Search Results (185)

Electric submersible pumps (ESPs) are critical for artificial lift operations; however, they are prone to frequent failures, often resulting in high operational costs and production downtime. Traditional ESP failure classifications are limited by lack of standardization and the conflation of failure modes with root causes. To address these limitations, this study proposes a new two-step integrated failure modes and root cause (IFMRC) classification system. The new framework clearly distinguishes between failure modes and root causes, providing a systematic, structured approach that enhances fault diagnosis and failure analysis and can lead to better failure prevention strategies. This methodology was validated using a case study of over 4000 ESP installations. The data came from Egypt’s Western Desert, covering a decade of operational data. The sources included ESP databases, workover records, and detailed failure investigation (DIFA) reports. The failure modes were categorized into electrical, mechanical, hydraulic, chemical, and operational types, while root causes were linked to environmental, design, operational, and equipment factors. Statistical analysis, in this case study, revealed that motor short circuits, low flow conditions, and cable short circuits were the most frequent failure modes, with excessive heat, scale deposition, and electrical grounding faults being the dominant root causes. This study underscores the importance of accurate root cause failure classification, robust data acquisition, and expanded failure diagnostics to improve ESP reliability. The proposed IFMRC framework addresses limitations in conventional taxonomies and facilitates ongoing enhancement of ESP design, operation, and maintenance in complex field conditions. Full article

Inverter-equipped heat pumps allow for increased energy efficiency. However, air conditioning (AC) systems often operate at low load ratios below where inverter control is effective, which reduces their energy efficiency. We developed an AC system that increases the apparent load ratio of the heat pump by using a phase-change material (PCM). Cooling and heating experiments were conducted with a PCM heat exchanger, which comprised aluminum plates and fins filled with paraffinic PCM. The result indicated a high heat transfer coefficient of >70 W/(m²·K). A simplified numerical model of the PCM heat exchanger as a lumped constant system was created based on the experiment. The calculations generally reproduced the experimental results, with root mean squared errors of 0.39 K for cooling and 0.84 K for heating, confirming their accuracy. Simulations were then conducted to evaluate the energy performance of the proposed system for the cooling season. While low load operation accounted for 39% of the total AC time for a non-PCM system, it was reduced to 2.7% for the proposed system. The proposed system demonstrated load ratios of 50–60% for most of the season, achieving an energy reduction of 11.4% owing to the improved efficiency at partial load ratios. Full article

Proton pump inhibitors (PPIs) are widely prescribed medications primarily used to treat gastroesophageal reflux disease, peptic ulcer disease, and upper gastrointestinal bleeding. Despite clear therapeutic benefits in appropriate contexts, widespread overprescribing and extended use without clear indications have prompted significant concerns about associated risks. Accumulating evidence, predominantly from observational studies, suggests that long-term PPI use may lead to complications such as vitamin and mineral deficiencies, increased risks of infections, dysbiosis, renal dysfunction, bone fractures, cardiovascular disease, and certain malignancies. This narrative review not only synthesizes the current evidence surrounding PPI-related harms and existing deprescribing guidelines but also offers a novel perspective on how stewardship principles can be applied to promote responsible PPI prescribing. In particular, we propose a stewardship-oriented deprescribing framework rooted in implementation science, focusing on provider behavior, patient engagement, and health system-level integration. Recognizing these potential harms, evidence-based deprescribing strategies such as tapering, intermittent dosing, and transitions to alternative therapies are critical to mitigate unnecessary patient exposure. Effective implementation of deprescribing requires addressing patient, provider, and institutional barriers through educational initiatives, policy support, and structured monitoring. By promoting judicious PPI prescribing and proactive stewardship practices, clinicians can significantly reduce medication-related harm and improve patient safety. Full article

The variable-speed operation mode of pumped storage units improves the regulation performance and endows the units with characteristics such as isolation from the power grid, thereby affecting the system stability. This study establishes a detailed mathematical model for the connection of doubly fed induction generator-based variable-speed pumped storage (DFIG-VSPS) to a single-machine infinite bus system under power generation conditions in the synchronous rotation direct-quadrature-zero coordinate system. The introduction of the eigenvalue method to analyze the small-disturbance stability of doubly fed variable-speed pumped storage units and the use of participation factors to calculate the degree of influence of each state variable on the small-disturbance stability of the units are innovations of this study. The participation factor enhances flexibility, continuity, and efficiency in doubly fed variable-speed pumped storage by optimizing dynamic power paths and enabling multi-objective control coordination. While eigenvalue analysis is not new, this study is the first to apply it with participation factors to DFIG-VSPS, addressing gaps in prior simplified models. Furthermore, based on the changes in the characteristic root trajectories, the influence of changes in the speed control system parameters and converter controller parameters on the system stability was determined. Finally, the conclusions obtained were verified through simulation. The results indicate that increasing the time constant of water flow inertia poses a risk of system instability, and the increase in proportional parameters and decrease in integral parameters of the power outer loop controller significantly affect the system stability. Full article

To address the challenges in predicting roof water hazards in weakly cemented strata of Northwest China, this study pioneers an integrated CNN-BiLSTM model for aquifer water abundance prediction. Focusing on the 1301E working face in the Yili No. 1 Coal Mine, we employed kriging interpolation to process sparse hydrological datasets (mean relative error: 8.7%), identifying five dominant controlling factors—aquifer burial depth, hydraulic conductivity, core recovery rate, sandstone–mudstone interbedded layer count, and sandstone equivalent thickness. The proposed bidirectional architecture synergizes CNN-based spatial feature extraction with BiLSTM-driven nonlinear temporal modeling, optimized via Bayesian algorithms to determine hyperparameters (32-channel convolutional kernels and 64-unit BiLSTM hidden layers). This framework achieves the comprehensive characterization of multifactorial synergistic effects. The experimental results demonstrate: (1) that the test set root mean square error (1.57 × 10⁻³) shows 65.3% and 85.9% reductions compared to the GA-BP and standalone CNN models, respectively; (2) that the coefficient of determination (R² = 0.9966) significantly outperforms the conventional fuzzy analytic hierarchy process (FAHP, error: 0.071 L/(s·m)) and BP-based neural networks; (3) that water abundance zoning reveals predominantly weak water-rich zones (q = 0.05–0.1 L/(s·m)), with 93.3% spatial consistency between predictions and pumping test data. Full article

The summer cultivation of lettuce in greenhouses frequently encounters heat stress challenges. In hydroponic systems, cooling the nutrient solution to reduce root zone temperature is an effective strategy to alleviate heat stress. To address the issue of temperature control instability in hydroponic nutrient solutions under high-temperature conditions, this study developed a nutrient solution temperature control system based on an adaptive DBO-fuzzy PID controller. Firstly, the system integrates high-precision sensor networks and air-source heat pump units, forming the hardware foundation. Simultaneously, a fuzzy PID controller optimized by the Dung Beetle Optimizer (DBO) algorithm was designed for this system, enabling real-time adjustment of quantization and scaling factors in the fuzzy controller. Simulation results showed that the DBO-Fuzzy PID achieved a settling time of 35.23 s, overshoot of 2.18%, and steady-state error of 0.009 °C. The DBO-Fuzzy PID controller exhibited faster and more stable disturbance rejection compared to traditional PID and fuzzy PID control, demonstrating enhanced stability and robustness. System performance tests in the summer greenhouse demonstrated that with a setpoint of 22 °C, the DBO-Fuzzy PID optimized nutrient solution temperature control system maintained an average temperature of 21.98 °C, closer to the target value and exhibiting better adaptability to high-temperature environments compared to traditional PID control. Cultivation experiments confirmed the system’s effectiveness in mitigating heat stress and maintaining optimal nutrient solution temperature for lettuce growth. The results can provide a theoretical basis and practical reference for precise and stable temperature control in hydroponic nutrient solutions. Full article

Gastroesophageal reflux disease (GERD) is a common chronic gastrointestinal disorder that greatly influences patients’ quality of life and represents a growing public health concern. Characterized by typical and atypical symptoms, GERD encompasses a range of clinical phenotypes and is associated with complications such as erosive esophagitis and Barrett’s esophagus. This review intends to provide a thorough overview of current scientific knowledge on the etiological factors, risk determinants, and pathophysiology of GERD, while exploring diagnostic challenges and therapeutic approaches. Proton pump inhibitors (PPIs) remain the mainstay of medical therapy; however, concerns regarding their long-term safety have encouraged interest in adjunctive and alternative strategies. Emerging pharmacological agents, plant-based treatments, and integrative approaches rooted in traditional medicine offer promising modalities for enhanced management. Additionally, dietary and lifestyle modifications such as weight control, meal timing, and avoidance of trigger foods, are essential components of effective care. A multidisciplinary framework incorporating pharmacological, nutritional, and behavioral strategies is emphasized as the most reliable path toward personalized and sustainable GERD management. This review further aims to synthesize current therapeutic modalities and evolving perspectives in the treatment of GERD. Full article

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that measures weak magnetic fields generated by neural electrical activity in the brain. Traditional MEG systems use superconducting quantum interference device (SQUID) sensors, which require cryogenic cooling and employ a dense array of sensors to capture magnetic field maps (MFMs) around the head. Recent advancements have introduced optically pumped magnetometers (OPMs) as a promising alternative. Unlike SQUIDs, OPMs do not require cooling and can be placed closer to regions of interest (ROIs). This study aims to optimize the layout of OPM-MEG sensors, maximizing information capture with a limited number of sensors. We applied a sequential selection algorithm (SSA), originally developed for body surface potential mapping in electrocardiography, which requires a large database of full-head MFMs. While modern OPM-MEG systems offer full-head coverage, expected future clinical use will benefit from simplified procedures, where handling a lower number of sensors is easier and more efficient. To explore this, we converted full-head SQUID-MEG measurements of auditory-evoked fields (AEFs) into OPM-MEG layouts with 80 sensor sites. System conversion was done by calculating a current distribution on the brain surface using minimum norm estimation (MNE). We evaluated the SSA’s performance under different protocols, for example, using measurements of single or combined OPM components. We assessed the quality of estimated MFMs using metrics, such as the correlation coefficient (CC), root-mean-square error, and relative error. Additionally, we performed source localization for the highest auditory response (M100) by fitting equivalent current dipoles. Our results show that the first 15 to 20 optimally selected sensors (CC > 0.95, localization error < 1 mm) capture most of the information contained in full-head MFMs. Our main finding is that for event-related fields, such as AEFs, which primarily originate from focal sources, a significantly smaller number of sensors than currently used in conventional MEG systems is sufficient to extract relevant information. Full article

This study aimed to evaluate the impact of a more cost-efficient strigolactone mimic SL-6 on Chlorella sorokiniana NIVA-CHL 176 growth in comparison with the strigolactone analog GR24 and the plant biostimulant functions of microalgal extracts. Three molar SL-6 concentrations were tested: 10⁻⁷ M, 10⁻⁸ M, and 10⁻⁹ M, respectively. Five parameters of microalgal growth were assessed: optical density, turbidity, biomass production, chlorophyll fluorescence, and pigment concentration. Results after 15 days of culturing revealed that the SL-6 treatments significantly enhanced biomass production (13.53% at 10⁻⁹ M), pigment synthesis, and photosystem II activity (14.38% at 10⁻⁹ M). The highest increases in pigments induced by SL-6 were 15.7% for chlorophyll a (at 10⁻⁸ M SL-6), 12.87% for chlorophyll b (at 10⁻⁹ M SL-6), 2.3% for carotenoids (at 10⁻⁸ M SL-6), and 10.78% for total pigments (at 10⁻⁸ M SL-6) per gram biomass compared to the solvent control (DMSO). Higher doses of GR24 and SL-6 (10⁻⁷ M) inhibited microalgal growth, reducing cell density, biomass production, and pigment synthesis. The microalgal extracts acted as plant biostimulants, stimulating root and shoot elongation and proton pump functioning of mung seedlings in the presence and absence of salt stress. The extracts from SL-6 biostimulated C. sorokiniana were more active as plant biostimulants than the extracts from the non-stimulated C. sorokiniana. Full article

This work involves the development of a hydrodynamic fertilizer injector (HFI), which uses an integrated axial-flow turbine (AFT) and a diaphragm pump to absorb liquid fertilizer. Three structural parameters—the number of impellers (M₁), average number of blades per impeller (M₂), and arrangement pattern (M₃)—are considered, and 12 AFT designs are developed. Using a combination of CFD numerical simulations and hydraulic performance testing, the response of the AFT output power (P), blade negative pressure (NP), and fertilizer injection flow rate (Q_inj) to structural parameters and inlet pressure (H) is investigated. The results show that the normalized root mean square error between the simulated outlet flow rate (Q_s) and the measured flow rate (Q_m) is 5.1%, indicating high accuracy in the grid motion simulation method. P increases first and then decreases with the increase in impeller speed (n). The maximum P (P_max) ranges from 150.1 to 201.4 W. P_max increases with H, decreases with increasing M₁ and M₂, and shows little change with M₃. At H = 0.14 MPa, M₁ and M₂ have a significant influence, and at H ≥ 0.14 MPa, M₁ becomes the most significant factor (p < 0.05). Low-speed flow and negative pressure cavitation zones at the leading edge of the blade suction surface cause flow blockage and affect the lifespan of the AFT. These regions decrease in size as H increases but increase with M₁. The negative pressure (NP) decreases as M₂ increases. When M₁, M₂, and M₃ are 2, 3, and identical (D33), the P_max of the AFT is maximized, increasing by 6.7% to 33.5% compared with those of the other combinations. The Q_inj of D33, D34, D43, and D44 at H = 0.12~0.18 MPa range from 288.6 to 847.3 L/h, which is 38.7% to 461.0% higher than that of domestic and international venturi injectors. When considering cavitation issues and the manufacturing cost of the AFT mold, D44 may be chosen. Although its Q_inj is 7.0% lower than that of D33, NP is reduced by 37.9%. These findings provide a basis for the development of the HFI with AFT as the driving unit. Full article

This paper presents a validated simulation model for heat pump-based energy recycling systems, with a focus on heat recovery applications in grocery stores. Heat is recovered through heat pumps from a subcritical CO₂-based refrigeration system, with exhaust air heat recovery used on demand according to the heating demand. The model is validated through a case study on a Finnish hypermarket-sized grocery store, where the heat pump system has been operational since 2020. Multi-objective energy optimization is used to validate the model by estimating critical decision variable values and providing error estimates compared to the measured data. The calibrated energy system model has a maximum mean bias error, MBE, of ±5% and a 10–15% coefficient of variation of root mean squared error, CV(RMSE), for the heat pump-related energy balance. Energy optimizations indicate that the control algorithm of the investigated heat pump system can be enhanced to reduce district heating consumption by 12%. The study emphasizes the need for numerous input parameters tailored to a system-specific layout to accurately reproduce the heat pump system’s control algorithm. Compared to a typical transcritical CO₂ booster system with heat recovery, the novel heat recovery system shows superior heat recovery potential and a high total COP for both heating and cooling. Full article

Silicon carbide is a covalently bonded engineering material and structural ceramic with excellent mechanical properties, high resistance to oxidation, corrosion, and wear, and tunable thermal conductivity. The exceptional thermal conductivity of silicon carbide ceramic promotes its candidature in many industrial applications, such as nuclear fuel capsule materials, substrate materials employed in semiconductor devices, heater plates, and heaters for processing semiconductor and gas seal rings employed in compressor pumps, among others. The synthesis of polycrystalline silicon carbide through the liquid-phase sintering approach results in lower thermal conductivity due to the presence of structural defects associated with grains, lattice impurities, grains’ random orientations, and the presence of secondary phases in polycrystalline silicon carbide ceramic. The conventional experimental method of enhancing thermal conductivity is laborious and expensive. This present work modeled the thermal conductivity of liquid-phase silicon carbide ceramic via intelligent approaches involving genetic algorithm-optimized support vector regression (SVR-GA), an extreme learning machine with a sine activation function (ELMS), and random forest regression (RFR). The descriptors for the models included the nature of sintering additives as well as their weights, sintering conditions, applied pressure, sintering temperature, and time. Using the mean absolute error (MAE) and root mean square error (RMSE) for performance assessment, it was observed that the ELMS outperformed the RFR and SVR-GA models with improvements of 40.50% and 25.76%, respectively, using the MAE metric and improvements of 16.57% and 24.43%, respectively, using the RMSE metric. The developed models were further used to investigate the effect of the weight of sintering additives and sintering time on the thermal conductivity of silicon carbide ceramic. The precision of the developed models facilitated a comprehensive investigation of the effect of sintering factors on thermal conductivity while hidden connections that exist between the factors are uncovered for enhancing application domains for silicon carbide ceramics. Full article

Innovation in cultivation methods is essential to address the growing challenges in agriculture, including abiotic and biotic stress, soil degradation, and climate change. Aeroponics, a particular type of hydroponics, presents a promising solution by improving yield and resource use efficiency, especially in controlled environments such as plant factories with artificial lighting (PFALs). Additionally, non-thermal plasma (NTP), a partially ionized gas containing reactive oxygen and nitrogen species, can affect plant development and physiology, further enhancing crop production. The objective of this study was to explore the potential of NTP as an innovative method to enhance crop production by treating the nutrient solution in aeroponic systems. During this study, three experiments were conducted to assess the effects of NTP-treated nutrient solutions on baby leaf lettuce (Lactuca sativa L.) aeroponically grown indoors. The nutrient solution was treated with ionized air in a treatment column separated from the aeroponic system by making the ionized air bubble from the bottom of the column. After 2 min of NTP application, a pump took the nutrient solution from the treatment column and sprayed it on the roots of plants. Various frequencies of NTP application were tested, ranging from 2.5% to 50% of irrigation events with nutrient solution activated with NTP. Results indicated that low-frequency NTP treatments (up to 5% of irrigations) stimulated plant growth, increasing leaf biomass (+18–19%) and enhancing the concentration of flavonoids (+16–18%), phenols (+20–21%), and antioxidant capacity (+29–53%). However, higher NTP frequencies (25% and above) negatively impacted plant growth, reducing fresh and dry weight and root biomass, likely due to excessive oxidative stress. The study demonstrates the potential of NTP as a tool for improving crop quality and yields in aeroponic cultivation, with optimal benefits achieved at lower treatment frequencies. Full article

This paper investigates the design methodologies of pure rolling helical gear pumps with various tooth profiles, based on the active design of meshing lines. The transverse active tooth profile of a pure rolling helical gear end face is composed of various function curves at key control points. The entire transverse tooth profile consists of the active tooth profile and the Hermite curve as the tooth root transition, seamlessly connecting at the designated control points. The tooth surface is created by sweeping the entire transverse tooth profile along the pure rolling contact curves. The fundamental design parameters, tooth profile equations, tooth surface equations, and a two-dimensional fluid model for pure rolling helical gears were established. The pressure pulsation characteristics of pure rolling helical gear pumps and CBB-40 involute spur gear pumps, each with different tooth profiles, were compared under specific working pressures. This comparison encompassed the maximum effective positive and negative pressures within the meshing region, pressure fluctuations at the midpoints of both inlet and outlet pressures, and pressure fluctuations at the rear sections of the inlet and outlet pressures. The results indicated that the proposed pure rolling helical gear pump with a parabolic tooth profile exhibited 42.81% lower effective positive pressure in the meshing region compared to the involute spur gear pump, while the maximum effective negative pressure was approximately 27 times smaller than that of the involute gear pump. Specifically, the pressure pulsations in the middle and rear regions of the inlet and outlet pressure zones were reduced by 33.1%, 6.33%, 57.27%, and 69.61%, respectively, compared to the involute spur gear pump. Full article

Phase transformations induced by short optical pulses are mainstream in studies on the dynamics of cooperative electronic states. We present a semiphenomenological modeling of spatiotemporal effects expected when optical excitons are intricate with the order parameter such as in, e.g., organic compounds with neutral-ionic ferroelectric phase transitions. A conceptual complication appears here, where both the excitation and the ground state ordering are built from the intermolecular electronic transfer. To describe both thermodynamic and dynamic effects on the same root, we adopt, for the phase transition, a view of the excitonic insulator—a hypothetical phase of a semiconductor that appears if the exciton energy becomes negative. After the initial pumping pulse, a quasi-condensate of excitons can appear as a macroscopic quantum state that then evolves, while interacting with other degrees of freedom which are prone to an instability. The self-trapping of excitons enhances their density, which can locally surpass a critical value to trigger the phase transformation. The system is stratified in domains that evolve through dynamical phase transitions and may persist even after the initiating excitons have recombined. Full article