A new distributed management mechanism for ASI based networks

Advanced Switching Interconnect (ASI) is a high-speed serial interconnect embodied in the Dolphin Express family of interconnect products. In order to support high availability, the ASI specification established a management infrastructure, which is in charge of maintaining network operation after the occurrence of a topological change. When such a change occurs, the management mechanism discovers the new topology, calculates a set of valid routing paths, and distributes them to endpoints within the fabric. Several implementations for such a management mechanism have been proposed that use a centralized approach. These solutions can have negative effects with respect to network service availability. With the aim of eliminating these potential negative effects, this paper proposes a distributed solution for the computation of new paths. The distributed solution is evaluated for management entities with different performance capabilities, and for a range of traffic patterns and load levels. Our results show that the new distributed solution significantly reduces the change assimilation time and the negative impact on the network service when it is compared to a centralized solution.     

Translational vitreous proteomics

The vitreous is an extracellular matrix that is still poorly understood. Although many constituents and characteristics have been previously determined, there are many attributes still being discovered. Currently, using protein arrays, MS, and bioinformatics, the vitreous provides a wealth of knowledge regarding ocular diseases and potential targets for personalized therapeutics.     

Feeding concentrates with different protein sources to high-yielding,mid-lactation Norwegian Red cows: Effect on cheese ripening

Soybean meal is one of the most important protein sources in concentrate feeds for dairy cows. The objective of the present study was to provide knowledge on the effects of using a novel yeast microbial protein source (Candida utilis) in concentrate feed for dairy cows on the production and quality of a Gouda-type cheese. Forty-eight Norwegian Red dairy cows in early to mid lactation were fed a basal diet of grass silage, which was supplemented with 3 different concentrate feeds. The protein source of the concentrates was based on conventional soybean meal (SBM), novel yeast (C. utilis; YEA), or barley (BAR; used as negative control because barley has a lower protein content). The experiment was carried out for a period of 10 wk, with the first 2 wk as an adaptation period where all dairy cows were fed grass silage and the SBM concentrate. The cows were then randomly allocated to 1 of the 3 different compound feeds: SBM, yeast, or barley. Cheeses were made during wk 8 and 9 of the experiment, with 4 batches of cheese made from milk from each of the 3 groups. The cheeses made from milk from cows fed SBM concentrate (SBM cheese) had a higher content of dl-pyroglutamic acid and free amino acids than the other cheeses, indicating a faster ripening in the SBM cheeses. Despite these differences, the sensory properties, the microbiota, and the Lactococcus population at 15 wk of ripening were not significantly different between the cheeses. This experiment showed that although the raw materials used in the concentrate feed clearly influenced the ripening of the cheeses, this did not affect cheese quality. Yeast (C. utilis) as a protein source in concentrate feed for dairy cows can be used as a replacement for soybean meal without compromising the quality of Norwegian Gouda-type cheeses.     

Bulk tank raw milk microbiota differs within and between farms: A moving goalpost challenging quality control

Microbial contamination of bovine raw milk often occurs at the farm. To acquire a deeper knowledge of the microbiota of farm tank milk, we studied milk from 45 farms situated in 2 geographical areas in Norway. Each farm was visited on 3 different occasions, with at least 2 wk between visits. We combined both bacterial cell counts and a sequence variant inference method of amplicon-based high-throughput sequencing to achieve a high-resolution overview of the microbiota in each sample. Compositional variation of the farm milk microbiota was shown in relation to the 2 areas, between the farms and between the sampling times. Despite the near constant level of bacteria enumerated in milk from each individual farm, the dominant microbiota differed significantly between the samplings. The predominant microbiota was dominated by spoilage genera, such as Pseudomonas and Bacillus, as well as the dairy fermentation genus Lactococcus and mastitis-causing organisms (Streptococcus). Analysis of the identified sequence variants within these genera showed that the populations of Pseudomonas and Lactococcus in milk had similar composition between the farms, but that Bacillus and, in particular, Streptococcus populations changed between collection days from the same farm and between farms and geographical areas. Furthermore, the levels and composition of Bacillus and Paenibacillus were different between the 2 geographical areas. The results presented here provide new insight into the farm milk microbiota and show that this microbiota is a dynamic community highly subject to variation.     

Interconnection Networks: Architectural Challenges for Utility Computing Data Centers

Advancing research will enable an interconnection network to support the same seamless virtualization found in other parts of hardware, such as CPUs. Such a network thus poses particular challenges as well as opportunities for a utility computing data center.     

Layered routing in irregular networks

Freedom from deadlock is a key issue in cut-through, wormhole, and store and forward networks, and such freedom is usually obtained through careful design of the routing algorithm. Most existing deadlock-free routing methods for irregular topologies do, however, impose severe limitations on the available routing paths. We present a method called layered routing, which gives rise to a series of routing algorithms, some of which perform considerably better than previous ones. Our method groups virtual channels into network layers and to each layer it assigns a limited set of source/destination address pairs. This separation of traffic yields a significant increase in routing efficiency. We show how the method can be used to improve the performance of irregular networks, both through load balancing and by guaranteeing shortest-path routing. The method is simple to implement, and its application does not require any features in the switches other than the existence of a modest number of virtual channels. The performance of the approach is evaluated through extensive experiments within three classes of technologies. These experiments reveal a need for virtual channels as well as an improvement in throughput for each technology class.     

Fault tolerance in partitioned manufacturing networks

Fault tolerance is especially important for computer systems that require a high degree of confidence. Computer Integrated Manufacturing (CIM) is an area where computer systems must not be disturbed by uncontrolled failures. This article deals with two problems that are related to fault tolerance and network partitions in automated manufacturing systems.The first problem relates to the distribution of information in partitioned data networks in CIM systems. We indicate how to overcome this problem by using the material network as a redundant data network:The second problem relates to fault detection and diagnosis in manufacturing systems. The problem is whether the indication of a fault means that a production unit itself has actually broken down, or that the indication is instead due to disturbances in the transmission of material. That is, the production unit continues to operate propcrly despite indications to the contrary. We describe how the material network can be used for detection and diagnosis.     

Models for fault tolerance in manufacturing systems

The field of fault tolerance in computer science and engineering has been thoroughly investigated over a long period of time. A great number of different approaches have been presented on means for improving fault tolerance under certain error conditions in computerized systems. One important area that has introduced computers in order to enhance productivity, flexibility and economy, is manufacturing systems in order to acquire computer-integrated manufacturing (CIM). Using computers in a manufacturing system introduces new sources of difficulties, as well as providing new possibilities for overcoming erroneous situations that might disturb production. The aim of this paper, is to describe how the use of different configurations for a manufacturing system can improve fault tolerance. One specific erroneous situation which may occur in CIM is the partitioning of a network. This situation can be handled satisfactorily by using the suggested manufacturing system configurations. Additional improvements to fault tolerance can be achieved through the introduction of data buffers and material buffers, This approach is described in this paper.     

Survival of lactic acid bacteria from fermented milks in an in vitro digestion model exploiting sequential incubation in human gastric and duodenum juice

In the present study, the survival of 9 lactic acid bacteria (5 Lactococcus strains, 3 Lactobacillus strains, and 1 strain of Enterococcus hirae), was investigated in vitro under conditions similar to human digestion using human gastric and duodenal juices. The tolerance of the bacteria was also tested with traditional methods using acidic conditions and bile salts. The strains were subjected to a model digestive system comprising sequential incubation in human gastric and duodenal juices, in a 2-step digestion assay at 37°C, simulating the human upper gastrointestinal tract with human gastric juices at pH 2.5 and human duodenal juices at pH 7. The bacterial strains were tested either as washed cells from culture media or in fermented milk. The initial in vitro testing in acid and bile salts showed that Lactobacillus strains and the E. hirae strain displayed a significantly higher acid tolerance than the lactococci. The lactobacilli and the Enterococcus numbers increased, whereas the lactococci decreased at least 1 log during the bile salt treatment. The Lactobacillus strains showed the highest survival rate in the model digestive system when washed bacterial cultures were used with a minor log reduction, whereas the lactococci numbers were reduced by at least log 4. However, when using fermented milks in the model digestion system it was demonstrated that the Enterococcus strain and 2 strains of Lactococcus lactis ssp. cremoris benefited significantly from the presence of the fermented milk as food matrix, with log numbers >log 7 and 5, respectively, after digestion of the fermented milk. The analyses reported comprise a comprehensive in vitro testing regimen suitable for evaluation of the survival of candidate probiotic bacteria in human digestion as an initial prescreen to clinical trials.