A Critical Review of the Implied Cost of Equity: A New Way to Estimate the Expected Return

For the last three decades, the Capital Asset Pricing Model (CAPM) has been a dominant model to calculate expected return. In early 1990% Fama and French (1992) developed the Fama and French Three Factor model by adding two additional factors to the CAPM. However even with these present models, it has been found that estimates of the expected return are not accurate (Elton, 1999; Fama &French, 1997). Botosan (1997) introduced a new approach to estimate the expected return. This approach employs an equity valuation model to calculate the internal rate of return (IRR) which is often called, 'implied cost of equity capital" as a proxy of the expected return. This approach has been gaining in popularity among researchers. A critical review of the literature will help inform hospitality researchers regarding the issue and encourage them to implement the new approach into their own studies.

Forecasting future prevalence of type 2 diabetes mellitus in Syria

Background Type 2 diabetes mellitus (T2DM) is increasingly becoming a major public health problem worldwide. Estimating the future burden of diabetes is instrumental to guide the public health response to the epidemic. This study aims to project the prevalence of T2DM among adults in Syria over the period 2003–2022 by applying a modelling approach to the country’s own data. Methods Future prevalence of T2DM in Syria was estimated among adults aged 25 years and older for the period 2003–2022 using the IMPACT Diabetes Model (a discrete-state Markov model). Results According to our model, the prevalence of T2DM in Syria is projected to double in the period between 2003 and 2022 (from 10% to 21%). The projected increase in T2DM prevalence is higher in men (148%) than in women (93%). The increase in prevalence of T2DM is expected to be most marked in people younger than 55 years especially the 25–34 years age group. Conclusions The future projections of T2DM in Syria put it amongst countries with the highest levels of T2DM worldwide. It is estimated that by 2022 approximately a fifth of the Syrian population aged 25 years and older will have T2DM.

Application of Intervention Analysis to Evaluate the Impacts of Special Events on Freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.

A escrita da escrita em (d)enunciação no espaço sócio-escolar: um espaço (em vão) para a (cri)atividade escrita

This thesis is a writing of (d)enunciation because it reveals the language experiencies of those individuals who take, in social school space, the social role of the teacher and of the student, for some reason, they feel restrained by a demand which prevents them of teaching and learning how to write – and, even, their own writing. On this basis, we consider some questions concerning Benveniste‘s theory of enunciation and the teaching and learning process in Portuguese from the triad among teacher – teaching of writing/ knowledge – student, making this theoretical area closer to the pedagogical one. We support in the working hypothesis that is based on the position of the loosening of this triad has its effects in the process of intervention-interference to the point where it does not leave a scar which can remain working on productive effects on the student‘s writing. As a consequence, we show two findings which allow us to think the teaching of writing in Portuguese is a space for writing creativity in such a way it reveals itself as a sine qua non condition for the institutionalized and subjective writing. The first finding is that taking genre as a model has some implications in the teaching and learning process of writing according to the instructions of the official documents. The second finding, as a result of the first one, is the assumption that genre is at the same time a model and a transgression and taking it as a (ex)sample opens space for writing creativity which ―is a transposition of the interior language‖ (BENVENISTE, 2014 [1968-1969], p. 132) in a way this creativity makes it intelligible and highlights what is a model (interactiveness) and a transgression (inventiveness). From such findings, we organize our heterogeneous corpus according to these procedures: recording the classes in audio; recording the interviews we made with teachers and students in audio; and constituting an archive with the students‘ writing production. From this corpus, we analyzed the (d)enunciative mo(ve)ments in the teacher – teaching of writing/ knowledge – student triad and the history of (d)enunciations, of language experiences. Besides, we analyzed the teacher‘s discourse in relation to the way he plans his classes based on the knowledge that must be taught and his own way of managing this knowledge in order to understand his interference in his students‘ writings. Our analyses (re)affirm that when the loosening of the triad happens, the students become lost, what makes them unable of working upon their own writing epilinguisticaly. Because of it, schools have lost their specificity as a place for teaching students how to read and write as they open space for training, only. On this basis, we consider that the effect of such a loosening generates complaints and denunciations. Therefore, based on such (d)enunciations, we present the Primary sketches of a proposition for intervention-interference in teaching how to write and we aim at introducing much knowledge to teachers and students in order to allow them to think about possible ways out.

Essays in Industrial Organization

This dissertation extends the empirical industrial organization literature with two essays on strategic decisions of firms in imperfectly competitive markets and one essay on how inertia in consumer choice can result in significant welfare losses. Using data from the airline industry I study a well-known puzzle in the literature whereby incumbent firms decrease fares when Southwest Airlines emerges as a potential entrant, but is not (yet) competing directly. In the first essay I describe this so-called Southwest Effect and use reduced-form analysis to offer possible explanations for why firms may choose to forgo profits today rather than wait until Southwest operates the route. The analysis suggests that incumbent firms are attempting to signal to Southwest that entry is unprofitable so as to deter its entry. The second essay develops this theme by extending a classic model from the IO literature, limit pricing, to a dynamic setting. Calibrations indicate the price cuts observed in the data can be captured by a dynamic limit pricing model. The third essay looks at another concentrated industry, mobile telecoms, and studies how inertia in choice (be it inattention or switching costs) can lead to consumers being on poorly matched cellphone plans and how a simple policy proposal can have a considerable effect on welfare.

Essays on the Dynamic Decisions of Homeowners and Retailers

Urban problems have several features that make them inherently dynamic. Large transaction costs all but guarantee that homeowners will do their best to consider how a neighborhood might change before buying a house. Similarly, stores face large sunk costs when opening, and want to be sure that their investment will pay off in the long run. In line with those concerns, different areas of Economics have made recent advances in modeling those questions within a dynamic framework. This dissertation contributes to those efforts.

Chapter 2 discusses how to model an agent’s location decision when the agent must learn about an exogenous amenity that may be changing over time. The model is applied to estimating the marginal willingness to pay to avoid crime, in which agents are learning about the crime rate in a neighborhood, and the crime rate can change in predictable (Markovian) ways.

Chapters 3 and 4 concentrate on location decision problems when there are externalities between decision makers. Chapter 3 focuses on the decision of business owners to open a store, when its demand is a function of other nearby stores, either through competition, or through spillovers on foot traffic. It uses a dynamic model in continuous time to model agents’ decisions. A particular challenge is isolating the contribution of spillovers from the contribution of other unobserved neighborhood attributes that could also lead to agglomeration. A key contribution of this chapter is showing how we can use information on storefront ownership to help separately identify spillovers.

Finally, chapter 4 focuses on a class of models in which families prefer to live

close to similar neighbors. This chapter provides the first simulation of such a model in which agents are forward looking, and shows that this leads to more segregation than it would have been observed with myopic agents, which is the standard in this literature. The chapter also discusses several extensions of the model that can be used to investigate relevant questions such as the arrival of a large contingent high skilled tech workers in San Francisco, the immigration of hispanic families to several southern American cities, large changes in local amenities, such as the construction of magnet schools or metro stations, and the flight of wealthy residents from cities in the Rust belt, such as Detroit.

Knowledge Modeling for The Outcome of Brain Stereotactic Radiosurgery

Purpose: To build a model that will predict the survival time for patients that were treated with stereotactic radiosurgery for brain metastases using support vector machine (SVM) regression.

Methods and Materials: This study utilized data from 481 patients, which were equally divided into training and validation datasets randomly. The SVM model used a Gaussian RBF function, along with various parameters, such as the size of the epsilon insensitive region and the cost parameter (C) that are used to control the amount of error tolerated by the model. The predictor variables for the SVM model consisted of the actual survival time of the patient, the number of brain metastases, the graded prognostic assessment (GPA) and Karnofsky Performance Scale (KPS) scores, prescription dose, and the largest planning target volume (PTV). The response of the model is the survival time of the patient. The resulting survival time predictions were analyzed against the actual survival times by single parameter classification and two-parameter classification. The predicted mean survival times within each classification were compared with the actual values to obtain the confidence interval associated with the model’s predictions. In addition to visualizing the data on plots using the means and error bars, the correlation coefficients between the actual and predicted means of the survival times were calculated during each step of the classification.

Results: The number of metastases and KPS scores, were consistently shown to be the strongest predictors in the single parameter classification, and were subsequently used as first classifiers in the two-parameter classification. When the survival times were analyzed with the number of metastases as the first classifier, the best correlation was obtained for patients with 3 metastases, while patients with 4 or 5 metastases had significantly worse results. When the KPS score was used as the first classifier, patients with a KPS score of 60 and 90/100 had similar strong correlation results. These mixed results are likely due to the limited data available for patients with more than 3 metastases or KPS scores of 60 or less.

Conclusions: The number of metastases and the KPS score both showed to be strong predictors of patient survival time. The model was less accurate for patients with more metastases and certain KPS scores due to the lack of training data.

Sediment and ice characteristics at a buried ice-wedge system at Barrow

Barrow, the northernmost point in Alaska, is one of the most intensively studied areas in the Arctic. However, paleoenvironmental evidence is limited for northern Alaska for the Lateglacial-Holocene transition. For a regional paleoenvironmental reconstruction, we investigated a permafrost ice-wedge tunnel near Barrow, Alaska. The studied site was first excavated in the early 1960s and intercepts a buried ice-wedge system at 3-6 m depth below the surface. A multi-methodological approach was applied to this buried ice-wedge system and the enclosing sediments, which in their combination, give new insight into the Late Quaternary environmental and climate history. Results of geochronological, sedimentological, cryolithological, paleoecological, isotope geochemical and microbiological studies reflect different stages of mid to late Wisconsin (MW to LW), Allerod (AD), Younger Dryas (YD), Preboreal (PB), and Late Holocene paleoenvironmental evolution. The LW age of the site is indicated by AMS dates in the surrounding sediments of 21.7 kyr BP at the lateral contact of the ice-wedge system as well as 39.5 kyr BP below the ice-wedge system. It is only recently that in this region, stable isotope techniques have been employed, i.e. to characterize different types of ground ice. The stable isotope record (oxygen: d18O; hydrogen: dD) of two intersecting ice wedges suggests different phases of the northern Alaskan climate history from AD to PB, with radiocarbon dates from 12.4 to 9.9 kyr BP (ranging from 14.8 to 10.6 kyr cal BP). Stable isotope geochemistry of ice wedges reveals winter temperature variations of the Lateglacial-Holocene transition including a prominent YD cold period, clearly separated from the warmer AD and PB phases. YD is only weakly developed in summer temperature indicators (such as pollen) for the northern Alaska area, and by consequence, the YD cold stadial was here especially related to the winter season. This highlights that the combination of winter and summer indicators comprehensively describes the seasonality of climate-relevant processes in discrete time intervals. The stable isotope record for the Barrow buried ice-wedge system documents for the first time winter climate change at the Lateglacial-Holocene transition continuously and at relatively high (likely centennial) resolution.

Impaired GABA Plasticity at ovBNST Synapses Predicts Compulsive Drinking in Schedule-Induced Polydipsia

Schedule-Induced Polydipsia (SIP) is an animal model of adjunctive drinking induced when a hungry rat receives food on a fixed interval of time. This model has been implemented as a model of compulsive behaviour and may represent a powerful tool to understand the neural mechanisms of compulsion. The bed nucleus of the stria terminalis (BNST) is thought to translate challenges to energy homeostasis into consummatory behaviours, and is therefore likely to contribute to drinking behaviours displayed by food restricted rats in the SIP paradigm. Furthermore, the BNST seems implicated in various compulsive behaviors, including compulsive water drinking in rats. Therefore, the goal of this project was to determine whether compulsive drinking in the SIP paradigm was associated with alterations in transmission at oval BNST (ovBNST) synapses. Rats undergoing the SIP procedure had restricted food access (1-hours/day) for a total of 29 days. After 7 days of food restriction and for the next 21 consecutive days, the rats had daily 2-hour access to operant conditioning chambers where they were presented with a 45-mg food pellet every minute. Water consumed during these 2-hour sessions was measured and the rats that drank 15 ml or more water for a minimum of 3 consecutive days were considered High Drinkers (HD; n=17) or otherwise, Low Drinkers (LD; n=13). Brain slices whole-cell patch clamp recordings conducted 18-hours after the last SIP training showed that chronic food restriction changed low frequency stimulation (LFS) - induced long-term potentiation of ovBNST inhibitory synaptic transmission (iLTP) into LFS - induced long-term depression (iLTD) in a majority of neurons, regardless of drinking behaviours. However, ad libitum access to food between the last day of SIP training and brain slice recordings (18-hour refeed) rescued LFS-induced iLTP in LD but not in HD, suggesting that impaired bi-directional plasticity of ovBNST synapses may contribute to compulsive drinking in the SIP paradigm.

Modeling, Analysis and Performance Comparison of Two Direct Sampling DCSK Receivers under Frequency Nonselective Fading Channels

Two direct sampling correlator-type receivers for differential chaos shift keying (DCSK) communication systems under frequency non-selective fading channels are proposed. These receivers operate based on the same hardware platform with different architectures. In the first scheme, namely sum-delay-sum (SDS) receiver, the sum of all samples in a chip period is correlated with its delayed version. The correlation value obtained in each bit period is then compared with a fixed threshold to decide the binary value of recovered bit at the output. On the other hand, the second scheme, namely delay-sum-sum (DSS) receiver, calculates the correlation value of all samples with its delayed version in a chip period. The sum of correlation values in each bit period is then compared with the threshold to recover the data. The conventional DCSK transmitter, frequency non-selective Rayleigh fading channel, and two proposed receivers are mathematically modelled in discrete-time domain. The authors evaluated the bit error rate performance of the receivers by means of both theoretical analysis and numerical simulation. The performance comparison shows that the two proposed receivers can perform well under the studied channel, where the performances get better when the number of paths increases and the DSS receiver outperforms the SDS one.

Management of public water supply to reduce power cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Simulation of Distributed Contact in String Instruments: a Modal Expansion Approach

Impactive contact between a vibrating string and a barrier is a strongly nonlinear phenomenon that presents several challenges in the design of numerical models for simulation and sound synthesis of musical string instruments. These are addressed here by applying Hamiltonian methods to incorporate distributed contact forces into a modal framework for discrete-time simulation of the dynamics of a stiff, damped string. The resulting algorithms have spectral accuracy, are unconditionally stable, and require solving a multivariate nonlinear equation that is guaranteed to have a unique solution. Exemplifying results are presented and discussed in terms of accuracy, convergence, and spurious high-frequency oscillations.

An Efficient Precoder Design for Multiuser MIMO Cognitive Radio Networks with Interference Constraints

We consider a linear precoder design for an underlay cognitive radio multiple-input multiple-output broadcast channel, where the secondary system consisting of a secondary base-station (BS) and a group of secondary users (SUs) is allowed to share the same spectrum with the primary system. All the transceivers are equipped with multiple antennas, each of which has its own maximum power constraint. Assuming zero-forcing method to eliminate the multiuser interference, we study the sum rate maximization problem for the secondary system subject to both per-antenna power constraints at the secondary BS and the interference power constraints at the primary users. The problem of interest differs from the ones studied previously that often assumed a sum power constraint and/or single antenna employed at either both the primary and secondary receivers or the primary receivers. To develop an efficient numerical algorithm, we first invoke the rank relaxation method to transform the considered problem into a convex-concave problem based on a downlink-uplink result. We then propose a barrier interior-point method to solve the resulting saddle point problem. In particular, in each iteration of the proposed method we find the Newton step by solving a system of discrete-time Sylvester equations, which help reduce the complexity significantly, compared to the conventional method. Simulation results are provided to demonstrate fast convergence and effectiveness of the proposed algorithm. 

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.