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A variety of genetic techniques have been devised to determine cell lineage relationships during tissue development. Some of these systems monitor cell lineages spatially and/or temporally without regard to gene expression by the cells, whereas others correlate gene expression with the lineage under study. The GAL4 Technique for Real-time and Clonal Expression (G-TRACE) system allows for rapid, fluorescent protein-based visualization of both current and past GAL4 expression patterns and is therefore amenable to genome-wide expression-based lineage screens. Here we describe the results from such a screen, performed by undergraduate students of the University of California, Los Angeles (UCLA) Undergraduate Research Consortium for Functional Genomics (URCFG) and high school summer scholars as part of a discovery-based education program. The results of the screen, which reveal novel expression-based lineage patterns within the brain, the imaginal disc epithelia, and the hematopoietic lymph gland, have been compiled into the G-TRACE Expression Database (GED), an online resource for use by the Drosophila research community. The impact of this discovery-based research experience on student learning gains was assessed independently and shown to be greater than that of similar programs conducted elsewhere. Furthermore, students participating in the URCFG showed considerably higher STEM retention rates than UCLA STEM students that did not participate in the URCFG, as well as STEM students nationwide.

Objective - Let's look into the sustainable entrepreneurial goals of university students in Can Tho, Vietnam, as well as the roles that demographic factors like gender, age, occupation, and marital status played in the process. Methodology/Technique - In addition, the study investigates how factors such as the current school year, school entrepreneurship training, family generation, field of study, and family business might affect a person's sustainable entrepreneurial intentions. The information needed for this research came from the participation of 284 student respondents who were enrolled in a variety of institutions in Can Tho, Vietnam. Finding - The study used t-tests and ANOVA to examine relationships between demographic factors (gender, age, occupation, and marriage) and current school year, school entrepreneurship training, family generation, field of study, and family business in relation to sustainable entrepreneurial intentions. Researchers were particularly interested in determining whether or not there was a link between these criteria and the ambition to maintain a viable business venture. According to the findings, the field of study and the current school year have a significant bearing on the students' plans to engage in environmentally responsible business. Novelty - These results contribute to our understanding of the demographic factors that play a role in determining the degree to which students attending institutions in Can Tho, Vietnam, have an interest in launching their own companies. These results may provide information useful to policymakers, educators, and other stakeholders in establishing targeted interventions and support systems to encourage sustainable entrepreneurship among students in the area. [ABSTRACT FROM AUTHOR]

Advancements in machine learning in general and in deep learning in particular have achieved great success in numerous fields. For personalized medicine approaches, frameworks derived from learning algorithms play an important role in supporting scientists to investigate and explore novel data sources such as metagenomic data to develop and examine methodologies to improve human healthcare. Some challenges when processing this data type include its very high dimensionality and the complexity of diseases. Metagenomic data that include gene families often have millions of features. This leads to a further increase of complexity in processing and requires a huge amount of time for computation. In this study, we propose a method combining feature selection using perceptron weight-based filters and synthetic image generation to leverage deep-learning advancements in order to predict various diseases based on gene family abundance data. An experiment was conducted using gene family datasets of five diseases, i.e. liver cirrhosis, obesity, inflammatory bowel diseases, type 2 diabetes, and colorectal cancer. The proposed method provides not only visualization for gene family abundance data but also achieved a promising performance level. [ABSTRACT FROM AUTHOR]

The present study contributes to the literature on the consequences of social inequality through a qualitative examination of the social functions and meanings of violence in the lives of 20 marginalized women. All of the women in the sample were at some point court involved and were victims, as well as perpetrators, of violence. Findings indicate a need to expand the extant theory to address enforcement (i.e., strengthening) of status level, social inequities (e.g., gendered power disparities), adding to the accommodation/resistance paradigm. Consistent with scholarship conceptualizing violence as contextual and gender as a socio-structural variable, results support the need to better understand the ways in which contexts of gendered inequality – and inequality in general – may promote processes through which survivors of violence accommodate, resist, and enforce oppression. Implications for research and practice related to social inequality are discussed. [ABSTRACT FROM AUTHOR]

This paper focuses on the valorizationof calcium carbonate-basedsolid wastes for the removal of hydrogen sulfide from gas phase. Twosolid wastes taken from industrial sites for the production of sodiumcarbonate and sodium bicarbonate by the Solvay process were analyzedby different physicochemical methods. Calcium carbonate was foundas the main component of both solid wastes. Trace amounts of otherelements such as Mg, Al, Fe, Si, Cl, Na, etc. were also present inthese wastes. These solid wastes showed higher sorption activity forthe removal of H2S, compared to a pure commercial calciumcarbonate. The contact time was found as an important parameter forthe complete H2S uptake. The addition of well-dispersediron-based particles could be carried out by the standard incipientwetness impregnation method. Sorbent containing 1 wt % of spiked ironhad the similar sorption behavior compared to a commercial activatedcarbon, in terms of reactivity and reactivation possibility. [ABSTRACT FROM AUTHOR]

Abstract Impaired hearing and cognition are disabling conditions among older adults. Research has presented inconsistent conclusions regarding hearing impairment posing a risk for cognitive impairment. We aimed to assess this from published evidence via searching PubMed and Embase, from the inception of the databases indexed to December 2, 2016. For those high-quality studies retrieved, relative risk (RR) and 95% confidence intervals (CIs) were combined to estimate the risk of cognitive impairment. Eleven cohort studies were included in the present study. Pooled results found that elderly people with disabled peripheral and central hearing function had a higher risk of cognitive impairment (for moderate/severe peripheral hearing impairment: RR = 1.29, 95% CI: 1.04–1.59 during a follow-up ≤6 years. RR = 1.57, 95% CI: 1.13–2.20 during a follow-up >6 years; for severe central hearing impairment, RR = 3.21, 95% CI: 1.19–8.69) compared to those with normal hearing function. We also recorded a dose-response trend for cognitive impairment as hearing thresholds rose. No evident bias from potential confounding factors was found with one exception: the length for clinical follow-up. Although results are preliminary because qualifying studies were few, statistical findings were consistent with older people identified as having greater levels of hearing loss, having a corresponding higher risk of cognitive impairment.

This article reports on responses from an online survey designed to explore the before, during and after lockdown experiences of higher education teacher educators in Vietnam (n = 145) who were required to use digital technologies and pedagogies exclusively in their teaching during the 2020/21 lockdown. The data is interpreted using the TPACK framework (Koehler & Mishra, 2009) which enables analysis of the participants' technological, pedagogical and content knowledge in relation to teaching online using digital tools. The findings indicate mixed responses and experiences of teacher educators during this period with many having struggled with new technologies and unfamiliar pedagogical strategies whilst others enjoyed the opportunity to develop new approaches to their teaching. The paper concludes with key recommendations for best practice in this sector going forward post pandemic including the development of national and institutional e-learning policies, improvements in IT infrastructure and increased provision of professional training. [ABSTRACT FROM AUTHOR]