Incentive Fees - Impact on Performance Measurement of Hedge Funds

This paper estimates the incentive fees impact on hedge funds returns by estimating the factor model using gross return and net return respectively. We used the latest twelve year data, including the high volatile data of 2008 and 2009, to do the regression. As a result, we find that the beta is underestimated from the regression, implying that the incentive fees do have the impact on hedge fund performance. Additionally, we adopted a rolling-over regression technique to duplicate the performance of the hedge funds using ten hedge fund strategies. We find that some additional beta return can be captured by replicating through the gross returns. In summary, the incentive fees should be taken into consideration when we are measuring the performances and risk exposures of the hedge funds

Testing alternative theories of gravity with space-based gravitational wave detectors

We use gravitational waves (GWs) from binary black holes (BBHs) and neutron stars inspiraling into intermediate-mass black holes to evaluate how accurately the future space-based GW detectors such as LISA, Taiji and TianQin and their combined networks can determine source parameters and constrain alternative theories of gravity. We find that, compared with single detector, the detector network can greatly improve the estimation errors of source parameters, especially the sky localization, but the improvement of the constraint on the graviton mass $m_g$ and the Brans-Dicke coupling constant $\omega_{BD}$ is small. We also consider possible scalar modes existed in alternative theories of gravity and we find the inclusion of the scalar mode has little effect on the constraints on source parameters, $m_g$, and $\omega_{BD}$ and the parametrized amplitude $A_B$ of scalar modes are small. For the constraint on the graviton mass, we consider both the effects in the GW phase and the transfer function due to the mass of graviton. With the network of LISA, Taiji and TianQin, we get the lower bound on the graviton Compton wavelength $\lambda_g\gtrsim 1.24 \times 10^{20}$ m for BBHs with masses $(10^6+10^7)M_\odot$, and $A_B< 5.7\times 10^{-4}$ for BBHs with masses $(1+2)\times 10^5M_\odot$; $\omega_{BD}>6.11\times10^{6}$ for neutron star-black hole binary with masses $(1.4+400)M_{\odot}$.Comment: 21 pages, 3 figures, 4 tables. Typos corrected and references updated. Published in PR

Multiobjective Transmission Network Planning considering the Uncertainty and Correlation of Wind Power

In order to consider the uncertainty and correlation of wind power in multiobjective transmission network expansion planning (TNEP), this paper presents an extended point-estimation method to calculate the probabilistic power flow, based on which the correlative power outputs of wind farm are sampled and the uncertain multiobjective transmission network planning model is transformed into a solvable deterministic model. A modified epsilon multiobjective evolutionary algorithm is used to solve the above model and a well-distributed Pareto front is achieved, and then the final planning scheme can be obtained from the set of nondominated solutions by a fuzzy satisfied method. The proposed method only needs the first four statistical moments and correlation coefficients of the output power of wind farms as input information; the modeling of wind power is more precise by considering the correlation between wind farms, and it can be easily combined with the multiobjective transmission network planning model. Besides, as the self-adaptive probabilities of crossover and mutation are adopted, the global search capabilities of the proposed algorithm can be significantly improved while the probability of being stuck in the local optimum is effectively reduced. The accuracy and efficiency of the proposed method are validated by IEEE 24 as well as a real system

A possible role of crustacean cardioactive peptide in regulating immune response in hepatopancreas of mud crab

Crustacean cardioactive peptide (CCAP), a cyclic amidated non-apeptide, is widely found in arthropods. The functions of CCAP have been revealed to include regulation of heart rate, intestinal peristalsis, molting, and osmotic pressure. However, to date, there has not been any report on the possible involvement of CCAP in immunoregulation in crustaceans. In this study, a CCAP precursor (designated as Sp-CCAP) was identified in the commercially important mud crab Scylla paramamosain, which could be processed into four CCAP-associated peptides and one mature peptide (PFCNAFTGC-NH2). Bioinformatics analysis indicated that Sp-CCAP was highly conserved in crustaceans. RT-PCR results revealed that Sp-CCAP was expressed in nerve tissues and gonads, whereas the Sp-CCAP receptor gene (Sp-CCAPR) was expressed in 12 tissues of S. paramamosain, including hepatopancreas. In situ hybridization further showed that an Sp-CCAPR-positive signal is mainly localized in the F-cells of hepatopancreas. Moreover, the mRNA expression level of Sp-CCAPR in the hepatopancreas was significantly up-regulated after lipopolysaccharide (LPS) or polyriboinosinic polyribocytidylic acid [Poly (I:C)] challenge. Meanwhile, the mRNA expression level of Sp-CCAPR, nuclear transcription factor NF-kappa B homologs (Sp-Dorsal and Sp-Relish), member of mitogen-activated protein kinase (MAPK) signaling pathway (Sp-P38), pro-inflammatory cytokines factor (Sp-TNFSF and Sp-IL16), and antimicrobial peptide (Sp-Lysozyme, Sp-ALF, Sp-ALF4, and Sp-ALF5) in the hepatopancreas were all up-regulated after the administration of synthetic Sp-CCAP mature peptide both in vivo and in vitro. The addition of synthetic Sp-CCAP mature peptide in vitro also led to an increase in nitric oxide (NO) concentration and an improved bacterial clearance ability in the hepatopancreas culture medium. The present study suggested that Sp-CCAP signaling system might be involved in the immune responses of S. paramamosain by activating immune molecules on the hepatopancreas. Collectively, our findings shed new light on neuroendocrine-immune regulatory system in arthropods and could potentially provide a new strategy for disease prevention and control for mud crab aquaculture

Visualization experiments of a solid cylinder suspended by laminar flow

Acknowledgments The financial supports from the Fundamental Research Funds for the Central Universities (XK1802-1) is gratefully acknowledged.Peer reviewedPostprin

Abnormal Glucose Metabolism and Insulin Resistance Are Induced via the IRE1α/XBP-1 Pathway in Subclinical Hypothyroidism

Subclinical hypothyroidism (SCH) and diabetes mellitus are closely related and often occur together in individuals. However, the underlying mechanism of this association is still uncertain. In this study we re-analyzed the data of a mature database (NHANES, 1999 ~ 2002) and found that both fasting plasma glucose levels and the proportion of hyperglycemic subjects among SCH patients were higher than that found in euthyroid controls. SCH was also associated with a 2.29-fold increased risk for diabetes. Subsequently, we established an SCH mouse model and subjected it to an oral glucose tolerance test (OGTT) and an insulin tolerance test (ITT). SCH mice exhibited impaired glucose and insulin tolerance. Increased HOMA-IR and decreased ISI indexes, indicating insulin resistance (IR), were also observed in the SCH state. Hepatic ERp29 and Bip, as well as IRE1α and XBP-1s, were induced significantly in SCH mice, suggesting the induction of endoplasmic reticulum (ER) stress, particularly involving the IRE1α/XBP-1s pathway. Interestingly, when we relieved ER stress using 4-phenyl butyric acid, abnormal glucose metabolism, and IR status in SCH mice were improved. Our findings suggest that ER stress, predominantly involving the IRE1α/XBP-1s pathway, may play a pivotal role in abnormal glucose metabolism and IR in SCH that may help develop potential strategies for the prevention and treatment of diabetes

An Adaptive Charging Strategy of Lithium-ion Battery for Loss Reduction with Thermal Effect Consideration

With the increasing deployment of the electric vehicles, the study of advanced battery charging strategy has become of great significance to improve charging performance with reduced loss. This paper presents an optimized adaptive charging strategy for EV battery packs based on a developed system loss model. An electrical model integrated with thermal properties for the lithium-ion battery with cooling as well as a full loss model for the power converter have been included in this complete model. To reduce the overall loss of the charging system, the influence of temperature and varying internal resistance at different state of charge (SOC) have been considered to obtain an objective function. Moreover, an enhanced particle swarm optimization (PSO) algorithm is proposed and applied to speed up convergence time as well as enhance the precision of the solution. The results show that this proposed strategy can reduce the total loss by 4.01 and a 7.48 decrease of the charging time compared with the classical approach without applying this optimization

Run-to-Run Control for Active Balancing of Lithium Iron Phosphate Battery Packs

\ua9 1986-2012 IEEE. Lithium iron phosphate battery packs are widely employed for energy storage in electrified vehicles and power grids. However, their flat voltage curves rendering the weakly observable state of charge are a critical stumbling block for charge equalization management. This paper focuses on the real-time active balancing of series-connected lithium iron phosphate batteries. In the absence of accurate in situ state information in the voltage plateau, a balancing current ratio (BCR) based algorithm is proposed for battery balancing. Then, BCR-based and voltage-based algorithms are fused, responsible for the balancing task within and beyond the voltage plateau, respectively. The balancing process is formulated as a batch-based run-to-run control problem, as the first time in the research area of battery management. The control algorithm acts in two timescales, including timewise control within each batch run and batchwise control at the end of each batch. Hardware-in-the-loop experiments demonstrate that the proposed balancing algorithm is able to release 97.1% of the theoretical capacity and can improve the capacity utilization by 5.7% from its benchmarking algorithm. Furthermore, the proposed algorithm can be coded in C language with the binary code in 118 328 bytes only and, thus, is readily implementable in real time