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The production performances of fractured tight gas wells are closely related to several complex and unknown factors, including the formation properties, fracture parameters, gas–water two-phase flow, and other nonlinear flow mechanisms. The rate transient analysis (RTA) results have significant uncertainties, which should be quantified to evaluate the formation and fracturing treatment better. This paper provides an efficient method for uncertainty quantification in the RTA of fractured tight gas wells with multiple unknown factors incorporated. The theoretical model for making forward predictions is based on a trilinear flow model, which incorporates the effects of two-phase flow and other nonlinear flow mechanisms. The normalized rates and material balance times of both water and gas phases are regarded as observations and matched with the theoretical model. The unknowns in the model are calibrated using the ensemble Kalman filter (EnKF), which applies an ensemble of multiple realizations to match the observations and updates the unknown parameters step by step. Finally, a comprehensive field case from Northwestern China is implemented to benchmark the proposed method. The results show that the parameters and rate transient responses have wide ranges and significant uncertainties before history matching, while all the realizations in the ensemble can have good matches to the field data after calibration. The posterior distribution of each unknown parameter in the model can be obtained after history matching, which can be used to quantify the uncertainties in the RTA of the fractured tight gas wells. The ranges and uncertainties of the parameters are significantly narrowed down, but the parameters are still with significant uncertainties. The main contribution of the paper is the provision of an efficient integrated workflow to quantify the uncertainties in RTA. It can be readily used in field applications of multi-fractured horizontal wells from tight gas reservoirs. Full article

Automatic milking systems (AMSs) are revolutionizing the dairy industry by boosting herd efficiency, primarily through an increased milk yield per cow and reduced labor costs. The performance of milking machines, whether traditional or automated, can be evaluated using advanced vacuum meters through dynamic testing. This process involves scrutinizing the system and milking routine to identify critical points, utilizing the VaDia™ logger (BioControl AS, Rakkestad, Norway). Vacuum recordings were downloaded and analyzed using the VaDia Suite™ software under the guidance of a milking specialist. Access to data from AMSs across various manufacturers and herds facilitated a retrospective study aimed at describing and comparing key milk emission parameters for different AMS brands while identifying potential mastitis risk factors. Using the proper statistical procedures of SPSS 29.1 (IBM Corp., Armonk, NY, USA), researchers analyzed data from 4878 individual quarter milkings from cows in 48 dairy herds. Results indicated a significant variability in milking parameters associated with quarter milk yield and AMS brand. Notably, despite AMSs standardizing teat preparation and stimulation, this study revealed a surprisingly high frequency of two major mastitis risk factors—bimodality and irregular vacuum fluctuations—occurring more frequently than in conventional milking systems. This study, one of the few comparing different AMS brands and their performance, highlights the crucial role of dynamic testing in evaluating AMS performance under real-world conditions. Full article

In the context of the electricity sector’s liberalization and deregulation, the accurate forecasting of electricity prices has emerged as a crucial strategy for market participants and operators to minimize costs and maximize profits. However, their effectiveness is hampered by the variable temporal characteristics of real-time electricity prices and a wide array of influencing factors. These challenges hinder a single model’s ability to discern the regularity, thereby compromising forecast precision. This study introduces a novel hybrid system to enhance forecast accuracy. Firstly, by employing an advanced decomposition technique, this methodology identifies different variation features within the electricity price series, thus bolstering feature extraction efficiency. Secondly, the incorporation of a novel multi-objective intelligent optimization algorithm, which utilizes two objective functions to constrain estimation errors, facilitates the optimal integration of multiple deep learning models. The case study uses electricity market data from Australia and Singapore to validate the effectiveness of the algorithm. The forecast results indicate that the hybrid short-term electricity price forecasting system proposed in this paper exhibits higher prediction accuracy compared to traditional single-model predictions, with MAE values of 7.3363 and 4.2784, respectively. Full article

This study presents a novel, machine-learning-based Automatic Incident Detection (AID) system for freeways. Through a comprehensive analysis of existing AID systems, the paper identifies their limitations and key performance metrics. VISSIM, a traffic simulation software, is employed to generate diverse, realistic traffic data incorporating factors significantly impacting AID performance. The developed system utilizes an Artificial Neural Network (ANN) trained via RapidMiner software. The ANN is designed to learn and differentiate normal and incident traffic patterns. Training yields a Detection Rate (DR) of 95.6%, a False Alarm Rate (FAR) of 1.01%, and a Mean Time to Detection (MTTD) of 0.89 min. Testing demonstrates continued effectiveness with a DR of 100%, a FAR of 1.29%, and a MTTD of 1.6 min. Furthermore, a sensitivity analysis is conducted to assess the influence of individual factors on system performance. Based on these findings, recommendations for enhancing AID systems are provided, promoting improved traffic safety and incident management. This research empowers transportation authorities with valuable insights to implement effective incident detection strategies, ultimately contributing to safer and more efficient freeways. Full article

A Si-based photodetector is the core device of Si-based optical interconnection; its material and performance are the key factors restricting its development. This paper conducts theoretical research on the issues of lattice mismatch between heterogeneous materials and low device responsivity in Si-based InGaAs photodetectors for the 1550 nm optical communication band. The material mismatch issue is addressed through the use of the high-aspect ratio trapping (ART) epitaxial technique, enabling the realization of high-performance Si-based III-V materials. By introducing a dielectric metasurface into the top layer of the structure, the light absorption efficiency is enhanced, realizing broadband optical absorption enhancement for Si-based photodetectors. This paper mainly focuses on designing the optimal parameters of the dielectric metasurface structure based on the finite-difference time-domain (FDTD) Solutions to achieve the performance analysis of a high-responsivity 1550 nm Si-based InGaAs photodetector. The results show that the quantum efficiency of the dielectric metasurface structure is theoretically estimated to be 88.8% and the response rate is 1.11 A/W, which is 2%~16% higher than that of the unetched structure in the whole band. The research results of this paper will provide new ideas for the development of novel, high-performance, and miniaturized Si-based photodetectors and lay a theoretical foundation for Si-based optical interconnection. Full article

Household energy consumption represents a significant share of global energy usage, highlighting the importance of understanding the factors that influence energy use and identifying potential strategies for conservation. The Caribbean region faces unique challenges in energy sustainability, driven by its heavy dependence on fossil fuels and rising energy demand due to its heavy reliance on fossil fuels and increasing energy demand. The primary aim of this study is to evaluate the current levels of energy awareness and energy consumption among households on the tropical Caribbean island of Curaçao and to determine practical energy-saving opportunities that can significantly reduce both energy consumption and costs. This paper is one of the first to evaluate energy awareness, energy use, and energy-saving opportunities among households in the Caribbean. The study included a literature review of key theories, concepts, and energy-saving strategies, along with a telephone survey of 382 households in Curaçao to examine household energy use, the factors shaping energy behavior, and the connections between energy consumption, behavior, and household income. The main findings of this study reveal that energy-efficient appliances are predominantly used in high-income households, with much lower adoption rates in middle- and low-income households. Cost savings, rather than environmental concerns, emerge as the primary motivation behind energy-saving behavior. Notably, the study highlights that most households in Curaçao are largely unaware of the full range of energy-efficient options available to them for reducing energy consumption. Based on the field study results, several recommendations are offered to enhance energy awareness, expand energy-saving opportunities, and ultimately reduce energy usage. Full article

The ongoing transition to energy systems with high shares of variable renewables motivates the development of novel thermal power cycles that operate economically at low capacity factors to accommodate wind and solar intermittency. This study presents two recuperated power cycles with low capital costs for this market segment: (1) the near-isothermal hydrogen turbine (NIHT) concept, capable of achieving combined cycle efficiencies without a bottoming cycle through fuel combustion in the expansion path, and (2) the intercooled recuperated water-injected (IRWI) power cycle that employs conventional combustion technology at an efficiency cost of only 4% points. The economic assessment carried out in this work reveals that the proposed cycles increasingly outperform combined cycle benchmarks with and without CO₂ capture as the plant capacity factor reduces below 50%. When the cost of fuel storage and delivery by pipelines is included in the evaluation, however, plants fired by hydrogen lose competitiveness relative to natural gas-fired plants due to the high fuel delivery costs caused by the low volumetric energy density of hydrogen. This important but uncertain cost component could erode the business case for future hydrogen-fired power plants, in which case the IRWI concept powered by natural gas emerges as a promising solution. Full article

Global warming and climate change are major concerns across multiple disciplines. Population growth, urbanization, and industrialization are significant contributing factors to such problems due to the escalating use of fossil fuels required to meet growing energy demands. The building sector uses the largest share of total global energy production and produces tons of greenhouse gas emissions. Emerging eco-friendly technologies, such as solar and wind energy harvesting, are being extensively explored; however, they are insufficient. Nature-inspired technologies could offer solutions to our problems. For instance, algae are microorganisms that use water, light, and CO₂ to produce energy and sustain life, and the exploitation of these characteristics in a built environment is termed algae building technology, which is a very efficient and green application suitable for a sustainable future. Algae-integrated façades show great versatility through biomass and energy production, wastewater treatment, shading, and thermal and acoustic insulation. In this paper, algae will be introduced as a robust tool toward a greener and more sustainable future. Algae building technology and its implementation will be demonstrated. Furthermore, steps for applying this sustainable strategy in Egypt will be discussed. Full article

The cultivation or ‘tillage’ system is one of the most important elements of agrotechnology. It affects the condition of the soil, significantly modifying its physical, chemical, and biological properties, and the condition of plants, starting from ensuring appropriate conditions for sowing and plant growth, through influencing the efficiency of photosynthesis and ultimately, the yield. It also affects air transmission and the natural environment by influencing greenhouse gas (GHG) emissions potentially. Ultimately, the cultivation system also has an impact on the farmer, providing the opportunity to reduce production costs. The described experiment was established in 1998 at the Brody Agricultural Experimental Station belonging to the University of Life Sciences in Poznań (Poland) on a soil classified as an Albic Luvisol, while the described measurements were carried out in the 2022/2023 season, i.e., 24 years after the establishment of the experiment. Two cultivation methods were compared: Conventional Tillage (CT) and No Tillage (NT). Additionally, the influence of two factors was examined: nitrogen (N) fertilization (0 N—no fertilization, and 130 N–130 kg N∙ha⁻¹) and the growth phase of the winter wheat plants (BBCH: 32, 65 and 75). The growth phase of the plants was assessed according to the method of the Bundesanstalt, Bundessortenamt and CHemische Industrie (BBCH). We present the results of soil properties, soil respiration, wheat plants chlorophyll fluorescence, and grain yield. In our experiment, due to low rainfall, NT cultivation turned out to be beneficial, as it was a key factor influencing the soil properties, including soil organic carbon (SOC) content and soil moisture, and, consequently, creating favorable conditions for plant nutrition and efficiency of photosynthesis. We found a positive effect of NT cultivation on chlorophyll fluorescence, but this did not translate into a greater yield in NT cultivation. However, the decrease in yield due to NT compared to CT was only 5% in fertilized plots, while the average decrease in grain yield resulting from the lack of fertilization was 46%. We demonstrated the influence of soil moisture as well as the growth phase and fertilization on carbon dioxide (CO₂) emissions from the soil. We can clearly confirm that the tillage system affected all the parameters discussed in the work. Full article

Renewable energy sources play a vital role in the energy mix with geothermal energy providing an opportunity to harness the natural heat coming from the Earth for sustainable power production. As innovative drilling technologies come to market, it is easier to extract heat from various localities across the globe, leading to significant development in the geothermal sector. The economic viability of this resource can be significantly impacted when energy output declines due to scale deposition. Scale formation is a major challenge in the exploitation of geothermal wells, particularly in liquid-dominated geothermal fields. One of the most robust forms of scale build-up common to higher temperature geothermal wellbores and surface equipment for power production is silica scaling. Silica is one of the Earth’s most abundant elements that can precipitate from brine due to various factors. The accumulation of scale deposits significantly impacts the lifespan and efficiency of surface equipment and geothermal wells by restricting fluid flow, thus reducing efficiency and performance. To guarantee the peak performance and longevity of geothermal systems, it is essential to implement a strategic maintenance plan for scaling reduction in geothermal systems. Throughout this review, relevant case studies highlight scaling reduction methods for silica scale in subsurface wellbores and surface facilities. Full article

In recent years, the enthusiasm for deep space missions has remained unabated, resulting in continuous advancements in the research field of space environment and particles. Many instruments carried on these missions have conducted detection of pickup ions (PUIs) in the solar system. For those instruments, simulation is an effective means and a crucial step for their performance optimization and future operation in-orbit. It holds great significance for the instrument’s in-orbit performance assessment, science operation optimization, and detection efficiency enhancement. In this paper, the traditional probability model and the Vasyliunas and Siscoe (V–S) model are used to generate the PUIs, which are the input for the simulation of the PUI detector. For further analysis, the numerical results of the simulation are processed to calculate the instrument’s geometric factor, mass resolution, and count rates. Then, two sets of experiments are carried out for the comparison of the traditional probability model and the V–S model. The results show that, for the simulation of the instrument in the design stage, the simulation results of the traditional probability model and the V–S model are not much different. However, for the simulation of the instrument performance in-orbit, the PUI data generated based on the V–S model gave a better result than those of the traditional probability model. This conclusion is of great significance for evaluating the detection ability of the PUI detector in future deep space explorations. Full article

This investigation focuses on the prevalent continental oil shale within the Triassic Chang 7, a member of the Yanchang Formation in the Ordos Basin and the Permian Lucaogou Formation in the Junggar Basin of western China, and delves into the impacts of hydrocarbon generation and the derived organic acids on the physical attributes of oil shale reservoirs. Water-soluble organic acids (WSOAs) were extracted via Soxhlet extraction and analyzed by a 940 ion chromatograph (Metrohm AG), supplemented with core observations, thin-section analyses, pyrolysis, and trace element assays, as well as the qualitative observation of pore structures via FIB-SEM scanning electron microscopy. The study discloses substantial disparities in the types and abundances of organic acids within the oil shale strata of the two regions, with mono-acids being conspicuously more prevalent than dicarboxylic acids. The spatial distribution of organic acids within the oil shale strata in the two regions is non-uniform, and their generation is inextricably correlated with the type of organic matter, thermal maturity, and depth at which they are buried. During diverse stages of diagenesis, the hydrocarbons and organic acids produced from the pyrolysis of organic matter not only exert an impact on the properties of pore fluids but also interact with diagenetic processes such as compaction, dissolution, and metasomatism to enhance the reservoir quality of oil shale. The synergy between chemical interactions and physical alterations collectively governs the migration and distribution patterns of organic acids as well as the characteristics of oil shale reservoirs. Furthermore, the sources of organic acids within the oil shale series in the two regions demonstrate pronounced dissimilarities, which are intimately associated with the peculiarities of their sedimentary milieu. The oil shale of the Yanchang Formation was formed in a warm and humid freshwater lacustrine basin environment, while the oil shale of the Lucaogou Formation was deposited in a brackish to saline lacustrine setting under an arid to semi-arid climatic regime. These variances not only illuminate the intricacy and multiplicity of the sedimentary attributes of oil shale but also accentuate the impact of the sedimentary environment on the genesis and distribution of organic acids, especially the transformation and optimization of reservoir dissolution by organic acids generated during hydrocarbon generation—a factor of paramount significance for the precise identification and effective development of the “sweet spot” area of shale oil. These areas, characterized by an abundance of organic matter, their maturity, and superior reservoir properties, are the foci of the efficient exploration and development of continental shale oil. Full article

With the frequent occurrence of natural disasters and the acceleration of urbanization, it is necessary to carry out efficient evacuation, especially when earthquakes, fires, terrorist attacks, and other serious threats occur. However, due to factors such as small targets, complex posture, occlusion, and dense distribution, the current mainstream algorithms still have problems such as low precision and poor real-time performance in crowd person detection. Therefore, this paper proposes EAAnet, a crowd person detection algorithm. It is based on YOLOv5, with CBAM (Convolutional Block Attention Module) introduced into the backbone, BiFPN (Bidirectional Feature Pyramid Network) introduced into the neck, and combined with a loss function of CIoU_Loss to better predict the person number. The experimental results show that compared with other mainstream detection algorithms, EAAnet has achieved significant improvement in precision and real-time performance. The precision value of all categories was 78.6%, which was increased by 1.8. Among these, the categories of riders and partially visible person were increased by 4.6 and 0.8, respectively. At the same time, the parameter number of EAAnet is only 7.1M, with a calculation amount of 16.0G FLOPs. Therefore, it is proved that EAAnet has the ability of the efficient real-time detection of the crowd person and is feasible in the field of emergency management. Full article

In this study, a closed multi-channel air-blowing plug seedling pick-up device and a combined plug tray were designed to address the issues of complex structure, high seedling damage rates and low pick-up efficiency in fully automated vegetable transplanter systems. The device operates by sealing the plug seedlings in a seedling cup, where compressed air is channeled into the sealed cavity through multiple passages during the seedling pick-up process. The upper surface of the seedling plug is subjected to uniform force, overcoming the friction and adhesion between the plug seedlings and the tray. This process presses the seedlings into the guide tube, completing the pick-up operation. A mechanical model for the plug seedlings was developed, and the kinetics of the pick-up process were analyzed. The multi-channel high-pressure airflow was simulated and evaluated, identifying three key parameters affecting seedling pick-up performance: water content of the seedling plug, air pressure during pick-up, and air-blowing duration. Using these factors as variables, and with seedling pick-up rate and substrate loss rate as evaluation indicators, single-factor experiments and a three-factor, three-level orthogonal experiment were conducted. The experiments’ results showed that the best seedling pick-up performance was achieved when the water content of the plug was 20%, the air pressure was 0.3 MPa, and the air-blowing time was 30 ms. Under these conditions, the seedling pick-up success rate was 97.22%, and the substrate loss rate was 10.46%. Full article

This study presents a comprehensive model for ultrasonic energy transfer (UET) using a 33-mode piezoelectric transducer to advance wireless sensor powering in challenging environments. One of the advantages of UET is that it is not stoppable by electromagnetic shielding and can penetrate metal. Existing models focus on feasibility and numerical analysis but lack an effective link between input and output power in different media applications. The proposed model fills this gap by incorporating key factors of link loss, including resonant frequency, impedance matching, acoustic coupling, and boundary conditions, to predict energy transfer efficiency more accurately. The model is validated through numerical simulations and experimental tests in air, metal, and underwater environments. An error analysis has shown that the maximum error between theoretical and experimental responses is 3.11% (air), 27.37% (water), and 1.76% (aluminum). This research provides valuable insights into UET dynamics and offers practical guidelines for developing efficient wireless powering solutions for sensors in difficult-to-access or electromagnetically shielded conditions. Full article