Evaluation of genetic substructure in the Irish Study of High-Density Schizophrenia Families

The presence of genetic substructure has the potential to diminish the chances of detecting a linkage signal. Using a Markov chain Monte Carlo procedure developed by Pritchard and colleagues and implemented in the program STRUCTURE, we evaluated the evidence for genetic substructure using genotypes from 37 microsatellite markers in affected individuals selected at random from 263 multiplex families in the Irish Study of High-Density Schizophrenia Families. We found no evidence for the presence of genetic substructure in this sample.

Strong configuration mixing among the fine-structure levels of Cl+

A large-scale configuration interaction (Cl) calculation using Program CIV3 of Hibbert is performed for the lowest 62 fine- structure levels of the singly charged chlorine ion. Our calculated energy levels agree very well with most of the NIST results and confirm the identification of the lowest P-1(o) as actually 3s(2)3p(3)(D-2(o))3d P-1(o) rather than the generally employed 3s3p(5) P-1(o) in measurements and calculations. Discrepancies in the energy positions of some symmetries are found and discussed. Some large oscillator strengths for allowed and intercombination transitions in both length and velocity gauges are presented. Their close agreement gives credence to the accuracy of our CI wavefunctions.

Electron-impact excitation of FeII - Collision strengths and effective collision strengths for low-lying fine-structure forbidden transitions

Context. Absorption or emission lines of Fe II are observed in many astrophysical spectra and accurate atomic data are required to interpret these lines. The calculation of electron-impact excitation rates for transitions among even the lowest lying levels of Fe II is a formidable task for theoreticians.

Aims. In this paper, we present collision strengths and effective collision strengths for electron-impact excitation of Fe II for low-lying forbidden transitions among the lowest 16 fine-structure levels arising from the four LS states 3d(6)4s D-6(e), 3d(7) F-4(e), 3d(6)4s D-4(e), and 3d(7) P-4(e). The effective collision strengths are calculated for a wide range of electron temperatures of astrophysical importance from 30-100 000 K.

Methods. The parallel suite of Breit-Pauli codes are utilised to compute the collision cross sections for electron-impact excitation of Fe II and relativistic terms are included explicitly in both the target and the scattering approximation. 100 LS or 262-jj levels formed from the basis configurations 3d(6)4s, 3d(7), and 3d(6)4p were included in the wavefunction representation of the target, including all doublet, quartet, and sextet terms. Collision strengths for a total of 34191 individual transitions were computed.

Results. A detailed comparison is made with previous theoretical works and significant differences were found to occur in the effective collision strengths, particularly at low temperatures.

Malware detection: program run length against detection rate

N-gram analysis is an approach that investigates the structure of a program using bytes, characters or text strings. This research uses dynamic analysis to investigate malware detection using a classification approach based on N-gram analysis. A key issue with dynamic analysis is the length of time a program has to be run to ensure a correct classification. The motivation for this research is to find the optimum subset of operational codes (opcodes) that make the best indicators of malware and to determine how long a program has to be monitored to ensure an accurate support vector machine (SVM) classification of benign and malicious software. The experiments within this study represent programs as opcode density histograms gained through dynamic analysis for different program run periods. A SVM is used as the program classifier to determine the ability of different program run lengths to correctly determine the presence of malicious software. The findings show that malware can be detected with different program run lengths using a small number of opcodes

Deciphering tissue-induced Klebsiella pneumoniae lipid A structure

The host launches an antimicrobial defense program upon infection. A long-held belief is that pathogens prevent host recognition by remodeling their surface in response to different host microenvironments. Yet direct evidence that this happens in vivo is lacking. Here we report that the pathogen Klebsiella pneumoniae modifies one of its surface molecules, the lipopolysaccharide, in the lungs of mice to evade immune surveillance. These in vivo-induced changes are lost in bacteria grown after isolation from the tissues. These lipopolysaccharide modifications contribute to survival in vivo and mediate resistance to colistin, one of the last options to treat multidrug-resistant Klebsiella. This work opens the possibility of designing novel therapeutics targeting the enzymes responsible for the in vivo lipid A pattern.