Labor unionization and supply-chain partners’ performance

We investigate whether labor unionization of customer firms affects the operating performance of their dependent suppliers. Using a sample of U.S. union elections, our regression discontinuity tests show that passing a union election leads to a 6.9 percentage-point decline in supplier operating margin in the following year. Such negative effects are more pronounced for customers with stronger bargaining power vis-à-vis dependent suppliers. Additional tests show that the reduced supplier operating margins are due to weakened top lines and, more specifically, to squeezed selling prices. Finally, consistent with increased labor costs, unionization is shown to significantly increase cost of goods sold and slow labor-force downsizing among customer firms. Overall, our evidence suggests that increased labor costs and financial inflexibility due to unionization induce customers to price-squeeze their dependent suppliers

Matrix representations of Sturm–Liouville problems with transmission conditions

AbstractWe identify a class of Sturm–Liouville equations with transmission conditions such that any Sturm–Liouville problem consisting of such an equation with transmission condition and an arbitrary separated or real coupled self-adjoint boundary condition has a representation as an equivalent finite dimensional matrix eigenvalue problem. Conversely, given any matrix eigenvalue problem of certain type and an arbitrary separated or real coupled self-adjoint boundary condition and transmission condition, we construct a class of Sturm–Liouville problems with this specified boundary condition and transmission condition, each of which is equivalent to the given matrix eigenvalue problem

Combined improved EEMD with SVM in ultra-low-dimensional ultra-small-sample application of multi-classification intelligent fault diagnosis

In actual intelligent fault diagnosis of mechanical equipment, the sample data that can be measured is very limited. How to identify the type of fault relies on as little as possible of the sample and as low as possible of the low-dimensional feature vector uniquely require research in actual mechanical machinery and equipment intelligent fault diagnosis. By using the threshold noise reduction, improving the cubic spine interpolation, signal SVM extending and so on to improve EEMD method; researched the cross-validation model grid optimization SVM parameters, obtained the optimal parameters of SVM by using Sigmoid kernel function; applied optimal excellent SVM parameters, SVM by using Sigmoid kernel function in the ultra-low-dimensional ultra-small-sample four categories intelligent fault diagnosis classification accuracy rate reached 100 %, SVM parameter optimization can enhance the method combined the improved EEMD with SVM in ultra-low-dimensional ultra-small-sample four categories fault diagnosis accuracy

Analysis of vibration traits of underwater vehicle propulsion shafting and optimization design of support parameters

In this paper, the calculation model of the propulsion shafting structure was established to solve the problem of flexural vibration of the shafting system for the underwater vehicle with relatively small scale. By using the transfer matrix method and the finite element method, the vibration characteristics of the shafting system subjected to the transverse unsteady excitation force were calculated by MATLAB software and ABAQUS software. Two aspects of the displacement response and the vibration power flow were analyzed and compared. Analysis showed that the results of the two methods were very close to each other and all met the requirements of vibration engineering calculation. The influence of the mass of propeller and the bearing stiffness in different positions on the vibration characteristics were analyzed by using the transfer matrix method. Finally, based on the transfer matrix method, the parameters of the bearing stiffness at different supports were optimized with design optimization, and then use ABAQUS software to verify the effectiveness of the optimization. The analysis results showed that, after optimization calculation, the vibration power flow input to the bases of different bearings were significantly decreased

A gene pattern mining algorithm using interchangeable gene sets for prokaryotes

<p>Abstract</p> <p>Background</p> <p>Mining gene patterns that are common to multiple genomes is an important biological problem, which can lead us to novel biological insights. When family classification of genes is available, this problem is similar to the pattern mining problem in the data mining community. However, when family classification information is not available, mining gene patterns is a challenging problem. There are several well developed algorithms for predicting gene patterns in a pair of genomes, such as FISH and DAGchainer. These algorithms use the optimization problem formulation which is solved using the dynamic programming technique. Unfortunately, extending these algorithms to multiple genome cases is not trivial due to the rapid increase in time and space complexity.</p> <p>Results</p> <p>In this paper, we propose a novel algorithm for mining gene patterns in more than two prokaryote genomes using interchangeable sets. The basic idea is to extend the pattern mining technique from the data mining community to handle the situation where family classification information is not available using interchangeable sets. In an experiment with four newly sequenced genomes (where the gene annotation is unavailable), we show that the gene pattern can capture important biological information. To examine the effectiveness of gene patterns further, we propose an ortholog prediction method based on our gene pattern mining algorithm and compare our method to the bi-directional best hit (BBH) technique in terms of COG orthologous gene classification information. The experiment show that our algorithm achieves a 3% increase in recall compared to BBH without sacrificing the precision of ortholog detection.</p> <p>Conclusion</p> <p>The discovered gene patterns can be used for the detecting of ortholog and genes that collaborate for a common biological function.</p

Transcriptome analysis reveals the time of the fourth round of genome duplication in common carp (Cyprinus carpio)

<p>Abstract</p> <p>Background</p> <p>Common carp (<it>Cyprinus carpio</it>) is thought to have undergone one extra round of genome duplication compared to zebrafish. Transcriptome analysis has been used to study the existence and timing of genome duplication in species for which genome sequences are incomplete. Large-scale transcriptome data for the common carp genome should help reveal the timing of the additional duplication event.</p> <p>Results</p> <p>We have sequenced the transcriptome of common carp using 454 pyrosequencing. After assembling the 454 contigs and the published common carp sequences together, we obtained 49,669 contigs and identified genes using homology searches and an ab initio method. We identified 4,651 orthologous pairs between common carp and zebrafish and found 129,984 paralogous pairs within the common carp. An estimation of the synonymous substitution rate in the orthologous pairs indicated that common carp and zebrafish diverged 120 million years ago (MYA). We identified one round of genome duplication in common carp and estimated that it had occurred 5.6 to 11.3 MYA. In zebrafish, no genome duplication event after speciation was observed, suggesting that, compared to zebrafish, common carp had undergone an additional genome duplication event. We annotated the common carp contigs with Gene Ontology terms and KEGG pathways. Compared with zebrafish gene annotations, we found that a set of biological processes and pathways were enriched in common carp.</p> <p>Conclusions</p> <p>The assembled contigs helped us to estimate the time of the fourth-round of genome duplication in common carp. The resource that we have built as part of this study will help advance functional genomics and genome annotation studies in the future.</p

Characterization of domains of self-adjoint ordinary differential operators of any order, even or odd

We characterize the domains of very general ordinary differential operators of any order, even or odd, with complex coefficients and arbitrary deficiency index