bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of artificial neural network for forecasting standardized precipitation and evapotranspiration index: A case study of Nigeria
Authors: Ogunrinde Akinwale T. , Oguntunde Phillip G. , Fasinmirin Johnson T. , Akinwumiju Akinola S. 
Published: May 2020

AbstractThe necessity to perform an accurate prediction of future characteristics of drought requires a robust and efficient technique that can deduce from historical data the stochastic relationship or dependency between history and future. In this study, the applicability of the artificial neural network (ANN) is used for forecasting the standardized precipitation and evapotranspiration index (SPEI) at 12‐month timescale for five candidate stations in Nigeria using predictive variable data from 1985 to 2008 (training) and tested data between 2009 and 2015. The predictive variables are monthly average precipitation, average air temperature, maximum temperature, minimum temperature, mean speed, mean solar radiation, sunshine hours, and two large‐scale climate indices (Southern Oscillation Index and North Atlantic Oscillation). From the several combinations of the input variables, training algorithms, hidden, and output transfer functions, a total of eight model runs stood out using a three‐layer ANN network. The most efficient ANN model architecture had 9,8,1 as the input, hidden, and output neurons, respectively, trained using the Levenberg‐Marquardt training algorithm and tansig as the activation and hidden transfer functions. Assessment on the efficiency of the model based on statistics indicate that the coefficient of determination, root mean square error, Nash‐Sutcliffe coefficient of efficiency and the mean absolute error ranges between 0.51 and 0.82; 0.57 and 0.75; 0.28 and 0.79; 0.44 and 0.56, respectively, during the testing period. The output of these findings shows that ANN modeling technique can play a significant role as a data‐driven model in forecasting monthly SPEI time series and drought characteristics in the study area, thereby leading to the development of an early warning system for the country.
Decision makers’ preferences of policy instruments
Authors: Veselý Arnošt , Petrúšek Ivan 
Published: May 2020

AbstractThe article empirically tests the theoretical propositions on instrument choice articulated by Linder and Peters and their followers. It examines whether decision makers tend to prefer some policy instruments over others, what the patterns of these preferences are, and how they can be explained. Using a survey of Czech ministerial and regional public officials involved in strategic policymaking (N = 1,112), the findings confirm that individuals exhibit clear patterns of instrument preference that are similar to theoretical typologies. However, the data do not confirm most other theoretical expectations: decision makers do not tend to prefer some instruments over others and their preference of policy instruments cannot be explained by educational background or the organization in which they work. Other factors so far unnoticed in theory (such as sex, age, or job task) seem to play a more significant role, which calls for reconsideration of instrument choice theory.
Morphological and molecular alterations of reactive astrocytes without proliferation in cerebral cortex of an APP/PS1 transgenic mouse model and Alzheimer's patients
Authors: Li Kun‐Yu , Gong Pi‐Fang , Li Jia‐Tong , Xu Nan‐Jie , Qin Song 
Published: May 2020

AbstractAstrocytes are fundamental for maintaining brain homeostasis and are commonly involved in the progression of neurodegenerative diseases including Alzheimer's disease (AD). In response to injury or toxic material, astrocytes undergo activation that results in hypertrophy and process ramification. Although numerous studies have shown that reactive astrocytes are intimately related to the pathogenesis of AD, their characteristic features including morphological and molecular alterations that occur during different stages of AD progression remain to be elucidated. Here, we crossed astrocyte‐specific reporter mice hGFAP‐CreERT2;Rosa‐tdTomato with APP/PS1 mice, and then used genetic tracing to characterize the morphological profiles and expression of molecular biomarkers associated with progressive β‐amyloid deposits in the cortical region of AD mice. Expression of glutamine synthetase (GS) was lower in cortical reactive astrocytes, in contrast to the higher expression of glial fibrillary acidic protein, of APP/PS1 mice and AD patients relative to that in cortical astrocytes of wild‐type mice and age‐matched controls, respectively. GS activity was also decreased obviously in the cortex of APP/PS1 mice at 6 and 12 months of age relative to that in the wild‐type mice of the same ages. Furthermore, cortical reactive astrocytes in APP/PS1 mice and AD patients did not undergo proliferation. Finally, based on RNA‐sequencing analysis, we identified differentially expressed transcripts of signal transduction molecules involved in early induction of reactive astrocytes in the cortex of APP/PS1 mice. These findings provide a morphological and molecular basis with which to understand the function and mechanism of reactive astrocytes in the progression of AD.
The ENIGMA‐Epilepsy working group: Mapping disease from large data sets
Authors: Sisodiya Sanjay M. , Whelan Christopher D. , Hatton Sean N. , Huynh Khoa , Altmann Andre , Ryten Mina , Vezzani Annamaria , Caligiuri Maria Eugenia , Labate Angelo , Gambardella Antonio , Ives‐Deliperi Victoria , Meletti Stefano , Munsell Brent C. , Bonilha Leonardo , Tondelli Manuela , Rebsamen Michael , Rummel Christian , Vaudano Anna Elisabetta , Wiest Roland , Balachandra Akshara R. , Bargalló Núria , Bartolini Emanuele , Bernasconi Andrea , Bernasconi Neda , Bernhardt Boris , Caldairou Benoit , Carr Sarah J.A. , Cavalleri Gianpiero L. , Cendes Fernando , Concha Luis , Desmond Patricia M. , Domin Martin , Duncan John S. , Focke Niels K. , Guerrini Renzo , Hamandi Khalid , Jackson Graeme D. , Jahanshad Neda , Kälviäinen Reetta , Keller Simon S. , Kochunov Peter , Kowalczyk Magdalena A. , Kreilkamp Barbara A.K. , Kwan Patrick , Lariviere Sara , Lenge Matteo , Lopez Seymour M. , Martin Pascal , Mascalchi Mario , Moreira José C.V. , Morita‐Sherman Marcia E. , Pardoe Heath R. , Pariente Jose C. , Raviteja Kotikalapudi , Rocha Cristiane S. , Rodríguez‐Cruces Raúl , Seeck Margitta , Semmelroch Mira K.H.G. , Sinclair Benjamin , Soltanian‐Zadeh Hamid , Stein Dan J. , Striano Pasquale , Taylor Peter N. , Thomas Rhys H. , Thomopoulos Sophia I. , Velakoulis Dennis , Vivash Lucy , Weber Bernd , Yasuda Clarissa Lin , Zhang Junsong , Thompson Paul M. , McDonald Carrie R. ,   ENIGMA Consortium Epilepsy Working Group
Published: May 2020

AbstractEpilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller‐scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well‐established by the ENIGMA Consortium, ENIGMA‐Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event‐based modeling analysis. We explore age of onset‐ and duration‐related features, as well as phenomena‐specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA‐Epilepsy.
Recovery of value‐added glycopeptides from edible bird's nest (EBN) co‐products: enzymatic hydrolysis, physicochemical characteristics and bioactivity
Authors: Ling Jin Wei Alvin , Chang Lee Sin , Babji Abdul Salam , Lim Seng Joe 
Published: May 2020

AbstractBACKGROUNDProcessing of edible bird's nest (EBN) requires extensive washing to remove impurities and produces huge amounts of EBN co‐products, which contain mainly feathers with glycoproteins attached, which are usually discarded. This study was conducted to recover the valuable EBN glycoproteins from the waste material. Enzymatic hydrolysis was applied to recover EBN glycopeptides from EBN co‐products (EBNcoP) and processed cleaned EBN (EBNclean) was used as control, which were then freeze‐dried into EBN hydrolysates (EBNhcoP and EBNhclean, respectively).RESULTSThe recovery yield for EBNhclean and EBNhcoP were 89.09 ± 0.01% and 47.64 ± 0.26%, respectively, indicating nearly 50% of glycopeptide can be recovered from the waste material. Meanwhile, N‐acetylneuraminic acid, a major acid sugar in EBN glycoproteins, of EBNhcoP increased by 229% from 58.6 ± 3.9 to 192.9 ± 3.1 g kg−1, indicating the enzymatic hydrolysis removed impurities and thus enhanced the N‐acetylneuraminic acid content. Total soluble protein was more than 330 g kg−1 for all the samples. Colour parameter showed that hydrolysate samples have greater L* (lightness) values. Chroma result indicates the intensity of all the samples were low (< 11). Fourier‐transform infrared (FTIR) spectrum displayed that the EBNhcoP exhibited similar functional groups with EBNhclean, indicating that the EBNcoP has similar functionality as EBNclean. Significantly higher (P ≤ 0.05) 1,1‐diphenyl‐2‐picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) activities were reported in EBNhcoP after the enzymatic reaction.CONCLUSIONEBNhcoP were successfully recovered from low value EBNcoP with enhanced antioxidant activities. The findings of this work are beneficial for the EBN industry to reduce wastage and enhance economic values of EBN co‐products, both economically and nutritionally. © 2020 Society of Chemical Industry
Low‐dose rapamycin‐induced autophagy in cochlear outer sulcus cells
Authors: Saegusa Chika , Hosoya Makoto , Nishiyama Takanori , Saeki Tsubasa , Fujimoto Chisato , Okano Hideyuki , Fujioka Masato , Ogawa Kaoru 
Published: May 2020

AbstractObjectivesAutophagy is an intracellular housekeeping process that degrades cytoplasmic organelles, damaged molecules, and abnormal proteins or pathogens and is essential for normal hearing. Recent studies revealed the essential roles of autophagy in hearing and balance. The aim of this study was to evaluate the activation state of rapamycin‐induced autophagy in cochlear outer sulcus cells (OSCs).MethodsWe used autophagy reporter transgenic mice expressing the green fluorescent protein‐microtubule‐associated protein light chain 3 (GFP‐LC3) fusion protein and counted GFP‐LC3 puncta in cochlear OSCs to evaluate the activation state of autophagy after oral administration of rapamycin.ResultsWe observed basal level GFP‐LC3 expression and an increase in the number of GFP‐LC3 puncta in cochlear OSCs by oral administration of rapamycin. This increase was detected when the daily rapamycin intake was as low as 0.025 mg/kg, and it was dose dependent. The increased number of puncta was more at the basal turn than the apical turn.ConclusionOral intake of low‐dose rapamycin activates autophagy in cochlear OSCs.Level of evidenceNA.
The delineation of largely deformed brain midline using regression‐based line detection network
Authors: Wei Hao , Tang Xiangyu , Zhang Minqing , Li Qingfeng , Xing Xiaodan , Sean Zhou Xiang , Xue Zhong , Zhu Wenzhen , Chen Zailiang , Shi Feng 
Published: May 2020

PurposeThe human brain has two cerebral hemispheres that are roughly symmetric and separated by a midline, which is nearly a straight line shown in axial computed tomography (CT) images in healthy subjects. However, brain diseases such as hematoma and tumors often cause midline shift, where the degree of shift can be regarded as a quantitative indication in clinical practice. To facilitate clinical evaluation, we need computer‐aided methods to automate this quantification. Nevertheless, most existing studies focused on the landmark‐ or symmetry‐based methods that provide only the existence of shift or its maximum distance, which could be easily affected by anatomical variability and large brain deformations. Intuitive results such as midline delineation or measurement are lacking. In this study, we focus on developing an automated and robust method based on the fully convolutional neural network for the delineation of midline in largely deformed brains.MethodsWe propose a novel regression‐based line detection network (RLDN) for the robust midline delineation, especially in largely deformed brains. Specifically, to improve the robustness of delineation in largely deformed brains, we regard the delineation of the midline as the skeleton extraction task and then use the multiscale bidirectional integration module to acquire more representative features. Based on the skeleton extraction, we incorporate the regression task into it to delineate more accurate and continuous midline, especially in largely deformed brains. Our study utilized the public CQ 500 dataset (128 subjects) for training with hold‐out validation on 61 subjects from a private cohort accrued from a local hospital.ResultsThe mean line distance error and F1‐score were 1.17 ± 0.72 mm with 0.78 on CQ 500 test set, and 4.15 ± 3.97 mm with 0.61 on the private dataset. Besides, significant differences (P < 0.05) were observed between our method and other comparative ones on these two datasets.ConclusionsThis work provides a novel solution to acquire robust delineation of the midline, especially in largely deformed brains, and achieves state‐of‐the‐art performance on the public and our private dataset, which makes it possible for automated diagnosis of relevant brain diseases in the future.
Wind turbine induced seismic signals: the large‐scale SMARTIE1 experiment and a concept to define protection radii for recording stations
Authors: Lerbs Nikolaus , Zieger Toni , Ritter Joachim , Korn Michael 
Published: May 2020

ABSTRACTWind turbines produce mechanical energy that can propagate to the ground and disturb sensitive measurements such as seismic recordings. The aim of the large‐scale experiment Seismic Monitoring And Research of wind Turbine Induced Emissions (SMARTIE1) at a single wind turbine in Pfinztal (SW Germany) is to understand how wind turbines emit seismic signals under different operating conditions and how these seismic signals propagate through the local subsurface. The main objectives of SMARTIE1 are the investigation of wind turbine induced seismic signals, the characteristics of their propagation behaviour, as well as the radiation pattern of a single wind turbine as defined using particle motions. Moreover, we quantify the emission of the wind turbine induced seismic signals with respect to the wind speed. The combination of the wind turbine's emission into the subsurface and the attenuation behaviour of the seismic signals (ground motion velocity) can be used to estimate protection radii around seismic stations to ensure the recording of seismic signals without noticeable influences of the wind turbines. In this study, we detect several discrete wind turbine induced frequency peaks ranging from 1 to 10 Hz. We identify a radiation pattern of the wind turbine, which could give further insights into the interaction between the movement of the wind turbine's nacelle and the generation of the wind turbine induced seismic signals. Using profile measurements with a maximum distance of almost 3 km each, we fit a power‐law decay for power spectral density proportional to . The attenuation factor, , ranges from 0.7 to 1.3 for lower frequencies between 1 and 4 Hz, and increases to = 2.3 for the higher frequency peak around 5.25 Hz. Finally, we present an example of estimation of a protection radius around the seismic station of the Collm Observatorium that is part of the German Regional Seismic Network. The example protection radius around Collm Observatorium regarding this single wind turbine is reached at a minimum distance of 3.7 km.
Influenza vaccine effectiveness and disease burden in children and adolescents with sickle cell disease: 2012‐2017
Authors: Kao Carol M. , Lai Kristina , McAteer John M. , Elmontser Mohnd , Quincer Elizabeth M. , Yee Marianne E.M. , Tippet Ashley , Jerris Robert C. , Lane Peter A. , Anderson Evan J. , Bakshi Nitya , Yildirim Inci 
Published: May 2020

AbstractBackgroundData are limited on the burden of influenza and seasonal influenza vaccine effectiveness (VE) in children with sickle cell disease (SCD).MethodsWe used a prospectively collected clinical registry of SCD patients 6 months to 21 years of age to determine the influenza cases per 100 patient‐years, vaccination rates, and a test‐negative case‐control study design to estimate influenza VE against medically attended laboratory‐confirmed influenza infection. Influenza‐positive cases were randomly matched to test‐negative controls on age and influenza season in 1:1 ratio. We used adjusted logistic regression models to compare odds ratio (OR) of vaccination in cases to controls. We calculated VE as [100% × (1 − adjusted OR)] and computed 95% confidence intervals (CIs) around the estimate.ResultsThere were 1037 children with SCD who were tested for influenza, 307 children (29.6%) had at least one influenza infection (338 infections, incidence rate 3.7 per 100 person‐years; 95% CI, 3.4‐4.1) and 56.2% of those tested received annual influenza vaccine. Overall VE pooled over five seasons was 22.3% (95% CI, −7.3% to 43.7%). Adjusted VE estimates ranged from 39.7% (95% CI, −70.1% to 78.6%) in 2015/2016 to −5.9% (95% CI, −88.4% to 40.4%) in the 2016/17 seasons. Influenza VE varied by age and was highest in children 1‐5 years of age (66.6%; 95% CI, 30.3‐84.0). Adjusted VE against acute chest syndrome during influenza infection was 39.4% (95% CI, −113.0 to 82.8%).ConclusionsInfluenza VE in patients with SCD varies by season and age. Multicenter prospective studies are needed to better establish and monitor influenza VE among children with SCD.
Hydrogen/deuterium adsorption and absorption properties on and in palladium using a combined plane wave and localized basis set method
Authors: Sakagami Hiroki , Tachikawa Masanori , Ishimoto Takayoshi 
Published: May 2020

AbstractDetailed information on the H/D isotope effects for adsorption on the surface and absorption in the bulk is important for understanding the nuclear quantum effect. To achieve this, we developed a new theoretical approach, namely, the combined plane wave and localized basis set (CPLB) method. By using the multicomponent quantum chemical method, which takes into account the quantum effect of a proton or deuteron, with the localized part of the CPLB method, direct analysis of the H/D isotope effect about adsorption and absorption is carried out. In this study, we performed a theoretical investigation of the H/D isotope effects for adsorption on a Pd(111) surface and absorption in bulk Pd. We clearly showed an H/D isotope effect on geometry during adsorption and absorption. Our developed CPLB approach is a powerful tool for analyzing the quantum nature of H/D in surface, bulk, and inhomogeneous systems.
Variations in water content of soil in apricot orchards in the western hilly regions of the Chinese Loess Plateau
Authors: Shi Dongping , Tan Hongbing , Rao Wenbo , Liu Zihao , Elenga Hartman Issombo 
Published: May 2020

AbstractLarge changes in land use and land cover types have been occurring in the hill and gully regions of the Loess Plateau since the end of the 1990s. This study revealed dynamic variations of soil water in different layers of representative land use and land cover types under different annual precipitation regimes and assessed the effects on soil water circulation in large areas of apricot [Armeniaca sibirica (L.) Lam.] trees, which have extensive and deep root systems. The results show distinct soil water deficit with a water content of generally <17% (60% of field capacity) in the deep layers of the soil profile of the apricot orchards. Several years after afforestation, perennial soil water deficit layers have subsequently developed around the root zone or even extended to deeper soil layers in the apricot orchards. In the soil profiles, increasing Cl contents are not related to increasing δ2H and δ18O values. This finding suggests that the extreme deficit of soil water and dry layer developments is mainly caused by intense transpiration, rather than by evaporation alone. The occurrence and development of soil water deficit layers in the deep soil profiles were the dominant factors that caused tree growth degradation and gradual death, due to lack of adequate stored soil water in the deep layers for use during a long arid time. Thus, the large‐scale establishment of arbor trees will likely lead to long‐term soil desiccation in the arid or semiarid regions on the Loess Plateau.
Multi-scale Modeling of Partially Stabilized Zirconia with Applications to TRIP-Matrix Composites
Authors: Rajendran Mohan Kumar , Budnitzki Michael , Kuna Meinhard 
Published: May 2020

Abstract
The understanding of how the microstructure influences the mechanical response is an essential pre-requisite for materials tailored to match specific requirements. The aim of this chapter is to further this understanding in the context of Mg-PSZ-TRIP-steel composites on three different scales using a set of methods ranging from phase-field simulations over micromechanics to continuum constitutive modeling. On the microscale, using a Ginzburg-Landau type phase-field model the effects of cooling- and stress-induced martensitic phase transformation in MgO-PSZ is clearly distinguished. Additionally with this method the role of energy barrier in variant selection and the effect of residual stress contributing to the stability of the tetragonal phase are also investigated. On the mesomechanical scale, an analytical 2D model for the martensitic phase transformation and self-accommodation of inclusions within linear elastic materials has been successfully developed. The influences of particle size and geometry, chemical driving force, temperature and surface energy on the $$t \rightarrow m$$

t
→
m

transformation are investigated in a thermostatic approach. On the continuum scale, a continuum material model for transformation plasticity in partially stabilized zirconia ceramics has been developed. Nonlinear hardening behavior, hysteresis and monoclinic phase fraction during a temperature cycle are analyzed. Finally, The mechanical properties of a TRIP steel matrix reinforced by ZrO$$_2$$

2

particles are analyzed on representative volume elements. Here the mechanical properties of the composite as function of volume fraction of both constituents and the strength of the interface are studied.
Sums of S-units in the solution sets of generalized Pell equations
Authors: Hajdu L. , Sebestyén P. 
Published: May 2020

AbstractIn this paper, we give various finiteness results concerning solutions of generalized Pell equations representable as sums ofS-units with a fixed number of terms. In case of one term, our result is effective, while in case of more terms, we are able to bound the number of solutions.