Effects of fiber from tropical corn and forage sorghum silages on intake, digestion, and performance of lactating dairy cows

Tropical corn silage was compared with sorghum silage as a basal forage in the diets of high producing dairy cows. Sorghum and tropical corn silages were each included in place of ground corn at incremental concentrations in the experimental diets. Eight separate diets were fed, four diets containing each silage ranging in forage neutral detergent fiber (NDF) from approximately 25 to 31% and ranging in total NDF from approximately 41 to 45%. Diets were arranged in a 2 x 4 factorial design and were fed to lactating cows (n = 24; pretrial mean milk production = 39 kg/d; body weight = 656 kg; and days in milk = 81). As concentrations of dietary NDF increased, intake and milk production decreased linearly. The impact of dietary NDF on intake was greater for diets based on tropical corn silage than for diets based on sorghum silage. Energy intake and milk production were reduced, but cows consumed more fiber when challenged with higher dietary concentrations of fiber. The in vitro rate and extent of digestion of dietary samples were correlated with intake response. The rate of in vitro fiber digestion was slower for samples that contained tropical corn silage than for samples that contained sorghum silage. In vivo digestibility measurements were influenced by intake and dietary composition. Results of this trial indicated that sorghum silage can have equal or slightly greater nutritional value than tropical corn silage when these forages are fed at equal concentrations of dietary fiber.     

Linguistic Knowledge, Processing Speed, and Metacognitive Knowledge in First- and Second-Language Reading Comprehension: A Componential Analysis.

The authors report results of a study into the role of components of first-language (L1; Dutch) and second-language (L2; English) reading comprehension. Differences in the contributions of components of L1 and L2 reading comprehension are analyzed, in particular processing speed in L1 and L2. Findings indicate that regression weights of the L1 and L2 components are different. Although correlations between most processing speed components and reading comprehension are substantial, there are no unique contributions to the explanation of either L1 or L2 reading comprehension when linguistic and metacognitive knowledge are accounted for. In addition, L1 reading comprehension is shown to have a large contribution to L2 reading comprehension, supporting theories of L1-L2 transfer of reading skills. Results are discussed from a developmental perspective. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

LATE CENOZOIC THERMAL GRADIENTS IN DEAD SEA TRANSFORM SYSTEM BASINS

Coal-rank measurements and heat-flow data from three rhomb-shaped grabens along the continental portion of the Dead Sea Transform—the Hula Depression, the Sea of Galilee and the Dead Sea Graben—reveal contrasting thermal regimes. The coalification profile the Hula Depression indicates a relatively high thermal gradient, averaging 40C/km, throughout the Late Cenozoic. Similarly, a relatively high heat flow, approx 1.77 HFU, was reported in the Sea of Galilee, 35 km to the south. Coalfieation profile, heat flow data and BHT measurements on the Dead Sea Graben (200 km to the south) reveal a considerably lower thermal regime (approx 0.7 HFU, 2OC/km) that has prevailed since the mid-Miocene.
However, the differences in the thermal regime do not represent different mechanisms of basin formation. With the corroboration of hydrological and geophysical data, it is suggested that the high thermal regime in the two northern basins reflects a regional phenomenon associated with the nearby extensive Golan-Jeble Druze young volcanic terrain. Therefore, it has no relationship to the mechanism of rhomb-shaped graben formation, and should not be cited in support of kinematic models requiring a high thermal regime.     

Changes in US government procurement policy

‘Shrinking government’ and ‘Empowerment” really mean something in the standards business. New US government policies will sharply curtail the use of “MIL” specifications and standards. This dramatic move offers industry a more active role by creating new ‘performance-based’ standards. This article reviews the US department of Defence (DoD) decision and its expected consequences in the context of Aerospace Fluid Power.     

Optimal time byzantine agreement for t <n/8 with linear-messages

Summary.  This paper presents a Byzantine Agreement protocol with n=8t+1, optimal number of rounds (namely min{ f+2, t+1} where f is number of actual faults), and messages of linear size (namely m≦n+O(log n), where m stands for message size). All previous protocols that stop in optimal time and tolerate t=O(n) faults require messages of size at least O(n ²). The new protocol uses a novel technique called Reconstructed Traversal which is based on the Reconstruction Principle and on the Coordinated Traversal protocol. Received: August 1992/Accepted: January 1995l     

Tight Bounds for Distributed Minimum-Weight Spanning Tree Verification

This paper introduces the notion of distributed verification without preprocessing. It focuses on the Minimum-weight Spanning Tree (MST) verification problem and establishes tight upper and lower bounds for the time and message complexities of this problem. Specifically, we provide an MST verification algorithm that achieves simultaneously $\tilde{O}(m)$ messages and $\tilde{O}(\sqrt{n} + D)$ time, where m is the number of edges in the given graph G, n is the number of nodes, and D is G’s diameter. On the other hand, we show that any MST verification algorithm must send $\tilde{\varOmega}(m)$ messages and incur $\tilde{\varOmega}(\sqrt{n} + D)$ time in worst case. Our upper bound result appears to indicate that the verification of an MST may be easier than its construction, since for MST construction, both lower bounds of $\tilde{\varOmega}(m)$ messages and $\tilde{\varOmega}(\sqrt{n} + D)$ time hold, but at the moment there is no known distributed algorithm that constructs an MST and achieves simultaneously $\tilde{O}(m)$ messages and $\tilde{O}(\sqrt{n} + D)$ time. Specifically, the best known time-optimal algorithm (using ${\tilde{O}}(\sqrt {n} + D)$ time) requires O(m+n ^3/2) messages, and the best known message-optimal algorithm (using ${\tilde{O}}(m)$ messages) requires O(n) time. On the other hand, our lower bound results indicate that the verification of an MST is not significantly easier than its construction.     

Toward more localized local algorithms: removing assumptions concerning global knowledge

Numerous sophisticated local algorithm were suggested in the literature for various fundamental problems. Notable examples are the MIS and $(\Delta +1)$ -coloring algorithms by Barenboim and Elkin (Distrib Comput 22(5–6):363–379, 2010), by Kuhn (2009), and by Panconesi and Srinivasan (J Algorithms 20(2):356–374, 1996), as well as the $O\mathopen {}(\Delta ^2)$ -coloring algorithm by Linial (J Comput 21:193, 1992). Unfortunately, most known local algorithms (including, in particular, the aforementioned algorithms) are non-uniform, that is, local algorithms generally use good estimations of one or more global parameters of the network, e.g., the maximum degree $\Delta $ or the number of nodes $n$ . This paper provides a method for transforming a non-uniform local algorithm into a uniform one. Furthermore, the resulting algorithm enjoys the same asymptotic running time as the original non-uniform algorithm. Our method applies to a wide family of both deterministic and randomized algorithms. Specifically, it applies to almost all state of the art non-uniform algorithms for MIS and Maximal Matching, as well as to many results concerning the coloring problem (In particular, it applies to all aforementioned algorithms). To obtain our transformations we introduce a new distributed tool called pruning algorithms, which we believe may be of independent interest.     

Piecewise regression model construction with sample efficient regression tree (SERT) and applications to semiconductor yield analysis

Forward stepwise regression analysis selects critical attributes all the way with the same set of data. Regression analysis is, however, not capable of splitting data to construct piecewise regression models. Regression trees have been known to be an effective data mining tool for constructing piecewise models by iteratively splitting data set and selecting attributes into a hierarchical tree model. However, the sample size reduces sharply after few levels of data splitting causing unreliable attribute selection. In this research, we propose a method to effectively construct a piecewise regression model by extending the sample-efficient regression tree (SERT) approach that combines the forward selection in regression analysis and the regression tree methodologies. The proposed method attempts to maximize the usage of the dataset's degree of freedom and to attain unbiased model estimates at the same time. Hypothetical and actual semiconductor yield-analysis cases are used to illustrate the method and its effective search for critical factors to be included in the dataset's underlying model.     

A simulation-based scheduling system for real-time optimization and decision making support

This paper presents an industrial application of simulation-based optimization (SBO) in the scheduling and real-time rescheduling of a complex machining line in an automotive manufacturer in Sweden. Apart from generating schedules that are robust and adaptive, the scheduler must be able to carry out rescheduling in real time in order to cope with the system uncertainty effectively. A real-time scheduling system is therefore needed to support not only the work of the production planner but also the operators on the shop floor by re-generating feasible schedules when required. This paper describes such a real-time scheduling system, which is in essence a SBO system integrated with the shop floor database system. The scheduling system, called OPTIMISE scheduling system (OSS), uses real-time data from the production line and sends back expert suggestions directly to the operators through Personal Digital Assistants (PDAs). The user interface helps in generating new schedules and enables the users to easily monitor the production progress through visualization of production status and allows them to forecast and display target performance measures. Initial results from this industrial application have shown that such a novel scheduling system can help both in improving the line throughput efficiently and simultaneously supporting real-time decision making.