Acidogenic fermentation of blended food‐waste in combination with primary sludge for the production of volatile fatty acids

The performance of a laboratory‐scale anaerobic acidogenic fermenter fed with a mixture of blended kitchen food‐waste and primary sludge from a sewage treatment plant was investigated for the production of volatile fatty acids (VFA). The operating variables for acidogenic fermentation were kitchen food‐waste content (10 and 25 wt %), hydraulic retention time (HRT: 1, 3 and 5 days), temperature (ambient: 18 ± 2 °C, and mesophilic: 35 ± 2 °C) and pH (varied from 5.2 to 6.7). The experimental results indicated that effluent VFA concentrations and VFA production rates were higher at ambient temperature than at mesophilic conditions. The net amount of VFA with 10 wt % food‐waste increased up to 920 mg dm^?3 with an increase of HRT, but contrasting results (a decrease of 2610 mg dm^?3) were found due to the conversion of VFA into biogas in the case of 25 wt % food‐waste, which increased significantly at HRT of 3–5 days. In terms of biogas composition (CO₂ and CH₄), the organic matter was converted into CO₂ through the oxidative pathway by facultative species at low temperature while mesophilic temperature and optimum pH (6.3–7.8) played a pivotal role in increasing rate of conversion of VFA into biogas by methanogenesis. Rates of VFA production and their conversion are dependent on the food‐waste content in the mixture. Yet, the higher concentration of food‐waste (25% compared with 10%) did not produce VFA proportionally due to the increased rate of conversion of VFA into gaseous products. The maximum VFA production rate (0.318 g VFA_produced g^?1 VS_fed day^?1) was achieved in the 10 wt % food‐waste at ambient temperature and at a 5‐day HRT. Copyright © 2005 Society of Chemical Industry     

Microstructural Evidence for Diffusion-Driven Tetragonal-to-Orthorhombic Phase Transformation in Y-Ba-Cu-O Superconductor

Microstructures of Y-Ba-Cu-O superconductor were observed using a polarized microscope. Orthorhombic and tetragonal phases were easily distinguished by the optical etching with cross-polarized light. In the specimen cooled rapidly in oxygen, it was possible to see the path of oxygen diffusion by observing the variation of the twin concentration. At the boundary between transformed and untransformed materials, evidence for diffusion-driven transformation could be clearly seen.     

Numerical and experimental investigation of three-dimensional flow in extrusion dies

The univariant element, Q₁ P₀, and the multivariant elements, QP₀ and R P₀, are compared for the numerical simulation of the flow in extrusion dies. The pressure distribution obtained by using the Q₁ P₀ element was found to be afflicted with the checkerboard pressure mode. On the other hand, the multivariant elements, Q P₀ and R P₀, gave accurate and physically reasonable velocity and pressure distributions. The computed values of the pressure drop across extrusion dies matched well with the pressure drop determined experimentally.     

Collapse-free thermal bonding technique for large area microchambers in plastic lab-on-a-chip applications

Bonding is an essential step to form microchannels or microchambers in lab-on-a-chip applications. In this paper, we present a novel plastic thermal bonding technique to seal and form large area microchambers (planar characteristic width and length on the order of 1 mm and characteristic thickness on the order of 10–100 μm) without collapse by introducing a holed pressure equalizing plate (HPEP) that includes holes of the same size and shape as the microchambers. To demonstrate the proposed technique, two types of large area microchambers [(1) 20 × 10 mm and 40 μm thick and (2) 12 × 2.5 mm and 120 μm thick] with microchannels were designed and replicated on plastic substrates by means of hot embossing and injection molding processes with prepared two nickel mold inserts. The replicated large area microchambers as well as the microchannels in the plastic lab-on-a-chip were successfully sealed (i.e., no leakage) and formed without any collapse by the proposed thermal bonding technique with the help of the HPEP.     

Metal Ions versus Protons: Tracking of Charge-Carrier Insertion into a Cathode Oxide in Aqueous Rechargeable Batteries

Protons in aqueous electrolytes can perform as an additional type of charge carrier for insertion/extraction in addition to the primary carrier cations in aqueous rechargeable batteries. Despite many diverse claims regarding the effect of protons, mutually conflicting experimental results and their interpretations without direct evidence have been reported over the last decade. Systematic examinations and analyses are thus imperative to clarify the conditions of proton insertion in aqueous rechargeable batteries. Utilizing V₂O₅ as a model cathode and beaker-type cells with a sufficient amount of ZnSO₄ aqueous electrolytes in this work, it is demonstrated that protons are inserted into the cathode prior to Zn-ions in low-pH conditions (pH ≤ 3.0). In stark contrast, the influence of protons on the discharge voltage and capacity is insignificant, when either the pH becomes higher (pH ≥ 4.0) or the electrolyte volume is considerably low in coin-type cells. Similar behavior of pH-dependent proton insertion is also verified in Na–, Mg–, and Al-ion electrolytes. Providing a resolution to the controversy regarding proton insertion, the present study emphasizes that the influence of protons substantially varies depending on the pH and relative volume of electrolytes in aqueous batteries.     

Surface modification of polyetherurethaneureas and their antithrombogenicity

Polyetherurethaneurea (PU) films were treated by oxygen plasma discharge followed by acrylic acid (AA) grafting. The carboxyl groups of the AA-grafted PU (PU-AA) surface were coupled with bovine serum albumin and heparin via water soluble carbodiimide. Surface characterization of the modified PUs was carried out by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and electron spectroscopy for chemical analysis (ESCA). The amount of immobilized albumin and heparin on the PU surface was 1.8 and 1.5 g/cm², respectively, as determined by the dye interaction method. Interactions between the surface-modified PUs and blood components such as plasma proteins and platelets were investigated to evaluate the blood compatibility of the samples. Plasma recalcification time (PRT) and activated partial thromboplastin time (APTT) of the albumin-immobilized PU (PU-Al) were almost the same as those of PU, while platelets were less adhered on the PU-Al than on PU. On the other hand, PRT and APTT of the PU-He were significantly longer than those of the PU, PU-AA, and PU-Al. Moreover, adhesion of platelets was effectively suppressed on the PU-He, leading to good in vitro blood compatibility.     

Optimization of optical lens-controlled scanning electron microscopic resolution using generalized regression neural network and genetic algorithm

A scanning electron microscope (SEM) is a sophisticated equipment employed for fine imaging of a variety of surfaces. In this study, prediction models of SEM were constructed by using a generalized regression neural network (GRNN) and genetic algorithm (GA). The SEM components examined include condenser lens 1 and 2 and objective lens (coarse and fine) referred to as CL1, CL2, OL-Coarse, and OL-Fine. For a systematic modeling of SEM resolution (R), a face-centered Box–Wilson experiment was conducted. Two sets of data were collected with or without the adjustment of magnification. Root-mean-squared prediction error of optimized GRNN models are GA 0.481 and 1.96×10^-12 for non-adjusted and adjusted data, respectively. The optimized models demonstrated a much improved prediction over statistical regression models. The optimized models were used to optimize parameters particularly under best tuned SEM environment. For the variations in CL2 and OL-Coarse, the highest R could be achieved at all conditions except a larger CL2 either at smaller or larger OL-Coarse. For the variations in CL1 and CL2, the highest R was obtained at all conditions but larger CL2 and smaller CL1.     

Investigating factors that influence social presence and learning outcomes in distance higher education

There are many factors that influence distance learning especially in higher education where collaborative and communicative discourse is necessary for pursuing knowledge. Social presence, among other factors, is an important concept to be facilitated, developed and sustained in distance higher education as it promotes and supports discourse based learning. This study examines the relationship among demographic and other variables, social presence and learning satisfaction. Results showed demographic variables, such as gender, online learning experience and work status were not significant factors in terms of influencing on either social presence or learning satisfaction. While media integration and instructor’s quality teaching were significant predictors of both social presence and learning satisfaction, interactivity among participants was a predictor of social presence but not of learning satisfaction. Along with the study findings, some implications were discussed for online learning practitioners in higher education setting.     

A multi-agent intelligent system for efficient ERP maintenance

The Enterprise Resource Planning (ERP) system is an enterprise-wide integrated software package designed to uphold the highest quality standards of business process. However, for the time being, when the business condition has been changed, the system may not guarantee that the process embedded in ERP is still best. Moreover, since the ERP system is very complex, maintaining the system by trial and error is very costly. Hence, this paper aims to construct a support system that adjusts ERP system to environmental changes. To do so, we adopt multi-agent intelligent technology that enables autonomous cooperation with one another to monitor ERP databases and to find any exceptional changes and then analyze how the changes will affect ERP performance. Moreover, Petri net is applied to manage the complexity and dynamics of agents’ behavior. To show the feasibility of the idea, a prototype agent system, ERP/PN, is proposed and an experiment is conducted.