Developing an emulsion separation material with one-step in-situ purifying capacity and enhanced security in applications, particularly for further scale-up, is of great value but remains a challenge. Herein, the amphiphilic sponge (PA@RGO@MS) was prepared via impregnation and in-situ growth of...

Three-dimensional (3D) materials that capture sunlight for desalination provide one promising solution to acquaring freshwater resources, but salt deposition and mechanical stability provide additional hurdles for continuous operation. Herein, this study presents a sustainable and elastic...

The development of highly efficient adsorptive material for the selective capture of Pd(II), and re-utilization of spent Pd(II)-loaded adsorbent as an efficient catalyst for organic synthesis are of great significance, but challenging. Particularly, the heterogeneous palladium-catalyzed Suzuki...

To overcome the recovery challenge of nanoscale photocatalysts, great endeavor has been paid to explore effective nano-TiO2 immobilization approaches, but comprehensive comparison between these methods is still lacking. Herein, four approaches, namely impregnation-calcination, sol-gel,...

In view of the high cost and sparse spatial resolution of offshore meteorological observations, ocean winds retrieved from satellites are valuable in offshore wind resource assessment as a supplement to<i> in situ</i> measurements. This study examines satellite synthetic aperture radar (SAR) images...

Driving patterns exert an important influence on the fuel economy of vehicles, especially hybrid electric vehicles. This paper aims to build a method to identify driving patterns with enough accuracy and less sampling time compared than other driving pattern recognition algorithms. Firstly a...

In the standard data analysis framework, data is first collected (once for all), and then data analysis is carried out. Moreover, the data-generating process is typically assumed to be exogenous. This approach is natural when the data analyst has no impact on how the data is generated. The...

This dissertation studies the US real estate investment trust (REIT) market to empirically examine several conditions of the noise trader model (NTM) — a behavioral theory that purports to explain departures of listed property share prices from their net asset values (NAV spreads). First, we...

In this paper, we study endogeneity problems in algorithmic decision-making where data and actions are interdependent. When there are endogenous covariates in a contextual multi-armed bandit model, a novel bias (self-fulfilling bias) arises because the endogeneity of the covariates spills over...

Financial asset price movement impacts product demand and thus influences operational decisions of a firm. We develop and solve a general model that integrates financial risk hedging into a price-setting newsvendor. The optimal hedging strategy is found analytically, which leads to an explicit...