This chapter is a short essay on discontinuous Galerkin methods for fractional (convection-) diffusion equations in one and two dimensions. The method is based on the local discontinuous Galerkin methods for the classical parabolic equation, i. e., decomposing the high-order derivative and rewriting the equation into a first-order system. Depending on the properties of fractional operators, we decompose it into several first-order derivatives and one fractional integral. Then we propose the corresponding numerical schemes and discuss their stability and convergence. Some algorithms in two dimensions are provided.
An empirical network model has been developed to predict the in-plane thermal conductivities along arbitrary directions for unidirectional fiber-reinforced composites lamina. Measurements of thermal conductivities along different orientations were carried out. Good agreement was observed between values predicted by the network model and the experimental data; compared with the established analytical models, the newly proposed network model could give values with higher precision. Therefore, this network model is helpful to get a wider and more comprehensive understanding of heat transmission characteristics of fiber-reinforced composites and can be utilized as guidance to design and fabricate laminated composites with specific directional or specific locational thermal conductivities for structures that simultaneously perform mechanical and thermal functions, i.e. multifunctional structures (MFS).
During the last two decades, renewable wind energy has become increasingly popular as a consequence of strong ecological concerns and appealing advantages with regard to economical energy solutions in remote communities. Furthermore, with very large wind farms emerging, the dispersed renewable wind energy is required to be fully connected to the electrical distribution networks. However, the integration of dispersed renewable wind energy will pose a great challenge to the power quality in the distribution networks when the weak nature of the grid in remote areas and the uncertainty of wind are taken into consideration.This paper presents a novel Modulated Power Filter Compensator (MPFC) for the distribution networks with dispersed renewable wind energy interfaced. A tri-loop error driven controller is used to adjust the PWM switching of the modulated power filter compensator. Full power factor correction and power quality improvement is validated under different operation conditions, like load switching and wind velocity excursions. The MPFC device is a member of novel FACTS based compensators developed by the first author.
Large numbers of mutations are postulated to occur as early events in carcinogenesis. For certain types of human tumors (mutator phenotypes) these mutations can be a driving force in generating clonogenic, causative genetic changes leading to multistage carcinogenesis. These low-level mutational events are highly significant due to their potential use as molecular markers for early identification of genomic instability that can lead to cancer and to their potential influence on the ability of tumors to resist drug treatment and/or metastasize. Detecting the presence and diversity of such genetic changes in human tumors is desirable due to their potential prognostic value. However, identification of these low-frequency genetic changes is difficult, since most mutations exist at mutant/wild-type ratios of <10 −3. We recently developed inverse PCR-based amplified restriction fragment-length polymorphism (iFLP), a new technology that combines inverse PCR, RFLP, and denaturing HPLC to allow scanning of the genome at several thousand positions per experiment for low-level point mutations. Using iFLP we previously demonstrated low-level mutations (mutation frequency <10 −3) in human colon cancer cells that harbor mismatch repair deficiency and in sporadic colon cancer surgical specimens. In the present work we investigated whether low-level mutations are also present in sporadic breast cancer surgical specimens. Using iFLP we identified widespread low-level mutations in two out of ten surgical specimens examined (20%). Examination of the microsatellite instability status of these samples demonstrated that the samples are stable (MSI-S). We conclude that low-level mutations are less frequent in breast cancer than in colon cancer; however, single nucleotide instability that generates such mutations may still be present in a fraction of breast cancers.
More than half of the total natural ionizing radiation dose received by the human population is caused by radon and thoron (Rn and Tn) and their progeny. To estimate the level of radiation due to radon and thoron and their progeny, an investigation was conducted in a residential area near the world’s largest open-pit mine of Bayan Obo in Inner Mongolia, China. The concentration of Rn, Tn, and their decay products in air and soil were studied by using AlphaGUARD, RAD7, and ERS-RDM-2S for a discrete period of time in three different locations. The average indoor concentration of radon and thoron was 62.6 ± 44.6 Bq/m3 and 108.3 ± 94.5 Bq/m3 respectively, and the outdoor concentration was 12.9 ± 6.3 Bq/m3 and 55.8 ± 18.5 Bq/m3, respectively. Relatively high concentrations were recorded in the area near to the mine, with a significant increasing trend observed in indoor thoron concentration. A prominent hotspot in thoron concentration was found in a single-story house with values 747 ± 150 Bq/m3. The equilibrium equivalent thoron concentration (EECTn) varies from 0.48 Bq/m3 to 2.36 Bq/m3 with an arithmetic mean of 1.37 ± 0.64 Bq/m3, and comparatively higher than EECRn. Concluding that the mining activity at Bayan Obo mine is significantly increasing the level of indoor thoron and its progeny in surroundings. It is suggested to further systematically investigate the indoor Rn and Tn progeny concentrations in the residential dwellings of the Bayan Obo mining area, and 232Th content of the building materials, to provide a basis for calculating the radiation dose.
The use of trained artificial neural networks (ANNs) for agricultural processing, handling, and process control, such as pattern recognition, classification and weight prediction, offers potential for multi-dimensional function fittings and enhanced accuracy in machine-vision based procedures. In this study, optimization of ANNs for machine vision based applications for better prediction accuracy has been conducted using soybean weighing as an example. Neural network systems consisting of a varying number of neurons trained under dissimilar algorithms were compared in determining the weights of soybeans based on the correlation of weight to features extracted from one- and two-direction images. Results show that imaging from the side of a soybean produces superior data to that of top-down images, and that with a properly trained neural network, weight predictions could be accurate up to a relative error of less than three percent. Furthermore, the continuous dependence of weight to features of the soybean suggested use of a training batch consisting of uniformly distributed weights.
The hypercrosslinked adsorption resins, modified with trimellitic anhydride (named FJ-1), concentrated sulfuric acid (named FJ-2) and p-hydroxy mandelic acid (named FJ-3) respectively, were successfully prepared by the crosslinking and chemical modification reaction and characterized by IR and BET. The adsorption properties and adsorption mechanism of phenol onto the FJ-1, FJ-2 and FJ-3 resins were studied by isotherm adsorption and adsorption kinetics experiments and compared with NDA99 resins. The results shown that the adsorption effect of phenol on the FJ-1 resins was best and the adsorption capacity of phenol on it decreased with increasing temperature. The adsorption process was mainly reversible exothermic physical adsorption. For the FJ-1 and FJ-2 resins, the Langmuir isotherm model can fit their adsorption process well. The Freundlich isotherm model can fit the adsorption process of the FJ-3 resins better than Langmuir isotherm model. The results of ΔH and ΔG shown that the adsorption of phenol on four kinds of resins was a feasible spontaneous endothermic process. ΔS showed the increasing randomness of the solid-solution interface during the adsorption of phenol on resins. Pseudo-first-order model and pseudo-second-order model were both described the adsorption of phenol onto the FJ-1 and NDA99 resins. The particle diffusion was the main control step of entire adsorption process.
Genetic parameters for height (H), diameter at breast height (DBH), stem straightness (STR), and under crown clear bole height (CH) of loblolly pine (Pinus taeda L.) were estimated for 255 families (209 open pollinated (OP) and 46 controlled pollinated (CP) families) using a family model and an individual tree model at age 1, 2, 3, 5, 11, and 15 years. Heritability estimates for growth traits of individual trees at age 11 years were the highest (0.17-0.78), and those at age 15 years were the lowest (0.05-0.74). Heritability estimates for DBH, STR, and CH were lower than those for H. Genetic correlations between H and DBH were generally strongly positive, attained a maximum values at age 2 to 3, and declined slightly thereafter. The genetic correlations between CH at age 11 and both H and DBH at different ages were moderate. Age-age genetic correlations for growth traits were moderate to high (0.56-0.91) at age 5 for half-rotation age (15 years), indicating the opportunity exists for early selection. Indirect selection from the age 5 to 11 years for H and DBH could be expected to produce gains of over 50% and 35% respectively, for these two ages, relative to direct selection at age 15. Efficiencies of early selection for H and DBH indicated that growth at maturity could be improved by early selection.
Advanced oxidation processes (AOPs) constitute a promising technology to treat wastewater containing organic pollutants that are not easily biodegradable. They have received increasing attention in the research and development of wastewater treatment technologies in recent decades for their removal or degradation of recalcitrant pollutants or as pretreatments to convert pollutants into smaller compounds, which can be treated using conventional biological methods. Polyvinyl alcohol (PVA) is a typical refractory organic pollutant. It has received special attention due to its low biodegradability and the large amount of PVA-containing wastewater discharged from textile and paper mills. This review focuses on PVA removal and PVA wastewater pretreatment by AOPs, which include ozonation, Fenton oxidation, persulfate oxidation, ultrasound cavitation, ionizing radiation, photocatalytic oxidation, wet air oxidation and electrochemical oxidation. The mechanistic degradation pathways of PVA by AOPs are also discussed. In addition, a new classification of AOPs is applied for PVA treatment.