Search results for: semantic trajectory

Authors: Marcus Maia

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The present study reports and discusses the use of eye tracking qualitative data in reading workshops in Brazilian middle and high schools and in Generative Syntax and Sentence Processing courses at the undergraduate and graduate levels at the Federal University of Rio de Janeiro, respectively. Both endeavors take the sentential level as the proper object to be metacognitively explored in language education (cf. Chomsky, Gallego & Ott, 2019) to develop innate science forming capacity and knowledge of language. In both projects, non-discrepant qualitative eye tracking data collected and quantitatively analyzed in experimental syntax and psycholinguistic studies carried out in Lapex (Experimental Psycholinguistics Laboratory of the Federal University of Rio de Janeiro) were displayed to students as a point of departure, triggering discussions. Classes would generally start with the display of videos showing eye tracking data, such as gaze plots and heatmaps from several studies in Psycholinguistics and Experimental Syntax that we had already developed in our laboratory. The videos usually triggered discussions with students about linguistic and psycholinguistic issues, such as the reading of sentences for gist, garden-path sentences, syntactic and semantic anomalies, the filled-gap effect, island effects, direct and indirect cause, and recursive constructions, among other topics. Active, problem-solving based methodologies were employed with the objective of stimulating student participation. The communication also discusses the importance of developing full literacy, epistemic vigilance and intellectual self-defense in an infodemic world in the lines of Maia (2022).

Keywords: reading, educational psycholinguistics, eye-tracking, active methodology

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Authors: Manish Kumar Asthana, Alicia Bundis, Zahn Xu, Braj Bhushan

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Despite ample cross-cultural studies with emotional valence, it is unclear if the emotions are universal or particular. Previous studies have shown that the individualist culture favors high-valence emotions compared to low-valence emotions. In contrast, collectivist culture favors low-valence emotions compared to high-valence emotions. In this current study, Chinese, Mexicans, and Indians reported valence and semantic-contingency. In total, 120 healthy participants were selected by ethnicity and matched for age and education. Each participant was presented 45 non-chromatic pictures, which were converted from chromatic pictures selected from International Affective Picture Database (IAPS) belonging to five-categories, i.e. (i) less pleasant, (ii) high pleasant, (iii) less unpleasant (iv) high unpleasant (v) neutral. The valence scores assigned to neutral, less-unpleasant, and high-pleasant pictures differed significantly between Chinese, Indian, and Mexicans participants. Significant effects demonstrated from the two-way ANOVAs, confirmed main significant effects of valence (F(1,117) = 24.83, p =0.000) and valence x country (F(2,117) = 2.74, p = 0.035). Significant effects emerging from the one-way ANOVAs were followed up through Bonferroni’s test post-hoc comparisons (p < 0.01). This analysis showed significant effect of neutral (F(2,119) = 6.50, p =0.002), less-unpleasant (F(2,119) = 13.79, p =0.000), and high-unpleasant (F(2,119) = 5.99, p =0.003). There were no significant differences in valence scores for the less-pleasant and more-pleasant between participants from three countries. The IAPS norms require modification for their appropriate application in individualist and collectivist cultures.

Keywords: cultural difference, affective processing, valence, non-chromatic, international affective picture system (IAPS)

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Authors: Muge Unal, Ahmet Cilek

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Urban identity, having a dynamic characteristic spatial and semantic aspects, is a phenomenon in an ever-changing. Urban identity formation includes not only a process of physical nature but also development and change processes that take place in the political, economic, social and cultural values, whether national and international level. Although the concept of urban transformation is basically regarded as the spatial transformation; in fact, it reveals a holistic perspective and transformation based on dialectical relationship existing between the spatial and social relationship. For this reason, urban renewal needs to address as not only spatial but also the impact of spatial transformation on social, cultural and economic. Implementation tools used in the perception of urban transformation are varied concepts such as urban renewal, urban resettlement, urban rehabilitation, urban redevelopment, and urban revitalization. The phenomenon of urban transformation begins with the Industrial Revolution. Until the 1980s, it was interpreted as reconsidering physical fossil on urban environment factor like occurring in rapid urbanization, changing in the spatial structure of the city, concentrating of the population in urban areas. However, after the 1980s, it has resided in a conceptual structure which requires to be addressed physical, economic, social, technological and integrity of information. In conclusion, urban transformation, when it enter the literature as a practice of planning, has been up to date in terms of the conceptual structure and content and also hasn’t remained behind converting itself. Urban transformation still maintains its simplest expression, while it transforms so fast converts the contents. In this study, the relationship between urban design and components of urban transformation were discussed with strategies used as a place in the historical process of urban transformation besides a general evaluation of the concept of urban renewal.

Keywords: conceptual approach, urban identity, urban regeneration, urban renewal

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Authors: Yan Huang

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Event-related potentials (ERPs) technique helps researchers to make continuous measures on the whole process of language comprehension, with an excellent temporal resolution at the level of milliseconds. The research on sentence processing has developed from the behavioral level to the neuropsychological level, which brings about a variety of sentence processing theories and models. However, the applicability of these models to L2 learners is still under debate. Therefore, the present study aims to investigate the neural mechanisms underlying English subjunctive mood processing by Chinese ESL learners. To this end, English subject clauses with subjunctive moods are used as the stimuli, all of which follow the same syntactic structure, “It is + adjective + that … + (should) do + …” Besides, in order to examine the role that language proficiency plays on L2 processing, this research deals with two groups of Chinese ESL learners (18 males and 22 females, mean age=21.68), namely, high proficiency group (Group H) and low proficiency group (Group L). Finally, the behavioral and neurophysiological data analysis reveals the following findings: 1) Syntax and semantics interact with each other on the SECOND phase (300-500ms) of sentence processing, which is partially in line with the Three-phase Sentence Model; 2) Language proficiency does affect L2 processing. Specifically, for Group H, it is the syntactic processing that plays the dominant role in sentence processing while for Group L, semantic processing also affects the syntactic parsing during the THIRD phase of sentence processing (500-700ms). Besides, Group H, compared to Group L, demonstrates a richer native-like ERPs pattern, which further demonstrates the role of language proficiency in L2 processing. Based on the research findings, this paper also provides some enlightenment for the L2 pedagogy as well as the L2 proficiency assessment.

Keywords: Chinese ESL learners, English subjunctive mood, ERPs, L2 processing

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Authors: Smart E. Amanfo

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Although the exact functional relationship between energy consumption and economic growth and development remains a complex social science, there is a sustained growing of agreement among energy economists and the likes on direct or indirect role of energy use in the development process, and as sustenance for many of societal achieved socio-economic and environmental developments in any economy. According to OECD, the world economy will double by 2050 in which the two members of BRICS (Brazil, Russia, India, China and South Africa) countries: China and India lead. There is a global apprehension that if countries constituting the epicenter of the present and future economic growth follow the same trajectory as during and after Industrial Revolution, involving higher energy throughputs, especially fossil fuels, the already known and models predicted threats of climate change and global warming could be exacerbated, especially in the developing economies. The international community’s challenge is how to address the trilemma of economic growth, social development, poverty eradication and stability of the ecological systems. This paper aims at providing the estimates of economic growth, energy consumption, and carbon dioxide emissions using BRICS members’ panel data from 1980 to 2017. The preliminary results based on fixed effect econometric model show positive significant relationship between energy consumption and economic growth. The paper further identified a strong relationship between economic growth and CO2 emissions which suggests that the global agenda of low-carbon-led growth and development is not a straight forward achievable The study therefore highlights the need for BRICS member states to intensify low-emissions-based production and consumption policies, increase renewables in order to avoid further deterioration of climate change impacts.

Keywords: BRICS, sustainability, sustainable development, energy consumption, economic growth

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Authors: Tianyue Wan

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Building a child-friendly city (CFC) contributes to improving the quality of urbanization. It also forms a local system committed to fulfilling children's rights and development. Yet, the work related to CFC is still at the initial stage in China. Therefore, taking Wuhan, the most populous city in central China, as the pilot city would offer some reference for other cities. Based on the analysis of theories and practice examples, this study puts forward the challenges of building a child-friendly city under the particularity of China's national conditions. To handle these challenges, this study uses four methods to collect status data: literature research, site observation, research inquiry, and semantic differential (SD). And it adopts three data analysis methods: case analysis, geographic information system (GIS) analysis, and analytic hierarchy process (AHP) method. Through data analysis, this study identifies the evaluation system and appraises the current situation of Wuhan. According to the status of Wuhan's child-friendly city, this study proposes three strategies: 1) construct the evaluation system; 2) establish a child-friendly space system integrating 'point-line-surface'; 3) build a digitalized service platform. At the same time, this study suggests building a long-term mechanism for children's participation and multi-subject supervision from laws, medical treatment, education, safety protection, social welfare, and other aspects. Finally, some conclusions of strategies about CFC are tried to be drawn to promote the highest quality of life for all citizens in Wuhan.

Keywords: action plan, child friendly city, construction strategy, urban space

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Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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Authors: Raya Morag

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This paper proposes a new paradigm for cinema/trauma studies - the trauma of the perpetrator. Canonical trauma research from Freud’s Aetiology of Hysteria to the present has been carried out from the perspective of identification with the victim, as have cinema trauma research and contemporary humanities-based trauma studies, climaxing during the 1990s in widespread interest in the victim vis-à-vis the Holocaust, war, and domestic violence. Breaking over 100 years of repression of the abhorrent and rejected concept of the perpetrator in psychoanalytic-based research proposes an uncanny shift in our conception of psychoanalysis' trajectory from women's 'hysteria' to 'post-traumatic stress disorder'. This new paradigm is driven by the global emergence of new waves of films (2007-2015) representing trauma suffered by perpetrators involved in the new style of war entailing deliberate targeting of non-combatants. Analyzing prominent examples from Israeli post-second Intifada documentaries (e.g., Ari Folman’s Waltz with Bashir), and post post-Iraq (and Afghanistan) War American documentaries (e.g., Errol Morris' Standard Operating Procedure), the paper discusses the limitations of victim trauma by the firm boundaries it (rightly) set in order to defend such victims of nineteenth and especially twentieth-century catastrophes; the epistemological processes needed in order to consider perpetrators’ trauma as an inevitable part of psychiatric-psychological and cultural perspectives on trauma, and, thus, the definition of perpetrators' trauma in contrast to victims'. It also analyzes the perpetrator's figure in order to go beyond the limitation of current trauma theory's relation to the Real, thus transgressing the 'unspeakableness' of the trauma itself. The paper seeks an exploration of what perpetrator trauma teaches us not only as a counter-paradigm to victim trauma, but as a reflection on the complex intertwining of the two paradigms in the twenty-first century collective new war unconscious, and on what psychoanalysis might offer us in the first decade of this terrorized-ethnicized century.

Keywords: American war documentaries, Israeli war documentaries, 'new war', perpetrator trauma

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Authors: Zongyao Sha

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Green vegetation plays a vital role in energy flows and matter cycles in terrestrial ecosystems, and vegetation phenology may not only be influenced by but also impose active feedback on climate changes. The phenological events of vegetation, such as the start of the season (SOS), end of the season (EOS), and length of the season (LOS), can respond to climate changes and affect gross primary productivity (GPP). Here we coupled satellite remote sensing imagery with FLUXNET observations to systematically map the shift of SOS, EOS, and LOS in global vegetated areas and explored their response to climate fluctuations and feedback on GPP during the last two decades. Results indicated that SOS advanced significantly, at an average rate of 0.19 days/year at a global scale, particularly in the northern hemisphere above the middle latitude (≥30°N) and that EOS was slightly delayed during the past two decades, resulting in prolonged LOS in 72.5% of the vegetated area. The climate factors, including seasonal temperature and precipitation, are attributed to the shifts in vegetation phenology but with a high spatial and temporal difference. The study revealed interactions between vegetation phenology and climate changes. Both temperature and precipitation affect vegetation phenology. Higher temperature as a direct consequence of global warming advanced vegetation green-up date. On the other hand, 75.9% and 20.2% of the vegetated area showed a positive correlation and significant positive correlation between annual GPP and length of vegetation growing season (LOS), likely indicating an enhancing effect on vegetation productivity and thus increased carbon uptake from the shifted vegetation phenology. Our study highlights a comprehensive view of the vegetation phenology changes of the global terrestrial ecosystems during the last two decades. The interactions between the shifted vegetation phenology and climate changes may provide useful information for better understanding the future trajectory of global climate changes. The feedback on GPP from the shifted vegetation phenology may serve as an adaptation mechanism for terrestrial ecosystems to mitigate global warming through improved carbon uptake from the atmosphere.

Keywords: vegetation phenology, growing season, NPP, correlation analysis

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Authors: Marie Komorna, Katerina Hadkova

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One reason why hearing disabilities as compared to other disabilities are considered to be less serious, is the belief that deaf and hard of hearing persons can read and write without problems and can therefore fairly easily compensate for problems related to their limited ability to hear sound. However in reality this is not the case, especially as regards written Czech, deaf persons are often not able to communicate their message clearly to its recipients. Their inability to communicate fully in written language is one of the most severe problems facing a number of deaf persons, a problem which they face and which makes it difficult for them to function in a sound-based environment. Despite this fact, this issue is one which has been given only a minimum of attention in the Czech Republic. That is why we decided to focus our research on this issue, specifically targeting written communication of deaf pupils in primary and secondary schools. The paper summarizes the background and objectives of this research. The written work of deaf respondents was obtained in response to a narrative based on a series of images which depicted a continuous storyline. Based on an analysis of the obtained written work we tried to describe the specifics of the narrative abilities of the deaf authors of these texts. We also analyzed other aspects and specific traits of text written by deaf authors at a phonetic-phonological, lexical-semantic, morphological and syntactic, respectively pragmatic level. Based on the results of the project it will be possible to increase knowledge of the communication abilities of deaf persons in written Czech. The obtained data may be used during future research and for teaching purposes and/or education concepts for teaching Czech to deaf pupils.

Keywords: communication competence, deaf, narrative, written texts

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Authors: Hui Shi

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This article examines the online popularity of Chinese neologism simida, which is a loanword derived from Korean declarative sentence-final suffix seumnida. Facilitated by corpus data obtained from Weibo, the Chinese counterpart of Twitter, this study analyzes the morphological and syntactical processes behind simida’s coinage, as well as the causes of its prevalence on Chinese social media. The findings show that simida is used by Weibo bloggers in two manners: (1) as an alternative word of 'Korea' and 'Korean'; (2) as a redundant sentence-final particle which adds a Korean-like speech style to a statement. Additionally, Weibo user profile analysis further reveals demographical distribution patterns concerning this neologism and highlights young Weibo users in the third-tier cities as the leading adopters of simida. These results are accounted for under the theoretical framework of social indexicality, especially how variations generate style in the indexical field. This article argues that the creation of such an ethnically-targeted neologism is a linguistic demonstration of Chinese netizen’s two-sided attitudes toward the previously heated Korean-wave. The exotic suffix seumnida is borrowed to Chinese as simida due to its high-frequency in Korean cultural exports. Therefore, it gradually becomes a replacement of Korea-related lexical items due to markedness, regardless of semantic prosody. Its innovative implantation to Chinese syntax, on the other hand, reflects Chinese netizens’ active manipulation of language for their online identity building. This study has implications for research on the linguistic construction of identity and style and lays the groundwork for linguistic creativity in the Chinese new media.

Keywords: Chinese neologism, loanword, humor, new media

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Authors: Kenneth D. Aiello, M. Simeone, Manfred Laubichler

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It is increasingly difficult to analyze emerging scientific fields as contemporary scientific fields are more dynamic, their boundaries are more porous, and the relational possibilities have increased due to Big Data and new information sources. In biomedicine, where funding, medical categories, and medical jurisdiction are determined by distinct boundaries on biomedical research fields and definitions of concepts, ambiguity persists between the microbiome, metabolome, and metagenome research fields. This ambiguity continues despite efforts by institutions and organizations to establish parameters on the core concepts and research discourses. Further, the explosive growth of microbiome, metabolome, and metagenomic research has led to unknown variation and covariation making application of findings across subfields or coming to a consensus difficult. This study explores the evolution and variation of knowledge within the microbiome, metabolome, and metagenome research fields related to ambiguous scholarly language and commensurable theoretical frameworks via a semantic analysis of key concepts and narratives. A computational historical framework of cultural evolution and large-scale publication data highlight the boundaries and overlaps between the competing scientific discourses surrounding the three research areas. The results of this study highlight how discourse and language distribute power within scholarly and scientific networks, specifically the power to set and define norms, central questions, methods, and knowledge.

Keywords: biomedicine, conceptual change, history of science, philosophy of science, science of science, sociolinguistics, sociology of knowledge

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Authors: Nour Eddine Nachouane, Aicha Knidiri

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The Hispano-Moorish art was born in 786 when Abd ar-Rahman built the first mosque in Cordoba. It is a still-living art in the trades of the big Moroccan cities. Everyone agrees that the different artistic forms of Arab-Muslim art find their full development in traditional Moroccan architecture, and this heritage allows artists and artisans to create magnificent masterpieces. Marrakech, by way of example, constitutes a symbolic city, which represents the reflection of a rich history of this art carried by a long artisanal tradition that is still living nowadays. Despite its ratification by UNESCO as intangible cultural heritage, and beyond official speeches, several of those craft trades are endangered, and with them the whole history of millennial savoir-faire. From the empirical study of the old historic center, 'the medina' of Marrakech, we explore in this article the opportunity offered by the tourism industry in order to protect these craft trades. We question artisans on the evolution of the sector and the challenges of the transmission of this heritage. We evoke the case of Spanish cities like Granada in a comparative reflection on the strategies and perceptions of the public administrations of a part, and, on the other hand, on the shared experience of artisans and tourists. In an interdisciplinary approach mixing anthropology, history, sociology, and even geography, we question the capacity of heritage processes to mobilize and involve a set of actors and activate a trajectory for the safeguarding of Andalusian arts and techniques. The basic assumption of this research is that the promotion of traditional craft trades through tourism and based on good scientific knowledge can present an original offer to cope with globalization and guarantee the transmission of that savoir-faire to new generations. Research in the field of Islamic arts does not constitute a retreat into the nationalist identity or a fixation on the past but an opening towards cultural diversity, free from any standardization.

Keywords: heritage, art andalusi, handcraft, tourism

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Samuel Abraham Berhane, Lingbing Bu

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This paper presents the spatiotemporal variability of aerosols, clouds, and precipitation within the major cities in Eritrea and it investigates the relationship between aerosols, clouds, and precipitation concerning the presence of aerosols over the study region. In Eritrea, inadequate water supplies will have both direct and indirect adverse impacts on sustainable development in areas such as health, agriculture, energy, communication, and transport. Besides, there exists a gap in the knowledge on suitable and potential areas for cloud seeding. Further, the inadequate understanding of aerosol-cloud-precipitation (ACP) interactions limits the success of weather modification aimed at improving freshwater sources, storage, and recycling. Spatiotemporal variability of aerosols, clouds, and precipitation involve spatial and time series analysis based on trend and anomaly analysis. To find the relationship between aerosols and clouds, a correlation coefficient is used. The spatiotemporal analysis showed larger variations of aerosols within the last two decades, especially in Assab, indicating that aerosol optical depth (AOD) has increased over the surrounding Red Sea region. Rainfall was significantly low but AOD was significantly high during the 2011 monsoon season. Precipitation was high during 2007 over most parts of Eritrea. The correlation coefficient between AOD and rainfall was negative over Asmara and Nakfa. Cloud effective radius (CER) and cloud optical thickness (COT) exhibited a negative correlation with AOD over Nakfa within the June–July–August (JJA) season. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model that is used to find the path and origin of the air mass of the study region showed that the majority of aerosols made their way to the study region via the westerly and the southwesterly winds.

Keywords: aerosol-cloud-precipitation, aerosol optical depth, cloud effective radius, cloud optical thickness, HYSPLIT

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Authors: Ryoo Hye Jin Agnes

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This study aims to investigate the efficacy of clickers in fostering L2 class interaction. In an L2 classroom, active learner-to-learner interactions and learner-to-teacher interactions play an important role in language acquisition. In light of this, introducing learning tools that promote such interactions would benefit L2 classroom by fostering interaction. This is because the anonymity of clickers allows learners to express their needs without the social risks associated with speaking up in the class. clickers therefore efficiently help learners express their level of understanding during the process of learning itself. This allows for an evaluative feedback loop where both learners and teachers understand the level of progress of the learners, better enabling classrooms to adapt to the learners’ needs. Eventually this tool promotes participation from learners. This, in turn, is believed to be effective in fostering classroom interaction, allowing learning to take place in a more comfortable yet vibrant way. This study is finalized by presenting the result of an experiment conducted to verify the effectiveness of this approach when teaching pragmatic aspect of Korean expressions with similar semantic functions. The learning achievement of learners in the experimental group was found higher than the learners’ in a control group. A survey was distributed to the learners, questioning them regarding the efficacy of clickers, and how it contributed to their learning in areas such as motivation, self-assessment, increasing participation, as well as giving feedback to teachers. Analyzing the data collected from the questionnaire given to the learners, the study presented data suggesting that this approach increased the scope of interactivity in the classroom, thus not only increasing participation but enhancing the type of classroom participation among learners. This participation in turn led to a marked improvement in their communicative abilities.

Keywords: second language acquisition, interaction, clickers, learner response system, output from learners, learner’s cognitive process

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Authors: Chan Kwong Tung

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Since Baddeley and Hitch’s seminal research in 1974 on working memory (WM), this topic has been of great interest to language educators. Although there are some variations in the definitions of WM, recent findings in WM have contributed vastly to our understanding of language learning, especially its effects on second language acquisition (SLA). For example, the phonological component of WM (PWM) and the executive component of WM (EWM) have been found to be positively correlated with language learning. This paper discusses two general, yet highly relevant WM findings that could directly affect the effectiveness of Chinese Language (CL) vocabulary teaching and learning, as well as the quality of its assessment. First, PWM is found to be critical for the long-term learning of phonological forms of new words. Second, EWM is heavily involved in interpreting the semantic characteristics of new words, which consequently affects the quality of learners’ reading comprehension. These two ideas are hardly discussed in the Chinese literature, both conceptual and empirical. While past vocabulary acquisition studies have mainly focused on the cognitive-processing approach, active processing, ‘elaborate processing’ (or lexical elaboration) and other effective learning tasks and strategies, it is high time to balance the spotlight to the WM (particularly PWM and EWM) to ensure an optimum control on the teaching and learning effectiveness of such approaches, as well as the validity of this language assessment. Given the unique phonological, orthographical and morphological properties of the CL, this discussion will shed some light on the vocabulary acquisition of this Sino-Tibetan language family member. Together, these two WM concepts could have crucial implications for the design, development, and planning of vocabularies and ultimately reading comprehension teaching and assessment in language education. Hopefully, this will raise an awareness and trigger a dialogue about the meaning of these findings for future language teaching, learning, and assessment.

Keywords: Chinese Language, working memory, vocabulary assessment, vocabulary teaching

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Authors: Sidra Shaw, Sarenna Shaw, Chae Joon Lee, Irimpan Mathews, Eric Koehn

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One of the biggest public health concerns of our time is increasing antimicrobial resistance. As of 2019, the CDC has documented more than 2.8 million serious antibiotic resistant infections in the United States. Currently, antibiotic resistant infections are directly implicated in over 750,000 deaths per year globally. On our current trajectory, British economist Jim O’Neill predicts that by 2050, an additional 10 million people (about half the population of New York) will die annually due to drug resistant infections. As a result, new biochemical pathways must be targeted to generate next generation antibiotic drugs that will be effective against drug resistant bacteria. One enticing target is the biosynthesis of DNA within bacteria, as few drugs interrupt this essential life process. Thymidylate synthase enzymes are essential for life as they catalyze the synthesis of a DNA building block, 2′-deoxythymidine-5′-monophosphate (dTMP). In humans, the thymidylate synthase enzyme (TSase) has been shown to be distinct from the flavin-dependent thymidylate synthase (FDTS) produced by many pathogenic bacteria. TSase and FDTS have distinct structures and mechanisms of catalysis, which should allow selective inhibition of FDTS over human TSase. Currently, C. diff is one of the most antibiotic resistant bacteria, and no drugs that target thymine biosynthesis exist for C. diff. Here we present the initial biochemical characterization of FDTS from C. diff. Specifically, we examine enzyme kinetics and binding features of this enzyme to determine the nature of interaction with ligands/inhibitors and understand the molecular mechanism of catalysis. This research will provide more insight into the targetability of the C. diff FDTS enzyme for novel antibiotic drugs.

Keywords: flavin-dependent thymidylate synthase, FDTS, clostridioides difficile, C. diff, antibiotic resistance, DNA synthesis, enzyme kinetics, binding features

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Authors: Juliet Udoudom

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Inappropriate complement selection constitutes one of the major features of non-standard complementation in the Nigerian users of English output of sentence construction. This paper investigates complement clause choice in Written Educated Nigerian English (ENE) and offers some results. It aims at determining preferred and dispreferred patterns of complement clause selection in respect of verb heads in English by selected Nigerian users of English. The complementation data analyzed in this investigation were obtained from experimental tasks designed to elicit complement categories of Verb – Noun -, Adjective – and Prepositional – heads in English. Insights from the Government – Binding relations were employed in analyzing data, which comprised responses obtained from one hundred subjects to a picture elicitation exercise, a grammaticality judgement test, and a free composition task. The findings indicate a general tendency for clausal complements (CPs) introduced by the complementizer that to be preferred by the subjects studied. Of the 235 tokens of clausal complements which occurred in our corpus, 128 of them representing 54.46% were CPs headed by that, while whether – and if-clauses recorded 31.07% and 8.94%, respectively. The complement clause-type which recorded the lowest incidence of choice was the CP headed by the Complementiser, for with a 5.53% incident of occurrence. Further findings from the study indicate that semantic features of relevant embedding verb heads were not taken into consideration in the choice of complementisers which introduce the respective complement clauses, hence the that-clause was chosen to complement verbs like prefer. In addition, the dispreferred choice of the for-clause is explicable in terms of the fact that the respondents studied regard ‘for’ as a preposition, and not a complementiser.

Keywords: complement, complement clause complement selection, complementisers, government-binding

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Authors: Wenbo Wang, Yi-Fang Brook Wu

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The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. As a means to address this phenomenon, automated fact-checking has emerged as a safeguard against the spread of misinformation and disinformation. Existing fact-checking approaches aim to determine whether a news claim is true or false, and they have achieved decent veracity prediction accuracy. However, the state-of-the-art methods rely on manually verified external information to assist the checking model in making judgments, which requires significant human resources. This study introduces a framework, SAC, which focuses on 1) augmenting the representation of a claim by incorporating additional context using general-purpose, comprehensive, and authoritative data; 2) developing a search function to automatically select relevant, new, and credible references; 3) focusing on the important parts of the representations of a claim and its reference that are most relevant to the fact-checking task. The experimental results demonstrate that 1) Augmenting the representations of claims and references through the use of a knowledge base, combined with the multi-head attention technique, contributes to improved performance of fact-checking. 2) SAC with auto-selected references outperforms existing fact-checking approaches with manual selected references. Future directions of this study include I) exploring knowledge graphs in Wikidata to dynamically augment the representations of claims and references without introducing too much noise, II) exploring semantic relations in claims and references to further enhance fact-checking.

Keywords: fact checking, claim verification, deep learning, natural language processing

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Authors: Min Chen, Rubi Gupta

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Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

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Authors: Michael Naderhirn, Marco Pavone

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Problem statement, motivation, and aim of work: So far, the development of control algorithms was done by control engineers in a way that the controller would fit a specification by testing. When it comes to the certification of an autonomous car in highly complex scenarios, the challenge is much higher since such a controller must mathematically guarantee to implement the rules of the road while on the other side guarantee aspects like safety and real time executability. What if it becomes reality to solve this demanding problem by combining Formal Verification and System Theory? The aim of this work is to present a workflow to solve the above mentioned problem. Summary of the presented results / main outcomes: We show the usage of an English like language to transform the rules of the road into system specification for an autonomous car. The language based specifications are used to define system functions and interfaces. Based on that a formal model is developed which formally correctly models the specifications. On the other side, a mathematical model describing the systems dynamics is used to calculate the systems reachability set which is further used to determine the system input boundaries. Then a motion planning algorithm is applied inside the system boundaries to find an optimized trajectory in combination with the formal specification model while satisfying the specifications. The result is a control strategy which can be applied in real time independent of the scenario with a mathematical guarantee to satisfy a predefined specification. We demonstrate the applicability of the method in simulation driving scenarios and a potential certification. Originality, significance, and benefit: To the authors’ best knowledge, it is the first time that it is possible to show an automated workflow which combines a specification in an English like language and a mathematical model in a mathematical formal verified way to synthesizes a controller for potential real time applications like autonomous driving.

Keywords: formal system verification, reachability, real time controller, hybrid system

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Authors: Travis Morris

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The purpose of this study is to measure the intersection of environmental security entities in terrorist propaganda. To the best of author’s knowledge, this is the first study of its kind to examine this intersection within terrorist propaganda. Rosoka, natural language processing software and frame analysis are used to advance our understanding of how environmental frames function as emotive triggers. Violent jihadi demagogues use frames to suggest violent and non-violent solutions to their grievances. Emotive triggers are framed in a way to leverage individual and collective attitudes in psychological warfare. A comparative research design is used because of the differences and similarities that exist between two variants of violent jihadi propaganda that target western audiences. Analysis is based on salience and network text analysis, which generates violent jihadi semantic networks. Findings indicate that environmental frames are used as emotive triggers across both data sets, but also as tactical and information data points. A significant finding is that certain core environmental emotive triggers like “water,” “soil,” and “trees” are significantly salient at the aggregate level across both data sets. All environmental entities can be classified into two categories, symbolic and literal. Importantly, this research illustrates how demagogues use environmental emotive triggers in cyber space from a subcultural perspective to mobilize target audiences to their ideology and praxis. Understanding the anatomy of propaganda construction is necessary in order to generate effective counter narratives in information operations. This research advances an additional method to inform practitioners and policy makers of how environmental security and propaganda intersect.

Keywords: propaganda analysis, emotive triggers environmental security, frames

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Authors: Hongbo Zhang, Xinlu Tang, Jiangwei Li, Chi Yan

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Home zone parking pilot (HPP) is a fast-growing segment in low-speed autonomous driving applications. It requires the car automatically cruise around a parking lot and park itself in a range of up to 100 meters inside a recurrent home/office parking lot, which requires precise parking lot mapping and localization solution. Although Lidar is ideal for SLAM, the car OEMs favor a low-cost fish-eye camera based visual SLAM approach. Recent approaches have employed segmentation models to extract semantic features and improve mapping accuracy, but these AI models are memory unfriendly and computationally expensive, making deploying on embedded ADAS systems difficult. To address this issue, we proposed a new method that utilizes object detection models to extract robust and accurate parking lot features. The proposed method could reduce computational costs while maintaining high accuracy. Once combined with vehicles’ wheel-pulse information, the system could construct maps and locate the vehicle in real-time. This article will discuss in detail (1) the fish-eye based Around View Monitoring (AVM) with transparent chassis images as the inputs, (2) an Object Detection (OD) based feature point extraction algorithm to generate point cloud, (3) a low computational parking lot mapping algorithm and (4) the real-time localization algorithm. At last, we will demonstrate the experiment results with an embedded ADAS system installed on a real car in the underground parking lot.

Keywords: ADAS, home zone parking pilot, object detection, visual SLAM

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Authors: Edilei Reis, Jose Carlos Felix

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This paper explores Waldir Dupont’s translations of William Faulkner’s novels to Brazilian Portuguese language in order to comprehend how his translation project regarding Faulkner’s works has addressed modernist traits of the novelist fiction, particularly the ambivalence of language, multiple and fragmented points of view and syntax. Wladir Dupont (1939-2014) was a prolific Brazilian journalist who benefitted from his experiences as an international correspondent living abroad (EUA and Mexico) to become an acclaimed translator later in life. He received a Jabuiti Award (Brazilian most prestigious literary award) for his translation of ‘La Otra Voz’ (1994), by Mexican poet, critic and translator Octavio Paz, a writer to whom he devoted the first years of his carrier as a translator. As Dupont pointed out in some interviews, the struggles in finding a way out to overcome linguistic and cultural obstacles in the process of translating texts from Spanish to Portuguese was paramount for ascertaining his engagement in the long-term project of translating to Brazilian Portuguese the fiction of William Faulkner. His first enterprise was the translation of Faulkner’s trilogy Snopes: The Hamlet (1940) and The Town (1957), the first two novels, were published in 1997 as O povoado and A cidade; in 1999 the last novel, The mansion (1959), was published as A mansão. In 2001, Dupont tackled what is considered one of the most challenging novels by the author due to his use of multiple points of view, As I lay dying (1930). In 2003, The Reivers (1962) was published under the title Os invictos. His enterprise finishes in 2012 with the publication of an anthology of Faulkner’s thriller short-stories Knight’s Gambit (1932) as Lance mortal. Hence, in this paper we will consider the Dupont’s trajectory as a translator, paying special attention to the way in which his identity as such is constituted through the process of translating Faulkner’s works.

Keywords: literary translation, translator’s identity, William Faulkner, Wladir DuPont

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Authors: Chrysovalanto Sofia Karatosidi, Dimitra Iordanoglou

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The overlap of leadership skills with personality traits, beliefs, values, and the integration of cognitive abilities, analytical and critical thinking skills into leadership competencies raises the need to segregate further and investigate them. Hence, the domains of cognitive functions that contribute to leadership effectiveness should also be identified. Organizational cognitive neuroscience and neuroleadership can shed light on the study of these critical leadership skills. As the first part of our research, this pilot study aims to explore the relationships between higher-order cognitive functions (executive functions), trait emotional intelligence (EI), personality, and general cognitive ability in leadership. Twenty-six graduate and postgraduate students were assessed on neuropsychological tests that measure important aspects of executive functions (EF) and completed self-reported questionnaires about trait EI, personality, leadership styles, and leadership effectiveness. Specifically, we examined four core EF—fluency (phonemic and semantic), information updating and monitoring, working memory, and inhibition of prepotent responses. Leadership effectiveness was positively associated with phonemic fluency (PF), which involves mental flexibility, in turn, an increasingly important ability for future leaders in this rapidly changing world. Transformational leadership was positively associated with trait EI, extraversion, and openness to experience, a result that is following previous findings. The relationship between specific EF constructs and leadership effectiveness emphasizes the role of higher-order cognitive functions in the field of leadership as an individual difference. EF brings a new perspective into leadership literature by providing a direct, non-invasive, scientifically-valid connection between brain function and leadership behavior.

Keywords: cognitive neuroscience, emotional intelligence, executive functions, leadership

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Authors: Saeedeh Imani Moqadam, Ilya Bobrov, Jérémy Epp, Nils Ellendt, Lutz Mädler

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High entropy alloys (HEAs), having adjustable properties and enhanced stability compared with intermetallic compounds, are solid solution alloys that contain more than five principal elements with almost equal atomic percentage. The concept of producing such alloys pave the way for developing advanced materials with unique properties. However, the synthesis of such alloys may require advanced processes with high cooling rates depending on which alloy elements are used. In this study, the micro spheres of different diameters of HEAs were generated via a drop-on-demand droplet generator and subsequently solidified during free-fall in an argon atmosphere. Such droplet generators can generate individual droplets with high reproducibility regarding droplet diameter, trajectory and cooling while avoiding any interparticle momentum or thermal coupling. Metallography as well as X-ray diffraction investigations for each diameter of the generated metallic droplets where then carried out to obtain information about the microstructural state. To calculate the cooling rate of the droplets, a droplet cooling model was developed and validated using model alloys such as CuSn%6 and AlCu%4.5 for which a correlation of secondary dendrite arm spacing (SDAS) and cooling rate is well-known. Droplets were generated from these alloys and their SDAS was determined using quantitative metallography. The cooling rate was then determined from the SDAS and used to validate the cooling rates obtained from the droplet cooling model. The application of that model on the HEA then leads to the cooling rate dependency and hence to the identification of process windows for the synthesis of these alloys. These process windows were then compared with cooling rates obtained in processes such as powder production, spray forming, selective laser melting and casting to predict if a synthesis is possible with these processes.

Keywords: cooling rate, drop-on-demand, high entropy alloys, microstructure, single droplet generation, X-ray Diffractometry

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Authors: Lijuan Zhou, Mengqi Wu, Changyong Niu

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Attributed graph clustering can utilize the graph topology and node attributes to uncover hidden community structures and patterns in complex networks, aiding in the understanding and analysis of complex systems. Utilizing contrastive learning for attributed graph clustering can effectively exploit meaningful implicit relationships between data. However, existing attributed graph clustering methods based on contrastive learning suffer from the following drawbacks: 1) Complex data augmentation increases computational cost, and inappropriate data augmentation may lead to semantic drift. 2) The selection of positive and negative samples neglects the intrinsic cluster structure learned from graph topology and node attributes. Therefore, this paper proposes a method called self-supervised Attributed Graph Clustering with Dual Contrastive Loss constraints (AGC-DCL). Firstly, Siamese Multilayer Perceptron (MLP) encoders are employed to generate two views separately to avoid complex data augmentation. Secondly, the neighborhood contrastive loss is introduced to constrain node representation using local topological structure while effectively embedding attribute information through attribute reconstruction. Additionally, clustering-oriented contrastive loss is applied to fully utilize clustering information in global semantics for discriminative node representations, regarding the cluster centers from two views as negative samples to fully leverage effective clustering information from different views. Comparative clustering results with existing attributed graph clustering algorithms on six datasets demonstrate the superiority of the proposed method.

Keywords: attributed graph clustering, contrastive learning, clustering-oriented, self-supervised learning

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Guillaume Richard, Sarra Zaied

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Marine waste quantities increase more and more, 5 million tons of plastic waste enter the ocean every year. Their spatiotemporal distribution is never homogeneous and depends mainly on the hydrodynamic characteristics of the environment, as well as the size and location of the waste. As part of optimizing collect of marine plastic wastes, it is important to measure and monitor their evolution over time. In this context, diverse studies have been dedicated to describing waste behavior in order to identify its accumulation in ocean areas. None of the existing tools which track objects at sea had the objective of tracking down a slick of waste. Moreover, the applications related to marine waste are in the minority compared to rescue applications or oil slicks tracking applications. These approaches are able to accurately simulate an object's behavior over time but not during the collection mission of a waste sheet. This paper presents numerical modeling of a boat’s wake impact on the floating marine waste behavior during a collection mission. The aim is to predict the trajectory of a marine waste slick to optimize its collection using meteorological data of ocean currents, wind, and possibly waves. We have made the choice to use Ocean Parcels which is a Python library suitable for trajectoring particles in the ocean. The modeling results showed the important role of advection and diffusion processes in the spatiotemporal distribution of floating plastic litter. The performance of the proposed method was evaluated on real data collected from the Copernicus Marine Environment Monitoring Service (CMEMS). The results of the evaluation in Cape of Good Hope (South Africa) prove that the proposed approach can effectively predict the position and velocity of marine litter during collection, which allowed for optimizing time and more than $90\%$ of the amount of collected waste.

Keywords: marine litter, advection-diffusion equation, sea current, numerical model

Procedia PDF Downloads 56