Search Results (955)

Mushrooms are eukaryotic organisms with absorptive heterotrophic nutrition, capable of feeding on organic matter rich in cellulose and lignocellulose. Since ancient times, they have been considered allies and, in certain cultures, they were seen as magical beings or food of the gods. Of the great variety of edible mushrooms identified worldwide, less than 2% are traded on the market. Although mushrooms have been valued for their multiple nutritional and healing benefits, some cultures perceive them as toxic and do not accept them in their culinary practices. Despite the existing skepticism, several researchers are promoting the potential of edible mushrooms. There are two main methods of mushroom cultivation: solid-state fermentation and submerged fermentation. The former is the most widely used and simplest, since the fungus grows in its natural environment; in the latter, the fungus grows suspended without developing a fruiting body. In addition, submerged fermentation is easily monitored and scalable. Both systems are important and have their limitations. This article discusses the main methods used to increase the performance of submerged fermentation with emphasis on the modes of operation used, types of bioreactors and application of morphological bioengineering of filamentous fungi, and especially the use of intelligent automatic control technologies and the use of non-invasive monitoring in fermentation systems thanks to the development of machine learning (ML), neural networks, and the use of big data, which will allow more accurate decisions to be made in the fermentation of filamentous fungi in submerged environments with improvements in production yields. Full article

Atmospheric and oceanic turbulence can severely degrade the orbital angular momentum (OAM) mode purity of vortex beams in cross-media optical links. Here, we propose a hybrid correction framework that fuses multiscale phase-screen modeling with a lightweight U-Net predictor for phase-distortion—driven solely by measured optical intensity—and augments it with a feed-forward, Gaussian-reference subtraction scheme for iterative compensation. In our experiments, this approach boosts the l = 3 mode purity from 38.4% to 98.1%. Compared to the Gerchberg–Saxton algorithm, the Gaussian-reference feed-forward method achieves far lower computational complexity and greater robustness, making real-time phase recovery feasible for OAM-based communications over heterogeneous channels. Full article

Background: Neonatal jaundice is common and can cause severe hyperbilirubinemia if untreated. The early identification of at-risk newborns is challenging despite the existing guidelines. Objective: This study aimed to identify the key maternal and neonatal risk factors for jaundice requiring phototherapy using machine learning. Methods: In this study hospital, phototherapy was administered following the American Academy of Pediatrics (AAP) guidelines when a neonate’s transcutaneous bilirubin level was in the high-risk zone. To identify the risk factors for phototherapy, we retrospectively analyzed the electronic medical records of 8242 neonates admitted between 2017 and 2022. Predictive models were trained using maternal and neonatal data. XGBoost showed the best performance (AUROC = 0.911). SHAP values interpreted the model. Results: Mode of delivery, neonatal feeding indicators (including daily formula intake and breastfeeding frequency), maternal BMI, and maternal white blood cell count were strong predictors. Cesarean delivery and lower birth weight were linked to treatment need. Conclusions: Machine learning models using perinatal data accurately predict the risk of neonatal jaundice requiring phototherapy, potentially aiding early clinical decisions and improving outcomes. Full article

Heuristic optimization is used to find sustainable cogeneration steam power plants with steam reheat and supercritical main steam parameters. Design solutions are analyzed for steam consumer (SC) pressures of 3.6 and 40 bar and a heat flow rate of 40% of the fuel heat flow rate. The objective functions consisted in simultaneous maximization of global and exergetic efficiencies, power-to-heat ratio in full cogeneration mode, and specific investment minimization. For 3.6 bar, the indicators improve with the increase in the ratio between reheating and main steam pressure. The increase in SC pressure worsens the performance indicators. For an SC steam pressure of 40 bar and 9 feed water preheaters, the ratio between reheating and main steam pressure should be over 0.186 for maximum exergetic efficiency and between 0.10 and 0.16 for maximizing both global efficiency and power-to-heat ratio in full cogeneration mode. The average global efficiency for an SC requiring steam at 3.6 bar is 4.4 percentage points higher than in the case with 40 bar, the average specific investment being 10% lower. The Pareto solutions found in this study are useful in the design of sustainable cogeneration supercritical power plants. Full article

This paper presents the design, simulation, and experimental validation of a dual-Circularly Polarized (CP) array antenna to be used as single element for a bistatic radar system, aimed at detecting and tracking objects in Low Earth Orbit (LEO). The antenna operates at 412 MHz in reception mode and consists of an array of 19 slotted-patch radiating elements with a cavity-based metallic superstrate, designed to support dual circular polarization. These elements are arranged in a hexagonal configuration, enabling the array structure to achieve a maximum realized gain of 17 dBi and a Side Lobe Level (SLL) below −17 dB while maintaining high polarization purity. Two identical analog feeding networks enable the precise control of phase and amplitude, allowing the independent reception of Right-Hand and Left-Hand Circularly Polarized (RHCP and LHCP) signals. Full-wave simulations and experimental measurements confirm the high performance and robustness of the system, demonstrating its suitability for integration into large-scale Space Situational Awareness (SSA) sensor networks. Full article

This paper addresses the challenge of maximizing power extraction in offshore wind energy systems through the development of an enhanced maximum power point tracking (MPPT) control strategy. Offshore wind energy is inherently intermittent, leading to discrepancies between power generation and electricity demand. To address this issue, we propose three advanced control algorithms to perform a comparative analysis: sliding mode control (SMC), the Integral Backstepping-Based Real-Twisting Algorithm (IBRTA), and Feed-Back Linearization (FBL). These algorithms are designed to handle the nonlinear dynamics and aerodynamic uncertainties associated with offshore wind turbines. Given the practical limitations in acquiring accurate nonlinear terms and aerodynamic forces, our approach focuses on ensuring the adaptability and robustness of the control algorithms under varying operational conditions. The proposed strategies are rigorously evaluated through MATLAB/Simulink 2024 A simulations across multiple wind speed scenarios. Our comparative analysis demonstrates the superior performance of the proposed methods in optimizing power extraction under diverse conditions, contributing to the advancement of MPPT techniques for offshore wind energy systems. Full article

Concentration polarization (CP) is one of the inherent problems that lowers the operating performance of forward osmosis (FO) membranes. Therefore, a quantitative evaluation of CP is vital to understand its impact on the FO process. This study systematically investigated the influences of different CPs on the osmotic pressure drop across the membrane under different conditions by using the water transmission coefficient, η_WT, defined as the ratio of the measured water flux to the theoretical water flux. The results showed that η_WT decreased with an increase in the concentration gradient between the draw solution (DS) and the feed solution (FS) under different conditions. The proportions of osmotic pressure drop caused by dilutive internal concentration polarization (ICP) increased, while those caused by concentrative external concentration polarization (ECP) decreased, in different types of DSs in FO mode. Both ECP and ICP were found to be capable of reducing osmotic pressure. However, the internal CP had the dominant influence. To better understand the adverse effects of CP, using an organic FS provided greater insight than using deionized (DI) water as the FS. As the FS concentration increased, the water flux reduced, and the adverse effects of CP worsened. CaCl₂ led to a greater reduction in water transfer efficiency than NaCl when used as the DS. In comparison to FO mode, pressure-retarded osmosis (PRO) mode led to greater pure water flux and flux decline. In FO mode, both the proportion of dilutive ICP and the η_WT decreased, while the proportion of concentrative ECP increased over time. However, in PRO mode, the proportions of dilutive ECP and concentrative ICP increased, and η_WT gradually decreased. Dilutive ICP had a significant negative effect on osmotic pressure in the former, while dilutive ECP was dominant in the latter. Full article

This study developed a two-dimensional multiphysics-coupled model for co-electrolysis of CO₂ and H₂O in solid oxide electrolysis cells (SOECs) using COMSOL Multiphysics, systematically investigating the influence mechanisms of key operating parameters including temperature, voltage, feed ratio, and flow configuration on co-electrolysis performance. The results demonstrate that increasing temperature significantly enhances CO₂ electrolysis, with the current density increasing over 12-fold when temperature rises from 923 K to 1423 K. However, the H₂O electrolysis reaction slows beyond 1173 K due to kinetic limitations, leading to reduced H₂ selectivity. Higher voltages simultaneously accelerate all electrochemical reactions, with CO and H₂ production at 1.5 V increasing by 15-fold and 13-fold, respectively, compared to 0.8 V, while the water–gas shift reaction rate rises to 6.59 mol/m³·s. Feed ratio experiments show that increasing CO₂ concentration boosts CO yield by 5.7 times but suppresses H₂ generation. Notably, counter-current operation optimizes reactant concentration distribution, increasing H₂ and CO production by 2.49% and 2.3%, respectively, compared to co-current mode, providing critical guidance for reactor design. This multiscale simulation reveals the complex coupling mechanisms in SOEC co-electrolysis, offering theoretical foundations for developing efficient carbon-neutral technologies. Full article

Background: Intermittent fasting (IF) can improve inflammatory status, but its effects may be dependent on the mode of fasting. Objectives: We performed a systematic review with pairwise and network meta-analyses to investigate the effects of different modes of IF on inflammatory markers in adults. Methods: Three database searches were conducted, including PubMed, Scopus, and Web of Science, from inception to June 2024. The searches used two keyword groups: “intermittent fasting” and “inflammatory markers”. Randomized and non-randomized trials investigating any IF mode on inflammatory markers, including interleukin (IL)-6, tumor necrosis factor (TNF)α, C-reactive protein (CRP), leptin, and adiponectin, were included. Standardized mean differences (SMDs) were calculated using random effects models for both analyses. Results: A total of 21 studies (839 participants) were included. Compared with controls, IF reduced TNF-α [SMD: −0.31, p = 0.009], CRP [SMD: −0.19, p = 0.04], and leptin [SMD: −0.57, p = 0.005] but did not significantly affect IL-6 or adiponectin. Among the IF modes, time-restricted feeding (TRF) showed the largest reduction in TNF-α [−0.39, p = 0.001]. TRF had the highest probability ranking for changes in IL-6, TNF-α, leptin, and adiponectin; however, the effects on IL-6 and adiponectin were not statistically significant. The 5:2 diet ranked highest for CRP. Conclusions: IF may be an effective dietary therapy for improving some inflammatory markers, with effects potentially influenced by the mode of IF. TRF had the highest rankings across multiple markers, though the findings were not uniformly significant. Additional longer-term trials are needed to fully elucidate the anti-inflammatory potential of IF. Full article

Kleptoplastidy is a nutrition mode in which cells of protists and some multicellular organisms acquire, maintain, and exploit chloroplasts of prey algae cells as photosynthesis reactors. It is an important aspect of the mixotrophic feeding strategy, which plays a role in the formation of harmful algae blooms (HABs). We developed a new mathematical model, in which kleptoplastidy is regarded as a mechanism of enhancing mixotrophy of protists. The model is constructed using three thought (theoretical) experiments and the concept of biological time. We propose to measure the contribution of kleptoplastidy to mixotrophy using a new ecological indicator: the kleptoplastidy index. This index is a function of two dimensionless variables, one representing the ratio of photosynthetic production of acquired chloroplasts versus native chloroplasts, and the other representing the balance between autotrophic and heterotrophic feeding modes. The index is tested by data for the globally distributed, bloom-forming potentially toxic mixotrophic dinoflagellates Prorocentrum cordatum. The model supports our hypothesis that kleptoplastidy can increase the division rate of algae significantly (by 40%), thus boosting their population growth and promoting blooms. The proposed model can contribute to advancements in ecological modeling aimed at forecasting and management of HABs that deteriorate marine coastal environments worldwide. Full article

This paper proposes an anti-disturbance model predictive fault-tolerance control strategy for open-circuit faults of five-phase flux intensifying fault-tolerant interior permanent magnet (FIFT-IPM) motors. This strategy is applicable to electric agricultural equipment that has an open winding failure. Due to the rich third-harmonic back electromotive force (EMF) content of five-phase FIFT-IPM motors, the existing model predictive current fault-tolerant control algorithms fail to effectively track fundamental and third-harmonic currents. This results in high harmonic distortion in the phase current. Hence, this paper innovatively proposes a multi-plane virtual vector model predictive fault-tolerant control strategy that can achieve rapid and effective control of both the fundamental and harmonic planes while ensuring good dynamic stability performance. Additionally, considering that electric agricultural equipment is usually in a multi-disturbance working environment, this paper introduces an adaptive gain sliding-mode disturbance observer. This observer estimates complex disturbances and feeds them back into the control system, which possesses good resistance to complex disturbances. Finally, the feasibility and effectiveness of the proposed control strategy are verified by experimental results. Full article

This paper proposes a novel high-gain, wideband, circularly polarized (CP) metasurface (MTS) antenna. The antenna is composed of a centrally symmetric MTS and a slot-coupled feeding network. Through characteristic mode analysis (CMA), parasitic patches and mode-suppressing patches are added around the MTS to enhance the desired modes and suppress the unwanted modes. Subsequently, a feeding network that merges a ring slot with an L-shaped microstrip line is utilized to excite two orthogonal modes with a 90° phase difference, thereby achieving CP and high-gain radiation. Finally, a prototype with dimensions of 0.9λ₀ × 0.9λ₀ × 0.05λ₀ is fabricated and tested. The measured results demonstrate an impedance bandwidth (IBW) of 39.5% (4.92–7.37 GHz), a 3 dB axial ratio bandwidth (ARBW) of 33.1% (5.25–7.33 GHz), and a peak gain of 9.4 dBic at 6.9 GHz. Full article

The rising demand for sustainable aquaculture necessitates innovative solutions to environmental and operational challenges. Biofloc technology (BFT) has emerged as an effective method, leveraging microbial communities to enhance water quality, reduce feed costs, and improve fish health. However, traditional BFT systems are susceptible to water quality fluctuations, demanding precise monitoring and control. This review explores the integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in smart BFT systems, highlighting their capacity to automate processes, optimize resource utilization, and boost system performance. IoT devices facilitate real-time monitoring, while AI-driven analytics provide actionable insights for predictive management. We present a comparative analysis of AI models, such as LSTM, Random Forest, and SVM, for various aquaculture prediction tasks, emphasizing the importance of performance metrics like RMSE and MAE. Furthermore, we discuss the environmental and economic impacts, including quantitative case studies on cost reduction and productivity increases. This paper also addresses critical aspects of AI model reliability, interpretability (SHAP/LIME), uncertainty quantification, and failure mode analysis, advocating for robust testing protocols and human-in-the-loop systems. By addressing these challenges and exploring future opportunities, this article underscores the transformative potential of AI and IoT in advancing BFT for sustainable aquaculture practices, offering a pathway to more resilient and efficient food production. Full article

Essential oils have emerged as promising alternatives for pest insect control. However, sublethal effects on insect reproduction and development are rarely explored, despite their relevance to integrated pest management (IPM). This study evaluated the sublethal effects of Piper hispidivervum C. DC. essential oil (EOPH) on the development and population growth of four populations of Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae), as well as the persistence of safrole residue in treated corn grains. Population development rates were determined using emergence curves and total emerged adults, while population growth was assessed by counting live insects in the feeding substrate at different storage intervals. Safrole residue persistence was analyzed using solid-phase microextraction in headspace mode (SPME-HS). Sublethal exposure to EOPH significantly reduced the development rate, total emergence, and growth in three of the four populations. The population from Crixás, GO, showed no significant reduction, with a population curve overlapping the control. The lethal dose was reduced by 98.20%, indicating low persistence and potential food safety. The EOPH exhibited sublethal effects on S. zeamais populations, reducing both development rates and population growth. This reduction varied among the populations studied. Further research is encouraged to explore its effects on different insect populations and under broader environmental conditions. Full article

Owing to its high energy efficiency, regenerative capability, and fast dynamic response, the Electromagnetic Energy-Feeding Shock Absorber has found widespread application in automotive suspension control systems. To further improve thrust control precision, this study presents a sliding mode thrust controller designed using an improved Gray Wolf Optimization algorithm. Firstly, an improved exponential reaching law is adopted, where a saturation function replaces the traditional sign function to enhance system tracking accuracy and stability. Meanwhile, a position update strategy from the particle swarm optimization (PSO) algorithm is integrated into the gray wolf optimizer (GWO) to improve the global search ability and the balance of local exploitation. Secondly, the improved GWO is combined with sliding mode control to achieve online optimization of controller parameters, ensuring system robustness while suppressing chattering. Finally, comparative analyses and simulation validations are conducted to verify the effectiveness of the proposed controller. Simulation results show that, under step input conditions, the improved GWO reduces the rise time from 0.0034 s to 0.002 s and the steady-state error from 0.4 N to 0.12 N. Under sinusoidal input, the average error is reduced from 0.26 N to 0.12 N. Under noise disturbance, the average deviation is reduced from 2.77 N to 2.14 N. These results demonstrate that the improved GWO not only provides excellent trajectory tracking and control accuracy but also exhibits strong robustness under varying operating conditions and random white noise disturbances. Full article