bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inverse electromagnetic obstacle scattering problems with multi-frequency sparse backscattering far field data
Authors: Arens Tilo , Ji Xia , Liu Xiaodong 
Published: September 2020

Abstract
This paper is dedicated to design a direct sampling method of inverse electromagnetic scattering problems, which uses multi-frequency sparse backscattering far field data for reconstructing the boundaries of perfectly conducting obstacles. We show that the smallest strip containing the unknown object can be approximately determined by the multi-frequency backscattering far field data at two opposite observation directions. The proof is based on the Kirchhoff approximation and Fourier transform. Such a strip is then reconstructed by an indicator, which is the absolute value of an integral of the product of the data and some properly chosen function over the frequency interval. With the increase of the number of the backscattering data, the location and shape of the underlying object can be reconstructed. Numerical examples are conducted to show the validity and robustness of the proposed sampling method, even with moderately sized frequencies. The numerical examples also show that the concave part of the underlying object can be well reconstructed, and the different connected components of the underlying object can be well separated.
EEG data augmentation: towards class imbalance problem in sleep staging tasks
Authors: Fan Jiahao , Sun Chenglu , Chen Chen , Jiang Xinyu , Liu Xiangyu , Zhao Xian , Meng Long , Dai Chenyun , Chen Wei 
Published: September 2020

Abstract

Objective.
Automatic sleep staging models suffer from an inherent class imbalance problem (CIP), which hinders the classifiers from achieving a better performance. To address this issue, we systematically studied sleep electroencephalogram data augmentation (DA) approaches. Furthermore, we modified and transferred novel DA approaches from related research fields, yielding new efficient ways to enhance sleep datasets. Approach. This study covers five DA methods, including repeating minority classes, morphological change, signal segmentation and recombination, dataset-to-dataset transfer, as well as generative adversarial network (GAN). We evaluated these mentioned DA methods by a sleep staging model on two datasets, the Montreal archive of sleep studies (MASS) and Sleep-EDF. We used a classification model with a typical convolutional neural network architecture to evaluate the effectiveness of the mentioned DA approaches. We also conducted a comprehensive analysis of these methods. Main results. The classification results showed that DA methods, especially DA by GAN, significantly improved the total classification performance in comparison with the baseline. The improvement of accuracy, F1 score and Cohen Kappa coefficient range from 0.90% to 3.79%, 0.73% to 3.48%, 2.61% to 5.43% on MASS and 1.36% to 4.79%, 1.47% to 4.23%, 2.22% to 4.04% on Sleep-EDF, respectively. DA methods improved the classification performance in most cases, whereas the performance of class N1 showed a subtle degradation in the F1 scores. Significance. Overall, our study proved that DA approaches are efficient in alleviating CIP lying in sleep staging tasks. Meanwhile, this study provided avenues for further improving the sleep staging accuracy using DA methods.
Drivers of increasing global crop production: A decomposition analysis
Authors: Blomqvist Linus , Yates Luke , Brook Barry W 
Published: September 2020

Abstract
Rising crop production over the last half century has had far-reaching consequences for human welfare and the environment. With food demand projected to rise, one of the central challenges in minimizing agriculture’s impacts on the climate and biodiversity is to increase crop production with higher yields rather than more cropland. However, quantifying progress is challenging. When analyzed at the most aggregated, global level, yields can be defined as the total crop output per unit area per year, but aggregate yields are driven by multiple factors, only some of which have a clear relationship to improved agricultural production. To date, there is no research that simultaneously determines how much of rising crop production has been met by rising aggregate yields versus cropland expansion, while also quantifying the unique contribution of each yield driver. Using LMDI decomposition analysis, we find that rising aggregate yields contributed far more than cropland expansion (89% compared to 11%). That is, growing global food demand has by and large been met by growing more crops on the same amount of land, rather than expanding cropland. Our second-stage decomposition showed that nearly two-thirds of aggregate yield improvements have come from pure yield, or the output of a given crop per unit of harvested cropland area in a given country per unit area per year. The remainder has come from less-discussed drivers of aggregate yields, including cropping intensity, changes in the geographic distribution of cropland, and crop composition. Further, we use attribution analysis to show the contributions to different decomposition factors from countries grouped by climate, income, and region, as well as from different crops. Such granular yet comprehensive breakdowns of crop production and aggregate yields offer more accurate forecasts and can help focus policies on the most promising levers to meet rising food demand sustainably.
Flash drought development and cascading impacts associated with the 2010 Russian heatwave
Authors: Christian Jordan I , Basara Jeffrey B , Hunt Eric D , Otkin Jason A , Xiao Xiangming 
Published: September 2020

Abstract
The 2010 western Russian heatwave was characterized by historically high surface temperatures that led to devastating impacts on the environment, economy, and society. Recent studies have attributed a quasi-stationary upper level ridge, sensible heat advection, and land-atmosphere temperature coupling as the primary components for the development of the heatwave event. The results in this study reveal that rapid drought intensification occurred prior to the extreme atmospheric conditions associated with the heatwave. The flash drought event developed from a lack of rainfall coupled with enhanced evaporative demand and resulted in rapid desiccation of the land surface. The region that underwent rapid drought intensification acted to prime the land-atmosphere interactions necessary to supplement the excessive surface temperatures experienced during the heatwave event. This area also provided a source region for the advection of warm, dry air to promote heatwave development downwind of the flash drought location. As such, the hydrometeorological extremes associated with the precursor flash drought and heatwave resulted in cascading impacts that severely affected ecosystems, agriculture, and human health. Given the findings from this research, we conclude that flash drought impacts should be expanded beyond vegetative and agricultural applications and should be viewed as a possible precursor and direct forcing for heatwave events and associated impacts.
Characterizing the association between low-income electric subsidies and the intra-day timing of electricity consumption
Authors: Sherwin Evan D , Azevedo Inês M L 
Published: September 2020

Abstract
Electricity rate subsidies are an important policy mechanism to help low-income households afford necessary energy services, bringing substantial quality of life benefits to roughly 30% of California households. Resulting increases in consumption may unintentionally increase costly peak demand while also raising emissions of greenhouse gases and criteria air pollution from electricity generation, potentially motivating additional measures to shift consumption to hours with fewer unintended consequences. In a difference-in-differences study of interval data from over 30 000 northern California dwellings, we find that enrollment in the California Alternate Rates for Energy subsidy is associated with a ∼13% increase in electricity consumption, varying modestly across regions and seasons, increasing by an additional ∼3% during summer peak times. We find that peak demand costs associated with CARE are about $45 M per year but could fall by ∼1/3 with peak shifting to level demand.
Rapidly rising transboundary atmospheric pollution from industrial and urban sources in Southeast Asia and its implications for regional sustainable development
Authors: Chen Qinqin , McGowan Suzanne , Gouramanis Chris , Fong Letisha , Balasubramanian Rajasekhar , Taylor David 
Published: September 2020

Abstract
Transboundary atmospheric pollution is a major concern throughout much of Southeast Asia (SEA), although most attention has, to date, focused on episodic haze events associated with biomass burning in the region. Here, we reconstruct long-term variations in transboundary inputs of chromium (Cr), an industrial pollutant, to Singapore over the period 1900–2017 by adopting a novel catchment-reservoir mass balance methodology that combines a national emissions inventory and a paleolimnological approach. Results show periods of low (before the 1950s) and relatively stable (the 1950s–1980s) levels of transboundary Cr deposition in Singapore followed by an unambiguous increase from ca. 1990 onwards, most likely linked to the onset of rapid industrialisation in neighbouring parts of Malaysia and Indonesia. Notably, from ca. 2000 onwards, fluxes of transboundary Cr deposition in Singapore further increased by 3% per year, almost doubling from 6 ± 3 tonne Cr yr−1 in 2000 to around 11 ± 3 tonne Cr yr−1 in 2017. This post-2000 rapid increase may reflect the effects of globalisation, pro-export driven economic growth policies and increasing capital inflows to the whole region, including from Singapore, all of which combined to drive industrialisation throughout much of SEA. The current trend of increasing transboundary pollution from anthropogenic activity highlights an urgent need for effective collaboration among countries in SEA in order to improve well-being and help guarantee sustainable development throughout the region.
Prognostic outcome prediction by semi-supervised least squares classification
Authors: Shi Mingguang , Sheng Zhou , Tang Hao 
Published: September 2020

Abstract
Although great progress has been made in prognostic outcome prediction, small sample size remains a challenge in obtaining accurate and robust classifiers. We proposed the Rescaled linear square Regression based Least Squares Learning (RRLSL), a jointly developed semi-supervised feature selection and classifier, for predicting prognostic outcome of cancer patients. RRLSL used the least square regression to identify the scale factors and then rank the features in available multiple types of molecular data. We applied the unlabeled multiple molecular data in conjunction with the labeled data to develop a similarity graph. RRLSL produced the constraint with kernel functions to bridge the gap between label information and geometry information from messenger RNA and microRNA expression profiling. Importantly, this semi-supervised model proposed the least squares learning with L2 regularization to develop a semi-supervised classifier. RRLSL suggested the performance improvement in the prognostic outcome prediction and successfully discriminated between the recurrent patients and non-recurrent ones. We also demonstrated that RRLSL improved the accuracy and Area Under the Precision Recall Curve (AUPRC) as compared to the baseline semi-supervised methods. RRLSL is available for a stand-alone software package (https://github.com/ShiMGLab/RRLSL).
A short abstract We proposed the Rescaled linear square Regression based Least Squares Learning (RRLSL), a jointly developed semi-supervised feature selection and classifier, for predicting prognostic outcome of cancer patients. RRLSL used the least square regression to identify the scale factors to rank the features in available multiple types of molecular data. RRLSL produced the constraint with kernel functions to bridge the gap between label information and geometry information from messenger RNA and microRNA expression profiling. Importantly, this semi-supervised model proposed the least squares learning with L2 regularization to develop the semi-supervised classifier. RRLSL suggested the performance improvement in the prognostic outcome prediction and successfully discriminated between the recurrent patients and non-recurrent ones.
Method Validation for Quantitative Analysis of Metribuzin in Wheat by Liquid Chromatography–Tandem Mass Spectrometry
Authors: Hazra Dipak Kumar , Purkait Aloke , Raghuwanshi Durgesh , Murthy K Sri Rama 
Published: September 2020

Abstract
A high-performance liquid chromatography–tandem mass spectrometry (LC–MS/MS) method was developed and validated for the accurate determination of metribuzin levels in wheat. The widespread use of this herbicide in the production of wheat is of concern and could follow as well as the need for methodology, which required simple sample preparation being needed. Validation of method was done as per single laboratory validation approach. Samples were extracted through a modified quick, cheap, effective, rugged and safe technique. Sample preparation includes extraction by acetonitrile solvent and cleans up by C18, primary secondary amine and anhydrous MgSO4 for dispersive solid-phase extraction. LC–MS/MS was calibrated at 5 calibration levels with high correlation coefficients (r2) &gt;0.995. Limit of detection and limit of quantitation of metribuzin were 0.01 and 0.03 μg/g, respectively. The mean recovery percentages lie in the range of 87–97 with standard deviation for repeatability (RSDa) &lt;10% at three spiking levels (0.03, 0.15 and 0.30 μg/g). Combined uncertainty (U = 0.0017) and expanded uncertainty (2U = 0.0033) were fairly consequential. The method may successfully be applied to other cereals samples for determination of metribuzin.
Chromatographic Separation of Fluoroquinolone Drugs and Drug Degradation Profile Monitoring through Quality-by-Design Concept
Authors: Asu Satya Prasad , Sompalli Naveen Kumar , Mohan Akhila Maheswari , Deivasigamani Prabhakaran 
Published: September 2020

Abstract
The article reports on the development of an efficient, robust and sensitive HPLC-DAD method for the simultaneous determination of five fluoroquinolone-based antimicrobial drugs, namely ciprofloxacin, moxifloxacin, norfloxacin, ofloxacin and pefloxacin in both aquatic and tablet formulations. The robustness of the high-performance liquid chromatography with diode-array detection (HPLC-DAD) method has been evaluated through the concepts of quality-by-design (QbD) and full factorial design of experiments (DoEs), using a Minitab 17 statistical tool. The proposed method offers sequential separation with well-defined peak shape and resolution, and has also been evaluated by following international council for harmonization (ICH) pharmaceutical guidelines. A linear signal response has been achieved for the target fluoroquinolones (FQ) drugs in the concentration range of 45–20,000 ng/mL, with an average correlation coefficient (r2) value of 0.9997, and a data precision and accuracy range of 99.3–100.9%, with an RSD value of ≤0.95%, for hexaplicate measurements. The methodology offers superior sensitivity for the target FQ drugs, with the limit of detection (LD) range of 10–25 ng/mL, and the limit of quantification (LQ) range of 51–86 ng/mL, respectively. Using the proposed method, the article carries the first of its kind report in studying the degradation profile monitoring and drug assay determination in tablet formulations and under various physiological buffer stress conditions, for pharmaceutical validation.
The problem and promise of scale in multilayer animal social networks
Authors: Robitaille Alec L , Webber Quinn M R , Turner Julie W , Vander Wal Eric 
Published: September 2020

Abstract
Scale remains a foundational concept in ecology. Spatial scale, for instance, has become a central consideration in the way we understand landscape ecology and animal space use. Meanwhile, scale-dependent social processes can range from fine-scale interactions to co-occurrence and overlapping home ranges. Furthermore, sociality can vary within and across seasons. Multilayer networks promise the explicit integration of the social, spatial, and temporal contexts. Given the complex interplay of sociality and animal space use in heterogeneous landscapes, there remains an important gap in our understanding of the influence of scale on animal social networks. Using an empirical case study, we discuss ways of considering social, spatial, and temporal scale in the context of multilayer caribou social networks. Effective integration of social and spatial processes, including biologically meaningful scales, within the context of animal social networks is an emerging area of research. We incorporate perspectives that link the social environment to spatial processes across scales in a multilayer context.
Sex-related differences of fatty acid-binding protein 4 and leptin levels in atrial fibrillation
Authors: López-Canoa J N , Couselo-Seijas M , Baluja A , González-Melchor L , Rozados A , Llorente-Cortés V , de Gonzalo-Calvo D , Guerra J M , Vilades D , Leta R , Martínez-Sande J L , García-Seara F J , Fernández-López X A , González-Juanatey J R , Eiras S , Rodríguez-Mañero M 
Published: September 2020

Abstract

Aims
Adiposity plays a key role in the pathogenesis of atrial fibrillation (AF). Our aim was to study the sex differences in adipokines levels according to AF burden.

Methods and results
Two independent cohorts of patients were studied: (i) consecutive patients with AF undergoing catheter ablation (n = 217) and (ii) a control group (n = 105). (i) Adipokines, oxidative stress, indirect autonomic markers, and leucocytes mRNA levels were analysed; (ii) correlation between biomarkers was explored with heatmaps and Kendall correlation coefficients; and (iii) logistic regression and random forest model were used to determine predictors of AF recurrence after ablation. Our results showed that: (i) fatty acid-binding protein 4 (FABP4) and leptin levels were higher in women than in men in both cohorts (P &lt; 0.01). In women, FABP4 levels were higher on AF cohort (20 ± 14 control, 29 ± 18 paroxysmal AF and 31 ± 17 ng/mL persistent AF; P &lt; 0.01). In men, leptin levels were lower on AF cohort (22 ± 15 control, 13 ± 16 paroxysmal AF and 13 ± 11 ng/mL persistent AF; P &lt; 0.01). (ii) In female with paroxysmal AF, there was a lower acetylcholinesterase and higher carbonic anhydrase levels with respect to men (P &lt; 0.05). (iii) Adipokines have an important role on discriminate AF recurrence after ablation. In persistent AF, FABP4 was the best predictor of recurrence after ablation (1.067, 95% confidence interval 1–1.14; P = 0.046).

Conclusion
The major finding of the present study is the sex-based differences of FABP4 and leptin levels according to AF burden. These adipokines are associated with oxidative stress, inflammatory and autonomic indirect markers, indicating that they may play a role in AF perpetuation.
Unpacking the implementation blackbox using 'actor interface analysis': how did actor relations and practices of power influence delivery of a free entitlement health policy in India?
Authors: Parashar Rakesh , Gawde Nilesh , Gupt Anadi , Gilson Lucy 
Published: September 2020

Abstract
Exploring the implementation blackbox from a perspective that considers embedded practices of power is critical to understand the policy process. However, the literature is scarce on this subject. To address the paucity of explicit analyses of everyday politics and power in health policy implementation, this article presents the experience of implementing a flagship health policy in India. Janani Shishu Suraksha Karyakram (JSSK), launched in the year 2011, has not been able to fully deliver its promises of providing free maternal and child health services in public hospitals. To examine how power practices, influence implementation, we undertook a qualitative analysis of JSSK implementation in one state of India. We drew on an actor-oriented perspective of development and used ‘actor interface analysis’ to guide the study design and analysis. Data collection included in-depth interviews of implementing actors and JSSK service recipients, document review and observations of actor interactions. A framework analysis method was used for analysing data, and the framework used was founded on the constructs of actor lifeworlds, which help understand the often neglected and lived realities of policy actors. The findings illustrate that implementation was both strengthened and constrained by practices of power at various interface encounters. The implementation decisions and actions were influenced by power struggles such as domination, control, resistance, contestation, facilitation and collaboration. Such practices were rooted in: Social and organizational power relationships like organizational hierarchies and social positions; personal concerns or characteristics like interests, attitudes and previous experiences and the worldviews of actors constructed by social and ideological paradigms like their values and beliefs. Application of ‘actor interface analysis’ and further nuancing of the concept of ‘actor lifeworlds’ to understand the origin of practices of power can be useful for understanding the influence of everyday power and politics on the policy process.
LRP2 controls sonic hedgehog-dependent differentiation of cardiac progenitor cells during outflow tract formation
Authors: Christ Annabel , Marczenke Maike , Willnow Thomas E 
Published: September 2020

AbstractConotruncal malformations are a major cause of congenital heart defects in newborn infants. Recently, genetic screens in humans and in mouse models have identified mutations in LRP2, a multi-ligand receptor, as a novel cause of a common arterial trunk, a severe form of outflow tract (OFT) defect. Yet, the underlying mechanism why the morphogen receptor LRP2 is essential for OFT development remained unexplained. Studying LRP2-deficient mouse models, we now show that LRP2 is expressed in the cardiac progenitor niche of the anterior second heart field (SHF) that contributes to the elongation of the OFT during separation into aorta and pulmonary trunk. Loss of LRP2 in mutant mice results in the depletion of a pool of sonic hedgehog-dependent progenitor cells in the anterior SHF due to premature differentiation into cardiomyocytes as they migrate into the OFT myocardium. Depletion of this cardiac progenitor cell pool results in aberrant shortening of the OFT, the likely cause of CAT formation in affected mice. Our findings identified the molecular mechanism whereby LRP2 controls the maintenance of progenitor cell fate in the anterior SHF essential for OFT separation, and why receptor dysfunction is a novel cause of conotruncal malformation.