Education and Women in the Informal Sector: A Cross-Country Analysis

This study investigates the effects of education on the participation of women in the informal sector of 40 developing countries using OLS linear regression. Through some econometric adjustments, the final model suggests that education, represented by years of schooling, is correlated with a 2.74% increase in women’s chances of being employed in this sub-sector of the economy. This means that the better educated still end up doing the jobs that do not require such knowledge. An implication of the result is that the current way which schooling is delivered to the poor might not be the most efficient way

Cotton farming and N cycling : adaptation to climate change

Climate models have projected the atmospheric carbon dioxide (CO2) concentration will double and a 1.1-6.4oC rise in global average temperature by the end of 21st century. Simultaneously, extreme weather events including flooding and drought have been predicted to increase in frequency and intensity. Such changes are expected to have profound effects on agriculture. Soil nitrogen (N) cycling, particularly nitrification and denitrification plays an important role in the availability of N in soils for plant uptake, and hence changes in these processes due to global change may considerably influence crop productivity. These N processes are microbially driven and little is known about the role of soil microorganisms in regulating the process rates and how they respond to environmental disturbances. Therefore, my study aimed to elucidate the responses of soil nitrification to climate change and extreme weather events, and subsequent consequences for crop yields, by using cotton as a model system. Additionally, the legacy effects of extreme weather events and the impacts of added N-fertilizer on soil N, C processes and microbial communities and the subsequent consequences for crop productivity were examined. First effects of waterlogging on soil nitrification and nitrifying community in cotton farming were examined. This study was a field-based experiment conducted at the Australian Cotton Research Institute (ACRI) in Narrabri, NSW. Waterlogging events simulated by running furrow irrigation for 120 hours were applied at the early and late flowering stages, respectively. Waterlogging had strong effects on soil moisture, pH, potential nitrification rate (PNR) and soil nitrate (NO3-) concentration. The abundance of ammonia-oxidizing bacteria (AOB) decreased approximately 10-fold whereas that of ammonia-oxidizing archaea (AOA) decreased about 2-fold after waterlogging. Shifts in AOB and AOA community structures were also observed after waterlogging. Significant correlations between both AOB and AOA communities and PNR were observed; however, AOB was more strongly correlated to PNR than AOA. Significant linear negative correlations between soil moisture and ammonia-oxidizing communities and PNR were also obtained. These results indicate that waterlogging impacted on soil physicochemical properties, resulting in changes in ammonia-oxidizing communities and nitrification activity. In the second chapter, the effects of elevated temperature (+1.1oC) alone and elevated temperature in combination with elevated CO2 (550 ppm) on soil nitrification and nitrifying communities in cotton farming were investigated using field-based environmentally-controlled chambers. This study was conducted at ACRI in Narrabri, NSW. Elevated temperature did not affect soil PNR and AOB community abundance and structure. The AOA community responded significantly to elevated temperatures by increasing its abundance and shifting their community structure. Combined elevated CO2 and temperature significantly increased both AOB and AOA abundance, and resulted in shifts in AOB and AOA community structures. Both AOB and AOA communities were significantly correlated with PNR, although AOA exhibited a weaker relationship with PNR than AOB. Effects of climate factors on soil nitrification and nitrifying community depended on the stage of cotton growth since treatment effects were only observed when cotton reached the early flowering stage. Thirdly, the responses of soil N processes (nitrification, denitrification, and N mineralization), functional microbial communities, crop growth and productivity to different N fertilizer regimes (0, 100, 200 and 300 kg N/ha) after exposure to waterlogging and prolonged-drought were investigated by conducting a glass-house experiment at Western Sydney University (WSU). Prolonged-drought prior to cotton planting established a strong legacy effect on soil N processes, ammonia-oxidizing communities, nosZ-containing community, plant growth and productivity. N fertilizer application up to 300 kg N/ha could not counteract the legacy effect of prolonged drought on soils and plants although N supply improved soil fertility. These results suggest that the depleted functional microbial communities may take a long time to recover after drought. Waterlogging prior to planting had a legacy effect on soil NO3- content and the nosZ-containing community. The legacy effect of waterlogging on soil NO3- was diminished completely by N addition. Despite an increase in nosZ gene abundance due to waterlogging before sowing, soil N availability and crop growth and productivity was not impacted. However, N loss from the plant-soil system can be significant if further waterlogging occurs, thereby potentially affecting crop yields. Finally, the responses of the soil bacterial community and microbial respiration to legacy effects of waterlogging and prolonged-drought, and N fertilizer addition were also examined. This experiment was carried out to examine links between N and C cycling in farming systems. Prolonged-drought prior to planting generated a strong legacy effect on soil bacterial abundance, diversity, and composition, and microbial respiration rates. N fertilizer supply increased soil bacterial abundance and diversity, and altered bacterial community composition. However, N fertilizer application up to 300 kg N/ha could not counteract the legacy effects of prolonged-drought on the soil bacterial community. Additionally, different bacterial phyla responded differently to the legacy effects of prolonged-drought and N supply. In contrast to prolonged-drought, waterlogging did not establish a legacy effect on the soil bacterial community and microbial respiration. This suggests that the soil bacterial community might be resistant to waterlogging or recover completely upon water stress. N fertilizer supply inhibited soil microbial respiration by inhibiting C-degraded enzyme activities. Some weak but significant correlations between soil total bacterial community and microbial respiration were observed; however, addition of N fertilizer weakened these relationships further. Overall, my study provides novel evidence of soil N cycling responses to climate change and extreme weather events in cotton farming systems. My study is the first to demonstrate a legacy effect from extreme weather events and external N supply on soil N and C processes, and subsequent consequences on crop productivity. Data obtained in this study will support the development of robust predictive models and adaptation strategies to sustain crop yields under future climatic conditions via effective N management

An Empirical Analysis of the Relationship among Social Institutions and Juvenile Arrests in Virginia

The United States has unusually high rates of violence among developed nations, including the victimization of and perpetration by youth. Using Institutional Anomie Theory (IAT) as the theoretical framework, this study analyzes the relationships between social institutions and crime and the interactive relationships among the institutions in a sample of Virginia localities. Multivariate analyses are conducted to produce additive and multiplicative models, and simple slope analyses are conducted to clarify interaction/moderation effects. Findings yield mixed support for IAT. Localities with higher levels of monthly welfare per recipient (a measure of polity) have lower juvenile violent crime arrest rates, and welfare moderates the relationship between income inequality and juvenile violent crime arrests. Controlling for all variables, no support was found for the direct effects of any other institution on juvenile violent crime arrests. Policy recommendations include maintenance of welfare programs and improvement of work participation supplementary programs

Impact of a Geriatric and Palliative Medicine Clerkship on Knowledge and Attitudes about End-Of-Life Care

Previous interventions of students and residents suggest that those which employ patient encounters increases attitude towards end-of-life care and performance on a palliative care knowledge examination, but those studies did not include geriatric preceptors. From a population of third-year medical students, the researcher surveyed attitudes and tested knowledge before and after a combined geriatric and palliative clerkship to determine the impact on these outcomes and if there were any differences among the preceptor or the clinical site. After the rotation, students’ perceptions of the importance that medical students learn about how to care for dying patients of resident and attending physicians increased from 77.5% to 89.6% (p <0.001) and 87.4% to 92.9% (p = 0.001) respectively. More students agreed that physicians have a responsibility to provide bereavement care (p < 0.001) and that depression is treatable among patients with terminal illness (p = 0.017). More students disagreed that they dread having to tell patients the truth about a terminal prognosis and still maintain hope (p = 0.003), that caring for dying patients is depressing (p < 0.001), and that they feel guilty after a death (p <0.001). Test scores increased from a mean of 59.8% to 70.4% (p < 0.001). There were no differences in attitude or knowledge among the preceptors or clinical sites. This rotation was associated with an increase in attitudes and knowledge regardless of the preceptor or clinical site. Results indicated that palliative educational programs should receive more institutional support to better prepare future physicians.Curriculum and Instruction, Department o

How Digital Natives Learn and Thrive in the Digital Age: Evidence from an Emerging Economy

As a generation of ‘digital natives,’ secondary students who were born from 2002 to 2010 have various approaches to acquiring digital knowledge. Digital literacy and resilience are crucial for them to navigate the digital world as much as the real world; however, these remain under-researched subjects, especially in developing countries. In Vietnam, the education system has put considerable effort into teaching students these skills to promote quality education as part of the United Nations-defined Sustainable Development Goal 4 (SDG4). This issue has proven especially salient amid the COVID−19 pandemic lockdowns, which had obliged most schools to switch to online forms of teaching. This study, which utilizes a dataset of 1061 Vietnamese students taken from the United Nations Educational, Scientific, and Cultural Organization (UNESCO)’s “Digital Kids Asia Pacific (DKAP)” project, employs Bayesian statistics to explore the relationship between the students’ background and their digital abilities. Results show that economic status and parents’ level of education are positively correlated with digital literacy. Students from urban schools have only a slightly higher level of digital literacy than their rural counterparts, suggesting that school location may not be a defining explanatory element in the variation of digital literacy and resilience among Vietnamese students. Students’ digital literacy and, especially resilience, also have associations with their gender. Moreover, as students are digitally literate, they are more likely to be digitally resilient. Following SDG4, i.e., Quality Education, it is advisable for schools, and especially parents, to seriously invest in creating a safe, educational environment to enhance digital literacy among students

Deep Transfer Learning: A Novel Collaborative Learning Model for Cyberattack Detection Systems in IoT Networks

Federated Learning (FL) has recently become an effective approach for cyberattack detection systems, especially in Internet-of-Things (IoT) networks. By distributing the learning process across IoT gateways, FL can improve learning efficiency, reduce communication overheads and enhance privacy for cyberattack detection systems. Challenges in implementation of FL in such systems include unavailability of labeled data and dissimilarity of data features in different IoT networks. In this paper, we propose a novel collaborative learning framework that leverages Transfer Learning (TL) to overcome these challenges. Particularly, we develop a novel collaborative learning approach that enables a target network with unlabeled data to effectively and quickly learn knowledge from a source network that possesses abundant labeled data. It is important that the state-of-the-art studies require the participated datasets of networks to have the same features, thus limiting the efficiency, flexibility as well as scalability of intrusion detection systems. However, our proposed framework can address these problems by exchanging the learning knowledge among various deep learning models, even when their datasets have different features. Extensive experiments on recent real-world cybersecurity datasets show that the proposed framework can improve more than 40% as compared to the state-of-the-art deep learning based approaches.Comment: 12 page

UIT-Saviors at MEDVQA-GI 2023: Improving Multimodal Learning with Image Enhancement for Gastrointestinal Visual Question Answering

In recent years, artificial intelligence has played an important role in medicine and disease diagnosis, with many applications to be mentioned, one of which is Medical Visual Question Answering (MedVQA). By combining computer vision and natural language processing, MedVQA systems can assist experts in extracting relevant information from medical image based on a given question and providing precise diagnostic answers. The ImageCLEFmed-MEDVQA-GI-2023 challenge carried out visual question answering task in the gastrointestinal domain, which includes gastroscopy and colonoscopy images. Our team approached Task 1 of the challenge by proposing a multimodal learning method with image enhancement to improve the VQA performance on gastrointestinal images. The multimodal architecture is set up with BERT encoder and different pre-trained vision models based on convolutional neural network (CNN) and Transformer architecture for features extraction from question and endoscopy image. The result of this study highlights the dominance of Transformer-based vision models over the CNNs and demonstrates the effectiveness of the image enhancement process, with six out of the eight vision models achieving better F1-Score. Our best method, which takes advantages of BERT+BEiT fusion and image enhancement, achieves up to 87.25% accuracy and 91.85% F1-Score on the development test set, while also producing good result on the private test set with accuracy of 82.01%.Comment: ImageCLEF2023 published version: https://ceur-ws.org/Vol-3497/paper-129.pd

On how religions could accidentally incite lies and violence: folktales as a cultural transmitter

Folklore has a critical role as a cultural transmitter, all the while being a socially accepted medium for the expressions of culturally contradicting wishes and conducts. In this study of Vietnamese folktales, through the use of Bayesian multilevel modeling and the Markov chain Monte Carlo technique, we offer empirical evidence for how the interplay between religious teachings (Confucianism, Buddhism, and Taoism) and deviant behaviors (lying and violence) could affect a folktale’s outcome. The findings indicate that characters who lie and/or commit violent acts tend to have bad endings, as intuition would dictate, but when they are associated with any of the above Three Teachings, the final endings may vary. Positive outcomes are seen in cases where characters associated with Confucianism lie and characters associated with Buddhism act violently. The results supplement the worldwide literature on discrepancies between folklore and real-life conduct, as well as on the contradictory human behaviors vis-à-vis religious teachings. Overall, the study highlights the complexity of human decision-making, especially beyond the folklore realm