Supervisory control based on minimal cuts and Petri net sub-controllers coordination

This paper addresses the synthesis of Petri net (PN) controller for the forbidden state transition problem with a new utilisation of the theory of regions. Moreover, as any method of control synthesis based on a reachability graph, the theory of regions suffers from the combinatorial explosion problem. The proposed work minimises the number of equations in the linear system of theory of regions and therefore one can reduce the computation time. In this paper, two different approaches are proposed to select minimal cuts in the reachability graph in order to synthesise a PN controller. Thanks to a switch from one cut to another, one can activate and deactivate the corresponding?PNcontroller. An application is implemented in a flexible manufacturing system to illustrate the present method. Finally, comparison with previous works with experimental results in obtaining a maximally permissive controller is presented.     

Pleurotusostreatus and Agaricus subrufescens: investigation of chemical composition and antioxidant properties of these mushrooms cultivated with different handmade and commercial supplements

In this study, the chemical composition, total phenolic content and antioxidant activity (DPPH, ORAC and FRAP assays) of A. subrufescens and P. ostreatus, cultivated with handmade and commercials supplements, were compared. Additionally, the compounds ergosterol, saccharopine, and hexitol were identified in A. subrufescens by HPLC-MS/MS. The antioxidant compound p-coumaric acid and dihexoses was found in both mushroom species. A. subrufescens presented higher total phenolic content (73.8 ± 0.6 mg GAE 100 g⁻¹) and antioxidant activity than P. ostreatus (16.6 ± 0.5 mg GAE 100 g⁻¹). The handmade supplement based on the waste of noble grains presented statistically similar phenolic content to the mushrooms cultivated with commercial ones Spawn Mate II SE (86.1 ± 1.4 and 92.9 ± 0.3 mg GAE 100 g⁻¹, respectively). Therefore, the results support the use of handmade supplements based on agro-wastes as a viable alternative to the use of high-cost commercial ones.     

Conductometric biosensor based on glucose oxidase and beta-galactosidase for specific lactose determination in milk

This paper investigates the development of a biosensor associating two distinct enzymatic activities, that of the beta-galactosidase and that of the glucose oxidase, in order to apply it for the quantitative detection of lactose in milk. To eliminate interferences with glucose, a differential mode of measurement was used. Results show a linear calibration curve for lactose concentration between 60 and 800 μM (0.03 to 0.3 g/L). Tests with real commercial milk samples were carried out to validate the conductometric biosensor.     

Occurrence of Yersinia enterocolitica in milk and dairy products in Morocco.

A total of 227 samples of milk and dairy products were examined for the presence of Yersinia enterocolitica. Yersinia spp. were recovered from 11 of 30 raw milks (36.6%), one of 20 pasteurized milks (5%), 15 of 63 traditional fermented milks (23.8%), seven of 94 cheeses and one of 20 cream samples (5%). The overall incidence of Y. enterocolitica in milk and dairy products was 6.6%. The other Yersinia species were Y. intermedia, Y. kristensenii, Y. frederiksenii and Y. pseudotuberculosis. Y. enterocolitica was detected only in raw milk (30% of the samples), in traditional fermented milks (6.3%) and in raw milk-made cheese (4%). The majority of the Y. enterocolitica isolates were of biotype 1 (environmental strains). The Celfulodin-Irgasan-Novobiocin (CIN) Agar was found to be more efficient than the Mac Conkey Agar in the isolation of Yersinia organisms.     

Improving the performance of retail stores subject to execution errors: coordination versus RFID technology

This paper analyzes a Newsvendor type inventory model in which a manufacturer sells a single product to a retailer store whose inventory is subject to errors stemming from execution problems. Hence, within the store, all of the products are not available on shelf for sales either because the replenishment of the shelf from the backroom is subject to execution errors that mainly result in products lost in the backroom or products misplaced on the other shelves of the store. We compare two situations: in the first situation, the two supply chain actors are aware of errors and optimize their ordering decisions by taking into account this issue. The second situation deals with the case where an advanced automatic identification system such as the Radio Frequency Identification technology is deployed in order to eliminate errors. Each situation is developed for three scenarios: in the centralized scenario, we consider a single decision-maker who is concerned with maximizing the entire supply chain’s profit; in the decentralized uncoordinated scenario, the retailer and the manufacturer act as different parties and do not cooperate. The third scenario is the decentralized coordinated scenario where we give conditions for coordinating the channel by designing a buyback contract. The authors would like to thank the editor, Prof. Dr. Hans-Otto Guenther, and two anonymous referees for their constructive comments to improve this article.     

Assessing sensor reliability for multisensor data fusion within the transferable belief model.

This paper presents a method for assessing the reliability of a sensor in a classification problem based on the transferable belief model. First, we develop a method for the evaluation of the reliability of a sensor when considered alone. The method is based on finding the discounting factor minimizing the distance between the pignistic probabilities computed from the discounted beliefs and the actual values of data. Next, we develop a method for assessing the reliability of several sensors that are supposed to work jointly and their readings are aggregated. The discounting factors are computed on the basis of minimizing the distance between the pignistic probabilities computed from the combined discounted belief functions and the actual values of data.