Modelling and analysing human behaviour in a department store using discrete event and agent based simulation

Discrete Event Simulation (DES) is a very popular simulation technique in Operational Research. Recently, there has been the emergence of another technique, namely Agent Based Simulation (ABS). Although there is a lot of literature relating to DES and ABS, we have found less that focuses on exploring the capabilities of both in tackling human behaviour issues. In order to understand the gap between these two simulation techniques, therefore, our aim is to understand the distinctions between DES and ABS models with the real world phenomenon in modelling and simulating human behaviour. In achieving the aim, we have carried out a case study at a department store. Both DES and ABS models will be compared using the same problem domain which is concerning on management policy in a fitting room. The behaviour of staffs while working and customers’ satisfaction will be modelled for both models behaviour understanding.

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Theoretical investigation of intra- and inter-cellular spatiotemporal calcium patterns in microcirculation

Microcirculatory vessels are lined by endothelial cells (ECs) which are surrounded by a single or multiple layer of smooth muscle cells (SMCs). Spontaneous and agonist induced spatiotemporal calcium (Ca2+) events are generated in ECs and SMCs, and regulated by complex bi-directional signaling between the two layers which ultimately determines the vessel tone. The contractile state of microcirculatory vessels is an important factor in the determination of vascular resistance, blood flow and blood pressure. This dissertation presents theoretical insights into some of the important and currently unresolved phenomena in microvascular tone regulation. Compartmental and continuum models of isolated EC and SMC, coupled EC-SMC and a multi-cellular vessel segment with deterministic and stochastic descriptions of the cellular components were developed, and the intra- and inter-cellular spatiotemporal Ca2+ mobilization was examined.^ Coupled EC-SMC model simulations captured the experimentally observed localized subcellular EC Ca2+ events arising from the opening of EC transient receptor vanilloid 4 (TRPV4) channels and inositol triphosphate receptors (IP3Rs). These localized EC Ca2+ events result in endothelium-derived hyperpolarization (EDH) and Nitric Oxide (NO) production which transmit to the adjacent SMCs to ultimately result in vasodilation. The model examined the effect of heterogeneous distribution of cellular components and channel gating kinetics in determination of the amplitude and spread of the Ca2+ events. The simulations suggested the necessity of co-localization of certain cellular components for modulation of EDH and NO responses. Isolated EC and SMC models captured intracellular Ca2+ wave like activity and predicted the necessity of non-uniform distribution of cellular components for the generation of Ca2+ waves. The simulations also suggested the role of membrane potential dynamics in regulating Ca2+ wave velocity. The multi-cellular vessel segment model examined the underlying mechanisms for the intercellular synchronization of spontaneous oscillatory Ca2+ waves in individual SMC. ^ From local subcellular events to integrated macro-scale behavior at the vessel level, the developed multi-scale models captured basic features of vascular Ca2+ signaling and provide insights for their physiological relevance. The models provide a theoretical framework for assisting investigations on the regulation of vascular tone in health and disease.^

Enabling effective operational decision making on a Combined Heat and Power System using the 5C architecture

The use of Cyber Physical Systems (CPS) to optimise industrial energy systems is an approach which has the potential to positively impact on manufacturing sector energy efficiency. The need to obtain data to facilitate the implementation of a CPS in an industrial energy system is however a complex task which is often implemented in a non-standardised way. The use of the 5C CPS architecture has the potential to standardise this approach. This paper describes a case study where data from a Combined Heat and Power (CHP) system located in a large manufacturing company was fused with grid electricity and gas models as well as a maintenance cost model using the 5C architecture with a view to making effective decisions on its cost efficient operation. A control change implemented based on the cognitive analysis enabled via the 5C architecture implementation has resulted in energy cost savings of over €7400 over a four-month period, with energy cost savings of over €150,000 projected once the 5C architecture is extended into the production environment.

Manipulating the structural and electronic properties of epitaxial NaNbO3 films via strain and stoichiometry

Due to their intriguing dielectric, pyroelectric, elasto-electric, or opto-electric properties, oxide ferroelectrics are vital candidates for the fabrication of most electronics. However, these extraordinary properties exist mainly in the temperature regime around the ferroelectric phase transition, which is usually several hundreds of K away from room temperature. Therefore, the manipulation of oxide ferroelectrics, especially moving the ferroelectric transition towards room temperature, is of great interest for application and also basic research. In this thesis, we demonstrate this using examples of NaNbO3 films. We show that the transition temperature of these films can be modified via plastic strain caused by epitaxial film growth on a structurally mismatched substrate, and this strain can be fixed by controlling the stoichiometry. The structural and electronic properties of Na1+xNbO3+δ thin films are carefully examined by among others XRD (e.g. RSM) and TEM and cryoelectronic measurements. Especially the electronic features are carefully analyzed via specially developed interdigitated electrodes in combination with integrated temperature sensor and heater. The electronic data are interpreted using existing as well as novel theories and models, they are proved to be closely correlated to the structural characteristics. The major results are: -Na1+xNbO3+δ thin films can be grown epitaxially on (110)NdGaO3 with a thickness up to 140 nm (thicker films have not been studied). Plastic relaxation of the compressive strain sets in when the thickness of the film exceeds approximately 10 – 15 nm. Films with excess Na are mainly composed of NaNbO3 with minor contribution of Na3NbO4. The latter phase seems to form nanoprecipitates that are homogeneously distributed in the NaNbO3 film which helps to stabilize the film and reduce the relaxation of the strain. -For the nominally stoichiometric films, the compressive strain leads to a broad and frequency-dispersive phase transition at lower temperature (125 – 147 K). This could be either a new transition or a shift in temperature of a known transition. Considering the broadness and frequency dispersion of the transition, this is actually a transition from the dielectric state at high temperature to a relaxor-type ferroelectric state at low temperature. The latter is based on the formation of polar nano-regions (PNRs). Using the electric field dependence of the freezing temperature, allows a direct estimation of the volume (70 to 270 nm3) and diameter (5.2 to 8 nm, spherical approximation) of the PNRs. The values confirm with literature values which were measured by other technologies. -In case of the off-stoichiometric samples, we observe again the classical ferroelectric behavior. However, the thermally hysteretic phase transition which is observed around 620 – 660 K for unstrained material is shifted to room temperature due to the compressive strain. Beside to the temperature shift, the temperature dependence of the permittivity is nearly identical for strained and unstrained materials. -The last but not least, in all cases, a significant anisotropy in the electronic and structural properties is observed which arises automatically from the anisotropic strain caused by the orthorhombic structure of the substrate. However, this anisotropy cannot be explained by the classical model which tries to fit an orthorhombic film onto an orthorhombic substrate. A novel “square lattice” model in which the films adapt a “square” shaped lattice in the plane of the film during the epitaxial growth at elevated temperature (~1000 K) nicely explains the experimental results. In this thesis we sketch a way to manipulate the ferroelectricity of NaNbO3 films via strain and stoichiometry. The results indicate that compressive strain which is generated by the epitaxial growth of the film on mismatched substrate is able to reduce the ferroelectric transition temperature or induce a phase transition at low temperature. Moreover, by adding Na in the NaNbO3 film a secondary phase Na3NbO4 is formed which seems to stabilize the main phase NaNbO3 and the strain and, thus, is able to engineer the ferroelectric behavior from the expected classical ferroelectric for perfect stoichiometry to relaxor-type ferroelectric for slightly off-stoichiometry, back to classical ferroelectric for larger off-stoichiometry. Both strain and stoichiometry are proven as perfect methods to optimize the ferroelectric properties of oxide films.

Hilbert Space Valued Signal Plus Noise Models: Analysis of Structural Breaks under High Dimensionality and Temporal Dependence

This thesis is concerned with change point analysis for time series, i.e. with detection of structural breaks in time-ordered, random data. This long-standing research field regained popularity over the last few years and is still undergoing, as statistical analysis in general, a transformation to high-dimensional problems. We focus on the fundamental »change in the mean« problem and provide extensions of the classical non-parametric Darling-Erdős-type cumulative sum (CUSUM) testing and estimation theory within highdimensional Hilbert space settings. In the first part we contribute to (long run) principal component based testing methods for Hilbert space valued time series under a rather broad (abrupt, epidemic, gradual, multiple) change setting and under dependence. For the dependence structure we consider either traditional m-dependence assumptions or more recently developed m-approximability conditions which cover, e.g., MA, AR and ARCH models. We derive Gumbel and Brownian bridge type approximations of the distribution of the test statistic under the null hypothesis of no change and consistency conditions under the alternative. A new formulation of the test statistic using projections on subspaces allows us to simplify the standard proof techniques and to weaken common assumptions on the covariance structure. Furthermore, we propose to adjust the principal components by an implicit estimation of a (possible) change direction. This approach adds flexibility to projection based methods, weakens typical technical conditions and provides better consistency properties under the alternative. In the second part we contribute to estimation methods for common changes in the means of panels of Hilbert space valued time series. We analyze weighted CUSUM estimates within a recently proposed »high-dimensional low sample size (HDLSS)« framework, where the sample size is fixed but the number of panels increases. We derive sharp conditions on »pointwise asymptotic accuracy« or »uniform asymptotic accuracy« of those estimates in terms of the weighting function. Particularly, we prove that a covariance-based correction of Darling-Erdős-type CUSUM estimates is required to guarantee uniform asymptotic accuracy under moderate dependence conditions within panels and that these conditions are fulfilled, e.g., by any MA(1) time series. As a counterexample we show that for AR(1) time series, close to the non-stationary case, the dependence is too strong and uniform asymptotic accuracy cannot be ensured. Finally, we conduct simulations to demonstrate that our results are practically applicable and that our methodological suggestions are advantageous.

Quantifying recreational shore angling catch and harvest in southern Portugal (north-east Atlantic Ocean): implications for conservation and integrated fisheries management

Recreational shore fishing along 250 km of the south and south-west coast of Portugal was studied based on roving creel and aerial surveys. Surveys were conducted between August 2006 and July 2007, following a stratified random-sampling design and provided information on catch and effort, harvest and discards, angler demographics and fishing habits. Overall, 192 roving creel surveys, 24 aerial surveys and 1321 interviews were conducted. Based on the aerial surveys, a mean +/- s.e. total fishing effort of 705 236 +/- 32 765 angler h year(-1) was estimated, corresponding to 166 430 +/- 9792 fishing trips year(-1). Average time spent per fishing trip was 4.7 h. A total of 48 species, belonging to 22 families, were recorded in roving creel surveys. The most important species was Diplodus sargus, accounting for 44% of the total catches by number and 48% by mass. Estimated mean +/- s.e. total annual recreational shore fishing catch was 160.2 +/- 12.6 t year(-1) (788 049 +/- 54 079 fishes year(-1)), of which 147.4 +/- 11.9 t year(-1) (589 132 +/- 42 360 fishes year(-1)) was retained. Although overall shore-based recreational catches only corresponded to 0.8% of the commercial landings (only common species considered), D. sargus catches by recreational shore anglers were considerable, corresponding to 65% of the commercial landings. The implications of these results for integrated fisheries management and conservation are discussed, and future research proposed.

Methods for integrating machine learning and constrained optimization

In the framework of industrial problems, the application of Constrained Optimization is known to have overall very good modeling capability and performance and stands as one of the most powerful, explored, and exploited tool to address prescriptive tasks. The number of applications is huge, ranging from logistics to transportation, packing, production, telecommunication, scheduling, and much more. The main reason behind this success is to be found in the remarkable effort put in the last decades by the OR community to develop realistic models and devise exact or approximate methods to solve the largest variety of constrained or combinatorial optimization problems, together with the spread of computational power and easily accessible OR software and resources. On the other hand, the technological advancements lead to a data wealth never seen before and increasingly push towards methods able to extract useful knowledge from them; among the data-driven methods, Machine Learning techniques appear to be one of the most promising, thanks to its successes in domains like Image Recognition, Natural Language Processes and playing games, but also the amount of research involved. The purpose of the present research is to study how Machine Learning and Constrained Optimization can be used together to achieve systems able to leverage the strengths of both methods: this would open the way to exploiting decades of research on resolution techniques for COPs and constructing models able to adapt and learn from available data. In the first part of this work, we survey the existing techniques and classify them according to the type, method, or scope of the integration; subsequently, we introduce a novel and general algorithm devised to inject knowledge into learning models through constraints, Moving Target. In the last part of the thesis, two applications stemming from real-world projects and done in collaboration with Optit will be presented.

Early-stage deformation localisation in thrust systems: new perspectives from carbonates in the Italian Southern Alps and Oman Mountains

This thesis investigates mechanisms and boundary conditions that steer the early localisation of deformation and strain in carbonate multilayers involved in thrust systems, under shallow and mid-crustal conditions. Much is already understood about deformation localisation, but some key points remain loosely constrained. They encompass i) the understanding of which structural domains can preserve evidence of early stages of tectonic shortening, ii) the recognition of which mechanisms assist deformation during these stages and iii) the identification of parameters that actually steer the beginning of localisation. To clarify these points, the thesis presents the results of an integrated, multiscale and multi-technique structural study that relied on field and laboratory data to analyse the structural, architectural, mineralogical and geochemical features that govern deformation during compressional tectonics. By focusing on two case studies, the Eastern Southern Alps (northern Italy), where deformation is mainly brittle, and the Oman Mountains (northeastern Oman), where ductile deformation dominates, the thesis shows that the deformation localisation is steered by several mechanisms that mutually interact at different stages during compression. At shallow crustal conditions, derived conceptual and numerical models show that both inherited (e.g., stratigraphic) and acquired (e.g., structural) features play a key role in steering deformation and differentiating the seismic behaviour of the multilayer succession. At the same time, at deeper crustal conditions, strain localises in narrow domains in which fluids, temperature, shear strain and pressure act together during the development of the internal fabric and the chemical composition of mylonitic shear zones, in which localisation took place under high-pressure (HP) and low-temperature (LT) conditions. In particular, results indicate that those shear zones acted as “sheltering structural capsules” in which peculiar processes can happen and where the results of these processes can be successively preserved even over hundreds of millions of years.

Data surveillance for infectious diseases: models, complex networks and machine learning

In this thesis, we investigate the role of applied physics in epidemiological surveillance through the application of mathematical models, network science and machine learning. The spread of a communicable disease depends on many biological, social, and health factors. The large masses of data available make it possible, on the one hand, to monitor the evolution and spread of pathogenic organisms; on the other hand, to study the behavior of people, their opinions and habits. Presented here are three lines of research in which an attempt was made to solve real epidemiological problems through data analysis and the use of statistical and mathematical models. In Chapter 1, we applied language-inspired Deep Learning models to transform influenza protein sequences into vectors encoding their information content. We then attempted to reconstruct the antigenic properties of different viral strains using regression models and to identify the mutations responsible for vaccine escape. In Chapter 2, we constructed a compartmental model to describe the spread of a bacterium within a hospital ward. The model was informed and validated on time series of clinical measurements, and a sensitivity analysis was used to assess the impact of different control measures. Finally (Chapter 3) we reconstructed the network of retweets among COVID-19 themed Twitter users in the early months of the SARS-CoV-2 pandemic. By means of community detection algorithms and centrality measures, we characterized users’ attention shifts in the network, showing that scientific communities, initially the most retweeted, lost influence over time to national political communities. In the Conclusion, we highlighted the importance of the work done in light of the main contemporary challenges for epidemiological surveillance. In particular, we present reflections on the importance of nowcasting and forecasting, the relationship between data and scientific research, and the need to unite the different scales of epidemiological surveillance.

Anaerobic And Aerobic Performances In Elite Basketball Players.

THE PURPOSE OF THIS STUDY WAS TO PROPOSE A SPECIFIC LACTATE MINIMUM TEST FOR ELITE BASKETBALL PLAYERS CONSIDERING THE: Running Anaerobic Sprint Test (RAST) as a hyperlactatemia inductor, short distances (specific distance, 20 m) during progressive intensity and mathematical analysis to interpret aerobic and anaerobic variables. The basketball players were assigned to four groups: All positions (n=26), Guard (n= 7), Forward (n=11) and Center (n=8). The hyperlactatemia elevation (RAST) method consisted of 6 maximum sprints over 35 m separated by 10 s of recovery. The progressive phase of the lactate minimum test consisted of 5 stages controlled by an electronic metronome (8.0, 9.0, 10.0, 11.0 and 12.0 km/h) over a 20 m distance. The RAST variables and the lactate values were analyzed using visual and mathematical models. The intensity of the lactate minimum test, determined by a visual method, reduced in relation to polynomial fits (2nd degree) for the Small Forward positions and General groups. The Power and Fatigue Index values, determined by both methods, visual and 3rd degree polynomial, were not significantly different between the groups. In conclusion, the RAST is an excellent hyperlactatemia inductor and the progressive intensity of lactate minimum test using short distances (20 m) can be specifically used to evaluate the aerobic capacity of basketball players. In addition, no differences were observed between the visual and polynomial methods for RAST variables, but lactate minimum intensity was influenced by the method of analysis.

The relationship between birth weight and insulin resistance in childhood

Chronic diseases that are typical of adulthood may originate in intra-uterine life through inadequate fetal development. The present epidemiological cohort study of 506 healthy children aged 5\20138 years evaluated the relationship between birth weight and insulin resistance in an age group that has been assessed in few similar studies. Insulin concentration was determined by chemiluminescence and insulin resistance by the homeostasis model assessment (HOMA). Blood glucose, total cholesterol and fractions (LDL cholesterol and HDL cholesterol) and TAG concentrations were determined by automated enzymatic methods. Linear regression analysis investigated the relationship between birth weight (assessed as a continuous variable and in three categories: small for gestational age, SGA; adequate for gestational age and large for gestational age) and the HOMA index, using backward stepwise selection and biological models to explain the causal pathway of the relationship. There were negativeassociations between birth weight (P < 0·001), SGA (P = 0·027) and the HOMA index, and a positive association between waist circumference (P < 0·001) and the HOMA index. Considering the significant associations between birth weight and waist circumference (P < 0·001) and waist circumference and insulin resistance (P < 0·001), we can probably suspect that lower birth weight is a common cause of higher waist circumference and insulin resistance. In summary, the results of the present study showed increased insulin resistance in apparently healthy, young children, who had lower weight at birth and higher measurements of waist circumference. There is a need to develop public health policies that adopt preventive measures to promote adequate maternal-fetal and child development and enable early diagnosis of metabolic abnormalities

Non-additive genetic effects on weights and performance of a Brazilian Bos taurus x Bos indicus beef composite

The aim of the present study was to evaluate the heterosis effects on weaning weight at 205 days (WW, N = 146,464), yearling weight at 390 days (YW, N = 69,315) and weight gain from weaning to yearling (WG, N = 59,307) in composite beef cattle. The fixed models were: RM, which included contemporary groups, class of age of dam, outcrossing percentages for direct and maternal effects, and additive direct and maternal ( AM) breed effects; R, RM model, minus AM breed effects, and H, RM model, minus additive breed effects. The estimates for W205 were in general positive (P < 0.01). The R and H models resulted in similar estimates, but they were very different from the ones estimated by the RM model. For W390, the R and H models resulted in general positive estimates (P < 0.05). For WG, the RM model resulted in general significant heterosis effects (P < 0.05). It can be concluded that the RM model seems to supply estimates of better quality (P < 0.01).

uvby-beta photometry of solar twins The solar colors, model atmospheres, and the T(eff) and metallicity scales

Aims. Solar colors have been determined on the uvby-beta photometric system to test absolute solar fluxes, to examine colors predicted by model atmospheres as a function of stellar parameters (T(eff), log g, [Fe/H]), and to probe zero-points of T(eff) and metallicity scales. Methods. New uvby-beta photometry is presented for 73 solar-twin candidates. Most stars of our sample have also been observed spectroscopically to obtain accurate stellar parameters. Using the stars that most closely resemble the Sun, and complementing our data with photometry available in the literature, the solar colors on the uvby-beta system have been inferred. Our solar colors are compared with synthetic solar colors computed from absolute solar spectra and from the latest Kurucz (ATLAS9) and MARCS model atmospheres. The zero-points of different T(eff) and metallicity scales are verified and corrections are proposed. Results. Our solar colors are (b - y)(circle dot) = 0.4105 +/- 0.0015, m(1,circle dot) = 0.2122 +/- 0.0018, c(1,circle dot) = 0.3319 +/- 0.0054, and beta(circle dot) = 2.5915 +/- 0.0024. The (b - y)(circle dot) and m(1,circle dot) colors obtained from absolute spectrophotometry of the Sun agree within 3-sigma with the solar colors derived here when the photometric zero-points are determined from either the STIS HST observations of Vega or an ATLAS9 Vega model, but the c(1,circle dot) and beta(circle dot) synthetic colors inferred from absolute solar spectra agree with our solar colors only when the zero-points based on the ATLAS9 model are adopted. The Kurucz solar model provides a better fit to our observations than the MARCS model. For photometric values computed from the Kurucz models, (b - y)(circle dot) and m(1,circle dot) are in excellent agreement with our solar colors independently of the adopted zero-points, but for c(1,circle dot) and beta circle dot agreement is found only when adopting the ATLAS9 zero-points. The c(1,circle dot) color computed from both the Kurucz and MARCS models is the most discrepant, probably revealing problems either with the models or observations in the u band. The T(eff) calibration of Alonso and collaborators has the poorest performance (similar to 140 K off), while the relation of Casagrande and collaborators is the most accurate (within 10 K). We confirm that the Ramirez & Melendez uvby metallicity calibration, recommended by Arnadottir and collaborators to obtain [Fe/H] in F, G, and K dwarfs, needs a small (similar to 10%) zero-point correction to place the stars and the Sun on the same metallicity scale. Finally, we confirm that the c(1) index in solar analogs has a strong metallicity sensitivity.

Chemical similarities between Galactic bulge and local thick disk red giants: O, Na, Mg, Al, Si, Ca, and Ti

Context. The formation and evolution of the Galactic bulge and its relationship with the other Galactic populations is still poorly understood. Aims. To establish the chemical differences and similarities between the bulge and other stellar populations, we performed an elemental abundance analysis of alpha- (O, Mg, Si, Ca, and Ti) and Z-odd (Na and Al) elements of red giant stars in the bulge as well as of local thin disk, thick disk and halo giants. Methods. We use high-resolution optical spectra of 25 bulge giants in Baade's window and 55 comparison giants (4 halo, 29 thin disk and 22 thick disk giants) in the solar neighborhood. All stars have similar stellar parameters but cover a broad range in metallicity (-1.5 < [Fe/H] < +0.5). A standard 1D local thermodynamic equilibrium analysis using both Kurucz and MARCS models yielded the abundances of O, Na, Mg, Al, Si, Ca, Ti and Fe. Our homogeneous and differential analysis of the Galactic stellar populations ensured that systematic errors were minimized. Results. We confirm the well-established differences for [alpha/Fe] at a given metallicity between the local thin and thick disks. For all the elements investigated, we find no chemical distinction between the bulge and the local thick disk, in agreement with our previous study of C, N and O but in contrast to other groups relying on literature values for nearby disk dwarf stars. For -1.5 < [Fe/H] < -0.3 exactly the same trend is followed by both the bulge and thick disk stars, with a star-to-star scatter of only 0.03 dex. Furthermore, both populations share the location of the knee in the [alpha/Fe] vs. [Fe/H] diagram. It still remains to be confirmed that the local thick disk extends to super-solar metallicities as is the case for the bulge. These are the most stringent constraints to date on the chemical similarity of these stellar populations. Conclusions. Our findings suggest that the bulge and local thick disk stars experienced similar formation timescales, star formation rates and initial mass functions, confirming thus the main outcomes of our previous homogeneous analysis of [O/Fe] from infrared spectra for nearly the same sample. The identical a-enhancements of thick disk and bulge stars may reflect a rapid chemical evolution taking place before the bulge and thick disk structures we see today were formed, or it may reflect Galactic orbital migration of inner disk/bulge stars resulting in stars in the solar neighborhood with thick-disk kinematics.