Industrial pollutants are a major contributor to urban air pollution, negatively impacting environmental sustainability and public health. To address this challenge, we propose a novel LSTM-Random Forest-Based Industrial Emission Control System that integrates the sequential modeling capabilities of LSTM networks with the robust interaction analysis of Random Forest algorithms. The system collects real-time data on key pollutants such as PM_2.5 , NO_2 , and CO, along with climatic variables including weather conditions, temperature, wind speed, humidity, and pressure, via IoT sensors positioned near industrial sources. The LSTM model forecasts emission patterns over both short and long-term horizons by capturing temporal dependencies in the data, while the Random Forest algorithm enhances prediction accuracy by incorporating contextual factors like industrial activity levels and weather conditions. Experimental evaluations demonstrate that our hybrid approach achieves more accurate and reliable forecasts than traditional methods, enabling dynamic adjustments in industrial operations to optimize production, activate emission control systems, and ensure regulatory compliance. This integrated strategy not only offers a flexible framework for reducing industrial emissions and promoting sustainable practices but also lays the groundwork for future enhancements such as comparisons with state-of-the-art models and the adoption of edge computing for real-time decision-making.
Introduction and Objective: Youth with type 1 diabetes (T1D) require consistent glycemic monitoring and insulin administration during the school day. However, the national shortage of school nurses creates a gap in diabetes care in youth with T1D during school hours.1,2 Telehealth-based interventions have been shown to improve clinical outcomes in youth with T1D.3-6 Avel eCare School Health (eCare) is a telemedicine service that provides access to virtual school nurses who assist with required care plans, glucose monitoring, and insulin dosing. The objective of this study was to evaluate the effectiveness of the eCare program on HbA1c and diabetes management in students with T1D. Methods: Youth aged 3-17 years with physician-diagnosed T1D, attending schools served by eCare, were included. Clinical outcomes included HbA1c values and parent-reported diabetes management questionnaire (DMQ) scores obtained at program implementation, then every 4-6 months until the end of the study. Historical HbA1c values up to 18 months before implementation were obtained by medical record abstraction. Longitudinal mixed-effect models were conducted and adjusted for child’s age, maternal education, insurance status, and T1D duration. All statistical analyses were performed using SAS v9.4. Results: Fifty-four youth were included in the HbA1c analysis (~14 values/youth), and 47 child/parent pairs were included in the DMQ analysis (~5 collections/youth). On average, HbA1c decreased 0.9% after program implementation (β=0.90; 95% CI: 0.64-1.17), and this improvement was sustained over time. Participation in the eCare program improved parent-reported DMQ scores; each day the student participated, the parent's DMQ score increased (β=0.005; 95% CI: 0.001-0.009). Conclusion: This study supports the utilization of telehealth school nursing services to improve diabetes care and management among children with T1D and their parents. These services provide an alternative solution for rural or underserved schools to support their students with T1D. Disclosure M.G. Moulton: None. K. Ziegler: None. C.W. dos Reis: None. M.L. Bell: None. S. Freed: None. C. Hockett: None. Funding BreakthroughT1D and Helmsley Charitable Trust (3-SRA-2022-1106-S-B)
Background High rates of chronic kidney disease (CKD) are well recognised in Australia's Indigenous people, but kidney replacement therapy (KRT) registrations give an incomplete view of disease burden and outcomes. We describe profiles and outcomes of Indigenous people with preterminal CKD in the renal specialty practices of the public health system in the state of Queensland, through a prospective cohort study. Methods Adults patients with non-dialysis CKD from twelve public renal speciality services in Queensland were recruited to the CKD QLD Registry and followed until the start of KRT, renal death without KRT, or nonrenal death, or until the censor date of June 2020. Information on demographic and clinical features, hospital admissions and outcomes was compiled from data collected by Queensland Health. Results 7,595 CKD patients were enrolled. 641 (8.4%) were Indigenous, more than twice their proportion in Queensland's population They lived more remotely than non-Indigenous patients, were more disadvantaged, were younger, more often female and more often had diabetes and had 35.3% greater hospital costs. They were 50% more likely to develop end stage kidney failure (ESKF), and when they did, more than twice as likely as nonIndigenous patients to start KRT, a function of their younger age. Notably, however, half of the Indigenous and 72% of the non-Indigenous patients with endpoints did not start KRT. The estimated 4.7-fold increase in incident KRT in Indigenous patients aligns well with official statistics. Conclusions Routinely collected service data reveal a more expansive view of CKD and its outcomes in Indigenous patients under renal specialty care in Queensland. Such surveillance can inform health services planning for CKD patients beyond expectations of KRT needs and can underpin ongoing evaluations.
Introducing the renewable poly(trimethylene ether glycol) (PO3G) as soft segments into bio-based poly(propylene terephthalate) (PTT), which is synthesized from the bio-based propylene glycol (PDO) monomer, results in thermoplastic polyester elastomers (PTT-PO3G) with superior thermomechanical properties. As the PO3G content in PTT-PO3G copolymers increased from 20 wt% to 60 wt%, the melting temperatures of these copolymers decreased from 220 to 174 degrees C, and the tensile strength decreased from 31.7 to 4.2 MPa with the Shore hardness falling from 60 to 26 D, whereas the elongation at break showed an increase tendency from 697 % to 1074 %. Characterizations utilizing dynamic thermomechanical analysis (DMA), small angle X-ray scattering (SAXS), and atomic force microscopy (AFM) revealed the presence of microphase separations in PTT-PO3G copolymers. The strength and moisture regain of PTT-PO3G-20 elastic fibers fabricated via an eco-friendly melt spinning technique reach 1.42 cN/dtex and 1.52 %, which are 58 % and 407 % higher than those of traditional wet-spun Spandex (R) fibers, respectively. Surprisedly, the resilience of PTT-PO3G-20 fibers exceeded 96 % at an elongation of 20 %, demonstrating its promising potential as a sustainable alternative to Spandex (R) fibers in textile applications. The excellent thermodynamic properties indicate that the bio-based PTT-PO3G copolymers have great potential to replace traditional petroleum-based elastomers for promoting the sustainable and low-carbon global development.
