Superconductor-ferromagnet interfaces in two-dimensional heterostructures present a unique opportunity to study the interplay between superconductivity and ferromagnetism. The realization of such ...nanoscale heterostructures in van der Waals (vdW) crystals remains largely unexplored due to the challenge of making atomically-sharp interfaces from their layered structures. Here, we build a vdW ferromagnetic Josephson junction (JJ) by inserting a few-layer ferromagnetic insulator Cr
Ge
Te
into two layers of superconductor NbSe
. The critical current and corresponding junction resistance exhibit a hysteretic and oscillatory behavior against in-plane magnetic fields, manifesting itself as a strong Josephson coupling state. Also, we observe a central minimum of critical current in some JJ devices as well as a nontrivial phase shift in SQUID structures, evidencing the coexistence of 0 and π phase in the junction region. Our study paves the way to exploring sensitive probes of weak magnetism and multifunctional building-blocks for phase-related superconducting circuits using vdW heterostructures.
To meet the real-time path planning requirements of intelligent vehicles in dynamic traffic scenarios, a path planning and evaluation method is proposed in this paper. Firstly, based on the B-spline ...algorithm and four-stage lane-changing theory, an obstacle avoidance path planning algorithm framework is constructed. Then, to obtain the optimal real-time path, a comprehensive real-time path evaluation mechanism that includes path safety, smoothness, and comfort is established. Finally, to verify the proposed approach, co-simulation and real vehicle testing are conducted. In the dynamic obstacle avoidance scenario simulation, the lateral acceleration, yaw angle, yaw rate, and roll angle fluctuation ranges of the ego-vehicle are ±2.39 m/s2, ±13.31°, ±13.26°/s, and ±0.938°, respectively. The results show that the proposed algorithm can generate real-time, available obstacle avoidance paths. And the proposed evaluation mechanism can find the optimal path for the current scenario.
The aim of this study was to determine the etiology tendency of acute pancreatitis (AP) in the Beijing region and the relationship with influencing factors.
This retrospective multicenter study ...enrolled 8 representative general hospitals from January 1, 2006 to December 31, 2010. The etiology tendency was analyzed, and the relationship was defined with sex, aging, severity, mortality, recrudesce rate, length of stay, and hospitalization cost.
The study enrolled 2461 patients. The total number was increasing year by year. Causes included biliary (1372, 55.75%), alcoholism (246, 10%), hypertriglyceridemia (255, 10.36%), and the others (588, 23.89%). Biliary AP was the most frequent primary cause. Hypertriglyceridemic AP increased at a faster rate than alcoholic AP. There was higher proportion of alcoholic and hypertriglyceridemic AP in men than in women. There is an increase of AP patients with ages 40 to 49 years and older than 70 years. Alcoholic and hypertriglyceridemic AP were higher in patients younger than the age of 50 years, and biliary pancreatitis was higher in patients older than 70 years. Severe AP was classified among 736 patients (29.9%). Etiology distribution was different between severe AP and mild AP (P < 0.001). Mortality in the hospital was 1.54%, and there was no difference in each group. Recrudesce of hypertriglyceridemic AP was higher (P < 0.01).
Acute pancreatitis patients increased year by year in Beijing. Gallstones were the predominant etiological factor. There were different etiology proportion of AP according age, sex, and severity.
Abstract The bulk photovoltaic effect (BPVE) in non-centrosymmetric materials has attracted significant attention in recent years due to its potential to surpass the Shockley-Queisser limit. Although ...these materials are strictly constrained by symmetry, progress has been made in artificially reducing symmetry to stimulate BPVE in wider systems. However, the complexity of these techniques has hindered their practical implementation. In this study, we demonstrate a large intrinsic photocurrent response in centrosymmetric topological insulator Ag 2 Te, attributed to the surface photogalvanic effect (SPGE), which is induced by symmetry reduction of the surface. Through diverse spatially-resolved measurements on specially designed devices, we directly observe that SPGE in Ag 2 Te arises from the difference between two opposite photocurrent flows generated from the top and bottom surfaces. Acting as an efficient SPGE material, Ag 2 Te demonstrates robust performance across a wide spectral range from visible to mid-infrared, making it promising for applications in solar cells and mid-infrared detectors. More importantly, SPGE generated on low-symmetric surfaces can potentially be found in various systems, thereby inspiring a broader range of choices for photovoltaic materials.
Porous design of SiC composites with lightweight, high strength and low thermal conductivity can be obtained by constructing porous silicon carbide nanowires（SiCNWs） network and controlling chemical ...vapor infiltration（CVI） process. The SiCNWs network with an optimized volume fraction（15.6%） and uniform pore structure was prepared by mixing SiCNWs and polyvinyl alcohol（PVA） firstly. SiCNWs reinforced porous SiC ceramic matrix composite（SiCNWs/SiC） with a small uniform pore can be obtained by controlling the CVI parameters. The morphology of the grown SiC matrix, from the spherical particles to the hexagonal pyramid particles, can be influenced by the CVI parameters, such as temperature and reactive gas concentration. The strength of the SiCNWs/SiC ceramic matrix composites reaches（194.3±21.3） MPa with a porosity of 38.9% and thermal conductivity of（1.9± 0.1） W/（m·K）, which shows the toughening effect and low thermal conductivity design.
The objective of this experiment was to investigate the effect of lactic acid bacteria (LAB) and cellulase (CE) on the fermentation quality, rumen degradation rate and bacterial community of mixed ...silage of soybean residue (SR) and corn stover (CS). The experiment adopted a single-factor experimental design. Four treatment groups were set up: the control group (CON), lactic acid bacteria treatment group (LAB), cellulase treatment group (CE) and lactic acid bacteria + cellulase treatment group (LAB + CE). Among them, the amount of added LAB was 1 × 10
CFU/g, and the amount of added CE was 100 U/g. After 56 days of mixed silage, samples were taken and analyzed, and the chemical composition, fermentation quality, rumen degradation rate and microbial diversity were determined. The results showed that the pH of each treatment group was significantly (
< 0.05) lower than that of CON, while the lactic acid and ammoniacal nitrogen contents of each treatment group were significantly higher than that of CON, with the highest contents in the LAB + CE group. The contents of DNFom (Ash-free NDF), ADFom (Ash-free ADF) and DM in the LAB + CE group were significantly lower than those in the CON group, while the content of crude protein (CP) was significantly higher than that in the CON group. The in situ effective degradation rates of DM (ISDMD), DNF (ISNDFD) and CP (ISCPD) were all significantly (
< 0.05) higher in each treatment group than in the control group. The results of principal component analysis showed that the bacterial composition of the LAB, CE and LAB + CE groups was significantly different from that of the CON group (
< 0.05). Bacterial genus level analysis showed that the content of lactic acid bacteria was significantly higher in the LAB + CE group than in the other treatment groups (
< 0.05), while the content of undesirable bacteria was significantly lower than in the other treatment groups. The results showed that the addition of Lactobacillus and/or cellulase in mixed silage of SR and CS could effectively improve the quality of mixed silage fermentation, rumen degradation rate and microbial diversity, with better results when Lactobacillus and cellulase were added together, which provides new ideas for better application of SR and CS in dairy production.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Fungi of the genus
Aspergillus
are ubiquitously distributed in nature, and some cause invasive aspergillosis (IA) infections in immunosuppressed individuals and contamination in agricultural ...products. Because microscopic observation and molecular detection of
Aspergillus
species represent the most operator-dependent and time-intensive activities, automated and cost-effective approaches are needed. To address this challenge, a deep convolutional neural network (CNN) was used to investigate the ability to classify various
Aspergillus
species. Using a dissecting microscopy (DM)/stereomicroscopy platform, colonies on plates were scanned with a 35× objective, generating images of sufficient resolution for classification. A total of 8,995 original colony images from seven
Aspergillus
species cultured in enrichment medium were gathered and autocut to generate 17,142 image crops as training and test datasets containing the typical representative morphology of conidiophores or colonies of each strain. Encouragingly, the Xception model exhibited a classification accuracy of 99.8% on the training image set. After training, our CNN model achieved a classification accuracy of 99.7% on the test image set. Based on the Xception performance during training and testing, this classification algorithm was further applied to recognize and validate a new set of raw images of these strains, showing a detection accuracy of 98.2%. Thus, our study demonstrated a novel concept for an artificial-intelligence-based and cost-effective detection methodology for
Aspergillus
organisms, which also has the potential to improve the public’s understanding of the fungal kingdom.
The objectives of this experiment were to investigate the effects of
-carbamylglutamate (NCG) on growth and slaughter performance, meat quality, nitrogen utilization, plasma antioxidant and amino ...acids of Holstein bulls. In this case, 24 Holstein bulls (490 ± 29.0 kg of body weights and 540 ± 6.1 d of age) were blocked by body weights and age and randomly assigned to 1 of 4 groups: (1) CON group: bulls were fed the control diet, (2) CON + NCG group: bulls were fed the control diet with 40 mg/kg BW NCG, (3) Urea group: bulls were fed the urea diet, and (4) Urea + NCG group: bulls were fed the urea diet with 40 mg/kg BW NCG. Feeding NCG significantly improved ADG, FCR, DM and CP digestibility, carcass weight, slaughter weight, DOP, eye muscle area, shear force (
= 0.001) and reduced L* of color, drip loss and cooking loss. Concurrently, feeding the urea diet induced a decreased ADG, carcass weight and slaughter weight, DOP, eye muscle area and shear force. NCG decreased contents of fecal N and urinary N, plasma urea in bulls and ammonia but increased N retention and utilization, plasma NO, plasma Arg, Leu, Ile and Tyr. On the other hand, feeding the urea diet increased urinary N, plasma urea and ammonia. Thus the study efficiently demonstrates that beef benefited from being fed a NCG product in the urea diet by enhancing its growth and slaughter performance, meat quality, nitrogen metabolism and plasma amino acids.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Superconducting magnetic energy storage‐battery hybrid energy storage system (HESS) has a broad application prospect in balancing direct current (DC) power grid voltage due to its fast dynamic ...response ability under low‐frequency/high‐frequency disturbances. Model‐predictive‐control (MPC) with characteristics such as high sampling rate and wide applicability could be applied to HESS. However, considering that the relevant circuit parameters would change with ambient temperature, interference and ageing, the effect of MPC may deteriorate inevitably. This article proposes an improved MPC strategy for SMES‐Battery HESS, taking moth‐flame‐optimisation (MFO) algorithm to calculate the circuit parameters in real time. The actual parameters are updated by MFO and then sent to model predictive controller to minimise the model mismatches. The advantages of high accuracy and fast convergence speed is verified by comparison with grey wolf optimisation and particle swarm optimisation. The simulation shows that by taking the proposed scheme, DC bus voltage are more stable and the superconducting magnetic energy storage can maintain more than 95% capacity utilisation and avoid over‐discharge even if the model parameters are inconsistent with the actual ones under circumstances of alternating current grid fault and fluctuation of new energy output.
Model predictive control (MPC) is an algorithm with excellent dynamic performance, which may be applied in SMES‐Battery HESS. This paper proposes an improved MPC strategy combined with moth‐flame optimisation (MFO) algorithm to solve the problem of mismatches between actual and model parameters. The improvements are invalidated by simulation under several conditions.
To solve the problem of the real-time path-planning of autonomous vehicles for obstacle avoidance on structured roads, a path-planning approach based on the B-spline algorithm is proposed in this ...paper. Firstly, the mechanism of driver path planning is analyzed, and a dynamic risk-identification model based on the support vector machine is proposed. It combines the driver’s risk perception characteristics and a risk model. Then, the B-spline algorithm model is improved based on the risk-identification model. Furthermore, road features, road constraints and dynamic constraints are considered to further optimize the planning algorithm. To verify the path-planning approach proposed in this paper, a co-simulation experiment based on CarSim/Simulink is conducted. Results show that the improved algorithm is effective in static and dynamic obstacles avoidance. The algorithm can generate collision-free obstacle avoidance paths, and the paths meet the real-time requirements and dynamic constraints of obstacle avoidance scenarios. In addition, the proposed algorithm optimizes the path according to the driver’s operating characteristics, which can further improve the safety and comfort of autonomous vehicles.
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