Estimating Markov-Switching ARMA Models with Extended Algorithms of Hamilton

This paper proposes two innovative algorithms to estimate a general class of N-state Markov-switching autoregressive moving-average (MS-ARMA) models with a sample of size T. To resolve the problem of NT possible routes induced by the presence of MA parameters, the first algorithm is built on Hamilton’s (1989) method and Gray’s (1996) idea of replacing the lagged error terms with their corresponding conditional expectations. We thus name it as the Hamilton-Gray (HG) algorithm. The second method refines the HG algorithm by recursively updating the conditional expectations of these errors and is named as the extended Hamilton-Gray (EHG) algorithm. The computational cost of both algorithms is very mild, because the implementation of these algorithms is very much similar to that of Hamilton (1989). The simulations show that the finite sample performance of the EHG algorithm is very satisfactory and is much better than that of the HG counterpart. We also apply the EHG algorithm to the issues of dating U.S. business cycles with the same real GNP data employed in Hamilton (1989). The turning points identified with the EHG algorithm resemble closely to those of the NBER’s Business Cycle Dating Committee and confirm the robustness of the findings in Hamilton (1989) about the effectiveness of Markov-switching models in dating U.S. business cycles.Markov-switching, ARMA process

Noninvasive prediction of Blood Lactate through a machine learning-based approach.

We hypothesized that blood lactate concentration([Lac]blood) is a function of cardiopulmonary variables, exercise intensity and some anthropometric elements during aerobic exercise. This investigation aimed to establish a mathematical model to estimate [Lac]blood noninvasively during constant work rate (CWR) exercise of various intensities. 31 healthy participants were recruited and each underwent 4 cardiopulmonary exercise tests: one incremental and three CWR tests (low: 35% of peak work rate for 15 min, moderate: 60% 10 min and high: 90% 4 min). At the end of each CWR test, venous blood was sampled to determine [Lac]blood. 31 trios of CWR tests were employed to construct the mathematical model, which utilized exponential regression combined with Taylor expansion. Good fitting was achieved when the conditions of low and moderate intensity were put in one model; high-intensity in another. Standard deviation of fitting error in the former condition is 0.52; in the latter is 1.82 mmol/liter. Weighting analysis demonstrated that, besides heart rate, respiratory variables are required in the estimation of [Lac]blood in the model of low/moderate intensity. In conclusion, by measuring noninvasive cardio-respiratory parameters, [Lac]blood during CWR exercise can be determined with good accuracy. This should have application in endurance training and future exercise industry

High-Efficiency Isolated Photovoltaic Microinverter Using Wide-Band Gap Switches for Standalone and Grid-Tied Applications

An isolated photovoltaic micro-inverter for standalone and grid-tied applications is designed and implemented to achieve high efficiency. System configuration and design considerations, including the proposed active-clamp forward-flyback resonant converter for the DC-DC stage and a dual-frequency full-bridge inverter for the DC-AC stage, are analyzed and discussed. A prototype microinverter system is built and tested. Experimental results verify the feasibility of the proposed system, which achieves 95% power conversion efficiency at full load

The mPEG-PCL Copolymer for Selective Fermentation of Staphylococcus lugdunensis Against Candida parapsilosis in the Human Microbiome.

Many human skin diseases, such as seborrheic dermatitis, potentially occur due to the over-growth of fungi. It remains a challenge to develop fungicides with a lower risk of generating resistant fungi and non-specifically killing commensal microbes. Our probiotic approaches using a selective fermentation initiator of skin commensal bacteria, fermentation metabolites or their derivatives provide novel therapeutics to rein in the over-growth of fungi. Staphylococcus lugdunensis (S. lugdunensis) bacteria and Candida parapsilosis (C. parapsilosis) fungi coexist in the scalp microbiome. S. lugdunensis interfered with the growth of C. parapsilosis via fermentation. A methoxy poly(ethylene glycol)-b-poly(ε-caprolactone) (mPEG-PCL) copolymer functioned as a selective fermentation initiator of S. lugdunensis, selectively triggering the S. lugdunensis fermentation to produce acetic and isovaleric acids. The acetic acid and its pro-drug diethyleneglycol diacetate (Ac-DEG-Ac) effectively suppressed the growth of C. parapsilosis in vitro and impeded the fungal expansion in the human dandruff. We demonstrate for the first time that S. lugdunensis is a skin probiotic bacterium that can exploit mPEG-PCL to yield fungicidal short-chain fatty acids (SCFAs). The concept of bacterial fermentation as a part of skin immunity to re-balance the dysbiotic microbiome warrants a novel avenue for studying the probiotic function of the skin microbiome in promoting health

Morus alba and active compound oxyresveratrol exert anti-inflammatory activity via inhibition of leukocyte migration involving MEK/ERK signaling

Background: Morus alba has long been used in traditional Chinese medicine to treat inflammatory diseases;however, the scientific basis for such usage and the mechanism of action are not well understood. This studyinvestigated the action of M. alba on leukocyte migration, one key step in inflammation.Methods: Gas chromatography-mass spectrometry (GC-MS) and cluster analyses of supercritical CO2 extractsof three Morus species were performed for chemotaxonomy-aided plant authentication. Phytochemistry andCXCR4-mediated chemotaxis assays were used to characterize the chemical and biological properties of M. albaand its active compound, oxyresveratrol. fluorescence-activated cell sorting (FACS) and Western blot analyses wereconducted to determine the mode of action of oxyresveratrol.Results: Chemotaxonomy was used to help authenticate M. alba. Chemotaxis-based isolation identifiedoxyresveratrol as an active component in M. alba. Phytochemical and chemotaxis assays showed that the crudeextract, ethyl acetate fraction and oxyresveratrol from M. alba suppressed cell migration of Jurkat T cells in responseto SDF-1. Mechanistic study indicated that oxyresveratrol diminished CXCR4-mediated T-cell migration via inhibitionof the MEK/ERK signaling cascade.Conclusions: A combination of GC-MS and cluster analysis techniques are applicable for authentication of theMorus species. Anti-inflammatory benefits of M. alba and its active compound, oxyresveratrol, may involve theinhibition of CXCR-4-mediated chemotaxis and MEK/ERK pathway in T and other immune cells