Effect of diethyl ether blended with neem oil methyl esters in CI engine

Vegetable oils are now considered to be a potential alternative that can be used in place of partial or total substitution of diesel fuels. In this study, we used diethyl ether as an oxygenated additive to investigate the possible use of higher percentages of biodiesel in an unmodified diesel engine. Neem oil was selected for biodiesel production. The tests were performed at a steady-state condition in a single-cylinder constant speed DI diesel engine. The combustion process involved in diesel engine would be improved and the particulate matter would be reduced if these biodiesels are blended. An experimental investigation is carried out to establish the emission characteristics of a direct injection diesel engine using diethyl ether as additive in Neat Neem oil Biodiesel. Emissions of hydro carbon oxides of nitrogen and carbon monoxide significantly reduced by adding diethyl ether into neem oil biodiesel at 10% and 20% on volume basis.     

Investigation on mining subsidence over Appin–West Cliff Colliery using time-series SAR interferometry

Advanced Time Series InSAR (ATS-InSAR) generally refers to those TS-InSAR methods with an external distributed scatterer selection module, e.g. SqueeSAR?, and GEOS-ATSA (Advanced Time-Series Analysis). It is being known as a very efficient tool for monitoring ground deformation over suburban or non-urban regions with great success. However, research conducted using C-band Envisat-based ATS-InSAR failed to produce reasonable outcome within Appin Colliery primarily due to the underground mining effect, which is located in the southeastern corner of the Southern Coalfield, New South Wales, Australia; thus, the general underground mining pattern cannot be formed. This work presents a modified ATS-InSAR method for mapping the ground deformation over underground mining region. More specifically, in order to achieve the best outcome, a modified measurement scatterer (MS) pixel selection method is introduced by including less reliable MS pixels through an Inverse Distance Weighted-based integration method. In addition, the proposed method is also applied to C-band Sentinel-1 image stacks for testing purpose, and the final result proved to be efficient to offer sufficient information to the mining industry and government for risk management purpose.     

Predictive Thermal Inactivation Model for Effects and Interactions of Temperature, NaCl, Sodium Pyrophosphate, and Sodium Lactate on Listeria monocytogenes in Ground Beef

The effects and interactions of heating temperature (60 °C to 73.9 °C), salt (0.0 % to 4.5 %?w/v), sodium pyrophosphate (0.0 % to 0.5 %?w/v), and sodium lactate (0.0 % to 4.5 %?w/v) on the heat resistance of a five-strain mixture of Listeria monocytogenes in 75 % lean ground beef were examined. Meat samples in sterile filtered stomacher bags were heated in a temperature controlled waterbath to determine thermal death times. The recovery medium was tryptic soy agar supplemented with 0.6 % yeast extract and 1 % sodium pyruvate. Weibull survival functions were employed to model the primary survival curves. Then, survival curve-specific estimated parameter values obtained from the Weibull model were used for determining a secondary model. The results indicate that temperature and salt have a large impact on the inactivation kinetics of L. monocytogenes, while sodium lactate (NaL) has an impact in the presence of salt. The model presented in this paper for predicting inactivation of L. monocytogenes can be used as an aid in designing lethality treatments meant to control the presence of this pathogen in ready-to-eat products.     

Coarse-grained modeling of model poly(urethane urea)s: Microstructure and interface aspects

Poly(urethane urea) elastomers are versatile and can be tailored to exhibit a broad range of mechanical response under high strain rate deformation. In this work, we utilize coarse-grained molecular dynamics simulations to elucidate the molecular mechanisms, particularly the effects of hard segment content, intermolecular interaction, and rigidity of the interface between the hard and soft segments on local morphology and rate-dependent stress-strain behavior in the ballistic regime. Simulation results qualitatively agree with available experimental data, where analysis of hard segment orientation during tensile and compression deformation and dynamic strain rate sensitivity was also performed. Further study of the intermolecular interaction on the stress-strain behavior reveals that it has a strong effect on strain hardening, particularly for a rigid interface, once the hard segment content reaches the percolation threshold. Simulation results also show that interface intermolecular interaction could become more dominant over interface rigidity in the initial stress-strain response, particularly below percolation.     

Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis

Caenorhabditis elegans vulval development is a paradigm system for understanding cell differentiation in the process of organogenesis. Through temporal and spatial controls, the fate pattern of six cells is determined by the competition of the LET-23 and the Notch signalling pathways. Modelling cell fate determination in vulval development using state-based models, coupled with formal analysis techniques, has been established as a powerful approach in predicting the outcome of combinations of mutations. However, computing the outcomes of complex and highly concurrent models can become prohibitive. Here, we show how logic programs derived from state machines describing the differentiation of C. elegans vulval precursor cells can increase the speed of prediction by four orders of magnitude relative to previous approaches. Moreover, this increase in speed allows us to infer, or ‘retrodict’, compatible genomes from cell fate patterns. We exploit this technique to predict highly variable cell fate patterns resulting from dig-1 reduced-function mutations and let-23 mosaics. In addition to the new insights offered, we propose our technique as a platform for aiding the design and analysis of experimental data.     

CoopStor: a cooperative reliable and efficient data collection protocol in fault and delay tolerant wireless networks

Wireless Networks - Internet of things consist in the deployment of constrained and battery-powered devices with a radio interface. Most industrial applications require to respect strict...     

Simulation-based conjoint ranking for optimal decision support process under aleatory uncertainty

Design chain management requires many decision makers throughout the product development process. It is critical to reduce complexity and uncertainty of the design process by correctly modeling subjective data associated with decision makers’ preferences. This paper aims at using decision support to find optimal designs by modeling respondent preferences and trade-offs with consideration of uncertainty. Specifically, a simulation-based ranking methodology is implemented and incorporated with traditional conjoint analysis. This process facilitates a schematic decision support process by alleviating user fatigue. In addition, incorporation of uncertainty in the ranking process provides the capability of producing robust and reliable products. The efficacy and applicability of simulation-based conjoint ranking is demonstrated with a case study of a power-generating shock absorber design.     

Focused SWOT: diagnosing critical strengths and weaknesses

Despite the problems involved in its use, SWOT (strengths-weaknesses-opportunities-threats) analysis remains a major strategic tool for listing the strengths and weaknesses of an organisation, for recording the major strengths and translating them into value. This paper presents a straightforward methodology for making a structured analysis of strengths and weaknesses, based on an analysis of important value-creating events and the strengths and weaknesses that caused these events. The focused SWOT methodology distils the strengths and weaknesses into core competences and core problems, by using the core-competence tree and the current-reality tree. The core competences and core problems are then linked into a plan of action aimed at preserving and leveraging the organisation's core competences, while defending against exposure to core problems. Applications of the methodology are presented and it is demonstrated in a detailed case study.