Digital Innovation in Organizational Research: A Systematic Review

As digital technologies penetrate and integrate into the industry, organizations are facing increasing pressures to apply digital innovation to update and transform their business models. To meet the growing need to guide the practice of digital innovation, progress have been made in the theoretical work of digital innovation management. However, due to digital innovation literature is increasing rapidly in recent years and research in different fields and disciplines is so fragmented, scholars are hard to have a general picture of digital innovation research. For the purpose of addressing this gap, this study tried to provide roadmap for the DI studies by answering the those questions: how digital innovation research evolved over time, how to understand the concept of digital innovation, and what research streams and opportunities exist in current digital innovation research. We conducted a systematic review with a hybrid methodology composed of bibliometric analysis and content analysis, covering the period 2010–2019. Results show that the current digital innovation research covers four perspectives: (1) connotation, process and outcome, (2) strategy, (3) resources, (4) organization and culture. Furthermore, we concluded research questions and opportunities for future research in different research fields

Donor–Acceptor Fluorophores for Energy-Transfer-Mediated Photocatalysis

Triplet–triplet energy transfer (EnT) is a fundamental activation pathway in photocatalysis. In this work, we report the mechanistic origins of the triplet excited state of carbazole-cyanobenzene donor–acceptor (D–A) fluorophores in EnT-based photocatalytic reactions and demonstrate the key factors that control the accessibility of the 3LE (locally excited triplet state) and 3CT (charge-transfer triplet state) via a combined photochemical and transient absorption spectroscopic study. We found that the energy order between 1CT (charge transfer singlet state) and 3LE dictates the accessibility of 3LE/3CT for EnT, which can be effectively engineered by varying solvent polarity and D–A character to depopulate 3LE and facilitate EnT from the chemically more tunable 3CT state for photosensitization. Following the above design principle, a new D–A fluorophore with strong D–A character and weak redox potential is identified, which exhibits high efficiency for Ni(II)-catalyzed cross-coupling of carboxylic acids and aryl halides with a wide substrate scope and high selectivity. Our results not only provide key fundamental insight on the EnT mechanism of D–A fluorophores but also establish its wide utility in EnT-mediated photocatalytic reactions

A coupled hydrological and hydrodynamic model for flood simulation

This paper presents a new flood modelling tool developed by coupling a full 2D hydrodynamic model with hydrological models. The coupled model overcomes the main limitations of the individual modelling approaches, i.e. high computational costs associated with the hydrodynamic models and less detailed representation of the underlying physical processes related to the hydrological models. When conducting a simulation using the coupled model, the computational domain (e.g. a catchment) is first divided into hydraulic and hydrological zones. In the hydrological zones that have high ground elevations and relatively homogeneous land cover or topographic features, a conceptual lumped model is applied to obtain runoff/net rainfall, which is then routed by a group of pre-acquired ‘unit hydrographs’ to the zone borders. These translated hydrographs will then be used to drive the full 2D hydrodynamic model to predict flood dynamics at high resolution in the hydraulic zones that are featured with complex topographic settings, including roads, buildings, etc. The new coupled flood model is applied to reproduce a major flood event that occurred in Morpeth, northeast England in September 2008. While producing similar results, the new coupled model is shown to be computationally much more efficient than the full hydrodynamic model

Hydraulic correction method (HCM) to enhance the efficiency of SRTM DEM in flood modeling

Digital Elevation Model (DEM) is one of the most important controlling factors determining the simulation accuracy of hydraulic models. However, the currently available global topographic data is confronted with limitations for application in 2-D hydraulic modeling, mainly due to the existence of vegetation bias, random errors and insufficient spatial resolution. A hydraulic correction method (HCM) for the SRTM DEM is proposed in this study to improve modeling accuracy. Firstly, we employ the global vegetation corrected DEM (i.e. Bare-Earth DEM), developed from the SRTM DEM to include both vegetation height and SRTM vegetation signal. Then, a newly released DEM, removing both vegetation bias and random errors (i.e. Multi-Error Removed DEM), is employed to overcome the limitation of height errors. Last, an approach to correct the Multi-Error Removed DEM is presented to account for the insufficiency of spatial resolution, ensuring flow connectivity of the river networks. The approach involves: (a) extracting river networks from the Multi-Error Removed DEM using an automated algorithm in ArcGIS; (b) correcting the location and layout of extracted streams with the aid of Google Earth platform and Remote Sensing imagery; and (c) removing the positive biases of the raised segment in the river networks based on bed slope to generate the hydraulically corrected DEM. The proposed HCM utilizes easily available data and tools to improve the flow connectivity of river networks without manual adjustment. To demonstrate the advantages of HCM, an extreme flood event in Huifa River Basin (China) is simulated on the original DEM, Bare-Earth DEM, Multi-Error removed DEM, and hydraulically corrected DEM using an integrated hydrologic-hydraulic model. A comparative analysis is subsequently performed to assess the simulation accuracy and performance of four different DEMs and favorable results have been obtained on the corrected DEM

Chinese Herbal Medicine and Its Application for Female Cancer

Chinese herbal medicines (CHMs) have been widely used to promote health and treat illnesses in daily medical care throughout Asia while mostly accepted as an alternative medical method in many nations of the western world. CHM has a unique therapeutic effect to reduce adverse effects on cancer patients caused by chemotherapy and surgery; however, we did not find any high-quality review for the claimed effects. In this review, we will summarize the history, basic theories and principles, and clinical applications of CHM for disorders, especially female cancers. Meta-analyses to evaluate the efficacy and safety of CHM in the treatment of ovarian cancer and breast cancer have been conducted. The results showed that combined CHMs and western medicines treatment (CHM-WM) had significantly relieved the symptoms and reduced the side effects after surgery and chemotherapy on both ovarian cancer and breast cancer. However, more high-quality and large-scale RCTs are necessary to confirm the efficacy and safety of CHM-WM intervention

Kalman Filtering for Genetic Regulatory Networks with Missing Values

The filter problem with missing value for genetic regulation networks (GRNs) is addressed, in which the noises exist in both the state dynamics and measurement equations; furthermore, the correlation between process noise and measurement noise is also taken into consideration. In order to deal with the filter problem, a class of discrete-time GRNs with missing value, noise correlation, and time delays is established. Then a new observation model is proposed to decrease the adverse effect caused by the missing value and to decouple the correlation between process noise and measurement noise in theory. Finally, a Kalman filtering is used to estimate the states of GRNs. Meanwhile, a typical example is provided to verify the effectiveness of the proposed method, and it turns out to be the case that the concentrations of mRNA and protein could be estimated accurately

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process, with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August, 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses