An optimal model for representing the kinetics of growth and product formation by Lactobacillus rhamnosus on multiple substrates

A comprehensive model was developed to simulate Lactobacillus rhamnosus growth on a medium containing multiple limiting carbon sources. The strategy of optimizing specific growth rate to predict growth on multiple substrates was demonstrated. The model predictions were based on parameters obtained from L. rhamnosus growth on individual substrates. The model was able to simulate the growth, substrate consumption, product formation and specific growth rate profiles of L. rhamnosus accurately. The model prediction that co-metabolism of glucose and pyruvate enhances growth rate of and flavor production by the bacterium was experimentally verified.     

Parameterized complexity of the induced subgraph problem in directed graphs

In this Letter, we consider the parameterized complexity of the following problem: Given a hereditary property P on digraphs, an input digraph D and a positive integer k, does D have an induced subdigraph on k vertices with property P? We completely characterize hereditary properties for which this induced subgraph problem is W[1]-complete for two classes of directed graphs: general directed graphs and oriented graphs. We also characterize those properties for which the induced subgraph problem is W[1]-complete for general directed graphs but fixed parameter tractable for oriented graphs. These results are among the very few parameterized complexity results on directed graphs.     

Drying and color characteristics of coriander foliage using convective thin-layer and microwave drying

Heat sensitive properties (aromatic, medicinal, color) provide herbs and spices with their high market value. In order to prevent extreme loss of heat sensitive properties when drying herbs, they are normally dried at low temperatures for longer periods of time to preserve these sensory properties. High energy consumption often results from drying herbs over a long period. Coriander (Coriandrum sativum L., Umbelliferae) was dehydrated in two different drying units (thin layer convection and microwave dryers) in order to compare the drying and final product quality (color) characteristics. Microwave drying of the coriander foliage was faster than convective drying. The entire drying process took place in the falling rate period for both microwave and convective dried samples. The drying rate for the microwave dried samples ranged from 42.3 to 48.2% db/min and that of the convective dried samples ranged from 7.1 to 12.5% db/min. The fresh sample color had the lowest L value at 26.83 with higher L values for all dried samples. The results show that convective thin layer dried coriander samples exhibited a significantly greater color change than microwave dried coriander samples. The color change index values for the microwave dried samples ranged from 2.67 to 3.27 and that of the convective dried samples varied from 4.59 to 6.58.     

Multi-stage classifier design

In many classification systems, sensing modalities have different acquisition costs. It is often unnecessary to use every modality to classify a majority of examples. We study a multi-stage system in a prediction time cost reduction setting, where the full data is available for training, but for a test example, measurements in a new modality can be acquired at each stage for an additional cost. We seek decision rules to reduce the average measurement acquisition cost. We formulate an empirical risk minimization problem (ERM) for a multi-stage reject classifier, wherein the stage k classifier either classifies a sample using only the measurements acquired so far or rejects it to the next stage where more attributes can be acquired for a cost. If we restrict ourselves to binary classification setting then, to solve the ERM problem, we show that the optimal reject classifier at each stage is a combination of two binary classifiers, one biased towards positive examples and the other biased towards negative examples. We use this parameterization to construct stage-by-stage global surrogate risk, develop an iterative algorithm in the boosting framework and present convergence and generalization results. We test our work on synthetic, medical and explosives detection datasets. Our results demonstrate that substantial cost reduction without a significant sacrifice in accuracy is achievable.     

Comparing stationary standing with an intermittent walking posture during assembly operations

The purpose of this investigation was to evaluate two different standing postures, intermittent walking (dynamic) and stationary, on 11 volunteers. While performing the activity in a stationary posture, volunteers worked barefoot for 25 minutes at a particular workstation, taking up to five passive breaks. The dynamic standing postural activity was similar in every respect with the exception of the nature of the breaks that were spent walking from one workstation to the other. Foot pressure was analyzed using a static evaluation variable (contact area) and a dynamic evaluation variable (area pressure change root mean square [aPcrms]). Foot center of pressure (COP) was analyzed using two of its features: excursion length (LEN) and root mean square velocity of excursions (VEL). In addition, a psychophysical study was used to distinguish the comfort levels of various muscles between the two postures. The quantifications of the four physiological variables revealed a lower comfort index (p < 0.05) in stationary standing compared to dynamic standing during assembling duties. This significant distinction was further corroborated by the results of the psychophysical test. Such a positive influence of the dynamic standing posture on standing comfort can be used to improve industrial productivity. © 2008 Wiley Periodicals, Inc.     

Gender and age differences in employee decisions about new technology: an extension to the theory of planned behavior

This research extends the theory of planned behavior by incorporating gender and age as moderators of user perceptions and individual adoption and sustained use of technology in the workplace. Individual reactions and technology use behavior were studied over a six-month period among 342 workers being introduced to a new software technology application. While previous studies in the literature have reported gender or age differences separately, the pattern of results from the study reported here indicated that gender effects in individual adoption and use of technology differed based on age. Specifically, gender differences in technology perceptions became more pronounced among older workers, but a unisex pattern of results emerged among younger workers. The theory and empirical results are also discussed in relation to the widely employed technology acceptance model. The results from this study suggest that old stereotypes that portray "technology" as a male-oriented domain may be disappearing; particularly among younger workers. In light of these findings, theoretical implications for researchers and practical suggestions for managers are discussed.     

Linear and logarithmic capacities in associative neural networks

A model of associate memory incorporating global linearity and pointwise nonlinearities in a state space of n-dimensional binary vectors is considered. Attention is focused on the ability to store a prescribed set of state vectors as attractors within the model. Within the framework of such associative nets, a specific strategy for information storage that utilizes the spectrum of a linear operator is considered in some detail. Comparisons are made between this spectral strategy and a prior scheme that utilizes the sum of Kronecker outer products of the prescribed set of state vectors, which are to function nominally as memories. The storage capacity of the spectral strategy is linear in n (the dimension of the state space under consideration), whereas an asymptotic result of n/4 log n holds for the storage capacity of the outer product scheme. Computer-simulated results show that the spectral strategy stores information more efficiently. The preprocessing costs incurred in the two algorithms are estimated, and recursive strategies are developed for their computation     

Selecting Agricultural Best Management Practices for Water Conservation and Quality Improvements Using Atanassov’s Intuitionistic Fuzzy Sets

Improper agricultural practices can affect ground water through leaching, surface water through runoff, algae infestations, deforestation, and air quality through burning operations and ammonia emissions. These effects may be mitigated through the institution of best management practices. The utility of best management practices (BMPs) is recognized and being actively promoted by agricultural agencies; however, identifying a set of mandatory BMPs is inappropriate given variations between climactic, demographic and geographic regions as well as differences in farming practices. In this study, a multi-criteria decision making model based on Attanassov’s Intuitionistic Fuzzy Set (A-IFS) theory is introduced and its utility to rank agricultural best management practices is illustrated using a case-study from South Texas. Implementation of the A-IFS MCDM method to the South Texas region resulted in “irrigation scheduling” being ranked as the most preferred alternative, while “brush control/management” was the least preferred. The A-IFS MCDM approach was particularly suitable for prioritizing and ranking agricultural best management practices because decision makers often tend to have both likes and dislikes with regards to specific BMPs and for a given evaluation attribute. Not only does the A-IFS MCDM method provide a single composite score to rank the BMP alternatives, but the output of the A-IFS MCDM method also includes upper and lower bounds that help identify the uncertainties in the decision making process.