A review of the stabilization of tropical lowland peats

The Deep Mixing Method, which involves the formation of in situ stabilized peat columns, is suitable for deep peat stabilization, whereas the mass stabilization technique is used to stabilize the soil of shallow peat deposits instead of the costly and problematic removal and replacement method. The concept of soil-cement stabilization involves the addition of water to cement, resulting in a chemical process known as cement hydration. Stabilization of peat by cement, which requires a significant strength increase in the cement-stabilized peat or organic soil, is attributed largely to physicochemical reactions that include cement hydration, hardening of the resulting cement paste and interactions between soil substances and primary and secondary cementation hydration products. The factors that affect these physicochemical reactions and the interactions of peat soil-cementation products that influence peat stabilization are the amount of solid particles, the water: soil ratio, the quantity of binder, the presence of humic and/or fulvic acids, the soil pH and the amount of organic matter in the peat. With the Air Curing Technique, stabilized peat samples for unconfined compressive strength (UCS) tests were kept at a normal air temperature of 30 ± 2 °C and strengthened by gradual moisture content reduction instead of the usual water-curing technique or water submersion methods that have been common practice in past experiments involving the stabilization of peat with cement. The principle of using the Air Curing Technique to strengthen stabilized peat is that peat soil at its natural moisture content contains sufficient water (water content from 198 to 417 %) that, when mixed with cement, a curing process takes place that causes the stabilized peat soil to gradually lose its moisture content and to become drier and harder throughout the curing period. This process does not require the addition of water.     

Design,characterization and ex vivo evaluation of chitosan film integrating of insulin nanoparticles composed of thiolated chitosan derivative for buccal delivery of insulin

The purpose of this study is to optimize and characterize of chitosan buccal film for delivery of insulin nanoparticles that were prepared from thiolated dimethyl ethyl chitosan (DMEC-Cys). Insulin nanoparticles composed of chitosan and dimethyl ethyl chitosan (DMEC) were also prepared as control groups. The release of insulin from nanoparticles was studied in vitro in phosphate buffer solution (PBS) pH 7.4. Optimization of chitosan buccal films has been carried out by central composite design (CCD) response surface methodology. Independent variables were different amounts of chitosan and glycerol as mucoadhesive polymer and plasticizer, respectively. Tensile strength and bioadhesion force were considered as dependent variables. Ex vivo study was performed on excised rabbit buccal mucosa. Optimized insulin nanoparticles were obtained with acceptable physicochemical properties. In vitro release profile of insulin nanoparticles revealed that the highest solubility of nanoparticles in aqueous media is related to DMEC-Cys nanoparticles. CCD showed that optimized buccal film containing 4% chitosan and 10% glycerol has 5.81?kg/mm² tensile strength and 2.47?N bioadhesion forces. Results of ex vivo study demonstrated that permeation of insulin nanoparticles through rabbit buccal mucosa is 17.1, 67.89 and 97.18% for chitosan, DMEC and DMEC-Cys nanoparticles, respectively. Thus, this study suggests that DMEC-Cys can act as a potential enhancer for buccal delivery of insulin.     

Optimization of Short Load Forecasting in Electricity Market of Iran Using Artificial Neural Networks

Accurate short-term load forecasting (STLF) is one of the essential requirements for power systems. In this paper, two different seasonal artificial neural networks (ANNs) are designed and compared in terms of model complexity, robustness, and forecasting accuracy. Furthermore, the performance of ANN partitioning is evaluated. The first model is a daily forecasting model which is used for forecasting hourly load of the next day. The second model is composed of 24 sub-networks which are used for forecasting hourly load of the next day. In fact, the second model is partitioning of the first model. Time, temperature, and historical loads are taken as inputs for ANN models. The neural network models are based on feed-forward back propagation which are trained and tested using data from electricity market of Iran during 2003 to 2005. Results show a good correlation between actual data and ANN outcomes. Moreover, it is shown that the first designed model consisting of single ANN is more appropriate than the second model consisting of 24 distinct ANNs. Finally ANN results are compared to conventional regression models. It is observed that in most cases ANN models are superior to regression models in terms of mean absolute percentage error (MAPE).     

Electro-optic investigation of the surface trapping efficiency in n-alkanethiol SAM passivated GaAs(001)

The electro-optic characteristics of the semi-insulating and n(+)-type GaAs(001) surfaces passivated with n-alkanethiol self-assembled monolayers were investigated using Kelvin probe surface photovoltage (SPV) and photoluminescence (PL) techniques. Referencing the equilibrium surface barrier height established in an earlier report, SPV measurements demonstrated a significant (>100 mV) increase in the non-equilibrium band-bending potential observed under low-level photo-injection. Modeling of the SPV accounts for these observations in terms of a large (>10(4)) decrease in the hole/electron ratio of surface carrier capture cross-sections, which is suggested to result from the electrostatic potential of the interfacial dipole layer formed upon thiol chemisorption. The cross-section effects are verified in the high-injection regime based on carrier transport modeling of the PL enhancement manifested as a reduction of the surface recombination velocity.     

Traffic differentiation support in vehicular delay-tolerant networks

Vehicular Delay-Tolerant Networking (VDTN) is a Delay-Tolerant Network (DTN) based architecture concept for transit networks, where vehicles movement and their bundle relaying service is opportunistically exploited to enable non-real time applications, under environments prone to connectivity disruptions, network partitions and potentially long delays. In VDTNs, network resources may be limited, for instance due to physical constraints of the network nodes. In order to be able to prioritize applications traffic according to its requirements in such constrained scenarios, traffic differentiation mechanisms must be introduced at the VDTN architecture. This work considers a priority classes of service (CoS) model and investigates how different buffer management strategies can be combined with drop and scheduling policies, to provide strict priority based services, or to provide custom allocation of network resources. The efficiency and tradeoffs of these proposals is evaluated through extensive simulation.     

Ductile crack growth and constraint in pipelines subject to combined loadings

An important failure mode of offshore pipelines is ductile fracture of the pipe wall triggered by a hypothetical welding defect. In this study, pipelines having an external part-through semi-circumferential crack of various sizes, subject to combined internal pressure and inelastic bending are considered. This is done to assess the response of pipelines during both their installation and operational conditions. Detailed 3D nonlinear finite element (FE) models of pipelines are developed. A row of elements ahead of the initial crack front are modeled using a voided plasticity material model, which enables simulation of crack growth and the subsequent fracture failure mode (denoted by the critical curvature, κ_crit). After discussing the typical response characteristics of such pipelines, the FE model is used to parametrically investigate the influence of varying pipe and crack dimensions, and also the internal pressure levels, on κ_crit. In the second part of this paper, the crack tip constraint ahead of a growing crack in such pipes is evaluated and systematically compared to the crack tip constraint of both the traditionally used deeply cracked Single Edge Notch Bend (SENB) specimens and the constraint-matched Single Edge Notch Tensile (SENT) specimens. This is achieved by comparing the crack resistance curves (R-curves) along with stress triaxiality and equivalent plastic strain fields evaluated ahead of a growing crack of the three systems. The results present grounds for justification of usage of SENT specimens in fracture assessment of such pipes as an alternative to the traditional overly conservative SENB specimens.     

Dental Composites with Magnesium Doped Zinc Oxide Nanoparticles Prevent Secondary Caries in the Alloxan-Induced Diabetic Model

Antibacterial restorative materials against caries-causing bacteria are highly preferred among high-risk patients, such as the elderly, and patients with metabolic diseases such as diabetes. This study aimed to enhance the antibacterial potential of resin composite with Magnesium-doped Zinc oxide (Mg-doped ZnO) nanoparticles (NPs) and to look for their effectiveness in the alloxan-induced diabetic model. Hexagonal Mg-doped ZnO NPs (22.3 nm diameter) were synthesized by co-precipitation method and characterized through ultraviolet-visible (UV-Vis), Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS) analysis. The Mg-doped ZnO NPs (1, 2.5 and 5% w/w) were then evaluated for antibacterial activity using a closed system in vitro biofilm model. Significant enhancement in the antibacterial properties was observed in composites with 1% Mg-doped ZnO compared to composites with bare ZnO reinforced NPs (Streptococcus mutans, p = 0.0005; Enterococcus faecalis, p = 0.0074, Saliva microcosm, p < 0.0001; Diabetic Saliva microcosm, p < 0.0001). At 1–2.5% Mg-doped ZnO NPs concentration, compressive strength and biocompatibility of composites were not affected. The pH buffering effect was also achieved at these concentrations, hence not allowing optimal conditions for the anaerobic bacteria to grow. Furthermore, composites with Mg-doped ZnO prevented secondary caries formation in the secondary caries model of alloxan-induced diabetes. Therefore, Mg-doped ZnO NPs are highly recommended as an antibacterial agent for resin composites to avoid biofilm and subsequent secondary caries formation in high-risk patients.     

Study of spray cooling of a pressure vessel head of a boiling water reactor

The present paper deals with a theoretical analysis of the spray cooling of a Reactor Pressure Vessel (RPV) head in a Boiling Water Reactor (BWR). To this end a detailed computational model has been developed. The model predicts the trajectories, diameters and temperatures of subcooled droplets moving in saturated vapor. The model has been validated through comparison with experimental data, in which droplet temperatures were measured as functions of the distance that they cover in saturated vapor from the moment they leave the sprinkler outlet to the moment they impact on the RPV head inner wall. The calculations are in very good agreement with measurements, confirming the model adequacy for the present study. The model has been used for a parametric study to investigate the influence of several parameters on the cooling efficiency of the spray system. Based on the study it has been shown that one of the main parameters that govern the temperature increase in a subcooled droplet is its initial diameter. Comparisons are also made between conclusions from the theoretical model and observations made through flow and temperature measurements in the plant (Forsmark 1 and 2). One of these observations is that the rate at which the RPV head temperature decreases on the way down from hot to cold standby is constant and independent of the sprinkling flow rate as long as the flow rate is above a certain minimum value. Accordingly, the theoretical model shows that if one assumes that the cooling of the RPV head is through a water film built on the inner wall due to sprinkling, the heat removal rate is only very weakly dependent on the sprinkling flow rate.     

Combined extraction processes of lipid from Chlorella vulgaris microalgae: microwave prior to supercritical carbon dioxide extraction

Extraction yields and fatty acid profiles from freeze-dried Chlorella vulgaris by microwave pretreatment followed by supercritical carbon dioxide (MW-SCCO(2)) extraction were compared with those obtained by supercritical carbon dioxide extraction alone (SCCO(2)). Work performed with pressure range of 20-28 Mpa and temperature interval of 40-70 °C, gave the highest extraction yield (w/w dry weight) at 28 MPa/40 °C. MW-SCCO(2) allowed to obtain the highest extraction yield (4.73%) compared to SCCO(2) extraction alone (1.81%). Qualitative and quantitative analyses of microalgae oil showed that palmitic, oleic, linoleic and α-linolenic acid were the most abundant identified fatty acids. Oils obtained by MW-SCCO(2) extraction had the highest concentrations of fatty acids compared to SCCO(2) extraction without pretreatment. Native form, and microwave pretreated and untreated microalgae were observed by scanning electronic microscopy (SEM). SEM micrographs of pretreated microalgae present tearing wall agglomerates. After SCCO(2), microwave pretreated microalgae presented several micro cracks; while native form microalgae wall was slightly damaged.     

Removal of cyanide in aqueous solution by oxidation with hydrogen peroxide in presence of copper-impregnated activated carbon

This work is devoted to the removal of free cyanide from aqueous solution by oxidation with hydrogen peroxide H₂O₂ catalyzed by copper-impregnated activated carbon. Effects of initial molar ratio [H₂O₂]₀/[CN⁻]₀, copper-impregnated activated carbon amount, pH and the temperature on cyanide removal have been investigated.The presence of copper-impregnated activated carbon has increased the reaction rate showing thus a catalytic activity. The rate of cyanides removal increases with the raise of the initial molar ratio [H₂O₂]₀/[CN⁻]0 and decreases with the increase in the pH from 8 to 12. The increase in the copper-impregnated activated carbon amount from 1.5 to 10 g/L in reaction solution has a beneficial effect. Beyond this value, the impact of activated carbon amount is not anymore significant. The temperature does not have a significant effect between 20 and 35 °C. The four successive times re-use of catalyst shows a good stability. The kinetics of cyanide removal has been found to be of pseudo-second-order with respect to cyanide and the rate constants have been determined. This process seems very interesting because the rate of cyanides removal is very fast, the reaction does not use soluble metal catalyst and it consumes only hydrogen peroxide as chemical product.