LANDSAT survey of near-shore ice conditions along the Arctic coast of Alaska

The author has identified the following significant results. Winter and spring near-shore ice conditions were analyzed for the Beaufort Sea 1973-77, and the Chukchi Sea 1973-76. LANDSAT imagery was utilized to map major ice features related to regional ice morphology. Significant features from individual LANDSAT image maps were combined to yield regional maps of major ice ridge systems for each year of study and maps of flaw lead systems for representative seasons during each year. These regional maps were, in turn, used to prepare seasonal ice morphology maps. These maps showed, in terms of a zonal analysis, regions of statistically uniform ice behavior. The behavioral characteristics of each zone were described in terms of coastal processes and bathymetric configuration

Measurement of Inclusive W and Z Boson Production Cross Sections in pp Collisions at s√=8 TeV

A measurement of total and fiducial inclusive W and Z boson production cross sections in pp collisions at s√=8  TeV is presented. Electron and muon final states are analyzed in a data sample collected with the CMS detector corresponding to an integrated luminosity of 18.2±0.5  pb−1. The measured total inclusive cross sections times branching fractions are σ(pp→WX)×B(W→ℓν)=12.21±0.03(stat)±0.24(syst)±0.32(lum)  nb and σ(pp→ZX)×B(Z→ℓ+ℓ−)=1.15±0.01(stat)±0.02(syst)±0.03(lum)  nb for the dilepton mass in the range of 60—120 GeV. The measured values agree with next-to-next-to-leading-order QCD cross section calculations. Ratios of cross sections are reported with a precision of 2%. This is the first measurement of inclusive W and Z boson production in proton-proton collisions at s√=8  TeV

Resting state connectivity and cognitive performance in adults with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy

Cognitive impairment is an inevitable feature of cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), affecting executive function, attention and processing speed from an early stage. Impairment is associated with structural markers such as lacunes, but associations with functional connectivity have not yet been reported. Twenty-two adults with genetically-confirmed CADASIL (11 male; aged 49.8 ± 11.2 years) underwent functional magnetic resonance imaging at rest. Intrinsic attentional/executive networks were identified using group independent components analysis. A linear regression model tested voxel-wise associations between cognitive measures and component spatial maps, and Pearson correlations were performed with mean intra-component connectivity z-scores. Two frontoparietal components were associated with cognitive performance. Voxel-wise analyses showed an association between one component cluster and processing speed (left middle temporal gyrus; peak −48, −18, −14; ZE = 5.65, pFWEcorr = 0.001). Mean connectivity in both components correlated with processing speed (r = 0.45, p = 0.043; r = 0.56, p = 0.008). Mean connectivity in one component correlated with faster Trailmaking B minus A time (r = −0.77, p < 0.001) and better executive performance (r = 0.56, p = 0.011). This preliminary study provides evidence for associations between cognitive performance and attentional network connectivity in CADASIL. Functional connectivity may be a useful biomarker of cognitive performance in this population

A mixed-method process evaluation of an East Midlands county summer 2021 holiday activities and food programme highlighting the views of programme co-ordinators, providers, and parents

BACKGROUND: The Holiday Activities and Food (HAF) Programme is a UK Government initiative created to alleviate food insecurity and promote health and well-being among children and their families, who are eligible for Free School Meals (FSM), during the school holidays. This process evaluation investigated factors that facilitated and acted as a barrier to the delivery of the HAF Programme from the perspectives of key stakeholders (Co-ordinators, Providers, and Parents) involved in the HAF Programme across an East Midlands county. METHODS: This evaluation utilized a mixed-methods approach, incorporating focus groups and online surveys to gain rich, multifaceted data. The focus groups were analyzed using a hybrid inductive-deductive thematic analysis and the online surveys were analyzed using mixed-methods approach due to the variation in question type (i.e., quantitative, Likert scale and open response) to align themes to the Government Aims and Standards of the HAF Programme. FINDINGS: The stakeholders highlighted several factors that facilitated and acted as a barrier to the delivery of the HAF Programme. Facilitating factors included existing and maintaining relationships between Co-ordinators, Providers, and facilities/schools/communities as this improved communication and attendance. Additionally, transport provision for those attending the Programme helped overcome barriers to attendance. The primary barrier of the Programme was the late awarding of the Programme contract as this limited the time available to prepare and organize the Programme. This in turn, had several “knock on” effects that created more barriers and resulted in some of the Government Aims and Standards not being met such as, nutrition education for children and parents. Despite the challenges faced, Co-ordinators and Providers were able to deliver the Programme and positively impact upon the children and their families that attended the Programme. CONCLUSION: Following the facilitators and barriers that were highlighted in this evaluation, several recommendations have been made to enhance the delivery of the HAF Programme and ensure Government Aims and Standards, to improve children and family's health and well-being, are attained

The Challenge of Machine Learning in Space Weather Nowcasting and Forecasting

The numerous recent breakthroughs in machine learning (ML) make imperative to carefully ponder how the scientific community can benefit from a technology that, although not necessarily new, is today living its golden age. This Grand Challenge review paper is focused on the present and future role of machine learning in space weather. The purpose is twofold. On one hand, we will discuss previous works that use ML for space weather forecasting, focusing in particular on the few areas that have seen most activity: the forecasting of geomagnetic indices, of relativistic electrons at geosynchronous orbits, of solar flares occurrence, of coronal mass ejection propagation time, and of solar wind speed. On the other hand, this paper serves as a gentle introduction to the field of machine learning tailored to the space weather community and as a pointer to a number of open challenges that we believe the community should undertake in the next decade. The recurring themes throughout the review are the need to shift our forecasting paradigm to a probabilistic approach focused on the reliable assessment of uncertainties, and the combination of physics-based and machine learning approaches, known as gray-box.Comment: under revie

The purpose of mess in action research: building rigour though a messy turn

Mess and rigour might appear to be strange bedfellows. This paper argues that the purpose of mess is to facilitate a turn towards new constructions of knowing that lead to transformation in practice (an action turn). Engaging in action research - research that can disturb both individual and communally held notions of knowledge for practice - will be messy. Investigations into the 'messy area', the interface between the known and the nearly known, between knowledge in use and tacit knowledge as yet to be useful, reveal the 'messy area' as a vital element for seeing, disrupting, analysing, learning, knowing and changing. It is the place where long-held views shaped by professional knowledge, practical judgement, experience and intuition are seen through other lenses. It is here that reframing takes place and new knowing, which has both theoretical and practical significance, arises: a 'messy turn' takes place

Measurement of the hadronic activity in events with a Z and two jets and extraction of the cross section for the electroweak production of a Z with two jets in pp collisions at s√=7 TeV

This is the publisher's version, also available electronically from http://link.springer.com/article/10.1007%2FJHEP10%282013%29062.The first measurement of the electroweak production cross section of a Z boson with two jets (Zjj) in pp collisions at s√=7 TeV is presented, based on a data sample recorded by the CMS experiment at the LHC with an integrated luminosity of 5 fb(−1). The cross section is measured for the ℓℓjj (ℓ = e, μ) final state in the kinematic region m(ℓℓ) > 50 GeV, m(jj) > 120 GeV, transverse momenta p(j)(T)>25 GeV and pseudorapidity |η(j)| < 4.0. The measurement, combining the muon and electron channels, yields σ = 154 ± 24 (stat.) ± 46 (exp. syst.) ± 27 (th. syst.) ± 3 (lum.) fb, in agreement with the theoretical cross section. The hadronic activity, in the rapidity interval between the jets, is also measured. These results establish an important foundation for the more general study of vector boson fusion processes, of relevance for Higgs boson searches and for measurements of electroweak gauge couplings and vector boson scattering

EphA2 as a Diagnostic Imaging Target in Glioblastoma: A Positron Emission Tomography/Magnetic Resonance Imaging Study

Noninvasive imaging is a critical technology for diagnosis, classification, and subsequent treatment planning for patients with glioblastoma. It has been shown that the EphA2 receptor tyrosine kinase (RTK) is overexpressed in a number of tumors, including glioblastoma. Expression levels of Eph RTKs have been linked to tumor progression, metastatic spread, and poor patient prognosis. As EphA2 is expressed at low levels in normal neural tissues, this protein represents an attractive imaging target for delineation of tumor infiltration, providing an improved platform for image-guided therapy. In this study, EphA2-4B3, a monoclonal antibody specific to human EphA2, was labeled with Cu-64 through conjugation to the chelator 1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA). The resulting complex was used as a positron emission tomography (PET) tracer for the acquisition of high-resolution longitudinal PET/magnetic resonance images. EphA2-4B3-NOTA-Cu-64 images were qualitatively and quantitatively compared to the current clinical standards of [F-18] FDOPA and gadolinium (Gd) contrast-enhanced MRI. We show that EphA2-4B3-NOTA-Cu-64 effectively delineates tumor boundaries in three different mouse models of glioblastoma. Tumor to brain contrast is significantly higher in EphA2-4B3-NOTA-Cu-64 images than in [F-18] FDOPA images and Gd contrast-enhanced MRI. Furthermore, we show that nonspecific uptake in the liver and spleen can be effectively blocked by a dose of nonspecific (isotype control) IgG

Runaway Events Dominate the Heavy Tail of Citation Distributions

Statistical distributions with heavy tails are ubiquitous in natural and social phenomena. Since the entries in heavy tail have disproportional significance, the knowledge of its exact shape is very important. Citations of scientific papers form one of the best-known heavy tail distributions. Even in this case there is a considerable debate whether citation distribution follows the log-normal or power-law fit. The goal of our study is to solve this debate by measuring citation distribution for a very large and homogeneous data. We measured citation distribution for 418,438 Physics papers published in 1980-1989 and cited by 2008. While the log-normal fit deviates too strong from the data, the discrete power-law function with the exponent $\gamma=3.15$ does better and fits 99.955% of the data. However, the extreme tail of the distribution deviates upward even from the power-law fit and exhibits a dramatic "runaway" behavior. The onset of the runaway regime is revealed macroscopically as the paper garners 1000-1500 citations, however the microscopic measurements of autocorrelation in citation rates are able to predict this behavior in advance.Comment: 6 pages, 5 Figure