Spin-rotor Interpretation of Identical Bands and Quantized Alignment in Superdeformed A ≈\approx 190 Nuclei

The ``identical'' bands in superdeformed mercury, thallium, and lead nuclei are interpreted as examples of orbital angular momentum rotors with the weak spin-orbit coupling of pseudo-$SU(3)$ symmetries and supersymmetries.Comment: 15 pages, revtex 3.0, 7 figures available upon request from [email protected]

Dimensional Crossover in the Large N Limit

We consider dimensional crossover for an $O(N)$ Landau-Ginzburg-Wilson model on a $d$-dimensional film geometry of thickness $L$ in the large $N$-limit. We calculate the full universal crossover scaling forms for the free energy and the equation of state. We compare the results obtained using ``environmentally friendly'' renormalization with those found using a direct, non-renormalization group approach. A set of effective critical exponents are calculated and scaling laws for these exponents are shown to hold exactly, thereby yielding non-trivial relations between the various thermodynamic scaling functions.Comment: 25 pages of PlainTe

An Integrated Approach for Characterizing Aerosol Climate Impacts and Environmental Interactions

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality

Constraining cloud lifetime effects of aerosols using A‐Train satellite observations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95434/1/grl29404.pd

Accelerating Innovation in the Creation of Biovalue : The Cell and Gene Therapy Catapult

The field of regenerative medicine (RM) has considerable therapeutic promise that is proving difficult to realize. As a result, governments have supported the establishment of intermediary agencies to “accelerate” innovation. This paper examines in detail one such agency, the UK's Cell and Gene Therapy Catapult (CGTC). We describe CGTC’s role as an accelerator agency and its value-narrative, which combines both “health and wealth.” Drawing on the notion of socio-technical imaginaries, we unpack the tensions within this narrative and its instantiation as the CGTC cell therapy infrastructure is built and engages with other agencies, some of which have different priorities and roles to play within the RM field

The Relationship Between IQ, Memory, Executive Function, and Processing Speed in Recent-Onset Psychosis: 1-Year Stability and Clinical Outcome

Studies commonly report poor performance in psychotic patients compared with controls on tasks testing a range of cognitive functions, but, because current IQ is often not matched between these groups, it is difficult to determine whether this represents a generalized deficit or specific abnormalities. Fifty-three first-episode psychosis patients and 53 healthy controls, one-to-one matched for sex, age, and full-scale current IQ, were compared on Wechsler Adult Intelligence Scale (WAIS) subtests representing indices of perceptual organization, verbal comprehension, processing speed, and working memory as well as other tests of executive function and episodic memory. The groups showed an equivalent pattern of performance on all WAIS subtests except digit symbol processing speed, on which the patients were significantly worse. Patients were also worse on measures where performance correlated with digit symbol score, namely working and verbal memory tasks. Standardized residual scores for each subtest were calculated for each patient using the difference between their actual subtest score and a predicted subtest score based on their full-scale IQ and the performance of controls. Scaled scores and residual scores were examined for relationships with clinical measures. Digit symbol–scaled score was significantly correlated with concurrent negative syndrome score at baseline, and digit symbol residual score significantly predicted residual negative symptoms at 1-year follow-up. In summary, our comparison of patients and controls precisely matched for IQ revealed that processing speed was attenuated in recent-onset schizophrenia, contributed significantly to working and episodic memory deficits, and was a prognostic factor for poor outcome at 1 year

Data-driven analysis of immune infiltrate in a large cohort of breast cancer and its association with disease progression, ER activity, and genomic complexity.

The tumor microenvironment is now widely recognized for its role in tumor progression, treatment response, and clinical outcome. The intratumoral immunological landscape, in particular, has been shown to exert both pro-tumorigenic and anti-tumorigenic effects. Identifying immunologically active or silent tumors may be an important indication for administration of therapy, and detecting early infiltration patterns may uncover factors that contribute to early risk. Thus far, direct detailed studies of the cell composition of tumor infiltration have been limited; with some studies giving approximate quantifications using immunohistochemistry and other small studies obtaining detailed measurements by isolating cells from excised tumors and sorting them using flow cytometry. Herein we utilize a machine learning based approach to identify lymphocyte markers with which we can quantify the presence of B cells, cytotoxic T-lymphocytes, T-helper 1, and T-helper 2 cells in any gene expression data set and apply it to studies of breast tissue. By leveraging over 2,100 samples from existing large scale studies, we are able to find an inherent cell heterogeneity in clinically characterized immune infiltrates, a strong link between estrogen receptor activity and infiltration in normal and tumor tissues, changes with genomic complexity, and identify characteristic differences in lymphocyte expression among molecular groupings. With our extendable methodology for capturing cell type specific signal we systematically studied immune infiltration in breast cancer, finding an inverse correlation between beneficial lymphocyte infiltration and estrogen receptor activity in normal breast tissue and reduced infiltration in estrogen receptor negative tumors with high genomic complexity

A seamless assessment of the role of convection in the water cycle of the West African Monsoon

A suite of 40 day UK Met Office Unified Model simulations over West Africa during summer 2006 are analyzed to investigate the causes of biases in the position of the rainbelt and to understand the role of convection in the regional water budget. The simulations include climate, global operational, and limited area runs (grid spacings from 1.5 to 40 km), including two 12 km runs, one with parameterized and one with explicit convection. The most significant errors in the water cycle terms occur in the simulations with parameterized convection, associated with the diurnal cycle and the location of the convection. Errors in the diurnal cycle increase the northward advection of moisture out of the Sahel toward the Sahara but decrease the advection of moisture into the Sahel from further south, which limits the availability of moisture for Sahelian rainfall. These biases occur within the first 24 h, showing that they originate from the representation of fast physical processes, specifically, the convection scheme. Once these rainfall regimes have been established, the terms of the water budgets act to reinforce the biases, effectively locking the rainbelt's latitude. One of the simulations with parameterized convection does, however, produce a better latitudinal distribution of rainfall because on the first day it is better able to trigger convection in the Sahel. Accurate representation of the diurnal cycle of convection and the ability to trigger convection in a high convective inhibition environment is key to capturing the water cycle of the region and will improve the representation of the West African Monsoon

Sea-breeze dynamics and convection initiation: the influence of convective parameterization in weather and climate model biases

There are some long-established biases in atmospheric models that originate from the representation of tropical convection. Previously, it has been difficult to separate cause and effect because errors are often the result of a number of interacting biases. Recently, researchers have gained the ability to run multiyear global climate model simulations with grid spacings small enough to switch the convective parameterization off, which permits the convection to develop explicitly. There are clear improvements to the initiation of convective storms and the diurnal cycle of rainfall in the convection-permitting simulations, which enables a new process-study approach to model bias identification. In this study, multiyear global atmosphere-only climate simulations with and without convective parameterization are undertaken with the Met Office Unified Model and are analyzed over the Maritime Continent region, where convergence from sea-breeze circulations is key for convection initiation. The analysis shows that, although the simulation with parameterized convection is able to reproduce the key rain-forming sea-breeze circulation, the parameterization is not able to respond realistically to the circulation. A feedback of errors also occurs: the convective parameterization causes rain to fall in the early morning, which cools and wets the boundary layer, reducing the land–sea temperature contrast and weakening the sea breeze. This is, however, an effect of the convective bias, rather than a cause of it. Improvements to how and when convection schemes trigger convection will improve both the timing and location of tropical rainfall and representation of sea-breeze circulations