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This retrospective study investigated the efficacy and economic outcomes of low molecular weight heparin (LMWH), fondaparinux sodium (FPX), and rivaroxaban after total hip arthroplasty (THA) under Enhanced Recovery After Surgery (ERAS). The clinical data of patients who underwent primary THA due to hip joint disease in our Hospital from October 2020 to June 2022 were retrospectively collected and analyzed. According to different anticoagulant methods, patients were divided into LMWH group (42 cases), FPX group (24 cases), and Rivaroxaban group (39 cases). Perioperative blood coagulation-related factors, D-dimer, platelet (PLT) changes, blood routine, blood loss, lower limb vein thrombosis (DVT), pulmonary embolism, and allogeneic blood transfusion were compared among the three groups. There was no statistical significance difference for coagulation indexes and Visual Analog Scale score before the operation among the three groups, but there were statistical significance differences for prothrombin time and international normalized ratio levels at 3 days after the operation. The postoperative drainage volume and blood loss of the three groups were different, but there were no significant differences in intraoperative blood loss, hidden blood loss, total blood loss, blood transfusion rate, DVT incidence rate and Visual Analog Scale score score 3 days after surgery among the three groups. Besides, the treatment cost in the LMWH group was significantly lower than that of the FPX group and the rivaroxaban group. Hence, Based on the ERAS concept, the use of LMWH, FPX, and Rivaroxaban after THA can effectively and safely prevent the occurrence of VTE and has no significant difference in postoperative pain, perioperative blood loss, and coagulation function. However, Rivaroxaban can be taken orally and has more advantages in some pharmacological effects, while LMWH is cheaper.

In this study, we investigated the effects of dietary lipids (DL) on the growth and lipid deposition of steelhead trout (Oncorhynchus mykiss) confined underwater using various equipment. Three diets formulated with 6%, 13%, and 20% DL (F6, F13, and F20) were fed to the fish. Fish (initial weight: 75.01 ± 1.36 g) in each dietary group were randomly cultured in three equipment groups: the control group; the submergence group, in which mesh and airstones were used to keep the experimental fish from the water surface; and the replenisher group, in which an air replenisher and airstones were utilized under the mesh. The results of this 70-day study showed that the growth and crude lipid content of the steelhead trout fish body increased significantly with increasing DL levels. No significant differences were observed in the liver among the different equipment groups, whereas the lipid contents in the muscle and the viscerosomatic index significantly decreased in the submerged group fed F20. The fitted curve analysis showed that the energy expenditure of continuous swimming and the success of replenishing the swim bladder may determine the strategy adopted by trout to cope with negative buoyancy. If the swim bladder was easily replenished, steelhead trout tended to convert excess energy into lipid stored in muscles, thereby reducing body density and maintaining neutral buoyancy. Otherwise, trout must burn lipid in their muscles to ensure energy supply to keep swimming for lift. We concluded that a high-lipid diet compensated for the loss of the energy used in resistance to negative buoyancy, and growth performance of steelhead trout improved.

The objective of this study was to investigate the effects of different rhythmic light spectra and intensities on growth performance and physiological and biochemical parameters of juvenile steelhead trout (Oncorhynchus mykiss). Seven treatments were randomly assigned to 21 tanks using a single-flow system for 13 weeks (N = 3), namely blue–purple–red light (BPR), red–purple–blue light (RPB), blue light (VB), and red light (VR). These light treatments alternated at 300, 900, and 1,200 lx, as well as a constant 900 lx of blue light (CB), red light (CR), and white light (CW). Results showed that the highest feed intake (FI), final body weight (FBW), and specific growth rate (SGR) were observed in the BPR treatment, which were significantly higher than those in the CW, CR, CB, and VB treatments. BPR treatment resulted in higher levels of insulin-like growth factor 1 (IGF-1), free triiodothyronine (FT3) and thyroxine (FT4), superoxide dismutase (SOD), and catalase (CAT), and total antioxidant capacity (T-AOC) activities were found. Fish exposed to BPR showed significantly enhanced lipase (LPS) and trypsin (Trp) activity in the stomach and gut tissues which promoted digestion. Trout exposed to a constant light spectra and intensity environment showed decreased activities of antioxidant and gastrointestinal digestive enzymes. Our results indicate the positive influence of BPR light conditions on the growth, stress response, digestion, and metabolism of juvenile steelhead trout, which is likely related to its similarity to the light rhythm in natural water environments, and can be used to improve growth and physiological status in the aquaculture trout.

Abstract Background Rainbow trout is an economically important fish in aquaculture and is a model species in environmental physiology. Despite earlier research on the seawater adaptability of rainbow trout at different temperature regimes, the influence on the liver and intestine in this species is still unknown. Two trials were conducted to investigate the effects of constant and diel cyclic temperatures on phospholipid fatty acid (PLFA) composition in the liver and intestine of rainbow trout during seawater acclimation. Results At the end of growth trial 1, fish at 9 and 12.5 °C showed significantly higher ratios of unsaturated to saturated (U/S) and unsaturation index (UI) than those at 16 °C in liver and intestine phospholipids. After day 1 of seawater acclimation, the U/S, UI, and average chain length (ACL) of liver and intestinal phospholipids in fish at 16 °C significantly increased. Two weeks after seawater acclimation, the liver and intestinal PLFA composition adapted to salinity changes. In trial 2, significantly higher U/S, UI, and ACL were found in intestinal phospholipids at 13 ± 2 °C. On the first day after seawater acclimation, UI and ACL in liver phospholipids significantly increased at 13 °C, while fish at 13 ± 2 °C showed significantly decreased U/S, UI, and ACL in the intestine. At the end of growth trial 2, liver PLFA compositions were stable, whereas intestinal PLFA at 13 and 13 ± 1 °C showed significantly decreased U/S, UI, and ACL. A two-way analysis of variance and principal component analysis revealed significant effects of different constant temperatures, seawater acclimation, and their interaction on the liver and intestinal phospholipids, a significant effect of diel cyclic temperature on intestinal phospholipids, and the effects of seawater acclimation and its interaction with diel cyclic temperature on liver phospholipids. Conclusion Temperatures of 9 and 12.5 °C could elevate membrane fluidity and thickness in the liver and intestine of rainbow trout in freshwater, whereas no significant effects were found with diel temperature variations. After seawater acclimation, constant and diel cyclic temperatures significantly influenced the membrane fluidity and thickness of the liver and intestine. Compared with constant temperature, diel temperature variation (13 ± 2 °C) can enhance the adaptability of rainbow trout during seawater acclimation.

To examine the growth and immune response of steelhead trout (Oncorhynchus mykiss) under conditions of differing light color, we investigated the effects of different red and blue light color combinations on plasma non-specific immunity, hepatic antioxidant capacity, and GH/IGF-1 axis gene expression in juvenile steelhead trout (initial weight: 34.67 ± 2.69 g). The 16-week trial was set up with six treatments in which light color varied at a constant light intensity of 150 lx: 12 h white light + 12 h dark (12 W), 12 h blue light + 12 h dark (12B), 12 h red light + 12 h dark (12 R), 1.5 h blue light + 9 h red light + 1.5 h blue light + 12 h dark (3B9R), 3 h blue light + 6 h red light + 3 h blue light + 12 h dark (6B6R), total 12 h of blue and red light + 12 h dark (T12BR). The results revealed that the 12B and 3B9R light environments significantly enhanced plasma immunoglobulin M levels in steelhead trout, and that the 3B9R light environment also promoted significant increases in the gene expression of hepatic growth hormone receptor, insulin-like growth factor 1, and insulin-like growth factor-binding protein. The 3B9R light environment was also found enhance the antioxidant capacity of trout by increasing hepatic superoxide dismutase, catalase, and glutathione peroxidase activities. In contrast, trout exposed to the 6B6R light environment showed significant reductions in growth and immune performance, and there were similar reductions in hepatic antioxidant capacity. Furthermore, fish exposed to the 12R light environment were found to be characterized by elevated levels of lipid peroxidation and malondialdehyde, which are indicative of hepatic stress. In addition, we observed that in response to light variation, there were elevations in the activities of glutamic oxaloacetic transaminase and lactic dehydrogenase in the plasma of steelhead trout, thereby indicating an inhibition of cardiomyocyte function. In summary, our findings indicate that a 3B9R light environment simulates the blue-red-blue daily rhythm of light color variation in natural underwater environments, which is beneficial with respect to enhancing the growth and immunity of steelhead trout, and could accordingly be used to provide suitable light conditions in commercial trout production. However, sudden changes in light color should be avoided in the aquaculture of trout.

The light spectrum varies with the altitude of the sun and shows different light colors in clear water. In this study, we aimed to investigate the response of juvenile steelhead trout Oncorhynchus mykiss (34.67 ± 2.69 g initial weight) under different light color conditions. The effects of different blue and red light combinations on plasma biochemical parameters, digestive enzyme activity, and RNA/DNA ratio were assessed in trout over 16 weeks. Six treatments were randomly assigned to 24 tanks with four replicates per treatment: a constant light intensity of 150 lx: 12 h white light then 12 h dark (12W); 12 h blue light then 12 h dark (12B); 12 h red light then 12 h dark (12R); 1.5 h blue light, 9 h red light, 1.5 h blue light, then 12 h dark (3B9R); 3 h blue light, 6 h red light, 3 h blue light, then 12 h dark (6B6R); and 12 h of both blue and red light then 12 h dark (T12BR). Fish exposed to the 3B9R light environment showed significantly increased plasma levels of total protein (TP), enhanced activities of midgut lipase, trypsin, and gastric lipase; and increased RNA content in the liver and muscle tissue to promote protein synthesis efficiency, thereby improving digestive and anabolic performance compared to fish in the other treatments. This indicates that steelhead trout have adapted well to such variable light conditions during long-term evolution. In contrast, trout exposed to the 6B6R light environment showed significant reductions in plasma glucose, TP, and triglyceride levels, decreased activity of gastrointestinal digestive enzymes, and reduced protein synthesis capacity in the muscle and liver, resulting in weakened digestive and anabolic performance. Furthermore, despite the high RNA content and RNA/DNA ratio in fish exposed to a 12R light environment, relatively high plasma cholesterol and triglycerides levels were observed, which might indicate oxidative stress. Therefore, this light is not considered suitable for long-term cultivation. In conclusion, the 3B9R treatment was the optimal light condition tested and can be used to improve the digestive and anabolic performance of steelhead trout.

Once an active distribution network of a cyber-physical system is in alert state, it is vulnerable to cross-domain cascading failures. It is necessary to transit the state of an active distribution network of cyber-physical system from an alert state to a normal state using a preventive control policy against cross-domain cascading failures. In fact, it is difficult to construct and analyze a preventive control policy via theoretical analysis methods or physical experimental methods. The theoretical analysis methods may not be accurate due to approximated models, and the physical experimental methods are expensive and time consuming for building prototypes. This paper presents a preventive control policy construction method based on a deep deterministic policy gradient idea (shorted as PCMD) to generate and optimize a preventive control policy with Artificial Intelligence (AI) technologies. It adopts the reinforcement learning technique to make full use of the available historical data to overcome the problems of high cost and low accuracy. Firstly, a preventive control model is designed based on the finite automaton theory, which can guide the data collection and learning policy selection. The control model considers the voltage stability, frequency stability, current overload prevention, and the control cost reduction as a feedback variable, without the specific power flow equations and differential equations. Then, after enough training, a local optimal preventive control policy can be constructed under the comparability condition among a fitted action-value function and a fitted policy function. The constructed preventive control policy contains some control actions to achieve a low cost and in accord with the principle of shortening a cross-domain cascading failures propagation sequence as far as possible. The PCMD is more flexible and closer to reality than the theoretical analysis methods and has a lower cost than the physical experimental methods. To evaluate the performance of the proposed method, an experimental case study, China Electric Power Research-Cyber-Physical System (shorted as CEPR-CPS), which comes from China Electric Power Research Institute, is carried out. The result shows that the effectiveness of preventive control policy construction with the PCMD is better than most current methods, such as the multi-agent method in terms of reducing the number of failure nodes and avoiding the state space explosion.

The AI-in-the-loop system (AIS) has been widely used in various autonomous decision and control systems, such as computing vision, autonomous vehicle, and collision avoidance systems. AIS generates and updates control strategies through learning algorithms, which make the control behaviors non-deterministic and bring about the test oracle problem in AIS testing procedure. The traditional system mainly concerns about properties of safety, reliability, and real-time, while AIS concerns more about the correctness, robustness, and stiffness of system. To perform an AIS testing with the existing testing techniques according to the testing requirements, this paper presents an extendable framework of AI-in-the-loop system testing by exploring the key steps involved in the testing procedure, named ExtendAIST, which contributes to define the execution steps of ExtendAIST and design space of testing techniques. Furthermore, the ExtendAIST framework provides three concerns for AIS testing, which include: (a) the extension points; (b) sub-extension points; and (c) existing techniques commonly present in each point. Therefore, testers can obtain the testing strategy using existing techniques directly for corresponding testing requirements or extend more techniques based on these extension points.

The effectiveness analysis of risk evaluation formulas has become a significant research area in spectrum-based fault localization (SBFL). The risk evaluation formula is designed and widely used to evaluate the likelihood of a program spectrum to be faulty. There are numerous empirical and theoretical studies to investigate and compare the performance between sixty risk evaluation formulas. According to previous research, these sixty risk evaluation formulas together form a partially ordered set. Among them, nine formulas are maximal. These nine formulas can further be grouped into five maximal risk evaluation formula groups so that formulas in the same group have the same performance. Moreover, previous research showed that we cannot theoretically compare formulas across these five maximal formula groups. However, experimental data “suggests” that a maximal formula in one group could outperform another one (from a different group) more frequently, though not always. This inspired us to further investigate the performance between any two maximal formulas in different maximal formula groups. Our approach involves two major steps. First, we propose a new condition to compare between two different maximal formulas. Based on this new condition, we present five different scenarios under which a formula performs better than another. This is different from the condition suggested by the previous theoretical study. We performed an empirical study to compare different maximal formulas using our condition. Our results showed that among two maximal risk evaluation formulas, it is feasible to identify one that can outperform the others more frequently.

Active distribution networks (ADNs) are a typical cyber−physical system (CPS), which consist of two kinds of interdependent sub-networks: power networks (PNs) and communication networks (CNs). The combination of typical characteristics of the ADN includes (1) a large number of distributed generators contained in the PN, (2) load redistribution in both the PN and CN, and (3) strong interdependence between the PN and CN, which makes ADNs vulnerable to cross-domain cascading failures (CCFs). In this paper, we focus on the robustness analysis of the ADN against the CCF. Rather than via the rate of the clusters with size greater than a predefined threshold, we evaluate the robustness of the ADN using the rate of the clusters containing generators after the CCF. Firstly, a synchronous probabilistic model is derived to calculate the proportions of remaining normal operational nodes after the CCF. With this model, the propagation of the CCF in the ADN can be described as recursive equations. Secondly, we analyze the relationship between the proportions of remaining normal operational nodes after the CCF and the distribution of distributed generators, unintentional random initial failure rate, the interdependence between the sub-networks, network topology, and tolerance parameters. Some results are revealed which include (1) the more distributed generators the PN contains, the higher ADN robustness is, (2) the robustness of the ADN is negatively correlated with the unintentional random initial failure rate, (3) the robustness of the ADN can be improved by increasing the average control fan in of each node in the PN and the average power fan in of each node in the CN, (4) the robustness of the ADN with Erdos−Renyi (ER) network topological structure is greater than that with Barabasi−Albert (BA) network topological structure under the same average node degree, and (5) the robustness of the ADN is greater, when the tolerance parameters increase. Lastly, some simulation experiments are conducted and experimental results also demonstrate that the conclusions above are effective to improve the robustness of the ADN against the CCF.

We report on novel chromosomal characteristics of Haliotis discus hannai from a breeding population at Fujian, China. The karyotypes of H. discus hannai we obtained from an abalone farm include a common type 2n = 36 = 10M + 8SM (82%) and two rare types 2n = 36 = 11M + 7SM (14%) and 2n = 36 = 10M + 7SM + 1ST (4%). The results of silver staining showed that the NORs of H. discus hannai were usually located terminally on the long arms of chromosome pairs 14 and 17, NORs were also sometimes located terminally on the short arms of other chromosomes, either metacentric or submetacentric pairs. The number of Ag-nucleoli ranged from 2 to 8, and the mean number was 3.61 ± 0.93. Among the scored interphase cells, 41% had 3 detectable nucleoli and 37% had 4 nucleoli. The 18S rDNA FISH result is the first report of the location of 18S rDNA genes in H. discus hannai. The 18S rDNA locations were highly polymorphic in this species. Copies of the gene were observed in the terminal of long or/and short arms of submetacentric or/and metacentric chromosomes. Using FISH with probe for vertebrate-like telomeric sequences (CCCTAA)3 displayed positive green FITC signals at telomere regions of all analyzed chromosome types. We found about 7% of chromosomes had breaks in prophase. A special form of nucleolus not previously described from H. discus hannai was observed in some interphase cells. It consists of many small silver-stained nucleoli gathered together to form a larger nucleolus and may correspond to prenucleolar bodies.

Many complex embedded systems are Mixed-Criticality Systems (MCSs). MCSs are often required to operate with the specified criticality level, but they may be subject to hazards that can induce random errors and burst errors, which may result in the abortion of an executing thread or even system failures. Current research only concentrates on schedulability analysis for MCSs and fails to further analyze system safety and consider the dependency relationship among threads. Taking random errors and burst errors as the research objects, we propose an architecture-basedMCSsafety analysis method with the integration of fault propagation analysis. Meanwhile, Architecture Analysis and Design Language (AADL) is employed to characterize the dependency relations among components. To compensate for the shortcomings of AADL, we create new AADL properties (AADL burst error properties) and propose new thread state machine (burst error-based thread state machine) semantics to describe the thread execution process with burst errors. Additionally, model transformation rules and assembly methods are proposed to apply probabilistic model checking for safety analysis, and PRISM models are derived from AADL models. Two formulae are also formulated to obtain quantitative safety properties for verifying occurrence probabilities of failures, and qualitative safety properties for generating corresponding witnesses to figure out propagation paths for fault propagation analysis respectively. Finally, the effectiveness of the proposed method is verified by adopting a Power Boat Autopilot (PBA) system. [ABSTRACT FROM AUTHOR]