XV. Yeast sequencing reports. Isolation and DNA sequence of the STE13 gene encoding dipeptidyl aminopeptidase

We have isolated a mutant which exhibits partial constitutivity for a -specific gene expression in α cells. The wild-type gene was cloned and demonstrated to be allelic to the STE13 gene, which encodes the dipeptidyl aminopeptidase involved in processing of the α-factor prepropheromone. Thus, the mating defect of the ste13 mutations in α cells may result both from the production of incompletely processed α-factor and from the increased expression of a -specific genes. The STE13 open reading frame of 931 amino acids contains a putative membrane-spanning segment near its amino terminus and is 31% identical to a second yeast dipeptidyl aminopeptidase (DAP2). A null mutant of STE13 has been constructed: it is viable and sporulation-proficient. The sequence has been deposited in the GenBank data library under Accession Number L21944.     

Distribution of diethylstilboestrol in pigs

The synthetic growth promoter diethylstilboestrol (DES) administered orally to pigs can be detected by radioimmunoassay (RIA) analysis of kidney, liver, faeces, bile and urine from animals fed continuously to slaughter, but not in muscle, fat or plasma. If treated animals are fed on material not containing DES for 72 h prior to slaughter, then the levels of parent compound and metabolite in all products decrease to become not significantly greater than those in control animals. The gross metabolism of DES in pigs and bovines appears to be similar.     

Item bias in cognitive screening measures: comparisons of elderly white, Afro-American, Hispanic and high and low education subgroups

A study of item bias in standard cognitive screening measures was conducted in a sample of Afro-American, Hispanic and non-Hispanic white elderly respondents who were part of a dementia case registry study. The methods of item-response theory were applied to identify biased items. Both cross-cultural and high and low education groups were examined to determine which items were biased. Out of 50 cognitive items examined from six widely used cognitive screening measures, 16 were identified as biased for either high and low education groups or ethnic/racial group membership.     

13C n.m.r. study of raw materials for carbon black

¹³C n.m.r. spectroscopy has been applied to investigate a number of coal tar and petroleum-derived carbon black feedstocks. Application of the J-modulated spin echo technique is especially rewarding, as this method renders the quaternary carbons directly detectable. Thus the quality of carbon black feedstocks can additionally be gauged on the basis of the contents of quaternary carbons, which is a direct indication of the carbon yield in the carbon black production process.     

On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.     

When Disaster Strikes

The importance of securing data against the threat of natural disasters i s something most MIS managers don't realize until it's too late. This column describes how two fires and an earthquake adversely affected several companies that were unprepared, or only partially prepared, for such disasters. It also discusses disaster recovery measures some MIS executives believe their companies should strengthen not only to protect the data center but to reduce their employees risk of losing valuable informa- tion from office files.     

A generalized finite-difference time-domain quantum method for the N-body interacting Hamiltonian

The Quantum Finite-Difference Time-Domain (FDTD-Q) method is a numerical method for solving the time evolution of the Schrödinger equation. It can be applied to systems of interacting particles, allowing for realistic simulations of quantum mechanics of various experimental systems. One of the drawbacks of the method is that divergences in the numerical evolution occur rather easily in the presence of interactions, which necessitates a large number of evolution steps or imaginary time evolution. We present a generalized (GFDTD-Q) method for solving the time-dependent Schrödinger equation including interactions between the particles. The new scheme provides a more relaxed condition for stability when the finite difference approximations for spatial derivatives are employed, as compared with the original FDTD-Q scheme. We demonstrate our scheme by simulating the time evolution of a two-particle interaction Hamiltonian. Our results show that the generalized method allows for stable time evolutions, in contrast to the original FDTD-Q scheme which produces a divergent solution.