Université du Québec à Montréal

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Using 6 longitudinal data sets, the authors estimate links between three key elements of school readiness--school-entry academic, attention, and socioemotional skills--and later school reading and math achievement. In an effort to isolate the effects of these school-entry skills, the authors ensured that most of their regression models control for cognitive, attention, and socioemotional skills measured prior to school entry, as well as a host of family background measures. Across all 6 studies, the strongest predictors of later achievement are school-entry math, reading, and attention skills. A meta-analysis of the results shows that early math skills have the greatest predictive power, followed by reading and then attention skills. By contrast, measures of socioemotional behaviors, including internalizing and externalizing problems and social skills, were generally insignificant predictors of later academic performance, even among children with relatively high levels of problem behavior. Patterns of association were similar for boys and girls and for children from high and low socioeconomic backgrounds.

In this article I describe and compare a number of alternative generic strategies for the analysis of process data, looking at the consequences of these strategies for emerging theories. I evaluate the strengths and weaknesses of the strategies in terms of their capacity to generate theory that is accurate, parsimonious, general, and useful and suggest that method and theory are inextricably intertwined, that multiple strategies are often advisable, and that no analysis strategy will produce theory without an uncodifiable creative leap, however small. Finally, I argue that there is room in the organizational research literature for more openness within the academic community toward a variety of forms of coupling between theory and data.

Temperament describes the idea that individual behavioural differences are repeatable over time and across situations. This common phenomenon covers numerous traits, such as aggressiveness, avoidance of novelty, willingness to take risks, exploration, and sociality. The study of temperament is central to animal psychology, behavioural genetics, pharmacology, and animal husbandry, but relatively few studies have examined the ecology and evolution of temperament traits. This situation is surprising, given that temperament is likely to exert an important influence on many aspects of animal ecology and evolution, and that individual variation in temperament appears to be pervasive amongst animal species. Possible explanations for this neglect of temperament include a perceived irrelevance, an insufficient understanding of the link between temperament traits and fitness, and a lack of coherence in terminology with similar traits often given different names, or different traits given the same name. We propose that temperament can and should be studied within an evolutionary ecology framework and provide a terminology that could be used as a working tool for ecological studies of temperament. Our terminology includes five major temperament trait categories: shyness-boldness, exploration-avoidance, activity, sociability and aggressiveness. This terminology does not make inferences regarding underlying dispositions or psychological processes, which may have restrained ecologists and evolutionary biologists from working on these traits. We present extensive literature reviews that demonstrate that temperament traits are heritable, and linked to fitness and to several other traits of importance to ecology and evolution. Furthermore, we describe ecologically relevant measurement methods and point to several ecological and evolutionary topics that would benefit from considering temperament, such as phenotypic plasticity, conservation biology, population sampling, and invasion biology.

A new measure of motivation toward education has been developed in French, namely the Echelle de Motivation en Education (EME). The EME is based on the tenets of self-determination theory and is composed of 28 items subdivided into seven sub-scales assessing three types of intrinsic motivation (intrinsic motivation to know, to accomplish things, and to experience stimulation), three types of extrinsic motivation (external, introjected, and identified regulation), and a motivation. The purpose of this investigation was to cross-culturally validate in English the EME. The EME was translated in English through appropriate methodological procedures and completed by university students. Results revealed that the English version of the scale renamed the Academic Motivation Scale (AMS), has satisfactory levels of internal consistency (mean alpha value = .81) and temporal stability over a one-month period (mean test-retest correlation = .79). In addition, results of a confirmatory factor analysis (LISREL) confirmed the seven-factor structure of the AMS. Finally, gender differences obtained with the EME were basically replicated with the AMS. In sum, the present findings provide adequate support for the factorial validity and reliability of the AMS and support its use in educational research on motivation.

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric\nlifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations).\nFor the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 TgCH4 yr-1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 TgCH4 yr-1 or 60% is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 TgCH4 yr-1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 TgCH4 yr-1 larger than our estimate for the previous decade (2000–2009), and 24 TgCH4 yr-1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30% larger global emissions (737 TgCH4 yr-1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼65% of the global budget, <30◦N) compared to mid-latitudes (∼30 %, 30–60◦ N) and high northern latitudes (∼4 %, 60–90◦N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters.\nSome of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 TgCH4 yr-1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 TgCH4 yr-1 by 8 TgCH4 yr-1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5% compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.\nThe data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al.,\n2020) and from the Global Carbon Project

Uncertainty quantification (UQ) methods play a pivotal role in reducing the impact of uncertainties during both optimization and decision making processes. They have been applied to solve a variety of real-world problems in science and engineering. Bayesian approximation and ensemble learning techniques are two widely-used types of uncertainty quantification (UQ) methods. In this regard, researchers have proposed different UQ methods and examined their performance in a variety of applications such as computer vision (e.g., self-driving cars and object detection), image processing (e.g., image restoration), medical image analysis (e.g., medical image classification and segmentation), natural language processing (e.g., text classification, social media texts and recidivism risk-scoring), bioinformatics, etc. This study reviews recent advances in UQ methods used in deep learning, investigates the application of these methods in reinforcement learning, and highlights fundamental research challenges and directions associated with UQ.

The charge storage mechanism in MnO 2 electrode, used in aqueous electrolyte, was investigated by cyclic voltammetry and X-ray photoelectron spectroscopy. Thin MnO 2 films deposited on a platinum substrate and thick MnO 2 composite electrodes were used. First, the cyclic voltammetry data established that only a thin layer of MnO 2 is involved in the redox process and electrochemically active. Second, the X-ray photoelectron spectroscopy data revealed that the manganese oxidation state was varying from III to IV for the reduced and oxidized forms of thin film electrodes, respectively, during the charge/discharge process. The X-ray photoelectron spectroscopy data also show that Na + cations from the electrolyte were involved in the charge storage process of MnO 2 thin film electrodes. However, the Na/Mn ratio for the reduced electrode was much lower than what was anticipated for charge compensation dominated by Na +, thus suggesting the involvement of protons in the pseudofaradaic mechanism. An important finding of this work is that, unlike thin film electrodes, no change of the manganese oxidation state was detected for a thicker composite electrode because only a very thin layer is involved in the charge storage process.

Passion is defined as a strong inclination toward an activity that people like, that they find important, and in which they invest time and energy. Two types of passion are proposed: obsessive and harmonious. Obsessive passion (OP) refers to a controlled internalization of an activity in one's identity that creates an internal pressure to engage in the activity that the person likes. Harmonious passion (HP) refers to an autonomous internalization that leads individuals to choose to engage in the activity that they like. HP promotes healthy adaptation whereas OP thwarts it by causing negative affect and rigid persistence. Results from four studies involving more than 900 participants from different populations supported the proposed conceptualization.

There are an increasing number of studies regarding active electrode materials that undergo faradaic reactions but are used for electrochemical capacitor applications. Unfortunately, some of these materials are described as "pseudocapacitive" materials despite the fact that their electrochemical signature (e.g., cyclic voltammogram and charge/discharge curve) is analogous to that of a "battery" material, as commonly observed for Ni(OH) 2 and cobalt oxides in KOH electrolyte. Conversely, true pseudocapacitive electrode materials such as MnO 2 display electrochemical behavior typical of that observed for a capacitive carbon electrode. The difference between these two classes of materials will be explained, and we demonstrate why it is inappropriate to describe nickel oxide or hydroxide and cobalt oxide/hydroxide as pseudocapacitive electrode materials.

Abstract Partial least squares‐based structural equation modelling (PLS‐SEM) is extensively used in the field of information systems, as well as in many other fields where multivariate statistical methods are used. One of the most fundamental issues in PLS‐SEM is that of minimum sample size estimation. The ‘10‐times rule’ has been a favourite because of its simplicity of application, even though it tends to yield imprecise estimates. We propose two related methods, based on mathematical equations, as alternatives for minimum sample size estimation in PLS‐SEM: the inverse square root method, and the gamma‐exponential method. Based on three Monte Carlo experiments, we demonstrate that both methods are fairly accurate. The inverse square root method is particularly attractive in terms of its simplicity of application. © 2016 John Wiley & Sons Ltd

Linguistic landscape refers to the visibility and salience of languages on public and commercial signs in agiven territory or region. It is proposed that the linguistic landscape may serve important informational and symbolic functions as a marker of the relative power and status of the linguistic communities inhabiting the territory. Using the theoretical framework of ethnolinguistic vitality, it was hypothesized that the experience of the linguistic landscape by members of a language group may contribute to social psychological aspects of bilingual development. Factor analysis results show that the linguistic landscape emerges as a distinct factor separate from other measures of linguistic contacts. This factor was an important correlate of subjective ethnolinguistic vitality representing perceptions of the vitality of the in-group language in various domains. The study also found relations between the Linguistic Landscape factor and degree of in-group language use, especially in institutional settings, suggesting a 'carryover effect" of the linguistic landscape on language behavior.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

PURPOSE: This study illuminates the concept of "aging in place" in terms of functional, symbolic, and emotional attachments and meanings of homes, neighbourhoods, and communities. It investigates how older people understand the meaning of "aging in place," a term widely used in aging policy and research but underexplored with older people themselves. DESIGN AND METHODS: Older people (n = 121), ranging in age from 56 to 92 years, participated in focus groups and interviews in 2 case study communities of similar size in Aotearoa New Zealand, both with high ratings on deprivation indices. The question, "What is the ideal place to grow older?" was explored, including reflections on aging in place. Thematic and narrative analyses on the meaning of aging in place are presented in this paper. RESULTS: Older people want choices about where and how they age in place. "Aging in place" was seen as an advantage in terms of a sense of attachment or connection and feelings of security and familiarity in relation to both homes and communities. Aging in place related to a sense of identity both through independence and autonomy and through caring relationships and roles in the places people live. IMPLICATIONS: Aging in place operates in multiple interacting ways, which need to be taken into account in both policy and research. The meanings of aging in place for older people have pragmatic implications beyond internal "feel good" aspects and operate interactively far beyond the "home" or housing.

One of the major impediments to the integration of lentic ecosystems into global environmental analyses has been fragmentary data on the extent and size distribution of lakes, ponds, and impoundments. We use new data sources, enhanced spatial resolution, and new analytical approaches to provide new estimates of the global abundance of surface-water bodies. A global model based on the Pareto distribution shows that the global extent of natural lakes is twice as large as previously known (304 million lakes; 4.2 million km2 in area) and is dominated in area by millions of water bodies smaller than 1 km2. Similar analyses of impoundments based on inventories of large, engineered dams show that impounded waters cover approximately 0.26 million km2. However, construction of low-tech farm impoundments is estimated to be between 0.1% and 6% of farm area worldwide, dependent upon precipitation, and represents ≫77,000 km2 globally, at present. Overall, about 4.6 million km2 of the earth's continental “land” surface (≫3%) is covered by water. These analyses underscore the importance of explicitly considering lakes, ponds, and impoundments, especially small ones, in global analyses of rates and processes.

Since their discovery in the late 1980s, neonicotinoid pesticides have become the most widely used class of insecticides worldwide, with large-scale applications ranging from plant protection (crops, vegetables, fruits), veterinary products, and biocides to invertebrate pest control in fish farming. In this review, we address the phenyl-pyrazole fipronil together with neonicotinoids because of similarities in their toxicity, physicochemical profiles, and presence in the environment. Neonicotinoids and fipronil currently account for approximately one third of the world insecticide market; the annual world production of the archetype neonicotinoid, imidacloprid, was estimated to be ca. 20,000 tonnes active substance in 2010. There were several reasons for the initial success of neonicotinoids and fipronil: (1) there was no known pesticide resistance in target pests, mainly because of their recent development, (2) their physicochemical properties included many advantages over previous generations of insecticides (i.e., organophosphates, carbamates, pyrethroids, etc.), and (3) they shared an assumed reduced operator and consumer risk. Due to their systemic nature, they are taken up by the roots or leaves and translocated to all parts of the plant, which, in turn, makes them effectively toxic to herbivorous insects. The toxicity persists for a variable period of time-depending on the plant, its growth stage, and the amount of pesticide applied. A wide variety of applications are available, including the most common prophylactic non-Good Agricultural Practices (GAP) application by seed coating. As a result of their extensive use and physicochemical properties, these substances can be found in all environmental compartments including soil, water, and air. Neonicotinoids and fipronil operate by disrupting neural transmission in the central nervous system of invertebrates. Neonicotinoids mimic the action of neurotransmitters, while fipronil inhibits neuronal receptors. In doing so, they continuously stimulate neurons leading ultimately to death of target invertebrates. Like virtually all insecticides, they can also have lethal and sublethal impacts on non-target organisms, including insect predators and vertebrates. Furthermore, a range of synergistic effects with other stressors have been documented. Here, we review extensively their metabolic pathways, showing how they form both compound-specific and common metabolites which can themselves be toxic. These may result in prolonged toxicity. Considering their wide commercial expansion, mode of action, the systemic properties in plants, persistence and environmental fate, coupled with limited information about the toxicity profiles of these compounds and their metabolites, neonicotinoids and fipronil may entail significant risks to the environment. A global evaluation of the potential collateral effects of their use is therefore timely. The present paper and subsequent chapters in this review of the global literature explore these risks and show a growing body of evidence that persistent, low concentrations of these insecticides pose serious risks of undesirable environmental impacts.

Three-phase AC-DC converters have been developed to a matured level with improved power quality in terms of power-factor correction, reduced total harmonic distortion at input AC mains, and regulated DC output in buck, boost, buck-boost, multilevel, and multipulse modes with unidirectional and bidirectional power flow. This paper presents an exhaustive review of three-phase improved power quality AC-DC converters (IPQCs) configurations, control strategies, selection of components, comparative factors, recent trends, their suitability, and selection for specific applications. It is aimed at presenting a state of the art on the IPQC technology to researchers, designers, and application engineers dealing with three-phase AC-DC converters. A classified list of around 450 research articles on IPQCs is also appended for a quick reference.

A new measure of motivation toward sport has been developed in French, namely the Echelle de Motivation vis-à-vis les Sports. Two studies were conducted to translate and validate this new measure in English. The Sport Motivation Scale (SMS) consists of seven subscales that measure three types of Intrinsic Motivation (IM; IM to Know, IM to Accomplish Things, and IM to Experience Stimulation), three forms of regulation for Extrinsic Motivation (Identified, Introjected, and External), and Amotivation. The first study confirmed the factor structure of the scale and revealed a satisfactory level of internal consistency. Correlations among the subscales revealed a simplex pattern confirming the self-determination continuum and the construct validity of the scale. Gender differences were similar to those obtained with the French-Canadian version. The more self-determined forms of motivation were associated with more positive responses on related consequences. In a second study, the SMS was administered on two occasions and revealed adequate test-retest reliability.

The first part of this paper proposes a continuum of ideological premises that seeks to account for the broad range of immigrant integration policies adopted by Western democratic states. In the second part, a review of Social Psychological models of immigrant acculturation strategies demonstrates the need to explain more clearly the interactive nature of immigrant and host community relations. The Interactive Acculturation Model (IAM) presented next proposes that relational outcomes are the product of the acculturation orientations of both the host majority and immigrant groups as influenced by state integration policies. The model makes predictions regarding the acculturation combinations most likely to produce consensual, problematic, and conflictual relational outcomes between immigrants and members of the host community. Social psychological research is needed to test the validity of the IAM model empirically.

CONTEXT: Electroencephalography (EEG) is a complex signal and can require several years of training, as well as advanced signal processing and feature extraction methodologies to be correctly interpreted. Recently, deep learning (DL) has shown great promise in helping make sense of EEG signals due to its capacity to learn good feature representations from raw data. Whether DL truly presents advantages as compared to more traditional EEG processing approaches, however, remains an open question. OBJECTIVE: In this work, we review 154 papers that apply DL to EEG, published between January 2010 and July 2018, and spanning different application domains such as epilepsy, sleep, brain-computer interfacing, and cognitive and affective monitoring. We extract trends and highlight interesting approaches from this large body of literature in order to inform future research and formulate recommendations. METHODS: Major databases spanning the fields of science and engineering were queried to identify relevant studies published in scientific journals, conferences, and electronic preprint repositories. Various data items were extracted for each study pertaining to (1) the data, (2) the preprocessing methodology, (3) the DL design choices, (4) the results, and (5) the reproducibility of the experiments. These items were then analyzed one by one to uncover trends. RESULTS: Our analysis reveals that the amount of EEG data used across studies varies from less than ten minutes to thousands of hours, while the number of samples seen during training by a network varies from a few dozens to several millions, depending on how epochs are extracted. Interestingly, we saw that more than half the studies used publicly available data and that there has also been a clear shift from intra-subject to inter-subject approaches over the last few years. About [Formula: see text] of the studies used convolutional neural networks (CNNs), while [Formula: see text] used recurrent neural networks (RNNs), most often with a total of 3-10 layers. Moreover, almost one-half of the studies trained their models on raw or preprocessed EEG time series. Finally, the median gain in accuracy of DL approaches over traditional baselines was [Formula: see text] across all relevant studies. More importantly, however, we noticed studies often suffer from poor reproducibility: a majority of papers would be hard or impossible to reproduce given the unavailability of their data and code. SIGNIFICANCE: To help the community progress and share work more effectively, we provide a list of recommendations for future studies and emphasize the need for more reproducible research. We also make our summary table of DL and EEG papers available and invite authors of published work to contribute to it directly. A planned follow-up to this work will be an online public benchmarking portal listing reproducible results.