Based on a constant volume combustion chamber, the initial ambient pressure effect on combustion performance and flame propagation of the active and passive pre-chamber ignition systems were studied. Compared with the passive pre-chamber, the active pre-chamber can significantly expand the lean combustion limit, enhance the ignition and combustion performance, and speed up the combustion of the main combustion chamber. At slightly lean combustion conditions, the heat release performance has a positive correlation with the initial ambient pressure. As the premixed λ increases, the heat release performance and the initial ambient pressure begin to become negatively correlated. Ignition delay can be minimized by controlling the excess air coefficient in the pre-chamber close to the stoichiometric ratio. The high ambient pressure in the constant volume chamber greatly reduces the mixture entrainment ability of the jet flame at lean combustion conditions, thereby reducing the combustion speed and peak heat release rate.

This paper develops a chemical model for a closed constant volume combustion of gaseous mixtures of methane and hydrogen. Since the combustion is strongly depending on temperature, pressure and fuel composition, they were chosen the actual corresponding thermodynamic systems using this kind of combustion, respectively the spark ignition reciprocating engines in order to evaluate the combustion parameters and exhaust flue gases composition. The actual cycles impose extra restrictive operational conditions through the engine volumetric compression ratio, the geometry of combustion volume, the mode to prepare the mixture of methane and hydrogen, the cooling system and the delivered power. The chemical model avoided the unknown influences in order to explain accurately the influence of hydrogen upon the constant volume combustion and flue gases composition. The model adopted simplifying hypotheses, respectively isentropic compression and expansion processes, closed constant volume combustion developed by two successive steps obeying to the energy and mass conservation laws and, flue gases exhaust described also by two steps, i.e. an isentropic expansion through the flow section of exhaust valves followed by a constant pressure stagnation (this succession is corresponding in fact to a throttling direct process). The chemical model supposed the homogeneous mixtures of gases with variable heat capacities function of temperatures, the Mendeleev - Clapeyron ideal gas state equation and, the variable chemical equilibrium constants for chosen chemical reactions. It was assumed that the flue gases chemistry is prevailing during the isentropic expansion and flue gases exhaust and has mainly a thermal ground. The chemical model allowed evaluation of flue gasses composition and of noxious emissions.

Gas turbine engines are widely used in various industries such as aviation, power generation, and marine propulsion due to their high efficiency and reliability. The combustion chamber of a gas turbine engine design contains a number of elements, including as the chamber's size and form, the fuel injection system, the ignition system, and the cooling system and it plays a critical role in the performance and efficiency of the engine. This research discusses the fabrication of a combustion chamber model for a gas turbine engine. The aim of this research is to develop a combustion chamber that is cost-effective, easily available, and can be fabricated in less time. The research covers the different types of combustion chambers used in gas turbine engines and compares their advantages and disadvantages. It then selects the best type of combustion chamber for the gas turbine engine based on its cost, availability, and fabrication time, Efficiency and high power to fuel ratio. The report also describes the fabrication process involved, including the techniques and materials used, along with safety precautions and environmental protection measures. Lastly, the research suggests future improvements and potential applications for the fabricated combustion chamber model.

A review discusses recent research findings spanning the last two decades concerning ultrasonic technologies applicable to the oil, gas, and coal sectors. Various experiments conducted in laboratories have demonstrated the efficacy, cost-effectiveness, and environmental friendliness of ultrasound in recovering and processing oil, bitumen, coal, and oil shale. Ultrasound enhances formation permeability, coal gas permeability, and oil viscosity, particularly when delivered in short, powerful pulses at medium frequencies. Combining ultrasound with traditional recovery methods has shown promising results, boosting recovery efficiency by up to 100%. At the same time, ultrasonic treatment reduces the use of traditional reagents, thereby reducing environmental pollution. Moreover, ultrasound treatment shows potential in tasks such as separating oil-water emulsions, desulfurization, dewaxing oil, coal enrichment, and extracting valuable metals from metal-bearing shales through hydrometallurgical leaching. However, widespread industrial implementation of ultrasonic technology necessitates further field and mathematical research.

This research aims to delve into the intricacies of combustion processes, specifically focusing on heating oil and a blend of heating oil with TPO (Tire Pirolysis Oil) in a self-developed evaporative combustion chamber featuring steam injection. The primary objective is to scrutinize the impact of steam injection on the combustion dynamics. Conducting a series of tests, the investigation involved the meticulous manipulation of stoichiometric ratios while introducing ambient air through gravity fuel flow. Subsequent iterations of these tests incorporated the introduction of steam into the ambient air stream. The examination encompassed the combustion of both heating oil and the TPO blend within the combustion chamber. The evaluation criteria comprised an in-depth analysis of flame characteristics, temperature distribution within the combustion chamber, and the quantification of emissions such as particulate matter (PM), nitrogen oxides (NOx), carbon dioxide (CO2), carbon monoxide (CO), and water vapor (H2O). Throughout the experimentation phase, commercially available diesel fuel served as the primary fuel source. To facilitate the tests, the combustion chamber under scrutiny was seamlessly integrated into an AVL engine test bench system. Essential parameters, including fuel consumption, were meticulously gauged using an AVL 735 fuel flow meter, while fuel temperature was monitored using the AVL 745 fuel temperature conditioning system. The intake air, a crucial element in the combustion process, was quantified with precision using an AVL Flowsonix sensor. Emission measurements were conducted meticulously using state-of-the-art equipment, with gaseous emissions analyzed using an AVL FTIR AMA i60 exhaust gas analyzer. Simultaneously, soot emissions were quantified through employment of an AVL Micro Soot sensor. This comprehensive approach not only delves into the fundamental aspects of combustion but also extends its reach to the exploration of innovative techniques, such as steam injection, to enhance combustion efficiency and reduce emissions. The integration of advanced measurement tools ensures a robust and thorough analysis of the combustion process and its environmental implications.

Dental pulp chamber volume is a fundamental measurement in the field of endodontics, but also in forensic sciences, teaching and training, or tissue engineering. This study evaluates the precision of cone beam computed tomography (CBCT) in comparison with computed micro-tomography (micro-CT) in evaluating pulp chamber volume of upper central incisors ex vivo. The intra-operator and inter-operator error were evaluated, and the results for the two techniques were compared with a T-test for paired samples. Intra-operator and inter-operator errors were >0.05, indicating an adequate reproducibility in each operator and no significant differences between their meas-urements. On the other hand, no significant differences between the two measurement techniques. The present results demonstrate that CBCT is a precise, feasible and reproducible technique for evaluation of dental pulp chamber volume ex vivo. Results provided with this method are suitable for different medical branches but also for teaching and training of undergraduate and post-graduate students. Furthermore, the findings of this study carry significant clinical implications, as accurate assessment of pulp chamber volume is critical in the diagnosis and treatment of various endodontic conditions. The ability of CBCT to provide reliable 3D dental anatomy measurements can enhance the planning of endodontic treatments by allowing for a better understanding of internal tooth morphology. Additionally, the precision and reproducibility of CBCT in assessing pulp chamber volume can contribute to improved clinical outcomes and reduced complications during endodontic procedures. These findings further support the increasingly vital role of CBCT in modern clinical practice and underscore its value as an indispensable tool in the field of dentistry.

Soil contamination and the uptake of contaminants by food crops is a global problem that differs significantly from region to region, with the key factors affecting the contaminants present in local soils being the mineralogical composition of the underlying layers and local human activity. The area of ​​the Pannonian region is known for the fact that agriculture has, historically, played an important role since Roman times, which was particularly influenced by human activity. In this study we performed a preliminary study of the contamination of soil samples across the Pannonian region, to determine the potential presence of harmful contaminants. Both soil and crop samples were analysed for the potential presence of heavy metals, with additional focus placed on the potential presence of microplastics in the region`s soil.

Research on engine operation using hydrogen may enable appropriate optimization of thrust and, therefore, performance related to its potential use in aircraft. It is particularly important that the share of hydrogen in combustion affects the reduction of combustion products such as carbon dioxide, carbon monoxide, nitrogen oxide, hydrocarbons and solid matter. This is in line with the new requirements regarding the increased supply of sustainable aviation fuels (SAF) and the related changes in emissions, i.e. reducing the harmful impact of exhaust gases on the environment. The paper presents the results of measurements carried out in the GTM400 MOD turbojet engine. Based on the research performed, the impact of hydrogen and aviation kerosene combustion on selected engine parameters was presented. The paper shows changes in the rotational speed and volume flow of JET A-1 fuel as a function of engine operation time. Changes in temperature measured at the edge of the flame tube were also examined. The tests confirmed that the combustion chamber works correctly in the selected area in the range of tested fuel mixtures. After incorporating hydrogen into the combustion process, the consumption of traditional JET A-1 fuel was significantly reduced.

The knowledge of the precise anatomy and dimensions of the pulp chamber in the different teeth allows the odontologist to perform correct diagnosis, as well as treatment planning and moni-toring. The clinical practice has introduced cone-beam computed tomography (CB-CT) as a method to evaluate the morphology and dimensions of the pulp chamber. Nevertheless, micro-computed tomography (micro-CT) is regarded as the gold standard in approaching those topics. Here we have designed an algorithm that takes as input DICOM images from in vivo CB-CT of permanent molars to determine the accuracy CB-CT for evaluation of pulp chamber volume. The values were compared with those from in vivo CB-CT (rough and expert manipulated) and ex vivo micro-CT. The relative errors obtained with the volume calculated by the algorithm vs. the volume measured by micro-CT do not exceed 5.7%; also, no significant differences were found between algorithm volumes vs. manipulated CB-CT volumes while all volumes were different from those obtained with automatic CB-CT software. These data demonstrate that volume algorithm CB-CT based may be a reliable technique for evaluation of the pulp chamber volume in permanent molars and can be useful in the diagnosis of pulp diseases, as well as in the planning and monitoring of their treatments.

Gas turbine power plants have important roles in the global power generation market. The examines thermodynamically the impact of steam injection for a combined cycle including a gas turbine cycle with a two-stage turbine and carbon dioxide recompression. The combined cycle is compared with the simple case without steam injection. Steam injection’s impact is observed on important parameters such as energy efficiency, exergy efficiency, and output power. It is revealed that steam injection reduces exergy destruction in components compared to the simple case. The efficiencies for both cases are obtained. The energy and exergy efficiencies respectively are found to be 30.4% and 29.4% for the simple case, and 35.3% and 34.1% for the case with steam injection. Also, incorporating steam injection reduces emissions of carbon dioxide.

The high dependence on light crude oil as the main source of energy in automobiles., industrial processes, source of raw material for various industrial synthesis have made the heavy crude more available in the world and open for research work on its potentials as a source of energy for the increasing population of the world in areas like energy source for powering big marine engines, energy source in heavy industrial machines e.t.c. Though the relatively unfavourable characteristics of heavy fuel oil such as; high viscosity, high probability of precipitating is a reasonable challenge to the possible utilization of heavy fuel as a source of energy in the areas highlighted above. These issues of heavy fuel oil are largely due to the presence of Asphaltene in it which is a large complex hydrocarbon in heavy fuel oil. Understanding the combustion potential of asphaltene is therefore an interesting and challenging problem that has attracted increasing attention from both academia and industry. This research work is aimed at carrying combustion studies on the Forcados (Ni-geria) heavy fuel fraction asphaltene HFFA extracted from Forcados crude Oil and examining its combustion characteristics with the view to examine it for future sweet heavy fuel generation for it source got low sulphur content, to ascertain the volatile composition, moisture and ash content. The HFFA extracted to determine physical characteristics of the HFFA extracted for fuel properties potentialities and this study was carried out to evaluate the chemical constituents of forcadous asphaltene lead-ing to the generaration of HFFA using GCMS. The Forcados asphaltene showed some good fuel properties when subjected to ce-tane number, API gravity, flash point and cloud point parameter test. Probing further with AAS for trace metal presence showed some high concentration on Chromium (Cr), Nickel (Ni), Iron (Fe), Lead (Pb), Cadmium (Cd), Copper (Cu), Manganese (Mn) and Zinc (Zn) indicating the potential for residual and soot formation after combus-tion. But still being a sweet asphaltene from Nigerian sweet crude source will be de-void of corrosive effect on machineries and heavy fuel engine if used to power it as in the case of high sulphur content in Venezuelan crude oil and some other world. The GCMS showed the decomposition of heavy crude asphaltene peaks and sig-naling the presence of heavy fuel fraction in the composition of the asphaltene while the FTIR and the UV-VIS identified the various functional groups in the compounds and the identification of signals that cannot be seen in the normal spectrum respec-tively.

The implementation of sentinel lymph node (SLN) biopsy is changing the scenario in the surgical treatment of early-stage cervical cancer and the oncologic safety of replacing bilateral pelvic lymphadenectomy with SLN biopsy is currently under investigation. One of the undisputed values of SLN biopsy is its diagnostic accuracy in detecting low-volume metastases (LVM) via pathologic ultrastaging. In early-stage cervical cancer, the reported incidence of LVM ranges from 4 to 20%. The prognostic impact and the role of adjuvant treatment in patients with LVM is still unclear. Some non-prespecified analyses in prospective studies showed no impact on the oncologic outcomes compared to node-negative disease. However, the heterogeneity of the studies, the differences in the disease stage and the use of adjuvant treatment, and the concomitant pelvic lymphadenectomy (PLND) make any conclusion on this topic hard. Current guidelines suggest considering micrometastasis (MIC) as a node-positive disease, while isolated tumor cells (ITC) as a node-negative disease, with a low level of evidence. This review aims to highlight the unanswered questions about the definition, identification, prognostic and therapeutic role of LVM and underline the present and future challenges we are facing. We hope this review will guide further research, giving robust evidence on LVM and their impact on clinical practice.

While various studies have explored the integration of sustainability in the construction sector of Tanzania, particularly in areas like energy efficiency and green building practices, there remains a significant gap in understanding the specific barriers to the selection of sustainable building materials (SBMs) in residential projects. This research intends to bridge this gap by identifying and analyzing the critical barriers that hinder the effective selection of SBMs in Tanzania's residential building projects. By employing qualitative interviews with experts from regulatory bodies, public developers, and academic researchers, the study provides a comprehensive overview of the barriers. To ensure the collection of relevant and insightful data, the study involved the selection of participants based on specific criteria tailored to each category of experts. To be able to analyze qualitatively the data collected, this study employed Atlas.ti and MS Excel software. The findings revealed six categories of critical barriers affecting the selection of SBMs for residential building projects in Tanzania were identified and analyzed: (1) Regulatory and Policy Barriers (2) Financial Barriers (3) Knowledge and Awareness Barriers (4) Technical Barriers (5) Market and Supply Chain Issues (6) Cultural and Social Barriers. Moreover, the lack of awareness and limited knowledge issue were as equally importantly voiced as regulatory and policy barriers to affect the effective selection of sustainable materials in Tanzania. This study underscores the need for targeted policy interventions that address the lack of awareness, financial difficulties, and the absence of comprehensive regulatory frameworks to promote the selection of sustainable materials.

This study investigates the characteristics of activated carbons derived from biomass plant residues: rice husk (OSL) of the genus Oryza, reed stalks (PhAC) of the genus Phragmites, pine sawdust (PSL) of the genus Pinus, and wheat straw (TAL) of the genus Triticum. Activation was carried out using potassium hydroxide, employing a two-stage pyrolysis under air. The study examined the influence of activation temperature, duration, concentration of the impregnating agent, and impregnation time. Characteristics such as sorbent porosity, bulk density, and hydrocarbon sorption capacity were determined. Adsorption capacity was assessed using BET analysis and the iodine number determination method, with the highest iodine number achieved being 2809 mg/g, indicating high adsorption capability. The structural morphology of the activated carbons was evaluated by SEM, and their chemical surface characteristics were identified by IR spectroscopy. Computational analysis of the nitrogen sorption isotherms using the Barrett-Joyner-Halenda (B-J-H) method and the Dubinin-Radushkevich (D-R) equation showed that activated carbon samples from rice husk and pine sawdust possess a developed specific surface area and contain micro- and mesopores. The Dubinin-Astakhov (D-A) approach was used to study the pore diameter of activated carbon, revealing significant findings on pore structure. The maximum micropore volume was found in activated carbon samples from pine sawdust (PSL), measuring 0.46 cm³/g. All activated carbon samples of plant origin were tested under field conditions for the remediation of oil-contaminated areas near the “Zhanatalap” oil field in the Atyrau region. By the 16th day, the oil-contaminated soil treated with rice husk activated carbon was cleaned by 67.1%.

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.

In the context of improving aircraft safety, this study focuses on the development and evaluation of a graphene-based ice detection system using an environmental chamber. The research is driven by the need for more accurate and efficient ice detection methods, crucial in mitigating in-flight icing hazards. The methodology employed involves testing flat graphene-based sensors in a controlled environment, simulating a variety of climatic conditions that could be experienced in an aircraft during its entire flight. The environmental chamber enabled precise manipulation of temperature and humidity levels, thereby providing a realistic and comprehensive test bed for sensor performance evaluation. The results were significant, revealing the graphene sensors’ heightened sensitivity and rapid response to the subtle changes in environmental conditions, especially the critical phase transition from water to ice. This sensitivity is the key to detecting ice formation at its onset, a critical requirement for aviation safety. The study concludes that graphene-based sensors, tested under varied and controlled atmospheric conditions, exhibit a remarkable potential in enhancing ice detection systems for aircraft. Their lightweight, efficient and highly responsive nature makes them a superior alternative to traditional ice detection technologies, paving the way for more advanced and reliable aircraft safety solutions.

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.

To realize the utilization of peanut shell, this study investigates the combustion behavior, chemical kinetics, and thermodynamic parameters of peanut shell using TGA under atmospheric air. Results indicate that increasing the heating rate leads to higher ignition, burnout, and peak temperatures, as observed in the TG/DTG curves shifting to the right. Analysis of combustion performance parameters suggest that higher heating rates can enhance combustion performances. Kinetic analysis using two model-free methods, KAS and FWO, shows that the activation energy (Eα) ranges from 93.30 to 109.65 kJ/mol for FWO and 89.72 to 103.88 kJ/mol for KAS. The data fit well with coefficient of determination values (R2) close to 1. Pre-exponential factors using FWO range from 2.19×106 to 8.06×107 s–1, and for KAS range from9.72×105 to 2.25×107 s–1. Thermodynamic analysis indicates a low-energy barrier (≤ ±6 kJ/mol) between activation energy and enthalpy changes, suggesting easy reaction initiation. Furthermore, variations in enthalpy (ΔH), Gibbs free energy (ΔG), and entropy (ΔS) upon conversion (α) suggest that peanut shell combustion is endothermic and non-spontaneous, with the generation of more homogeneous or well-ordered products as combustion progresses. These findings offer a theoretical basis and data support for the further utilization of agricultural biomass.

Given the conceptual confusion between resilience and sustainability in organizations in the literature, the present study reviews the 27-year global literature on resilience and sustainability in organizations to clarify the relationship between the two, and derive a framework as cutting-edge knowledge on how to ensure resilience and sustainability in organizations. Findings uncover five schools of thought: Sustainable Business Strategy, Predictive Analytics, Sustainable Supply Chain, Ecological Resilience and Sustainable Leadership. A cutting-edge framework, comprising sustainability practices, sustainability outputs, sustainability and resilience outcomes, is derived to guide future research and inform practitioners on how to ensure resilience and sustainability in their organizations.

The nozzle is the key element of the water jet generator for energy conversion. In order to explore the influence of the nozzle diameter on the pressure characteristics of the supercharged pulsed water jet plenum chamber, a supercharged pulsed water jet pressure acquisition system was established, and the Equations of motion and theoretical pressurization ratio equations of the supercharged pulsed water jet generator were established. The pressurization chamber pressure acquisition experiments under different nozzle diameters were carried out. The research results indicate that there is a critical nozzle diameter. When the nozzle diameter is less than the critical diameter, the pressure in the boost chamber is equal to the product of the driving pressure and boost ratio. As the nozzle changes, there is no significant change in the peak pressure and frequency of the boost chamber; When the nozzle diameter is greater than the critical diameter, there is a non-linear relationship between the boost chamber pressure and the driving pressure. As the nozzle diameter gradually increases, the actual boost ratio gradually decreases, and the peak pressure of the boost chamber further decreases. The nozzle diameter can no longer provide a load for the establishment of fluid pressure in the boost chamber. The research results provide a research basis for further controlling the pressure characteristics of the boost pulse water jet.

This article explores the use of vegetation indices (VIs) in remote sensing for estimating standing wood volume and volume increments in forest ecosystems. The study investigates the correlations between various VIs and wood volume across different forest stand age classes, focusing on the effectiveness of commonly used indices such as Squared Ratio Simple Red Edge (SQSR) and Red-Edge Ratio Vegetation Index (RERVI), as well as other typical indicators including Enhanced Vegetation Index (EVI), Red-Edge EVI (RE-EVI), and Green Normalized Difference Vegetation Index (GNDVI). Additionally, the analysis considers a pair of indicators based on blue and near-infrared channels, resembling the Blue-normalized Difference Vegetation Index (BNDVI). The research reveals that quadratic and power-law models of SQSR and RERVI demonstrate higher correlations (>0.40) with wood volume, especially in younger forest stands (>0.80). Furthermore, the study highlights the potential of NDII and NDWI indices for estimating volume increments in certain classes of forest stands (0.70). However, correlations vary across different forest stand classes, suggesting the need for further investigation into the reliability of VIs for monitoring wood volume and volume increments in forest ecosystems. Overall, this research contributes to the understanding of the applicability of VIs in remote sensing for forest management and ecosystem monitoring.

This study investigates the impact of thin flame combustor design on hydrogen flame characteristics and combustion performance through numerical simulations. Variations in flame shape and combustibility between 100% methane and 100% hydrogen combustion are analyzed. Three combustor header shapes (flat, concave, and convex) are modeled to assess their influence on flame behavior. Results show distinct flow patterns, with concave headers promoting strong central flows and convex headers dispersing the flow outward. Temperature field analysis indicates that hydrogen flames have higher temperatures and shorter quenching distances compared to methane flames. A comparative analysis of combustion products is conducted to evaluate combustion performance and NOx emissions. Consequently, the concave header has high combustibility and increases temperatures and NOx fraction in hydrogen combustion.

Visualization of volumetric data holds great importance, particularly in medical and biomedical applications. Various imaging techniques, such as FMRI and 3D microscopy, are employed to generate volumetric data, used in medical practice, research, and teaching. Commonly utilized tools like 3D Slicer, Fiji, and MATLAB ® aid in rendering and analyzing 3D images. However, these tools may lack comprehensive rendering functionality and face challenges in handling computational demands as data sizes grow. To address these limitations, this work introduces a GPU-supported renderer with a MATLAB ® interface. This solution gives the user flexible control over rendering parameters and optimizes data transfer through a memory management system. By leveraging the computational power of NVIDIA GPUs, the renderer enables complex and high-quality renderings, enhancing speed and efficiency. It therefore facilitates the analysis and visualization of volumetric data within an integrated environment, namely MATLAB ®, streamlining their workflows. This advancement provides valuable opportunities for researchers and medical professionals to explore and comprehend volumetric data effectively.

Resonance inductive coupling is widely used for wireless power transfer (WPT) in medical applications. In this paper, we analyze the LCL-compensated WPT structure and propose a novel constant voltage transmission system based on gain estimation, without any extra feedback from the receiver. The system is capable for implant neural stimulation where the load impedance and the coupling coefficient are both variable. Compared to existing methods for constant voltage transmission, our approach offers advantages in compact size and the compatibility with the industrial, scientific and medical (ISM) band. We validate the load-independent resonant characteristic and the feasibility of constant voltage transmission using an experimental prototype working at 6.78MHz. Finally, we discuss the structure of the implant stimulator and methods of applying the proposed WPT system.

This study proposes and validates a novel combustion control system for Oil-Fired Boilers aimed at reducing air pollutant emissions through flame image prediction. The proposed system is easily applicable to existing ships. Traditional proportional combustion control systems supply fuel and air at fixed ratios according to the set steam load, without considering the emission of air pollutants. To address this, a stable and immediate control system is proposed, which adjusts the air supply to modify the combustion state. The combustion control system utilizes oxygen concentration predictions from flame images via SEF+SVM as control inputs, and applies Internal Model Control (IMC)-based Proportional-Integral (PI) control for real-time combustion control. Due to the complexity of modeling the image-based system, IMC parameter tuning through experimentation is essential for achieving effective control performance. Experiments conducted on a 3000 kg/h marine oil-fired boiler in actual operation optimized the controller parameters for stability and responsiveness, and validated their effectiveness. The results demonstrate the potential of the proposed system to improve combustion efficiency and reduce emissions of air pollutants. This study provides a feasible and effective solution for enhancing the environmental performance of marine oil-fired boilers. Given its ease of application to existing ships, it is expected to contribute to sustainable air pollution reduction across the maritime environment.

Demand for environmentally friendly types of energy is growing all over the world, which naturally increases the intensity of work on the production of hydrogen-containing fuel mixtures. Steam reforming of methanol is one of the most effective areas of research, as it is a process with low energy consumption. The results of steam reforming of methanol on the catalysts prepared by solution combustion synthesis (SCS) and impregnation by moisture capacity are presented. Investigation of the activity of Cu-Ce-Al catalysts of different composition was carried out for production of hydrogen and comparison of SCS with traditional impregnation method. Methanol conversion reaches 99%, while the selectivity of H2 was 88%, at 500 °C. It was found that CuAl2O4 spinel formation is due to substitution of Al3+ with Cu2+ Ce3+ cations. A consequence CuAl2O4 and CeAlO3 lattice parameters increase because of difference in ionic radius of Al3+ (0.53 Å) and Cu2+ (0.73 Å), Ce3+ (1.07 Å). Advantages of SCS catalysts in steam reforming of methanol were shown. The aim of this research is to develop a new catalyst for conversion of methanol into hydrogen containing fuel mixtures, which will further promote the organization of a new era of environmentally friendly energy-saving production methods.

Porter's diamond model was used because it is an index in the field of competitiveness and increasing the index of competition in the international arena. In order to measure actions in the field of commerce and marketing trends and its compliance with Porter's diamond model, an organization named Isfahan Chamber of Commerce, Industries, Mines and Agriculture was selected from among the existing non-governmental organizations in Iran. This non-governmental organization, having different departments has members and subgroups related and influential in the field of commerce and marketing. In order to answer the question raised in this research, that is, to determine the position of the Isfahan Chamber of Commerce, Industries, Mines and Agriculture in Porter's diamond model, by referring to this organization in person, the available documents, information and data available in a descriptive-survey manner. It was reviewed until October 2022. All key activities and works performed in this organization in the period from March 2019 to March 2022 were identified and separated according to the internal factors of Porter's Diamond model. Finally, the credibility and effectiveness of this non-governmental organization as a link between the private sector and the government was measured in the Porter's diamond model.

To verify the concept of the metasurfaced reverberation chamber (MRC) which was proposed. This paper reports on measurements in the reverberation chamber (RC) performance by using a 1-bit random coding metasurfaced stirrer. The measurement results are validated and compared with that from two mechanical stirrers (horizontal stirrer and vertical stirrer). Figures of merit such as quality factor (Q factor), number of samples, standard deviation, angle autocorrelation, average K-factor, total scattering cross section (TSCS) and the enhanced back scattering coefficient (eb) are presented. Results indicate the feasibility of the MRC technique in the operation frequency of the RC. And it is possible to enlarge the test volume of the RC by using the 1-bit random coding metasurface stirrer.

This paper introduces a novel method for accurately calculating the upper biomass of single trees using Light Detection And Ranging (LiDAR) point cloud data. The proposed algorithm involves classifying the tree point cloud into two distinct ones: the trunk point cloud and the crown point cloud. Each part is then processed using specific techniques to create a 3D model and determine its volume. The trunk point cloud is segmented based on individual stems, with each stem further divided into slices that are modeled as cylinders. On the other hand, the crown point cloud is analyzed by calculating its footprint and gravity center. The footprint is further divided into angular sectors, with each being used to create a rotating surface around the vertical line passing through the gravity center. All models are represented in a matrix format, simplifying the process of minimizing and calculating the tree’s upper biomass, consisting of crown biomass and trunk biomass. To validate the proposed approach, both terrestrial and airborne datasets are utilized. A comparison with existing algorithms in the literature confirms the effectiveness of the new method. The study shows that the proposed algorithm achieves an average fit between 0.01 m and 0.49 m for individual trees.

The organic material present at the same depth in the reservoir has the potential for conversion, as indicated by analyses conducted before and after combustion in the development of heavy oil. This paper examines the oxidation and pyrolysis reaction pathways of hydrocarbons, specifically benzaldehyde (C₇H₆O) and naphthalene (C₁₀H₈), before and after combustion using molecular dynamics simulations. The primary products formed under various temperature conditions include H₂O, HO₂, CO, and CO₂. The discussion includes the number of molecules, such as HO and H, as well as their temperature variations. The activating group functions as an electron donor, while the inactivating group serves as an electron acceptor. The oxidation and pyrolysis reactions of naphthalene and the synthesis pathway of benzaldehyde are also explored. The C-C dissociation pathway in the early stages of combustion and the process of C-C bond synthesis in the later stages of the reactions are investigated through dynamic simulations at different temperatures: 3000 K, 3500 K, and 4000 K, with a particular focus on the reaction network at 4000 K. The application of the molecular reaction dynamics method to heavy oil combustion research is the primary objective of this work. This study aims to provide a novel approach to investigating hydrocarbon conversion at high temperatures and offers recommendations for enhanced oil recovery.

Keywords: Biomass pyrolysis, Chemical Looping Combustion, Life Cycle Assessment, Environmental Impacts, Carbon Footprint.

Hydrogen plays a key role in the transition to a carbon-free economy. One of the areas of hydrogen use is the substitution of hydrocarbon fuel in gas turbine engines and power plants. This review article discusses the features of hydrogen combustion and their influence on the characteristics of combustion chambers in comparison with methane. The paper presents both the results of a study of pure hydrogen or methane and methane-hydrogen mixtures with different hydrogen content. Among the main features, it is worth noting a smaller ignition delay time and higher laminar flame speed with a shift in its maximum value to a rich mixture, which significantly affects on flashback inside burners premixer, especially at elevated air temperatures. Another feature is the increased temperature of the flame, which can lead to an increase in the rate of nitrogen oxides formation. However, wider combustion concentration ranges contribute to the stable combustion of hydrogen at temperatures lower than those of methane. Along with this, it was shown that even at the same adiabatic temperature, more nitrogen oxides are formed in a hydrogen flame than in a methane flame, which indicates an additional mechanism for NOx formation in addition to the Zeldovich mechanism. The article also summarizes some of the results of a study on the effect of hydrogen on the occurrence of thermoacoustic instability, which depends on the initial nature of pulsations during methane combustion. The presented data will be useful both to engineers who are engaged in solving the problems of designing hydrogen combustion devices, and to scientists in this field of study.

The dielectric constant (ε) reflects the ability of a material to align and orient electrical dipoles within its structure in response to an externally applied electric field; the greater the polarizability of molecules, the greater the value of dielectric constant. In this study a data set of 86 polymers was investigated to develop a structure-property quantitative relations (QSPR) model to predict the dielectric constant in polymers. An initial set of 1273 descriptors was used to select a best set of descriptors and to construct two machine learning models with Gradient Boosting Regressor (GB_A and GB_B). The best performing model (GB_A) with 8 descriptors, exhibited a performance of (R2train) = 0.938 and (R2test) = 0.802. The models were internally validated by 5 folds cross-validation, demonstrating robustness. Additionally, using the Accumulative Local Effect (ALE) technique, we analyzed the relationship between the 8 descriptors involved and the impact of these descriptors to dielectric constant of polymers.

Digital photogrammetry has attracted widespread attention in the field of geotechnical and geological survey due to its low-cost, ease of use and contactless mode. In this work, with the purpose of studying the progressive block surficial detachments of a landslide we developed a monitoring system based on fixed multi-view time-lapse cameras. Thanks to a new-developed photogrammetric algorithm based on the comparison of photo sequences through a structural similarity metric and the computation of the disparity map of two convergent views we can quickly detect the occurrence of collapse events, determine their location and calculate the collapse volume. With the field data obtained at the Perarolo landslide site (Belluno Province, Italy), we have preliminary tested the effectiveness of the algorithm and its accuracy in the volume calculation. The method of quickly and automatically obtaining collapse information proposed in this paper can extend the potentials of landslide monitoring system based on videos or photo sequence and it will be of great significance for further research on the link between the frequency of collapse events and the driving factors.

We reduplicate the Book “Dark Energy” by M. Li, X-D. Li, and Y. Wang, given zero-point energy calculation with an unexpected “length’ added to the ‘width’ of a graviton wave just prior to specifying the creation of ‘gravitons’, using the Rosen and Israelit model of a nonsingular universe. In doing so we are in addition to obtaining a wavelength 10^30 times greater than Planck’s length so we can calculate DE, may be able to with the help of the Rosen and Israelit model have a first approximation as to the arrow of time, and a universe with massive gravity. We have left the particulars of the nonsingular starting point undefined but state that the Rosen and Israelit model postulates initial temperatures of 10^-180 Kelvin and also a value of about Planck temperature, at 10^-3 centimeters radii value which may satisfy initial conditions asked by t’Hooft for describing an arrow of time. A key assumption is that the DE is formed at 10^-3 cm, after an expansion of 10^30 times in radii, from the Planck length radius nonsingular starting point. The given starting point for DE in this set of assumptions is where there is a change in the cosmic acceleration, to a zero value, according to Rosen and Israel, with time t = 1.31 times 10^-42 seconds. Which may be where we may specify a potential magnitude, V, which has ties into inflaton physics. The particulars of the model from Rosen and Israelit allow a solution to be found, without discussion of where that nonsingular starting point came from, a point the author found in need of drastic remedies and fixes.

Soot combustion experiments with 5%O2/He were conducted using model soot, and four distinct compositions of CexPr1-xO2-δ oxides were prepared, varying nominal cerium com-positions (x=0, 0.2, 0.3, and 1). The catalyst samples were comprehensively characterized using techniques such as XRD, Raman spectroscopy, HR-TEM, N2 adsorption at −196 °C, XPS, O2-TPD, H2-TPR, and work function measurements. The Pr-rich compositions, rang-ing from Ce0.3Pr0.7O2-δ to PrO2-δ, resulted in a significant increase in the total evolved O2 amounts and enhanced catalyst reducibility. However, a decrease in textural properties of the catalysts was noted, being particularly important for the pure praseodymia under the synthesis route conducted. The catalytic activity was investigated under two contact modes of mixing between soot and catalyst: loose and tight. The results revealed that the catalytic performance is associated with the surface contact in tight contact mode and with the combination of surface/subsurface/bulk oxygen mobility and the BET surface ar-ea in loose contact mode. Notably, the T10 and T50 parameters were achieved at much lower temperatures than the uncatalyzed soot combustion, even under loose contact conditions. Specifically, the 50% conversion was achieved at 511℃ and 538℃ for Ce0.3Pr0.7O2 and Ce0.2Pr0.8O2, respectively. While no direct correlation between catalytic activity and work function was observed a significant relationship emerges between work function values and the formation of oxy-gen vacancies, whatever the conditions used for these measurements. On the other hand, the ability to generate a high population of oxygen vacancies at low temperatures, rather than the direct activation of gas-phase O2, influences the catalytic performance of Pr-doped ceria catalysts, highlighting the importance of surface/subsurface oxygen vacancy generation, which was the parameter which showed better correlation with the catalytic activity, whatever the soot conversion value or the mode of contact considered.

Research on high-volume fly ash concrete, which utilizes large quantities of fly ash, has been actively conducted to promote resource recycling and reduce carbon dioxide emissions. However, while cement mixed with fly ash exhibits different temperature sensitivities compared to traditional cement, its hydration and mechanical properties vary depending on curing conditions. Despite this, there is a significant gap in research on this topic. In this study, high-volume fly ash concrete was produced with fly ash replacement rates of 35 % and 55 %. Compression strength tests were performed at various curing ages under three different curing temperature conditions, and the results were analyzed. Additionally, an isothermal calorimeter was used to analyze hydration characteristics under different curing conditions. The results indicated that concrete with high fly ash content was more sensitive to curing temperature compared to ordinary Portland cement.

In Active Flow Control (AFC) applications, to activate the boundary layer the use of pulsating flow has notorious energy advantages versus constant blowing/suction jet injections. For a given AFC application, five parameters, jet location and width, inclination angle, frequency of injection and momentum coefficient need to be tuned. Two main devices are nowadays capable of injecting pulsating flow with the sufficient momentum coefficient to delay the boundary layer separation, these are the Zero Net Mass Flow actuators (ZNMFA) and the Fluidic Oscillators (FO). In the present research, a novel FO configuration is analyzed for the first time at relatively high Reynolds numbers, fluid is considered as incompressible. After obtaining the typical linear correlation between the incoming Reynolds number and the outlet flow oscillating frequency, the effect of outlet width and mixing chamber wedge inclination angle dimensional modifications is addressed, modifications of the outlet width are observed to create large variations on the FO performance. The origin of the self-sustained oscillations is also analyzed in the present manuscript and greatly helps in clarifying the forces acting on the jet inside the mixing chamber. In fact we can conclude saying that the current FO configuration is pressure driven although the mass flow forces appear to be a much more relevant than in previous FO configurations studied.

Cobalt oxide nanoparticles are promising candidates for various kinds of practical application. The interest of researchers and scientists in these nanoparticles is due to their unique physical and chemical properties such as density, melting point, magnetic characteristics and band gap. The need to develop high performance and low-cost technologies for obtaining Co3O4 nanoparticles is a major reason in research in this area. The widespread commercial use of Co3O4 nanoparticles will open doors for numerous novel cost effective technologies, which are mostly dependent on the type of synthesis method and raw materials. A possible solution to this problem is to use Cobalt nitrates as a cost-effective precursor using the solution combustion method. Solution combustion synthesis method is one of the best candidate methods that have the potential for high performance and is also cost-effective. This review examines recent progress in the synthesis of Co3O4 nanoparticles by solution combustion method and underscores their significance across various fields, highlighting the need for further research and exploration of their multifaceted applications. In addition, the most recent advancements in the applications of Co3O4 nanoparticles in sensitive sensing, catalysis, supercapacitors/batteries and water treatment/pollutants removal are reviewed and described, focusing on current trends, challenges, and future outlooks.

In the current study, a two-dimensional numerical study is carried out to investigate the performance of a novel Double-chamber Parallel Flexible Valves micropump, which utilized the electrowetting-on-dielectrics (EWOD) effect to drive the microfluid flow. By observing the flow fields, the internal circulations are seen on both the left and right side of the pump. The generation of the backflow is discussed by tracking the movement of the vortices. Only slight flow fluctuation is seen in the micropump. Based on the simulation outcomes, the structural parameters including the width of the inlet/outlet, the width of the pumping channel and the diverging angle in the micropump are analyzed, the influence of these parameters on the pumping volume and the maximum pressure have been discussed. Eventually, a group of optimal parameter combinations is given according to the results to extend the operating potential of the micropump.

Estimating Forest growing stock volume (GSV) is crucial for forest growth and resource management, as it reflects forest productivity. National measurements are laborious and costly, however integrating satellite data such as optical, Synthetic Aperture Radar (SAR), and Airborne Laser Scanning (ALS) with National Forest Inventory (NFI) data and machine learning (ML) methods has transformed forest management. In this study, Random Forest (RF), Support Vector Regression (SVR), and Extreme Gradient Boosting (XGBoost) were used to predict GSV using Estonian NFI data, Sentinel-2 imagery, and ALS point cloud data. Four variable combinations were tested: CO1 (vegetation indices and LiDAR), CO2 (vegetation indices and individual band reflectance), CO3 (LiDAR and individual band reflectance), and CO4 (a combination of vegetation indices, individual band reflectance, and LiDAR). Across Estonia's geographical regions, RF consistently delivered the best performance. In the northwest (NW), RF achieved an R² of 0.63 and an RMSE of 125.39 m³/plot. In the southwest (SW), it achieved an R² of 0.73 and an RMSE of 128.86 m³/plot. In the northeast (NE), RF achieved an R² of 0.64 and an RMSE of 133.77 m³/plot, and an R² of 0.70 and an RMSE of 120.72 m³/plot was achieved in the southeast (SE). These results underscore RF's precision in predicting GSV across diverse environments, though refining variable selection and improving tree species data could further enhance accuracy.

Induction heating is a fast, reproducible, and efficient heating method used in various manufacturing processes. However, there is no established additive manufacturing (AM) process based on induction heating using wire as feedstock. This study investigates a novel approach to AM based on inductive heating, where a steel wire is melted and droplets are detached periodically using a two-winding induction coil. The process parameters and energy input into the droplets are characterized. The induction generator exhibits sluggish response to the excitation voltage, resulting in a lag in the coil current. The process is captured using a high-speed camera, revealing regular droplet formation and uniform size and shape when operated within an appropriate process window. Larger drops and increased spatter formation occur outside this window. The proposed method allows for the production of droplets with almost spherical shapes. Further analysis and characterization of droplet formation and energy input provide insights into process optimization and overall efficiency.

The evidential value of an mtDNA match between biological remains and its potential donor is determined by the random match probability of the haplotype. This probability is based on the haplotype’s population frequency estimate. Consequently, implementing a population study representative of the population relevant to the forensic case is vital to correctly evaluating the evidence. The emerging number of poaching cases and the limited availability of such data emphasizes the need for improved fallow deer mtDNA population databank for forensic purposes, including targeting the entire mitochondrial control region. By sequencing the whole mitochondrial control region in 138 animals from five populations in Hungary we found four different haplotypes, including one which has not yet been described. Our results, supplemented with data already available from previous research do not support the possibility of determining the population of origin, although some patterns of geographical separation can be distinguished. Estimates of molecular diversity indicate approximately similarly low mtDNA diversity (Hd=0.565 and π = 0.002), compared with data from other countries. The calculated random match probability of 0.547 shows a high probability of coincidence and, therefore, a limited capacity for exclusion. Consequently, it may be necessary to search for polymorphic sites on other mitochondrial gene sections or to sequence the entire mitogenome of fallow deer.

Residual stress (RS) is the most challenging problem in metal additive manufacturing (AM) since the build-up of high tensile RS may influence the fatigue life, corrosion resistance, crack initiation, and failure of the additively manufactured components. While tensile RS is inherent in all the AM processes, fast and accurate prediction of stress state within the part is extremely valuable and would result in optimization of the process parameters in achieving a desired RS and control of the build process. This paper proposes a physics-based analytical model to rapidly and accurately predict the RS within the additively manufactured part. In this model, a transient moving point heat source (HS) is utilized to determine the temperature field. Due to the high temperature gradient within the proximity of the melt pool area, material experience high thermal stress. Thermal stress is calculated by combining three sources of stresses known as stresses due to the body forces, normal tension, and hydrostatic stress in a homogeneous semi-infinite medium. The thermal stress determines the RS state within the part. Consequently, by taking the thermal stress history as an input, both the in-plane and out of plane RS distributions are found from incremental plasticity and kinematic hardening behavior of the metal by considering volume conservation in plastic deformation in coupling with the equilibrium and compatibility conditions. In this modeling, material properties are temperature-sensitive since the steep temperature gradient varies the properties significantly. Moreover, the energy needed for the solid-state phase transition is reflected by modifying the specific heat employing the latent heat of fusion. Furthermore, the multi-layer and multi-scan aspects of metal AM are considered by including the temperature history from previous layers and scans. Results from the analytical RS model presented excellent agreement with XRD measurements employed to determine the RS in the Ti-6Al-4V specimens.

Background: Assessing the impact of bone health clinical management in breast cancer (BC) patients receiving adjuvant endocrine therapy and designing a personalized clinical pathway to reduce bone loss, in an Italian research hospital. Methods: The primary endpoint was to assess (through the process improvement organizational method) the clinical pathway that post-surgical BC patients prescribed with endocrine therapy undergo to prevent bone loss. The secondary endpoint was to design a personalized clinical pathway for a prompt implementation of guidelines, to assess and possibly prescribe antiresorptive therapy. Results: During the first year of the new diagnostic therapeutic assistance pathway execution, an 60% increase in Dual-Energy X-ray Absorptiometry evaluations within 30 days and a 39.5% increase in antiresorptive therapy prescription within 90 days (since prescription of endocrine therapy) were shown, thus increasing patients’ compliance. Conclusion: Case managers and bone health specialists in this context can improve patients’ adherence to therapies and bone health, helping physicians to expand their collaboration.

This article provides a detailed analysis of non-invasive techniques for prediction and diagnosis of faults in internal combustion engines, focusing on the application of the Proknow-C and Methodi Ordinatio systematic review methods. Initially, the relevance of these techniques in promoting energy sustainability and mitigating greenhouse gas emissions is discussed, aligning with the Sustainable Development Goals (SDGs) of Agenda 2030 and the Paris Agreement. The systematic review conducted in the subsequent sections offers a comprehensive mapping of the state-of-the-art, highlighting the effectiveness of combining these methods in categorizing and systematizing relevant scientific literature. The results reveal significant advancements in the use of artificial intelligence (AI) and digital signal processors (DSP) to enhance fault diagnosis, as well as underscore the crucial role of non-invasive techniques in minimizing interference in monitored systems. Finally, concluding remarks point towards future research directions, emphasizing the need to develop digital twins for internal combustion engines and identify gaps for further improvements in fault diagnosis and prediction techniques.

Two-dimensional periodic Stokes flow of viscous incompressible fluid in a rectangular cavity with constant velocities applied to the top and bottom walls is considered. The study of chaotic advection regimes is reduced to the sequential solving of two problems. To solve the first problem, the analytical method of superposition, that allows to obtain any desired accuracy of the velocity field, is used. To solve the second problem, which is associated with obtaining the trajectories of individual fluid particles, numerical calculations of the Cauchy problem were performed. An analysis of the boundary conditions accuracy was performed based on the control of local integration. The advection of the selected volume of fluid in the rectangular cavity under the periodic motion of walls for a finite period time based on piecewise spline cubic interpolation is modelled. The obtained numerical results agree with well-known experimental data.

The recent demand for reducing pollutant and CO2 emissions from internal combustion engines has created an urgent need for the development of ultra-lean burn engines that ensure combus-tion stability and reducing knocking tendency. One of the most promising methods is the Pre-chamber Spark Ignition (PCSI) system, where a jet of high-energy reactive gases, produced by pilot combustion in a pre-chamber, ignites the main combustion event in the cylinder. Given the intricate phenomena inherent to PCSI systems, conducting 3D CFD studies is imperative for a comprehensive analysis and optimal design. Furthermore, the detailed CFD model, combined with the calibrated 0-D/1-D model, is anticipated to yield a significant amount of new data that would be difficult to obtain through experimental approaches, making it essential for advancing our understanding and optimization of these systems. However, recently published papers re-port that some state-of-the-art models developed for conventional SI operation may not be pre-dictive under the challenging conditions of TJI systems, particularly under lean conditions. This review elucidates the reasons behind the widespread adoption of CFD in the optimal design of PCSI engines. It presents significant examples and delves into the potential and challenges of employing CFD not just as a predictive tool but also as a design instrument for enhancing PCSI engine performance.

I extend earlier work that derived a Born rule for nuclear-decay cloud chamber tracks (Mott problem) without invoking quantum measurement axioms. The key ingredient there was the identification of sites at which the cross section for ionization by a passing charged particle is singular at ionization threshold. This singularity arose from a Penning-like process involving molecular polarization in sub-critical vapor clusters. In the present paper, I propose a simple experiment to determine if similar ionization physics takes place in the mica window of a Geiger counter and drives the collimation of spherically-symmetric wavefunctions outside the counter tube into ion tracks inside. The experiment measures the count rate from a radioactive point source as a function of source-window separation. I have performed a proof-of-concept of this experiment; results are consistent with the singular-ionization picture. I consider implications for the Stern-Gerlach experiment and superconducting qubits. I detail further work required to flesh out these results more rigorously.

Planck's constant plays an important role in quantum mechanics but has little physical meaning apart from its contribution to the formulas. Evaluating each of the constant's unit dimensions gives a more granular account of the physical phenomena described by the equations. These formulas show how classical and quantum mechanical equations are related, and they give consistent descriptions of phenomena like momentum and energy in classical and quantum systems.

Background and objectives: sickle cell disease is the most common hemoglobinopathy in the world. It is considered to be a real public health problem. Sickle cell patients are subjected to several factors causing inflammation such as iron metabolism. The study aimed to look for inflammation in children with sickle cell disease in Cameroon, identify the factors associated with inflammation, and raise the consequences for the patient including the iron profile and the profile of the hemogram. Materials and methods: We conducted an analytical cross-sectional study for 03 months. The sickle cell disease patients coming and/or followed at the Hematology Department of the Regional Hospital of Bafoussam and the Central Hospital of Yaoundé have been recruited. The exploration of inflammation was made by determining CRP, IL6, and ferritin concentrations. The hematological parameters and iron profile were evaluated using standard methods. Statistical analysis of the data was performed; Univariate and multivariate logistic regression analyses allowed to identification of factors associated with inflammation in patients, using the statistical tool R version 4.1.1.. The proportions were compared with the chi-square test when the expected numbers were greater than 5 and the Fisher test when not. Results: The frequency of inflammation in the population was 42.3%. Hyperferritinemia was significantly greater (p<0.001) in patients with inflammation compared to the non-inflammatory patients (96.8% and 76.7% respectively). Patients with inflammation showed a significant elevation of iron parameters (p<0.05). In addition, ferritin and IL6 elevation were associated with inflammation during sickle cell disease respectively (Or = 4.96; 95% CI [1.15-36.42]; p=0.056) and (Or =6.23; 95% CI [1.43-45.96]; p=0.030). Conclusions: The elevated iron in plasma is an effect of inflammation in sickle cell patients. Hence the need of controlling inflammation and iron in the latter is necessary.

Inertinite, a product of wildfire, holds important information on global temperature change. The relationship between its reflectance and temperature has been widely used to identify wildfire events in paleo-sedimentary environments, but the currently used equations relating inertinite reflectance and combustion temperature are subject to large errors. Therefore, to clarify the relationship between inertinite reflectance and combustion temperature further, we systematically analyzed the changes in inertinite reflectance under different combustion durations based on literature data. The results confirmed that inertinite reflectance is related to combustion duration. Disregarding combustion duration, the combustion equation is T=267.52+110.19*Ro(R²=0.91), where T is the combustion temperature, Ro% is the measured inertinite reflectance, and R² is the correlation coefficient. Under a combustion duration of 1 hour, the equation is T=273.57+113.89*Ro(R²=0.91), and under a combustion duration longer than 4 hours, the equation is T=232.91+110.6*Ro(R²=0.94). These three equations not only account for the temporal factor but are also more precise than the commonly used formula. This study provides a scientific basis for research on paleo-wildfire.

Understanding the factors affecting semen quality is important for optimizing male reproductive efficiency. The present study aimed to evaluate the seminal quality associated with breed, age, season, and sperm counting chamber in boar ejaculates. A total of 22 sexually mature and healthy boars from maternal and sire commercial breeds were utilized as semen donors, with an average age (mean ± standard deviation) of 21.0 ± 7.2 months. Boars were housed individually in well-ventilated pens and fed a standard breeder mix. Semen samples were collected from each boar in dry and rainy season. The boars were grouped according to age into three categories: &lt;12 months, 12-24 months, and &gt;24 months. Only ejaculates with at least 75 % morphologically normal sperm and more than 8.5 x 109 total sperm per ejaculate were used. The samples were analyzed using the Computer-Assisted Semen Analysis (CASA) ISAS®v1 system. Results showed that younger boars (&lt;12 months) exhibited higher total and progressive sperm motility and faster swimming patterns compared to older boars. The percentages of total motility and fast spermatozoa were increased by rainy season. The kinematics variables showed significant differences (P&lt;0.05) between sperm counting chambers. Duroc and Landrace breeds presented spermatozoa with greater total motility, while terminal sire line breeds showed accelerated linear progressiveness (P&lt;0.05). Overall, the impact of various factors on seminal and kinematic variables in boar ejaculates, including age, season, genetic breed composition, and sperm counting chamber enables to better understand the semen quality of boar ejaculates. This highlights the importance of optimizing swine reproductive management practices in sexually active boars.

This paper presents a control algorithm for soft-switching series LC converters. The conventional voltage-to-voltage controller is split into a master and a slave controller. The master controller implements constant-current-constant-voltage (CCCV) control, required for demanding applications, i.e. lithium battery charging or laboratory power supplies. It defines the set-current for the open-loop current slave controller, which generates the PWM parameters. The power supply achieves fast large-signal responses, e.g. from 5 V to 24 V, where 95% of the target value is reached in less than 400 µs. The design is evaluated extensively in simulation and on a prototype. A consensus between simulation and measurement is achieved.

The pre-chamber technologies can improve the ignition performance of IC engines by more than two orders in magnitude and thereby substantial economic benefits. Compared with the common pre-chamber, a plug-and-play passive scheme is suitable for quick retrofit, which is getting more attention from the automobile industry. Good scavenging is the precondition for improving turbulent jet ignition performance for a passive pre-chamber. Therefore, detailed evaluations of the scavenging process and turbulent jet ignition deserve investigations for new pre-chamber schemes. In this paper, the effects of design parameters on ignition processes of plug-and-play passive pre-chamber were numerically studied, allowing for the lateral angle, orifice diameter, and vertical angle design. Seven pre-chamber schemes were evaluated, and four optimal ones were selected for bench tests. The characteristics of the scavenging process, turbulent jet ignition, and main-chamber combustion were investigated and analyzed. The results show that allowing for the trade-off between ignition energy and scavenging efficiency, the volume ratio of the pre-chamber to clearance is recommended to be 0.2~0.7%, and the corresponding area-volume ratio is 0.003~0.006 mm-1. Compared with the original natural gas engine, the pre-chamber retrofit can save up to 13.2% fuel consumption, which presents a significant improvement in fuel economy.

(1) Background: Malaria remains a global public health problem. Unfortunately, the resistance of malaria vectors to insecticides commonly used threatens disease control and elimination efforts. Molecular mechanisms helping some malaria vectors to now survive to greater doses of insecticides remains poorly understood. Here, we elucidated the pattern of resistance escalation in the main malaria vector Anopheles gambiae in a pesticide-driven agricultural hotspot in Cameroon and its impact on vector control tools; (2) Methods: Larval stages and indoor blood-fed females (F0) were collected in Mangoum in May and November and forced to lay eggs; the emerging mosquitoes were used for WHO tube, synergist and cone tests. Molecular identification was done using SINE PCR whereas TaqMan-based PCR was used for genotyping of L1014F/S and N1575Y kdr and the G119S-ACE1 resistance markers. Transcription profile of candidate resistance genes was performed using qRT-PCR methods. Characterization of the breeding water and soil from Mangoum was also performed using HPLC technique; (3) Results: An. gambiae s.s. was the only species in Mangoum with 4.10 % infection with Plasmodium. These mosquitoes were resistant to all the four classes of insecticides with mortality rates &lt;7% for pyrethroids and DDT and &lt;54% for carbamates and organophophates. This population also exhibited high resistance intensity to pyrethroids (permethrin, alpha-cypermethrin and deltamethrin) after exposure to 5X and 10X discriminating doses and Synergist assays with PBO revealed only a partial recovery of susceptibility to permethrin, alpha-cypermethrin and deltamethrin. Only PBO-based nets (Olyset plus and permaNet 3.0) and Royal Guard showed an optimal efficacy. A high amount of alpha-cypermethrin was detected in breeding sites (5.16 fold LOD) suggesting ongoing selection from agricultural pesticides. The 1014F-kdr allele was fixed (100%) whereas the 1575Y-kdr (37.5%) and the 119S Ace-1R (51.1%) are moderately present. Elevated expression of P450s respectively in permethrin and deltamethrin resistant mosquitoes [CYP6M2 (10 and 34-fold), CYP6Z1(17 and 29-fold), CYP6Z2 (13 and 65-fold), CYP9K1 (13 and 87-fold)] supports their role in the observed resistance besides other mechanisms including chemosensory genes as SAP1 (28 and 13-fold), SAP2 (5 and 5-fold),SAP3 (24 and 8-fold) and cuticular genes as CYP4G16 (6 and 8-fold) and CYP4G17 (5 and 27-fold). However, these candidate genes were not associated with resistance escalation as expression level did not differ significantly between 1x, 5x and 10x surviving mosquitoes. (4) Conclusions: Intensive and multiple resistance is being selected in malaria vectors from pesticide-based agricultural hotspot of Cameroon leading to loss of efficacy of pyrethroid-only nets. Further studies are needed to decipher the molecular basis underlying such resistance escalation to better assess its impact on control interventions.

In modern physics, it is assumed that the Planck length is a derived constant from Newton's gravitational constant, the Planck constant and the speed of light, $l_p=\sqrt{\frac{G\hbar}{c^3}}$. This was first discovered by Max Planck in 1899. We suggest a way to find the Planck length independent of any knowledge of Newton's gravitational constant or the Planck constant, but still dependent on the speed of light (directly or indirectly).

This paper describes the proposal and development of a proof of concept (PoC) for a data logger system designed for operation and fault detection in bench testing of combustion engines. The main objective was to develop a data logger system that collects data on vibration, sound, temperature, and CO2 levels to identify ignition and combustion faults, thereby contributing to reducing greenhouse gas emissions (GHG). The paper presents (i) the proposal and development and (ii) the open-source code: proof of concept for a data logger system focused on detecting faults and monitoring the operational condition of benchtop combustion engines. The results indicate the feasibility of the PoC for data acquisition and dataset creation for Research and Development purposes.

The purpose of this project was to demonstrate the potential of converting an existing internal combustion engine for hydrogen operation at relatively low cost and to optimize the combustion process for ultra-low NOx emissions. The conversion has been carried out on a 450cc naturally aspirated single cylinder engine. The first baseline measurements and setup have shown lower NOx emissions than the baseline gasoline engine (without catalytic converter) for similar power output and engine efficiency. Further optimization of the combustion process allowed to achieve Euro VI and (latest European Commission proposal) Euro VII heavy-duty NOx limits without exhaust gas aftertreatment system (EATS) in steady state conditions. The concept is very promising and the knowledge gained should allow for further optimization to achieve near zero NOx emissions at high engine efficiency and power output with supercharging. It should also allow an efficient conversion of other engine types for different applications. In particular, a project with the aim to convert a heavy duty 6 cylinder engine intended for public transport buses has started. It follows a feasibility study which has shown the competitiveness of the hydrogen engine for this application.

Background: In response to the COVID-19 pandemic, the European Association of Urology (EAU) Guidelines defined priority groups to guide the prioritization of surgery for urological malignancies. The objective of this study was to evaluate the impact of the COVID-19 prioritization recommendations on tumor pathological characteristics in a real-world setting at our academic referral Institution. Methods: We compared baseline and pathological tumor features of all patients with urological malignancies treated during the pandemic period (2020-2021) versus in the post-pandemic period (2022-2023). Our institution adhered to the International recommendations and prioritized those cases defined as “high-risk”. Results: Data of 9196 patients treated for urological malignancies were reviewed and grouped according to period of surgery (4401 in the pandemic vs 4785 in non-pandemic period). The overall number of surgical procedures was comparable for all diseases except for the number of radical prostatectomy (1117 vs 1405; p=0.03) and partial nephrectomy (609 vs 759; p=0.02) which were significantly lower in the pandemic period. Regarding tumors’ pathological features, none of the recorded variable was found to differ according to period of surgery, including disease stage, tumor grading, presence of necrosis, lymphovascular invasion, histological variants. Conclusion: A correct policy of prioritization of oncological pathologies during emergency periods and a centralization of oncological cases in reference centers reduces the possible risk of worsening cancer disease features related to the reorganization of healthcare resources.

This study aims to investigate the impact of body heat loss on the thermal and aerodynamic conditions in a whole-body cryotherapy chamber. The underlying hypothesis is that the heat generated by the human body alters the thermal and aerodynamic environment inside the cabin. A numerical study was conducted to test this hypothesis to analyze the thermodynamic exchanges between the human body and the cabin during a 3-minute whole-body cryotherapy session. The computational fluid dynamics (CFD) approach was used to study the unsteady heat transfer between the human body and the interior of the cryotherapy cabin. A thermal boundary condition, based on a mathematical model developed from experimental data, was applied to simulate skin cooling kinetics over time. The post-processing of the 3D results, including temperature, velocity fields, and thermal flux maps at the body surface, provided insight into the thermo-convective mechanisms involved in a whole-body cryotherapy session. The study found that body heat loss significantly affects the temperature fields inside the cabin, leading to global modifications of the aeraulic and thermal conditions. These findings suggest that cryotherapy protocols may need to be adjusted or the cabin set temperature optimized to enhance the therapeutic benefits.

Despite the efforts made to stop the tuberculosis (TB) epidemic, it still remains one of the leading causes of death from an infectious disease. Previous work in the group uncovered a new family of amides which showed promising activities against Mycobacterium tuberculosis. A closer look at the literature showed that these compounds are structurally related to the DNB family of DprE1 inhibitors, so, we decided to study a wide range of substituted amides and determine their activity, focusing on unexplored structures related to the dinitrobenzamides (DNB) found in the literature. To synthesize our library of compounds we started from 3,5-dinitrobenzoic acid to form the nitroaromatic core that is characteristic of the DNB’s, to which we then added linear or cyclic amine moieties. Additionally, the impact of terminal aromatic moieties was also assessed for some derivatives, via an ether, ester, or amide bond. In order to obtain the desired derivatives, multiple synthetic approaches were used, mainly focused on nucleophilic addition/elimination reactions, SN2 reactions and Mitsunobu reactions. The activity was impacted mainly by two structural features, the addition of an aromatic moiety as a terminal group and the type of the linker. The most interesting compounds exhibited activities comparable to isoniazid and DNB1. Computational studies were also performed aimed at understanding their possible interactions with DprE1. The most active compounds are a good starting point for further development, and we plan to study an extended family of compounds based in those structures.

OpenToolFlux is an open-source software to estimate soil gas fluxes from gas concentration time-series data generated by automatic chamber systems. This paper describes the physical equipment used as well as software design and workflow. The software is a command-line application that imports tabular time-series data from the analyzer following the instructions specified in a configuration file by the user, performs configurable data-cleaning operations, and outputs a data file with volumetric flux estimates as well as diagnostic plots. The software can be configured according to the specifics of physical equipment and experimental setup and is therefore applicable in a wide range of studies.

This study proposes a redesign of asymmetric single-chamber microbial fuel cells (a-SCMFC) with the goal of optimizing energy production. The new approach is based on the introduction of an Intermediate Microfluidic Septum (IMS) as a relatively simple and inexpensive method to opti-mize both electrolyte flow and species transfer inside the devices. SCMFCs with the novel IMS, operated with sodium acetate as the carbon source, demonstrate to enhance the energy recovery (Erec) factor, defined as the ratio between the energy yield and the inner volume of electrolyte. In standard operative conditions, cells with IMS exhibit Erec value of (37±1) J/m3, with respect to (3.0±0.3) J/m3 of control cells. Furthermore, changing sodium acetate concentration the Erec values change accordingly. By monitoring the activity of a-SCMFCs for over one-year, beneficial impact of the IMS on both the initial inoculation phase and the long-term stability of electrical perfor-mance were observed. These improvements suggest the effectiveness of IMS to allow the de-velopment of efficient biofilms, likely due to the reduction in oxygen diffusion towards the anode. Electrochemical characterizations confirm that the presence of the IMS impacts the diffusion processes inside the electrolytic chamber, supporting the hypothesis of a beneficial effect on oxygen diffusion.

In this study on volume determination in waste sorting facilities, we evaluate the effectiveness of ultrasonic sensors and address waste-material-specific challenges. Although ultrasonic sensors offer a cost-effective automation solution, their accuracy is affected by irregular waste shapes, varied compositions, and environmental factors. Notable inconsistencies in volume measurements between storage bunkers and conveyor belts underscore the need for a comprehensive approach to standardize bale production. With prediction reliability being constrained by limited data sets, undocumented modifications to machine-settings and sensor failures, this task renders a challenging application area for Machine Learning. We explore related research and present dataset analyses from three distinct waste sorting facilities in Europe, addressing issues as sensor usability, data quality and material specifics. Our analysis suggests promising strategies and future directions for enhancing waste volume measurement accuracy, ultimately aiming to advance sustainable waste management.

With reference to our earlier published views on large nuclear gravitational constant , nuclear elementary charge and strong coupling constant , in this paper, we present simple relations for nuclear stability range, binding energy of isotopes and magic proton numbers.

We generalize the idea of quantum clock time to quantum spacetime reference frame via physical realization of a reference system by quantum rulers and clocks. Omitting the internal degrees of freedom (such as spins) of the physical rulers and clocks, only considering their metric properties, the spacetime reference frame is described by a bosonic non-linear sigma model (NLSM). We study the quantum behavior of the system under approximations, and obtain (1) a cosmological constant valued (2/π)ρ_c0 (ρ_c0 the critical density at near current epoch) which is very close to the observations; (2) an effective Einstein-Hilbert term; (3) the ratio of variance to mean-squared of spacetime interval tends to a universal constant 2/π in the infrared region. This effect is testable by observing a linear dependence between the inherent quantum variance and mean-squared of the redshifts from cosmic distant spectral lines. The proportionality is expected to be the observed percentage of the dark energy. The equivalence principle is also generalized to the quantum level.

In the context of autosomal dominant polycystic kidney disease (ADPKD), total kidney volume (TKV) plays a key role as biomarker of disease progression and response to therapy and has been recently recognized as enrichment biomarker and possible surrogate endpoint. Several imaging modalities and methods are available to calculate TKV, and the choice depends on the purpose of use. Technological advancements have made it possible to accurately assess cyst burden, that can be crucial to assess the disease state and help identifying rapid progressors. Moreover, the development of automated algorithms has increased the efficiency of total kidney and cyst volume measurements. Beyond total kidney and cyst volume, the quantification and characterization of non-cystic kidney tissue show potential to early stratify ADPKD patients, monitor disease progression, and possibly predict renal function loss. A broad spectrum of kid-ney MRI techniques are available to characterize kidney tissue, showing promise to non-invasively pick up early signs of ADPKD progression. Radiomics has been used to extract tex-tural features from ADPKD images, providing valuable information about the heterogeneity of the cystic and non-cystic components. This review provides an overview of ADPKD imaging bi-omarkers, focusing on quantification methods, potential, and necessary steps towards successful translation to clinical practice.

This review summarises the main numerical models of fuel droplet heating and evaporation (DHE) in combustion engines across the different scales by accessing the nano/micro, meso and macroscopic fluid elements. The phenomena of multi-physics, multi-scale and multi-phase fluid flow and heat transfer are fully investigated when the fuel droplet (dodecane) is heating and evaporated into a background gas (nitrogen) crossing the liquid-vapour (LV) interface, kinetic region (i.e., Knudsen layer) and the bulk regions of liquid and gas in terms of molecular dynamics (MD) simulations, kinetic theory modelling (i.e., direct numerical solutions of Boltzmann equations) and convectional fluid dynamics approach, respectively. The evaporation coefficient of fuel evaporating molecules and their velocity distributions at the LV interface derived from MD simulations formulate a new kinetic boundary condition (KBC). Moreover, a novel kinetic model considering the inelastic collision between fuel molecules alongside the new KBC enables us to describe the non-equilibrium gas dynamics of fuel vapour and gas mixture in Knudsen layer (KL). Heat and mass flux analysis of the fuel droplet under combustion engine conditions can be accurately assessed by implementing the inelastic collision between fuel molecules in KL and a temperature-dependent evaporation coefficient at the LV interface into DHE. The surface temperature of fuel droplet and its evaporation time, which play a significant role in resolving the ignition delay and hence the combustion phasing in engines, can also be well estimated. The multi-scale modelling of fuel DHE will make significantly potential input into the cleaner engine targeting the low-carbon emissions and enhance the capability of the existing computational fluid dynamics (CFD) solvers.

Copper-based nanoparticles were synthesized using the glycine–nitrate process (GNP) by using copper nitrate trihydrate [Cu(NO₃)₂‧3H₂O] as the main starting material and glycine [C₂H₅NO₂] as the complexing and incendiary agent. The as-prepared powders were characterized through X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) analysis, X-ray photoelectron spectroscopy, and scanning electron microscopy. Using Cu(NO₃)₂.3H₂O as the oxidizer (N) and glycine as fuel (G), we obtained CuO, mixed-valence copper oxides (CuO + Cu₂O, G/N = 0.3–0.5), and metallic Cu (G/N = 0.7). The XRD and BET results indicated that increasing the glycine concentration (G/N = 0.7) and reducing particle surface area increased the yield of metallic Cu. The effects of varying reaction parameters such as catalyst activity, catalyst dose, and H₂O₂ concentration on nonylphenol-9-polyethoxylate (NP9EO) degradation were assessed. With a copper‐based catalyst in a heterogeneous system, the NP9EO and total organic carbon removal efficiencies were 83.1% and 70.6%, respectively, under optimum operating conditions (pH, 6.0; catalyst dose, 0.3 g/L; H₂O₂ concentration, 0.05 mM). The results suggested that removal efficiency increased with an increase in H₂O₂ concentration but decreased when the H₂O₂ concentration exceeded 0.0.5 mM. Furthermore, the trend of photocatalytic activity was as follows: G/N = 0.5 > G/N = 0.7 > G/N = 0.3. The G/N = 0.5 catalysts showed the highest photocatalytic activity and resulted in 94.6% NP9EO degradation in 600 min.

Recent observations of the dark energy density have demonstrated the fine-tuning problem, and the challenges faced by theoretical modeling. In this study, we apply the self-similar symmetry (SSS) model, describing the hierarchical structure of the universe based on the Dirac large numbers hypothesis, to Einstein's cosmological term. We introduce a new similarity dimension, D_B, in the SSS model. Using the D_B SSS model, the cosmological constant Λ is simply expressed as a function of the cosmic microwave background (CMB) temperature. The result shows that both the gravitational constant G and Λ are coupled with the CMB temperature, which simplifies the solution of Einstein's field equations for the variable Λ-G model.

The stage of a super-early scale-invariant Universe is considered on the basis of the Poincaré–Weyl gauge theory of gravity in a Cartan–Weyl space-time. An approximate solution has been found that demonstrates an inflationary behavior of the scale factor and, at the same time, a sharp exponential decrease in the effective cosmological constant from a huge value at the beginning of the Big Bang to an extremely small (but not zero) value in the modern era, which solves the well-known “cosmological constant problem”.

Environmental preservation presents numerous challenges, particularly in capturing carbon di-oxide. Despite multiple studies on this topic, there remains a need for additional capture plants, particularly in the energy sector. The power industry emits flue gas during its post-combustion process, and capturing carbon dioxide from this gas would make power plants more environ-mentally friendly while aiding the preservation of the planet. The work conducted in This study aimed to investigate the gap in knowledge to contribute to the development of a better world without harming it. The identified research gap reveals no established optimal monoethanola-mine (MEA) solvent concentration for the process. A simulation was performed using Aspen Hysys to analyze the absorption efficiency at higher solvent concentrations and address this is-sue. The input data was obtained from a flue gas capture plant in the UK. The results obtained from discrete increments indicate an optimal solid result for an MEA concentration of 36 wt.%. Further analysis of temperature and pressure revealed that other solvents, such as diethanola-mine (DEA) and triethanolamine (TEA), are more stable at higher concentrations and that DEA and TEA at the same concentration as MEA consumed significantly less energy to capture carbon dioxide.

Stabilization of planar premixed flame front on a lattice (porous) burner is considered. It is rigorously mathematically proved that there exist two different stabilization regimes: one with flame front located nearby the surface of the burner, and another with flame front located inside the lattice. These two regimes result in qualitatively different gas temperature profiles along the flow, that is monotonic and non-monotonic, respectively. Boundary between the two regimes is described in terms of dependence of the lattice solid material temperature on flow Peclet number. Likewise temperature profiles, such dependencies may be both monotonic and non-monotonic. Transition between the two types of dependencies is controlled by Arrhenius number. Conclusions of the study are supported by numerical analysis. They also compare favourably with available experimental data. Novelty of the present approach is fundamentally rigorous analytical analysis of the problem.

Here we will model the curvature and contraction of space-time using as a basis the equation of state of an ideal gas and the Hawking´s equation for the temperature of a black hole. We will use this mathematical model to hypothesize that the Boltzmann´s constant depends on the state of matter, that is, there is a known Boltzmann´s constant for flat space-time and an effective Boltzmann´s constant for curved space-time. This model will allow us to quantify the structure of space-time and will serve as a basis to determine the origin of gravity and the origin of elementary particles. Using the Shannon-Boltzmann-Gibbs entropy relation, we will demonstrate that information is not lost and depends on the state of matter, the information is encoded and depends on the effective Boltzmann´s constant.

With the continuous improvement and observable benefits of electric vehicles (EVs), major logistic companies are introducing more EVs into their conventional fleets. This gives rise to a new type of vehicle routing problem with mixed vehicles, where heterogeneous internal combustion vehicles (ICVs) and electric vehicles are considered in route planning. In addition, certain deliveries that are not efficient on any type of vehicles, are outsourced to third-party common carriers. In this paper, we define this problem as a mixed vehicle routing problem with common carriers (MVRPC). The objective of such problems is to minimize the transportation costs by considering routes with ICVs and EVs, the possibility of visiting recharging stations, outsourcing options, and drivers’ layover regulations. This variant of the vehicle routing problems has many practical applications, particularly in the design of long-haul transportation and last-mile delivery services. Effective MVRPC solutions play a key role in promoting the going Green image and optimally allocating resources. The problem has received limited attention in the literature likely because addressing all the needed aspects is especially challenging. To solve the large-scale problem, we develop a branch-and-cut pricing framework that relies on strong cuts and customized labeling algorithms. Numerical experiments highlight the effectiveness of our algorithm. This success can be attributed to tailored critical resources, dynamically bounded bidirectional labeling procedures, strong dominance criteria, and implementation strategies.

We propose a promising model of discrete spacetime based on nonassociative geometry and complex networks. Our approach treats space as a simplicial 3-complex (or complex network), built from "atoms" of spacetime and entangled states forming n-dimensional simplices (n=1,2,3). At large scales, a highly connected network is a coarse, discrete representation of a smooth spacetime. We show that for high temperatures, the network describes disconnected discrete space. At the Planck temperature, the system experiences the phase transition, and for low temperatures, the space becomes a triangulated discrete space. We show that the cosmological constant depends on the universe’s topology. The "foamy" structure, analogous to Wheeler’s "spacetime foam," significantly contributes to the effective cosmological constant, which is determined by the Euler characteristic of the universe.

Although the presence of dark energy is well established from various observations, its true nature is still not well understood. The cosmological constant term seems to be the preferred candidate. In earlier work we had a constant cosmological constant term to limit the sizes of large-scale structures at lower redshifts. In this work, we extend this to large scale structures at higher redshifts. Here we invoke a time varying cosmological constant to set constraints on sizes of galaxies at high redshifts and see that they are consistent with their observed sizes. The time-varying cosmological constant also provides a possible solution to the puzzle of structure formation of large disk galaxies (like the Wolfe disk) observed at very early stages of the Universe. Future observations of galaxies at even higher redshifts could support our approach.

In this study, the generality and prediction accuracy of a generalised series model for large eddy simulation of premixed and non-premixed turbulent combustion is explored. The model is based on Taylor series expansion of the chemical source term in scalar space and implemented into OpenFOAM. The mathematical model does not depend on the combustion regimes, and has the correct limiting behaviour. The numerical error sources are outlined and analysed. The model is first applied to a piloted methane/air non-premixed jet flame (Sandia Flame D). The statistical (time-averaged and RMS) results agree well with experimental measurements, particularly with regard to the mixture fraction, velocity, temperature, and concentrations of major species CH4, CO2, H2O, and O2. The concentrations of intermediates CO and H2 are over-predicted, due to the limitations of the reduced reaction mechanism employed. Then, a Bunsen piloted flame is simulated. Most of the statistical properties of both reactive species and progress variable are well reproduced. The only major discrepancy evident is in the temperature, which is attributed to the experimental uncertainties of temperature fields in the pilot stream. These findings have demonstrated the model`s generality for both premixed and non-premixed combustion simulation, as well as the accuracy of prediction of reactive species distribution.

This study focuses on the increased risk of high heat release and asphyxiation (toxic gas poisoning) in the event of a fire of polyurethane (PU) and MDF-based building materials, which are commonly used in building fires. Among them, polyurethane (PU) building materials are essential for buildings except in Europe and some other countries due to their excellent thermal insulation performance, but problems of short-term heat release and spread of toxic gases in the event of a fire continue to occur. To overcome these problems, researchers are actively working on introducing various flame retardants into building materials. Therefore, in this study, we produced a laboratory-sized (500mm*500mm) plate flame retardant board that can be utilized as a building material with a lower heat release rate and a lower toxicity index by mixing expanded graphite and ceramic binder as flame retardants in a main material based on the cellulose of waste paper by replacing the existing building materials with a hot-press method. According to the ISO-5660-1 test on the heat release rate of the plate flame retardant board, the THR value was 2.9 (MJ/m2) for 10 minutes, showing an effect of reducing the THR value by 36.3 (MJ/m2) compared to the THR value of 39.2 (MJ/m2) of the specimen made using only paper. In addition, the toxicity index of the flame retardant board was checked through the NES 713 test. As a result, the test specimen showed a toxicity index of 0.7, which is 2.4 lower than the toxicity index of 3.1 of MDF, which is utilized as a conventional building material. Based on the results of this study, the cellulose fire retardant board showed the effect of reducing the heat release rate and toxicity index of building materials in a building fire, which reduces the risk of rapid heat spread and smoke toxicity. This has the potential to improve the evacuation time (A-SET) of evacuees in fires. It is also important to show that recycling waste paper and utilizing it as the main material for building materials can be an alternative in terms of sustainable development.

There are some controversies about 2G bioethanol and it is in need of a reliable test data in order to make a further analysis and proof. In collecting basic data from three classes of typical raw materials, such as wheat, maize stalk juice, and straw, it was found that 4.32 tons straw or 3.358 tons wheat is needed to produce 1-ton bioethanol. Using the coefficient of variation calculation and analysis method, it is able to obtain the C.V. value of straw fermentation efficiency 0.08932<0.15, indicating the fermentation technology and process of 2G bioethanol is already quite mature and reliable, without risk, and also with a raw material cost advantage. There is a problem in that the C.V. value of straw volume is 1.2648>0.95, indicating 2G bioethanol is in an extremely high-risk area. Using the straw volume calculation method, building and its costs – capital expenditure of 2G bioethanol plant is approximately seven times that of a wheat ethanol plant. This should be some of the important reasons why it is noncompetitive, extremely high price, and requiring government subsidies. Straw volume data study has caused the 2G bioethanol plant to require more cement, steel, equipment, and other materials. Thus, there are ample reasons to question the CO2 emissions and its carbon footprint of 2G bioethanol plant. Actually, the volume is not the only existing problem, it is necessary to re-evaluate and discuss the definition of 2G bioethanol and its future.

We introduce two symmetric concepts to physics: “distance” (space and time in one) and “wavematter” (electromagnetic wave packet and matter in one). We claim that physics has chosen the wrong concept of time: It is not aware that the time of a moving object flows in a direction other than my time. We provide 15 proofs for our claim by solving 15 mysteries of physics graphically! For example, we prove that length contraction and time dilation are actually geometrical effects in a 4D manifold that we call “Euclidean spacetime” (ES). We prove that the discrepancy in calculating the Hubble constant stems from a systematic error in the redshift measurement. We prove that what I deem wave, deems itself matter, which solves wave–particle duality. We even untangle quantum entanglement without the issue of non-locality. We finally understand why alternative theories of Euclidean relativity have failed: They are all based on four dimensions of space rather than distance. A huge amount of energy was injected into ES at a point that we take as origin. Ever since has this energy been moving radially away at the speed of light. We live in the 3D hypersurface of an expanding 4D hypersphere. Hyperspherical coordinates have the great advantage that they reduce all that is ever happening to just one formula. So, it is the Theory of Everything in these coordinates: “Energy is covering radial distance which, divided by Euclidean time, is equal to the speed of light.” Acceleration and force like gravitation emerge from a rotation of objects in ES and a subsequent projection to 3D space. Matching the symmetry simplifies physics.

The cosmological constant problem is examined by taking an Einstein--scalar with a Higgs-type potential and scrutinizing the infrared structure induced by finite temperature effects. A variant optimal perturbation theory is implemented in the recently proposed quantum-gravitational framework. The optimized renormalized mass, i.e., the renormalized mass determined by the variant optimal perturbation theory, of the scalar field turns out to be on the order of the temperature. This shifts the cosmological constant problem to compatibility of the consequent perturbative analysis. The compatibility is guaranteed essentially by renormalization group invariance of physical quantities. We point out the resummation behind the invariance.

Iterations of continuous maps are the simplest models of generic dynamical systems. In particular, circle maps display several key properties of complex dynamics, such as phase-locking and the quasi-periodicity route to chaos. Our work points out that Planck’s constant may be derived from the scaling behavior of circle maps in the asymptotic limit.

To account for the very low mass density associated with Dark Energy and the Cosmological Constant, a new approach to the ground state of empty space is presented. The resulting model for the vacuum state associated with empty space proposes a crystalline-like texture for the chromatic structure of empty space. This vacuum state has the appropriate mass density and predicts acceleration for the Universe expansion. Furthermore, the model predicts that this texture is anisotropic and may lead to measurable changes in the production of electron and positron pairs by gamma rays incident on a solid crystal of low mass density such as graphite.

In this article it is shown how Milgrom’s acceleration constant is related with the Ω_Λ, Ω_m and Ω_B values of the matter distribution within observable universe as defined in the Standard Model of Cosmology, established by the Planck Collaboration Group. The result is a two-parameter model for the observable universe. The two parameters are the age of the universe and Milgrom’s acceleration constant. It is shown that these are sufficient to calculate the amounts of matter and dark energy in the universe, as well as the contributions of dark matter and baryonic matter in the matter part. The numerical results are in agreement with those of the Lamda-CDM model.

Introduction: Laeverin is an extravillous trophoblast marker playing a significant role in the trophoblast migration. The purpose of this study was to evaluate the association between the amniotic and serum laeverin concentrations at 16-22 weeks of gestation and the fetal and placental ultrasound measurements in healthy, unaffected pregnancies. Materials and methods: This was a prospective cross-sectional study. Pregnant women with singleton pregnancies undergoing amniocentesis were recruited consecutively. Fetal structural malformations and/or aneuploidy were exclusion criteria. Fetal biometric parameters and placental growth/perfusion were measured in 44 high-risk pregnancies who had no pregnancy complication and any other chronic disease. Maternal serum and amniotic levels of laeverin were essayed with sandwich enzyme-linked immunosorbent assay. Results: Serum laeverin levels are decreasing slightly with the maternal age in mid-gestation. Serum laeverin level correlated negatively slightly with head size of the fetus with the gestational length at delivery (β=-0.38, 95% confidence interval (CI) -0.03-0.01), while the amniotic laeverin level correlated strongly with the abdominal circumference of the fetus (β=-0.64, 95% CI: -0.03-0.01). Furthermore, laeverin level in the amnion correlated moderately and positively with the placental volume (β=0.46, 95% CI: 0.01-0.08). Conclusions: Laeverin levels detected in the serum and in the amniotic fluid denotes the fetoplacental growth in uncomplicated high-risk pregnancies.

Membrane gas absorption technology and solar-assisted regeneration system are two promising approaches to reduce high energy consumption associated with carbon dioxide capture from coal fired power plants. In the present study, a solar-assisted hollow fiber membrane contactor (SOL-HFMC) power plant is proposed to capture and desorb CO₂ in hollow fiber membrane contactors with the assistance of solar thermal collectors. Techno-economic assessment and sensitivity analysis of the proposed system is carried out in three studied locations with different weather conditions for a 580 MWe pulverized coal power plant. Research results show that, the output capacity and net efficiency of the SOL-HFMC power plant are significantly higher than those of the reference power plant regardless whether TES system is applied or not. In addition, CEI of the SOL-HFMC power plant with TES system is 4.36 kg CO₂/MWh, 4.45 kg CO₂/MWh and 4.66 kg CO₂/MWh lower than that of the reference power plant. The prices of membrane, vacuum tube collector and phase change material should be reduced to achieve lower LCOE and COR values. Specifically for SOL-HFMC power plant with TES system, the corresponding vacuum tube collector price shall be lower than 25.70 $/m² for Jinan, 95.20 $/m² for Xining, and 128.70 $/m² for Lhasa, respectively. To be more competitive than solar-assisted ammonia-based post-combustion CO₂ capture power plant, the membrane price in Jinan, Xining and Lhasa shall be reduced to 0.012 $/m, 0.015 $/m and 0.016 $/m for the sake of LCOE, and 0.03 $/m, 0.033 $/m and 0.034 $/m for the sake of COR, respectively. The findings can provide guidance for decision-making and risk management strategies.

: Innovative solutions are now being researched to manage the ever-increasing amount of data required to optimize the performance of internal combustion engines. Machine Learning ap-proaches have shown to be a valuable tool for signal prediction due to their real-time and cost-effective deployment. Among them, the architecture consisting of Long Short-Term Memory (LSTM) and one-dimensional Convolutional Neural Networks (1DCNN) has emerged as a highly promising and effective option for replacing the role of physical sensors. The architecture com-bines the capacity of LSTM to detect patterns and relationships in smaller segments of the signal with the ability of 1DCNN to detect patterns and relationships in larger segments of the signal. The purpose of this work is to assess the feasibility of substituting a physical device dedicated to calculating the torque supplied by a spark-ignition engine. The suggested architecture was trained and tested using signals from the field during a test campaign conducted under transient operating conditions. The results reveal that LSTM+1DCNN is particularly well suited for signal prediction with considerable variability. It constantly outperforms other architectures used for comparison, with average error percentages of less than 2%, proving the architecture's ability to replace physical sensors.

The previously developed models for fuel droplet heating and evaporation processes, mainly the Discrete Multi Component Model (DMCM), and Multi-Dimensional Quasi-Discrete Model (MDQDM) are investigated for the aerodynamic combustion simulation. The models have been recently improved, and generalised for a broad range of bio-fossil fuel blends so that the application areas are broadened with increased accuracy. The main distinctive features of these models are that they consider the impacts of species thermal conductivities and diffusivities within the droplets to account for the temperature gradient, transient diffusion of species and recirculation. A formulation of fuel surrogates is made, using the recently introduced model, referred to as ‘’Complex Fuel Surrogate Model (CFSM)’’ and analysing their heating, evaporation, and combustion characteristics. The CFSM is aimed to reduce the full composition of fuel to a much smaller number of components based on their mass fractions, and to formulate fuel surrogates. Such approach has provided a proof of concept with the implementation of the developed model into a commercial CFD code ANSYS-Fluent. A case study is made for the CFD modelling of gas-turbine engine using kerosene fuel surrogate. The surrogate is proposed using the CFSM. The model is implemented into ANSYS-Fluent via a user-defined function to provide the first full simulation of the combustion process. Detailed chemical mechanism is also implemented into ANSYS Chemkin for the combustion study.

Metal 3D printing technology is a promising manufacturing method. The quality of the printed product can pass for mechanical application, if the anisotropy of the microstructure, imperfections, deformation, and residual stress of the printed sample could be lower than the appropriate level or if they are fully illuminated. Thermal stress is one of the significant reasons for deformation in the 3D printed samples. Thermal stresses are the direct consequence of the local temperature gradient. In this research, the effect of the temperature printer’s chamber (from room temperature to 900 C) was studied on thermal stress and subsequent total deformation in the printed sample. The printed sample is a six-layers-printed walk, which could be considered as a building block of other complex shapes and give us inside about deformation. The computational results show a meaningful reduction in thermal stress and deformation at the higher temperature of the printer’s chamber. The lower final deformation of the printed sample is an important subject, especially for samples with complex shapes.

Recent algorithmic-based research in the stock market has predominantly focused on ultra-high-frequency trading and index estimation. We developed an improved algorithm to address the need for a low-frequency, real-world trading model to build on the existing high hit-ratio and low maximum drawdown. We utilized established price indicators, Stochastic and Williams %R, and introduced a volume factor to increase the model's safety to enhance the model's performance. This improved algorithm demonstrated superior returns while maintaining high hit-ratio and low maximum drawdown. Specifically, we leveraged the existing algorithm to trade using 2X and 3X signals, incorporating volume data, the 52-week average, standard deviation, and other factors. The data set comprised SPY ETF price and volume from 2010 to 2023, covering over 13 years. Our enhanced algorithmic trading model outperformed both the benchmark and previous results, achieving a hit rate of over 90%, a maximum drawdown of less than 1%, an average of 1.5 trades per year, a total return of +519.3%, and an annualized return (AnnR) of +15.1%. The analysis demonstrates that the model's simplicity, ease of application, and comprehensibility can assist investors in making informed investment decisions albeit the past performance does not guarantee future returns.

Antibiotic-loaded bone cement (ALBC) plays a pivotal role in infection prevention and treatment related to musculoskeletal surgery. The release efficacy of antibiotics from ALBC is closely tied to its surface area, yet little is known about the effective release depth. To investigate the relationship between surface area, volume, and antibiotic elution, spheric ALBC specimens with consistent outer diameters but different internal metal sphere diameters were prepared. Two vancomycin doses were utilized in ALBC specimens with an outer diameter of 35 mm: high (4 g) and low (1 g). Each dosage group included five specimens containing embedded metal spheres with diameters of 15, 25, 29, 32, or 33 mm. The resulting shell-like ALBC specimens had thicknesses of 10 mm, 5 mm, 3 mm, 1.5 mm, or 1 mm, respectively. The specimens were immersed in sterile phosphate buffer solution, and antibiotic elution was measured at designated sampling times (1, 3, 6, 10, 24, 48, 72, and 168 hours). Methylene blue was employed to visualize penetration depth. Vancomycin elution did not display statistically significant differences between high- and low-dose groups. In both groups, specimens with 1 mm thickness exhibited a higher vancomycin release efficiency (high-dose group: 18560±5474 μg, 6.7%; low-dose group: 2017±419 μg, 2.6%), decreasing sharply in thicker ALBC specimens. Methylene blue penetration depth showed no apparent difference between high-dose and low-dose groups. ALBC thickness does not significantly impact antibiotic elution, while surface area and antibiotic dose exert notable effects. These in vitro findings offer potential applications in clinical treatments for musculoskeletal infections.

The authors of the article analyze the existing methods and models of technological preparation of machine-building industries. The structure of a three-level simulation model with network-centric control, the structures of individual elements of the simulation model and the process of simulation modeling are described. The criteria for choosing a rational option for the processing technological route have been determined. During the research, a simulation program was implemented in C++. It allows you to select the optimal scenario for the operation of a production site based on two criteria: time and cost. The volume of implementation is about 2x103 lines of code. A diagram of the modeling algorithm for the implemented program, a description of the classes and their interactions are given in the article. The developed simulation model was tested at a machine-building enterprise using the example of the “Pusher” part, manufactured under single-unit production condi-tions. The technological equipment used for the manufacture of this part was formed in the form of input data of the simulation model. The results of simulation modeling for the selected part are described. For each variant of the technological processing route, the values of variable costs and the duration of the production cycle were determined.

The COVID-19 pandemic caused significant training disruptions during the 2020-21 season due to lockdowns, quarantines, and strict adherence to pandemic protocols. The main purpose of this study was to determine how pandemic training restrictions affected training volume and performance in one collegiate swim team. Cumulative training volume data, across a 28-week season, were compared between a pandemic (2020-2021) versus non-pandemic (2019-2020) season. Swimmers were categorized into three groups (Sprinters, Mid-Distance, and Long-Distance) based on training group. Performance times in 25 swimmers who competed in Regional Championships, during both the non-pandemic and pandemic year, were compared via 1-way ANOVA. 26 male and 22 female swimmers commenced the 2020-21 (pandemic) season, with 23% of swimmers voluntarily opting out. Three COVID-19 cases were confirmed (2%) by the medical staff with no long-term effects. Significant reductions in average swim volume were verified in Sprinters (32,867±10,135 vs.14,800±7,995yards;p<0.001), Mid-Distance (26,457±10,692 vs.17,054±9.923yards;p<0.001), and Long-Distance (37,600±14,430 vs.22,254±14,418yards;p<0.001) swimmers (non-pandemic vs. pandemic season, respectively). In the Regional performance analyses, the Sprinters swam faster (n=8;-0.5±0.6secs), while Mid-Distance (n=10;0.17±2.1secs) and Long-Distance (n=7;6.0±4.9secs) swimmers swam slower (F=11.76;p=0.0003;r²=0.52). Thus, the pandemic caused significant reductions in swim training volume, with Sprinters performing better and Long-Distance swimmers performing worse at Regional Championships.

Automation of forest field reference data collection has been an intensive research objective for laser scanning scientists ever since the invention of terrestrial laser scanning more than two decades ago. Recently, it has been proposed that such automated data collection providing both the tree heights and stem curves would require a combination of above-canopy UAV point clouds and terrestrial point clouds. In this study, we demonstrate that an under-canopy UAV laser scanning system utilizing a rotating laser scanner can alone provide accurate estimates of the canopy height and the stem volume for the majority of the trees in a boreal forest. To this end, we mounted a rotating laser scanner based on a Velodyne VLP-16 sensor onboard a manually piloted UAV. The UAV was commanded with the help of a live video feed from the onboard camera of the UAV. Since the system was based on a rotating laser scanner providing varying view angles, all important elements such as treetops, branches, trunks, and ground could be recorded with laser hits. In an experiment including two different forest structures, namely sparse and obstructed canopy, we showed that our system can measure the heights of individual trees with a bias of -20 cm and a standard error of 40 cm in the sparse forest and with a bias of -65 cm and a standard error of 1 m in the obstructed forest. The accuracy of the obtained tree height estimates was equivalent to airborne above-canopy UAV surveys conducted in similar forest conditions. The higher underestimation and higher inaccuracy in the obstructed site can be attributed to three trees with a height exceeding 25 m and the applied laser scanning system VLP-16 that had a limited height measurement capacity when it comes to trees taller than 25 m. Additionally, we used our system to estimate the stem volumes of individual trees with a standard error at the level of 10%. This level of error is equivalent to the error obtained when merging above-canopy UAV laser scanner data with terrestrial point cloud data. Future research is needed for testing new sensors, for implementing autonomous operation inside canopies through collision avoidance and navigation through canopies, and for developing robust methods that work also with more complex forest structure. The results show that we do not necessarily need a combination of terrestrial point clouds and point clouds collected using above-canopy UAV systems in order to accurately estimate the heights and the volumes of individual trees.

Hyperbaric oxygen therapy (HBOT) is a well-established treatment for carbon monoxide (CO) poisoning. HBOT is performed in a hyperbaric chamber, which increases the atmosphere absolute (ATA) and oxygen concentration in the chamber. To ensure patient safety during HBOT, a gas monitoring system is used to monitor the oxygen levels, ATA, and other parameters. This study aims to perform the safety evaluation of the monoplace hyperbaric chamber compared to a gas monitoring system in the treatment of CO poisoning. In addition, it examined the clinical characteristics of the patients diagnosed with CO poisoning who performed HBOT. In the safety evaluation of the monoplace chamber, it was compared the values of oxygen (O2), carbon dioxide (CO2), humidity, and temperature were measured in the hyperbaric chamber and gas monitoring system when operating at 2.0 ATA and 3.0 ATA. Moreover, in the clinical characteristics of patients with CO poisoning who performed HBOT, 1,006 patients were analyzed by using the data registry. Under the condition at 3.0 ATA, the average CO2 was higher in the hyperbaric chamber than in the gas monitoring system (p&lt;0.001). Also, the average humidity was higher in the hyperbaric chamber than in the gas monitoring system (p=0.004). Under the condition at 2.0 ATA, the average humidity was higher in the hyperbaric chamber than in the gas monitoring system (p&lt;0.001). Also, the average temperature was lower in the hyperbaric chamber than in the gas monitoring system (p&lt;0.001). The mean age of the 1,006 CO poisoning patients who received HBOT was 44.93±19.78 years. According to the source of CO, 680 patients (67.6%) visited ER most commonly due to charcoal. The median maximal CO exposure time and time from rescue to ER were 4.0 hours and 3.09 hours, respectively. The median GCS score at the scene or ER was 15. According to the underlying comorbidities, psychiatric diseases (19.5%) were the most common, followed by hypertension (18.1%) and diabetes mellitus (11.5%). In the emergency room, some patients had appeared symptoms such as loss of consciousness (59.8%), shock (6.7%), or seizure (8.3%). The results of this study could be expected that HBOT can be effectively performed by monitoring the gas concentration change inside the hyperbaric chamber.

The constant ħ is elevated to a dynamical field, coupling to other fields, and itself, through the Lagrangian density derivative terms. The spatial and temporal dependence of ħ falls directly out of the field equations themselves. Three solutions are found: a free field with a tadpole term; a standing-wave non-propagating mode; a non-oscillating non-propagating mode. The first two could be quantized. The third corresponds to a zero-momentum classical field that naturally decays spatially to a constant with no ad-hoc terms added to the Lagrangian. An attempt is made to calibrate the constants in the third solution based on experimental data. The three fields are referred to as actons. It is tentatively concluded that the acton origin coincides with a massive body, or point of infinite density, though is not mass dependent. An expression for the positional dependence of Planck’s constant is derived from a field theory in this work that matches in functional form that of one derived from considerations of Local Position Invariance violation in GR in another paper by this author. Astrophysical and Cosmological interpretations are provided. A derivation is shown for how the integrand in the path integral exponent becomes Lc/ħ(r), where Lc is the classical action. The path that makes stationary the integral in the exponent is termed the “dominant” path, and deviates from the classical path systematically due to the position dependence of ħ. The meaning of variable ħ is seen to be related to the rate of time passage along each path increment. The changes resulting in the Euler-Lagrange equation, Newton’s first and second laws, Newtonian gravity, Friedmann equation with a Cosmological Constant, and the impact on gravitational radiation for the dominant path are shown and discussed.

The thermodynamics of black holes is discussed for the case, when the Newton constant G is not a constant, but is the thermodynamic variable. This gives for the first law of the Schwarzschild black hole thermodynamics: d S BH = − A d K + d M T BH , where the gravitational coupling K = 1 / 4 G , M is the black hole mass, A is the area of horizon, and T BH is Hawking temperature. From this first law it follows that the dimensionless quantity M 2 / K is the adiabatic invariant, which in principle can be quantized if to follow the Bekenstein conjecture. From the Euclidean action for the black hole it follows that K and A serve as dynamically conjugate variables. This allows us to calculate the quantum tunneling from the black hole to the white hole, and determine the temperature and entropy of the white hole.

In this paper we show that the Schwarzschild radius can be extracted easily from any gravitationally-linked phenomena without having knowledge of the Newton gravitational constant or the mass size of the gravitational object. Further, the Schwarzschild radius can be used to predict any gravity phenomena accurately, again without knowledge of the Newton gravitational constant and also without knowledge of the size of the mass, although this may seem surprising at first. Hidden within the Schwarzschild radius are the mass of the gravitational object, the Planck mass (their relative mass), and the Planck length. We do not claim to have all the answers, but this seems to indicate that gravity is quantized, even at a cosmological scale, and this quantization is directly linked to the Planck units. This also supports our view that the Newton gravitational constant is a universal composite constant of the form $G=\frac{l_p^2{c}^3}{\hslash }$ , rather than relying on the Planck units as a function of G. This does not mean that Newton’s gravitational constant is not a universal constant, but that it is instead a composite universal constant that depends on the Planck length, the speed of light, and the Planck constant. Further, $\frac{G\times 1\hspace{0.17em}\mathrm{weight}\hspace{0.17em}\mathrm{unit}}{c^2}=\frac{G}{c^2}$ is the Schwarzschild radius off one weight unit. So G is only needed when we want to use gravity to find the weight of an object, such as weighing the Earth. This is, to our knowledge, the first paper that shows how a long series of major gravity predictions and measurements can be completed without any knowledge of the mass size of the object, or Newton’s gravitational constant. As a minimum we think it provides an interesting new angle for evaluating existing gravity theories, and it may even give us a small hint on how to combine quantum gravity with Newton and Einstein gravity.