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This paper aims to evaluate the effectiveness of the Chinese crop insurance program in terms of farmers' utility and welfare. A simulation model based on the power utility function was first developed to evaluate the effectiveness of crop insurance. Then, the Monte Carlo approach was used to generate the datasets of area, price, yield, cost, and income based on the characteristics of representative farmers, which were clustered and calibrated using the farm-level data of 574 individual farmers from five Chinese provinces. Finally, the effectiveness of Chinese crop insurance was evaluated by comparing the certainty equivalence (CE) of farmers’ utility/welfare under alternative crop insurance scenarios. Government subsidy is a necessary premise for implementing the crop insurance program. The government should subsidize more than 50% of the crop insurance premium to motivate more farmers to participate in the program. The findings also show that the current crop insurance program in China has increased the farmers’ welfare but still need to be improved to achieve the Pareto improvement and to make full use of the financial fund of the government. This paper is believed to not only extend academic research but also has significant implications for policymakers, especially in the context of rapid development of Chinese crop insurance with much issues such as rate, subsidy and coverage level needed to be improved.

Switched mode power converters are nonlinear systems, and it is a constant challenge to improve their modeling accuracy and control performance. In this paper, a State Switched Discrete-time Model (SSDM) is proposed, which achieves a higher accuracy at a high frequency than that of conventional state averaged models. Instead of averaging the converter states for approximation, the states within each switching cycle are considered in the modeling. Based on total differential equations of switching-ON and switching-OFF durations, the inductor current and output voltage within a cycle are accurately calculated, which derives the SSDM. Furthermore, a Digital Predictive Voltage Programmed (DPVP) control strategy is derived through the SSDM. Through voltage prediction, a suitable duty ratio is calculated that regulates the output voltage to its reference value in the minimum switching cycles. In this way, the converter achieves a very fast load/line transient response and reference tracking speed, and it exhibits a high stability under deviated inductance. Finally, the accuracy of SSDM and the system stability are proved by frequency response analyses and experiments.

Advances in cancer treatment have led to significant improvements in long-term survival in many types of cancer, but heart dysfunction and heart failure, associated with cancer treatment, have also increased. Anthracyclines are the main cause of this type of cardiotoxicity. In this study, we describe a combined experimental and cell morphology analysis approach for the high-throughput measurement and analysis of a cardiomyocyte cell profile, using partial least square linear discriminant analysis (PLS-LDA) as the pattern recognition algorithm. When screening a small-scale natural compound library, rosmarinic acid (RosA), as a candidate drug, showed the same cardioprotective effect as the positive control. We investigated the protective mechanism of RosA on a human cardiomyocyte cell line (AC16) and human induced pluripotent stem-cell-derived cardiomyocytes (hiPSC-CMs). We showed that RosA pretreatment suppressed doxorubicin (Dox)-induced cell apoptosis and decreased the activity of caspase-9. RosA promotes the expression of Heme oxygenase-1 (HO-1) and reduces the production of reactive oxygen species (Ros), which is induced by Dox. Meanwhile, it can also promote the expression of cardiac-development-related protein, including histone deacetylase 1 (HDAC1), GATA binding protein 4 (GATA4) and troponin I3, cardiac type (CTnI). Collectively, our data support the notion that RosA is a protective agent in hiPSC-CMs and has the potential for therapeutic use in the treatment of cancer therapy-related cardiac dysfunction and heart failure.

In this study, the effects of hydrogen on the electrochemical behavior and stress corrosion behavior of C110 steel in CO _2 environment was explored by electrochemical hydrogen charging, four-point bending stress loading and electrochemical test. The results show that with the raise of applied stress, the film resistance, transfer resistance of corrosion products decrease, and I _corr increases. After hydrogen charging, C110 steel has greater activity, and the combined action of external stress further promotes the corrosion reaction. The application of stress will destroy the formation of corrosion product film and reduce its protection. However, when the stress is further increased to 102% σ _s , the larger grains will be broken into smaller grains, so that the surface area of the film will be increased again and the protection of the substrate will be enhanced. The main corrosion products analyzed by XRD are α -Fe, Fe _2 O _3 and MgFe _2 O _4 . The applied stress will not change the phase composition of the corrosion products.

Temporal associations in longitudinal nontargeted metabolomics data are generally ignored by common pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA). To discover temporal patterns in longitudinal metabolomics, a multitask learning (MTL) method employing structural regularization was proposed. The group regularization term of the proposed MTL method enables the selection of a small number of tentative biomarkers while maintaining high prediction accuracy. Meanwhile, the nuclear norm imposed into the regression coefficient accounts for the interrelationship of the metabolomics data obtained on consecutive time points. The effectiveness of the proposed method was demonstrated by comparison study performed on a metabolomics dataset and a simulating dataset. The results showed that a compact set of tentative biomarkers charactering the whole antipyretic process of Qingkailing injection were selected with the proposed method. In addition, the nuclear norm introduced in the new method could help the group norm to improve the method’s recovery ability.

In refineries, amine-based chemical absorption is an effective technique to treat acid impurities (i.e. H2S and CO2) in hydrogen flows. Therefore, introducing chemical absorption units for acid impurity removal in refinery hydrogen networks could enhance the recovery and reuse of hydrogen, reducing the fresh hydrogen consumption. In this work, a novel pinch-based graphical method is proposed for integration of hydrogen network with chemical absorption untis for impurity removal. The proposed method is able to target the maximum fresh hydrogen saved by introducing impurity removal while minimizing the total flow rate of hydrogen sources fed to the impurity removal unit. Any hydrogen sources in a hydrogen network can be treated as the feedstock of the impurity removal unit. A case study is performed to illustrate the applicability of this graphical method.

The dried roots of Euphorbia kansui S.L.Liou ex S.B.Ho have long been used to treat edema in China. However, the severe toxicity caused by Euphorbia kansui (EK) has seriously restricted its clinical application. Although EK was processed with vinegar to reduce its toxicity, the detailed mechanisms of attenuation in toxicity of EK stir-fried with vinegar (VEK) have not been well delineated. Diterpenoids are the main toxic ingredients of EK, and changes in these after processing may be the underlying mechanism of toxicity attenuation of VEK. 3-O-(2′E,4′Z-decadienoyl)-20-O-acetylingenol (3-O-EZ) is one of the diterpenoids derived from EK, and the content of 3-O-EZ was significantly reduced after processing. This study aims to explore the underlying mechanisms of toxicity reduction of VEK based on the change of 3-O-EZ after processing with vinegar. Based on the chemical structure of 3-O-EZ and the method of processing with vinegar, simulation experiments were carried out to confirm the presence of the product both in EK and VEK and to enrich the product. Then, the difference of peak area of 3-O-EZ and its hydrolysate in EK and VEK were detected by ultra-high-performance liquid chromatography (UPLC). Furthermore, the toxicity effect of 3-O-EZ and its hydrolysate, as well as the underlying mechanism, on zebrafish embryos were investigated. The findings showed that the diterpenoids (3-O-EZ) in EK can convert into less toxic ingenol in VEK after processing with vinegar; meanwhile, the content of ingenol in VEK was higher than that of EK. More interestingly, the ingenol exhibited less toxicity (acute toxicity, developmental toxicity and organic toxicity) than that of 3-O-EZ, and 3-O-EZ could increase malondialdehyde (MDA) content and reduce glutathione (GSH) content; cause embryo oxidative damage by inhibition of the succinate dehydrogenase (SDH) and superoxide dismutase (SOD) activity; and induce inflammation and apoptosis by elevation of IL-2 and IL-8 contents and activation of the caspase-3 and caspase-9 activity. Thus, this study contributes to our understanding of the mechanism of attenuation in toxicity of VEK, and provides the possibility of safe and rational use of EK in clinics.

In this paper, a class of nonlinear p-Laplace diffusion BAM Cohen-Grossberg neural networks (BAM CGNNs) with time delays is investigated. In the case of p>1 with p≠2, the authors construct novel Lyapunov functional to overcome the mathematical difficulties of nonlinear p-Laplace diffusion time-delay model with parameter uncertainties, deriving the LMI-based robust stability criterion applicable to computer MATLAB LMI toolbox and deleting the boundedness of the amplification functions. And in the case of p=2, LMI-based sufficient conditions are also inferred for robust input-to-state stability of reaction-diffusion Markovian jumping BAM CGNNs with the event-triggered control, which is different from those of many previous related literature. In particular, the role of diffusion can be reflected in newly acquired criteria. Finally, numerical examples verify the effectiveness of the proposed methods.

Due to the wide deployment of wireless local area networks (WLAN), received signal strength (RSS)-based indoor WLAN localization has attracted considerable attention in both academia and industry. In this paper, we propose a novel page rank-based indoor mapping and localization (PRIMAL) by using the gene-sequenced unlabeled WLAN RSS for simultaneous localization and mapping (SLAM). Specifically, first of all, based on the observation of the motion patterns of the people in the target environment, we use the Allen logic to construct the mobility graph to characterize the connectivity among different areas of interest. Second, the concept of gene sequencing is utilized to assemble the sporadically-collected RSS sequences into a signal graph based on the transition relations among different RSS sequences. Third, we apply the graph drawing approach to exhibit both the mobility graph and signal graph in a more readable manner. Finally, the page rank (PR) algorithm is proposed to construct the mapping from the signal graph into the mobility graph. The experimental results show that the proposed approach achieves satisfactory localization accuracy and meanwhile avoids the intensive time and labor cost involved in the conventional location fingerprinting-based indoor WLAN localization.

Model performance of the partial least squares method (PLS) alone and bagging-PLS was investigated in online near-infrared (NIR) sensor monitoring of pilot-scale extraction process in Fructus aurantii. High-performance liquid chromatography (HPLC) was used as a reference method to identify the active pharmaceutical ingredients: naringin, hesperidin and neohesperidin. Several preprocessing methods and synergy interval partial least squares (SiPLS) and moving window partial least squares (MWPLS) variable selection methods were compared. Single quantification models (PLS) and ensemble methods combined with partial least squares (bagging-PLS) were developed for quantitative analysis of naringin, hesperidin and neohesperidin. SiPLS was compared to SiPLS combined with bagging-PLS. Final results showed the root mean square error of prediction (RMSEP) of bagging-PLS to be lower than that of PLS regression alone. For this reason, an ensemble method of online NIR sensor is here proposed as a means of monitoring the pilot-scale extraction process in Fructus aurantii, which may also constitute a suitable strategy for online NIR monitoring of CHM.

To realize accurate current control for a boost converter, a precise measurement of the inductor current is required to achieve high resolution current regulating. Current sensors are widely used to measure the inductor current. However, the current sensors and their processing circuits significantly contribute extra hardware cost, delay and noise to the system. They can also harm the system reliability. Therefore, current sensorless control techniques can bring cost effective and reliable solutions for various boost converter applications. According to the derived accurate model, which contains a number of parasitics, the boost converter is a nonlinear system. An Extended Kalman Filter (EKF) is proposed for inductor current estimation and output voltage filtering. With this approach, the system can have the same advantages as sensored current control mode. To implement EKF, the load value is necessary. However, the load may vary from time to time. This can lead to errors of current estimation and filtered output voltage. To solve this issue, a load variation elimination effect elimination (LVEE) module is added. In addition, a predictive average current controller is used to regulate the current. Compared with conventional voltage controlled system, the transient response is greatly improved since it only takes two switching cycles for the current to reach its reference. Finally, experimental results are presented to verify the stable operation and output tracking capability for large-signal transients of the proposed algorithm.

Therapeutic strategies for neurological deficits and for promoting nerve regeneration after peripheral nerve injuries have received much focus in clinical research. Advances in basic research in recent years have increased our understanding of the anatomy of peripheral nerves and the importance of the microenvironment. Various new intervention methods have been developed, but with varying effectiveness. In the present study, we selected 911 papers on different repair methods for peripheral nerve injury from the Web of Science and indexed in the Science Citation Index from 2010 to 2014. We quantitatively examine new repair methods and strategies using bibliometrics, and we discuss the present state of knowledge and the problems and prospects of various repair methods, including nerve transfer, neural transplantation, tissue engineering and genetic engineering. Our findings should help in the study and development of repair methods for peripheral nerve injury.

Laser-induced breakdown spectroscopy (LIBS) was applied to perform a rapid elemental analysis and provenance study of Blumea balsamifera DC. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were implemented to exploit the multivariate nature of the LIBS data. Scores and loadings of computed principal components visually illustrated the differing spectral data. The PLS-DA algorithm showed good classification performance. The PLS-DA model using complete spectra as input variables had similar discrimination performance to using selected spectral lines as input variables. The down-selection of spectral lines was specifically focused on the major elements of B. balsamifera samples. Results indicated that LIBS could be used to rapidly analyze elements and to perform provenance study of B. balsamifera.

Neuritin plays a key role in neural development and regeneration by promoting neurite outgrowth and synapse maturation. However, the mechanism of neuritin in modulating neurite growth has not been elucidated. Here, using yeast two-hybrid we screened and discovered the interaction of neuritin and neuralized (NEURL1), which is an important regulator that can activate Notch signaling through promoting endocytosis of Notch ligand. And then we identified the interaction of neuritin and neuralized by co-immunoprecipitation (IP) assays, and clarified that neuritin and NEURL1 were co-localized on the cell membrane of SH-SY5Y cells. Moreover, neuritin significantly suppressed Notch ligand Jagged1 (JAG1) endocytosis promoted by NEURL1, and then inhibited the activation of Notch receptor Notch intracellular domain (NICD) and decreased the expression of downstream gene hairy and enhancer of split-1 (HES1). Importantly, the effect of neuritin on inhibiting Notch signaling was rescued by NEURL1, which indicated that neuritin is an upstream and negative regulator of NEURL1 to inhibit Notch signaling through interaction with NEURL1. Notably, recombinant neuritin restored the retraction of neurites caused by activation of Notch, and neurite growth stimulated by neuritin was partially blocked by NEURL1. These findings establish neuritin as an upstream and negative regulator of NEURL1 that inhibits Notch signaling to promote neurite growth. This mechanism connects neuritin with Notch signaling, and provides a valuable foundation for further investigation of neuritin’s role in neurodevelopment and neural plasticity.

BACKGROUND:Non-coding circular RNAs (circRNAs) have displayed dysregulated expression in several human cancers. Here, we profiled the circRNA expression of papillary thyroid carcinoma (PTC) tumors to improve our understanding of PTC pathogenesis. METHODS:Microarray profiling was performed on 18 thyroid samples, consisting of six PTC tumors, six matching contralateral normal samples, and six benign thyroid lesions. After low-intensity filtering, hierarchical clustering revealed the circRNA expression patterns. Statistical analysis followed by qRT-PCR validation identified the differential circRNAs. MicroRNA (miRNA) target prediction software identified putative miRNA response elements (MREs), which were used to construct a network map of circRNA-miRNA interactions for the differential circRNAs. Bioinformatics platforms predicted cancer-related circRNA-miRNA associations and putative downstream target genes, respectively. RESULTS:A total of 88 circRNAs and 10 circRNAs were significantly upregulated and downregulated, respectively, in PTC tumors relative to normal thyroid tissue, while 129 circRNAs and 226 circRNAs were significantly upregulated and downregulated, respectively, in PTC tumors relative to benign thyroid lesions. A total of 12 upregulated and four downregulated circRNAs were overlapping between the foregoing comparisons. One downregulated circRNA (hsa_circRNA_100395) showed interactive potential with two cancer-related miRNAs (miR-141-3p and miR-200a-3p). From this analysis, we identified several promising cancer-related genes that may be targets of the dysregulated hsa_circRNA_100395/miR-141-3p/miR-200a-3p axis in PTC tumors. CONCLUSIONS:circRNA dysregulation may play a role in PTC pathogenesis, and several key circRNAs show promise as candidate biomarkers for PTC. The hsa_circRNA_100395/miR-141-3p/ miR-200a-3p axis may be involved in the pathogenesis of PTC.

Introduction. Double aortic arch is a congenital vascular abnormality in which the connected segments and their branches course between and compress the trachea and esophagus, often resulting in invariable airway compression. Case Presentation. A 4-year-old boy with a history of recurrent wheezing was admitted to our hospital for evaluation of asthma based on his past medical history, persistent cough, wheezing, and airway hyperresponsiveness by lung function test. Double aortic arch was diagnosed with computed tomography angiogram. After surgery, the respiratory infection improved strikingly. Early diagnosis and treatment may prevent chronic, irreversible complications. Conclusion. We present a case of double aortic arch masquerading as asthma.

Previously, we reported that cAMP/PKA signaling is involved in GPER-mediated coronary relaxation by activating MLCP via inhibition of RhoA pathway. In the current study, we tested the hypothesis that activation of GPER induces coronary artery relaxation via inhibition of RhoA/Rho kinase pathway by cAMP downstream targets, exchange proteins directly activated by cAMP (Epac) as well as PKA. Our results show that Epac inhibitors, brefeldin A (BFA, 50 μM), or ESI-09 (20 μM), or CE3F4 (100 μM), all partially inhibited porcine coronary artery relaxation response to the selective GPER agonist, G-1 (0.3-3 μM); while concurrent administration of BFA and PKI (5 μM), a PKA inhibitor, almost completely blocked the relaxation effect of G-1. The Epac specific agonist, 8-CPT-2Me-cAMP (007, 1-100 μM), induced a concentration-dependent relaxation response. Furthermore, the activity of Ras-related protein 1 (Rap1) was up regulated by G-1 (1 μM) treatment of porcine coronary artery smooth muscle cells (CASMCs). Phosphorylation of vasodilator-stimulated phosphoprotein (p-VASP) was elevated by G-1 (1 μM) treatment, but not by 007 (50 μM); and the effect of G-1 on p-VASP was blocked by PKI, but not by ESI-09, an Epac antagonist. RhoA activity was similarly down regulated by G-1 and 007, whereas ESI-09 restored most of the reduced RhoA activity by G-1 treatment. Furthermore, G-1 decreased PGF2α-induced p-MYPT1, which was partially reversed with either ESI-09 or PKI; whereas, concurrent administration of ESI-09 and PKI totally prevented the inhibitory effect of G-1. The inhibitory effects of G-1 on p- MLC levels in CASMCs were mostly restored by either ESI-09 or PKI. These results demonstrate that activation of GPER induces coronary artery relaxation via concurrent inhibition of RhoA/Rho kinase by Epac/Rap1 and PKA. GPER could be a potential drug target for preventing and treating cardiovascular diseases.

In digital current mode controlled DC-DC converters, conventional current sensors might not provide isolation at a minimized price, power loss and size. Therefore, a current observer which can be realized based on the digital circuit itself, is a possible substitute. However, the observed current may diverge due to the parasitic resistors and the forward conduction voltage of the diode. Moreover, the divergence of the observed current will cause steady state errors in the output voltage. In this paper, an optimal current observer is proposed. It achieves the highest observation accuracy by compensating for all the known parasitic parameters. By employing the optimal current observer-based predictive current controller, a buck converter is implemented. The converter has a convergently and accurately observed inductor current, and shows preferable transient response than the conventional voltage mode controlled converter. Besides, costs, power loss and size are minimized since the strategy requires no additional hardware for current sensing. The effectiveness of the proposed optimal current observer is demonstrated experimentally.

The complex structure of fish and multispecies composition complicate the analysis of acoustic data. Consequently, it is difficult to obtain a highly accurate rate of classification by using current approaches. A method of fish classification based on the wavelet packet and bi-spectrum is proposed in this paper. To verify this method, firstly, an ex situ experiment has been performed with three kinds of fish: Crucian carp (Carassius auratus), Yellow-headed catfish (Pelteobagrus fulvidraco) and Bluntnose black bream (Megalobrama amblycephale). The backscattering signals of these fishes are obtained. Secondly, the wavelet packet decomposition of backscattering envelop is done, and the energy of main frequency bands which is reconstructed from each node are calculated. Thirdly, the bi- spectrum of envelop which is constructed using the backscattering of main frequency band in order to filtering the high frequency noise, is extracted as the additional feature. The sub-band energy of wavelet packet and the bi-spectrum are combined as the characteristic indicator to describe the fish feature. Finally, three kinds of fish are successfully classified by the RBF support vector machine classifier. The results reveal that the proposed method has a highly accuracy rate of classification at fish with different shapes.

Near infrared chemical imaging (NIR-CI) combines conventional near infrared (NIR) spectroscopy with chemical imaging, thus provides spectral and spatial information simultaneously. It could be utilized to visualize the spatial distribution of the ingredients in a sample. The data acquired using NIR-CI instrument are hyperspectral data cube (hypercube) containing thousands of spectra. Chemometric methodologies are necessary to transform spectral information into chemical information. Partial least squares (PLS) method was performed to extract chemical information of chlorpheniramine maleate in pharmaceutical formulations. A series of samples which consisted of different CPM concentrations (w/w) were compressed and hypercube data were measured. The spectra extracted from the hypercube were used to establish the PLS model of CPM. The results of the model were Rval2 0.981, RMSEC 0.384%, RMSECV 0.483%, RMSEP 0.631%, indicating that this model was reliable.

Oxidative stress is the main pathogenesis of diabetic microangiopathy, which can cause microvascular endothelial cell damage and destroy vascular barrier. In this study, it is found that carnosol protects human microvascular endothelial cells (HMVEC) through antioxidative mechanisms. First, we measured the antioxidant activity of carnosol. We showed that carnosol pretreatment suppressed tert-butyl hydroperoxide (t-BHP)-induced cell viability, affected the production of lactate dehydrogenase (LDH) as well as reactive oxygen species (ROS), and increased the produce of nitric oxide (NO). Additionally, carnosol promotes the protein expression of vascular endothelial cadherin (VE-cadherin) to keep the integrity of intercellular junctions, which indicated that it protected microvascular barrier in oxidative stress. Meanwhile, we investigated that carnosol can interrupt Nrf2-Keap1 protein−protein interaction and stimulated antioxidant-responsive element (ARE)-driven luciferase activity in vitro. Mechanistically, we showed that carnosol promotes the expression of heme oxygenase 1(HO-1) and nuclear factor-erythroid 2 related factor 2(Nrf2). It can also promote the expression of endothelial nitric oxide synthase (eNOS). Collectively, our data support the notion that carnosol is a protective agent in HMVECs and has the potential for therapeutic use in the treatments of microvascular endothelial cell injury.

Flood catastrophe risk assessment is imperative for the steady development of agriculture under the context of global climate change, and meanwhile, it is an urgent scientific issue need to be solved in agricultural risk assessment discipline. This paper developed the methodology of flood catastrophe risk assessment, which can be shown as the standard process of crop loss calculation, Monte Carlo simulation, the generalized extreme value distribution (GEV) fitting, and risk evaluation. Data on crop loss were collected based on hectares covered by natural disasters, hectares affected by natural disasters, and hectares destroyed by natural disasters using the standard equation. Monte Carlo simulation based on appropriate distribution was used to expand sample size to overcome the insufficiency of crop loss data. Block maxima model (BMM) approach based on the extreme value theory was for modeling the generalized extreme value distribution (GEV) of flood catastrophe loss, and then flood catastrophe risk at the provincial scale in China was calculated. The Type III Extreme distribution (Weibull) has a weighted advantage of modeling flood catastrophe risk for grain production. The impact of flood catastrophe to grain production in China was significantly serious, and high or very high risk of flood catastrophe mainly concentrates on the central and eastern regions of China. Given the scenario of suffering once-in-a-century flood disaster, for majority of the major-producing provinces, the probability of 10% reduction of grain output is more than 90%. Especially, the probabilities of more than 15% decline in grain production reach up to 99.99, 99.86, 99.69, and 91.60% respectively in Anhui, Jilin, Liaoning, and Heilongjiang. Flood catastrophe assessment can provide multifaceted information about flood catastrophe risk that can help to guide management of flood catastrophe.

Euphorbia kansui stir-fried with vinegar (V-kansui) has promising biological activities toward treating malignant ascites with reduced toxicity compared to crude kansui. But the mechanism concerning promoting the excretion of ascites has not been systematically studied. The purpose of this paper was to investigate the possible mechanism of V-kansui in treating malignant ascites, including metabolic pathways and molecular mechanism using an integrated serum and urine metabolomics coupled with network pharmacology. Serum and urine samples of rats were collected and analyzed by ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS). A comparison with crude kansui was also made to demonstrate the feasibility of processing. Principle component analysis (PCA) and orthogonal partial least square discriminate analysis (OPLS-DA) were conducted to discriminate the groups, search important variables and reveal the possible pathways. A compound-target-metabolite network was finally constructed to identify the crucial targets to further understand the molecular mechanism. Sixteen significant metabolites contributing to the discrimination of model and control groups were tentatively screened out. They were mainly involved in the arachidonic acid metabolism, steroid hormone biosynthesis and primary bile acid to possibly reduce inflammatory and modulate the renin-angiotensin-aldosterone system to achieve treating malignant ascites. A bio-network starting from the compounds and ending in the metabolites was constructed to elucidate the molecular mechanism. HSP90AA1, ANXA2, PRDX6, PCNA, SOD2 and ALB were identified as the potential key targets that were responsible for the treatment of malignant ascites by the parameter combining the average shortest path length and betweenness centrality. The correlated 17 compounds were considered as the potential active ingredients in V-kansui. In addition, the metabolomics showed that the effect of V-kansui was almost in accordance with crude kansui. These results systematically revealed the mechanism of V-kansui against malignant ascites for the first time using metabolomics coupled with network pharmacology. V-kansui could be a promising safe and therapeutic medicine for the excretion of ascites.

In servo systems, encoders are usually used to measure the position and speed signals of electric machines. But in a low speed range, the traditional M/T method has a larger time delay, which will cause an increase of the speed loop order and degradation of the speed loop performance. A method employed to reduce the delay of speed feedback by using a reduced-order Extended Kalman Filter (EKF) is introduced in this paper. The speed of the permanent magnet synchronous motor is estimated by the reduced-order EKF in a low speed range, which reduces the delay of speed feedback and extends the cutoff frequency of the speed loop to improve the dynamic performance of the servo system. In order to solve the issues that the traditional full-order EKF is sensitive to the inertia of the system and computationally complex, a composite load torque observer (CLTO) is proposed in this paper. The load torque and the friction torque are simultaneously observed by the CLTO. Additionally, the CLTO is used to reduce the order of the EKF, which reduces the sensitivity of EKF on inertia to enhance the robustness of the algorithm and simplifies the computational complexity. The feasibility and effectivity of the above method are verified by simulations and experiments.

Purpose: The paper validates a model which approximates a relationship between perceived uncertainty of consumers and two antecedents & three mitigators which explain the value of Food Traceability System (FTS). Methodology/Approach: The proposed model was drawn from Pavlou et al. (2007) study which applied the principal-agent perspectives, and this study contributes to the current literature by improving understanding of the structure of perceived uncertainty of a food product with credence good with this model. Findings: The study assesses the value and effects of FTS in reducing perceived uncertainty of beef from various origins and suggests important implications for stakeholders in beef sector regarding feasibility and marketability of FTS. Research Limitation/Implication: Findings evidently reflect the current market circumstance regarding consumers’ concerns and Perceived Uncertainty towards import food products for their credence nature. Different aspects of FTS were found to have the mediating role in reducing Perceived Uncertainty in China and South Korea. Originality/Value of paper: The study assesses the value and effects of FTS in reducing perceived uncertainty of beef from various origins and suggests important implications for stakeholders in beef sector regarding feasibility and marketability of FTS.

In this paper, a simple and efficient rule based energy management system for battery and supercapacitor hybrid energy storage system (HESS) used in electric vehicles is presented. The objective of the proposed energy management system is to focus on exploiting the supercapacitor characteristics and on increasing the battery lifetime and system efficiency. The role of the energy management system is to yield battery reference current, which is subsequently used by the controller of the DC/DC converter. First, a current controller is designed to realize load current distribution between battery and supercapacitor. Then a voltage controller is designed to ensure the supercapacitor SOC to fluctuate within a preset reasonable variation range. Finally, a commercial experimental platform is developed to verify the proposed control strategy. In addition, the energy efficiency and the cost analysis of the hybrid system are carried out based on the experimental results to explore the most cost-effective tradeoff.

Layered double hydroxide (LDH) is a layered solid containing positively charged layers with negatively charged anions as an interchangeable interlayer. In this research, Mg(Al)O supports were synthesized with three different Mg:Al molar ratios, and bimetallic PtSn catalysts were loaded onto the supports via the anion exchange method. The properties of ethane dehydrogenation of the PtSn/Mg(Al)O catalysts were investigated. The results show that the structure and properties of the PtSn/Mg(Al)O catalysts were influenced by the Mg:Al molar ratio of the hydrotalcites, which consequently influenced the ethane dehydrogenation performance. When the Mg:Al ratio was 5:1, the ethane dehydrogenation performance was optimal, relative to the Mg:Al ratios of 2:1 and 10:1.

In this research, a new triterpenoid, tirucalla-8,24-diene-3β,11β-diol-7-one (1), and eupha-8,24-diene-3β,11β-diol-7-one (2), which was isolated from Euphorbia kansui for the first time, together with twelve other known compounds (3–14), were isolated from the ethyl acetate extract of Euphorbia kansui. Their structures were elucidated based on High resolution electrospray ionization mass spectrometry (HR-ESI-MS), Infrared Spectroscopy (IR), 1D and 2D Nuclear Magnetic Resonance (NMR) data. Both constituents 1 and 2 exhibited moderate cytotoxicity against colon cancer HCT-116, gastric cancer MKN-45 and breast cancer MCF-7.

We conducted a meta-analysis to comprehensively evaluate the correlations of ezrin expression with pathological characteristics and the prognosis of osteosarcoma. The MEDLINE (1966–2013), the Cochrane Library Database, EMBASE, CINAHL, Web of Science (1945–2013), and the Chinese Biomedical Database were searched without language restrictions. Meta-analyses conducted using STATA software were calculated. Ten studies met the inclusion criteria, including 459 patients with osteosarcoma. Meta-analysis results illustrated that ezrin expression may be closely associated with the recurrence of osteosarcoma or metastasis in osteosarcoma. Our findings also demonstrated that patients with grade III-IV osteosarcoma showed a higher frequency of ezrin expression than those with histological grade I-II osteosarcoma. Furthermore, we found that patients with positive expression of ezrin exhibited a shorter overall survival than those with negative ezrin expression. The results also indicated that positive ezrin expression was strongly correlated with poorer metastasis-free survival. Nevertheless, no significant relationships were observed between ezrin expression and clinical variables (age and gender). In the current meta-analysis, our results illustrated significant relationships of ezrin expression with pathological characteristics and prognosis of osteosarcoma. Thus, ezrin expression could be a promising marker in predicting the clinical outcome of patients with osteosarcoma.

Location estimation plays a crucial role in Location-Based Services (LBSs) with satisfactory user experience. The Wireless Local Area Network (WLAN) localization approach is preferred as a cost-efficient solution to indoor localization on account of the widely-deployed WLAN infrastructures. In this paper, we propose a new WLAN Received Signal Strength (RSS)-based indoor localization approach using the semi-supervised manifold alignment with dimension expansion. In concrete terms, we first construct an innovative objective function based on the augmented physical coordinates and the corresponding WLAN RSS measurements. Second, the closed-form solution to the objective function is derived out according to the Lagrange multiplier equation, which results in the manifold in physical coordinate space. Third, the target location is estimated by matching the transformed newly-collected RSS against the manifold. The localization performance with noise perturbation is analyzed upon the constructed objective function, and meanwhile, the closed-form solution to the objective function with respect to multiple types of measurements is also derived out for the sake of leveraging all of the potential measurements for indoor localization. The extensive testing results show that the proposed approach performs well in localization accuracy even at low calibration load, and its performance can be further improved by using multiple types of measurements for localization.

In the Drosophila female germline, spatially and temporally specific translation of mRNAs governs both stem cell maintenance and the differentiation of their progeny. However, the mechanisms that control and coordinate different modes of translational repression within this lineage remain incompletely understood. Here we present data showing that Mei-P26 associates with Bam, Bgcn and Sxl and nanos mRNA during early cyst development, suggesting that this protein helps to repress the translation of nanos mRNA. Together with recently published studies, these data suggest that Mei-P26 mediates both GSC self-renewal and germline differentiation through distinct modes of translational repression depending on the presence of Bam.

Crop’s risk assessment induced by natural disasters needs to develop in the fine scale. It is required that risk assessment can be performed on county-level space scale and month-based time scale. But with the thinning of space and time scales, disaster samples would decline greatly and severely limit the usage of risk assessment method based on the statistic of samples. Therefore, in this paper, a new method on base of metrological data and crop’s vulnerability models was proposed to assess risk variability among months on county scale. Since the weather stations cannot cover all the counties, the IDW method was used to interpolate the daily rainfall for each county by its nearby 3 stations. Moreover, based on the flood record data, the vulnerability function between crop’s flood-effected area and average daily rainfall in a storm was regressed. Using the information diffusion model of nonparametric kernel density, the probability density function of average daily rainfall in a storm for each month of each county was fitted. Finally, the expected disaster-effected area of crops as risk measure for each month of each county was calculated on the combination of probability function and vulnerability function. Through the case study in three northeastern provinces of China, a serial of risk maps on county-level and month-level scales were produced to be used to recognize the rules of risk variability in space and time.

Endothelin-1 (ET-1) autocrine and paracrine signaling modulate cell proliferation of tumor cells by activating its receptors, endothelin A receptor (ETAR) and endothelin B receptor (ETBR). Dysregulation of ETAR activation promotes tumor development and progression. The potential of ETAR antagonists and the dual-ETAR and ETBR antagonists as therapeutic approaches are under preclinical and clinical studies. Salvianolic acid A (Sal A) is a hydrophilic polyphenolic derivative isolated from Salvia miltiorrhiza Bunge (Danshen), which has been reported as an anti-cancer and cardio-protective herbal medicine. In this study, we demonstrate that Sal A inhibits ETAR activation induced by ET-1 in both recombinant and endogenous ETAR expression cell lines. The IC50 values were determined as 5.7 µM in the HEK293/ETAR cell line and 3.14 µM in HeLa cells, respectively. Furthermore, our results showed that Sal A suppressed cell proliferation and extended the doubling times of multiple cancer cells, including HeLa, DU145, H1975, and A549 cell lines. In addition, Sal A inhibited proliferation of DU145 cell lines stimulated by exogenous ET-1 treatment. Moreover, the cytotoxicity and cardio-toxicity of Sal A were assessed in human umbilical vein endothelial cells (HUVEC) and Human-induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs), which proved that Sal A demonstrates no cytotoxicity or cardiotoxicity. Collectively, our findings indicate that Sal A is a novel anti-cancer candidate through targeting ETAR.

Since driving cycle greatly affects load power demand, driving cycle identification (DCI) is proposed to predict power demand that can be expected to prepare for the power distribution between battery and supercapacitor. The DCI is developed based on a learning vector quantization (LVQ) neural network method, which is assessed in both training and validation based on the statistical data obtained from six standard driving cycles. In order to ensure network accuracy, characteristic parameter and slide time window, which are two important factors ensuring the network accuracy for onboard hybrid energy storage system (HESS) applications in electric vehicles, are discussed and designed. Based on the identification results, Multi-level Haar wavelet transform (Haar-WT) is proposed for allocating the high frequency components of power demand into the supercapacitor which could damage battery lifetime and the corresponding low frequency components into the battery system. The proposed energy management system can better increase system efficiency and battery lifetime compared with the conventional sole frequency control. The advantages are demonstrated based on a randomly generated driving cycle from the standard driving cycle library via simulation.

Due to drug-induced potential congestive heart failure and irreversible dilated cardiomyopathies, preclinical evaluation of cardiac dysfunction is important to assess the safety of traditional or novel treatments. The embryos of Nelumbo nucifera Gaertner seeds are a homology of traditional Chinese medicine and food. In this study, we applied the real time cellular analysis (RTCA) Cardio system, which can real-time monitor the contractility of cardiomyocytes (CMs), to evaluate drug safety in rat neonatal CMs and human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). This study showed detailed biomechanical CM contractility in vitro, and provided insights into the cardiac dysfunctions associated with liensinine and neferine treatment. These effects exhibited dose and time-dependent recovery. Neferine showed stronger blocking effect in rat neonatal CMs than liensinine. In addition, the effects of liensinine and neferine were further evaluated on hiPS-CMs. Our study also indicated that both liensinine and neferine can cause disruption of calcium homeostasis. For the first time, we demonstrated the potential cardiac side effects of liensinine or neferine. While the same inhibition was observed on hiPS-CMs, more importantly, this study introduced an efficient and effective approach to evaluate the cardiotoxicity of the existing and novel drug candidates.

To accurately, safely, and efficiently evaluate the bitterness of Traditional Chinese Medicines (TCMs), a robust predictor was developed using robust partial least squares (RPLS) regression method based on data obtained from an electronic tongue (e-tongue) system. The data quality was verified by the Grubb’s test. Moreover, potential outliers were detected based on both the standardized residual and score distance calculated for each sample. The performance of RPLS on the dataset before and after outlier detection was compared to other state-of-the-art methods including multivariate linear regression, least squares support vector machine, and the plain partial least squares regression. Both R2 and root-mean-squares error (RMSE) of cross-validation (CV) were recorded for each model. With four latent variables, a robust RMSECV value of 0.3916 with bitterness values ranging from 0.63 to 4.78 were obtained for the RPLS model that was constructed based on the dataset including outliers. Meanwhile, the RMSECV, which was calculated using the models constructed by other methods, was larger than that of the RPLS model. After six outliers were excluded, the performance of all benchmark methods markedly improved, but the difference between the RPLS model constructed before and after outlier exclusion was negligible. In conclusion, the bitterness of TCM decoctions can be accurately evaluated with the RPLS model constructed using e-tongue data.

BACKGROUND: While HPV infection is the main cause of cervical cancer, genetic susceptibility to HPV infection is not well understood. Tumor necrosis factor alpha (TNF-alpha), involved in the defense against HPV infection, plays an important role in cervical cancer progression and regression. The aim of this study was to investigate the relationship between the TNF-alpha rs1800629 polymorphism and risk of HPV infection or cervical cancer. METHODS: Three groups were involved in this study of Chinese women. Group 1 consisted of 285 high risk HPV positive cervical cancer patients, Group 2, 225 high risk HPV positive patients without cervical cancer, and Group 3, 318 HPV negative women with no cervical cancer. Blood samples were obtained from all patients and genotyped by PCR-RLFP. Fifty randomly selected samples were further sequenced. RESULTS: The allele and genotype distributions of the TNF-alpha rs1800629 polymorphism were not significantly different between each of the groups (P>0.05). There are no significant relationship between rs1800629 polymorphism and high risk HPV infection (OR = 0.649, 95% CI: 0.253-1.670, P = 0.371), cervical cancer (OR = 0.993, 95% CI: 0.376-2.618, P = 0.988), or cervical cancer with HPV infection (OR = 0.663, 95% CI: 0.250-1.758, P = 0.409). CONCLUSIONS: We demonstrated that there is no association between TNF rs1800629 polymorphism and the HPV infection, or cervical cancer with HPV infection.