Investigating the impacts of street environment on pre-owned housing price in Shanghai using street-level images

[EN] Studies considering street environment quality’s impact on housing value were limited to top-down variables such as the green ratio measured from satellite maps. In contrast, this study quantified street views’ impacts on the value of second-hand commodity residential properties in Shanghai based on analysis of street view imagery. (1) It applied computer vision to objectively measure street features from largely accessible street view imagery. (2) Based on the classical urban design measures frameworks, it applied machine learning to evaluate human perceived street quality as street scores systematically, in contrast to the common practice of doing so in a more intuition-based fashion. (3) It further identified important indicators from both human-centered street scores as well as the more objective street feature measures with positive or adverse effects on property values based on a hedonic modeling method. The estimation suggested both street scores and features are significant and nonnegligible. For the perceived street scores (from 0-10 scale), neighborhoods with a unit increase in their “enclosure” or “safety” score enjoy price premium of 0.3% to 0.6%. Meanwhile, streets with 10% greater tree canopy exposure are attributable to a 0.2% increase in the property value. This study enriched our current understanding at a micro level of the factors that impact property values from the perspective of the built environment. It introduced human-centered perception of street scores and objective measures of street features as spatial variables into the analysis of neighborhood attribute vectors.Qiu, W.; Huang, X.; Li, X.; Li, W.; Zhang, Z. (2020). Investigating the impacts of street environment on pre-owned housing price in Shanghai using street-level images. Editorial Universitat Politècnica de València. 29-39. https://doi.org/10.4995/CARMA2020.2020.11410OCS293

Enhancement of Heat-Cured Cement Paste with Tannic Acid

The Improvement of Cement-Based Materials\u27 Performance by Natural Organic Compounds Can Greatly Promote the Green and Sustainable Development of the Construction Industry. However, Such Compounds Are Not Widely Used Yet Because of their Retarding Effect on Cement. in This Study, the Retardation Effect of Tannic Acid (TA, a Well-Known Retarding Compound) is overcome and the Enhancing Effect is Achieved by Adding Less Than 0.1% Content and Curing Samples in Thermal Regime. Then the Mechanism of TA Enhancing Heat-Cured Cement Pastes is Studied Systematically. Mechanical Properties Results Suggest that Addition of 0.025% TA Can Reduce the Compressive and Flexural Strengths of Cement Pastes by Up to 3.4% and 17.1% under Normal Curing Regime at 3 Days, But Enhance These Two Strengths by More Than 11.4% and 34.6% after Thermal Curing, Respectively. XRD Patterns and TGA Analysis Indicate that, under Thermal Curing Regime, 0.025% TA Can Improve the Hydration Degree of Cement Where the Bound Water Content is Increased by 21.4%. SEM Observations and MIP Results Show that TA Can Compact the Microstructure and the Porosity is Decreased by More Than 7.0%. Furthermore, FTIR Spectrums Prove that TA Can Bond with Hydration Products. Molecular Dynamics Simulation Demonstrates that TA Cross-Links with Calcium Silicate Hydrates (C–S–H) through Ionic and Hydrogen Bonds, Which Could Increase the Tensile Strength by 12.5% and the Ultimate Strain by 100%

Wavelet Power and Shannon Entropy Applied to Acoustic Emission Signals for Corrosion Detection and Evaluation of Reinforced Concrete

Acoustic emission (AE) signals detected from corrosion test on a steel reinforced concrete beam subjected to the coupling effects of corrosive wet-dry cycles and static load are analyzed by power spectral density, wavelet transform, and Shannon entropy. The degradation process of the corroded reinforced concrete beam can be divided into four stages on the basis of the accumulated event number (AEN). Due to the difference of material properties, steel reinforcement and concrete matrix have distinguished AE features. The time-frequency characteristics of AE signals can reflect the microstructural degradation mechanism of steel corrosion and concrete cracking. The corrosion evaluation entails investigating the evolution of the wavelet power mathematically by Shannon entropy. The frequency-entropy clearly exhibits the relative power distribution of AE signal in a certain frequency region. With the accumulation of steel corrosion and concrete deterioration, the increment of the overall entropy integration is considerably apparent. The variation of frequency-entropy curve reveals the corrosion revolution of the reinforced concrete members under static load, which is represented by a transforming from corrosion-induced micro cracking to load-induced localized cracking

Structure basis for the unique specificity of medaka enteropeptidase light chain

Thermal stresses concern not renewed type of stresses, that is once having liberated, they cannot accumulate more. The estimation of purely thermoelastic contribution to a lithosphere stress state gives the additional information, allowing to predict the danger connected with such natural factors, as seismic and volcanic activity. Some theoretical thermoelastic problems for the geological environment of a difficult outline with non-uniform thermophysical characteristics are considered. The decision is received on the basis of a numerical finite elements method. Influence of the model fixation, the geometrical factor and boundary conditions on distribution of thermal stresses and dislocation is investigated. Computing experiments have shown, that the size of the maximum thermal stresses reaches 500 bar. The maximum values of vertical dislocation are reached by 90 m, and horizontal — 50 m. Neutral plane position are precisely defined. Термоупругие напряжения относятся к невозобновляемому типу напряжений, то есть, однажды высвободившись, напряжения не могут накапливаться вновь. Расчет термоупругого вклада в напряженное состояние литосферы дает дополнительную информацию, позволяющую оценить опасность, связанную с такими природными явлениями, как сейсмичность и вулканическая активность. Рассмотрено несколько теоретических моделей для геологической среды сложного очертания с неоднородными теплофизическими характеристиками. Решение получено на основе численного метода конечных элементов. Исследовано влияние «закрепления» модели, геометрического фактора, неоднородных граничных условий на распределение термоупругих напряжений и перемещений. Вычислительные эксперименты показали, что величина максимальных термоупругих напряжений достигает 500 б. Максимальные величины вертикальных перемещений не превышают 90 м, горизонтальных — 50 м. Положение нейтральной плоскости определяется точно. На основі методу скінченних елементів отримано детальний розподіл термопружних напружень і переміщень для неоднорідного геологічного середовища. Досліджено взаємний вплив геометрії середовища й неоднорідних граничних умов на розподіл термопружних напружень та переміщень

Data and Knowledge Co-driving for Cancer Subtype Classification on Multi-Scale Histopathological Slides

Artificial intelligence-enabled histopathological data analysis has become a valuable assistant to the pathologist. However, existing models lack representation and inference abilities compared with those of pathologists, especially in cancer subtype diagnosis, which is unconvincing in clinical practice. For instance, pathologists typically observe the lesions of a slide from global to local, and then can give a diagnosis based on their knowledge and experience. In this paper, we propose a Data and Knowledge Co-driving (D&K) model to replicate the process of cancer subtype classification on a histopathological slide like a pathologist. Specifically, in the data-driven module, the bagging mechanism in ensemble learning is leveraged to integrate the histological features from various bags extracted by the embedding representation unit. Furthermore, a knowledge-driven module is established based on the Gestalt principle in psychology to build the three-dimensional (3D) expert knowledge space and map histological features into this space for metric. Then, the diagnosis can be made according to the Euclidean distance between them. Extensive experimental results on both public and in-house datasets demonstrate that the D&K model has a high performance and credible results compared with the state-of-the-art methods for diagnosing histopathological subtypes. Code: https://github.com/Dennis-YB/Data-and-Knowledge-Co-driving-for-Cancer-Subtypes-Classificatio

Integrated energy system optimization and scheduling method considering the source and load coordinated scheduling of thermal-storage electric boilers and electric vehicles

The northern regions of China face the challenges of the mismatch of the power supply and demand, as well as serious wind curtailment issues, caused mainly by the limitation of the “with heat to determine electricity” mode for combined heat and power generation during the winter season. To further absorb the surplus wind power and alleviate restrictions, a comprehensive energy system optimization method for parks based on coordinated scheduling between sources and loads is proposed in this paper. First, the implementation of a heat-storage electric boiler on the source side further achieves the decoupling of heat and power. Second, an optimized scheduling method for electric vehicles combining incentive scheduling and orderly scheduling is proposed on the load side, which helps flatten the load curve. Finally, a tiered carbon trading mechanism is introduced and a community integrated energy system (CIES) optimization scheduling model is established with the aim of minimizing the total cost of the CIES, and the problem is solved using the CPLEX commercial solver. The simulation results indicate that the overall system efficiency is significantly improved through the coordinated scheduling of power sources and loads. Specifically, the integration rate of wind power increases by 3.91% when compared to the sole consideration of the integrated demand response. Furthermore, the peak shaving and off-peak filling effect is considerably enhanced compared to the utilization of only thermal-storage electric boilers. Additionally, the implementation of coordinated scheduling leads to a reduction in the total system cost by 2764.32 yuan and a decrease in total carbon emissions by 3515.4 kg. These findings provide compelling evidence that the coordinated scheduling of power sources and loads surpasses the limitations of thermal power units, strengthens the demand response capability of electric vehicles, and enhances the economic benefits of the CIES

Stabilization for a class of rectangular descriptor systems via time delayed dynamic compensator

Abstract: This paper focuses on the stabilization problem for a class of rectangular descriptor systems through dynamic compensation. Such class of systems may not be stabilized by delayfree dynamic compensators, while delayed dynamic compensator could achieve such purpose. We provide a design scheme of time-delayed dynamic compensator which makes the closed-loop system admissible. The design involves solving a quadratic matrix inequality, and consequently, we build a linear matrix inequality (LMI) based algorithm to compute compensator gains. We verify that, under certain circumstances for which delay-free dynamic compensators fail to stabilize, the proposed method works well. An illustrative example demonstrates the usefulness of the present scheme