Search Results (6)

The Chinese mitten crab (Eriocheir sinensis), as an aquatic food with high economic value, is favored by consumers for its high nutritional value and unique flavor. Its physiological status during temporary rearing and live transportation determines changes in meat quality, nutrition, flavor and food safety. Environmental stresses during this process are prone to inducing physiological disturbances in the crabs, resulting in reduced survival rates and degraded product quality. This paper systematically reviews the impacts of four pivotal environmental factors, namely dissolved oxygen (DO) levels, ambient temperature, water salinity, and ammonia nitrogen concentration, on the survival performance and quality maintenance of E. sinensis during temporary holding and live transport. It comprehensively clarifies the mechanisms through which fluctuations in these factors elicit physiological stress, oxidative damage, and metabolic disorders in the crabs while evaluating effective mitigation strategies such as gradient cooling and precise water quality regulation. In addition, key research gaps in the field are identified, including the lack of real-time vitality monitoring technologies and species-specific standardized transportation protocols, and future directions involving the integration of sensor technologies and adaptive environmental regulation are proposed. In summary, the survival status and quality of E. sinensis during temporary rearing and live transportation are synergistically regulated by various environmental factors. Developing scientific strategies can effectively mitigate the adverse effects of environmental stress, ensure food safety, and provide a theoretical basis for the live preservation, processing, and transportation of aquatic products. Full article

Dust accumulation on photovoltaic (PV) modules reduces power generation efficiency, and traditional water-based cleaning is impractical in arid regions. Inspired by the classical acoustic phenomenon of Chladni figures—specifically the mechanism where an acoustic standing wave field drives the regular migration and accumulation of particles—this study proposes a waterless dust removal method using low-frequency ultrasonic vibration via piezoelectric excitation. Impedance analysis identifies optimal electromechanical coupling at 28 kHz. Experiments demonstrate that higher driving voltages accelerate cleaning, with recovery rates saturating beyond 125 V. Notably, intense friction and collisions between particles within high-density dust layers consume substantial kinetic energy, significantly multiplying the required cleaning time. Macroscopic transport analysis reveals that dust removal relies on the synergy of vibration-induced adhesion decoupling and gravity-driven transport. Sufficient tangential gravity is crucial for macroscopic particle removal, and tilt angles above 30° provide the necessary downward driving force to ensure smooth particle sliding. Under optimal conditions, the system achieves an over 97% short-circuit current recovery at a low power consumption of ~10 W, providing a theoretical basis for waterless PV self-cleaning systems. Full article

Geothermal energy is a clean, renewable, and baseload-stable resource of strategic importance for carbon neutrality. Hot dry rock (HDR) reservoirs are characterized by high temperatures, great depths, and abundant reserves. However, their extremely low natural permeability requires artificial fracturing to establish effective heat exchange networks. Conventional hydraulic fracturing in enhanced geothermal systems (EGS) faces major challenges under HDR conditions, including excessive water consumption, strong water–rock interactions, and elevated induced seismicity risks, limiting its engineering applicability. Waterless or low-water fracturing technologies offer alternative stimulation pathways due to their distinctive physicochemical properties. Existing reviews have mainly addressed individual aspects, such as specific fracturing media or proppant transport, without systematically integrating recent advances in supercritical CO₂ fracturing, foam fracturing, liquid nitrogen fracturing, and hybrid-fluid fracturing technologies, or comprehensively evaluating their engineering implications. This review systematically analyzed the fracturing mechanisms, heat exchange performance, environmental risks, and HDR-specific engineering challenges of these technologies. Results indicate that waterless/low-water fracturing technologies enhance heat extraction efficiency by generating complex fracture networks while mitigating seismic and reservoir damage risks. However, large-scale application requires further advances in the high-temperature stability of fracturing media, material durability, multiphase flow control, and field validation. Full article

Waterless transportation for live grouper is a novel mode of transport that not only saves money, but also lowers wastewater pollution. Technical obstacles remain, however, in achieving intelligent monitoring and a greater survival rate. During live grouper waterless transportation, the stress response is a key indicator that affects the survival life-span of the grouper. Studies based on breathing rate analysis have demonstrated that among many stress response parameters, breathing rate is the most direct parameter to reflect the intensity. Conventional measurement methods, which set up sensors on the gills of groupers, interfere with the normal breathing of living aquatic products and are complex in system design. We designed a new breathing monitoring system based on a completely non-destructive approach. The system allows the real-time monitoring of living aquatic products’ breathing rate by simply placing the millimeter wave radar on the inner wall of the incubator and facing the gills. The system we developed can detect more parameters in the future, and can replace the existing system to simplify the study of stress responses. Full article

This study focused on the anesthetic waterless keep-alive transport technique for turbot. MS-222 and eugenol were used to anesthetize turbot and then the waterless keep-alive transport was conducted. The blood physiological changes and flesh quality changes of turbot were evaluated after cooling and during the simulated waterless transport. The results show that the temperature lowered from 13 to 2 °C, resulting in a decrease in moisture, fat and protein contents of all samples. Compared to the control turbot, the turbots treated with MS-222 and eugenol presented higher pH and glycogen content. During the simulated waterless transport, the pH, ATP and glycogen contents in MS-222- and eugenol-treated turbots decreased and the IMP and lactate levels increased. For the blood biochemical indices, blood glucose, cortisol and urea nitrogen increased with the increase in transport time in MS-222- and eugenol-treated turbots. At sampling time, the changes in blood physiological indices were significantly higher in the control samples than those in the MS-222- and eugenol-treated samples. The results indicate that the turbot samples treated with MS-222 or eugenol could reduce stress during cooling and simulated waterless transport. Full article

Accurate prediction of forthcoming oxygen concentration during waterless live fish transportation plays a key role in reducing the abnormal occurrence, increasing the survival rate in delivery operations, and optimizing manufacturing costs. The most effective ambient monitoring techniques that are based on the analysis of historical process data when performing forecasting operations do not fully consider current ambient influence. This is likely lead to a greater deviation in on-line oxygen level forecasting in real situations. Therefore, it is not advisable for the system to perform early warning and on-line air adjustment in delivery. In this paper, we propose a hybrid method and its implementation system that combines a gray model (GM (1, 1)) with least squares support vector machines (LSSVM) that can be used effectively as a forecasting model to perform early warning effectively according to the dynamic changes of oxygen in a closed system. For accurately forecasting of the oxygen level, the fuzzy C-means clustering (FCM) algorithm was utilized for classification according to the flatfish’s physical features—i.e., length and weight—for more pertinent training. The performance of the gray model-particle swarm optimization-least squares support vector machines (GM-PSO-LSSVM) model was compared with the traditional modeling approaches of GM (1, 1) and LSSVM by applying it to predict on-line oxygen level, and the results showed that its predictions were more accurate than those of the LSSVM and grey model. Therefore, it is a suitable and effective method for abnormal condition forecasting and timely control in the waterless live transportation of flatfish. Full article