113 research outputs found
Bioremediation of polycyclic aromatic hydrocarbon (PAH)-contaminated soils in a roller baffled bioreactor
Contamination of soil with Polycyclic Aromatic Hydrocarbons (PAHs) is a serious environmental issue because some PAHs are toxic, carcinogenic and mutagenic. Bioremediation is a promising option to completely remove PAHs from the environment or convert them to less harmful compounds. One of the main challenges in bioremediation of PAHs in a conventional roller bioreactor is the limitation on mass transfer due to the strong hydrophobicity and low water solubility of these compounds. To address this challenge, a novel bead mill bioreactor (BMB) was developed by Riess et al. (2005) which demonstrated a significant improvement in the rates of mass transfer and biodegradation of PAHs. In this study, to further improve mass transfer rates, baffles have been installed in both the conventional and bead mill bioreactors. Mass transfer rates of 1000 mg L-1 suspended naphthalene, 2-methylnaphthalene and 1,5-dimethylnaphthalene, three model compounds of PAHs, have been investigated in four bioreactors: conventional (control), baffled, BMB and baffled bead mill bioreactors. The baffled bioreactor provided mass transfer coefficients (KLa) that were up to 7 times higher than those of the control bioreactor. Bioremediation of suspended naphthalene or 2-methylnaphthalene as a single substrate and their mixtures was studied using the bacterium Pseudomonas putida ATCC 17484. Both baffled and bead mill bioreactors provided maximum bioremediation rates that were 2 times higher than the control bioreactor. The maximum bioremediation rates of 2-methylnaphthalene were further increased in the presence of naphthalene by a factor of 1.5 to 2 compared to the single substrate. Another rate-limiting step for bioremediation of PAH-contaminated soil is the strong sorption between the contaminant and soil. To find out the effect of sorption on the bioavailability of naphthalene, the appropriate sorption isotherms for three types of soils (sand, silt and clay) have been determined. It was observed that the sorption capacity of soils for naphthalene was proportional to the organic carbon content of the soils. The mass transfer of soil-bound naphthalene from the artificially prepared contaminated soils with short contamination history to the aqueous phase was studied in both the control and bead mill bioreactors. It was observed that the mass transfer was unexpectedly fast due to the increased interfacial surface area of naphthalene particles and the weak sorption between naphthalene and soils. It was concluded that artificially, naphthalene contaminated soils would likely not be any more difficult to bioremediate than pure naphthalene particles
Analytic Bethe Ansatz for 1-D Hubbard model and twisted coupled XY model
We found the eigenvalues of the transfer matrices for the 1-D Hubbard model
and for the coupled XY model with twisted boundary condition by using the
analytic Bethe Ansatz method. Under a particular condition the two models have
the same Bethe Ansatz equations. We have also proved that the periodic 1-D
Hubbard model is exactly equal to the coupled XY model with nontrivial twisted
boundary condition at the level of hamiltonians and transfer matrices.Comment: 22 pages, latex, no figure
Multichannel Seismic Deconvolution Using Bayesian Method
In this paper, we propose an algorithm for multichannel blind deconvolution of seismic signals, which exploits variational Bayesian method. It is related to the Kullback-Leibler divergence, which measures the independence degree of deconvolved data sequence. We assume that the reflectivity sequence is almost the same for each receiver while the noise level may differ at each channel. Compared to blind deconvolution of a single seismic trace, multichannel blind deconvolution provides an accurate convergence of the estimated parameters and reflectivity sequence
Biomechanical analysis of the Maxillary Sinus Floor Membrane During internal Sinus Floor Elevation With Implants at Different angles of the Maxillary Sinus angles
OBJECTIVE: This study analyzed and compared the biomechanical properties of maxillary sinus floor mucosa with implants at three different maxillary sinus angles during a modified internal sinus floor elevation procedure.
METHODS: 3D reconstruction of the implant, maxillary sinus bone, and membrane were performed. The maxillary sinus model was set at three different angles. Two internal maxillary sinus elevation models were established, and finite element analysis was used to simulate the modified maxillary sinus elevation process. The implant was elevated to 10 mm at three maxillary sinus angles when the maxillary sinus floor membrane was separated by 0 and 4 mm. The stress of the maxillary sinus floor membrane was analyzed and compared.
RESULTS: When the maxillary sinus floor membrane was separated by 0 mm and elevated to 10 mm, the peak stress values of the implant on the maxillary sinus floor membrane at three different angles were as follows: maxillary sinus I: 5.14-78.32 MPa; maxillary sinus II: 2.81-73.89 MPa; and maxillary sinus III: 2.82-51.87 MPa. When the maxillary sinus floor membrane was separated by 4 mm and elevated to 10 mm, the corresponding values were as follows: maxillary sinus I: 0.50-7.25 MPa; maxillary sinus II: 0.81-16.55 MPa; and maxillary sinus III: 0.49-22.74 MPa.
CONCLUSION: The risk of sinus floor membrane rupture is greatly reduced after adequate dissection of the maxillary sinus floor membrane when performing modified internal sinus elevation in a narrow maxillary sinus. In a wide maxillary sinus, the risk of rupture or perforation of the wider maxillary sinus floor is reduced, regardless of whether traditional or modified internal sinus elevation is performed at the same height
Skinner operant conditioning model and robot bionic self-learning control
Fuzzy Skinner Operant Conditioning Automaton (FSOCA) sastavljen je na temelju Operant Conditioning mehanizma primjenom teorije neizrazitih skupova. Osnovno obilježje automata FSOCA je sljedeće: neizraziti rezultati stanja pomoću Gausove funkcije koriste se kao skupovi neizrazitog stanja; neizrazita pravila preslikavanja (fuzzy mapping rules) kod fuzzy-conditioning-operacije zamjenjuju stohastičke "conditioning-operant" skupove preslikavanja. Stoga se automat FSOCA može koristiti za opisivanje, simuliranje i dizajniranje raznih samo-organizirajućih radnji fuzzy nesigurnog sustava. Automat FSOCA najprije usvaja online algoritam grupiranja (clustering) u svrhu podjele ulaznog prostora (input space) te koristi intenzitet pobude pravila preslikavanja kako bi odlučio treba li generirati novo pravilo preslikavanja da bi broj pravila preslikavanja bio ekonomičan. Dizajnirani FSOCA automat primijenjen je za reguliranje balansiranja gibanja robota s dva kotača. Kako se učenje nastavlja, odabrana vjerojatnoća fuzzy operanta koji optimalno slijedi postepeno će se povećavati, entropijsko djelovanje fuzzy operanta će se postepeno smanjivati pa će se automatski generirati i izbrisati neizrazita pravila preslikavanja. Nakon otprilike sedamnaest krugova obuke, odabrane vjerojatnosti neizrazitog posljedičnog optimalnog operanta postupno teže prema jednoj, entropija djelovanja neizrazitog operanta postupno se smanjuje i broj neizrazitih pravila preslikavanja postaje optimalan. Tako robot postupno uči vještinu balansiranja gibanja.A Fuzzy Skinner Operant Conditioning Automaton (FSOCA) is constructed based on Operant Conditioning Mechanism with Fuzzy Set theory. The main character of FSOCA automaton is: the fuzzed results of state by Gaussian function are used as fuzzy state sets; the fuzzy mapping rules of fuzzy-conditioning-operation replace the stochastic "conditioning-operant" mapping sets. So the FSOCA automaton can be used to describe, simulate and design various self-organization actions of a fuzzy uncertain system. The FSOCA automaton firstly adopts online clustering algorithm to divide the input space and uses the excitation intensity of mapping rule to decide whether a new mapping rule needs to be generated in order to ensure that the number of mapping rules is economical. The designed FSOCA automaton is applied to motion balanced control of two-wheeled robot. With the learning proceeding, the selected probability of the optimal consequent fuzzy operant will gradually increase, the fuzzy operant action entropy will gradually decrease and the fuzzy mapping rules will automatically be generated and deleted. After about seventeen rounds of training, the selected probabilities of fuzzy consequent optimal operant gradually tend to one, the fuzzy operant action entropy gradually tends to minimum and the number of fuzzy mapping rules is optimum. So the robot gradually learns the motion balance skill
Long-term spatial and temporal variation of CO2 partial pressure in the Yellow River, China
10.5194/bg-12-921-2015Biogeosciences124921-93
Use of parenteral caffeinum natrio-benzoicum: an underestimated risk factor for HCV transmission in China
Fuzzy sphere bimodule, ABS construction to the exact soliton solutions
In this paper, we set up the bi-module of the algebra on fuzzy
sphere. Based on the differential operators in moving frame, we generalize the
ABS construction into fuzzy sphere case. The applications of ABS construction
are investigated in various physical systems.Comment: Latex file without figure, 13 page
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