Deep Learning-based Marine Target Detection Method with Multiple Feature Fusion

Considering the problem of radar target detection in the sea clutter environment, this paper proposes a deep learning-based marine target detector. The proposed detector increases the differences between the target and clutter by fusing multiple complementary features extracted from different data sources, thereby improving the detection performance for marine targets. Specifically, the detector uses two feature extraction branches to extract multiple levels of fast-time and range features from the range profiles and the range-Doppler (RD) spectrum, respectively. Subsequently, the local-global feature extraction structure is developed to extract the sequence relations from the slow time or Doppler dimension of the features. Furthermore, the feature fusion block is proposed based on adaptive convolution weight learning to efficiently fuse slow-fast time and RD features. Finally, the detection results are obtained through upsampling and nonlinear mapping to the fused multiple levels of features. Experiments on two public radar databases validated the detection performance of the proposed detector

Soil Moisture Contribution to Winter Wheat Water Consumption from Different Soil Layers under Straw Returning

To study the contribution of moisture from different straw-treated and irrigated soil layers to the water consumption of winter wheat in dry farming, a 2-year straw treatment and regulated deficit irrigation experiment was implemented. The field experiment was carried out with 0% (S0), 1% (S1), and 2% (S2) straw returning amounts, and 75 mm (V3), 60 mm (V2), and 45 mm (V1) irrigation volumes. This experiment involved nine treatments, used to quantitatively analyze the ratio and variation of soil water use from different soil layers via the direct contrast method (DCM) and the multiple linear mixed model (MLMM). The results show the following: (1) The distribution of precipitation isotope compositions displayed a repeated trend of first decreasing and then increasing during the study period. Regression analysis showed that the local meteoric water line (LMWL): δD = 6.37δ18O − 3.77 (R2 = 0.832). (2) With increasing soil depth, the δ18O value decreased gradually, and the maximum δ18O value of the soil water within each growth period was distributed at 10 cm. (3) Under the same irrigation amount, δ 18O increased with increasing straw return at 0–20 cm and decreased with increasing straw return at 20–80 cm. (4) The comparison results of the DCM and MLMM were consistent. During the jointing and flowering stages, 0–30 cm soil water was the main source of water for winter wheat. The contribution of soil water below 30 cm had a decreasing trend from the jointing stage to the flowering stage. The average contribution rates of the 0–30 cm soil layer during the jointing and flowering stages were 23.07% and 23.15%, respectively. These findings have important implications for studying the soil water cycle in the context of farming

The displacement of teeth and stress distribution on periodontal ligament under different upper incisors proclination with clear aligner in cases of extraction: a finite element study

Abstract Objectives To investigate the displacement of dentition and stress distribution on periodontal ligament (PDL) during retraction and intrusion of anterior teeth under different proclination of incisors using clear aligner (CA) in cases involving extraction of the first premolars. Methods Models were constructed, consisting of the maxilla, PDLs, CA and maxillary dentition without first premolars. These models were then imported to finite element analysis (FEA) software. The incisor proclination determined the division of the models into three groups: Small torque (ST) with U1-SN = 100°, Middle torque (MT) with U1-SN = 110°, and High torque (HT) with U1-SN = 120°. Following space closure, a 200 g intrusion force was applied at angles of 60°, 70°, 80°, and 90° to the occlusal plane, respectively. Results CA therapy caused lingual tipping and extrusion of incisors, mesial tipping and intrusion of canines, and mesial tipping of posterior teeth in each group. As the proclination of incisors increased, the incisors presented more extrusion and minor retraction, and the teeth from the canine to the second molar displayed an increased tendency of intrusion. The peak Von Mises equivalent stress (VMES) value successively decreased from the central incisor to the canine and from the second premolar to the second molar, and the VMES of the second molar was the lowest among the three groups. When the angle between the intrusion force and occlusal plane got larger, the incisors exhibited greater intrusion but minor retraction. Conclusions The "roller coaster effect" usually occurred in cases involving premolar extraction with CA, especially in patients with protruded incisors. The force closer to the vertical direction were more effective in achieving incisor intrusion. The stress on PDLs mainly concentrated on the cervix and apex of incisors during the retraction process, indicating a possibility of root resorption

A Five-Hole Pressure Probe Based on Integrated MEMS Fiber-Optic Fabry-Perot Sensors

The five-hole pressure probe based on Micro-Electro-Mechanical Systems (MEMS) technology is designed to meet the needs of engine inlet pressure measurement. The probe, including a pressure-sensitive detection unit and a five-hole probe encapsulation structure, combines the advantages of a five-hole probe with fiber optic sensing. The pressure-sensitive detection unit utilizes silicon-glass anodic bonding to achieve the integrated and batch-producible manufacturing of five pressure-sensitive Fabry–Perot (FP) cavities. The probe structure and parameters of the sensitive unit were optimized based on fluid and mechanical simulations. The non-scanning correlation demodulation technology was applied to extract specific cavity lengths from multiple interference surfaces. The sealing platform was established to analyze the sealing performance of the five-hole probe and the pressure-sensitive detection unit. The testing platform was established to test the pressure response characteristics of the probe. Experimental results indicate that the probe has good sealing performance between different air passages, making it suitable for detecting pressure from multiple directions. The pressure responses are linear within the range of 0–250 kPa, with the average pressure sensitivity of the five sensors ranging from 11.061 to 11.546 nm/kPa. The maximum non-linear error is ≤1.083%

Spatial population distribution dynamics of big cats and ungulates with seasonal and disturbance changes in temperate natural forest

Wildlife conservation and management in human-dominated landscapes are major concerns for wildlife ecologists and managers. The dynamics of human disturbance, combined with seasonal limitations in the availability of nutritious foods, may restrict wildlife population growth and recovery. However, understanding how large mammal species adjust their population distribution in forest habitats with seasonal changes in food and disturbances requires a deeper and more extensive analysis. In this study, we found that three ungulate species, roe deer (Capreolus pygargus), sika deer (Cervus nippon), and wild boar (Sus scrofa), employ robust, conservative, and flexible distribution strategies, respectively, to adapt to the effects of seasonal changes and human disturbances. Moreover, croplands, villages, and grazing have some negative effects on the distribution of roe deer and sika deer, while wild boar can be highly abundant near human land use. Additionally, roe deer, sika deer, and wild boar are also affected by the abundance of shrub species they consume. During the cold season, the populations of the Amur tiger (Panthera tigris altaica) and Amur leopard (P. pardus orientalis) were primarily located near roads and dense forests, respectively. In the warm season, the distribution of both big cats was influenced by prey abundance, and Amur tigers also avoided grazing livestock. Nevertheless, the negative effects of human land use on Amur tigers and wild boars increased during the warm season, which was attributed to more frequent human activities during that time. Consequently, it is crucial to implement season-specific habitat management, particularly by regulating human disturbances during the warm season, in order to promote the recovery and expansion of populations of big cats and ungulates