909 resultados para deferred correction


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Background The leading causes of morbidity and mortality for people in high-income countries living with HIV are now non-AIDS malignancies, cardiovascular disease and other non-communicable diseases associated with ageing. This protocol describes the trial of HealthMap, a model of care for people with HIV (PWHIV) that includes use of an interactive shared health record and self-management support. The aims of the HealthMap trial are to evaluate engagement of PWHIV and healthcare providers with the model, and its effectiveness for reducing coronary heart disease risk, enhancing self-management, and improving mental health and quality of life of PWHIV. Methods/Design The study is a two-arm cluster randomised trial involving HIV clinical sites in several states in Australia. Doctors will be randomised to the HealthMap model (immediate arm) or to proceed with usual care (deferred arm). People with HIV whose doctors are randomised to the immediate arm receive 1) new opportunities to discuss their health status and goals with their HIV doctor using a HealthMap shared health record; 2) access to their own health record from home; 3) access to health coaching delivered by telephone and online; and 4) access to a peer moderated online group chat programme. Data will be collected from participating PWHIV (n = 710) at baseline, 6 months, and 12 months and from participating doctors (n = 60) at baseline and 12 months. The control arm will be offered the HealthMap intervention at the end of the trial. The primary study outcomes, measured at 12 months, are 1) 10-year risk of non-fatal acute myocardial infarction or coronary heart disease death as estimated by a Framingham Heart Study risk equation; and 2) Positive and Active Engagement in Life Scale from the Health Education Impact Questionnaire (heiQ). Discussion The study will determine the viability and utility of a novel technology-supported model of care for maintaining the health and wellbeing of people with HIV. If shown to be effective, the HealthMap model may provide a generalisable, scalable and sustainable system for supporting the care needs of people with HIV, addressing issues of equity of access. Trial registration Universal Trial Number (UTN) U111111506489; ClinicalTrial.gov Id NCT02178930 submitted 29 June 2014

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The problem of reconstruction of a refractive-index distribution (RID) in optical refraction tomography (ORT) with optical path-length difference (OPD) data is solved using two adaptive-estimation-based extended-Kalman-filter (EKF) approaches. First, a basic single-resolution EKF (SR-EKF) is applied to a state variable model describing the tomographic process, to estimate the RID of an optically transparent refracting object from noisy OPD data. The initialization of the biases and covariances corresponding to the state and measurement noise is discussed. The state and measurement noise biases and covariances are adaptively estimated. An EKF is then applied to the wavelet-transformed state variable model to yield a wavelet-based multiresolution EKF (MR-EKF) solution approach. To numerically validate the adaptive EKF approaches, we evaluate them with benchmark studies of standard stationary cases, where comparative results with commonly used efficient deterministic approaches can be obtained. Detailed reconstruction studies for the SR-EKF and two versions of the MR-EKF (with Haar and Daubechies-4 wavelets) compare well with those obtained from a typically used variant of the (deterministic) algebraic reconstruction technique, the average correction per projection method, thus establishing the capability of the EKF for ORT. To the best of our knowledge, the present work contains unique reconstruction studies encompassing the use of EKF for ORT in single-resolution and multiresolution formulations, and also in the use of adaptive estimation of the EKF's noise covariances. (C) 2010 Optical Society of America

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The Earth's ecosystems are protected from the dangerous part of the solar ultraviolet (UV) radiation by stratospheric ozone, which absorbs most of the harmful UV wavelengths. Severe depletion of stratospheric ozone has been observed in the Antarctic region, and to a lesser extent in the Arctic and midlatitudes. Concern about the effects of increasing UV radiation on human beings and the natural environment has led to ground based monitoring of UV radiation. In order to achieve high-quality UV time series for scientific analyses, proper quality control (QC) and quality assurance (QA) procedures have to be followed. In this work, practices of QC and QA are developed for Brewer spectroradiometers and NILU-UV multifilter radiometers, which measure in the Arctic and Antarctic regions, respectively. These practices are applicable to other UV instruments as well. The spectral features and the effect of different factors affecting UV radiation were studied for the spectral UV time series at Sodankylä. The QA of the Finnish Meteorological Institute's (FMI) two Brewer spectroradiometers included daily maintenance, laboratory characterizations, the calculation of long-term spectral responsivity, data processing and quality assessment. New methods for the cosine correction, the temperature correction and the calculation of long-term changes of spectral responsivity were developed. Reconstructed UV irradiances were used as a QA tool for spectroradiometer data. The actual cosine correction factor was found to vary between 1.08-1.12 and 1.08-1.13. The temperature characterization showed a linear temperature dependence between the instrument's internal temperature and the photon counts per cycle. Both Brewers have participated in international spectroradiometer comparisons and have shown good stability. The differences between the Brewers and the portable reference spectroradiometer QASUME have been within 5% during 2002-2010. The features of the spectral UV radiation time series at Sodankylä were analysed for the time period 1990-2001. No statistically significant long-term changes in UV irradiances were found, and the results were strongly dependent on the time period studied. Ozone was the dominant factor affecting UV radiation during the springtime, whereas clouds played a more important role during the summertime. During this work, the Antarctic NILU-UV multifilter radiometer network was established by the Instituto Nacional de Meteorogía (INM) as a joint Spanish-Argentinian-Finnish cooperation project. As part of this work, the QC/QA practices of the network were developed. They included training of the operators, daily maintenance, regular lamp tests and solar comparisons with the travelling reference instrument. Drifts of up to 35% in the sensitivity of the channels of the NILU-UV multifilter radiometers were found during the first four years of operation. This work emphasized the importance of proper QC/QA, including regular lamp tests, for the multifilter radiometers also. The effect of the drifts were corrected by a method scaling the site NILU-UV channels to those of the travelling reference NILU-UV. After correction, the mean ratios of erythemally-weighted UV dose rates measured during solar comparisons between the reference NILU-UV and the site NILU-UVs were 1.007±0.011 and 1.012±0.012 for Ushuaia and Marambio, respectively, when the solar zenith angle varied up to 80°. Solar comparisons between the NILU-UVs and spectroradiometers showed a ±5% difference near local noon time, which can be seen as proof of successful QC/QA procedures and transfer of irradiance scales. This work also showed that UV measurements made in the Arctic and Antarctic can be comparable with each other.

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Accurate and stable time series of geodetic parameters can be used to help in understanding the dynamic Earth and its response to global change. The Global Positioning System, GPS, has proven to be invaluable in modern geodynamic studies. In Fennoscandia the first GPS networks were set up in 1993. These networks form the basis of the national reference frames in the area, but they also provide long and important time series for crustal deformation studies. These time series can be used, for example, to better constrain the ice history of the last ice age and the Earth s structure, via existing glacial isostatic adjustment models. To improve the accuracy and stability of the GPS time series, the possible nuisance parameters and error sources need to be minimized. We have analysed GPS time series to study two phenomena. First, we study the refraction in the neutral atmosphere of the GPS signal, and, second, we study the surface loading of the crust by environmental factors, namely the non-tidal Baltic Sea, atmospheric load and varying continental water reservoirs. We studied the atmospheric effects on the GPS time series by comparing the standard method to slant delays derived from a regional numerical weather model. We have presented a method for correcting the atmospheric delays at the observational level. The results show that both standard atmosphere modelling and the atmospheric delays derived from a numerical weather model by ray-tracing provide a stable solution. The advantage of the latter is that the number of unknowns used in the computation decreases and thus, the computation may become faster and more robust. The computation can also be done with any processing software that allows the atmospheric correction to be turned off. The crustal deformation due to loading was computed by convolving Green s functions with surface load data, that is to say, global hydrology models, global numerical weather models and a local model for the Baltic Sea. The result was that the loading factors can be seen in the GPS coordinate time series. Reducing the computed deformation from the vertical time series of GPS coordinates reduces the scatter of the time series; however, the long term trends are not influenced. We show that global hydrology models and the local sea surface can explain up to 30% of the GPS time series variation. On the other hand atmospheric loading admittance in the GPS time series is low, and different hydrological surface load models could not be validated in the present study. In order to be used for GPS corrections in the future, both atmospheric loading and hydrological models need further analysis and improvements.

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A better understanding of the limiting step in a first order phase transition, the nucleation process, is of major importance to a variety of scientific fields ranging from atmospheric sciences to nanotechnology and even to cosmology. This is due to the fact that in most phase transitions the new phase is separated from the mother phase by a free energy barrier. This barrier is crossed in a process called nucleation. Nowadays it is considered that a significant fraction of all atmospheric particles is produced by vapor-to liquid nucleation. In atmospheric sciences, as well as in other scientific fields, the theoretical treatment of nucleation is mostly based on a theory known as the Classical Nucleation Theory. However, the Classical Nucleation Theory is known to have only a limited success in predicting the rate at which vapor-to-liquid nucleation takes place at given conditions. This thesis studies the unary homogeneous vapor-to-liquid nucleation from a statistical mechanics viewpoint. We apply Monte Carlo simulations of molecular clusters to calculate the free energy barrier separating the vapor and liquid phases and compare our results against the laboratory measurements and Classical Nucleation Theory predictions. According to our results, the work of adding a monomer to a cluster in equilibrium vapour is accurately described by the liquid drop model applied by the Classical Nucleation Theory, once the clusters are larger than some threshold size. The threshold cluster sizes contain only a few or some tens of molecules depending on the interaction potential and temperature. However, the error made in modeling the smallest of clusters as liquid drops results in an erroneous absolute value for the cluster work of formation throughout the size range, as predicted by the McGraw-Laaksonen scaling law. By calculating correction factors to Classical Nucleation Theory predictions for the nucleation barriers of argon and water, we show that the corrected predictions produce nucleation rates that are in good comparison with experiments. For the smallest clusters, the deviation between the simulation results and the liquid drop values are accurately modelled by the low order virial coefficients at modest temperatures and vapour densities, or in other words, in the validity range of the non-interacting cluster theory by Frenkel, Band and Bilj. Our results do not indicate a need for a size dependent replacement free energy correction. The results also indicate that Classical Nucleation Theory predicts the size of the critical cluster correctly. We also presents a new method for the calculation of the equilibrium vapour density, surface tension size dependence and planar surface tension directly from cluster simulations. We also show how the size dependence of the cluster surface tension in equimolar surface is a function of virial coefficients, a result confirmed by our cluster simulations.

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Protein conformations and dynamics can be studied by nuclear magnetic resonance spectroscopy using dilute liquid crystalline samples. This work clarifies the interpretation of residual dipolar coupling data yielded by the experiments. It was discovered that unfolded proteins without any additional structure beyond that of a mere polypeptide chain exhibit residual dipolar couplings. Also, it was found that molecular dynamics induce fluctuations in the molecular alignment and doing so affect residual dipolar couplings. The finding clarified the origins of low order parameter values observed earlier. The work required the development of new analytical and computational methods for the prediction of intrinsic residual dipolar coupling profiles for unfolded proteins. The presented characteristic chain model is able to reproduce the general trend of experimental residual dipolar couplings for denatured proteins. The details of experimental residual dipolar coupling profiles are beyond the analytical model, but improvements are proposed to achieve greater accuracy. A computational method for rapid prediction of unfolded protein residual dipolar couplings was also developed. Protein dynamics were shown to modulate the effective molecular alignment in a dilute liquid crystalline medium. The effects were investigated from experimental and molecular dynamics generated conformational ensembles of folded proteins. It was noted that dynamics induced alignment is significant especially for the interpretation of molecular dynamics in small, globular proteins. A method of correction was presented. Residual dipolar couplings offer an attractive possibility for the direct observation of protein conformational preferences and dynamics. The presented models and methods of analysis provide significant advances in the interpretation of residual dipolar coupling data from proteins.

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Diagnostic radiology represents the largest man-made contribution to population radiation doses in Europe. To be able to keep the diagnostic benefit versus radiation risk ratio as high as possible, it is important to understand the quantitative relationship between the patient radiation dose and the various factors which affect the dose, such as the scan parameters, scan mode, and patient size. Paediatric patients have a higher probability for late radiation effects, since longer life expectancy is combined with the higher radiation sensitivity of the developing organs. The experience with particular paediatric examinations may be very limited and paediatric acquisition protocols may not be optimised. The purpose of this thesis was to enhance and compare different dosimetric protocols, to promote the establishment of the paediatric diagnostic reference levels (DRLs), and to provide new data on patient doses for optimisation purposes in computed tomography (with new applications for dental imaging) and in paediatric radiography. Large variations in radiation exposure in paediatric skull, sinus, chest, pelvic and abdominal radiography examinations were discovered in patient dose surveys. There were variations between different hospitals and examination rooms, between different sized patients, and between imaging techniques; emphasising the need for harmonisation of the examination protocols. For computed tomography, a correction coefficient, which takes individual patient size into account in patient dosimetry, was created. The presented patient size correction method can be used for both adult and paediatric purposes. Dental cone beam CT scanners provided adequate image quality for dentomaxillofacial examinations while delivering considerably smaller effective doses to patient compared to the multi slice CT. However, large dose differences between cone beam CT scanners were not explained by differences in image quality, which indicated the lack of optimisation. For paediatric radiography, a graphical method was created for setting the diagnostic reference levels in chest examinations, and the DRLs were given as a function of patient projection thickness. Paediatric DRLs were also given for sinus radiography. The detailed information about the patient data, exposure parameters and procedures provided tools for reducing the patient doses in paediatric radiography. The mean tissue doses presented for paediatric radiography enabled future risk assessments to be done. The calculated effective doses can be used for comparing different diagnostic procedures, as well as for comparing the use of similar technologies and procedures in different hospitals and countries.

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In uplink OFDMA, carrier frequency offsets (CFO) and/or timing offsets (TO) of other users with respect to a desired user can cause multiuser interference (MUI). In practical uplink OFDMA systems (e.g., IEEE 802.16e standard), effect of this MUI is made acceptably small by requiring that frequency/timing alignment be achieved at the receiver with high precision (e.g., CFO must be within 1 % of the subcarrier spacing and TO must be within 1/8th of the cyclic prefix duration in IEEE 802.16e), which is realized using complex closed-loop frequency/timing correction between the transmitter and the receiver. An alternate open-loop approach to handle the MUI induced by large CFOs and TOs is to employ interference cancellation techniques at the receiver. In this paper, we first analytically characterize the degradation in the average output signal-to-interference ratio (SIR) due to the combined effect of large CFOs and TOs in uplink OFDMA. We then propose a parallel interference canceller (PIC) for the mitigation of interference due to CFOs and TOs in this system. We show that the proposed PIC effectively mitigates the performance loss due to CFO/TO induced interference in uplink OFDMA.

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This research has been prompted by an interest in the atmospheric processes of hydrogen. The sources and sinks of hydrogen are important to know, particularly if hydrogen becomes more common as a replacement for fossil fuel in combustion. Hydrogen deposition velocities (vd) were estimated by applying chamber measurements, a radon tracer method and a two-dimensional model. These three approaches were compared with each other to discover the factors affecting the soil uptake rate. A static-closed chamber technique was introduced to determine the hydrogen deposition velocity values in an urban park in Helsinki, and at a rural site at Loppi. A three-day chamber campaign to carry out soil uptake estimation was held at a remote site at Pallas in 2007 and 2008. The atmospheric mixing ratio of molecular hydrogen has also been measured by a continuous method in Helsinki in 2007 - 2008 and at Pallas from 2006 onwards. The mean vd values measured in the chamber experiments in Helsinki and Loppi were between 0.0 and 0.7 mm s-1. The ranges of the results with the radon tracer method and the two-dimensional model were 0.13 - 0.93 mm s-1 and 0.12 - 0.61 mm s-1, respectively, in Helsinki. The vd values in the three-day campaign at Pallas were 0.06 - 0.52 mm s-1 (chamber) and 0.18 - 0.52 mm s-1 (radon tracer method and two-dimensional model). At Kumpula, the radon tracer method and the chamber measurements produced higher vd values than the two-dimensional model. The results of all three methods were close to each other between November and April, except for the chamber results from January to March, while the soil was frozen. The hydrogen deposition velocity values of all three methods were compared with one-week cumulative rain sums. Precipitation increases the soil moisture, which decreases the soil uptake rate. The measurements made in snow seasons showed that a thick snow layer also hindered gas diffusion, lowering the vd values. The H2 vd values were compared to the snow depth. A decaying exponential fit was obtained as a result. During a prolonged drought in summer 2006, soil moisture values were lower than in other summer months between 2005 and 2008. Such conditions were prevailing in summer 2006 when high chamber vd values were measured. The mixing ratio of molecular hydrogen has a seasonal variation. The lowest atmospheric mixing ratios were found in the late autumn when high deposition velocity values were still being measured. The carbon monoxide (CO) mixing ratio was also measured. Hydrogen and carbon monoxide are highly correlated in an urban environment, due to the emissions originating from traffic. After correction for the soil deposition of H2, the slope was 0.49±0.07 ppb (H2) / ppb (CO). Using the corrected hydrogen-to-carbon-monoxide ratio, the total hydrogen load emitted by Helsinki traffic in 2007 was 261 t (H2) a-1. Hydrogen, methane and carbon monoxide are connected with each other through the atmospheric methane oxidation process, in which formaldehyde is produced as an important intermediate. The photochemical degradation of formaldehyde produces hydrogen and carbon monoxide as end products. Examination of back-trajectories revealed long-range transportation of carbon monoxide and methane. The trajectories can be grouped by applying cluster and source analysis methods. Thus natural and anthropogenic emission sources can be separated by analyzing trajectory clusters.

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When heated to high temperatures, the behavior of matter changes dramatically. The standard model fields go through phase transitions, where the strongly interacting quarks and gluons are liberated from their confinement to hadrons, and the Higgs field condensate melts, restoring the electroweak symmetry. The theoretical framework for describing matter at these extreme conditions is thermal field theory, combining relativistic field theory and quantum statistical mechanics. For static observables the physics is simplified at very high temperatures, and an effective three-dimensional theory can be used instead of the full four-dimensional one via a method called dimensional reduction. In this thesis dimensional reduction is applied to two distinct problems, the pressure of electroweak theory and the screening masses of mesonic operators in quantum chromodynamics (QCD). The introductory part contains a brief review of finite-temperature field theory, dimensional reduction and the central results, while the details of the computations are contained in the original research papers. The electroweak pressure is shown to converge well to a value slightly below the ideal gas result, whereas the pressure of the full standard model is dominated by the QCD pressure with worse convergence properties. For the mesonic screening masses a small positive perturbative correction is found, and the interpretation of dimensional reduction on the fermionic sector is discussed.

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This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

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16-electrode phantoms are developed and studied with a simple instrumentation developed for Electrical Impedance Tomography. An analog instrumentation is developed with a sinusoidal current generator and signal conditioner circuit. Current generator is developed withmodified Howland constant current source fed by a voltage controlled oscillator and the signal conditioner circuit consisting of an instrumentation amplifier and a narrow band pass filter. Electronic hardware is connected to the electrodes through a DIP switch based multiplexer module. Phantoms with different electrode size and position are developed and the EIT forward problem is studied using the forward solver. A low frequency low magnitude sinusoidal current is injected to the surface electrodes surrounding the phantom boundary and the differential potential is measured by a digital multimeter. Comparing measured potential with the simulated data it is intended to reduce the measurement error and an optimum phantom geometry is suggested. Result shows that the common mode electrode reduces the common mode error of the EIT electronics and reduces the error potential in the measured data. Differential potential is reduced up to 67 mV at the voltage electrode pair opposite to the current electrodes. Offset potential is measured and subtracted from the measured data for further correction. It is noticed that the potential data pattern depends on the electrode width and the optimum electrode width is suggested. It is also observed that measured potential becomes acceptable with a 20 mm solution column above and below the electrode array level.

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One mole of diethyl dixanthogen reacts with 26 moles of chloramine-T, and this reaction can be used for the determination of the dixanthogen. Higher alkyl dixanthogens react in a more complicated fashion, but may still be estimated using an empirical correction.

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A better understanding of the limiting step in a first order phase transition, the nucleation process, is of major importance to a variety of scientific fields ranging from atmospheric sciences to nanotechnology and even to cosmology. This is due to the fact that in most phase transitions the new phase is separated from the mother phase by a free energy barrier. This barrier is crossed in a process called nucleation. Nowadays it is considered that a significant fraction of all atmospheric particles is produced by vapor-to liquid nucleation. In atmospheric sciences, as well as in other scientific fields, the theoretical treatment of nucleation is mostly based on a theory known as the Classical Nucleation Theory. However, the Classical Nucleation Theory is known to have only a limited success in predicting the rate at which vapor-to-liquid nucleation takes place at given conditions. This thesis studies the unary homogeneous vapor-to-liquid nucleation from a statistical mechanics viewpoint. We apply Monte Carlo simulations of molecular clusters to calculate the free energy barrier separating the vapor and liquid phases and compare our results against the laboratory measurements and Classical Nucleation Theory predictions. According to our results, the work of adding a monomer to a cluster in equilibrium vapour is accurately described by the liquid drop model applied by the Classical Nucleation Theory, once the clusters are larger than some threshold size. The threshold cluster sizes contain only a few or some tens of molecules depending on the interaction potential and temperature. However, the error made in modeling the smallest of clusters as liquid drops results in an erroneous absolute value for the cluster work of formation throughout the size range, as predicted by the McGraw-Laaksonen scaling law. By calculating correction factors to Classical Nucleation Theory predictions for the nucleation barriers of argon and water, we show that the corrected predictions produce nucleation rates that are in good comparison with experiments. For the smallest clusters, the deviation between the simulation results and the liquid drop values are accurately modelled by the low order virial coefficients at modest temperatures and vapour densities, or in other words, in the validity range of the non-interacting cluster theory by Frenkel, Band and Bilj. Our results do not indicate a need for a size dependent replacement free energy correction. The results also indicate that Classical Nucleation Theory predicts the size of the critical cluster correctly. We also presents a new method for the calculation of the equilibrium vapour density, surface tension size dependence and planar surface tension directly from cluster simulations. We also show how the size dependence of the cluster surface tension in equimolar surface is a function of virial coefficients, a result confirmed by our cluster simulations.

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Recently, focus of real estate investment has expanded from the building-specific level to the aggregate portfolio level. The portfolio perspective requires investment analysis for real estate which is comparable with that of other asset classes, such as stocks and bonds. Thus, despite its distinctive features, such as heterogeneity, high unit value, illiquidity and the use of valuations to measure performance, real estate should not be considered in isolation. This means that techniques which are widely used for other assets classes can also be applied to real estate. An important part of investment strategies which support decisions on multi-asset portfolios is identifying the fundamentals of movements in property rents and returns, and predicting them on the basis of these fundamentals. The main objective of this thesis is to find the key drivers and the best methods for modelling and forecasting property rents and returns in markets which have experienced structural changes. The Finnish property market, which is a small European market with structural changes and limited property data, is used as a case study. The findings in the thesis show that is it possible to use modern econometric tools for modelling and forecasting property markets. The thesis consists of an introduction part and four essays. Essays 1 and 3 model Helsinki office rents and returns, and assess the suitability of alternative techniques for forecasting these series. Simple time series techniques are able to account for structural changes in the way markets operate, and thus provide the best forecasting tool. Theory-based econometric models, in particular error correction models, which are constrained by long-run information, are better for explaining past movements in rents and returns than for predicting their future movements. Essay 2 proceeds by examining the key drivers of rent movements for several property types in a number of Finnish property markets. The essay shows that commercial rents in local markets can be modelled using national macroeconomic variables and a panel approach. Finally, Essay 4 investigates whether forecasting models can be improved by accounting for asymmetric responses of office returns to the business cycle. The essay finds that the forecast performance of time series models can be improved by introducing asymmetries, and the improvement is sufficient to justify the extra computational time and effort associated with the application of these techniques.