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The Al–Mn alloy heat exchanger fin production process includes a brazing treatment at s high temperature of 600 °C, in which coarse grains are preferred for their high resistance to deformation at elevated temperatures by decreasing the grain boundary sliding. In this study, Al-1.57Mn-1.57Zn-0.58Si-0.17Fe alloy foils cold rolled by 81.7% (1.1 mm in thickness) and 96.5% (0.21 mm in thickness) were annealed at 100–550 °C for 1 h to investigate their recrystallization behavior, grain sizes, and precipitates by increasing the annealing temperature, using micro-hardness measurement, electron back-scattered diffraction (EBSD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) techniques. The micro-hardness results showed that the recrystallization finishing temperatures for the two samples were almost the same, 323 ± 2 °C. The EBSD results showed that when the annealing temperature decreased from 550 to 400 °C, the recrystallized grain sizes of the two samples were nearly identical—both increased slightly. Further decreasing the annealing temperature from 400 to 330 °C caused the grain sizes to increase more, with the thinner foil sample having a more significant increase. The SEM and TEM observations showed that the micron-sized primary-phase remained unchanged during the annealing process. The nano-sized secondary phase precipitates formed during the hot-rolling process experienced a coarsening and dissolving process upon annealing. The particle size of the secondary phase increased from 32 nm to 44 nm and the area fraction decreased from 4.2% to 3.8%. The nucleation analysis confirmed that the large primary-phase could act as a nucleation site through particle stimulated nucleation (PSN) mode. The relatively dense secondary phase precipitates with small sizes at lower temperatures could provide higher Zener drag to the grain boundaries, leading to fewer nuclei and thereafter coarser grains. The coarsening of the recrystallized grains in the foils could be implemented through thickness reduction and/or precipitation processes to form densely distributed nano-sized precipitates. [ABSTRACT FROM AUTHOR]

Rail surface defects are potential danger factors for railway systems, and visual inspection of surface defects plays a vital role in rail maintenance. Recently, the methods based on deep learning have been widely used in rail inspection systems, but such systems often face the problem of a lack of defect samples for training deep learning models at start‐up, which is called the cold‐start problem. It is challenging to obtain sufficient defect samples since defects are sparse and even non‐existent for a running railway system. Therefore, a synthetic‐to‐realistic domain adaptation (SRDA) method is proposed for real‐world rail inspection. SRDA adapts synthetic images to look more realistic for reducing the domain gap between synthetic images and realistic rail surface images and obtains translated images that consist of synthetic defect information and realistic rail background. After that, the translated images are used to train a detector for rail inspection of rail surface defects. In order to make the detector more robust to complex backgrounds, SRDA generates images with the same defect‐level semantics but with different texture appearances and makes the detector align these images in the learned feature space. In addition, the synthetic and realistic rail surface defects (SRRSD) dataset containing 20,662 images is built. The experimental results on SRRSD show that SRDA achieves higher detection performance than other established domain adaption methods with 19.0% for F1score${\mathrm{F}}1\ {\mathrm{score}}\ $ and 26.7% for average precision. [ABSTRACT FROM AUTHOR]

The nucleation and growth processes of pure Fe/pure Al intermetallic compounds (IMCs) during heat treatment at 380 °C and 520 °C were observed through in situ scanning electron microscopy (SEM). The size of the IMCs were statistically analyzed using image analysis software. The types and distribution of IMCs were characterized using transmission electron microscopy (TEM) and electron backscattering diffraction (EBSD). The results showed that: at 380 °C, the primary phase of the Fe/Al composite intermetallic compounds was Fe4Al13, formed on the Fe side and habituated with Fe. The IMC was completely transformed from the initial Fe4Al13 to the most stable Fe2Al5, and the Fe2Al5 was the habitus with Fe during the process of holding at 380 °C for 15 min to 60 min. At 380 °C, the initial growth rate of the IMC was controlled by reaction, and the growth rate of the thickness and horizontal dimensions was basically the same as 0.02–0.17 μm/min. When the IMC layer thickness reached 4.5 μm, the growth rate of the thickness changed from reaction control to diffusion control and decreased to 0.007 μm/min. After heat treatment at 520 °C (≤20 min), the growth of IMC was still controlled by the reaction, the horizontal growth rate was 0.53 μm/min, the thickness growth rate was 0.23 μm/min, and the main phase of the IMC was the Fe2Al5 phase at 520 °C/20 min. [ABSTRACT FROM AUTHOR]

Vehicles transporting hazardous material (HAZMAT) pose a severe threat to highway safety, especially in road tunnels. Vehicle reidentification is essential for identifying and warning abnormal states of HAZMAT vehicles in road tunnels. However, there is still no public dataset for benchmarking this task. To this end, this work releases a real-world tunnel HAZMAT vehicle reidentification dataset, VisInt-THV-ReID, including 10,048 images with 865 HAZMAT vehicles and their spatiotemporal information. A method based on multimodal information fusion is proposed to realize vehicle reidentification by fusing vehicle appearance and spatiotemporal information. We design a spatiotemporal similarity determination method for vehicles based on the spatiotemporal law of vehicles in tunnels. Compared with other reidentification methods based on multimodal information fusion, i.e., PROVID, Visual + ST, and Siamese-CNN, experimental results show that our approach significantly improves the vehicle reidentification recognition precision. [ABSTRACT FROM AUTHOR]

In the process of exploitation, transportation and refining of high-sulfur crude oil, a large number of oil sludge (OS) with high sulfur content is produced. Pyrolysis has been proved to be an effective method for OS disposal, but for solid waste with high sulfur content, lots of sulfur-containing gases will be released during thermal disposal. The addition of calcium oxide in pyrolysis process is an economical and effective way to capture sulfur-containing gases. In order to understand the pyrolysis process of OS with CaO, a thermogravimetric analyser was used to conduct pyrolysis experiments of OS with different Ca/S molar ratios (0, 1, 2 and 3) at different heating rates (10°C/min, 20°C/min, 30°C/min and 40°C/min). The results showed that with the increase of CaO addition the derivative thermogravimetric curves showed a gentle trend. In addition, new weight loss peaks were occurred at 700–900°C and after 1100°C, which were the decomposition of calcium carbonate and calcium sulfate, respectively. The kinetic parameters were solved by Friedman, FWO, and Starink methods, and the results were similar, with an average activation energies (E) value of 214 kJ/mol. The change trend of the activation energy was followed by an increase and then a decrease corresponding to the change of energy demand for the reaction. The calculated average values of ΔH, ΔG and ΔS were about 207, 447 and −0.3250 kJ/mol, respectively. When the conversion rate was 0.5, the thermodynamic parameters reached their maximum values. [ABSTRACT FROM AUTHOR]

Flutter design is important for the design of new aircraft types, for which flutter tests are an important verification measure. Atmospheric turbulence excitation is a common form of excitation in flutter flight tests. The modal parameter estimation of the turbulence response is a key aspect to ensure accurate data processing of flutter test results. Atmospheric turbulence excitation acts on the structural system, and the turbulence response thus simultaneously contains both the randomness of the excitation signal and the determinism of the structure system. In view of the turbulence response characteristics, this paper addresses the incoherence of atmospheric turbulence excitation and the orthogonality of the frequency domain from a multichannel response. The turbulence response is used to perform modal parameter identification in the frequency domain. The power spectral density matrix can be calculated from the multichannel turbulence response using the periodogram method. Singular value decomposition is then performed on the power spectral density matrix at each spectral pin based on the orthogonality of the frequency domain. The maximum singular value of each spectral pin forms a curve over the entire frequency band, which is the autopower spectral density function of the system, the system is directly identified at the frequency domain using the polynomial fitting in the frequency domain, and the modal parameters (frequency, damping ratio) are calculated according to the fitted transfer function. This paper verifies the theoretical feasibility of the proposed method using simulation data. The engineering applicability is verified based on the turbulence response from the flutter flight test of a certain aircraft type. [ABSTRACT FROM AUTHOR]

Vehicles carrying hazardous material (hazmat) are severe threats to the safety of highway transportation, and a model that can automatically recognize hazmat markers installed or attached on vehicles is essential for intelligent management systems. However, there is still no public dataset for benchmarking the task of hazmat marker detection. To this end, this paper releases a large-scale vehicle hazmat marker dataset named VisInt-VHM, which includes 10,000 images with a total of 20,023 hazmat markers captured under different environmental conditions from a real-world highway. Meanwhile, we provide an compact hazmat marker detection network named HMD-Net, which utilizes a revised lightweight backbone and is further compressed by channel pruning. As a consequence, the trained-model can be efficiently deployed on a resource-restricted edge device. Experimental results demonstrate that compared with some established methods such as YOLOv3, YOLOv4, their lightweight versions and popular lightweight models, HMD-Net can achieve a better trade-off between the detection accuracy and the inference speed. [ABSTRACT FROM AUTHOR]

Rail surface inspection using visual inspection system is an important part of railway maintenance. However, accurate and efficient identification of possible defects remains challenging. This paper proposes a background-oriented defect inspector (BODI) to improve defect detection by considering specified characteristics of the track during inspection. Reformulating the inspection task in this manner offers a new way to model rail surface images. More specifically, BODI features a random sampling stage to obtain a compact background representation without any prior information. A sufficient number of random selections generates adequate and diverse background statistics, and defect-determination and a fusion of procedures then determine whether current pixel belongs to the background. Finally, a background update mechanism and parallelism ensure real-time applicability. The proposed BODI is evaluated on a working railway line. The experimental results demonstrate that it outperforms state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Computer vision based methods have been widely used in surface defect inspection. However, most of these approaches are task specific, and it is hard to transfer them to similar detection scenarios. This paper proposes an entity sparsity pursuit (ESP) method to identify surface defects. Based on the observation that surface image textures usually form a low-rank structure and the structure can be violated by the presence of rare defects, we formulate the detection task as a low-rank and ESP problem. To alleviate the feature shortage issue existed in industrial gray-scale images, we customize a kind of intuitive features for surface defect inspection. Different from previous work utilizing complicated regularization terms, we resort to mine intrinsic priors of defect images, which can be neatly incorporated into the designed architecture. The proposed model is compact and able to detect surface defects in an unsupervised manner. To fully evaluate the presented method, we conduct a series of experiments using three real-world and one synthetic defect datasets. Experimental results demonstrate that ESP outperforms state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Computer vision systems have attracted much attention in recent years for use in detecting surface defects on rails; however, accurate and efficient recognition of possible defects remains challenging due to the variations shown by defects and also noise. This paper proposes a coarse-to-fine model (CTFM) to identify defects at different scales. The model works on three scales from coarse to fine: subimage level, region level, and pixel level. At the subimage level, the background subtraction model exploits row consistency in the longitudinal direction, and strongly filters the defect-free range, leaving roughly identified subimages within which defects may exist. At the next level, the region extraction model, inspired by visual saliency models, locates definite defect regions using phase-only Fourier transforms. At the finest level, the pixel subtraction model uses pixel consistency to refine the shape of each defect. The proposed method is evaluated using Type-I and Type-II rail surface defect detection data sets and an actual rail line. The experimental results show that CTFM outperforms state-of-the-art methods according to both the pixel-level index and the defect-level index. [ABSTRACT FROM AUTHOR]

There is minimal published research information on optimal fertilizer rates for growing organic herbs in a greenhouse container system under warm climate in south Florida. Our objective was to determine the optimum organic fertilizer rate for container herb production in a greenhouse for basil (Ocimum basilicum), coriander (Coriandrum sativum), and dill (Anethum graveolens) using Perdue certified organic fertilizer (Agri Recycle, 4-2-3, Seaford, DE) (4N-0.85P-0.25K). The organic fertilizer was mixed with potting medium (Fafard, Conrad Fafard, Inc.; Agawam, MA) at four rates: 0, 10.6, 21.1, and 31.7 g of fertilizer per L of potting medium. Results indicated an increase in nitrogen in plant tissue with an increase in fertilizer rate for all herbs and both trials. Based on statistical results from the fresh and dry weights of the herbs, the Purdue fertilizer rate for optimum production should be between 21.1 and 31.7 g of fertilizer per L of potting media. The lower fertilizer rate (21.1 g) is more attractive for overall production since it would result in a lower cost than using the 31.7 g fertilizer rate. This recommendation is based on the fertilizer chosen, the herb, the potting media, and the location of this study. [ABSTRACT FROM AUTHOR]

An accurate information on the amount and location of Land use and land cover (LULC) changes is necessary to develop and implement a sustainable-urban planning.This research investigates the potential of an integrated Multi-Layer Perceptron and Markov Chain Analysis (MLP-MCA) to map and accurately predict the future LULC change scenarios in Lagos Metropolitan Region of Nigeria. Multi-temporal LULC datasets derived from remotely sensed Landsat images from 1984, 2000 and 2015 were used for modeling, validation and prediction. Predicted LULC changes for 2030 and 2050 were performed based on the LULC map of 2015 using MLP-MCA method. The result reveals a significant expansion of built-up areas during the whole study period. Analysis of LULC distribution in Lagos metropolitan region shows that about 50% of urban land expansion happened beyond the administrative boundary of Lagos State during the period of 2000-2015. It is predicted that more than 75% of future urban growth will occur across the border of Lagos State, in the neighbouring Ogun State by 2050. These results imply that a strong and consistent collaboration between different states is crucial to establish an effective regional planning framework and ensure a proper planned growth of the metropolitan region. [ABSTRACT FROM AUTHOR]

Stable carbon and nitrogen isotope values (δ13C and δ15N) were used to evaluate trophic niche overlap between two filter-feeding fishes (known together as bigheaded carp) native to China, silver carp (Hypophthalmichthys molitrix) and bighead carp (Hypophthalmichthys nobilis), and three native filter-feeding fish including bigmouth buffalo (Ictiobus cyprinellus), gizzard shad (Dorosoma cepedianum) and paddlefish (Polyodon spathula) in the lower Missouri River, USA, using the Bayesian Stable Isotope in R statistics. Results indicate that except for bigmouth buffalo, all species displayed similar trophic niche size and trophic diversity. Bigmouth buffalo occupied a small trophic niche and had the greatest trophic overlap with silver carp (93.6%) and bighead carp (94.1%) followed by gizzard shad (91.0%). Paddlefish had a trophic niche which relied on some resources different from those used by other species, and therefore had the lowest trophic overlap with bigheaded carp and other two native fish. The trophic overlap by bigheaded carp onto native fish was typically stronger than the reverse effects from native fish. Average niche overlap between silver carp and native species was as high as 71%, greater than niche overlap between bighead carp and native fish (64%). Our findings indicate that bigheaded carps are a potential threat to a diverse and stable native fish community. [ABSTRACT FROM AUTHOR]

For recycling waste refractory materials in metallurgical industry, porous alumina ceramics were prepared via pore forming agent method from α-Al 2 O 3 powder and slide plate renewable material. Effects of slide plate renewable material (SPRM) on densification, mechanical strength, thermal conductivity, phase composition and microstructure of the porous alumina ceramics were investigated. The results showed that SPRM effectively affected physical and thermal properties of the porous ceramics. With the increase of SPRM, apparent porosity of the ceramic materials firstly increased and then decreased, which brought an opposite change for the bulk density and thermal conductivity values, whereas the bending strength didn’t decrease obviously. The optimum sample A2 with 50 wt% SPRM introducing sintered at 1500 °C obtained the best properties. The water absorption, apparent porosity, bulk density, bending strength and thermal conductivity of the sample were 31.7%, 62.8%, 1.71 g/cm 3 , 47.1 ± 3.7 MPa and 1.73 W/m K, respectively. XRD analysis indicated that a small quantity of silicon carbide and graphite in SPRM have been oxidized to SiO 2 during the firing process, resulting in rising the porous microstructures. SEM micrographs illustrated that rod-like mullite grains combined with plate-like corundum grains to endow the samples with high bending strength. This study was intended to confirm the preparation of porous alumina ceramics with high porosity, good mechanical properties and low thermal conductivity by using SPRM as pore forming additive. [ABSTRACT FROM AUTHOR]

Rail inspection based on visual inspection system (VIS) has drawn much attention recently, since VIS is automatic, fast, nondestructive, and objective. However, visual rail inspection is still a challenge to accurately identify possible defects involving a large variety of visual appearances. This paper presents an automatic visual inspection system to address these difficulties. Rail surface images are first obtained by the system, and then fed into the proposed hierarchical inspection framework containing coarse extractor and fine extractor. Specifically, the coarse extractor handles this defect inspection problem by exploring characteristics of rail background instead of defect itself, and focuses on finding the background modes. The fine extractor, which integrates the longitudinal context information and transversal prior information, is presented to largely reduce the impacts of other irregulars. The proposed method is evaluated on labeled Type-I and Type-II rail surface discrete defects data sets and a practical rail line. The experimental results demonstrate that our method outperforms the state-of-the-art works. [ABSTRACT FROM PUBLISHER]

Effective scene representation is a fundamental part of high-resolution scene classification systems. In this letter, we present a holistic scene representation method, i.e., the two-level feature representation (TLFR) model. The TLFR is composed of low-level and high-level features. Low-level features are obtained by computing the residual error between a local descriptor and its corresponding visual word, and the high-level features are obtained using a proposed selection-constrained sparse coding method. In addition, low-level features in a cluster are integrated by summation pooling, whereas high-level features are fused by maximization pooling. The holistic scene representation is finally generated by incorporating these two levels of features into the bag-of-visual-words framework. Experimental results show that the TLFR model is robust to translation and rotation variations and demonstrates promising performance with the Land Use and Land Cover Database data set and a newly released Singapore data set. [ABSTRACT FROM PUBLISHER]

Introduction: The water-level fluctuation in the Three Gorges Reservoir Region has changed dramatically as a result of the hydroelectric project for flood control and power generation. The riparian seasonal hydrological environment also has changed from summer flooding with winter drought to summer drought with winter flooding. The changes of riparian seed bank and vegetation were investigated to determine the effects of the seasonal flooding on the composition and spatial distribution of riparian soil seed bank and the similarity of seed bank to standing vegetation. Case description: We conducted intensive riparian soil sampling (525 samples) along altitude gradient in the Shanmu River, a tributary of the Yangzi River in the reservoir region of China. Seed bank density, species richness and composition of soil seed bank were examined using the seedling-emergence method. The seasonal hydrological conditions resulted in a decrease in species diversity and an increase in the distribution heterogeneity of the soil seed bank. The soil seed bank was composed of 48 species from 22 families and 40 genera. Most species were annual and perennial herbaceous Polygonaceae, Asteraceae, and Poaceae. Rumex dentatus was the predominant species accounting for 27.0 % of the total seeds. Diversity and composition of the seed bank changed along an altitude gradient and soil depth. Maximum species richness was found in the top soil layer at 165 m and 175 m above sea level. The mean overall seed density of the soil seed bank was 13,475.3 ind m. Density and the number of seeds increased initially and then decreased with increased altitude. Maximum seed density (22,500.2 ind m) was found at 165 m above sea level in the intermediately flooded riverbank, with the seed number accounting for 27.8 % of the total soil seed bank. Average seed density declined significantly with soil depth. The similarity of seed bank to standing vegetation was relatively high. Discussion and Evaluation: The environmental heterogeneity created by the wide range and seasonal flooding led to the changes in biodiversity and seed density along altitude gradient. The seasonal flooding also led to the increase in the similarity of seed bank to standing vegetation as their composition both degraded. Conclusions: The seasonal flooding due to the dam reshape the composition and spatial distribution of riparian soil seed bank and limit the vegetation to a grassland dominated by a few annuals and perennials in the Three Gorges Reservoir Region. [ABSTRACT FROM AUTHOR]

Carbon and nitrogen stable isotopes (δ 13 C and δ 15 N) have been used as indicators for environmental changes in aquatic ecosystems. In this study, δ 13 C and δ 15 N values of select flora taxa were evaluated as indicators of human-induced eutrophication in an Everglades wetland which has been impaired by the source and quality of inflow and the alteration of hydrological pattern. Results showed that δ 13 C of cattail ( Typha domingensis Pers.) increased with the decrease in total phosphorus (TP) concentration. Limited data for sawgrass ( Cladium jamaicenses Crantz) collected at three study sites along the nutrient gradient also show a similar change in δ 13 C. However, δ 13 C of periphyton and bladderwort ( Utricularia sp.) decreased with the decrease in TP concentration. The elevated δ 13 C values of emergent vascular plants (cattail and sawgrass) were likely the results of decreases in stomatal conductance, carboxylation and 13 C fractionation under nutrient stress. This is supported by corresponding decreases in photosynthetic rate of cattail along the decreasing nutrient gradient. In contrast, δ 15 N values of all flora taxa increased with the increase in TP concentration. Findings from this study indicate that δ 13 C of emergent plants is a sensitive indicator for nutrient stress while δ 15 N of major flora species may serve as a robust indicator for wetland eutrophication. [ABSTRACT FROM AUTHOR]

Understanding the carbon sources supporting aquatic consumers in large rivers is essential for the protection of ecological integrity and for wildlife management. The relative importance of terrestrial and algal carbon to the aquatic food webs is still under intensive debate. The Yangtze River is the largest river in China and the third longest river in the world. The completion of the Three Gorges Dam (TGD) in 2003 has significantly altered the hydrological regime of the middle Yangtze River, but its immediate impact on carbon sources supporting the river food web is unknown. In this study, potential production sources from riparian and the main river channel, and selected aquatic consumers (invertebrates and fish) at an upstream constricted-channel site (Luoqi), a midstream estuarine site (Huanghua) and a near dam limnetic site (Maoping) of the TGD were collected for stable isotope (δ13C and δ15N) and IsoSource analyses. Model estimates indicated that terrestrial plants were the dominant carbon sources supporting the consumer taxa at the three study sites. Algal production appeared to play a supplemental role in supporting consumer production. The contribution from C4 plants was more important than that of C3 plants at the upstream site while C3 plants were the more important carbon source to the consumers at the two impacted sites (Huanghua and Maoping), particularly at the midstream site. There was no trend of increase in the contribution of autochthonous production from the upstream to the downstream sites as the flow rate decreased dramatically along the main river channel due to the construction of TGD. Our findings, along with recent studies in rivers and lakes, are contradictory to studies that demonstrate the importance of algal carbon in the aquatic food web. Differences in system geomorphology, hydrology, habitat heterogeneity, and land use may account for these contradictory findings reported in various studies. [ABSTRACT FROM AUTHOR]