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Maryland is actively working towards doubling its Renewable Portfolio Standard (RPS) target, aiming to increase the share of renewable energy from 25% by 2020 to 50% by 2030. Furthermore, Maryland stands out as a state that strongly supports solar initiatives, offering incentives and
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Maryland is actively working towards doubling its Renewable Portfolio Standard (RPS) target, aiming to increase the share of renewable energy from 25% by 2020 to 50% by 2030. Furthermore, Maryland stands out as a state that strongly supports solar initiatives, offering incentives and specialized programs to assist residents in adopting solar energy solutions. The paper presents a multi-stage approach: Stage 1—Location Selection Process, Stage 2—Technical Feasibility Study, and Stage 3—Economical Feasibility Study. In Stage 1, the study focuses on three potential solar farm locations in Maryland: Westover, Princess Anne, and Eden. Stages 2 and 3 involve a feasibility assessment with detailed technical analysis using the NREL System Advisor Model (SAM) and PVWatts to determine monthly power to the grid and Energy Yield. Subsequently, economic feasibility is assessed using the NREL Clean Renewable Energy Estimation Simulation Tool (CREST), focusing on competitive levelized costs of energy (LCOE), payback time, and cumulative cash flows. Results indicate that all three locations exhibit promising solar irradiance levels, system outputs, and potential energy yields. Due to high solar irradiation, the Westover area has the highest energy yield at 1583.13 kWh/kW, while Princess Anne boasts the highest system output at 333.59 GWh. The economic evaluation suggests that all three locations become profitable within a two-year payback time, with competitive levelized costs of energy (LCOE). Westover emerges as the most cost-effective option at 5.99 cents/kWh, attributed to its higher solar irradiation values and energy yield compared to Princess Anne and Eden. Cumulative cash flows provide insights into long-term profitability, with Princess Anne, MD, having the highest Cumulative Cash Flow over 25 years at $183,383,304. By evaluating technical and economic aspects, this feasibility study offers quantitative insights to guide decision-making for the installation of Solar PV, considering both technological and economic feasibility.
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Speech separation, sometimes known as the “cocktail party problem”, is the process of separating individual speech signals from an audio mixture that includes ambient noises and several speakers. The goal is to extract the target speech in this complicated sound scenario and either
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Speech separation, sometimes known as the “cocktail party problem”, is the process of separating individual speech signals from an audio mixture that includes ambient noises and several speakers. The goal is to extract the target speech in this complicated sound scenario and either make it easier to understand or increase its quality so that it may be used in subsequent processing. Speech separation on overlapping audio data is important for many speech-processing tasks, including natural language processing, automatic speech recognition, and intelligent personal assistants. New speech separation algorithms are often built on a deep neural network (DNN) structure, which seeks to learn the complex relationship between the speech mixture and any specific speech source of interest. DNN-based speech separation algorithms outperform conventional statistics-based methods, although they typically need a lot of processing and/or a larger model size. This study presents a new end-to-end speech separation network called ESC-MASD-Net (effective speaker separation through convolutional multi-view attention and SuDoRM-RF network), which has relatively fewer model parameters compared with the state-of-the-art speech separation architectures. The network is partly inspired by the SuDoRM-RF++ network, which uses multiple time-resolution features with downsampling and resampling for effective speech separation. ESC-MASD-Net incorporates the multi-view attention and residual conformer modules into SuDoRM-RF++. Additionally, the U-Convolutional block in ESC-MASD-Net is refined with a conformer layer. Experiments conducted on the WHAM! dataset show that ESC-MASD-Net outperforms SuDoRM-RF++ significantly in the SI-SDRi metric. Furthermore, the use of the conformer layer has also improved the performance of ESC-MASD-Net.
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A proposed low-temperature forging method is presented to enhance stainless steel bearings by creating a martensitic subsurface layer, significantly boosting bearing fatigue life due to increased surface hardness. This technique induces beneficial residual stresses, particularly in axial bearings, streamlining their construction and improving
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A proposed low-temperature forging method is presented to enhance stainless steel bearings by creating a martensitic subsurface layer, significantly boosting bearing fatigue life due to increased surface hardness. This technique induces beneficial residual stresses, particularly in axial bearings, streamlining their construction and improving machine elements. Challenges persist, especially with radial bearings, but simplicity in axial bearing forging promotes compact, resource-efficient facility construction. Future research will focus on applying this technique to axial bearing washers, potentially replicating success in other bearing components. Despite the energy expenditure on cooling during forging, the substantial increase in bearing fatigue life offsets this, enhancing overall durability and reliability of critical machine components. Integration of this forging technique into bearing fabrication appears seamless, offering a promising trade-off between energy use and enhanced performance.
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In this paper, we constructed a new and robust fixed point iterative scheme called the UO iterative scheme for the approximation of a contraction mapping. The scheme converges strongly to the fixed point of a contraction mapping. A rate of convergence result is
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In this paper, we constructed a new and robust fixed point iterative scheme called the UO iterative scheme for the approximation of a contraction mapping. The scheme converges strongly to the fixed point of a contraction mapping. A rate of convergence result is shown with an example, and our scheme, when compared, converges faster than some existing iterative schemes in the literature. Furthermore, the stability and data dependence results are shown. Our new scheme is applied in the approximation of the solution to the oxygen diffusion model. Finally, our results are applied in the approximation of the solution to the boundary value problems using Green’s functions with an example.
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Gliomas represent the most commonly occurring tumors in the central nervous system and account for approximately 80% of all malignant primary brain tumors. With a high malignancy and recurrence risk, the prognosis of high-grade gliomas is poor, with a mean survival time of
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Gliomas represent the most commonly occurring tumors in the central nervous system and account for approximately 80% of all malignant primary brain tumors. With a high malignancy and recurrence risk, the prognosis of high-grade gliomas is poor, with a mean survival time of 12–18 months. While contrast-enhanced MRI serves as the standard diagnostic imaging modality for gliomas, it faces limitations in the evaluation of recurrent gliomas, failing to distinguish between treatment-related changes and tumor progression, and offers no direct therapeutic options. Recent advances in imaging modalities have attempted to address some of these limitations, including positron emission tomography (PET), which has demonstrated success in delineating tumor margins and guiding the treatment of recurrent gliomas. Additionally, with the advent of theranostics in nuclear medicine, PET tracers, when combined with therapeutic agents, have also evolved beyond a purely diagnostic modality, serving both diagnostic and therapeutic roles. This review will discuss the growing involvement of theranostics in diagnosing and treating recurrent gliomas and address the associated impact on quality of life and functional recovery.
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by
Tannia Vargas-Tierras, Mirian Jiménez-Gutiérrez, Sandra Pastrano, Gino Chávez, Vanessa Morales-León, María Morales-León, Fernando Paredes and Wilson Vásquez-Castillo
Water effluent pollution in the Ecuadorian Amazon occurs mainly due to the lack of sewage infrastructure, wastewater treatment plants in urban and rural areas, and agricultural and livestock activities. Consequently, understanding water quality is crucial because of its dynamic nature, influenced by various
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Water effluent pollution in the Ecuadorian Amazon occurs mainly due to the lack of sewage infrastructure, wastewater treatment plants in urban and rural areas, and agricultural and livestock activities. Consequently, understanding water quality is crucial because of its dynamic nature, influenced by various activities along its course. We evaluated and compared the water quality status of the El Salvador River with the current standards of the Ministry of the Environment, Water, and Ecological Transition in Ecuador and with Decree No. 115/2003 on water quality and water pollution management. The water quality index was determined through random sampling at seven locations along the river. The results show good water quality, with contamination indices ranging from 84 to 87. When comparing the results with the standards, all water quality parameters met the standards for recreational purposes. However, considering the river’s uses for agricultural activities, we compared the water with additional standards from legislation outlined by the Environment Ministry and found that the nitrate content exceeded permissible limits due to runoff from the surrounding crops, causing a potential risk to human health. Therefore, incorporating helophyte plants is a promising option that would promote the health of this aquatic ecosystem and others.
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Biaxial compression tests based on an elliptical tunnel were conducted to study the failure characteristics and the meso-crack evolution mechanism of tunnels with different cross-sections constructed in sandstone. The progressive crack propagation process around the elliptical tunnel was investigated using a real-time digital
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Biaxial compression tests based on an elliptical tunnel were conducted to study the failure characteristics and the meso-crack evolution mechanism of tunnels with different cross-sections constructed in sandstone. The progressive crack propagation process around the elliptical tunnel was investigated using a real-time digital image correlation (DIC) system. Numerical simulations were performed on egg-shaped, U-shaped, and straight-walled arched tunnels based on the mesoscopic parameters of the elliptical tunnel and following the principle of an equal cross-sectional area. The meso-crack evolution and stress conditions of the four types of tunnels were compared. The results show that (1) fractures around an elliptical tunnel were mainly distributed at the end of the long axis and mainly induce slabbing failure, and the failure mode is similar to a V-shaped notch; (2) strain localization is an important characteristic of rock fracturing, which forebodes the initiation, propagation, and coalescence paths of macro-cracks; and (3) the peak loads of tunnels with egg-shaped, U-shaped, and straight-walled arched cross-sections are 98.76%, 97.56%, and 90.57% that of an elliptical cross-section. The elliptical cross-section shows the optimal bearing capacity.
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This study investigates the in vitro activity of Nα-aroyl-N-aryl-phenylalanine amides (AAPs), previously identified as antimycobacterial RNA polymerase (RNAP) inhibitors, against a panel of 25 non-tuberculous mycobacteria (NTM). The compounds, including the hit compound MMV688845, were selected based on their structural
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This study investigates the in vitro activity of Nα-aroyl-N-aryl-phenylalanine amides (AAPs), previously identified as antimycobacterial RNA polymerase (RNAP) inhibitors, against a panel of 25 non-tuberculous mycobacteria (NTM). The compounds, including the hit compound MMV688845, were selected based on their structural diversity and previously described activity against mycobacteria. Bacterial strains, including the M. abscessus complex, M. avium complex, and other clinically relevant NTM, were cultured and subjected to growth inhibition assays. The results demonstrate significant activity against the most common NTM pathogens from the M. abscessus and M. avium complexes. Variations in activity were observed against other NTM species, with for instance M. ulcerans displaying high susceptibility and M. xenopi and M. simiae resistance to AAPs. Comparative analysis of RNAP β and β′ subunits across mycobacterial species revealed strain-specific polymorphisms, providing insights into differential compound susceptibility. While conservation of target structures was observed, differences in compound activity suggested influences beyond drug–target interactions. This study highlights the potential of AAPs as effective antimycobacterial agents and emphasizes the complex interplay between compound structure, bacterial genetics, and in vitro activity.
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Second language (L2) teachers’ emotions can influence their well-being and students’ performance. However, most of the existing studies have focused on the role of individual factors in affecting L2 teachers’ emotions, while leaving environmental factors underexplored. To fill this gap, this study aimed
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Second language (L2) teachers’ emotions can influence their well-being and students’ performance. However, most of the existing studies have focused on the role of individual factors in affecting L2 teachers’ emotions, while leaving environmental factors underexplored. To fill this gap, this study aimed to examine how the four dimensions of a supportive work environment (SWE) (perceived climate, PC; supervisory relationship, SR; peer group interaction, PGI; and perceived organization support, POS) relate to L2 teachers’ emotions (enjoyment, anxiety, pride, and anger). A sample of 406 Chinese L2 teachers completed two valid scales to measure their SWE and emotions. The data were analyzed by Partial Least Squares-Structural Equation Modeling (SEM) using Smart PLS 3 software. The results showed that (1) PC, PGI, and POS had a positive and significant effect on enjoyment, while SR had no significant effect; (2) PGI and POS had a negative and significant effect on anxiety, while PC and SR had no significant effect; (3) PGI had a positive and significant effect on pride, while the other three dimensions had no significant effect; and (4) POS had a negative and significant effect on anger, while the other three dimensions had no significant effect. The study concludes with some implications for L2 teachers’ education.
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Graphitic carbon nitride (g-C3N4), recognized for its considerable potential as a heterogeneous photocatalyst in water splitting, has attracted extensive research interest. By using density functional theory (DFT) calculations, the regulatory role of p-block metal (PM) single
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Graphitic carbon nitride (g-C3N4), recognized for its considerable potential as a heterogeneous photocatalyst in water splitting, has attracted extensive research interest. By using density functional theory (DFT) calculations, the regulatory role of p-block metal (PM) single atoms on the photocatalytic activity of g-C3N4 in overall water splitting was systematically explored. The incorporation of PM atoms (Ge, Sn and Pb) led to a reduction in the overpotentials required for both the oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER). Combined with the electronic structures analysis via hybrid functional, it was found that the introduction of Ge, Sn or Pb optimizes the positions of the valence band maximum (VBM) and the conduction band minimum (CBM), providing a robust driving force for HER and ensuring substantial driving force for OER. Meanwhile, the presence of these three PMs induces the spatial separation of VBM and CBM, inhibiting the recombination of carriers. These findings have significant implications for the design and preparation of efficient photocatalysts.
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Quantum physics is intrinsically probabilistic, where the Born rule yields the probabilities associated with a state that deterministically evolves. The entropy of a quantum state quantifies the amount of randomness (or information loss) of such a state. The degrees of freedom of a
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Quantum physics is intrinsically probabilistic, where the Born rule yields the probabilities associated with a state that deterministically evolves. The entropy of a quantum state quantifies the amount of randomness (or information loss) of such a state. The degrees of freedom of a quantum state are position and spin. We focus on the spin degree of freedom and elucidate the spin-entropy. Then, we present some of its properties and show how entanglement increases spin-entropy. A dynamic model for the time evolution of spin-entropy concludes the paper.
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The assassin bug Sycanus bifidus has a wide distribution across southern China. This study explored its distribution and evolution by analyzing mitochondrial and nuclear ribosomal RNA genes, revealing how Pleistocene climate and geological changes shaped its phylogeography. We identified two main clades, A
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The assassin bug Sycanus bifidus has a wide distribution across southern China. This study explored its distribution and evolution by analyzing mitochondrial and nuclear ribosomal RNA genes, revealing how Pleistocene climate and geological changes shaped its phylogeography. We identified two main clades, A and B, that diverged in the Middle Pleistocene. Hainan Island’s populations form a unique group within Clade A, suggesting that the Qiongzhou Strait served as a dispersal corridor during glaciation. Rising sea levels likely separated the Hainan population afterward. Ecological niche modeling showed that both populations have been viable since the last interglacial period, with demographic analyses indicating possible expansions during the Middle and Late Pleistocene, driven by favorable climates. This study highlights the significant effects of Pleistocene sea-level and climatic changes on the distribution and evolution of S. bifidus in China.
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Defect complexes consisting of point defects induced by the doping of rare earth elements (Nd, Er) into lutetium oxide (Lu2O3) host were investigated with respect to defect formation energies and defect configurations using atomistic simulations with General Utility Lattice
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Defect complexes consisting of point defects induced by the doping of rare earth elements (Nd, Er) into lutetium oxide (Lu2O3) host were investigated with respect to defect formation energies and defect configurations using atomistic simulations with General Utility Lattice Program (GULP). The site preferences of the substitutional point defects of the dopants and the occupation between the two available cationic sites, the 8b and 24d sites, were analyzed. Additionally, the impacts of Li on the doping of rare earth elements into Lu2O3 were revealed from the viewpoints of energy and structure. Dopant pairs in the nearest neighbor configurations (8b + 8b), (8b + 24d), and (24d + 24d) were considered. The results contribute to the understanding of structures of defects in rare earth-doped Lu2O3.
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Hydrogen plays a leading role in achieving a future with net zero greenhouse gas emissions. The present challenge is producing green hydrogen to cover the fuel demands of transportation and industry to gain independence from fossil fuels. This review’s goal is to critically
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Hydrogen plays a leading role in achieving a future with net zero greenhouse gas emissions. The present challenge is producing green hydrogen to cover the fuel demands of transportation and industry to gain independence from fossil fuels. This review’s goal is to critically demonstrate the existing methods of biomass treatment and assess their ability to scale up. Biomass is an excellent hydrogen carrier and biomass-derived processes are the main target for hydrogen production as they provide an innovative pathway to green hydrogen production. Comparing the existing processes, thermochemical treatment is found to be far more evolved than biological or electrochemical treatment, especially with regard to scaling prospects.
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In modern China, industrialization has formed a critical foundation for the transition to modernization. However, the spatiotemporal evolution patterns and driving mechanisms of urban industrial development in Nanjing from 1840 to 1949 remain unclear. Based on textual historical sources, this study examined the
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In modern China, industrialization has formed a critical foundation for the transition to modernization. However, the spatiotemporal evolution patterns and driving mechanisms of urban industrial development in Nanjing from 1840 to 1949 remain unclear. Based on textual historical sources, this study examined the spatiotemporal patterns of urban industrial development in Nanjing from 1840 to 1949 by using spatial analysis methods, GeoDetector, regression models and industrial structure indices. The results reveal the following: (1) The overall spatial distribution pattern of the industry in modern Nanjing exhibited a “one main, one secondary” dual-center “ladle-shaped” arrangement. Over time, industry has expanded from the urban center toward the east and north. (2) The modernization level of different industries was uneven, exhibiting a “center-periphery” spatial pattern. (3) At the micro level, transportation and population density were the primary influencing factors for industrial location, whereas at the macro level, government intervention mainly affected the industrialization pattern. (4) The industrial development pattern in modern Nanjing, in alignment with the “pole-axis” spatial system, serves as a microcosm of China’s urban modernization transition. This study represents the application of GIS methods in the humanities and provides valuable insights for urban planning and development.
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Automotive radar is one of the key sensors for intelligent driving. Radar image sequences contain abundant spatial and temporal information, enabling target classification. For existing radar spatiotemporal classifiers, multi-view radar images are usually employed to enhance the information of the target and 3D
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Automotive radar is one of the key sensors for intelligent driving. Radar image sequences contain abundant spatial and temporal information, enabling target classification. For existing radar spatiotemporal classifiers, multi-view radar images are usually employed to enhance the information of the target and 3D convolution is employed for spatiotemporal feature extraction. These models consume significant hardware resources and are not applicable to real-time applications. In this paper, RadarTCN, a novel lightweight network, is proposed that achieves high-accuracy online target classification using single-view radar image sequences only. In RadarTCN, 2D convolution and 3D-TCN are employed to extract spatiotemporal features sequentially. To reduce data dimensionality and computational complexity, a multi-layer max pooling down-sampling method is designed in a 2D convolution module. Meanwhile, the 3D-TCN module is improved through residual pruning and causal convolution is introduced for leveraging the performance of online target classification. The experimental results demonstrate that RadarTCN can achieve high-precision online target recognition for both range-angle and range-Doppler map sequences. Compared to the reference models on the CARRADA dataset, RadarTCN exhibits better classification performance, with fewer parameters and lower computational complexity.
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Respiratory tract diseases caused by influenza virus and SARS-CoV-2 can represent a serious threat to the health of pregnant women. Immunological remodulation for fetus tolerance and physiological changes in the gestational chamber expose both mother and child to fearful complications and a high
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Respiratory tract diseases caused by influenza virus and SARS-CoV-2 can represent a serious threat to the health of pregnant women. Immunological remodulation for fetus tolerance and physiological changes in the gestational chamber expose both mother and child to fearful complications and a high risk of hospitalization. Vaccines to protect pregnant women from influenza and COVID-19 are strongly recommended and vaccine co-administration could be advantageous to increase coverage of both vaccines. The attitude to accept both vaccines is affected by several factors: social, cultural, and cognitive-behavioral. In Palermo, Italy, during the 2021–2022 influenza season, a cross-sectional study was conducted to evaluate pregnant women’s intention to adhere to co-administration of influenza and COVID-19 vaccines. The determinants of vaccination attitude were investigated through the administration of a questionnaire and the Health Action Process Approach theory was adopted to explore the cognitive behavioral aspects. Overall, 120 pregnant women were enrolled; mean age 32 years, 98.2% (n = 118) of Italian nationality and 25.2% (n = 30) with obstetric or pathological conditions of pregnancy at risk. Factors significantly associated with the attitude to co-administration of influenza and COVID-19 vaccines among pregnant women were: high level of education (OR = 13.96; p < 0.001), positive outcome expectations (OR = 2.84; p < 0.001), and self-efficacy (OR = 3.1; p < 0.001). Effective strategies to promote the co-administration of the influenza vaccine and the COVID-19 vaccine should be based on the communication of the benefits and positive outcomes of vaccine co-administration and on the adequate information of pregnant women.
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The waterfowl industry represents a narrow, yet economically significant, sector within the poultry industry. Although less prominent, the waterfowl sector is nonetheless of equal importance to any other livestock sector in terms of antimicrobial resistance and animal health issues. This study assesses the
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The waterfowl industry represents a narrow, yet economically significant, sector within the poultry industry. Although less prominent, the waterfowl sector is nonetheless of equal importance to any other livestock sector in terms of antimicrobial resistance and animal health issues. This study assesses the antimicrobial resistance profile of Pasteurella multocida bacterial strains isolated from clinical cases in Hungary’s duck and goose populations, determining the minimal inhibitory concentration (MIC) of 27 samples collected from 15 different locations. The results indicate that the isolated strains were susceptible to most antibiotics, except for notable resistance to enrofloxacin. These findings support that Pasteurella multocida largely retained its susceptibility. However, the observed resistance to enrofloxacin suggests overuse of fluoroquinolones, which indicates the potential need for stricter regulation of their use in the poultry industry.
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Biodiesel stands at the forefront as a replacement for fossil diesel in compression ignition engines, particularly in the transportation sector where diesel engines are the primary movers. However, biodiesel production is hampered by poor heat and mass transfer during the transesterification reaction, leading
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Biodiesel stands at the forefront as a replacement for fossil diesel in compression ignition engines, particularly in the transportation sector where diesel engines are the primary movers. However, biodiesel production is hampered by poor heat and mass transfer during the transesterification reaction, leading to long production times and high costs due to inefficient energy utilisation. This study targets heat and mass transfer issues during the production of biodiesel via a synergic approach that combines microwave-assisted heating and microfluidics via a polyethylene terephthalate glycol (PETG) microchannel reactor. The transesterification reaction of palm oil and methanol was investigated using a full factorial design of experiments (DOE) method. Biodiesel yield was quantified via gas chromatographic analysis, and the results were optimised using statistical analysis. Optical analysis of slug quantification within the microchannel revealed that small slugs, smaller than 1 mm, accelerated the transesterification reaction. The composite-optimised experimental results, aimed at minimising energy costs and environmental impacts while maximising fatty acid methyl ester (FAME) yield, indicate a reaction temperature of 50 °C, a catalyst loading of 1.0 wt.%, and a 3:1 methanol to oil molar ratio. Regression analysis revealed that the reaction temperature was statistically insignificant when utilising the PETG microchannel reactor. This key finding positively impacts biodiesel production as it relates to significantly reduced energy intensity, costs, and emissions. Overall, this research work paves a pathway toward an energy-efficient and sub-minute rapid transesterification reaction, highlighting the effectiveness of microwave heat delivery and effects of microfluidics via the PETG microchannel reactor in overcoming heat and mass transfer barriers in biodiesel production.
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Neointimal hyperplasia is the main cause of vascular graft failure in the medium term. Vitamin D receptor activation modulates the biology of vascular smooth muscle cells and has been reported to protect from neointimal hyperplasia following endothelial injury. However, the molecular mechanisms are
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Neointimal hyperplasia is the main cause of vascular graft failure in the medium term. Vitamin D receptor activation modulates the biology of vascular smooth muscle cells and has been reported to protect from neointimal hyperplasia following endothelial injury. However, the molecular mechanisms are poorly understood. We have now explored the impact of the selective vitamin D receptor activator, paricalcitol, on neointimal hyperplasia, following guidewire-induced endothelial cell injury in rats, and we have assessed the impact of paricalcitol or vehicle on the expression of key cell stress factors. Guidewire-induced endothelial cell injury caused neointimal hyperplasia and luminal stenosis and upregulated the expression of the growth factor growth/differentiation factor-15 (GDF-15), the cytokine receptor CD74, NFκB-inducing kinase (NIK, an upstream regulator of the proinflammatory transcription factor NFκB) and the chemokine monocyte chemoattractant protein-1 (MCP-1/CCL2). Immunohistochemistry confirmed the increased expression of the cellular proteins CD74 and NIK. Paricalcitol (administered in doses of 750 ng/kg of body weight, every other day) had a non-significant impact on neointimal hyperplasia and luminal stenosis. However, it significantly decreased GDF-15, CD74, NIK and MCP-1/CCL2 mRNA expression, which in paricalcitol-injured arteries remained within the levels found in control vehicle sham arteries. In conclusion, paricalcitol had a dramatic effect, suppressing the stress response to guidewire-induced endothelial cell injury, despite a limited impact on neointimal hyperplasia and luminal stenosis. This observation identifies novel molecular targets of paricalcitol in the vascular system, whose differential expression cannot be justified as a consequence of improved tissue injury.
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Urban tailwater typically has a low carbon-to-nitrogen ratio and adding external carbon sources can effectively improve the denitrification performance of wastewater. However, it is difficult to determine the dosage of additional carbon sources, leading to insufficient or excessive addition. Therefore, it is necessary
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Urban tailwater typically has a low carbon-to-nitrogen ratio and adding external carbon sources can effectively improve the denitrification performance of wastewater. However, it is difficult to determine the dosage of additional carbon sources, leading to insufficient or excessive addition. Therefore, it is necessary to prepare solid slow-release carbon source (SRC) materials to solve the difficulty in determining the dosage of carbon sources. This study selected two SRCs of slow-release carbon source 1 (SRC1) and slow-release carbon source 2 (SRC2), with good slow-release performance after static carbon release and batch experiments. The composition of SRC1 was: hydroxypropyl methylcellulose/disodium fumarate/polyhydroxy alkanoate (HPMC/DF/PHA) at a ratio of 3:2:4, with an Fe3O4 mass fraction of 3%. The composition of SRC2 was: HPMC/DF/PHA with a ratio of 1:1:1 and an Fe3O4 mass fraction of 3%. The fitted equations of carbon release curves of SRC1 and SRC2 were y = 61.91 + 7190.24e−0.37t and y = 47.92 + 8770.42e−0.43t, respectively. The surfaces of SRC1 and SRC2 had a loose and porous morphological structure, which could increase the specific surface area of materials and be more conducive to the adhesion and metabolism of microorganisms. The experimental nitrogen removal by denitrification with SRCs showed that when the initial total nitrogen concentration was 40.00 mg/L, the nitrate nitrogen (NO3−-N) concentrations of the SRC1 and SRC2 groups on the 10th day were 2.57 and 2.66 mg/L, respectively. On the 20th day, the NO3−-N concentrations of the SRC1 and SRC2 groups were 1.67 and 2.16 mg/L, respectively, corresponding to removal efficiencies of 95.83% and 94.60%, respectively. The experimental results indicated that SRCs had a good nitrogen removal effect. Developing these kinds of materials can provide a feasible way to overcome the difficulty in determining the dosage of carbon sources in the process of heterotrophic denitrification.
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In this paper, we consider a low-latency Mobile Edge Computing (MEC) network where multiple User Equipment (UE) wirelessly reports to a decision-making edge server. At the same time, the transmissions are operated with Finite Blocklength (FBL) codes to achieve low-latency transmission. We introduce
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In this paper, we consider a low-latency Mobile Edge Computing (MEC) network where multiple User Equipment (UE) wirelessly reports to a decision-making edge server. At the same time, the transmissions are operated with Finite Blocklength (FBL) codes to achieve low-latency transmission. We introduce the task of Age upon Decision (AuD) aimed at the timeliness of tasks used for decision-making, which highlights the timeliness of the information at decision-making moments. For the case in which dynamic task generation and random fading channels are considered, we provide a task AuD minimization design by jointly selecting UE and allocating blocklength. In particular, to solve the task AuD minimization problem, we transform the optimization problem to a Markov Decision Process problem and propose an Error Probability-Controlled Action-Masked Proximal Policy Optimization (EMPPO) algorithm. Via simulation, we show that the proposed design achieves a lower AuD than baseline methods across various network conditions, especially in scenarios with significant channel Signal-to-Noise Ratio (SNR) differences and low average SNR, which shows the robustness of EMPPO and its potential for real-time applications.
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This research explores Indigenous land-based perspectives on environmental sustainability, centering on the Khasis Indigenous community in Bangladesh. With a critical connection to their land-based cultural heritage and environment, the Khasis community offers a distinctive perspective for examining environmental challenges. Emphasizing the traditional land-based
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This research explores Indigenous land-based perspectives on environmental sustainability, centering on the Khasis Indigenous community in Bangladesh. With a critical connection to their land-based cultural heritage and environment, the Khasis community offers a distinctive perspective for examining environmental challenges. Emphasizing the traditional land-based knowledge and practices of the Khasis, as well as their insights on environmental challenges, this study employs a land-based theoretical framework. It sheds light on the adaptive strategies of Khasis Indigenous communities amidst shifting environmental conditions, illustrating how they integrate sustainable practices into daily life by drawing upon Indigenous land-based knowledge and practices to mitigate environmental risks. Additionally, the research scrutinizes the challenges faced by the Khasis in preserving their land-based knowledge, practices, and identity in the face of a global environmental crisis. The findings contribute to broader discussions on Indigenous land-based knowledge and practices and their significance in contemporary climate discourse. By amplifying the voices of the Khasis Indigenous community’s land-based knowledge and practices, this study advocates for the incorporation of Indigenous perspectives into climate policies and interventions. It underscores the necessity for a more inclusive and culturally sensitive approach to environmental sustainability, one that acknowledges and respects the resilience of Indigenous communities like the Khasis in Bangladesh.
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