Training and Turnover in Organizations

We present a two-level model of organizational training and agent production. Managers decide whether or not to train based on both the costs of training compared to the benefits and on their expectations and observations of the number of other firms that also train. Managers also take into account the sum of their employees' contributions and the average tenure length within their organization. Employees decide whether or not to contribute to production based on their expectations as to how other employees will act. Trained workers learn over time and fold their increased productivity into their decision whether or not to contribute. We find that the dynamical behavior at the two levels is closely coupled: the evolution of the industry over time depends not only on the characteristics of training programs, learning curves, and cost-benefit analyses, but on the vagaries of chance as well. For example, in one case, the double dilemma can be resolved for the industry as a whole and productivity then increases steadily over time. In another, the organizational level dilemma may remain unresolved and workers may contribute at fluctuating levels. In this case the overall productivity stays low. We also find a correlation between high productivity and low turnover and show that a small increase in training rates can lead to explosive growth in productivity.Comment: 9 pages. Also available through anonymous ftp from parcftp.xerox.com in the directory pub/dynamics as training.p

A Taxonomic and Ecological Study of the Ants on the Campus of the University of New Mexico

This thesis attempts to indicate some of the ways in which the ants of the campus of the University of New Mexico affect man within the small area of the campus. However, my purpose of doing the study has not been strictly limited by practical considerations. Until now, no systematic study has been made of the Formicidae of the University of New Mexico Campus. Since the habitats produced artificially by man on the University of New Mexico Campus have resulted in favoring certain species of ants not found by the writer elsewhere in the region, the present study is valuable

TSUNAMIGENIC SOURCES IN THE INDIAN OCEAN

Based on an assessment of the repeat periods of great earthquakes from past seismicity, convergence rates and paleoseismological results, possible future source zones of tsunami generating earthquakes in the Indian Ocean (possible seismic gap areas) are identified along subduction zones and zones of compression. Central Sumatra, Java, Makran coast, Indus Delta, Kutch-Saurashtra, Bangladesh and southern Myanmar are identified as possible source zones of earthquakes in near future which might cause tsunamis in the Indian Ocean, and in particular, that could affect India. The Sunda Arc (covering Sumatra and Java) subduction zone, situated on the eastern side of the Indian Ocean, is one of the most active plate margins in the world that generates frequent great earthquakes, volcanic eruptions and tsunamis. The Andaman- Nicobar group of islands is also a seismically active zone that generates frequent earthquakes. However, northern Sumatra and Andaman-Nicobar regions are assessed to be probably free from great earthquakes (M!8.0) for a few decades due to occurrence of 2004 Mw 9.3 and 2005 Mw 8.7 earthquakes. The Krakatau volcanic eruptions have caused large tsunamis in the past. This volcano and a few others situated on the ocean bed can cause large tsunamis in the future. List of past tsunamis generated due to earthquakes/volcanic eruptions that affected the Indian region and vicinity in the Indian Ocean are also presented

What's in your next-generation sequence data? An exploration of unmapped DNA and RNA sequence reads from the bovine reference individual.

BackgroundNext-generation sequencing projects commonly commence by aligning reads to a reference genome assembly. While improvements in alignment algorithms and computational hardware have greatly enhanced the efficiency and accuracy of alignments, a significant percentage of reads often remain unmapped.ResultsWe generated de novo assemblies of unmapped reads from the DNA and RNA sequencing of the Bos taurus reference individual and identified the closest matching sequence to each contig by alignment to the NCBI non-redundant nucleotide database using BLAST. As expected, many of these contigs represent vertebrate sequence that is absent, incomplete, or misassembled in the UMD3.1 reference assembly. However, numerous additional contigs represent invertebrate species. Most prominent were several species of Spirurid nematodes and a blood-borne parasite, Babesia bigemina. These species are either not present in the US or are not known to infect taurine cattle and the reference animal appears to have been host to unsequenced sister species.ConclusionsWe demonstrate the importance of exploring unmapped reads to ascertain sequences that are either absent or misassembled in the reference assembly and for detecting sequences indicative of parasitic or commensal organisms

Adiabatic Quantum Computing for Random Satisfiability Problems

The discrete formulation of adiabatic quantum computing is compared with other search methods, classical and quantum, for random satisfiability (SAT) problems. With the number of steps growing only as the cube of the number of variables, the adiabatic method gives solution probabilities close to 1 for problem sizes feasible to evaluate via simulation on current computers. However, for these sizes the minimum energy gaps of most instances are fairly large, so the good performance scaling seen for small problems may not reflect asymptotic behavior where costs are dominated by tiny gaps. Moreover, the resulting search costs are much higher than for other methods. Variants of the quantum algorithm that do not match the adiabatic limit give lower costs, on average, and slower growth than the conventional GSAT heuristic method.Comment: added discussion of discrete adiabatic method, and simulations with 30 bits 8 pages, 8 figure

Genomic divergences among cattle, dog and human estimated from large-scale alignments of genomic sequences

BACKGROUND: Approximately 11 Mb of finished high quality genomic sequences were sampled from cattle, dog and human to estimate genomic divergences and their regional variation among these lineages. RESULTS: Optimal three-way multi-species global sequence alignments for 84 cattle clones or loci (each >50 kb of genomic sequence) were constructed using the human and dog genome assemblies as references. Genomic divergences and substitution rates were examined for each clone and for various sequence classes under different functional constraints. Analysis of these alignments revealed that the overall genomic divergences are relatively constant (0.32–0.37 change/site) for pairwise comparisons among cattle, dog and human; however substitution rates vary across genomic regions and among different sequence classes. A neutral mutation rate (2.0–2.2 × 10(-9) change/site/year) was derived from ancestral repetitive sequences, whereas the substitution rate in coding sequences (1.1 × 10(-9) change/site/year) was approximately half of the overall rate (1.9–2.0 × 10(-9) change/site/year). Relative rate tests also indicated that cattle have a significantly faster rate of substitution as compared to dog and that this difference is about 6%. CONCLUSION: This analysis provides a large-scale and unbiased assessment of genomic divergences and regional variation of substitution rates among cattle, dog and human. It is expected that these data will serve as a baseline for future mammalian molecular evolution studies

Quality assessment parameters for EST-derived SNPs from catfish

<p>Abstract</p> <p>Background</p> <p>SNPs are abundant, codominantly inherited, and sequence-tagged markers. They are highly adaptable to large-scale automated genotyping, and therefore, are most suitable for association studies and applicable to comparative genome analysis. However, discovery of SNPs requires genome sequencing efforts through whole genome sequencing or deep sequencing of reduced representation libraries. Such genome resources are not yet available for many species including catfish. A large resource of ESTs is to become available in catfish allowing identification of large number of SNPs, but reliability of EST-derived SNPs are relatively low because of sequencing errors. This project was designed to answer some of the questions relevant to quality assessment of EST-derived SNPs.</p> <p>Results</p> <p>wo factors were found to be most significant for validation of EST-derived SNPs: the contig size (number of sequences in the contig) and the minor allele sequence frequency. The larger the contigs were, the greater the validation rate although the validation rate was reasonably high when the contigs contain four or more EST sequences with the minor allele sequence being represented at least twice in the contigs. Sequence quality surrounding the SNP under test is also crucially important. PCR extension appeared to be limited to a very short distance, prohibiting successful genotyping when an intron was present, a surprising finding.</p> <p>Conclusion</p> <p>Stringent quality assessment measures should be used when working with EST-derived SNPs. In particular, contigs containing four or more ESTs should be used and the minor allele sequence should be represented at least twice. Genotyping primers should be designed from a single exon, completely avoiding introns. Application of such quality assessment measures, along with large resources of ESTs, should provide effective means for SNP identification in species where genome sequence resources are lacking.</p

Box–Cox Transformation and Random Regression Models for Fecal egg Count Data

Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used in an effort to achieve normality before analysis. However, the transformed data are often still not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box–Cox transformation to approach normality and to estimate (co)variance components. We also proposed using random regression models (RRM) for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box–Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated

Genomic data as the “hitchhiker's guide” to cattle adaptation: tracking the milestones of past selection in the bovine genome

The bovine species have witnessed and played a major role in the drastic socio-economical changes that shaped our culture over the last 10,000 years. During this journey, cattle hitchhiked on human development and colonized the world, facing strong selective pressures such as dramatic environmental changes and disease challenge. Consequently, hundreds of specialized cattle breeds emerged and spread around the globe, making up a rich spectrum of genomic resources. Their DNA still carry the scars left from adapting to this wide range of conditions, and we are now empowered with data and analytical tools to track the milestones of past selection in their genomes. In this review paper, we provide a summary of the reconstructed demographic events that shaped cattle diversity, offer a critical synthesis of popular methodologies applied to the search for signatures of selection (SS) in genomic data, and give examples of recent SS studies in cattle. Then, we outline the potential and challenges of the application of SS analysis in cattle, and discuss the future directions in this field