Comparitive Study On Antioxidant Properties Of Dendrobium Officinale (tiepishihu)

For ages, Chinese herbs, such as Dendrobium Officinale (DO), have been used in Asian regions for treating various illnesses due to the high medicinal value. In this study, the DO plant Acetone and Ethanolic extracts possibly containing antioxidants were tested using different methodologies for comparison and determination of specific antioxidant capacity. The total phenolic content assay expressed as Gallic Acid Equivalent showed 9.43±;0.23 mg GAE /g of extract. Further analysis using DPPH· assay indicated that antioxidants presented in the sample were able to significantly scavenge 37% and 44% radicals at the concentrations of 25mg/ml and 50mg/mL respectively, after a period of 2 hours (p\u3c0.05). ORAC and ABTS assays showed consistent radical scavenging results that Ethanol extracted DO sample had significantly higher AOC than the Acetone fraction. In addition, α-glucosidase assay was included to test efficacy in postprandial hyperglycemic condition, where the result indicated a significantly higher inhibitory effect by DO Acetone fraction compare to Ethanol fraction, 11~18% vs. 5.4% (p\u3c0.05). Although DO did not contain significantly high level of phenolic antioxidants, additional researches on different purified fractions such as polysaccharide compounds including evaluations of possible synergistic effects would be part of prospective experiments to show possible improvement on antioxidant capacity

A novel traveling-wave-based method improved by unsupervised learning for fault location of power cables via sheath current monitoring

In order to improve the practice in maintenance of power cables, this paper proposes a novel traveling-wave-based fault location method improved by unsupervised learning. The improvement mainly lies in the identification of the arrival time of the traveling wave. The proposed approach consists of four steps: (1) The traveling wave associated with the sheath currents of the cables are grouped in a matrix; (2) the use of dimensionality reduction by t-SNE (t-distributed Stochastic Neighbor Embedding) to reconstruct the matrix features in a low dimension; (3) application of the DBSCAN (density-based spatial clustering of applications with noise) clustering to cluster the sample points by the closeness of the sample distribution; (4) the arrival time of the traveling wave can be identified by searching for the maximum slope point of the non-noise cluster with the fewest samples. Simulations and calculations have been carried out for both HV (high voltage) and MV (medium voltage) cables. Results indicate that the arrival time of the traveling wave can be identified for both HV cables and MV cables with/without noise, and the method is suitable with few random time errors of the recorded data. A lab-based experiment was carried out to validate the proposed method and helped to prove the effectiveness of the clustering and the fault location

Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks

Skeleton based action recognition distinguishes human actions using the trajectories of skeleton joints, which provide a very good representation for describing actions. Considering that recurrent neural networks (RNNs) with Long Short-Term Memory (LSTM) can learn feature representations and model long-term temporal dependencies automatically, we propose an end-to-end fully connected deep LSTM network for skeleton based action recognition. Inspired by the observation that the co-occurrences of the joints intrinsically characterize human actions, we take the skeleton as the input at each time slot and introduce a novel regularization scheme to learn the co-occurrence features of skeleton joints. To train the deep LSTM network effectively, we propose a new dropout algorithm which simultaneously operates on the gates, cells, and output responses of the LSTM neurons. Experimental results on three human action recognition datasets consistently demonstrate the effectiveness of the proposed model.Comment: AAAI 2016 conferenc

Effet de la corrosion sur les propriétés mécaniques de l'armature corrodée et la performance structurale résiduelle des poutres corrodées

The thesis aims to study the influence of chloride corrosion on the mechanical properties ofthe reinforcement and RC beams. The experiments were based on two corroded beams named B2Cl2 and B2Cl3, with a corroded age of 26 years and 28 years respectively. Two noncorroded beams B2T2 and B2T3 which were cast in the same condition and same time were also tested in order to make clear the corrosion effect.The mechanical properties of the corroded reinforcement were investigated by the tensiontests. The yield strength and ultimate strength were studied based on the residual gravimetrical cross-section. The results found that the impact of corrosion on the ductility was more significant than that of the strength. The shape of residual cross-section was considered to be in deep relationships with the ductility of the reinforcement.The flexural performances of the beams were studied. The results showed that the corrosion deteriorated the capacity and the ductility of the corroded beams. The corrosion degree of reinforcement was found in linear with the residual yield capacity of the corroded beams.The short-span beams were formed from the corroded beams after bending tests. Mechanical tests were carried out directly to check the response of the corroded beams. The corroded short-span beams failed in bending mode with good ductility while the non-corroded beams performed a brittle shear failure mode, which showed that the corrosion of reinforcement could change the failure modes.The corrosion products were collected from the corroded reinforcement of B2Cl3. XRD andTG experiments were conducted so as to identify the composition of the corrosion products.The expansive coefficient of the corrosion products was deduced, which could be helpful forthe further research on the cracking mechanism of the concrete coverCette thèse s’intéresse à l’étude l’effet de la corrosion sur les propriétés mécaniques des armatures corrodées et les performances mécaniques résiduelles des poutres corrodées. L’étude est basée sur deux poutres corrodées notées B2CL2 et B2CL3, conservées respectivement 26 ans et 28 ans en ambiance saline. Deux poutres non corrodées B2T2 et B2T3 conservées en conditions ambiantes ont également été testés afin d’identifier l'effet de la corrosion indépendamment du vieillissement.Les propriétés mécaniques des armatures corrodées ont été étudiées par des essais de traction.La limite d'élasticité et résistance à la rupture ont été étudiées sur la base de la section transversale résiduelle évaluée par perte de masse. Les résultats ont montré que les effets de la corrosion sur la diminution ductilité étaient très importants. La forme de la section transversale résiduelle apparait comme étant un paramètre essentiel affectant la ductilité de l'armature.Les performances résiduelles en flexion des poutres corrodées ont été étudiées. Les résultats montrent que la corrosion réduit la capacité portante et de façon plus significative, la flèche maximale à rupture en raison d’un changement de mode de rupture. La diminution de la charge de plasticité apparait en relation avec la perte de section d’acier tendu due à la corrosion Des poutres de portées courtes ont été réalisées à partir des poutres corrodées après les essais de flexion. Les tests mécaniques ont été effectués en flexion pour vérifier la réponse des poutres courtes corrodées. Les poutres courtes corrodées ont péri en flexion avec une bonne ductilité tandis que les poutres courtes non corrodées ont péri comme prévu en cisaillement suivant un mode de rupture fragile, qui a montré que la corrosion de l'armature pouvait modifier les modes de défaillance.Les produits de corrosion ont été recueillis à partir de l'armature corrodée de B2Cl3. Des expériences XRD et TG ont été menées afin d'identifier la composition des produits de corrosion. Le coefficient d'expansion des produits de corrosion a été déduit, ce qui pourrait être utile pour les recherches futures concernant le mécanisme de fissuration du béton d'enrobage

Actuarial Ratemaking in Agricultural Insurance

A scientific agricultural (re)insurance pricing approach is essential for maintaining sustainable and viable risk management solutions for different stakeholders including farmers, governments, insurers, and reinsurers. The major objective of this thesis is to investigate high dimensional solutions to refine the agricultural insurance and reinsurance pricing. In doing so, this thesis develops and evaluates three high dimensional approaches for constructing actuarial ratemaking framework for agricultural insurance and reinsurance, including credibility approach, high dimensional copula approach, and multivariate weighted distribution approach. This thesis comprehensively examines the ratemaking process, including reviews of different detrending methods and the generating process of the historical loss cost ratio's (LCR's, which is defined as the ratio of indemnities to liabilities). A modified credibility approach is developed based on the Erlang mixture distribution and the liability weighted LCR. In the empirical analysis, a comprehensive data set representing the entire crop insurance sector in Canada is used to show that the Erlang mixture distribution captures the tails of the data more accurately compared to conventional distributions. Further, the heterogeneous credibility premium based on the liability weighted LCR’s is more conservative, and provides a more scientific approach to enhance the reinsurance pricing. The agriculture sector relies substantially on insurance and reinsurance as a mechanism to spread loss. Climate change may lead to an increase in the frequency and severity of spatially correlated weather events, which could lead to an increase in insurance costs, or even the unavailability of crop insurance in some situations. This could have a profound impact on crop output, prices, and ultimately the ability to feed the world rowing population into the future. This thesis proposes a new reinsurance pricing framework, including a new crop yield forecasting model that integrates weather and crop production information from different risk geographically related regions, and closed form reinsurance pricing formulas. The framework is empirically analyzed, with an original weather index system we set up, and algorithms that combine screening regression (SR), cross validation (CV) and principle component analysis (PCA) to achieve efficient dimension reduction and model selection. Empirical results show that the new forecasting model has improved both in-sample and out-of-sample forecasting abilities. Based on this framework, weather risk management strategies are provided for agricultural reinsurers. Adverse weather related risk is a main source of crop production loss, and in addition to farmers, this exposure is a major concern to insurers and reinsurers who act as weather risk underwriters. To date, weather hedging has had limited success, largely due to challenges regarding basis risk. Therefore, this thesis develops and compares different weather risk hedging strategies for agricultural insurers and reinsurers, through investigating the spatial dependence and aggregation level of systemic weather risks across a country. In order to reduce basis risk and improve the efficiency of weather hedging strategies, this thesis refines the weather variable modeling by proposing a flexible time series model that assumes a general hyperbolic (GH) family for the margins to capture the heavy-tail property of the data, together with the Lévy subordinated hierarchical Archimedean copula (LSHAC) model to overcome the challenge of high-dimensionality in modeling the dependence of weather risk. Wavelet analysis is employed to study the detailed characteristics within the data from both time and frequency scales. Results show that it is of great importance of capturing the appropriate dependence structure of weather risk. Further, the results reveal significant geographical aggregation benefits in weather risk hedging, which means that more effective hedging may be achieved as the spatial aggregation level increases. It has been discussed that it is necessary to integrate auxiliary variables such as weather, soil, and other information into the ratemaking system to refine the pricing framework. In order to investigate a possible scientific way to reweight historical loss data with auxiliary variables, this thesis proposes a new premium principle based on multivariate weighted distribution. Some designable properties such as linearity and stochastic order preserving are derived for the new proposed multivariate weighted premium principle. Empirical analysis using a unique data set of the reinsurance experience in Manitoba from 2001 to 2011 compares different premium principles and shows that integrating auxiliary variables such as liability and economic factors into the pricing framework will redistribute premium rates by assigning higher loadings to more risky reinsurance contracts, and hence help reinsurers achieve more sustainable profits in the long term