An investigation into physicochemical characteristics of ash produced from combustion of oil palm biomass wastein a boiler

Ash derived from combustion of Malaysian oil palm biomass (empty fruit bunches consisting of fibers) was physically and chemically characterized in order to provide a comprehensive understanding of its specific properties in terms of toxicity, compositions and reusability. Principal analyses conducted include particle size distribution, scanning electron microscopy, elemental dispersive X-ray, elemental analysis, toxicity characteristic leaching procedure (TCLP) as well as thermogravimetric, X-ray diffractometry and Fourier-transform infrared analyses. TCLP result indicated that the oil palm ash (OPA) should not be classified as toxic wastes in terms of heavy metal leachability since leachable copper, cadmium, lead and nickel concentrations were detected below the stipulated leachability limits. It was determined that the OPA contained high amount of potassium as well as presence of silica which implied its suitability to be reused as crude fertilizer or cement replacement material.     

优化移动多媒体传输链的功耗

消费者对于移动多媒体的需求是毫无疑问的，满足这些需求的技术已经开发成功，对于设计人员而言，剩下的问题就是如何利用这些技术，并将成功的产品带入市场。本文将讨论如何减省移动多媒体设备内关键元件的功耗，此外也会对现今移动多媒体设备设计人员所面对的工程挑战作出概括的分析，并就目前及新涌现的硅技术，提出可克服这些工程挑战的解决方案。     

Investigations of surface characterization of silicone rubber due to tracking phenomena under a.c. and d.c. voltages

In the present work, tracking phenomena has been studied with silicone rubber material under the a.c. and d.c. voltages following IEC-587 standards. The surface condition of the tracked zone was analysed using wide angle X-ray diffraction (WAXD) and thermogravimetric differential thermal analysis (TG-DTA) studies. The tracking time was different for a.c. and d.c. voltages.     

Enzymic and in sacco methods to estimate rumen degradation of food protein in cattle

BACKGROUND: Two factorial studies compared enzymic and in sacco methods to estimate degradation of ruminant foods. Enzyme degradation (in vitro = enzyme) was determined from the release of leucine‐equivalent amino acid (LA) crude protein (CP) from sunflower meal (SF), maize gluten meal (MG), distillers' dark grain (DG) and field beans (FB) after their separate incubations with Streptomyces griseus enzyme for 0–24 h. In sacco crude protein (CP) degradation of these foods was estimated during washing (0 h) and rumen incubations in fistulated cows for 2–24 h. The LA data were expressed as g LA per either kg of CP (LACP) or acid‐hydrolysable LA (HLA) of each food and compared with in sacco data. RESULTS: These methods showed comparable degradation with time (P < 0.01). The in sacco and HLA were greater than LACP for all foods except MG where in sacco value was either lower or equal to LACP depending upon the incubation time (P > 0.05 or P < 0.05). Conversely, HLA was significantly (P < 0.01) greater than LACP from 2 h onwards. At 0 h, in sacco values were significantly greater than those of enzyme for SF, DG and FB (P < 0.05) but not for MG. The foods differed significantly for degradation constants (a, b, c) in each method (P < 0.05). CONCLUSIONS: Despite variations between in sacco and enzyme estimates for different foods, the relationships between these estimates suggest that the HLA enzyme method has the potential to estimate food degradation. Copyright © 2007 Society of Chemical Industry     

ECFGM: enriched control flow graph miner for unknown vicious infected code detection

Vicious codes, especially viruses, as a kind of impressive malware have caused many disasters and continue to exploit more vulnerabilities. These codes are injected inside benign programs in order to abuse their hosts and ease their propagation. The offsets of injected virus codes are unknown and their targets usually are latent until they are executed and activated, what in turn makes viruses very hard to detect. In this paper enriched control flow graph miner, ECFGM in short, is presented to detect infected files corrupted by unknown viruses. ECFGM uses enriched control flow graph model to represent the benign and vicious codes. This model has more information than traditional control flow graph (CFG) by utilizing statistical information of dependent assembly instructions and API calls. To the best of our knowledge, the presented approach in this paper, for the first time, can recognize the offset of infected code of unknown viruses in the victim files. The main contributions of this paper are two folds: first, the presented model is able to detect unknown vicious code using ECFG model with reasonable complexity and desirable accuracy. Second, our approach is resistant against metamorphic viruses which utilize dead code insertion, variable renaming and instruction reordering methods.