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We lower bound the rank of a tensor by a linear combination of the ranks of three of its unfoldings, using Sylvester's rank inequality. In a similar way, we lower bound the symmetric rank by a linear combination of the symmetric ranks of three unfoldings. Lower bounds on the rank and symmetric rank of tensors are important for finding counterexamples to Comon's conjecture. A real counterexample to Comon's conjecture is a tensor whose real rank and real symmetric rank differ. Previously, only one real counterexample was known. We divide the construction into three steps. The first step involves linear spaces of binary tensors. The second step considers a linear space of larger decomposable tensors. The third step is to verify a conjecture that lower bounds the symmetric rank, on a tensor of interest. We use the construction to build an order six real tensor whose real rank and real symmetric rank differ., 26 pages, 3 figures, v2: updated to match published version

Any firm whose business strategy has an exposure constraint that limits its potential gain naturally considers expansion, as this can increase its exposure. We model business expansion as an enlargement of the opportunity set for business policies. However, expansion is irreversible and has an opportunity cost attached. We use the expected optimization of utility to formulate this as a novel stochastic control problem combined with an optimal stopping time, and we derive an explicit solution for exponential utility. We apply the framework to an investment and a reinsurance scenario. In the investment problem, the cost and incentives to increase the trading exposure are analyzed, while the optimal timing for an insurer to launch its reinsurance business is investigated in the reinsurance problem. Our model predicts that the additional income gained through business expansion is the key incentive for a decision to expand. Interestingly, companies may have this incentive but are likely to wait for a period of time before expanding, although situations of zero opportunity cost or specific restrictive conditions on the model parameters are exceptions to waiting. The business policy remains on the boundary of the opportunity set before expansion during the waiting period. The length of the waiting period is related to the opportunity cost, return, and risk of the expanded business.

As the size of the population aged 65 and older continues to grow, the incidence and mortality rates of Alzheimer’s disease (AD) are increasing annually. Unfortunately, current treatments only treat symptoms temporarily and do not alter the patients’ life expectancy or course of AD. Mesenchymal stem cells (MSCs) have shown a certain therapeutic potential in neurodegenerative diseases including AD due to their neuroinflammatory regulation and neuroprotective effects. However, the low survival and homing rates of MSCs after transplantation seriously affect their therapeutic effectiveness. Therefore, appropriate in vitro preconditioning is necessary to increase the survival and homing rates of MSCs to improve their effectiveness in treating AD. Here we summarize the therapeutic mechanisms of MSCs in AD and the chemical reagents used for the pretreatment of MSCs.

This study explores the impacts of directionality on disfluency of sight translation (ST) between English and Chinese. The author adopts four disfluency indicators, namely silent pause (SP), filled pause (FP), repetition (Rt), and repair (Rr) to answer: (1) What are the features of disfluency in ST in two directions? (2) What is the correlation between directionality and disfluency in ST? The results show: (1) The incidence of SP is the highest in both E-C and C-E ST, followed by FP, then Rr, and finally Rt; many student interpreters do the most basic pre-task preparation poorly, leading to a large number of SPs; many SPs coincide with respiration and those over 10 seconds occur only in E-C ST; (2) There are no statistically significant differences between E-C and C-E ST in terms of the four disfluency indicators. In other words, directionality exerts no significant effect on disfluency of student interpreters' ST.

Innovation drives enterprises to carry out Research and development(R&D)activities, which leads to R&D manipulation. Reducing R&D manipulation is beneficial to improve the R&D performance of enterprises. Based on the data from 2008 to 2021, this paper studies the relationship between whether it is a family enterprise and the level of enterprise R&D manipulation, and finds that the level of R&D manipulation of family enterprise is lower. Family enterprises and non-family enterprises play an important role in the national economy. We should strengthen the supervision of the level of R&D manipulation of non-family enterprises and improve the corresponding policies and systems. The research results of this paper also have some enlightening effects on how to adopt strategic strategies and corporate governance in order to improve the competitiveness of family enterprises in the competition.

The tourism industry has entered the stage of popular development worldwide. At the same time, business activities in various industries are becoming increasingly frequent. As a new type of hotel, the economic hotel provides good facilities and services for guests while charging relatively low prices. Although the current economic hotel has a good development space, its human resource management still exposes many problems, such as the lack of a performance evaluation system, poor salaries and treatment of employees, and unqualified employee training. These problems have hindered the good development of the hotel in the future and are not conducive to the hotel obtaining a lasting competitive advantage. If economic hotels want to change this situation, they need to establish a scientific and perfect staff incentive mechanism system. Based on reading a large number of existing literatures on related topics, this paper summarizes the concepts and opinions of representative scholars on the establishment of employee incentive mechanisms in economic hotels. At the same time, starting from the theoretical concept, this paper investigates employees' evaluation of the employee incentive mechanism implemented by their work hotels in the form of questionnaires to summarize the problems existing in the current economic hotels in terms of employee salary and welfare, performance appraisal, training and learning, promotion space, etc., o analyze the current problems hindering the development of economical hotels and propose corresponding solutions.

Objective: Controlling coccidiosis disease in poultry is significant for healthy breeding, but antibiotic residues can pose a great threat to food safety, the ecological environment, and human health. A special anticoccidial drug called Hainanmycin has been widely used in Asian countries for many years, while a few studies focus on its detection. In this study, we established a hydrophiliclipophilic balance (HLB) purification and ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method to determine the hainanmycin in chicken liver. Methods: It was extracted from the sample with 0.1% formic acid-methanol (10+90, v/v) and then it was purified on a hydrophilic-lipophilic balance (HLB) cartridge. Chromatography separation was performed on an RP-C18 column, and detection of the hainanmycin was done by positive electrospray ionization (ESI＋) under the multiple reaction monitoring (MRM) modes. Results: The quantification ion pair was m/z 907.5 and m/z 846.4. The calibration curve showed excellent linearity in the range of 10 to 1000 μg·L-1, with a correction coefficient of 0.99. When spiked at 5, 100, and 500 μg·kg-1, the recoveries ranged from 80.82% to 88.09%, with the intra-day and interday coefficients of variation from 10.76% to 13.48% and from 10.80% to 12.71%, respectively. The limit of quantification (LOQ) and detection(LOD) were 5.05 μg·mL-1 and 1.55 μg·mL-1, respectively. Conclusion: This method showed high sensitivity and accuracy for determining hainanmycin in chicken liver.

Firstly, a typical slope on Liu-An highway was selected as the research object. Then, based on the Sarma algorithm and considering the influence factors such as inhomogeneous boundary conditions, water content and reinforcement Angle, A slope stability analysis system based on the improved Sarma algorithm is developed to build an engineering geological model and a remote intelligent monitoring system platform for the slope. On this basis, we select the slope of typical road sections for remote monitoring and pre-warning. ArcGIS technology is used to carry out difference analysis of monitoring data, realize GIS 3D visualization, and verify the 3D visualization monitoring effect of the system. The results show that the system is stable and reliable. The range and precision meet the specification requirements, and can effectively realize the 3D visualization monitoring of highway slope. It can also realize four-level pre-warning, which lays a foundation for the long-term safe operation of highway.

Acute coronary syndrome(ACS) refers to a group of clinical symptoms caused by acute myocardial ischemia, including unstable angina pectoris, acute myocardial infarction, and sudden ischemic death. In recent years, studies have shown that the main mechanism of its occurrence is the rupture of plaque and the consequent intravascular thrombosis. Multiple factors may lead to the occurrence of the disease. However, the mechanism of the histomorphological change from pre-fragmentation to post-fragmentation is still unclear. Vasospasm may also play an important role. Prevention of plaque formation and rupture or prevention of thrombosis by antithrombotic therapy is effective in reducing the incidence of acute coronary syndrome, and coronary intervention also reduces the mortality of acute coronary syndrome. Some new therapies, such as gene therapy, are still in the experimental stage. At the same time, people should improve the awareness of disease prevention, and the most active prevention is the best means of disease treatment.

Nowadays, the fluctuation of housing prices is a key concern of homeowners, the real estate market and the government. The researchers found that it was possible to predict house prices accurately by analyzing relevant attributes and using the most effective models. However, due to the impact of the COVID-19 pandemic, there is still a research gap on which model is more suitable for predicting housing prices after the outbreak of COVID-19. Therefore, this study collected the latest real estate data of Guangzhou in China through the web crawler, trained the random forest regression model with collected data, and obtained a model that could predict the housing price by inputting corresponding attributes. The MSE of the trained regression model is 2802, MAE is 534, and the determination coefficient (R²_score) is 0.89, while the MSE of the trained XGBoost regression model is 3108, MAE is 643, and the determination coefficient (R²_score) is 0.87.The random forest regression model has been shown to be more accurate at predicting Guangzhou house prices after the COVID-19 outbreak. Our paper has great potential in house price prediction under the pandemic situation.