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Background: People with metabolically healthy (MHO) and metabolically unhealthy obesity (MUO) differ for the presence or absence of cardio-metabolic complications, respectively. Objective: Based on these differences, we are interested in deepening whether these obesity phenotypes could be linked to changes in microbiota and metabolome profiles. In this respect, the overt role of microbiota taxa composition and relative metabolic profiles is not completely understood. At this aim, biochemical and nutritional parameters, fecal microbiota, metabolome and SCFA compositions were inspected in patients with MHO and MUO under a restrictive diet regimen with a daily intake ranging from 800 to 1200 kcal. Methods: Blood, fecal samples and food questionnaires were collected from healthy controls (HC), and an obese cohort composed of both MHO and MUO patients. Most impacting biochemical/anthropometric variables from an a priori sample stratification were detected by applying a robust statistics approach useful in lowering the background noise. Bacterial taxa and volatile metabolites were assessed by qPCR and gas chromatography coupled with mass spectrometry, respectively. A targeted GC–MS analyses on SCFAs was also performed. Results: Instructed to follow a controlled and restricted daily calorie intake, MHO and MUO patients showed differences in metabolic, gut microbial and volatilome signatures. Our data revealed higher quantities of specific pro-inflammatory taxa (i.e., Desulfovibrioand Prevotellagenera) and lower quantities of Clostridium coccoides groupin MUO subset. Higher abundances in alkane, ketone, aldehyde, and indole VOC classes together with a lower amount of butanoic acid marked the faecal MUO metabolome. Conclusions: Compared to MHO, MUO subset symptom picture is featured by specific differences in gut pro-inflammatory taxa and metabolites that could have a role in the progression to metabolically unhealthy status and developing of obesity-related cardiometabolic diseases. The approach is suitable to better explain the crosstalk existing among dysmetabolism-related inflammation, nutrient intake, lifestyle, and gut dysbiosis.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.cie.2010.08.019 Byline: E. Trovato (a), P. Castagliola (b), G. Celano (c), S. Fichera (c) Keywords: Short production run; Process dispersion; Statistical process control; Control charts; Cost minimization Abstract: Short-run productions are common in industrial environments where flexibility is required in the manufacturing of parts and several product variants can be produced. Monitoring process stability during the production run is strategic to avoid the occurrence of an excessive number of non conforming units which can lead to excessive scrap or rework costs. The selection of the best control strategy can be obtained with respect to an economic objective by minimizing the cost associated with the implementation strategy. In this paper, several strategies including preventive maintenance, Shewhart, EWMA and CUSUM control charts are compared to monitor process dispersion. Constraints related to the line productivity and the inspection activities configuration have been included in the problem formulation. A proper optimization algorithm has been developed to cope with the investigated problem. A large benchmark of process scenarios has been investigated and the obtained results show that the selection of the best strategy is not a straightforward task due to the influence of several process operating parameters. Finally, a numerical example is detailed to get more insight about the investigated problem. Author Affiliation: (a) Ecole des Mines de Nantes, Nantes, France (b) Universite de Nantes & IRCCyN UMR CNRS 6597, Nantes, France (c) Dipartimento di Ingegneria Industriale e Meccanica, Universita di Catania, Catania, Italy Article History: Received 24 November 2009; Revised 28 July 2010; Accepted 30 August 2010 Article Note: (footnote) [star] This manuscript was processed by Area Editor E.A. Elsayed.

In this paper a multi-objective genetic algorithm for the scheduling of a mixed model assembly line is proposed, pursuing the line stop time minimisation together with the component usage smoothing. Specific features of the developed GA are step by step random selection of diversified crossover and mutation operators, population control for the substitution of duplicate chromosomes, and in-process updating of GA control parameters. Three different formulation of the fitness function were been tested with some distinct line configurations. KEY WORDS Mixed Model Assembly Lines, Multi-Objective scheduling, Genetic Algorithm.

Byline: P. Castagliola, G. Celano, S. Fichera, F. Giuffrida This paper proposes a Variable Sampling Interval version of the Fixed Sampling Interval S2-EWMA control chart developed by Castagliola (2004) and dedicated to the monitoring of the sample variance of a process. In this paper, we explain how the various parameters of this VSI S2-EWMA control chart can be computed and how the use of the VSI feature significantly improves the statistical efficiency of FSI S2-EWMA chart, thus representing an effective tool in the detection of process out-of-control conditions. An optimal design strategy based on the Average Time to Signal (ATS) is presented and a comparison with the FSI procedure is performed.

AbstractIn this paper, a new phase II EWMA-type chart for count data, based on the sign statistic, is proposed and applied to the monitoring of the location of an unknown continuous distribution. The most valuable characteristics of this new chart are that: a) it only uses positive integer-valued weights to account for the past process history, b) the plotted statistic is always an integer, and c) its run length properties can be exactlyobtained without resorting to expensive simulations or unreliable approximations. We provide the methodology to compute the exact run length properties of the proposed chart and the algorithms to obtain the optimal chart parameters through the minimization of the out-of-control average run length. We also compare the statistical performance of this new EWMA-type sign chart vs. two classical continuous type EWMA sign charts, a CUSUM-type sign chart and a GWMA-type sign chart. The computational evaluations show that the proposed EWMA control chart outperforms the other control charts for a wide range of location shifts. Finally, two examples implementing this new EWMA type sign chart are given.

Lettuce and tomato seeds were treated in Petri dishes with a humic acid derived from an oxidized coal and with fractions of the same humic acid obtained by ultrafiltration through membranes of known molecular cutoff and by extracting with buffers set at pH 4 and pH 5. The unfractionated humic acid was applied at 40, 100, 1000, and 5000 mg l-1 whereas the humic fractions were applied at 40, 100, and 200 mg l-1. Germination parameters such as the number of total germinated seeds, the velocity of seed germination, the fresh weight and dry weight of total seedlings were measured and related to the chemical and physicochemical properties of the humic material. No increase in the germination percentage or the germination rate was observed for either lettuce or tomato seeds. The fresh weight of total seedlings and per seedling increased in treatments with unfractionated humic acid with increasing concentrations for both lettuce and tomato plants without showing signs of growth inhibition up to 5000 mg l-1. This was attributed to cell elongation and more efficient water uptake. For the lettuce, the fresh weight both of total seedlings and per seedling was enhanced by treating the seeds with fractions of low molecular weight and high content of acidic functions, whereas the dry weight both of total seedlings and per seedling did not change with the humic fraction used. For the tomato seeds in contrast, the dry weight both of total seedlings and per seedling was increased by the use of unfractionated humic acid and by some of the humic fractions. An uptake of humic material by growing tomato seedlings was inferred.