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Wetland reclamation was an intrinsic part of nineteenth-century global agricultural transformations. In Swedish research, reclamation has mainly been situated in larger general processes of population rise, commercialization and societal/technological development. The intersection of reclamation, physical environments and local economies has seldom been studied in detail. This paper conducts a local analysis of nineteenth-century wetland reclamation in two parishes in Sweden, Knätte and Mörlunda, through combining a study of specific reclamation processes with an analysis of local agrarian-economic development. The results show that these processes varied depending on specific historical-geographical circumstances. In Knätte, reclamation was not primarily related to population rise, but to increasing commercialization during the period. The case in Mörlunda instead shows how reclamation was first a response to increasing population but later developed into a project of agricultural market adaptation. In both cases, the physical environment led to varying degrees of geographic constraint in the process. In combination, these results point to the importance of detailed case studies in nuancing our understanding of nineteenth-century wetland reclamation both in Sweden and internationally. • Local factors are important for nuancing general trends in wetland reclamation. • In Sweden, population rise and commercialization are considered primary drivers. • The active drivers vary between the compared cases, depending on context. • Reclamation was primarily a part of local agrarian developments. • Wider relations of the local economy, for example through trade, also impacted. [ABSTRACT FROM AUTHOR]

• Low-velocity impacts can cause microscopic and invisible damage to Carbon Fiber Reinforced Polymer (CFRP) structures, potentially compromising their integrity and leading to catastrophic failures. In this paper, an impact localization system for CFRP structures was developed by using Fiber Bragg Grating (FBG) sensors. The time difference of arrival (TDOA) between signals from different FBG sensors are collected to characterize the impact location, and an impact localization method of CFRP structure based on CNN-LSTM-Attention is proposed. The following conclusions can be made from this study: • A monitoring system of impact on CFRP structures was developed by using fiber Bragg grating (FBG) sensors, and impact signals detected by FBG sensors are demodulated by edge-filtering at high speed. • The Time Difference of Arrival (TDOA) between signals from different FBG sensors are collected to characterize the impact location, the occurrence time of the first trough in the low-frequency narrowband signal component is extracted as the arrival time of impact signal, which is found to be sensitive to the location of impact and thus can be used as features for impact localization. • An impact localization method of CFRP structure based on CNN-LSTM-Attention is proposed. The time differences in the arrival of impact signal detected by different FBG sensors are used as features, and attention mechanism is introduced into the CNN-LSTM model of impact localization to emphasizes the arrival time difference of impact signal detected by nearby FBG sensors. • The impact localization method was developed and validated on a CFRP plate by using FBG sensors. Comparative analysis of localization performance between different models confirms the effectiveness and satisfactory performance of the proposed method. Low-velocity impacts can cause microscopic and invisible damage to carbon fiber reinforced polymer (CFRP) structures, potentially compromising their integrity and leading to catastrophic failures. Therefore, obtaining precise information about the impact location is crucial for monitoring the health of CFRP structures. In this paper, an impact localization system for CFRP structures was developed by using fiber Bragg grating (FBG) sensors, and impact signals detected by FBG sensors are demodulated by edge-filtering at high speed. An impact localization method of CFRP structure based on CNN-LSTM-Attention is proposed. The time difference of arrival (TDOA) between signals from different FBG sensors are collected to characterize the impact location, and attention mechanism is introduced into the CNN-LSTM model to augment the significance of TDOA of impact signal detected by proximal FBG sensors. The model is trained using the training set, its parameters are optimized using the validation set and the localization performance of different models are compared by the test set. The proposed impact localization method based on CNN-LSTM-Attention model was verified on a CFRP plate with an experiment area of 400 mm*400 mm. Experimental results prove the effectiveness and satisfactory performance of the proposed method. [ABSTRACT FROM AUTHOR]

This paper addresses the need to understand the structure of sustainability change in the face of the unpredictability of modern civilization. The aim of the paper is to examine the structure of sustainability change in relation to smaller spatial units such as the regions of the European Union and to compare these results with those achieved at the country level. For this purpose, the sustainable development indicators available in the Eurostat database were analyzed. Studies published to date have tended to focus on the performance of national economies or selected regions. In this article, the available data on regions are also analyzed. The study aims to compare the level of sustainable development achieved at the level of EU countries and regions located within them. Methodologically, the study uses advanced methods of comparative analysis, and the synthesis of the data enables the construction of a synthetic measure using taxonomic methods, facilitating the classification of EU countries and regions into clusters. The results highlight significant divergences in sustainability achievements between EU countries and regions. The study reveals the importance of studying sustainable development in smaller geographical cross-sections. The results highlight the need to expand access to data at the regional level (sustainability indicators) to facilitate more comprehensive analyses and inform targeted policy interventions. Looking to the future, the study recommends further research into the inter-linkages between sustainability and other critical areas in EU regions, such as innovation and competitiveness. • A new approach to studying sustainable development from a regional perspective has been proposed. • An in-depth analysis of the current level of sustainability in EU regions was carried out. • The diversity of sustainable development in the countries of the EU has been described. [ABSTRACT FROM AUTHOR]

Over the last decade, clinical practice guidelines (CPGs) have become an important asset for daily life in healthcare organizations. Efficient management and digitization of CPGs help achieve organizational objectives and improve patient care and healthcare quality by reducing variability. However, digitizing CPGs is a difficult, complex task because they are usually expressed as text, and this often leads to the development of partial software solutions. At present, different research proposals and CPG-derived CDSS (clinical decision support system) do exist for managing CPG digitalization lifecycles (from modeling to deployment and execution), but they do not all provide full lifecycle support, making it more difficult to choose solutions or proposals that fully meet the needs of a healthcare organization. This paper proposes a method based on quality models to uniformly compare and evaluate technological tools, providing a rigorous method that uses qualitative and quantitative analysis of technological aspects. In addition, this paper also presents how this method has been instantiated to evaluate and compare CPG-derived CDSS by highlighting each phase of the CPG digitization lifecycle. Finally, discussion and analysis of currently available tools are presented, identifying gaps and limitations. [Display omitted] [ABSTRACT FROM AUTHOR]

The Intel DPC++ Compatibility Tool is a component of the Intel oneAPI Base Toolkit. This tool automatically transforms CUDA code into Data Parallel C++ (DPC++), thus assisting in the migration process. DPC++ is an implementation of the programming standard for heterogeneous computing known as SYCL, which unifies the development of parallel applications on CPUs, GPUs or even FPGAs. This paper analyzes the DPC++ Compatibility Tool by considering the manual intervention required and the problems encountered while migrating the Rodinia benchmarks. For this suite, this tool achieves an impressive rate of almost 87% for code successfully migrated. Moreover, a comparative study of the performance obtained by the migrated code was carried out, showing a moderate overhead in most of the migrated examples. Finally, a performance comparison on different devices was also performed. • Performance and portability are big challenges in heterogeneous computing. • Intel DPC++ Compatibility Tool transforms CUDA code into Data Parallel C++ (DPC++) easing the migration process. • A comparative study of the performance obtained by the migrated code is performed with Rodinia benchmarks. [ABSTRACT FROM AUTHOR]

• A study space analysis of the entire literature on child-directed speech reveals considerable gaps in research efforts with respect to comparisons between child- and adult-directed speech for several combinations of input domains and learning outcomes. • Studies that compare learning outcomes between child-directed and adult-directed speech have to date focussed mainly on prosodic, phonetic, and phonological features of child-directed speech and on the ability to discriminate between child-and adult-directed speech. Evidence about learning benefits from other input features and learning outcomes is limited. • Thus, claims that child-directed speech facilitates language learning do not generalise across other input domains and learning outcomes and should more accurately represent the limitations of the available evidence. Future research efforts would benefit from filling the identified gaps in the study space. Because child-directed speech (CDS) is ubiquitous in some cultures and because positive associations between certain features of the language input and certain learning outcomes have been attested it has often been claimed that the function of CDS is to aid children's language development in general. We argue that for this claim to be generalisable, superior learning from CDS compared to non-CDS, such as adult-directed speech (ADS), must be demonstrated across multiple input domains and learning outcomes. To determine the availability of such evidence we performed a study space analysis of the research literature on CDS. A total of 942 relevant papers were coded with respect to (i) CDS features under consideration, (ii) learning outcomes and (iii) whether a comparison between CDS and ADS was reported. The results show that only 16.2% of peer-reviewed studies in this field compared learning outcomes between CDS and ADS, almost half of which focussed on the ability to discriminate between the two registers. Crucially, we found only 20 studies comparing learning outcomes between CDS and ADS for morphosyntactic and lexico-semantic features and none for pragmatic and extra-linguistic features. Although these 20 studies provided preliminary evidence for a facilitative effect of some specific morphosyntactic and lexico-semantic features, overall CDS-ADS comparison studies are very unevenly distributed across the space of CDS features and outcome measures. The disproportional emphasis on prosodic, phonetic, and phonological input features, and register discrimination as the outcome invites caution with respect to the generalisability of the claim that CDS facilitates language development across the breadth of input domains and learning outcomes. Future research ought to resolve the discrepancy between sweeping claims about the function of CDS as facilitating language development on the one hand and the narrow evidence base for such a claim on the other by conducting CDS-ADS comparisons across a wider range of input features and outcome measures. [ABSTRACT FROM AUTHOR]

This study explores how well various machine learning classifiers can identify mean-motion resonances in the main belt using supervised learning. The most popular classifiers are assessed: k-Nearest Neighbours, Decision Tree, Gradient Boosting, AdaBoost, Random Forest, and Naïve Bayes. In contrast to previous studies that often relied on default ML configurations, this research conducts a detailed investigation, fine-tuning, and testing of each classifier across various parameters. The results show that simpler models, especially k-Nearest Neighbours and Decision Tree, perform better than more complex ones, particularly in terms of F 1 scores. The paper provides guides on selecting features, parameters, and training set sizes for optimal classifier performance and outlines a method for developing effective machine-learning models for asteroid classification. • Fine-tuning classifiers boosts performance in asteroid classification. • kNN and Decision Trees outperform in mean-motion resonance identification. • Naïve Bayes is effective with minimal initial dataset. [ABSTRACT FROM AUTHOR]

In this paper, we propose a set-analytic approach to the study of intersectionality. Our approach builds on the intersectional view that combinations of attributes, such as black females , should be understood as qualitatively distinct states, not reducible to their component attributes. We show that interaction-based, quantitative approaches are not only inconsistent with the core assumptions of intersectionality but also may underestimate the presence of penalties linked to multi-category memberships. In contrast, we show that truth table analysis, a core feature of Qualitative Comparative Analysis, directly implements several of the core methodological concerns of the intersectionality perspective. The truth table approach offers two important advantages. (1) It provides a foundation for the comparison of logically 'adjacent' configurations—combinations of case characteristics that differ by only a single attribute. (2) It can accommodate case attributes that vary by level or degree in a set-theoretic, intersectional framework. [ABSTRACT FROM AUTHOR]

Mesh-based Eulerian and particle-based Lagrangian models are common computational fluid dynamics (CFD) tools for simulating wave-structure interactions. While Eulerian models are efficient in terms of computational time, they are limited in their ability to handle large interface discontinuities between two flows and complex structure motion responses. Conversely, Lagrangian models are suitable for such discontinuities and motion responses but can be computationally expensive. However, there is a lack of comprehensive discussion on the (dis)advantages of hybrid Eulerian-Lagrangian models, which have the potential to achieve both numerical efficiency and flexibility through a combined use of mesh and particles. This paper presents a comparative study of a hybrid Eulerian-Lagrangian Particle-In-Cell (PIC) model and the widely-used OpenFOAM model, applied to a variety of complex wave interactions with floating offshore renewable energy structures in both 2D and fully 3D domains. We found that both models demonstrate good performance in simulating complex floating structures. Additionally, it is the first time that the two models have been compared in parallel on the same computing facility, allowing us to directly show their computational efficiency. The PIC model has the advantage of using staggered grids, which enables it to achieve computational efficiency comparable to the pure mesh-based OpenFOAM. The findings of this study provide researchers and practitioners in the field of computational fluid dynamics with a clear understanding of the performance of the hybrid Eulerian-Lagrangian PIC model and OpenFOAM for simulating complex fluid-structure interaction problems. [ABSTRACT FROM AUTHOR]

• The relationship between MHBM and VCHBM is unveiled by deriving the transformation matrices for their nonlinear algebraic equations. • A new efficient formulation for alternating Frequency-Time method (AFT) in VCHBM is proposed to avoid unnecessarily time-consuming symbolic operations. • A phase condition for arc-length continuation method (ALC) in VCHBM is proposed to perform a robust and efficient continuation in the solution branches. • It is found that MHBM demonstrates a higher computational efficiency but VCHBM provides a more robust and accurate result. Quasi-periodic solutions widely exist in nonlinear dynamical systems, which are the one of the most important dynamical behaviors but much more difficult to obtain full- or semi-analytically than equilibria and periodic solutions. Recently, multi-harmonic balance method (MHBM) and variable-coefficient harmonic balance method (VCHBM) have been proposed to determine the quasi-periodic solutions semi-analytically. In this paper, after a brief review on the two methods, that is, MHBM uses a multi-dimensional Fourier series and VCHBM a variable-coefficient Fourier series, the relationship between them is unveiled particularly for the case of quasi-periodic solutions consisting of two frequency components. The transform matrices between the algebraic equations of the Fourier coefficients in the two methods are derived. Furthermore, a new formulation for alternating Frequency-Time method (AFT) and a phase condition for arc-length continuation method (ALC) in VCHBM are proposed to make the method more efficient and robust. Through the application of two examples, it is found that when the two methods choose equal harmonic order and thus have the same number of unknowns, MHBM demonstrates higher computational efficiency but VCHBM shows more robust and accurate, especially for the quasi-periodic solutions in the nonlinear dynamical systems with a single-frequency excitation. This paper provides insight views into the features of MHBM and VCHBM.. [ABSTRACT FROM AUTHOR]

Finding a novel drug is a very long and complex procedure. Using computer simulations, it is possible to accelerate the preliminary phases by performing a virtual screening that filters a large set of drug candidates to a manageable number. This paper presents the implementations and comparative analysis of two GPU-optimized implementations of a virtual screening algorithm targeting novel GPU architectures. This work focuses on the analysis of parallel computation patterns and their mapping onto the target architecture. The first method adopts a traditional approach that spreads the computation for a single molecule across the entire GPU. The second uses a novel batched approach that exploits the parallel architecture of the GPU to evaluate more molecules in parallel. Experimental results showed a different behavior depending on the size of the database to be screened, either reaching a performance plateau sooner or having a more extended initial transient period to achieve a higher throughput (up to 5x), which is more suitable for extreme-scale virtual screening campaigns. • Analyze and compare two CUDA implementations of a real-world virtual screening application with a completely different design. • Experimental results show how a batched approach yields a much higher throughput than an approach that spreads the computation across the GPU. • To explain the performance, we performed a detailed analysis considering the algorithm, hardware characteristics, and input features. [ABSTRACT FROM AUTHOR]

The site selection for Low Impact Development (LID) practices is a significant process. It affects the effectiveness of LID in controlling stormwater surface runoff, volume, flow rate, and infiltration. This research paper presents a comprehensive review of various methods used for LID site selection. It starts by introducing different methods and tools. Three main methods: index-based methods, GIS-based multi-criteria decision analysis (MCDA), and multi-criteria models and tools, are discussed in detail. A comparative analysis of these methods is then conducted based on ten different criteria. These criteria include the number of variables, data properties, the scale of analysis, benefits maximization approach, multi-attribute decision analysis, user-friendliness, community and stakeholder participation, and the validation methods. This comparison reveals limitations in each method. These include inadequate data availability and quality, lack of evaluation methods, comprehensive assessment criteria and spatial explicitness. These challenges underscore the need for future research to prioritize spatial clarity, broaden criteria, improve data quality through standardization, incorporate field visits and remote sensing for robust results, integrate big data, and develop web-based, open-source tools for enhanced accessibility. These key strategies provide valuable insights for advancing LID site selection methods. • Reviews key LID site selection methods. • Comparative analysis based on multiple factors. • Highlights method limitations, prompting further research in LID site selection. • Recommends improvements and new methods to address research gaps. [ABSTRACT FROM AUTHOR]

This paper presents the compact analytical model of underlap gate stack (GS) graded channel (GC) junction accumulation mode (JAM) junctionless (JL) FET. At first, a comparative analysis between the two different graded channel schemes and non-graded channel is performed based on I ON , I OFF and I ON / I OFF ratio. The scheme that yields the higher I ON / I OFF ratio along with smaller I OFF , is adopted in the proposed JL FET for further analysis. The 2D analytical modeling of the GS-GC-JAM-JL FET deals with the determination of surface potential, threshold voltage, subthreshold drain current, DIBL and subthreshold swing. Results obtained from analytical model and simulations are compared and an excellent match is found. Thus the present paper establishes the outstanding ability of proposed underlap GS-GC-JAM-JL FET architecture to shield the short channel effects without sacrificing its performance, and therefore, proves it as a potential candidate for ultra-low power applications. • Analytical modeling of GS-GC-JAM-JL FET is presented here. • Comparative analysis between the various graded channel schemes with non-graded channels is done based on I ON , I OFF and I ON /I OFF ratio. • Graded channel scheme that yields the higher I ON /I OFF ratio with smaller I OFF , is incorporated in the proposed JL FET for further analysis. • Proposed underlap GS-GC-JAM-JL FET architecture shields the short channel effects without sacrificing its performance. [ABSTRACT FROM AUTHOR]

This paper challenges conventional understandings of how we think about consumer food waste by investigating the food purchasing/wasting views and practices of 102 Colorado (USA) residents (67 households). The methods used in this study included the triangulation of surveys, self-reported pictures of food waste and related daily reports over a two-week period, and focus groups. Understanding who is, and what are, driving food waste is important if the aim is to create policy interventions that meaningfully mitigate loss. This paper approaches concepts like consumer sovereignty and agency through a non-essentialist lens, which is to say it repositions food waste as a mode of ordering as opposed to an outcome of discrete, self-evident products-e.g., attitudes, autonomous consumers. Doing this opens the analysis up to connections that might otherwise go unrecognized when those categories are assumed to be absolute and obvious. After presenting numerical data gleaned from online surveys, findings are organized around the following themes: humans-as-assemblage; storage devices-as-assemblage; and mobility-as-assemblage. The paper concludes synthesizing these themes while suggesting interventions mindful of these fluid socio-material coming-togethers. [ABSTRACT FROM AUTHOR]

• The percentage of studies using both sexes subjects was significantly higher in 2015–2019 than in 2000–2014. • Clinical studies showed a drastically higher percentage of both-sexes studies than basic studies utilizing other mammalians. • Reasons for the use of single-sex subjects mainly included insufficient subject numbers and misconceptions of females. • The variations in inclusion and analysis of the sexes across different biomedical disciplines for alcohol research were wide. • Implementation of NIH SABV policy increased ratio of NIH-funded papers with sex-based analysis. We aimed to assess the sex-inclusive and sex-based analysis bias in alcohol research for the past 20 years. Data were abstracted from 2988 original research articles published from 2000 through 2019 in 51 representative journals across 9 biomedical disciplines. An analysis in 5-year intervals revealed that the percentage of studies using participants of both sexes was significantly higher between 2015 and 2019 than between 2000 and 2014. When stratified, clinical studies showed a higher percentage of both-sex studies compared to basic studies using animals. The reasons for the use of single-sex cohorts mainly included insufficient participant numbers and misconceptions surrounding the hormonal variability of females. Implementation of the NIH SABV policy promoted the ratio of NIH-funded papers with sex-based analyses. In conclusion, sex bias in alcohol-related biomedical studies has improved over the past 20 years, particularly after the implementation of the SABV policy. Although clinical studies increasingly included sex-based analysis, basic studies were biased towards the use of males. [ABSTRACT FROM AUTHOR]

Most literature on food waste shows that food that ends up in the garbage can is often no longer considered as enjoyable, or even as edible. In this paper, we decided to focus on assessments of whether leftover food is still considered as worth eating, to provide a better understanding of the production of domestic food waste. We constructed a pluridisciplinary approach, combining sensory analysis and sociology. The first part was conducted in a test kitchen under controlled conditions: 50 participants had to sort out and decide to keep or to throw away different types of refrigerated leftovers. The second part used in-depth interviews with half of these participants (N = 25) to explore their food habits and perceptions and handling of leftovers at home. The first section of the paper presents the theoretical framework of the study, which is grounded in practice theory. Then we detail the methodology and the results. We show that sorting out leftovers is a process mobilizing embodied knowledge and resulting from domestic practices implemented to avoid waste, such as storing or reusing leftovers. In the discussion, we analyze the sorting of refrigerated food products as a compound practice, situated at the intersection of provisioning, cooking, meal organization, and judgment of taste (Warde, 2013). Using this theoretical framework enables us to understand the heterogeneity observed in the outcome of the sorting process as the result of its weak degree of regulation. The sorting out practice is thus consistent with different modes of engagement such as food waste prevention, health maintenance, or providing enjoyable family meals. We conclude by providing suggestions of policy recommendations regarding domestic refrigeration, food storage, and assessment practices. [ABSTRACT FROM AUTHOR]

This paper is based on a presentation given at the Annual Meeting of the Society for the Study of Ingestive Behavior in July 2021 and provides a personal view on some of the milestones in the discovery of amylin as a constituent of pancreatic islet amyloid deposits, as a pancreatic beta-cell hormone, and on its role in physiology and pathophysiology. Only selected effects of amylin are discussed here because we recently published extensive reviews on the physiology and pathophysiology of amylin. Amylin was discovered as the main constituent of islet amyloid that is predominantly found in pancreatic islets in type 2 diabetics. These deposits, and in particular small oligomer aggregates of amylin seem to contribute to the progressive beta-cell damage seen in type 2 diabetics. Amylin is also a physiologically relevant circulating hormone with diverse metabolic functions, e.g. inhibition of eating, of pancreatic glucagon secretion and of gastric emptying. Knowledge of these types of functions and amylin's mechanisms of action lead to the development of amylin analogues that are now among the most promising anti-obesity targets in clinical testing. With this review, I want to give a short overview of 35 exciting years of amylin research. [ABSTRACT FROM AUTHOR]

The brain is thought to implement two decision-making systems: a goal-directed system in which decisions are made through planning on the basis of action-outcome relationships, and a habitual system in which behaviour reflects stimulus-response associations. A prominent theory of addiction sees it as arising due to an extreme dominance of habit over goal-directed action. The balance between these systems is thought to be arbitrated by the relative precision of their separate predictions of reward. In this paper, we argue that various factors in addiction create hyper-precise reward predictions in the habitual system and hypo-precise reward predictions in the goal-directed system, shifting the balance of behavioural control in favour of habit. Based on this, we offer a theoretical account of the utility of episodic future thinking in addiction, interpreting it as increasing the precision of reward estimates in the goal-directed system, thereby enhancing the control of this system over behaviour. [ABSTRACT FROM AUTHOR]

In this paper, several deep fully convolutional neural networks for image segmentation such as residual UNet, VGG16 encoder–decoder, FCN-DenseNet, PSPNet, and GCN are employed for delamination detection and localisation in composite materials. All models were trained and validated on our previously generated dataset that resembles full wavefield measurements acquired by scanning laser Doppler vibrometer. Additionally, a thorough comparison between all presented models is provided based on several evaluation metrics. Furthermore, the models were verified on experimentally acquired data with a Teflon insert representing delamination showing that the developed models can be used for delamination size estimation. The achieved accuracy in the current implemented models surpasses the accuracy of previous models with an improvement up to 22.47% for delamination identification. • Deep semantic segmentation techniques for delamination identification in CFRP. • Comparative study of five fully convolutional neural networks. • The training on synthetic data resulted in good generalisation capabilities. • Validation on experimental data. [ABSTRACT FROM AUTHOR]

Hypothesis testing is one of the fundamental paradigms of statistical inference. The three canonical hypothesis testing procedures available in the statistical literature are the likelihood ratio (LR) test, the Wald test and the Rao (score) test. All of them have good optimality properties and past research has not identified any of these three procedures to be a clear winner over the other two. However, the classical versions of these tests are based on the maximum likelihood estimator (MLE), which, although the most optimal estimator asymptotically, is known for its lack of robustness under outliers and model misspecification. In the present paper we provide an overview of the analogues of these tests based on the minimum density power divergence estimator (MDPDE), which presents us with an alternative option that is strongly robust and highly efficient. Since these tests have, so far, been mostly studied for univariate responses, here we primarily focus on their performances for several important hypothesis testing problems in the multivariate context under the multivariate normal model family. [ABSTRACT FROM AUTHOR]

Child eating behaviours have consistently been linked to child weight status. Yet, changes in child eating behaviours during early obesity treatment are rarely evaluated. Psychometric evaluation of the Child Eating Behaviour Questionnaire (CEBQ) is common, but results are sample-dependent and included items may not capture the full range of the underlying traits. Rasch analysis can overcome these disadvantages. The aim of this paper was to assess child eating behaviours measured by the CEBQ after a 12-month obesity intervention applying the Rasch model for the validation of the CEBQ. The Rasch-based fit statistics were applied in children from two samples, Australian and Swedish (n = 1724). Changes in eating behaviours amongst children aged 4-6 years were examined in the More and Less RCT for obesity treatment (n = 177), which compared a parenting programme (with and without boosters) against standard treatment. Parents completed the CEBQ at four time points over 12-months. Linear mixed models were applied to estimate treatment effects on the CEBQ, refined according to Rasch, over time. We found that the validity of CEBQ was confirmed after removing 4 items (item fit statistics outside range 0.5-1.5). When the refined CEBQ was used in the assessment of the RCT, there were no differences in parental reports of changes in children's eating behaviours between the parenting programme and standard treatment (group-by-time interactions p > 0.05). However, in the total sample food approach behaviours decreased while fussy eating behaviours increased (p < 0.05). In conclusion, the refined CEBQ proved to be a valid tool for examining parent-reported child eating behaviours. Early obesity treatment may decrease eating behaviours associated with higher child weight. Future research should address the associations between changes in child weight status and eating behaviours. [ABSTRACT FROM AUTHOR]

We conceptualize the journey to ethical veganism in the stages of the transtheoretical model of change, from precontemplation through contemplation, preparation, action, and maintenance. At each stage, we explore the psychological barriers to progressing towards veganism, discuss how they manifest, and explore ways to overcome them. It is hoped that this paper can be used as a guide for animal advocates to identify the stage an individual is at, and understand and overcome the social and psychological barriers they may face to progressing. We argue that, while many people are ignorant of the cruel practices entailed in animal farming, many deliberately avoid thinking about the issue, are unable to appreciate the scale of the issue, and simply tend to favour the status quo. When engaging with the issue of farm animal suffering, meat-eaters are largely driven by cognitive dissonance, which manifests as motivated reasoning aimed at protecting one's image of oneself and one's society. This is facilitated by confirmation bias and complicit media which cater to the preferred views of their meat-eating audience. Even once convinced of veganism, habit and willpower present further barriers to acting on those beliefs. This is all in the context of a speciesist and carnistic culture where meat consumption is normal, farming is noble, and vegans are 'others'. We locate and elucidate each of these biases within the stages of the transtheoretical model and discuss the implications of this model for animal advocates and for further research. [ABSTRACT FROM AUTHOR]

This paper evaluates responses to the NASA Langley Challenge on Optimization under Uncertainty. The challenge respondents were tasked to quantify the aleatory and epistemic uncertainty impacting the predictions of a computational model calibrated according to a limited number of sub-system and full-system observations. In addition, they evaluated the global sensitivity of the model's prediction with respect to the epistemic variables in order to choose a few of them for refinement. Ultimately, they had to find a reliability-based design that is robust to all/most epistemic realizations within their identified range of uncertainty. The assessments presented herein evaluate the proposed responses within a synthetic validation framework. This framework gauges the ability of the designs to satisfy the reliability requirements imposed upon them against additional data. These data correspond to additional realizations of the aleatory variables, and to the true but unknown value of the epistemic variables. Best practices and lessons learned are set forth based on the comparative analysis of the various responses. [ABSTRACT FROM AUTHOR]

Food desire is an intense motivational state a consumer experiences toward food that accounts for much of consumption. While extant research has shown that experiencing desire elicits consumption imagery, it remains unclear whether consumption imagery alone instigates desire. Even though this directional relationship has been often speculated upon, little empirical study has considered it. This paper empirically identifies imagined consumption as an antecedent of food desire. Six studies show that consumption imagery increases food desire and suggest that this impact is due to induced feelings of deprivation. Our findings also show that increased desire explains previously researched outcomes of imagery, such as a higher willingness to pay for and consumption volumes of the imagined food. [ABSTRACT FROM AUTHOR]

A reduction of meat consumption and shift to plant-based diets, especially in industrialized countries, is acknowledged as crucial for reaching climate targets, addressing public health problems, and protecting animal welfare. While scholarly research distilled drivers of meat consumption and barriers to its reduction, insights into the effectiveness of measures to initiate such a profound change in consumer behaviour are relatively scarce. This paper presents a systematic literature review on consumption-side interventions in the context of meat consumption across scholarly disciplines. Our analysis confirms that existing research predominantly assessed interventions addressing personal factors of behavioural change such as knowledge and emotions. Whether these interventions are effective depends on whether information (i) is provided on health, animal welfare or environmental effects, (ii) is emotionally or cognitively framed, and (iii) is aligned with consumers' information needs. Moreover, linking meat to living animals or to the humanness of animals activates negative emotions and, thus, reduces meat consumption. Further, increasing the visibility and variety of vegetarian dishes in food environments decreases meat-eating. Also, educational courses on how to shop and cook vegetarian food are effective in reducing meat consumption. There is less evidence on the effectiveness of interventions addressing socio-cultural factors such as social norms. Regarding future research directions, existing research mainly investigated the influence of interventions on attitudes and behavioural intentions. Hence, there is still a need for studies to assess more long-term effects of intervention measures on actual meat consumption and their potential to initiate fundamental changes in dietary habits. [ABSTRACT FROM AUTHOR]

Traditional food marketing stimulates adolescents' consumption of energy-dense, nutrient-poor foods. These dietary behaviours may track into adulthood and lead to weight gain, obesity and related non-communicable diseases. While social media use in adolescents has proliferated, little is known about the content of food marketing within these platforms, and how this impacts adolescents' dietary behaviours. This paper aimed to obtain expert insights on factors involved in the association between social media food marketing (SMFM) and adolescent dietary behaviours, and to explore their views on key priorities, challenges and strategies for future SMFM research and policies. One-on-one semi-structured interviews (n = 17) were conducted with experts from Western Europe, Australia and North America, in the fields of public health (policy), nutrition science, social media marketing, adolescent medicine, clinical psychology, behavioural sciences, communication, food industry, social influencing, and social marketing. The experts' collective responses identified that the line between food content posted by social media users and food companies is blurred. Adolescents' processing of SMFM may be mostly implicit, involving social comparison, emotional engagement, and attaching symbolic meanings to foods. Mediating factors and adolescent-specific and SMFM-specific moderating factors potentially influencing adolescents' response to SMFM were summarized in a Social Ecological model. Experts agreed that there is limited scientific evidence on adolescent-targeted SMFM and there are no strict regulations in place to protect adolescents from unhealthy SMFM, while adolescents are active social media users who are cognitively vulnerable to implicit marketing tactics. Adolescent-targeted SMFM should be controlled by encouraging healthy food marketing or limiting junk food marketing. Also, prioritizing both quantitative research on SMFM exposure and its impact, and qualitative research to obtain adolescents' perspectives, is crucial to advocate for regulatory changes regarding adolescent-targeted SMFM content. [ABSTRACT FROM AUTHOR]

Nudges are changes in choice architecture (i.e., the environment in which people make decisions) aiming to steer a person's decision to a particular choice, without restricting alternative options or changing financial incentives. These strategies have been extensively used to promote healthy eating, above all among youths, whose behaviors can still be easily shaped compared to older people's. The current paper describes two studies aiming to investigate the effectiveness of nudging interventions in promoting healthy eating among university students. The first study consisted of a systematic review mapping all the published studies which describe the effectiveness of this kind of intervention worldwide. Twelve eligible records were selected after a search of three different databases. Information about the publication of the record, the adopted research methods and the described intervention was retrieved from each selected record. Based on this review's results, a new nudging intervention was developed to promote healthy food choice among Italian university students. The intervention aimed to modify students' choice for each of the Italian meal courses: first course (pasta, rice or soup), second course (meat, fish, cheese or cured meat), side dish, bread, and fruit. An Italian university cafeteria was observed in two phases: a pre-intervention phase (baseline) and a post-intervention phase (nudging strategies were implemented in the cafeteria's architecture). The applied nudging intervention was effective in promoting healthy choices in relation to the second course, the side dish, and the bread, but it did not significantly affect choices related to the first course or the fruit. Implications of these results and suggestions for future interventions are discussed. [ABSTRACT FROM AUTHOR]

Consumers often struggle to assess food's environmental impact. A product ranking based on a standardized scoring approach (aggregating multiple indicators) that is easily accessible, for instance, via a mobile app, could serve as a simple decision aid for consumers. However, to avoid information overload, research is needed in which format such information should be presented. This paper examines how different information levels of an eco-score ranking influence decision uncertainty and sustainable food choice. In an online experiment (n = 332, representative by age and gender), we compared a basic eco-ranking and an extended eco-ranking (eco-rank plus additional indicators: transportation distance and eco-certifications) against a control group (no eco-ranking) in three different food categories: milk, juice, and eggs. The basic eco-ranking successfully lowered decision uncertainty compared to the two other groups. In contrast, the extended eco-ranking did not reduce consumers' decision uncertainty level. Further, the basic (extended) eco-ranking increased the likelihood of choosing a sustainable product by 26 (17) percentage points compared to the control group. Thus, providing access to a simple eco-ranking can help avoid information overload and increase sustainable consumption. [ABSTRACT FROM AUTHOR]

Evidence demonstrates that participation in regular physical activity (PA) reduces the risk of morbidity and mortality. However, current PA guidelines are focused on weekly accumulation of 150 min of moderate intensity PA as a threshold. Although recent developments of this guidance have discussed the merits of short bouts of physical activity, guidance that sets large behavioural goals for PA has not been successful in supporting the public to become sufficiently physically active and a 'one-size fits all' approach to PA guidelines may not be optimal. A complementary 'whole day' approach to PA promotion (i.e. incorporating PA throughout the day) that could motivate the population to be more physically active, is a concept we have called 'Snacktivity™'. The Snacktivity™ approach promotes small or 'bite' size bouts (e.g. 2-5 min) of PA accumulated throughout the whole day. Snacktivity™ is consistent with the small change approach which suggest that behaviour change and habit formation are best achieved through gradual building of task self-efficacy, celebrating small successes. Snacktivity™ also offers opportunities to "piggyback" on to existing behaviours/habits, using them as prompts for Snacktivity™. Moreover, small behaviour changes are easier to initiate and maintain than larger ones. A plethora of evidence supports the hypothesis that Snacktivity may be a more acceptable and effective way to help the public reach, or exceed current PA guidelines. This paper outlines the evidence to support the Snacktivity™ approach and the mechanisms by which it may increase population levels of physical activity. Future research directions for Snacktivity™ are also outlined. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative functional magnetic resonance imaging (fMRI) protocol to study real verbal interactions while limiting the impact of speech-related movement artefacts. This protocol is based on a sparse sampling acquisition technique and allowed participants to complete a referential communication task with a real interaction partner. During verbal interactions, speakers adjust their verbal productions depending on their interlocutors' knowledge of the referents being mentioned. These adjustments have been linked to theory of mind (ToM), the ability to infer other's mental states. We thus sought to determine if the brain regions supporting ToM would also be activated during a referential communication task in which participants have to present movie characters that vary in their likelihood of being known by their interlocutor. This pilot study establishes that the sparse sampling strategy is a viable option to study the neural correlates of referential communication while minimizing movement artefacts. In addition, the brain regions supporting ToM were recruited during the task, though specifically for the conditions where participants could adjust their verbal productions to the interlocutor's likely knowledge of the referent. This study therefore demonstrates the feasibility and relevance of a sparse-sampling approach to study verbal interactions with fMRI, including referential communication. [ABSTRACT FROM AUTHOR]

Mass media extensively inform societies about events threatening the global food supply (e.g., pandemics or Brexit). Consumers exposed to such communication may perceive food resources as becoming scarcer. In line with an evolutionary account, these perceptions can shift decision-making in domains such as food preferences or prosociality. However, existing literature has solely focused on actual and past food insecurity experiences threatening mostly low-income families, thus neglecting the future-oriented perceptions among the general population. This paper broadens the food insecurity research scope by developing a new construct-anticipated food scarcity (AFS)-which is defined as the perception that food resources are becoming less available (in the future). We have developed and psychometrically validated the 8-item Anticipated Food Scarcity Scale (AFSS) in eight studies (N = 1333). The 8-item AFSS is unidimensional and has good psychometric qualities. The scale is sensitive to food scarcity cues and, therefore, can be used in experimental research. Moreover, its relatively narrow set of items makes it an exceptionally potent tool for use in online surveys, field settings, and lab studies. Taken together, the AFSS presents an alternative approach to food scarcity measurement in affluent societies and, consequently, can foster novel research on food waste, prosocial behaviors, and other similar topic areas. [ABSTRACT FROM AUTHOR]

In many countries suicide rates have been trending upwards for close to twenty years-presenting a public health crisis. Most suicide attempts and deaths are associated with psychiatric illness, usually a depressive disorder. Subanesthetic ketamine is the only FDA-approved antidepressant that works in hours not weeks-thus potentially transforming treatment of suicidal patients. We reviewed all randomized controlled trials of the effect of ketamine on suicidal ideation to determine if ketamine rapidly reduces suicidal ideation [SI] in depressed patients and how long the benefit persists after one dose and if the route of administration or dose affects the outcome. A systematic review was conducted as per PRISMA [preferred reporting items for systematic reviews and meta-analyses] criteria. PubMed search inclusive of "ketamine" and "suicide" yielded 358 results. Papers (N = 354) were then read by at least two authors, identifying 12 meeting eligibility requirements and eleven RCTs examining whether ketamine treatment ameliorated SI. Four of five RCTs examined racemic ketamine (0.5 mg/kg) given intravenously and found an advantage for ketamine over control for rapid reduction in SI in acutely depressed patients. Two studies examined intranasal esketamine in depressed suicidal patients and found no advantage over saline. One study examined outcome six weeks after a single intravenous dose of ketamine and found benefit for SI sustained relative to 24 h post-dose. Further research is warranted into: optimal dosing strategy, including number and frequency; and long-term efficacy and safety. Ultimately, it remains to be shown that ketamine's benefit for SI translates into prevention of suicidal behavior. [ABSTRACT FROM AUTHOR]

• Virtual agents are permeating and interacting on publicly visible human networks. • We compare posting behavior of and user reactions to virtual and human influencers. • The human-like virtual influencer seems to be penalized for her almost human appearance. • Uncanny Valley is seen for positive reactions to the human-like virtual influencer. • A reverse effect is observed for doubt and negative reactions. As virtual agents become prevalent in many domains, virtual influencers have gone live on social media platforms, integrating human networks and interacting with users. Building on research on human-computer interactions, the Uncanny Valley hypothesis, and Computers Are Social Actors paradigm, this paper aims to investigate (1) virtual agents' similarity to humans in terms of behaviour in human networks and (2) reactions to human versus virtual agents in human networks where this interaction is publicly visible. We analyse the posting behaviour of and reactions to one human, one human-like virtual, and one anime-like virtual influencer active on a popular social media platform via text and emoji postings over an 11-month period. We find that, despite the general positive atmosphere of the platform, the human-like virtual influencer receives significantly lower positive reactions, providing evidence for the Uncanny Valley. Additional measures of negative reactions show a similar pattern. We discuss these results within the context of authenticity and social identity on social media, providing recommendations for the implementation of virtual influencers in human social networks. [ABSTRACT FROM AUTHOR]

• Proposing the general multi-predictor (GMP) framework. • Explaining two typical methods are special cases of the GMP framework. • Using the eight neighboring pixels of to-be-embedded pixel of IPVO to propose new predictors. • Using different number of predictors to predict pixels of different complexities. Sorting-based reversible data hiding (RDH) methods like pixel-value-ordering (PVO) can predict pixel values accurately and achieve an extremely low distortion on the embedded image. However, the excellent performance of these methods was not well explained in previous works, and there are unexploited common points among them. In this paper, we propose a general multi-predictor (GMP) framework to summarize PVO-based RDH methods and explain their high prediction accuracy. Moreover, by utilizing the proposed GMP framework, a more efficient sorting-based RDH method is given as an example to show the generality and applicability of our framework. Comparing with other PVO-based methods, the proposed example method can achieve significant improvement in embedding performance. It is hopeful that more efficient sorting-based RDH algorithms can be designed according to our proposed framework by designing better predictors and their combination methods. [ABSTRACT FROM AUTHOR]

Bilingual language representation and cognitive control effects may reflect the dynamic interactions among the complex learning environment, genotype of the individual, and developing cognitive abilities. In this paper we propose a framework considering such interactions. Specifically, we present a nonlinear, developmentally-oriented perspective in which each individual represents a developmental trajectory in multidimensional space. These trajectories focus on the cognitive ecosystem (and how said ecosystem changes over time) and individual expertise (which affects and is affected by the ecosystem). The interactions between ecosystem and expertise lead to the emergence of a system that is built to handle the communicative needs of the individual. [ABSTRACT FROM AUTHOR]

Household food waste is a significant environmental challenge, and almost half of the total global food waste comes from households. Thus, it is crucial to understand why food is wasted at home. This paper proposes a new method, Fridge Studies, that provides knowledge on food waste drivers adding to the research currently documenting the amounts and types of food wasted. Fridge studies is based on social practice theory, suggesting that waste is produced through food handling practices. By rummaging through the fridge together with the study participants, this method provides thick descriptions of practices that generate food waste in an efficient manner. Researchers and participants talk while rummaging, selecting food items and telling their story, as well as photographing the fridge and its content. The method was developed as part of three projects on sustainable food consumption in Norway and has been employed in 57 households. [ABSTRACT FROM AUTHOR]

• Development of a new gaze-based interaction method: EyeTAP (Eye tracking point-and-select by Targeted Acoustic Pulse). • EyeTAP is an effective and robust alternative to gaze-based interaction techniques. • EyeTAP may lead to less fatigue compared to dwell-time and more convenient than other speech activated gaze-based techniques. • Sound inputs and contact-free interaction of EyeTAP make it a feasible method for users with severe disabilities. One of the main challenges of gaze-based interactions is the ability to distinguish normal eye function from a deliberate interaction with the computer system, commonly referred to as 'Midas touch'. In this paper we propose EyeTAP (Eye tracking point-and-select by Targeted Acoustic Pulse) a contact-free multimodal interaction method for point-and-select tasks. We evaluated the prototype in four user studies with 33 participants and found that EyeTAP is applicable in the presence of ambient noise, results in a faster movement time, and faster task completion time, and has a lower cognitive workload than voice recognition. In addition, although EyeTAP did not generally outperform the dwell-time method, it did have a lower error rate than the dwell-time in one of our experiments. Our study shows that EyeTAP would be useful for users for whom physical movements are restricted or not possible due to a disability or in scenarios where contact-free interactions are necessary. Furthermore, EyeTAP has no specific requirements in terms of user interface design and therefore it can be easily integrated into existing systems. [ABSTRACT FROM AUTHOR]