“I have to rest all the time because you are not allowed to play”: Exploring children’s perceptions of autonomy during sleep-time in long day care services

Daytime sleep is a significant part of the daily routine for children attending early childhood education and care (ECEC) services in Australia and many other countries. The practice of sleep-time can account for a substantial portion of the day in ECEC and often involves a mandated sleep/rest period for all children, including older preschool-aged children. Yet, there is evidence that children have a reduced need for daytime sleep as they approach school entry age and that continuation of mandated sleep-time in ECEC for preschool-aged children may have a negative impact on their health, development, learning and well-being. Mandated sleep-time practices also go against current quality expectations for services to support children’s agency and autonomy in ECEC. This study documents children’s reports of their experiences of sleep-time in ECEC. Semi-structured interviews were conducted with 54 preschool-aged children (44–63 months) across four long day ECEC services that employed a range of sleep-time practices. Findings provide a snapshot of children’s views and experiences of sleep-time and perceptions of autonomy-supportive practices. These provide a unique platform to support critical reflection on sleep-time policies and practices, with a view to continuous quality improvement in ECEC. This study forms part of a programme of work from the Sleep in Early Childhood research group. Our work examines sleep practices in ECEC, the subsequent staff, parent and child experiences and impacts on family and child learning and development outcomes.

Towards real-time understanding of processes in pharmaceutical powder technology

There is a need for better understanding of the processes and new ideas to develop traditional pharmaceutical powder manufacturing procedures. Process analytical technology (PAT) has been developed to improve understanding of the processes and establish methods to monitor and control processes. The interest is in maintaining and even improving the whole manufacturing process and the final products at real-time. Process understanding can be a foundation for innovation and continuous improvement in pharmaceutical development and manufacturing. New methods are craved for to increase the quality and safety of the final products faster and more efficiently than ever before. The real-time process monitoring demands tools, which enable fast and noninvasive measurements with sufficient accuracy. Traditional quality control methods have been laborious and time consuming and they are performed off line i.e. the analysis has been removed from process area. Vibrational spectroscopic methods are responding this challenge and their utilisation have increased a lot during the past few years. In addition, other methods such as colour analysis can be utilised in noninvasive real-time process monitoring. In this study three pharmaceutical processes were investigated: drying, mixing and tabletting. In addition tablet properties were evaluated. Real-time monitoring was performed with NIR and Raman spectroscopies, colour analysis, particle size analysis and compression data during tabletting was evaluated using mathematical modelling. These methods were suitable for real-time monitoring of pharmaceutical unit operations and increase the knowledge of the critical parameters in the processes and the phenomena occurring during operations. They can improve our process understanding and therefore, finally, enhance the quality of final products.

A simple method for estimating growth parameters from multiple length-frequency data in presence of continuous recruitment

The extended recruitment season for short-lived species such as prawns biases the estimation of growth parameters from length-frequency data when conventional methods are used. We propose a simple method for overcoming this bias given a time series of length-frequency data. The difficulties arising from extended recruitment are eliminated by predicting the growth of the succeeding samples and the length increments of the recruits in previous samples. This method requires that some maximum size at recruitment can be specified. The advantages of this multiple length-frequency method are: it is simple to use; it requires only three parameters; no specific distributions need to be assumed; and the actual seasonal recruitment pattern does not have to be specified. We illustrate the new method with length-frequency data on the tiger prawn Penaeus esculentus from the north-western Gulf of Carpentaria, Australia.

Continuous after-the-fact leakage-resilient eCK-secure key exchange

Security models for two-party authenticated key exchange (AKE) protocols have developed over time to capture the security of AKE protocols even when the adversary learns certain secret values. Increased granularity of security can be modelled by considering partial leakage of secrets in the manner of models for leakage-resilient cryptography, designed to capture side-channel attacks. In this work, we use the strongest known partial-leakage-based security model for key exchange protocols, namely continuous after-the-fact leakage eCK (CAFL-eCK) model. We resolve an open problem by constructing the first concrete two-pass leakage-resilient key exchange protocol that is secure in the CAFL-eCK model.

Testing the simulation capability of APSIM-ORYZA under different levels of nitrogen fertiliser and transplanting time regimes in Korea

APSIM-ORYZA is a new functionality developed in the APSIM framework to simulate rice production while addressing management issues such as fertilisation and transplanting, which are particularly important in Korean agriculture. To validate the model for Korean rice varieties and field conditions, the measured yields and flowering times from three field experiments conducted by the Gyeonggi Agricultural Research and Extension Services (GARES) in Korea were compared against the simulated outputs for different management practices and rice varieties. Simulated yields of early-, mid- and mid-to-late-maturing varieties of rice grown in a continuous rice cropping system from 1997 to 2004 showed close agreement with the measured data. Similar results were also found for yields simulated under seven levels of nitrogen application. When different transplanting times were modelled, simulated flowering times ranged from within 3 days of the measured values for the early-maturing varieties, to up to 9 days after the measured dates for the mid- and especially mid-to-late-maturing varieties. This was associated with highly variable simulated yields which correlated poorly with the measured data. This suggests the need to accurately calibrate the photoperiod sensitivity parameters of the model for the photoperiod-sensitive rice varieties in Korea.

The effects of sliding velocity and sliding time on nanocrystalline tribolayer development and properties in copper

The growth of the nanocrystalline tribolayer produced in oxygen free high conductivity copper after sliding against 440C stainless steel was studied. Tests were conducted on a pin-on-disk tribometer at sliding velocities of 0.05 and 1.0 m/s and sliding times of 0.1 to 10,000 s. Subsurface deformation and the growth of the tribolayer as a function of time were studied with the use of transmission electron microscopy and ion induced secondary electron microscopy. A continuous nanocrystalline tribolayer was produced after as little as 10 s of sliding at both sliding velocities. The tribolayer produced by sliding at 0.05 m/s continued to grow at sliding times up to 10,000 s and developed texture. Dynamic recrystallization of the tribolayer at a sliding velocity of 1.0 m/s inhibited the growth of a continuous anocrystalline tribolayer.

Continuous combined microwave and hot air treatment of apples for fruit fly (Bactrocera tryoni and B. jarvisi) disinfestation

Apples at 24 ± 2 °C were heated in a pilot scale hot air assisted (40 °C) continuous pentagonal microwave system, to evaluate the effectiveness of this treatment on insect mortality (variety Mutsu) and fruit quality (variety Granny Smith). An average temperature of 53.4 ± 1.3 °C at core, bottom and flesh of the apple was recorded at the end of the treatment. One hundred percent mortality of the most tolerant stage of Queensland fruit fly (Bactrocera tryoni, Froggatt) and Jarvis's fruit fly (Bactrocera jarvisi, Tryon), were observed when the Mortality value (M52, equivalent time of isothermal treatment at 52 °C) at the slowest heating point applicable for each experiment was ≥ 50 min and ≥ 37 min, respectively. Results showed that microwave heat treatment is effective for insect disinfestation without any adverse impact on total soluble solids, flesh or peel firmness of the treated apples. The treated apples recorded a significantly higher pH and lower ion leakage than the untreated apples after 3 or 4 weeks. Therefore, the microwave heat treatment has the potential to be developed as an alternative chemical free quarantine treatment against economically significant insect pests. Industrial relevance Hot air assisted microwave heating of fruits and vegetables, is more cost effective compared to vapour heat treatment and ionising radiation for disinfestation of insects. Microwave treatment is environmentally friendly compared to fumigation and chemical treatments. Hot air assisted microwave disinfestation can be performed at farms or centralised pack houses since the capital cost would be comparatively lower than vapour heat or ionising radiation treatments.

Continuous Distribution Kinetics for Photopolymerization of Alkyl Methacrylates

The photopolymerization of methyl,ethyl,butyl, and hexyl methacrylates in solution was studied. The effect of initial initiator and monomer concentrations on the time evolution of polymer concentration (M) over bar (n) and PDI was examined. The reversible chain addition and beta-scission, and primary radical termination steps were included in the mechanism along with the classical steps. The rate equations were derived using continuous distribution kinetics and solved numerically to fit the experimental data. The regressed rate coefficients compared well with the literature data. The model predicted the instantaneous increase in (M) over bar (n) and PDI to steady state values. The rate coefficients exhibited a linear increase with the size of alkyl chain of the alkyl methacrylates.

Clinical Studies on Epidural and Spinal Postoperative Analgesia : With Special Reference to Continuous Techniques of Administration and Adjuvant Drugs

Continuous epidural analgesia (CEA) and continuous spinal postoperative analgesia (CSPA) provided by a mixture of local anaesthetic and opioid are widely used for postoperative pain relief. E.g., with the introduction of so-called microcatheters, CSPA found its way particularly in orthopaedic surgery. These techniques, however, may be associated with dose-dependent side-effects as hypotension, weakness in the legs, and nausea and vomiting. At times, they may fail to offer sufficient analgesia, e.g., because of a misplaced catheter. The correct position of an epidural catheter might be confirmed by the supposedly easy and reliable epidural stimulation test (EST). The aims of this thesis were to determine a) whether the efficacy, tolerability, and reliability of CEA might be improved by adding the α2-adrenergic agonists adrenaline and clonidine to CEA, and by the repeated use of EST during CEA; and, b) the feasibility of CSPA given through a microcatheter after vascular surgery. Studies I IV were double-blinded, randomized, and controlled trials; Study V was of a diagnostic, prospective nature. Patients underwent arterial bypass surgery of the legs (I, n=50; IV, n=46), total knee arthroplasty (II, n=70; III, n=72), and abdominal surgery or thoracotomy (V, n=30). Postoperative lumbar CEA consisted of regular mixtures of ropivacaine and fentanyl either without or with adrenaline (2 µg/ml (I) and 4 µg/ml (II)) and clonidine (2 µg/ml (III)). CSPA (IV) was given through a microcatheter (28G) and contained either ropivacaine (max. 2 mg/h) or a mixture of ropivacaine (max. 1 mg/h) and morphine (max. 8 µg/h). Epidural catheter tip position (V) was evaluated both by EST at the moment of catheter placement and several times during CEA, and by epidurography as reference diagnostic test. CEA and CSPA were administered for 24 or 48 h. Study parameters included pain scores assessed with a visual analogue scale, requirements of rescue pain medication, vital signs, and side-effects. Adrenaline (I and II) had no beneficial influence as regards the efficacy or tolerability of CEA. The total amounts of epidurally-infused drugs were even increased in the adrenaline group in Study II (p=0.02, RM ANOVA). Clonidine (III) augmented pain relief with lowered amounts of epidurally infused drugs (p=0.01, RM ANOVA) and reduced need for rescue oxycodone given i.m. (p=0.027, MW-U; median difference 3 mg (95% CI 0 7 mg)). Clonidine did not contribute to sedation and its influence on haemodynamics was minimal. CSPA (IV) provided satisfactory pain relief with only limited blockade of the legs (no inter-group differences). EST (V) was often related to technical problems and difficulties of interpretation, e.g., it failed to identify the four patients whose catheters were outside the spinal canal already at the time of catheter placement. As adjuvants to lumbar CEA, clonidine only slightly improved pain relief, while adrenaline did not provide any benefit. The role of EST applied at the time of epidural catheter placement or repeatedly during CEA remains open. The microcatheter CSPA technique appeared effective and reliable, but needs to be compared to routine CEA after peripheral arterial bypass surgery.

Quantum Space-Time and Noncommutative Gauge Field Theories

Arguments arising from quantum mechanics and gravitation theory as well as from string theory, indicate that the description of space-time as a continuous manifold is not adequate at very short distances. An important candidate for the description of space-time at such scales is provided by noncommutative space-time where the coordinates are promoted to noncommuting operators. Thus, the study of quantum field theory in noncommutative space-time provides an interesting interface where ordinary field theoretic tools can be used to study the properties of quantum spacetime. The three original publications in this thesis encompass various aspects in the still developing area of noncommutative quantum field theory, ranging from fundamental concepts to model building. One of the key features of noncommutative space-time is the apparent loss of Lorentz invariance that has been addressed in different ways in the literature. One recently developed approach is to eliminate the Lorentz violating effects by integrating over the parameter of noncommutativity. Fundamental properties of such theories are investigated in this thesis. Another issue addressed is model building, which is difficult in the noncommutative setting due to severe restrictions on the possible gauge symmetries imposed by the noncommutativity of the space-time. Possible ways to relieve these restrictions are investigated and applied and a noncommutative version of the Minimal Supersymmetric Standard Model is presented. While putting the results obtained in the three original publications into their proper context, the introductory part of this thesis aims to provide an overview of the present situation in the field.

Diagnostic Tests Based on Quantile Residuals for Nonlinear Time Series Models

This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.

A novel approach for large-scale polypeptide folding based on elastic networks using continuous optimization

We present a new computationally efficient method for large-scale polypeptide folding using coarse-grained elastic networks and gradient-based continuous optimization techniques. The folding is governed by minimization of energy based on Miyazawa–Jernigan contact potentials. Using this method we are able to substantially reduce the computation time on ordinary desktop computers for simulation of polypeptide folding starting from a fully unfolded state. We compare our results with available native state structures from Protein Data Bank (PDB) for a few de-novo proteins and two natural proteins, Ubiquitin and Lysozyme. Based on our simulations we are able to draw the energy landscape for a small de-novo protein, Chignolin. We also use two well known protein structure prediction software, MODELLER and GROMACS to compare our results. In the end, we show how a modification of normal elastic network model can lead to higher accuracy and lower time required for simulation.

Three-Dimensional Unsteady Flow With Heat and Mass Transfer Over a Continuous Stretching Surface

A numerical solution of the unsteady boundary layer equations under similarity assumptions is obtained. The solution represents the three-dimensional unsteady fluid motion caused by the time-dependent stretching of a flat boundary. It has been shown that a self-similar solution exists when either the rate of stretching is decreasing with time or it is constant. Three different numerical techniques are applied and a comparison is made among them as well as with earlier results. Analysis is made for various situations like deceleration in stretching of the boundary, mass transfer at the surface, saddle and nodal point flows, and the effect of a magnetic field. Both the constant temperature and constant heat flux conditions at the wall have been studied.

Accurate mass-based analysis in human sport doping control : Application of liquid chromatography - time-of-flight mass spectrometry

Human sport doping control analysis is a complex and challenging task for anti-doping laboratories. The List of Prohibited Substances and Methods, updated annually by World Anti-Doping Agency (WADA), consists of hundreds of chemically and pharmacologically different low and high molecular weight compounds. This poses a considerable challenge for laboratories to analyze for them all in a limited amount of time from a limited sample aliquot. The continuous expansion of the Prohibited List obliges laboratories to keep their analytical methods updated and to research new available methodologies. In this thesis, an accurate mass-based analysis employing liquid chromatography - time-of-flight mass spectrometry (LC-TOFMS) was developed and validated to improve the power of doping control analysis. New analytical methods were developed utilizing the high mass accuracy and high information content obtained by TOFMS to generate comprehensive and generic screening procedures. The suitability of LC-TOFMS for comprehensive screening was demonstrated for the first time in the field with mass accuracies better than 1 mDa. Further attention was given to generic sample preparation, an essential part of screening analysis, to rationalize the whole work flow and minimize the need for several separate sample preparation methods. Utilizing both positive and negative ionization allowed the detection of almost 200 prohibited substances. Automatic data processing produced a Microsoft Excel based report highlighting the entries fulfilling the criteria of the reverse data base search (retention time (RT), mass accuracy, isotope match). The quantitative performance of LC-TOFMS was demonstrated with morphine, codeine and their intact glucuronide conjugates. After a straightforward sample preparation the compounds were analyzed directly without the need for hydrolysis, solvent transfer, evaporation or reconstitution. The hydrophilic interaction technique (HILIC) provided good chromatographic separation, which was critical for the morphine glucuronide isomers. A wide linear range (50-5000 ng/ml) with good precision (RSD<10%) and accuracy (±10%) was obtained, showing comparable or better performance to other methods used. In-source collision-induced dissociation (ISCID) allowed confirmation analysis with three diagnostic ions with a median mass accuracy of 1.08 mDa and repeatable ion ratios fulfilling WADA s identification criteria. The suitability of LC-TOFMS for screening of high molecular weight doping agents was demonstrated with plasma volume expanders (PVE), namely dextran and hydroxyethylstarch (HES). Specificity of the assay was improved, since interfering matrix compounds were removed by size exclusion chromatography (SEC). ISCID produced three characteristic ions with an excellent mean mass accuracy of 0.82 mDa at physiological concentration levels. In summary, by combining TOFMS with a proper sample preparation and chromatographic separation, the technique can be utilized extensively in doping control laboratories for comprehensive screening of chemically different low and high molecular weight compounds, for quantification of threshold substances and even for confirmation. LC-TOFMS rationalized the work flow in doping control laboratories by simplifying the screening scheme, expediting reporting and minimizing the analysis costs. Therefore LC-TOFMS can be exploited widely in doping control, and the need for several separate analysis techniques is reduced.

Adaptive optimization of continuous bioreactor using neural network model

An adaptive optimization algorithm using backpropogation neural network model for dynamic identification is developed. The algorithm is applied to maximize the cellular productivity of a continuous culture of baker's yeast. The robustness of the algorithm is demonstrated in determining and maintaining the optimal dilution rate of the continuous bioreactor in presence of disturbances in environmental conditions and microbial culture characteristics. The simulation results show that a significant reduction in time required to reach optimal operating levels can be achieved using neural network model compared with the traditional dynamic linear input-output model. The extension of the algorithm for multivariable adaptive optimization of continuous bioreactor is briefly discussed.