Marital Satisfaction Over the Family Life Cycle Among Taiwanese Couples

The purpose of this study was to determine whether or not there were different subjective reports of marital satisfaction or dissatisfaction across the life cycle for Taiwanese couples. In examining this question two of the three selected instruments demonstrated sufficient reliability so as to be included in the overall study, namely, the Marital Adjustment Scale (MAS) and the Spanier Dyadic Adjust Scale (SDAS). These instruments were translated from English to Chinese, then administered to 259 couples volunteering to participate in the study. Couples were grouped according to their placement along the life cycle. The results of the study indicate that there is indeed a difference in the amount of reported marital satisfaction across the life cycle; however, there is no evidence that males or females differ in their perception of the amount of marital satisfaction experienced. Multiple regression examined the factors determined from the two scales for their influence on male and female reports of marital satisfaction at varying stages of the life cycle. While many findings were noted, three are of relative significance. First, couples in the first stage of the life cycle and those in the last stage report that companionate behavior is of critical importance. Secondly, in the second stage of the life cycle, female respondents did not identify any variable as significant regardless of the instrument. Finally, there is an interesting dip in marital satisfaction at the point in time when families begin to launch their children and enter the empty nest. Recommendations include continued research on assessing what variables are related to marital satisfaction in this population. Secondly, marital and family therapy clinical training is viewed as important, especially at this time in this culture. Finally, there are various ways in which enrichment and prevention programs would facilitate the longevity of relationships, thus deterring divorce

University faculty members’ perceptions of their teaching efficacy

[[abstract]]The purpose of this study was to investigate faculty members' perceptions of teaching efficacy and their relation to faculty members' backgrounds. A questionnaire measuring six dimensions of teaching efficacy was distributed to faculty members at 17 universities in Taiwan, yielding 513 complete sets of responses. Faculty members felt efficacious, from the greatest to the least, in the following dimensions: course design, class management, interpersonal relation, learning assessment, technology usage, and instructional strategy. Faculty members of public universities show higher perceptions of their efficacy than do those of private universities. Faculty members in education report a higher level of efficacy than faculty members in other disciplines. Females score higher than males in class management and learning assessment. Faculty members with less than six years of teaching experience indicate lower perceptions of teaching efficacy in course design than other faculty members. Faculty members teaching courses completely matching their specialties feel more confident in their teaching than those teaching partially-matched courses. However, there is no significant difference between faculty members with teaching training and those without training experience.[[journaltype]]國外[[incitationindex]]SSCI[[countrycodes]]GB

Students Language Performance and TOEFL Preparation Program, Are they connected?

This study examines and describes the relationship between TOEFL preparation Program and Students; language performance. The study also examines the program's effect on students' TOEFL scores improvement. Using spss v.22 in analyzing the data, the researcher employed three groups of students consisting of 15 students, namely the control group, treatment 1 group, and the treatment two groups. Thus, descriptive statistics present verifiable data in numerical form, which uses statistical procedures to tabulate, describe, reflect, and summarize data properties. The two variables data examined, TOEFL paper-based testing score and FCE Cambridge speaking test score, are the focus of the research, free from context generalization of the phenomenon. The result is presented statistically using quantitative methodology. The control group was not exposed to any treatment, while 1 group was given basic general English lessons, and the treatment 2 group was trained using the specially designed TOEFL preparation course. The study result shows significant effects on the improvement of TOEFL score on the treatment 1 group's pre-test mean, the standard of deviation, and the standard error mean were 350.07, 22.745, and 5.873, respectively. The treatment 2 group's mean, the standard of deviation, and the standard error mean were 355.40, 20.117, and 5.194, respectively, and the treatment 1 group' post-test mean, the standard of deviation, and the standard error mean were 387.27, 35.204, and 9.090, respectively. The treatment 2 group's mean, standard of deviation, and standard error mean were 436.87, 44.912, and 6.925, respectively. However, the study result shows that the correlation p-value = .083 indicates no significant correlation between TOEFL Preparation students' language performance

Melanogenesis Inhibitory Activity of Two Generic Drugs: Cinnarizine and Trazodone in Mouse B16 Melanoma Cells

More than 200 generic drugs were screened to identify the inhibitory activity on melanogenesis in mouse B16 melanoma cells. Cinnarizine and trazodone were identified as melanogenesis inhibitors. The inhibitory effects of the two drugs on cell survival, melanogenesis, and tyrosinase activity were investigated. The results showed that both cinnarizine and trazodone inhibited melanogenesis in B16 cells by a dose-dependent manner at the non-cytotoxic concentrations. Based on the results of the present study, seeking new melanogenesis inhibitors from generic drugs is an alternative approach to developing new depigmenting agents in cosmeceuticals. Moreover, cinnarizine and trazodone were proven to be good candidates as skin-whitening agents for treatment of skin hyperpigmentation

Environment Diversification with Multi-head Neural Network for Invariant Learning

Neural networks are often trained with empirical risk minimization; however, it has been shown that a shift between training and testing distributions can cause unpredictable performance degradation. On this issue, a research direction, invariant learning, has been proposed to extract invariant features insensitive to the distributional changes. This work proposes EDNIL, an invariant learning framework containing a multi-head neural network to absorb data biases. We show that this framework does not require prior knowledge about environments or strong assumptions about the pre-trained model. We also reveal that the proposed algorithm has theoretical connections to recent studies discussing properties of variant and invariant features. Finally, we demonstrate that models trained with EDNIL are empirically more robust against distributional shifts.Comment: In Proceedings of 36th Conference on Neural Information Processing Systems (NeurIPS 2022

Examining the Relationships Between Distance Education Students’ Self-Efficacy and Their Achievement

This study aimed to examine the relationships between students’ self-efficacy (SSE) and students’ achievement (SA) in distance education. The instruments were administered to 100 undergraduate students in a distance university who work as migrant workers in Taiwan to gather data, while their SA scores were obtained from the university. The semi-structured interviews for 8 participants consisted of questions that showed the specific conditions of SSE and SA. The findings of this study were reported as follows: There was a significantly positive correlation between targeted SSE (overall scales and general self-efficacy) and SA. Targeted students' self-efficacy effectively predicted their achievement; besides, general self- efficacy had the most significant influence. In the qualitative findings, four themes were extracted for those students with lower self-efficacy but higher achievement—physical and emotional condition, teaching and learning strategy, positive social interaction, and intrinsic motivation. Moreover, three themes were extracted for those students with moderate or higher self-efficacy but lower achievement—more time for leisure (not hard-working), less social interaction, and external excuses. Providing effective learning environments, social interactions, and teaching and learning strategies are suggested in distance education

Variability of morphology in beat-to-beat photoplethysmographic waveform quantified with unsupervised wave-shape manifold learning for clinical assessment

We investigated the beat-to-beat fluctuation of the photoplethysmography (PPG) waveform. The motivation is that morphology variability extracted from the arterial blood pressure (ABP) has been found to correlate with baseline condition and short-term surgical outcome of the patients undergoing liver transplant surgery. Numerous interactions of physiological mechanisms regulating the cardiovascular system could underlie the variability of morphology. We used the unsupervised manifold learning algorithm, Dynamic Diffusion Map, to quantify the multivariate waveform morphological variation. Due to the physical principle of light absorption, PPG waveform signals are more susceptible to artifact and are nominally used only for visual inspection of data quality in clinical medical environment. But on the other hand, the noninvasive, easy-to-use nature of PPG grants a wider range of biomedical application, which inspired us to investigate the variability of morphology information from PPG waveform signal. We developed data analysis techniques to improve the performance and validated with the real-life clinical database

Purple urine bag syndrome in nursing homes: Ten elderly case reports and a literature review

Purple urine bag syndrome (PUBS) is a rare occurrence, in which the patient has a purple-colored urine bag following urinary catheterization for hours to days. Most of authors believe it is a mixture of indigo (blue) and indirubin (red) that becomes purple. Previous study showed that PUBS occurred predominantly in chronically catheterized, constipated women. We collected 10 elderly patients with PUBS in two nursing homes. The first two cases were identified by chart review in 1987 and 2003, and then later eight cases (42.1%) were collected among 19 urinary catheterized elderly in the period between January 2007 and June 2007. In the present report, PUBS probably can occur in any patients with the right elements, namely urinary tract infection (UTI) with bacteria possessing these enzymes, diet with enough tryptophan, and being catheterized. Associations with bed-bound state, Alzheimer’s, or dementia from other causes are reflections of the state of such patients who are at higher risk for UTI, and hence PUBS occurred. Although we presented PUBS as a harmless problem, prevention and control of the nosocomial catheter-associated UTIs (CAUTIs) has become very important in the new patient-centered medical era. Thus, we should decrease the duration of catheterization, improve catheter care, and deploy technological advances designed for prevention, especially in the elderly cared for in nursing homes

A Shallow Ritz Method for Elliptic Problems with Singular Sources

In this paper, a shallow Ritz-type neural network for solving elliptic equations with delta function singular sources on an interface is developed. There are three novel features in the present work; namely, (i) the delta function singularity is naturally removed, (ii) level set function is introduced as a feature input, (iii) it is completely shallow, comprising only one hidden layer. We first introduce the energy functional of the problem and then transform the contribution of singular sources to a regular surface integral along the interface. In such a way, the delta function singularity can be naturally removed without introducing a discrete one that is commonly used in traditional regularization methods, such as the well-known immersed boundary method. The original problem is then reformulated as a minimization problem. We propose a shallow Ritz-type neural network with one hidden layer to approximate the global minimizer of the energy functional. As a result, the network is trained by minimizing the loss function that is a discrete version of the energy. In addition, we include the level set function of the interface as a feature input of the network and find that it significantly improves the training efficiency and accuracy. We perform a series of numerical tests to show the accuracy of the present method and its capability for problems in irregular domains and higher dimensions