Vector Angle Research Articles

Enzymatic Stoichiometry Reveals the Metabolic Limitations of Soil Microbes under Nitrogen and Phosphorus Addition in Chinese Fir Plantations.

Increasing nitrogen (N) deposition alters the availability of soil nutrients and is likely to intensify phosphorus (P) limitations, especially in P-limited tropical and subtropical forests. Soil microorganisms play vital roles in carbon (C) and nutrient cycling, but it is unclear whether and how much N and P imbalances affect the soil's microbial metabolism and mechanisms of nutrient limitations. In this study, a 3-year field experiment of N and P addition (control (CK), 100 kg N ha-1 yr-1 (N), 50 kg P ha-1 yr-1 (P), and NP) was set up to analyze the extracellular enzyme activities and stoichiometry characteristics of the top mineral soils in Chinese fir plantations with different stand ages (7, 20, and 33 years old). The results showed that the enzyme activities associated with the acquisition of C (β-1,4-glucosidase (BG) and β-d-cellobiohydrolase (CBH)) and P (acid phosphatases (APs)) in the N treatment were significantly higher than those in the CK treatment. Moreover, vector analysis revealed that both the vector's length and angle increased in stands of all ages, which indicated that N addition aggravated microbial C and P limitations. The P and NP treatments both significantly decreased the activity of AP and the enzymes' N:P ratio, thereby alleviating microbial P limitations, as revealed by the reduction in the vector's angle. Stand age was found to promote all enzymatic activities but had no obvious effects on the limitation of microbial metabolism with or without added nutrients in the soils under Chinese fir. Available N, Olsen-P, and pH were the main drivers of microbial metabolic limitations related to C nutrients. These results provide useful data for understanding the change in soil microbial activity in response to environmental changes, and suggest that P fertilization should be considered for management to improve productivity and C sequestration in Chinese fir plantation in the context of increased deposition of N.

Online detection of mixed oil interface in multi-product pipeline using near-infrared spectroscopy

To ensure the quality of refined oil products of sequential transportation, it is necessary to monitor and judge the interfaces between pure oils and mixed oil for guiding accurate mixed oil cutting. In this study, near-infrared spectroscopy (NIRS) was used to investigate the change trend of oil concentration and thus judge the interfaces. The methods of standard deviation of continuous spectra, principal component analysis, difference spectrum, and vector angle θ were used to analyze the online oil NIR spectra to detect the interfaces, respectively. The results show that θ of the spectra pretreated by the combination of airPLS and 1st derivative is the best for reflecting the concentration change trend of mixed oil and judging the interfaces. The interface between the forward pure oil and mixed oil can be judged by a fixed θ threshold, and the interface between the rear pure oil and mixed oil can be judged by a fixed first-order derivative value of the five-parameter logistic fitted curve of θ. This method is not affected by the interference and oil composition change of different batches and does not require oil properties and pipeline parameters, thus it has a good prospect in the oil pipeline transportation field.

Data-Driven Control-Oriented Modeling for Response of Fluidic Thrust Vectoring

Response to control input is of significance to the application of real-time active flow control (AFC). In this paper, a novel data-driven framework is used to discover the underlying physics of the dynamic response process of fluidic thrust vectoring (FTV), a typical application of AFC. In the proposed framework, sparse identification of a nonlinear dynamics (SINDy) algorithm is used to identify the governing equations of the flow control responses of sets of noisy measurement data. The clustering algorithm is then used to seek the generalized coefficients of basis functions for different sets of data, which improve the robustness of the model to noisy measurement data. First, a simulated mechanical system is used to validate the effect of the framework. To simplify the modeling, control performance and characteristics are investigated in a detailed manner. Then a dimensionless parameter ΔCp based on the pressure coefficient is found to exhibit a linear relationship with the vector angle under different working conditions. This parameter is introduced in the proposed framework to model the dynamic process of response to control input. The obtained governing equations can describe the dynamic process accurately based on the validation of testing data. The form of the governing equation is rewritten and analyzed based on the control theory, revealing the physics of this process, which is significant to practical AFC implementation.

Effects of 40 Years of Fertilizer Application on the Characteristics of Soil Enzymatic Stoichiometry in Black Soil

Microorganisms produce extracellular enzymes to meet elemental requirements and cope with stoichiometric imbalances of resources. To gain insights into the cycling of C, N, and P, the activities of the C∶N∶P acquisition enzymes have been extensively investigated. To detect the effects of long-term fertilization practices on soil nutrient balance and characteristics of soil enzymatic stoichiometry in black soil, four different fertilization treatments were selected： no fertilization （CK）, nitrogen fertilizer （N）, phosphorus fertilizer （P）, and combination of nitrogen and phosphorus fertilizers （NP）. Soil samples were collected in both April 2021 and April 2022 to determine soil enzyme activities and their stoichiometric characteristics. The results showed that soil acid phosphatase and β-D-glucosidase activities were significantly higher in the N and NP treatments than in CK by 68%-158% and 26%-222%, respectively. Soil β-N-acetylaminoglucosidase activities were significantly higher in the P and NP treatments, with the highest around 75.48 nmol·（g·h）-1 and 106.81 nmol·（g·h）-1, respectively. Two-way ANOVA analysis showed that N and P inputs had a great impact on soil enzyme activities. Redundancy analysis showed that the main factors controlling enzyme activities were soil pH, microbial biomass phosphorus, and soil available P content. It was found that N inputs significantly increased enzyme vector length, which was ranged from 1.32 to 1.52, and the enzyme vector angles were all larger than 45°, suggesting C and P co-limited in the black soils. These findings suggest that 40 years of fertilization have had a great impact on soil enzymes and the related resource use strategy, which provides great implications for assessing soil nutrients balance and soil sustainability.

Detection of pedestrians and vehicles on foggy roads based on improved YOLOv7

Abstract Nowadays, object detection technology plays an indispensable role in the direction of automatic vehicle driving. However, inclement weather, such as fog and haze, poses severe challenges to the ability to understand visual perception and scene understanding of automatic driving technology, making it extremely difficult. Therefore, this paper proposes an improved YOLOv7 algorithm. Firstly, Gaussian blur and Gaussian noise are used to process the original data set, reducing the sensitivity of our model to image information, improving the ability to adapt to changing environments and tasks, and enhancing the generalization performance. Then, using the SIOU loss function, we optimize the algorithm to accelerate the convergence speed while considering the vector angle problem. Add Coordinate Attention integrates accurate position information into the coding network, optimizes the recognition accuracy of the model for a specific position, significantly improves its overall feature extraction ability, and captures key features more accurately, thereby improving the overall performance, capturing key information, and reducing the possibility of missed detection. The introduction of CoordConv into ELAN in the backbone allows for a more sensitive perception of the position of objects during image processing, thus improving the accuracy of its recognition and positioning. The RepGhostNet structure is introduced into the neck to realize the implicit reuse of features. According to the experiments in this paper, our improved YOLOv7 algorithm achieves 87.3% map in the RTTS data set and partial synthetic fog KITTI data set, which improves by 3.9% based on the original model.

The failure mechanism of the Baishi landslide in Beichuan County, Sichuan, China

The Baishi landslide was located in the western part of Beichuan County, Sichuan Province, China. The landslide experienced multiple minor collapses at the front part, accompanying with numerous tensile cracks. To comprehensively grasp the stability conditions and predict the moment of failure of the landslide, deformation monitoring of the landslide has been carried out from the moment that the landslide was reported until it failed. This study analyzed the different phases of landslide deformation and its failure mechanism through the analysis of monitoring data. The result showed that the failure manifests both the retrogressive and advancing features. The landslide was divided into several zones based on the spatial variation of the deformation characteristics. Moreover, the improved tangential angle criterion is applied to categorize the deformation phases of a landslide. Investigating the surface displacement vectors and vector angles of landslides plays a significant role for ascertaining the failure and sliding mechanism. The monitoring results revealed that the front part of the landslide played a key role in the stability of the landslide. Therefore, the monitoring data from this zone were crucial for predicting the moment of complete landslide failure.

Oblique spin injection to graphene via geometry controlled magnetic nanowires

We exploit the geometry of magnetic nanowires, which define 1D contacts to an encapsulated graphene channel, to introduce an out-of-plane component in the polarisation of spin carriers. By design, the magnetic nanowires traverse the angled sides of the 2D material heterostructure. Consequently, the easy axis of the nanowires is inclined, and so the local magnetisation is oblique at the injection point. As a result, when performing non-local spin valve measurements we simultaneously observe both switching and spin precession phenomena, implying the spin population possesses both in-plane and out-of-plane polarisation components. By comparing the relative magnitudes of these components, we quantify the angle of the total spin polarisation vector. The extracted angle is consistent with the angle of the nanowire at the graphene interface, evidencing that the effect is a consequence of the device geometry. This simple method of spin-based vector magnetometry provides an alternative technique to define the spin polarisation in 2D spintronic devices.

Influence of Double-Ducted Serpentine Nozzle Configurations on the Interaction Characteristics between the External and Nozzle Flow of Aircraft

To clarify the influence of the serpentine nozzle configurations on the flow characteristics and aerodynamic performance of aircraft, the flow features and aerodynamic performances of the double-ducted serpentine nozzles with different aspect ratios (AR), length–diameter ratios (LDR) and shielding ratios (SR) are numerically investigated. The results show that the asymmetric nozzle flow occurs due to the curved profile of serpentine nozzles, and a local accelerating effect exists at the S-bend, causing the increase in wall shear stress. The unilateral unsymmetrical expansion of the tail jet in the upward direction interacts with the separated external flow of the afterbody, forming an obvious cross-shock wave and shear layer structure. The surface pressure of the afterbody increases along the external flow direction, and decreases sharply in the separation point of the boundary layer. With the increase in AR and LDR, the local accelerating effect of the nozzle flow weakens, while with the increase in SR, the accelerating effect increases. The total pressure recovery coefficient, flow coefficient and axial thrust coefficient all decrease with the increase in AR, LDR, and SR. The thrust vector angle decreases with the increase in AR but is less affected by LDR and SR.

Response of soil microbial homeostasis to soil ecological stoichiometric balance in a World Natural Heritage area

Soil microbial biomass stoichiometry homeostasis is essential for microorganism survival and ecosystem stability. Despite its importance, research on soil microbial homeostasis in Natural World Heritage Sites (NWHS) is lacking. This study analyzed ecological stoichiometry and microbial homeostasis in surface (0–20 cm) and subsurface (20–40 cm) soils across various vegetation types in Fanjing Mountain, an NWHS in China. The objective was to explore microbial homeostasis in relation to soil ecological stoichiometry and identify key influencing factors. Results indicated that microbial biomass stoichiometry in surface soil is higher than in subsurface soil for 5 vegetation types, mirroring nutrient stoichiometry but contrasting enzyme stoichiometry. Vector length (VL) suggests higher C limitation in subsurface soil for all vegetation types, while vector angle (VA) shows P limitation in surface soil of certain types and N limitation in subsurface soil across all types. Random forest analysis revealed that the microbial carbon-nitrogen ratio (MB C/N) was mainly contributed by C/N (14.11 %), SOC (12.31 %), pH (10.52 %), NH4+-N, SWC, NO3--N in the surface soil, and NO3--N (15.74 %), altitude, SWC, SOC, C/N in the subsurface soil, whereas for the microbial carbon-phosphorus ratio (MB C/P), altitude (12.16 %), SWC (9.86 %), and AP were the main contributing factors in the surface soil, and in the subsurface soil, altitude (10.49 %), C/P, SWC, SOC, and TP. This study provides insights into ecological stoichiometry, homeostasis, and nutrient limitations in Fanjing Mountain, aiding vegetation nutrient balance management in NWHS.

Association between echocardiography-derived haemodynamic force parameters and left ventricular reverse remodelling after cardiac resynchronization therapy.

Cardiac resynchronization therapy (CRT) may induce left ventricular (LV) reverse remodelling (=LV response) in patients with heart failure. Intraventricular pressure gradients can be quantified using echocardiography-derived haemodynamic forces (HDF). The aim was to evaluate the association between baseline HDF and LV response and to compare the change of HDF after CRT between LV responders and LV non-responders. The following HDF parameters were assessed: 1)apical-basal (AB) strength, 2)lateral-septal strength, 3)force vector angle, 4)systolic AB impulse, 5)systolic force vector angle. LV response was defined as a reduction of LV end-systolic volume ≥15% at six months. One hundred ninety-six patients were included (64±11 years, 122(62%) men), 136(69%) showed LV response. On multivariable logistic regression analysis, the force vector angle in the complete heart cycle (OR 1.083 (95%CI 1.018, 1.153), p=0.012) and the systolic force vector angle (OR 1.089 (95%CI 1.021, 1.161), p=0.009), both included in separate models, were independently associated with LV response. Six months after CRT, LV responders had greater AB strength, AB impulse and higher force vector angles, while LV non-responders only showed improvement in the force vector angle in the complete heart cycle. The orientation of HDF at baseline is associated with LV response to CRT. Six months after CRT, the orientation of HDF improves in LV responders and LV non-responders, while the magnitude of AB HDF only improves in LV responders.

Effects of exogenous copper on microbial metabolic function and carbon use efficiency of Panax notoginseng planting soil.

Soil copper (Cu) pollution is a serious environmental risk in the Panax notoginseng planting area. However, the effect of Cu on soil microbial metabolism and nutrient cycling in this area remains unknown. Therefore, Biolog ECO-plate and enzyme stoichiometry methods were utilized in this study to investigate the impact of exogenous Cu (control: 0 mg·kg-1; Cu100: 100 mg·kg-1; Cu400: 400 mg·kg-1; and Cu600: 600 mg·kg-1) on the metabolic function of soil microbial and nutrient limitation in the P. notoginseng soil. The results indicated that Cu100 significantly increased soil organic carbon (SOC), total phosphorus (TP), soil C:N, microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) 9.89%, 15.65%, 17.91%, 61.87%, and 90.56% higher than the control, respectively. Moreover, the carbon source utilization ratio of carbohydrates, amino acids, and amphiphilic compounds of Cu100 also increased by 7.16%, 25.47%, and 84.68%, respectively, compared with the control. The activities of β-1,4-glucosidase, cellobiohyrolase, leucine amino peptidase, β-1,4-N-acetylglucosaminidase, and phosphatase significantly decreased with increasing Cu concentration. Soil enzyme stoichiometry showed that all treatments were limited by nitrogen (vector angle < 45°; 19.045-22.081). Cu600 led to the lowest carbon limitation (1.798) and highest carbon use efficiency (CUE:0.267). The PLS-SEM model also showed that MBC, MBN, MBP, and microbial diversity positively affected carbon and nitrogen limitation (0.654 and 0.424). Soil carbon, nitrogen, phosphorus, stoichiometric ratio, MBC, MBN, and MBP positively affected CUE (0.527 and 0.589). The microbial diversity index significantly negatively affected CUE (-1.490). Multiple linear stepwise regression analyses showed that CUE was mainly influenced by MBC, AP, C:P, and LAP. Thus, P. notoginseng soil can benefit soil microbial carbon and nitrogen limitations at low Cu concentrations. Clarifying the metabolic activity and nutritional status of microorganisms under Cu stress can provide some theoretical basis for realizing China's comprehensive and effective management and control policies for environmental risks from metals by 2035.

Stockpiling turf alters microbial carbon and nitrogen use efficiency on the Tibetan Plateau

Microbial carbon use efficiency (CUE) and nitrogen use efficiency (NUE) are crucial parameters reflecting soil C and N sequestration. Concerns about how artificial activities disturb alpine meadow ecosystem are increasing, but the knowledge of variances in microbial CUE and NUE in response to turf storage remains scarce. Here, we conducted a turf storage experiment on the Tibetan Plateau with two common storage methods, laying turfs method (LT) and stacking turfs method (ST). Plant litter, aboveground and belowground biomass declined considerably in the LT and ST than those in natural meadow. Soil pH and available phosphorus were significantly lower, but soil organic carbon, total nitrogen, dissolved organic carbon, and available nitrogen were substantially higher in stored turfs (both ST and LT) than in natural meadow. These results led to a differentiation in nutrient status among treatments. Vetor model indicated a stronger C limitation (vector length > 0.61) in ST than that in the LT and a shift from N to P limitation (vector angle >55°) in all stored turfs. Microbial CUE was prominently higher in the LT than those in the ST, signifying that microbes allocated more exogenous C to self-growth in the LT. Microbial NUE declined considerably in stored turfs, indicating a great proportion of N used for catabolic process instead of anabolic process. Microbial CUE and NUE were tightly linked to nutrient content and availability, enzymatic stoichiometry, microbial traits and plant biomass. Our results suggest that variations in microbial CUE and NUE were indirectly regulated by soil physicochemical properties via mediating nutrient imbalance and enzymatic stoichiometry in stored turfs.

Pengaruh Sudut Terhadap Besar Resultan Gaya Vektor: Kajian Eksperimental Menggunakan Praktikum Cookbook Laboratory

Vectors are fundamental concepts in mathematics and physics that play a crucial role in various scientific and engineering applications. This study investigates the relationship between the angle and magnitude of the resultant force vector using the Cookbook Laboratory practical approach. The experiment involved combining two forces at different angles and measuring the resultant force. The results indicate a linear relationship between the angle and magnitude of the resultant force, suggesting that as the angle increases, the magnitude of the resultant force also increases. However, this finding contradicts the theoretical prediction of an inverse relationship. This discrepancy is attributed to experimental limitations, particularly parallax error, which may have affected the accuracy of the measurements. Further experiments are recommended to minimize parallax error and obtain more accurate results. A thorough understanding of vector concepts and measurement techniques is essential for comprehending the relationship between angle and resultant force magnitude. Keywords: Angle; Cookbook Laboratory; Resultant Force; Vector.

Adaptive Weighted Data Fusion for Line Structured Light and Photometric Stereo Measurement System.

Line structured light (LSL) measurement systems can obtain high accuracy profiles, but the overall clarity relies greatly on the sampling interval of the scanning process. Photometric stereo (PS), on the other hand, is sensitive to tiny features but has poor geometrical accuracy. Cooperative measurement with these two methods is an effective way to ensure precision and clarity results. In this paper, an LSL-PS cooperative measurement system is brought out. The calibration methods used in the LSL and PS measurement system are given. Then, a data fusion algorithm with adaptive weights is proposed, where an error function that contains the 3D point cloud matching error and normal vector error is established. The weights, which are based on the angles of adjacent normal vectors, are also added to the error function. Afterward, the fusion results can be obtained by solving linear equations. From the experimental results, it can be seen that the proposed method has the advantages of both the LSL and PS methods. The 3D reconstruction results have the merits of high accuracy and high clarity.

Influence of ionospheric resonators on daily dynamics of the first Schumann resonance spectral parameters according to data from a meridional chain of ULF magnetometers

We have experimentally studied the influence of the local ionosphere, namely the ionospheric Alfvén resonator (IAR) and the lower ionospheric resonator at altitudes 80–300 km (sub-IAR) on the amplitude and polarization of the first Schumann resonance. The study is based on spectral analysis of data from simultaneous monitoring of ULF magnetic noise components at a meridional chain of stations: high-latitude stations Barentsburg and Lovozero, mid-latitude observatory NNGU NIRFI (NL, Nizhny Novgorod Region), a low-latitude station in Israel. We have also used monitoring data from the Borok and Crete observatories. At the stations in dark conditions, significant variations were found in the spectrum of the polarization parameter ε at the frequency of the first Schumann resonance (SR). Moreover, these variations had different character at different observatories. Analysis of the daily dynamics of the parameter ε has shown that these variations are associated with the influence of local sub-IAR having different optical thickness and quality factor at these observatories. The influence of sub-IAR on polarization in the SR band was found to depend on the ratio of the boundary frequency fb (the frequency that separates the negative and positive polarization of ULF magnetic noise) to the frequency of the first SR. The IAR influence on the polarization and amplitude of magnetic fields in the frequency band of the first Schumann resonance was discovered only at the NL and Lovozero stations: a high-quality Alfvén resonator in the ionosphere above the NL station could cause the SR frequency band to change and its central frequency to shift. Analysis of low-frequency data from the observatories separated by distances of 400 km has revealed that the influence of local ionospheric resonators can lead to a difference in the amplitude characteristics of the first SR even at such distances. It has also been shown that the influence of the IAR and sub-IAR resonators on the azimuthal angle of the magnetic field vector in the frequency band of the first SR is less noticeable and can generate variations in this parameter by 10°–20°. Numerical calculations performed for the spherical waveguide model made it possible to adequately interpret the features of the daily dynamics of the parameter ε in the frequency range of the first SR.

Влияние ионосферных резонаторов на суточную динамику спектральных параметров первого шумановс-кого резонанса по данным меридиональной сети УНЧ-магнито-метров

We have experimentally studied the influence of the local ionosphere, namely the ionospheric Alfvén resonator (IAR) and the lower ionospheric resonator at altitudes 80–300 km (sub-IAR) on the amplitude and polarization of the first Schumann resonance. The study is based on spectral analysis of data from simultaneous monitoring of ULF magnetic noise components at a meridional chain of stations: high-latitude stations Barentsburg and Lovozero, mid-latitude observatory NNGU NIRFI (NL, Nizhny Novgorod Region), a low-latitude station in Israel. We have also used monitoring data from the Borok and Crete observatories. At the stations in dark conditions, significant variations were found in the spectrum of the polarization parameter ε at the frequency of the first Schumann resonance (SR). Moreover, these variations had different character at different observatories. Analysis of the daily dynamics of the parameter ε has shown that these variations are associated with the influence of local sub-IAR having different optical thickness and quality factor at these observatories. The influence of sub-IAR on polarization in the SR band was found to depend on the ratio of the boundary frequency fb (the frequency that separates the negative and positive polarization of ULF magnetic noise) to the frequency of the first SR. The IAR influence on the polarization and amplitude of magnetic fields in the frequency band of the first Schumann resonance was discovered only at the NL and Lovozero stations: a high-quality Alfvén resonator in the ionosphere above the NL station could cause the SR frequency band to change and its central frequency to shift. Analysis of low-frequency data from the observatories separated by distances of 400 km has revealed that the influence of local ionospheric resonators can lead to a difference in the amplitude characteristics of the first SR even at such distances. It has also been shown that the influence of the IAR and sub-IAR resonators on the azimuthal angle of the magnetic field vector in the frequency band of the first SR is less noticeable and can generate variations in this parameter by 10°–20°. Numerical calculations performed for the spherical waveguide model made it possible to adequately interpret the features of the daily dynamics of the parameter ε in the frequency range of the first SR.

Enzyme stoichiometry reveals microbial nitrogen limitation in stony soils

Resource limitation for soil microorganisms is the crucial factor in nutrient cycling and vegetation development, which are especially important in arid climate. Given that rock fragments strongly impact hydrologic and geochemical processes in arid areas, we hypothesized that microbial resource (C and N) limitation will increase along the rock fragment content (RFC) gradient. We conducted a field experiment in Minjiang river arid valleys with four RFC content (0 %, 25 %, 50 %, and 75 %, V V−1) and four vegetation types (Artemisia vestita, Bauhinia brachycarpa, Sophora davidii, and the soil without plants). Activities of C (β-1,4-glucosidase, BG), N (β-1,4-N-acetyl-glucosaminidase, NAG; L-leucine aminopeptidase, LAP), and P (acid phosphatase, ACP) acquiring enzymes were investigated to assess the limitations by C, N or P. In unplanted soil, the C acquiring enzyme activity decreased by 43 %, but N acquiring enzyme activity increased by 72 % in 75 % RFC than those in rock-free soils (0 % RFC). Increasing RFC reduced C:N and C:P enzymatic ratios, as well as vector length and vector angle (< 45°). Plants increased the activities of C and N acquiring enzymes in soils, as well as C:P and N:P enzyme activities, as well as vector length (by 5.6 %–25 %), but decreased vector angle (by 13 %–21 %). Enzyme stoichiometry was dependent on biotic and abiotic factors, such as soil water content, soil C:N, and total content of phospholipid fatty acids, reflecting microbial biomass content. Increased RFC shifted enzymatic stoichiometry toward lower C but stronger N limitation for microorganisms. Vegetation increased microbial C and N limitation, and impacted the enzymatic activities and stoichiometry depending on shrub functional groups. Consequently, the direct effects of vegetation, nutrient availability and microbial biomass content, as well as indirect effects of soil properties collectively increased microbial resource limitations along the RFC gradient.

Research on Path Planning Algorithm of Driverless Ferry Vehicles Combining Improved A* and DWA.

In view of the fact that the global planning algorithm cannot avoid unknown dynamic and static obstacles and the local planning algorithm easily falls into local optimization in large-scale environments, an improved path planning algorithm based on the integration of A* and DWA is proposed and applied to driverless ferry vehicles. Aiming at the traditional A* algorithm, the vector angle cosine value is introduced to improve the heuristic function to enhance the search direction; the search neighborhood is expanded and optimized to improve the search efficiency; aiming at the problem that there are many turning points in the A* algorithm, a cubic quasi-uniform B-spline curve is used to smooth the path. At the same time, fuzzy control theory is introduced to improve the traditional DWA so that the weight coefficient of the evaluation function can be dynamically adjusted in different environments, effectively avoiding the problem of a local optimal solution. Through the fusion of the improved DWA and the improved A* algorithm, the key nodes in global planning are used as sub-target punctuation to guide the DWA for local planning, so as to ensure that the ferry vehicle avoids obstacles in real time. Simulation results show that the fusion algorithm can avoid unknown dynamic and static obstacles efficiently and in real time on the basis of obtaining the global optimal path. In different environment maps, the effectiveness and adaptability of the fusion algorithm are verified.

Enzyme Activity Stoichiometry Suggests That Fertilization, Especially Nitrogen Fertilization, Alleviates Nutrient Limitation of Soil Microorganisms in Moso Bamboo Forests

Rational application of N fertilizer is essential for maintaining the long-term productivity of Moso bamboo forests. Microbial activity is a crucial indicator of soil quality. Changes in soil nutrient resources due to N addition can lead to microbial nutrient limitations, thereby impeding the maintenance of soil quality. Currently, there is limited research on the effects of N application on microbial nutrient limitations in Moso bamboo forest soils. To examine the changes in extracellular enzyme activity and microbial nutrient limitations in Moso bamboo forest soils following N application, we conducted an N application experiment in northern Guizhou. The findings revealed that the N3 treatment (726 kg·N·hm−2·yr−1) significantly reduced β-glucosidase (BG) activity by 27.61% compared to the control group (no fertilization). The N1 (242 kg·N·hm−2·yr−1), N2 (484 kg·N·hm−2·yr−1), and N3 treatments notably increased the activities of leucine aminopeptidase (LAP) and N-acetyl-β-D-glucosidase (NAG) by 11.45% to 15.79%. Acid phosphatase (ACP) activity remained unaffected by fertilization. N application treatments significantly decreased the C:Ne and C:Pe ratios, while the N:Pe ratio was less influenced by N fertilizer application. Scatter plots and vector characteristics of enzyme activity stoichiometry suggested that microorganisms in the study area were limited by C and N, and N fertilizer application reduced the vector length and increased the vector angle, indicating that N application alleviated the C and N limitation of microorganisms in Moso bamboo forests. Redundancy Analysis (RDA) demonstrated that microbial biomass phosphorus (MBP) was the most critical factor affecting extracellular enzyme activity and stoichiometry. Furthermore, Random Forest Regression analysis identified MBP and the N:Pm ratio as the most significant factors influencing microbial C and N limitation, respectively. The study demonstrated that N application modulates the microbial nutrient acquisition strategy by altering soil nutrient resources in Moso bamboo forests. Formulating fertilizer application strategies based on microbial nutrient requirements is more beneficial for maintaining soil quality and sustainably managing Moso bamboo forests. Additionally, our study offers a theoretical reference for understanding carbon cycling in bamboo forest ecosystems in the context of substantial N inputs.

YOLO-CCS: Vehicle detection algorithm based on coordinate attention mechanism

Accurate and fast vehicle detection is a key factor in the field of intelligent transportation. To solve the problems such as low recognition accuracy, slow detection speed, and poor robustness existing in current vehicle detection algorithms. This paper proposes a vehicle detection algorithm based on YOLOv5 and the coordinate attention mechanism (CA) named YOLO-CCS. YOLO-CCS enables the network to focus on the vehicle itself during the feature extraction process, reduces the loss of feature information and improves the effect of vehicle detection. In our algorithm, we firstly expand YOLOv5s with CA blocks at the location of feature extraction section of network backbone and enhance the extraction capabilities of key features, and suppress the interference of complex backgrounds by embedding position information. Secondly, to enable the network to extract rich feature information and improve the feature fusion capability of the network, we introduce the faster implementation of the Cross Stage Partial (CSP) Bottleneck with 2 convolutions (C2f) in the backbone and neck of the network, which has more residual blocks and skip connections, which provides rich feature semantic information, and heightens the feature extraction capabilities of the network. Thirdly, we integrate the SCYLLA-IOU (SIOU) loss function suitable for YOLO-CCS. So we can leverage the vector angle between the real box and the predicted box to further improve the accuracy of the algorithm and accelerate the convergence of the model. Experimental results show that, compared with the baseline model YOLOv5s, the mAP50 and mAP50−95 of our method increase by 3.2% and 1.7% respectively. Compared with other YOLO based models, mAP50 has increased by approximately 4%. And the detecting speed of YOLO-CCS algorithm reaches 48 FPS, which can meet the real-time requirements of vehicle detection.