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Abstract Background To analyze the effects of different anesthesia depths on perioperative heart rate variability and hemodynamics in middle-aged and elderly patients undergoing general anesthesia, and to provide a basis for clinical application. Methods A total of 111 patients with gastric cancer who were treated with epidural anesthesia combined with general anesthesia were selected as the study subjects, and the patients were randomly divided into group A, group B and group C. The bispectral index (BIS) was maintained by adjusting the infusion speed of anesthetics, the BIS of group A was maintained at 50 ~ 59, the BIS of group B was maintained at 40 ~ 49, and the BIS of group C was maintained at 30 ~ 39. The high-frequency power (HFP), low-frequency power (LFP), total power (TP), mean arterial pressure (MAP), heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP) were measured before anesthesia induction (T1), immediately after intubation (T2), 3 min after intubation (T3), and 6 min after extubation (T4). The cognitive function of the patients was evaluated before and 48 h after surgery. Results The HFP, LFP/HFP, TP, HR, DBP and SBP between the three groups at T1 ~ T3 are significantly difference from each other (P

Abstract Background Pneumothorax is the most frequent complication after CT-guided percutaneous transthoracic lung biopsy (CT-PTLB). Many studies reported that injection of autologous blood patch (ABP) during biopsy needle withdrawal could reduce the pneumothorax and chest tube insertion rate after CT-PTLB, but the result is debatable. The aim of this systematic review and meta-analysis is to synthesize evidence regarding the efficacy of ABP procedure in patients receiving CT-PTLB. Methods Eligible studies were searched in Pubmed, Embase and Web of Science databases. The inclusion criteria were studies that assessed the relationship between ABP and the pneumothorax and/or chest tube insertion rate after CT-PTLB. Subgroup analyses according to study type, emphysema status and ABP technique applied were also conducted. Odds ratio (OR) with 95% confidence interval (CI) were calculated to examine the risk association. Results A total of 10 studies including 3874 patients were qualified for analysis. Our analysis suggested that ABP reduced the pneumothorax (incidence: 20.0% vs. 27.9%, OR = 0.67, 95% CI = 0.48–0.66, P

Abstract Background Postpartum depression (PPD) following a cesarean delivery is a frequently seen complication. Despite the prophylactic effects of ketamine, the impact of esketamine on PPD in women undergoing cesarean section remains uncertain. This study aimed to assess the effectiveness of esketamine as an adjunct to patient-controlled intravenous analgesia (PCIA) in preventing PPD in women undergoing caesarean section. Methods A total of 275 parturients undergoing caesarean section and subsequent patient-controlled intravenous analgesia (PCIA) were randomly assigned to receive either the control treatment (sufentanil 2 µg/kg + tropisetron 10 mg) or the experimental treatment with additional esketamine (1.5 mg/kg). The primary outcome measured was the incidence of postpartum depression (PPD), classified by Edinburgh Postnatal Depression Scale (EPDS) scores equal to or greater than 13 indicating PPD. Secondary outcomes included cumulative sufentanil consumption during specific time periods (0–24 h, 24–48 h, and 0–48 h) after the surgical procedure and numerical rating scale (NRS) scores at rest and during movements. Results The final analysis included a total of 246 postpartum women who had undergone caesarean delivery. On postoperative day 42, the incidence of depression among the control group was 17.6%, which was significantly higher compared to the esketamine group with a rate of 8.2% (P = 0.02). The EPDS scores also showed a significant difference between the two groups, with a mean score of 9.02 ± 2.21 in the control group and 6.87 ± 2.14 in the esketamine group (p

Developing environmental-friendly materials with high-density energy storage is of paramount importance to meet the burgeoning demands for energy storage. In this study, we harness the modulation of a multicomponent solid solution by introducing KNN as a third element into the BNT–BST system, thereby achieving a marked enhancement in both energy storage performance and the temperature stability of the dielectric constant. BNBST–4KNN stands out for its exceptional dielectric stability, with a dielectric constant variation rate within 10% across a broad temperature range of [Formula: see text]C to [Formula: see text]C, a feat attributed to the flattening and broadening of the [Formula: see text] peak. BNBT–2KNN exhibits superior energy storage capabilities, with an energy storage density of 1.324 J/cm3 and an energy storage efficiency of 72.3%, a result of the P–E loop becoming more slender. These advancements are pivotal for the sustainable progression of energy storage technologies.

In this study, BNBT-KNN-xTa2O5 was designed and synthesized, successfully achieving a reduction in the relaxor-ferroelectric phase transition temperature. Synergy between temperature-dependent ferroelectric testing and dielectric spectroscopy confirmed that the depoling temperature gradually decreased with increasing doping concentration. Fitting of the relaxation parameter and freezing temperature substantiated that the incorporation of Ta2O5 increased the degree of relaxation in BNBT-KNN-xTa2O5, thereby effectively lowering the relaxor-ferroelectric phase transition temperature.

Liver fibrosis occurs in response to chronic damage and inflammation to the liver. Leaving untreated, it can lead to decreased liver function and can eventually progress to cirrhosis, a more advanced and irreversible state of liver damage. Clinical investigations showed that chronic liver disease associated with neurological symptoms including anxiety, depression, and cognitive decline. However, few therapeutic options are available for treating liver and related brain pathologies simultaneously. In this study, we aim to find therapeutic candidates that target the liver-brain axis. Gossypetin, a flavonoid from sedum, shows promising capability in treating liver and brain pathologies in CCl4-induced mouse model. Short term of gossypetin administration is sufficient to ameliorate impaired liver function and pre-existing liver fibrosis, suppress MKK3/6-p38 MAPK and p53 activation, and abolish the activation of hepatic stellate cells and Kupffer cells. Although we observe no neuronal loss in the brain of mice with liver fibrosis, we do observe astrogliosis and microglial activation in certain brain regions, especially the hippocampus. Brief gossypetin administration also shows potential in alleviating neuroinflammation in these regions. These results suggest that gossypetin can target the liver-brain axis and be a promising candidate for treating chronic liver fibrosis patients with neurological symptoms.

Abstract Purpose The present study aimed to explore the anticancer activity of hirsuteine (HST), an indole alkaloid from the traditional Chinese herbal medicine Uncaria rhynchophylla, against colorectal cancer (CRC) and the underlining mechanism. Methods MTT, colony formation, flow cytometry and MDC staining were conducted to confirm the antiproliferative effect of HST on human CRC cells harboring different p53 status. Protein expressions were evaluated by the Western blot analysis. p53 protein half-life and the interaction between p53 and MDM2 were investigated using cycloheximide (CHX)-chase assay and Co-immunoprecipitation (Co-IP), respectively. Transcriptional activity of p53 was examined by qRT-PCR and Chromatin immunoprecipitation (ChIP). Xenograft tumor in nude mice was created to evaluate in vivo anticancer effect of HST against CRC. Results HST inhibited cell growth, arrested cell cycle and induced autophagy, showing efficient anticancer effects on CRC cells independent of p53 status. In HCT-8 cells, HST prolonged wtp53 half-life, and upregulated mRNA level of p21, suggesting that HST activated the p53 pathway through enhancement of wtp53 stability and transcriptional activity. Meanwhile in SW620 cells, HST induced MDM2-mediated proteasomal degradation of mutp53R273H, increased the DNA-binding ability of mutp53R273H at the p21 promoter, and upregulated mRNA levels of p21 and MDM2, demonstrating the depletion of mutp53R273H and restoration of its wild-type-like properties by HST. p53 knockdown by siRNA significantly impaired the growth inhibition of HST on HCT-8 and SW620 cells. Moreover, HST showed anticancer effects in xenograft tumors, accompanied with an opposite regulation of wtp53 and mutp53 R273H in mechanism. Conclusion This study revealed the anticancer efficacy of HST against CRC via opposite modulation of wtp53 and mutp53 R273H, indicating the potential of HST to be a CRC drug candidate targeting p53 signaling.

When a high impedance grounding fault occurs in the power cables, the current at the fault point is extremely low and the fault characteristics are too weak to be detected by the reflectometry. Interfered by the multiple reflections, the fault is hard to be located in the field. In order to solve the problem of conventional frequency domain reflectometry, a high impedance grounding fault location method for 10 kV distribution cables is proposed in this paper, which is based on the reflection coefficient spectrum. Firstly, the equivalent model of cable distributed parameters is established, and the reflection coefficient spectrum at the cable head is derived. Then, according to the theorem of integral transformation and generalized orthogonality, the diagnostic function is built in the spatial domain. Besides, the Kaiser window is introduced to improve the location sensitivity. Finally, the feasibility of the method is verified by simulated and experimental results. It is shown that this method can effectively eliminate the impact of multiple reflections, and precisely locate the single- and multi-point grounding faults. The fault location error is within 0.2%.

Abstract Electron‐correlated materials have been drawing ever‐increasing attention due to their fascinating physical behaviors and extensive application scenarios. In this review, a new method for material research and design (R&D), named structural‐functional unit ordering (SFU ordering), which is presented, overcomes the shortcomings—for example, the limitation of finite chemical elements and long R&D circle‐of conventional strategy and thus provides guidance for the design of these high‐performance functional materials on demand. Meanwhile, with the development of material characterization technologies, SFUs of different scales and types can be directly observed, which, moreover, regulate the corresponding orderings. The review, starts with an introduction of the profile for SFU ordering and the synergistic effect between SFUs. Then, studies on several new high‐performance electronic‐correlated materials, for example, a ferromagnetic semiconductor with local spin, ferromagnetic metals with spin topologies, ferroelectric thin films with polar topologies, piezoelectric thin films with nanopillars enclosed by charged boundaries, thermoelectric materials with local ferromagnetic nanoparticles and topotactic phase transformation with conducting nanofilaments are stated in detail one by one. The vital aspect is the breaking of local symmetry, the construction, the structure, of SFUs and their orderings existing or theoretically existing, together with the enhanced/new performance. All in all, the main comments of the review tend to the remaining challenges, promising design approaches for the SFUs, and their orderings for high‐performance functional materials.

Abstract Recently, automated vehicles have been recognized as a promising tool to address the problem of on‐ramp merging. However, the complexity of the problem includes ignorance of the vehicle's lateral dynamics, the limitation of the fixed merging point, the mismatch problem caused by the sequential optimization scheme, and the fixed terminal states assumption. These factors make it intractable in practical driving scenarios. This paper proposed an integrated optimization model for on‐ramp automated vehicles, which can guide the vehicle to complete the merging behaviour from the ramp lane to the main lane safely and efficiently. A merging path is first constructed in the two‐dimensional plane with two critical parameters recommended by a neural network predictor, enabling it to incorporate both longitudinal and lateral dynamics. Then, an integrated Mixed Integer Quadratic Program (MIQP) model is built to determine the optimal velocity profiles and merging gap simultaneously while considering the safety and efficiency factors. Specifically, with the introduction of discretization and linearization techniques, linear collision avoidance constraints and smooth transition constraints can be built, which can address the challenging computational problem. The effectiveness of the proposed model is validated through the microscopic and macroscopic numerical results under different levels of mixed traffic.

Aiming at the voltage sag compensation of the long-distance sparse distribution network, this paper proposed a multi-objective optimization method based on improved S-CDAS dominance and NSGA-III genetic algorithm. Firstly, aiming at the difficulty of solving the power flow for distribution network with unified power quality conditioners (UPQC), an alternating iteration algorithm of power flow calculation was presented. Secondly, this paper proposed an adaptive controlling of dominance based on extreme solutions. The algorithm dynamically fitted the Pareto frontier according to the extreme solutions in the iterative process to strengthen the dominance region of the optimal set. The algorithm results showed that the improved S-CDAS dominance could improve the convergence speed and result of NSGA-III algorithm while preserving its diversity. Finally, through PSCAD simulation, the effectiveness of the proposed algorithms was proved, and the effect of UPQC on voltage sag in long-distance sparse distribution network was verified. In conclusion, the UPQC configuration method proposed in this paper can consider the diversity of convergence direction and speed, which plays an effective role in the voltage sag compensation of long-distance sparse distribution network.

Abstract Lane‐changing is a basic driving behaviour, which largely impacts on traffic safety and efficiency. With the development of technology, the automated lane‐changing system has attracted extensive attention. Among it, the trajectory planning part is a challenging problem owing to the complexity and diversity of the driving situations. The planner requires the real‐time capability to produce safe and comfortable trajectories for coping with the dynamically changing environment. Based on this, the paper proposes a lane‐changing trajectory planning model in dynamic driving environments. The model constructs a neural network to predict the end position of the ego vehicle, and then adopts the mathematical programming method to solve the optimal lane‐changing trajectory that guarantees the ride safety and comfort. With the assistance of the neural network, the lane‐changing trajectory planning problem is converted into a quadratic programming (QP) model, thereby achieving rapid solution of the model. Moreover, to train the proposed algorithm, a novel approach for generating the scenario data is designed, which can generate rich and diverse traffic scenarios at a low cost. The simulation results show that the proposed model can plan a lane‐changing trajectory quickly and effectively, and the ego vehicle can follow the planned trajectory safely and comfortably.

The unified power quality conditioner (UPQC) has prospects in power quality management considering green energy integration. This paper proposes an optimization method for the location and capacity planning of UPQCs in the distribution grid with distributed generators. The planning and dispatching of UPQCs are combined into a coupled optimization model in this paper. The dual-controlled-source model is proposed and well used to describe the operation state of UPQC. Fluctuations in the output of wind generators and photovoltaic power plants are also taken into account. The improved golden eagle optimization (IMOGEO) algorithm, based on the two-archive strategy, can better balance the convergence and diversity of the non-dominated solution set. A case study is carried out based on the modified IEEE 33-node distribution grid model including DGs and loads with a diurnal variation. The optimized schemes of location and capacity are obtained, and the corresponding dispatching strategies display the superiority in both voltage variation and line loss. The results verify the effectiveness and advantages of the proposed method.

UBA6 is an E1 enzyme that can activate both ubiquitin and FAT10. Here, the authors employ X-ray crystallography and biochemical techniques to explain this dual specificity, and identify UBA6 variants that are selectively impaired in the activation of either ubiquitin or FAT10.

Since the Electromagnetic Transient (EMT) process of the high-voltage submarine cable has a great influence on the safe and stable operation of the transmission system, it is necessary to analyze its EMT process under actual engineering. In this study, PSCAD (EMTDC) is used to simulate the internal overvoltages (power-frequency overvoltages and switching overvoltages) of the submarine cable transmission system. Under the working conditions considered in this study, the maximum power-frequency overvoltage in the system occurs in the case of single-phase fault earthing, which is 1.147 p.u. The maximum switching overvoltage is 1.321 p.u., and the 2% overvoltage is 1.276 p.u. The above results are all able to meet the regulations of the internal overvoltages. By simulating the overvoltages in the system, the operation states of the system can be obtained, which is of great significance to improve the transmission reliability of the submarine cable system.

Numerous technological advancements in the 21st century depend on the creation of novel materials possessing enhanced properties; there is a growing reliance on materials that can be optimized to serve multiple functions. To efficiently save time and meet the requirements of diverse applications, high-throughput and combinatorial approaches are increasingly employed to explore and design superior materials. Among them, gradient thin-film deposition is one of the most mature and widely used technologies for high-throughput preparation of material libraries. This review summarizes recent progress in gradient thin-film deposition fabricated by magnetron sputtering, multi-arc ion plating, e-beam evaporation, additive manufacturing, and chemical bath deposition, providing readers with a fundamental understanding of this research field. First, high-throughput synthesis methods for gradient thin films are emphasized. Subsequently, we present the characteristics of combinatorial films, including microstructure, oxidation, corrosion tests, and mechanical properties. Next, the screening methods employed for evaluating these properties are discussed. Furthermore, we delve into the limitations of high-throughput preparation and characterization techniques for combinatorial films. Finally, we provide a summary and offer our perspectives.

Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications. However, the low accuracy and poor convergence of these algorithms have been challenging for system operators. The bird swarm algorithm (BSA), a new bio- heuristic cluster intelligent algorithm, can potentially address these challenges; however, its computational iterative process may fall into a local optimum and result in premature convergence when optimizing small portions of multi-extremum functions. To analyze the impact of a multi-objective economic–environmental dispatching of a microgrid and overcome the aforementioned problems of the BSA, a self-adaptive levy flight strategy-based BSA (LF–BSA) was proposed. It can solve the dispatching problems of microgrid and enhance its dispatching convergence accuracy, stability, and speed, thereby improving its optimization performance. Six typical test functions were used to compare the LF–BSA with three commonly accepted algorithms to verify its excellence. Finally, a typical summer-time daily microgrid scenario under grid-connected operational conditions was simulated. The results proved the feasibility of the proposed LF–BSA, effectiveness of the multi- objective optimization, and necessity of using renewable energy and energy storage in microgrid dispatching optimization.

In recent decades, studies on short-term traffic speed forecasting of the large-scale road are a new challenge for researchers and engineers. Especially based on deep learning neural networks, studies on short-term traffic forecasting have achieved mush-room growth. This study proposes a stacked Bidirectional Gated Recurrent Unit neural network model to predict the traffic speed of the expressway over different estimation time intervals in an effective manner. By building a multiscale-grid model, it can take less time to derive a set of key traffic parameters of different scales to predict traffic speed of the various-scale road. The speed prediction of small-scale sections can cover more detailed road spatial features preparing for Vehicle Navigation System, and the speed prediction of large-scale sections can establish the real-time traffic control strategies. In order to validate the effectiveness of the proposed model, we use the floating car data, with an updating frequency of 1 minute from the urban freeway of Beijing, for model training and testing. The experimental results show that the stacked BiGRU network with the multiscale-grid model enables to capture the spatial-temporal characteristics of traffic speed efficiently. Furthermore, the BiGRU with two layers (BiGRU-2L) outperforms benchmark models in the prediction of the traffic speed, which presents a significant advantage in reducing the overfitting problem, decreasing the excessive time-consuming and improving the effective use of limited computation resources.

An electrochemical determination of Pb ^2+ by cyclic voltammetry, differential pulse voltammetry and differential pulse anodic stripping voltammetry in various waters using a glassy carbon electrode modified with graphene/Nafion mixture has been developed. A series of optimum conditions such as graphene concentration, modifying amount, Nafion concentration, scanning speed, pH, accumulation potential and time were optimized. Under optimal experiments, some evaluation indexes were analyzed. Graphene/Nafion/GCE was successfully used in the detection and quantification of Pb ^2+ in various real water samples using three methods above. Differential pulse anodic stripping voltammetry method that is adopted to study the linear range and the detection limit for Pb ^2+ proved to be more effective than the other two. The wider range is 0.02∼24.15 μ M, the lower detection limit is 5.1 mM and the recovery is 96.1%∼109.0%. To sum up, it will provide a theoretical basis and the practical method for the analysis of heavy metal polltants in different kinds of water.

It is well established that estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2) could be regarded as prognostic factors in breast cancer. Ultrasound-guided fine needle aspiration cytology (FNAC) has revolutionized the management of cancers, providing less invasive and quick diagnostic method. There are hardly any studies on the correlation between cytomorphology and prognostic biomarkers. We retrospectively analyzed the immunohistochemistry and the fluorescence in situ hybridization of breast cancer specimens from 252 patients, who have been diagnosed as breast cancer at our hospital. Morphological features of cytology smears were scored. The relationship between cytological features and three biomarkers were analyzed. Based on this, we developed a system to predict the status of biomarkers. The results indicated that some cytological parameters, especially the features of nucleoli, were distinctively related to the makers’ expression. In the novel scoring system, a cutoff of 12.0 provided a statistical discrimination for cytological grading. We concluded that cytomorphological features were associated with prognostic factors. The HR+ neoplasms showed scattered micronucleoli, while HER2+ neoplasms demonstrated centered macronucleoli. We summarized a scoring system to predict the status of three factors. This may help us to broaden the application of breast cancer cytology.

This study proposes a new adaptive traffic signal control scheme to effectively manage dynamically fluctuating traffic flows through intersections. A spatial-temporal representation of the traffic state at an intersection has been designed to efficiently identify traffic patterns from complex intersection environments, and a deep neural network (long short-term memory network, LSTM) is used to determine look-ahead signal control decisions based on the estimated long-term feedback from a given traffic state. The actor-critic algorithm, one of the reinforcement learning-based algorithms, is adopted to obtain the essential parameters of the LSTM deep neural network through multiple interactions between a simulated environment and the corresponding adaptive traffic signal controller. A realistic model environment comprising a 24-hour time-varying traffic demand including rush hour and non-rush hour situations served as the basis for traffic generation in the numerical experiments to confirm the effectiveness of the proposed scheme. The results of these experiments show that, compared to an optimized fixed time plan (Synchro), the proposed scheme can reduce waiting times at intersections by an astounding 50% with consequential benefits of reducing fuel consumptions, emissions, queue lengths, and vehicle delays whilst increasing mean speeds.

Abstract As a nonthermal sterilization technology, electron‐beam irradiation (EBI) has attracted great interests for microbial inactivation in food preservation. In this study, the inactivation of inoculated Listeria innocua, natural microbiota, and quality of fresh noodles treated by EBI during refrigerated storage were evaluated. Results showed that the initial L. innocua population (6.38 log CFU/g) was significantly reduced to an undetectable level by treatment with 3.0 kGy EBI. Moreover, treatment with 3 kGy EBI significantly reduced the initial total bacteria counts and fungal counts (mold and yeast) from 5.66 and 3.15 log CFU/g to 2.90 and 2.11 log CFU/g, respectively. However, along with the storage process, the inoculated L. innocua and natural microbiota were recovered resulting in the increased populations of the spoilage microorganisms. Increasing the dose of EBI to 4.0 kGy or 5.0 kGy, the L. innocua population was inhibited to the undetectable level and the microbiological quality of the fresh noodles was kept in the acceptable level during the 28 day storage. In addition, changes of the physicochemical indicators including pH value, color, cooking characteristics, texture, and sensory of fresh noodles treated with EBI were delayed during storage. These results reveal that EBI treatment can improve the microbiological safety and shelf life of fresh noodles without impairing quality.

The crane-form pipeline (CFP) system is a kind of petrochemical mechanical equipment composed of multiple rotating joints and rigid pipelines. It is often used to transport chemical fluid products in the factory to tank trucks. In order to realize the automatic alignment of the CFP and the tank mouth, the trajectory tracking control problem of the CFP must be solved. Therefore, a saturated nonsingular fast terminal sliding mode (SNFTSM) algorithm is proposed in this paper. The new sliding mode manifold is constructed by the nonsingular fast terminal sliding mode (NFTSM) manifold, saturation functions and signum functions. Further, according to the sliding mode control algorithm and the dynamic model of the CFP system, the SNFTSM controller is designed. Owing to the existence of saturation functions in the controller, the stability analysis using the Lyapunov equation needs to be discussed in different cases. The results show that the system states can converge to the equilibrium point in finite time no matter where they are on the state’s phase plane. However, due to the existence of signum functions, the control signal will produce chattering. In order to eliminate the chattering problem, the form of the controller is improved by using the boundary layer function. Finally, the control effect of the algorithm is verified by simulation and compared with the NTSM, NFTSM and SNTSM algorithms. From the comparison results, it is obvious that the controller based on the SNFTSM algorithm can effectively reduce the amplitude of the control torque while guaranteeing the fast convergence of the CFP system state error. Specifically, compared with the NFTSM algorithm, the maximum input torque can even be reduced by more than half.

Forests are composed of landscape spatial units (patches) of different sizes, shapes, and characteristics. The forest landscape pattern and its trends are closely related to resistance to disturbance, restoration, stability, and the biodiversity of the forest landscape and directly influence the benefits and sustainable exploitation of forest landscape resources. Therefore, forest landscape patterns and the driving forces have increasingly attracted the attention of researchers. The present study analyzed the spatial and temporal dynamics of woodland landscape patterns in typical hilly mountainous areas in southern China using ArcGIS, landscape pattern index, and morphological spatial pattern analysis. Meanwhile, a logistic regression model was used to analyze the drivers of woodland change in Anyuan County from three aspects: natural, geographic location, and socio-economic conditions. The total area of woodland decreased during the 10-year study period, with a net decrease of 4959.27 ha, mainly due to conversion into cultivated land, garden land, and construction land. Patch density, edge density, and aggregation index of woodlands increased over time, indicating enhanced fragmentation, stable and complex patch edges, and increased patch connectivity. Conversely, the highest patch index values exhibited decreasing trends, indicating decreases in the dominant patch type. Morphological spatial pattern analysis results showed that the core area was dominant and the islet area increased over time, which also indicates enhanced fragmentation. Forest landscape change is the result of environmental change, ecological processes, and human disturbance, with geographical location and social economy having greater influences on forest landscape change. Human activities such as navel orange cultivation, returning cultivated land to forest, and land occupation for construction were the major factors driving woodland change. The results provide reference that could facilitate forest management and sustainable forest resource utilization.

Abstract Background Castleman’s disease (CD) is an uncommon type of benign proliferation of the lymphoid tissue, characterized by local or systemic lymphadenopathy that most frequently appears in the mediastinum; involvement of the kidney is uncommon, and proliferation originating from the kidney is extremely rare. Herein, we report a rare case of hyaline vascular Castleman’s disease (HV-CD) in a 56-year-old male patient and discuss its morphological characteristics and differential diagnoses including mantle cell lymphoma (MCL), follicular lymphoma (FL), and nodal marginal zone lymphoma (NMZL). Case presentation A right upper-middle renal mass was detected after physical examination in a 56-year-old man without any clinical symptoms and a previous partial resection of the right kidney. Microscopically, the lymphoid follicles were increased in number and had expanded mantle zones and atrophic germinal centers. Vascular proliferation and hyalinization in the interfollicular zones were observed. Immunohistochemical staining showed CD20-positive cells in the mantle zones; CD21 and CD35 were expressed in the dendritic cells, CD3 was positive in a small number of T cells, and CD38 and CD138 were positive in the plasma cells. Additionally, Ki-67 expression was positive in the follicle centers. In contrast, staining for Bcl-2 in the germinal centers and cyclin D1 were negative. The immunohistochemical analysis combined with the morphological results supported the diagnosis of HV-CD. The patient recovered well after surgery. Conclusions Primarily renal HV-CD without lymph node hyperplasia or clinical symptoms is extraordinarily rare and different from the multicentric-type CD (MCD) with kidney involvement. Therefore, it is extremely important to improve the awareness of this diagnosis. Attention should be paid to the difference between HV-CD and common lymph node reactive hyperplasia, MCL, FL, NMZL, and so on. To avoid misdiagnosis as a renal malignant tumor requiring radical resection, distinguishing these diseases is crucial.

In this paper, the attitude tracking control for a spacecraft system based on a novel adaptive integral-type terminal sliding mode fault-tolerant control strategy is investigated. First, a basic fault-tolerant control scheme is designed to ensure the spacecraft attitude tracking performance in the presence of the actuator fault, external disturbance, and actuator saturation when the rotational inertia of a spacecraft system is known. Second, combined with adaptive laws, a modified fault-tolerant control scheme is proposed to compensate the actuator fault and system uncertainty which contains external disturbance and the inertia uncertainty, separately. The actuator fault is compensated more directly and accurately. The benefits of this approach are that the proposed control scheme can enable the merits of the integral-type terminal sliding mode control, such as nonsingularity, fast convergence speed, and small steady-state errors. Finally, the simulation results are given to demonstrate the effectiveness of the proposed fault-tolerant control schemes.

Minichromosome maintenance protein 5 (MCM5) is a critical cell cycle regulator; its role in DNA replication is well known, but whether it is involved in the regulation of organogenesis in a cell cycle-independent way, is far from clear. In this study, we found that a loss of mcm5 function resulted in a mildly smaller liver, but that mcm5 overexpression led to liver bifida. Further, the data showed that mcm5 overexpression delayed endodermal migration in the ventral–dorsal axis and induced the liver bifida. Cell cycle analysis showed that a loss of mcm5 function, but not overexpression, resulted in cell cycle delay and increased cell apoptosis during gastrulation, implying that liver bifida was not the result of a cell cycle defect. In terms of its mechanism, our data proves that mcm5 represses the expression of cxcr4a, which sequentially causes a decrease in the expression of itgb1b during gastrulation. The downregulation of the cxcr4a-itgb1b cascade leads to an endodermal migration delay during gastrulation, as well as to the subsequent liver bifida during liver morphogenesis. In conclusion, our results suggest that in a cell cycle-independent way, mcm5 works as a gene expression regulator, either partially and directly, or indirectly repressing the expression of cxcr4a and the downstream gene itgb1b, to coordinate endodermal migration during gastrulation and liver location during liver organogenesis.

Aberration-corrected scanning transmission electron microscopy (AC-STEM) has evolved into the most powerful characterization and manufacturing platform for all materials, especially functional materials with complex structural characteristics that respond dynamically to external fields. It has become possible to directly observe and tune all kinds of defects, including those at the crucial atomic scale. In-depth understanding and technically tailoring structural defects will be of great significance for revealing the structure-performance relation of existing high-property materials, as well as for foreseeing paths to the design of high-performance materials. Insights would be gained from piezoelectrics and thermoelectrics, two representative functional materials. A general strategy is highlighted for optimizing these functional materials’ properties, namely defect engineering at the atomic scale.

This study proposes a trajectory planning method for an automated lane change maneuver. We consider that the spatiotemporal trajectory of a controlled vehicle can be represented by a polynomial function and estimate the parameters of the polynomial function through nonlinear programming that does not rely on the assumed time horizon of lane change and the assumed final state of the controlled vehicle. When the controlled vehicle achieves its target lane, the state of this vehicle should be constrained by both the position and the speed of the forward vehicle. We integrate a car-following model into the nonlinear programming to constrain the state of the controlled vehicle at the end of the lane change. Notably, the interaction factors are taken into consideration: the motion of the vehicle that follows the controlled vehicle in the target lane can be influenced by the trajectory planning results of the controlled vehicle. The proposed trajectory planning method can simultaneously estimate the motion of the following vehicle and plan the trajectory for the controlled vehicle. Our proposed model can also work for curved road sections. We represent the curve information in the nonlinear programming by a regression model. We solve the nonlinear programming through the sequential quadratic program (SQP) algorithm and design a method to specify an initial guess for the algorithm. This paper finally demonstrates the effect of the proposed trajectory planning method under different scenarios.

Urban road intersection bottleneck has become an important factor in causing traffic delay and restricting traffic efficiency. It is essential to explore the prediction of the operating performance at intersections in real-time and formulate corresponding strategies to alleviate intersection delay. However, because of the sophisticated intersection traffic condition, it is difficult to capture the intersection traffic Spatio-temporal features by the traditional data and prediction methods. The development of big data technology and the deep learning model provides us a good chance to address this challenge. Therefore, this paper proposes a multi-task fusion deep learning (MFDL) model based on massive floating car data to effectively predict the passing time and speed at intersections over different estimation time granularity. Moreover, the grid model and the fuzzy C-means (FCM) clustering method are developed to identify the intersection area and derive a set of key Spatio-temporal traffic parameters from floating car data. In order to validate the effectiveness of the proposed model, the floating car data from ten intersections of Beijing with a sampling rate of 3s are adopted for the training and test process. The experiment result shows that the MFDL model enables us to capture the Spatio-temporal and topology feature of the traffic state efficiently. Compared with the traditional prediction method, the proposed model has the best prediction performance. The interplay between these two targeted prediction variables can significantly improve prediction accuracy and efficiency. Thereby, this method predicts the intersection operation performance in real-time and can provide valuable insights for traffic managers to improve the intersection’s operation efficiency.

The Jiaoshiba shale gas field is located in the Fuling area of the Sichuan Basin, with the Upper Ordovician WufengâLower Silurian Longmaxi Fm as the pay zone. At the bottom of the pay zone, a high-quality shale gas reservoir about 20Â m thick is generally developed with high organic contents and gas abundance, but its resistivity is relatively low. Accordingly, the gas saturation calculated by formulas (e.g. Archie) using electric logging data is often much lower than the experiment-derived value. In this paper, a new method was presented for calculating gas saturation more accurately based on non-electric logging data. Firstly, the causes for the low resistivity of shale gas reservoirs in this area were analyzed. Then, the limitation of traditional methods for calculating gas saturation based on electric logging data was diagnosed, and the feasibility of the neutronâdensity porosity overlay method was illustrated. According to the response characteristics of neutron, density and other porosity logging in shale gas reservoirs, a model for calculating gas saturation of shale gas was established by core experimental calibration based on the density logging value, the density porosity and the difference between density porosity and neutron porosity, by means of multiple methods (e.g. the dual-porosity overlay method by optimizing the best overlay coefficient). This new method avoids the effect of low resistivity, and thus can provide normal calculated gas saturation of high-quality shale gas reservoirs. It works well in practical application. This new method provides a technical support for the calculation of shale gas reserves in this area. Keywords: Shale gas, Gas saturation, Low resistivity, Non-electric logging, Volume density, Compensated neutron, Overlay method, Reserves calculation, Sichuan Basin, Jiaoshiba shale gas field

To enhance the seismic resilience of coupled reinforced concrete shear walls, a new damper working in the replaceable coupling beam is proposed in present study. The new damper is a combination of metallic damper and viscoelastic (VE) damper. The metallic damper consists of an I-shaped steel beam with multiple low-yield-point steel plate webs paralleled to each other; the VE damper is composed of multiple layers of VE material bonded between multiple steel plates. Through the composite use of viscoelastic material and low-yield-point steel, the new damper is expected to work effectively against both the earthquake and the wind. To study the respective mechanical behavior of each component of the combined new damper, eight metallic dampers, two VE dampers, and one combined damper are tested under cyclic loading first. The variable parameters of the metallic damper are strength grade of web steel, web dimensions, and end stiffener configuration. It is found that the effect of the strength grade of web steel is most significant. Compared with the metallic damper using the steel web with normal strength grade, the ductility, ultimate plastic shear rotation, and cumulative plastic shear rotation of the damper using the low-yield-point steel web are much larger. The effect of web dimensions on the deformation capacity is slight. With the addition of end stiffener, plasticity concentrates thereby, which prevents the flange-to-end plate weld fracture. The VE damper exhibits extraordinary deformability. The storage modulus, shear loss modulus and loss factor of the VE material decrease with the increase of strain amplitude. The storage modulus and shear loss modulus of the VE material decrease slightly as the excitation frequency increases within the range between 0.1 and 1 Hz, and the effect of the excitation on the loss factor is not significant. At last, the combined damper, an assembly of one metallic damper component and two VE damper components, is tested, which exhibits stable hysteretic behavior and excellent deformability. The predicted yield shear strength and elastic stiffness agree well with test results.

Intermittent arc grounding fault frequently occurs in non-solidly earthed networks. Establishing an accurate arc model is the basis for analysis of fault characteristics. First of all, an improved cybernetic arc model is introduced in this study, which can effectively demonstrate arcing process through controlling the arc length, and which is applied to simulation analysis of intermittent arc grounding fault. Then, a novel method is proposed to identify when the arc would extinguish or restrike. Arc extinction is determined by comparing the stable ignition voltage and air withstand voltage, while arc reignition is dependent on the competition between recovery voltage and air withstand voltage. Finally, a typical simulation model of 10 kV distribution network is built via PSCAD, and impacts of arc model parameters on fault characteristics are analysed. Comparison between simulation results and field data indicates that the arc model can accurately describe arc characteristics and that the intermittent arc grounding overvoltage generated by the suggested method is consistent with the actual case. In the Petersen coil grounded system, arc reignition times turns to be fewer, intermittent arc duration shorter and the overvoltage amplitude lower than those in the isolated neutral system.

Because of the mechanism complexity, coupling, and time-space characteristic of alkali-surfactant-polymer (ASP) flooding, common methods are very hard to be implemented directly. In this paper, an iterative dynamic programming (IDP) based on a biorthogonal spatial-temporal Wiener modeling method is developed to solve the enhanced oil recovery for ASP flooding. At first, a comprehensive mechanism model for the enhanced oil recovery of ASP flooding is introduced. Then the biorthogonal spatial-temporal Wiener model is presented to build the relation between inputs and states, in which the Wiener model is expanded on a set of spatial basis functions and temporal basis functions. After inferring the necessary condition of solutions, these basis functions are determined by the snapshot method. Furthermore, a theorem is proved to identify parameters in the Wiener model. Combined with the least square estimation (LSE), all unknown parameters are determined. In addition, the ARMA model is applied to build the model between states and outputs, whose parameters are identified by recursive least squares (RLS). Thus, the whole modeling process for ASP flooding is finished. At last, the IDP algorithm is applied to solve the enhanced oil recovery problem for ASP flooding based on the identification model to obtain the optimal injection strategy. Simulations on the ASP flooding with four injection wells and nine production wells show the accuracy and effectiveness of the proposed method.

As one of the model organisms of Parkinson’s disease (PD) research, the zebrafish has its advantages, such as the 87% homology with human genome and transparent embryos which make it possible to observe the development of dopaminergic neurons in real time. However, there is no midbrain dopaminergic system in zebrafish when compared with mammals, and the location and projection of the dopaminergic neurons is seldom reported. In this study, Vmat2:GFP transgenic zebrafish was used to observe the development and distribution of dopaminergic neurons in real time. We found that diencephalon (DC) 2 and DC4 neuronal populations were detected at 24 hpf. All DC neuronal populations as well as those in locus coeruleus, raphe nuclei and telencephalon were detected at 48 hpf. Axons were detected at 72 hpf. At 96 hpf, all the neuronal populations were detected. For the first time we reported axons from the posterior tubercle of ventral diencephalon projected to subpallium in vivo. However, when compared with results from whole mount tyrosine hydroxylase immunofluorescence staining in wild type zebrafish, we found that DC2 and DC4 neuronal populations were mainly dopaminergic, while DC1, DC3, DC5 and DC6 might not. Neurons in pretectum and telencephalon were mainly dopaminergic, while neurons in locus coeruleus and raphe nuclei might be noradrenergic. Our study makes some corrections and modifications on the development, localization and distribution of zebrafish dopaminergic neurons, and provides some experimental evidences for the construction of the zebrafish PD model.

Three-phase unbalance is an important power quality issue that can cause many negative effects to the power system. Effective mitigation and management of voltage unbalance will benefit from the knowledge of how the unbalanced sources contribute to the voltage asymmetry at the point of evaluation (POE). In this paper, a method is proposed to assess the overall unbalance contribution of the multiple unbalanced sources at the point of common coupling (PCC). Firstly, the equivalent circuit for analysis is established and the unbalance contribution indices are proposed. Then a method is proposed to determine whether the dominant unbalanced polluter is at the upstream or downstream of POE. If the main unbalanced source is identified to be downstream of POE, a procedure is further proposed to determine the individual contribution of the multiple unbalanced sources. Moreover, for the multiple unbalanced source condition, the current flowing in each feeder is proposed to be used for the contribution estimation instead of the current actually emitted by the unbalanced source. Finally, a method is proposed to estimate the equivalent negative sequence impedance of the aggregate loads. Simulation and field analysis results validate the effectiveness and accuracy of the method.

An off-line optimization approach of high precision minimum time feedrate for CNC machining is proposed. Besides the ordinary considered velocity, acceleration, and jerk constraints, dynamic performance constraint of each servo drive is also considered in this optimization problem to improve the tracking precision along the optimized feedrate trajectory. Tracking error is applied to indicate the servo dynamic performance of each axis. By using variable substitution, the tracking error constrained minimum time trajectory planning problem is formulated as a nonlinear path constrained optimal control problem. Bang-bang constraints structure of the optimal trajectory is proved in this paper; then a novel constraint handling method is proposed to realize a convex optimization based solution of the nonlinear constrained optimal control problem. A simple ellipse feedrate planning test is presented to demonstrate the effectiveness of the approach. Then the practicability and robustness of the trajectory generated by the proposed approach are demonstrated by a butterfly contour machining example.

Polymer flooding is one of the most important technologies for enhanced oil recovery (EOR). In this paper, an optimal control model of distributed parameter systems (DPSs) for polymer injection strategies is established, which involves the performance index as maximum of the profit, the governing equations as the fluid flow equations of polymer flooding, and the inequality constraint as the polymer concentration limitation. To cope with the optimal control problem (OCP) of this DPS, the necessary conditions for optimality are obtained through application of the calculus of variations and Pontryagin’s weak maximum principle. A gradient method is proposed for the computation of optimal injection strategies. The numerical results of an example illustrate the effectiveness of the proposed method.