Level of natural hepatotoxin (Indospicine) contamination in Australian camel meat

Camel meat production for human consumption and pet food manufacture accounts for a relatively small part of overall red meat production in Australia. Reliable statistical data for the Australian production and consumption of camel meat are not available; however, it is estimated that 300,000 feral camels roam within the desert of central Australia, with an annual usage of more than 3000 camels for human consumption, 2000 for pet food manufacture and a smaller number for live export. Despite a small Australian camel meat production level, the usage of camel meat for pet food has been restricted in recent years due to reports of serious liver disease and death in dogs consuming camel meat. This camel meat was found to contain residues of indospicine, a non-proteinogenic amino acid found in certain Indigofera spp., and associated with mild to severe liver disease in diverse animals after dietary exposure to this hepatotoxin. The extent of indospicine-contaminated Australian camel meat was previously unknown, and this study ascertains the prevalence of such residue in Australian camel meat. In this study, indospicine levels in ex situ (95 samples collected from an abattoir in Queensland) and in situ (197 samples collected from camels after field culling in central Australia) camel meat samples were quantitated using a validated ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The quantitation results showed 46.7% of the in situ- and 20.0% of the ex situ-collected camel meat samples were contaminated by indospicine (more than the limit of detection (LOD) of 0.05 mg kg^–1 fresh weight). The overall indospicine concentration was higher (p < 0.05) in the in situ-collected samples. Indospicine levels detected in the present study are considered to be low; however, a degree of caution must still be exercised, since the tolerable daily intake for indospicine is currently not available for risk estimation.     

Decision Tree-Based Data Mining and Rule Induction for Identifying High Quality Groundwater Zones to Water Supply Management: a Novel Hybrid Use of Data Mining and GIS

Water Resources Management - Groundwater is an important source to supply drinking water demands in both arid and semi-arid regions. Nevertheless, locating high quality drinking water is a major...     

Performance analysis of multi-antenna relay networks with imperfect channel estimation

In this paper, we present the performance of multi-antenna selective combining decode-and-forward (SC-DF) relay networks over independent but non-identical Nakagami-m fading channels with imperfect channel estimation. The outage probability, moment generating function (MGF) and symbol error probability (SEP) will be derived in closed-form using the SNR statistical characteristics. To make the analysis trackable, we have derived the MGF and SEP for integer values of fading severity, m. Also, to make the relations more simple, we develop high signal to noise ratio (SNR) analysis for the performance metrics of our system. Subsequently, we propose optimal and adaptive power allocation algorithms along with the equal power allocation method. Finally, for comparison with analytical formulas, we perform some Monte-Carlo simulations.     

Anisotropic loss of toughness with physical aging of work toughened polycarbonate

We have studied the response of mechanically toughened and physically aged polycarbonate primarily using Charpy impact and ultrasonic wave speed measurements. The toughening was conducted through plastic compression on as‐received PC. The Charpy impact tests showed anisotropic toughening, both in the absorbed energy and in the mode of fracture. The amount of toughening with plastic compression, even though anisotropic, is centered around the response of annealed and quenched samples, which represent the response of an unaged PC. There was an anisotropic drop in the toughness of some samples with aging. The time of this drop was uncorrelated in the different directions and disappeared for the highly toughened samples. This transition was bimodal and statistically distributed between either a fully ductile or a fully brittle failure. As the samples were prepared in a manner to remove induced residual stresses, this drop in toughening may be associated with an intrinsic anisotropic thermal aging of the deformed material. POLYM. ENG. SCI., 54:794–804, 2014. © 2013 Society of Plastics Engineers     

Induction time,storage capacity,and rate of methane hydrate formation in the presence of SDS and silver nanoparticles

In this communication, the kinetic parameters of methane hydrate formation (induction time, quantity and rate of gas uptake, storage capacity (SC), and apparent rate constant) in the presence of sodium dodecyl sulfate (SDS), synthetized silver nanoparticles (SNPs), and mixture of SDS?+?SNPs have been studied. Experimental measurements were performed at temperature of 273.65?K and initial pressure of 7?MPa in a 460?cm³ stirred batch reactor. Our results show that adding SDS, SNPs and their mixture increases the quantity of gas uptake, water to hydrate conversion, and SC of methane hydrate formation, noticeably. Using 300?ppm SDS increases the SC and the quantity of methane uptake 615, and 770%, respectively, compared with pure water. Investigating the hydrate growth rate at the start of hydrate formation process shows that, using SNPs, SDS, and their mixture increases the initial apparent rate constant of hydrate rate, considerably. Our results show that the system of methane?+?water?+?SDS 500?ppm?+?SNPs 45?µM represents the maximum value of initial apparent rate constant, compared with other tested systems.     

Solving non-convex economic dispatch problem with valve point effects using modified group search optimizer method

This paper presents a novel solution based on the group search optimizer (GSO) methodology in order to determine the feasible optimal solution of the economic dispatch (ED) problem considering valve loading effects. The basic disadvantage of the original GSO algorithm is the fact that it gives a near-optimal solution rather than an optimal one in a limited runtime period. In this paper, a new modified group search optimizer (MGSO) is presented for improving the scrounger and ranger operators of GSO. The proposed MGSO is applied on different test systems and compared with most of the recent methodologies. The results show the effectiveness of the proposed method and prove that MGSO can be applicable for solving the power system economic load dispatch problem, especially in large scale power systems.     

Study of the behavior of mechanically stabilized earth (MSE) walls subjected to differential settlements

The limit equilibrium (LE) analysis has been used to design MSE walls. Presumably, the deflection of MSE walls can be limited to an acceptable range by ensuring sufficient factors of safety (FOSs) for both external and internal stabilities. However, unexpected ground movements, such as movements induced by excavations, volume changes of expansive soils, collapse of sinkholes, and consolidations of underlying soils, can induce excessive differential settlements that may influence both the stability and the serviceability of MSE walls. In this study, a numerical model, which was calibrated by triaxial tests and further by a specially-designed MSE wall tests, investigated the behavior of an MSE wall as well as the influence of various factors on the performance of the MSE wall when the wall facing settled relatively to the reinforced zone. The numerical results showed that the differential settlement would cause substantial vertical and horizontal movements for the MSE wall, as well as an increase in lateral earth pressure and geosynthetic reinforcement strain. The maximum horizontal movement and increase of the lateral earth pressure occurred at about 1.0 m above the toe. The differential settlement resulted in a critical plane that coincided with the plane of 45°+?/2. The maximum increase of the strain for each geogrid layer occurred in that plane, and the bottom layer had the greatest strain increase among all layers of reinforcement. The study further indicated that the surcharge, backfill friction angle, tensile stiffness of geogrid, reinforcement length and MSE wall height had noticeable influences on horizontal and vertical movements, and strain in geosynthetics. According to the results, the MSE wall that had a higher factor of safety would have less movements and geosynthetic strain increase. In contrast, only the friction angle, tensile stiffness and MSE wall height showed some degree of influence on the lateral earth pressure due to differential settlements.     

Permeability of high-performance concrete subjected to elevated temperature (600 °C)

Permeability is one of the most important parameters to quantify the durability of high-performance concrete. Permeability is closely related with the spalling phenomenon in concrete at elevated temperature. This parameter is commonly measured on non-thermally damaged specimens. This paper presents the results of an experimental investigation carried out to study the effect of elevated temperature on the permeability of high-performance concrete. For this purpose, three types of concrete mixtures were prepared: (i) control high-performance concrete; (ii) high-performance concrete incorporating polypropylene fibres; and (iii) high-performance concrete made with lightweight aggregates. A heating–cooling cycle was applied on 160 × 320 mm, 110 × 220 mm, and 150 × 300 mm cylindrical specimens. The maximum test temperature was kept as either 200 or 600 °C. After the thermal treatment, 65 mm thick slices were cut from each cylinder and dried prior to being subjected to permeability test. Results of thermal gradients in the concrete specimens during the heating–cooling cycles, compressive strength, and splitting tensile strength of concrete mixtures are also presented here. A relationship between the thermal damage indicators and permeability is presented.     

Prediction of compressive strength of self-compacting concrete containing bottom ash using artificial neural networks

The paper presents a comparative performance of the models developed to predict 28 days compressive strengths using neural network techniques for data taken from literature (ANN-I) and data developed experimentally for SCC containing bottom ash as partial replacement of fine aggregates (ANN-II). The data used in the models are arranged in the format of six and eight input parameters that cover the contents of cement, sand, coarse aggregate, fly ash as partial replacement of cement, bottom ash as partial replacement of sand, water and water/powder ratio, superplasticizer dosage and an output parameter that is 28-days compressive strength and compressive strengths at 7 days, 28 days, 90 days and 365 days, respectively for ANN-I and ANN-II. The importance of different input parameters is also given for predicting the strengths at various ages using neural network. The model developed from literature data could be easily extended to the experimental data, with bottom ash as partial replacement of sand with some modifications.