bluuebunny/crossref_metadata_2025_split huggingface dataset:
Statistical modeling of phenology in Bavaria based on past and future meteorological information
Authors: Ziegler Katrin , Pollinger Felix , Böll Susanne , Paeth Heiko 
Published: March 2020

AbstractPlant phenology is well known to be affected by meteorology. Observed changes in the occurrence of phenological phases are commonly considered some of the most obvious effects of climate change. However, current climate models lack a representation of vegetation suitable for studying future changes in phenology itself. This study presents a statistical-dynamical modeling approach for Bavaria in southern Germany, using over 13,000 paired samples of phenological and meteorological data for analyses and climate change scenarios provided by a state-of-the-art regional climate model (RCM). Anomalies of several meteorological variables were used as predictors and phenological anomalies of the flowering date of the test plant Forsythia suspensa as predictand. Several cross-validated prediction models using various numbers and differently constructed predictors were developed, compared, and evaluated via bootstrapping. As our approach needs a small set of meteorological observations per phenological station, it allows for reliable parameter estimation and an easy transfer to other regions. The most robust and successful model comprises predictors based on mean temperature, precipitation, wind velocity, and snow depth. Its average coefficient of determination and root mean square error (RMSE) per station are 60% and ± 8.6 days, respectively. However, the prediction error strongly differs among stations. When transferred to other indicator plants, this method achieves a comparable level of predictive accuracy. Its application to two climate change scenarios reveals distinct changes for various plants and regions. The flowering date is simulated to occur between 5 and 25 days earlier at the end of the twenty-first century compared to the phenology of the reference period (1961–1990).
Fast electrodeposition of zinc onto single zinc nanoparticles
Authors: Zampardi Giorgia , Compton Richard G. 
Published: March 2020

AbstractThe zinc deposition reaction onto metallic zinc has been investigated at the single particle level through the electrode-particle collision method in neutral solutions, and in respect of its dependence on the applied potential and the ionic strength of a sulphate-containing solution. Depending on the concentration of sulphate ions in solution, different amounts of metallic zinc were deposited on the single Zn nanoparticles. Specifically, insights into the electron transfer kinetics at the single particles were obtained, indicating an electrically early reactant-like transition state, which is consistent with the rate-determining partial de-hydration/de-complexation process. Such information on the reaction kinetics at the nanoscale is of vital importance for the development of more efficient and long-lasting nanostructured Zn-based negative electrodes for Zn-ion battery applications.
Interactions between barotropic tides and mesoscale processes in deep ocean and shelf regions
Authors: Stanev Emil Vassilev , Ricker Marcel 
Published: March 2020

AbstractThe interactions between barotropic tides and mesoscale processes were studied using the results of a numerical model in which tidal forcing was turned on and off. The research area covered part of the East Atlantic Ocean, a steep continental slope, and the European Northwest Shelf. Tides affected the baroclinic fields at much smaller spatial scales than the barotropic tidal scales. Changes in the horizontal patterns of the M2 and M4 tidal constituents provided information about the two-way interactions between barotropic tides and mesoscale processes. The interaction between the atmosphere and ocean measured by the work done by wind was also affected by the barotropic tidal forcing. Tidal forcing intensified the transient processes and resulted in a substantial transformation of the wave number spectra in the transition areas from the deep ocean to the shelf. Tides flattened the sea-surface height spectra down to ~ k−2.5 power law, thus reflecting the large contribution of the processes in the high-frequency range compared to quasi-geostrophic motion. The spectra along sections parallel or normal to the continental slope differ from each other, which indicates that mesoscale turbulence was not isotropic. An analysis of the vorticity spectra showed that the flattening was mostly due to internal tides. Compared with the deep ocean, no substantial scale selectivity was observed on the shelf area. Particle tracking showed that the lengths of the Lagrangian trajectories increased by approximately 40% if the barotropic tidal forcing was activated, which contributed to changed mixing properties. The ratio between the horizontal and vertical scales of motion varied regionally depending on whether barotropic tidal forcing was included. The overall conclusion is that the barotropic tides affect substantially the diapycnal mixing.
A wideband blocker-resilient direct delta sigma receiver with selective input-impedance matching
Authors: Ul Haq Faizan , Englund Mikko , Östman Kim B. , Stadius Kari , Kosunen Marko , Koli Kimmo , Ryynänen Jussi 
Published: March 2020

AbstractThis paper presents a wideband blocker-tolerant direct $$\varDelta \varSigma$$ΔΣ receiver (DDSR). Blockers are attenuated through selective input impedance matching and reduced gain design. The selective input impedance profile provides a low impedance at blocker frequencies enabling blocker attenuation, while the in-band impedance is boosted to matched condition through an up-converted positive feedback from the DDSR output. In addition, with the help of reduced gain design, near band blocker gain is minimized, further improving the blocker resilience. The receiver is designed for configurable operation from 0.7–2.7 GHz and a baseband bandwidth of 10 MHz. Simulated in a 28 nm technology, the DDSR demonstrates a maximum noise figure of 6.2 dB, and achieves a peak SNDR of 53 dB with an out-of-band 1 dB input compression point of $$-\,11$$-11 dBm at a 100 MHz offset.
Depicting Dementia: Representations of Cognitive Health and Illness in Ten Picturebooks for Children
Authors: Caldwell Elizabeth F. , Falcus Sarah , Sako Katsura 
Published: March 2020

AbstractIt is estimated that a third of children know someone living with dementia, and there are now many picturebooks for young children that help to explain the changes dementia can bring to family life. Despite their number, there has been little examination of what these books communicate about health and illness. To address this, the current study presents a close visual and textual analysis of 10 recent picturebooks in English that aim to teach children about dementia. Our analysis reveals that in these books dementia is exclusively framed in terms of ageing, and as an illness of older adults. Furthermore, the books rely heavily on mechanistic metaphors to explain the causes of dementia. However, at the same time the “still the same person” narrative is dominant. This narrative emphasises the importance of foregrounding the unique history and personality of the person living with dementia, and offers a way to help children to continue meaningful relationships with their relatives. These books employ often ageist tropes of decline in the depiction of dementia and yet at the same time support a narrative of ongoing personhood, reflecting the complexity of broader social discourses around dementia and selfhood.
Discrete-time survival forests with Hellinger distance decision trees
Authors: Schmid Matthias , Welchowski Thomas , Wright Marvin N. , Berger Moritz 
Published: March 2020

AbstractRandom survival forests (RSF) are a powerful nonparametric method for building prediction models with a time-to-event outcome. RSF do not rely on the proportional hazards assumption and can be readily applied to both low- and higher-dimensional data. A remaining limitation of RSF, however, arises from the fact that the method is almost entirely focussed on continuously measured event times. This issue may become problematic in studies where time is measured on a discrete scale$$t = 1, 2, ...$$t=1,2,..., referring to time intervals$$[0,a_1), [a_1,a_2), \ldots $$[0,a1),[a1,a2),…. In this situation, the application of methods designed for continuous time-to-event data may lead to biased estimators and inaccurate predictions if discreteness is ignored. To address this issue, we develop a RSF algorithm that is specifically designed for the analysis of (possibly right-censored) discrete event times. The algorithm is based on an ensemble of discrete-time survival trees that operate on transformed versions of the original time-to-event data using tree methods for binary classification. As the outcome variable in these trees is typically highly imbalanced, our algorithm implements a node splitting strategy based on Hellinger’s distance, which is a skew-insensitive alternative to classical split criteria such as the Gini impurity. The new algorithm thus provides flexible nonparametric predictions of individual-specific discrete hazard and survival functions. Our numerical results suggest that node splitting by Hellinger’s distance improves predictive performance when compared to the Gini impurity. Furthermore, discrete-time RSF improve prediction accuracy when compared to RSF approaches treating discrete event times as continuous in situations where the number of time intervals is small.
Powering and puzzling: climate change adaptation policies in Bangladesh and India
Authors: Stock Ryan , Vij Sumit , Ishtiaque Asif 
Published: March 2020

AbstractSouth Asia is a region uniquely vulnerable to climate-related impacts. Climate change adaptation in India and Bangladesh evolves using powering and puzzling approaches by policy actors. We seek to answer the question:how do powering and puzzling approaches influence the climate change adaptation policy design and implementation processes in Bangladesh and India?We adopted two strategies to collect and analyze data: semi-structured interviews and discourse analysis. We found that adaptation policymaking is largely top-down, amenable to techno-managerial solutions, and not inclusive of marginalized actors. In Bangladesh, power interplays among ministerial agencies impair the policy implementation process and undermine the success of puzzling. Local-scale agencies do not have enough authority or power to influence the overall implementation processes occurring at higher scales of governance. The powering of different actors in Bangladesh is visible through a duality of mandates and a lack of integration of climate adaptation strategies in different government ministries. The powering aspect of India’s various adaptation policies is the lack of collective puzzling around the question of differentiated vulnerability by axes of social difference. Paradoxically, India has a puzzling approach ofhiding behind the poorin international negotiations. Moving forward, both countries should strive to have more inclusive and equitable adaptation policymaking processes that enable the participation of marginalized populations and represent their anxieties and aspirations. Identifying policy-relevant insights from South Asia using the powering and puzzling approaches can foster adaptation policy processes that facilitate empowerment, the missing piece of the adaptation policymaking puzzle.
Predicting key educational outcomes in academic trajectories: a machine-learning approach
Authors: Musso Mariel F. , Hernández Carlos Felipe Rodríguez , Cascallar Eduardo C. 
Published: March 2020

AbstractPredicting and understanding different key outcomes in a student’s academic trajectory such as grade point average, academic retention, and degree completion would allow targeted intervention programs in higher education. Most of the predictive models developed for those key outcomes have been based on traditional methodological approaches. However, these models assume linear relationships between variables and do not always yield accurate predictive classifications. On the other hand, the use of machine-learning approaches such as artificial neural networks has been very effective in the classification of various educational outcomes, overcoming the limitations of traditional methodological approaches. In this study, multilayer perceptron artificial neural network models, with a backpropagation algorithm, were developed to classify levels of grade point average, academic retention, and degree completion outcomes in a sample of 655 students from a private university. Findings showed a high level of accuracy for all the classifications. Among the predictors, learning strategies had the greatest contribution for the prediction of grade point average. Coping strategies were the best predictors for degree completion, and background information had the largest predictive weight for the identification of students who will drop out or not from the university programs.
Rewiring higher education for the Sustainable Development Goals: the case of the Intercultural University of Veracruz, Mexico
Authors: Perales Franco Cristina , McCowan Tristan 
Published: March 2020

AbstractIn the framework of the Sustainable Development Goals, higher education has been given a key role in addressing societal challenges, reducing poverty, ensuring sustainable livelihoods and protecting the natural environment. Yet there has been a singular lack of imagination as regards the institutional forms that might help support this vision. This article reports on the findings of an exploratory qualitative case study of the Intercultural University of Veracruz, one of a number of institutions created in Mexico to ensure access for indigenous populations, to promote local development and to provide a space for intercultural dialogue. The findings show a number of ways in which this innovative institution provides opportunities for supporting the SDGs that go beyond conventional universities. The university addresses SDG4 by enabling access for marginalised populations, and through its engaged teaching, research and community engagement also contributes to environmental protection, health, livelihoods, gender equality and a range of other goals. However, it also presents challenges to the global framework, highlighting the lack of attention to culture, language, identity and knowledge traditions, and in critiquing the very basis of its conception of development. Implications are drawn out more broadly for the relationship between higher education and international development in the contemporary era.
Custom tissue engineered aneurysm models with varying neck size and height for early stage in vitro testing of flow diverters
Authors: Villadolid Camille , Puccini Brandon , Dennis Benjamin , Gunnin Tessa , Hedigan Conor , Cardinal Kristen O’Halloran 
Published: March 2020

AbstractEndovascular techniques for treating cerebral aneurysms are rapidly advancing and require testing to optimize device configurations. The purpose of this work was to customize tissue-engineered aneurysm “blood vessel mimics” (aBVMs) for early stage in vitro assessment of vascular cell responses to flow diverters and other devices. Aneurysm scaffolds with varying neck size and height were created through solid modeling, mold fabrication, mandrel creation, and electrospinning. Scaffold dimensions and fiber morphology were characterized. aBVMs were created by depositing human smooth muscle and endothelial cells within scaffolds, and cultivating within perfusion bioreactors. These vessels were left untreated or used for flow diverter implantation. Cellular responses to flow diverters were evaluated at 3 days. Custom scaffolds were created with aneurysm neck diameters of 2.3, 3.5, and 5.5 mm and with aneurysm heights of 2, 5, and 8 mm. A set of scaffolds with varying neck size was used for aBVM creation, and dual-sodding of endothelial and smooth muscle cells resulted in consistent and confluent cellular linings. Flow diverters were successfully implanted in a subset of aBVMs, and initial cell coverage over devices was seen in the parent vessel at 3 days. Direct visualization of the device over the neck region was feasible, supporting the future use of these models for evaluating and comparing flow diverter healing. Tissue-engineered aneurysm models can be created with custom neck sizes and heights, and used to evaluate cellular responses to flow diverters and other endovascular devices.
Adaptive ML-Based Frame Length Optimisation in Enterprise SD-WLANs
Authors: Coronado Estefanía , Thomas Abin , Riggio Roberto 
Published: March 2020

AbstractSoftware-Defined Networking (SDN) is gaining a lot of traction in wireless systems with several practical implementations and numerous proposals being made. Despite instigating a shift from monolithic network architectures towards more modulated operations, automated network management requires the ability to extract, utilise and improve knowledge over time. Beyond simply scrutinizing data, Machine Learning (ML) is evolving from a simple tool applied in networking to an active component in what is known as Knowledge-Defined Networking (KDN). This work discusses the inclusion of ML techniques in the specific case of Software-Defined Wireless Local Area Networks (SD-WLANs), paying particular attention to the frame length optimization problem. With this in mind, we propose an adaptive ML-based approach for frame size selection on a per-user basis by taking into account both specific channel conditions and global performance indicators. By relying on standard frame aggregation mechanisms, the model can be seamlessly embedded into any Enterprise SD-WLAN by obtaining the data needed from the control plane, and then returning the output back to this in order to efficiently adapt the frame size to the needs of each user. Our approach has been gauged by analysing a multitude of scenarios, with the results showing an average improvement of 18.36% in goodput over standard aggregation mechanisms.
Understanding urban flood vulnerability and resilience: a case study of Kuantan, Pahang, Malaysia
Authors: Safiah Yusmah M. Y. , Bracken L. J. , Sahdan Z. , Norhaslina H. , Melasutra M. D. , Ghaffarianhoseini A. , Sumiliana S. , Shereen Farisha A. S. 
Published: March 2020

AbstractMalaysia is frequently affected by the annual flooding event caused by the seasonal monsoon which accounts for significant losses. Flood risk, exposure and damage potential are increasing, causing the level of poverty and vulnerability to rise. The annual occurrence of the flood hazard has forced residents to prepare beforehand to help them spring back to their daily life faster. This study aimed to investigate and understand the vulnerability and resilience of the victims towards floods in Kuantan, Pahang. A qualitative approach of focus group discussion (FGD) is used to obtain detailed and authentic information. A total of thirty-one (31) participants who were flood victims took part in the FGD. Six groups were formed for the FGD based on different criteria such as gender, age, education background, occupation, monthly income and social class. Each FGD group consisted of four to six participants. When the participants were asked to rank their top five daily challenges, many thought that flooding is not a threat compared to food, because flooding occurs annually and is predictable. The results showed that the participants are well aware of the causes of the vulnerability faced by them due to the flooding event. Reasons highlighted from the results for the flood occurrence are the demography of the area, the location of the houses, the improper and inaccurate information and evacuation plan, the management of the transit centre and the lack of preparation by the community. The participants also thought that poor dissemination of early warning information and flood control infrastructures from the government and other related agencies caused the victims to have insufficient time to prepare for emergencies, hence causing the recovery process to be slower. However, from their hands-on experiences, they were able to put forward suggestions on the resilience towards flood for future references.
Carbon and nitrogen cycling in a lead polluted grassland evaluated using stable isotopes (δ13C and δ15N) and microbial, plant and soil parameters
Authors: Rijk Ingrid J. C. , Ekblad Alf 
Published: March 2020

AbstractAimsCarbon (C) and nitrogen (N) cycling are key ecosystem functions potentially altered by heavy metal pollution. We used an ecosystem approach to study the long-term effect of lead (Pb) on C and N cycles in a natural grassland in a former shooting range.MethodsMicrobial activity was evaluated by substrate-induced respiration (SIR) in situ,adding isotopically labelled C4-sugar to the soil. C and N contents and natural abundance of isotopes were measured in grass leaves, soil and microbial biomass together with root biomass.ResultsA reduced microbial activity and microbial biomass per area, together with a higher soil C stock and C:N ratio suggested a lower microbial decomposition in high Pb compared to low Pb areas. A more closed N cycle in the high Pb area was indicated by 2–3‰ lower δ15N in leaves and soil compared to low Pb areas. Higher δ13C in leaves and higher root biomass but similar leaf nutrient contents indicated plant responses and adaptions to the high Pb.ConclusionsThe applied ecosystem approach revealed that Pb slowed down the C and N cycles, possibly by indirect effects rather than by direct toxicity. The ecosystem seems to have adapted to altered conditions.
Capacities, Removable Sets and Lp-Uniqueness on Wiener Spaces
Authors: Hinz Michael , Kang Seunghyun 
Published: March 2020

AbstractWe prove the equivalence of two different types of capacities in abstract Wiener spaces. This yields a criterion for the Lp-uniqueness of the Ornstein-Uhlenbeck operator and its integer powers defined on suitable algebras of functions vanishing in a neighborhood of a given closed set Σ of zero Gaussian measure. To prove the equivalence we show the Wr,p(B,μ)-boundedness of certain smooth nonlinear truncation operators acting on potentials of nonnegative functions. We discuss connections to Gaussian Hausdorff measures. Roughly speaking, if Lp-uniqueness holds then the ‘removed’ set Σ must have sufficiently large codimension, in the case of the Ornstein-Uhlenbeck operator for instance at least 2p. For p = 2 we obtain parallel results on truncations, capacities and essential self-adjointness for Ornstein-Uhlenbeck operators with linear drift. These results apply to the time zero Gaussian free field as a prototype example.