A model of non‐isothermal degradation of nutrients,pigments and enzymes

Published isothermal degradation curves for chlorophyll A and thiamine in the range 100–150 °C and the inactivation curves of polyphenol oxidase (PPO) in the range 50–80 °C could be described by the model C(t)/C₀ = exp[?b(T)tⁿ] where C(t) and C₀ are the momentary and initial concentrations, respectively, b(T) a temperature dependent ‘rate parameter’ and n, a constant. This suggested that the temporal degradation/inactivation events of all three had a Weibull distribution with a practically constant shape factor. The temperature dependence of the ‘rate parameter’ could be described by the log logistic model, b(T) = log_e[1 + exp[k(T ? T_c)], where T_c is a marker of the temperature level where the degradation/inactivation occurs at a significant rate and k the steepness of the b(T) increase once this temperature range has been exceeded. These two models were combined to produce a non‐isothermal degradation/inactivation model, similar to one recently developed for microbial inactivation. It is based on the assumption that the local slope of the non‐isothermal decay curve, ie the momentary decay rate, is the slope of the isothermal curve at the momentary temperature at a time that corresponds to the momentary concentration of the still intact or active molecules. This model, in the form of a differential equation, was solved numerically to produce degradation/inactivation curves under temperature profiles that included heating and cooling and oscillating temperatures. Such simulations can be used to assess the impact of planned commercial heat processes on the stability of compounds of nutritional and quality concerns and the efficacy of methods to inactivate enzymes. Simulated decay curves on which a random noise was superimposed were used to demonstrate that the degradation/inactivation parameters, k and T_c, can be calculated directly from non‐isothermal decay curves, provided that the validity of the Weibullian and log logistic models and the constancy of the shape factor n could be assumed. Copyright © 2004 Society of Chemical Industry     

Impact of biodiesel bulk modulus on injection pressure and injection timing. The effect of residual pressure

As the demand for energy rises fossil fuel reserves are depleted daily, increasing the interest in alternative fuels. Biodiesel is one of the best candidates in this class and its use is expected to expand rapidly throughout the world. Numerous researchers have been investigating how biodiesel affects combustion, pollutant formation and exhaust aftertreatment. There is general agreement that its combustion characteristics are similar to those of standard diesel fuel, except for a shorter ignition delay, a higher ignition temperature, and greater ignition pressure and peak heat release. Engine power output is similar with both fuels. As regards emissions, reductions in particulate matter (PM) and carbon monoxide (CO) and increases in nitrogen oxides (NOx) are described with most biodiesel blends. The latter is referred to as the ‘biodiesel NOx effect’. The vast majority of researchers who explored the effect of biodiesel did so in mechanical injection engines. They found that the primary mechanism by which biodiesel increases NOx emissions is by an inadvertent advance in the start of injection timing, caused by a higher modulus and viscosity. However, more recent studies show that NOx emissions also increase in biodiesel-fuelled common rail engines, and that in some cases they actually decrease in engines with mechanically controlled fuel injection systems. This cannot be explained solely by differences in compressibility and remains an open question. The present study provides a contribution to the discussion in this field by describing a new method to evaluate the injection advance in engines with mechanically controlled pumps. The experimental data show that the advances in the start of injection timing, using biodiesel rather than mineral diesel, are smaller than those calculated with standard methods and may even not occur at all, depending on injection system design. In addition, they demonstrate that, contrary to common belief, injection pressure does not always increase when using biodiesel. These data may help explain why some researchers have found similar or even reduced NOx emission also with mechanical injection systems.     

Reliability of RF MEMS switches due to charging effects and their circuital modelling

The reliability of RF MEMS switches is typically reduced by charging effects occurring in the dielectrics. The aim of this paper is to discuss these effects, and to propose analytical and equivalent circuit models which account for most of the physical contributions present in the structure.     

Threshold protocols in survivor set systems

Many replication protocols employ a threshold model when expressing failures they are able to tolerate. In this model, one assumes that no more than t out of n components can fail, which is a good representation when failures are independent and identically distributed (IID). In many real systems, however, failures are not IID, and a straightforward application of threshold protocols yields suboptimal results. Here, we examine the problem of transforming threshold protocols into survivor-set protocols tolerating dependent failures. Our main goal is to show the equivalence between the threshold model and the core/survivor set model. Toward this goal, we develop techniques to transform threshold protocols into survivor set ones. Our techniques do not require authentication, self-verification or encryption. Our results show in one case that we can transform a threshold protocol to a subset by spreading a number of processes across processors. This technique treats a given threshold algorithm as a black box, and consequently can transform any threshold algorithm. However, it has the disadvantage that the transformation is not possible for all sets of survivor sets. The second technique instead focuses on transforming voters: functions that evaluate to a value out of a set of tallied values in a replication protocol. Voters are an essential part of many fault-tolerant protocols, and we show a universal way of transforming them. With such a transformation we expect that a large number of protocols in the literature can be directly transformed with our technique. It is still an open problem, however, if the two models are equivalent, and our results constitute an important first step in this direction.     

Binary integer programming formulations for scheduling in market-driven foundries

This paper describes the development and solution of binary integer formulations for production scheduling problems in market-driven foundries. This industrial sector is comprised of small and mid-sized companies with little or no automation, working with diversified production, involving several different metal alloy specifications in small tailor-made product lots. The characteristics and constraints involved in a typical production environment at these industries challenge the formulation of mathematical programming models that can be computationally solved when considering real applications. However, despite the interest on the part of these industries in counting on effective methods for production scheduling, there are few studies available on the subject. The computational tests prove the robustness and feasibility of proposed models in situations analogous to those found in production scheduling at the analyzed industrial sector.     

A Phenomenological Model of the Peroxide Value’s Rise and Fall During Lipid Oxidation

During isothermal lipid oxidation at relatively high temperatures, the peroxide concentration frequently peaks while at relatively low temperatures it only rises slowly. These are two manifestations of a process where formation and degradation happen simultaneously on different time scales. A phenomenological mathematical model, comprising a decay factor superimposed on an accumulation term can describe these scenarios. Each has a characteristic time constant shortened by raising the temperature and a rate constant that increases with it. The model’s mathematical structure and the magnitude of its coefficients depend on the particular system. However, regardless of the chosen expressions, if the degradation characteristic time falls within or just beyond the experiment’s duration, a peak peroxide value will be observed whose height and shape will primarily depend on the other model’s parameters. If this characteristic time is far outside the time of the experiment , no peak will be recorded. The model need not be unique and no detailed knowledge of the oxidation mechanisms is required for its formulation. Consequently it can be derived directly from experimental peroxide value versus time relationships, without the need to monitor the intermediate reactions by specialized instrumental methods such as DSC. Through the formation term adjustment, the model can also account for the temperature dependent lag in the rise of the peroxide value and/or the appearance of its peak.