Showing papers by "Tongji University published in 2006"

Privacy preserving association rule mining in vertically partitioned data

Abstract: A privacy preserving association rule mining algorithm was introducedThis algorithm preserved privacy of individual values by computing scalar productMeanwhile the algorithm of computing scalar product was given and the security was analyzed

Improved Bioproduction of Short-Chain Fatty Acids (SCFAs) from Excess Sludge under Alkaline Conditions

Abstract: The production of short-chain fatty acids (SCFAs) from excess sludge was conducted in batch fermentation tests at different pH values ranging from 4.0 to 11.0. Experimental results of the impacts of different pHs on SCFAs production showed that during the first 8-day fermentation time the total SCFAs production at either pH 9.0 or pH 10.0 was much greater than that at acidic or neutral pH, and the maximal yield of 256.2 mg SCFAs−COD per gram of volatile suspended solids (VSS) was at pH 10.0, which was, respectively, over 3 and 4 times that at pH 5.0 and uncontrolled pH. Clearly, SCFAs production from excess sludge could be significantly improved and maintained stable by controlling the fermentation pH at 10.0. The composition of SCFAs and the percent distribution of individual SCFAs accounting for total SCFAs at pH 10.0 were analyzed. The SCFAs consisted of acetic, propionic, iso-butyric, n-butyric, iso-valeric, and n-valeric acids, and acetic acid was the most prevalent product with a fraction of 40−55%....

Encapsulating drugs in biodegradable ultrafine fibers through co-axial electrospinning.

Abstract: This article describes an electrospinning process to fabricate double-layered ultrafine fibers. A bioabsorbable polymer, Polycaprolactone (PCL), was used as the outer layer or the shell and two medically pure drugs, Resveratrol (RT, a kind of antioxidant) and Gentamycin Sulfate (GS, an antibiotic), were used as the inner layers or the cores. Morphology and microstructure of the ultrafine fibers were characterized by scanning electron microscope (SEM) and transmission electron microscopy (TEM), whereas mechanical performance of them was understood through tensile test. In vitro degradation rates of the nanofibrous membranes were determined by measuring their weight loss when immersed in pH 7.4 phosphate-buffered saline (PBS) mixed with certain amount of Pseudomonas lipase for a maximum of 7 days. The drug release behaviors of the RT and GS were measured using a high performance liquid chromatography (HPLC) and ultraviolet-visible (UV-vis) spectroscopy, respectively. It has been found that the drug solutions without any fiber-forming additive could be encapsulated in the PCL ultrafine fibers, although they alone cannot be made into a fiber form. Beads on the fiber surface influenced the tensile behavior of the ultrafine fibers remarkably. When the core solvent was miscible with the shell solvent, higher drug concentration decreased the bead formation and thus favored the mechanical performance. The situation, however, became different if the two solvents were immiscible with each other. The degradation rate was closely related to hydrophilicity of the drugs in the cores. Higher hydrophilicity apparently led to faster degradation. The release profiles of the RT and GS exhibited a sustained release characteristic, with no burst release phenomenon.

Binary tree of SVM: a new fast multiclass training and classification algorithm

Abstract: We present a new architecture named Binary Tree of support vector machine (SVM), or BTS, in order to achieve high classification efficiency for multiclass problems. BTS and its enhanced version, c-BTS, decrease the number of binary classifiers to the greatest extent without increasing the complexity of the original problem. In the training phase, BTS has N-1 binary classifiers in the best situation (N is the number of classes), while it has log4/3((N+3)/4) binary tests on average when making a decision. At the same time the upper bound of convergence complexity is determined. The experiments in this paper indicate that maintaining comparable accuracy, BTS is much faster to be trained than other methods. Especially in classification, due to its Log complexity, it is much faster than directed acyclic graph SVM (DAGSVM) and ECOC in problems that have big class number

Rapid and effective adsorption of lead ions on fine poly(phenylenediamine) microparticles.

Abstract: Fine microparticles of poly(p-phenylenediamine) (PpPD) and poly(m-phenylenediamine) (PmPD) were directly synthesized by a facile oxidative precipitation polymerization and their strong ability to adsorb lead ions from aqueous solution was examined. It was found that the degree of adsorption of the lead ions depends on the pH, concentration, and temperature of the lead ion solution, as well as the contact time and microparticle dose. The adsorption data fit the Langmuir isotherm and the process obeyed pseudo-second-order kinetics. According to the Langmuir equation, the maximum adsorption capacities of lead ions onto PpPD and PmPD microparticles at 30 degrees C are 253.2 and 242.7 mg g(-1), respectively. The highest adsorptivity of lead ions is up to 99.8 %. The adsorption is very rapid with a loading half-time of only 2 min as well as initial adsorption rates of 95.24 and 83.06 mg g(-1) min(-1) on PpPD and PmPD particles, respectively. A series of batch experiment results showed that the PpPD microparticles possess an even stronger capability to adsorb lead ions than the PmPD microparticles, but the PmPD microparticles, with a more-quinoid-like structure, show a stronger dependence of lead-ion adsorption on the pH and temperature of the lead-ion solution. A possible adsorption mechanism through complexation between Pb(2+) ions and ==N-- groups on the macromolecular chains has been proposed. The powerful lead-ion adsorption on the microparticles makes them promising adsorbents for wastewater cleanup.

Avoiding propionic acid accumulation in the anaerobic process for biohydrogen production

Abstract: The accumulation of propionic acid in the anaerobic process will result in low efficiency of the methanogenic phase due to the low acetogenic rate of propionic acid, and hence low wastewater treatment efficiency. The reasons for propionic acid accumulation in the acidogenic phase and the relationship between the accumulation and biohydrogen generation were studied and a strategy for avoiding propionic acid accumulation in the anaerobic process for biohydrogen generation is also introduced. The experimental results indicate that changing pH and oxidation–reduction potential (ORP) can result in the variation of fermentation type, and maintaining lower ORP and avoiding pH of 5.5 will reduce the accumulation of propionic acid in the anaerobic process. Higher biohydrogen generation rate is not always accompanied with the accumulation of propionic acid. In the acidogenic reactor of two-phase separated anaerobic process, ethanol type fermentation, in which pH at 4.5 below, can produce much more biohydrogen but without accumulation of propionic acid. Thus, ethanol-type fermentation is a better selection when using an acidogenic reactor of a two-phase separated anaerobic process to efficiently produce biohydrogen with simultaneous organic wastewater pre-treatment.

The relationship between coronary artery disease and abnormal glucose regulation in China: the China Heart Survey

Abstract: Aim The aim of this article is to characterize the glucometabolic state of patients with coronary artery disease (CAD) in China. Methods and results This multicentre study recruited 3513 patients hospitalized for CAD, of whom 35.1% were admissions for acute CAD and 64.9% were elective admissions for CAD. At entry, 1153 patients had known type 2 diabetes and 97 had newly diagnosed diabetes [fasting plasma glucose level (FPG) > or =7.0 mmol/L]. Oral glucose tolerance tests (OGTTs) performed in the remaining patients revealed that 26.9% had diabetes and 37.3% had impaired glucose regulation (IGR). The prevalence of abnormal glucose regulation (AGR) was similar in the acute and elective admissions groups. Overall, the proportion of patients with diagnosed diabetes increased from 32.8% at baseline to 52.9% post-OGTT analysis. In total, 87.4% of patients with IGR and 80.5% of patients with diabetes would have remained undiagnosed if OGTTs had not been performed. Conclusion AGR is common in patients with CAD. The prevalence of AGR is underestimated by FPG testing alone. OGTTs should be routinely used to assess the glucometabolic state of patients with CAD. Individuals identified with IGR or type 2 diabetes should receive treatment to reduce the progression of AGR and associated complications.

Coaxial Electrospun Poly(L‐Lactic Acid) Ultrafine Fibers for Sustained Drug Delivery

Abstract: A coaxial electrospinning technique to fabricate core‐shell ultrafine fiber mats for drug delivery application is described in this paper. Poly (L‐lactic acid) (PLLA) and tetracycline hydrochloride...

Fabrication of porous electrospun nanofibres

Abstract: Immiscible biopolymers of gelatin (Gt) and polycaprolactone (PCL) were first electrospun into a biomimicking composite fibre of Gt/PCL. Based on a phase separation study of the electrospun fibres, a leaching method was employed to generate 3D porous nanofibres by selectively removing the water soluble component of gelatin in a 37 °C aqueous solution of phosphate buffered saline. It was found that leaching treatment gave rise to a unique nanotopography containing grooves, ridges and elliptical pores on the surface as well as inside of the resultant individual nanofibres. Brunauer–Emmett–Teller (BET) area measurement indicated that the formed 3D porous fibres also brought in a pronounced increase of the surface area of fibres. The BET surface area of the porous fibres was observed to be about 2.4 times that of the precursor fibres, up to 15.84 m2 g−1 at its relatively large size of 800 nm diameter. The 3D porous fibres herein prepared could have considerable value for uses in developing highly integrated cell–scaffold tissue complexes and other industrial applications.

The probability density evolution method for dynamic response analysis of non-linear stochastic structures

Abstract: The probability density evolution method (PDEM) for dynamic responses analysis of non-linear stochastic structures is proposed. In the method, the dynamic response of non-linear stochastic structures is firstly expressed in a formal solution, which is a function of the random parameters. In this sense, the dynamic responses are mutually uncoupled. A state equation is then constructed in the augmented state space. Based on the principle of preservation of probability, a one-dimensional partial differential equation in terms of the joint probability density function is set up. The numerical solving algorithm, where the Newmark-Beta time-integration algorithm and the finite difference method with Lax–Wendroff difference scheme are brought together, is studied. In the numerical examples, free vibration of a single-degree-of-freedom non-linear conservative system and dynamic responses of an 8-storey shear structure with bilinear hysteretic restoring forces, subjected to harmonic excitation and seismic excitation, respectively, are investigated. The investigations indicate that the probability density functions of dynamic responses of non-linear stochastic structures are usually irregular and far from the well-known distribution types. They exhibit obvious evolution characteristics. The comparisons with the analytical solution and Monte Carlo simulation method demonstrate that the proposed PDEM is of fair accuracy and efficiency. Copyright © 2005 John Wiley & Sons, Ltd.

Variance Component Estimation in Linear Inverse Ill-posed Models

Abstract: Regularization has been applied by implicitly assuming that the weight matrix of measurements is known. If measurements are assumed to be heteroscedastic with different unknown variance components, all regularization techniques may not be proper to apply, unless techniques of variance component estimation are directly implemented. Although variance component estimation techniques have been proposed to simultaneously estimate the variance components and provide a means of regularization, the regularization parameter is treated as if it were also an extra variance component. In this paper, we assume no prior information on the model parameters and do not treat the regularization parameter as an extra variance component. Instead, we first analyze the biases of estimated variance components due to the regularization parameter and then propose bias-corrected variance component estimators. The results have shown that they work very well. Finally, we propose and investigate through simulations an iterative scheme to simultaneously estimate the variance components and the regularization parameter, in order to eliminate the effect of regularization parameter on variance components and the effect of incorrect prior weights or initial variance components on the regularization parameter.