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[Introduction] In response to the inability of existing communication conditions to meet the intelligent O&M and ecological monitoring needs of offshore wind farm, this article explores and proposes a 5G customized network scheme to solve the problems of poor signal accessibility, incomplete network coverage, and low smoothness in offshore wind farms. [Methods] In this paper, a comprehensive O&M and monitoring scheme was proposed by using 5G customized network technology, which was as follows: through the deployment of 5G macro base stations outdoors, 5G indoor distribution in towers, and underwater laying of optical networks, the 3D coverage of wind farm communication networks was realized; Based on 5G slicing technology, one network could be used for multiple purposes to meet the needs of offshore wind farms for network differentiation; computing nodes were deployed in the centralized control center computer room, and private network data was forwarded through the edge UPF (user plane function) to achieve computing-network integration. [Result] The intelligent management and ecological environment monitoring scheme for offshore wind farms based on 5G technology proposed in this article has been piloted and tested based on the project. The test results show that the maximum effective coverage radius of 5G base stations reaches 11.3 km, and the stable transmission uplink rate reaches 5 Mbps, meeting the needs of observation data return and unmanned ship video return in the sea area. By deploying two 2.1G 8TR enhanced base stations on the booster station and wind turbine to enhance sea area coverage, the pull-net test around the wind farm verified that the 5G private network can effectively cover wind farms, with a coverage rate of 98.4%, which can basically meet the coverage needs of the entire wind farm. [Conclusion] This scheme utilizes a 5G private network to cover the sea area of the wind farm and achieves underwater communication through STN (Smart Transport Network) and underwater optical networks. Consequently, it innovatively constructs a 3D ocean monitoring and communication network, laying the communication foundation for the intelligent management and ecological environment monitoring of offshore wind farms.

Triphenyl phosphate (TPhP) serves as a major organophosphorus flame retardant, and its induced neurodevelopmental toxicity has attracted widespread attention, but the mechanism remains unclear. In this study, we involved zebrafish to explore the new mechanism of TPhP inducing oxidative stress and ferroptosis to promote neurodevelopmental toxicity. The results suggested that TPhP affected the embryonic development, reduced the number of new neurons, and led to abnormal neural behavior in zebrafish larvae. TPhP also induced ROS accumulation, activated the antioxidant defense signal Nrf2 and Keap1, and significantly changed the activities of Acetylcholinesterase (AChE), Adenosine triphosphatase (ATPase) and glutathione S-transferase (GST). In addition, TPhP induced ferroptosis in zebrafish, which was reflected in the increase of Fe2+ content, the abnormal expression of GPX4 protein and genes related to iron metabolism (gpx4a, slc7a11, acsl4b, tfa, slc40a1, fth1b, tfr2, tfr1a, tfr1b and ncoa4). Astaxanthin intervention specifically inhibited ROS levels, and reversed SLC7A11 and GPX4 expression levels and Fe2+ metabolism thus alleviating ferroptosis induced by TPhP. Astaxanthin also partially reversed the activity of AChE, GST and the expression of neurodevelopmental-related genes (gap43, gfap, neurog1 and syn2a), so as to partially rescue the embryonic developmental abnormalities and motor behavior disorders induced by TPhP. More interestingly, the expression of mitochondrial apoptosis-related protein BAX, anti-apoptotic protein BCL-2, Caspase3 and Caspase9 was significantly altered in the TPhP exposed group, which could be also reversed by Astaxanthin intervention. In summary, our results suggested that TPhP exposure can induce oxidative stress and ferroptosis, thereby causing neurodevelopment toxicity to zebrafish, while Astaxanthin can partially reverse oxidative stress and reduce the neurodevelopmental toxicity of zebrafish larvae by activating Nrf2/Keap1/HO-1 signaling pathway.

Abstract In underground engineering such as mining and tunnel excavation, the rock mass is often subjected to repeated loading and unloading stress environments. Herein, true triaxial cyclic loading and unloading tests are carried out on fine sandstone and medium‐fine sandstone specimens with cracks of different angles. The test results show that the mechanical properties of fine sandstone and medium‐fine sandstone samples show obvious differences, and the crack angle has a significant effect on the mechanical properties of the sandstone specimen. During the experimentation, the expansion phenomenon of medium‐fine sandstone is more obvious than that of fine sandstone, and its brittleness is also weaker. The damage law of the sample has nothing to do with the type of sandstone. The damage caused by the stress in the σ1 direction varies linearly with the cumulative damage of the specimen, however, the damage caused by the directions of σ2 and σ3 grow nonlinearly in terms of the cumulative damage of the specimen. The hysteretic loop dissipated energy of the same type of sandstone specimens at different angles are dissimilar, and the dissipated energy increases with the increase of the crack angle. Based on the equivalent irreversible strain and the hysteretic loop dissipated energy, the damage law of the rock strength is analyzed. The obtained results reveal that the index based on the equivalent irreversible strain is helpful in exploring the damage degree of rock in the initial stage of cyclic loading and unloading. Furthermore, the damage index established based on the energy dissipation concept is beneficial to predicting the damage and failure law of rock in the advanced stage of loading.

Abstract The effect of crack angle on energy evolution during sandstone failure subjected to true triaxial cyclic loading and unloading is of great concern. However, the energy consumed in the crack initiation and compaction process is generally referred to the dissipated energy, which is inaccurate. To reveal the energy law in the breaking process of sandstone, a complex cyclic loading and unloading test is carried out on precast angled sandstone samples by employing the triaxial test system. The area integral methodology is exploited to evaluate the evolution of total energy density, elastic energy density, dissipated energy density, and plastic energy density of the rock samples of different crack angles. The variations of these four energy density levels in terms of the number of loading and unloading cycles and the upper limit of stress are explained and discussed. The obtained results reveal that during the entire cycle of loading and unloading, the variations of the above‐mentioned factors of the rock sample fairly do not rely on the crack angle. The energy density increases with the number of cycles, and the total energy density and elastic energy density significantly increase faster than the consumption mode. The growth rate of the dissipative energy density is greater than that of the plastic energy density. Additionally, the aforementioned four energy quantities grow in a quadratic manner as a function of the upper limit of the loading stress. The releasable elastic energy gradually magnifies by increasing the upper limit of the loading stress. The plasticity density first decreases and then increases, reflecting the change law of the irreversible plastic deformation caused by newly developed cracks in the rock sample. The elastic energy density, the fitting coefficient of the dissipated energy density, and the total energy density are employed to define the characteristic coefficients of the rock energy storage and energy dissipation. The results indicate that the larger the rock crack angle, the stronger the energy storage energy and the weaker the energy dissipation capacity. It also explains that how the strength of the rock sample becomes higher as the crack angle increases.

As a substitute for polybrominated diphenyl ethers (PBDEs), organophosphate flame retardant triphenyl phosphate (TPhP) is widely used in our daily products and diffusely exists in our living surroundings, but there is a paucity of information concerning its neurodevelopmental toxicity. Herein, we investigated the effects of TPhP exposure on developmental parameters, locomotor behavior, oxidative stress, apoptosis and transcriptional levels in zebrafish at different developmental stages, so as to explore the effects of TPhP exposure on zebrafish neural development and the underlying molecular mechanisms. TPhP concentration gradient exposure reduced the survival rate, hatchability, heart rate, body length and eye distance of zebrafish embryos/larvae, and caused malformations of zebrafish larvae. TPhP also leads to abnormal locomotor behaviors, such as reduced swimming distance and swimming speed, and impaired panic avoidance reflex to high light stimulation. TPhP caused ROS accumulation in 96 hpf larvae and induced Nrf2-antioxidant response in zebrafish. In addition, TPhP further activated mitochondrial signaling pathways, which affected apoptosis in the zebrafish eye region, resulting in visual impairment. Neurodevelopmental (mbpa, syn2a, foxo3a and pax6a), Retinoid acid metabolism (cyp26a1, raraa, rbp5, rdh1, crabp1a and rbp2a) and apoptosis-related genes (bcl2a, baxa and casp9) revealed the molecular mechanism of abnormal behavior and phenotypic symptoms, and also indicated that 96 hpf larvae are more sensitive than 7 dpf larvae. Thus, in the present study, we revealed the neurotoxic effects of TPhP at different early life stages in zebrafish, and zebrafish locomotor behavior impairments induced by TPhP exposure are attributed to co-regulation of visuomotor dysfunction and neuro-related genes. These results suggest that the safety of TPhP in organisms and even in humans needs to be further studied.

Background: Polybrominated diphenyl ethers (PBDEs), a group of brominated flame retardants (BFRs), were reported exist extensively in various ecological environmental. Studies have indicated that PBDEs induce reproductive toxic effects on human health, but the mechanisms remain poorly understood. In this study, the adult female zebrafish were used to investigate the effects of 2, 2′, 4, 4′-tetrabromodiphenyl ether (BDE-47) on the reproductive endocrine system and its mechanism. Methods: Female zebrafish (AB strains) were continuously exposed to BDE-47 at the concentrations of 0, 10, 50, 100 and 500 µg/L till 21 days. The morphology of ovary were stained and evaluated with hematoxylin-eosin (H&E), and levels of sex hormones including follicle-stimulating hormone (FSH), luteinizing hormone (LH), testosterone (T) and 17β-estradiol (E2) and the biomarkers of oxidative stress such as superoxide dismutase (SOD) and malondialdehyde (MDA), were measured via ELISA. Subsequently, the expression of genes along the hypothalamic pituitary-gonad (HPG) and oxidative stress were determined using quantitative real-time PCR (qRT-PCR). Result: The results showed that exposure to high level of BDE-47 reduced the index of condition factor (CF) and gonadosomatic index (GSI). Treatment with BDE-47 impaired the normal development and structure of oocytes in zebrafish ovary. Moreover, the steroid hormone of FSH, LH, T and E2 were significantly decreased in BDE-47 exposure group. A dose-dependent elevation in SOD activity and MDA levels were recorded. Meanwhile, the transcription level of cyp19a, cyp19b, fshβ, lhβ were up-regulated while the transcription of fshr, lhr, cyp17a, 17βhsd were down-regulated in the gonad of female adult zebrafish. Conclusion: Exposure to BDE-47 have detrimental impact on the development of ovary, decreasing sex hormone levels, inducing oxidative damage as well as altering HPG axis-related genes.

Polybrominated biphenyl ethers (PBDEs) are new persistent pollutants that are widely exist in the environment and have many toxic effects. However, their toxicity mechanisms on neurodevelopment are still unclear. In this study, zebrafish embryos were exposed to 2, 2′, 4, 4′-tetrabromodiphenyl ether (BDE-47) (control, 10, 50 and 100 μg/L) at 2 h postfertilization (hpf) – 7 dpf. Locomotion analysis indicated that BDE-47 increased spontaneous coiling activity in zebrafish embryos under high-intensity light stimuli and decreased locomotor in zebrafish larvae. RNA-Seq analysis revealed that most of the up-regulated pathways were related to the metabolism of cells and tissues, while the down-regulated pathways were related to neurodevelopment. Consistent with the locomotion and KEGG results, BDE-47 affected the expression of genes for central nervous system (gfap, mbpa, bdnf & pomcb), early neurogenesis (neurog1 & elavl3), and axonal development (tuba1a, tuba1b, tuba1c, syn2a, gap43 & shha). Furthermore, BDE-47 interfered with gene expression of the Wnt signaling pathway, especially during embryonic stages, suggesting that the mechanisms of BDE-47 toxicity to zebrafish at various stages of neurodevelopment may be different. In summary, early neurodevelopment effects and metabolic disturbances may have contributed to the abnormal neurobehavioral changes induced by BDE-47 in zebrafish embryos/larvae, suggesting the neurodevelopmental toxicity of BDE-47.

The pore-scale mechanism of the waterflooding contributes to enhancing oil recovery, which has been widely emphasized in the petroleum industry. In this paper, the performances and accuracy of three tracking interface algorithms, including VOF, LS, and VOSET, are compared and analyzed through two-phase flow in the conceptual model of pore-throat. The results show that the VOSET method combines the advantages of the other two methods, which not only satisfies the mass conservation but also improves the continuity of the physical quantities near the interface. Then, based on the binary image of the pore, the two-dimensional micro pore model is reconstructed by extracting image contour. The grid independence of the reconstructed pore model is verified by the single-phase flow simulation. The waterflooding process in the reconstructed pore model is simulated using the VOSET method, and the effects of displacement speed and wettability on the oil recovery are analyzed. The morphologies of residual oil under different conditions of wettability are investigated and analyzed. The study provides a basic theory for modeling the pore-scale oil-water flow and optimizing the scheme of the water injection.

Detecting litchis in a complex natural environment is important for yield estimation and provides reliable support to litchi-picking robots. This paper proposes an improved litchi detection model named YOLOv5-litchi for litchi detection in complex natural environments. First, we add a convolutional block attention module to each C3 module in the backbone of the network to enhance the ability of the network to extract important feature information. Second, we add a small-object detection layer to enable the model to locate smaller targets and enhance the detection performance of small targets. Third, the Mosaic-9 data augmentation in the network increases the diversity of datasets. Then, we accelerate the regression convergence process of the prediction box by replacing the target detection regression loss function with CIoU. Finally, we add weighted-boxes fusion to bring the prediction boxes closer to the target and reduce the missed detection. An experiment is carried out to verify the effectiveness of the improvement. The results of the study show that the mAP and recall of the YOLOv5-litchi model were improved by 12.9% and 15%, respectively, in comparison with those of the unimproved YOLOv5 network. The inference speed of the YOLOv5-litchi model to detect each picture is 25 ms, which is much better than that of Faster-RCNN and YOLOv4. Compared with the unimproved YOLOv5 network, the mAP of the YOLOv5-litchi model increased by 17.4% in the large visual scenes. The performance of the YOLOv5-litchi model for litchi detection is the best in five models. Therefore, YOLOv5-litchi achieved a good balance between speed, model size, and accuracy, which can meet the needs of litchi detection in agriculture and provides technical support for the yield estimation and litchi-picking robots.

It is necessary to develop automatic picking technology to improve the efficiency of litchi picking, and the accurate segmentation of litchi branches is the key that allows robots to complete the picking task. To solve the problem of inaccurate segmentation of litchi branches under natural conditions, this paper proposes a segmentation method for litchi branches based on the improved DeepLabv3+, which replaced the backbone network of DeepLabv3+ and used the Dilated Residual Networks as the backbone network to enhance the model’s feature extraction capability. During the training process, a combination of Cross-Entropy loss and the dice coefficient loss was used as the loss function to cause the model to pay more attention to the litchi branch area, which could alleviate the negative impact of the imbalance between the litchi branches and the background. In addition, the Coordinate Attention module is added to the atrous spatial pyramid pooling, and the channel and location information of the multi-scale semantic features acquired by the network are simultaneously considered. The experimental results show that the model’s mean intersection over union and mean pixel accuracy are 90.28% and 94.95%, respectively, and the frames per second (FPS) is 19.83. Compared with the classical DeepLabv3+ network, the model’s mean intersection over union and mean pixel accuracy are improved by 13.57% and 15.78%, respectively. This method can accurately segment litchi branches, which provides powerful technical support to help litchi-picking robots find branches.

In this paper, a novel inline optical fiber sensor for curvature and temperature measurement simultaneously has been proposed and demonstrated, which can measure two parameters with very little crosstalk. Two combinational mechanisms of anti-resonant reflecting optical waveguide and inline Mach–Zehnder interference structure are integrated into a 3 mm-long single hole twin suspended core fiber (SHTSCF). The 85 μm hole core gives periodic several dominant resonant wavelengths in the optical transmission spectrum, acting as the anti-resonant reflecting optical waveguide (ARROW). The modes in two suspended cores and the cladding form the comb pattern. Reliable sensor sensitivity can be obtained by effective experiments and demodulation. Through intensity demodulation of the selected dip of Gaussian fitting, the curvature sensitivity can be up to −7.23 dB/m−1. Through tracking the MZI dip for wavelength demodulation, the temperature sensitivity can be up to 28.8 pm/°C. The sensor is simple in structure, compact, and has good response, which can have a bright application in a complex environment.

With the widespread application of microgrids, a number of adjacent microgrids in a certain area will form multi-microgrids (MMGs) with three-phase/single-phase (TP/SP) architecture. Owing to the complicated structure and the various operation modes of MMGs, it is an urgent problem that how to achieve seamless handoff between multiple operation modes in the MMGs. Based on the analysis of the topology of MMGs with TP/SP architecture and the hierarchical control architecture, this study proposes the islanding partition method algorithm correspondingly. The discrete particle swarm optimisation algorithm is proposed to solve the problem by establishing the comprehensive evaluation of islanding MMGs with TP/SP architecture, which can effectively solve the problem of dimension explosion when the number of microgrids increases. The results of simulation show the applicability of the proposed strategy for MMGs.

Recurrent neural network (RNN) has been widely applied to many sequential tagging tasks such as natural language process (NLP) and time series analysis, and it has been proved that RNN works well in those areas. In this paper, we propose using RNN with long short-term memory (LSTM) units for server load and performance prediction. Classical methods for performance prediction focus on building relation between performance and time domain, which makes a lot of unrealistic hypotheses. Our model is built based on events (user requests), which is the root cause of server performance. We predict the performance of the servers using RNN-LSTM by analyzing the log of servers in data center which contains user’s access sequence. Previous work for workload prediction could not generate detailed simulated workload, which is useful in testing the working condition of servers. Our method provides a new way to reproduce user request sequence to solve this problem by using RNN-LSTM. Experiment result shows that our models get a good performance in generating load and predicting performance on the data set which has been logged in online service. We did experiments with nginx web server and mysql database server, and our methods can been easily applied to other servers in data center.

A scientific and effective coordinated control strategy is crucial to the safe and economic operation of a microgrid (MG). With the continuous improvement of the renewable energy source (RES) penetration rate in MG, the randomness and intermittency of its output lead to the increasing regulation pressure of the conventional controllable units, the increase of the operating risk of MG and the difficulty in improving the operational economy. To solve the mentioned problems and take advantage of hybrid energy storage system (HESS), this study proposes a multi-time scale coordinated control scheme of “day-ahead optimization (DAO) + intraday rolling (IDR) + quasi-real-time correction (QRTC) + real-time coordinated control (RTCC).” Considering the shortcomings of existing low prediction accuracy of distributed RES and loads, the soft constraints such as unit commitment scheduling errors and load switching scheduling errors are introduced in the intraday rolling model, allowing the correction of day-ahead unit commitment and load switching schedule. In the quasi-real-time coordinated control, an integrated criterion is introduced to decide the adjustment priority of the distributed generations. In the real-time coordinated control, the HESS adopts an improved first order low pass filtering algorithm to adaptively compensate the second-level unbalanced power. Compared with the traditional coordinated control strategy, the proposed improved model has the advantages of good robustness and fast solving speed and provides some guidance for the intelligent solution for stable and economic operation of stand-alone MG with HESS.

With the rapid development of microgrids (MGs) in recent years, it is anticipated that combinations of multiple microgrids—multi-microgrids (MMGs)—will gradually become a new form of power grid. A safe and efficient black start strategy for MMGs is in urgent demand because of their complicated structure and control systems. In this paper, first, we analyze the topology and control system of residential-type MMGs with three-phase/single-phase (TP/SP) architecture. Second, a black start strategy based on a hierarchical control scheme is presented, including the selection strategy for the main power supply and master microgrid, the stand-alone operation strategy, and the grid-connected operation strategy. After the selection of the main power supplies, the master MG is determined. Hereby, all sub-microgrids (SMGs) execute the stand-alone algorithm. When the synchronous connection condition is satisfied, the slave SMGs connect to the master MG who provides the voltage and frequency support. Meanwhile, the control algorithm transfers to the grid-connected algorithm, with the grid dispatching value set to zero. Finally, experimental results from the MMG experimental setup in the Clean Energy Technology Laboratory (CETLAB) are presented to verify the effectiveness and feasibility of the proposed black start strategy.