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Disinfection byproducts of haloacetaldehydes disrupt hepatic lipid metabolism and induce lipotoxicity in high-fat culture conditions
Get PDFUnhealthy lifestyles, obesity, and environmental pollutants are strongly correlated with the development of nonalcoholic fatty liver disease (NAFLD). Haloacetaldehyde-associated disinfection byproducts (HAL-DBPs) at various multiples of concentrations found in finished drinking water together with high-fat (HF) were examined to gauge their mixed effects on hepatic lipid metabolism. Using new alternative methods (NAMs), studying effects in human cells in vitro for risk assessment, we investigated the combined effects of HF and HAL-DBPs on hepatic lipid metabolism and lipotoxicity in immortalized LO-2 human hepatocytes. Coexposure of HAL-DBPs at various multiples of environmental exposure levels with HF increased the levels of triglycerides, interfered with de novo lipogenesis, enhanced fatty acid oxidation, and inhibited the secretion of very low-density lipoproteins. Lipid accumulation caused by the coexposure of HAL-DBPs and HF also resulted in more severe lipotoxicity in these cells. Our results using an in vitro NAM-based method provide novel insights into metabolic reprogramming in hepatocytes due to coexposure of HF and HAL-DBPs and strongly suggest that the risk of NAFLD in sensitive populations due to HAL-DBPs and poor lifestyle deserves further investigation both with laboratory and epidemiological tools. We also discuss how results from our studies could be used in health risk assessments for HAL-DBPs
I reflect, therefore I am!:exploring the use of a voluntary online reflective journal as a learning tool among postgraduate dental students
Get PDFIntroduction: Reflection is widely used in all aspects of teaching and learning in dental education and makes a fundamental part of all learning activities for dental students. However, reflective tasks are often used with a clear purpose, for example in completing e-portfolios or dealing with critical incidences. This study explores the use of an optional online journal that Postgraduate (PG) dental students were encouraged to use as part of their own development. Aim: to explore how PG dental students perceive the use of optional online journals. Materials and Methods: data were collected via an anonymous questionnaire that included a word pool, Likert scale statements and free text comment sections (Appendix 1). Results: 31 students (93%) responded to the questionnaire with high focus on the usefulness of the journal showing 58% selecting “connecting with tutors” and 41% selecting “keeping track” of own learning and progress. The word “reflection” was selected by 87% of participants when describing the use of the journal. Some participants, 29%, considered the journal as “added pressure”, and 41% felt it was “extra work” as the journal, although voluntary, presented an added task to complete. All students made at least one entry on the online journal. Discussion and Conclusion: The use of an optional online journal can be a useful tool in establishing connection between dental students and their tutors. Some postgraduate dental students valued the benefits of reflective journal without it being linked to assessments. Some concerns were reported around the time constraints as well as the added work related to taking part in such activity
5G and beyond 5G technologies enabling Industry 5.0: network applications for robotics
Get PDFThe convergence of cloud and edge computing, along with distributed AI and the latest 5G/6G communications, is revolutionizing collaboration, connectivity, and interaction. These digital advancements pave the way for a new era of AI-powered robots, enabling them to navigate unfamiliar scenarios and adapt in the long term by seamlessly engaging with the digital realm. Consequently, these innovative applications generate diverse, continuous, and rapidly evolving data transmission requirements that traditional network resource management struggles to satisfy in terms of Quality of Service (QoS). In this paper, we take a step beyond focusing solely on network-side traffic engineering efforts. Instead, we explore the potential of application-side traffic shaping within non-public networks to address these demanding transmission needs. Within the framework of optimizing Quality of Experience, we discuss on how the 5G-ERA project focuses on a multi-domain learning process for autonomous robotics using an intent-based networking approach for optimized resource management within the network validated by the use cases within the project enabling the transition from Industry 4.0 to Industry 5.0. Our central aim is to efficiently control and direct data traffic within the confines of the private network, ensuring it aligns with predefined objectives. While this methodology can be applied in various contexts, it is essential to establish precise intentions rooted in domain expertise. This innovative approach serves as a valuable complement to conventional network resource management methods typically employed at the network infrastructure level.
Few-shot hyperspectral remote sensing image classification via an ensemble of meta-optimizers with update integration
Get PDFHyperspectral images (HSIs) with abundant spectra and high spatial resolution can satisfy the demand for the classification of adjacent homogeneous regions and accurately determine their specific land-cover classes. Due to the potentially large variance within the same class in hyperspectral images, classifying HSIs with limited training samples (i.e., few-shot HSI classification) has become especially difficult. To solve this issue without adding training costs, we propose an ensemble of meta-optimizers that were generated one by one through utilizing periodic annealing on the learning rate during the meta-training process. Such a combination of meta-learning and ensemble learning demonstrates a powerful ability to optimize the deep network on few-shot HSI training. In order to further improve the classification performance, we introduced a novel update integration process to determine the most appropriate update for network parameters during the model training process. Compared with popular human-designed optimizers (Adam, AdaGrad, RMSprop, SGD, etc.), our proposed model performed better in convergence speed, final loss value, overall accuracy, average accuracy, and Kappa coefficient on five HSI benchmarks in a few-shot learning setting
Exploring the impact of business analytics on strategic decision-making in uncertain environments
No full textBusiness analytics presents significant opportunities for enhancing strategic decision-making (SDM), yet a significant knowledge gap exists in our understanding of the interplay among environmental dynamism, business analytics use, environmental scanning, and rational and intuitive SDM. This paper aims to address this gap by leveraging the information processing view. Analyzing 218 survey responses using partial least squares (PLS) path modeling, the study underscores the influence of environmental dynamism on both business analytics use and environmental scanning. Furthermore, it reveals that while business analytics positively influences rational SDM, it exerts a negative effect on intuitive SDM. Additionally, environmental scanning partially mediates the link between business analytics use and rational SDM. Moreover, rational SDM exhibits a negative correlation with intuitive SDM. This study contributes to the literature by introducing a novel theoretical framework, enriching the information processing view, and deepening our understanding of how strategic information processing capabilities influence nonroutine and crucial SDM. Furthermore, it furnishes practical insights for organizations employing business analytics within dynamic contexts to enhance their SDM processes
Developing care experienced young peoples’ participation as peer researchers in an inter-disciplinary study: applying the ‘Ability-Motivation-Opportunity’ framework
Get PDFThere is a growing trend towards the use of participatory methods, within health and social care research and an increase in the inclusion of Peer Researchers in leaving care studies internationally. Whilst multiple benefits have been identified, they are not automatic and consideration also needs to be given to the complexities involved and how challenges might be mitigated. This paper focuses on the participation of care-experienced young people as Peer Researchers in an inter-disciplinary study examining how to sustain, scale and spread innovation to support young people’s transitions from care. It shares learning from a nested action research study that was co-developed to explore and support Peer Researchers’ contribution to and participation in the wider study. Key learning from the qualitative survey and focus groups centred on the discovery and application of the Ability-Motivation-Opportunity (‘A-M-O’) theoretical framework [Applebaum, E., Bailey, T., Berg, P., & Kalleberg, A. L. (2000). Manufacturing advantage: why high performance work systems pay off. ILR Press.] and its use to explore, analyse, reflect on and develop the Peer Researcher role. The application of A-M-O as an analytical and reflective tool offers a valuable and practical way to develop Peer Researchers’ contribution to and participation in and beyond health and social care research studies
Predictive modelling of Air Quality Index (AQI) across diverse cities and states of India using machine learning: investigating the influence of Punjab's stubble burning on AQI variability
Get PDFAir pollution is a common and serious problem nowadays and it cannot be ignored as it has harmful impacts on human health. To address this issue proactively, people should be aware of their surroundings, which means the environment where they survive. With this motive, this research has predicted the AQI based on different air pollutant concentrations in the atmosphere. The dataset used for this research has been taken from the official website of CPCB. The dataset has the air pollutant concentration from 22 different monitoring stations in different cities of Delhi, Haryana, and Punjab. This data is checked for null values and outliers. But, the most important thing to note is the correct understanding and imputation of such values rather than ignoring or doing wrong imputation. The time series data has been used in this research which is tested for stationarity using The Dickey-Fuller test. Further different ML models like CatBoost, XGBoost, Random Forest, SVM regressor, time series model SARIMAX, and deep learning model LSTM have been used to predict AQI. For the performance evaluation of different models, I used MSE, RMSE, MAE, and R2. It is observed that Random Forest performed better as compared to other models
Complete chloroplast genome characterization of three Plagiomnium species and the phylogeny of family Mniaceae
No full textThe taxonomic concepts and phylogenetic relations among genera of the family Mniaceae have given rise to much controversy in recent years, including Mnium, Plagiomnium, and Pohlia. Chloroplast genome study of these genera will be helpful to reflect the fact of this relationship. In this study, we sequenced three species in the Plagiomnium genus using an Illumina HiSeq 4000 platform. The complete chloroplast genomes of P. rostratum, P. succulentum and P. vesicatum were 125,196 bp, 124,689 bp, and 124,663 bp in length, which all contained a quadripartite structure including two copies of the invert repeats (IR, 10,120 bp, 9,818 bp, and 9,665 bp), one large single copy region (LSC, 86,395 bp, 86,299 bp, and 86,532 bp), and one single copy region (SSC, 18,561 bp, 18,754 bp, and 18,801 bp). The overall GC contents were 29.8%, 30.5%, and 30.5% respectively. The simple sequence repeats (SSRs) were detected in conjunction with Plagiomnium acutum, with variable sites genes observed: rpoC2, ycf1, and ycf2. Combined with the other three sequences published in Mniaceae, analyses of codon usage, repeats sequences, GC contents, and gene features revealed similarities among the seven species in Mniaceae. The trend of nucleotide diversity (Pi) in the seven complete chloroplast genomes showed Pi > 0.056: trnI-rpl23, petG-petL-psbE, trnK-chlB, trnG-trnR-atpA, rpoB-trnC-ycf66, ndhB, trnN-ndhF, and rps15-ycf1. We confirmed the phylogenetic relationships that Plagiomnium genus is a sister group with Mnium, while the Pohlia genus is not a monophyletic group. Phylogenetic analyses corroborated the monophyly of Mniaceae and supported the transfer of the Pohlia genus into Mniaceae
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