The effects of ozonated water on the microbial counts and the shelf life attributes of fresh‐cut spinach

Fresh‐cut vegetables became more and more popular due to healthy eating habits, with main problem safety of the product because of microbial spoilage as well as visual and nutritional quality changes. Ozone may act as a sanitizer; however, due to its strong oxidant activity care is needed, as in some cases, that is, if the dose being used is too high, the quality of the produce may be reduced. In this study, ozonated water at various concentrations and dipping times (0, 0.4, 0.8, or 1.2 mg/L for 0, 1, 15, or 30 s) were tested. Results revealed that application of ozonated water (0.8 mg/L for 30 s) before packaging reduced yellowing and maintained compositional characteristics of the fresh‐cut spinach leaves, ensuring a shelf‐life extension of 3 days. Moreover, a positive effect on microbial population control was recorded during the first 5 days of storage.

Practical applications

The use of chlorine or other chemicals in fresh‐cut industry is decreasing while alternatives treatments are proposed. Ozone even had remarkable antimicrobial action however because of its oxidation action could be negative for the horticultural products. This work investigated the efficiency of ozone treatment (concentration and dipping time) to control yellowing of fresh‐cut spinach as well as the effect on microbial counts and leaves composition. The information obtained from this study provide the chance to extend the postharvest life of a highly perishable product with an alternative to chemical treatment that could be easily applied in processing line.     

Relative validity of a semiquantitative food frequency questionnaire designed for schoolchildren in western Greece

Water soluble β-carotene (WS-BC) is a carotenoid form that has been developed as a food colorant. WS-BC is known to contain 10% of all-trans β-carotene (AT-BC). The aim of the present study was to investigate in vivo tissue uptake of AT-BC after the administration of WS-BC into rats. Seven-week-old male rats were administered 20 mg of WS-BC dissolved in saline by intravenous injection into the tail vein. At 0, 6, 24, 72, 120 and 168 hours (n = 7/time), blood was drawn and liver, lungs, adrenal glands, kidneys and testes were dissected. The levels of AT-BC in the plasma and dissected tissues were quantified with HPLC. After intravenous administration, AT-BC level in plasma first increased up to 6 h and returned to normal at 72 h. In the testes, the AT-BC level first increased up to 24 h and then did not decrease but was retained up to 168 h. In the other tissues, the level first increased up to 6 h and then decreased from 6 to 120 or 168 h but did not return to normal. The accumulation of WS-BC in testes but not in the other 5 tissues examined may suggest that AT-BC was excreted or metabolized in these tissues but not in testes. Although WS-BC is commonly used as a food colorant, its effects on body tissues are still not clarified. Results of the present study suggest that further investigations are required to elucidate effects of WS-BC on various body tissues.     

Detection and classification of winding faults in windmill generators using Wavelet Transform and ANN

This paper exploits the Wavelet Transform (WT) analysis along with Artificial Neural Networks (ANN) for the diagnosis of electrical machines winding faults. A novel application is presented exploring the problem of automatically identifying short circuits of windings, which often appear during machine manufacturing and operation. Such faults are usually resulting from electrodynamics forces generated during the flow of large short circuit currents, as well as forces occurring when the machines are transported. The early detection and classification of winding failures is of particular importance, as these kinds of defects can lead to winding damage due to overheating, imbalance, etc. Application results and investigations of windmill generator winding turn-to-turn faults between adjacent winding wires are presented. The ANN approach is proven effective in detecting and classifying faults based on WT features extracted from high frequency measurements of the admittance, current, or voltage responses.     

Statistical analysis of major accidents in petrochemical industry notified to the major accident reporting system (MARS)

The European major accident reporting system (MARS) was created within the framework of European Union (EU) directive 82/501, the so-called "SEVESO" directive, and in order to register all the major industrial accidents notified to the European Union authorities from the member states. Statistical analysis of these accidents offers significant data to the understanding and prevention of industrial accidents. This paper makes an analysis of some characteristics of major accidents in the petrochemical sector included in MARS. The statistical analysis focused on the main categorization fields of the MARS short reports and additionally a refinement of the immediate causes of major accidents with focus on the organizational factors was attempted through the details provided in the full reports of the database.     

Entropy-Based Sensor Placement Optimization for Waterloss Detection in Water Distribution Networks

The work presented herein addresses the problem of sensor placement optimization in urban water distribution networks by use of an entropy-based approach, for the purpose of efficient and economically viable waterloss incident detection. The proposed method is applicable to longitudinal rather than spatial sensing, thus to devices such as acoustic, pressure, or flow sensors acting on pipe segments. The method utilizes the maximality, subadditivity and equivocation properties of entropy, coupled with a statistical definition of the probability of sensing within a pipe segment, to assign an entropy metric to each pipe segment and subsequently optimize the location of sensors in the network based on maximizing the total entropy in the network. The method proposed is a greedy-search heuristic.     

Treating scalability and modelling human countermeasures against local preference worms via gradient models

A network worm is a specific type of malicious software that self propagates by exploiting application vulnerabilities in network-connected systems. Worm propagation models are mathematical models that attempt to capture the propagation dynamics of scanning worms as a means to understand their behaviour. It turns out that the emerged scalability in worm propagation plays an important role in order to describe the propagation in a realistic way. On the other hand human-based countermeasures also drastically affect the propagation in time and space. This work elaborates on a recent propagation model (Avlonitis et al. in J Comput Virol 3, 87–92, 2007) that makes use of Partial Differential Equations in order to treat correctly scalability and non-uniform behaviour (e.g., local preference worms). The aforementioned gradient model is extended in order to take into account human-based countermeasures that influence the propagation of local-preference worms in the Internet. Certain aspects of scalability emerged in random and local preference strategies are also discussed by means of random field considerations. As a result the size of a critical network that needs to be studied in order to describe the global propagation of a scanning worm is estimated. Finally, we present simulation results that validate the proposed analytical results and demonstrate the higher propagation rate of local preference worms compared with random scanning worms.     

‘Closing the loop’ in biological systems modeling — From the in silico to the in vitro

This work presents a holistic ‘closed loop’ approach for the development of models of biological systems. The ever-increasing availability of experimental information necessitates the advancement of a systematic methodology to organise and utilise these data. Herein, we present a biological model building framework that maps the treatment of the information from the initial conception of the model, through its experimental validation and finally to its application in model-based optimisation studies. We highlight and discuss current issues associated with the development of mathematical models of biological systems and share our perspective towards a holistic ‘closed loop’ approach that will facilitate the control of the in vitro through the in silico.     

A linear-time optimal-message distributed algorithm for minimum spanning trees

In an earlier paper, Awerbuch presented an innovative distributed algorithm for solving minimum spanning tree (MST) problems that achieved optimal time and message complexity through the introduction of several advanced features. In this paper, we show that there are some cases where his algorithm can create cycles or fail to achieve optimal time complexity. We then show how to modify the algorithm to avoid these problems, and demonstrate both the correctness and optimality of the revised algorithm.Received: 9 February 2003, Accepted: 2 April 2004, Published online: 20 July 2004Mart Molle: This material is based upon work supported by the National Science Foundation under CAREER Grant No. 9985195, and Nortel Networks and UC CoRe fund C99-14.     

Efficient range query processing in metric spaces over highly distributed data

Similarity search in P2P systems has attracted a lot of attention recently and several important applications, like distributed image search, can profit from the proposed distributed algorithms. In this paper, we address the challenging problem of efficient processing of range queries in metric spaces, where data is horizontally distributed across a super-peer network. Our approach relies on SIMPEER (Doulkeridis et al. in Proceedings of VLDB, pp. 986–997, 2007), a framework that dynamically clusters peer data, in order to build distributed routing information at super-peer level. SIMPEER allows the evaluation of exact range and nearest neighbor queries in a distributed manner that reduces communication cost, network latency, bandwidth consumption and computational overhead at each individual peer. In this paper, we extend SIMPEER by focusing on efficient range query processing and providing recall-based guarantees for the quality of the result retrieved so far. This is especially useful for range queries that lead to result sets of high cardinality and incur high processing costs, while the complete result set becomes overwhelming for the user. Our framework employs statistics for estimating an upper limit of the number of possible results for a range query and each super-peer may decide not to propagate further the query and reduce the scope of the search. We provide an experimental evaluation of our framework and show that our approach performs efficiently, even in the case of high degree of distribution.     

Performance-based multiobjective optimum design of steel structures considering life-cycle cost

A new methodology for the performance-based optimum design of steel structures subjected to seismic loading considering inelastic behavior is proposed. The importance of considering life-cycle cost as an additional objective to the initial structural cost objective function in the context of multiobjective optimization is also investigated. Life-cycle cost is considered to take into account during the design phase the impact of future earthquakes. For the solution of the multiobjective optimization problem, Evolutionary Algorithms and in particular an algorithm based on Evolution Strategies, specifically tailored to meet the characteristics of the problem at hand, are implemented. The constraints of the optimization problem are based on the provisions of European design codes, while additional constraints are imposed by means of pushover analysis to control the load and deformation capacity of the structure.