A Framework for Explaining Black–White Inequality in Homeownership Sustainability

Why do housing outcomes differ by race? To understand Black–White disparities in homeownership sustainability, this study proposes a conceptual framework that emphasizes Black homeowners’ socioeconomic challenges, challenges that go beyond the mortgage market, and focuses on the mediating role of liquid assets. Data from the Panel Study of Income Dynamics (PSID) enable a test of the framework through an examination of racial differences in the exit rates of homeowners during the recent housing crisis. The findings suggest that liquid assets played a significant role in such disparities. This is a pre-print of an article published in Demography. The final authenticated version is available online at https://doi.org/10.1007/s13524-020-00894-

Model and Integrate Medical Resource Available Times and Relationships in Verifiably Correct Executable Medical Best Practice Guideline Models (Extended Version)

Improving patient care safety is an ultimate objective for medical cyber-physical systems. A recent study shows that the patients' death rate is significantly reduced by computerizing medical best practice guidelines. Recent data also show that some morbidity and mortality in emergency care are directly caused by delayed or interrupted treatment due to lack of medical resources. However, medical guidelines usually do not provide guidance on medical resource demands and how to manage potential unexpected delays in resource availability. If medical resources are temporarily unavailable, safety properties in existing executable medical guideline models may fail which may cause increased risk to patients under care. The paper presents a separately model and jointly verify (SMJV) architecture to separately model medical resource available times and relationships and jointly verify safety properties of existing medical best practice guideline models with resource models being integrated in. The SMJV architecture allows medical staff to effectively manage medical resource demands and unexpected resource availability delays during emergency care. The separated modeling approach also allows different domain professionals to make independent model modifications, facilitates the management of frequent resource availability changes, and enables resource statechart reuse in multiple medical guideline models. A simplified stroke scenario is used as a case study to investigate the effectiveness and validity of the SMJV architecture. The case study indicates that the SMJV architecture is able to identify unsafe properties caused by unexpected resource delays.Comment: full version, 12 page

Significant late Jurassic counterclockwise rotations of the Yanshiping region, east North Qiangtang terrane, implication on Lhasa - Qiangtang initial collision

Abstract HKT-ISTP 2013 A

Control Strategy of Photovoltaic DC Microgrid Based on Fuzzy EEMD

In order to improve the accuracy of power time series regulation of DC microgrid photovoltaic power generation and its hybrid energy storage system, a set of empirical mode decomposition (EEMD) control strategy based on fuzzy algorithm optimization is proposed in this paper. Through EEMD decomposition of photovoltaic power data, a set of eigenmode component functions is obtained, the EEMD power decomposition method is designed, and the EEMD optimization fuzzy control strategy is established. Finally, the effectiveness and accuracy of the controller are verified by simulation experiments. The results show that compared with the ordinary EEMD power decomposition control method, the proposed method can achieve better control effect under different power fluctuation characteristics, improve the strong randomness and fluctuation of distributed generation fluctuation, and has strong applicability

Energy barrier at the N719-dye/CsSnI3 interface for photogenerated holes in dye-sensitized solar cells

This report is to address the question if black γ-polymorph of cesium tin tri-iodide (B-γ-CsSnI3) can be used as a solid-state hole-transport material in the conventional DSSCs with the N719 dye to replace the liquid electrolyte as reported by I. Chung et al. on Nature 485, 486, (2012). Here we demonstrate rigorously that B-γ-CsSnI3 is not energetically possible to collect photogenerated holes because of the large energy barrier at the interface of N719/B-γ-CsSnI3. Therefore, it cannot serve as a hole-transporter for the conventional DSSCs although it is a good hole-conducting material. A solution-based method was employed to synthesize the B-γ-CsSnI3 polycrystalline thin-films used for this work. These thin-films were then characterized by X-ray diffraction, Hall measurements, optical reflection, and photoluminescence (PL). Particularly, spatially resolved PL intensity images were taken after B-γ-CsSnI3 was incorporated in the DSSC structure to insure the material integrity. The means of ultraviolet photoemission spectroscopy (UPS) was used to reveal why B-γ-CsSnI3 could not act as the substitute of liquid electrolyte in the conventional DSSCs. For the completeness, other two related compounds, one is the yellow polymorph of CsSnI3 and other is Cs2SnI6 with tetravalent tin instead of double-valent tin in CsSnI3 were also investigated by UPS

An unsupervised domain adaptation method towards multi-level features and decision boundaries for cross-scene hyperspectral image classification.

Despite success in the same-scene hyperspectral image classification (HSIC), for the cross-scene classification, samples between source and target scenes are not drawn from the independent and identical distribution, resulting in significant performance degradation. To tackle this issue, a novel unsupervised domain adaptation (UDA) framework toward multilevel features and decision boundaries (ToMF-B) is proposed for the cross-scene HSIC, which can align task-related features and learn task-specific decision boundaries in parallel. Based on the maximum classifier discrepancy, a two-stage alignment scheme is proposed to bridge the interdomain gap and generate discriminative decision boundaries. In addition, to fully learn task-related and domain-confusing features, a convolutional neural network (CNN) and Transformer-based multilevel features extractor (generator) is developed to enrich the feature representation of two domains. Furthermore, to alleviate the harm even the negative transfer to UDA caused by task-irrelevant features, a task-oriented feature decomposition method is leveraged to enhance the task-related features while suppressing task-irrelevant features, and enabling the aligned domain-invariant features can be contributed to the classification task explicitly. Extensive experiments on three cross-scene HSI benchmarks have validated the effectiveness of the proposed framework

Engineering two-dimensional metal oxides and chalcogenides for enhanced electro- and photocatalysis

Two-dimensional (2D) metal oxides and chalcogenides (MOs & MCs) have been regarded as a new class of promising electro- and photocatalysts for many important chemical reactions such as hydrogen evolution reaction, CO2 reduction reaction and N2 reduction reaction in virtue of their outstanding physicochemical properties. However, pristine 2D MOs & MCs generally show the relatively poor catalytic performances due to the low electrical conductivity, few active sites and fast charge recombination. Therefore, considerable efforts have been devoted to engineering 2D MOs & MCs by rational structural design and chemical modification to further improve the catalytic activities. Herein, we comprehensively review the recent advances for engineering technologies of 2D MOs & MCs, which are mainly focused on the intercalation, doping, defects creation, facet design and compositing with functional materials. Meanwhile, the relationship between morphological, physicochemical, electronic, and optical properties of 2D MOs & MCs and their electro- and photocatalytic performances is also systematically discussed. Finally, we further give the prospect and challenge of the field and possible future research directions, aiming to inspire more research for achieving high-performance 2D MOs & MCs catalysts in energy storage and conversion fields