Does culture diversity affect innovation? Evidence from Chinese business group affiliated firms

We analyze how intra-group culture diversity affect group affiliated firm’s innovation. Our findings suggest that the more inconsistency on risk preference among affiliated firms in one group, the less impact of affiliated firm’s own risk culture on innovation. Specifically, we document that intra-group culture diversity impedes individual affiliated firm’s innovation through managerial and controlling agency problems. The heterogeneity test shows that size, executives, headquarter connected, location, state ownership and information quality of affiliated firms can affect intragroup culture diversity on innovation. We prove that intra-group culture diversity impedes innovation on group affiliated firms, which means a dark side of business group affiliation

Consumer Stated Preference for Acer Laptop from Online Reviews

Consumer preference is a hot topic in the domain of marking management and e-commerce. Many previous studies have been conducted in this field. Whereas, there are rarely studies building on the particular commodity such as laptop. Therefore, this study explores comprehensive features that affect consumer preference for laptops by mining the online reviews. Firstly, we collect 6531 online reviews for Acer laptop from Amazon.cn and code these reviews with Nvivo10. Secondly, we develop a feature-based consumer preference model named MCPL based on the review text analysis. Considering the data imbalance of the collected 6531 product reviews, we adopt a random cluster sampling method to extract 50 groups with 100 samples per group. Then the correspondent regression analyses are conducted for the 50 groups of reviews. Finally, the meta-analysis is creatively conducted to integrate the multiple liner regression results of different groups. According to the result of meta-analysis, we demonstrate dominant features on behalf of the consumer preference of laptop and draw practical implications for enterprise competition strategies to facilitate product design or improvement

Localization and interaction of interlayer excitons in MoSe2_2/WSe2_2 heterobilayers

Transition metal dichalcogenide (TMD) heterobilayers provide a versatile platform to explore unique excitonic physics via properties of the constituent TMDs and external stimuli. Interlayer excitons (IXs) can form in TMD heterobilayers as delocalized or localized states. However, the localization of IX in different types of potential traps, the emergence of biexcitons in the high-excitation regime, and the impact of potential traps on biexciton formation have remained elusive. In our work, we observe two types of potential traps in a MoSe$_2$/WSe$_2$ heterobilayer, which result in significantly different emission behavior of IXs at different temperatures. We identify the origin of these traps as localized defect states and the moir{\'e} potential of the TMD heterobilayer. Furthermore, with strong excitation intensity, a superlinear emission behavior indicates the emergence of interlayer biexcitons, whose formation peaks at a specific temperature. Our work elucidates the different excitation and temperature regimes required for the formation of both localized and delocalized IX and biexcitons, and, thus, contributes to a better understanding and application of the rich exciton physics in TMD heterostructures.Comment: 18 pages, 15 figures incl supplemental materia

Cellular Internalization and Cytotoxicity of Aptamers Selected from Lung Cancer Cell

Abstract In this work, single-stranded DNA (ssDNA) aptamers against EGFR-transfected A549 cells, one type of non-small cell lung cancer (NSCLC) cells, were selected by cell-SELEX (systematic evolution of ligands by exponential enrichment) and were evaluated. The selected aptamers had high affinity to the A549 cells with dissociation constants in the nanomolar rang. Moreover, the aptamers were able to internalize into the cells, which is advantageous over most of the other existing aptamers. One of the selected aptamers showed significant cytotoxicity by inhibiting the cell proliferation and inducing cell apoptosis. These aptamers are expected to be new molecular probes for cancer cell targeting and drug delivery

Laser-Like Emission from a Sandwiched MoTe2 Heterostructure on a Silicon Single-Mode Resonator

Molybdenum ditelluride (MoTe2) has recently shown promise as a gain material for silicon photonics. Reliable single-mode operation and material stability remain two of the major issues that need to be addressed to advance this exciting technology, however. Here, laser-like emission from a sandwiched MoTe2 heterostructure on a silicon single-mode resonator is reported. The heterostructure consists of a layer of MoTe2 sandwiched between thin films of hexagonal boron nitride. It is known that tellurium compounds are sensitive to oxygen exposure, which leads to rapid degradation of the exposed layers in air. By encapsulating the MoTe2 gain material, much improved environmental stability is observed. Using a recently introduced single-mode resonator design, better control over the mode spectrum of the cavity is exercised and single-mode operation with a wide free spectral range is demonstrated. At room temperature, a Q-factor of 4500 and a threshold of 4.2 kW cm−2 at 1319 nm wavelength are achieved. These results lend further support to the paradigm of 2D material-based integrated light sources on the silicon platform

Neutrophil-to-lymphocyte ratio and incident end-stage renal disease in Chinese patients with chronic kidney disease: results from the Chinese Cohort Study of Chronic Kidney Disease (C-STRIDE)

Abstract Background Chronic kidney disease (CKD) leads to end-stage renal failure and cardiovascular events. An attribute to these progressions is abnormalities in inflammation, which can be evaluated using the neutrophil-to-lymphocyte ratio (NLR). We aimed to investigate the association of NLR with the progression of end stage of renal disease (ESRD), cardiovascular disease (CVD) and all-cause mortality in Chinese patients with stages 1–4 CKD. Methods Patients with stages 1–4 CKD (18–74 years of age) were recruited at 39 centers in 28 cities across 22 provinces in China since 2011. A total of 938 patients with complete NLR and other relevant clinical variables were included in the current analysis. Cox regression analysis was used to estimate the association between NLR and the outcomes including ESRD, CVD events or all-cause mortality. Results Baseline NLR was related to age, hypertension, serum triglycerides, total serum cholesterol, CVD history, urine albumin to creatinine ratio (ACR), chronic kidney disease-mineral and bone disorder (CKD-MBD), hyperlipidemia rate, diabetes, and estimated glomerular filtration rate (eGFR). The study duration was 4.55 years (IQR 3.52–5.28). Cox regression analysis revealed an association of NLR and the risk of ESRD only in patients with stage 4 CKD. We did not observe any significant associations between abnormal NLR and the risk of either CVD or all-cause mortality in CKD patients in general and CKD patients grouped according to the disease stages in particular. Conclusion Our results suggest that NLR is associated with the risk of ESRD in Chinese patients with stage 4 CKD. NLR can be used in risk assessment for ESRD among patients with advanced CKD; this application is appealing considering NLR being a routine test. Trial registration ClinicalTrials.gov Identifier NCT03041987. Registered January 1, 2012. (retrospectively registered) ( https://www.clinicaltrials.gov/ct2/show/NCT03041987?term=Chinese+Cohort+Study+of+Chronic+Kidney+Disease+%28C-STRIDE%29&rank=1 )https://deepblue.lib.umich.edu/bitstream/2027.42/148285/1/12967_2019_Article_1808.pd

Optimizing Conservation Planning for Multiple Cohabiting Species

Conservation planning often involves multiple species occupying large areas including habitat sites with varying characteristics. For a given amount of financial resources, designing a spatially coherent nature reserve system that provides the best possible protection to targeted species is an important ecological and economic problem. In this paper, we address this problem using optimization methods. Incorporating spatial criteria in an optimization framework considering spatial habitat needs of multiple species poses serious challenges because of modeling and computational complexities. We present a novel linear integer programming model to address this issue considering spatial contiguity and compactness of the reserved area. The model uses the concept of path in graph theory to ensure contiguity and minimizes the sum of distances between selected sites and a central site in individual reserves to promote compactness. We test the computational efficiency of the model using randomly generated data sets. The results show that the model can be solved quite efficiently in most cases. We also present an empirical application of the model to simultaneous protection of two cohabiting species, Gopher Tortoise and Gopher Frogs, in a military installation in Georgia, USA

Data from: How large spatially-explicit optimal reserve design models can we solve now? an exploration of current models’ computational efficiency

Spatially-explicit optimal reserve design models select best sites from a set of candidate sites to assemble nature reserves to protect species (or habitats) and these reserves display certain spatial attributes which are desirable for species. These models are formulated with linear 0-1 programming and solved using standard optimization software, but they were run on different platforms, resulting in discrepant or even conflicting messages with regard to their computational efficiency. A fair and accurate comparison of the convenience of these models would be important for conservation planners who use these models. In this article we considered eight models presented in the literature and tested their computational efficiency using randomly generated data sets containing up to 2000 sites. We focused on reserve contiguity and compactness which are considered crucial to species persistence. Our results showed that two of those models, namely Williams (2002) and Önal et al. (2016), stand out as the most efficient models. We also found that the relative efficiency of these models depends on the scope of analysis. Specifically, the Williams (2002) model solves more of the test problems when contiguity is the only spatial attribute and a large subset of the candidate sites needs to be selected. When compactness is considered also, the Önal et al. (2016) model generally performs better. Large scale models are found to be difficult to solve in a reasonable period of time. We discussed factors that may affect those models' computational efficiency, including model size, share of selected sites, model structure, and input data. These results provide useful insight and guidance to conservation practitioners and researchers who focus on spatial aspects and work with large-scale data sets

Data from: How large spatially-explicit optimal reserve design models can we solve now? an exploration of current models’ computational efficiency

Spatially-explicit optimal reserve design models select best sites from a set of candidate sites to assemble nature reserves to protect species (or habitats) and these reserves display certain spatial attributes which are desirable for species. These models are formulated with linear 0-1 programming and solved using standard optimization software, but they were run on different platforms, resulting in discrepant or even conflicting messages with regard to their computational efficiency. A fair and accurate comparison of the convenience of these models would be important for conservation planners who use these models. In this article we considered eight models presented in the literature and tested their computational efficiency using randomly generated data sets containing up to 2000 sites. We focused on reserve contiguity and compactness which are considered crucial to species persistence. Our results showed that two of those models, namely Williams (2002) and Önal et al. (2016), stand out as the most efficient models. We also found that the relative efficiency of these models depends on the scope of analysis. Specifically, the Williams (2002) model solves more of the test problems when contiguity is the only spatial attribute and a large subset of the candidate sites needs to be selected. When compactness is considered also, the Önal et al. (2016) model generally performs better. Large scale models are found to be difficult to solve in a reasonable period of time. We discussed factors that may affect those models' computational efficiency, including model size, share of selected sites, model structure, and input data. These results provide useful insight and guidance to conservation practitioners and researchers who focus on spatial aspects and work with large-scale data sets

GAMS code

This file contains the 10 GAMS programs written for the contiguity and compactness models tested in the article, plus the one written for the modified Onal&Briers (2006) model