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A deep neural network architecture is proposed based on integrating the convolutional neural network Faster R-CNN with the Feature Pyramid Network module. Based on this approach, an algorithm is developed for detecting and classifying transport media in images along with a corresponding model. The cross-platform medium ML.NET is used to teach the proposed model. Results of comparing the effectiveness of the application of the proposed approach and the convolutional neural networks YOLO v4 and Faster R-CNN are presented. An improved accuracy of detection and localization of different types of vehicles in ultra-high resolution images is demonstrated. Examples of the processing of images of the earth's surface in ultra-high resolution are given, along with corresponding recommendations. [ABSTRACT FROM AUTHOR]

We propose an algorithm for monitoring dynamic objects using integral optical flow, based on constructing a zone of interest for the motion and determining the vector structures, which let us determine the state of moving objects as the nature of the motion changes. Using the algorithm, we can analyze not only the motion of the object as a whole but also its internal changes. Determining the stages for development of the dynamic object using integral optical flow improves the accuracy in predicting the evolution of such objects and improves the quality of solutions to many problems involving automation of monitoring complex motion of dynamic objects. [ABSTRACT FROM AUTHOR]

Endophytes play an important role in the growth and development of the host. However, the study of endophytes is mostly focused on plants and animals, and reports on microorganisms associated with fungus are relatively rare. We studied the microorganisms associated with Tricholoma matsutake fruiting bodies picked from three main T. matsutake-producing areas in Sichuan, China, by both culture-dependent and culture- independent methods. Altogether 13 fungus, 15 yeast and 14 bacterial strains were isolated from the T. matsutake fruiting bodies. The most abundant cultivable fungus, yeast and bacteria isolates were assigned as Fusarium solanis, Cryptococcus sp. and Pseudomonas sp., respectively. Terminal-restriction fragment length polymorphism analysis (T-RFLP) showed that the bacteria in T. matsutake were abundant and diverse. Betaand gamma-proteobacteria, Acidobacteria, Bacteroidetes and Sphingobacterium were found in samples from all collecting sites. Among these bacteria, we may find some strains that can promote the growth of T. matsutake. [ABSTRACT FROM AUTHOR]

Himalayas, are among the areas most vulnerable to global warming, however, little is known about warming impacts on the crops. Therefore, the actual affects of anticipated warming on winter wheat were tested in Tibet, China. During the period 1988-2012, Tibet region has experienced a large increase in daily mean, minimum and maximum temperatures during wheat growing seasons by 0.50, 0.67 and 0.51 oC every ten years, respectively. The de-trended wheat yield increased by 34.4 kg ha-1 year-1 during this period. According to the historical data, 1 °C increase in daily mean temperature could get 370.6 kg ha-1 gain in wheat yield. Similar gains in wheat yield were found in a field warming experiment with an increase of 1.1 °C in daily mean temperature. The field warming caused a significant reduction in the pre-anthesis phase and entire growth period by 14 and 13 days, respectively. The green leaf areas and spike number in the warmed plots were significantly higher than that in non-warmed plots, while the grain number per spike was significantly lower in the former than the later (P<0.05). The main mechanism underlying the positive affects of this moderate warming on wheat yield is through improving plant development and growth during the pre-anthesis phase by mitigating the low temperature limitation. This study suggests that further efforts should be directed towards the improvement on agriculture infrastructure to utilize the positive affects of climatic warming on crop production. [ABSTRACT FROM AUTHOR]

The vibration and buckling behavior of hybrid composite plates with a general state of nonuniform initial stress in thermal environments are investigated. Governing equations including the effects of transverse shear deformation are established using the energy variation method. The initial stress is taken to be a combination of uniaxial extension and pure bending stresses. The temperature distribution in the hybrid plate is assumed to be a combined uniform and linear temperature change in the transverse direction. An example problem on an initially and thermally stressed laminated plate is solved. The effects of various parameters on the thermal induced vibration and stability of hybrid composite plates are studied. The natural frequency and buckling load are found to be sensitive to the thickness ratio of Al to CRFP layers, the state of initial stresses, and temperature rise. [ABSTRACT FROM AUTHOR]

A fast and effective methodology integrating the finite-element and Taguchi methods is presented to determine the optimal design conditions of the injection molding process for short-fiber-reinforced polycarbonate composites. The finite-element-based flow simulation software, M-flow, was employed to simulate the molding process to obtain the fiber orientation distributions required. The Taguchi optimization technique was used to identify the optimal settings of injection molding parameters to maximize the shear layer thickness. The effects of four main parameters - the filling time, melt temperature, mold temperature, and injection speed - on the fiber orientation or the shear layer thickness were investigated and discussed. It is found that the dominant parameter is the filling time. The best levels of the four parameters to acquire the thickest shear layer are also identified. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the quantity of prenatal care as a risk factor for giving birth to low birth weight (LBW), preterm, and small for gestational age (SGA) infants in a sample of women diagnosed with depressive disorder.Method: Our study used a population-based dataset, Taiwan's National Health Insurance Research Database, which we linked to Taiwan's birth certificate registry to identify a total of 5283 new mothers with depressive disorder. Multivariate logistic regression analyses were performed to measure the risk of giving birth to LBW, preterm, and SGA infants, relating to the number of prenatal care visits (10 or more, 8 to 9, and 7 or less) made by mothers with depressive disorder.Results: After adjusting for a woman's age, monthly income, urbanization level of place of residence, geographic location, marital status, substance abuse, arterial hypertension, diabetes, anemia, coronary heart disease, malpresentation, insufficient or excessive fetal growth, placenta or previa abruption, and infant's sex and parity, regression analyses revealed that mothers with a history of depressive disorder who received prenatal care 7 times or less were 4.21 (95% CI 3.34 to 5.32, P < 0.001), 5.37 (95% CI 4.33 to 6.67, P < 0.001), and 2.41 (95% CI 2.03 to 2.86, P < 0.001) times as likely to have LBW, preterm, and SGA babies, respectively, compared with mothers with depressive disorder who received prenatal care visits 10 times or more.Conclusions: Mothers with a history of depressive disorder who make fewer prenatal care visits were at an increased risk of LBW, SGA, and preterm birth, compared with women with a history of depressive disorder who made an adequate number of prenatal visits. [ABSTRACT FROM AUTHOR]