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Sprouts are popular due to their high nutritional content, including vitamins, minerals, antioxidants, and enzymes. However, the conditions favorable for sprouting, such as warm and humid environments, are also ideal for the growth of bacteria, including food‐borne pathogens. Here, we analyzed the growth and developed predictive models of locally isolated and commercial strains of Salmonella enterica and Listeria monocytogenes in alfalfa sprouts under various constant temperatures, ranging from 5°C to 25°C. Our findings indicated that these pathogens could grow at 5°C in sprouts, albeit with a low growth rate. A rapid increase in concentration occurred at temperatures of 10°C and above. The fitted models demonstrated high performance, with R2 values ranging from 0.964 to 0.997 and RMSE values ranging from 0.15 to 0.51, respectively. Based on the fitted values, bias factor (Af) values varied between 1.01 and 1.06, with all accuracy factor (Bf) values at 1.00. Acceptable prediction zone (APZ) values ranged from 81.8% to 100%. Validation of the models under dynamic temperature conditions for specific strains showed acceptable performance. This study enhances our understanding of S. enterica and L. monocytogenes growth in alfalfa sprouts. The findings of this study could be used to improve the risk assessment of these pathogens in alfalfa sprouts. [ABSTRACT FROM AUTHOR]

A method based on an iterative Fourier-transform algorithm (IFTA) with phase optimization for phase-only multilevel diffractive optical elements (DOEs) is presented. Phase optimization by minimizing the mean-squared error composed of an amplitude-weighted probability-density function is performed in the IFTA iterations to ensure that the wavefront difference is minimized and thus to improve the DOEs' performance. Using the proposed method, we obtained a small standard deviation of diffraction efficiency of 20 uneven-phase DOEs, showing that DOEs with high diffraction efficiency did not vary significantly with the initial conditions. The simulation results of even- and uneven-phase four-level DOEs designed by use of direct and stepwise quantization IFTA methods are compared. OCIS codes: 050.1970, 050.1380.

With the growth of big data and open data in recent years, the importance of data anonymization is increasing. Original data need to be anonymized to prevent personal identification from being revealed before being released to the public. There is a growing variety of de-identification methods which have been proposed to reduce the privacy issues, however, there is still much to be improved. The purpose of this study is to demonstrate the possibilities of re-identification from masked data, and to compare the pros and cons of different de-identification methods. A set of electronic toll collection data from Taiwan was used and we successfully re-identified vehicles with specific patterns. Four de-identification methods were performed and finally we compared the strengths and weaknesses of these methods and evaluated their appropriateness. [ABSTRACT FROM AUTHOR]

This integrative literature review evaluates the effectiveness of power toothbrushes (PTBs) compared to manual toothbrushes (MTBs) across various populations, focusing on plaque removal, gingival health, calculus reduction, and stain removal. PTBs equipped with advanced technologies such as oscillating-rotating and high-frequency sonic mechanisms have been examined for their potential to enhance oral hygiene. Special attention is given to vulnerable groups, including the elderly and individuals with intellectual disabilities, to assess how PTBs meet their specific oral health needs. A comprehensive literature search was conducted in databases including PubMed, Cochrane Library, Embase, and Google Scholar using keywords such as "power toothbrush", "electric toothbrush", "manual toothbrush", "plaque removal", "gingivitis", "calculus", "dental stains", "oral hygiene", "elderly", and "intellectual disabilities". Studies published between 2000 and 2024 were selected based on their relevance to the PTB and MTB comparison, with an emphasis on outcomes related to oral hygiene efficacy. As this review is narrative rather than systematic, it focuses on synthesizing existing knowledge without applying strict inclusion or exclusion criteria. The results indicate that PTBs generally outperform MTBs in reducing plaque, gingivitis, and stains, though the benefits for special populations are less pronounced but still significant. However, practical issues such as user experience and mechanical reliability of PTBs warrant further investigation. In conclusion, this review enhances the understanding of PTB effectiveness, guides consumer choices, and informs future technological advancements in dental care practices., Competing Interests: The authors declare no competing interests., (© 2024 Yeh et al.)

Almost of HIV/AIDS cases in Taiwan occur in the age range of 20 to 29 yrs. Many of the reported cases are in the college-age and infection might have occurred through unprotected sexual behaviors. This study was to identify the effectiveness of a video-based intervention has important implications for health provider to plan evidence-based address the specific needs of college students.The research design of this study was based on TranstheoreticalModel (TTM). In addition, through an experimental design with groups: (i) to evaluate the effectiveness of a video-based intervention on the TTM stages of change,condom use self-efficacy, perceived benefits of and barriers to condom use by Taiwanese college students and (ii) to explore the factors affecting the TTM constructs for condom use. Overall, students have higher score in the pretest HIV knowledge scale, pretest self-efficacy scale and perceived benefits scale than the posttest. The score in perceived barriers scale of condom use also reduced after receiving intervention. This result shows that the videos and health education intervention can be effective in changing the college's intention to use condoms.

Passing the national licensure examination for registered nurses (NCLEX-RN) in the US is a critical outcome of the nursing program. Research has been conducted to identify which nursing students are at risk for not passing the NCLEX-RN test. The purpose of this study was to investigate whether any of several student covariates can be used to accurately identify associate in science in nursing (ASN) students that are at-risk for failing the NCLEX-RN test. Covariates included in the study were demographics, students' pre-admission grade point average (GPA), the scores of test of essential skills (TEAS), and the assessment technologies institute® (ATI)'s comprehensive scores for a pre-RN examination test. Chi-squared automatic interaction detection, or CHAID analysis, was used to develop the model. One covariate, ATI comprehensive test scores, was found to accurately identify all at-risk ASN students. The model explained that students identified as "at-risk" had a failure rate nearly two-and-a-half times as high as the general population.