Corporate Diversification And Firm Performance Impact On Chief Executive Officers Salary

The purpose of this research is to examine CEO salary and to explore whether the independent variables (international diversification, industrial diversification, market-based performance, accounting-based performance) are associated with CEO salary. Corporate diversification in this study is divided into international diversification and industrial diversification. Data for the study was obtained from annual reports of CEO salary on the ExecuComp database. Compensation data collected from the annual reports encompassed 2,448 CEOs from 1,622 firms. The dependent variable was developed from a review of CEO salary and accounting literature. The hypothesized predictors of CEO salary were identified through a review of existing studies. The results show that the higher the degree of international diversification and/or industrial diversification, the more CEOs receive in fixed salary. In addition, this study found that CEO salary is a better predictor of accounting performance than stock return performance

Evidence-based design for childbirth environments: the impacts of window view and daylight exposure on the health of post-cesarean section women

Hospital caesarean rates in the U.S. have soared to a record high of over 32.9% in 2009, making Cesarean Section a significant issue for women’s health. Prior studies have shown that natural and physical environments have significant impacts on human health. However, few studies have been published examining impacts of natural and physical environments within healthcare facilities on patients’ health outcomes, both mental and physiological. This research explores the effects of the built environment for childbirth, specifically in terms of daylight exposure and window views, on women’s recovery from post-Cesarean Section. The researcher examined the impact of the built environment on recovery such as patient-controlled analgesic (PCA) usage, length of stay, perceived pain, and general wellbeing of women who have undergone Cesarean Sections. The researcher recruited a total of 296 women undergoing Cesarean Sections and use of PCA for pain control after their Cesarean Sections from 3 tertiary hospitals in Taiwan for this research; with assistance from 19 physicians and 38 registered nurses. The study took nearly 9 months to complete data collection and an additional 14 months for data cleaning and analysis. Data collection methods include self-administered questionnaires, reviews of medical charts, and observations. The researcher applied BPI-SF (Brief Pain Inventory Short Form) to measure perceived pain and used SF-36, a well-validated health-status questionnaire with 36 short questions, to measure general well-being of the participants. Information regarding PCA usage and length of stay were extracted from charts. Some confounding variables such as socioeconomic data were collected through self-administered questionnaires. The subjects were asked to evaluate the percentage of natural components from their window view and their satisfaction. Daylight exposure of each patient was measured by a Konica Minolta Illuminance Meter T-10 twice a day after their delivery and throughout their hospital stay according to a predetermined guideline. Results of a series of regression analyses have showed that amount of daylight exposure have statistically significant association with improvement of PF (physical function). Therefore, increasing daylight exposure could improve physical wellbeing. In addition, patients’ satisfaction with their window view has a statistically significant and positive impact on improving perceived pain (pain severity). Results of focus-group discussion also suggest that if window view with favorable natural contents is unavailable, artworks such as nature scene murals or landscape paintings or photos, may provide positive distractions for patients. Redesigning patient wards to maximize the amount of daylight exposure patients receive and to increase satisfaction of window views may decrease usage of analgesic and reduce patients’ perceived pain. The three different combinations of two window view-related variables rated by independent raters (“window view satisfaction” and “percentage of natural content in window view”) were adopted into a series of regression models. Results of these analyses also show that window view satisfaction significantly decreases analgesics usage, reduces perceived pain and improves some dimensions of wellbeing. To maximize patient benefit and well-being, health care architects should design patient rooms to receive maximum daylight exposure, create maximum patient satisfaction with visual impacts, and expand patients’ window views. Incorporating the above-mentioned design considerations should contribute to future best practices for patient room design which may decrease the use of medication (analgesic) and therefore substantially reduce healthcare costs

The impact of stock market policy announcement on commodity prices and share prices

It has been an important issue to analyze the possible impact of macroeconomic effects, such as: exchange rate or interest rate, on the commodity prices since 1970s because of the tremendous volatility of commodity prices on the US. Thereafter, there are a lot of literature in agricultural economics relative to the empirical study. But the results of these literature are ambiguous. On the other hand, Blandchard (1981) incorporated the stock market into the traditional IS-LM model and discussed the interaction between stock market and economy. The financial sector plays an important role to affect the time path of commodity prices it cannot be ignored since agricultural industry is just one of sector among the whole economy. The main purpose of this article is to add the stock market into the two-goods economy. One is commodity product and the other is nonagricultural product. According the model including commodity market, nonagricultural product market, monetary market and stock market and under the assumptions of perfect substitutes between stock and bond and perfect foresight expectation, the effect of stock market policies, such as financing interest rate, financing ratio, on dynamics of commodity and share prices will be analyzed. The result shows that in the long run the impact of stock policies on commodity prices depends on the relative magnitudes of price effect of commodity and interest rate effect. While in the short run, whether share price overshooting or not it depends on the length of time between announcement and implement of policies.commodity prices, share prices, financing interest rate, financing ratio, dynamics

THE INTELLECTUAL CAPITAL AND JOURNALISTS\u27 PERFORMANCE

In the age of knowledge-based economy, intellectual capital (IC) is of growing and substantial importance more so than the tangible assets such as land and financial capital. IC includes human capital, organizational capital and social capital. IC has become a driving force for an organization to stay competitive. Journalists are vital human capital in a news organization. They are the knowledge workers who need both independence (autonomy) and interdependence (teamwork) in order to accumulate and share knowledge. In addition to playing the role as \u27gate-keepers\u27 in the information delivery process, part of a journalist\u27s job is to develop relationships with news sources from outside of the organization. Therefore, journalists are also the social capital in their organization. A news organization loses both human and social capital whenever a journalist resigns or job-hops. The purpose of this research is to examine relationships between IC and journalists? performance in the media. We argue that journalists embody both human and social capitals which are mediated by job autonomy which journalists need in order to achieve high individual job performance. We also argue that organizational capital is mediated by team-level task interdependence which also leads to better individual job performance

Quantum-Inspired Sublinear Algorithm for Solving Low-Rank Semidefinite Programming

Semidefinite programming (SDP) is a central topic in mathematical optimization with extensive studies on its efficient solvers. In this paper, we present a proof-of-principle sublinear-time algorithm for solving SDPs with low-rank constraints; specifically, given an SDP with $m$ constraint matrices, each of dimension $n$ and rank $r$, our algorithm can compute any entry and efficient descriptions of the spectral decomposition of the solution matrix. The algorithm runs in time $O(m\cdot\mathrm{poly}(\log n,r,1/\varepsilon))$ given access to a sampling-based low-overhead data structure for the constraint matrices, where $\varepsilon$ is the precision of the solution. In addition, we apply our algorithm to a quantum state learning task as an application. Technically, our approach aligns with 1) SDP solvers based on the matrix multiplicative weight (MMW) framework by Arora and Kale [TOC '12]; 2) sampling-based dequantizing framework pioneered by Tang [STOC '19]. In order to compute the matrix exponential required in the MMW framework, we introduce two new techniques that may be of independent interest: $\bullet$ Weighted sampling: assuming sampling access to each individual constraint matrix $A_{1},\ldots,A_{\tau}$, we propose a procedure that gives a good approximation of $A=A_{1}+\cdots+A_{\tau}$. $\bullet$ Symmetric approximation: we propose a sampling procedure that gives the \emph{spectral decomposition} of a low-rank Hermitian matrix $A$. To the best of our knowledge, this is the first sampling-based algorithm for spectral decomposition, as previous works only give singular values and vectors.Comment: 37 pages, 1 figure. To appear in the Proceedings of the 45th International Symposium on Mathematical Foundations of Computer Science (MFCS 2020

Regulation of Skp2 Expression and Activity and Its Role in Cancer Progression

The regulation of cell cycle entry is critical for cell proliferation and tumorigenesis. One of the key players regulating cell cycle progression is the F-box protein Skp2. Skp2 forms a SCF complex with Skp1, Cul-1, and Rbx1 to constitute E3 ligase through its F-box domain. Skp2 protein levels are regulated during the cell cycle, and recent studies reveal that Skp2 stability, subcellular localization, and activity are regulated by its phosphorylation. Overexpression of Skp2 is associated with a variety of human cancers, indicating that Skp2 may contribute to the development of human cancers. The notion is supported by various genetic mouse models that demonstrate an oncogenic activity of Skp2 and its requirement in cancer progression, suggesting that Skp2 may be a novel and attractive therapeutic target for cancers

Quantum-Inspired Algorithms for Solving Low-Rank Linear Equation Systems with Logarithmic Dependence on the Dimension

We present two efficient classical analogues of the quantum matrix inversion algorithm [16] for low-rank matrices. Inspired by recent work of Tang [27], assuming length-square sampling access to input data, we implement the pseudoinverse of a low-rank matrix allowing us to sample from the solution to the problem Ax = b using fast sampling techniques. We construct implicit descriptions of the pseudo-inverse by finding approximate singular value decomposition of A via subsampling, then inverting the singular values. In principle, our approaches can also be used to apply any desired “smooth” function to the singular values. Since many quantum algorithms can be expressed as a singular value transformation problem [15], our results indicate that more low-rank quantum algorithms can be effectively “dequantised” into classical length-square sampling algorithms