El papel mediador del optimismo académico y el capital psicológico positivo de los profesores de EFL/ESL en la efectividad docente

A growing scholarly attention has been paid to the psycho-emotional side of second/foreign language (L2) education in the past decade. Optimal teaching and student achievement are no longer solely governed by teachers’ pedagogical skills and practices. Instead, various psycho-affective variables mediate the process of teaching English and its effectiveness. However, the way EFL/ESL teachers’ academic optimism and positive psychological capital influence their pedagogical effectiveness in light of demographic factors is neglected. To fill this gap, this study used three online questionnaires to examine the predictive role of 338 Chinese EFL/ESL teachers’ academic optimism and positive psychological capital in their pedagogical effectiveness. The results of structural equation modeling (SEM) and the standardized regression weights demonstrated a strong correlation between demographic factors and teacher’s academic optimism and teacher’s positive psychological capital. Moreover, a strong association was observed between teacher’s positive psychological capital and teacher effectiveness, while academic optimism did not correlate with teacher effectiveness. Furthermore, positive psychological capital could predict about 67% of changes in Chinese EFL/ESL teachers’ pedagogical effectiveness. The study also discusses the implications and suggestions for further research to deepen L2 educators’ knowledge of teacher-psychology.En la última década, los aspectos psicoemocionales de la educación en segunda lengua extranjera (l2) han atraído cada vez más la atención de los círculos académicos. La mejor enseñanza y el rendimiento de los estudiantes ya no dependen únicamente de las habilidades y prácticas docentes de los profesores. Por el contrario, diversas variables psicoemocionales juegan un papel mediador en el proceso de enseñanza del inglés y sus efectos. Sin embargo, bajo la influencia de factores demográficos, se ha ignorado el impacto del optimismo académico y el capital psicológico positivo de los profesores de EFL / ESL en su efectividad docente. Para llenar este vacío, el estudio utilizó tres cuestionarios en línea para investigar el efecto predictivo del optimismo académico y el capital psicológico positivo de 338 profesores chinos de EFL / ESL en su efectividad docente. Los resultados del modelado de ecuaciones estructurales (sem) y los pesos de regresión estandarizados muestran una fuerte correlación entre los factores demográficos y el optimismo académico de los docentes y el capital psicológico positivo de los docentes. Además, hay una fuerte correlación entre el capital psicológico positivo de los docentes y la eficacia de los docentes, mientras que no hay correlación entre el optimismo académico y la eficacia de los docentes. Además, el capital psicológico positivo puede predecir un cambio del 67% en la efectividad docente de los profesores chinos EFL / esl. El estudio también discutió la iluminación y sugerencias de nuevos estudios para profundizar los conocimientos psicológicos de los educadores de segunda lengua

Domain-Independent Dynamic Programming and Constraint Programming Approaches for Assembly Line Balancing Problems with Setups

We propose domain-independent dynamic programming (DIDP) and constraint programming (CP) models to exactly solve type-1 and type-2 assembly line balancing problem with sequence-dependent setup times (SUALBP). The goal is to assign tasks to assembly stations and to sequence these tasks within each station, while satisfying precedence relations specified between a subset of task pairs. Each task has a given processing time and a setup time dependent on the previous task on the station to which the task is assigned. The sum of the processing and setup times of tasks assigned to each station constitute the station time and the maximum station time is called the cycle time. For type-1 SUALBP, the objective is to minimize the number of stations, given a maximum cycle time. For type-2 SUALBP, the objective is to minimize the cycle time, given the number of stations. On a set of diverse SUALBP instances, experimental results show that our approaches significantly outperform the state-of-the-art mixed integer programming models for SUALBP-1. For SUALBP-2, the DIDP model outperforms the state-of-the-art exact approach based on logic-based Benders decomposition. By closing 76 open instances for SUALBP-2, our results demonstrate the promise of DIDP for solving complex planning and scheduling problems.Comment: 35 pages, 6 figures, submitted to Informs Journal on Computin

Influence of Intergenerational Parenting on Gross Motor Skills Among Children Aged 3-6 Years Old

The stage of 3-6 years old is a critical period for the development of children\u27s gross motor skills, influencing their growth and development. Intergenerational parenting is a common way of family education in China. Studies have shown that the rough intergenerational parenting concept and limited energy of the elderly reduce the quality of life of the children under care (Qimeng Jiang, Nan Zhou, 2020). However, no research focused on the influence of intergenerational parenting on gross motor skills. This study aimed to explore the influence of different intergenerational parenting style on gross motor skills among children aged 3-6 years old. The participants were 62 children (25 boys and 37 girls) aged 3-6 years old from Liaoning Province. All of the participants were under intergenerational parenting. Gross motor skills were assessed using the Test of Gross Motor Development-Third Edition (TGMD-3), which includes locomotor skills and ball skills components. The intergenerational parenting status was divided into parent-dominated intergenerational parenting and grandparent-dominated intergenerational parenting according to a questionnaire (Lu Ye, 2020). The parenting style included authoritative, authoritarian and tolerant styles. The scores of three styles were determined by the grandparents-reported Chinese version of Parental Authority Questionnaire. Descriptive statistics, independent t-test and Pearson correlation were employed and the significant levels were set at 0.05. The results showed that participants had lower mean scores in both locomotor skills (Mboy = 12.58±4.42, Mgirl =13.51 ±3.03) and ball skills (Mboy = 8.46±2.9, Mgirl = 8.04±3.34) compared to the Chinese norm. There was no significant difference between parent-dominated and grandparent-dominated intergenerational parenting (M Parent-dominated =22.90±4.15, M grandparent-dominated = 20.48±4.47; t = 1.269, p = 0.209). Correlation analysis indicated a small association between the score of locomotor skills and authoritative style (r = 0.269, p \u3c 0.05). No significant relationship was found between other parenting styles and the scores of TGMD-3. It is concluded that intergenerational parenting may negatively influence children’s gross motor development. Parent-dominated and grandparent-dominated intergenerational parenting may not have differences in children’s motor development. The authoritative parenting style of intergenerational education has certain impacts on children\u27s gross motor skills, especially on children\u27s locomotor skills

Robust Disentangled Variational Speech Representation Learning for Zero-shot Voice Conversion

Traditional studies on voice conversion (VC) have made progress with parallel training data and known speakers. Good voice conversion quality is obtained by exploring better alignment modules or expressive mapping functions. In this study, we investigate zero-shot VC from a novel perspective of self-supervised disentangled speech representation learning. Specifically, we achieve the disentanglement by balancing the information flow between global speaker representation and time-varying content representation in a sequential variational autoencoder (VAE). A zero-shot voice conversion is performed by feeding an arbitrary speaker embedding and content embeddings to the VAE decoder. Besides that, an on-the-fly data augmentation training strategy is applied to make the learned representation noise invariant. On TIMIT and VCTK datasets, we achieve state-of-the-art performance on both objective evaluation, i.e., speaker verification (SV) on speaker embedding and content embedding, and subjective evaluation, i.e., voice naturalness and similarity, and remains to be robust even with noisy source/target utterances.Comment: Accepted to 2022 ICASS

A comparison of the damage from UV emitted by Solaria and sunlight

Ultraviolet (UV) rays play an important role in the formation of Vitamin D. However, exposure to UV for long duration can cause negative health effects on people, such as sunburn and skin cancer. The sun is not the only source of UV, Solaria, like tanning bed and tanning lamp, also emit UV rays. People using solaria do not necessarily recognize that their skin might be damaged by the UV emissions. This essay describes the benefits and shortcomings of UV rays and then, undertakes a literature review to compare the carcinogenic effects of UV from Solaria and sunlight leading to non-melanoma cancer, including squamous cell carcinoma (SCC) and basal cell carcinoma (BCC). The findings are that the odds of getting BCC when exposed to sunlight for longer than 14 hours are close to the odds for typical solaria users, but the odds of getting SCC when exposed to sunlight for longer than 14 hours is higher than typical solaria users. Finally, appropriate strategies are suggested for prevention of UV injury. The target readers are people at risk of UV injury leading to skin diseases, such as those who might work outside and those who are interested in using solaria. The public health importance of knowing effects induced by UV and prevention ways is to help people avoid the potential damage from them

Enhancing High-Resolution 3D Generation through Pixel-wise Gradient Clipping

High-resolution 3D object generation remains a challenging task primarily due to the limited availability of comprehensive annotated training data. Recent advancements have aimed to overcome this constraint by harnessing image generative models, pretrained on extensive curated web datasets, using knowledge transfer techniques like Score Distillation Sampling (SDS). Efficiently addressing the requirements of high-resolution rendering often necessitates the adoption of latent representation-based models, such as the Latent Diffusion Model (LDM). In this framework, a significant challenge arises: To compute gradients for individual image pixels, it is necessary to backpropagate gradients from the designated latent space through the frozen components of the image model, such as the VAE encoder used within LDM. However, this gradient propagation pathway has never been optimized, remaining uncontrolled during training. We find that the unregulated gradients adversely affect the 3D model's capacity in acquiring texture-related information from the image generative model, leading to poor quality appearance synthesis. To address this overarching challenge, we propose an innovative operation termed Pixel-wise Gradient Clipping (PGC) designed for seamless integration into existing 3D generative models, thereby enhancing their synthesis quality. Specifically, we control the magnitude of stochastic gradients by clipping the pixel-wise gradients efficiently, while preserving crucial texture-related gradient directions. Despite this simplicity and minimal extra cost, extensive experiments demonstrate the efficacy of our PGC in enhancing the performance of existing 3D generative models for high-resolution object rendering.Comment: Accepted at ICLR 2024. Project page: https://fudan-zvg.github.io/PGC-3