Search

To solve the problem of inaccurate prediction of the stack life of proton exchange membrane fuel cells, this paper first proposed a fuel-cell aging prediction method based on method Savitzky–Golay Smoothing and Group Method of Data, which was based on the data drive. Savitzky–Golay Smoothing is an optimal piecewise fitting method based on polynomial in the time domain and using the least square method through moving window, which is widely used in data flow smoothing and denoising. Group Method of Data is a modeling method of the complex nonlinear dynamic system. The inner criterion and outer criterion are used in the training set and test set respectively, and the optimal solution is finally solved by iterative screening. The method presented in this paper was verified by 1020 h fuel cell aging experiment. The experimental results show that: the MSE, RMSE, R of the test data are respectively 6.3935e−05, 0.0079959, and 0.99616. The data-driven prediction method proposed in this paper can be used for fuel cell aging prediction and fault warning.

Abstract In cross-country skiing competitions, the choice of pacing strategy is of decisive significance to athletes' performance. A reasonable pacing strategy is essential for athletes to improve their performance. In this paper, the mathematical models of cross-country skiing simulation and pacing optimization are established, including motion model, athlete power output model, and optimization model. The actual competition data of a Chinese athlete in Guyangshu 1.5 km track was compared with the model simulation results. The whole process time error is less than 3%, which verifies the accuracy of the motion and power output model. Gauss pseudo-spectral method is applied to the optimization model. By changing the distribution of athletes' power output, the racing time is minimized under the condition that the total energy output remains unchanged. Compared with the pacing strategy before optimization, the optimized racing time was shortened by 12.6 s, which verifies the effectiveness of the optimization model. Optimized results show that in the first significant uphill section, a recommendation is to use a more conservative strategy, while in the latter half of uphill sections the power output should be increased.

This paper introduces the development of clean energy in Sichuan province and the work done by the company in serving the development of clean energy. It mainly includes vigorously building power transmission channels to meet the needs of clean energy consumption, strengthening power grid planning and construction, serving the rapid development of new energy, tapping the potential of power grid operation, increasing the space of clean energy consumption, adopting multiple measures simultaneously, flexible trading, and increasing the intensity of clean energy consumption. And to solve the current situation and difficulties, put forward relevant policies and suggestions. It mainly includes suggestions to promote the construction of Sichuan electric power transmission channel, to call on the state to establish a policy mechanism to ensure Sichuan clean energy transmission and absorption, to arrange the development scale and progress of natural gas distributed energy, new energy, and other power sources in a reasonable and orderly manner. It is suggested that the development scale and progress of various power sources such as natural gas distributed energy and new energy should be reasonably and orderly arranged.

Abstract Background The successful establishment of a species population following a single introduction of a few individuals to a non-native area has been limited. Nevertheless, the oriental fire-bellied toad (Bombina orientalis) population in Beijing is purportedly descended from a single introduction of about 200 individuals translocated from Yantai, Shandong Province, China, in 1927. Results To resolve the introduction process and to understand the genetic consequences since that introduction approximately 90 years ago, we investigated the population’s genetic diversity and structure using 261 toads from Beijing and two native Shandong populations and inferred the species’ introduction history using simulation-based approaches. Analysis of mitochondrial DNA (mtDNA) sequences showed the two haplotypes found in Beijing nested within Yantai haplotypes, thus corroborating the historical record of the translocation source. The mtDNA and 11 nuclear microsatellite markers revealed both considerably lower genetic diversity in Beijing than in the source population and strong genetic differentiation between them. Although the current census population in Beijing may be in the range of a few thousand, the effective population size was estimated at only 20–57. Simulations also suggest that this population may have descended from 40–60 founders. Conclusions The Beijing population’s genetic patterns were consistent with the consequences of a severe bottleneck during introduction followed by genetic drift. The introduction trajectory constructed for this B. orientalis population reveals the genetic footprints of a small population sustained in isolation for nearly a century. Our results provide an intriguing example of establishment success from limited founders and may inform ex situ conservation efforts as well as the management of biological invasions.

The traditional method of urea production is a carbon-emitting, energy-intensive technology that contradicts the concept of carbon neutrality. Fortunately, the use of renewable energy in electrochemical synthesis has shown great potential for producing high-value nitrogen products, making electrocatalytic urea production a promising and sustainable approach. However, the low yield and Faraday efficiency, as well as the unclear mechanism of C-N bond formation, limit its large-scale industrial development. Researchers are seeking higher-performance electrocatalysts. This article discusses in detail the latest progress in the electrochemical synthesis of urea using carbon dioxide and various nitrogen sources, including catalyst design and preparation, as well as the mechanism of C-N coupling reactions. It also provides comprehensive analysis on the challenges and prospects facing urea electro-synthesis. The development of targeted and efficient new catalysts for urea synthesis is anticipated to bring about more sustainable and cost-effective production methods.

The purpose of this paper is to propose a novel aircraft wing loads calculation model, called long short-term memory residual network (LSTM-ResNet), which can evaluate the loads based on the strain distribution. To achieve this goal, firstly, the data acquisition experiment is designed and performed with a real aircraft wing. In this experiment, we used the Fiber Bragg Grating (FBG) technology as the measurement method to collect strain-load data from the aircraft wing. Then, we propose the LSTM-ResNet model with the one-dimensional convolutional(1D-CNN) architecture. This model is capable of extracting the temporal and spatial representational information from the strain-load data of the aircraft wing. Experimental results demonstrate that the proposed method effectively evaluate the loads of the aircraft wing. To prove the superiority of LSTM-ResNet model, we compared the proposed model with existing loads calculation methods on our experimental dataset. The results show it has a competitive average relative error (0.08%). Moreover, those promising results may pave the way to use the deep learning algorithm in aircraft wing loads calculation.

In recent decades, China's rapid urbanization has produced numerous economic benefits while simultaneously creating substantial risks to ecological security. China's 14th Five-Year Plan and the United Nations Sustainable Development Goals (SDGs) have recently explicitly called for the coordinated development of ecological security and urbanization. Given this context, it is important to explore the mechanism by which ecological security and urbanization are coupled and coordinated to promote sustainable development. In this study, an index of the relationship between ecological security and urbanization was established via high-resolution data, and a ''Computation-Verification-Coupling'' (CVC) framework was constructed. The accuracy of the ecological security index was verified using a linear regression model, and the coordination level between ecological security and urbanization was analyzed via a coupled coordination model (CCM). The results revealed a steady increase in the ecological security index from 2010 to 2020; the proportion of the area above the medium level increased from 63.1 % to 74.1 %. The urbanization index in core counties exhibited rapid growth, with level V urbanized areas expanding from 5.5 % to 9.9 %. The ecological security verification model produced a coefficient of determination (R²) of 0.75685, indicating a satisfactory degree of predictive capability. From 2010–2020, the coupled coordination improved, with the high coordination area accounting for 48.8 % and the extreme discoordination area decreasing from 1.8 % to 1.0 %. Coordinated development exhibited a stable progression, characterized by a cyclical evolution from initial coupling to antagonistic coupling and finally to coordinated development. This framework can be used not only to investigate the relationship between ecological security and urbanization but also to provide a quantifiable measure of progress toward achieving the SDGs.

ObjectiveSpontaneous isolated abdominal aortic dissection (SIAAD) is a rare aortic emergency and not yet fully understood. This study aims to report the characteristics and treatments of 31 patients with SIAAD in the past 12 years.MethodsA total of 31 consecutive patients with SIAAD between 2010 and 2022 were included. The clinical manifestations, treatment strategies, and outcomes were reviewed. Following the SVS/STS reporting standard, we compared the clinical characteristics with different locations of primary entry, or different numbers of dissected zones. Furthermore, we compared the effects of surgical and conservative therapies on the outcome during the follow-up.ResultsAmong the 31 patients with SIAAD, 16 (51.6%) were in the acute phase on admission. The primary entry of SIAAD was mainly located in Zone 9 (67.7%). Most patient presented with dissection involving 1 or 2 aortic zones (61.3%). In addition, 35.5% and 64.5% of SIAADs involved the visceral and iliac arteries, respectively. Compared with asymptomatic SIAADs, the symptomatic ones had longer dissection lengths (P = 0.008) and tended to involve iliac artery more frequently (P = 0.098). There were differences in the number of dissected aortic zones (P = 0.005) among patients with primary entry located in Zone 5 (Supraceliac aorta), Zone 6–8 (Paravisceral aorta) and Zone 9 (Infrarenal aorta). The involvement of visceral artery (P = 0.039) and iliac artery (P = 0.006) was significantly different between the subgroups of SIAAD involving one, two, and three or more aortic zones. The cumulative incidence of adverse false lumen progression events was significantly lower (P = 0.000) and the rate of false lumen thrombogenesis or disappearance was higher in patients receiving surgery (P = 0.001). The cumulative all-cause mortality was 9.7% at 1-year, and 19.7% at 5-year, with no significant difference between surgical and conservative therapies.ConclusionsClinical features of SIAAD vary depending on the location of the primary entry and the number of dissected aortic zones. Although surgery was not associated with a lower all-cause mortality compared with conservative therapy, it was associated with a lower incidence of adverse false lumen progression and a higher rate of aortic remodeling.

Abstract Developing sustainable and clean energy‐conversion techniques is one of the strategies to simultaneously meet the global energy demand, save fossil fuels and protect the environment, in which nanocatalysts with high activity, selectivity and durability are of great importance. Intermetallic nanocrystals, featuring their ordered atomic arrangements and predictable electronic structures, have been recognized as a type of active and durable catalysts in energy‐related applications. In this minireview, the very recent progress in the syntheses and electrocatalytic applications of noble metal‐based intermetallic nanocrystals is summarized. Various synthetic strategies, including the conventional thermal annealing approach and its diverse modifications, as well as the wet‐chemical synthesis, for the construction of binary, ternary and high‐entropy intermetallic nanocrystals have been discussed with representative examples, highlighting their strengths and limitations. Then, their electrocatalytic applications toward oxygen reduction reaction, small molecule oxidation reactions, hydrogen evolution reaction, CO2/CO reduction reactions, and nitrogen reduction reaction are discussed, with the emphasis on how the ordered intermetallic structures contribute to the enhanced performance. We conclude the minireview by addressing the current challenges and opportunities of intermetallic nanocrystals in terms of syntheses and electrocatalytic applications.

Background: The blood shortage in China has become a nationwide issue, which poses a threat to critical medical treatments and puts patients at risk. To address this problem, blood donation recruitment and retention campaigns have been launched, with university students being recognized as an important target audience. To recruit this particular population effectively, it is crucial to comprehend their motivations for donating blood. Methods: This study used a modified and extended Ajzen's Theory of Planned Behavior to explain the determinants of blood donation intention among N = 1165 China's young adults through an online cross-sectional survey, utilizing a snowball sampling technique to recruit participants. Results: In line with previous TPB-based studies, we found positive associations between attitude (β = 0.071, p

A giant electric field on a subwavelength scale is highly beneficial for boosting the light–matter interaction. In this paper, we investigated a hybrid structure consisting of a hemispheric dimer array and a gold film and realized resonant mode coupling of the surface lattice resonance (SLR) and surface plasmon polariton (SPP). Mode coupling is demonstrated by observing anti-crossing in reflection spectra, which corresponds to Rabi splitting. Although the resonance coupling does not enter the strong coupling regime, an improved quality factor (Q~350) and stronger electric field enhancement in the gap region of the dimer (i.e., hot spot) in our hybrid structure are obtained compared to those of the single dimer or dimer array only. Remarkably, the magnitude of electric field enhancement over 500 can be accessible. Such high field enhancement makes our hybridized structure a versatile platform for the realization of ultra-sensitive biosensing, low-threshold nanolasing, low-power nonlinear optical devices, etc.

Safety barriers (SBs) are important means of reducing failure risks of process systems. As barriers vary in type and function, their effectiveness needs to be evaluated in order to find a more reasonable configuration strategy. However, in practice, there is often a lack of accurate and complete data relating to SBs, which poses a significant challenge in quantitatively assessing their effectiveness. To address this issue, in this study, we propose a semi-quantitative approach for evaluating the effectiveness of both preventive and protective barriers in process systems by integrating expert elicitation, interval-valued intuitionistic fuzzy numbers (IVIFNs), and a bow-tie model. In this approach, the bow-tie model is first applied to describe the system failure scenarios and the action phases of the barriers, and then IVIFNs with expert judgment are introduced to obtain the failure probabilities of basic events and the effects of SBs. Subsequently, the effectiveness of each barrier is measured by comparing the relative change in failure risk due to the addition of the barrier. To verify the feasibility of this approach, a natural gas storage tank with some barriers was analyzed. The results show that the regular inspection of the deformation or damage of the storage tank has the highest effectiveness, followed by the installation and regular maintenance of safety electrical equipment. Furthermore, compared to a single barrier, multiple barriers can significantly reduce the system risk.

During the growth stage of soybean seedlings, it is crucial to quickly and precisely identify them for emergence rate assessment and field management. Traditional manual counting methods have some limitations in scenarios with large-scale and high-efficiency requirements, such as being time-consuming, labor-intensive, and prone to human error (such as subjective judgment and visual fatigue). To address these issues, this study proposes a rapid detection method suitable for airborne edge devices and large-scale dense soybean seedling field images. For the dense small target images captured by the Unmanned Aerial Vehicle (UAV), the YOLOv5s model is used as the improvement benchmark in the technical solution. GhostNetV2 is selected as the backbone feature extraction network. In the feature fusion stage, an attention mechanism—Efficient Channel Attention (ECA)—and a Bidirectional Feature Pyramid Network (BiFPN) have been introduced to ensure the model prioritizes the regions of interest. Addressing the challenge of small-scale soybean seedlings in UAV images, the model’s input size is set to 1280 × 1280 pixels. Simultaneously, Performance-aware Approximation of Global Channel Pruning for Multitask CNNs (PAGCP) pruning technology is employed to meet the requirements of mobile or embedded devices. The experimental results show that the identification accuracy of the improved YOLOv5s model reached 92.1%. Compared with the baseline model, its model size and total parameters were reduced by 76.65% and 79.55%, respectively. Beyond these quantitative evaluations, this study also conducted field experiments to verify the detection performance of the improved model in various scenarios. By introducing innovative model structures and technologies, the study aims to effectively detect dense small target features in UAV images and provide a feasible solution for assessing the number of soybean seedlings. In the future, this detection method can also be extended to similar crops.

In recent years, nanobodies have played an increasingly crucial role in virus neutralization, ELISA detection, and medical imaging. This study aimed to explore a universal expression strategy in Pichia pastoris using three nanobodies, denoted Va, Vb, and Vc, as model proteins. Initially, plasmids pLD-AOXα and pLD-AOX were engineered to minimize the risk of antibiotic resistance gene drift. Optimization of promoters and signal peptides resulted in a 1.38-fold and 1.89-fold increase in Va production. Further optimization of gene dosage led to an additional 1.39-fold enhancement in Va yield. Subsequently, 25 molecular chaperones were co-expressed with Va under the control of the wild-type AOX1 promoter, with HAC1 further increasing Va yield by 1.5-fold. By fine-tuning the promoter strength for HAC1, Va production was increased by 2.41-fold under the control of the 55p promoter. Finally, through high-density fermentation, the Va yield reached 2.13 g/L, representing a 49.8-fold increase compared to the initial strain 1-AOXα-Va in shake-flask culture. Integration of pLD-55p-HAC1 into the GS115 genome resulted in the H55 host, and the transformation of multicopy plasmids into this host led to a 1.98-fold increase in Vb yield and a 2.34-fold increase in Vc yield, respectively. The engineering of antibiotic-free parental plasmids, modification of expression components, gene dosage optimization, and the H55 host are regarded as a composite strategy which will pave the way for efficient expression of nanobodies in the future.

In petroleum engineering, accurately predicting particle settling velocity during various stages of a well’s life cycle is vital. This study focuses on settling velocities of both spherical and non-spherical particles in Newtonian and non-Newtonian fluids. Utilizing a dataset of 931 experimental observations, an artificial neural network (ANN) model with a 7-42-1 architecture is developed (one input layer, one hidden layer with 42 neurons, and one output layer). This model effectively incorporates particle settling orientation and the inclusion of the settling area ratio, enhancing its predictive accuracy. Achieving an average absolute relative error (AARE) of 8.51%, the ANN model surpasses traditional empirical correlations for settling velocities in both Newtonian and power-law fluids. Key influencing factors, such as the consistency index and particle equivalent diameter, were identified. This approach in ANN model construction and data analysis represents a significant advancement in understanding particle dynamics.

Abstract Background Clinical staging of gastric cancer (GC) before treatment is essential. Endoscopic ultrasound (EUS) is a recommended staging tool, but its efficacy remains controversial. Our previous prospective study evaluated the potential value of EUS for T staging and presented discrepancies. In this study, we aimed to evaluate the efficacy of EUS in T staging by comparing it with pathological staging. We analyze the factors that can potentially affect accuracy to identify suitable subgroups for EUS staging. Methods Data from a total of 1763 consecutive patients with GC from January 2015 to December 2017 were analyzed. Results from EUS and pathological T staging were compared. The factors that might affect EUS’s accuracy were analyzed. Results The sensitivity, specificity, positive predictive value, and negative predictive value of EUS in patients with early GC were 62.08%, 96.13%, 90.94%, and 80.21%, respectively. The accuracy rates of uT1, uT2–uT4, and uT3–uT4 were 90.94%, 79.02%, and 78.39%, respectively. In multivariate analysis, underestimation was more likely to be observed in patients with tumors located in the middle or upper third of the stomach. Overestimation was more likely to be observed in patients with tumors located in the lower third or those without ulcer. Other factors affecting accuracy included ulcer, differentiation, larger size and undergoing surgery. Conclusion Our findings highlight the role of EUS in determining the T staging of GC. Overestimation and underestimation in T-staging were significantly associated with the tumor location in early GC, and a decision-making algorithm was proposed for clinical practice in early cancers based on these findings.

Abstract Low‐frequency oscillation, harmonic oscillation and harmonic instability issues in railway vehicle‐grid systems pose challenges to the system stability and safe operation. Previous studies constructed the linear time‐invariant impedance model of vehicle‐grid system, which ignored the internal frequency coupling and loss of model accuracy. To fill this gap, the impedance modelling method based on the harmonic linearisation method of the vehicle‐grid system is proposed. The derived model provides a clear physical insight into the harmonic coupling relations between ac and dc variables and improves the model accuracy. Then, a systematic analysis of harmonic stability in the railway vehicle‐grid system is analysed based on the proposed model. The electrical and control parameters on system stability at the frequencies above and below the fundamental frequency are summarised. The mechanisms of these oscillation issues in railway vehicle‐grid systems are then discussed. Finally, the model accuracy and stability analysis results are verified by the frequency scan method and hardware‐in‐the‐loop results.