Production Tasks Research Articles

Intrahemispheric White Matter Asymmetries and Interhemispheric Connections Underlying the Lateralization of Language Production and Spatial Attention in Left-Handers

ABSTRACT Leftward language production and rightward spatial attention are salient features of functional organization in most humans, but their anatomical basis remains unclear. Interhemispheric connections and intrahemispheric white matter asymmetries have been proposed as important factors underlying functional lateralization. To investigate the role of white matter connectivity in functional lateralization, we first identified 96 left-handers using visual half field naming tasks. They were then divided into atypical and typical functional dominance based on the lateralization of brain activation in a word generation task (for language production) and a landmark task (for spatial attention). Using a novel fixel-based framework, we obtained fiber-specific properties of white matter pathways. Results showed, first, that differences between two language dominance groups occurred in the asymmetry of the superior longitudinal fasciculus-III (SLF-III), whereas differences between two spatial attention dominance groups occurred in the rostrum and rostral body of the corpus callosum. However, the directions of functional lateralization were not associated with the directions of white matter asymmetries. Second, the degree of language lateralization was predicted by SLF-III asymmetry and the rostral body of the corpus callosum, whereas the degree of spatial attention lateralization was predicted by the rostrum of the corpus callosum. Notably, the degree of each functional lateralization was positively correlated with the anterior and middle callosal connections, supporting the excitatory model of the corpus callosum. The results suggest that language lateralization is shaped by a combined effect of intra- and interhemispheric connections, whereas spatial attention lateralization relies more on interhemispheric connections.

The Acquisition of de: Investigating Recursive Possession in Mandarin-Speaking Kids

Recursive grammar is the sole cognitive mechanism unique to human languages. This study investigates three aspects of the acquisition of the recursive possessive marker de by Mandarin-speaking children: the feasibility of recursive possessive (RP) levels, performance in both cognition and competence, and the age at which these abilities emerge. Following a development theory of recursive possessives in language acquisition, we conducted two tasks—comprehension and production—each comprising 12 questions. The comprehension task involved a truth-value judgment, while the production task consisted of a question-and-answer session. Forty-eight preschoolers, aged three to five, were recruited from a kindergarten and divided into three age groups. Additionally, 16 adults were randomly recruited to serve as a baseline for comparison. The results revealed that significant effects of levels of recursive possessiveness were observed only in five-year-old Mandarin-speaking children, not in their three- and four-year-old counterparts. The comprehension task was significantly easier for all participants compared to the production task, suggesting that understanding the material was not challenging for any group, with no substantial differences noted among them. The results demonstrated that age effects were critical for younger children in adopting RPs. Specifically, three- and four-year-old Mandarin-speaking children demonstrated the ability to comprehend multiple levels of RP but struggled to produce them. In contrast, five-year-olds exhibited adult-like comprehension and the ability to produce Level 1 RP.

Metaphor comprehension and production in verbally able children with Autism Spectrum Disorder.

Research in the field of figurative language processing in Autism Spectrum Disorders (ASD) has demonstrated that autistic individuals experience systematic difficulties in the comprehension of different types of metaphors. However, there is scarce evidence regarding metaphor production skills in ASD. Importantly, the exact source of metaphor processing difficulties in ASD remains largely controversial. The debate has mainly focused on the mediating role of structural language skills (i.e., lexical knowledge) and cognitive abilities (i.e., Theory of Mind and executive functions) in ASD individuals' ability to comprehend and generate metaphors. The present study examines metaphor comprehension and production in 18 Greek-speaking verbally able children with ASD and 31 typically-developing (TD) controls. Participants completed two tasks, namely, a low-verbal multiple-choice sentence-picture matching task that tested their ability to comprehend conventional predicate metaphors, and a sentence continuation task that assessed their ability to generate metaphors. The study also included measures of fluid intelligence, expressive vocabulary, and working memory within the sample. The results show that the ASD group had significantly lower performance than the TD group in both metaphor comprehension and production. The findings also reveal that expressive vocabulary skills were a key factor in the metaphor comprehension and production performance of the children with ASD. Working memory capacity was also found to correlate significantly with metaphor comprehension performance in the ASD group. Conversely, no correlations were found in the TD group with neither of the above factors. Of note, children with ASD generated significantly more inappropriate responses and no-responses to the metaphor production task compared with the control group. The overall results reveal that children with ASD had difficulty with both comprehending and using metaphorical language. The findings also indicate that TD children may employ diverse cognitive strategies or rely on different underlying skills when processing metaphors compared with children with ASD.

Force reflections of auditory and tactile action-effect weighting in motor planning

Most voluntary actions have only few goals, which provides considerable freedom in the selection of action parameters. Recent studies showed that task-irrelevant aspects of the task context influence the motor parameters of the actions in a way which seems to reflect the relative importance of these aspects within the underlying action representation. The present study investigated how the intensity of auditory action-effects affected force exertion patterns in a self-paced action production task. Participants applied force impulses with their index finger on a force-sensitive resistor every three seconds. In four separate conditions, force impulses elicited no sound, or elicited tones with 69, 59 or 49 dB intensity. The results showed that participants applied more force when tone intensity was lower, and when tones were absent. These force differences were also present in the first 60 ms following tone onset, implying that these reflected differences in motor planning. The results are compatible with the notion that actions are represented in terms of their sensory effects, which are weighted differently—presumably to maintain an optimal level of overall auditory and tactile stimulation in the present case. These results hint at the potential usefulness of motor parameters as readouts of action intentions.

Knowledge of English Affixes in Thai EFL Learners of Science and Language Programs

This study investigated the knowledge of affixes on vocabulary development among English as a Foreign Language (EFL) learners, focusing on the differentiation between students studying science and those studying the language. Affix knowledge, encompassing both prefixes and suffixes, is essential for expanding word family knowledge, serving as a cognitive bridge to proliferate word family members. To explore this, 111 secondary school students from a semi-urban Thai school, split into 53 science and 58 language program students, were assessed through receptive and productive affix knowledge tests. The findings reveal that science program students outperformed their language counterparts in receptive affix knowledge tests. Additionally, results indicated a learning continuum in affix acquisition, with students showing better average performance on receptive tests compared to more complex productive tasks. Notably, affix knowledge concerning prefixes was superior to that of suffixes across both test types. Moreover, the correlational analysis revealed a medium to strong relationship between English affix knowledge and vocabulary knowledge. The findings also suggest that suffix knowledge has a greater impact on productive vocabulary than on receptive vocabulary. Regression analysis supports the correlation results, highlighting that a deeper understanding of affixes is linked to stronger vocabulary knowledge in both comprehension and usage. These results suggest a structured progression in affix learning, from recognition to production, and underline the significance of affix knowledge in vocabulary expansion for EFL learners. The study emphasizes the need for further research into the mechanisms of affix acquisition and its role in language learning curricula.

AEDN-YOLO: an efficient one-stage detection network for strip steel surface defects

Steel surface defect detection is one of the key tasks in industrial production and quality control. Research on defect detection using deep learning algorithms has shown promising results. However, due to the complex backgrounds, large differences in defect sizes, and diverse defect types present in steel strip surface defect images, existing deep learning algorithms struggle to achieve precise detection. To address these challenges, this paper proposes an efficient detection model named AEDN-YOLO. Firstly, an adaptive feature extraction (AFE) module is designed, embedded into C2f to better capture irregularly shaped objects. Secondly, the Triplet Attention module is incorporated into the bottom layer of the backbone network to enhance the model’s ability to locate defect features accurately. Additionally, replace the standard convolution in the neck network with GSConv, which not only accelerates feature fusion to improve detection speed but also enlarges the model’s receptive field to enhance detection accuracy. Finally, add a small target detection layer to enhance the detection capability for tiny defects. The model achieves mAP of 81.7% and 72.7% on the NEU-DET and GC10-DET datasets, respectively, with a detection speed of 72.1 FPS. Compared to mainstream defect detection algorithms, the proposed algorithm enables accurate and efficient detection of steel surface defects.

Dissociating Cerebellar Regions Involved in Formulating and Articulating Words and Sentences.

We investigated which parts of the cerebellum are involved in formulating and articulating sentences using (i) a sentence production task that involved describing simple events in pictures; (ii) an auditory sentence repetition task involving the same sentence articulation but not sentence formulation; and (iii) an auditory sentence-to-picture matching task that involved the same pictorial events and no overt articulation. Activation for each of these tasks was compared to the equivalent word processing tasks: noun production, verb production, auditory noun repetition, and auditory noun-to-picture matching. We associate activation in bilateral cerebellum lobule VIIb with sequencing words into sentences because it increased for sentence production compared to all other conditions and was also activated by word production compared to word matching. We associate a paravermal part of right cerebellar lobule VIIIb with overt motor execution of speech, because activation was higher during (i) production and repetition of sentences compared to the corresponding noun conditions and (ii) noun and verb production compared to all matching tasks, with no activation relative to fixation during any silent (nonspeaking) matching task. We associate activation within right cerebellar Crus II with covert articulatory activity because it activated for (i) all speech production more than matching tasks and (ii) sentences compared to nouns during silent (nonspeaking) matching as well as sentence production and sentence repetition. Our study serendipitously segregated, for the first time, three distinct functional roles for the cerebellum in generic speech production, and it demonstrated how sentence production enhanced the demands on these cerebellar regions.

Results of experimental development of a laboratory water distillation installation based on a heat pump and a photovoltaic panel

Modern technologies and the continuous rise in water consumption require efficient and environmentally friendly methods of its extraction. According to the energy development strategy of the Russian Federation until 2035, the use of alternative energy sources in industry is a priority task for production. The use of renewable resources to produce distilled water for the needs of enterprises is becoming increasingly important. The innovative technology of a laboratory installation, combining water distillation using a heat pump and a photovoltaic panel, allows not only to obtain purified water, but also to heat the coolant before chemical purification. To create a laboratory stand, it is necessary to study the operating principles of the installation, divide the device into units: the main stand and the vacuum distiller, then model a three-dimensional image of each part of the complex in the SolidWorks software package. Based on the obtained models, a functional diagram of the complex is developed to obtain a coolant of the given parameters, and an algorithm is compiled for predicting the temperature of the heated water in the heat pump. The obtained installation test results are processed, and compared with theoretical data from tables of refrigerant properties, and a conclusion is drawn. The technology for producing purified water is aimed at replacing imported technologies and using renewable energy sources. The development of technologies for producing clean water is a priority for the development of the Russian energy sector. The results obtained indicate the potential of the laboratory installation for use in various areas where a reliable and environmentally friendly supply of distilled water is required, for example, in coastal areas for industrial facilities or agricultural enterprises.

Individual differences in attention and working memory modulate the process of tone merging: evidence from Macau Cantonese

Cognitive functions, including attention and working memory, have been recognized to be associated with tone processing. However, it remains unclear how these cognitive functions might modulate the process of tone merging. In Macau Cantonese, three pairs of tones are currently undergoing or have completed merging, exhibiting different rates and ranges of merging within the speech community, providing a valuable opportunity to investigate this issue. Through a perception task, a production task, and a series of cognitive function tasks, we examined differences in cognitive performances among individuals distinguishing different tone pairs and explored the correlations between various indices of tone processing and cognitive functions. The results revealed that the completed merging of the T2–T5 pair showed no significant correlation with cognitive functions in perception and production. The T3–T6 pair, with an intermediate merging speed, exhibited a significant positive correlation between cognitive functions and both their perception and production. In contrast, the T4–T6 pair, characterized by a slower merging speed, showed a correlation only in the perception modality. Our findings suggested that cognitive functions affect tones at different stages of the merging process, influencing their perception and production in distinct ways. The results provide a novel perspective on the origin of tonal variation and the relationship between perception and production.

Применение эволюционных и роевых методов для оптимизации многопараметрического управления процессом нанесения гальванического покрытия

One of the key parameters of the quality of ceramic coatings is its thickness, which must meet technical requirements and provide the necessary degree of corrosion protection, wear resistance and appearance of the coating. Ensuring the uniformity of the galvanic coating is one of the most important and complex tasks of high-tech machine-building production, for which a number of methods have been proposed, such as controlling current modes, the location of electrodes in the bath, and the electrolyte flow rate. However, in most cases, these methods require solving the problem of optimal multiparametric control. Prompt and accurate optimization when changing the conditions of electrolysis (electrode potentials, composition and properties of the electrolyte), as well as, if necessary, taking into account the multi-extreme nature of the dependence of the uniformity coefficient on the process parameters (current density, interelectrode distance, electrolyte flow rate) is a rather complex and ambiguous multifactorial task that limits the use of classical methods for- the claim of a global extreme. The article explores the possibility and expediency of using intelligent heuristic methods, such as evolutionary and swarm methods, to solve this problem. Objective. The objective of this study is to determine the effectiveness of using genetic algorithms and the particle swarm method to solve the problem of optimizing the multiparametric control of the electroplating process. Materials and methods. Methods of mathematical modeling, methods and software environment of numerical modeling and optimization were used to conduct the study. Results. The article investigates the effectiveness of the application of evolutionary and swarm optimization methods in relation to the process of applying chrome plating in a galvanic bath with many anodes with multiparametric control of current density, interelectrode distance and electrolyte flow rate. The best approximation to the extreme of the uniformity coefficient can be achieved by genetic algorithms using the mutation operation and the particle swarm method, while achieving the extreme using the particle swarm method is achieved in fewer iterations. Conclusion. The results of the study substantiate the expediency of using evolutionary and swarm methods to solve the problem of optimizing the multiparametric control of the electroplating process, while it is possible to increase the efficiency of these methods due to additional tuning.

Distorted time perception in patients with neurocognitive impairment

BackgroundTime perception is known to be distorted in patients with neuropsychiatric disorders. Therefore, this study aims to investigate the correlation between cognitive decline and time distortion by examining time perception in participants with neurocognitive impairment (Alzheimer's disease [AD], vascular dementia [VD], and Parkinson's disease dementia [PDD]) compared to those with subjective cognitive impairment (SCI). MethodsOverall, 569 participants with cognitive decline complaints between 2013 and 2022 were investigated. Participants were subjected to a verbal estimation task, time production task, time comparison task, and neuropsychological assessments. ResultsTime perception abilities were distorted in patients with neurocognitive impairment compared to those with SCI. Despite similar educational backgrounds, the vascular cognitive impairment (VCI)/VD group demonstrated the lowest MMSE scores (22.4 ± 4.2, p-value <0.001) and larger time-estimation errors. Patients with VCI/VD significantly underestimated time in the 35-s (19.6 ± 12.6s) and 60-s (28.7 ± 19.9s) tasks. In the time production task, patients with VCI/VD produced shorter times in their 15-s (12.7 ± 4.3; p-value = 0.001), 30-s (23.6 ± 8.3; p value < 0.001), and 60-s (43.8 ± 18.9; p-value <0.001) trials. In the time comparison task, the VCI/VD group had significantly fewer correct answers than that in the SCI groups (6.0 ± 1.3 vs. 7.1 ± 0.9, p-value <0.001). Correlation analysis revealed that multiple cognitive functions are involved in the time perception tasks. ConclusionsPatients with VCI/VD had the poorest time perception. These findings may provide a modest contribution to understanding the underlying pathophysiology and psychological connections related to temporal abilities in time perception.

L2 Spanish clitics among Brazilian Portuguese-speaking learners: the predictive role of lexical knowledge

We examined the acquisition of third-person accusative clitics (e.g., lo, la, los, las) in L2 Spanish among Brazilian Portuguese (BP) speakers. In BP, the animacy of the referent is the main feature constraining accusative pronoun use while, in Spanish, animacy does not affect clitic realization. We tested Lardiere’s (2008; 2009) Feature Reassembly Hypothesis (FRH), Schwartz &amp;amp; Sprouse’s (1996) Full Transfer/Full Access hypothesis (FT/FA), and the suitability of productive vocabulary knowledge as a proxy for overall proficiency and its predictive power for the acquisition of clitics. 74 BP-speaking L2 Spanish learners and a comparison group of 23 native Spanish speakers completed a language background questionnaire, a vocabulary test (Prueba Léxica de Español y Portugués/Prova Léxica de Espanhol e Português, PLEP), an elicited production task, and an acceptability judgment task. Only the L2 Spanish participants completed the tasks in both languages. Our findings are consistent with the FRH, showing that the participants successfully disassemble animacy features from their L1 when acquiring the non-animacy-driven clitics in Spanish. However, animacy effects were found in the L2 production data but not in their receptive grammatical knowledge. Furthermore, animacy effects were not dependent on proficiency as no interactions between these factors were found, thus rejecting the existence of a full transfer stage.

A behavioral conditional diffusion probabilistic model for human motion modeling in multi-action mixed human-robot collaboration

Collision avoidance is priority for human-robot collaboration (HRC). Human motions have stochastic, making it difficult for robots to recognize humans. To establish accurate human motion models is important to recognize humans. In the collaboration process, the action categories may suddenly and continuously switch to adapt to complex production tasks, namely, the stochastic of human motions, and we call this collaboration process as multi-action mixed HRC. The previous HRC rarely considered the stochastic of human motions. However, the stochastic in multi-action mixed HRC brings great challenges to human motion modeling. On the one hand, the same observed motions may develop into different action categories, the motion distribution need to be predicted. On the other hand, the connected motions between two action categories are missing, and need to be predicted. To address these two problems, this study introduced diffusion probabilistic models to capture the stochastic of human motions. However, the current diffusion probabilistic models cannot realize the high-accuracy human motion prediction. Most of them did not consider the condition distribution in diffusion process, and did not comprehensively capture the spatiotemporal characteristics between human and robot. To solve the above problems, a behavioral conditional probabilistic diffusion model (BCDPM) is proposed. The BCDPM model can capture the stochastic of human motions to model the human motion distribution. A mask mechanism is combined with diffusion prior generated by BCDPM model to predict the missing connected motions. The BCDPM model consists of the designed constrain network, the denoising network, and enhanced memory graph neural network. The constrain network can generate the condition distribution, the denoising network and enhanced memory graph neural network can capture the short term and long term spatiotemporal characteristics, respectively. Moreover, the overlapping motion primitives are explicitly encoded into the implicit BCDPM model to mine commonalities of motions. The results show the proposed method can obtain excellent accuracy in prediction and outstanding F1 score in collision detection experiment.

Influences of early and intense L2 exposure on L1 causal verb production: Comparison of 5-, 7-, and 9-year-old bilingual and monolingual children

This study investigates the influences of early and intense L2 exposure on children’s L1 causative verb production, assessed by an experimental causative verb production task. Turkish expresses causality by morphological and lexical means, whereas English does so by periphrastic and lexical means. Learning L2 English might enhance L1 Turkish causative verb production by highlighting the parallels and contrasts in causal expressions between the languages, which may result in an enriched L1 causative use. Five-, 7 -, and 9-year-old L1-Turkish L2-English bilingual ( n = 80) and L1-Turkish monolingual ( n = 80) children participated in the study in L1-Turkish. Results indicated that language group differences only emerged for the use of morphological causative verbs in favor of 5-year-old bilinguals compared with monolingual peers. Age group differences occurred only for the monolingual group and only for morphological verbs. Specifically, monolingual 7- and 9-year-olds performed better than monolingual 5-year-olds. Causative verb-type differences were only seen for 5-year-old monolinguals, who performed better for lexical than morphological verbs; in contrast, 5-year-old bilinguals performed equally well on the two types of causatives, and better than 5-year-old monolinguals on morphological causatives. Overall, these findings indicate that learning an L2 with structural similarities and differences compared with L1 might enhance children’s awareness and correct use of causal linguistic structures.

A local space transfer learning-based parallel Bayesian optimization with its application

The optimization of process parameters in polyolefin production can bring significant economic benefits to the factory. However, due to small data sets, high costs associated with parameter verification cycles, and difficulty in establishing an optimization model, the optimization process is often restricted. To address this issue, we propose using a transfer learning Bayesian optimization strategy to improve the efficiency of parameter optimization while minimizing resource consumption. Specifically, we leverage Gaussian process (GP) regression models to establish an integrated model that incorporates both source and target grade production task data. We then measure the similarity weights of each model by comparing their predicted trends, and utilize these weights to accelerate the solution of optimal process parameters for producing target polyolefin grades. In order to enhance the accuracy of our approach, we acknowledge that measuring similarity in a global search space may not effectively capture local similarity characteristics. Therefore, we propose a novel method for transfer learning optimization that operates within a local space (LSTL-PBO). This method employs partial data acquired through random sampling from the target task data and utilizes Bayesian optimization techniques for model establishment. By focusing on a local search space, we aim to better discern and leverage the inherent similarities between source tasks and the target task. Additionally, we incorporate a parallel concept into our method to address multiple local search spaces simultaneously. By doing so, we can explore different regions of the parameter space in parallel, thereby increasing the chances of finding optimal process parameters. This localized approach allows us to improve the precision and effectiveness of our optimization process. The performance of our method is validated through experiments on benchmark problems, and we discuss the sensitivity of its hyperparameters. The results show that our proposed method can significantly improve the efficiency of process parameter optimization, reduce the dependence on source tasks, and enhance the method's robustness. This has great potential for optimizing processes in industrial environments.

A hybrid method for the intelligent effectiveness management of production operators

AbstractThe paper presents a hybrid method for the effective management of human resources when executing production processes. The method was proposed for managing production operators in systems of relatively high complexity—with the possibility of multiple alternative ways of designating operators to production stations. The method combines a novel approach of assessing the effectiveness of production operators, the use of an intelligent algorithm and the risk assessment method. The concept of effectiveness was used in the sense of a praxeological approach. Availability, performance and quality were defined as its components, and were evaluated through the prism of losses occurring in production processes. The aim of the study is to develop a hybrid method in order to delegate production operators to tasks, not only on the basis of a competence metric, but also on the basis of an individual effectiveness indicator and the risk assessment of production process stages. For this purpose, a novel method of assessing the effectiveness of the use of available resources when implementing production processes (based on a set of quantitative indicators and taking into account the categorization of production losses) was juxtaposed using the Tabu Search algorithm and the FMEA method. The method enables a near-optimal solution to be generated—one in which operators are assigned to production tasks in the most effective way possible, which in turn minimizes both the risk of production delays and quality defects due to operator fault.

Salient semantics

Semantic features are components of concepts. In philosophy, there is a predominant focus on those features that are necessary (and jointly sufficient) for the application of a concept. Consequently, the method of cases has been the paradigm tool among philosophers, including experimental philosophers. However, whether a feature is salient is often far more important for cognitive processes like memory, categorization, recognition and even decision-making than whether it is necessary. The primary objective of this paper is to emphasize the significance of researching salient features of concepts. I thereby advocate the use of semantic feature production tasks, which not only enable researchers to determine whether a feature is salient, but also provide a complementary method for studying ordinary language use. I will discuss empirical data on three concepts, conspiracy theory, female/male professor, and life, to illustrate that semantic feature production tasks can help philosophers (a) identify those salient features that play a central role in our reasoning about and with concepts, (b) examine socially relevant stereotypes, and (c) investigate the structure of concepts.

Exploring the Relationship Between Working Memory Capacity and L2 Oral Fluency

This study investigated the relationship between working memory capacity (WMC) and L2 oral fluency and explored the maintenance of newly presented information in L2 speaking production. When performing speech production tasks, knowledge from long-term memory is at frequent use and hence involves the operation of the episodic buffer, one component of the working memory system, where information is retrieved from long-term memory and stored in chunks as we speak in chunks. In this study, we measured WMC by assessing chunk capacity and chunk size held in and retrieved from the episodic buffer. Chunk capacity was measured by Pair-word Speaking Task; chunk size was measured by Procedure Description Task; and oral fluency was measured by speech rate and mean length of run using an IELTS speaking task. Twenty-nine English-major students participated in this study. The results showed a strong positive correlation between chunk capacity and the two measures of fluency while chunk size negatively correlated with fluency. Data from the recall interviews revealed that participants employed various strategies for the maintenance of the presented information which involved different types of information binding.

Cartoons Influence on Primary School Pupils Towards Violence and Aggression in Niger State

Screen plays, including cartoons, are a crucial part of children's lives, helping to satisfy their energy and keep them engaged both at home and in school. Research has found that aggression and violence are prevalent among primary school pupils, and scholars have called for further investigation into the possible causes of this issue. Biological and personal factors such as family dynamics, fear of abandonment, punishment, sexual assault, and domestic violence have been studied extensively. However, little research has been conducted on the impact of entertainment media, specifically cartoons, on primary school students' aggression and violence. This study aims to fill this gap by examining the influence of cartoons on the attitudes of children towards violence and aggression of primary school pupils in Niger state. The study adopted a descriptive survey design. Purposive sampling technique was adopted in selecting 120 primary school pupils from 12 schools across the three senatorial zones in Niger state. Four research questions were answered and questionnaire was used as instrument for data collection. The quantitative data were analyzed using descriptive statistics and T-test at 0.05 level of significance. The results showed that cartoon had a positive influence on primary school pupils (x ̅ =1.44 on a threshold of 1.50). Also, it was discovered that cartoons affects pupils’ time to focus on productive tasks (x ̅ =1.62 on a threshold of 1.50), among others. The result of the difference between pupils’ reaction to cartoons based on gender showed that there was a significant difference (t = -3.28; df = 248; p&lt;0.05). Also, the result of the difference between the reactions of pupils to cartoon among public and private schools pupils indicated that there was a significant difference (t = 2.70; df = 248; p&lt;0.05). Following these findings, recommendations are made for parents to pay greater attention to presenting their children with carefully chosen cartoons that could have a positive impact on them. For the teachers, it was recommended that they should create a classroom environment that is less conducive to aggressive or violent behaviour so as to curb whatsoever the pupils might have learnt in their respective homes. Pupils are advised to be aware of their attitudes towards aggression and violence and take steps to stop such behaviour among themselves and their peers. Recommendations are made for curriculum planners to incorporate media literacy and social-emotional learning into the curriculum. Policy makers are advised to develop guidelines for media content, invest in research, and provide funding as these would aid in promoting positive attitudes towards aggression and violence among cartoon viewing pupils.

Framework design of distributed P2P2G energy transaction considering photovoltaic power and dispatch of manufacturing facilities

In this paper, a distributed peer-to-peer-to-grid (P2P2G) energy transaction framework considering photovoltaic generation and dispatch of manufacturing facilities is designed to increase the penetration of renewable energy resource. The factory with typical manufacturing assembly production task, photovoltaic panels and battery is regarded as a micro-grid (MG) to participate in the energy transaction market. The designed framework contains two levels. In the upper level, each MG determines the scheduling of manufacturing facilities and battery and the quantities of P2P2G energy transactions based on the given P2P energy transaction price and distribution locational marginal price (DLMP), in which the complex typical manufacturing assembly process is formulated as a kind of deferable load and the DLMP is updated according to the optimal power flow (OPF) of the network. In the lower level, peer-to-peer (P2P) energy transaction prices are updated by non-cooperative games and the homologous Rosen-Nash equilibrium points are obtained by using Nikaido-Isoda relaxation and alternating direction method of multipliers (ADMM) algorithm. The efficacy of the designed framework is demonstrated by a case study, and the results indicate the designed framework can improve the utilisation rate of renewable energy.