A simple variance formula for population size estimators by conditioning

This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling n units from a population of size N. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.

A maternal influence on the conditioning to plant cues of Aphidius colemani Viereck, parasitizing the aphid Myzus persicae Sulzer

The offspring of parasitoids, Aphidius colemani Viereck, reared on Brussels sprouts and emerging from Myzus persicae Sulzer on a fully defined artificial diet, show no preferences in a four-way olfactometer, either for the odour of the diet, the odour of Brussels sprouts, or the odour of two other crucifers (cabbage and Chinese cabbage). A similar lack of odour preferences is shown when the host aphids are exposed for parasitization (for 48 h) on cabbage, Chinese cabbage or wheat. However, if parasitization occurs on Brussels sprouts, a weak but statistically highly significant response to Brussels sprout odour is observed. Although as many as 30-35% of the parasitoids show no response to any odour, another 35% respond positively to the odour of Brussels sprout compared with responses to the odours of cabbage, Chinese cabbage or wheat of only approximately 10%. An analagous result is obtained when the parent parasitoids are reared on cabbage. In this case, significant positive responses of their offspring to cabbage odour occur only if the 48-h parasitization has occurred also on cabbage. However, with parasitoids from Brussels sprouts parasitizing the aphids for 48 h also on Brussels sprouts, the offspring subsequently emerging from pupae excised from the mummies show no preference for Brussels sprout odour. Thus, although the Brussels sprout cue had been experienced early in the development of the parasitoids, they only become conditioned to it when emerging from the mummy. Both male and female parasitoids respond very similarly in all experiments. It is proposed that the chemical cue (probably glucosinolates in these experiments) is most likely in the silk surrounding the parasitoid pupa, and that the mother may leave the chemical in or around the egg at oviposition, inducing chemical defences in her offspring to the secondary plant compounds that the offspring are likely to encounter.

Effects of prolonged conditioning on dormancy and germination of Striga hermonthica

The impact of environment on the germination biology of Striga hermonthica was studied in the laboratory by conditioning seeds at various water potentials and urea concentrations at 17.5 to 37.5°C for up to 133 days. The experimental results presented in this research are related to the effects of temperature, water potential and urea nitrogen concentration during conditioning on subsequent germination percentage of S. hermonthica. Maximum germination in S. hermonthica seeds was observed at conditioning temperatures of 20 to 25°C within the range investigated of 17.5 to 37.5°C. Water stress and also urea during conditioning suppressed maximum germination. However, the conditioning temperature ranges at which maximum germination percentages occur vary with water stress and also urea concentration. In the presence of a high concentration of urea (3.16 mM), temperatures required for maximum germination narrowed to between 17.5 to 20°C. The optimum period of conditioning decreased with increase in water stress and also urea concentration similar to previous reports. The implications of these findings on Striga hermonthica field infestations have been investigated and being reported in another paper. Germination was greatly suppressed by conditioning environments including 3.16 mM urea and at 37.5°C. At the high concentration of 3.16 mM, temperatures required for maximum germination narrowed to between 17.5 and 20°C. Optimum conditioning period decreased with water stress and with increase in urea concentration.

Modelling effects of prolonged conditioning on dormancy and germination of Striga hermonthica

The impact of environment on the germination biology of the parasite was studied in the laboratory with seeds conditioned at various water potentials, urea concentrations and at 17.5 to 37.5°C for up to 133 days. Maximum germination was observed at 20 to 25°C. Water stress and urea suppressed maximum germination. The final percentage germination response to period of conditioning showed a non-linear relationship and suggests the release of seeds from dormancy during the initial period and later on dormancy induction. Germination percentage increased with increase in conditioning period to a threshold and remained stable for variable periods followed by a decline with further extension of conditioning time. The decline in germination finally terminated in zero germination in most treatments before the end of experimentation. The investigated factors of temperature, water potential and urea showed clear effects on the expression of dormancy pattern of the parasite. The effects of water potential and urea were viewed as modifying a primary response of seeds to temperature during conditioning. The changes in germinability potential during conditioning were consistent with the hypothesis that dormancy periods are normally distributed within seed populations and that loss of primary dormancy precedes induction of secondary dormancy. Hence an additive mathematical model of loss of primary dormancy and induction of secondary as affected by environment was developed as: G = {[Φ-1 (Kp+ (po+pnN+pwW) (T-Tb) t)]-[Φ-1 (Ks+ ((swW+sa)+sorT)t)]}[Φ-1(aT2+bT+c+cwW)].

A simple variance formula for population size estimators by conditioning

This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling n units from a population of size N. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

Synthesis of a catechol-based poly(ether ether ketone) ("o-PEEK") by classical step-growth polymerization and by entropically driven ring-opening polymerization of macrocyclic oligomers

An amorphous, catechol-based analogue of PEEK ("o-PEEK") has been prepared by a classical step-growth polymerization reaction between catechol and 4,4'-difluorobenzophenone and shown to be readily soluble in a range of organic solvents. Copolymers with p-PEEK have been investigated, including an amorphous 50: 50 composition and a semicrystalline though still organic-soluble material comprising 70% p-PEEK. o-PEEK has also been obtained by entropy-driven ring-opening polymerization of the macrocyclic oligomers (MCO's) formed by cyclo-condensation of catechol with 4,4'-difluorobenzophenone under pseudo-high-dilution conditions. The principal products of this latter reaction were the cyclic dimer 3a (20 wt %), cyclic trimer 3b (16%) cyclic tetramer 3c (14%), cyclic pentamer 3d (13%) and cyclic hexamer 3e (12%). Macrocycles 3a-c were isolated as pure compounds by gradient column chromatography, and the structures of the cyclic dimer 3a and cyclic tetramer 3c were analyzed by single-crystal X-ray diffraction. A mixture of MCO's, 3, of similar composition, was obtained by cyclodepolymerization of high molar mass o-PEEK in dilute soluion.

Failure of a control strategy for a hybrid air-conditioning and wind catchers/towers system at Bluewater shopping malls in Kent

Purpose – To evaluate the control strategy for a hybrid natural ventilation wind catchers and air-conditioning system and to assess the contribution of wind catchers to indoor air environments and energy savings if any. Design/methodology/approach – Most of the modeling techniques for assessing wind catchers performance are theoretical. Post-occupancy evaluation studies of buildings will provide an insight into the operation of these building components and help to inform facilities managers. A case study for POE was presented in this paper. Findings – The monitoring of the summer and winter month operations showed that the indoor air quality parameters were kept within the design target range. The design control strategy failed to record data regarding the operation, opening time and position of wind catchers system. Though the implemented control strategy was working effectively in monitoring the operation of mechanical ventilation systems, i.e. AHU, did not integrate the wind catchers with the mechanical ventilation system. Research limitations/implications – Owing to short-falls in the control strategy implemented in this project, it was found difficult to quantify and verify the contribution of the wind catchers to the internal conditions and, hence, energy savings. Practical implications – Controlling the operation of the wind catchers via the AHU will lead to isolation of the wind catchers in the event of malfunctioning of the AHU. Wind catchers will contribute to the ventilation of space, particularly in the summer months. Originality/value – This paper demonstrates the value of POE as indispensable tool for FM professionals. It further provides insight into the application of natural ventilation systems in building for healthier indoor environments at lower energy cost. The design of the control strategy for natural ventilation and air-conditioning should be considered at the design stage involving the FM personnel.

Water-soluble precursors of beef flavour. Part II: effect of post-mortem conditioning

Changes in glycolytic metabolites, nucleotide degradation products, free amino acids and other amino compounds were monitored in beef muscle (M. longissimus lumborum), stored for 21 days at 4 degrees C, in order to evaluate how post-mortem conditioning may affect flavour formation in beef. The major effects observed in sugar-related substances were the dephosphorylation of the phosphates of glucose, fructose and mannose, to yield their free sugars, as well as the breakdown of inosine 5'-monophosphate, to give a sixfold increase in ribose. Total reducing sugars increased by only 15% during conditioning, while glycogen levels remained unchanged from 2 days post-slaughter. Free amino acids increased during conditioning, particularly between days 7 and 14. Phenylalanine, methionine, lysine, leucine and isoleucine were the amino acids showing the greatest increase with conditioning time, with methionine, in particular, showing a sevenfold increase during the conditioning period. The effects of these precursor changes on cooked beef flavour are discussed. (c) 2007 Elsevier Ltd. All rights reserved.

M-estimator, and D-optimality model construction using orthogonal forward regression

This correspondence introduces a new orthogonal forward regression (OFR) model identification algorithm using D-optimality for model structure selection and is based on an M-estimators of parameter estimates. M-estimator is a classical robust parameter estimation technique to tackle bad data conditions such as outliers. Computationally, The M-estimator can be derived using an iterative reweighted least squares (IRLS) algorithm. D-optimality is a model structure robustness criterion in experimental design to tackle ill-conditioning in model Structure. The orthogonal forward regression (OFR), often based on the modified Gram-Schmidt procedure, is an efficient method incorporating structure selection and parameter estimation simultaneously. The basic idea of the proposed approach is to incorporate an IRLS inner loop into the modified Gram-Schmidt procedure. In this manner, the OFR algorithm for parsimonious model structure determination is extended to bad data conditions with improved performance via the derivation of parameter M-estimators with inherent robustness to outliers. Numerical examples are included to demonstrate the effectiveness of the proposed algorithm.

Part load operation coefficient of air-conditioning system of public building

IPLV overall coefficient, presented by Air-Conditioning and Refrigeration Institute (ARI) of America, shows running/operation status of air-conditioning system host only. For overall operation coefficient, logical solution has not been developed, to reflect the whole air-conditioning system under part load. In this research undertaking, the running time proportions of air-conditioning systems under part load have been obtained through analysis on energy consumption data during practical operation in all public buildings in Chongqing. This was achieved by using analysis methods, based on the statistical energy consumption data distribution of public buildings month-by-month. Comparing with the weight number of IPLV, part load operation coefficient of air-conditioning system, based on this research, does not only show the status of system refrigerating host, but also reflects and calculate energy efficiency of the whole air-conditioning system. The coefficient results from the processing and analyzing of practical running data, shows the practical running status of area and building type (actual and objective) – not clear. The method is different from model analysis which gets IPLV weight number, in the sense that this method of coefficient results in both four equal proportions and also part load operation coefficient of air-conditioning system under any load rate as necessary.