bluuebunny/crossref_metadata_2025_split huggingface dataset:
Density compensated diodes for small field dosimetry: comprehensive testing and implications for design
Authors: Georgiou Georgios , Kumar Sudhir , Würfel Jan U , Underwood Tracy S A , Thompson James M , Hill Mark A , Rowbottom Carl G , Fenwick John D 
Published: May 2020

Abstract

Purpose. In small megavoltage photon fields, the accuracies of an unmodified PTW 60017-type diode dosimeter and six diodes modified by adding airgaps of thickness 0.6–1.6 mm and diameter 3.6 mm have been comprehensively characterized experimentally and computationally. The optimally thick airgap for density compensation was determined, and detectors were micro-CT imaged to investigate differences between experimentally measured radiation responses and those predicted computationally. Methods. Detectors were tested on- and off-axis, at 5 and 15 cm depths in 6 and 15 MV fields ≥ 0.5 × 0.5 cm2. Computational studies were carried out using the EGSnrc/BEAMnrc Monte Carlo radiation transport code. Experimentally, radiation was delivered using a Varian TrueBeam linac and doses absorbed by water were measured using Gafchromic EBT3 film and ionization chambers, and compared with diode readings. Detector response was characterized via the

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formalism, choosing a 4 × 4 cm2 reference field. Results. For the unmodified 60017 diode, the maximum error in small field doses obtained from diode readings uncorrected by

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factors was determined as 11.9% computationally at +0.25 mm off-axis and 5 cm depth in a 15 MV 0.5 × 0.5 cm2 field, and 11.7% experimentally at −0.30 mm off-axis and 5 cm depth in the same field. A detector modified to include a 1.6 mm thick airgap performed best, with maximum computationally and experimentally determined errors of 2.2% and 4.1%. The 1.6 mm airgap deepened the modified dosimeter’s effective point of measurement by 0.5 mm. For some detectors significant differences existed between responses in small fields determined computationally and experimentally, micro-CT imaging indicating that these differences were due to within-tolerance variations in the thickness of an epoxy resin layer. Conclusions. The dosimetric performance of a 60017 diode detector was comprehensively improved throughout 6 and 15 MV small photon fields via density compensation. For this approach to work well with good detector-to-detector reproducibility, tolerances on dense component dimensions should be reduced to limit associated variations of response in small fields, or these components should be modified to have more water-like densities.
Estimation of the single-particle band gap and exciton binding energy in two dimensional insulators: a modified G0W0-BSE method approach
Authors: Rukelj Zoran , Despoja Vito 
Published: May 2020

Abstract
In this paper we present an alternative G0W0-BSE procedure, suitable for calculation of the quasi-particle and optical properties in 2D semiconductors. The method completely excludes the spurious Coulomb interaction with 2D crystal replicas. The calculated band gap energies of hexagonal boron nitride (hBN), MoS2 and MoTe2 monolayers are in good agreement with other theoretical results. The 2D Bethe–Salpeter equation is derived and reduced to a 2D-hydrogen Schrödinger equation in which enter the G0W0 band gap, DFT effective masses, and RPA screened Coulomb interaction. This formulation is applied to the problems of determining exciton binding energies and estimating the quasiparticle band gap in hBN, as well as in some transition-metal dichalcogenides. A semiclassical procedure is used in the limit of high polarizability λ in order to obtain the analytical expression for exciton binding energies.
Universal spectral features of different classes of random-diffusivity processes
Authors: Sposini Vittoria , Grebenkov Denis S , Metzler Ralf , Oshanin Gleb , Seno Flavio 
Published: May 2020

Abstract
Stochastic models based on random diffusivities, such as the diffusing-diffusivity approach, are popular concepts for the description of non-Gaussian diffusion in heterogeneous media. Studies of these models typically focus on the moments and the displacement probability density function. Here we develop the complementary power spectral description for a broad class of random-diffusivity processes. In our approach we cater for typical single particle tracking data in which a small number of trajectories with finite duration are garnered. Apart from the diffusing-diffusivity model we study a range of previously unconsidered random-diffusivity processes, for which we obtain exact forms of the probability density function. These new processes are different versions of jump processes as well as functionals of Brownian motion. The resulting behaviour subtly depends on the specific model details. Thus, the central part of the probability density function may be Gaussian or non-Gaussian, and the tails may assume Gaussian, exponential, log-normal, or even power-law forms. For all these models we derive analytically the moment-generating function for the single-trajectory power spectral density. We establish the generic 1/f
2-scaling of the power spectral density as function of frequency in all cases. Moreover, we establish the probability density for the amplitudes of the random power spectral density of individual trajectories. The latter functions reflect the very specific properties of the different random-diffusivity models considered here. Our exact results are in excellent agreement with extensive numerical simulations.
Rabi oscillation study of strong coupling in a plasmonic nanocavity
Authors: Huang Yuming , Wu Fan , Yu Li 
Published: May 2020

Abstract
Strong interaction between emitters and plasmonic nanocavity has various applications in quantum fields at room temperature. As Rabi oscillation gives the direct proof to the energy exchange in strong coupling, it is more intuitive and necessary to analyze the interaction in time domain. In this paper, we give the Rabi oscillation in a high-dissipation plasmonic nanocavity by using full-quantum method and draw a new strong coupling criterion about mode volume which provides a significant guidance in plasmonic nanocavitys nanofabrication. Moreover, we reveal the relation between Rabi oscillation and Rabi splitting, which is beneficial for exploring emitter–plasmon hybrid systems time-domain property through frequency-domain response. An emitter–hexagon hybrid system with ultrasmall mode volume is designed to verify our theory. The numerical simulation shows good agreements with our theoretical results. Our work has applications in quantum information and quantum computing in the future.
Cyclone Fani: the tug-of-war between regional warming and anthropogenic aerosol effects
Authors: Zhao Lin , Simon Wang S-Y , Becker Emily , Yoon Jin-Ho , Mukherjee Avik 
Published: May 2020

Abstract
Before Cyclone Amphan took place in 2020, Cyclone Fani (May 2019) is the strongest pre-monsoon cyclone in the Bay of Bengal (BOB) since 1991, killing 90 people in eastern India and Bangladesh while causing US$1.81 billion of damages. Fani developed during a period of high concentration of anthropogenic aerosols in the BOB with abnormally high sea surface temperature (SST), thereby presenting an opportunity to understand the compound effects of atmospheric aerosols and regional climate warming on a tropical cyclone. A quantitative attribution analysis was conducted using the Weather Research and Forecasting model with chemistry (WRF-Chem) run at the convection-permitting (4 km) grid spacing, accompanied by an ensemble of coarser-resolution simulations to quantify the uncertainty. The removal of post-1990 trends in the tropospheric variables and SST from WRF-Chem’s initial conditions (IC) and boundary conditions (BC, including the lateral and lower boundary conditions) resulted in a reduction of cyclone precipitation by about 51% during the 5 d of April 28-May 2. The removal of tropospheric warming shows approximately twice as strong an effect on Fani (39% reduction in precipitation) as that of SST warming (22% reduction). When aerosol’s direct and indirect effects were removed from the simulations, i.e., no aerosol influence on radiation and cloud microphysics, Fani initially strengthened but later weakened, as measured by geopotential height and precipitation amounts. These results suggest that aerosol and its interaction with the atmosphere acted to mitigate the strengthening effect of anthropogenic warming on Fani, but was not strong enough to entirely counteract it. Although the ensemble of coarser simulations appears to overestimate Cyclone Fani in terms of precipitation, the direction of the effects is in agreement with that obtained from the 4 km simulations. Given the increasing anthropogenic aerosols in the BOB, future attribution studies using more sophisticated dynamical aerosol models on BOB tropical cyclones are urged.
Green space structures and schizophrenia incidence in Taiwan: is there an association?
Authors: Chang Hao-Ting , Wu Chih-Da , Wang Jung-Der , Chen Po-See , Wang Ying-Jan , Su Huey-Jen 
Published: May 2020

Abstract
A growing body of research indicates overall greenness offers potential psychological benefits. However, few studies have explored green space structures and their potential association with mental disorders. The aim of this study was to determine the existence of such an association. From two million randomly sampled people in Taiwan’s National Health Insurance Research Database, we selected 3823 patients that received a first-time diagnosis of schizophrenia from 2005–2016. Moreover, we used a geographic information system and a landscape index to quantify three characteristics of green space structures including area and edge, shape, and proximity. Additionally, we collected the normalized difference vegetation index and enhanced vegetation index data to reconfirm the association between overall greenness and schizophrenia incidence. We used the indices to determine individuals’ exposure according to their residential township. Spearman’s correlation analysis was conducted to select variables by considering their collinearity. Cox proportional-hazards models were applied to assess the relationship between green space exposure and schizophrenia incidence following adjustment for potential confounders, such as air pollution (NO2, SO2, ozone, and PM10), temperature, precipitation, and socioeconomic status, which are risk factors. We found a negative association between most green space structures indices and schizophrenia incidence. Our findings suggest that for green spaces, a larger mean patch area and edge density, higher complex (higher perimeter–area ratio), and greater proximity (higher contiguity index, aggregation index, and contagion index), may reduce the risk of schizophrenia. A sensitivity test and subgroup analysis revealed similar results.
Quantum metric statistics for random-matrix families
Authors: Berry M V , Shukla Pragya 
Published: May 2020

Abstract
The quantum metric tensor G

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for parameterised families of quantum states, in particular the trace G = trG

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, depends on the symmetry of the system (e.g. time-reversal), and the dimension N of the underlying matrices. Modelling the families by the stationary Gaussian ensembles of random-matrix, theory, we calculate the probability distribution of G, exactly for N = 2, and approximately for N = 3 and N → ∞. Codimension arguments establish the scalings of the distributions near the singularities at G → ∞ and G = 0, near which asymptotics gives the explicit analytic behaviour. Numerical simulations support the theory.
Bipolar photoresponse ultraviolet photodetectors based on ZnO nanowires
Authors: Zarezadeh E , Ghorbani A 
Published: May 2020

Abstract
A comparative study on the photoresponse of zinc oxide nanowires in direct-current (DC) and alternating-current (AC) domains is presented. Zinc oxide ultraviolet photodetectors exhibit positive photoconductivity in DC domain which means that the resistance decreases upon illumination. However, in the frequency domain, zinc oxide nanowires exhibit a solid frequency-modulated response to the ultraviolet illumination leading to a tunable photoconductivity. It is shown that in AC domain the photoresponse of zinc oxide nanowires can be finely adjusted from the positive photoconductivity (resistance decrement) to negative photoconductivity (resistance increment) simply by tuning the driving frequency. Frequency-modulated photoresponse of zinc oxide nanostructures provides an exclusive platform for the realization of dual-response or bipolar photoresponse ultraviolet photodetectors which could be of high technological importance. The zinc oxide nanowires exhibit a responsivity of +180 mA W−1 to the ultraviolet illumination in the DC mode. The nanowires show an almost equal but negative responsivity in the AC domain. Practical implication of the bipolar ultraviolet photodetectors based on ZnO nanowires is presented.
Fast Learning Through Deep Multi-Net CNN Model For Violence Recognition In Video Surveillance
Authors: Mumtaz Aqib , Bux Sargano Allah , Habib Zulfiqar 
Published: May 2020

AbstractThe violence detection is mostly achieved through handcrafted feature descriptors, while some researchers have also employed deep learning-based representation models for violent activity recognition. Deep learning-based models have achieved encouraging results for fight activity recognition on benchmark data sets such as hockey and movies. However, these models have limitations in learning discriminating features for violence activity classification with abrupt camera motion. This research work investigated deep representation models using transfer learning for handling the issue of abrupt camera motion. Consequently, a novel deep multi-net (DMN) architecture based on AlexNet and GoogleNet is proposed for violence detection in videos. AlexNet and GoogleNet are top-ranked pre-trained models for image classification with distinct pre-learnt potential features. The fusion of these models can yield superior performance. The proposed DMN unleashed the integrated potential by concurrently coalescing both networks. The results confirmed that DMN outperformed state-of-the-art methods by learning finest discriminating features and achieved 99.82% and 100% accuracy on hockey and movies data sets, respectively. Moreover, DMN has faster learning capability i.e. 1.33 and 2.28 times faster than AlexNet and GoogleNet, which makes it an effective learning architecture on images and videos.
Protecting the outside: biological tools to manipulate the skin microbiota
Authors: O'Sullivan Julie N , Rea Mary C , Hill Colin , Ross R Paul 
Published: May 2020

ABSTRACT
Interest surrounding the role that skin microbes play in various aspects of human health has recently experienced a timely surge, particularly among researchers, clinicians and consumer-focused industries. The world is now approaching a post-antibiotic era where conventional antibacterial therapeutics have shown a loss in effectiveness due to overuse, leading to the looming antibiotic resistance crisis. The increasing threat posed by antibiotic resistance is compounded by an inadequate discovery rate of new antibiotics and has, in turn, resulted in global interest for alternative solutions. Recent studies have demonstrated that imbalances in skin microbiota are associated with assorted skin diseases and infections. Specifically, restoration of this ecosystem imbalance results in an alleviation of symptoms, achieved simply by applying bacteria normally found in abundance on healthy skin to the skin of those deficient in beneficial bacteria. The aim of this review is to discuss the currently available literature on biological tools that have the potential to manipulate the skin microbiota, with particular focus on bacteriocins, phage therapy, antibiotics, probiotics and targets of the gut-skin axis. This review will also address how the skin microbiota protects humans from invading pathogens in the external environment while discussing novel strategies to manipulate the skin microbiota to avoid and/or treat various disease states.
From Montserrat to Settler-Colonial Australia: the Intersecting Histories of Caribbean Slave-owning Families, Transported British Radicals, and Indigenous Peoples
Authors: Curthoys Ann 
Published: May 2020

Abstract
When the British government abolished slavery in the Caribbean and compensated the slave-owners, some of the beneficiaries and/or their children and grandchildren went to Australia to make a new life and if possible a new fortune. This essay traces the history of one such family, the Shiells of Montserrat, alongside two other contemporaneous histories – that of Yorkshire radical and convict, John Burkinshaw, and his family, into which one of the Shiells married, and that of the several Indigenous communities these families encountered. Through the experiences of these disparate and intersecting family groups, we can gain insight into both the lived experience and the wider imperial context of the expansion of Australian settler colonialism.
Variational analysis of the discontinuous Galerkin time-stepping method for parabolic equations
Authors: Saito Norikazu 
Published: May 2020

Abstract
The discontinuous Galerkin (DG) time-stepping method applied to abstract evolution equation of parabolic type is studied using a variational approach. We establish the inf-sup condition or Babuška–Brezzi condition for the DG bilinear form. Then, a nearly best approximation property and a nearly symmetric error estimate are obtained as corollaries. Moreover, the optimal order error estimates under appropriate regularity assumption on the solution are derived as direct applications of the standard interpolation error estimates. Our method of analysis is new for the DG time-stepping method; it differs from previous works by which the method is formulated as the one-step method. We apply our abstract results to the finite element approximation of a second-order parabolic equation with space-time variable coefficient functions in a polyhedral domain, and derive the optimal order error estimates in several norms.
Economic evaluations of big data analytics for clinical decision-making: a scoping review
Authors: Bakker Lytske , Aarts Jos , Uyl-de Groot Carin , Redekop William 
Published: May 2020

AbstractObjectiveMuch has been invested in big data analytics to improve health and reduce costs. However, it is unknown whether these investments have achieved the desired goals. We performed a scoping review to determine the health and economic impact of big data analytics for clinical decision-making.Materials and MethodsWe searched Medline, Embase, Web of Science and the National Health Services Economic Evaluations Database for relevant articles. We included peer-reviewed papers that report the health economic impact of analytics that assist clinical decision-making. We extracted the economic methods and estimated impact and also assessed the quality of the methods used. In addition, we estimated how many studies assessed “big data analytics” based on a broad definition of this term.ResultsThe search yielded 12 133 papers but only 71 studies fulfilled all eligibility criteria. Only a few papers were full economic evaluations; many were performed during development. Papers frequently reported savings for healthcare payers but only 20% also included costs of analytics. Twenty studies examined “big data analytics” and only 7 reported both cost-savings and better outcomes.DiscussionThe promised potential of big data is not yet reflected in the literature, partly since only a few full and properly performed economic evaluations have been published. This and the lack of a clear definition of “big data” limit policy makers and healthcare professionals from determining which big data initiatives are worth implementing.
Optimization of Nitrogen Fertilizer Application Enhances Biocontrol Function and Net Income
Authors: Wang Leyun , Gao Feng , Reddy Gadi V P , Zhao Zihua 
Published: May 2020

Abstract
The intensive use of nitrogen fertilizer has been a common approach for pursuing higher crop yields. However, the ecological effects of such use on the tritrophic interactions (crop–insect pest–natural enemy) and on the ecological and economic benefits of such use are poorly understood. Here, we investigated the effects of low, medium, and high levels of nitrogen fertilizer inputs (70, 140, and 280 kg/ha/yr) on cereal aphid (Sitobion avenae Fabricius [Hemiptera: Aphididae], Schizaphis graminum Rondani [Hemiptera: Aphididae], and Rhopalosiphum padi L. [Hemiptera: Aphididae]) abundance, primary parasitism rates, crop yield, and net income in winter wheat (Triticum aestivum [Poales: Poaceae] cv. Zhou 22) for 2 yr. A higher input of nitrogen fertilizer significantly enhanced the abundance of cereal aphids, while their primary parasitism rates (26.9 ± 3.5% in 2018 and 24.9 ± 4.5% in 2019) were highest at the medium nitrogen level. The performance of participants in the wheat–aphids–parasitoids system was likewise mediated by the nitrogen fertilizers. Meanwhile, wheat yield significantly increased with moderate increases in the nitrogen level, although overuse of nitrogen fertilizer did not significantly further enhance wheat yield. Finally, we found either low or overuse of nitrogen fertilizers resulted in lower net income than did medium nitrogen fertilization. These results demonstrate the need to reevaluate and adjust fertilizer use to optimize the eco-economic and sustainable management of agroecosystems.
Detection of Asian Citrus Psyllid (Hemiptera: Psyllidae) in Ethiopia: A New Haplotype and its Implication to the Proliferation of Huanglongbing
Authors: Ajene Inusa J , Khamis Fathiya , Ballo Shifa , Pietersen Gerhard , van Asch Barbara , Seid Nurhussen , Azerefegne Ferdu , Ekesi Sunday , Mohamed Samira 
Published: May 2020

AbstractDiaphorina citri Kuwayama, also known as the Asian citrus psyllid, is a pest of citrus known for its transmission of Candidatus Liberibacter asiaticus (Ca. L. asiaticus), the causal bacterium of Huanglongbing. The African citrus triozid Trioza erytreae (Del Guercio) (Hemiptera: Triozidae) has been the putative vector of Candidatus Liberibacter africanus (Ca. L. africanus) which causes the African citrus greening disease, until the recent detection of D. citri on the continent. Following reports of D. citri in Kenya and Tanzania, we surveyed citrus plants to establish the presence/absence of D. citri in Ethiopia in citrus-growing regions ranging from 900 to 2,460 m above sea level (masl). Diaphorina citri adults were detected in five of the surveyed sites in Ethiopia. Adult insects encountered were collected using an aspirator and stored in 97% ethanol. The mitochondrial cytochrome oxidase 1 (mt COI) gene of the collected insects was amplified using LepF1/LepR1 primers, and sequences obtained showed low variation, which fell within the acceptable range of species. BLAST was used to query the sequences obtained, and all the sequences linked to D. citri accessions that are available in GenBank. The analysis of the sequences revealed a new haplotype of the species that differs from haplotypes previously reported. Phylogenetic relationships of our samples and other D. citri reference sequences was inferred using the Maximum-likelihood method. Monophyly was observed between the samples and the publicly available sequences from global accessions. This is the first report of the presence of D. citri in Ethiopia.