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Uncertainties about the efficacy of influenza vaccination for populations with heart failure (HF) in preventing cardiovascular outcomes, as well as lack of effective vaccination strategies, may contribute to low vaccine coverage rate (VCR) in China and globally. We assessed the feasibility of a strategy to promote influenza vaccines in patients hospitalized with acute HF in China and to inform the design of a hybrid effectiveness-implementation cluster randomized trial to evaluate this strategy on mortality and hospital re-admission. We conducted a cluster randomized pilot trial involving 11 hospitals in Henan Province in China, with mixed-methods evaluation between December 2020 and April 2021. A process evaluation involved interviews with 51 key informants (patients, health professionals, policy makers). The intervention included education about influenza vaccination and availability of free vaccines administered prior to hospital discharge for HF patients, while usual care included attending community-based points of vaccination (PoV) for screening and vaccination. Implementation outcomes focused on reach, fidelity, adoption, and acceptability. Recruitment rates were assessed for trial feasibility. Effectiveness outcomes were influenza VCR, HF-specific rehospitalizations and mortality at 90 days. A total of 518 HF patients were recruited from 7 intervention and 4 usual care hospitals (mean of 45 participants per hospital per month). VCR was 89.9% (311/346, 86.1-92.8%) in the intervention group and 0.6% (1/172, 0.0-3.7%) in the control group. The process evaluation demonstrated reach to patients with lower socioeconomic and education status. There was good fidelity of the intervention components, with education and PoV set up processes being adapted to local hospital workflow and workforce capacity. Intervention was acceptable and adopted by patients and health professionals. However, outside of a trial setting, concerns were raised around vaccination reimbursement costs, workforce accountability and capacity. The intervention strategy appears feasible and acceptable for improving VCR in HF patients at county-level hospitals in China. Trial registration: This pilot trial is registered with the acronym PANDA II Pilot (Population Assessment of Influenza and Disease Activity) at ChiCTR.org.cn (ChiCTR2000039081).

Training a dialogue policy using deep reinforcement learning requires a lot of exploration of the environment. The amount of wasted invalid exploration makes their learning inefficient. In this paper, we find and define an important reason for the invalid exploration: dead-ends. When a conversation enters a dead-end state, regardless of the actions taken afterward, it will continue in a dead-end trajectory until the agent reaches a termination state or maximum turn. We propose a dead-end resurrection (DDR) algorithm that detects the initial dead-end state in a timely and efficient manner and provides a rescue action to guide and correct the exploration direction. To prevent dialogue policies from repeatedly making the same mistake, DDR also performs dialogue data augmentation by adding relevant experiences containing dead-end states. We first validate the dead-end detection reliability and then demonstrate the effectiveness and generality of the method by reporting experimental results on several dialogue datasets from different domains.

Training a deep reinforcement learning-based dialogue policy with brute-force random sampling is costly. A new training paradigm was proposed to improve learning performance and efficiency by combining curriculum learning. However, attempts in the field of dialogue policy are very limited due to the lack of reliable evaluation of difficulty scores of dialogue tasks and the high sensitivity to the mode of progression through dialogue tasks. In this paper, we present a novel versatile adaptive curriculum learning (VACL) framework, which presents a substantial step toward applying automatic curriculum learning on dialogue policy tasks. It supports evaluating the difficulty of dialogue tasks only using the learning experiences of dialogue policy and skip-level selection according to their learning needs to maximize the learning efficiency. Moreover, an attractive feature of VACL is the construction of a generic, elastic global curriculum while training a good dialogue policy that could guide different dialogue policy learning without extra effort on re-training. The superiority and versatility of VACL are validated on three public dialogue datasets.

Additional file 2: Figure S2. The taxonomic representation of statistically and biologically differences between High 25(OH)D group and Low 25(OH)D group. The color of discriminative taxa represents the taxa is more abundant in the corresponding group (High 25(OH)D group in blue, Low 25(OH)D group in orange).

Additional file 3: Figure S3. Functional PICRUSt analysis among the LVD and HVD group. Kyoto Encyclopedia of Genes(A) and Genomes and cluster of orthologous group(B) was used to further investigate the mechanism of intestinal flora.

Additional file 4: Figure S4. Heat map for spearman correlation analysis between fecal metabolites and discriminative genera at the family level. Only significant values (p < 0.05 after FDR adjustment) are shown. Orange and blue colors represent significant positive correlations and negative correlations. Darker color represents stronger correlations.

Additional file 4: Figure S4. Heat map for spearman correlation analysis between fecal metabolites and discriminative genera at the family level. Only significant values (p < 0.05 after FDR adjustment) are shown. Orange and blue colors represent significant positive correlations and negative correlations. Darker color represents stronger correlations.

Additional file 1. Table S1. PCR primers used in this study.

Additional file 3: Figure S3. Functional PICRUSt analysis among the LVD and HVD group. Kyoto Encyclopedia of Genes(A) and Genomes and cluster of orthologous group(B) was used to further investigate the mechanism of intestinal flora.

Additional file 2: Figure S2. The taxonomic representation of statistically and biologically differences between High 25(OH)D group and Low 25(OH)D group. The color of discriminative taxa represents the taxa is more abundant in the corresponding group (High 25(OH)D group in blue, Low 25(OH)D group in orange).

Additional file 1: Figure S1. Rarefaction curves in observed_species of all the samples. The rarefaction curves constructed from the sequenced data has been basically stable, indicating that the sequenced data has benn basically stable at this sequencing depth.

Additional file 1

Deep reinforcement learning has shown great potential in training dialogue policies. However, its favorable performance comes at the cost of many rounds of interaction. Most of the existing dialogue policy methods rely on a single learning system, while the human brain has two specialized learning and memory systems, supporting to find good solutions without requiring copious examples. Inspired by the human brain, this paper proposes a novel complementary policy learning (CPL) framework, which exploits the complementary advantages of the episodic memory (EM) policy and the deep Q-network (DQN) policy to achieve fast and effective dialogue policy learning. In order to coordinate between the two policies, we proposed a confidence controller to control the complementary time according to their relative efficacy at different stages. Furthermore, memory connectivity and time pruning are proposed to guarantee the flexible and adaptive generalization of the EM policy in dialog tasks. Experimental results on three dialogue datasets show that our method significantly outperforms existing methods relying on a single learning system.

Deep reinforcement learning has shown great potential in training dialogue policies. However, its favorable performance comes at the cost of many rounds of interaction. Most of the existing dialogue policy methods rely on a single learning system, while the human brain has two specialized learning and memory systems, supporting to find good solutions without requiring copious examples. Inspired by the human brain, this paper proposes a novel complementary policy learning (CPL) framework, which exploits the complementary advantages of the episodic memory (EM) policy and the deep Q-network (DQN) policy to achieve fast and effective dialogue policy learning. In order to coordinate between the two policies, we proposed a confidence controller to control the complementary time according to their relative efficacy at different stages. Furthermore, memory connectivity and time pruning are proposed to guarantee the flexible and adaptive generalization of the EM policy in dialog tasks. Experimental results on three dialogue datasets show that our method significantly outperforms existing methods relying on a single learning system.

Here, we established a novel, efficient, and cost-effective rooting culture system for highbush blueberry (Vaccinium corymbosum). This method overcomes the inefficient, expensive, and time-consuming nature of traditional methods and provides a theoretical basis for the industrial rooting of micropropagated blueberry seedlings. Semisolid half-strength woody plant medium (1/2WPM), supplemented with carrageenan as fixing material, was packed into high molecular polypropylene plastic bags. Optimum response of ‘Ozarkblue’ was observed in 1/2WPM supplemented with 0.1 mg/l indole-3-butyric acid (IBA); 97.7% rooting rate was achieved at 45 days after culture, with the average root number and length reaching 6.5 ± 0.39 and 3.5 ± 0.16 cm, respectively. The highest rooting rate of ‘Weiwa Kuahuat’ (84.0%) was achieved with 0.5 mg/l IBA, resulting in a favorable average root number (3.0 ± 0.43) and length (3.0 ± 0.43 cm). ‘Sierra’ showed the highest rooting rate (100.0%) in the presence of 1.0 mg/l IBA, with an average root number and length of 5.9 ± 0.9 and 3.9 ± 0.62 cm, respectively. The earliest and fastest rooting was recorded when shoots were transplanted into bags for 13 days. A space utilization experiment showed that the density of well-grown blueberry seedlings achieved in bags (1600 seedlings/m2) was superior to that obtained using traditional in vitro and ex vitro rooting methods (270 and 420 seedlings/m2, respectively). This is the first report of a complete rooting system that could serve as a feasible blueberry rooting method with superior rooting time, rooting rate, medium consumption, space requirement, and portability. We established a novel, efficient, and cost-effective rooting culture system for the micro-propagation of highbush blueberry seedlings that overcomes many of the drawbacks of traditional methods of industrial rooting.

Ordered lamellar superstructured zirconia (OLSZ) was successfully synthesized via a reflux-hydrothermal method. ZrOCl2, NaOH and methanol were used as zirconium source, precipitant and template, respectively. Methanol induced and directed the hierarchical structures: 0.57-nm thick ultrathin crystal framework, 1.14-nm periodic lamellar superstructure, several nanometers thick petal-like multilayered nanosheets, and flowers-like higher-level structure. OLSZ presented outstanding hierarchical thermostabilities up to 800 °C. The synthetic mechanism was proposed based on Gibbs theory and calculations. Compared with surfactant method, methanol template route presents many advantages, such as green, facile, efficient and low-cost, moreover the template is very easy to remove. This novel small molecule template strategy will be of great significance for the synthesis of other superstructured materials.

A green manufacturing technology named “electrostatic minimum quantity lubrication (EMQL)” with water-based Al2O3 nanoparticle fluids as cutting fluids was developed in order to improve the cutting property and minimize oil mist concentration during the machining process. The capillary penetration mechanism, oil mist concentration, and heat transfer property of Al2O3 fluid EMQL were investigated. The cutting performance of Al2O3 fluid EMQL and traditional minimum quantity lubrication (MQL) was compared. The results showed that EMQL could improve the penetrability and heat transfer capacity of the lubricant effectively. Compared with Al2O3 fluid MQL and oil-based MQL, Al2O3 fluid EMQL reduced oil mist concentration and cutting temperature remarkably and showed similar cutting performances compared with the oil-based MQL. The excellent performance of this water-based Al2O3 fluid EMQL technology was mainly due to that EMQL could promote a further penetration of the charged Al2O3 nanofluid droplets into the cutting region, which thus reduced the friction force, and the tool durability was maintained obviously and finally presented better machining performance.

Both thermodynamic performance and techno-economic analysis of compound power cycles for enhanced geothermal systems have been investigated in this study. Thermodynamic analysis were carried out for four power generation systems: single-flash (SF) system, double-flash (DF) system, flash-ORC (FORC) system; and double-flash-ORC (DFORC) system. By choosing the maximum net power output as an objective function, optimization is done based on comparisons among the four systems with a goal of increasing the net power output by 20% under the condition that the SF is replaced by one of the compound systems (DF, FORC, and DFORC). As an original contribution, five maps useful for real applications have been generated for selecting optimum geothermal power cycles under different geofluid’s conditions, with consideration of five ORC working fluids (R123, R152a, isobutane, n-pentane and R245fa). The boundaries that determine whether the compound systems have advantages over the SF system are functions of the geofluid temperature, geofluid dryness, and the type of the working fluid used by the ORC. In the techno-economic study, Levelized Electricity Cost (LEC) and Payback Period (PBP) analyses were carried out. The results from the LEC and PBP studies show good agreement. For the three scenarios analyzed, each of the compound power systems has a better engineering economic performance than the SF system. For the “common” heat source condition investigated, comparison among the three compound systems shows that the DF system has a lowest levelized electricity cost and the shortest payback period; the FORC and DFORC show similar techno-economic performance and have advantages over the SF system.

An effective pretreatment method of carbon fiber reinforced plastic (CFRP) aircraft skin was proposed. In this article, the function of the amino thermosetting abrasives entrained by the airflow on the CFRP aircraft skin is introduced and discussed to achieve the purpose of enhancing the coating adhesion and prolonging the service life. An orthogonal experiment with five factors and four levels was designed and carried out, including jet pressure, target distance and impact angle, moving speed and particle size. The best pretreatment process was obtained by analyzing surface morphology, wettability and adhesion. The erosion mechanism of CFRP coating pretreatment with abrasive impact was studied emphatically. The results show that the critical pressure for fiber damage is 0.4 MPa, and the better surface energy is 38.0 mN/m. Semi-ductile erosion has been identified as the main erosion mechanism of amino thermosetting abrasives eroding CFRP. Effective assurance was provided for the improved surface of the aircraft CFRP skin and enhanced coating adhesion in this study.

Earthquakes can cause serious damage to traffic infrastructures, among which the impact on bridge structure is the most important. Therefore, in order to assess bridges serviceability, it is important to master their damage mechanism and to analyze its probability of occurrence under a given seismic action. Various uncertainties, like the location of epicentre of future earthquakes and their magnitudes, make this task quite challenging. We are also required to consider different earthquake scenarios and the damaged states of bridge components associated with those earthquakes. To suppress these difficulties, this study proposed a new method of performance-based seismic fragility and risk assessment for bridges. The proposed method included three steps: (1) performance-based seismic fragility estimation of a five-span continuous rigid frame bridge, (2) seismic hazard analysis for locations of the bridge, and (3) seismic risk analysis of the bridge. The proposed method that considered the performance of the bridge and the uncertainty in the location of the earthquake epicentre and magnitudes can provide valuable references for seismic-resistant design of multispan continuous rigid frame bridges in the future.

Dual active bridge isolated bidirectional DC-DC converters-DAB-IBDCs, with the two-way power flow ability and high frequency isolation, can match the different level voltage resource easily, and are the critical unit to connect the different power such as battery, generator and loads etc. The three level neural point clamp-3L-NPC IBDC can fulfills high voltage converting with lower rated power devices, and can increase the power rate extent remarkably and improve the electromagnetic compatibility as the same. In this paper the control strategies of 3L-NPC IBDC were invested in detail and the operation modes were divided two types according to relationship between the duty cycle of the inner bridge and the phase shift ratio of the two bridges. The current, output voltage and transfer power characteristics are analyzed and analytical expression is given according the three sub-modes under model respectively. The current of the neural point must be kept balance to ensure the two clamp capacitors have the approximately equal voltage in one period in the both operation modes. The results show that the 3L-NPC IBDC is feasible and have a good prospect in the high power converters.

Geographically and temporally weight regression (GTWR) estimates regression coefficients and fitted value by weighted least squares (WLS), which under the assumption of the same minimum random variance. As without considering the spatio-temporal heteroscedasticity, it may reduce the accuracy of estimation. Local polynomial estimation is a nonparametric estimation method to eliminate heteroscedasticity in statistics. On the basis of the local polynomial estimation, the local polynomial geographically and weight regression temporally (LPGTWR) approach is proposed in this paper. It reconstructs the spatio-temporal coefficients using three-dimensional Taylor Series in order to satisfy the Gauss-Markov assumption of independent identical distribution. Then estimate the regression coefficients and fitting value using weighted least squares. The experiments use both simulated data and real data to compare LPGTWR, GTWR and local linear-fitting-based geographically weight regression (LGWR). Experiments using simulated data showed that LPGTWR can significantly improve the accuracy of estimation not only in goodness-of-fit of the fitted value, but also in reducing bias of the coefficient estimation and the estimation. It is useful by adopting LPGTWR to eliminate heteroscedasticity effect and improve estimation accuracy.

The process of phloem unloading and post-unloading transport of photoassimilate is critical to crop output. Xanthoceras sorbifolia is a woody oil species with great biomass energy prospects in China; however, underproduction of seeds seriously restricts its development. Here, our cytological studies by ultrastructural observation revealed that the sieve element-companion cell complex in carpellary bundle was symplasmically interconnected with surrounding parenchyma cells at the early and late fruit developmental stages, whereas it was symplasmically isolated at middle stage. Consistently, real-time imaging showed that fluorescent tracer 6(5)carboxyfluorescein was confined to phloem strands at middle stage but released into surrounding parenchymal cells at early and late stages. Enzymatic assay showed that sucrose synthase act as the key enzyme catalyzing the progress of Suc degradation post-unloading pathway whether in pericarp or in seed, while vacuolar acid invertase and neutral invertase play compensation roles in sucrose decomposition. Sugar transporter XsSWEET10 had a high expression profile in fruit, especially at middle stage. XsSWEET10 is a plasma membrane-localized protein and heterologous expression in SUC2-deficient yeast strain SUSY7/ura3 confirmed its ability to uptake sucrose. These findings approved the transition from symplasmic to apoplasmic phloem unloading in Xanthoceras sorbifolia fruit and XsSWEET10 as a key candidate in sugar transport.

Solar enhanced natural draft dry cooling tower(SENDDCT) is a new heat rejection device that uses solar energy to increase the cooling efficiency of natural draft dry cooling tower. In this paper, an experiment study was carried out t under natural conditions to investigate the effect of solar radiation intensity on the performance of SENDDCT. Meanwhile, a same-size CFD model was developed by using FLUENT to analyze the influence of ambient temperature on the cooling performance of SENDDCT. The results verified that SENNDCT can enhance heat transfer rate of natural draft dry cooling tower when ambient temperature was high at noon, solar radiation increased heat transfer rate by an average of 16.5% during the experiment. Air mass flow and heat transfer rate decreased with the increase of ambient temperature.

In this study, the optimum flash and evaporation temperatures have been selected for the following four geothermal power generation systems: single-flash system (SF), double-flash system (DF), flash-organic Rankine cycle system (FORC), and double-flash-organic Rankine cycle system (DFORC). Optimization is based on the maximum net power output of each system, with the pump and fan consumptions being taken into account. Under the given geofluid’s condition (temperature= 170oC; dryness= 0.2), the optimum flash temperature of SF, the optimum 2nd-stage flash temperature of DF, the optimum evaporation temperatures of FORC and DFORC are found to be 150oC, 100oC, 100oC, and 70oC, respectively. More scenarios have been analyzed for geofluid’s temperatures ranging from 80oC-260oC and geofluid’s dryness values of 0, 0.2, and 0.4 respectively. The result shows that the optimum 2nd-stage flash temperature of DF is close to the optimum evaporation temperature of FORC under the same geofluid’s condition, especially when the geofluid’s temperature is below 170oC and the dryness is below 0.2.

Geographically weighted regression (GWR) approach will be affected by the quantity of label data. However, it is difficult to get labeled data but easy to get the unlabeled data in applications. Therefore it is indispensable to find an useful way that can use the unlabeled data to improve the regression results. As we know semi-supervised learning is a class of supervised learning tasks and techniques that also make use of unlabeled data for training typically a small amount of labeled data with a large amount of unlabeled data. So this article develops a semi-supervised-learning geographically weighted regression (SSLGWR). Firstly it builds the GWR model by labeled data. Then the unlabeled data can be calculated the value by the GWR model and they will be signed as new labeled data. Thirdly, use both labeled data and new labeled data to rebuild the GWR model to improve the model's precision. The experiments use both simulated data and real data to compare GWR COGWR and SSLGWR. Mean square error is closed as the framework to estimate the models. Experiments using simulated data have shown that the proposed model improves the performance by 39.66%, 11.92% and 0.94% relative to 10%,30% and 50% label data. And experiments using real data have shown that the proposed model improves the performance by 8.94%, 3.36% and 5.87%. The results demonstrate that there are substantial benefits of SSLGWR in the improvement of GWR.

Proceedings of Graphics Interface 2019, Kingston, Ontario, Canada, 28 - 31 May 2019, Radiance caching is used to accelerate global illumination computations, exploiting the spatial coherence of indirect illumination on surfaces. We propose a new radiance caching approach capable of more correctly reconstructing inter-reflections between glossy surfaces, all while improving performance compared to previous approaches. Contrary to previous works, our view-dependent radiance caching scheme does not heavily rely fundamentally on basis-space representations such as spherical harmonics, and can directly treat outgoing radiance at surfaces instead of incoming radiance distributions. We introduce a new view-dependent record placement strategy and adapt recent Hessian-based error metrics to our view-dependent records [8]. To do so, we derive and compute more accurate derivatives of radiance at surfaces in the scene.

There exists many complicated $k$-noncrossing pseudoknot RNA structures in nature based on some special conditions. The special characteristic of RNA structures gives us great challenges in researching the enumeration, prediction and the analysis of prediction algorithm. We will study two kinds of typical $k$-noncrossing pseudoknot RNAs with complex structures separately., Comment: 117 pages, 79 figures. The thesis has been defended and published in summer of 2012. This version is updated for correcting several unmeant mistakes and clerical error. It is very thankful for Prof. Christian Reidys and Prof. Qinghu Hou's guidance

An extracellular organic solvent-tolerant lipase-producing bacterium was isolated from oil-contaminated soil samples and was identified taxonomically as Pseudomonas stutzeri, from which the lipase was purified and exhibited maximal activity at temperature of 50 °C and pH of 9.0. Meanwhile, the lipase was stable below or at 30 °C and over an alkaline pH range (7.5-11.0). Ca2+ could significantly improve the lipase thermal stability which prompts a promising application in biocatalysis through convenient medium engineering. The lipase demonstrated striking features such as distinct stability to the most tested hydrophilic and hydrophobic solvents (25 %, v/v), and DMSO could activate the lipase dramatically. In the enzyme-catalyzed resolution, lipase ZS04 manifested excellent enantioselective esterification toward the (R)-1-(4-methoxyphenyl)-ethanol (MOPE), a crucial chiral intermediate in pharmaceuticals as well as in other analogs with strict substrate specificity and theoretical highest conversion yield. This strong advantage over other related schemes made lipase ZS04 a promising biocatalyst in organic synthesis and pharmaceutical applications.

A novel surface patterning nanorod (hydroxyapatite nano labyrinth, HANL), covered with labyrinthine nanogrooves on surface, was successfully synthesized with the assistance of tetrahydrofuran (THF). THF as the sole organic molecule not only promoted HA crystal growth, but also induced and stabilized the hierarchical nanorod. XRD results indicated that HANLs were of high phase purity and were well crystallized. SEM and TEM images showed that HANLs were of the length of 75–425 nm and the width of 20–85 nm, and were of 1-9-nm wide grooves covering over the surface which were also confirmed by the N2 adsorption analysis. The synthetic mechanism was proposed and explained in thermodynamics combined with theoretic calculations. This novel hierarchical HANLs may have great potential applications in bone replacement materials, composites, adsorbents, carriers, etc. This THF assisted synthetic strategy is green, low-cost, efficiently and surfactant-free, and may be useful in surface patterning other functional materials.

Plenty of in-process vulnerabilities are blamed on various out of bound memory accesses. Previous prevention methods are mainly based on software checking associated with performance overhead, while traditional hardware protection mechanisms only work for inter-process memory accesses. In this paper we propose a novel hardware based in-process isolation system called PULP (Protection by User Level Partition). PULP modifies processor core by associating program counter and virtual memory address to achieve in-process data isolation. PULP partitions the program into two distinct parts, one is reliable, called primary functions, and the other is unreliable, called secondary functions, the accessible memory range of which can be configured via APIs. PULP automatically checks the memory bound when executing load/store operations in secondary functions. A RISC-V based FPGA prototype is implementated and functional test shows that PULP can effectively prevent in-process bug, including the Heartbleed and other buffer overflow vulnerabilities, etc. The total runtime overhead of PULP is negligible, as there is no extra runtime overhead besides configuring the API. We run SPEC2006 to evaluate the average performance, considering the LIBC functions as secondary functions. Experimental timing results show that, running bzip2, mcf, and libquantum, PULP bears low runtime overhead (less than 0.1%). Analysis also shows that PULP can be used effectively to prevent the newest "Spectre" bug which threats nearly all out-of-order processors.

Transformed hairy roots had been efficiently induced from the seedlings of Fagopyrum tataricum Gaertn. due to the infection of Agrobacterium rhizogenes. Hairy roots were able to display active elongation with high root branching in 1/2 MS medium without growth regulators. The stable introduction of rolB and aux1 genes of A. rhizogenes WT strain 15834 into F. tataricum plants was confirmed by PCR analysis. Besides, the absence of virD gene confirmed hairy root was bacteria-free. After six different media and different sources of concentration were tested, the culturing of TB7 hairy root line in 1/2 MS liquid medium supplemented with 30 g l(-1) sucrose for 20 days resulted in a maximal biomass accumulation (13.5 g l(-1) fresh weight, 1.78 g l(-1) dry weight) and rutin content (0.85 mg g(-1)). The suspension culture of hairy roots led to a 45-fold biomass increase and a 4.11-fold rutin content increase in comparison with the suspension culture of non-transformed roots. The transformation frequency was enhanced through preculturing for 2 days followed by infection for 20 min. The UV-B stress treatment of hairy roots resulted in a striking increase of rutin and quercetin production. Furthermore, the hairy root lines of TB3, TB7, and TB28 were chosen to study the specific effects of UV-B on flavonoid accumulation and flavonoid biosynthetic gene expression by qRT-PCR. This study has demonstrated that the UV-B radiation was an effective elicitor that dramatically changed in the transcript abundance of ftpAL, FtCHI, FtCHS, FtF3H, and FtFLS-1 in F. tataricum hairy roots.

Simuler efficacement l'éclairage global est l'un des problèmes ouverts les plus importants en infographie. Calculer avec précision les effets de l'éclairage indirect, causés par des rebonds secondaires de la lumière sur des surfaces d'une scène 3D, est généralement un processus coûteux et souvent résolu en utilisant des algorithmes tels que le path tracing ou photon mapping. Ces techniquesrésolvent numériquement l'équation du rendu en utilisant un lancer de rayons Monte Carlo. Ward et al. ont proposé une technique nommée irradiance caching afin d'accélérer les techniques précédentes lors du calcul de la composante indirecte de l'éclairage global sur les surfaces diffuses. Krivanek a étendu l'approche de Ward et Heckbert pour traiter le cas plus complexe des surfaces spéculaires, en introduisant une approche nommée radiance caching. Jarosz et al. et Schwarzhaupt et al. ont proposé un modèle utilisant le hessien et l'information de visibilité pour raffiner le positionnement des points de la cache dans la scène, raffiner de manière significative la qualité et la performance des approches précédentes. Dans ce mémoire, nous avons étendu les approches introduites dans les travaux précédents au problème du radiance caching pour améliorer le positionnement des éléments de la cache. Nous avons aussi découvert un problème important négligé dans les travaux précédents en raison du choix des scènes de test. Nous avons fait une étude préliminaire sur ce problème et nous avons trouvé deux solutions potentielles qui méritent une recherche plus approfondie., Efficiently simulating global illumination is one of the most important open problems in computer graphics. Accurately computing the effects of indirect illumination, caused by secondary bounces of light off surfaces in a 3D scene, is generally an expensive process and often solved using algorithms such as path tracing or photon mapping. These approaches numerically solve the rendering equation using stochastic Monte Carlo ray tracing. Ward et al. proposed irradiance caching to accelerate these techniques when computing the indirect illumination component on diffuse surfaces. Krivanek extended the approach of Ward and Heckbert to handle the more complex case of glossy surfaces, introducing an approach referred to as radiance caching. Jarosz et al. and Schwarzhaupt et al. proposed a more accurate visibility-aware Hessian-based model to greatly improve the placement of records in the scene for use in an irradiance caching context, significantly increasing the quality and performance of the baseline approach. In this thesis, we extended similar approaches introduced in these aforementioned work to the problem of radiance caching to improve the placement of records. We also discovered a crucial problem overlooked in the previous work due to the choice of test scenes. We did a preliminary study of this problem, and found several potential solutions worth further investigation.

This paper describes the concept of address elements and proposes a fuzzy Chinese-geocoding method via using fuzzy mathematics principle. The segmentation accuracy is improved by employed elements identification mechanism techniques, moreover, the best matching result is derived by calculating the MI indicator. The simulation error related to re-matched method is obtained through quality control module strategy. The verification of proposed approach is given via experiment related to fuzzy Chinese-geocoding method in Harbin, and evaluated via matching rate and positional error.

In order to use enterprises' distribution data effectively and maximize their social and economic values, a multi-level grid partition method for enterprise distribution data is proposed which divides the voluminous data into reasonable size. This method uses the provinces or municipalities of nationwide as the coarsest division, then a quad-tree is constructed to partition the points of enterprises according to their locations. Each node in the quad-tree has a limit of points, when the number of points in a node beyond the limit, the node is divided into four nodes with roughly the same number of points in each quadrant. This process proceeds recursively until no node contains points more than the limit. Enterprise distribution data of Harbin is used in experiments to test the feasibility and effectiveness of this method, the results of the experiments show that the enterprises distribution data are divided rapidly and accurately to the grid, which improve the applicability of the data and the convenience of data integration.

This paper presents a site selection algorithm for water resources points based on GIS technology. By analyzing the relationship between supply and demand constraints, it plans points-site and solves the water resources allocation problem. The main idea of this algorithm is as follows. Consider the situation of current water resources supply, define new points-sites where settlements are insufficient of water and calculate their service capabilities on the spatial constrains. By iteratively picking the point-sites with maximum service capabilities and updating the situation of supply and demand, a solution can be found with this greedy strategy. Although suboptimal, the algorithm has the merit of simplicity and concision. Water resources distribution system using this algorithm is implemented on the base of real geographic data from Qinghai province. Results of the application and discussion are provided in this paper.

Recognition of petechia tongue is still a challenging problem due to different color, morphology and texture in tongue image. This paper presents a new method to automatically recognition of petechia tongue based on LoG and Gabor feature with spatial information. The proposed approach begins with a normalized LoG filter to locate the suspected petechia areas in tongue image. In the subsequent step, the spatial position feature and Gabor feature were extracted as a feature descriptor of these regions. Support vector machine is used as a classifier to classify these suspected petechia areas into petechia and non-petechia areas. Finally, the proposed method judge whether the tongue image have petechia according to the proportion of petechia regions to all suspected petechia regions. Experimental results on two hundred tongue images indicate the better performance of our method, the accuracy achieves to 84.91%.

Domestic sewage was treated with subsurface wastewater infiltration system covered by two different turf grass, namely, Festuca aroundinaces Schres and Zoysiajaponica Steud to study the removal effects of N and P. The result show that TN concentration of Festuca around inaces Schres varied from 46.8 to 52.7 gi¤kg-1 and it was significantly higher than that of Zoysia japonica Steud. The TP concentration of Festuca aroundinaces Schres varied from 4.64to 5.89 g i¤ kg-1 and there were no prominent differences between the two turf grass. The average nitrogen amount taken out by Festuca aroundinaces Schres are 0.237gi¤m-2i¤d-1, 0.180 gi¤m-2i¤d-1 and 0.118 gi¤m-2i¤d-1 in different month which are significantly higher than that of Zoysia japonicaSteud. The nitrogen removal rates of Festuca aroundinacesSchres clippings are 21.4%, 13.1% and 11.8% in September, November and December respectively. The average phosphorous amount taken out by Festuca aroundinacesSchres are 23.4 mg i¤ m-2 i¤ d-1, 15.1 mg i¤ m-2 i¤ d-1 and 13.8mgi¤m-2i¤d-1 in different month which are significantly higher than that of Zoysia japonica Steud. The phosphorous removal rates of Festuca aroundinaces Schres clippings are 30.2%,24.4% and 22.4% in September, October and November respectively.