bluuebunny/crossref_metadata_2025 huggingface dataset:
Nature-Based Climate Solutions in European Schools: A Pioneering Co-designed Strategy Towards Urban Resilience
Authors: Baró Francesc , Camacho David A. , Perez del Pulgar Carmen , Ruiz-Mallén Isabel , García-Serrano Pablo
Published: September 2022

As cities around the world are increasingly facing the impacts of climate change, a growing number of municipalities are leading collaborative projects to adapt schools to rising temperatures. The implementation of nature-based solutions (NBS) is highlighted as an important component to be included in these initiatives given their multifunctional and cost-effective character. However, the challenges and upscaling opportunities of these pioneering projects are still not well understood nor systematically studied on a comparative basis. This study explores and compares three European pilot nature-based projects aiming to make schools more resilient to climate change impacts while creating other co-benefits for children and the wider local community. These projects are Oasis (Paris), Climate Shelters (Barcelona) and Care in School Environments (Madrid). Building on a framework for assessing the co-benefits of urban NBS, the comparative analysis explores the selection criteria of schools and their equity implications, the multifunctional role of NBS beyond climate adaptation, the main aspects and challenges related to the co-design process and the subsequent project implementation and the potential for upscaling at the city level. Based on this exploration, we contend that nature-based climate adaptation projects in schools can be a spearhead for a wider community-based strategy towards urban resilience.
Reporting CCI and Learning Technology Research
Authors: Giannakos Michail
Published: September 2022

Designing and conducting high quality research is extremely important in CCI and learning technology research. However, the same high-quality needs to be followed during the reporting of the work. At the end of the day, this what the reviewers and readers will credit – therefore, reporting is of equal importance. This chapter provides information on how you should structure your article and the information that is usually required. This chapter is intended to serve as a template for CCI and learning technology researchers. Moreover, I have summarized some recommendations based on my experience, as well as on published guidelines and recommendations from neighboring fields.
BPS correlators for AdS3/CFT2
Authors: Gaberdiel Matthias R. , Nairz Beat
Published: September 2022

Abstract

The BPS correlators of the symmetric product orbifold SymN(𝕋4) are reproduced from the dual worldsheet theory describing strings on AdS3× S3× 𝕋4 with minimal (k = 1) NS-NS flux. More specifically, we show that the worldsheet duals of the symmetric orbifold BPS states can be identified with their lift to the covering surface, thereby making the matching of the correlators essentially manifest. We also argue that the argument can be generalised to arbitrary descendants, using suitable DDF operators on the worldsheet.
Similar rate of return to sports activity between posterior-stabilised and cruciate-retaining primary total knee arthroplasty in young and active patient
Authors: D’Ambrosi Riccardo , Mangiavini Laura , Loucas Rafael , Loucas Marios , Brivio Angela , Mariani Ilaria , Ursino Nicola , Migliorini Filippo
Published: September 2022

Purpose

Cruciate-retaining and posterior-stabilised implant designs are available for primary total knee arthroplasty. However, whether the implant design is associated with a difference in the level of activity still remains unclear. This clinical trial compared posterior-stabilised and cruciate-retaining implants in sport-related patient-reported outcome measures, range of motion, rate of return to sport, and weekly time dedicated to sport in active adults. It was also hypothesised that in young and active patients both implants lead to a similar rate of return to sport in terms of hours per week, type of sport, and joint mobility.

Methods

All patients were evaluated preoperatively and for a minimum of 36 months follow-up. The University of California Los Angeles activity scores, High-Activity Arthroplasty Score, and Visual Analogue Scale were administered preoperatively and at the last follow-up. The range of motion was investigated at admission and the last follow-up. Data concerning the hours per week dedicated to sports and the type of sport practiced were also collected at admission and at the last follow-up. The Kaplan–Meier Curve was performed to compare implant survivorship.

Results

Data from 227 procedures (cruciate-retaining: 109, posterior-stabilised: 118) were prospectively collected. At the last follow-up, no difference was reported in The University of California Los Angeles activity scores (p = 0.6), High-Activity Arthroplasty Score (p = 0.1), Visual Analogue Scale (p = 0.9), flexion (p = 0.7) and extension (p = 0.4). No difference was found in the rate of return (p = 0.1) and weekly hours dedicated to sport (p = 0.3). The Kaplan–Meier curve evidenced no statistically significant difference in implant survivorship (p = 0.6).

Conclusions

At approximately five years of follow-up, no difference was reported between cruciate-retaining and posterior-stabilised implants in active adults in sport-related patient-reported outcomes measures, range of motion, pain, weekly time dedicated to sport, rate of return to sport, and implant survivorship.

Level of evidence

Level II, prospective study.
Slow-oscillatory tACS does not modulate human motor cortical response to repeated plasticity paradigms
Authors: Bradley Claire , Elliott Jessica , Dudley Samuel , Kieseker Genevieve A. , Mattingley Jason B. , Sale Martin V.
Published: September 2022

Previous history of activity and learning modulates synaptic plasticity and can lead to saturation of synaptic connections. According to the synaptic homeostasis hypothesis, neural oscillations during slow-wave sleep play an important role in restoring plasticity within a functional range. However, it is not known whether slow-wave oscillations—without the concomitant requirement of sleep—play a causal role in human synaptic homeostasis. Here, we aimed to answer this question using transcranial alternating current stimulation (tACS) to induce slow-oscillatory activity in awake human participants. tACS was interleaved between two plasticity-inducing interventions: motor learning, and paired associative stimulation (PAS). The hypothesis tested was that slow-oscillatory tACS would prevent homeostatic interference between motor learning and PAS, and facilitate plasticity from these successive interventions. Thirty-six participants received sham and active fronto-motor tACS in two separate sessions, along with electroencephalography (EEG) recordings, while a further 38 participants received tACS through a control montage. Motor evoked potentials (MEPs) were recorded throughout the session to quantify plasticity changes after the different interventions, and the data were analysed with Bayesian statistics. As expected, there was converging evidence that motor training led to excitatory plasticity. Importantly, we found moderate evidence against an effect of active tACS in restoring PAS plasticity, and no evidence of lasting entrainment of slow oscillations in the EEG. This suggests that, under the conditions tested here, slow-oscillatory tACS does not modulate synaptic homeostasis in the motor system of awake humans.
Bromelain-based enzymatic burn debridement: Spanish multidisciplinary consensus
Authors: Serracanta Jordi , Baena Jacinto , Martinez-Mendez José R. , Sanchez-Sanchez Manuel , Lopez-Suso Eugenia , Galeiras Rita , Perez-del-Caz Maria Dolores , Vivo-Benlloch Carmen , Monclus-Fuertes Enrique , Casalduero-Viu Jacobo , Martin-Playa Patricia , Ugalde-Gutierrez Marta , Gacto-Sanchez Purificacion , Rincon-Ferrari Maria Dolores , Piqueras-Perez Jose Maria , Martin-Luengo Ana
Published: September 2022

Background

Bromelain-based enzymatic debridement is gaining increased interest from burn specialists in the last few years. The objective of this manuscript is to update the previous, first Spanish consensus document from 2017 (Martínez-Méndez et al. 43:193–202, 2017), on the use of enzymatic debridement with NexoBrid® in burn injuries, adding the clinical experience of a larger panel of experts, integrating plastic surgeons, intensivists, and anesthesiologists.

Methods

A consensus guideline was established by following a modified Delphi methodology of a 38-topic survey in two rounds of participation. Items were grouped in six domains: general indication, indication in critical patients, pain management, conditions for NexoBrid® application, NexoBrid® application technique, and post-debridement wound care.

Results

In the first round, experts established consensus (strongly agree or agree) on 13 of the 38 statements. After the second round, a consensus was reached on 24 of the 25 remaining statements (97.2%).

Conclusions

The present updated consensus document provides recommendations on the use of bromelain-based enzymatic debridement NexoBrid®, integrating the extensive clinical experience of plastic surgeons, intensivists, and anesthesiologists in Spain. Further clinical trials and studies are required to corroborate, modify, or fine tune the current statements.

Level of evidence: Not ratable
Metal implants on abdominal CT: does split-filter dual-energy CT provide additional value over iterative metal artifact reduction?
Authors: Wichtmann Hildegard M. , Laukamp Kai R. , Manneck Sebastian , Appelt Konrad , Stieltjes Bram , Boll Daniel T. , Benz Matthias R. , Obmann Markus M.
Published: September 2022

Purpose

To assess image quality and metal artifact reduction in split-filter dual-energy CT (sfDECT) of the abdomen with hip or spinal implants using virtual monoenergetic images (VMI) and iterative metal artifact reduction algorithm (iMAR).

Methods

102 portal-venous abdominal sfDECTs of patients with hip (n = 71) or spinal implants (n = 31) were included in this study. Images were reconstructed as 120kVp-equivalent images (Mixed) and VMI (40–190 keV), with and without iMAR. Quantitative artifact and image noise was measured using 12 different ROIs. Subjective image quality was rated by two readers using a five-point Likert-scale in six categories, including overall image quality and vascular contrast.

Results

Lowest quantitative artifact in both hip and spinal implants was measured in VMI190keV-iMAR. However, it was not significantly lower than in MixediMAR (for all ROIs, p = 1.00), which were rated best for overall image quality (hip: 1.00 [IQR: 1.00–2.00], spine: 3.00 [IQR:2.00–3.00]). VMI50keV-iMAR was rated best for vascular contrast (hip: 1.00 [IQR: 1.00–2.00], spine: 2.00 [IQR: 1.00–2.00]), which was significantly better than Mixed (both, p < 0.001). VMI50keV-iMAR provided superior overall image quality compared to Mixed for hip (1.00 vs 2.00, p < 0.001) and similar diagnostic image quality for spinal implants (2.00 vs 2.00, p = 0.51).

Conclusion

For abdominal sfDECT with hip or spinal implants MixediMAR images should be used. High keV VMI do not further improve image quality. IMAR allows the use of low keV images (VMI50keV) to improve vascular contrast, compared to Mixed images.

Graphical abstract
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

Persistence 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

In 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

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

In 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

This 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

Photochromic 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

Multiple 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

We 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

Context

Cross-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.

Objectives

We 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.

Methods

Juvenile 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.

Results

Floodplain-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.

Conclusions

These 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

Choosing 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

This 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

People 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

The 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

In 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.
Minimal automorphic superpositions of crowns
Authors: Schröder Bernd S. W.
Published: September 2022

After an overview of uses and explorations of minimal automorphic ordered sets, we present a criterion when certain superpositions of crowns are minimal automorphic. A key lemma to exclude certain retracts can also be applied to ordered sets recently presented in Schröder (Order, https://doi.org/10.1007/s11083-021-09574-3, 2021).
Triaxial compression behavior of large-scale jointed coal: a numerical study
Authors: Wang Xiaoqing , Gao Fuqiang
Published: September 2022

Accurate estimation of the triaxial compression behavior of jointed coal is essential for coal mining. Few studies addressed the triaxial compression behavior of large-scale rock mass, especially with real joint geometry. We employed a numerical synthetic rock mass (SRM) method to study the triaxial compression behavior of jointed coal. Jointed-coal specimens were constructed based on in-situ joint measurements and microparameter calibration against laboratory experiments. A series of triaxial compression tests under different loading orientations and confining pressures were numerically performed to obtain joint and confining-pressure effects on the triaxial compression behavior and reveal the failure mechanism of jointed coal. Results suggest that the triaxial compression behavior of the jointed coal has strong joint and confining-pressure effects. Joints weaken the strength and elastic modulus, reduce the lateral deformation, and affect the geometries of the shear-rupture surface. An increase in the confining pressure causes the peak and residual strength increase significantly. With an increase in the confining pressure, the elastic modulus increases sharply at low confining pressure, the mechanical behavior transitions from brittleness to ductility, the failure mode transitions from shear-rupture surface to plastic flow, and the joint effect diminishes and even disappears. The jointed coal fails by means of a shear-rupture surface under triaxial compression loading with a confining pressure (which is not too high), and the geometries of the shear-rupture surface vary with the distribution of joints.
Hydro-mechanical response of Opalinus Clay in the CO2 long-term periodic injection experiment (CO2LPIE) at the Mont Terri rock laboratory
Authors: Sciandra Dario , Kivi Iman Rahimzadeh , Vilarrasa Víctor , Makhnenko Roman Y. , Rebscher Dorothee
Published: September 2022

Guaranteeing the sealing capacity of caprocks becomes paramount as CO2 storage scales up to the gigaton scale. A significant number of laboratory experiments have been performed with samples of intact rock, showing that low-permeability and high-entry pressure caprocks have excellent sealing capacities to contain CO2 deep underground. However, discontinuities, such as bedding planes, fractures and faults, affect the rock properties at the field scale, being at the same time challenging to monitor in industrial-scale applications. To bridge these two spatial scales, Underground Research Laboratories (URLs) provide a perfect setting to investigate the field-scale sealing capacity of caprocks under a well-monitored environment. In particular, the CO2 Long-term Periodic Injection Experiment (CO2LPIE) at the Mont Terri rock laboratory, Switzerland, aims at quantifying the advance of CO2 in Opalinus Clay, an anisotropic clay-rich rock with bedding planes dipping 45° at the experiment location. To assist in the design of CO2LPIE and have an initial estimate of the system response, we perform plane-strain coupled Hydro-Mechanical simulations using a linear transversely isotropic poroelastic model of periodic CO2 injection for 20 years. Simulation results show that pore pressure changes and the resulting stress variations are controlled by the anisotropic behavior of the material, producing a preferential advance along the bedding planes. CO2 cannot penetrate into Opalinus Clay due to the strong capillary effects in the nanoscale pores, but advances dissolved into the resident brine. We find that the pore pressure oscillations imposed at the injection well are attenuated within tens of cm, requiring a close location of the monitoring boreholes with respect to the injection interval to observe the periodic signal.

Article highlights

Underground rock laboratory experiments permit examining the caprock sealing capacity at a representative scale for CO2 storage;

We perform coupled transverse isotropic hydro-mechanical simulations to gain insight on the response of shaly rock to CO2 periodic injection;

Simulation results assist in the design of the injection amplitude and period and monitoring of the long-term periodic CO2 injection experiment.
A Survey on Object Instance Segmentation
Authors: Sharma Rabi , Saqib Muhammad , Lin C. T. , Blumenstein Michael
Published: September 2022

In recent years, instance segmentation has become a key research area in computer vision. This technology has been applied in varied applications such as robotics, healthcare and intelligent driving. Instance segmentation technology not only detects the location of the object but also marks edges for each single instance, which can solve both object detection and semantic segmentation concurrently. Our survey will give a detail introduction to the instance segmentation technology based on deep learning, reinforcement learning and transformers. Further, we will discuss about its development in this field along with the most common datasets used. We will also focus on different challenges and future development scope for instance segmentation. This technology will provide a strong reference for future researchers in our survey paper.
Identifying key challenges and needs in digital mental health moderation practices supporting users exhibiting risk behaviours to develop responsible AI tools: the case study of Kooth
Authors: Nichele Elena , Lavorgna Anita , Middleton Stuart E.
Published: September 2022

Digital platforms for mental health and wellbeing purposes have become increasingly common to help users exhibiting risk behaviours (e.g. self-harming, eating-related disorders) across all ages, opening new frontiers in supporting vulnerable users. This study stems from a larger project, which explores how responsible AI solutions can up-scale existing manual moderation approaches and better target interventions for young people who ask for help or engage in risk behaviours online. This research aims to better understand the challenges and needs of moderators and digital counsellors, i.e. the ‘behind the scenes’. Through this case study, the authors intend to contribute to the development of responsible AI tools that are fit for purpose and better understand the challenges. The key focus lies on Kooth.com, the UK’s leading free online confidential service offering counselling and emotional wellbeing support to young people in the UK through its online web-based and pseudo-anonymous digital platform.
Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods
Authors: Sahiner Mehmet
Published: September 2022

The present paper examines the relative out-of-sample predictive ability of GARCH, GARCH-M, EGARCH, TGARCH and PGARCH models for ten Asian markets by using three different time frames and two different methods, considering the features of volatility clustering, leverage effect and volatility persistence phenomena, for which the evidence of existence is found in the data. Five measures of comparison are employed in this research, and a further dimension is investigated based on the classification of the selected models, in order to identify the existence or lack of any differences between the recursive and rolling window methods. The empirical results reveal that asymmetric models, led by the EGARCH model, provide better forecasts compared to symmetric models in higher time frames. However, when it comes to lower time frames, symmetric GARCH models tend to outperform their asymmetric counterparts. Furthermore, linear GARCH models are penalized more by the rolling window method, while recursive method places them amongst the best performers, highlighting the importance of choosing a proper approach. In addition, this study reveals an important controversy: that one error statistic may suggest a particular model is the best, while another suggests the same model to be the worst, indicating that the performance of the model heavily depends on which loss function is used. Finally, it is proved that GARCH-type models can appropriately adapt to the volatility of Asian stock indices and provide a satisfactory degree of forecast accuracy in all selected time frames. These results are also supported by the Diebold-Mariano (DM) pairwise comparison test.
Classical Numerical Analysis
Authors: Salgado Abner J. , Wise Steven M.
Published: September 2022

Numerical Analysis is a broad field, and coming to grips with all of it may seem like a daunting task. This text provides a thorough and comprehensive exposition of all the topics contained in a classical graduate sequence in numerical analysis. With an emphasis on theory and connections with linear algebra and analysis, the book shows all the rigor of numerical analysis. Its high level and exhaustive coverage will prepare students for research in the field and become a valuable reference as they continue their career. Students will appreciate the simple notation, clear assumptions and arguments, as well as the many examples and classroom-tested exercises ranging from simple verification to qualifying exam-level problems. In addition to the many examples with hand calculations, readers will also be able to translate theory into practical computational codes by running sample MATLAB codes as they try out new concepts.
Epidemic Cities
Authors: Carbone Antonio
Published: September 2022

Epidemic Cities provides an overview of the history of epidemics through a particular focus on a range of cities in different regions of the world. The dual focus on both epidemics and specific cities provides an unusual perspective on global history: the analysis of globally circulating epidemics enables reconstructing a variety of wide-reaching entanglements, on the one hand. On the other hand, the concentration with specific urban settings highlights differences and the unevenness engendered by global entanglements. After an introduction concerning the history of the relationship between medicine, epidemics, and cities, the book focuses on the history of three epidemic diseases and how they affected Paris, Buenos Aires, Hong Kong, Bombay, and Baltimore. The timings of major pandemics punctuate the structure of the book: cholera pandemics from the 1830s to the late nineteenth century, bubonic plague at the turn of the twentieth century, and finally tuberculosis until the mid-twentieth century.
Role of particle-laden interfaces in shear-induced deformation of colloidal droplets
Authors: Luo Zheng Yuan , Qi Jie , Bai Bo Feng
Published: September 2022

In this study, basing on the level-set and point-particle methods, we have developed a numerical methodology for simulating the dynamics of colloidal droplets under flow conditions in which the particle–particle, particle–interface and particle–fluid interactions are all taken into account efficiently. By using this methodology, we have determined the essential role of particle-laden interfaces in the deformation of colloidal droplets in simple shear flow with relatively low particle concentrations. Generally, adsorbed particles strongly enhance the deformability of the whole droplet, which is principally attributed to the particle-induced reduction of the effective surface tension. Systematic simulations are performed to reveal the detailed roles of interparticle interactions and particle surface coverage in the deformation of particle-covered droplets. Most importantly, we find the promotion effect of adsorbed particles on the droplet deformation cannot be completely included via the effective capillary number characterizing the particle-induced overall reduction of the effective surface tension, which is particularly obvious at high particle coverage. We propose two potential reasons for this surprising phenomenon, i.e. the convection-induced non-uniform distribution of adsorbed particles over the droplet surface and the particle-induced reduction of the droplet surface mobility, which have not been discussed yet in previous numerical and experimental studies of particle-covered droplets in shear flow.
Vortex structures in the wake of a marine propeller operating close to a free surface
Authors: Di Mascio A. , Dubbioso G. , Muscari R.
Published: September 2022

The present paper analyses the vortical structures in the wake of a naval propeller operating underneath a free surface using detached-eddy simulation. We investigate the flow topology for several loading conditions and compare it with analogous observations behind a propeller operating in open water. We show that the wake topology is similar to that observed in open water only for low-loading conditions. For mild blade loading, the free surface's presence seems to stabilize the flow. On the contrary, for high blade loading, the mutual interaction between the vortex system and the free surface leads to vortex breakdown that overshadows the multiple pairing mechanisms observed in open-water conditions.