bluuebunny/crossref_metadata_2025_split huggingface dataset:
Infrared Fourier Spectrometer 2 (IKFS‐2) radiance assimilation at ECMWF
Authors: Eresmaa Reima 
Published: September 2020

AbstractMeteorological satellites launched as part of the Russian space programme have not been widely used in global numerical weather prediction (NWP) to date. There is particular interest in the Meteor‐M series of sun‐synchronous spacecraft, as it is anticipated that future launches will operate in currently unobserved orbital planes complementary to those occupied by Europe, the United States, and China. One of the sensors carried on board these satellites is the Infrared Fourier Spectrometer 2 (IKFS‐2), which observes a spectrum of atmospheric radiation over the wavenumber range 660–2,000.5 cm−1. The IKFS‐2 is thus similar to earlier hyperspectral sensors such as the Infrared Atmospheric Sounding Interferometer (IASI) and the Cross‐track Infrared Sounder (CrIS), both of which have been used operationally at the European Centre for Medium‐range Weather Forecasts (ECMWF) for many years. This study investigates the quality of IKFS‐2 radiance measurements from the Meteor‐M‐N2 satellite and performs assimilation experiments to assess the impact of these data on the ECMWF analysis and forecasting system. Measured by statistical indicators of the observation fit to short‐range forecasts, the IKFS‐2 performs as well as IASI and CrIS amongst channels sensitive to stratospheric and tropospheric temperature. The assimilation experiments indicate up to 0.5% improvement in headline forecast scores, although the medium‐range impact is mixed and for most parts nonsignificant. One factor that currently limits the impact of IKFS‐2 is poor data timeliness and availability: observations are available for assimilation typically only 75% of the time during the test periods. It is expected, though, that such logistical problems can be overcome, and efforts are already underway to improve data dissemination.
Evaluation of adjoint‐based observation impacts as a function of forecast length using an Observing System Simulation Experiment
Authors: Privé N.C. , Errico Ronald M. , Todling Ricardo , El Akkraoui Amal 
Published: September 2020

AbstractAdjoints of numerical weather prediction models may be employed for forecast sensitivity to observations (FSO) in order to monitor the contribution of ingested observation data on short‐term forecast skill. However, the calculation of short‐term forecast error is difficult, due to the lack of a truly independent dataset for verification. In an Observing System Simulation Experiment (OSSE) framework, the Nature Run is able to provide a true and complete verification dataset and allows accurate evaluation of short‐term forecast errors. In this work, an OSSE developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office is used to explore the impact of observational data on forecasts in the 6–48 hour range. An adjoint of the Global Earth Observing System model is employed to compare the observation impacts estimated using both self‐analysis verification and the true Nature Run verification. Self‐analysis verification is found to inflate the estimated forecast‐error growth during the early forecast period, resulting in overestimations of observation impacts, particularly in the 6–12 hour forecast range. By 48 hours, the self‐analysis verification estimates of forecast error and observation impacts match the true values more closely. The fraction of beneficial observations is also overinflated at short forecast times when self‐analysis verification is used. The progression of impacts of an individual observation or data type depends on the character of growth of the initial‐condition error that each observation affects.
Prediction of the quasi‐biennial oscillation with a multi‐model ensemble of QBO‐resolving models
Authors: Stockdale Timothy N. , Kim Young‐Ha , Anstey James A. , Palmeiro Froila M. , Butchart Neal , Scaife Adam A. , Andrews Martin , Bushell Andrew C. , Dobrynin Mikhail , Garcia‐Serrano Javier , Hamilton Kevin , Kawatani Yoshio , Lott Francois , McLandress Charles , Naoe Hiroaki , Osprey Scott , Pohlmann Holger , Scinocca John , Watanabe Shingo , Yoshida Kohei , Yukimoto Seiji 
Published: September 2020

AbstractA multi‐model study is carried out to investigate the ability of models to predict the evolution of the quasi‐biennial oscillation (QBO) up to 12 months in advance. All models are initialised from common reanalysis data, and forecasts run for a common set of 30 start dates over 15 years. All models have high skill in predicting the phase evolution of the QBO at 20–30 hPa, with slightly more variable results at higher and lower levels. Other aspects of the predicted QBO are of variable quality, and in some cases are consistently poor. QBO easterlies are too weak in all models at 20–50 hPa, while westerlies can be either too strong or too weak. This results in both a reduced amplitude of the QBO and a westerly bias in zonal‐mean winds, notably at 30 hPa. At 70 hPa models tend to have reduced QBO amplitude and an easterly bias. Despite these failings, a multi‐model ensemble of bias‐ and variance‐corrected forecasts can be used to give accurate and reliable QBO forecasts up to at least a year ahead. Analysis of the zonal momentum budget during the first month of the forecast shows that large‐scale forcing from Eliassen–Palm flux divergence and vertical advection are handled fairly well by the models, although vertical advection terms tend to be weaker than reanalysis estimates. Total tendencies show common errors, suggesting common failings in gravity‐wave drag treatments. Teleconnections from the QBO to Northern Hemisphere winter circulation are also examined, and do not appear to be realistic beyond the first month. Analysis of initialised forecasts is a powerful tool for diagnosing the accuracy of model processes driving the QBO.
A mixed HWMA‐CUSUM mean chart with an application to manufacturing process
Authors: Abid Muhammad , Mei Sun , Nazir Hafiz Zafar , Riaz Muhammad , Hussain Shahid 
Published: September 2020

AbstractMemory‐type control charts play a significant role to identify slight changes in the parameters of the production process. In this article, we have proposed a new cumulative sum chart that utilizes the statistic of the homogeneously weighted moving average chart. The performance of the proposed chart is studied using Monte Carlo simulations. The proposed chart is compared with some existing charts under different run length profiles. The run length profile comparisons reveal that the proposed chart performs superior as compared to the existing control charts. A real‐life application using a manufacturing process dataset is also part of this study.
Unique features and emerging in vitro models of human placental development
Authors: Shibata Shun , Kobayashi Eri H. , Kobayashi Norio , Oike Akira , Okae Hiroaki , Arima Takahiro 
Published: September 2020

AbstractBackgroundThe placenta is an essential organ for the normal development of mammalian fetuses. Most of our knowledge on the molecular mechanisms of placental development has come from the analyses of mice, especially histopathological examination of knockout mice. Choriocarcinoma and immortalized cell lines have also been used for basic research on the human placenta. However, these cells are quite different from normal trophoblast cells.MethodsIn this review, we first provide an overview of mouse and human placental development with particular focus on the differences in the anatomy, transcription factor networks, and epigenetic characteristics between these species. Next, we discuss pregnancy complications associated with abnormal placentation. Finally, we introduce emerging in vitro models to study the human placenta, including human trophoblast stem (TS) cells, trophoblast and endometrium organoids, and artificial embryos.Main findingsThe placental structure and development differ greatly between humans and mice. The recent establishment of human TS cells and trophoblast and endometrial organoids enhances our understanding of the mechanisms underlying human placental development.ConclusionThese in vitro models will greatly advance our understanding of human placental development and potentially contribute to the elucidation of the causes of infertility and other pregnancy complications.
River connectivity restoration for upstream‐migrating European river lamprey: The efficacy of two horizontally‐mounted studded tile designs
Authors: Lothian Angus J. , Tummers Jeroen S. , Albright Atticus J. , O'Brien Pat , Lucas Martyn C. 
Published: September 2020

AbstractMany rivers are heavily fragmented, resulting from anthropogenic cross‐channel structures. Cost‐effective solutions are needed to restore habitat connectivity for migratory fishes, including those of conservation concern, such as the European river lamprey (Lampetra fluviatilis). Studded material is becoming increasingly used as a low‐cost retrofit solution for lamprey passage at sloping weirs, although little is known about the efficacy of the material or what stud arrangements may be most effective. This study tested whether expanding a single‐density studded tile (SDT) lane from 1 to 2‐m width increased passage success (nreleased = 133), and also compared the passage performance between a SDT lane and a dual‐density studded tile (DDT) lane (nreleased = 115) at a sloping weir, using PIT telemetry. No passage was recorded (nattempted = 89) at the 2‐m wide SDT lane, but 61.6% (npassed/attempted = 53/86) passed using DDT/SDT lane combination. However, increased passage efficiency was likely a result of high river flow (Q2.0‐Q30.6) during DDT/SDT comparison versus low (Q8.3‐Q88.5) while the 2‐m wide SDT lane was employed. There was no evidence that passage occurred using solely one stud configuration. It is, therefore, hypothesised that passage of river lamprey at weirs is more dependent on flow regime than the provision of either stud configuration. However, with 46.1% (npassed/released = 53/115) of those released during DDT/SDT comparison passing on the instrumented section (10.5% of weir face), the provision of studded tiles may aid in lamprey passage at high flows, presumably as the tiles generate a low‐velocity boundary layer that can be utilised as lamprey swim above the studs.
Spectroscopic Determination of Ice‐Induced Interfacial Strain on Single‐Layer Graphene
Authors: Kattel Subash , Scougale William R. , Murphy Joseph R. , Pasco Samuel R. , Ackerman John , Alvarado Vladimir , Rice William D. 
Published: September 2020

AbstractReliably determining the physical properties of ice (e.g., crystal structure, adhesion strength, interfacial state, and molecular orientation) has proven to be both challenging and highly dependent on experiment‐specific conditions, including surface roughness, ice formation, water purity, and measurement method. Here, non‐destructive measurements of single‐layer graphene (SLG) interfaced with bulk ice are used to determine temperature‐dependent, ice‐induced strain and estimate ice‐created strain elastic density in SLG. The use of SLG enables the precise study of interfacial strain by monitoring the 2D Raman mode. Upon ice formation, a clear, ≈2 cm−1 decrease in the 2D mode frequency is observed, which is ascribed to a 0.012% biaxial tensile shear strain at the ice–SLG interface. From this shear strain value, the ice‐created SLG elastic strain energy density is estimated to be 2.4 μJ m−2. In addition to these Raman strain measurements, intentionally ionized water is used to show that water‐mediated charging of the SLG surface manifests itself in a distinctly different manner than ice‐induced strain. Finally, the localized nature of the Raman probe is used to map SLG regions with and without ice, suggesting that this method cannot only determine ice‐induced interfacial strain, but also correlate ice adhesion properties with surface roughness and topology.
Cascade Reactions Catalyzed by Planar Metal–Organic Framework Hybrid Architecture for Combined Cancer Therapy
Authors: Mu Jing , He Liangcan , Fan Wenpei , Tang Wei , Wang Zhantong , Jiang Chao , Zhang Dongyang , Liu Yijing , Deng Hongzhang , Zou Jianhua , Jacobson Orit , Qu Junle , Huang Peng , Chen Xiaoyuan 
Published: September 2020

AbstractChemical transformation in cellular environment is critical for regulating biological processes and metabolic pathways. Harnessing biocatalytic cascades to produce chemicals of interest has become a research focus to benefit industrial and pharmaceutic areas. Nanoreactors, which can act as artificial cell‐like devices to organize cascade reactions, have been recently proposed for potential therapeutic applications for life‐threatening illnesses. Among various types of nanomaterials, there is a growing interest in 2D metal–organic frameworks (MOFs). By virtue of the ultralarge specific surface area, high porosity, and structural diversity, 2D MOF nanosheets hold great promise for a broad spectrum of biomedical use. Herein, a unique planar MOF‐based hybrid architecture (GMOF‐LA) is introduced by incorporating ultrasmall gold nanoparticles (Au NPs) as nanozyme and l‐Arginine (l‐Arg) as nitric oxide (NO) donor. The prepared Au NPs enable oxidation of glucose into hydrogen peroxide, which drives biocatalytic cascades to covert l‐Arg into NO. Interestingly, the well‐designed nanosheets not only possess excellent catalytical activity for NO generation, resulting in gas therapeutic effect, but also serve as a desired photosensitizer for photodynamic therapy. This study establishes a good example of exploring bioinspired nanoreactors for cooperative anticancer effect, which may pave the path for future “bench‐to‐bedside” design of nanomedicine.
Keywords‐driven web APIs group recommendation for automatic app service creation process
Authors: Gong Wenwen , Lv Chao , Duan Yucong , Liu Zengguang , Khosravi Mohammad R. , Qi Lianyong , Dou Wanchun 
Published: September 2020

SummaryWith the ever‐increasing popularity of web application programming interfaces (APIs) sharing communities, it is becoming a promising way for software developers to design and create their interesting Apps through composing a set of selected web APIs that can collectively fulfill the App functions expected by the App developer. However, the App developer's web APIs selection decision‐makings are often nontrivial due to the massive candidate APIs as well as their diverse functions. Furthermore, it is difficult to guarantee that the selected web APIs are compatible enough. Moreover, traditional web APIs recommendation approaches only return a recommended APIs list, which are often not sufficient to accommodate the App developer's undetermined and fuzzy personalized preferences. Considering the above challenges, a novel keywords‐driven web APIs recommendation approach called keywords‐driven and compatibility‐aware multiple API group recommendation is proposed in this article for green and compatible software, which cannot only satisfy the App developer's functional requirements, but also return a group of web APIs recommended lists. Each returned list includes a set of compatible web APIs. Finally, we design a series of experiments based on a real‐world web APIs dataset, that is, PW dataset crawled from www.programmableWeb.com. Experimental reports compared with other competitive approaches in existing literatures indicate the effectiveness and efficiency of our proposal in this work.
A machine learning framework for domain generating algorithm based malware detection
Authors: G. P. Akhila , R. Gayathri , S. Keerthana , Gladston Angelin 
Published: September 2020

AbstractReal‐time detection of domain names that are generated using the domain generating algorithms (DGA) is a challenging cyber security challenge. Traditional malware control methods, such as blacklisting, are insufficient to handle DGA threats. In this paper, a machine learning framework for identifying and detecting DGA domains is proposed to alleviate the threat. The proposed machine learning framework consists of a two‐level model. In the two‐level model, the DGA domains are classified apart from normal domains and then the clustering method is used to identify the algorithms that generate those DGA domains.
Development and validation of a gas chromatography–mass spectrometry method for determination of 30 fragrance substances in cosmetic products
Authors: Fardin‐Kia Ali Reza , Zhou Wanlong 
Published: September 2020

AbstractA QuEChERS sample preparation, for a broad‐range of cosmetic products, followed by gas chromatography–mass spectrometry analysis was developed for the simultaneous determination of 30 fragrance substances. The sample preparation step was optimized for different leave‐on and rinse‐off cosmetic products. A small amount of sample (1 g) was extracted with acetonitrile, the extract was subject to a rapid QuEChERS clean up followed by centrifugation and the organic layer was collected for gas chromatography–mass spectrometry analysis. The gas chromatography–mass spectrometry method was developed on a mid‐polarity GC capillary column (30 m, ZB‐35HT) to obtain maximum separation of the targeted compounds in less than 60 min. Using this method, the method limit of detection and the method limit of quantitation for the 30 fragrance substances, were determined as 0.1–1.2 µg/g and 0.33–4.0 µg/g, respectively. For most of the fragrance substances, the spike recovery values were 80–120% with a relative standard deviation < 10% for all fragrance substances in three tested matrices (shampoo, lotion, and deodorant). This method was applied to evaluate 42 commercial cosmetic products purchased from nine different countries. Of the 30 leave‐on products, 18 products measured at least one fragrance above 10 µg/g and 5 of the 12 rinse‐off products measured at least one fragrance above 100 µg/g. According to the European regulation (EC, No 1223/2009, ANNEX III), 24 of these fragrance substances are subject to specific labeling requirements if any individual concentration exceeds 10 µg/g for leave‐on and 100 µg/g for rinse‐off products. Our results show that this method can be applied to various cosmetic products for determination of fragrance substances designated “allergens” in the European Union.
Effect of Different Modifications (Physical and Chemical) on Morphological, Pasting, and Rheological Properties of Black Rice (Oryza sativa L. Indica) Starch: A Comparative Study
Authors: Dhull Sanju Bala , Punia Sneh , Kumar Manoj , Singh Shivdeep , Singh Parhlad 
Published: September 2020

AbstractThe demand for black rice has increased rapidly in the past years because of the distinctive color, characteristic flavor, nutritional value, and health benefits. This study aims to investigate the chemical and physical modifications on morphology, pasting, thermal, and rheological properties of black rice starch. The highest swelling power is observed for octenyl succinic anhydride modified black rice starch whereas gamma irradiated rice starch shows the lowest value. Rheometer analysis shows that physical and chemical modifications generally alter the pasting characteristics of starches which may be attributed to the excessive degradation of starch granules. Native black rice starch granules are of small size and irregular in shapes with sharp angles and edges. After modifications, rice starch granules surface lose natural morphology. All native and modified rice starch exhibit the typical A‐type X‐ray patterns of cereal starches. Results of present study provides a better understanding of functional properties of native and modified black rice starches for their possible applications in food products.
Evaluating the complexity of engineered systems: A framework informed by a user case study
Authors: Potts Matthew W. , Johnson Angus , Bullock Seth 
Published: September 2020

AbstractEvaluating the complexity of an engineered system is challenging for any organization, even more so when operating in a System‐of‐Systems (SoS) context. Here, we analyze one particular decision support tool as an illustratory case study. This tool has been used for several years by Thales Group to evaluate system complexity across a variety of industrial engineering projects. The case study is informed by analysis of semistructured interviews with systems engineering experts within the Thales Group. This analysis reveals a number of positive and negative aspects of (i) the tool itself and (ii) the way in which the tool is embedded operationally within the wider organization. While the first set of issues may be solved by making improvements to the tool itself, informed by further comparative analysis and growing literature on complexity evaluation, the second “embedding challenge” is distinct, seemingly receiving less attention in the literature. In this paper, we focus on addressing this embedding challenge, by introducing a complexity evaluation framework, designed according to a set of principles derived from the case study analysis; namely that any effective complexity evaluation activity should feature collaborative effort toward building an evaluation informed by a shared understanding of contextually relevant complexity factors, iterative (re‐)evaluation over the course of a project, and progressive refinement of the complexity evaluation tools and processes themselves through linking project evaluations to project outcomes via a wider organizational learning cycle. The paper concludes by considering next steps including the challenge of assuring that such a framework is being implemented effectively.
Data‐driven identification and modeling of earthquake‐excited building structures regarding soil‐structure interaction
Authors: Gong Nan , Li Peizhen , Shan Jiazeng , Ouyang Yuting 
Published: September 2020

SummaryData‐driven identification and modeling of the integrated soil‐structure interaction (SSI) structure system are significantly important for real‐world structures subjected to earthquakes in various engineering disciplines. The representative mechanical modeling for the overall system with SSI effect is firstly presented, and the differential evolution algorithm is introduced for model‐based iterative identification on physical parameters including stiffness and damping coefficients. The performance and reliability of the proposed methodology are systematically investigated through a numerical model‐based parametric study. Incorporation of the model selection, the incomplete measurement and noise effect on the proposed method is revealed and discussed subsequently. Then, the present method is experimentally investigated and validated using two illustrative examples, corresponding to a 12‐story large‐scale structural model and a nine‐story real‐world building structure. The performance in terms of feasible estimation and reliable prediction by using the optimally identified physical model is demonstrated through the time history comparison of measurable acceleration responses in different seismic events.