, our numerical studies for $n$ of order $10^4$ gives $\alpha = 0.333 \pm 0.005$. We argue that $\alpha=1/3$ exactly in this case.Comment: replaced with published versio

Inelastic J/psi Photoproduction

Inelastic photoproduction of $J/\psi$ particles at high energies is one of the processes to determine the gluon distribution in the nucleon. We have calculated the QCD radiative corrections to the color-singlet model of this reaction. They are large at moderate photon energies, but decrease with increasing energies. The cross section and the $J/\psi$ energy spectrum are compared with the available fixed-target photoproduction data and predictions are given for the HERA energy range.Comment: 14 pages, latex, 7 uuencoded figure

Universality Class of Thermally Diluted Ising Systems at Criticality

The universality class of thermally diluted Ising systems, in which the realization of the disposition of magnetic atoms and vacancies is taken from the local distribution of spins in the pure original Ising model at criticality, is investigated by finite size scaling techniques using the Monte Carlo method. We find that the critical temperature, the critical exponents and therefore the universality class of these thermally diluted Ising systems depart markedly from the ones of short range correlated disordered systems. Our results agree fairly well with theoretical predictions previously made by Weinrib and Halperin for systems with long range correlated disorder.Comment: 7 pages, 6 figures, RevTe

Anomalous tag diffusion in the asymmetric exclusion model with particles of arbitrary sizes

Anomalous behavior of correlation functions of tagged particles are studied in generalizations of the one dimensional asymmetric exclusion problem. In these generalized models the range of the hard-core interactions are changed and the restriction of relative ordering of the particles is partially brocken. The models probing these effects are those of biased diffusion of particles having size S=0,1,2,..., or an effective negative "size" S=-1,-2,..., in units of lattice space. Our numerical simulations show that irrespective of the range of the hard-core potential, as long some relative ordering of particles are kept, we find suitable sliding-tag correlation functions whose fluctuations growth with time anomalously slow ($t^{{1/3}}$), when compared with the normal diffusive behavior ($t^{{1/2}}$). These results indicate that the critical behavior of these stochastic models are in the Kardar-Parisi-Zhang (KPZ) universality class. Moreover a previous Bethe-ansatz calculation of the dynamical critical exponent $z$, for size $S \geq 0$ particles is extended to the case $S<0$ and the KPZ result $z=3/2$ is predicted for all values of $S \in {Z}$.Comment: 4 pages, 3 figure

An evaluation of automated GPD threshold selection methods for hydrological extremes across different scales

This study investigated core components of an extreme value methodology for the estimation of high-flow frequencies from agricultural surface water run-off. The Generalized Pareto distribution (GPD) was used to model excesses in time-series data that resulted from the ‘Peaks Over Threshold’ (POT) method. First, the performance of eight different GPD parameter estimators was evaluated through a Monte Carlo experiment. Second, building on the estimator comparison, two existing automated GPD threshold selection methods were evaluated against a proposed approach that automates the threshold stability plots. For this second experiment, methods were applied to discharge measured at a highly-instrumented agricultural research facility in the UK. By averaging fine-resolution 15-minute data to hourly, 6-hourly and daily scales, we were also able to determine the effect of scale on threshold selection, as well as the performance of each method. The results demonstrate the advantages of the proposed threshold selection method over two commonly applied methods, while at the same time providing useful insights into the effect of the choice of the scale of measurement on threshold selection. The results can be generalised to similar water monitoring schemes and are important for improved characterisations of flood events and the design of associated disaster management protocols

Elucidating the performance of hybrid models for predicting extreme water flow events through variography and wavelet analyses

Accurate prediction of extreme flow events is important for mitigating natural disasters such as flooding. We explore and refine two modelling approaches (both separately and in combination) that have been demonstrated to improve the prediction of daily peak flow events. These two approaches are firstly, models that aggregate fine resolution (sub-daily) simulated flow from a process-based model (PBM) to daily, and secondly, hybrid models that combine PBMs with statistical and machine learning methods. We propose the use of variography and wavelet analyses to evaluate these models across temporal scales. These exploratory methods are applied to both measured and modelled data in order to assess the performance of the latter in capturing variation, at different scales, of the former. We compare change points detected by the wavelet analysis (measured and modelled) with the extreme flow events identified in the measured data. We found that combining the two modelling approaches improves prediction at finer scales, but at coarser scales advantages are less pronounced. Although aggregating fine-scale model outputs improved the partition of wavelet variation across scales, the autocorrelation in the signal is less well represented as demonstrated by variography. We demonstrate that exploratory time-series analyses, using variograms and wavelets, provides a useful assessment of existing and newly proposed models, with respect to how they capture changes in flow variance at different scales and also how this correlates with measured flow data – all in the context of extreme flow events. © 2021 Elsevier B.V