bluuebunny/crossref_metadata_2025_split huggingface dataset:
Supplementing Environmental Assessments with Cumulative Effects Scenario Modeling for Grizzly Bear Connectivity in the Bow Valley, Alberta, Canada
Authors: Carlson Matt , Young Hilary , Linnard Adam , Ryan Max 
Published: September 2022

AbstractPersistence of sensitive wildlife in populated regions requires conservation strategies that address gradual expansion of development footprint and human activity. The project-based environmental assessment regime for municipal development is poorly suited to provide necessary strategic perspective, given its focus on local and short-term impacts. We used the ALCES cumulative effects model to strategically assess impacts to grizzly bears (Ursus arctos) in the Bow Valley of Alberta, Canada. Landscape simulation mapped expansion of past and potential future development footprint in the region over multiple decades. Consequences to movement connectivity for grizzly bears were estimated by applying a least cost path analysis to the landscape simulation. An index of recreational activity was derived from fitness tracking data and integrated with the landscape simulation to model change in recreational activity through time. Maps of grizzly bear connectivity and recreational activity were combined to calculate human-bear conflict risk. The analysis suggests that connectivity has been altered through displacement to upslope areas by settlement expansion, such that surrounding natural areas have become important for grizzly bear connectivity. These areas are also popular for outdoor recreation, resulting in elevated human-bear conflict risk which can be expected to increase if development and human activity continue to expand in high connectivity areas. Conservation of wildlife in populated regions will be supported by broadening the scope of environmental assessment to address cumulative effects of development footprint and human activity over large spatial and temporal scales.
Fast 3D face reconstruction from a single image combining attention mechanism and graph convolutional network
Authors: Deng Zhuoran , Liang Yan , Pan Jiahui , Liao Jiacheng , Hao Yan , Wen Xing 
Published: September 2022

AbstractIn recent years, researchers have made significant contributions to 3D face reconstruction with the rapid development of deep learning. However, learning-based methods often suffer from time and memory consumption. Simply removing network layers hardly solves the problem. In this study, we propose a solution that achieves fast and robust 3D face reconstruction from a single image without the need for accurate 3D data for training. In terms of increasing speed, we use a lightweight network as a facial feature extractor. As a result, our method reduces the reliance on graphics processing units, allowing fast inference on central processing units alone. To maintain robustness, we combine an attention mechanism and a graph convolutional network in parameter regression to concentrate on facial details. We experiment with different combinations of three loss functions to obtain the best results. In comparative experiments, we evaluate the performance of the proposed method and state-of-the-art methods on 3D face reconstruction and sparse face alignment, respectively. Experiments on a variety of datasets validate the effectiveness of our method.
Long-term survivorship of an exchangeable-neck hip prosthesis with a Ti-alloy/Ti-alloy neck–stem junction
Authors: Baleani Massimiliano , Toni Aldo , Ancarani Cristina , Stea Susanna , Bordini Barbara 
Published: September 2022

Abstract
Introduction
Breakage of exchangeable-neck (EN) and adverse local tissue reactions (ALTRs) to neck–stem junction (NSJ) damage products are responsible for increasing the revision rate of EN hip prostheses. We investigated the survivorship of an EN hip prosthesis including a NSJ with both components made of titanium alloy (Ti-alloy/Ti-alloy) to assess whether, and to what extent, EN breakage and NSJ damage affected implant survivorship.

Materials and methods
Using data from a hip replacement registry, we determined survivorship of 2857 EN prostheses. Long-offset configurations of head and EN were implanted in heavy (> 90 kg) patients only in 23 hips. We investigated under which conditions EN breakages or ALTRs occurred. We also measured titanium (Ti) and vanadium (V) blood concentrations in 24 patients with a unilateral well-working prosthesis.

Results
The 17-year survival rates for any reason and aseptic loosening of any component were 88.9% (95%CI 87.5–90.1; 857 hips at risk) and 96.9% (95%CI 96.0–97.6), respectively. There were two cases of EN breakage and one case of ALTR (metallosis), due to rim-neck impingement, out of 276 revisions. After an average period of 9.8 years (range 7.8–12.8 years), the maximum Ti and V blood concentrations in patients with a well-working prosthesis were 5.0 µg/l and 0.16 µg/l, respectively.

Conclusion
The present incidence of EN breakage or ALTR is lower than those reported in other studies evaluating EN hip prosthesis survivorship. This study suggests that (i) the risk of EN breakage is reduced by limiting the use of long-offset configurations in heavy patients and (ii) Ti-alloy/Ti-alloy NSJ damage products do not promote ALTR nor significantly alter the rate of implant loosening. Since design decisions and implant configuration determine the NSJ strength, the NSJ strength in working conditions must be thoroughly investigated to proper define the clinical indications for any EN design.
XAI4EEG: spectral and spatio-temporal explanation of deep learning-based seizure detection in EEG time series
Authors: Raab Dominik , Theissler Andreas , Spiliopoulou Myra 
Published: September 2022

AbstractIn clinical practice, algorithmic predictions may seriously jeopardise patients’ health and thus are required to be validated by medical experts before a final clinical decision is met. Towards that aim, there is need to incorporate explainable artificial intelligence techniques into medical research. In the specific field of epileptic seizure detection there are several machine learning algorithms but less methods on explaining them in an interpretable way. Therefore, we introduce XAI4EEG: an application-aware approach for an explainable and hybrid deep learning-based detection of seizures in multivariate EEG time series. In XAI4EEG, we combine deep learning models and domain knowledge on seizure detection, namely (a) frequency bands, (b) location of EEG leads and (c) temporal characteristics. XAI4EEG encompasses EEG data preparation, two deep learning models and our proposed explanation module visualizing feature contributions that are obtained by two SHAP explainers, each explaining the predictions of one of the two models. The resulting visual explanations provide an intuitive identification of decision-relevant regions in the spectral, spatial and temporal EEG dimensions. To evaluate XAI4EEG, we conducted a user study, where users were asked to assess the outputs of XAI4EEG, while working under time constraints, in order to emulate the fact that clinical diagnosis is done - more often than not - under time pressure. We found that the visualizations of our explanation module (1) lead to a substantially lower time for validating the predictions and (2) leverage an increase in interpretability, trust and confidence compared to selected SHAP feature contribution plots.
Active and passive sensitivity analysis for the second-order active RC filter families using operational amplifier: a review
Authors: Hassanein Ahmed M. , Said Lobna A. , Madian Ahmed H. , Radwan Ahmed G. , Soliman Ahmed M. 
Published: September 2022

AbstractThis work is a review article that sheds light on the active and passive sensitivities of the active RC filters based on opamp. This work provides a detailed analysis through different filters realization criteria and sensitivity summary tables and quantitative insight by discussing the most significant. However, some are almost forgotten, filters families in the literature over decades. A detailed mathematical analysis for the passive sensitivity to compare the filters’ realizations is presented. The concept of dealing between filter design theory and filter design circuit realization is highlighted. Some filters families are chosen from the literature for the analysis. Some detailed specifications tables for each filter family are given. Monte Carlo simulation is carried out on some filters to compare their passive sensitivity. Furthermore, the effect of the active sensitivity of some filters is verified through simulation by adjusting the input common-mode voltage to lower the DC gain of the amplifier. The results of the simulation match with the theoretical analysis and the summary provided in the specifications tables.
Preparation of Photochromic and Photoluminescent Nonwoven Fibrous Mat from Recycled Polyester Waste
Authors: Ahmed Hend , Abdelrahman Meram S. , Al-Balakocy Naser G. , Wen Zhen , Khattab Tawfik A. 
Published: September 2022

AbstractPhotochromic and photoluminescent clothes can be described as smart textiles that alter their color and emission spectra upon exposure to a light stimulus. Recycled nonwoven polyester fabrics screen-printed with rare-earth strontium aluminate nanoparticles were developed to introduce photochromic and photoluminescent properties. Both spinning and preparation of nonwoven fibrous mat was performed industrially starting from recycled polyester waste. Aqueous-based phosphor-binder nanocomposites containing different concentrations of inorganic phosphor with excellent thermal and photostability were applied directly onto nonwoven polyester fabrics. The screen-printing process produced a uniform photochromic and photoluminescent film onto the nonwoven polyester surface that showed strong green emission color (440 nm) under UV light even at lower phosphor concentrations (0.5 wt%) in the printing paste. The excitation wavelength of the printed nonwoven polyester samples was monitored at 382 nm. Long-persistent greenish-yellow phosphorescence was detected in the dark at higher phosphor concentrations. The morphological microscopic data of phosphor nanoparticles and printed nonwoven polyester fabrics were collected using various analytical methods. TEM analysis of phosphor nanoparticles designated diameters of 4–11 nm, whereas XRD analysis indicated a crystal size of 9 nm. The printed cloth exhibited a quick and reversible photochromic emission when exposed to ultraviolet light. The ultraviolet protection, antimicrobial and superhydrophobic properties were improved with increasing the pigment concentration in the printing paste. The static contact and slide angles improved in the ranges of 108.6°–132.6°, and 12°–7°, respectively. The effects of increasing the phosphor concentration in the printing paste on the comfort features and colorfastness were examined.
New Interior-Point Approach for One- and Two-Class Linear Support Vector Machines Using Multiple Variable Splitting
Authors: Castro Jordi 
Published: September 2022

AbstractMultiple variable splitting is a general technique for decomposing problems by using copies of variables and additional linking constraints that equate their values. The resulting large optimization problem can be solved with a specialized interior-point method that exploits the problem structure and computes the Newton direction with a combination of direct and iterative solvers (i.e. Cholesky factorizations and preconditioned conjugate gradients for linear systems related to, respectively, subproblems and new linking constraints). The present work applies this method to solving real-world binary classification and novelty (or outlier) detection problems by means of, respectively, two-class and one-class linear support vector machines (SVMs). Unlike previous interior-point approaches for SVMs, which were practical only with low-dimensional points, the new proposal can also deal with high-dimensional data. The new method is compared with state-of-the-art solvers for SVMs that are based on either interior-point algorithms (such as SVM-OOPS) or specific algorithms developed by the machine learning community (such as LIBSVM and LIBLINEAR). The computational results show that, for two-class SVMs, the new proposal is competitive not only against previous interior-point methods—and much more efficient than they are with high-dimensional data—but also against LIBSVM, whereas LIBLINEAR generally outperformed the proposal. For one-class SVMs, the new method consistently outperformed all other approaches, in terms of either solution time or solution quality.
From Irrevocably Modulated Filtrations to Dynamical Equations Over Random Networks
Authors: Mengütürk Levent Ali 
Published: September 2022

AbstractWe develop a probabilistic information framework via what we call irrevocably modulated filtrations produced by non-invertible matrix-valued jump processes acting on multivariate observation processes carrying noisy signals. Under certain conditions, we provide dynamical representations of conditional expectation martingales in systems where signals from randomly changing information networks may get irreversibly amalgamated or switched-off over random time horizons. We apply the framework to scenarios where the flow of information goes through multiple modulations before reaching observing agents. This leads us to introduce a Lie-type operator as a morphism between spaces of sigma-algebras, which quantifies information discrepancy caused by different modulation sequences. As another example, we show how random graphs can be used to generate irrevocably modulated filtrations that lead to pure noise scenarios. Finally, we construct systems that exhibit gradual decay of additional sources of information through the choice of spectral radii of the modulators.
Floodplain trophic subsidies in a modified river network: managed foodscapes of the future?
Authors: Sturrock Anna M. , Ogaz Mollie , Neal Kelly , Corline Nicholas J. , Peek Ryan , Myers Dana , Schluep Sierra , Levinson Marissa , Johnson Rachel C. , Jeffres Carson A. 
Published: September 2022

AbstractContextCross-boundary subsidies create important growth opportunities for a range of taxa. In modified river systems, remnant patches of floodplain and flood bypasses become ephemeral hotspots of zooplankton production, however, the extent to which these prey items are (or could be) transported downstream is unclear.ObjectivesWe investigated the diet of juvenile salmon under varying hydroclimatic conditions to assess the importance of floodplain-produced prey subsidies in an otherwise food-scarce region.MethodsJuvenile salmon (n = 3033) and zooplankton were sampled across the California Central Valley Sacramento-San Joaquin River Delta in 2014–2018, incorporating a range of climatic conditions including drought and flood. Salmon stomach fullness and diet composition, and ambient zooplankton densities were used to assess spatiotemporal patterns in prey production and consumption.ResultsFloodplain-produced cladocerans provided ephemeral food pulses to juvenile salmon in downstream riverine habitats. Salmon had the fullest stomachs in wetter years (2016–2017) and the emptiest stomachs in the final year of a multi-year drought (2015). Cladoceran abundances in the water column and salmon diets were highest during wet periods and below floodplains, and decreased with increasing distance downstream, consistent with flow-mediated trophic subsidies.ConclusionsThese data emphasize the importance of maintaining diverse, interconnected habitats to support resilient fish populations and the potential for managing floodplains to boost prey production and delivery. Here, the inundation of a flood bypass (or lack of) played a pivotal role shaping the juvenile salmon foodscape. As freshwater ecosystems are increasingly transformed by large-scale engineering, it is important to coordinate infrastructure, habitat and flow modifications to maximize climate resilience and trophic benefits to target species.
In search for the most preferred solution in value efficiency analysis
Authors: Ravanos Panagiotis , Karagiannis Giannis 
Published: September 2022

AbstractChoosing the Most Preferred Solution (MPS), namely a real or artificial Decision Making Unit (DMU) reflecting the decision maker’s preferences over the desirable structure of inputs and outputs, is of particular importance in Value Efficiency Analysis (VEA). In this paper, we review various MPS choices used in the VEA literature and propose some new, which rely respectively on the relative position of frontier DMUs, the Most Productive Scale Size (MPSS), the Average Production Unit (APU), and common vectors of weights. The suggested MPS choices reflect overall organizational goals such as the pursuit of scale economies and the maximization of structural efficiency, or the need to assess DMUs against common standards because of limited control over the resources allocated to them or autonomy in setting their own priorities. The potential implications of using different MPSs in VEA are illustrated by providing comparative empirical results using a dataset of 526 Greek cotton farms.
The Role of Hierarchy in Realizing Collective Leadership in a Self-Managing Organization
Authors: Kummelstedt Christopher 
Published: September 2022

AbstractThis article is about leadership in a self-managing organization. Empirically, it is grounded in a participatory action research study stretching over two years, oriented around the following question: how does instances of hierarchical leadership and collective leadership interact across different dimensions of power in a self-managing organization? The article concludes that although this self-managing organization is largely governed in the day-to-day through collective leadership, this outcome still relies on hierarchical management of discourse and the processes which replace authority. That is, the article concludes that there is a dynamic between hierarchical and collective forms of leadership in this specific self-managing organization that serves to make its mode of self-management viable. In terms of practice, the results suggests that truly radical decentralization of decision making in the day-to-day is possible and can be highly effective. Furthermore, perhaps counterintuitively, results suggests that there can be a role for quite pronounced hierarchical leadership in making collective leadership flourish – at least when transitioning from a managerial hierarchy. Further research into this area might study organizations that are originally started as self-managing organizations and see if the same role for hierarchical management of collective leadership exists also in this type of case.
Adolescents’ implicit attitudes towards people with immigrant background: Differences and correlates
Authors: König Sabrina , Stang-Rabrig Justine , McElvany Nele 
Published: September 2022

AbstractPeople with an immigrant background can be affected by stereotypes and discrimination. As adolescence is an important developmental stage, this study investigated whether adolescents hold (negative) implicit attitudes towards people with Turkish immigrant background and whether adolescents differ in the extent of attitudes. Additionally, the relevance of perceived discrimination, identification with culture of residence, motivation to act without predjudice, and quality and quantity of contact to people with Turkish immigrant background for the extent of implicit attitudes was analysed. Analyses are based on 244 adolescents (60.7% female, 1.6% diverse; 13.1% with Turkish immigrant background, 16.8% with immigrant background other than Turkish) who participated in an online study. An implicit association test revealed that negative implicit attitudes towards people with a Turkish immigrant background were present among adolescents. Unlike adolescents with a Turkish immigrant background, adolescents without immigrant background and with immigrant background other than Turkish hold negative implicit attitudes on average. For the total sample, it was found that low perceived discrimination was related to negative implicit attitudes. The results are discussed with respect to substantive and methodological aspects. Implications for research and practice are derived.
When Water Quality Crises Drive Change: A Comparative Analysis of the Policy Processes Behind Major Water Contamination Events
Authors: Khan Nameerah , Charles Katrina J. 
Published: September 2022

AbstractThe occurrence of major water contamination events across the world have been met with varying levels of policy responses. Arsenic—a priority water contaminant globally, occurring naturally in groundwater, causing adverse health effects—is widespread in Bangladesh. However, the policy response has been slow, and marked by ineffectiveness and a lack of accountability. We explore the delayed policy response to the arsenic crisis in Bangladesh through comparison with water contamination crises in other contexts, using the Multiple Streams Framework to compare policy processes. These included Escherichia coli O157:H7 and Campylobacter in Walkerton, Canada; lead and Legionella in Flint, Michigan, USA; and chromium-6 contamination in Hinkley, California, USA. We find that, while water contamination issues are solvable, a range of complex conditions have to be met in order to reach a successful solution. These include aspects of the temporal nature of the event and the outcomes, the social and political context, the extent of the public or media attention regarding the crisis, the politics of visibility, and accountability and blame. In particular, contaminants with chronic health outcomes, and longer periods of subclinical disease, lead to smaller policy windows with less effective policy changes. Emerging evidence on health threats from drinking water contamination raise the risk of new crises and the need for new approaches to deliver policy change.
Replacement of microsatellite markers by imputed medium-density SNP arrays for parentage control in German warmblood horses
Authors: Nolte Wietje , Alkhoder Hatem , Wobbe Mirell , Stock Kathrin F. , Kalm Ernst , Vosgerau Sarah , Krattenmacher Nina , Thaller Georg , Tetens Jens , Kühn Christa 
Published: September 2022

AbstractIn horses, parentage control is currently performed based on an internationally standardized panel of 17 microsatellite (MS) markers comprising 12 mandatory and five optional markers. Unlike MS, single nucleotide polymorphism (SNP) profiles support a wider portfolio of genomic applications, including parentage control. A transition to SNP-based parentage control is favorable, but requires additional efforts for ensuring generation-overlapping availability of marker genotypes of the same type. To avoid double genotyping of either parents or offspring for changing to SNP technology and enable efficient transition, we tested whether MS genotypes used for parentage control could be reliably imputed from a medium-density SNP panel in German warmblood horses. Imputation accuracy was tested in a tenfold cross-validation with two approaches: within breed (option A) and across breeds (option B). Average imputation accuracies of 97.98% (A) and 96.17% (B) were achieved, respectively. Due to interbreed differences in genotyping rates, five MS markers of low genotyping rate (GTR; < 90%) could be imputed with higher accuracy within breed (98.18%) than across breeds (90.73%). MS markers with high GTR performed homogeneously well in option B (98.44%) and showed slightly lower accuracy in option A (97.90%). Among these markers, AHT5 proved to be problematic for imputation regardless of the approach, revealing accuracies of 86.40% (A) and 88.70% (B). Better results for MS markers with high GTR and savings in computational processing justified the choice of option B for routine implementation. To date, more than 9500 horses have undergone the new parentage control based on imputed MS genotypes.