MACRO DYNAMICS OF THE REAL ESTATE MARKET VALUE: TEMPORAL EFFECTS

The aim of this research is to establish a methodological background for understating the real estate macro dynamics and the role played by architecture in explaining the real estate market value fluctuations. Although various models of the housing market fluctuations have been developed, the fundamental question of what drives the real estate market value is still peculiarly neglected. Housing market value fluctuations can be largely explained by macroeconomic fundamentals, housing market indicators as well as the social, political and cultural situation. After assessing these fundamentals of the real estate market value, other factors may be added such as short-term dynamics and irrational factors, contributing to an instantaneous unpredictability of the real estate market. Nowadays there is a belief in society that housing is an investment opportunity. An assumption can be made about the speculative and irrational nature of the housing market, having impact on the real estate market value. Comparing the housing market to the stock market, the housing market has much higher cost of carry and complicated administration to it; and therefore, the real estate market is highly inefficient. Because of the irrational nature of human behavior, similarly to stock prices, the housing market is driven by expectations. The originality of this research lies in the fact that irrationality of human behavior suggests looking at other sciences, with architecture being a tool to bring those irrationalities into the real estate market. Given that behavioral economics accounts for a significant part of irrationality of market behavior, the hypothesis can be ventured that architecture, as a human interaction in the process, can have its own causal role in fixing real estate market value

Towards high-fidelity microwave driven multi-qubit gates on microfabricated surface ion traps

For quantum computers to become a reality, high-fidelity logic gates are required to be implemented on a scalable architecture. The IQT group follows an approach based on using a magnetic field gradient and microwave radiation to implement the required operations. To demonstrate their scalability to many quantum bit systems, these operations need to be implemented on micro-fabricated surface ion traps. In this thesis I describe the technologies I developed for surface ion traps with magnetic field gradients. This entailed the design, assembly and operation of two surface ion trap systems with permanent magnets for generating large magnetic field gradients of 140T=m, novel in-vacuum radio-frequency and microwave emitters for implementing high-speed quantum state manipulation and development of robust and reliable laser control systems required for stable long-term experimental operation

Predicting molecular vibronic spectra using time-domain analog quantum simulation

Spectroscopy is one of the most accurate probes of the molecular world. However, predicting molecular spectra accurately is computationally difficult because of the presence of entanglement between electronic and nuclear degrees of freedom. Although quantum computers promise to reduce this computational cost, existing quantum approaches rely on combining signals from individual eigenstates, an approach that is difficult to scale because the number of eigenstates grows exponentially with molecule size. Here, we introduce a method for scalable analog quantum simulation of molecular spectroscopy, by performing simulations in the time domain. Our approach can treat more complicated molecular models than previous ones, requires fewer approximations, and can be extended to open quantum systems with minimal overhead. We present a direct mapping of the underlying problem of time-domain simulation of molecular spectra to the degrees of freedom and control fields available in a trapped-ion quantum simulator. We experimentally demonstrate our algorithm on a trapped-ion device, exploiting both intrinsic electronic and motional degrees of freedom, showing excellent quantitative agreement for a single-mode vibronic photoelectron spectrum of SO$_2$.Comment: 13 pages, 8 figure

Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Strategic planning: balance between public space, maritime sector and its impact on shadow economy

The balance between real estate developments and infrastructure of maritime sector in the coastal area of a city is explored in this study. Network of public spaces, maritime sector and its impact on shadow economy are main objectives of this research. New real estate developments next to water have valuable benefits resulting in overall attractiveness of cityscape. However, coordination between strategic city planning, urban design and maritime sector is required to achieve best results. Also, inferior planning of ports and other maritime infrastructure could lead to increased shadow economy, which makes significant negative impact on overall economy and in-turn ability to successfully develop further public space

Macro dynamics of the real estate market value: temporal effects

The aim of this research is to establish a methodological background for understating the real estate macro dynamics and the role played by architecture in explaining the real estate market value fluctuations. Although various models of the housing market fluctuations have been developed, the fundamental question of what drives the real estate market value is still peculiarly neglected. Housing market value fluctuations can be largely explained by macroeconomic fundamentals, housing market indicators as well as the social, political and cultural situation. After assessing these undamentals of the real estate market value, other factors may be added such as short-term dynamics and irrational factors, contributing to an instantaneous unpredictability of the real estate market. Nowadays there is a belief in society that housing is an investment opportunity. An assumption can be made about the speculative and irrational nature of the housing market, having impact on the real estate market value. Comparing the housing market to the stock market, the housing market has much higher cost of carry and complicated administration to it; and therefore, the real estate market is highly inefficient. Because of the irrational nature of human behavior, similarly to stock prices, the housing market is driven by expectations. The originality of this research lies in the fact that irrationality of human behavior suggests looking at other sciences, with architecture being a tool to bring those irrationalities into the real estate market. Given that behavioral economics accounts for a significant part of irrationality of market behavior, the hypothesis can be ventured that architecture, as a human interaction in the process, can have its own causal role in fixing real estate market value

Microeconomics of architecture: between market and public

The position of architecture between market goods and public goods is addressed in this study. A transition of architectural objects of built environment from market goods towards public or nonmarket goods is presented in literature review. The real estate market value is highly influenced by concepts of externalities and public goods, therefore being highly spatially dependent and making the process of the real estate valuation more complex. The internalization of these externalities and public goods is impossible because of the nature of public space in the city. The concept of value and different types of value, like exchange, use, image, social, environmental, cultural value, are also presented in literature review. These different types of value are transferred to value in exchange when estimating market value. The aim of research is to calculate the amount of the real estate market value that is influenced by externalities, public or nonmarket goods. The process of value transfers between market and public is also discussed in this study. In the research part prices of similar apartments in cities of Kaunas, Vilnius and Klaipėda (Lithuania) are compared to measure the coefficient of variance. Newly constructed apartment buildings with partial finishing interior within city boundaries are selected expecting their price to vary only because of different amount of externalities and public goods available inside district/region of selected building or provided by the actual building itself. The results show that up to 29% of the real estate market value is influenced by public or nonmarket goods. Implications of further research suggest controlling for market segmentation and architectural quality variables

The identification of spatial bubbles in a real estate market

There is great interest in identifying and modelling real estate market bubbles over time. However, the spatial dimension of those bubbles gets less attention. While building on the theory of real estate market equilibrium and formation of market bubbles, this research focuses on the spatial bubbles of the market value of apartments inside a city. This approach adds another dimension to the phenomena of real estate market bubbles. The scientific problem of this study is whether the spatial differentiation of real estate encourages the formation of spatial bubbles in real estate market. The object of research is the spatial bubbles in real estate market. The aim of research is to identify the impact of spatial bubbles on real estate market value. Because of the nature of real estate market, the supply and demand of real estate does not match, therefore real estate almost never reaches the equilibrium market value and bubbles appear. The main idea behind this research is that the supply and demand equilibrium model can be applied not only to the changes over time but also across space inside a city. The spatial bubbles appear because of unexplained variance. The empirical research focuses on unexplained variance across space of market value of homogeneous apartments in two major cities in Lithuania. The prominent variance is eliminated through careful selection of projects and control variables such as floor and size of an apartment, distance to civic points and location. Up to 39% of unexplained variance of apartment market value across space was found when looking at 3D diagrams of residualised apartment market value of the selected cities. The main reasons behind formation of those spatial bubbles should be addressed by further research for deeper understanding of the phenomenon of spatial bubble formation