Search for signature inversion in the pi i(13/2) circle times upsilon i1(3/2) bands in Au-182,Au-184,Au-186

Search for low-spin signature inversion in the pi i(13/2) circle times nu i(13/2) bands in odd-odd Au-182,Au-184,Au-186 has been conducted through the standard in-beam gamma-spectroscopy techniques. The experiments for Au-182 and 186Au have been performed in the Japan Atomic Energy Agency (JAEA) via the Sm-152(Cl-35,5n)Au-182 and Yb-172(F-19,5n)Au-186 reactions, respectively. A study of Au-184 has been made using a multi-detector array GASP in LNL, Italy, via the Tb-159(Si-29,4n)Au-184 reaction. The pi i(13/2) circle times nu i(13/2) bands in these three nuclei have been identified and extended up to high-spin states. In particular, the inter-band connection between the pi i(13/2) nu i(13/2) band and the ground-state band in 184 Au has been established, leading to a firm spin-and-parity assignment for the pi i(13/2) circle times nu i(13/2) band. The low-spin signature inversion is found in the pi i(13/2) circle times nu i(13/2) bands in Au-182,Au-184,Au-186 according to our spin-assignment and the signature crossing observed at high-spin states.

Identification of a new band and its signature inversion in Re-174

High spin states in Re-174 are investigated via the Sm-152(Al-27, 5n gamma)Re-174 reaction and gamma-gamma coincidence relationships are analysed carefully. A new band is identified due to its spectroscopic connection with the known pi 1/2(-)[541] circle times nu 1/2(-)[521] band. This band is proposed to be the ground-state band built on the pi 1/2(-)[541] circle times nu 5/2(-)[512] configuration in view of the low-lying intrinsic states in the neighbouring odd-mass nuclei. It is of particular interesting that the new band exhibits a phenomenon of low-spin signature inversion, providing a new situation for theoretical investigations.

Search for signature inversion in the pi i(13/2)circle times nu i(13/2) bands in Au-182,Au-184,Au-186

Search for low-spin signature inversion in the pi i(13/2) circle times nu i(13/2) bands in odd-odd Au-182,Au-184,Au-186 has been conducted through the standard in-beam gamma-spectroscopy techniques via the Sm-152(Cl-35,5n) Au-182, Yb-172(F-19,5n) (186)An, and Tb-159(Si-29,4n) (184)An reactions, respectively. The pi i(13/2) circle times nu i(13/2) bands in these three nuclei have been identified and extended up to high-spin states. In particular, the inter-band connection between the pi i(13/2) circle times nu i(13/2) band and the ground-state band in Au-184 has been established, leading to a firm spin-and-parity assignment for the pi i(13/2) circle times nu i(13/2) band. The low-spin signature inversion is found in the pi i(13/2) circle times nu i(13/2) bands according to our spin-assignment and-the signature crossing observed at high-spin states.

Low-spin signature inversion in the pi h(9/2)circle times nu i(13/2) oblate band

Excited states in Tl-188,Tl-190 have been studied experimentally by means of in-beam gamma spectroscopy techniques, and resulted in the identification of a strongly coupled band based on the pi h(9/2) circle times nu i(13/2) configuration with oblate deformation. The oblate band in doubly odd Tl nuclei shows low-spin signature inversion. It is the first experimental observation of low-spin signature inversion for a band associated with the oblate pi h(9/2) circle times nu i(13/2) configuration.

Signature inversion in pi h(9/2) circle times nu i(13/2) oblate band of Tl-188

High-spin Level structure of Tl-188 has been studied via Gd-157 (Cl-35,4n) fusion-evaporation reaction at beam energy of 170MeV. A rotational band built on the pi h(9/2) circle times nu i(13/2) configuration with oblate deformation has been established. Spin values have been proposed to the pi h(9/2) circle times nu i(13/2) oblate band based on the similarities between the oblate band of Tl-188 and those in odd-odd Tl190-200. With the spin assignments, the low-spin signature inversion has been revealed for the pi h(9/2) circle times nu i(13/2) oblate band of Tl-188. The low-spin signature inversion can be interpreted qualitatively in the framework of the quasi-particles plus rotor model including a J dependent p-n residual interaction.

Hematopoietic gene promoters subjected to a group-combinatorial study of DNA samples: identification of a megakaryocytic selective DNA signature

Identification of common sub-sequences for a group of functionally related DNA sequences can shed light on the role of such elements in cell-specific gene expression. In the megakaryocytic lineage, no one single unique transcription factor was described as linage specific, raising the possibility that a cluster of gene promoter sequences presents a unique signature. Here, the megakaryocytic gene promoter group, which consists of both human and mouse 5' non-coding regions, served as a case study. A methodology for group-combinatorial search has been implemented as a customized software platform. It extracts the longest common sequences for a group of related DNA sequences and allows for single gaps of varying length, as well as double- and multiple-gap sequences. The results point to common DNA sequences in a group of genes that is selectively expressed in megakaryocytes, and which does not appear in a large group of control, random and specific sequences. This suggests a role for a combination of these sequences in cell-specific gene expression in the megakaryocytic lineage. The data also point to an intrinsic cross-species difference in the organization of 5' non-coding sequences within the mammalian genomes. This methodology may be used for the identification of regulatory sequences in other lineages.

Use of 16S ribosomal RNA gene analyses to characterize the bacterial signature associated with poor oral health in West Virginia.

BACKGROUND: West Virginia has the worst oral health in the United States, but the reasons for this are unclear. This pilot study explored the etiology of this disparity using culture-independent analyses to identify bacterial species associated with oral disease. METHODS: Bacteria in subgingival plaque samples from twelve participants in two independent West Virginia dental-related studies were characterized using 16S rRNA gene sequencing and Human Oral Microbe Identification Microarray (HOMIM) analysis. Unifrac analysis was used to characterize phylogenetic differences between bacterial communities obtained from plaque of participants with low or high oral disease, which was further evaluated using clustering and Principal Coordinate Analysis. RESULTS: Statistically different bacterial signatures (P<0.001) were identified in subgingival plaque of individuals with low or high oral disease in West Virginia based on 16S rRNA gene sequencing. Low disease contained a high frequency of Veillonella and Streptococcus, with a moderate number of Capnocytophaga. High disease exhibited substantially increased bacterial diversity and included a large proportion of Clostridiales cluster bacteria (Selenomonas, Eubacterium, Dialister). Phylogenetic trees constructed using 16S rRNA gene sequencing revealed that Clostridiales were repeated colonizers in plaque associated with high oral disease, providing evidence that the oral environment is somehow influencing the bacterial signature linked to disease. CONCLUSIONS: Culture-independent analyses identified an atypical bacterial signature associated with high oral disease in West Virginians and provided evidence that the oral environment influenced this signature. Both findings provide insight into the etiology of the oral disparity in West Virginia.

A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.

There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent.

Bottlenose dolphins exchange signature whistles when meeting at sea.

The bottlenose dolphin, Tursiops truncatus, is one of very few animals that, through vocal learning, can invent novel acoustic signals and copy whistles of conspecifics. Furthermore, receivers can extract identity information from the invented part of whistles. In captivity, dolphins use such signature whistles while separated from the rest of their group. However, little is known about how they use them at sea. If signature whistles are the main vehicle to transmit identity information, then dolphins should exchange these whistles in contexts where groups or individuals join. We used passive acoustic localization during focal boat follows to observe signature whistle use in the wild. We found that stereotypic whistle exchanges occurred primarily when groups of dolphins met and joined at sea. A sequence analysis verified that most of the whistles used during joins were signature whistles. Whistle matching or copying was not observed in any of the joins. The data show that signature whistle exchanges are a significant part of a greeting sequence that allows dolphins to identify conspecifics when encountering them in the wild.

Effect of lesion morphology on microwave signature in 2-D ultra-wideband breast imaging

This paper studies the possibility of distinguishing between benign and malignant masses by exploiting the morphology-dependent temporal and spectral characteristics of their microwave backscatter response in ultra-wideband breast cancer detection. The spiculated border profiles of 2-D breast masses are generated by modifying the baseline elliptical rings based upon the irregularity of their peripheries. Furthermore, the single- and multilayer lesion models are used to characterize a distinct mass region followed by a sharp transition to background, and a blurred mass border exhibiting a gradual transition to background, respectively. Subsequently, the complex natural resonances (CNRs) of the backscatter microwave signature can be derived from the late-time target response and reveal diagnostically useful information. The fractional sequence CLEAN algorithm is proposed to estimate the lesions' delay intervals and identify the late-time responses. Finally, it is shown through numerical examples that the locations of dominant CNRs are dependent on the lesion morphologies, where 2-D computational breast phantoms with single and multiple lesions are investigated. The analysis is of potential use for discrimination between benign and malignant lesions, where the former usually possesses a better-defined, more compact shape as opposed to the latter.

Statistical Monitoring of Dynamic Multivariate Processes: Part II: Identifying Fault Magnitude and Signature

This paper builds on work presented in the first paper, Part 1 [1] and is of equal significance. The paper proposes a novel compensation method to preserve the integrity of step-fault signatures prevalent in various processes that can be masked during the removal of both auto- and cross correlation. Using industrial data, the paper demonstrates the benefit of the proposed method, which is applicable to chemical, electrical, and mechanical process monitoring. This paper, (and Part 1 [1]), has led to further work supported by EPSRC grant GR/S84354/01 involving kernel PCA methods.