One of the research priorities in atmospheric chemistry is to advance our understanding of heterogeneous reactions and their effect on the composition of the troposphere. Chemistry on aqueous surfaces is particularly important in this regard because of their ubiquity and expanse. They range from the surfaces of oceans (360 million km²), cloud and aerosol drops (~10 trillion km²) to the fluids lining the human lung (~200 m²). Typically, ambient air contains reactive gases that may affect human health, influence climate and participate in biogeochemical cycles. Despite their importance, reactions between gases and solutes at air-aqueous interfaces are not well understood. New, surface-specific techniques are required that detect and identify the intermediates and products of such reactions as they happen on liquids. This is a tall order because genuine interfacial reactions are faster than mass diffusion into bulk liquids, and may produce novel species at low concentrations. Herein, we review evidence that validates online pneumatic ionization mass spectrometry of liquid microjets dosed by reactive gases as a technique meeting such requirements. Next, we call attention to results obtained by this approach on reactions of ozone, nitrogen dioxide and hydroxyl radicals with various solutes on aqueous surfaces. The overarching conclusion is that the outermost layers of aqueous solutions are unique media, where equilibria shift and reactions proceed faster than, in some cases along different pathways from the bulk liquids. The fact that the rates and mechanisms of reactions at air-aqueous interfaces may not be deduced from experiments in bulk liquids opens new conceptual frameworks and lines of research, and adds an overlooked dimension to atmospheric chemistry.

The increasing demand for higher power in rocket launchers is driving the development of higher power nozzles, achieved essentially by increasing the expansion ratio. However, this can lead to flow separation and resulting unsteady, asymmetrical forces, called side loads, which can limit the life of both the nozzle itself and other engine components. If this problem can be overcome, engine performance can be significantly increased. Therefore, various separation control methods have been proposed, but none have been fully implemented to date due to the uncertainties associated with modeling and predicting the flow phenomena. A numerical study of high area ratio rocket engine is presented to analyze the aeroelastic performance of the structure under the condition of flow separation. The finite volume method, the 2nd order upwind scheme and the extended wall function are used to analyze the flow inside the rocket nozzle and the transition of the Free Shock Separation (FSS) to Restricted Shock Separation (RSS) separation pattern ) to be discussed in detail. Since the location of the flow separation point depends heavily on the flow.

The alternating stress caused by periodic high-pressure injection and extraction in gas storage can potentially induce fault slippage, compromising the sealing integrity of faults within these facil-ities. Understanding the mechanical behavior of faults under alternating stress is crucial for en-suring the long-term stability and safety of gas storage operations. To explore the impact of fault dip angle and fault gouge strength on fault slip characteristics, fault samples were prepared with uniaxial compressive strengths of 20.1, 30.2, 42.4, and 51.4 MPa at two distinct dip angles. Triaxial compression experiments were conducted under alternating stress conditions corresponding to operational pressures at a specific gas storage in China. Results indicate that faults with dip angles of 30° and 45° tend to fail at their weakest points. Increasing strength of fault gouge shifts failure mechanisms from interfacial failure between gouge and surrounding rock towards internal gouge failure, often accompanied by shear failure across sections, resulting in characteristic "X"-shaped conjugate shear failures. The decrease in the ratio of bedrock strength to fault gouge strength elucidates the observed phenomena of initial reduction followed by increased fault deformation. Transition points for faults with 30° and 45° dips occur around the strength ratios of 1.7/1 and 1.2/1, respectively. Fault damage exhibits a negative correlation with fault gouge strength and a positive correlation with fault dip angle. Samples with higher strength fault gouge at a 30° dip angle generally incur less damage compared to those with lower strength fault gouge at a 45° dip angle. Moreover, higher maximum static friction coefficients denote greater fault resistance to slipping, with 30° faults consistently demonstrating superior resistance compared to 45° faults. Additionally, higher strength fault gouge consistently enhances slip resistance under identical dip angles.

In the process of oil and gas development and production, when the flow rate in the wellbore is large, the materials underground will be eroded, causing the operation to be unable to proceed smoothly and reducing the efficiency of oil and gas production. Therefore, optimizing the anti-erosion coating under high-speed flow conditions in wellbore is a very interesting thing. It can greatly improve operational efficiency. In this paper, laser cladding was used to prepare the new coating used in the PDC drill bit. Then, the effects of tungsten carbide and multi-layer graphene on the microstructure and properties of the tungsten carbide coating were studied. The research results indicate that, for new coatings, 60% tungsten carbide and 0.3% graphene are the optimal ratios. After adding WC, the hardness has significantly improved. However, when the WC content further increases more than 30%, the increase in hardness is relatively small. In addition, when the content of graphene is more than 0.3%, the branched structure became thicker, and not only the segregation of Cr, Si and W became very obvious again, but also the segregation of Fe occurred at the Ni enrichment site. The research results contribute to improving oil and gas production and operational efficiency under high-speed fluid flow conditions in the wellbore.

Emphasizing the importance of acoustic attenuation in maintaining compliance with stringent noise regulations and enhancing workplace safety, the analysis covers the theoretical and practical aspects of sound attenuation in a turboengine testing stand. This paper presents a preliminary analysis and also an evaluation of a procedure for projecting a noise attenuator for industrial application and especially for turboengine test stands. While primarily focusing on the static acoustic behavior of the attenuator, considerations were also made regarding flow dynamics, Mach number-dependent attenuation, pressure drop, and self-generated noise aspects to provide a comprehensive perspective in selecting the optimal design configuration. The study investigates different calculation methods for assessment of the noise reduction for linear and staggered baffles, applied on a scaled reduced model of attenuator. Thus, the critical parameters and projecting requirements necessary for effective noise reduction in high-performance turboengine testing environments will be evaluated in a down-scaled model. Key factors examined include the selection of design parameters and configurations from various options. Advanced computational methods, like analytic and finite element analysis (FEM) are utilized to predict the acoustic performance and identify potential design optimizations. Experimental validation is performed to corroborate the simulation results, ensuring the reliability and efficiency of the attenuator. The findings indicate that a well-designed sound attenuator module can significantly reduce noise levels without compromising the operational performance of the turboengine inside a test cell.

This study investigates the performance and environmental impact of n-butanol blended with Jet-A fuel in turbo-engines, aiming to assess its viability as a sustainable aviation fuel (SAF). The research involves experimental testing of various blends, ranging from low to high concentrations of methanol, to determine their effects on engine performance and emissions. The experimental setup includes comprehensive measurements of engine parameters such as thrust, fuel consumption rates, and exhaust gas temperatures. Emissions of nitrogen oxides (NOx), particulate matter (PM), carbon monoxide (CO), and unburned hydrocarbons (HC) are also analysed to evaluate environmental impacts. Key findings indicate that n-butanol/Jet-A blends can significantly enhance combustion efficiency and reduce emissions compared to conventional Jet-A fuel. Higher n-butanol concentrations lead to improved thermal efficiency and lower NOx and CO emissions. However, PM emissions slightly increase with higher methanol content. The study underscores the potential of n-butanol as a SAF for turbo-engines, highlighting its ability to mitigate environmental impacts while maintaining or improving engine performance. This research supports the feasibility of integrating n-butanol into Jet-A blends for turbo-engine applications, emphasizing its role in achieving more environmentally friendly aviation operations.

This study aims to investigate the interfacial tension, emulsion stability, and the impact on oil displacement effectiveness of mixed systems containing nonionic surfactants and amphoteric surfactants at different ratios. To achieve this, three different emulsion stability formulations were prepared by mixing betaine and nonionic surfactants in ratios of 1:1, 3:2, and 3:1 respectively. By adjusting the proportions of betaine and nonionic surfactants, variations in interfacial tension and emulsion formation among the three mixed systems were studied to analyze the mechanism of interaction between betaine and nonionic surfactants and evaluate their effects on crude oil displacement and enhanced oil recovery in reservoirs. Subsequently, microscopic and macroscopic oil displacement experiments were conducted on the three mixed systems, along with experiments on emulsion flow resistance. The aim was to verify the oil displacement effectiveness of different mixed systems and further understand their potential applications in reservoirs. By comprehensively analyzing the experimental results, optimal ratios and conditions for the mixed systems were determined. The experimental results indicate that the emulsification system formed by mixing betaine and nonionic surfactants at a ratio of 3:1 achieves molecular synergies through electrostatic interactions and mixed adsorption with betaine, resulting in a compact arrangement of interface membranes and demonstrating a synergistic effect in reducing interfacial tension to an ultra-low value of 10 -4 mN/m. Additionally, as the proportion of betaine surfactant increases, the viscosity of the aqueous phase liquid film increases, the rate of thinning of the liquid film slows down, the rate of water release slows down, and the stability of the emulsion increases. Microscopic oil displacement experiments verified that the three mixed systems increase oil washing efficiency through low interfacial tension and emulsification stripping action, thereby increasing the oil displacement mechanism's coefficient. Emulsion flow resistance experiments demonstrated that as the proportion of betaine surfactant increases, the system exhibits better plugging ability. However, macroscopic oil displacement experiments revealed differences in compatibility between different emulsion stability solutions and rocks with different permeabilities. The mixed system of betaine and nonionic surfactants at a ratio of 3:1 exhibits the best emulsification plugging ability in rocks with a permeability of 109mD, while the 1:1 mixed system performs best in rocks with a permeability of 12mD. This holds significant theoretical and practical significance for reservoir development and enhanced production.

In the realm of metal steel and iron manufacturing, there is a constant drive to optimize production efficiency and enhance the quality of the final products. This abstract explores a paradigm shift in this industry through the utilization of Computational Fluid Dynamics (CFD) as a powerful tool for achieving these goals .The study focuses on various critical aspects of the manufacturing process. Firstly, it delves into three-phase processes such as slag and gas entrainment in liquid steel, which have a significant impact on the overall product quality. Understanding and optimizing these processes is crucial to ensure the desired chemical composition and physical properties of the final metal.The abstract investigates the role of CFD in vacuum degassing, a process that plays a pivotal role in removing impurities, such as hydrogen and oxygen, from the liquid steel. By leveraging CFD to simulate and analyze the fluid flow patterns, researchers and engineers can design more efficient vacuum degassing systems, leading to improved product purity and reduced waste.Another crucial aspect explored in this abstract is the alloy melt and mixing process. By employing CFD simulations, researchers can gain insights into the movement of different alloy components and optimize their distribution within the melt. This aids in achieving the desired alloy composition, ensuring uniformity, and enhancing the mechanical properties of the final product.In addition, the study delves into the movement and flotation of inclusions, which are unwanted impurities present in the metal. CFD can be utilized to model and analyze the behavior of these inclusions, enabling engineers to design efficient strategies for their removal, thereby enhancing the purity and integrity of the final product.Moreover, the abstract considers the impact of melt temperature losses, which can occur during different stages of the manufacturing process. By employing CFD, it becomes possible to understand and mitigate these temperature losses, leading to improved energy efficiency and better control over the manufacturing parameters.Part 1 of this abstract critically evaluates the use of CFD in iron making, analyzing its benefits and limitations. It highlights how CFD can aid in process optimization, improving the understanding of complex phenomena involved in iron making, and ultimately leading to enhanced production efficiency.Part 2 focuses on the application of CFD in steel making and steel operation. It explores the fluid flow dynamics during different stages of steel production, including refining, casting, and rolling. By leveraging CFD, engineers can optimize these processes, leading to improved product quality, reduced defects, and increased productivity.This abstract demonstrates the transformative potential of Computational Fluid Dynamics in metal, steel, and iron manufacturing. By utilizing CFD as a tool to model and analyze complex fluid flow phenomena, researchers and engineers can revolutionize the production process, maximizing efficiency, and ensuring high-quality end products.

Driven by mounting environmental apprehensions stemming from the over dependence on fossil fuels in energy and transportation sectors, extensive exploration into alternative energy sources, particularly biomass, has stimulated profound research on harnessing the potential of computational and mathematical techniques. This comprehensive survey delves into optimal models and strategies, unveiling their pivotal role in the design of biomass gasification processes.of hydrogen through biomass gasification. In this study, we aim to provide a comprehensive overview of the computational and mathematical techniques employed in optimizing biomass gasification processes, with a specific focus on enhancing hydrogen yield. Through an extensive literature review, various models and strategies will be examined, including thermodynamic analysis, kinetic modeling, reactor design, and process optimization. By uncovering the power of these techniques, we aim to contribute to the advancement of sustainable and efficient biomass utilization for the hydrogen-based future economy.This paper aims to provide an updated and comprehensive coverage of the investigations conducted on the potential of producing hydrogen from biomass through gasification. To achieve this, we incorporate the latest works that have utilized numerical modeling, simulation, optimization techniques, process heat integration, and co-generation in their studies. By encompassing these aspects, we aim to offer a broader and more in-depth re-appraisal of the subject matter. This will ensure that readers gain a holistic understanding of the advances made in the field and the potential for sustainable hydrogen production of biomass gasification.Through a meticulous re-appraisal and analysis of each subject, we can identify their respective strengths and areas that require further research effort. By thoroughly examining numerical modeling, simulation, optimization techniques, process heat integration, and co-generation, we can assess their effectiveness and applicability in the context of biomass gasification for hydrogen production. This analysis shed light on the areas where these techniques excel, as well as pinpoint limitations or gaps in current understanding. By identifying these areas, we can highlight the need for further research and development, enabling us to make significant advancements in biomass gasification processes and pave the way for a sustainable and efficient hydrogen-based future economy..

The erosion of surface pipelines induced by proppant flowback during shale gas production is significant. The surface pipelines in a shale gas field in the Sichuan Basin experienced perforation failures after only five months of service. To investigate the erosion features of L360N, coatings, and ceramics and optimize the selection of two protective materials, a gas-solid two-phase flow jet erosion experimental device was used to explore the erosion resistance of L360N, coating, and ceramic under different impact velocities (15 m/s, 20 m/s, and 30 m/s). An energy dispersive spectroscope, a scanning electron microscope, and a laser confocal microscope were employed to analyze erosion morphologies. With the increase in flow velocity, erosion depth and erosion rate of L360N, coating, and ceramic increased and peaked under an impact velocity of 30 m/s. Maximum erosion rate and maximum erosion depth of L360N were respectively 0.0350 mg/g and 37.5365 µm. Its primary material removal mechanism was plowing of solid particles and microcracks were distributed on the material surface under high flow velocities. Maximum erosion rate and maximum erosion depth of coating were respectively 0.0217 mg/g and 18.9964 µm. Its primary material removal mechanism was the detachment of the binder phase Co caused by plowing. Maximum erosion rate and maximum erosion depth of ceramics were respectively 0.0108 mg/g and 12.4856 µm. The erosion mechanisms were micro-cutting and plowing. Under different particle impact velocity, different erosion morphologies were observed, but the primary erosion mechanism was the same. The erosion resistance of ceramics was higher than that of coating. Therefore, ceramic lining materials could be used to protect the easily eroded parts, such as pipeline bends and tees, and reduce the failure rate by more than 93%. The study provided the data and theoretical basis for the theoretical study on oil and gas pipeline erosion and pipeline material selection.

Carbon dioxide (CO2)miscible fracturing huff and puff technology plays a pivotal role in enhancing the recovery rate of crude oil, particularly in reservoirs with challenging physical properties, strong water sensitivity, high injection pressure, and complex water injection dynamics. In this study, the oil-increasing mechanism and huff and puff effect of CO2 miscible fracturing fluid are investigated through a comprehensive experimental approach. Specifically, experiments on PVT gas injection expansion, minimum miscible pressure, and CO2 miscible fracturing huff and puff are conducted on the G fault block reservoir in J Oilfield. The findings demonstrate that injecting CO2 into reservoirs leads to oil volume expansion, viscosity reduction, and saturation pressure increase. Additionally, the inclusion of solubilizers and viscosity reducers further enhances the efficiency of crude oil extraction. Solubilizers not only improve oil recovery but also reduce the minimum miscible pressure required for effective CO2 dispersion. Furthermore, the shut-in time, permeability, and huff and puff method all have considerable impacts on huff and puff recovery rate. This study offers valuable technical insights, supporting the application of CO2 miscible fracturing huff and puff technology to enhance oil recovery in low-permeability reservoirs.

Pore structure characterization and fractal analysis have great significance for understanding and evaluating tight limestone reservoirs. In this work, the pore structure of tight limestone is characterized combined with low-temperature nitrogen adsorption (LTNA) and low-field nuclear magnetic resonance (NMR), and the fractal dimension of tight limestone pore structure is discussed based on LTNA and NMR data. The results indicate that the pores of tight limestone have H3 and H4 types, the pore size distribution (PSD) of H3 type is a wave distribution ranging from 2 to 10 nm, and the PSD of H4 type is a unimodal distribution ranging from 2 to 10 nm. The transverse relaxation time (T2) spectrum of tight limestone shows single peak (DF), double peak (SF) and three peak (TF), and the T2 spectrums for micropores, mesopores and macropores range from 0.1 to 10 ms, from 10 to 100 ms, and greater than 100 ms, respectively. The LTNA fractal dimension of tight limestone (DL) ranges between 2.4446 and 2.7688, with an average of 2.5729, and the NMR fractal dimensions of micropores (DNMR1), mesopores (DNMR2) and macropores (DNMR3) are distributed between 0.3744 to 1.1293, 2.4263 to 2.9395 and 2.6582 to 2.9989, respectively. Moreover, there is no correlation between fractal dimension and permeability and porosity, a negative correlation between DL and average pore radius, a positive correlation between DL and specific surface area, and a positive correlation between DNMR2 and DNMR3 and micropore content, while DNMR2 and DNMR3 are negatively correlated with the content of mesopores and macropores.

Keywords: liquid alloys, microstratification, dispersed particles, spontaneous dispersion, criteria for true (entropic) spontaneous dispersion, mechanisms of quasi-spontaneous dispersion, methods and results for assessing size of dispersed particles.

Objectives. The aim of the study is to identify relevant research topics based on pooled bibliometric data of International Journal of Hydrogen Energy publications from 2022-2024, collected from The Lens and ScienceDirect platforms. Data source. Bibliometric records of International Journal of Hydrogen Energy articles published in 2022-2024 from The Lens and ScienceDirect platforms were used. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility. Results. The study showed the feasibility of merging bibliometric records from the open platforms ScienceDirect and The Lens, which complement each other. The 'Fields of Study' data of The Lens can be rationally interpreted as system keywords similar to Scopus Index Keywords. The possibility of using 'Fields of Study' data in a method similar to bibliographic coupling is shown. The practicality of using an Alluvial diagram to show the co-occurrence of the four terms was demonstrated. The study also emphasizes the advisability of joint use of VOSviewer and Scimago Graphica programs for complex visualization of bibliometric analysis results. The study identified two dominant publication topics in International Journal of Hydrogen Energy for 2022-2024, which can be described in terms of: 'Catalysis, Hydrogen, Physical_chemistry, Chemical_engineering, Nanotechnology, Electrochemistry, Organic_chemistry, Materials_science' and 'Electrical_engineering, Hydrogen_production, Renewable_energy, Environmental_science, Hydrogen_economy, Hydrogen, Engineering'.

Objectives. The aim of this study was to demonstrate the ability to visualize the results of the Scilit platform's bibliometric data analysis on the topic "AI & Machine Learning" to identify publications reflecting specific issues of the topic. Data source. Bibliometric records exported from the Scilit platform on the topic "AI & Machine Learning" for the years 2021–2023 were used. For each year, 6,000 records were downloaded in CSV and RIS format. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility, GSDMM algorithm. Used services: Elicit, QuillBot, Litmaps. Results. It has been shown that bibliometric data from the open access abstract database Scilit can serve as a quality alternative to subscription-only databases. Data exported from the Scilit platform require preprocessing to make them available in a format that can be processed by programs such as VOSviewer and Scimago Graphica. The use of GSDMM and FP-growth algorithms is effective for structuring bibliometric data for further visualization. The Scimago Graphica software provides wide possibilities for building compound diagrams, in particular, for representing the network of keywords in such important coordinates for bibliometric analysis as average year of publication and average normalized citation, as well as for building an alluvial diagram of co-occurrence of more than two keywords. The possibility of using such services as elicit.com, quillbot.com and app.litmaps.com to accelerate the selection of publications on the topic under study is shown.

Background. Keyword co-occurrence analysis is a crucial tool for comprehending research trends, identifying relevant studies, and gaining insight into the connections between various concepts and topics. Objective. This study focuses on analyzing the co-occurrence of keywords using FP-growth algorithm and direct search methods. Materials and methods. The methodology involved extracting bibliometric data of Energies journal for 2023-2024 from MDPI publisher platform, keyword lemmatization and keyword co-occurrence estimation. Clustering and visualization were performed using Multidendrograms and Scimago Graphica software. Results. The results showed that the FP-growth algorithm can achieve a close match with the direct search results, which facilitates data preparation for clustering. In addition, finding the co-occurrence of three or more keywords significantly reduced the number of possible combinations, which allowed the identification of specific research topics. Conclusions. This study highlights the usefulness of the FP-growth algorithm in keyword analysis and provides insights into ways to refine search queries to abstract databases for the purpose of designing and writing literature and systematic reviews.

Relevance of the subject. Keyword selection is critical to finding relevant literature and requires justification for querying abstract databases and other sources to ensure accuracy and completeness. The topic of Energy Systems is of great importance due to the introduction of renewable energy sources, modern control methods, and complex energy systems during the energy transition. The aim of this study. The goal of this paper was to identify keywords that would be useful to subject matter experts when collecting literature on a particular topic, based on entries in the IEEE Terms field. Data. Bibliometric data were exported from the IEEE Xplore platform in the following order: for 2019-2023, 2000 records sorted by relevance, for 2024, 1680 records current as of April 11, 2024. Analytical methods applied and software used. VOSviewer, Scimago Graphica implementing the Clauset-Newman-Moore algorithm and agglomerative hierarchical clustering method implemented in Multidendrograms. Results. The main issues of the Energy Systems topic are presented in tabular and graphical formats. The fpgrowth utility offers flexible data preparation options, which makes it worthwhile to conduct a separate study to analyze the score of co-occurrence terms given by its algorithm.

Purpose of publication: - Preparation of bibliometric data exported from the Scilit platform on energy efficiency and conservation for further analysis to identify relevant research topics. - To identify potential issues in the processing of data exported from the Scilit platform. - Providing colleagues with the opportunity to use the prepared data and examples of their analysis for independent research on topical issues of energy efficiency and energy conservation using materials provided by the Scilit platform. Research Materials: Files in CSV and RIS formats exported from Scilit for the query "energy conservation OR efficiency" in Common Fields [Title, Abstract, Keyword], using filters: Content Type → Journal Article; Year→2021-2023; Subject → Industrial Engineering (29.8K), Energy and Fuel Technology (9.8K), Manufacturing Engineering (9.2K). A total of 30K records sorted by their relevance (10K for each year) were exported. Data are current as of 14-03-2024. Methods: Preprocessing of title, annotation, and keyword field texts using lemmatization dictionaries collected on GitHub, removal of keywords taken from GATE and spaCy, and "manual" editing. Using VOSviewer to analyze publication topics by clustering keywords based on their co-occurrence. Using Scimago Graphica to build bubble diagrams.Application of the GSDMM algorithm for clustering bibliometric records by title and annotation texts. Creation of a dictionary for this algorithm using the keyword field.Use of the Carrot2 demo version and the NMF algorithm for a more detailed analysis of the topics of the record clusters obtained from GSDMM. Results: are presented in the form of initial and interim tables and graphs obtained in the course of this study. The full tables are provided as references to the attached materials. Supplementary material for this preprint on figshare: Chigarev, Boris (2024). Supplementary material for preprint "Analyzing the Possibilities of Using the Scilit Platform to Identify Current Energy Efficiency and Conservation Issues". figshare. Dataset. https://doi.org/10.6084/m9.figshare.25574058.v1

This study presents the evaluation of an ion exchange resin-based installation designed for the recycling of engine coolants, specifically ethylene glycol (EG) and propylene glycol (PG). The recycling process aims to restore the coolant to meet the stringent ASTM standards for both new and recycled coolants. A combination of physical-chemical methods, gas chromatography-mass spectrometry (GC-MS), and inductively coupled plasma mass spectrometry (ICP-MS) was employed to analyze and validate the purity and performance of the recycled product. The experimental setup included performance tests to assess the efficacy of the recycled coolants in comparison to new coolant standards. The results demonstrate that the recycled EG coolants exhibit comparable quality to new coolants, with all critical parameters falling within the acceptable ASTM limits. This indicates that the ion exchange resin method is a viable and efficient solution for the recycling of engine coolants, offering an environmentally friendly alternative to the disposal of used coolants while ensuring compliance with industry standards.

With the offshore oil-gas fields entering decline phase, high-efficiency separation of oil-gas-water mixtures becomes a significant challenge. As essential equipment for separation, the three-phase separators play a key role in Offshore Oil-Gas production. However, level control is critical in the operation of three-phase gravity separators on offshore facilities, as it directly affects the efficacy and safety of the separation process. This paper introduces an advanced deep deterministic policy gradient with adaptive learning rate weights (ALRW-DDPG) control algorithm, which improves the convergence and stability of the conventional DDPG algorithm. An adaptive learning rate weight function is meticulously designed, and an ALRW-DDPG algorithm network is constructed for simulating three-phase separator liquid level control. The effectiveness of the ALRW-DDPG algorithm is subsequently validated through simulation experiments. The results show that the ALRW-DDPG algorithm achieves a 15.38% improvement in convergence rate compared to the traditional DDPG algorithm, and the control error is significantly smaller than that of PID and DDPG algorithms.

Developing a dependable gas and condensate value chain is vital for the ongoing prosperity of the oil and gas industries. To achieve this, NNPC is enhancing its production facilities by employing process modeling and simulation with the assistance of Symmetry iCON®. As a part of this initiative, a simulation model was created using the Symmetry iCON® pipe plexus solver to simulate the dynamic environment of the gas and condensate pipeline network in the Nigerian Southern region. To validate the model, data from a single month, specifically December 2022, was utilized. Furthermore, the algorithm was utilized to generate projections for the month of January 2023, providing valuable insights into its effectiveness. The study also highlighted the significance of accurately estimating the characteristics and properties of a pseudo component of C6+ in relation to thermodynamics and material properties, which was a particularly insightful finding. he assessment of this property has transitioned from being relatively unimportant to becoming critically important, primarily due to the lack of condensate data monitoring at specific terminals. However, it's worth noting that the model currently has an error margin of 4-6% when predicting the data. As more information becomes available in the future, the model can be easily fine-tuned to better align with the actual conditions, allowing for more accurate predictions.

The liquid droplet cooling technique for fast scanning chip calorimetry (FSC) is introduced, increasing the cooling rate for large samples on a given sensor. Reaching higher cooling rates and using a gas as the cooling medium, the common standard for ultra-fast temperature control in cooling, requires reducing the lateral dimensions of the sample and sensor. The maximum cooling rate is limited by the heat capacity of the sample and the heat exchange between the gas and the sample. The enhanced cooling performance of the new liquid droplet cooling technique is demonstrated for both metals and polymers, on examples of solidification of large samples of indium, high-density polyethylene (HDPE), and poly (butylene 2,6-naphthalate) (PBN). It was found that the maximum cooling rate can be increased up to 5 MK/s in room temperature environment, that is, by 2 orders of magnitude, compared to standard gas cooling. Furthermore, modifying the droplet size and using coolants at different temperatures provide options to adjust the cooling rate in the temperature ranges of interest.

Homogeneous and heterogeneous chemical reactions in partially ionized magneto-nano-liquid are investigated theoretically using finite element method (FEM). The effects of ions and electrons collisions on the transport of heat and mass are analyzed for both the cases of heterogeneous and homogeneous chemical reactions. The simultaneous effects of dispersion of nanosized particles in partially ionized nano-liquid in the presence of magnetic field are also investigated. Through numerical experiments, it is noted that the temperature of partially ionized nano-liquid increases when electrons collision rate and ion collisions are increased. The transport rate of reacting species decreases when heterogeneous and homogeneous chemical reactions strengths are increased. It is also observed that the effect of electron collisions on the flow in y-direction is the same to that of ion collisions on the flow in y-direction. Homogeneous and heterogeneous chemical reactions have similar effects on concentration of chemically reacting species in qualitative sense. However, in quantitative sense, homogeneous chemical reaction has more significant effect on the concentration reacting species as compared to heterogeneous chemical reaction.

The article presents the results of the technical-economical study regarding the optimization of the FDM parameters (Lh – the height of the layer deposited in one pass and Id – the filling percentage) for the manufacture of PETG and ASA parts. To carry out the technical-economical study, we used the fundamental principle of value analysis, which consists in maximizing the ratio between Vi/Cp, where Vi - represents the mechanical characteristic, and Cp - represents the production cost. The results of the study show that for the tensile specimens made of PETG, the parameter that significantly influences the results of the Vi/Cp ratios is Lh, and in the case of the compression specimens made of PETG, the parameter that significantly influences the results of the Vi/Cp ratios is Id. In the case of specimens manufactured by FDM from ASA, the parameter that decisively influences the results of the Vi/Cp ratios of the tensile and compression specimens is Id – the filling percentage. By performing optimization of the process parameters with multiple responses, we identified the optimal parameters for FDM manufacturing of parts from PETG and ASA: Lh = 0.20 mm and Id = 100%.

In order to establish the formation patterns of the Co–Mg oxide system, samples with different Co:Mg ratios and heat treatment temperatures were synthesized and studied. Study of the sam-ples confirmed the phase transition of MgxCo2–xO4 spinels into corresponding solid solutions at 800–900 °C. The similarity of formation patterns for different compositions is shown. The rock-salt oxide in low-temperature samples is an anion-modified paracrystalline phase that forms a “true” solid solution only upon spinel decomposition. TPR profiles of decomposed Co3O4 spinel show surface Co3O4 peaks and a wide peak corresponding to well-crystallized CoO, while par-tial Co3O4 TPR up to 380 °C results in dispersed and amorphous CoO. High-temperature non-stoichiometric samples are poorly reduced, indicating their low oxygen reactivity. Spinel reoxidation after heat treatment to 1100 °C by calcination at 750 °C showed complete regenera-tion for MgCo2O4–Co3O4 samples and its absence in case of an excess of MgO relative to stoi-chiometry. Based on the data obtained, it can be concluded that the processes governing the formation of Co–Mg oxide systems are determined by both Co:Mg ratio and the heat treatment conditions, potentially providing the possibility of fine tuning for specific catalytic processes.

The objective of this work was to investigate the deacidification of bio-oils (BOs) from triglyceride-based biomass through the application of liquid-liquid extraction (LLE) in a simple stage, using methanol and water as a binary solvent and feed/solvent ratio of 1/1. For this, the effects of process parameters such as the water content present in the solvent, the content of carboxylic acids present in the bio-oil, and the extraction temperature on the deacidification process through the efficiency and distribution coefficient were evaluated, as well as the effects of such parameters on the quality of deacidified bio-oils through physical-chemical analyzes and GC-MS analysis. The results show that such process parameters significantly affect the quality of deacidified bio-oils. The ideal condition to have the highest acid removal, i.e., the highest deacidification efficiency (72.65%), is the one in which the deacidification process is performed with aqueous methanol (5% water) at 35 °C and for BOs that have a total acid number (TAN) equal to 24.38 mg KOH/g. Therefore, the process of deacidification by LLE using aqueous methanol is a promising alternative for removing carboxylic acids and other oxygenated compounds, contributing significantly to the upgrading or improving biofuels produced by catalytic thermal cracking.

Carboxylic acids such as acetic acid and propionic acid have been investigated as representative components for fast pyrolysis (FP) bio-oil upgrading. Selective catalytic conversion of carboxylic acids can enhance bio-refinery processing economics through catalyst preservation and process intensification. Various metal-doped molybdenum carbide bead catalysts have been synthesized and developed in this work. Our aim is to enable selective conversion of carboxylic acids. In the case of acetic acid conversion, calcium doped Mo₂C beads offer the highest yield of acetone ~96% at 450 °C among undoped and Ca or Ni doped catalysts. By comparing hot gas filter with and without Ca-Mo₂C catalyst tested with real FP vapors, the former showed a 36.7% reduction of acetic acid, a 37.5% reduction of small ketones in aqueous phase, and a ~50% reduction of methoxies (methoxy phenols and methoxy aromatics) in organic phase. The conversion resulted in the formation of more long chain chemicals in the organic phase, which are more amendable for downstream upgrading.

Food analysis demands fast methods for routine control and high throughput of samples. Chromatographic separation enables simultaneous determination of numerous compounds in complex matrices, several approaches increasing separation efficiency and speed of analysis were involved. In this work, modern types of column with monolithic rod or superficially porous particles were employed and compared for determination of eight synthetic food dyes, their chromatographic performance was evaluated. During method optimization, cyano stationary phase Chromolith Performance CN 100 × 4.6 mm and Ascentis Express ES-CN 100 × 4.6 mm, 5 µm were selected for the separation of polar colorants. The separation was performed by gradient elution of acetonitrile/methanol and 2% water solution of ammonium acetate at flow rate 2.0 ml min-1. Mobile phase composition and the gradients were optimized in order to enable efficient separation on both columns. The method using fused-core particle column provided higher separation efficiency, narrow peaks of analytes resulted in increased peak capacity and shortening of analysis time. After the validation, the method was applied for analysis of colored beers, soft drinks and candies.

Pd EnCat™ 30 is a palladium catalyst broadly used in several hydrogenation and cross-coupling reactions. It is known for its numerous beneficial features, which include high-yielding performance, easy recovery, and reusability. However, the available data regarding its recyclability in Suzuki coupling reactions are limited to a few reaction cycles and, therefore, fail to explore its full potential. Our work focuses on investigating the extent of Pd EnCat™ 30 reusability in Suzuki cross-coupling reactions by measuring its performance according to isolated yields of product. Our findings demonstrate that Pd EnCat™ 30 can be reused over a minimum of 30 reaction cycles, which is advantageous in terms of cost reduction and more sustainable chemical production.

In order to achieve the dual carbon goal and simplify the decarbonization process, a CO2 recovery process of the fire-flooding exhaust was designed. The process adopted the two-stage membrane separation method to recover CO2 and obtain high purity CO2 rich flow, and then through the mixed refrigerant liquefaction and rectification column, food grade liquid CO2 was obtained. HYSYS process simulation shows that for the fire-flooding exhaust with a flow rate of 1000 kg/h and a given composition, the process can achieve a CO2 recovery of 69.02%, total product sales S=2086.8 yuan/h, and specific power consumption of 2.818 kW∙h/kg. On this basis, a hybrid simulation platform of HYSYS & Matlab was established. Taking the specific power consumption of the product as the objective function, sequential quadratic programming (SQP) algorithm was adopted to optimize the process, and the optimized specific power consumption was reduced by 18.8%. Finally, by adjusting N2/CO2 components, the adaptability of the optimization condition was analyzed.

This study explores the dynamics of liquid holdup in a lab-scale co-current two-phase upflow moving packed bed reactor, specifically examining how superficial gas velocity influences the line average external liquid holdup at a fixed superficial liquid velocity. Utilizing Gamma-ray Densitometry (GRD) for precise measurements, this research extends to determining line average internal porosity within catalyst particles and the overall external bed porosity. Conducted with an air-water system within a bed packed with 3 mm extrudate porous particles, the study presents a novel methodology to calculate liquid holdup, grounded in Beer–Lambert's law. Findings reveal a decrease in liquid holdup corresponding with increased superficial gas velocity across axial and radial locations, with a notable transition from bubbly to pulse flow regime at a critical velocity of 3.8 cm/sec. Additionally, the lower sections of the packed bed exhibited higher external liquid holdup compared to the middle sections at varied gas velocities. The liquid holdup distribution appeared uniform at lower flow rates, whereas higher flow rates favored the middle sections.

Background: Pleurotus ostreutus is one of the world’s most commonly consumed mushrooms. Cultivation of mushrooms using wood resources usually results in environmental issues of deforestation. Juncao grass Pennisetum sp, Arundo Donax, and Methodology: Miscanthus are the culture mediums used in this research which offered a composting system most particularly for a simple formulation, cheap and feasible for small farms in cultivating oyster mushrooms. Results: The present study assessed the different junco grass as a substrate for growing Pleurotus ostreatus given the enzyme activities, growth, and yields. In addition, on the other hand, Lignin peroxidase (LiP) was the most active enzyme in each culture material among the other enzyme activities expressed differently between substrate and growing stages. Fruiting bodies harvested on giant grass,Arundo donax,and miscanthus,substrate weighed 159.2g/bag,132g/bag, and 65.1g/bag on average respectively. The biological efficiency of pleurotus cultivated in three different substrates was 75.2%, 63.4%, and 28.7%, respectively. Lignin peroxidase (LiP) was the most active enzyme followed by Laccase in each substrate. At the same time, other enzyme activities were differently expressed between substrate and different developmental stages. Nutrient analysis revealed significant variations, with differences in polysaccharides, proteins, and amino acids among substrates as well as the presence of heavy metals as arsenic, lead, mercury, and cadmium content in all samples was within safe limits. Conclusion: Findings from this study will serve as a solid foundation for future studies aimed at characterizing different substrate responses on enzyme activity. This research provides a sustainable footprint for subsequent research promoting eco-friendly mushroom production. The obtained results indicate that Arundo donax should be a good substrate in place of giant grass, using miscanthus is not productive based on the results obtained in this research the juncao grasses offer a sustainable approach that reduces reliance on wood-based substrates and enhances environmental sustainability.

This study aims to quantify greenhouse gas (GHG) emissions from China's sludge treatment industry and explore the potential of novel technologies to mitigate these emissions, promoting sustainable sludge management practices. Using a life cycle assessment approach, the total GHG emissions from sludge treatment in 2017 were estimated at 18.54 Mt CO2-eq, with significant regional variations. Incineration contributed the highest emissions (1,011.53 kg CO2-eq/t dry sludge), followed by landfill (717.51 kg CO2-eq/t) and land application (276.41 kg CO2-eq/t). The uneven distribution of emissions across cities highlights the need for targeted mitigation strategies that consider local sustainability challenges. Principal component analysis revealed that economic factors and treatment scale significantly influence emissions, emphasizing the importance of integrating sustainability goals with economic development. To reduce the carbon footprint of sludge treatment and enhance sustainability, the mitigation potential and costs of various technologies were evaluated, including thermal conversion, anaerobic digestion, hydrothermal processes, and wet oxidation. These technologies offer GHG emission reductions ranging from 0.09 to 0.46 t CO2-eq/t dry solids compared to conventional methods, while also promoting resource recovery and circular economy principles. However, further optimization is necessary to enhance their environmental and economic performance, ensuring long-term sustainability. By implementing these technologies and adopting optimization strategies, China's sludge treatment industry can significantly contribute to achieving the country's carbon neutrality goal and fostering sustainable development.

Pneumatic nebulizers (as variations based on the Collison nebulizer) have been widely used for producing fine aerosol droplets from a liquid material. The basic working principle of those nebulizers has been qualitatively described as utilization of the negative pressure associated with an expanding gas jet to syphon liquid into the jet stream, then to blow and shear into liquid sheets, filaments, and eventually droplets. Detailed quantitative analysis based on fluid mechanics theory is desirable, to gain in-depth understanding of the liquid aspiration mechanism among other aspects of the Collison nebulizer behaviour. The purpose of present work is to investigate the nature of negative pressure distribution associated with compressible gas jet flow in the Collison nebulizer by a computational fluid dynamics (CFD) analysis, using an OpenFOAM® compressible flow solver. The value of the negative pressure associated with a gas jet flow is examined by varying geometric parameters of the jet expansion channel adjacent to the outlet of jet orifice. Such an analysis can provide valuable insights into fundamental mechanisms for liquid aspiration, helpful for designing improved pneumatic atomizer in the Aerosol Jet® direct-write system for micro-feature, high-aspect-ratio material deposition

A challenge in building large-scale superconducting quantum processors is the precise control and manipulation of the qubit state. However, the crosstalk between the microwave control lines impedes the parallel execution of high-fidelity digital and analog quantum operations. Here, we propose and demonstrate a universal compensation protocol for calibrating the microwave signal crosstalk. We also introduce amplified error sequences to optimize the accuracy. Furthermore, we show a definitive improvement in parallel gate operations with crosstalk cancellation, demonstrating the technique's effectiveness. This work paves the way for superconducting hardware that features automated calibration of microwave crosstalk, leading to enhanced fidelities in multiqubit circuits.

One objective of this paper is to investigate bifurcation of solutions of Ornstein-Zernike equation in liquid state theory for the gas-liquid coexistence region of simple fluids. The analysis uses a discrete form of the Ornstein-Zernike equation in real space, together with a closure relation which provides nearly self consistent thermodynamic properties of fluids governed by interaction potentials like the Lennard-Jones potential. Accurate asymptotic forms of correlation functions are incorporated in the real space algorithm so as to mitigate the influence of cutoff length used in the discrete approximations. It is found that there is no spinodal on the vapor side on a sub-critical isotherm. But there are fold bifurcation points on the vapor and liquid sides together with a 'no-real-solution-region' in between. This is followed by a region of negative compressibility extending up to the spinodal on the liquid side. The emerging picture is quite similar to that in the case of the hypernetted-chain-closure. It is also found that complex solutions connect the physical solutions that exist outside the 'no-real-solution-region' as well as in region of negative compressibility. The second objective of the paper, in the light of bifurcation scenario, is to evolve an interpretation of the coupling-parameter expansion of correlation functions pertaining to the region of negative compressibility. It is shown that the expansion provides an accurate description of results of the restricted ensembles, implied in mean field theories and simulation methods. Bifurcation of singlet density to inhomogeneous distributions at a spinodal is also established using a simple equation, which uses the direct correlation function. Thus the paper reestablishes the fact that restriction to a homogeneous singlet density is the root cause of all inconsistencies found in the gas-liquid coexistence region.

The hydrodynamic behavior of the air-acetic acid system in a bubble column is studied using a differential pressure transmitter, double probe optical fiber probe, and the electrical resistance tomography (ERT) technique. The superficial gas velocity ranges from 0.016 to 0.094 m/s under ambient temperature and pressure. The influences of viscosity and surface tension on gas holdup, bubble rising velocity, and bubble chord distribution in the column are discussed with different mass fractions of an acetic acid solution. The results show that as the mass fraction of acetic acid increases, the surface tension of the liquid phase decreases, and the viscosity first increases and then decreases. This causes the gas holdup in the column to first increase and then decrease, and reaches the maximum value at an acetic acid mass fraction of 55% to 60%. The rising velocity of the bubbles in the column is high in the central region and has a low-value distribution near the wall. The bubble chord length distribution is concentrated, and the distribution of the bubble chord length in the column becomes narrow with any decrease in surface tension. Studying the hydrodynamic behavior of a bubble column with the air-acid system is of great significance considering the absence of data on air-organic acid systems.

Analyses of the three predominant types of sedimentation – clastic, carbonate and black shale – revealed their discontinuity/continuity in different facies environments of the Middle and Late Devonian of the central part of the Volga-Urals petroleum province, namely (1) in depressions, both condensed and non-condensed, (2) on the slopes of depressions and (3) in shallow water environments represented by tectonic arches or localised biohermal uplifts. The regional zonation of conodonts, correlated with the global chronostratigraphic scheme, substantiates the stratigraphic completeness of the general Devonian sequence in this area. In particular, the sedimentation of organic-rich black shales, traditionally considered as source rocks, lasted more than 29 million years, starting from the Late Eifel and ending at the Devonian-Carboniferous boundary. There was only one hiatus in the deposition of both black shales and carbonate sediments, lasting about 2.5 million years at the end of the Frasnian. That interval is dominated by clastic sediments, which are considered to be the most productive reservoirs of the Volga-Ural province. In the time interval from the beginning of the Eifel to the end of the Frasnian (about 17 Ma), (a) clastic sediments show the highest accumulation rates; (b) the most complete sequences occur in depressions; and (c) arches and uplifts show the most significant gaps in the geological record. During Famennian, (a) clastic sedimentation has completely ceased; (b) differences between the slopes of troughs and shallow-water environments have diminished, resulting in stable accumulation of carbonate sediments in both settings; (c) the decrease in sequence thickness (up to 50 m) in depressions suggests reduced accumulation rates of deep-water organic-rich black shales. The results help to understand the complex spatial relationship between different coexisting sedimentation types and focus attention to the incompleteness of the geological record in different environments.

High-precision conical threads are widely used in responsible joints in the drilling of oil and gas wells. Difficult underground drilling conditions due to the occurrence of significant mechanical loads and an aggressive environment in wells require the use of workable materials that are often difficult to machine. The huge need for such connections dictates the use of high-performance cutting tools, which means that high demands are placed on their effective geometric performance. The study describes the theoretical dependence of the profile precision of the tapered drill-string tool-joint threads of all standard sizes on the complex of a cutting tool geometric parameters and cutting tool setting accuracy. The experiments include an assessment of the geometric accuracy of the profile of the obtained NC23 thread connector, depending on the values of the installation angles and the declared tangential displacement of the standard threaded carbide insert.

Enhancing the Efficiency of Natural Gas Liquid (NGL) Extraction and Fractionation Trains: An Integrated Approach of Simulation Analysis, Advanced Modifications, and Technological Advancements. Through comprehensive research, innovative solutions such as the heat pump aided distillation (HPAD) system and self-heat recuperation technology (SHRT) have been developed to significantly reduce the energy consumption associated with conventional distillation systems. To identify a practical system for NGL fractionation trains, this study extensively examined and compared various HPAD and SHRT options to retrofit a single column. The objective was to find the most suitable and efficient solution for the fractionation process of natural gas liquids (NGLs). The retrofit options analyzed in this study encompassed a range of techniques, including vapor compression (VC), mechanical vapor re-compression (MVR), thermal vapor re-compression (TVR), bottom flashing (BF), side heat exchanger (SHE), intermediate heating and cooling (IHC), self-heat recuperative (SHR), and modified self-heat recuperative (MSHR) distillation. These methods were carefully examined to determine their suitability and effectiveness in improving the performance of NGL fractionation trains.In this study, a depropanizer column, typically employed in conventional NGL plants, was selected as a case study. The simulation software Aspen HYSYS V7.3 was employed to model and analyze eight retrofit designs based on predefined criteria. The simulation data was carefully evaluated to identify the most efficient design for minimizing energy consumption. Among the retrofit options, the mechanical vapor re-compression (MVR) technique demonstrated the most significant energy cost reduction, with a remarkable 68.11 percent improvement compared to the base case conventional column. These findings highlight the potential of MVR as an effective solution for lowering energy costs in NGL fractionation trains.Following the MVR retrofit option, the study found that vapor compression (VC) achieved a considerable energy cost reduction of 66.65 percent, closely followed by modified self-heat recuperative (MSHR) at 64.02 percent, bottom flashing (BF) at 62.88 percent, self-heat recuperative (SHR) at 55.85 percent, side heat exchanger (SHE) at 54.23 percent, intermediate heating and cooling (IHC) at 39.54 percent, and thermal vapor re-compression (TVR) also at 39.54 percent. These findings highlight the significant potential for energy savings offered by these retrofit options, with VC being the most popular choice, closely followed by MSHR, BF, SHR, SHE, IHC, and TVR.

Global public health systems have continuously faced challenges from the advent of novel infectious illnesses, necessitating quick and efficient actions to stop their spread.First discovered in Saudi Arabia in 2012, Middle East respiratory syndrome (MERS) is a viral respiratory disorder caused by the Middle East respiratory syndrome coronavirus (MERS-CoV). Since then, the nation has reported most cases and fatalities related to this sickness, with occasional outbreaks happening in other nations and regions. Severe sickness and high mortality are caused by MERS-CoV, especially in older persons and those with underlying chronic conditions. Through intimate contact, the virus can spread from people to dromedary camels and vice versa. It has sparked multiple epidemics both domestically and abroad in the Middle East, raising the possibility of fatalities and widespread transmission, especially in susceptible groups. The Riyadh region was the main target of the most current MERS-CoV outbreak in Saudi Arabia, which began in 2023 and ended on September 1, 2023, with 312 confirmed cases and ninety-seven fatalities. With the use of published studies and their contributions to the field, we hope to present a thorough overview of the MERS-CoV outbreak in Saudi Arabia in this review of the literature, including its epidemiological investigation, public health response, impact, and lessons learned. In addition to highlighting the importance and continued relevance of this problem, our work suggests ways to lower the risk of MERS-CoV transmission and avert further outbreaks.

The electric vehicle (EV) industry is experiencing rapid growth, accompanied by continuous advancements in charging infrastructure to satisfy the rising need for fast and reliable charging. Particularly, the focus has shifted towards EV fast charging (EVFC) and its impact on the power grid. This paper presents a comprehensive analysis and survey of scholarly literature and projects conducted in this field over the past decade. The findings highlight the rising demand for EVFC and the need to address its potential adverse effects on the power grid. However, there is a noticeable lack of clear research guidance regarding charging time. To tackle these challenges and pave the way for future solutions, extensive research on DC fast charging, ultra-fast charging, and the integration of vehicle-to-grid (V2G) systems is required. This review paper thoroughly investigates the development of fast charging technology for electric vehicles (EVs), including its advantages and comparative analyses from various perspectives. Furthermore, it delves into the advancements in DC fast charging infrastructure, emphasizing charging standards and control modes. The study also investigates different categories of battery chargers for both on-board and off-board charging. Additionally, it explores the classification of DC-DC converters in the context of DC fast charging stations, discusses control strategies for EV systems, identifies existing challenges, and outlines future trends in EV fast charging.

Recently, there has been increasing attention toward inhaled nanoparticles (NPs) to develop in-halation therapies for diseases associated with the pulmonary system and investigate the toxic ef-fects of hazardous environmental particles on human lung health. Taking advantage of microfluidic technology for cell culture applications, lung-on-a-chip devices with great potential in replicating the lung air-blood barrier (ABB) have opened new research insights in preclinical pathology and therapeutic studies associated with aerosol NPs. Surprisingly, the air interface in such devices, which makes them tremendously unique among the other common liquid-based cellular mi-crosystems and enables exposure of cultivated cells to the drug/toxic aerosols, has been largely disregarded. Accordingly, there exists a significant research gap in the comprehensive under-standing of the NPs’ dynamics in the lung-on-a-chip devices, which is momentous to control the injection of aerosols to the target area and attain a desired physiochemical efficacy. To address this research gap, a numerical parametric study is presented to provide a deep insight into the dynamic behavior of the airborne NPs in a gas-liquid dual-channel lung-on-a-chip device with a porous membrane separating the channels. A finite element multi-physics model is developed to enable a particle tracing investigation simultaneously in both air and medium phases to replicate the in vivo conditions avoiding laborious and costly experimental trials. The results include the impact of fluid flow as well as geometrical properties on the distribution, deposition, and translocation of the NPs with diameters ranging from 10 nm to 900 nm in the lung-on-a-chip. The obtained results strongly suggest the aerosol injection of NPs instead of the aqueous solution for more efficient deposition on the substrate of the air channel and higher translocation to the media channel. The current study proposes to optimize the affecting parameters to control the injection and delivery of aerosol par-ticles into the lung-on-chip device depending on the objectives of biomedical investigations and provides optimized values for some specific cases. Therefore, this study can assist scientists and researchers in complementing their experimental investigation in future preclinical studies on pulmonary pathology associated with inhaled hazardous and toxic environmental particles, as well as therapeutic studies for developing inhalation drug delivery.

Maritime data not only identify financial resources that can significantly enhance the efficiency of shipping companies but also play a pivotal role in promoting eco-friendly and sustainable shipping practices. However, active corporate strategies are required to include maritime data essential for the commercial operation of autonomous ships in the form of corporate assets by transparent evaluating the data. The aim of this study is to review previous studies on da-ta-valuation models, identify a valuation model suitable for maritime business, consider the characteristics of maritime data. The analytic hierarchy process (AHP) method is used to derive priorities for valuing maritime data assets, with emphasis placed on the characteristics of mari-time data, followed by the character of the future-oriented maritime-data market and the da-ta-valuation model. The results obtained that the most important factors in selecting a maritime data-valuation model by analyzing the AHP method were identified as the characteristics of the maritime data(M1). The next most important factors analyzed were the features of the mari-time-data market(M2) and the features of the maritime data-valuation model(M3) in order. In addition, the characteristics of maritime data were preferentially considered among the main criteria, and the market approach (A2) was selected as the most optimal valuation model. The potential impact of this implementation could contribute to the establishment of an intelligent technology market by estimating the value of data and developing a platform for maritime data trading, allowing for more efficient data sharing and utilization by maritime autonomous sur-face ship(MASS).

Background: Microscopic examination of acid-fast stained sputum smears for detecting mycobacterial acid-fast bacilli (AFB) remains the most economical and readily available method for laboratory diagnosis of tuberculosis (TB). However, this conventional approach has limitations, including low sensitivity and labor-intensive procedures. Methods: An automated microscopy system incorporating artificial intelligence (AI) and machine learning for AFB identification was evaluated. The study was conducted at an Infectious Disease Hospital in Jiangsu Province, China, utilizing an intelligent microscope system (TB-Scan, Wellgen Medical, Kaohsiung). A total of 1,000 sputum smears were included in the analysis, with the system capturing digital microscopic images and employing an image recognition model to automatically identify and classify AFB. Referee technicians provided the gold standard for discrepant results. Results: The automated system demonstrated an overall accuracy of 95.00% (950/1,000), sensitivity of 91.24% (177/194), and specificity of 95.91% (773/806). Notably, the system identified 21 smears as positive that were previously reported as negative, with referee technicians confirming 17 of these as true positive and retracting the test results accordingly. Recalculating the performance, the accuracy increased to 96.70% (967/1,000), sensitivity to 91.94% (194/211), and specificity to 97.97% (773/789), with a false negative rate of 8.06% (17/211) and a false positive rate of 2.03% (16/789). Conclusions: The incorporation of AI and machine learning into an automated microscopy system demonstrated the potential to enhance the sensitivity and efficiency of AFB detection in sputum smears compared to conventional manual microscopy. This approach holds promise for widespread application in TB diagnostics and potentially other fields requiring labor-intensive microscopic examination.

Among the various types of gas sensors, the chemoresistive gas sensors based on metal oxides are considered the most attractive ones due to their simple operation, low costs and miniaturization. Thin films of V2O5 undoped and doped with TiO2 were studied as nitrogen dioxide, methane and hydrogen sensors. The experimental kinetics of the electrical conductivity changes due to introduction and removal of gas on metal oxide gas sensors were successfully explained in terms of the Langmuir adsorption theory.

Firefighters Protective Clothing consist of several layers of different properties and functions. The layers create barriers against dangerous outer factor. However, they are also barriers to transport of sweat produced by human organism. It causes that very often sweat in the form of vapor is not transferred effectively from the human organism through the FPC to environment. This leads to sweat condensation on the skin of the FPC user causing his discomfort. In order to ensure as good as possible physiological comfort of firefighter while firefighting and other rescue actions it is necessary to take into consideration the transport of condensed sweat in the multilayer textile set creating the FPC. In the presented work four variants of multilayer textile sets for the FPC have been tested in the aspect of liquid moisture transport. Measurement was performed by means of the Moisture Management Tester (MMT290) – innovative instrument manufactured by the SDL Atlas. Obtained results showed that the transfer of sweat in liquid form occurs only in the inner, next to skin layer of the multilayer sets for the FPC.

Molecular-scale density fluctuations at equilibrium produce cavities in a liquid and can be analyzed to shed light on the statistics of the number of molecules occupying observation volumes of increasing radius. An information theory approach led to the conclusion that these probabilities should follow a Gaussian distribution function. This prediction has been confirmed by computer simulations in different liquid models if the size of the observation volume is not large. The reversible work of cavity creation is exactly linked to the probability of finding zero molecules in a given observation volume. The Gaussian formula for the latter probability is scrutinized to arrive at the enthalpy and entropy changes associated with cavity creation. The reversible work of cavity creation has a purely entropic origin due to the solvent-excluded volume effect produced by the inaccessibility of a given region of the configurational space. The consequent structural reorganization of liquid molecules leads to exactly compensating enthalpy and entropy changes. These results are in line with those obtained in a direct statistical mechanical study by Lee.

Natural gas hydrate, also known as combustible ice and mainly composed of methane, it is identified as the potential clean energy in the 21th century. Due to its large reserves, gas hydrate can ease problems caused by energy resource shortage and has gained attention around the world. In this paper, we focus on the exploration and development of gas hydrate as well as discussing its status and future development trend in China and abroad, then we analyze its opportunities and challenges in China from four aspects: resource, technology, economy and police with five forces model and PEST method. The results show, China has abundance gas hydrate resource; however the backward technologies and inadequate investment has seriously hindered the future development of gas hydrate, so China should establish relevant cooperation framework and intuitional arrangement to attract more investment as well as breaking through technical difficulties to make gas hydrate commercialization as soon as possible.

The technical feasibility of solar photovoltaic (PV) direct current (DC) nanogrids are well-established, but the components of nanogrids are primarily commercially focused on alternating current (AC)-based systems. Thus, DC converter-based designs at the system level require personnel with high degree of technical knowledge and this results in high costs. To enable a democratization of the technology by reducing the costs this study provides a novel modular plug-and-play open source DC nanogrid. The system can be customized according to consumer requirements, enabling the supply of various voltage levels to accommodate different device voltage needs. The step-by-step design process of the converter, controller, data logger, and assembly of the complete system is provided. A time-domain simulation and stability analysis of the designed system were conducted in MATLAB/Simulink as well as experimental validation. The results show transforming the nanogrid from a distribution network to a device makes it suitable for various user-specific applications, such as remotely supplying power to campsites, emergency vehicles like ambulances, and small houses lacking grid electricity. The modular DC nanogrid includes all the features available in a DC distribution network as well as data logging, which enhances the user experience and promotes the use of solar-powered DC grid systems.

Transportation contributes significantly to greenhouse gas emissions, with electrification offering a promising solution. This study evaluates the degradation of State of Health (SOH) over 2.5 years for electrified buses under different charging protocols: DC Fast charging and Flash charging. The vehicles’ models, charging protocols, and financial implications are discussed. High-level simulations reveal that after 2.5 years, the Flash charging vehicle’s SOH reaches 88.93%, while the DC fast charging vehicle reaches 89.46%, showing a 0.47% difference. This slight variance is attributed to Flash charging vehicles avoiding full charge/discharge cycles, reducing battery aging impact. Considering this minimal SOH degradation difference, the choice between DC Fast charging and Flash charging primarily hinges on capital expenditure disparities. Flash charging, with its lower initial battery capacity and reduced capital costs, presents a compelling alternative for city busoperators seeking to electrify their fleets.

In this work, we propose an in-house simulation tool designed for the analysis and optimization of bifacial photovoltaic (PV) modules, which are currently under the spotlight in the renewable energy scenario. The tool is conceived to support researchers and engineers by providing fast and accurate predictions of the PV module yield under various operating and environmental conditions. For a chosen geographical site, the impact of module orientation, tilt, albedo, sky conditions, ambient temperature, and so on, can be effortlessly determined. In case of nonuniformity across the cells dictated by localized architectural shading, dirt, bird drops, defects, a circuit-based cell-level approach can be activated to compute the module production. An extensive simulation campaign is performed by assuming that the panels are installed in Naples without loss of generality. Results are shown to give detailed insights into the performance of bifacial modules, thus providing unambiguous guidelines for their correct installation. Further analyses are conducted to demonstrate the tool capability to quantify the detrimental influence of a poorly-irradiated cell on the backside, as well as of cracked cells.

It is an utmost importance to characterize drug candidates as early in the development pipeline as possible. Appropriate application of the emerging high throughput analytical techniques unlocks the opportunities to obtain experimental data for in vitro absorption, distribution, metabolism and elimination (ADME) profiling of large compound libraries which is crucial for selection of lead compounds. In an usual scenario, only one drug candidate will be selected from thousands of early compounds based on several stability and screening results. A high to medium throughput screening approaches could significantly accelerates the subsequent research and production phases. Traditionally, the analysis of metabolic stability assays heavily relies on high throughput LC-MS/MS techniques to meet with the lead profiling demands. In this study presented an innovative experimental approach that can offer a refreshing alternative. Laser Assisted Rapid Evaporative Ionization Mass Spectrometry (LA-REIMS) is a quick and efficient method for characterizing complex biological samples without laborious sample preparation and chemical separation. Therefore, using an automated LA-REIMS well plate reader as fast as 8 seconds per sample, we assessed the oxidative metabolic stability of active agents using biomimetic metalloporphyrin-based oxidative model reactions at various pH for commercially available drug substances and compared stability measurements with traditional HPLC-DAD-MS results.

Fast-scan cyclic voltammetry (FSCV) is an electrochemical sensing technique that can be used for neurochemical sensing with high spatiotemporal resolution. Carbon fiber microelectrodes (CFMEs) are traditionally used as FSCV sensors. However, CFMEs are prone to electrochemical fouling caused by oxidative byproducts of repeated serotonin (5-HT) exposure, which makes them less suitable as a chronic 5-HT sensor. Our team is developing a boron-doped diamond microelectrode (BDDME) that has previously been shown to be relatively resistant to fouling caused by protein adsorption (biofouling). We sought to determine if the BDDME exhibits resistance to electrochemical fouling, which we explored on electrodes fabricated with either femtosecond laser cutting or physical cleaving. We recorded the oxidation current response after 25 repeated injections of 5-HT in a flow-injection-cell and compared the current drop from the first to the last injection. The 5-HT responses were compared to dopamine (DA), a neurochemical that is known to produce minimal fouling oxidative byproducts and have a stable repeated response. Physical cleaving of the BDDME yielded a reduction in fouling due to 5-HT compared to the CFME and the femtosecond laser cut BDDME. However, the femtosecond laser cut BDDME exhibited a large increase in sensitivity over the cleaved BDDME. An extended stability analysis was conducted for all device types following 5-HT fouling tests. This analysis demonstrated an improvement in the long-term stability of boron doped diamond over CFMEs, as well as a diminishing sensitivity of the laser cut BDDME over time. This work reports the electrochemical fouling performance of the BDDME when it is repeatedly exposed to DA or 5-HT, which informs the development of a chronic, diamond-based electrochemical sensor for long-term neurotransmitter measurements in vivo.

There are unsolved problems related to inflation, gravity, dark matter, dark energy, missing antimatter, and the birth of the universe. Some of them can be better answered by assuming the existence of aether and hypoatoms. Both were created during the inflation in the very early universe. While aether forms vacuum, hypoatoms, composed of both matter and antimatter and believed to be neutrinos, form all observable matter. In vacuum, aether exists between the particle-antiparticle dark matter form and the dark energy form in a dynamic equilibrium: A + A-bar = gamma + gamma. The same reaction stabilizes hypoatoms and generates a 3-dimensional sink flow of aether that causes gravity. Based on the hypoatom structure, the singularity does not exist inside a black hole; the core of the black hole is a hypoatom star or neutrino star. By gaining enough mass, ca. 3 X 10²² M_sun, to exceed neutrino degeneracy pressure, the black hole collapses or annihilates into the singularity, thus turning itself into a white hole or a Big Bang. The universe is anisotropic. Its center, or where the Big Bang happened, is at 0.66^+0.03_-0.01 times the radius of the observable universe at Galactic coordinates (l, b) = (286⁺¹⁰_-10, -43⁺⁷_-6). If we look from the Local Group to the center of the universe, the universe is rotating clockwise.

There are many pollution and environment problem in the human ecosystem. There are different methods are used to removal of sulfur from sour gases for example Basic Claus process and Modified Claus process . There are different chemical software are used for simulation and optimization of Claus process for example Aspen Plus and Chemcad ECT. The Gibbs free energy method is introduced and model of Claus process. There are new parameter are introduced in reaction furnace to reduce the error from 33% to 7 %. The waste heat boiler is installed at the reaction furnace in which high pressure stream is produced and study the decomposition the hydrogen sulphide. The new rate of reaction is introduced of the enhancement of H2 production in chemical process. The simulation of reaction furnace in Aspen plus software is the maximum utilization of process. Due to suitable operating condition of reaction furnace is caused the maximum destruction of ammonia gas in the reactor. When we are increasing the oxygen concentration and temperature of feed is causing decreasing the ammonia production in reaction furnace. It is below than acceptance value of ammonia is 150 ppm in the reaction furnace. The presence of oxygen components, Sulfur oxide, hydroxide components are effect on decreasing the amount of ammonia in furnace and temperature is about at 1350⁰C. It is noted that when the production of sulfur recovery is decrease in Claus process and the production of carbon monoxide is increase in the thermal section at the existence. Now we are work on parametric studies of furnace that could be causes the production of ammonia destruction and CO emission in the Claus process. Due to optimize the reaction furnace parameter are help to get large of sulfur production, ammonia gas destruction, increased the catalyst life and decreased of dangerous gases.

The article delves into the crucial realm of compressing hydrogen in its gaseous state, a pivotal process for enhancing its viability in both civil and industrial sectors. The study initiates by providing a concise overview and comparison of diverse hydrogen storage methodologies, laying the groundwork with an in-depth analysis of hydrogen's thermophysical properties. It scrutinizes plausible configurations for hydrogen compression, aiming to strike a delicate balance between energy consumption, predominantly derived from the fuel itself, and the requisite number of compression stages. Notably, to render hydrogen storage competitive in terms of volume, pressures of at least 350 bar are deemed essential, albeit at an energy cost amounting to approximately 10% of the fuel's calorific value. Multi-stage compression emerges as a crucial strategy, not solely for energy efficiency, but also to curtail temperature rise, with an upper limit set at 200°C. This nuanced approach is underlined by the exploration of compression levels commonly cited in the literature, particularly 350 bar and 700 bar. Ultimately, the study advocates for a three-stage compression system as a pragmatic compromise, capable of achieving high-pressure solutions while keeping compression work below 10 MJ/kg, a threshold indicative of sustainable energy utilization.

Glioblastoma is the most common and malignant primary brain tumor. Despite a century of research efforts, the survival of patients has not significantly improved. Currently, diagnosis is based on neuroimaging techniques followed by histopathological and molecular analysis of resected or biopsied tissue. A recent paradigm shift in diagnostics ranks the molecular analysis of tissue samples as the new gold standard over classical histopathology, thus correlating better with the biological behavior of glioblastoma and clinical prediction, especially when a tumor lacks the typical hallmarks for glioblastoma. Liquid biopsy aims to detect and quantify tumor-derived content, such as nucleic acids (DNA/RNA), circulating tumor cells (CTC), or extracellular vesicles (EV) in biofluids, mainly blood, cerebrospinal fluid (CSF), or urine. Liquid biopsy has the potential to overcome the limitations of both neuroimaging and tissue-based methods to identify early recurrence and to differentiate tumor progression from pseudoprogression, without the risks of repeated surgical biopsies. This review highlights the origins and time-frame of liquid biopsy in glioblastoma and points to recent developments, limitations and challenges of adding liquid biopsy to support the clinical management of glioblastoma patients.

The ionic liquid A327H+Cl- is generated by reaction of the tertiary amine A327 (industrial mixture of tri-octil and tri-decyl amines) and hydrochloric acid solutions. Further, the extraction of Au(III) by A327H+Cl- ionic liquid under various variables, including metal and ionic liquid concentrations, has been investigated. Results indicate that A327H+AuCl4- is formed, by an exothermic (ΔHº= -3 kJ/mol) reaction, in the organic solution. Aqueous ionic strength influences the formation constants values and the specific interaction theory (SIT) is used to estimate the interaction coefficient between AuCl4- and H+. Gold (III) is stripped using thiocyanate media, and from the strip solutions, gold is precipitated as gold nanoparticles.

The transition to cleaner energy sources, particularly in hard-to-abate industrial sectors, often requires gradual integration of new technologies. Hydrogen, crucial for decarbonization, is explored as a fuel in blended combustions. Blending or replacing fuels impacts combustion stability and heat transfer rates due to differing densities. An extensive literature review examines blended combustion, focusing on hydrogen-methane mixtures. While industrial burners claim to accommodate up to 20% hydrogen, theoretical support is lacking. A novel thermodynamic analysis methodology is introduced, evaluating methane-hydrogen combustion using the Wobbe index. Findings highlight practical limitations beyond 25% hydrogen volume, necessitating a shift to "totally hydrogen" combustion. Blended combustion can be proposed as a medium-term strategy, acknowledging hydrogen's limited penetration. Higher percentages require burner and infrastructure redesign.

Waste glycerol can be subjected to various processing operations, including purification and re-fining, to obtain glycerol of appropriate purity. In addition, alternative methods of utilising waste glycerol are also being sought, e.g. by converting it into other valuable chemical products or biofuels. Therefore, various technologies are being developed to utilise this type of waste effectively and sustainably. The production of value-added products from waste glycerol is an important issue that determines the improvement of the economic viability of biofuel production and corresponds to the model of a waste-free and emission-free circular economy. This paper characterised the mechanisms and evaluated the efficiency of existing methods of microbiological utilisation of waste glycerol into liquid biofuels, including biodiesel, bioethanol and biobutanol, and identified further directions for the production of value-added products. In addition, a bibliographical analysis of publications re-lated to the production of liquid fuels and economically valuable products from glycerol was carried out, the progress of research and application work was assessed and directions for future research were identified.

To better understand the shape memory materials and self-healing materials, a new series of liquid-crystalline shape memory polyurethane (LC-SMPU) composites, named SMPU-OOBAm, were successfully prepared by incorporating 4-octyldecyloxybenzoic acid (OOBA) into the PEG-based SMPU. The effect of OOBA on the structure, morphology and properties has been carefully investigated. The results demonstrate that SMPU-OOBAm have liquid crystalline properties, triple-shape memory properties and self-healing properties. The incorporated OOBA promotes the crystallizability of both soft and hard segments of SMPU, and the crystallization rate of the hard segment of SMPU decreases when the OOBA-content increases. Additionally, the SMPU-OOBAm forms a two-phase separated structure (SMPU phase and OOBA phase), and it shows two-step modulus changes upon heating. Therefore, the SMPU-OOBAm shows triple-shape memory behavior, and the shape recovery ratio decreases with an increase in the OOBA content. Finally, SMPU-OOBAm shows self-healing properties. The new mechanism can be ascribed to the heating-induced “bleeding” of OOBA in the liquid crystalline state and the subsequent re-crystallization upon cooling. This successful combination of liquid crystalline properties, triple-shape memory properties and self-healing properties make the SMPU-OOBAm composites with many promise applications in smart optical devices, smart electronic devices and smart sensors.

Phased injection of natural gas into internal combustion marine engines is a promising solution for optimizing performance and reducing harmful emissions, particularly unburned methane, a potent greenhouse gas. This innovative practice distinguishes itself from continuous injection because it allows for more precise control of the combustion process with only a slight increase in system complexity. By synchronizing the injection of natural gas with the intake and exhaust valve opening and closing times while also considering the gas path in the manifolds, methane release into the atmosphere is significantly reduced, making a substantial contribution to efforts to address climate change. Moreover, phased injection improves the efficiency of marine engines, resulting in reduced overall fuel consumption, lower fuel costs, and increased ship autonomy. This technology has been tested on a single-cylinder, large-bore, four-stroke research engine designed for marine applications, operating in dual-fuel mode with diesel and natural gas. Performance was compared with that of the conventional continuous feeding method. Evaluation of the effect on equivalent CO2 emissions indicates a potential reduction of up to approximately 20%. This reduction effectively brings greenhouse gas emissions below those of the diesel baseline case, especially when injection control is combined with supercharging control to optimize the air-fuel ratio.

The primary objective of this study was to demonstrate the potential of digital image analysis as a tool to identify microplastic (MP) particles in surface waters and to facilitate their characterisation in terms of 2D and 3D morphology. Digital image analysis preceded by microscopic analysis was used for an exhaustive quantitative and qualitative evaluation of MPs isolated from the Vistula river. Using image processing procedures, 2D and 3D shape descriptors were determined. The Principal Components Analysis (PCA) was used to interpret the relationships between the parameters studied, characterising MP particle geometry, type and colour. This multivariate analysis of the data allowed 3 or 4 main factors to be extracted, explaining approximately 90% of the variation in the data characterising MP morphology. It was found that the first principal component for granules, flakes and films was largely represented by strongly correlated with 2D shape descriptors (area, perimeter, equivalent area diameter) and 3D shape descriptors (CSF, Compactness, Dimensionality). Considering the scraps, PC1 was represented by only five of the above descriptors, and the Compactness variable had the largest contribution to PC2. In addition, for granules, flakes and films, a relationship between 2D shape and the colour of their particles could be observed. For the most numerous MP group identified of multicoloured scraps, no such association was found. The results of our study can be used for further multivariate analysis regarding the presence of microplastic floating on the river surface, with a particular focus on particles of secondary origin. This is of key importance for optimising future efforts in conducting small-scale and multidimensional monitoring of and reducing plastics in the aquatic environment.

Timber-concrete composite (TCC) systems join the positive aspects of engineered wood products (good seismic behaviour, low thermal conductivity, environmental sustainability, good behaviour under fire if appropriately designed) with those of concrete (high thermal inertia, durability, excellent fire resistance). TCC facades are typically composed by an internal insulated timber-frame wall and an external concrete slab, separated by a ventilated air cavity. However, there is very limited knowledge concerning the performance of TCC facades, especially for what concerns their thermal behaviour. The present paper deals with the development and optimisation of a 2D CFD model for the analysis of TCC ventilated façades thermal behaviour. The model is calibrated and validated against the experimental data collected during the annual monitoring of a real TCC ventilated envelope in the north of Italy. Also, a new solver algorithm is developed to significantly speed up the simulation. The final model can be used for the time-efficient analysis and optimisation of the thermal performance of TCC ventilated facades, as well as other ventilated facades with external massive cladding, avoiding the expensive and time-consuming construction of mock-ups, or the use of comparably slow (conventional) CFD solvers that are less suitable for optimization studies.

As technology advances, people are increasingly adopting IoT (Internet of Things) devices in smart cities. These devices are equipped with sensors that are connected everywhere, from energy infrastructure and transportation to telecommunications, health and human services, waste management, public safety, and more. People want to access sensor data anytime and everywhere to make better decisions and improve their lives. To achieve this, a sensor integration model has been developed where multiple sensors are integrated under one gateway to manage and share sensor data. However, effective sharing of sensor data requires data security, privacy, confidentiality, fairness, effective architectural design, and low communication and computation costs. These issues need to be addressed in the sensor integration model in smart cities. Existing storage models face challenges in managing sensor data effectively. To overcome these issues and hurdles, a data storage framework leveraging blockchain technology has been proposed within the sensor integration model. This framework ensures data security, privacy, confidentiality, and a fair and transparent financial model, all while minimizing communication and computation costs.

Radical reactions are powerful in the synthesis of diverse molecular scaffolds bearing functional groups. In pervious review articles, we have presented 1,2-difunctionalizations, remote 1,3-, 1,4-, 1,5-, 1,6- and 1,7-difunctionalizations, and addition followed by cyclization reactions. Presents in this paper are radical cyclization followed by the second functionalization reactions. The second functionalization could be realized by atom transfer reactions, radical or transition metal-assisted coupling reactions, and reactions with neutral molecules, cationic and anionic species.

This overview initially describes insect immune reactions and then brings together present knowledge of the interactions of vector insects with their invading parasites and pathogens. It is a way of introducing this special issue with subsequent papers presenting the latest details of these interactions in each particular group of vectors. Hopefully, this paper will fill a void in the literature since brief descriptions of vector immunity have now been brought together in one publication and could form a starting point for those interested and new to this important area. Descriptions are given on the immune reactions of mosquitoes, blackflies, sandflies, tsetse flies, lice, fleas and triatomine bugs. Cellular and humoral defences are described separately but emphasis is made on the co-operation of these processes in the completed immune response. The paper also emphasises the need of great care in extracting haemocytes for subsequent study as appreciation of their fragile nature is sometimes overlooked with non-sterile media, smearing techniques and excessive centrifugation sometimes used. The potential vital role of eicosanoids in the instigation of many of the immune reactions described is also discussed. Finally, the priming of the immune system, mainly in mosquitoes, is considered and one possible mechanism is presented

Materials based on platinum metals with very good catalytic activity were tested in the reduction of p–nitrophenol (pNP) to p–aminophenol (pAP). The majority of presented catalytic materials are based on the adsorption of p–nitrophenol on the surface of the catalyst simultaneously with molecular hydrogen, coming from sodium borohydride in an aqueous medium, which reduces it. In the present paper, a catalytic material based on osmium dispersed in n–decanol or n–dodecanol is presented, which also works as an emulsion membrane, for the absorption of p–nitrophenol and molecular hydrogen at the n–alcohol aqueous solution interface. The hydrogenation of p–nitrophenol is carried out in a reaction and separation column in which the acid receiving phase emulsion is dispersed in the osmium nanodispersion, in n–alcohols. This emulsion circulates from the base of the column to its upper part in co-current or counter-current with the source phase consisting of p–nitrophenol and sodium borohydride. Experiments show that the circulation of counter-current phases is superior to that in co-current, and the emulsion based on n–decanol is more efficient than the one based on n–dodecanol. The increase in the pH difference between the source and receiving phases leads to the increase in the conversion of p–nitrophenol to p–aminophenol. The efficiency of separation of the reaction product in the receiving phase is lower than the conversion at the same operating time. The apparent catalytic rate constant (kapp) of the new catalytic material based on the emulsion membrane with nanodispersion of osmium nanoparticles (0.1×10−3 for n–dodecanol and 0.9×10−3 for n-decanol) is lower by an order of magnitude compared to those based on adsorption on catalysts from platinum metal group. The advantage of the tested membrane catalytic material is that it extracts p–aminophenol in the acid receiving phase. The paper proposes a mechanism of the studied reduction system.

Refractory materials are used worldwide in process equipment. However, gaseous and liquid process products penetrate the surface layer, and deep into the volume of refractories destructing rather expensive constructions complicated to repair. To address this challenge, there is a need to develop protective coatings for refractory that can limit the penetration of working media and extend their operational lifespan. In this work, the application of gas-dynamic cold spraying (CGDS) to produce a coating on the refractory using fine titanium dioxide (TiO2) particles is explored. These particles are accelerated within a nitrogen flow, passing through a Laval nozzle, and then sprayed onto a fireclay surface. The mechanisms of particle deposition and layer formation on porous surfaces through experiments and numerical simulations were investigated. The geometry of a typical refractory pore was determined, which was then incorporated into Computational Fluid Dynamics (CFD) simulations to model the cold spraying process of porous substrates. As a result, the influence of the particle size on its velocity and angle of penetration into pores was established. Experimental findings demonstrate the effective closure of pores and the formation of a particle layer on the refractory surface. Furthermore, the nanoindentation tests for the refractory samples showcase capabilities for checking coating thickness for porous materials.

The paper presents a proposal for an in-house mathematical model of a liquid flat-plate solar collector. The proposed model is a one-dimensional distributed parameter model enabling simulations of the collector operation under arbitrarily variable boundary conditions. The model is based on the solution of energy balance equations for all components of the collector. The formulated differential equations are solved iteratively using an implicit difference scheme. In order to obtain a stable numerical solution, it is necessary to use appropriate steps of the time and spatial division. These were found by comparing the results obtained from the model with the results of the analytical solution available in the literature for the transient state, which constitutes the novelty of the present study. The accuracy of the results obtained from the model was verified experimentally by comparing the measured and the calculated history of the fluid temperature at the outlet of the collector. The calculation of the collector time constant is proposed in the paper as an example of the model practical application. The results of the time constant calculation were compared with the values obtained experimentally on the test stand. This is another novelty of the presented research. The analysed collector instantaneous efficiency was then calculated for selected outdoor conditions. The presented mathematical model can also be used to verify the correctness of the collector operation. Comparing, on an ongoing basis, the measured and the calculated values of the fluid temperature at the collector outlet, conclusions can be drawn about the process of solar glass fouling or glycol gelling. The model's simplicity and the low computational demands enable such comparisons in an online mode.

The effect of H2S with high concentrations on catalytic dry reforming of methane (DRM) process has seldom been focused on previously. Herein, a thermodynamic analysis of the DRM reactions in the presence of H2S with the concentration varying in 0-20 vol% was conducted firstly. Several typical types of catalysts including MgO, NiO/MgO and LaNiO3 in different states were prepared for executing DRM at 800 C, 0.1 MPa in the feed of 20 vol% CO2 and 20 vol% CH4 balanced with N2. The catalytic performance of each catalyst for DRM process under conditions of absence and presence of H2S was compared. A promotion effect of increasing H2S concentration on both the conversions of CO2 and CH4 and the molar yields of CO and H2 was observed on all the catalysts especially the MgO and the pristine NiO/MgO. While a significant decline in catalytic activity of either the reduced NiO/MgO or the reduced LaNiO3 catalyst after adding H2S, moderate reactant conversions still sustained. The results of process analysis and catalyst structure characterization suggest that H2S participation can contribute to the increment in CO2 and CH4 conversion, and active S-adsorbed species may play the key role of catalysis in the reactions involving H2S.

The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for high-quality digitization of content from pages and whiteboards to sharable online material. But capturing this information is not always easy, nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop and clean an image of a page or whiteboard. Unlike equivalent systems, no user intervention is required during processing and the result is a high-contrast, low-noise image with a clean homogenous background. Results are presented for a selection of scenarios showing the versatility of the design. CleanPage is compared with two market leader scanning apps using two testing approaches: real paper scans and ground-truth comparisons. These comparisons are achieved by a new testing methodology that allows scans to be compared to unscanned counterparts, by using synthesized images. Real paper scans are tested using image quality measures. An evaluation of standard image quality assessments is included in this work and a novel quality measure for scanned images is proposed and validated. The user experience for each scanning app is assessed, showing CleanPage to be fast and easier to use.

The absorption of medium-chain fatty acids (MCFA) depends on the solubility of these components in the gastric fluid. Parameters such as the total MCFA concentration, carboxyl ionization level, and carbon chain length affect the solubility of these molecules. Moreover, the enzymatic lipolysis of solubilized triacylglycerol (TAG) molecules may depend on the carbon chain length of the fatty acids (FAs) components and their positions on the glycerol backbone. This present study aimed at investigating the effect of electrolyte usually formed during the gastric digestion phase on the solubility of MCFA, and evaluating the influence of the FA carbon chain length on the lipolysis rate during the in vitro digestion simulation. The results obtained here showed that the increasing of electrolyte concentrations tend to decrease the mutual solubility of systems composed by the caproic and caprylic fatty acids + sodium chloride, sodium bicarbonate, and potassium chloride solutions. We also observed that a conventional version of the thermodynamic UNIQUAC model was able to correlate the liquid-liquid phase behavior of the electrolyte solutions. Regarding the in vitro digestion simulation, the experimental data indicated that the action of the pancreatic enzyme occurred preferentially in TAG molecules comprised of short and medium-chain fatty acids.

(Background) Canine mammary tumors (CMT) have emerged as an important model for understanding pathophysiological aspects of human disease. Liquid biopsy (LB), which relies on blood-borne biomarkers and offers minimal invasiveness, holds promise for reflecting the disease status of patients. Small extracellular vesicles (SEVs) and their protein cargo have recently gained attention as potential tools for disease screening and monitoring. (Objectives) This study aimed to isolate SEVs from canine patients and analyze their proteomic profile to assess their diagnostic and prognostic potential. (Methods) Plasma samples were collected from female dogs grouped into CMT (malignant and benign), healthy controls, relapse, and remission groups. SEVs were isolated and characterized using ultracentrifugation (UC), nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM). Proteomic analysis of circulating SEVs was conducted using Liquid Chromatography–Mass Spectrometry (LC–MS). (Results) While no significant differences were observed in the concentration and size of exosomes among the studied groups, proteomic profiling revealed important variations. Mass spectrometry identified exclusive proteins that could serve as potential biomarkers for mammary cancer. These included Inter-alpha-trypsin inhibitor heavy chain (ITIH2 and ITI4), phosphopyruvate hydratase or alpha enolase (ENO1), eukaryotic translation elongation factor 2 (eEF2), actin (ACTB), transthyretin (TTR), beta-2-glycoprotein 1 (APOH) and gelsolin (GSN) found in female dogs with malignant tumors. Additionally, Vitamin D-binding protein (VDBP), also known as group-specific component (GC), was identified as a protein present during remission. (Conclusion) The results underscore the potential of proteins found in SEVs as valuable biomarkers in CMT. Despite the lack of differences in vesicle concentration and size between the groups, the analysis of protein content revealed promising markers with potential applications in CMT diagnosis and monitoring. These findings suggest a novel approach in the development of more precise and effective diagnostic tools for this challenging clinical condition.

This study addresses the challenge of treating skin cancer effectively, especially in visible areas like the face, where traditional methods may be undesirable. Current options, including surgery and radiation therapy, have limitations such as complexity, expense, and imprecise dose delivery. The proposed solution involves additively manufacturing personalized patches using diagnostic imaging data, offering a targeted and controlled dose of beta-emitting isotopes like Y-90. The patches, tailored to the tumor's shape and depth, aim to minimize damage to healthy tissues and structures. Through 3D printing technology we demonstrated the feasibility of creating individualized applicators filled with radioisotopes, that have the potential to deliver therapeutic doses while ensuring patient comfort and affordability. This innovative approach, based on radiation delivery simulations, offers a promising future alternative to conventional radiation therapy methods. Clinical trials are required to validate its efficacy and safety, but the potential for reduced radiation exposure and enhanced treatment precision positions this personalized and targeted therapy as a valuable advancement in skin cancer treatment.

Interest grows in designing silicon-on-insulator slot waveguides to trap optical fields in subwavelength-scale slots and developing their optofluidic devices. However, it is worth noting that the inherent limitations of the waveguide structures may result in high optical losses and short optical paths, which challenge the device performance in optofluidics. Incorporating the planar silicon-based slot waveguide concept into a silica-based hollow-core fiber can provide a perfect solution to realize an efficient optofluidic waveguide. Here we propose a subwavelength-scale liquid-core hybrid fiber (LCHF), where the core is filled with carbon disulfide and surrounded by a silicon ring in a silica background. The waveguide properties and the Stimulated Raman Scattering (SRS) effect in the LCHF are investigated. The fraction of power inside the core of 56.3% allows an improved sensitivity in optical sensing; while the modal Raman gain of 23.60 m-1·W-1 is 2 times larger than that generated around a nano fiber with the interaction between the evanescent optical field and the surrounding Raman media benzene-methanol, which enables a significant low-threshold SRS effect. Besides, this in-fiber structure features compactness, robustness, flexibility, ease of implementation in both trace sample consumption and reasonable liquid filling duration, as well as compatibility with optical fiber systems. The detailed analyses of the properties and utilizations of the LCHF suggest a promising in-fiber optofluidic platform, which provides a novel insight into optofluidic devices, optical sensing, nonlinear optics, etc.

Radical reactions in water or aqueous media are important for organic synthesis, realizing high yielding processes under non-toxic and environmentally friendly conditions. This overview includes (i) a general introduction to organic chemistry in water and aqueous media, (ii) synthetic approaches in-, on- and with-water as well as in heterogeneous phase, (iii) reaction of carbon-centered radicals with water (or deuterium oxide) activated through coordination with various Lewis acids, (iv) photocatalysis in water and aqueous media, and (v) synthetic applications bioinspired from naturally occurring processes. A wide range of chemical processes and synthetic strategies under different experimental conditions have been reviewed that lead to important functional group translocation and transformation reactions, leading to the preparation of complex molecules. These results reveal how water as a solvent/medium/reagent in radical chemistry has matured over the last two decades and how further discoveries are foreseen to come in the near future.

News on the stock market contains positive or negative sentiments depending on whether the information provided is favorable or unfavorable to the stock market. This study aims to discover the news sentiment and classify news according to its sentiments with the application of PhoBERT, a Natural Language Processing model designed for the Vietnamese language. A collection of nearly 40,000 articles on financial and economic websites is used to train the model. After training, the model succeeds in assigning news to different classes of sentiments with an accuracy level of over 81%. The research also aims to investigate how investors concern about the daily news by testing the movements of the market before and after the news is released. The analysis results show that there is an insignificant difference in the stock price as a response to the news. However, investors tend to overreact to negative and positive news in the Vietnam stock market.

In this study, 12 organic waste materials were subjected to TG/DTG thermogravimetric analysis and DSC calorimetric analysis. These analyses provided basic information about thermochemical transformations and degradation rates during organic waste pyrolysis. Waste materials were chosen to cover the most abundant waste that can be found in the municipal solid waste stream. Based on TG results, kinetic parameters according to Coats–Redfern method were determined. The pyrolysis activation energy was the highest for cotton 134.5 kJ∙(mol∙K)-1 and the lowest for leather 25.2 kJ∙(mol∙K)-1. The DSC analysis showed number of transformations occurred during pyrolysis for each material. For each transformation, normalized energy required for transformation, or released during transformation were determined and then summarized to present energy balance. The study found that only for three waste materials: PET (-220.1 J⸱g-1), leather (-66.9 J⸱g-1), and chicken meat (-130.3 J⸱g-1) energy balance was negative, while the highest positive balance value was found for potato peelings (367.8 J⸱g-1). The obtained results may be applied for the modelling of energy and mass balance of municipal solid waste pyrolysis.

Motivated by the way animals react in nature, we introduce a fully-connected neural-network model, which incorporates the external pattern presented to the system as a fundamental tool of the recognition process. In this new scenario, in the absence of this external field, memories are not attractors inside basins of attraction, as in usual attractor neural networks, although basins may be created according to the external pattern, thus allowing storing a much larger number of memories. The key point consists in calibrating the influence of the external pattern such as to cancel the noise generated by those memories not correlated with the external pattern.We illustrate how this proposal works by including this new contribution in the standard Hopfield model, showing a significant increase in its recognition capacity (typically by a factor $10^{2}$). As an additional feature of this model, we show its ability to react promptly to changes in the external environment, a crucial attribute of living beings. This procedure can be applied to a wide variety of neural-network models to increase considerably their recognition and reaction capabilities.

In this short review paper we have assembled the main characteristics of partial oxidation reactions (oxidative dehydrogenation and selective oxidation to olefins or oxygenates, as aldehydes and carboxylic acids and nitriles), as well as total oxidation, particularly for depollution, environmental issues and wastewater treatments. Both gas-solid and liquid-solid media have been considered with recent and representative examples within these fields. We have also discussed about their potential and prospective industrial applications. Particular attention has been brought to new raw materials stemming from biomass and to liquid-solid catalysts cases. This review paper also summarizes the progresses made in the use of unconventional activation methods for performing oxidation reactions, highlighting the synergy of these technologies with heterogeneous catalysis. Focus has been centered on usual catalysts activation methods but also on less usual ones, such as the use of ultrasounds, microwaves, grinding (mechanochemistry) and photo-activated processes, as well as their combined use.

(200 words) Imidazolium ionic liquids containing acetylacetone, thenoyltrifluoroacetone, or 8-hydroxyquinoline, respectively, were used as the extracting agents for the separation of traces of iron (III) from its aqueous solutions with or without citric and oxalic acids. The results show that 8-hydroxyquinoline in imidazolium ionic liquids extract iron quantitatively from all the tested solutions including complexing ones, regardless indications of unexpected iron behavior/speciation.

Acrylates and methacrylates are widely used, especially in the dental industry, but can cause adverse skin reactions. These compounds, including 2-hydroxyethyl methacrylate, triethylene glycol dimethacrylate, and bisphenol A-glycidyl methacrylate, are strong contact irritants or allergens. Found in dental prostheses, composite resins, dentin bonding materials, and glass ionomers, they pose a higher risk of exposure for dental personnel. Clinically, acrylate allergies manifest as facial rashes, eczema with cracked skin on fingers (pulpitis), nail dystrophy, and periungual dermatitis. Recently, the highest frequency of allergic reactions to acrylates has shifted from dentistry to the beauty industry due to increased use in artificial nails, eyelashes, and hair extensions. This has led to greater sensitization. Acrylates are also used in medical applications, such as bone cement for orthopedic endoprostheses, soft contact lenses, hearing aids, histological preparations, and wound dressings, which can also cause allergic reactions. Severe dermatitis from surgical glue containing acrylates has been documented, and diabetic medical devices are potential sources of allergic contact dermatitis. Given the extensive use and prolonged skin contact of products containing acrylates and methacrylates, this review aims to present current knowledge and literature on reactions to these compounds across different industries.

Strangeness flavor is abundant and in chemical equilibrium in the primordial Quark-Gluon Plasma(QGP) filling the early Universe. Upon hadronization near to T=150 MeV one may think that relatively short lived massive strange hadrons decay rapidly and strangeness disappears. However, we show using detailed balance considerations for inverse decay reactions that the back reaction repopulate strangeness keeping it in chemical equilibrium at least to the time when strange antibaryons annihilate near T≃30-50 MeV. However, our present study is focused on the meson sector of the hadronic Universe. Specifically, we establish here the temperature range in which the expansion of the Universe becomes faster compared to the production processes which balance natural strangeness decay: In the temperature interval 33MeV<T<20MeV: μ±+νμ→K±, π+π→K and l−+l+→ϕ reactions in sequence become slower compared to the characteristic Hubble time.

Abstract: Qatar and other Gulf States have a diverse range of marine vegetation that is adapted to the stressful environmental conditions of seawater. The industrial wastewater produced by oil and gas activities adds further detrimental conditions for marine aquatic photosynthetic organ-isms on the Qatari coastlines. Thus, these organisms experience severe stress from both seawater and industrial wastewater. This review discusses the biodiversity in seawater around Qatar, as well as remediation methods and metabolic pathways to reduce the negative impacts of heavy metals and petroleum hydrocarbons produced during these activities. These methods include phyto-stabilization phyto-accumulation, phyto-volatilization, and phyto-degradation. Phy-to-degradation in particular is discussed in detail, including metabolic pathways such as alkane and aromatic-compound degradation pathways. The role of microorganisms that are adjacent to or associated with these aquatic marine organisms is discussed, including rhizosphere biodeg-radation. In this type of biodegradation, exudates are released by plant roots and supply nutrients to microorganisms in the rhizosphere, which enhances their ability to degrade organic pollutants. Special attention is paid to mangrove forests and their roles in remediating shores polluted by industrial wastewater. Seagrasses (Halodule uninervis, Halophila ovalis, and Thalassia hemprichii) and seaweeds (Chlorophyta, Phaeophyta, and Rhodophyta) around the peninsula of Qatar are also discussed.

Many natural and artificial liquid environments such as rivers, oceans, lakes, water storage tanks, aquariums, and urban water distribution systems, are difficult to access. As a result, technology is needed to enable autonomous liquid sampling to monitor water quality and ecosystems. The existing in-situ sample acquisition and handling systems for liquid environments are currently limited to a single use and are semi-autonomous, relying on an operator. Liquid sampling systems should be robust and light and withstand long-term operation in remote locations. The system components involved in liquid sampling should be sterilisable to ensure reusability. Here, we introduce a prototype of a liquid sampler that can be used in various liquid environments and may be valuable for the scientific characterisation of different natural, remote, and planetary settings. The Autonomous Planetary Liquid Sampler (APLS) is equipped with pre-programmed fully autonomous extraction, cleaning, and sterilisation functionalities. It can operate in temperatures between -10 ℃ and 60 ℃ and pressure of up to 0.24 MPa (~24 m depth below mean sea level on Earth). As part of the control experiment, we demonstrate its safe and robust autonomous opera-tion in a laboratory environment using a liquid media with Bacillus subtilis. A typical sampling procedure required 28 s to extract 250 mL of liquid, 5 s to fill the MilliQ water, 25 s for circulation within the system for cleaning and disposal, and 200 s to raise the system temperature from ~30 °C ambient laboratory temperature to 150 °C. The temperature is then maintained for another 3.2 hours to sterilise the critical parts, allowing a setup reset for a new experiment. In the future, the liquid sampler will be combined with various existing analytical instruments to characterise the liquid solution and enable the autonomous, systematic monitoring of liquid environments on Earth.

Gas and power networks are tightly coupled and interact with each other due to physically interconnected facilities. In an integrated gas and power network, a contingency observed in one system may cause iterative cascading failures, resulting in network wide disruptions. Therefore, understanding the impacts of the interactions in both systems is crucial for governments, system operators, regulators and operational planners, particularly, to ensure security of supply for the overall energy system. Although simulation has been widely used in the assessment of gas systems as well as power systems, there is a significant gap in simulation models that are able to address the coupling of both systems. In this paper, a simulation framework that models and simulates the gas and power network in an integrated manner is proposed. The framework consist of a transient model for the gas system and a steady state model for the power system based on AC-Optimal Power Flow. The gas and power system model are coupled through an interface which uses the coupling equations to establish the data exchange and coordination between the individual models. The bidirectional interlink between both systems considered in this studies are the fuel gas offtake of gas fired power plants for power generation and the power supply to LNG terminals and electric drivers installed in gas compressor stations and underground gas storage facilities. The simulation framework is implemented into an innovative simulation tool named SAInt (Scenario Analysis Interface for Energy Systems) and the capabilities of the tool are demonstrated by performing a contingency analysis for a real world example. Results indicate how a disruption triggered in one system propagates to the other system and affects the operation of critical facilities. In addition, the studies show the importance of using transient gas models for security of supply studies instead of successions of steady state models, where the time evolution of the line pack is not captured correctly.

. Protein cysteine S-glycosylation is a relatively rare and less well characterized post-translational modification (PTM). Creating reliable model proteins that carry this modification is challenging. The lack of available model or natural S-glycosylated proteins significantly hampers the development of MS-based methodologies for detecting protein cysteine S-glycosylation in real-world proteomic studies. There is also limited MS-sequencing data describing easier to create synthetic S-glycopeptides. Here, we present the results of an in-depth manual analysis of automatically annotated CID/HCD spectra for model S-glucopeptides. The CID spectra show a long series of y/b-fragment ions with retained S-glucosylation, regardless of the dominant m/z signals corresponding to neutral loss of 1,2-anhydroglucose from the precursor ions. In addition, the spectra show signals manifesting glucosyl transfer from the cysteine position onto Lys, Arg side chains, and a peptide N-terminus. Other spectral evidence indicates that the N-glucosylated initial products of transfer are converted into N-furanosylated (i.e., glycated) structures due to Amadori rearrangement. We discuss the peculiar transfer of the glucose oxocarbenium ion (Glc+) to positively charged guanidinium residue (ArgH+) and propose a mechanism for the gas-phase Amadori rearrangement involving a hydride ion shift.

More than 700 anthocyanins are described so far, and many different sources are rich in these natural pigments. During the last few years, researchers have been focusing of strategies to recover and purify anthocyanins, from simple liquid-liquid extractions to more advanced supercritical CO2 extractions, however, with such a huge number of different sources, it’s extremely hard to get a simple and fast methodology that fits several sources, not only by the structural nature of the anthocyanins but also by the presence of specific groups of natural compounds. Using simple methodologies like solid-phase extraction resins represents a powerful economical and efficiency strategy. In this work, we tested several sources of structurally distinct anthocyanins, including purple basil, purple cabbage, purple sweet potato, butterfly pea flower, cornflower and wild pansy, in different resins to assess their efficiency in the obtention of anthocyanin-pure extracts. The results showed us that the combination of oasis HLB® resin followed by a cation-exchange SPE with DSC-MCAX® resulted in high-purity anthocyanin extracts for all the cases.

The goal of background reconstruction is to recover the background image of a scene from a sequence of frames showing this scene cluttered by various moving objects. This task is fundamental in image analysis, and is generally the first step before more advanced processing, but difficult because there is no formal definition of what should be considered as background or foreground and the results may be severely impacted by various challenges such as illumination changes, intermittent object motions, highly cluttered scenes, etc. We propose in this paper a new iterative algorithm for background reconstruction, where the current estimate of the background is used to guess which image pixels are background pixels and a new background estimation is performed using those pixels only. We then show that the proposed algorithm, which uses stochastic gradient descent for improved regularization, is more accurate than the state of the art on the challenging SBMnet dataset, especially for short videos with low frame rates, and is also fast, reaching an average of 52 fps on this dataset when parameterized for maximal accuracy using GPU acceleration and a Python implementation.

Redox mediators comprising I–, Co3+, and Ti3C2Tx MXene were applied to dye-sensitized solar cells (DSCs). In the as-prepared DSCs (I-DSCs), wherein hole conduction occurred via the redox reaction of I−/I3− ions, the power conversion efficiency (PCE) was not altered by the addition of Ti3C2Tx MXene. The I-DSCs were exposed to light to produce Co2+/Co3+-based cells (Co-DSCs), wherein the holes were transferred via the redox reaction of Co2+/Co3+ ions. A PCE of 9.01% was achieved in a Co-DSC with Ti3C2Tx MXene (Ti3C2Tx-Co-DSC), which indicated an improvement from the PCE of a bare Co-DSC without Ti3C2Tx MXene (7.27%). It was also found that the presence of Ti3C2Tx MXene in the redox mediator increased the hole collection, dye regeneration, and electron injection efficiencies of the Ti3C2Tx-Co-DSC, leading to an improvement in both the short-circuit current and the PCE when compared with those of the bare Co-DSC without MXene.

The ever-growing concerns about global warming and the rapid depletion of fossil fuels have triggered a rising interest in research for cleaner, more efficient and cost-effective energy generation. Organic Rankine cycle systems have immense potential to become a strong alternative to conventional methods of energy generation. However, such systems’ efficiency is limited by the performance of the incorporated gas expanders or prime movers. Conventional gas expanders often utilize ports or cam-operated valves. Ported expanders offer limited efficiency and controllability, and produce high emissions causing a large amount of heated and compressed gas to be wasted. Cam-operated valves, in contrast, increase expansion performance compared to ported expanders, however, they have no variability and adaptability to changes in system parameters such as gas pressure, temperature, dryness fraction, and load variation to name a few. On a positive note, this issue can be addressed by adopting a variable timing and fast-operating, control valve with an accurate and adaptive control mechanism at the expander inlet. A properly designed and controlled valve can greatly improve the system performance of gas expanders and pave the way for an efficient low-cost alternative energy generation. This manuscript provides a comparative review of recent progress on the design, modeling, optimization, and control aspects of valves for gas expanders. A clear pathway on the scope of further development is also drawn based on the present state of the art.

Owing to the growing concerns due to dwindling fossil fuel reserves, increasing energy demand and climate emergency, it is imperative to develop and deploy sustainable energy technologies to ensure future energy supply as well as transition to the net zero world. In this context, there is great potential in the biorefinery concept for supplying drop in biofuels in the form of biodiesel. Biodiesel as a fuel can certainly bridge the gap where electrification or the use of hydrogen is not feasible, for instance heavy vehicles, farm and marine transportation sector. However, biodiesel industry also leads to formation of large amount of crude glycerol as the byproduct. Crude glycerol due to presence of several impurities may not be a suitable feedstock for all high value products derived from glycerol but fits well with glycerol esterification for producing glycerol acetins, which have numerous applications. This review critically looks at the processes using nanostructured solid/liquid acid catalysts for glycerol esterification including the economic viability of the scale up.

Considering the high potential of hydrogen (H₂) as a clean energy carrier, the implementation of high performance and cost-effective biohydrogen (bioH₂) purification techniques is of vital importance, particularly in fuel cell applications. In this context, membrane technology is a potentially energy-saving solution to obtain high-quality biohydrogen. The most promising poly(ionic liquid) (PIL) - ionic liquid (IL) composite membranes previously studied by our group for CO₂/N₂ separation, containing pyrrolidinium-based PILs with fluorinated or cyano-functionalized anions, were chosen as starting point to explore the potential of PIL–IL membranes for CO₂/H₂ separation. The CO₂ and H₂ permeation properties at the typical conditions of biohydrogen production (T =308 K and 100 kPa of feed pressure) were measured and discussed. PIL–IL composites prepared with [C(CN)₃]^– anion showed higher CO₂/H₂ selectivities and H₂ diffusivities compared to those containing [NTf₂]^– anion. All the membranes revealed CO₂/H₂ separation performances above the upper bound for this specific separation, highlighting the composite incorporating 60 wt% of [C₂mim][C(CN)₃] IL.

Background: The Coronavirus Disease 2019 (COVID-19) pandemic presented a new challenge in modern medicine. The development of vaccines was followed by massive population vaccinations. A few reports on post-vaccination allergic reactions have made patients and medical personnel uneasy as to anti-COVID-19 vaccines’ allergising potential. Most of the studies in this area to date have been small, and some that were based on global databases skipped most of the allergic diseases and concentrated only on anaphylaxis. We aimed to analyse the incidence of serious allergic reactions based on the EudraVigilance (EV) database, regardless of the reported symptoms and allergy mechanism. Methods: The total number of administrated vaccine doses was extracted on the 5th October 2023 from Vaccine Tracker and included all administrations since vaccinations began in the European Economic Area (EEA). Data on serious allergic reactions to COVID-19 vaccines was extracted from the EudraVigilance database with the same time point. The code names of 147 allergic symptoms or diseases were used. Results: The frequency of serious allergic reactions per 100,000 administered vaccine doses was 1.53 for Comirnaty, 2.16 for Spikevax, 88.6 for Vaxzevria, 2.11 for Janssen, 7.9 for Novavax, 13.3 for VidPrevtyn Beta and 3.1 for Valneva. The most prevalent reported reactions were oedema (0.46) and anaphylaxis (0.40). Only 6% of these reactions were delayed hypersensitivity-oriented. Conclusions: The overall frequency of potential serious allergic reactions to COVID-19 is very rare. Therefore, COVID-19 vaccines seem to be safe for human use. The lowest frequency of allergic reaction was observed for Comirnaty and the highest for Vaxzevria.

Bayesian formulations of learning imply that whenever the evidence for a correlation between events in an animal’s habitat is sufficient, the correlation is learned. This implies that regularities can be learnt rapidly, from small numbers of learning examples. This speed of learning gives maximum possible fitness, and no faster learning is possible. There is evidence in many domains that animals and people can learn at nearly Bayesian optimal speeds. These domains include associative conditioning, and the more complex domains of navigation and language. There are computational models of learning which learn at near-Bayesian speeds in complex domains, and which can scale well – to learn thousands of pieces of knowledge (i.e., relations and associations). These are not neural net models. They can be defined in computational terms, as algorithms and data structures at David Marr’s [1] Level Two. Their key data structures are composite feature structures, which are graphs of multiple linked nodes. This leads to the hypothesis that animal learning results not from deep neural nets (which typically require thousands of training exam-ples), but from neural implementations of the Level Two models of fast learning; and that neu-rons provide the facilities needed to implement those models at Marr’s Level Three. The required facilities include feature structures, dynamic binding, one-shot memory for many feature struc-tures, pattern-based associative retrieval, unification and generalization of feature structures. These may be supported by multiplexing of data and metadata in the same neural fibres.

This paper presents technical solutions to increase Industry 4.0 maturity. Within the “5G-Enabled Manufacturing” project, a 5G network has been deployed at the shop floor to enable fast and scalable connectivity. This network was used to connect a grinding machine to a private cloud to enable visibility and transparency of the production data, which is the basis for Industry 4.0 and smart manufacturing. Results indicate a present lack of commercially available product independent solutions for interconnection and data transfer despite the availability of open standards and well-documented demonstrator projects. The solution is described and discussed regarding technical interoperability, focusing on the system layout, communication standards, and open systems. From the discussion, it is derived that manufacturing end-users are in need to expand and further internalize knowledge on future information and communication technologies to reduce their dependency on equipment and technology providers.

Enhancing the management and monitoring of oil and gas processes demands developing precise predictive analytics techniques. Over the past two years, oil and its prediction have advanced significantly using conventional and modern Machine Learning techniques. Several review articles detail the developments in predictive maintenance and technical and non-technical aspects of influencing the uptake of big data. The absence of references for machine learning techniques impacts the effective optimization of predictive analytics in the oil and gas sector. This review paper offers readers thorough information on the latest machine learning methods utilized in this industry's predictive analytical modelling. The review covers forms of Machine Learning techniques used in predictive analytic modelling from 2021 to 2023 (91 articles). It provides an overview of the details of the papers that were reviewed, comprising of the model’s categories, the data's temporality, field, and name, the dataset's type, predictive analytics (classification or clustering or prediction), the models' input and output parameters, performance metrics, optimal model, and benefits and its drawbacks. Additionally, suggestions for future research directions are provided to raise the potential of the associated knowledge and increase the accuracy of oil and gas predictive analytics models.

Fe-(9, 19, 28, 37)wt.% Cr alloys were corroded at 700 and 800 ^oC for 70 h under 1 atm of N₂, 1 atm of N₂/3.2%H₂O-mixed gas, and 1 atm of N₂/3.1%H₂O/2.42%H₂S-mixed gas. The corrosion rate of Fe-9Cr alloy increased with the addition of H₂O, and furthermore with the addition of H₂S in N₂ gas. Fe-9Cr alloy was always nonprotective. In contrast, Fe-(19, 28, 37) wt.%Cr alloys were protective in N₂ and N₂/H₂O-mixed gas because of formation of the Cr₂O₃ layer. They were, however, nonprotective in N₂/H₂O/H₂S-mixed gas because sulfidation dominated to form the outer FeS layer and the inner Cr₂S₃ layer containing some FeCr₂S₄.