bluuebunny/crossref_metadata_2025_split huggingface dataset:
Generic rotation sets
Authors: PAVEZ-MOLINA SEBASTIÁN 
Published: December 2020

AbstractLet$(X,T)$be a topological dynamical system. Given a continuous vector-valued function$F \in C(X, \mathbb {R}^{d})$called apotential, we define its rotation set$R(F)$as the set of integrals ofFwith respect to allT-invariant probability measures, which is a convex body of$\mathbb {R}^{d}$. In this paper we study the geometry of rotation sets. We prove that ifTis a non-uniquely ergodic topological dynamical system with a dense set of periodic measures, then the map$R(\cdot )$is open with respect to the uniform topologies. As a consequence, we obtain that the rotation set of a generic potential is strictly convex and has$C^{1}$boundary. Furthermore, we prove that the map$R(\cdot )$is surjective, extending a result of Kucherenko and Wolf.
Antimicrobial never events: Objective application of a framework to assess vancomycin appropriateness
Authors: Liu Jiajun , Mercuro Nicholas J. , Davis Susan L. , Palmo Tenzin , Kashyap Shivek , Patel Twisha S. , Petty Lindsay A. , Yarnold Paul R. , Kaye Keith S. , Scheetz Marc H. 
Published: December 2020

AbstractTo address appropriateness of antibiotic use, we implemented an electronic framework to evaluate antibiotic “never events” (NEs) at 2 medical centers. Patient-level vancomycin administration records were classified as NEs or non-NEs. The objective framework allowed capture of true-positive vancomycin NEs in one-third of patients identified by the electronic strategy.
How Predatory Informal Rules Outlast State Reform: Evidence from Postauthoritarian Guatemala
Authors: Schwartz Rachel A. 
Published: December 2020

ABSTRACTThe coexistence of predatory informal rules alongside formal democratic institutions is a defining, if pernicious, feature of Latin America’s political landscape. How do such rules remain so resilient in the face of bureaucratic reforms? This article explicates the mechanisms underlying the persistence of such rules and challenges conventional explanations through process-tracing analysis in one arena: Guatemala’s customs administration. During Guatemala’s period of armed conflict and military rule, military intelligence officers introduced a powerful customs fraud scheme that endured for more than 20 years, despite state reforms. Its survival is best attributed to the ability of the distributional coalition underwriting the predatory rules to capture new political and economic spaces facilitated by political party and market reforms. This illustrates that distributional approaches to institutional change must attend to how those with a stake in the status quo may continue to uphold perverse institutional arrangements on the margins of state power.
The names don't matter but the numbers do: searching for stability in Carboniferous brachiopod paleocommunities from the North American Midcontinent
Authors: Strotz Luke C. , Lieberman Bruce S. 
Published: December 2020

AbstractA key question in paleoecology and macroevolution is whether assemblages of species (paleocommunities) are persistent entities that endure over millions of years. While community turnover in the face of abiotic change is the presumed norm, paleocommunities have been shown to persist for long time periods and regardless of environmental disruption. It remains an open question, however, as to what processes allow for this. We investigate these questions by analyzing the Carboniferous brachiopod paleocommunities from the Midcontinent of North America. These diverse communities were subjected to repeated and geologically rapid changes in sea level. Using a suite of statistical techniques, we characterize the nature and scope of changes in these paleocommunities over time. We find that, at the paleocommunity scale, there is no evidence for obdurate ecological stasis, with fluctuations in both taxonomic composition and the associated abundance of taxa. However, at a higher ecological scale, stability is manifest, as diversity patterns remain stable across time, with a consistent number of species that can exist in any given paleocommunity. This suggests ecological rules such as taxon packing are in effect, resulting in a form of ecological stability even in the face of constant disequilibrium, and parallels ecological patterns of disruption and recovery previously observed for invertebrate communities from modern marine systems. Based on these results, we advocate for consideration of different hierarchical entities and scales when interpreting the ecological dynamics of fossil assemblages, as focusing exclusively on changes in taxon identity/abundance or diversity levels can lead to very different results.
End-of-life Decisions for Patients with Prolonged Disorders of Consciousness in England and Wales: Time for Neuroscience-informed Improvements
Authors: CATLEY PAUL , PYWELL STEPHANIE , TANNER ADAM 
Published: December 2020

AbstractThis article explores how the law of England and Wales1 has responded thus far to medical and clinical advances that have enabled patients with prolonged disorders of consciousness to survive. The authors argue that, although the courts have taken account of much of the science, they are now lagging behind, with the result that some patients are being denied their legal rights under the Mental Capacity Act 2005. The article further argues that English law does not comply with the United Kingdom’s commitments under the United Nations Convention on the Rights of Persons with Disabilities. Stressing the need for the law to keep in step with advances in science, the article concludes with robust recommendations for improvements, based on the latest research in neuroscience, to the way in which life-sustaining treatment decisions are made. This would mean that the wishes of patients, including those with covert awareness, can be better reflected in best interests assessments.
Human Biobanking in Developed and Developing Countries: An Ethico-Legal Comparative Analysis of the Frameworks in the United Kingdom, Australia, Uganda, and South Africa
Authors: MAHOMED SAFIA 
Published: December 2020

AbstractAlthough the concept of biobanking is not new, the open and evolving nature of biobanks has created profound ethical, legal, and social implications, including issues around informed consent, community engagement, secondary uses of materials over time, ownership of materials, data sharing, and privacy. Complexities also emerge because of increasing international collaborations and differing national positions. In addition, the degrees and topics of concern vary as legislative, ethical, and social frameworks differ across developed and developing countries. Implementing national laws in an internationally consistent manner is also problematic. However, these concerns should not cause countries, especially developing countries, to lag behind as this novel wave of research gains momentum, particularly while several biobank initiatives are already underway in the developing world. As the law has always struggled to keep up with the fast-evolving scientific arena, this article seeks to identify the ethico-legal frameworks in place in the United Kingdom, Australia, Uganda, and South Africa, for human biobank research, in an attempt to compare and contextualize the approaches to human biobanking in specific developed and developing countries.
Role of Geostrophic Currents in Future Changes of Coastal Upwelling in the California Current System
Authors: Ding Hui , Alexander Michael A. , Jacox Michael G. 
Published: December 2020

AbstractGiven the importance of coastal upwelling in the California Current System (CCS), there is a considerable interest in predicting its response to global warming. However, upwelling changes are often treated as synonymous with changes in upwelling‐favorable winds, while the role of geostrophic transport is unaccounted for. Here, we examine the respective roles of Ekman and geostrophic transports using the Community Earth System Model Large Ensemble. In some parts of the CCS, the contribution of geostrophic transport to long‐term changes in upwelling is equal or greater than the contribution from Ekman transport. The combination of the two transports nearly close the momentum budget, and thus reproduce the mean state, interannual variability, and long‐term changes in upwelling. These results highlight the importance of accounting for ocean circulation when quantifying upwelling and its variability and change.
Atmospheric River Lifecycle Responses to the Madden‐Julian Oscillation
Authors: Zhou Yang , Kim Hyemi , Waliser Duane E. 
Published: December 2020

AbstractWe investigate how the Madden‐Julian Oscillation (MJO), the dominant mode of tropical subseasonal variability, modulates the lifecycle of cool‐season North Pacific atmospheric rivers (ARs). When the enhanced (suppressed) convection center is located over the Indian Ocean (western Pacific), more AR events originate over eastern Asia and with fewer over the subtropical northern Pacific. When the enhanced (suppressed) convection is over the western Pacific (Indian Ocean), the opposite changes occur, with more AR events originate over the subtropical northern Pacific and fewer over eastern Asia. Dynamical processes involving anomalous MJO wind and seasonal mean moisture are found to be the dominant factors impacting these variations in AR origins. The MJO‐related anomalous geopotential height patterns are also shown to modulate the propagation of the AR events. These MJO–AR lifecycle relationships are further supported by model simulations.
Statistical Forecasts for the Occurrence of Precipitation Outperform Global Models over Northern Tropical Africa
Authors: Vogel Peter , Knippertz Peter , Gneiting Tilmann , Fink Andreas H. , Klar Manuel , Schlueter Andreas 
Published: December 2020

AbstractShort‐term global ensemble predictions of rainfall currently have no skill over northern tropical Africa when compared to simple climatology‐based forecasts, even after sophisticated statistical postprocessing. Here, we demonstrate that 1‐day statistical forecasts for the probability of precipitation occurrence based on a simple logistic regression model have considerable potential for improvement. The new approach we present here relies on gridded rainfall estimates from the Tropical Rainfall Measuring Mission for July‐September 1998–2017 and uses rainfall amounts from the pixels that show the highest positive and negative correlations on the previous two days as input. Forecasts using this model are reliable and have a higher resolution and better skill than climatology‐based forecasts. The good performance is related to westward propagating African easterly waves and embedded mesoscale convective systems. The statistical model is outmatched by the postprocessed dynamical forecast in the dry outer tropics only, where extratropical influences are important.
Differing Mechanisms of New Particle Formation at Two Arctic Sites
Authors: Beck Lisa J. , Sarnela Nina , Junninen Heikki , Hoppe Clara J. M. , Garmash Olga , Bianchi Federico , Riva Matthieu , Rose Clemence , Peräkylä Otso , Wimmer Daniela , Kausiala Oskari , Jokinen Tuija , Ahonen Lauri , Mikkilä Jyri , Hakala Jani , He Xu‐Cheng , Kontkanen Jenni , Wolf Klara K. E. , Cappelletti David , Mazzola Mauro , Traversi Rita , Petroselli Chiara , Viola Angelo P. , Vitale Vito , Lange Robert , Massling Andreas , Nøjgaard Jakob K. , Krejci Radovan , Karlsson Linn , Zieger Paul , Jang Sehyun , Lee Kitack , Vakkari Ville , Lampilahti Janne , Thakur Roseline C. , Leino Katri , Kangasluoma Juha , Duplissy Ella‐Maria , Siivola Erkki , Marbouti Marjan , Tham Yee Jun , Saiz‐Lopez Alfonso , Petäjä Tuukka , Ehn Mikael , Worsnop Douglas R. , Skov Henrik , Kulmala Markku , Kerminen Veli‐Matti , Sipilä Mikko 
Published: December 2020

AbstractNew particle formation in the Arctic atmosphere is an important source of aerosol particles. Understanding the processes of Arctic secondary aerosol formation is crucial due to their significant impact on cloud properties and therefore Arctic amplification. We observed the molecular formation of new particles from low‐volatility vapors at two Arctic sites with differing surroundings. In Svalbard, sulfuric acid (SA) and methane sulfonic acid (MSA) contribute to the formation of secondary aerosol and to some extent to cloud condensation nuclei (CCN). This occurs via ion‐induced nucleation of SA and NH3 and subsequent growth by mainly SA and MSA condensation during springtime and highly oxygenated organic molecules during summertime. By contrast, in an ice‐covered region around Villum, we observed new particle formation driven by iodic acid but its concentration was insufficient to grow nucleated particles to CCN sizes. Our results provide new insight about sources and precursors of Arctic secondary aerosol particles.
Actionable and incidental neuroradiological findings in twins with neurodevelopmental disorders
Authors: Myers Lynnea , Ho Mai-Lan , Cauvet Elodie , Lundin Karl , Carlsson Torkel , Kuja-Halkola Ralf , Tammimies Kristiina , Bölte Sven 
Published: December 2020

AbstractWhile previous research has investigated neuroradiological findings in autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD), the entire range of neurodevelopmental disorders (NDDs) has not yet been well-studied using magnetic resonance imaging (MRI). Considering the overlap among NDDs and simultaneous development of the brain and face, guided by molecular signaling, we examined the relationship of actionable and incidental (non-actionable) MRI findings and NDD diagnoses together with facial morphological variants and genetic copy number variants (CNVs). A cross-sectional study was conducted with a twin cohort 8–36 years of age (57% monozygotic, 40% dizygotic), including 372 subjects (46% with NDDs; 47% female) imaged by MRI, 280 with data for facial morphological variants, and 183 for CNVs. Fifty-one percent of participants had MRI findings. Males had a statistically significantly higher percentage of MRI findings (57.7%) compared with females (43.8%, p = 0.03). Twin zygosity was not statistically significantly correlated with incidence or severity of specific MRI findings. No statistically significant association was found between MRI findings and any NDD diagnosis or facial morphological variants; however, MRI findings were statistically significantly associated with the number of CNVs (OR 1.20, 95% CI 1.00–1.44, p = 0.05, adjusted OR for sex 1.24, 95% CI 1.03–1.50, p = 0.02). When combining the presence of MRI findings, facial morphological variants, and CNVs, statistically significant relationships were found with ASD and ADHD diagnoses (p = 0.0006 and p = 0.002, respectively). The results of this study demonstrate that the ability to identify NDDs from combined radiology, morphology, and CNV assessments may be possible. Additionally, twins do not appear to be at increased risk for neuroradiological variants.
Hierarchic distributed stabilization of a class of three‐dimensional formations for underactuated agents
Authors: El‐Hawwary Mohamed I. 
Published: December 2020

AbstractThe paper presents a distributed hierarchic control design solving a formations problem in three dimension. The agents are modelled as thrust‐underactuated rigid bodies. The class of formations addressed encompasses path following of closed convex paths with shape, size, orientation, relative displacements and relative agents' on‐path angular positions all seen as formation parameters. This problem can be seen as a generalization of circular formation problems which acquired particular attention in the field of multi‐agents, and the agents model used is one that usually models certain unmanned aerial vehicles and other autonomous vehicles. The solution relies on reduction‐based set stabilization where the problem is broken down into simpler nested sub‐problems. The results illustrate how addressing complex control problems using hierarchical set stabilization is natural, simplifies the solution, and provides useful properties. The results are illustrated via simulations.
An average consensus‐based power‐sharing among VOC‐based distributed generations in multi‐bus islanded microgrids
Authors: Tran Trung Thai , Sowa Igor , Raisz David , Monti Antonello 
Published: December 2020

AbstractThis study proposes a hierarchical control structure for load power‐sharing among distributed generations (DG) in a multi‐bus microgrid (MG). The proposed control structure uses an average consensus‐based distributed protocol (CDP) for the secondary control layer and virtual oscillator control (VOC) as a primary controller. The proposed method can nullify the power‐sharing inaccuracy caused by the mismatches of the equivalent impedances seen from the outputs of DGs. The eigenvalue‐based small‐signal analysis is used to analyse the secondary controller and communication time‐delay on system stability. The results of the stability analysis are used to design secondary controller and time‐delay compensator. The validity of the proposed method is verified by both offline simulations in Matlab/Simulink and control hardware‐in‐the‐loop (CHiL) using a real‐time Opal‐RT platform.
Optimised CNN in conjunction with efficient pooling strategy for the multi‐classification of breast cancer
Authors: Sharma Shallu , Mehra Rajesh , Kumar Sumit 
Published: December 2020

AbstractTissue analysis using histopathological images is the most prevailing as well as a challenging task in the treatment of cancer. The clinical assessment of tissues becomes very tough as high variability in the magnification levels makes the situation worst for any pathologist to deal with the benign and malignant stages of cancer. One of the possible ways to address such a pathetic situation could be an advanced machine learning approach. Hence, a convolutional neural network (CNN) architecture is proposed to create an automated system for magnification independent multi‐classification of breast cancer histopathological images. This automated system offers high productivity and consistency in diagnosing the eight different classes of breast cancer from a balanced BreakHis dataset. The system utilises an efficient training methodology to learn the discerning features from images of different magnification levels. Data augmentation techniques are also employed to overcome the problem of overfitting. Additionally, the performance of CNN architecture has been improved in a significant manner by adopting an appropriate pooling strategy and optimisation technique. Based on that, we have achieved an accuracy of 80.76%, 76.58%, 79.90%, and 74.21% at the magnification 40X, 100X, 200X, and 400X, respectively. The proposed model outperforms the handcrafted approaches with an average accuracy of 80.47% at 40X magnification level.
Light field editing in the gradient domain
Authors: Sevcenco Ioana , Agathoklis Panajotis 
Published: December 2020

AbstractThis paper presents a new method for light field applications such as content replacement and fusion in the gradient domain. This approach is inspired by successful gradient domain based image and video editing techniques. A necessary and important part of gradient‐based solutions is recovering the signal of interest from artificially generated, and typically non‐integrable, gradient data. As such, a new algorithm is developed to reconstruct a light field from a given gradient data set. In the algorithm, first, the 4D Haar wavelet decomposition of the light field is obtained from the given gradient data. Then, the light field is obtained from a wavelet synthesis step. This algorithm is intended as a building block for gradient‐based light field editing methods, and as such, its performance is analysed on a set of benchmark light field data sets. The proposed reconstruction algorithm is an essential part in developing solutions for two light field problems: light field editing and light field fusion. Results show that processing light fields in the gradient domain offers significant advantages over processing in the intensity domain.
FPGA‐based favourite skin colour restoration using improved histogram equalization with variable enhancement degree and ensemble extreme learning machine
Authors: Sahani Mrutyunjaya , Swain Bhanja Kishor , Dash Pradipta Kishore 
Published: December 2020

AbstractThis paper presents skin color enhancement based on favorite skin color to agree with user‐defined favorite skin color using improved histogram equalization with variable enhancement degree (IHEwVED) and machine learning methods. The skin color to be adjusted in the input image is shifted to favorite skin color by using novel control parameters of the proposed IHEwVED method. Three different novel display device‐dependent color image processing methods are introduced based on hsv and yiq color space to obtain the desired enhanced output images. A reduced convolutional neural network and the novel ensemble extreme learning machine (EELM) architectures are developed and implemented in a field‐programmable gate array to test, synthesize, and validate the recognition capability of the user‐defined favorite skin color. The less computational complex proposed IHEwVED‐EELM method recognizes 45 to 50 favorite skin color per second of test images by consuming 0.035 second training time with training root mean square error (RMSE) of 0.0048 and testing RMSE of 0.01208. Finally, a stand‐alone favorite skin color restoration system is developed using the high‐speed video processor NI‐PXI‐1031 based on the IHEwVED‐EELM method in the Python‐OpenCV environment. The laboratory experimental performances ascertain the real‐time ability of the proposed favorite skin color restoration method.
EP‐LSTM: Novel prediction algorithm for moving object destination
Authors: Li Bingrong , Pi Dechang , Hou Mengru 
Published: December 2020

AbstractPredicting the destination of a moving object is a popular research subject in location‐based services. By predicting destinations, suggestions can be offered to people regarding their trips. At present, there are problems such as data sparsity and long‐term dependence based on historical trajectory prediction methods, which affect the accuracy of prediction. To solve data sparsity problem, this paper has devised an improved minimum description length method, which incorporates weighting parameters and optimizes the partitioning of trajectories with undirected complete graph. Long–short‐term memory is a trajectory‐prediction model that solves the problem of long‐term dependence, but the model tends to have vanishing gradient issues when used to process longer sequences. This is because the hidden layers of long–short‐term memory is largely affected by the lengths of sequences. Using embedded technology, the authors convert trajectory sequences into embedded vector sequences, and thus propose a deep‐learning prediction model, EP‐LSTM (Embedded Processing ‐ Long Short Term Memory), which integrates embedded technology and long–short‐term memory. The authors have conducted a great amount of testing with real data sets, comparing EP‐LSTM with currently available predicting methods. The results have shown that EP‐LSTM not only effectively solves data sparsity and long‐term dependence but also achieves a high degree of prediction accuracy.