Evidence for a spin-aligned neutron-proton paired phase from the level structure of (92)Pd

Shell structure and magic numbers in atomic nuclei were generally explained by pioneering work that introduced a strong spin-orbit interaction to the nuclear shell model potential. However, knowledge of nuclear forces and the mechanisms governing the structure of nuclei, in particular far from stability, is still incomplete. In nuclei with equal neutron and proton numbers (N = Z), enhanced correlations arise between neutrons and protons (two distinct types of fermions) that occupy orbitals with the same quantum numbers. Such correlations have been predicted to favour an unusual type of nuclear superfluidity, termed isoscalar neutron-proton pairing, in addition to normal isovector pairing. Despite many experimental efforts, these predictions have not been confirmed. Here we report the experimental observation of excited states in the N = Z = 46 nucleus (92)Pd. Gamma rays emitted following the (58)Ni((36)Ar,2n)(92)Pd fusion-evaporation reaction were identified using a combination of state-of-the-art high-resolution γ-ray, charged-particle and neutron detector systems. Our results reveal evidence for a spin-aligned, isoscalar neutron-proton coupling scheme, different from the previous prediction. We suggest that this coupling scheme replaces normal superfluidity (characterized by seniority coupling) in the ground and low-lying excited states of the heaviest N = Z nuclei. Such strong, isoscalar neutron-proton correlations would have a considerable impact on the nuclear level structure and possibly influence the dynamics of rapid proton capture in stellar nucleosynthesis.     

The interaction of indol-3-acetic acid with the uncoupler and non-uncoupler herbicides

Summary Auxin was shown to be able to cancel the growth inhibitory effect imposed by those herbicides which are not known as strong uncouplers of oxidative phosphorylation, while it was unable to do so with regards to the uncoupler herbicides.     

Evaluating the Impacts of Virtual Organization Absorption on the Quality of Urban Private Constructions; the System Dynamics Approach

Quality compliance checking of urban private constructions in Iran follows a fragmented pattern. By considering this fragmentation along with the inherent complexities of the quality compliance checking, it becomes urgent to look closer at this mechanism to find a way for making improvements. Since there is no determination to change the existing mechanism, this study discusses the use of virtual organizations as a strategy to enhance the level of quality. To this end, according to the intended approach for developing virtual organizations, this study identifies the capabilities of this type of systems in the first step. Then, this research evaluates the impacts of virtual organization absorption on the quality of urban private constructions. In this evaluation, the paper applies the system dynamics approach as the modeling tool due to its ability to address complexities and feedback structures. The resulted dynamic model needs initial values and requires functions to be able to run the simulation. In this case, the Delphi Technique is used to extract the functions and the values. After importing the resulted values and functions into the model, the focus group is used for the validation. The result of this analysis represents the positive impacts of the virtual organization absorption in the quality compliance checking mechanism. Fifty-percent improvement in the quality level of urban private constructions after a twenty-year period is one of the results, which could be considered as an indicator of virtual organization impacts.

     

A data-mining approach to biomarker identification from protein profiles using discrete stationary wavelet transform

Objective： To develop a new bioinformatic tool based on a data-mining approach for extraction of the most informative proteins that could be used to find the potential biomarkers for the detection of cancer. Methods： Two independent datasets from serum samples of 253 ovarian cancer and 167 breast cancer patients were used. The samples were examined by surfaceenhanced laser desorption/ionization time-of-flight mass spectrometry （SELDI-TOF MS）. The datasets were used to extract the informative proteins using a data-mining method in the discrete stationary wavelet transform domain. As a dimensionality reduction procedure, the hard thresholding method was applied to reduce the number of wavelet coefficients. Also, a distance measure was used to select the most discriminative coefficients. To find the potential biomarkers using the selected wavelet coefficients, we applied the inverse discrete stationary wavelet transform combined with a two-sided t-test. Results： From the ovarian cancer dataset, a set of five proteins were detected as potential biomarkers that could be used to identify the cancer patients from the healthy cases with accuracy, sensitivity, and specificity of 100%. Also, from the breast cancer dataset, a set of eight proteins were found as the potential biomarkers that could separate the healthy cases from the cancer patients with accuracy of 98.26%, sensitivity of 100%, and specificity of 95.6%. Conclusion： The results have shown that the new bioinformatic tool can be used in combination with the high-throughput proteomic data such as SELDI-TOF MS to find the potential biomarkers with high discriminative power.