Energy Ratio Research Articles

Biosurfactant induced microwave disintegration of macroalgae for fermentative biohydrogen production

Biosurfactant-induced microwave disintegration (BSMD), an energy and cost effective pretreatment method, has been proposed to increase biohydrogen production from marine macroalgae (Chaetomorpha antennina). Microwave disintegration (MD) was performed for microwave powers from 90 to 540 Watts in varied periods from 0 to 60 mins. During this MD process, a disintegration time of 25 mins and microwave power of 360 W were obtained as optimum conditions, resulting in the dissolvable organics release (DOR) of 1860 mg/L and a disintegration efficiency (DE) of 14.3%. BSMD was implemented by adding the biosurfactant dosages from 0.005 to 0.05 g/g TS with the optimum power of MD at various intervals of time of 0–30 min. The optimum biosurfactant dosage for efficient disintegration in BSMD was 0.03 g/g TS, resulting in 19.55% DE and 2542 mg/L of DOR in 10 mins. BSMD sample showed increased volatile fatty acid (VFA) production of about 1393 mg/L than MD (1000 mg/L). In addition, BSMD consumed less input energy (IE) of (480 kWh / kg of solids) than MD (1200kWh / kg of solids). The highest amount of biohydrogen was produced by BSMD (120 mL H2/g COD) than MD (78 mL H2/g COD). The results showed BSMD method was energy-efficient for producing biohydrogen with an energy ratio of 1.96, and economical with a net profit of 74.78 $.

Enhancing sustainable ethanol fuel production from cassava in Vietnam

This study focused on developing a comprehensive model to perform techno-economic analysis and calculate greenhouse gas emissions and net energy balance of cassava-based ethanol production in Vietnam. Four steps were involved in this study: (1) collecting data on the cassava-based ethanol conversion pathway, (2) modeling an ethanol production plant, (3) calculating greenhouse gas emissions and net energy balance, and (4) evaluating economic feasibility. The total capital investment and production cost per liter of ethanol are 0.6 $/l/yr and 0.4 $/l, respectively. The fossil energy consumption and net energy ratio during cultivation, transportation, production, and use of ethanol are 12.4 MJ/l and 1.70, respectively. The total greenhouse gas emissions of cassava-based ethanol production are 1252 gCO2eq/l or 59.1 gCO2eq/MJ, which equals 63 % of greenhouse gas emissions from gasoline. This finding confirms that cassava-based ethanol can be an alternative fuel based on economic feasibility and environmental benefit by reducing greenhouse gas emissions in Vietnam.

Controllable quantum scars induced by spin–orbit couplings in quantum dots

Spin–orbit couplings (SOCs), originating from the relativistic corrections in the Dirac equation, offer nonlinearity in the classical limit and are capable of driving chaotic dynamics. In a nanoscale quantum dot confined by a two-dimensional parabolic potential with SOCs, various quantum scar states emerge quasi-periodically in the eigenstates of the system, when the ratio of confinement energies in the two directions is nearly commensurable. The scars, displaying both quantum interference and classical trajectory features on the electron density, due to relativistic effects, serve as a bridge between the classical and quantum behaviors of the system. When the strengths of Rashba and Dresselhaus SOCs are identical, the chaos in the classical limit is eliminated as the classical Hamilton’s equations become linear, leading to the disappearance of all quantum scar states. Importantly, the quantum scars induced by SOCs are robust against small perturbations of system parameters. With precise control achievable through external gating, the quantum scar induced by Rashba SOC is fully controllable and detectable.

Is bovine somatotropin an alternative strategy to overcome the detrimental effects of high-gain diets on prepubertal Holstein × Gyr heifers?

Feeding high-gain diets and an inadequate energy and protein ratio during pre-puberty may lead to impaired growth and mammary gland development of heifers. Thus, frequent application of bovine somatotropin (bST) may prevent future losses in productivity, improve mammary development and animal performance. We aimed to evaluate the effects of bST on digestibility, performance, blood metabolites, mammary gland development, and carcass composition of high-performance prepubertal Holstein × Gyr heifers. Thirty-four Holstein × Gyr heifers with an average initial body weight of 218 ± 49 kg and 14 ± 4 months of age were submitted to an 84-day trial evaluating the effects of no bST or bST injections. Treatments were randomly assigned to each animal within one of the tree blocks. The bST did not influence digestibility or performance parameters. Regarding blood results, IGF1 concentration presented an interaction between treatment and day, where bST heifers had the highest IGF1 concentration. Heifers receiving bST also showed increased ribeye area; however, only an experimental day effect for backfat thickness was observed, with greater accumulation of carcass fat on day 84. Heifers receiving bST had lower pixels/mm² on parenchyma, characteristic of greater parenchymal tissue. Moreover, heifers on bST treatment also had reduced pixels/mm2, characteristic of reduced fat pad tissue. Lastly, bST injections did not influence liver and muscle gene expression, nor most genes evaluated in mammary gland tissue, except for IGFBP3 expression, which was greater for bST heifers. In summary, we confirm the efficacy of bST injections to overcome the detrimental effects of high-gain diets on mammary gland growth and to improve lean carcass gain of prepubertal Holstein × Gyr heifers.

Scheduling based on residual energy of sensors to extend the lifetime of network in wireless sensor network

The maximum amount of sensor energy is consumed during broadcasting. Hence in order to make delay with the network lifetime of a wireless sensor network (WSN), there is a need of optimum utilization of sensor energy. Scheduling in media access control (MAC) layer plays a critical role in the designing of WSN to avoid collision and conserve more energy. The Distributed energy aware MAC (DE-MAC) is one such efficient and feasible MAC protocol that addresses the energy management issues in WSN. This work proposes an extension of DE-MAC framework by allocating varying period slots to the nodes based on their residual energy level. Energy of all the nodes is exchanged at regular intervals. Accordingly, the nodes with low energy are allocated less time slots for broadcast and are made to sleep for more time. Simulation is carried out using NS2 (network simulator 2) and the efficiency and performance results are compared with DE-MAC for analysis. Improvement in performance for various parameters such as residual energy, throughput, and packet delivery ratio can be observed.

Experimental and theoretical investigation on a novel solar-assisted absorption-resorption heat pump (ARHP) system towards clean heating

Among thermally-activated heat pumps, absorption-resorption heat pump (ARHP) is dominant by the ability of combining with low-temperature heat for efficient space heating. In this work, an ARHP experimental prototype is developed based on the previous thermodynamic cycle and tested to obtain the operation details such as coefficient of performance (COP), supply water temperature, heating capacity and so on. The experimental and the previous theoretical results are compared and mutually verified. The exact performance of the solar-assisted ARHP heating system is then investigated and compared with that of the conventional vapor compression heat pump (VCHP) in terms of primary energy ratio (PER) and primary energy saving ratio (PESR). The experimental results show that the COP increases greatly from 1.125 to 1.353 when the heat source temperature increases from 90 °C to 150 °C at the ambient temperature and return water temperature of 0 °C and 30 °C, respectively. Under given conditions, the measured heating capacity reaches a maximum value of 18.5 kW, 9.0 % lower than the rated value. The theoretical results reveal that solar fraction above 30 % can make PER of the solar-assisted ARHP heating system comprehensively greater than that of the reference VCHP system. Optimal solar contribution to space heating can be achieved based on the proposed ARHP if solar heat is dividedly utilized in its temperature zones of 10–35 °C, 35–83 °C and above 83 °C.

A comparative study on NH3/H2 and NH3/CH3OH combustion and emission in an optical SI engine

Ammonia is an attractive carbon-free fuel but suffers from poor combustion characteristics and heavy emissions. Green hydrogen and methanol are recognized as the most promising combustion promoters for enhancing ammonia reactivity in pursuit of a carbon–neutral solution. Nonetheless, a comparative study on ammonia combustion and emissions, incorporating hydrogen and methanol enrichment, is currently absent under actual engine conditions. In this work, the combustion performance, visualized flame characteristics, and pollution emissions of ammonia were investigated in an optical engine, allowing for low-level hydrogen and methanol enrichment, specifically at energy ratios of 5%, 10%, and 15%. We have identified the crucial role of hydrogen and methanol enrichment in enhancing various aspects of ammonia engine performance, including thermal efficiency, combustion stability, flame initiation and propagation, and nitrogen-based emissions. Specifically, hydrogen enrichment demonstrates a more pronounced effect on reducing cyclic variations, whereas methanol enrichment exhibits a greater influence on increasing thermal efficiency, manifesting improved controllability in combustion phasing. Combustion visualizations show the contribution of hydrogen enrichment to the formation process of the initial flame kernel, which is reflected as a lower cyclic variation from a macroscopic perspective, and meanwhile, methanol enrichment features a stronger acceleration effect during the turbulent flame propagation process. Furthermore, the quantification of flame response to turbulence is solved and observed much higher effects for NH3/CH3OH blends than for NH3/H2 blends, indicating a distinctly different mechanism of facilitation by methanol enrichment. Regarding nitrogen-based emissions, both hydrogen and methanol enrichment lead to a substantial reduction in NH3 slip and N2O emissions, consistent with observed variations in combustion stability. However, methanol enrichment induces noticeable decreases in NOx emissions, while hydrogen enrichment exhibits an opposing trend. The present study demonstrates the beneficial impacts of hydrogen and methanol enrichment on improving ammonia combustion and emissions, with the underlying reason correlated to flame dynamics and thermochemical interactions.

Agricultural Waste Valorization: Exploring Environmentally Friendly Approaches to Bioenergy Conversion

The pursuit of sustainable energy production through the conversion of agricultural waste into different bioenergy resources is of paramount importance given its potential to mitigate environmental impact while meeting energy demands. In this review, a comprehensive overview of the technologies for the biochemical and thermochemical conversion of agricultural waste into bioenergy is provided. A summary of the process of its conversion into different bioenergy products such as biogas, bio-oil, and biofuel is provided, in addition to the potential advantages and challenges faced using different biomass conversion technologies. The review highlights the potential of agricultural waste valorization to address the current energy demand while at the same time contributing to environmental benefits and greenhouse gas emission reductions. Moreover, this review highlights some significant gaps for improvement. These include the challenges in the pretreatment of agricultural waste biomass in optimizing the conversion rates and lowering the required energy consumption throughout the process while enhancing both the quantity and quality of the output. Some recommendations are proposed to address the identified challenges. These include the need for further studies for a thorough assessment to evaluate the efficacity and sustainability of agricultural waste valorization technologies. Assessment methods such as life cycle assessment (LCA), life cycle analysis (LCA), net energy ratio (NER) calculations, life cycle costing (LCC), as well as techno-economic assessment (TEA), are recommended, together with collaboration among governments, farmers, and researchers, as well as the integration of cutting-edge technologies to enhance various aspects of agricultural waste, optimizing the conversion process, cost efficiency, time management, and labor requirements, consequently boosting the conversion efficiency and product quality.

The Size–Linewidth Relation and Signatures of Feedback from Quiescent to Active Star Forming Regions in the LMC

To investigate the effects of stellar feedback on the gravitational state of giant molecular clouds (GMCs), we study 12CO and 13CO Atacama Large Millimeter/submillimeter Array maps of nine GMCs distributed throughout the Large Magellanic Cloud (LMC), the nearest star-forming galaxy to our own. We perform noise and resolution matching on the sample, working at a common resolution of 3.″5 (0.85 pc at the LMC distance of 50 kpc), and we use the Spectral Clustering for Molecular Emission Segmentation clustering algorithm to identify discrete substructure, or “clumps.” We supplement these data with three tracers of recent star formation: 8 μm surface brightness, continuum-subtracted Hα flux, and interstellar radiation field energy density inferred from dust emission. The 12CO clumps identified cover a range of 3.6 dex in luminosity-based mass and 2.4 dex in average 8 μm surface brightness, representative of the wide range of conditions of the interstellar medium in the LMC. Our observations suggest evidence for increased turbulence in these clouds. While the turbulent linewidths are correlated with clump surface density, in agreement with previous observations, we find even better correlation with the three star formation activity tracers considered, suggesting stellar energy injection plays a significant role in the dynamical state of the clumps. The excess linewidths we measure do not appear to result from opacity broadening. 12CO clumps are found to be typically less gravitationally bound than 13CO clumps, with some evidence of the kinetic-to-gravitational potential energy ratio increasing with star formation tracers. Further multiline analysis may better constrain the assumptions made in these calculations.

A New Data Processing Approach for the SHPB Test Based on PSO-TWER

This study addresses the challenge of accurately determining the arrival time of stress wave signals in SHPB test data processing. To eliminate human error, we introduce the time-window energy ratio method and evaluate six filters for noise reduction using box fractal dimensions. A mathematical model is established to optimize the stress equilibrium and impact process, which is solved using particle swarm optimization, resulting in the PSO-TWER method. We explore the impact of inertia weight and calculation methods on optimization outcomes, defining a stress equilibrium evaluation index. The results indicate that time-window length significantly affects arrival-time outputs, and the dynamic inertia weight factor enhances optimization convergence. The method accurately determines arrival times and effectively screens test data, providing a robust approach for SHPB test data processing.

Role of proton exchange membrane fuel cell in efficiency improvement of ammonia–hydrogen fusion zero-carbon powertrains for long-haul, heavy-duty transportation

Ammonia fuel, a transport zero-carbon energy carrier with a much lower life-cycle greenhouse gas footprint than existing fuels and the ability to overcome the storage and transportation challenges of hydrogen fuel, is an effective means of realizing the energy transition for long-haul, heavy-duty transportation such as heavy trucks. Although the efficient use of liquid ammonia fuel cannot be realized directly at this stage, it can be realized indirectly by converting ammonia fuel into hydrogen and combining the hydrogen generated with ammonia in an ammonia–hydrogen fusion fuel supply method. In this study, we assess four ammonia–hydrogen fusion-fueled zero-carbon powertrains for heavy-duty commercial vehicles, each of which is designed to determine its most efficient green zero-carbon fuel utilization scenario at the point of steady state operation as well as over the entire power-demand interval. It was found that the required engine capacity decreases with the increase of the hydrogen energy ratio in the ammonia–hydrogen composite fuel. Considering the indicated thermal efficiency of the engine and the combustion stability in the cylinder, the ammonia–hydrogen composite fuel with 30% hydrogen energy share was selected for the matching design of the powertrains. The study results show that powertrain equipped with engine and fuel cell are more energy efficient than others. The powertrain with range extender consisting of the engine and fuel cell takes ammonia dissociation separation unit and fuel cell as an important part of engine exhaust gas heat recovery, which reduces the dependence of ammonia cracking hydrogen production on electric heating power. By regulating the energy distribution ratio between the engine and the fuel cell, the system can be maintained at a high level of energy efficiency. Under different power requirements of highway application scenarios, the system efficiency is not less than 36%, and the system energy utilization efficiency is higher than 44%. Compared to engine direct drive powertrain, engine range-extended powertrain, and fuel cell range-extended powertrain, the average system efficiency increases by 30.8%, 8.68%, and 14.24%, while the average system energy utilization increased by 41.12%, 25.26%, and 39.43%, respectively.

Hybrid Secure Cluster-Based Routing Algorithm for Enhanced Security and Efficiency in Mobile Ad Hoc Networks

ABSTRACT This research addresses critical gaps in Mobile Ad hoc Networks (MANETs) by proposing a hybrid secure cluster-based routing algorithm, focusing on enhancing network security, robustness, and reliability through multipath routing. Methodologically, the approach integrates Convolutional Neural Networks (CNN) for optimal path routing and Emperor Penguin Optimization (EPO) for clustering, introducing a novel combination for efficient cluster head selection. A novel contribution lies in the development of a prediction technique utilizing a trust assessment algorithm to calculate direct trust ratings at each node, incorporating fuzzy values between zero and one. Trust values are further influenced by node performance, adding a dynamic dimension to the trust evaluation process. Key novelties include the emphasis on energy efficiency, network longevity, remaining energy, security level, bandwidth, and packet delivery ratio as evaluation criteria. The proposed CNN-EPO model demonstrates superior results compared to traditional routing protocols, achieving a remarkable 95% energy efficiency, a heightened security level of 99%, and a throughput reaching up to 8 Mbps. Additionally, the Packet Delivery Ratio (PDR) attains close to 99% and routing overhead remains below 0.5, ensuring efficiency in challenging network scenarios with 50 adversaries. In summary, this research contributes a comprehensive solution to MANET challenges, introducing a novel hybrid routing algorithm, incorporating advanced methodologies for path optimization and clustering. These outcomes highlight how important the suggested strategy is to improve the existing state of the art in MANETs.

Sensitivity investigation of drilling efficiency to operational parameters of a drifter

Drilling operations are extensively used for underground excavation, and their efficiency has a direct impact on project duration and expense. Adjusting the operational parameters during the drilling process is important for improving drilling efficiency. In this study, the sensitivity of drilling efficiency to operational parameters was investigated. Full-scale drilling tests for a dolomite block were conducted using a hydraulic drifter, and the ‘measurement while drilling’ system was used to record the drilling data. Orthogonal schemes were designed to arrange the tests, and the penetration rate, specific energy and rate–energy ratio were regarded as evaluation indices to assess the drilling efficiency. The sensitivity of the evaluation indices to operational parameters was analysed using both range analysis and variance analysis. Results show that the optimal combination of parameters within the test range was determined to be the propelling pressure of 8.5 MPa, percussive pressure of 17.5 MPa and rotary speed of 250 r/min to obtain the maximum drilling efficiency. The sensitivity sequence of the rate–energy ratio was propelling pressure, percussive pressure and rotary speed, with weights of 54.0, 38.7 and 7.3%, respectively. These findings can provide a valuable reference for adjusting the operational parameters of hydraulic drifters to optimise drilling efficiency.

Defect detection of grouting sleeve connection with energy ratio change in frequency domain

Controlling the grouting density is the key to ensure the construction quality of precast structures. Since the grouting sleeve is embedded in concrete, it is difficult to detect the grouting compactness of the sleeve. In this paper, the frequency domain analysis technique is used for non-destructive testing of concrete components with grouting defects. The collected ultrasonic testing signals are calibrated-denoised-decomposed-reconstructed. The damage degree of the grouting signal is evaluated and analyzed by quantifying the energy value of different frequency signals with two norms. Considering the effect of the random distribution of aggregates on the propagation of ultrasonic stress waves, a three-dimensional multi-point detection model and a two-dimensional plane single-point model based on piezoelectric effect are set up respectively. Results show that frequency energy distribution of the grout-deficient signal is concentrated to low-frequency range than that of grout-compact signal. When grouting defect accumulates to a certain extent, the main frequency may move from high-frequency band to lower-frequency band. Although the aggregates in different concrete components are randomly distributed, the test results of the two-dimensional plane model show that the validity of the defect quantitative index is 72%. The experimental tests results show that the method of using frequency energy transfer to lower-frequency band to determine grouting defects is effective, with a detection validity of 66.7%. Therefore, the non-destructive testing method for grouting sleeve compactness proposed in this paper can provide reference for engineering testing application.

Evidence for a nearly orthogonal rotator in GX 301–2 with phase-resolved cyclotron resonant scattering features

Abstract Cyclotron resonant scattering features (CRSFs) are the absorption features in the X-ray spectra of strongly magnetized accretion neutron stars (NSs), which are probably the most reliable probe to the surface magnetic fields of NSs. The high mass X-ray binary GX 301–2 exhibits a very wide, variable and complicated CRSF in the average spectra, which should be two absorption lines based on NuStar and Insight-HXMT observations. With the Insight-HXMT frequent observations, we performed the phase-resolved spectroscopy and confirmed two cyclotron absorption lines in the phase-resolved spectra, with their centroid energy ratio ∼1.6 − 1.7 in the super-critical luminosity case. A major hindrance in understanding those CRSFs is the very poorly constrained magnetic inclination angle, which is also a fundamental property of a NS and key to understanding the emission characteristics of a pulsar. Comparing the phase-resolved CRSF with simulated X-ray spectra, the magnetic inclination angle is found to be ≳ 70○, i.e., nearly orthogonal between the NS’s spin and magnetic axies. The implications of an orthogonal rotator and magnetic structure evolution in the accreting X-ray binary are also discussed.

Physiological adaptations to semi‐aquatic habits: the thermogenic macronutrient intake of the Eurasian otter

Abstract Maintaining thermal homeostasis in water is a major challenge for semi‐aquatic mammals, which entails morphological, behavioural and physiological adaptations. Foraging strategies and dietary‐induced thermogenesis (DIT) contribute to regulating body temperature in cold environments. As DIT differs among macronutrients, semi‐aquatic mammals may be expected to regulate their macronutrient ratios to enhance their capability of thermoregulating. We estimated the nutritional intake target of a widespread semi‐aquatic mustelid, Eurasian otter Lutra lutra by reviewing the available literature on otters' diet throughout Europe and assessing the nutritional composition of non‐commercial fish species forming the bulk of otter diet through laboratory analyses. The macronutrient intake target for the otter was assessed as 61% protein and 39% lipid energy ratios. The mean percent protein energy was higher than that reported for typical hypercarnivores and tended to increase with decreasing water temperatures. The additional source of heat provided by the thermogenic effect induced by protein digestion may contribute to balance heat loss, compensating for the costs associated with protein overconsumption. If, as suggested by fossil records, semi‐aquatic habits appeared after the development of otter's ‘fish specialist’ dentition, the thermogenic effect of its fish‐based diet may have promoted the tight relationship occurring between otters and water habitats.

Reliable arrival time picking of acoustic emission using ensemble machine learning models

This study presents an innovative method for accurately picking the first-wave arrival time in acoustic emission (AE) localization, particularly effective in environments with low or variable signal-to-noise ratios (SNR). Utilizing an ensemble learning model, it synergizes multiple automatic arrival time estimation algorithms to enhance both consistency and robustness. The model, rooted in decision tree methodologies, integrates a variety of techniques, including Akaike information criterion (AIC), improved AIC, Hinkley, energy ratios, and wavelet transformation-based binary map. Its efficacy is demonstrated through testing on 549 manually annotated AE datasets, where the model’s predictions were benchmarked against manual picks, showcasing superior accuracy and robustness in AE event source localization. Evaluations of the model’s performance across various ensemble machine learning models highlighted its ability to significantly diminish localization errors, achieving an average absolute error of less than 1.5 mm. The study also delved into the impact of base pickers and the size of the training dataset on the model’s predictions. Findings indicated consistent performance across different decision tree models, with the accuracy of base pickers and training set size playing a significant role in outcomes. This research culminates in a decision tree-based ensemble machine learning solution that effectively estimates AE first-wave arrival times with high accuracy and robustness, even amidst fluctuating SNR conditions. Its adaptability and interpretability greatly reduce source localization errors in practical AE monitoring, effectively overcoming challenges associated with imprecise arrival time picking.

Improvement of dynamic response and energy conversion ratio of a global type solenoid for high-speed valve by using an innovative magnet ring

The transient behavior and energy transmission of a global type solenoid for high-speed valve (HSV) depend upon the magnetic force acting on the sphere. Rapid responses are challenging to achieve because of the limited power supply energy, which makes it hard to optimize the magnetic force through its own structural characteristics for HSV. Aiming to obtain higher magnetic force without increasing the input electric power, an innovative magnet radial ring is presented and a relative evaluation of magnetic forces exerted on a global type solenoid for HSVs is conducted. A hollow-plunger-type magnet radial ring is engineered as a novel magnet ring form. The magnetic forces and transient action time of the conventional HSV and innovative HSV are evaluated by means of finite element method (FEM) analysis and demonstrated by verification of the experimental data. The assessment of the magnetic forces involves every solenoid with a diverse magnet ring shape with the variation of height and thickness. The suggested novel magnet ring successfully increases the magnetic force applied to the sphere by changing the internal magnetic connection structure and increasing the mechanical energy conversion ratio, according to a methodical comparison of the two HSVs' transient performances. Meanwhile the innovative magnet ring can reduce the strength of iron loss occurred in the magnetic field of HSV to realize the reduction of useless power loss. At the magnetization position at the attraction, the magnetic force is 17.35 N, while the magnetic ring increases the magnetic force to 28.84 N. Also, the maximum rising speed of the magnetic force is improved from 14945 N/ms to 38904 N/ms, and the transient action time is reduced from 3.74 ms to 1.30 ms. For the mechanical energy and iron loss energy in energy conversion occurred in solenoid, the mechanical energy ratio increases from 16.2 % (conventional valve) to 27.8 % (innovative valve) with height 26 mm and thickness 3.5 mm, while the iron loss energy ratio decreases from 40.7 % (conventional valve) to 31.8 % (innovative valve) synchronously.

Tailored Meal-Type Food Provision for Diabetes Patients Can Improve Routine Blood Glucose Management in Patients with Type 2 Diabetes: A Crossover Study.

This study aimed to determine whether patients with type 2 diabetes can benefit from a meal plan designed based on diabetes management guidelines to improve blood glucose levels. Participants were divided into intervention and control groups. The intervention group consumed a diabetic diet for 2 weeks, while the control group consumed their normal diet. After 2 weeks, the groups switched their dietary regimens. The participants' demographic and clinical characteristics were evaluated, including factors such as blood pressure, blood lipid levels, weight and waist circumference, blood glucose levels (self-monitored and continuously monitored), nutritional status, and blood-based markers of nutrient intake. The dietary intervention group improved waist circumference, body fat percentage, low-density lipoprotein cholesterol, triglyceride levels, and glucose. The energy composition ratio of carbohydrates and proteins changed favorably, and sugar intake decreased. In addition, the proportion of continuous glucose monitoring readings within the range of 180-250 mg/dL was relatively lower in the intervention group than that of the control group. Meals designed based on diabetes management guidelines can improve clinical factors, including stable blood glucose levels in daily life, significantly decrease the carbohydrate energy ratio, and increase the protein energy ratio. This study can help determine the role of dietary interventions in diabetes management and outcomes.

Laminar and kinetic burning characteristics of ethanol/methane/hydrogen fuel: Experimental and numerical analysis

In this essay, the effects of ethanol addition on the fuels of Hydrogen methane mixing fuel were discussed. The laminar burning characteristics of ethanol/hydrogen/methane mixture under different ethanol content, pressure (1 bar, 2 bar), and equivalence ratios (0.7–1.4) were experimentally and numerically simulated. Results show that increasing ethanol content reduces the laminar burning velocity (LBV) and shifts the peak LBV towards higher equivalence ratios, attributed to the fuel mixture's decreased average combustion heat. For a 20 % ethanol content, the LBV peak appears at φ = 1.3, while for 50 % and 80 % ethanol content, it appears at φ = 1.2 locations. An empirical correlation for LBV as a function of ethanol concentration was developed, demonstrating predictions within a 4 % error margin compared to experimental data. High accuracy fittings of activation energy, ethanol concentration, and equivalence ratio were achieved, with correlation coefficients exceeding 0.9. Numerical simulations pinpointed key reactions and the relationship between free radicals and LBV, highlighting a pronounced correlation between OH radicals and LBV under lean conditions (coefficient of 1.0583), and a strong correlation with H radicals under rich conditions (coefficient of 1.01657), this indicates that OH and H are involved in the key chain reaction that promote the burning process.