Background: Many researches on maltreated and foster children highlighted internalized and externalized symptoms in this population. However, few studies have looked at how a child interacts with caregivers in the context of foster care. Purpose: The purpose of this study is to explore the Emotion Regulation Strategies (ERS) of children in foster care and to highlight those most used in family and placement contexts. The parents’ and foster carers’ ERS are also analyzed in order to understand the co-regulatory processes at work. Method: An in-depth analysis of observation sequences was performed. Three data collection times were included in the observation protocol, spaced across a period of 6 months (t1, t2 and t3). Each observation, recorded using a video camera, comprised 45 minutes of free time and 15 minutes of structured tasks. Transcription and coding of ERS was performed for each sequence using a microanalytic method from the observations. Both children's and adults' ERS were coded. Results: Children tended to be readily distracted when interacting with adults. This behavior was more frequently observed with parents than with foster carers. While they tended to display relatively normative processes with a foster carer, they turned to pathological avoidance mechanisms such as physical venting or self-stimulation during their interactions with parents which highlighted the child’s disorganized behaviors in family context. Observations of interactions during structured tasks showed a significant reduction in distraction processes in adult-child relationships. Conclusion: This study highlights the prevalence of distraction behavior in foster children during their interactions with caregivers. It provides insight into how structured interactions create a containing framework that mitigates children's avoidance behaviors and so enhances adult-child collaboration.
Background: Nations marked by a Marxist-Leninist ideology have suffered greatly due to a culture of abuse emphasized by the absolute absence of psychology, thus contributing to a diminished ability in recognizing the consequences of traumatic experiences. Objective: To improve the assessment of the presence and severity of posttraumatic stress disorder (PTSD) in such a cultural context, our paper aimed at developing an alternative self-report measure for PTSD - the Post Traumatic Symptom Scale (PTSs), developed by clinicians with wide relevant expertise, based on the natural language people use to describe its subjective experience. This research used multiple samples consistent with the corresponding objectives. Mokken Scale Analysis and the Classical Test Theory were both employed. The proposed scale was tested against five competing PTSD models, whilst also investigating the symptoms' clusters in two different samples by using, to our knowledge, a network analysis approach for the first time. Method: The results indicated excellent psychometric properties regarding internal consistency and temporal reliability, as well as convergent and discriminant validity. The results of MSA showed that the scale fully conforms to the assumptions of the monotone homogeneity model, interpreted as positive evidence for its use in clinical purposes. The factor analyses pointed that the newer models outperformed the standard DSM-5 model, with bifactor models displaying better fit indexes than second-order models. Finally, a distinct pattern of symptom activation in the high-risk group (i.e. first-responders) was found, bringing support for symptoms overlapping between PTSD and affective disorders, thus reinforcing the idea of bridge symptoms which has significant clinical implications. Results: This study presents an alternative sound instrument for measuring PTSD symptomatology focused on how people naturally describe their subjective experiences. Theoretical and practical implications are discussed alongside limitations. Highlights: The construction of PTSs encompasses cultural trauma and one's subjective experience.PTSs was tested against the five major competing models of PTSD.Network analyses suggest different patterns in a student sample vs. a first-responders one, with the accent on the negative alterations in cognitions and mood (NACM) model.
The rapid increase in the number of Earth Observation (EO) systems generates a massive amount of heterogeneous data. It has raised big issues in collecting, preprocessing, storing, and the visualization these data. However, traditional techniques are facing serious challenges when dealing with big EO data dimensions (i.e., Volume, Veracity, Variety, and Velocity), especially in natural hazards management. Therefore, big data techniques and tools attract more attention. In this paper we propose a multidimensional model framework for Big EO data warehousing. This framework includes 3 parts: (1) Data collection and preprocessing, being responsible for collecting data and improving their quality; (2) Data loading and storage, performing the ingestion task which consists of transferring the data from external resources to the Big data platform for storage; and (3) Visualization and interpretation, aiming to provide spatio-temporal analysis. This framework could be useful for decision-makers in monitoring the effects of drought disasters and, consequently, planning the mitigation and remediation measures. Experiments are carried out on drought monitoring in China along the period 2000-2020. The input data include remote sensing data, biophysical data, and climatological data. The results reveal that the proposed framework has a higher retrieval speed and a greater elasticity with different kinds (i.e. spatial, temporal, or spatiotemporal) of requests compared to traditional frameworks, indicating its superiority.
In today's high manufacturers' competition, companies attempt to involve new advanced technologies to retain their market share. With smart technology, process and production methods are improved to suit the new manufacturers' needs. Now in the era of industry 4.0, the production techniques have to be developed to fulfil the customers' demands. Indeed, industry 4.0 promotes the development of traditional factories to digitalization and networking. The aim of this paper is to characterize and analyze the transformation 4.0 process adopted by a factory producing spherical bushels. This study is conducting by FlexSim software to establish a production simulation platform; which manages in real time the production and supply; through the Material Requirement Planning (MRP), the logistics warehouse and the Cyber Physical Production System (CPPS). Moreover, we optimized the statistical findings of simulation by load-capacity adjustment method. It allows increasing the occupancy rates of equipment. The results show the developed platform can significantly rise the production efficiency and practical for smart industry and can be extended for other cases. The developed simulation platform present a basis for a future digital twin of the company.
Managerial sciences are generally considered to be the art of efficiently running business. Their influence, though, extends far beyond the corporate sphere and they play an important part in public administration and in particular in its dialog with society at large. Here, from the viewpoint of historical institutionalism, we document one of the earliest successful examples of the wider application of management science: the 1914 antitrust rules (the Clayton Antitrust and Federal Trade Commission Acts) from the perspectives of economic scholars as technical experts, the early years of the Wilson administration, and the spheres of business and society. The societal debate about business and efficiency and the successive implementation of scientific managerial ideas in the administrative sphere, saw management science permeate the whole of American society and become an almost irrefutable aspect of everyday life and representations, thereby enabling it to spread well beyond the boundaries of the firm. Evidence for Practice From a Science, Technology and Society (STS) perspective, managerial thinking extends far beyond technical debates or shared practices. Efficiency plays a dual role as a value and as a criterion of the optimal use of resources, which should be incorporated into public policy design with respect to business regulation. Negotiation between public administration and social actors is multidimensional and requires identifiable and accountable leaders. Clayton Antitrust legislation emergence can bring some return on experience to current debates about Digital Market Act at European Union level.
The idea that interpreting a lexeme typically involves a context-dependent process of meaning construction has in recent years become common ground in linguistic theory. This view is very explicit in relevance theory (Sperber and Wilson 1995), which posits that speakers systematically infer ad hoc concepts (Carston 2002). Such an approach raises theoretical issues, though. First, it directly poses a challenge for the exact nature of (and difference between) concepts and ad hoc concepts (Carston 2002, 249). In addition, as Wilson (2011, 2016) and Carston (2013, 2016) point out, this view also uncovers the following paradox: if speakers are assumed to follow a path of least effort (relevance heuristics), why should they so systematically infer ad hoc concepts rather than test the encoded concept first? The aim of this paper is to reflect on this theoretical puzzle. It will first be argued that the hypotheses formulated both by Wilson and by Carston seem rather post hoc and fail to fully resolve the apparent paradox. Attention will then be given to the assumed nature of (ad hoc) concepts to show that the problem can be resolved when an alternative (non-atomic) view of concepts in terms of meaning potential is adopted.
This work investigates the structure of rank-metric codes in connection with concepts from finite geometry, most notably the q-analogues of projective systems and blocking sets. We also illustrate how to associate a classical Hamming-metric code to a rank-metric one, in such a way that various rank-metric properties naturally translate into the homonymous Hamming-metric notions under this correspondence. The most interesting applications of our results lie in the theory of minimal rank-metric codes, which we introduce and study from several angles. Our main contributions are bounds for the parameters of a minimal rank-metric codes, a general existence result based on a combinatorial argument, and an explicit code construction for some parameter sets that uses the notion of a scattered linear set. Throughout the paper we also show and comment on curious analogies/divergences between the theories of error-correcting codes in the rank and in the Hamming metric.
The challenge of air pollution and climate change has resulted in the emergence internationally of emission trading systems (ETSs) related mainly to SO2 emissions and CO2 emissions. Although the effectiveness of ETSs has been discussed extensively, it remains unclear whether such policies aimed at reducing different types of emissions are able to achieve overall emissions reductions. Based on China's pilots of SO2 ETS and CO2 ETS, we employ a DID model and investigate the synergistic effects of SO2 ETS and CO2 ETS. The results show first, that the SO2 ETS and CO2 ETS reduced SO2 and CO2 emissions, indicating effective implementation of these policies, second, that the synergistic emissions reduction effect suggests that the SO2 ETS has a limited effect on reducing CO2 emissions due to the maturity of SO₂ capture technologies but that the CO2 ETS significantly reduced SO2 emissions and achieved the co-benefits of SO2 emission reduction, third, further analysis showed that the co-benefits of CO2 ETS derive from reduced fossil energy consumption and improved energy efficiency whereas the impact of the SO2 ETS is limited. This work adds to empirical evidences on the synergistic effects of ETS, which is conductive to optimize the policy design to achieve synergistic emissions reduction effect.
Problématique et enjeux À l'heure actuelle, les patients sont invités à participer à la prise de décision et leurs représentants sont souvent appelés à siéger dans les instances administratives chargées de définir la politique de santé. Pour mieux faire entendre leurs voix, il convient de faire partager aux décideurs leurs expériences de vie sous une forme mesurable qui reflète leurs priorités. Méthode Notre étude s'inscrit dans le cadre général des études mixtes quali-quanti à dominance quantitative. La technique d'élicitation des préférences choisie est celle du best and worst scaling (Louviere and Woodworth, 1992). Les individus ont été soumis à différentes situations hypothétiques et devaient choisir quel critère de jugement, ils estimaient être le plus important (« best ») et le moins important (« worst »). Des entretiens semi-structurés ont été menés, avec l'aide de sociologues, sur un échantillon raisonné de vingt-quatre femmes âgées de 53 à 88 ans ayant subi une fracture ostéoporotique récente ; 21 attributs relatifs aux obstacles et 21 relatifs aux leviers ont été identifiés. Un questionnaire a été construit sur la base d'un plan d'expérience en Blocs Incomplets Equilibrés (BIE). Il a été administré à un échantillon représentatif de 353 patients du panel Metaskope constitué selon la méthode des quotas. Les écarts types, les coefficients de variation des réponses et les scores moyens d'importance ont été calculés par items ainsi que les intervalles de confiance correspondants. La probabilité qu'un critère soit choisi comme le plus ou le moins important a été estimée grâce à un modèle logit multinomial. La méthode des classes latentes a été utilisée pour identifier « à l'aveugle » les regroupements qui pouvaient s'opérer. Trois classes ont été statistiquement isolées. Résultat Au total, 324 patients ont été recrutés dans l'étude, 78,70 % de l'échantillon étaient des femmes et 21,30 % des hommes. L'âge moyen était de 68±1,4 ans ; 19,75 % des patients habitaient dans une agglomération rurale. ;15,43 % en région parisienne et 30,56 % dans une agglomération de plus de 100 000habitants. L'analyse de comptage (AC) a permis d'identifier six obstacles majeurs à la mise en œuvre d'une politique efficace de prévention secondaire de l'ostéoporose. L'analyse statistique (AS) a permis d'identifier 10 obstacles significativement majeurs. Parmi eux, le fait que les patients victimes de fractures n'associent pas celles-ci à la maladie, mais à un choc violent dont ils croient avoir été victimes (#6 classé au 1er rang dans les deux analyses) ; le manque d'information sur la nature et les conséquences de la maladie (#19 classé au 2nd rang) ; et les réticences des patients vis-à-vis des traitements chimiques (#1 classé au rang 2 dans l'AC et 4ème dans l'AS). La méthode statistique des classes latentes a permis de différencier trois sous-populations aux préférences diverses : les rebelles, les ignorants et les victimes du système. Par exemple, l'obstacle 1 a été classé comme le plus important par les répondants appartenant à la classe des « rebelles », mais seulement 17ème par ceux de la classe des « victimes ». L'obstacle 6 « ma fracture est sans lien avec l'ostéoporose » se retrouve, toutefois en bonne place dans les trois populations. Conclusion La mise en œuvre d'une politique secondaire de l'ostéoporose efficace passe par une amélioration de l'éducation des patients, de la formation des professionnels de la santé et de l'organisation du système de soins. Déclaration de liens d'intérêts Les auteurs n'ont pas précisé leurs éventuels liens d'intérêts.
With the development of wind power which is the great substitute for traditional energy, it is worth conducting an in-depth exploration of the hourly wind speed time series which is chaotic due to the complex weather. In this paper, the hybrid intelligent framework is proposed as an integrated prediction tool with high accuracy for signal pre-processing, data prediction, and result optimization of short-term hourly wind speed. Specifically, its excellent performance is guaranteed through adequate information extraction on three stages. The first stage is completed in the signal pre-processing module that the interference information is cleaned up from the hourly wind speed signal via de-noising. The second stage is conducted in the data prediction module that the hidden regular information is fully extracted via the decomposition method. The third stage is performed in the resulting optimization module that the residual information is recovered via error modification. For illustration, the performance of the proposed framework is evaluated through historical hourly wind speed, taken from publicly available Sotavento wind farms. The obtained experimental results indicate that de-noising is beneficial to capturing the real trend, but it may negatively impact short-term prediction accuracy. For the hybrid prediction model based on the empirical mode decomposition-based method, the de-noising mode integrating into the decomposition process is more effective than independent de-noising. The second stage is the key to improving the forecasting performance that, adopting the decomposition method, the average fitting performance is improved by 52.84% than the single models. Before the third stage, chaos test is necessary to determine whether there is a requirement of error modification. In summary, the proposed prediction framework can capture the complex characteristics for different short-term hourly wind speed time series, achieving greater performance than the other comparative models.
This study seeks to develop quantified methods for the description of conceptual metaphors. The study examines the target concept of boredom in contemporary English and Russian. It aims to not only identify which metaphors are used in the two languages, but also how they are used. Using the qualitative-quantitative approach of ‘behavioural profiles’, the study examines comparable informal and personal written language in both cultures, revealing that the most frequent metaphoric conceptualisations of boredom are as death, as an enemy or as an illness. Moreover, the study also shows quantitatively that, despite shared metaphor structures across the languages, there is some difference in how they are used. Through these results, the study highlights that the description of conceptual metaphors needs to pay more attention to their use but also demonstrates the importance of quantitative tools for those usage descriptions.
This study relies on 45 exogenous drivers to improve the accuracy in forecasting EUA volatility. Several popular linear and nonlinear predictive regressions, including individual factor analysis, the combination forecast method, the diffusion index model and the supervised learning method, are used to generate volatility forecasts at the monthly frequency. Our empirical results reveal that the diffusion index model and combination forecast method can hardly drive the EUA volatility in a data-rich world owing to worse forecasting performance of individual factors; however, the supervised learning method can successfully predict the EUA volatility. Additionally, the WilderHill new energy global innovation index, Euro corporate bond return spread, GSCI gold index and Euro Area government bond yield spread can extremely drive EUA volatility in terms of individual factor analysis, frequency of variable selection and factor importance. Our findings provide crucial implications to market participants and emission companies, who should pay more attention to the price movement of European bond market, gold and clean energy.
Nowadays, improving the sustainability of urban freight transport is of paramount importance. The work aims to help freight transport actors in the evaluation of sustainability with a vision that considers the specificities of the city. Thus, we propose a conceptual approach to define sustainability dimensions that are not only the economic, the environmental and the social/societal dimensions, but also the political and spatial ones. They are of particular interest noteworthy so as to evaluate urban freight transport sustainability. We also introduce the concepts of weak, limited and strong sustainability. The proposed approach is used to construct adequate indicators for decision support in urban freight transport.
Previous research has suggested not only that gender discrimination is widespread in law firms, conditioning women’s career paths and full integration into the legal profession, but also that female lawyers are more likely than their male counterparts to perceive unfair treatment. However, little research exists on how female lawyers’ perceptions of gender discrimination may affect their individual work experiences, in particular their attitudes toward their job and their career. This article aims to fill this gap by examining how perceived gender discrimination affects female lawyers’ job satisfaction with their career prospects and work–life balance, as well as their intentions to leave the legal profession. With a focus on the under-researched French case, it draws on the quantitative analysis of the data collected from an online survey administered to 663 female Parisian lawyers. Results show that perceptions of discrimination negatively affect women’s satisfaction with regard to their career prospects and work–life balance, but do not have any influence on their quitting intentions. By adopting a ‘view from below’ on the individual work experiences of female lawyers, the article sheds new light on the dynamics of women’s disadvantage in legal careers.
The transport is one of the most important sectors that affect the economic development. However, its sustainability may be disturbed due to the remarkable increase in the number of vehicles in city centers and its bad consequences, hence the importance of assessing the transport system and the performance of its different components. Therefore, several evaluation methods were introduced to help decision-makers assess sustainability and many indicators were developed to track the progress of sustainable transport system. This work provides a literature review about the existing approaches used to assess transport sustainability through composite indicators. It aims at analyzing the trends in the existing literature, identifying gaps in evaluating sustainability and suggesting future research perspectives. A total of 47 studies conducted in the period 2002–2022 are examined. The obtained results show that few researchers focused on freight transportand most researchers considered only traditional sustainability dimensions. In addition, the performed analysis demonstrates that the use of different methods of normalization, weighting and aggregation influences the result given by composite indicator. Finally, a set of recommendations for precise and correct sustainability assessment is presented in order to develop future research.
This study considers the methodological implications of the usage-based model (Langacker 1987) for a description of prototype-structured categorisation (Lakoff 1987). The usage-based model places repeated analogical judgements at the heart of language processing as well as positing that the repetition of this process, across speech events, is responsible for grammatical competence. Semasiological structure represents one of the most challenging types of conceptual categorisation and is the focus of the case study on the semantics of the lexeme time in contemporary American English. The study examines the meth-odological adequacy of the Behavioural Profile Approach (Dirven et al. 1982; Geeraerts et al. 1994; Gries 2003) in accounting for that complexity in a cogni-tively plausible manner. It is shown how the method quantifiably accounts for the emergent many-to-many structures interpretable as structured polysemy.
Reading is increasingly taking place on digital media, which are vectors of attentional disruption. This manuscript aims to characterize attentional disruption during reading on a computer screen in an ecological environment. To this end, we collected information relating to reader interruptions (number, type, duration, position, mental effort, and valence) and self-caught mind wandering (occurrence, position) throughout the reading session for high and low media multitaskers in their own specific ecological environment, at home. Comprehension of the narrative text was assessed both with surface and inferential questions. In total, 74 participants (M = 22.16, SD = 2.35) took part in the experiment. They reported attentional disruptions on average every 4 mins during reading. Moreover, there were more attentional disruptions during the first half of the text. Most interruptions were short and little mental effort was required to process them. We made a distinction between media-related and media-unrelated related interruptions. Multiple linear regression analyses showed that media-unrelated interruptions were actually related to better performance for both inferential and surface level questions. Furthermore, media-related interruptions were more frequent for high than low media multitaskers. Pleasure experienced when reading the text was also a significant predictor of comprehension. The results are discussed with regard to Long-Term Working Memory and strategies that the readers could have implemented to recover the thread of their reading.
This paper presents an operational annotation system for (dis)fluencies in typical and atypical speech, based on existing standard annotation schemes previously established in the literature. Grounded in a functional approach to (dis)fluency, we address some of the conceptual and technical limitations found in previous annotation models, and offer an integrated and inclusive system which is compatible with different multi-layered annotation software such as Praat or ELAN. Our aim is twofold: to create comparable annotated corpora both in typical and atypical speech, and to provide natural language processing and the health sector with applications for diagnostic and therapy in speech disorders.
We introduce a database (IDEST) of 250 short stories rated for valence, arousal, and comprehensibility in two languages. The texts, with a narrative structure telling a story in the first person and controlled for length, were originally written in six different languages (Finnish, French, German, Portuguese, Spanish, and Turkish), and rated for arousal, valence, and comprehensibility in the original language. The stories were translated into English, and the same ratings for the English translations were collected via an internet survey tool ( N = 573). In addition to the rating data, we also report readability indexes for the original and English texts. The texts have been categorized into different story types based on their emotional arc. The texts score high on comprehensibility and represent a wide range of emotional valence and arousal levels. The comparative analysis of the ratings of the original texts and English translations showed that valence ratings were very similar across languages, whereas correlations between the two pairs of language versions for arousal and comprehensibility were modest. Comprehensibility ratings correlated with only some of the readability indexes. The database is published in osf.io/9tga3, and it is freely available for academic research.
In this paper, we present a review of studies that have collected and annotated errors produced by people with dyslexia from corpora of written texts (six studies involving English, Spanish, German and French). Such resources are useful for studying the spelling difficulties of people with dyslexia. Results can be used for the design and development of assistive technologies. This paper also presents our contribution: a new study of errors from two corpora of typed texts written by French-speaking people with dyslexia. It details the methodology used to annotate the spelling errors extracted from these corpora and the analysis of these errors. The results of our study are compared to the results of the previous studies.
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