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"Joel, Linda"
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Evaluation of Waste Plastic Pyrolysis Oil Performance with Diethyl Ether Additive on Insulated Piston Diesel Engine
Considering the amount of waste plastics has risen significantly, energy may be extracted from it. Not only is it possible to dispose of waste plastics by converting them to fuel, but it is also possible to extract energy from them. Our research is motivated by the prospect of using waste plastics as a source of energy through waste plastic pyrolysis oil (WPPO). The innovation of this research is that it will assess the efficiency of plastic pyrolysis oil derived from Low-Density Polyethylene (LDPE) on a Thermal Barrier Coated (TBC) piston engine. The incremental ratio of WPPO to pure diesel with the addition of diethyl ether (DEE) was determined and its output and exhaust emission standards were evaluated using a direct injection single cylinder low heat rejection diesel engine. The results for the WPPO blends were promising as with TBCW20DEE10 demonstrating a 5 to 15% increase in carbon monoxide under different load conditions. TBCW20DEE10 confirmed a greater reduction of hydrocarbons varying from 5 to 12 %. At half load condition, TBCW20DEE10 emits approximately 3.5 % less unit of smoke.
Journal Article
Investigation of hydrogen peroxide and ethanol blends as sustainable energy for gasoline engine applications
The increasing demand for energy efficiency and environmental sustainability has driven extensive research into alternative fuels and emission reduction strategies for internal combustion engines. The use of fuel additives, such as hydrogen peroxide and ethanol blends, has emerged as a promising approach to enhance combustion and mitigate harmful emissions. This study investigates the effects of gasoline, ethanol-gasoline, and hydrogen peroxide-ethanol fuel blends on the performance and emissions of a spark-ignition engine across varying engine loads. By exploring the synergistic effects of fuel additives and optimizing engine operating parameters, this research aims to pave the way for reduced emissions, improved fuel efficiency, and a cleaner automotive industry, aligning with global efforts to mitigate the environmental impact of transportation. The results show that both ethanol and hydrogen peroxide significantly improve thermal efficiency, with the combination of both additives providing the highest efficiency gains. Fuel consumption is reduced with the introduction of these additives, particularly with the combined use of E10 and H₂O₂. Emission analysis reveals substantial reductions in carbon monoxide and hydrocarbon emissions, highlighting the environmental benefits of these additives. Contour plots are utilized to visualize and interpret the relationships between engine load, fuel composition, and emissions profiles.
Journal Article
Investigation and Optimization of Process Parameters of Abrasive Water Jet Cutting on C360 Brass Alloy through Design of Experiments
Many scientists concentrate on features of water jet cutting by researching various input parameters, abrasive mesh sizes to improve improved processing conditions without the expense. In this work, the treatment of abrasive water jet should be planned to ensure minimal surface roughness and maximum substrate removal. C360 brass alloy is considered to optimize the parameters for cutting including the abrasive feed, stand-off distance and nozzle speeds via the design of experiments supported with response surface methodology.
Journal Article
IPH2O: Island Parallel-Harris Hawks Optimizer-Based CLSTM for Stock Price Movement Prediction
Stock price movement forecasting is the process of predicting the future price of a financial and company stock from chaotic data. In recent years, many financial institutions and academics have shown interest in stock market forecasting. The accurate and successful predictions of the future price of stock yield a substantial profit. However, the current approaches are a major challenge due to the dynamic, chaotic, high-noise, non-linear, highly complex, and nonparametric characteristics of stock data. Furthermore, it is not sufficient to consider only the target firms' information because the stock prices of the target firms may be influenced by their related firms. Significant profits can be made by correct forecasting of stock prices, while poor forecasts can cause huge problems. Thus, we propose a novel Island Parallel-Harris Hawks Optimizer (IP-HHO)-optimized Convolutional Long Short Term Memory (ConvLSTM) with an autocorrelation model to predict stock price movement. Then, using the IP-HHO algorithm, the hyperparameters of ConvLSTM are optimized to minimize the Mean Absolute Percentage Error (MAPE). Four different types of financial time series datasets are utilized to validate the performance of the evaluation measures such as root mean square error, MAPE, Index of Agreement, accuracy, and F1 score. The results show that the IP-HHO-optimized ConvLSTM model outperforms others by improving the prediction rate accuracy and effectively minimizing the MAPE rate by 19.62%.
Journal Article
Novel Mutations in the Voltage-Gated Sodium Channel of Pyrethroid-Resistant Varroa destructor Populations from the Southeastern USA
The parasitic mite Varroa destructor has a significant worldwide impact on bee colony health. In the absence of control measures, parasitized colonies invariably collapse within 3 years. The synthetic pyrethroids tau-fluvalinate and flumethrin have proven very effective at managing this mite within apiaries, but intensive control programs based mainly on one active ingredient have led to many reports of pyrethroid resistance. In Europe, a modification of leucine to valine at position 925 (L925V) of the V. destructor voltage-gated sodium channel was correlated with resistance, the mutation being found at high frequency exclusively in hives with a recent history of pyrethroid treatment. Here, we identify two novel mutations, L925M and L925I, in tau-fluvalinate resistant V. destructor collected at seven sites across Florida and Georgia in the Southeastern region of the USA. Using a multiplexed TaqMan® allelic discrimination assay, these mutations were found to be present in 98% of the mites surviving tau-fluvalinate treatment. The mutations were also found in 45% of the non-treated mites, suggesting a high potential for resistance evolution if selection pressure is applied. The results from a more extensive monitoring programme, using the Taqman® assay described here, would clearly help beekeepers with their decision making as to when to include or exclude pyrethroid control products and thereby facilitate more effective mite management programmes.
Journal Article
Policy Challenges in Modern Health Care
Health care delivery in the United States is an enormously complex enterprise, and its $1.6 trillion annual expenditures involve a host of competing interests. While arguably the nation offers among the most technologically advanced medical care in the world, the American system consistently under performs relative to its resources. Gaps in financing and service delivery pose major barriers to improving health, reducing disparities, achieving universal insurance coverage, enhancing quality, controlling costs, and meeting the needs of patients and families. Bringing together twenty-five of the nation's leading experts in health care policy and public health, this book provides a much-needed perspective on how our health care system evolved, why we face the challenges that we do, and why reform is so difficult to achieve. The essays tackle tough issues including: socioeconomic disadvantage, tobacco, obesity, gun violence, insurance gaps, the rationing of services, the power of special interests, medical errors, and the nursing shortage.
eBook
Neighborhood environment and incident diabetes, a neighborhood environment-wide association study (‘NE-WAS’): Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)
The prevalence of type 2 diabetes is increasing among the Hispanic/Latino population. Type 2 diabetes incidence rates vary between neighborhoods, but no single aspect of the neighborhood environment is known to cause type 2 diabetes. Using data from the Hispanic Community Health Study/Study of Latinos cohort of 16,415 Hispanic/Latino adults in four major US cities, we conducted a neighborhood environment-wide association study to identify neighborhood measures or clusters of measures associated with diabetes incidence. Two-hundred and four neighborhood measures were calculated at the census tract level or within a 1-km buffer of participants’ residential addresses. Independent covariate-adjusted and survey-weighted Poisson regressions were run for each neighborhood measure and incident diabetes. Principal component analysis of neighborhood measures was conducted to reduce dimensionality. No coherent pattern of neighborhood measures or principal component scores were associated with diabetes incidence within the cohort, though established individual-level risk factors such as age and family history were strongly associated with diabetes incidence. Results from our analysis did not indicate specific neighborhood measures, clusters, or patterns. Individual, rather than neighborhood, factors distinguish incident diabetes cases from non-cases.
Journal Article
Cigarette Smoking Decreases Global MicroRNA Expression in Human Alveolar Macrophages
Human alveolar macrophages are critical components of the innate immune system. Cigarette smoking-induced changes in alveolar macrophage gene expression are linked to reduced resistance to pulmonary infections and to the development of emphysema/COPD. We hypothesized that microRNAs (miRNAs) could control, in part, the unique messenger RNA (mRNA) expression profiles found in alveolar macrophages of cigarette smokers. Activation of macrophages with different stimuli in vitro leads to a diverse range of M1 (inflammatory) and M2 (anti-inflammatory) polarized phenotypes that are thought to mimic activated macrophages in distinct tissue environments. Microarray mRNA data indicated that smoking promoted an \"inverse\" M1 mRNA expression program, defined by decreased expression of M1-induced transcripts and increased expression of M1-repressed transcripts with few changes in M2-regulated transcripts. RT-PCR arrays identified altered expression of many miRNAs in alveolar macrophages of smokers and a decrease in global miRNA abundance. Stratification of human subjects suggested that the magnitude of the global decrease in miRNA abundance was associated with smoking history. We found that many of the miRNAs with reduced expression in alveolar macrophages of smokers were predicted to target mRNAs upregulated in alveolar macrophages of smokers. For example, miR-452 is predicted to target the transcript encoding MMP12, an important effector of smoking-related diseases. Experimental antagonism of miR-452 in differentiated monocytic cells resulted in increased expression of MMP12. The comprehensive mRNA and miRNA expression profiles described here provide insight into gene expression regulation that may underlie the adverse effects cigarette smoking has on alveolar macrophages.
Journal Article
High-fat feeding promotes obesity via insulin receptor/PI3K-dependent inhibition of SF-1 VMH neurons
The authors report that insulin activates PI3K signaling in SF-1–expressing neurons of the ventromedial hypothalamus to regulate their firing frequency. Mice with insulin receptor deficiency in these neurons show protection from the metabolic effects of exposure to high-fat diet.
Steroidogenic factor 1 (SF-1)-expressing neurons of the ventromedial hypothalamus (VMH) control energy homeostasis, but the role of insulin action in these cells remains undefined. We show that insulin activates phosphatidylinositol-3-OH kinase (PI3K) signaling in SF-1 neurons and reduces firing frequency in these cells through activation of K
ATP
channels. These effects were abrogated in mice with insulin receptor deficiency restricted to SF-1 neurons (SF-1
ΔIR
mice). Whereas body weight and glucose homeostasis remained the same in SF-1
ΔIR
mice as in controls under a normal chow diet, they were protected from diet-induced leptin resistance, weight gain, adiposity and impaired glucose tolerance. High-fat feeding activated PI3K signaling in SF-1 neurons of control mice, and this response was attenuated in the VMH of SF-1
ΔIR
mice. Mimicking diet-induced overactivation of PI3K signaling by disruption of the phosphatidylinositol-3,4,5-trisphosphate phosphatase PTEN led to increased body weight and hyperphagia under a normal chow diet. Collectively, our experiments reveal that high-fat diet–induced, insulin-dependent PI3K activation in VMH neurons contributes to obesity development.
Journal Article