Search results

The early care and education (ECE) workforce plays a pivotal role in shaping early childhood developmental trajectories and simultaneously experiences significant mental health disparities. The purpose of this study is to investigate how social determinants of health and external stressors are associated with the mental health of ECE staff, which represent a low-resourced segment of the workforce; how psychological capital (psycap) can mitigate these associations.

The authors administered an 89-item survey to 332 ECE staff employed in 42 Head Start centers in the USA. The authors ran three hierarchical linear regression models to analyze associations between social determinants of health, external sources of stress, psycap and potential moderation effects and mental health outcomes.

Individuals experiencing greater finance-related stress reported 0.15 higher scores on the depression scale and 0.20 higher scores on the anxiety scale than those experiencing less finance-related stress (p < 0.05). Individuals experiencing greater work-related stress reported 1.26 more days of poorer mental health in the past month than those experiencing less work-related stress (p < 0.01). After controlling for all sociodemographic variables and sources of stress, psycap was significantly and negatively associated with depressive symptomology (b-weight = −0.02, p < 0.01) and the number of poor mental health days reported in the past month (b-weight = −0.13, p < 0.05). Moderation models suggest that higher levels of psycap may mitigate the association between work-related stress and the number of poor mental health days reported in the past month (b-weight = −0.06, p = 0.02).

The implications of these findings suggest a need for policy change to mitigate social determinants of health and promote pay equity and multi-level interventio ns that target workplace-related stressors and psycap to combat poor mental health of the ECE workforce.

The purpose of the study is distributed generation planning in a radial delivery framework to identify an appropriate location with a suitable rating of DG units energized by renewable energy resources to scale back the power loss and to recover the voltage levels. Though several algorithms have already been proposed through the target of power loss reduction and voltage stability enhancement, further optimization of the objectives is improved by using a combination of heuristic algorithms like DE and particle swarm optimization (PSO).

The identification of the candidate buses for the location of DG units and optimal rating of DG units is found by a combined differential evolution (DE) and PSO algorithm. In the combined strategy of DE and PSO, the key merits of both algorithms are combined. The DE algorithm prevents the individuals from getting trapped into the local optimum, thereby providing efficient global optimization. At the same time, PSO provides a fast convergence rate by providing the best particle among the entire iteration to obtain the best fitness value.

The proposed DE-PSO takes advantage of the global optimization of DE and the convergence rate of PSO. The different case studies of multiple DG types are carried out for the suggested procedure for the 33- and 69-bus radial delivery frameworks and a real 16-bus distribution substation in Tamil Nadu to show the effectiveness of the proposed methodology and distribution system performance. From the obtained results, there is a substantial decrease in the power loss and an improvement of voltage levels across all the buses of the system, thereby maintaining the distribution system within the framework of system operation and safety constraints.

A comparison of an equivalent system with the DE, PSO algorithm when used separately and other algorithms available in literature shows that the proposed method results in an improved performance in terms of the convergence rate and objective function values. Finally, an economic benefit analysis is performed if a photo-voltaic based DG unit is allocated in the considered test systems.

The purpose of this study is to investigate the phonological metathesis phenomenon in the early speech of Arabic-speaking children. Based on analysis of a longitudinal data from 11 children's speech, the study mainly aims at investigating (1) the characteristics/nature of the phonological metathesis process in early child speech and (2) how it is different from adult phonological metathesis. The study explores the causes behind the metathesis phonological process in child speech.

This paper explored the phonological metathesis phenomenon based on a longitudinal study of 11 monolingual Arabic speakers of Yemeni-Ibbi Dialect (YIA) and cross-linguistic data from various languages.

The data analysis showed that metathesis phenomenon in child speech has several characteristics. It occurs at an early age, at 2 years and decreases with age. It was found that metathesis occurs mostly in disyllabic and trisyllabic words or more complex syllabic words, but metathesis rarely occurs in monosyllabic words in children's speech. The results indicated that unlike metathesis in adult speech, metathesis in children's speech occurs in undeliberate, slow, fast speech. The study explored that adjacency of sounds with similar phonological features, the ease of pronunciation, or the sonority effect are the motivations that trigger metathesis phenomenon to occur in child speech.

In the literature, the metathesis phonological process has got a little attention from researchers, and this is due to the rare cases of metathesis and the inconsistency of cases and the occurrence of metathesis. However, there is no consensus among the researchers about the causes of emergence and the occurrences behind the metathesis process. However, this study argues that the metathesis process has unique characteristics in child speech in comparison to adult speech and that there are some causes for metathesis to occur in human speech particularly in children's data such as adjacency of sounds with similar phonological features or sonority effect.

Despite the growing attention on the relevance of improved building management systems with cognition in recent years in the architecture, engineering, construction and operation (AECO) community, no review has been conducted to understand the human-environment interaction features of cyber-physical systems (CPS) and digital twins (DTs) in developing the concept of a cognitive building (CB). Thus, this paper aims to review existing studies on CPS and DTs for CB to propose a comprehensive system architecture that considers human-environment interactions.

Scientometric analysis and content analysis were adopted for this study.

The scientometric analysis of 1,042 journal papers showed the major themes of CPS/DTs for CB, and these can be categorized into three key technologies to realize CB in the AECO community: CPS, DTs and cognitive computing (CC). Content analysis of 44 relevant publications in the built environment assisted in understanding and evidently confirming the claim of this study on the integration of CPS and DTs for CB in construction by also involving the CC. It is found and confirmed that CB can be realized with CPS and DTs along with the CC. A CB system architecture (CBSA) is proposed from the three key technologies considering the human-environment interactions in the loop. The study discovered the potential applications of the CBSA across the building lifecycle phases, including the design, construction and operations and maintenance, with the potential promise of endowing resilience, intelligence, greater efficiency and self-adaptiveness. Based on the findings of the review, four research directions are proposed: human-environment interactions, CB for sustainable building performance, CB concept for modular buildings and moving beyond CB.

This study stands out for comprehensively surveying the intellectual core and the landscape of the general body of knowledge on CPS/DTs for CB in the built environment. It makes a distinctive contribution to knowledge as it does not only propose CBSA by integrating CPS and DTs along with CC but also suggests some potential practical applications. These may require expert judgments and real case examples to enhance reproducibility and validation.