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Related Data for: Synthesis and cytotoxicity of copper(II) semicarbazone complexes with lipophilic counter-anions
No full textA series of (2,4-dihydroxybenzaldehyde dibenzyl semicarbazone) perfluoroalkyl carboxylato copper(II) complexes, [CF3(CF2)nCO2(LH)Cu] (LH2 = 2,4-dihydroxybenzaldehyde dibenzyl semicarbazone; n = 0, 2, 4, 6; 1–4), and (2,4-dihydroxybenzaldehyde dibenzyl semicarbazone) pyridine copper(II) perfluoroalkyl carboxylates, [(LH)(py)Cu]+[CF3(CF2)nCO2]− (5–8) were synthesized. The lipophilicity of these compounds was determined by reverse-phase thin layer chromatography and correlated with their cytotoxicity towards MOLT-4 human leukaemia cells. Cytotoxicity is more strongly correlated with lipophilicity for the non-ionic compounds (1–4) than for the ionic compounds (5–8). Compounds 5–8 (IC50 2.8–3.8 μM) are generally more cytotoxic than compounds 1–4 (IC50 3.6–8.4 μM). They also exhibit slightly higher cytotoxicity than the parent anticancer compound [(LH)(py)Cu]+[NO3]− (IC50 4.15 μM), suggesting that it is possible to enhance the cytotoxicity of [(LH)(py)Cu]+[NO3]− by replacing nitrate with anions of higher lipophilicity. Attempts to synthesize the non-fluorinated analogue [(LH)(py)Cu]+[CH3CO2]− resulted in the formation of the deprotonated complex [L(py)Cu], whose structure was confirmed by X-ray crystallography. The structural parameters indicate that the deprotonation site is the hydrazonic nitrogen of the semicarbazone ligand
Related Data for: Growth, physiology and nutritional quality of C4 halophyte Portulaca oleracea L. grown aeroponically in different percentages of artificial seawater under different light-emitting diode spectral qualities
No full textEdible halophyte Portulaca oleracea L., known as purslane, was grown in two percentages of artificial seawater (ASW) under two combined red (R) and blue (B) LED spectra. High salinity (40% ASW) negatively affected shoot productivity and leaf growth of purslane compared to those grown in 10% ASW. Photosynthetic pigment and total reduced nitrogen concentrations were significantly higher in purslane grown in 10% ASW than in 40% ASW. However, LED spectral quality did not markedly influence these parameters. Grown in 10% ASW under R/B 2.2, purslane had the highest maximum nitrate reductase activity, while those in 40% ASW under R/B 2.2 had the highest activation state. Under both light qualities, purslane had a sevenfold increase in proline concentration in 40% ASW than in 10% ASW. Total phenolic compounds’ concentration was the highest in 10% ASW under R/B 0.9, while there were no significant differences in the accumulation of total soluble sugars and ascorbic acids among all plants. Antioxidant enzymes activities were lower in 40% ASW under R/B 2.2 compared to the other conditions. In conclusion, salinity affected the yield, physiology and nutritional quality of purslane. The impacts of LED spectral quality on purslane were only reflected by certain physiological and nutritional parameters
Related Data for: Multimodal composing in the English classroom: Recontextualising the curriculum to learning
No full textAs literacy curricula around the world expand to include multimodal meaning-making, the challenge that remains is how teachers can design engaging and effective learning experiences in this context and the nature of their guidance to students in developing their multimodal literacy. Our paper focuses on the topic of multimodal composing, where students create artefacts to learn and demonstrate their learning. We seek to understand how teachers can design for students’ learning through multimodal composing with the use of a pedagogic metalanguage. Our data is drawn from a design-based research project on the teaching and learning of multimodal literacy in two secondary schools in Singapore. We discuss the implications of the design and evaluation of students’ learning through multimodal composing and reflect on the nature of the design work by teachers as they negotiate the curriculum requirements and make sense of their professional learning
Related Data for: Problematic mobile phone use among youth athletes: A topic modelling approach
No full textThe study provided an exploratory investigation into problematic mobile phone use among youth athletes. The study aimed to identify the factors contributing to problematic use and effects of problematic use among youth athletes. 369 Singaporean youth athletes, aged between 12 and 19 years old, participated in the study. A structural topic modelling approach using the R package stm was used to analyse the data. The process generated a list of topics for each of the open-ended survey questions. Subsequent interpretation was done to label the topics and group them into higher thematic categories. The prevalence of problematic mobile phone use in the sampled population was 40.65%. The analysis produced 38 topics for factors and 36 topics for effects. For factors, the higher thematic categories were habitual/compulsive use, accessibility/utility, alleviation of boredom/moods, lack of control, coping with school/work, entertainment, and communication. For effects, the higher thematic categories were time wastage/insufficient time, distraction/loss of focus, sleep/tiredness, sport-related areas, and addiction. The study provided novel insight into issues surrounding problematic mobile phone use among youth athletes. Future research needs to be conducted to further investigate the topics and themes that emerged
Related Data for: In-shoe plantar pressure profiles in amateur basketball players – Implications for footwear recommendation and orthoses use
No full textBackground: Biomechanical analysis of foot loading characteristics may provide insights into the injury mechanisms and guide orthotic prescription for basketball players. This study aimed to quantify in-shoe plantar pressure profiles in amateur players when executing typical basketball movements.
Methods: Twenty male university basketball players performed four basketball-specific movement tasks—running, maximal forward sprinting, maximal 45° cutting, and layup—in a pair of standardized basketball shoes fitted with an in-shoe plantar pressure measurement system. Peak pressure (PP) and pressure-time integral (PTI) data were extracted from ten plantar regions. One-way repeated-measures analysis of variance was performed across the tasks, with significance set at P
Results: Distinct plantar pressure distribution patterns were observed among the four movements. Compared with running, significantly higher (P
Conclusions: Compared with running, sprinting and layup demonstrated higher plantar loading in the forefoot region, and 45° cutting yielded increased plantar loading in most regions of the foot. Understanding the plantar pressure characteristics of different movements may be useful in optimizing footwear designs, orthosis use, or training strategies to minimize regional plantar loading during amateur basketball play.</p
Related Data for: Children’s digital multimodal composing: Implications for learning and teaching
No full textThis paper explores the implications of children’s out-of-school digital multimodal composing practices on learning and teaching in the formal educational context. It adopts a case study approach where publicly accessible YouTube video productions of three children around the world are examined. Applying a multimodal discourse analysis approach, we analyse the children’s videos and discuss what they suggest about the children’s literacies and skills. We argue that children’s digital multimodal composing practices demonstrate their creativity, critical thinking, and a semiotic awareness. Following the case studies, we discuss how the educators can respond to students’ out-of-school literacy activities by creating the ‘third space’ for learning in schools
Related Data for: Contextualizing physical data in professional handball: Using local positioning systems to automatically define defensive organizations
No full textIn handball, the way the team organizes itself in defense can greatly impact the player’s activity and displacement during the play, therefore impacting the match demands. This paper aims (1) to develop an automatic tool to detect and classify the defensive organization of the team based on the local positioning system data and check its classification quality, and (2) to quantify the match demands per defensive organization, i.e., defining a somehow cost of specific defensive organizations. For this study, LPS positional data (X and Y location) of players from a team in the Spanish League were analyzed during 25 games. The algorithm quantified the physical demands of the game (distance stand, walk, jog, run and sprint) broken down by player role and by specific defensive organizations, which were automatically detected from the raw data. Results show that the different attacking and defending phases of a game can be automatically detected with high accuracy, the defensive organization can be classified between 1–5, 0–6, 2–4, and 3–3. Interestingly, due to the highly adaptive nature of handball, differences were found between what was the intended defensive organization at a start of a phase and the actual organization that can be observed during the full defensive phase, which consequently impacts the physical demands of the game. From there, quantifying for each player role the cost of each specific defensive organization is the first step into optimizing the use of the players in the team and their recovery time, but also at the team level, it allows to balance the cost (i.e., physical demand) and the benefit (i.e., the outcome of the defensive phase) of each type of defensive organization
Related Data for: Many-dimensional model of adolescent school enjoyment: A test using machine learning from behavioral and social-emotional problems
No full textThere is an emerging, many-dimensional model of human functioning that has yet to be rigorously tested in adolescent psychopathology. The model is based, in part, on research suggesting stronger predictive power at the level of single items compared to the commonly used smaller number of higher-level constructs represented by scores or factors. Here, the model is tested in research relevant for the understanding how psychopathology relates to adolescent school enjoyment. We compared, explained, and clustered machine learning model results from a set of 99 self-reported items from different instruments that measured the behavioral and social-emotional problems of adolescents to predict school enjoyment. There is support for a many-dimensional model. Individual items had unique variances beyond noise that incrementally added out-of-sample predictive power above construct-level prediction, particularly for nonlinear machine learning classifiers. Explainable machine learning uncovered important predictors of low school enjoyment, and these were specific nuances of withdrawn/depressive behaviors, elevated fears and anxieties, lowered sensation-seeking, and some conduct problems—what we term risk nuances (cf. risk factors). Clustering further identified shared risk nuances among different groups of individuals with low school enjoyment. Our results suggest that item nuances are important in revealing many ways in which adolescents’ behavioral and social-emotional problems relate to school enjoyment at the individual and group levels. A many-dimensional model can complement current descriptive, predictive, and intervention efforts in adolescent psychopathology
Related data for: Global fall and rise of digital learning inequality
No full textRelated data for: Global fall and rise of digital learning inequalit
Related Data for Thesis/Dissertation: Differentiated instruction to support students with dyslexia in Singapore: The mediating role of self-efficacy on teachers' attitudes towards inclusion
No full textTo support an increasing number of students with Special Educational Needs (SEN) in mainstream schools, it is important for teachers to differentiate their instruction to meet the varied needs of students. This study examined the current levels of use of differentiated instruction and academic progress monitoring practices among 98 Primary School English Language (EL) teachers in Singapore (81% female, average of 16.1 years in service) to support students with dyslexia in their classroom. It also explores teachers’ existing attitudes towards inclusion, self-efficacy for inclusive practices, and perceptions of student diversity. The study also examined if teachers’ attitudes, self-efficacy, and perceptions of student diversity can predict their use of differentiated instruction and academic progress monitoring practices, and the mediating role of teachers’ self-efficacy for inclusive practices. Results indicated that teachers’ self-efficacy significantly predicted their differentiated instruction and academic progress monitoring practices. Teachers’ perceptions of student diversity significantly predicted their differentiated instruction practices and marginally predicted academic progress monitoring practices. However, teachers’ attitudes towards inclusion did not predict both differentiated instruction and academic progress monitoring practices. Teachers’ self-efficacy for inclusive practices fully mediated the relationship between teachers’ attitudes towards inclusion and their differentiated instruction practices. Findings from this study add to our understanding on the influence of various teacher factors on teachers’ inclusive practices in the classroom and highlights the importance of building teachers’ self-efficacy for inclusive practices. Limitations, possible future research, and implications of the results were discussed