bluuebunny/crossref_metadata_2025_split huggingface dataset:
Body Composition of National Collegiate Athletic Association
(NCAA) Division I Female Soccer Athletes through Competitive
Seasons
Authors: Roelofs Erica , Bockin April , Bosch Tyler , Oliver Jonathan , Bach Christopher W. , Carbuhn Aaron , Stanforth Philip R. , Dengel Donald R. 
Published: July 2020

AbstractThe purpose of this study was to examine body composition of National Collegiate
Athletic Association Division I female soccer players by position and season.
One hundred seventy-five female athletes were categorized by positions of
forward (n=47), midfielder (n=51), defender (n=57), and
goalkeeper (n=20). A dual X-ray absorptiometry scan assessed percent
body fat, total lean mass, total fat mass, arm and leg lean mass and fat mass,
and visceral adipose tissue. Goalkeepers had significantly higher total, arm,
and leg lean mass and fat mass compared to all other positions (p<0.05).
For seasonal changes, body fat percentage was significantly higher in winter
off-season (26.7%) compared to summer off-season (25.7%) and
pre-season (25.8%; p<0.01) for all positions. Total and leg lean
mass was significantly lower in winter off-season compared to all other seasons,
and total lean mass was significantly higher in summer off-season than
pre-season (p<0.01). Overall, goalkeepers were significantly different
than all other positions. Body fat percentage increased and lean mass decreased
in winter off-season indicating potential undesired changes in training
and/or nutrition over the break whereas lean mass was the highest in
summer off-season potentially reflecting the emphasis on resistance training and
increased volume of training.
Current Insights into Exercise-based Cardiac Rehabilitation in Patients with Coronary Heart Disease and Chronic Heart Failure
Authors: Nichols Simon , McGregor Gordon , Breckon Jeff , Ingle Lee 
Published: July 2020

AbstractCardiac rehabilitation is a package of lifestyle secondary prevention
strategies designed for patients with coronary heart disease and chronic
heart failure. A community-based cardiac rehabilitation programme provides
patients with a structured exercise training intervention alongside
educational support and psychological counselling. This review provides an
update regarding the clinical benefits of community-based cardiac
rehabilitation from a psycho-physiological perspective, and also focuses on
the latest epidemiological evidence regarding potential survival benefits.
Behaviour change is key to long-term adoption of a healthy and active
lifestyle following a cardiac event. In order for lifestyle interventions
such as structured exercise interventions to be adopted by patients,
practitioners need to ensure that behaviour change programmes are mapped
against patient’s priorities and values, and adapted to their level
of readiness and intention to engage with the target behaviour. We review
the evidence regarding behaviour change strategies for cardiac patients and
provide practitioners with the latest guidance. The ‘dose’
of exercise training delivered to patients attending exercise-based cardiac
rehabilitation is an important consideration because an improvement in peak
oxygen uptake requires an adequate physiological stimulus to invoke positive
physiological adaptation. We conclude by critically reviewing the latest
evidence regarding exercise dose for cardiac patients including the role of
traditional and more contemporary training interventions including high
intensity interval training.
Estudo comparativo da função e qualidade de vida de pacientes submetidos à artroplastia total do joelho com plataformas tibiais fixa e móvel
Authors: Nacca Daiane Cavenaghi , Amaro Joicemar Tarouco , Miyahira Mateus Kenji Christo , Novaretti João Victor , Astur Diego Costa , Cohen Moisés 
Published: July 2020

Resumo
Objetivo Comparar a função e qualidade de vida dos pacientes submetidos a artroplastia total de joelho (ATJ) com plataforma tibial fixa e plataforma tibial móvel.
Métodos Foram avaliados 240 pacientes com diagnóstico de osteoartrose de joelho, em um ensaio clínico, randomizados em dois grupos: grupo A, composto por 120 pacientes submetidos a ATJ com plataforma tibial fixa, e grupo B, formado por 120 pacientes com plataforma móvel. Todos foram avaliados de acordo com a função e qualidade de vida pelos questionários de Western Ontario and McMaster Universities Arthritis Index (WOMAC) e Short Form Health Survey(SF-36), e escores de dor, por meio da escala visual analógica (EVA) de dor, no pré-operatório e com 6meses, 1ano, 2anos, 4anos e 8anos de cirurgia.
Resultados Com relação aos diversos domínios do SF-36, o comportamento médio dos escores de capacidade funcional, aspectos físicos, dor e aspectos emocionais foram estatisticamente diferentes ao longo do seguimento, em ambos os grupos. Os demais domínios de qualidade de vida não apresentaram diferenças. Assim como na EVA de dor, o escore médio do WOMAC de dor apresentou melhora ao longo do seguimento em ambos os grupos. Entretanto, com dois anos de seguimento, foram estaticamente piores no grupo A, se igualando ao grupo B nos outros momentos de acompanhamento.
Conclusão Com 2anos de pós-operatório, os escores de dor do WOMAC e daEVA foram piores no grupo submetido aATJ com plataforma tibial fixa. Porém, as diferenças não permaneceram no médioprazo, sugerindo que a artroplastia com plataforma tibial móvel tem uma vantagem no curto prazo, podendo auxiliar no processo de reabilitação.
Primary Squamous Cell Carcinoma of Breast Responsive to Platinum and Taxane-Based Chemotherapy: A Rare Entity and Review Literature
Authors: Pandey Jagjit K. , Kumar Amarjeet , Ranjan Amit ,   Surabhi
Published: July 2020

AbstractPure primary squamous cell carcinoma (SCC) of the breast is a rare malignancy which constitutes < 0.1% of all primary invasive breast carcinomas. It is considered to be more aggressive compared with other infiltrating ductal cancers, and knowledge concerning treatment patterns and outcomes is limited. We treated a 50-year-old woman with SCC of left breast, having metastatic fixed axillary lymph nodes. The tumor was hormone receptor negative. Paclitaxel and carboplatin-based neoadjuvant chemotherapy was given with a good response, followed by modified radical mastectomy. Adjuvant radiotherapy was given to the chest and axilla in view of two lymph nodes positive for tumor out of 12. No local and systemic recurrence encountered in 1 year of follow-up. Surgery along with platinum and taxane-based chemotherapy and radiotherapy is an effective mode of treatment for SCC in other parts of the body. More data is necessary to formulate management guidelines, and further define if there is any role for systemic chemotherapy, radiation therapy, or hormonal blockade.
BAlN alloy for enhanced two-dimensional electron gas characteristics of GaN/AlGaN heterostructures
Authors: Lin Rongyu , Liu Xinwei , Liu Kaikai , Lu Yi , Liu Xinke , Li Xiaohang 
Published: July 2020

Abstract
Emerging wide bandgap BAlN alloys have potential for improved III-nitride power devices, including high electron mobility transistors (HEMTs). Yet, few relevant studies have been carried out. In this work, we have investigated the use of the B0.14Al0.86N alloy as part or the entirety of the interlayer between the GaN buffer and the AlGaN barrier in the conventional GaN/AlGaN heterostructure. The numerical results show considerable improvement of the two-dimensional electron gas (2DEG) concentration with small 2DEG leakage into the ternary layer by replacing the conventional AlN interlayer by either the B0.14Al0.86N interlayer or the B0.14Al0.86N/AlN hybrid interlayer. Consequently, the transfer characteristics can be improved. The saturation current can be enhanced as well. For instance, the saturation currents for HEMTs with the 0.5 nm B0.14Al0.86N/0.5 nm AlN hybrid interlayer and the 1 nm B0.14Al0.86N interlayer are 5.8% and 2.2% higher than that for the AlN interlayer when VGS−Vth = +3 V.
Detecting trace methane levels with plasma optical emission spectroscopy and supervised machine learning
Authors: Vincent Jordan , Wang Hui , Nibouche Omar , Maguire Paul 
Published: July 2020

Abstract
Trace methane detection in the parts per million range is reported using a novel detection scheme based on optical emission spectra from low temperature atmospheric pressure microplasmas. These bright low-cost plasma sources were operated under non-equilibrium conditions, producing spectra with a complex and variable sensitivity to trace levels of added gases. A data-driven machine learning approach based on partial least squares discriminant analysis was implemented for CH4 concentrations up to 100 ppm in He, to provide binary classification of samples above or below a threshold of 2 ppm. With a low-resolution spectrometer and a custom spectral alignment procedure, a prediction accuracy of 98% was achieved, demonstrating the power of machine learning with otherwise prohibitively complex spectral analysis. This work establishes proof of principle for low cost and high-resolution trace gas detection with the potential for field deployment and autonomous remote monitoring.
Qubit transformations on Rashba ring with periodic potential
Authors: Kregar Ambrož , Ramšak Anton 
Published: July 2020

Abstract
A spin-qubit transformation protocol is proposed for an electron in a mesoscopic quantum ring with tunable Rashba interaction controlled by the external electric field. The dynamics of an electron driven around the ring by a series of Landau–Zenner-like transitions between a finite number of local voltage gates is determined analytically. General single-qubit transformations are demonstrated to be feasible in a dynamical basis of localized pseudo-spin states. It is also demonstrated that by the use of suitable protocols based on changes of the Rashba interaction full Bloch sphere can be covered. The challenges of a possible realization of the proposed system in semiconductor heterostructures are discussed.
Brownian motion-induced amplitude noise in vapor-cell frequency standards
Authors: Micalizio S , Godone A , Gozzelino M , Levi F 
Published: July 2020

Abstract
We demonstrate that the Brownian motion of alkali metal atoms in buffer gas gives rise to a significant source of frequency instability in vapor cell clocks. We consider, in particular, laser pumped cell devices working in pulsed operation and using a resonant Gaussian light beam to detect the clock transition. It is well known that the diffusion motion through the buffer gas results from many random walks performed by the atoms, as a consequence of the collisions with other atoms/molecules. Owing to this random-walk behavior, the atoms explore different intensity regions of the Gaussian laser beam, reducing the forward light transmission and causing amplitude fluctuations at the photodetector. The contribution of this so called transit noise to the clock frequency stability turns out in the low 10−14 region for a centimeter-scale cell, at the same level of other amplitude noises, like laser relative intensity noise and shot noise. As a consequence, even if it is not the main source of instability in currently used vapor cell clocks, Brownian motion-induced noise represents a novel source of frequency fluctuations and it should be accounted for in the clock stability budget. A preliminary evaluation of the transit noise is also reported for microcell devices.
Satellite and airborne remote sensing of gross primary productivity in boreal Alaskan lakes
Authors: Kuhn Catherine , Bogard Matthew , Johnston Sarah Ellen , John Aji , Vermote Eric , Spencer Rob , Dornblaser Mark , Wickland Kim , Striegl Rob , Butman David 
Published: July 2020

Abstract
In terrestrial and marine ecosystems, remote sensing has been used to estimate gross primary productivity (GPP) for decades, but few applications exist for shallow freshwater ecosystems.Here we show field-based GPP correlates with satellite and airborne lake color across a range of optically and limnologically diverse lakes in interior Alaska. A strong relationship between in situ GPP derived from stable oxygen isotopes (δ18O) and space-based lake color from satellites (e.g. Landsat-8, Sentinel-2 and CubeSats) and airborne imagery (AVIRIS-NG) demonstrates the potential power of this technique for improving spatial and temporal monitoring of lake GPP when coupled with additional field validation measurements across different systems. In shallow waters clear enough for sunlight to reach lake bottoms, both submerged vegetation (macrophytes and algae) and phytoplankton likely contribute to GPP. The stable isotopes and remotely sensed shallow lake color used here integrate both components. These results demonstrate the utility of lake color as a feasible means for mapping lake GPP from remote sensing. This novel methodology estimates GPP from remote sensing in shallow lakes by combining field measurements of oxygen isotopes with airborne, satellite and CubeSat imagery. This use of lake color for providing insight into ecological processes of shallow lakes is recommended, especially for remote arctic and boreal landscapes.
Shifting biomass allocation determines community water use efficiency under climate warming
Authors: Quan Quan , Zhang Fangyue , Meng Cheng , Ma Fangfang , Zhou Qingping , Sun Fubao , Niu Shuli 
Published: July 2020

Abstract
Understanding how net primary production (NPP) and its allocation respond to climate warming is of fundamental importance in predicting ecosystem carbon (C) cycle and C-climate feedback. Especially, the optimal partitioning theory suggests that plants preferentially allocate photosynthates toward the above- or below-ground parts to acquire the limiting resources to maximize their growth rate and optimize resource use under environmental change. However, it remains elusive on how NPP allocation changes and regulates community water-use efficiency (WUEc) under climate warming. In this study, we conducted a manipulative warming experiment with three levels of warming treatments (control, + 1.5 °C and + 2.5 °C) to explore the response of NPP allocation and its regulation on WUEc in an alpine meadow. Results showed that above-ground NPP (ANPP) and below-ground NPP (BNPP) responded differently to warming. On average, W1.5 (+ 1.5 °C) and W2.5 (+ 2.5 °C) treatments increased BNPP by 28.98% and 33.28% and increased NPP by 20.05% and 38.70%, respectively, across 4 years. Whereas no consistent warming effect on ANPP was observed across years. The fraction of BNPP to total NPP (fBNPP) responded positively to warming under low ambient temperature and community biomass while it responded negatively under high ambient temperature and community biomass. Notably warming-induced changes in fBNPP negatively correlated with warming-induced changes in WUEc. These results suggested that warming effect on NPP allocation was largely contextually dependent and implied important biological regulation on WUEc. The emerging trade-offs between NPP allocation and WUEc reflect adaptation strategy of plant community under climate change.
An International Collaboration towards Transformed Engineering Practice in Digital Earth
Authors: Desha C , Caldera S , Fukui H , Yasumoto S 
Published: July 2020

Abstract
Building on an appreciation of the ‘Time Lag Dilemma’ (previously published by the first author) and drawing on lived experiences (2017-18), the authors briefly describe the course and its assessment items. The authors also reflect on the benefits for academics in both universities to build capacity for embedding Digital Earth related knowledge and skills within their own coursework. The success of the course has immediate implications for ISDE community collaboration and capacity building within higher education, and more broadly bridging the gap between engineering and geospatial disciplines in the workplace. It is clear that the education sector has a key role to play in improving capacity to use digital and spatial information for meaningful enquiry and problem-solving.
Knowledge extraction from Copernicus satellite data
Authors: Dumitru C O , Schwarz G , Datcu M 
Published: July 2020

Abstract
We describe two alternative approaches of how to extract knowledge from high- and medium-resolution Synthetic Aperture Radar (SAR) images of the European Sentinel-1 satellites. To this end, we selected two basic types of images, namely images depicting arctic shipping routes with icebergs, and - in contrast - coastal areas with various types of land use and human-made facilities. In both cases, the extracted knowledge is delivered as (semantic) categories (i.e., local content labels) of adjacent image patches from big SAR images. Then, machine learning strategies helped us design and validate two automated knowledge extraction systems that can be extended for the understanding of multispectral satellite images.
A Docker-based HPC architecture for RS imagery processing
Authors: Hu Fenghua , Zhang Jingliang 
Published: July 2020

Abstract
Remote sensing imagery processing requires strong computing demand. HPC can provides powerful computing capability and has been proved as an efficient approach for acceleration. To build and deploy a HPC is costly due to its complexity and need of dedicated hardware and this restricts its application in RS field. Docker is a container technology and can simplify software deployment and improve resource utilization. This paper proposes an architecture which is based on Docker and can lower the barrier to use HPC for average user. It greatly simplifies deployment of HPC as well as improve the resource utilization by sharing with other applications.
Accurately monitoring urbanization at global scale – the world settlement footprint
Authors: Marconcini M , Gorelick N , Metz-Marconcini A , Esch T 
Published: July 2020

Abstract
Reliably monitoring global urbanization is of key importance for supporting a variety of applications involving the analysis of human presence (e.g., socioeconomic development, population distribution, risks assessment, epidemiology, conservation areas protection, etc.). To this purpose, in order to accurately outline the actual settlement extent globally we generated the World Settlement Footprint (WSF) 2015, i.e. a 10m resolution binary mask derived by jointly exploiting multitemporal optical and radar satellite imagery, which outperforms all other existing similar layers. Furthermore, to characterize the urbanization occurred in the last three decades, we recently completed the WSF Evolution, i.e. a novel dataset outlining the growth of settlement extent globally at 30m spatial resolution on a yearly basis from 1985 to 2015.
Unidata Science Gateway for Enabling Science as a Service to Facilitate Open Science and Reproducible Research
Authors: Ramamurthy M 
Published: July 2020

Abstract
Unidata, an NSF-funded geoscience cyberinfrastructure facility, has deployed data infrastructure and data-proximate scientific workflows and analysis tools, using cloud computing technologies, for analyzing and visualizing well-documented datasets that combine robust access to well-documented datasets. Docker containers and Jupyter notebooks, and other analytic methods are enabled via “Software as a Service” and “Data as a Service”. The collective impact of these services is to enable scientists to not only conduct their research but also share their work with other researchers.
A process for the accurate reconstruction of pre-filtered and compressed digital aerial images
Authors: Scarmana Gabriel , MacDougall Kevin 
Published: July 2020

Abstract
The study of compression and decompression methods is crucial for storage and/or transmission of large numbers of image data which is required for archiving aerial photographs, satellite images and digital ortho-photos. Hence, the proposed work aims to increment the compression ratio (CR) of digital images in general. While emphasis is made on aerial images, the same principle may find applications to other types of raster based images. The process described here involves the application of pre-defined low-pass filters (i.e. kernels) prior to applying standard image compression encoders. Low-pass filters have the effect of increasing the dependence between neighbouring pixels which can be used to improve the CR. However, for this pre-filtering process to be considered as a compression instrument, it should allow for the original image to be accurately restored from its filtered counterpart.
The development of the restoration process presented in this study is based on the theory of least squares and assumes the knowledge of the filtered image and the low-pass filter applied to the original image. The process is a variant of a super-resolution algorithm previously described, but its application and adaptation to the filtering and restoration of images, in this case (but not exclusively) aerial imagery, using a number of scales and filter dimensions is the expansion detailed here. An example of the proposed process is detailed in the ensuing sections. The example is also indicative of the degree of accuracy that can be attained upon applying this process to gray-scale images of different entropies and coded in a lossy or lossless mode.
How Citizen Science and Artificial Intelligence can support Digital Earth
Authors: Schade Sven , Delipetrev Blagoj , Mitton Irena , Kotsev Alexander 
Published: July 2020

Abstract
The Digital Earth vision stimulates thinking on how to benefit from new data sources and technologies. In this contribution, we particularly focus on the application of machine learning algorithms on data that has been collected with mobile devices. We present experiences from Copernicus and the identification of (alien) species in order to open a discussion about the possibilities and limits of using Citizen Science and Artificial Intelligence for Digital Earth.
Application of mathematical morphology in digital images for extraction of airport tracks
Authors: Godoy T G , Silva E A , Cardim G P , Ferreira A L A 
Published: July 2020

Abstract
The products created using remote sensing enables the detection of desired shapes, making possible the update of Cartographic products that can used for a variety of purposes. Techniques of digital image processing are generally used in methodologies of detection and identification of changes. Accordingly, this work aims to present the results of using the Mathematical Morphology (MM) techniques to the extraction of airport tracks from digital images for cartographic products updating.
Intellectual Information Platform bringing together diverse data and models for the interdisciplinary projects implementation and environmental management
Authors: Zelentsov V , Potryasaev S , Pimanov I , Semenov A 
Published: July 2020

Abstract
The structure of the Intellectual Information Platform (IIP) and examples of its application for decision-making support in environmental management are considered. The IIP structure is based on a service-oriented architecture. The flexible nature of IIP software allows to integrate a wide range of environmental parameters assessment models and diverse initial data, including earth remote sensing data. Results of case studies for different IIP applications such as water bodies monitoring, forestry management, flood forecasting, etc., showed full-scale implementation of the IIP required functionality.