A Tale of Two Provinces: The Institutional Environment and Foreign Ownership in China

In this paper, we use a unique dataset covering joint ventures in two provinces of China, Jiangsu and Zhejiang, to test the effect of the institutional environment for domestic private firms on ownership structures of FDI projects. Unlike many studies on this subject, we approach the issue from the perspective of local firms seeking FDI rather than from the perspective of foreign firms seeking to invest in China. Applying the prevailing bargaining framework in studies on ownership structures of FDI projects, we find that a more liberal institutional environment for domestic private firms is associated with less foreign ownership of the joint ventures operating there. Several mechanisms can contribute to this outcome. One is that a more liberal institutional environment may enhance the bargaining power of those domestic firms negotiating with foreign firms to form alliances (the capability effect). The other mechanism is that a more liberal institutional environment may reduce some of the auxiliary benefits associated with FDI—such as greater property rights granted to foreign investors—and thereby attenuate incentive to form alliances with foreign firms (the incentive effect).http://deepblue.lib.umich.edu/bitstream/2027.42/40053/3/wp667.pd

A Tale of Two Provinces: The Institutional Environment and Foreign Ownership in China

In this paper, we use a unique dataset covering joint ventures in two provinces of China, Jiangsu and Zhejiang, to test the effect of the institutional environment for domestic private firms on ownership structures of FDI projects. Unlike many studies on this subject, we approach the issue from the perspective of local firms seeking FDI rather than from the perspective of foreign firms seeking to invest in China. Applying the prevailing bargaining framework in studies on ownership structures of FDI projects, we find that a more liberal institutional environment for domestic private firms is associated with less foreign ownership of the joint ventures operating there. Several mechanisms can contribute to this outcome. One is that a more liberal institutional environment may enhance the bargaining power of those domestic firms negotiating with foreign firms to form alliances (the capability effect). The other mechanism is that a more liberal institutional environment may reduce some of the auxiliary benefits associated with FDI—such as greater property rights granted to foreign investors—and thereby attenuate incentive to form alliances with foreign firms (the incentive effect).China, FDI, private sector, institutional environment, joint venture

The Hydrodynamic Interaction in Polymer Solutions Simulated with Dissipative Particle Dynamics

We analyzed extensively the dynamics of polymer chains in solutions simulated with dissipative particle dynamics (DPD), with a special focus on the potential influence of a low Schmidt number of a typical DPD fluid on the simulated polymer dynamics. It has been argued that a low Schmidt number in a DPD fluid can lead to underdevelopment of the hydrodynamic interaction in polymer solutions. Our analyses reveal that equilibrium polymer dynamics in dilute solution, under a typical DPD simulation conditions, obey the Zimm model very well. With a further reduction in the Schmidt number, a deviation from the Zimm model to the Rouse model is observed. This implies that the hydrodynamic interaction between monomers is reasonably developed under typical conditions of a DPD simulation. Only when the Schmidt number is further reduced, the hydrodynamic interaction within the chains becomes underdeveloped. The screening of the hydrodynamic interaction and the excluded volume interaction as the polymer volume fraction is increased are well reproduced by the DPD simulations. The use of soft interaction between polymer beads and a low Schmidt number do not produce noticeable problems for the simulated dynamics at high concentrations, except that the entanglement effect which is not captured in the simulations.Comment: 27 pages, 13 page

Circular RNA and intervertebral disc degeneration: unravelling mechanisms and implications

Low back pain (LBP) is a major public health problem worldwide and a significant health and economic burden. Intervertebral disc degeneration (IDD) is the reason for LBP. However, we have not identified effective therapeutic strategies to address this challenge. With accumulating knowledge on the role of circular RNAs in the pathogenesis of IDD, we realised that circular RNAs (circRNAs) may have tremendous therapeutic potential and clinical application prospects in this field. This review presents an overview of the current understanding of characteristics, classification, biogenesis, and function of circRNAs and summarises the protective and detrimental circRNAs involved in the intervertebral disc that have been studied thus far. This review is aimed to help researchers better understand the regulatory role of circRNAs in the progression of IDD, reveal their clinical therapeutic potential, and provide a theoretical basis for the prevention and targeted treatment of IDD

Blockchain-assisted Undisclosed IIoT Vulnerabilities Trusted Sharing Protection with Dynamic Token

With the large-scale deployment of industrial internet of things (IIoT) devices, the number of vulnerabilities that threaten IIoT security is also growing dramatically, including a mass of undisclosed IIoT vulnerabilities that lack mitigation measures. Coordination Vulnerabilities Disclosure (CVD) is one of the most popular vulnerabilities sharing solutions, in which some security workers (SWs) can develop undisclosed vulnerabilities patches together. However, CVD assumes that sharing participants (SWs) are all honest, and thus offering chances for dishonest SWs to leak undisclosed IIoT vulnerabilities. To combat such threats, we propose an Undisclosed IIoT Vulnerabilities Trusted Sharing Protection (UIV-TSP) scheme with dynamic token. In this article, a dynamic token is an implicit access credential for an SW to acquire an undisclosed vulnerability information, which is only held by the system and constantly updated as the SW access. Meanwhile, the latest updated token can be stealthily sneaked into the acquired information as the traceability token. Once the undisclosed vulnerability information leaves the SW host, the embedded self-destruct program will be automatically triggered to prevent leaks since the destination MAC address in the traceability token has changed. To quickly distinguish dishonest SWs, trust mechanism is adopted to evaluate the trust value of SWs. Moreover, we design a blockchain-assisted continuous logs storage method to achieve the tamper-proofing of dynamic token and the transparency of undisclosed IIoT vulnerabilities sharing. The simulation results indicate that our proposed scheme is resilient to suppress dishonest SWs and protect the IoT undisclosed vulnerabilities effectively.Comment: 10 pages,12 figure

A novel autoregressive rainflow-integrated moving average modeling method for the accurate state of health prediction of lithium-ion batteries.

The accurate estimation and prediction of lithium-ion battery state of health are one of the important core technologies of the battery management system, and are also the key to extending battery life. However, it is difficult to track state of health in real-time to predict and improve accuracy. This article selects the ternary lithium-ion battery as the research object. Based on the cycle method and data-driven idea, the improved rain flow counting algorithm is combined with the autoregressive integrated moving average model prediction model to propose a new prediction for the battery state of health method. Experiments are carried out with dynamic stress test and cycle conditions, and a confidence interval method is proposed to fit the error range. Compared with the actual value, the method proposed in this paper has a maximum error of 5.3160% under dynamic stress test conditions, a maximum error of 5.4517% when the state of charge of the cyclic conditions is used as a sample, and a maximum error of 0.7949% when the state of health under cyclic conditions is used as a sample

An improved rainflow algorithm combined with linear criterion for the accurate li-ion battery residual life prediction.

Li-ion battery health assessment has been widely used in electric vehicles, unmanned aerial vehicle and other fields. In this paper, a new linear prediction method is proposed. By weakening the sensitivity of the Rainflow algorithm to the peak data, it can be applied to the field of battery, and can accurately count the number of Li-ion battery cycles, and skip the cumbersome link of parameter identification. Then, a linear criterion is proposed based on the idea of proportion, which makes the life prediction of Li-ion battery linear. Under the verification of multiple sets of data, the prediction error of this method is kept within 2.53%. This method has the advantages of high operation efficiency and simple operation, which provides a new idea for battery life prediction in the field of electric vehicles and aerospace

Personalized Estimate of Chemotherapy-Induced Nausea and Vomiting: Development and External Validation of a Nomogram in Cancer Patients Receiving Highly/Moderately Emetogenic Chemotherapy.

Chemotherapy-induced nausea and vomiting (CINV) is presented in over 30% of cancer patients receiving highly/moderately emetogenic chemotherapy (HEC/MEC). The currently recommended antiemetic therapy is merely based on the emetogenic level of chemotherapy, regardless of patient's individual risk factors. It is, therefore, critical to develop an approach for personalized management of CINV in the era of precision medicine.A number of variables were involved in the development of CINV. In the present study, we pooled the data from 2 multi-institutional investigations of CINV due to HEC/MEC treatment in Asian countries. Demographic and clinical variables of 881 patients were prospectively collected as defined previously, and 862 of them had full documentation of variables of interest. The data of 548 patients from Chinese institutions were used to identify variables associated with CINV using multivariate logistic regression model, and then construct a personalized prediction model of nomogram; while the remaining 314 patients out of China (Singapore, South Korea, and Taiwan) entered the external validation set. C-index was used to measure the discrimination ability of the model.The predictors in the final model included sex, age, alcohol consumption, history of vomiting pregnancy, history of motion sickness, body surface area, emetogenicity of chemotherapy, and antiemetic regimens. The C-index was 0.67 (95% CI, 0.62-0.72) for the training set and 0.65 (95% CI, 0.58-0.72) for the validation set. The C-index was higher than that of any single predictor, including the emetogenic level of chemotherapy according to current antiemetic guidelines. Calibration curves showed good agreement between prediction and actual occurrence of CINV.This easy-to-use prediction model was based on chemotherapeutic regimens as well as patient's individual risk factors. The prediction accuracy of CINV occurrence in this nomogram was well validated by an independent data set. It could facilitate the assessment of individual risk, and thus improve the personalized management of CINV