Full chain energy analysis of fuel ethanol from cassava in Thailand

An assessment of net energy and supply potentials was performed to evaluate cassava utilization for fuel ethanol in Thailand. Just recently, the Thai government approved the construction of 12 cassava ethanol plants with the total output of 3.4 million liters per day by the next 2 years (2007 and 2008). The cassava fuel ethanol (CFE) system involves three main segments: cassava cultivation including processing, ethanol conversion, and transportation. All materials, fuels, and human labor inputs to each segment were traced back to the primary energy expense level. Positive Net Energy Value and Net Renewable Energy Value, 8.80 MJ/L and 9.15 MJ/L, respectively, found for the CFE system in Thailand proved that it is energy efficient. Without coproduct energy credits, CFE in Thailand is even more efficient than CFE in China and corn ethanol in the United States. Regarding supply potentials, about 35% of the national cassava production would be used to feed approved CFE factories. A shift of cassava to ethanol fuel rather than its current use for chip/pellet products could be a probable solution.     

Thermoplastic Starch–PVA Nanocomposite Films Reinforced with Nanocellulose from Oil Palm Empty Fruit Bunches (OPEFBs): Effect of Starch Type

ABSTRACT

This research studied the effect of three types of starch on the properties of thermoplastic starch (TPS)–Poly (vinyl alcohol) (PVA)–cellulose nanocomposite films. Three different types of starch with amylose and amylopectin contents used were corn starch, cassava starch, and sago starch. Meanwhile, the nanocellulose was isolated from oil palm empty fruit bunches (OPEFBs) by mechanical treatment using ultrafine grinder. The nanocomposite films were made by evaporation casting method. It was found that the difference of amylose content in the native starch affected the properties of nanocomposite films. Meanwhile, the nanocellulose added into matrix TPS–PVA could increase tensile strength of TPS–PVA nanocomposite films.     

Flavonoid content and antioxidant activity of vegetables from Indonesia

Extracts from 11 vegetables of Indonesian origin were screened for flavonoid content, total phenolics, and antioxidant activity. The flavonols myricetin, quercetin, and kaempferol and flavones luteolin and apigenin were quantified by HPLC. Flavonoid content in mg/100 g fresh weight (fw) was apparently initially reported for Cosmos caudatus H.B.K. (52.19), Polyscias pinnata (52.19), Pluchea indica Less. (6.39), Nothopanax scutellarius (Burm.f.) Merr (5.43), Talinum triangulare (Jacq.) Willd. (3.93), Pilea melastomoides (Poir.) Bl. (2.27), and Etlingera elatior (Jack) R.M.Sm (1.18). The flavonoid content of the vegetables studied were mainly quercetin and kaempferol and ranged from 0.3 to 143 mg/100 g fw, with the highest level found in Sauropus androgynus (L) Merr. C. caudatus H.B.K. had the greatest total phenols among the vegetables analysed, with 1.52 mg GAE/100 g fw. P. indica Less. and C. caudatus H.B.K. had the highest antioxidant activity as measured by ferric cyanide reducing power, DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2′-azino-bis-(3-ethylbenzthiazoline-6-sulphonic acid) scavenging, and inhibition of linoleic acid oxidation. Therefore, S. androgynus (L) Merr, C. caudatus H.B.K., and P. pinnata were identified as potentially rich sources of dietary flavonoids and antioxidants.     

Static hazard elimination for a logical circuit using quantum dot cellular automata

Microsystem Technologies - Quantum dot cellular automata (QCA) is an upcoming nano-technology for its high speed and low power operation in the field of nano-science and nano-electronics. As QCA...     

Formulation-optimization of solid lipid nanocarrier system of STAT3 inhibitor to improve its activity in triple negative breast cancer cells

In the present study, solid lipid nanoparticles (SLNs) have been formulated as a carrier system for effective intracellular delivery of STAT3 inhibitor, niclosamide (Niclo) to triple negative breast cancer (TNBC) cells. Emulsification-solvent evaporation method was employed in formulation of Niclo-loaded SLNs (Niclo-SLNs). The formula of Niclo-SLN was optimized by Box–Behnken design and characterized for their shape, size, and surface charge. The in vitro anti-cancer efficacy of Niclo-SLNs was studied in TNBC cells. The prepared Niclo-SLNs were found to be spherical with the particle size of 112.18?±?1.73?nm and zetapotential of 23.8?±?2.7?mV. In the in vitro anticancer study the Niclo SLNs show a better cytotoxicity than the naïve Niclo, which is attributed to improved cell uptake of SLN formulation. In conclusion, the results of the present study demonstrate that the formulation of Niclo as SLNs will improve the anticancer efficacy against TNBC.     

Direct synthesis of highly crystalline single-phase hexagonal tungsten oxide nanorods by spray pyrolysis

The metastable state hexagonal-tungsten oxide (h-WO₃) has been attracting attention over the past decade because of its high reactivity that arises from the hexagonal channels in its crystal structure. Simplification of the process used to synthesize h-WO₃ is an important step to facilitate the industrial applications of this material. In this study, we addressed this challenge by developing a spray pyrolysis process to synthesize highly crystalline h-WO₃. The ratio of the monoclinic to the hexagonal phase was controlled by adjusting the segregation time. Single-phase h-WO₃ nanorods were synthesized using a carrier gas flow rate of 1?L/min, which was equivalent to a segregation time of 18.4?s. The ability of the h-WO₃ nanorods to adsorb nitrogen and carbon dioxide was evaluated to confirm the presence of hexagonal channels in the crystal structure.     

Pellet—clad bonding during PCMI

Pellet—clad mechanical interaction adjacent to the mouths of radial cracks in the pellet can lead to local clad strain intensification. in particular, if during operation bonding has occurred between the pellet and the clad, preventing relative azimuthal motion, very high strains would result and many clad failures would be expected. These are however not observed. We present here the results of a detailed analysis of the stress field in the region of the mouth of the pellet crack. These show there to be very high radial tensile stresses, not previously predicted, acting on the bond. Such stresses provide a highly plausible mechanism for the failure of the bond. These will permit the strain associated with the opening of pellet cracks during power ramps to be distributed over a relatively large arc of the cladding, and thus explain the low failure rate observed.     

Mycotoxin Detection Plays “Cops and Robbers”: Cyclodextrin Chemosensors as Specialized Police?

As in a cops and robbers play we discover new mycotoxins and metabolites everyday and we are forced to develop new molecules quickly as chemo- or biosensors or to modify existing molecules able to recognize these new hazardous compounds. This will result in an enormous cost saving to agro-food industry through the prevention and reduction of product recalls and reduced treatment costs. Here we present a brief review of the rapid methods used to detect mycotoxins, considering usefulness and limits. Then we propose a new fast, efficient and cheap methodology, based on a combination of computer chemistry aided design and fluorescence, that can help to drive synthesis in a more efficient way.     

Autonomous diagnostics and prognostics in machining processes through competitive learning-driven HMM-based clustering

A prerequisite to widespread deployment of condition-based maintenance (CBM) systems in industry is autonomous yet effective diagnostics and prognostics algorithms. The concept of ‘autonomy’ in the context of diagnostics and prognostics is usually based on unsupervised clustering techniques. This paper employs an unsupervised competitive learning algorithm to perform hidden Markov model (HMM) based clustering of multivariate temporal observation sequences derived from sensor signal(s). This method improves autonomy of the diagnostic engine over the more traditional classifier based diagnostics models. Classifier models, such as the model presented by Baruah and Chinnam [Baruah, P. and Chinnam, R.B., 2005. HMM for diagnostics and prognostics in machining processes. International Journal of Production Research, 43 (6), 1275–1293] employ ‘labelled’ feature vectors for supervised model building and subsequent health-state classification during condition monitoring. Improving the autonomy of the diagnostics model also improves the autonomy of the prognostics module that often builds upon information extracted through the diagnostics module. We have validated the proposed methods on a physical test-bed that involved monitoring drill-bits on a CNC machine outfitted with thrust-force and torque sensors. Experimental results demonstrate the ability of this method to estimate on-line the remaining-useful-life of a drill-bit with significant accuracy.