beta-Delayed proton decays in the rare-earth region near drip line

The history of experimental study on beta-delayed proton decays in the rare-earth region was simply reviewed. The physical results of the beta-delayed proton decays obtained at IMP, Lanzhou over the last 10 years were summarized, mainly including the first observation of 9 new beta-delayed proton precursors along the odd-Z proton drip line and the new data for 2 waiting-point nuclei in the rp-process. The results were compared and discussed with different nuclear model calculations. Finally, the perspective in near future was briefly introduced.

Laser Driven Nuclear Physics at ELI–NP

High power lasers have proven being capable to produce high energy γ-rays, charged particles and neutrons, and to induce all kinds of nuclear reactions. At ELI, the studies with high power lasers will enter for the first time into new domains of power and intensities: 10 PW and 10^23 W/cm^2. While the development of laser based radiation sources is the main focus at the ELI-Beamlines pillar of ELI, at ELI-NP the studies that will benefit from High Power Laser System pulses will focus on Laser Driven Nuclear Physics (this TDR, acronym LDNP, associated to the E1 experimental area), High Field Physics and QED (associated to the E6 area) and fundamental research opened by the unique combination of the two 10 PW laser pulses with a gamma beam provided by the Gamma Beam System (associated to E7 area). The scientific case of the LDNP TDR encompasses studies of laser induced nuclear reactions, aiming for a better understanding of nuclear properties, of nuclear reaction rates in laser-plasmas, as well as on the development of radiation source characterization methods based on nuclear techniques. As an example of proposed studies: the promise of achieving solid-state density bunches of (very) heavy ions accelerated to about 10 MeV/nucleon through the RPA mechanism will be exploited to produce highly astrophysical relevant neutron rich nuclei around the N~126 waiting point, using the sequential fission-fusion scheme, complementary to any other existing or planned method of producing radioactive nuclei.

The studies will be implemented predominantly in the E1 area of ELI-NP. However, many of them can be, in a first stage, performed in the E5 and/or E4 areas, where higher repetition laser pulses are available, while the harsh X-ray and electromagnetic pulse (EMP) environments are less damaging compared to E1.

A number of options are discussed through the document, having an important impact on the budget and needed resources. Depending on the TDR review and subsequent project decisions, they may be taken into account for space reservation, while their detailed design and implementation will be postponed.

The present TDR is the result of contributions from several institutions engaged in nuclear physics and high power laser research. A significant part of the proposed equipment can be designed, and afterwards can be built, only in close collaboration with (or subcontracting to) some of these institutions. A Memorandum of Understanding (MOU) is currently under preparation with each of these key partners as well as with others that are interested to participate in the design or in the future experimental program.

Kernspektroskopie an N=40 und N=82 Nukliden

Der astrophysikalische r-Prozeß (schneller Neutroneneinfang), ist verantwortlich für die Nukleosynthese einer großen Zahl von Elementen, die schwerer als Eisen sind. Benutzt man das ''waiting-point''-Modell, so kann die Häufigkeitsverteilung der Elemente durch drei nukleare und drei stellare Input-Parameter beschrieben werden. Für einen gegebenen Satz von stellaren Parametern definiert die Neutronenseparationsenergie (Sn) den r-Prozeß-Pfad. Die beta-Zerfall-Halbwertszeit (T1/2) der Kerne im r-Prozeß-Pfad bestimmt die Häufigkeit des Vorläufers und bezieht man die Neutronenemissionswahrscheinlichkeit (Pn) mit ein, so auch die endgültige Häufigkeitsverteilung. Von besonderer Wichtigkeit sind die neutronenreichen ''waiting-point''-Isotope. Zum Beispiel sind die N=82 Isotope verantwortlich für den solaren A~130 Häufigkeits-Peak. Diese Arbeit befaßt sich mit der Identifizierung und der Untersuchung von Zerfallseigenschaften neutronenreicher Isotope des Mangan (A=61 bis 69) und Cadmium (A=130 bis 132). Neutronenreiche Nuklide zu erzeugen und zu detektieren ist ein komplizierter und zeitaufwendiger Prozeß, nichts desto trotz erfolgreich. Das Hauptproblem bei dieser Art von Experimenten ist der hohe isobare Untergrund. Aus diesem Grunde wurden speziell entwickelte Anregungsschemata für Mangan und Cadmium eingesetzt, um die gewünschten Isotope mittels Laser-Resonanzionisation chemisch selektiv zu ionisieren. Bei CERN/ISOLDE war es möglich im Massenbereich von 60^Mn bis 69^Mn neue Halbwertszeiten und Pn-Werte zu bestimmen. Für 64^Mn und 66^Mn konnten darüber hinaus erstmals noch partielle Zerfallsschemata aufgestellt werden. Es zeigte sich, daß die Ergebnisse teilweise recht überraschend waren, da sie nicht durch das QRPA-Modell vorhergesagt wurden. Mit Hilfe vergleichender Studien des Gesamttrends der Niveausystematiken der gg-Kerne von 26_Fe, 30_Zn, 32_Ge, 24_Cr und 28_Ni konnte ein Verschwinden der sphärischen N=40 Unterschale und die Existenz einer neuen Region mit signifikanter Deformation nachgewiesen werden, die vermutlich ihr ''Zentrum'' bei 64^Cr hat. Ebenfalls zeigen Studien der Niveausystematik bei 48Cd und der Vergleich mit 46_Pd, 54_Xe, 52_Te und 50_Sn, erste Hinweise eines Schalenquenchings bei N=82. Es wurde die Messung der Halbwertszeit von 130^Cd verbessert und die Halbwertszeiten von 131^Cd und 132^Cd erstmals bestimmt. Die neuen Daten können nur erklärt werden, wenn man bei der QRPA-Rechnung verbotene Übergänge mitberücksichtigt. Es genügt nicht, die Rechnung für reinen Gamow-Teller-Zerfall durchzuführen.

Visualization of oligonucleotide probes and point mutations in interphase nuclei and DNA fibers using rolling circle DNA amplification

Rolling circle amplification (RCA) is a surface-anchored DNA replication reaction that can be exploited to visualize single molecular recognition events. Here we report the use of RCA to visualize target DNA sequences as small as 50 nts in peripheral blood lymphocytes or in stretched DNA fibers. Three unique target sequences within the cystic fibrosis transmembrane conductance regulator gene could be detected simultaneously in interphase nuclei, and could be ordered in a linear map in stretched DNA. Allele-discriminating oligonucleotide probes in conjunction with RCA also were used to discriminate wild-type and mutant alleles in the cystic fibrosis transmembrane conductance regulator, p53, BRCA-1, and Gorlin syndrome genes in the nuclei of cultured cells or in DNA fibers. These observations demonstrate that signal amplification by RCA can be coupled to nucleic acid hybridization and multicolor fluorescence imaging to detect single nucleotide changes in DNA within a cytological context or in single DNA molecules. This provides a means for direct physical haplotyping and the analysis of somatic mutations on a cell-by-cell basis.

Landau-Zener problem with waiting at the minimum gap and related quench dynamics of a many-body system

We discuss a technique for solving the Landau-Zener (LZ) problem of finding the probability of excitation in a two-level system. The idea of time reversal for the Schrodinger equation is employed to obtain the state reached at the final time and hence the excitation probability. Using this method, which can reproduce the well-known expression for the LZ transition probability, we solve a variant of the LZ problem, which involves waiting at the minimum gap for a time t(w); we find an exact expression for the excitation probability as a function of t(w). We provide numerical results to support our analytical expressions. We then discuss the problem of waiting at the quantum critical point of a many-body system and calculate the residual energy generated by the time-dependent Hamiltonian. Finally, we discuss possible experimental realizations of this work.

Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

Thermal properties, sizes, and size distribution of Jupiter-family cometary nuclei

We present results from SEPPCoN, an on-going Survey of the Ensemble Physical Properties of Cometary Nuclei. In this report we discuss mid-infrared measurements of the thermal emission from 89 nuclei of Jupiter-family comets (JFCs). All data were obtained in 2006 and 2007 using imaging capabilities of the Spitzer Space Telescope. The comets were typically 4-5 AU from the Sun when observed and most showed only a point-source with little or no extended emission from dust. For those comets showing dust, we used image processing to photometrically extract the nuclei. For all 89 comets, we present new effective radii, and for 57 comets we present beaming parameters. Thus our survey provides the largest compilation of radiometrically-derived physical properties of nuclei to date. We have six main conclusions: (a) The average beaming parameter of the JFC population is 1.03 ± 0.11, consistent with unity; coupled with the large distance of the nuclei from the Sun, this indicates that most nuclei have Tempel 1-like thermal inertia. Only two of the 57 nuclei had outlying values (in a statistical sense) of infrared beaming. (b) The known JFC population is not complete even at 3 km radius, and even for comets that approach to ˜2 AU from the Sun and so ought to be more discoverable. Several recently-discovered comets in our survey have small perihelia and large (above ˜2 km) radii. (c) With our radii, we derive an independent estimate of the JFC nuclear cumulative size distribution (CSD), and we find that it has a power-law slope of around -1.9, with the exact value depending on the bounds in radius. (d) This power-law is close to that derived by others from visible-wavelength observations that assume a fixed geometric albedo, suggesting that there is no strong dependence of geometric albedo with radius. (e) The observed CSD shows a hint of structure with an excess of comets with radii 3-6 km. (f) Our CSD is consistent with the idea that the intrinsic size distribution of the JFC population is not a simple power-law and lacks many sub-kilometer objects.

A Hundred Comets: The Visual-Wavelength Observations of the Survey of Ensemble Physical Properties of Cometary Nuclei (SEPPCoN)

We present new results from SEPPCoN, a Survey of Ensemble Physical Properties of Cometary Nuclei. This project is currently surveying 100 Jupiter-family comets (JFCs) to measure the mid-infrared thermal emission and visible reflected sunlight of the nuclei. The scientific goal is to determine the distributions of radius, geometric albedo, thermal inertia, axial ratio, and color among the JFC nuclei. In the past we have presented results from the completed mid-IR observations of our sample [1]; here we present preliminary results from ongoing, broadband visible-wavelength observations of nuclei obtained from a variety of ground-based facilities (Mauna Kea, Cerro Pachon, La Silla, La Palma, Apache Point, Table Mtn., and Palomar Mtn.), including contributions from the Near Earth Asteroid Telescope project (NEAT) archive. The nuclei were observed at high heliocentric distance (usually over 4 AU) and so many comets show either no or little contamination from dust coma. While several nuclei have been observed as snapshots, we have multiepoch photometry for many of our targets. With our datasets we are building a large database of photometry, and such a database is essential to the derivation of albedo and shape of a large number of nuclei, and to the understanding of biases in the survey. Support for this work was provided by NSF and the NASA Planetary Astronomy program. Reference: [1] Fernandez, Y.R., et al. 2007, BAAS 39, 827.

Small- and waiting-time behaviour of the thin-film-equation

We consider the small-time behavior of interfaces of zero contact angle solutions to the thin-film equation. For a certain class of initial data, through asymptotic analyses, we deduce a wide variety of behavior for the free boundary point. These are supported by extensive numerical simulations. © 2007 Society for Industrial and Applied Mathematics

A moving point approach to model shallow ice sheets: a study case with radially-symmetrical ice sheets

Predicting the evolution of ice sheets requires numerical models able to accurately track the migration of ice sheet continental margins or grounding lines. We introduce a physically based moving point approach for the flow of ice sheets based on the conservation of local masses. This allows the ice sheet margins to be tracked explicitly and the waiting time behaviours to be modelled efficiently. A finite difference moving point scheme is derived and applied in a simplified context (continental radially-symmetrical shallow ice approximation). The scheme, which is inexpensive, is validated by comparing the results with moving-margin exact solutions and steady states. In both cases the scheme is able to track the position of the ice sheet margin with high precision.

A moving-point approach to model shallow ice sheets: a study case with radially symmetrical ice sheets

Predicting the evolution of ice sheets requires numerical models able to accurately track the migration of ice sheet continental margins or grounding lines. We introduce a physically based moving-point approach for the flow of ice sheets based on the conservation of local masses. This allows the ice sheet margins to be tracked explicitly. Our approach is also well suited to capture waiting-time behaviour efficiently. A finite-difference moving-point scheme is derived and applied in a simplified context (continental radially symmetrical shallow ice approximation). The scheme, which is inexpensive, is verified by comparing the results with steady states obtained from an analytic solution and with exact moving-margin transient solutions. In both cases the scheme is able to track the position of the ice sheet margin with high accuracy.

A Psychoanalytic Reading of Vladimir and Estragon in Samuel Beckett’s Waiting for Godot

Much has been written about Samuel Beckett’s Waiting for Godot, but as far as I am aware no one has compared the two characters of Vladimir and Estragon in order to analyse what makes Vladimir more willing to wait than Estragon. This essay claims that Vladimir is more willing to wait because he cannot deal with the fact that they might be waiting in vain and he involves himself more in his surrounding than Estragon. It is Vladimir who waits for Godot, not Estragon, and Vladimir believes that Godot will have all the answers. This will be explored by examining four topics, all of which will be dealt with from a psychoanalytical point of view and in relation to waiting. Consciousness in relation to the decision to wait; Uncertainty in relation to the unknown outcome of waiting; Coping mechanisms in relation to ways of dealing with waiting; Ways of waiting in relation to waiting-time and two kinds of waiting-characters.

Spatial characteristics of borromean, tango, samba and all-bound halo nuclei

We report a renormalized zero-range interaction approach to estimate the size of generic weakly bound three-body systems where two particles are identical. We present results for the neutron-neutron root-mean-square distances of the halo nuclei 6He, 11Li, 14Be and 20C, where the systems are taken as two halo neutrons with an inert point-like core. We also report an approach to obtain the neutron-neutron correlation function in halo nuclei. In this case, our results suggest a review of the corresponding experimental data analysis. © 2007 American Institute of Physics.