Short-term safety or long-term failure? Empirical evidence of the impact of securitization on bank risk

Based on a sample of U.S. commercial banks from 2002 to 2012, this paper shows that bank loan securitization has a significant and positive impact on both Z-scores and the likelihood of bank failure, indicating a short-term risk reduction and a long-term risk increase effect. We also find disparate impacts between mortgage and non-mortgage securitization. Loan sale activities are found to have a similar impact to securitization

Securitization and bank efficiency

We examine whether loan securitization has an impact on bank efficiency. Using a sample of large US commercial banks from 2002 to 2012, we find that bank loan securitization has a significant and positive impact on bank efficiency, and this relationship is stronger for banks with higher capital ratios, higher default risk, and lower level of liquidity and diversification. Our results are robust to Heckman self-selection correction and difference-in-difference (DID) analysis. In addition, these results are found mainly in non-mortgage loan securitizations but not in mortgage loan securitizations. Finally, we show that loan sales also have a positive impact on bank efficiency

Traditional Chinese Medicine syndrome-related herbal prescriptions in treatment of malignant tumors

AbstractObjectiveTo investigate the distribution characteristics of TCM syndromes and the related herbal prescriptions for malignant tumors (MT).MethodsA clinical database of the TCM syndromes and the herbal prescriptions in treatment of 136 MT patients were established. The data were then analyzed using cluster and frequency analysis.ResultsAccording to the cluster analysis, the TCM syndromes in MT patients mainly included two patterns: deficiency of both Qi and Yin and internal accumulation of toxic heat. The commonly-prescribed herbs were Huangqi (Astraglus), Nüzhenzi (Fructus Ligustri Lucidi), Lingzhi (Ganoderma Lucidum), Huaishan (Dioscorea Opposita), Xiakucao (Prunella Vulgaris), and Baihuasheshecao (Herba Hedyotidis).ConclusionDeficiency of Qi and Yin is the primary syndrome of MT, and internal accumulation of toxic heat is the secondary syndrome. The herbs for Qi supplementation and Yin nourishment are mainly used, with the assistance of herbs for heat-clearance and detoxification

Testbeds for Transition Metal Dichalcogenide Photonics: Efficacy of Light Emission Enhancement in Monomer vs. Dimer Nanoscale Antennae

Monolayer transition metal dichalcogenides are uniquely-qualified materials for photonics because they combine well defined tunable direct band gaps and selfpassivated surfaces without dangling bonds. However, the atomic thickness of these 2D materials results in low photo absorption limiting the achievable photo luminescence intensity. Such emission can, in principle, be enhanced via nanoscale antennae resulting in; a. an increased absorption cross-section enhancing pump efficiency, b. an acceleration of the internal emission rate via the Purcell factor mainly by reducing the antennas optical mode volume beyond the diffraction limit, and c. improved impedance matching of the emitter dipole to the freespace wavelength. Plasmonic dimer antennae show orders of magnitude hot-spot field enhancements when an emitter is positioned exactly at the midgap. However, a 2D material cannot be grown, or easily transferred, to reside in mid-gap of the metallic dimer cavity. In addition, a spacer layer between the cavity and the emissive material is required to avoid non-radiative recombination channels. Using both computational and experimental methods, in this work we show that the emission enhancement from a 2D emitter- monomer antenna cavity system rivals that of dimers at much reduced lithographic effort. We rationalize this finding by showing that the emission enhancement in dimer antennae does not specifically originate from the gap of the dimer cavity, but is an average effect originating from the effective cavity crosssection taken below each optical cavity where the emitting 2D film is located. In particular, we test an array of different dimer and monomer antenna geometries and observe a representative 3x higher emission for both monomer and dimer cavities as compared to intrinsic emission of Chemical Vapor Deposition synthesized WS2 flakes.Comment: 31 pages, 5 figure

Distribution and Variation of Mining-Induced Stress in the Reverse Fault-Affected Coal Body

This study aimed to explore the stress distribution and variation of reverse fault-affected mined coal body. A mechanical analysis model of the coal body in the reverse fault area was first established, then the coal body stress characterization equation was derived, and the stress distribution pattern on the coal body was calculated. Subsequently, applying the Mohr–Coulomb strength criterion revealed the following relationship: the closer is the distance to the reverse fault, the worse is the stability of the coal body, and that the coal body strength influences the stress concentration of the coal body in front of the working face. Moreover, simulation with FLAC3D was carried out to verify the coal body stress calculated by the mechanical model as well as the fluctuation of the coal body stress concentration. It could be concluded that while mining the hanging wall of the reverse fault, the stress concentration of mined coal body decreases with the increase of reverse fault dip angle, but increases with the increase of reverse fault throw; the stress concentration magnitude generated during footwall mining is lesser than that during hanging-wall mining. In other words, the magnitude of coal body stress concentration can be affected by the hanging wall and footwall mining, as well as parameters of the reverse fault. Finally, intrinsically safe GZY25 borehole stress sensors were used to monitor the coal body stresses in the reverse fault area under the influence of mining in Xinchun Coal Mine and ZuoQiuka Coal Mine. It was found that the coal body stress concentration in front of the working face either increased gradually or increased first before decreasing. It can be concluded that with the decrease of the distance between the working face and reverse fault, the vertical stress of the coal body increases, and the vertical stress of the coal body begins to increase obviously at a certain position. At this point, the vertical stress of the coal body can be generalized to 1.02–1.39 times of the initial vertical stress. Furthermore, the stress concentration coefficient of coal body is related to the distance from the reverse fault, and two changes occur: ① if the coal-bearing capacity does not exceed its strength, the coal stress in front of the working face increases gradually, and the stress concentration factor increases gradually; ② the stress concentration coefficient of mining coal body increases first, such that when the coal body bearing capacity exceeds its strength, the coal body fails and loses all its effective bearing capacity, followed by the decrease in coal body stress concentration coefficient

Development and evaluation of healthy cities

The Healthy Cities and Sustainable Development Goals are interlinked, and the Healthy Cities movement has received widespread response and support worldwide over the past 30 years. The European Healthy Cities Networks covers about 1,400 cities. China started the Healthy Cities Movement in 1994 and put forward the Healthy China Strategy in the report of 19th national congress of CPC. Based on the impact of COVID-19 and Henan floods on urban health, it is necessary to incorporate some unconventional indicators into the Healthy Cities evaluation indicator framework. In addition, structured data cannot fully describe certain indicators, so the collection of unstructured data is equally important

Short-term safety or long-term failure? Empirical evidence of the impact of securitization on bank risk

Based on a sample of U.S. commercial banks from 2002 to 2012, this paper shows that bank loan securitization has a significant and positive impact on both Z-scores and the likelihood of bank failure, indicating a short-term risk reduction and a long-term risk increase effect. We also find disparate impacts between mortgage and non-mortgage securitization. Loan sale activities are found to have a similar impact to securitization

Analysis of Factors Affecting the Severity of Automated Vehicle Crashes Using XGBoost Model Combining POI Data

The research and development of autonomous vehicle (AV) technology have been gaining ground globally. However, a few studies have performed an in-depth exploration of the contributing factors of crashes involving AVs. This study aims to predict the severity of crashes involving AVs and analyze the effects of the different factors on crash severity. Crash data were obtained from the AV-related crash reports presented to the California Department of Motor Vehicles in 2019 and included 75 uninjured and 18 injured accident cases. The points-of-interest (POI) data were collected from Google Map Application Programming Interface (API). Descriptive statistics analysis was applied to examine the features of crashes involving AVs in terms of collision type, crash severity, vehicle movement preceding the collision, and degree of vehicle damage. To compare the classification performance of different classifiers, we use two different classification models: eXtreme Gradient Boosting (XGBoost) and Classification and Regression Tree (CART). The result shows that the XGBoost model performs better in identifying the injured crashes involving AVs. Compared with the original XGBoost model, the recall and G-mean of the XGBoost model combining POI data improved by 100% and 11.1%, respectively. The main features that contribute to the severity of crashes include weather, degree of vehicle damage, accident location, and collision type. The results indicate that crash severity significantly increases if the AVs collided at an intersection under extreme weather conditions (e.g., fog and snow). Moreover, an accident resulting in injuries also had a higher probability of occurring in areas where land-use patterns are highly diverse. The knowledge gained from this research could ultimately contribute to assessing and improving the safety performance of the current AVs

Exploring the Mechanism of Crashes with Autonomous Vehicles Using Machine Learning

The safety issue has become a critical obstacle that cannot be ignored in the marketization of autonomous vehicles (AVs). The objective of this study is to explore the mechanism of AV-involved crashes and analyze the impact of each feature on crash severity. We use the Apriori algorithm to explore the causal relationship between multiple factors to explore the mechanism of crashes. We use various machine learning models, including support vector machine (SVM), classification and regression tree (CART), and eXtreme Gradient Boosting (XGBoost), to analyze the crash severity. Besides, we apply the Shapley Additive Explanations (SHAP) to interpret the importance of each factor. The results indicate that XGBoost obtains the best result (recall = 75%; G-mean = 67.82%). Both XGBoost and Apriori algorithm effectively provided meaningful insights about AV-involved crash characteristics and their relationship. Among all these features, vehicle damage, weather conditions, accident location, and driving mode are the most critical features. We found that most rear-end crashes are conventional vehicles bumping into the rear of AVs. Drivers should be extremely cautious when driving in fog, snow, and insufficient light. Besides, drivers should be careful when driving near intersections, especially in the autonomous driving mode