The Metastasectomy and Timing of Pulmonary Metastases on the Outcome of Osteosarcoma Patients

Background The author intended to clarify the therapeutic effect and prognostic factors of metastasectomy and timing of pulmonary metastases in osteosarcoma patents. Methods Data was obtained retrospectively on all consecutive osteosarcoma patients from 1985 to 2005 in author's institute. Fifty-two patients with pulmonary nodules were identified, including 24 patients undergoing pulmonary metastasectomy treatment. These patients were categorized into four groups: group 1, patients with lung metastases at the initial presentation; group 2, lung metastases identified during the period of pre-operative chemotherapy; group 3, lung metastases identified during period of the post-operative chemotherapy; group 4, lung metastases identified after therapy for the primary osteosarcoma completed. Results In our study, the 2-, 3-, and 5-year overall survival rates for 52 patients were 49%, 39% and 20%. The 2-year overall survival rates were 18% for group 1, 32% for group 3, and 70% for group 4 (p < 0.001). The 5-year overall survival rate was 34% for group 4. Patients who underwent metastesectomy showed a better survival outcome as compared with the patients not undergoing metastasectomy (p = 0.003). The 2-year and 5-year overall survival rates of only one lung metastatic nodule were 62% and 50%, and for initially multiple lung metastatic nodules, 45% and 5%, respectively. In addition, the patients presented with lung metastases had a worse prognosis as compared with those without initial lung metastases (p = 0.0001). Conclusions The patients having single metastatic nodule showed a better prognosis than those with multiple lung nodules. Furthermore, those patients who underwent metastasectomy survived longer than those not undergoing metastasectomy. Patients who had late metastases after complete chemotherapy had a better prognosis; whereas those who had metastases identified at the initial presentation predicted a poor prognosis

A SEEMINGLY UNRELETED REGRESSION ANALYSIS ON THE TRADING BEHAVIOR OF MUTUAL FUND INVESTORS

This paper provides a comprehensive investigation on the causality relationship between fund performance and trading flows. We analyze if investors behave asymmetrically in fund purchasing and selling by seemingly unrelated regression which comprises several individual relationships that are linked by the fact that their disturbances or the error terms are correlated. The empirical result shows a significantly negative relationship between fund performance and purchase flows for domestic funds. The magnitude of domestic funds redemption negatively affects current return, but not for international funds. As previousfund return positively affects current net flows,the further lagged performances have no significant impact on the trading flows, revealing that fund investors are sensitive only to short-term past performance. Most importantly, while negative fund performance leads to the increases in redemption, positive performance contrarily leads to the decreases in purchase. The evidences strongly indicate an asymmetry behavior of fund investors in the return-purchase causality relations

Formation of Long Single Quantum Dots in High Quality InSb Nanowires Grown by Molecular Beam Epitaxy

We report on realization and transport spectroscopy study of single quantum dots (QDs) made from InSb nanowires grown by molecular beam epitaxy (MBE). The nanowires employed are 50-80 nm in diameter and the QDs are defined in the nanowires between the source and drain contacts on a Si/SiO$_2$ substrate. We show that highly tunable QD devices can be realized with the MBE-grown InSb nanowires and the gate-to-dot capacitance extracted in the many-electron regimes is scaled linearly with the longitudinal dot size, demonstrating that the devices are of single InSb nanowire QDs even with a longitudinal size of ~700 nm. In the few-electron regime, the quantum levels in the QDs are resolved and the Land\'e g-factors extracted for the quantum levels from the magnetotransport measurements are found to be strongly level-dependent and fluctuated in a range of 18-48. A spin-orbit coupling strength is extracted from the magnetic field evolutions of a ground state and its neighboring excited state in an InSb nanowire QD and is on the order of ~300 $\mu$eV. Our results establish that the MBE-grown InSb nanowires are of high crystal quality and are promising for the use in constructing novel quantum devices, such as entangled spin qubits, one-dimensional Wigner crystals and topological quantum computing devices.Comment: 19 pages, 5 figure

Parallel Acceleration and Improvement of Gravitational Field Optimization Algorithm

The Gravitational Field Algorithm, a modern optimization algorithm, mainly simulates celestial mechanics and is derived from the Solar Nebular Disk Model (SNDM). It simulates the process of planetary formation to search for the optimal solution. Although this optimization algorithm has more advantages than other optimization algorithms in multi-peak optimization problems, it still has the shortcoming of long computation time when dealing with large-scale datasets or solving complex problems. Therefore, it is necessary to improve the efficiency of the Gravitational Field Algorithm (GFA). In this paper, an optimization method based on multi-population parallel is proposed to accelerate the Gravitational Field Algorithm. With the help of the parallel mechanism in MATLAB, the algorithm execution speed will be improved by using the parallel computing mode of multi-core CPU. In addition, this paper also improves the absorption operation strategy. By comparing the experimental results of eight classical unconstrained optimization problems, it is shown that the computational efficiency of this method is improved compared with the original Gravitational Field Algorithm, and the algorithm accuracy has also been slightly improved

Are investors’ portfolios enhanced by incorporating CTA index funds?

[[abstract]]By exploring the CTA index with other representative indices across stock, bond, currency, futures, oil, gold and commodity markets, we reveal several impressive findings for the CTA index. First, an upward trend exists for the CTA index without obvious drops. Second, a lower correlation is shown between the CTA index and each of these indices without exceptions. Third, neither causality nor cointegration is revealed as well. The findings revealed above seldom coexist for other financial commodities, implying that investors are able to enhance their portfolios by incorporating CTA index funds according to the portfolio selection proposed by Markowitz (1952).[[incitationindex]]SSCI[[booktype]]紙

Optimizing Logical Execution Time Model for Both Determinism and Low Latency

The Logical Execution Time (LET) programming model has recently received considerable attention, particularly because of its timing and dataflow determinism. In LET, task computation appears always to take the same amount of time (called the task's LET interval), and the task reads (resp. writes) at the beginning (resp. end) of the interval. Compared to other communication mechanisms, such as implicit communication and Dynamic Buffer Protocol (DBP), LET performs worse on many metrics, such as end-to-end latency (including reaction time and data age) and time disparity jitter. Compared with the default LET setting, the flexible LET (fLET) model shrinks the LET interval while still guaranteeing schedulability by introducing the virtual offset to defer the read operation and using the virtual deadline to move up the write operation. Therefore, fLET has the potential to significantly improve the end-to-end timing performance while keeping the benefits of deterministic behavior on timing and dataflow. To fully realize the potential of fLET, we consider the problem of optimizing the assignments of its virtual offsets and deadlines. We propose new abstractions to describe the task communication pattern and new optimization algorithms to explore the solution space efficiently. The algorithms leverage the linearizability of communication patterns and utilize symbolic operations to achieve efficient optimization while providing a theoretical guarantee. The framework supports optimizing multiple performance metrics and guarantees bounded suboptimality when optimizing end-to-end latency. Experimental results show that our optimization algorithms improve upon the default LET and its existing extensions and significantly outperform implicit communication and DBP in terms of various metrics, such as end-to-end latency, time disparity, and its jitter

Rod-like mesoporous silica nanoparticles with rough surfaces for enhanced cellular delivery

Novel rod-like mesoporous silica nanoparticles with a rough surface have been prepared with 37% higher cellular uptake and drug delivery efficacy compared to their counterparts with a smooth surface