Study of the reaction e^{+}e^{-} -->J/psi\pi^{+}\pi^{-} via initial-state radiation at BaBar

We study the process $e^+e^-\to J/\psi\pi^{+}\pi^{-}$ with initial-state-radiation events produced at the PEP-II asymmetric-energy collider. The data were recorded with the BaBar detector at center-of-mass energies 10.58 and 10.54 GeV, and correspond to an integrated luminosity of 454 $\mathrm{fb^{-1}}$. We investigate the $J/\psi \pi^{+}\pi^{-}$ mass distribution in the region from 3.5 to 5.5 $\mathrm{GeV/c^{2}}$. Below 3.7 $\mathrm{GeV/c^{2}}$ the $\psi(2S)$ signal dominates, and above 4 $\mathrm{GeV/c^{2}}$ there is a significant peak due to the Y(4260). A fit to the data in the range 3.74 -- 5.50 $\mathrm{GeV/c^{2}}$ yields a mass value $4244 \pm 5$ (stat) $\pm 4$ (syst)$\mathrm{MeV/c^{2}}$ and a width value $114 ^{+16}_{-15}$ (stat)$\pm 7$(syst)$\mathrm{MeV}$ for this state. We do not confirm the report from the Belle collaboration of a broad structure at 4.01 $\mathrm{GeV/c^{2}}$. In addition, we investigate the $\pi^{+}\pi^{-}$ system which results from Y(4260) decay

Seismic human loss estimation for an earthquake disaster using neural network

In Iran, earthquakes cause enormous damage to the people and economy. If there is a proper estimation of human losses in an earthquake disaster, it could be appropriately responded and its impacts and losses will be decreased. Neural networks can be trained to solve problems involving imprecise and highly complex nonlinear data. Based on the different earthquake scenarios and diverse kind of constructions, it is difficult to estimate the number of injured people. With respect to neural network's capabilities, this paper describes a back propagation neural network method for modeling and estimating the severity and distribution of human loss as a function of building damage in the earthquake disaster. Bam earthquake data in 2003 were used to train this neural network. The final results demonstrate that this neural network model can reveal much more accurate estimation of fatalities and injuries for different earthquakes in Iran and it can provide the necessary information required to develop realistic mitigation policies, especially in rescue operation

Transcutaneous flow related variables measured in vivo: the effects of gender

BACKGOUND: The identification of potential sources of error is a crucial step for any new assessment technique. This is the case for transcutaneous variables, such as flow and arterial gases, which have been applied as functional indicators of various aspects of human health. Regarding gender, a particular subject-related determinant, it is often claimed that women present higher transcutaneous oxygen pressure (tcpO(2)) values than men. However, the statistical significance of this finding is still uncertain. METHODS: The haemodynamical-vascular response to a local reactive hyperaemia procedure (the tourniquet cuff manoeuvre) was studied in two previously selected group of volunteers (n = 16; 8 women and 8 men). The effect of gender was assessed under standardised experimental conditions, using the transcutaneous flow-related variables tcpO(2)-tcpCO(2) and Laser-doppler Flowmetry (LDF). RESULTS: Regarding tcpO(2), statistically significant differences between genders were not found, although higher values were consistently found for the gases in the female group. Regarding LDF, high statistically significant differences (p < 0.005) were found, with the men's group presenting the highest values and variability. Other derived parameters used to characterise the vascular response following the cuff-deflation (t-peak) were similar in both groups. CONCLUSIONS: The relative influence of gender was not clearly demonstrated using these experimental conditions. However the gender-related LDF differences suggest that further investigation should be done on this issue. Perhaps in the presence of certain pathological disparities involving peripheral vascular regulation, other relationships may be found between these variables

Light-Induced Responses of Slow Oscillatory Neurons of the Rat Olivary Pretectal Nucleus

Background: The olivary pretectal nucleus (OPN) is a small midbrain structure responsible for pupil constriction in response to eye illumination. Previous electrophysiological studies have shown that OPN neurons code light intensity levels and therefore are called luminance detectors. Recently, we described an additional population of OPN neurons, characterized by a slow rhythmic pattern of action potentials in light-on conditions. Rhythmic patterns generated by these cells last for a period of approximately 2 minutes. Methodology: To answer whether oscillatory OPN cells are light responsive and whether oscillatory activity depends on retinal afferents, we performed in vivo electrophysiology experiments on urethane anaesthetized Wistar rats. Extracellular recordings were combined with changes in light conditions (light-dark-light transitions), brief light stimulations of the contralateral eye (diverse illuminances) or intraocular injections of tetrodotoxin (TTX). Conclusions: We found that oscillatory neurons were able to fire rhythmically in darkness and were responsive to eye illumination in a manner resembling that of luminance detectors. Their firing rate increased together with the strength of the light stimulation. In addition, during the train of light pulses, we observed two profiles of responses: oscillationpreserving and oscillation-disrupting, which occurred during low- and high-illuminance stimuli presentation respectively. Moreover, we have shown that contralateral retina inactivation eliminated oscillation and significantly reduced the firin

Recent Advances in Our Understanding of the Role of Meltwater in the Greenland Ice Sheet System

Nienow, Sole and Cowton’s Greenland research has been supported by a number of UK NERC research grants (NER/O/S/2003/00620; NE/F021399/1; NE/H024964/1; NE/K015249/1; NE/K014609/1) and Slater has been supported by a NERC PhD studentshipPurpose of the review:  This review discusses the role that meltwater plays within the Greenland ice sheet system. The ice sheet’s hydrology is important because it affects mass balance through its impact on meltwater runoff processes and ice dynamics. The review considers recent advances in our understanding of the storage and routing of water through the supraglacial, englacial, and subglacial components of the system and their implications for the ice sheet Recent findings:   There have been dramatic increases in surface meltwater generation and runoff since the early 1990s, both due to increased air temperatures and decreasing surface albedo. Processes in the subglacial drainage system have similarities to valley glaciers and in a warming climate, the efficiency of meltwater routing to the ice sheet margin is likely to increase. The behaviour of the subglacial drainage system appears to limit the impact of increased surface melt on annual rates of ice motion, in sections of the ice sheet that terminate on land, while the large volumes of meltwater routed subglacially deliver significant volumes of sediment and nutrients to downstream ecosystems. Summary:  Considerable advances have been made recently in our understanding of Greenland ice sheet hydrology and its wider influences. Nevertheless, critical gaps persist both in our understanding of hydrology-dynamics coupling, notably at tidewater glaciers, and in runoff processes which ensure that projecting Greenland’s future mass balance remains challenging.Publisher PDFPeer reviewe

Causes and consequences of cerebral small vessel disease. The RUN DMC study: a prospective cohort study. Study rationale and protocol

Contains fulltext : 96704.pdf (publisher's version ) (Open Access)BACKGROUND: Cerebral small vessel disease (SVD) is a frequent finding on CT and MRI scans of elderly people and is related to vascular risk factors and cognitive and motor impairment, ultimately leading to dementia or parkinsonism in some. In general, the relations are weak, and not all subjects with SVD become demented or get parkinsonism. This might be explained by the diversity of underlying pathology of both white matter lesions (WML) and the normal appearing white matter (NAWM). Both cannot be properly appreciated with conventional MRI. Diffusion tensor imaging (DTI) provides alternative information on microstructural white matter integrity. The association between SVD, its microstructural integrity, and incident dementia and parkinsonism has never been investigated. METHODS/DESIGN: The RUN DMC study is a prospective cohort study on the risk factors and cognitive and motor consequences of brain changes among 503 non-demented elderly, aged between 50-85 years, with cerebral SVD. First follow up is being prepared for July 2011. Participants alive will be included and invited to the research centre to undergo a structured questionnaire on demographics and vascular risk factors, and a cognitive, and motor, assessment, followed by a MRI protocol including conventional MRI, DTI and resting state fMRI. DISCUSSION: The follow up of the RUN DMC study has the potential to further unravel the causes and possibly better predict the consequences of changes in white matter integrity in elderly with SVD by using relatively new imaging techniques. When proven, these changes might function as a surrogate endpoint for cognitive and motor function in future therapeutic trials. Our data could furthermore provide a better understanding of the pathophysiology of cognitive and motor disturbances in elderly with SVD. The execution and completion of the follow up of our study might ultimately unravel the role of SVD on the microstructural integrity of the white matter in the transition from "normal" aging to cognitive and motor decline and impairment and eventually to incident dementia and parkinsonism

Functional Brain Networks Develop from a “Local to Distributed” Organization

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward ‘segregation’ (a general decrease in correlation strength) between regions close in anatomical space and ‘integration’ (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more “distributed” architecture in young adults. We argue that this “local to distributed” developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing “small-world”-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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