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Elliptic flow from nuclear collisions is a hadronic observable sensitive to the early stages of system evolution. We report first results on elliptic flow of charged particles at midrapidity in Au+Au collisions at sqrt[sNN] = 130 GeV using the STAR Time Projection Chamber at the Relativistic Heavy Ion Collider. The elliptic flow signal, v2, averaged over transverse momentum, reaches values of about 6% for relatively peripheral collisions and decreases for the more central collisions. This can be interpreted as the observation of a higher degree of thermalization than at lower collision energies. Pseudorapidity and transverse momentum dependence of elliptic flow are also presented.
We present the results of two-pion production in tagged quasi-free np collisions at a deutron incident beam energy of 1.25 GeV/c measured with the High-Acceptance Di-Electron Spectrometer (HADES) installed at GSI. The specific acceptance of HADES allowed for the first time to obtain high-precision data on π+π− and π−π0 production in np collisions in a region corresponding to large transverse momenta of the secondary particles. The obtained differential cross section data provide strong constraints on the production mechanisms and on the various baryon resonance contributions (∆∆, N(1440), N(1520), ∆(1600)). The invariant mass and angular distributions from the np → npπ+π −and np → ppπ−π0 reactions are compared with different theoretical model predictions.
Subvisible cirrus clouds (SVCs) may contribute to dehydration close to the tropical tropopause. The higher and colder SVCs and the larger their ice crystals, the more likely they represent the last efficient point of contact of the gas phase with the ice phase and, hence, the last dehydrating step, before the air enters the stratosphere. The first simultaneous in situ and remote sensing measurements of SVCs were taken during the APE-THESEO campaign in the western Indian ocean in February/March 1999. The observed clouds, termed Ultrathin Tropical Tropopause Clouds (UTTCs), belong to the geometrically and optically thinnest large-scale clouds in the Earth's atmosphere. Individual UTTCs may exist for many hours as an only 200–300 m thick cloud layer just a few hundred meters below the tropical cold point tropopause, covering up to 105 km2. With temperatures as low as 181 K these clouds are prime representatives for defining the water mixing ratio of air entering the lower stratosphere.
Mechanisms by which subvisible cirrus clouds (SVCs) might contribute to dehydration close to the tropical tropopause are not well understood. Recently Ultrathin Tropical Tropopause Clouds (UTTCs) with optical depths around 10−4 have been detected in the western Indian ocean. These clouds cover thousands of square kilometers as 200–300 m thick distinct and homogeneous layer just below the tropical tropopause. In their condensed phase UTTCs contain only 1–5% of the total water, and essentially no nitric acid. A new cloud stabilization mechanism is required to explain this small fraction of the condensed water content in the clouds and their small vertical thickness. This work suggests a mechanism, which forces the particles into a thin layer, based on upwelling of the air of some mm/s to balance the ice particles, supersaturation with respect to ice above and subsaturation below the UTTC. In situ measurements suggest that these requirements are fulfilled. The basic physical properties of this mechanism are explored by means of a single particle model. Comprehensive 1-D cloud simulations demonstrate this stabilization mechanism to be robust against rapid temperature fluctuations of +/−0.5 K. However, rapid warming (ΔT>2 K) leads to evaporation of the UTTC, while rapid cooling (ΔT<−2 K) leads to destabilization of the particles with the potential for significant dehydration below the cloud.
Electroencephalography (EEG) represents a widely established method for assessing altered and typically developing brain function. However, systematic studies on EEG data quality, its correlates, and consequences are scarce. To address this research gap, the current study focused on the percentage of artifact-free segments after standard EEG pre-processing as a data quality index. We analyzed participant-related and methodological influences, and validity by replicating landmark EEG effects. Further, effects of data quality on spectral power analyses beyond participant-related characteristics were explored. EEG data from a multicenter ADHD-cohort (age range 6 to 45 years), and a non-ADHD school-age control group were analyzed (ntotal = 305). Resting-state data during eyes open, and eyes closed conditions, and task-related data during a cued Continuous Performance Task (CPT) were collected. After pre-processing, general linear models, and stepwise regression models were fitted to the data. We found that EEG data quality was strongly related to demographic characteristics, but not to methodological factors. We were able to replicate maturational, task, and ADHD effects reported in the EEG literature, establishing a link with EEG-landmark effects. Furthermore, we showed that poor data quality significantly increases spectral power beyond effects of maturation and symptom severity. Taken together, the current results indicate that with a careful design and systematic quality control, informative large-scale multicenter trials characterizing neurophysiological mechanisms in neurodevelopmental disorders across the lifespan are feasible. Nevertheless, results are restricted to the limitations reported. Future work will clarify predictive value.
Elliptic flow from nuclear collisions is a hadronic observable sensitive to the early stages of system evolution. We report first results on elliptic flow of charged particles at midrapidity in Au+Au collisions at sqrt(s_NN)=130 GeV using the STAR TPC at RHIC. The elliptic flow signal, v_2, averaged over transverse momentum, reaches values of about 6% for relatively peripheral collisions and decreases for the more central collisions. This can be interpreted as the observation of a higher degree of thermalization than at lower collision energies. Pseudorapidity and transverse momentum dependence of elliptic flow are also presented.
Subvisible cirrus clouds (SVCs) may contribute to dehydration close to the tropical tropopause. The higher and colder SVCs and the larger their ice crystals, the more likely they represent the last efficient point of contact of the gas phase with the ice phase and, hence, the last dehydrating step, before the air enters the stratosphere. The first simultaneous in situ and remote sensing measurements of SVCs were taken during the APE-THESEO campaign in the western Indian ocean in February/March 1999. The observed clouds, termed Ultrathin Tropical Tropopause Clouds (UTTCs), belong to the geometrically and optically thinnest large-scale clouds in the Earth´s atmosphere. Individual UTTCs may exist for many hours as an only 200--300 m thick cloud layer just a few hundred meters below the tropical cold point tropopause, covering up to 105 km2. With temperatures as low as 181 K these clouds are prime representatives for defining the water mixing ratio of air entering the lower stratosphere.
Mechanisms by which subvisible cirrus clouds (SVCs) might contribute to dehydration close to the tropical tropopause are not well understood. Recently Ultrathin Tropical Tropopause Clouds (UTTCs) with optical depths around 10-4 have been detected in the western Indian ocean. These clouds cover thousands of square kilometers as 200-300 m thick distinct and homogeneous layer just below the tropical tropopause. In their condensed phase UTTCs contain only 1-5% of the total water, and essentially no nitric acid. A new cloud stabilization mechanism is required to explain this small fraction of the condensed water content in the clouds and their small vertical thickness. This work suggests a mechanism, which forces the particles into a thin layer, based on upwelling of the air of some mm/s to balance the ice particles, supersaturation with respect to ice above and subsaturation below the UTTC. In situ measurements suggest that these requirements are fulfilled. The basic physical properties of this mechanism are explored by means of a single particle model. Comprehensive 1-D cloud simulations demonstrate this stabilization mechanism to be robust against rapid temperature fluctuations of +/- 0.5 K. However, rapid warming (Delta T > 2 K) leads to evaporation of the UTTC, while rapid cooling (Delta T < -2 K) leads to destabilization of the particles with the potential for significant dehydration below the cloud
Background: Germinal center-derived B cell lymphomas are tumors of the lymphoid tissues representing one of the most heterogeneous malignancies. Here we characterize the variety of transcriptomic phenotypes of this disease based on 873 biopsy specimens collected in the German Cancer Aid MMML (Molecular Mechanisms in Malignant Lymphoma) consortium. They include diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt’s lymphoma, mixed FL/DLBCL lymphomas, primary mediastinal large B cell lymphoma, multiple myeloma, IRF4-rearranged large cell lymphoma, MYC-negative Burkitt-like lymphoma with chr. 11q aberration and mantle cell lymphoma.
Methods: We apply self-organizing map (SOM) machine learning to microarray-derived expression data to generate a holistic view on the transcriptome landscape of lymphomas, to describe the multidimensional nature of gene regulation and to pursue a modular view on co-expression. Expression data were complemented by pathological, genetic and clinical characteristics.
Results: We present a transcriptome map of B cell lymphomas that allows visual comparison between the SOM portraits of different lymphoma strata and individual cases. It decomposes into one dozen modules of co-expressed genes related to different functional categories, to genetic defects and to the pathogenesis of lymphomas. On a molecular level, this disease rather forms a continuum of expression states than clearly separated phenotypes. We introduced the concept of combinatorial pattern types (PATs) that stratifies the lymphomas into nine PAT groups and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma signatures. Inflammation signatures in combination with healthy B cell and tonsil characteristics associate with better overall survival rates, while proliferation in combination with inflammation and plasma cell characteristics worsens it. A phenotypic similarity tree is presented that reveals possible progression paths along the transcriptional dimensions. Our analysis provided a novel look on the transition range between FL and DLBCL, on DLBCL with poor prognosis showing expression patterns resembling that of Burkitt’s lymphoma and particularly on "double-hit" MYC and BCL2 transformed lymphomas.
Conclusions: The transcriptome map provides a tool that aggregates, refines and visualizes the data collected in the MMML study and interprets them in the light of previous knowledge to provide orientation and support in current and future studies on lymphomas and on other cancer entities.