Theoretical and experimental approaches towards the determination of solute effective diffusivities in foods

The aim of this review paper is to present experimental methodologies and the mathematical approaches used to determine effective diffusivities of solutes in food materials. The paper commences by describing the diffusion phenomena related to solute mass transfer in foods and effective diffusivities. It then focuses on the mathematical formulation for the calculation of effective diffusivities considering different diffusion models based on Fick's second law of diffusion. Finally, experimental considerations for effective diffusivity determination are elucidated primarily based on the acquirement of a series of solute content versus time curves appropriate to the equation model chosen. Different factors contributing to the determination of the effective diffusivities such as the structure of food material, temperature, diffusion solvent, agitation, sampling, concentration and different techniques used are considered. (c) 2005 Elsevier Inc. All rights reserved.

Ligand dynamics in myoglobin: calculation of infrared spectra for photodissociated NO

We present molecular dynamics simulations of the photodissociated state of MbNO performed at 300 K using a fluctuating charge model for the nitric oxide (NO) ligand. After dissociation, NO is observed to remain mainly in the centre of the distal haem pocket, although some movement towards the primary docking site and the xenon-4 pocket can be seen. We calculate the NO infrared spectrum for the photodissociated ligand within the haem pocket and find a narrow peak in the range 1915-1922 cm(-1). The resulting blue shift of 1 to 8 cm(-1) compared to gas-phase NO is much smaller than the red shifts calculated and observed for carbon monoxide (CO) in Mb. A small splitting, due to NO in the xenon-4 pocket, is also observed. At lower temperatures, the spectra and conformational space explored by the ligand remain largely unchanged, but the electrostatic interactions with residue His64 become increasingly significant in determining the details of the ligand orientation within the distal haem pocket. The investigation of the effect of the L29F mutation reveals significant differences between the behaviour of NO and that of CO, and suggests a coupling between the ligand and the protein dynamics due to the different ligand dipole moments.

Analysis of disputed single-parent/child and sibling relationships using 16 STR loci

This study describes the validation of short tandem repeat (STR) systems for the resolution of cases of disputed parentage where only a single parent is available for testing or where the claimed relationship of both parents is in doubt and also cases where sibship must be tested. Three separate multiplex systems the Second Generation Multiplex, Powerplex 1.2 and FFFL have been employed, giving a total of 16 STR loci. Both empirical and theoretical approaches to the validation have been adopted. Appropriate equations have been derived to calculate likelihood ratios for different relationships, incorporating a correction for subpopulation effects. An F(ST) point estimate of 1% has been applied throughout. Empirically, 101 cases of alleged father, alleged mother and child where analysed using six SLP systems and also using the three multiplex STR systems. Of the 202 relationships tested, 197 were independently resolved by both systems, providing either clear evidence of non-parentage or strong support for the relationship.

Automatic X-ray screening of aircraft hold luggage

R. Benjamin (1995) addressed the application of the “object 3D” X ray reconstruction technique for electronically “unpacking” suspect items, when screening aircraft luggage. However, there is no satisfactory solution to the mass screening of hold luggage. Computed Tomography, CT, entails excessive radiation dosages, and its rate of throughput is quite inadequate. A novel variant of “object 3D” is therefore put forward, adapting some of the technology of existing cabin luggage screening systems-but on a substantially larger scale-which does achieve the required throughput at an acceptable radiation dosage and cost.

Variable selection for financial distress classification using a genetic algorithm

This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature.

Physics-based modelling for remote sensing of snow

Remote sensing is the only practicable means to observe snow at large scales. Measurements from passive microwave instruments have been used to derive snow climatology since the late 1970’s, but the algorithms used were limited by the computational power of the era. Simplifications such as the assumption of constant snow properties enabled snow mass to be retrieved from the microwave measurements, but large errors arise from those assumptions, which are still used today. A better approach is to perform retrievals within a data assimilation framework, where a physically-based model of the snow properties can be used to produce the best estimate of the snow cover, in conjunction with multi-sensor observations such as the grain size, surface temperature, and microwave radiation. We have developed an existing snow model, SNOBAL, to incorporate mass and energy transfer of the soil, and to simulate the growth of the snow grains. An evaluation of this model is presented and techniques for the development of new retrieval systems are discussed.

A three-regime model of speculative behaviour: modelling the evolution of the S&P 500 composite index

We examine whether a three-regime model that allows for dormant, explosive and collapsing speculative behaviour can explain the dynamics of the S&P 500. We extend existing models of speculative behaviour by including a third regime that allows a bubble to grow at a steady rate, and propose abnormal volume as an indicator of the probable time of bubble collapse. We also examine the financial usefulness of the three-regime model by studying a trading rule formed using inferences from it, whose use leads to higher Sharpe ratios and end of period wealth than from employing existing models or a buy-and-hold strategy.

Validation of the FALL3D ash dispersion model using observations of the 2010 Eyjafjallajökull volcanic ash clouds

During April-May 2010 volcanic ash clouds from the Icelandic Eyjafjallajökull volcano reached Europe causing an unprecedented disruption of the EUR/NAT region airspace. Civil aviation authorities banned all flight operations because of the threat posed by volcanic ash to modern turbine aircraft. New quantitative airborne ash mass concentration thresholds, still under discussion, were adopted for discerning regions contaminated by ash. This has implications for ash dispersal models routinely used to forecast the evolution of ash clouds. In this new context, quantitative model validation and assessment of the accuracies of current state-of-the-art models is of paramount importance. The passage of volcanic ash clouds over central Europe, a territory hosting a dense network of meteorological and air quality observatories, generated a quantity of observations unusual for volcanic clouds. From the ground, the cloud was observed by aerosol lidars, lidar ceilometers, sun photometers, other remote-sensing instru- ments and in-situ collectors. From the air, sondes and multiple aircraft measurements also took extremely valuable in-situ and remote-sensing measurements. These measurements constitute an excellent database for model validation. Here we validate the FALL3D ash dispersal model by comparing model results with ground and airplane-based measurements obtained during the initial 14e23 April 2010 Eyjafjallajökull explosive phase. We run the model at high spatial resolution using as input hourly- averaged observed heights of the eruption column and the total grain size distribution reconstructed from field observations. Model results are then compared against remote ground-based and in-situ aircraft-based measurements, including lidar ceilometers from the German Meteorological Service, aerosol lidars and sun photometers from EARLINET and AERONET networks, and flight missions of the German DLR Falcon aircraft. We find good quantitative agreement, with an error similar to the spread in the observations (however depending on the method used to estimate mass eruption rate) for both airborne and ground mass concentration. Such verification results help us understand and constrain the accuracy and reliability of ash transport models and it is of enormous relevance for designing future operational mitigation strategies at Volcanic Ash Advisory Centers.

High resolution Northern Hemisphere wintertime mid-latitude dynamics during the Last Glacial Maximum

Hourly winter weather of the Last Glacial Maximum (LGM) is simulated using the Community Climate Model version 3 (CCM3) on a globally resolved T170 (75 km) grid. Results are compared to a longer LGM climatological run with the same boundary conditions and monthly saves. Hourly-scale animations are used to enhance interpretations. The purpose of the study is to explore whether additional insights into ice age conditions can be gleaned by going beyond the standard employment of monthly average model statistics to infer ice age weather and climate. Results for both LGM runs indicate a decrease in North Atlantic and increase in North Pacific cyclogenesis. Storm trajectories react to the mechanical forcing of the Laurentide Ice Sheet, with Pacific storms tracking over middle Alaska and northern Canada, terminating in the Labrador Sea. This result is coincident with other model results in also showing a significant reduction in Greenland wintertime precipitation – a response supported by ice core evidence. Higher-temporal resolution puts in sharper focus the close tracking of Pacific storms along the west coast of North America. This response is consistent with increased poleward heat transport in the LGM climatological run and could help explain “early” glacial warming inferred in this region from proxy climate records. Additional analyses shows a large increase in central Asian surface gustiness that support observational inferences that upper-level winds associated with Asian- Pacific storms transported Asian dust to Greenland during the LGM.

Volume-based size distribution of accumulation and coarse particles (PM0.1–10) from cooking fume during oil heating

Particulate matter generated during the cooking process has been identified as one of the major problems of indoor air quality and indoor environmental health. Reliable assessment of exposure to cooking-generated particles requires accurate information of emission characteristics especially the size distribution. This study characterizes the volume/mass-based size distribution of the fume particles at the oil-heating stage for the typical Chinese-style cooking in a laboratory kitchen. A laser-diffraction size analyzer is applied to measure the volume frequency of fume particles ranged from 0.1 to 10 μm, which contribute to most mass proportion in PM2.5 and PM10. Measurements show that particle emissions have little dependence on the types of vegetable oil used but have a close relationship with the heating temperature. It is found that volume frequency of fume particles in the range of 1.0–4.0 μm accounts for nearly 100% of PM0.1–10 with the mode diameter 2.7 μm, median diameter 2.6 μm, Sauter mean diameter 3.0 μm, DeBroukere mean diameter 3.2 μm, and distribution span 0.48. Such information on emission characteristics obtained in this study can be possibly used to improve the assessment of indoor air quality due to PM0.1–10 in the kitchen and residential flat.

The maximum rate of mammal evolution

How fast can a mammal evolve from the size of a mouse to the size of an elephant? Achieving such a large transformation calls for major biological reorganization. Thus, the speed at which this occurs has important implications for extensive faunal changes, including adaptive radiations and recovery from mass extinctions. To quantify the pace of large-scale evolution we developed a metric, clade maximum rate, which represents the maximum evolutionary rate of a trait within a clade. We applied this metric to body mass evolution in mammals over the last 70 million years, during which multiple large evolutionary transitions occurred in oceans and on continents and islands. Our computations suggest that it took a minimum of 1.6, 5.1, and 10 million generations for terrestrial mammal mass to increase 100-, and 1,000-, and 5,000- fold, respectively. Values for whales were down to half the length (i.e., 1.1, 3, and 5 million generations), perhaps due to the reduced mechanical constraints of living in an aquatic environment. When differences in generation time are considered, we find an exponential increase in maximum mammal body mass during the 35 million years following the Cretaceous–Paleogene (K–Pg) extinction event. Our results also indicate a basic asymmetry in macroevolution: very large decreases (such as extreme insular dwarfism) can happen at more than 10 times the rate of increases. Our findings allow more rigorous comparisons of microevolutionary and macroevolutionary patterns and processes. Keywords: haldanes, biological time, scaling, pedomorphosis

Changes of the equilibrium line altitude since the Little Ice Age in the Nepalese Himalayas

Changes of the equilibrium-line altitude (ELA) since the end of the Little Ice Age (LIA) in eastern Nepal have been studied using glacier inventory data. The toe-to-headwall altitude ratios (THARs) for individual glaciers were calculated for 1992, and used to estimate the ELA in 1959 and at the end of the LIA. THAR for debris-free glaciers is found to be smaller than for debris-covered glaciers. The ELAs for debris-covered glaciers are higher than those for debris-free glaciers in eastern Nepal. There is considerable variation in the reconstructed change in ELA (ΔELA) between glaciers within specific regions and between regions. This is not related to climate gradients, but results from differences in glacier aspect: southeast- and south-facing glaciers show larger ΔELAs in eastern Nepal than north- or west-facing glaciers. The data suggest that the rate of ELA rise may have accelerated in the last few decades. The limited number of climate records from Nepal, and analyses using a simple ELA–climate model, suggest that the higher rate of the ΔELA between 1959 and 1992 is a result of increased warming that occurred after the 1970s at higher altitudes in Nepal.

Symmorphosis through dietary regulation: a combinatorial role for proteolysis, autophagy and protein synthesis in normalising muscle metabolism and function of hypertrophic mice after acute starvation

Animals are imbued with adaptive mechanisms spanning from the tissue/organ to the cellular scale which insure that processes of homeostasis are preserved in the landscape of size change. However we and others have postulated that the degree of adaptation is limited and that once outside the normal levels of size fluctuations, cells and tissues function in an aberant manner. In this study we examine the function of muscle in the myostatin null mouse which is an excellent model for hypertrophy beyond levels of normal growth and consequeces of acute starvation to restore mass. We show that muscle growth is sustained through protein synthesis driven by Serum/Glucocorticoid Kinase 1 (SGK1) rather than Akt1. Furthermore our metabonomic profiling of hypertrophic muscle shows that carbon from nutrient sources is being channelled for the production of biomass rather than ATP production. However the muscle displays elevated levels of autophagy and decreased levels of muscle tension. We demonstrate the myostatin null muscle is acutely sensitive to changes in diet and activates both the proteolytic and autophagy programmes and shutting down protein synthesis more extensively than is the case for wild-types. Poignantly we show that acute starvation which is detrimental to wild-type animals is beneficial in terms of metabolism and muscle function in the myostatin null mice by normalising tension production.

A laboratory incubation method for determining the rate of microbiological degradation of skeletal muscle tissue in soil

A controlled laboratory experiment is described, in principle and practice, which can be used for the of determination the rate of tissue decomposition in soil. By way of example, an experiment was conducted to determine the effect of temperature (12°C, 22°C) on the aerobic decomposition of skeletal muscle tissue (Organic Texel × Suffolk lamb (Ovis aries)) in a sandy loam soil. Measurements of decomposition processes included muscle tissue mass loss, microbial CO2 respiration, and muscle tissue carbon (C) and nitrogen (N). Muscle tissue mass loss at 22°C always was greater than at 12°C (p < 0.001). Microbial respiration was greater in samples incubated at 22°C for the initial 21 days of burial (p < 0.01). All buried muscle tissue samples demonstrated changes in C and N content at the end of the experiment. A significant correlation (p < 0.001) was demonstrated between the loss of muscle tissue-derived C (C1) and microbially-respired C (Cm) demonstrating CO2 respiration may be used to predict mass loss and hence biodegradation. In this experiment Q10 (12°C - 22°C) = 2.0. This method is recommended as a useful tool in determining the effect of environmental variables on the rate of decomposition of various tissues and associated materials.

Multiprobabilistic prediction in early medical diagnoses

This paper describes the methodology of providing multiprobability predictions for proteomic mass spectrometry data. The methodology is based on a newly developed machine learning framework called Venn machines. Is allows to output a valid probability interval. The methodology is designed for mass spectrometry data. For demonstrative purposes, we applied this methodology to MALDI-TOF data sets in order to predict the diagnosis of heart disease and early diagnoses of ovarian cancer and breast cancer. The experiments showed that probability intervals are narrow, that is, the output of the multiprobability predictor is similar to a single probability distribution. In addition, probability intervals produced for heart disease and ovarian cancer data were more accurate than the output of corresponding probability predictor. When Venn machines were forced to make point predictions, the accuracy of such predictions is for the most data better than the accuracy of the underlying algorithm that outputs single probability distribution of a label. Application of this methodology to MALDI-TOF data sets empirically demonstrates the validity. The accuracy of the proposed method on ovarian cancer data rises from 66.7 % 11 months in advance of the moment of diagnosis to up to 90.2 % at the moment of diagnosis. The same approach has been applied to heart disease data without time dependency, although the achieved accuracy was not as high (up to 69.9 %). The methodology allowed us to confirm mass spectrometry peaks previously identified as carrying statistically significant information for discrimination between controls and cases.