Pricing Factors in Real Estate Markets: A Simple Preference Based Approach

Conventional wisdom tells us that the price level of properties should be supported by the rent they receive. This paper examines the pricing factors of properties by analyzing how individuals allocate their income to housing consumption and other goods, which in turn become the rent (or implicit rent) to support property values. Our model’s results can explain several puzzling observations in property markets, including why the variance of property appreciation rates is much higher than that of income growth rates in the same area.Preference-based model, pricing factors, property appreciation, property markets

A Rational Explanation for Boom-and-Bust Price Patterns in Real Estate Markets

This paper develops a stylized model to provide a rational explanation for the boom-and-bust price movement pattern that we frequently observe in the real world. Our stylized model indicates that there are three conditions to form a boom-and-bust price pattern in a community: a move-in of high income residents, wide income gap between new and existing residents, and supply process that leads to an inventory buildup. It seems that, based on these three conditions, China is more likely to experience a boom-and-bust price movement pattern than a developed country with a more mature and less vibrant economy.Real Estate Cycles; Boom-and-Bust; Supply Decision; Moving Costs

Leveraging per Image-Token Consistency for Vision-Language Pre-training

Most existing vision-language pre-training (VLP) approaches adopt cross-modal masked language modeling (CMLM) to learn vision-language associations. However, we find that CMLM is insufficient for this purpose according to our observations: (1) Modality bias: a considerable amount of masked tokens in CMLM can be recovered with only the language information, ignoring the visual inputs. (2) Under-utilization of the unmasked tokens: CMLM primarily focuses on the masked token but it cannot simultaneously leverage other tokens to learn vision-language associations. To handle those limitations, we propose EPIC (lEveraging Per Image-Token Consistency for vision-language pre-training). In EPIC, for each image-sentence pair, we mask tokens that are salient to the image (i.e., Saliency-based Masking Strategy) and replace them with alternatives sampled from a language model (i.e., Inconsistent Token Generation Procedure), and then the model is required to determine for each token in the sentence whether they are consistent with the image (i.e., Image-Text Consistent Task). The proposed EPIC method is easily combined with pre-training methods. Extensive experiments show that the combination of the EPIC method and state-of-the-art pre-training approaches, including ViLT, ALBEF, METER, and X-VLM, leads to significant improvements on downstream tasks

Poly[(μ-5,7-dihydr­oxy-4-oxo-2-phenyl-4H-chromene-8-sulfonato)potassium(I)]

In the polymeric title compound, [K(C15H9O7S)]n, the potassium cation is five-coordinated by four sulfonate O atoms and one carbonyl O atom. Two intra­molecular O—H⋯O hydrogen bonds stabilize the conformation of the anion. The polymeric three-dimensional supra­molecular architecture is formed via coordination inter­actions and π–π stacking inter­actions involving centrosymmetrically related pyrone rings, with a centroid–centroid separation of 3.513 (2) Å

Ethyl 5,8-dibromo-2-dibromo­methyl-6,7-dimeth­oxyquinoline-3-carb­oxy­late

The title compound, C15H13Br4NO4, was obtained via radical bromination reaction of ethyl 6,7-dimeth­oxy-2-methyl­quinoline-3-carboxyl­ate and N-bromo­succinimide (NBS) in the presence of benzoyl peroxide (BPO) under photocatalytic conditions. The quinoline ring system is approximately planar with a maximum deviation from the mean plane of 0.035 (1) Å. The dihedral angle between the six-membered rings is 2.33 (2)°. The meth­oxy O atoms of the two neighboring meth­oxy groups are in-plane while their methyl C atoms are located on either side of the quinolyl ring plane at distances of −1.207 (1) and 1.223 (1) Å

Predictors of betel quid chewing behavior and cessation patterns in Taiwan aborigines

BACKGROUND: Betel quid, chewed by about 600 million people worldwide, is one of the most widely used addictive substances. Cessation factors in betel quid chewers are unknown. The present study explores prevalence and the quit rate of betel quid chewing in Taiwan aborigines. Our goal was to delineate potential predictors of chewing cessation. METHODS: A stratified random community-based survey was designed for the entire aborigines communities in Taiwan. A total of 7144 participants were included between June 2003 and May 2004 in this study. Information on sociodemographic characteristics, such as gender, age, obesity, education years, marital status, ethnicity, and habits of betel quid chewing, smoking and drinking was collected by trained interviewers. RESULTS: The prevalence of betel quid chewers was 46.1%. Betel quid chewing was closely associated with obesity (OR = 1.61; 95% CI: 1.40–1.85). Betel quid chewers were most likely to use alcohol and cigarettes together. Quit rate of betel quid chewers was 7.6%. Betel quid chewers who did not drink alcohol were more likely to quit (OR = 1.89; 95% CI: 1.43–2.50). Alcohol use is a significant factor related to cessation of betel quid chewing, but smoking is not. CONCLUSION: Taiwan aborigines have a high prevalence of betel quid chewers and a low quit rate. Alcohol use is strongly association with betel quid chewing. Efforts to reduce habitual alcohol consumption might be of benefit in cessation of betel quid chewing

Modeling of Nonlinear Aggregation for Information Fusion Systems with Outliers Based on the Choquet Integral

Modern information fusion systems essentially associate decision-making processes with multi-sensor systems. Precise decision-making processes depend upon aggregating useful information extracted from large numbers of messages or large datasets; meanwhile, the distributed multi-sensor systems which employ several geographically separated local sensors are required to provide sufficient messages or data with similar and/or dissimilar characteristics. These kinds of information fusion techniques have been widely investigated and used for implementing several information retrieval systems. However, the results obtained from the information fusion systems vary in different situations and performing intelligent aggregation and fusion of information from a distributed multi-source, multi-sensor network is essentially an optimization problem. A flexible and versatile framework which is able to solve complex global optimization problems is a valuable alternative to traditional information fusion. Furthermore, because of the highly dynamic and volatile nature of the information flow, a swift soft computing technique is imperative to satisfy the demands and challenges. In this paper, a nonlinear aggregation based on the Choquet integral (NACI) model is considered for information fusion systems that include outliers under inherent interaction among feature attributes. The estimation of interaction coefficients for the proposed model is also performed via a modified algorithm based on particle swarm optimization with quantum-behavior (QPSO) and the high breakdown value estimator, least trimmed squares (LTS). From simulation results, the proposed MQPSO algorithm with LTS (named LTS-MQPSO) readily corrects the deviations caused by outliers and swiftly achieves convergence in estimating the parameters of the proposed NACI model for the information fusion systems with outliers

A Multi-port Smart Transformer for Green Airport Electrification

Green transportation and renewable energy production have attracted a global attention due to the needs of decreasing the environmental impact and still sustain increased energy needs. In this framework, the aircraft and airports are facing a profound renovations towards green technologies, among which the electrical ones are playing a central role. This paper explores how a Smart Transformer can upgrade the existing airport power system, enabling an efficient interface for renewable energy, electric vehicles and the future hybrid/electric aircraft, substituting the ground power units and enabling a smarter behavior of the electrical grid