China's Sovereign Wealth Fund : Weakness and Challenges

The establishment of sovereign wealth funds in large developing countries has generated hot debate among participants in the international financial market. When accumulated foreign exchange reserves surpass a sufficient and an appropriate level, the costs, risks and impacts on the macro-economy of countries holding reserves need to be considered. The Chinese Government established China Investment Corporation (CIC) in 2007 to diversify its investment of foreign reserves and to raise investment income. However, because of certain conflicts of interest and institution-design caveats, CIC possesses some internal weakness, including a vague orientation, mixed investment strategies and inefficient bureaucratic style. Although the subprime crisis has softened certain regulations and lessened rejection by the USA of CIC potential investments, the increased volatility and uncertainty of the market means that CIC is facing some new challenges in terms of its investment decisions. Moreover, CIC is competing with other Chinese investment institutions for injections of funds from the Chinese Government.CIC, external challenge, internal weakness, foreign exchange reserve management

editorial

Sustainable farming plays an important role in modern agriculture and offers a solution to the problems caused by the way most of our food is grown today. Today’s industrial farming methods, many stemming from the Green Revolution of the 1950s and 1960s, are depleting our natural resources through monocultures and the overuse of pesticides and fertilizers, among other practices, while leaving people with unequal access to food and nutrition around the world

Nonlinear dynamics and control in a tumor-immune system

Advances in modeling tumor-immune dynamics and therapies offer deeper understandings of the mechanism of tumor evolution in the interdisciplinary field of mathematics and immune-oncology. The main mathematical models are constructed in terms of ordinary differential equations (ODEs) or partial differential equations (PDEs) and analyzed through tools such as Poincaré map, simulation, or numerical bifurcation analysis to understand the system properties. These models succeed in characterizing essential features of tumor behaviors including periodic bursts and the existence of latency. In relationship to practice, these models are also applied to estimate the feasibility and efficacy of treatments ranging from traditional chemotherapy to immunotherapy (ACI). In recent literature, there have been applications of control methods such as optimal control, hybrid automata, and feedback linearization-based tracking control with almost disturbance decoupling in the studies of tumor-immune systems. This thesis presents an attempt to apply the bifurcation control method with washout filters in tumor treatments. This thesis research investigates the dynamics and controlling of the tumor-immune response of immunotherapies, mainly the Adoptive Cell Immunotherapy (ACI) and Interleukin-2 (IL-2). The first part of the thesis presents the nonlinear dynamics of the classic nonlinear ODE tumor-immune model given by Denise Kirschner and John Carl Panetta in 1998. This model concentrates on the nonlinear phenomena of the tumor-immune system under immunotherapies, primarily the bifurcation phenomenon along with the antigenicity of effector cells. Bifurcation phenomena refer to the qualitative changes in system dynamics due to quasi-static changes in system parameters. Antigenicity refers to a capability to distinguish tumor cells from healthy cells. The Kirschner-Panetta model captures a saddle-node bifurcation and a Hopf bifurcation of the tumor-immune response, which separates the tumor evolution into three stages, the “dangerous equilibrium”, the periodic recurrence, and the “safe equilibrium”. The second part applies and analyzes several control strategies on the immunotherapies based on the KP model in order to eradicate tumors or inhibit tumor growths. The first section studies the combination immunotherapy of ACI and IL-2 as an open-loop control system based on Kirschner’s work, which generates a locally asymptotically stable equilibrium. In the second section, this thesis provides a new idea of treatment in the tumor-immune system, that is a closed-loop control strategy taking advantage of its bifurcation structure by applying dynamic feedback control with a washout filter of ACI or IL-2. Bifurcation control moves the Hopf bifurcation point without changing the equilibrium structure as the bifurcation parameter varies. In this tumor-immune case, the linear dynamic feedback control with a washout filter of ACI could either extend the “safe equilibrium” region or reduce the amplitude of the tumor population at the stage of tumor recurrence. In addition, other bifurcation amplitude controls of either ACI or IL-2 are attempted to reduce the amplitudes of periodic orbits of the tumor immune system but without obvious effects

Editorial

Carbon neutral or low carbon is a key feature or basic rule of an eco-city. Low carbon means less carbon dioxide. This concept is a leading concept in modern society, like low carbon economy, low carbon products and low carbon environment. In this issue, we will read several articles about low carbon

Cloud Computing for Detecting High-Order Genome-Wide Epistatic Interaction via Dynamic Clustering

Backgroud: Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. Results: In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Conclusions: Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS