bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modes of coastal precipitation over southwest India and their relationship with intraseasonal variability
Authors: Hunt Kieran M. R. , Turner Andrew G. , Stein Thorwald H. M. , Fletcher Jennifer K. , Schiemann Reinhard K. H. 
Published: September 2020

AbstractThe west coast of India, dominated by the Western Ghats mountain range, is among the rainiest places in the Tropics. The interaction between the land–sea contrast of the coast, the monsoonal westerlies, and the oblique mountains is subject to complex intraseasonal variability, which has not previously been explored in depth. This study investigates that variability from the perspective of the land–sea contrast, using empirical orthogonal function analysis to discern regimes of onshore and offshore rainfall over southwest India and the eastern Indian Ocean. Locally, it is found that the rainfall is most sensitive to midtropospheric humidity: when this is anomalously high, deep convection is encouraged; when this is anomalously low, it is suppressed. A moisture‐tracking algorithm is employed to determine the primary sources of the anomalously wet and dry midtropospheric air. There are important secondary contributions from low‐level vorticity and cross‐shore moisture flux. The dominant control on intraseasonal variability in coastal precipitation is found to be the Boreal Summer Intraseasonal Oscillation (BSISO): over 75% of the strongest offshore events occur during phases 3 and 4; and about 40% of the strongest onshore events occur during phases 5 and 6. The location of monsoon low‐pressure systems is also shown to be important in determining the magnitude and location of coastal rainfall.
First‐principle study of doping effects (Ti, Cu, and Zn) on electrochemical performance of Li2MnO3 cathode materials for lithium‐ion batteries
Authors: Moradi Zahra , Heydarinasab Amir , Pajoum Shariati Farshid 
Published: September 2020

AbstractLi‐rich layered Mn‐based oxide (LMO) cathode materials, with the formation of Li2MnO3, have attracted much attention due to their potential in various applications with high energy density. However, these cathode materials for Lithium‐ion batteries still suffer from drawbacks such as poor rate capability and voltage decay, which makes further investigation vital and rational. Here, the doping strategy is employed to investigate the effect of TM = Ti, Cu, and Zn on Li2Mn0.5TM0.5O3 cathode materials for improving electrochemical performances of Li2MnO3. Electrochemical properties such as voltage, electrical conductivity, safety, structural stability, and kinetics and mechanism of Li‐ion diffusion are evaluated and compared. All doped cathodes decrease the voltage reduction and improve the electrical conductivity coefficient in comparison with LMO. Doping Cu notably increases the electrical conductivity of LMO by 77%. Ti doping exhibits the potential to increase the maximum voltage of LMO and structural stability. Doping Zn and Cu elements can delay the oxygen loss significantly, which leads to a higher life cycle and safety. In addition, doping Zn is expected to have a higher Li‐ion diffusion coefficient due to its low energy barrier and partial charge of oxygen atoms in its cathode structure. This first‐principle study of doping effects of TM = Ti, Cu, and Zn with α = 0.5 in Li2Mn0.5TMαO3 may be a useful leading study for further investigation into the synthesis of lithium‐rich materials with enhanced electrochemical performance.
Single‐Particle Entanglement
Authors: Azzini Stefano , Mazzucchi Sonia , Moretti Valter , Pastorello Davide , Pavesi Lorenzo 
Published: September 2020

AbstractThis review is about single‐particle entanglement. Entanglement occurs when the state of a quantum system with at least two degrees of freedom has a particular non‐separable form. In the case of single‐particle entanglement, this quantum correlation is shared by the same particle being it a photon, a neutron, an ion, or an atom. Here, the basics of quantum entanglement are discussed focusing on the case it is related to the degrees of freedom of a single particle. It is discussed how the violation of peculiar inequalities in this context rules out any realistic non‐contextual hidden variable theory alternative to quantum mechanics. Moreover, experiments that demonstrate single‐particle entanglement for photons, neutrons, and atoms are discussed. Finally, the applications of single‐particle entanglement as a resource for quantum information are discussed and specifically quantum key distribution is detailed, where the use of single‐particle entangled photons allows to improve the security of the BB84 protocol.
On phase deficit of the super‐twisting second‐order sliding mode control algorithm
Authors: Boiko Igor 
Published: September 2020

SummaryThe notion of phase deficit was introduced in [12], which allows one to determine if a nonlinear system can reveal finite‐time or asymptotic convergence. Twisting and suboptimal second‐order sliding mode control algorithms and a conventional relay feedback system were analyzed from the perspective of the phase deficit. However, phase deficit for the super‐twisting algorithm was not determined at that time due to the complexity of the problem. Therefore, although it is known that the super‐twisting algorithm reveals finite‐time convergence (when no parasitic dynamics are present), it was not supported by the criterion based on the phase deficit. In the current article this problem has been solved through an open‐loop interpretation of the phase deficit, which is proposed in the article. Another problem addressed in the article is the relationship between the frequency characteristics of the system and the type of convergence (finite‐time or asymptotic). The mechanism of convergence is analyzed through considering time‐varying frequency of self‐excited oscillations and phase lag of the linear part of the system.
Stochastic approximation with nondecaying gain: Error bound and data‐driven gain‐tuning
Authors: Zhu Jingyi , Spall James C. 
Published: September 2020

SummaryOur problem of interest is to minimize a sequence of scalar‐valued loss functionsfk(·)or to locate the root(s) of a sequence of vector‐valued functionsgk(·)corresponding to timewith respect to a parameter. The available information for the minimization/root‐finding is the noise‐corrupted observation(s) of eitherfk(·)orgk(·)evaluated at afewof certain design pointsonly. Taking both the dynamics and randomness into consideration, we use stochastic approximation (SA) algorithms to solve the time‐varying problem, but with a nondecaying gain (stepsize). The tracking performance of the nondecaying gain SA algorithm is guaranteed by a computable bound for the root‐mean‐squared error and mean‐absolute‐deviation. The only assumption imposed on the drifts is that the average distance between two consecutive underlying true parameters is bounded from above—this assumption allows the varying target to change abruptly. The error term arising from using the noisy evaluation offk(·)orgk(·)in constructing the search direction is assumed to have bounded second‐moment—this allows for biased estimator to be used in the SA algorithms. Given the lenient assumptions on the drift and error term, the error bounds apply to a broad class of time‐varying scenarios and are useful for finite‐sample analysis. Since the tracking capability characterizes the average performance across all possible sample paths, it may not provide much guidance on the gain‐tuning strategies useful for one single run. Hence, we propose a data‐dependent gain‐tuning strategy based on estimating the Hessian information and the noise level. The adaptive rule is advantageous as it enables the step size to vary with information gathered during the progress of the estimation procedure.
Object detection, recognition, and tracking from UAVs using a thermal camera
Authors: Leira Frederik S. , Helgesen Håkon Hagen , Johansen Tor Arne , Fossen Thor I. 
Published: September 2020

AbstractIn this paper a multiple object detection, recognition, and tracking system for unmanned aerial vehicles (UAVs) has been studied. The system can be implemented on any UAVs platform, with the main requirement being that the UAV has a suitable onboard computational unit and a camera. It is intended to be used in a maritime object tracking system framework for UAVs, which enables a UAV to perform multiobject tracking and situational awareness of the sea surface, in real time, during a UAV operation. Using machine vision to automatically detect objects in the camera's image stream combined with the UAV's navigation data, the onboard computer is able to georeference each object detection to measure the location of the detected objects in a local North‐East (NE) coordinate frame. A tracking algorithm which uses a Kalman filter and a constant velocity motion model utilizes an object's position measurements, automatically found using the object detection algorithm, to track and estimate an object's position and velocity. Furthermore, a global‐nearest‐neighbor algorithm is applied for data association. This is achieved using a measure of distance that is based not only on the physical distance between an object's estimated position and the measured position, but also how similar the objects appear in the camera image. Four field tests were conducted at sea to verify the object detection and tracking system. One of the flight tests was a two‐object tracking scenario, which is also used in three scenarios with an additional two simulated objects. The tracking results demonstrate the effectiveness of using visual recognition for data association to avoid interchanging the two estimated object trajectories. Furthermore, real‐time computations performed on the gathered data show that the system is able to automatically detect and track the position and velocity of a boat. Given that the system had at least 100 georeferenced measurements of the boat's position, the position was estimated and tracked with an accuracy of 5–15 m from 400 m altitude while the boat was in the camera's field of view (FOV). The estimated speed and course would also converge to the object's true trajectories (measured by Global Positioning System, GPS) for the tested scenarios. This enables the system to track boats while they are outside the FOV of the camera for extended periods of time, with tracking results showing a drift in the boat's position estimate down to 1–5 m/min outside of the FOV of the camera.
The coronavirus disease (COVID‐19) pandemic: simulation‐based assessment of outbreak responses and postpeak strategies
Authors: Struben Jeroen 
Published: September 2020

AbstractIt is critical to understand the impact of distinct interventions on the ongoing coronavirus disease pandemic. I develop a behavioral dynamic epidemic model for multifaceted policy analysis comprising endogenous virus transmission (from severe or mild/asymptomatic cases), social contacts, and case testing and reporting. Calibration of the system dynamics model to the ongoing outbreak (31 December 2019–15 May 2020) using multiple time series data (reported cases and deaths, performed tests, and social interaction proxies) from six countries (South Korea, Germany, Italy, France, Sweden, and the United States) informs an explanatory analysis of outbreak responses and postpeak strategies. Specifically, I demonstrate, first, how timing and efforts of testing‐capacity expansion and social‐contact reduction interplay to affect outbreak dynamics and can explain a large share of cross‐country variation in outbreak pathways. Second, absent at‐scale availability of pharmaceutical solutions, postpeak social contacts must remain well below prepandemic values. Third, proactive (targeted) interventions, when complementing general deconfinement readiness, can considerably increase admissible postpeak social contacts.© 2020 System Dynamics Society
Performance analysis of distributed storage clusters based on kernel and userspace traces
Authors: Daoud Houssem , Dagenais Michel R. 
Published: September 2020

SummaryDistributed storage systems are commonly used in modern computing. They are highly scalable and offer data replication and fault tolerance. The complexity of those systems makes them difficult to debug using traditional tools. The existing tools are able to evaluate the overall performance of such systems but they do not provide enough information to find the root cause of performance issues. In this article, we propose a tracing‐based performance analysis framework for storage clusters. We use a tracing strategy that reduces the tracing overhead in production systems. The traces collected from the different storage nodes are correlated and used to generate a data model that represents the cluster. Userspace tracing is used to gather data from the storage daemons, while Kernel tracing is used to provide detailed information about operating system internals such as disk queues, network queues and process scheduling. Efficient data structures are used to store the model and to generate metrics and graphical views. Our tool is used in different real world scenarios and is able to investigate interesting performance problems including I/O latencies, data replication and storage nodes failures.
Influence of super absorbent polymer on mechanical, rheological, durability, and microstructural properties of self‐compacting concrete using non‐biodegradable granite pulver
Authors: Rajamony Laila Lija , Gurupatham Beulah Gnana Ananthi , Roy Krishanu , Lim James B. P. 
Published: September 2020

AbstractThis paper presents an experimental study to investigate the influence of super absorbent polymer (SAP) on mechanical, rheological, durability, and microstructural properties of self‐compacting concrete using a comparatively new environmental waste known as granite pulver (GP). The effectiveness of replacing cement by GP at 5, 10, 15, and 20% by weight, was investigated. The SAPs were used at volume fractions of 0.1 to 1% to the GP‐SSC (Granite Pulver‐Self‐cured Self‐compacting Concrete) mixtures to counteract self‐desiccation during the hydration of concrete. Along with the SAP, super plasticizer, and flyash (FA) were also added to improve the workability of the GP‐SSC mixtures. The physical, chemical, and microstructural properties of the cement, GP and flyash samples were determined. From the results, it was found that the GPs along with the SAPs increases the compressive strength by around 0.1%, when a replacement of cement by GP up to 15% was made with an addition of 0.3% of SAP. Similarly, an increase of 9.1% in flexural strength was observed for GP‐SSC mixtures, when 15% of GP along with 0.4% of SAP was added. The addition of SAP beyond 0.4% in GP‐SSC mixtures affects the filling and passing abilities. Therefore, with optimal replacement of cement by GP, the mechanical and durability properties of GP‐SSC mixtures can be improved, reducing the detrimental effects of GPs from the environment. Influence of SAP and GP waste in GP‐SSC mixtures. Analyzed mechanical, rheological, durability, and microstructural properties. Replacement of cement by GP up to 15% is favorable. 0.3% of SAP addition improves the pore structure and strength. Morphological and mineralogical studies prove GP as an effective cement replacement.
Advances in real‐time fiber‐optic Raman spectroscopy for early cancer diagnosis: Pushing the frontier into clinical endoscopic applications
Authors: Heng Howard Peng Sin , Shu Chi , Zheng Wei , Lin Kan , Huang Zhiwei 
Published: September 2020

AbstractReal‐time fiber‐optic Raman spectroscopy has emerged as a compelling approach for biomedical diagnosis and characterization. This article reviews the following topics related to real‐time in vivo clinical Raman system development, such as (a) modern Raman instrumentation; (b) current developments in miniaturized fiber‐optic Raman probe designs and fabrications and (c) data processing techniques, artificial intelligence and machine learning for Raman classification and diagnosis. These synergistic advances over the past few decades play a central role in developing this unique label‐free biomolecular probe into a clinically relevant tool. The growing body of clinical literature at in vivo Raman endoscopy is an embodiment of an emerging powerful diagnostic technique that would revolutionize the future of healthcare in medicine. The past two decades of Raman endoscopic work are summarized with an emphasis on in vivo studies, illustrating the promising potential of real‐time fiber‐optic Raman spectroscopy to improve the early detection and diagnosis of precancer and cancer in vivo during clinical endoscopic examination. The challenges that exist in the widespread clinical implementation of this unique Raman diagnostic tool will be discussed, and the potential outlook in biomedical applications will also be outlined, particularly in endoscopy.
Social and environmental impacts on sleep in captive Asian elephants (Elephas maximus)
Authors: Evison Emma , McKenzie Andrew , Holmes Lisa 
Published: September 2020

AbstractModern zoos strive to improve standards of animal management, husbandry and welfare of their animals as part of a continual evaluation process. Elephants (Elephantidae) have received particular attention in recent years due to the challenge of providing environments which promote natural behavior and opportunities for social interaction. A number of measures have been proposed to measure wellbeing, with sleep quality increasingly being used. Sleep is a vital aspect of life for cell replenishment as well as optimal development of young. Sleep deprivation can lead to immunosuppression and illness; therefore animal managers have a responsibility to ensure they reduce the potential for disturbance through noise, light, or other environmental factors. The social environment also plays an essential role in wellbeing, particularly for species that live in multi‐generational family units. In this study the nocturnal behavior of a multi‐generational captive herd was observed to determine impacts of husbandry changes on sleep duration and bout length (measured as recumbent rest). As expected, average total duration of sleep was higher in younger elephants and rates were comparable to those reported in other studies of Asian elephants. Overnight access to an outdoor paddock in warmer weather increased overall average bout length of sleep in the herd. Average total duration of sleep also increased for the herd following the movement of an unrelated adult female who had previously shown weak bonds with other herd members. This indicates that social compatibility is a vital component of elephant welfare, impacting not only behavioral interactions but sleep quality and duration.
Shedding new light on early sex determination in zebrafish
Authors: King Alex C. , Gut Michelle , Zenker Armin K. 
Published: September 2020

AbstractIn contrast to established zebrafish gene annotations, the question of sex determination has still not been conclusively clarified for developing zebrafish,Danio rerio,larvae, 28 dpf or earlier. Recent studies indicate polygenic sex determination (PSD), with the genes being distributed throughout the genome. Early genetic markers of sex in zebrafish help unravel co-founding sex-related differences to apply to human health and environmental toxicity studies. A qPCR-based method was developed for six genes: cytochrome P450, family 17, subfamily A, polypeptide 1 (cyp17a1); cytochrome P450, family 19, subfamily A, polypeptide 1a (cyp19a1a); cytochrome P450, family 19, subfamily A, polypeptides 1b (cyp19a1b); vitellogenin 1 (vtg1); nuclear receptor subfamily 0, group B, member 1 (nr0b1), sry (sex-determining region Y)-box 9b (sox9b) and actin, beta 1 (actb1), the reference gene. Sry-box 9a (Sox9a), insulin-like growth factor 3 (igf3) and double sex and mab-3 related transcription factor 1 (dmrt1), which are also known to be associated with sex determination, were used in gene expression tests. Additionally, Next-Generation-Sequencing (NGS) sequenced the genome of two adult female and male and two juveniles. PCR analysis of adult zebrafish revealed sex-specific expression of cyp17a1, cyp19a1a, vtg1, igf3 and dmrt1, the first four strongly expressed in female zebrafish and the last one highly expressed in male conspecifics. From NGS, nine female and four male-fated genes were selected as novel for assessing zebrafish sex, 28 dpf. Differences in transcriptomes allowed allocation of sex-specific genes also expressed in juvenile zebrafish.
A mortar-type finite element approach for embedding 1D beams into 3D solid volumes
Authors: Steinbrecher Ivo , Mayr Matthias , Grill Maximilian J. , Kremheller Johannes , Meier Christoph , Popp Alexander 
Published: September 2020

AbstractIn this work we present a novel computational method for embedding arbitrary curved one-dimensional (1D) fibers into three-dimensional (3D) solid volumes, as e.g. in fiber-reinforced materials. The fibers are explicitly modeled with highly efficient 1D geometrically exact beam finite elements, based on various types of geometrically nonlinear beam theories. The surrounding solid volume is modeled with 3D continuum (solid) elements. An embedded mortar-type approach is employed to enforce the kinematic coupling constraints between the beam elements and solid elements on non-matching meshes. This allows for very flexible mesh generation and simple material modeling procedures in the solid, since it can be discretized without having to account for the reinforcements, while still being able to capture complex nonlinear effects due to the embedded fibers. Several numerical examples demonstrate the consistency, robustness and accuracy of the proposed method, as well as its applicability to rather complex fiber-reinforced structures of practical relevance.
Explainable Machine Learning in Credit Risk Management
Authors: Bussmann Niklas , Giudici Paolo , Marinelli Dimitri , Papenbrock Jochen 
Published: September 2020

AbstractThe paper proposes an explainable Artificial Intelligence model that can be used in credit risk management and, in particular, in measuring the risks that arise when credit is borrowed employing peer to peer lending platforms. The model applies correlation networks to Shapley values so that Artificial Intelligence predictions are grouped according to the similarity in the underlying explanations. The empirical analysis of 15,000 small and medium companies asking for credit reveals that both risky and not risky borrowers can be grouped according to a set of similar financial characteristics, which can be employed to explain their credit score and, therefore, to predict their future behaviour.
Early Buddhist Oral Transmission and the Problem of Accurate Source Monitoring
Authors: Anālayo Bhikkhu 
Published: September 2020

AbstractA comparative study of two early Buddhist textual collections, theAṭṭhaka-vaggaand theUdāna, points to a process during which commentarial material gradually became part of the canonical text during oral transmission. This relates to the problem of inaccurate monitoring of the source from which a particular type of information stems, which can be related to the potential impact of mindfulness on the generation of false memories. Although the cultivation of mindfulness tends to strengthen various aspects of memory, its potential to empower the mind’s ability to associate can at times result in errors of memory or recognition. The overall picture that emerges in this way helps understand a pattern evident in early Buddhist oral texts, which reflect a concern with precise transmission but at the same time also show substantial additions of later material.