Search

As an emerging research hotspot in contemporary remote sensing, hyperspectral change detection (HCD) has attracted increasing attention in remote sensing Earth observation, covering land mapping changes and anomaly detection. This is primarily attributable to the unique capacity of hyperspectral imagery (HSI) to amalgamate both the spectral and spatial information in the scene, facilitating a more exhaustive analysis and change detection on the Earth's surface, proving to be successful across diverse domains, such as disaster monitoring and geological surveys. Although numerous HCD algorithms have been developed, most of them face three major challenges: (i) susceptibility to inherent data noise, (ii) inconsistent accuracy of detection, especially when dealing with multi-scale changes, and (iii) extensive hyperparameters and high computational costs. As such, we propose a singular spectrum analysis-driven-lightweight network for HCD, where three crucial components are incorporated to tackle these challenges. Firstly, singular spectrum analysis (SSA) is applied to alleviate the effect of noise. Next, a 2-D self-attention-based spatial–spectral feature-extraction module is employed to effectively handle multi-scale changes. Finally, a residual block-based module is designed to effectively extract the spectral features for efficiency. Comprehensive experiments on three publicly available datasets have fully validated the superiority of the proposed SSA-LHCD model over eight state-of-the-art HCD approaches, including four deep learning models. [ABSTRACT FROM AUTHOR]

Centrifugal granulation technology using a spinning cup opens a potential way to recycle steel slag that is currently difficult to reuse. The objective of this research was to study the flow characteristics of a molten slag–metal mixture that was produced during smelting reduction in molten steel slag, passing over a spinning cup, so as to explore the feasibility of using centrifugal granulation technology to treat the steel slag. This was achieved by developing and implementing a computational fluid dynamics (CFD) model that incorporated free-surface multiphase flow to predict the thickness of the liquid slag film at the edge of the spinning cup (slag film thickness for short), which was an important parameter for estimating the size of the slag particles resulting from centrifugal granulation of the molten slag–metal mixture. The influences of various relevant parameters, including spinning cup diameter, slag feeding rate, cup spinning speed, etc., on the slag film thickness were analyzed. Additionally, hot experiments on centrifugal granulation of a molten slag–metal mixture were conducted to verify the results of the numerical simulations. The experimental results indicated a progressive reduction in the Sauter mean diameter of the slag particles as the metallic iron content in the slag increased. Specifically, when the iron content rose from 5% to 15% at a cup spinning speed of 2500 RPM, the Sauter mean diameter decreased by 13.77%. The numerical simulation results showed that the slag film thickness had a positive relationship to the slag feeding rate but a negative relationship to the spinning cup diameter and the cup spinning speed. Furthermore, the ratio between the mean slag particle diameter and the slag film thickness decreased nearly linearly with the increase in the metallic iron content in slag, with the average ratio being approximately 4.25, and this relationship was useful for estimating the slag particle size from the slag film thickness. Therefore, the present research results can provide theoretical guidance for the industrial application of spinning cup centrifugal granulation technology to effectively treat and recycle steel slags. [ABSTRACT FROM AUTHOR]

A microbial fungicide developed from Bacillus subtilis NCD-2 has been registered for suppressing verticillium wilt in crops in China. Spores are the main ingredient of this fungicide and play a crucial role in suppressing plant disease. Therefore, increasing the number of spores of strain NCD-2 during fermentation is important for reducing the cost of the fungicide. In this study, five kinds of carbon sources were found to promote the metabolism of strain NCD-2 revealed via Biolog Phenotype MicroArray (PM) technology. L-arabinose showed the strongest ability to promote the growth and sporulation of strain NCD-2. L-arabinose increased the bacterial concentration and the sporulation efficiency of strain NCD-2 by 2.04 times and 1.99 times compared with D-glucose, respectively. Moreover, L-arabinose significantly decreased the autolysis of strain NCD-2. Genes associated with arabinose metabolism, sporulation, spore resistance to heat, and spore coat formation were significantly up-regulated, and genes associated with sporulation-delaying protein were significantly down-regulated under L-arabinose treatment. The deletion of msmX, which is involved in arabinose transport in the Bacillus genus, decreased growth and sporulation by 53.71% and 86.46% compared with wild-type strain NCD-2, respectively. Complementing the mutant strain by importing an intact msmX gene restored the strain's growth and sporulation. [ABSTRACT FROM AUTHOR]

Plant disease control has long been a critical issue in agricultural production and relies heavily on the identification of plant diseases, but traditional disease identification requires extensive experience. Most of the existing deep learning-based plant disease classification methods run on high-performance devices to meet the requirements for classification accuracy. However, agricultural applications have strict cost control and cannot be widely promoted. This paper presents a novel method for plant disease classification using a binary neural network with dual attention (DABNN), which can save computational resources and accelerate by using binary neural networks, and introduces a dual-attention mechanism to improve the accuracy of classification. To evaluate the effectiveness of our proposed approach, we conduct experiments on the PlantVillage dataset, which includes a range of diseases. The F 1 s c o r e and A c c u r a c y of our method reach 99.39% and 99.4%, respectively. Meanwhile, compared to AlexNet and VGG16, the C o m p u t a t i o n a l c o m p l e x i t y of our method is reduced by 72.3% and 98.7%, respectively. The P a r a m s s i z e of our algorithm is 5.4% of AlexNet and 2.3% of VGG16. The experimental results show that DABNN can identify various diseases effectively and accurately. [ABSTRACT FROM AUTHOR]

In the final approach stage of rendezvous and docking of a spacecraft, the pose parameters of the target spacecraft need to meet docking or berthing capture conditions. Visible light visual measurement systems are increasingly employed in spacecraft ground tests to extract the geometric features of spacecraft to calculate and verify the accuracy of pose parameters. Most current feature-segmentation algorithms are unable to break through the scale transformation problem of spacecraft movement and the noise interference of multi-layer insulation materials in imaging. To overcome these challenges, we propose a novel feature segmentation algorithm based on the framework of deep convolutional neural networks. Firstly, a full convolution model of the encoding-decoding structure is constructed based on data for the ground test. A feature concatenation module is applied and combined with a network backbone to improve the segmentation performance. Then, a comprehensive loss function is presented and optimized by the pose characteristics of the spacecraft in the approach phase. Furthermore, a specific spacecraft simulation dataset to train and test our segmentation model is built through data augmentation. The experimental results verify that the proposed method achieves accurate segmentation of spacecraft of different scales, suppresses the interference caused by multilayer insulation material, and has strong robustness against motion ambiguity. The pixel accuracy of our proposed method reaches 96.5%, and the mean intersection over union is 93.0%. [ABSTRACT FROM AUTHOR]

Based on the three-dimensional (3D) steady-state CFD numerical simulations conducted previously on an industrial Kalugin top combustion hot blast stove, a two-dimensional (2D) transient CFD numerical model for a single channel (hole) of a column of checker bricks in the regenerator of the same hot stove was established in the present work. The average mass flowrate and temperature of the flue gas flowing into the checker brick holes during the combustion period predicted by the 3D model were used as the inlet boundary conditions of the 2D model. Inside the hole of the checker bricks, processes of fluid flow and heat transfer of the flue gas during the combustion period and those of cold air during the hot-air-supply period were simulated using the 2D model for multiple operation cycles (combustion and hot-air-supply periods) of the hot stove, enabling rapid predictions of hot-air temperature under different operating conditions. The simulation results show that when the fuel gas flowrate and air consumption coefficient during the combustion period are controlled within the range of 80,000–100,000 Nm3/h and 1.02–1.28, respectively, a hot-air temperature in the range from 1273 °C to 1295 °C can be obtained during the hot-air-supply period. Applying this optimized operating condition to the industrial hot stove investigated in this study can achieve significant effects of reducing fuel gas flowrate by 8.6% and increasing hot-air temperature by 32 °C. In addition, a regression analysis on the numerical simulation results and the data measured from the industrial hot stove yields a roughly linear relationship between the dome temperature during the combustion period and the hot-air temperature during the hot-air-supply period, that is, the hot-air temperature would be increased by about 16 °C for every increment of 10 °C in the dome temperature, for instance. Therefore, the influences of the operating parameters on heat transfer characteristics in the regenerator and on hot-air temperature obtained in the present work provide a useful reference for guiding the hot stove operation optimization to achieve significant energy saving and emission reduction through facilitating more efficient combustion to minimize fuel gas consumption in steel plants. [ABSTRACT FROM AUTHOR]

Solutions for enhancing parameter identification effects for multivariate equation-error systems in random interference and parameter coupling conditions are considered in this paper. For the purpose of avoiding the impact of colored noises on parameter identification precision, an appropriate filter is utilized to process the autoregressive moving average noise. Then, the filtered system is transformed into a number of sub-identification models based on system output dimensions. Founded on negative gradient search, a new multivariate filtering algorithm employing a partial coupling approach is proposed, and a conventional gradient algorithm is derived for comparison. Parameter identification for multivariate equation-error systems has a high estimation accuracy and an efficient calculation speed with the application of the partial coupling approach and the data filtering method. Two simulations are performed to reveal the proposed method's effectiveness. [ABSTRACT FROM AUTHOR]

With the rapid development of smart grids and distributed energy sources, the home energy management system (HEMS) is becoming a hot topic of research as a hub for connecting customers and utilities for energy visualization. Accurate forecasting of future short-term residential electricity demand for each major appliance is a key part of the energy management system. This paper aims to explore the current research status of household-level short-term load forecasting, summarize the advantages and disadvantages of various forecasting methods, and provide research ideas for short-term household load forecasting and household energy management. Firstly, the paper analyzes the latest research results and research trends in deep learning load forecasting methods in terms of network models, feature extraction, and adaptive learning; secondly, it points out the importance of combining probabilistic forecasting methods that take into account load uncertainty with deep learning techniques; and further explores the implications and methods for device-level as well as ultra-short-term load forecasting. In addition, the paper also analyzes the importance of short-term household load forecasting for the scheduling of electricity consumption in household energy management systems. Finally, the paper points out the problems in the current research and proposes suggestions for future development of short-term household load forecasting. [ABSTRACT FROM AUTHOR]

Fusarium wilt, caused by Fusarium oxysporum, is one of the most notorious diseases of cash crops. The use of microbial fungicides is an effective measure for controlling Fusarium wilt, and the genus Bacillus is an important resource for the development of microbial fungicides. Fusaric acid (FA) produced by F. oxysporum can inhibit the growth of Bacillus, thus affecting the control efficacy of microbial fungicides. Therefore, screening FA-tolerant biocontrol Bacillus may help to improve the biocontrol effect on Fusarium wilt. In this study, a method for screening biocontrol agents against Fusarium wilt was established based on tolerance to FA and antagonism against F. oxysporum. Three promising biocontrol bacteria, named B31, F68, and 30833, were obtained to successfully control tomato, watermelon, and cucumber Fusarium wilt. Strains B31, F68, and 30833 were identified as B. velezensis by phylogenetic analysis of the 16S rDNA, gyrB, rpoB, and rpoC gene sequences. Coculture assays revealed that strains B31, F68, and 30833 showed increased tolerance to F. oxysporum and its metabolites compared with B. velezensis strain FZB42. Further experiments confirmed that 10 µg/mL FA completely inhibited the growth of strain FZB42, while strains B31, F68, and 30833 maintained normal growth at 20 µg/mL FA and partial growth at 40 µg/mL FA. Compared with strain FZB42, strains B31, F68, and 30833 exhibited significantly greater tolerance to FA. [ABSTRACT FROM AUTHOR]

Bacillus spp. is one kind of the important representative biocontrol agents against plant diseases and promoting plant growth. In this study, the whole genomic sequence of bacterial strain HMB26553 was obtained. A phylogenetic tree based on the genome and ANI (average nucleotide identity), as well as dDDH (digital DNA–DNA hybridization), was constructed, and strain HMB26553 was identified as Bacillus velezensis. Fourteen biosynthetic gene clusters responsible for secondary metabolite were predicted via anti-SMASH, and six secondary metabolites were identified by UHPLC-QTOF-MS/MS (ultra-high-performance liquid chromatography coupled to quadrupole-time-of-flight tandem mass spectrometry). When the phytopathogen Rhizoctonia solani was treated with B. velezensis HMB26553, the mycelial structure changed, ROS (reactive oxygen species) accumulated, and the mitochondrial membrane potential decreased. Characteristics of strain HMB26553 were predicted and confirmed by genomic information and experiments, such as producing IAA, siderophore, extracellular enzymes and biofilm, as well as moving and promoting cotton growth. All these results suggested the mechanisms by which B. velezensis HMB26553 inhibits pathogen growth and promotes cotton growth, which likely provided the potential biocontrol agent to control cotton Rhizoctonia damping-off. [ABSTRACT FROM AUTHOR]

In order to study the behavior of molten blast furnace slag ligament breakup into droplets by centrifugal granulation with a spinning cup, three-dimensional transient CFD model simulations were performed in the present work to study the process of the slag deformation into ligaments upon leaving the spinning cup, which eventually disintegrate into droplets. The formation of molten slag ligaments at the edge of the spinning cup and their disintegration into droplets were numerically revealed so that the behavior and mechanism of the slag ligament breakup into droplets could be investigated. This work specifically examined the influence of cup spinning speed on the diameter and length of the molten slag ligaments around the cup periphery and the diameter of the droplets produced. The simulation results show that, for the same slag flowrate, with the increase in cup spinning speed, the slag film thickness at the cup edge decreases, the number of molten slag ligaments increases, and the diameter of the ligaments decreases, thus reducing the diameter of slag droplets. Moreover, as the number of molten slag ligaments increases as a result of the increased cup spinning speed, the flowrate of a single ligament decreases, so that the ligament disintegrates in a shorter radial distance, that is, the length of the ligament is shortened. In addition, this work also investigated the behavior and mechanism of a single molten slag ligament breakup into droplets. It was found that the process of molten slag ligament breakup into droplets under the action of centrifugal force and surface tension can also be approximately explained by the theory of the Rayleigh disintegration mechanism. [ABSTRACT FROM AUTHOR]

Bacillus subtilis strain NCD-2 is a promising biocontrol agent for soil-borne plant diseases and shows potential for promoting the growth of some crops. The purposes of this study were to analyze the colonization ability of strain NCD-2 in different crops and reveal the plant growth promotion mechanism of strain NCD-2 by rhizosphere microbiome analysis. qRT-PCR was used to determine the populations of strain NCD-2, and microbial communities' structures were analyzed through amplicon sequencing after application of strain NCD-2. Results demonstrated that strain NCD-2 had a good growth promotion effect on tomato, eggplant and pepper, and it was the most abundant in eggplant rhizosphere soil. There were significantly differences in the types of beneficial microorganisms recruited for different crops after application of strain NCD-2. PICRUSt analysis showed that the relative abundances of functional genes for amino acid transport and metabolism, coenzyme transport and metabolism, lipid transport and metabolism, inorganic ion transport and metabolism, and defense mechanisms were enriched in the rhizospheres of pepper and eggplant more than in the rhizospheres of cotton, tomato and maize after application of strain NCD-2. In summary, the colonization ability of strain NCD-2 for five plants was different. There were differences in microbial communities' structure in rhizosphere of different plants after application of strain NCD-2. Based on the results obtained in this study, it was concluded that the growth promoting ability of strain NCD-2 were correlated with its colonization quantity and the microbial species it recruited. [ABSTRACT FROM AUTHOR]

Aiming at the mode of liquid ligament disintegration into droplets in the process of the centrifugal granulation of molten blast furnace slag using a spinning cup, in order to gain an in-depth understanding of the behavior and mechanism of droplet formation by liquid ligament disintegration and to obtain appropriate conditions to control the size of the produced slag granules, a three-dimensional CFD model describing water–air two-phase flow with a free surface was established in this work for simulating the process of a single water ligament breakup into droplets under the action of gravity, surface tension and inertial forces, so as to compare with the process of a molten slag ligament disintegration into droplets due to centrifugal force exerted by the spinning cup. By studying the disintegration behavior and mechanism of a single water ligament, the similar phenomenon of a molten slag ligament disintegration is examined. The numerical simulation results on the breakup of a single water ligament show that the length of the ligament before its disintegration and the diameter of the droplets formed both increase with the increase of the velocity of the ligament initially exiting a capillary nozzle. In addition, an experimental set-up was established in the laboratory to conduct cold physical model simulation experiments on single water or liquid paraffin ligament disintegration. The experimental results are compared with the numerical simulation results so that the reliability of the CFD model is verified. The results of the present study show that, in the centrifugal granulation process of blast furnace slag using a spinning cup operated in the ligament disintegration mode, the breakup of a single molten slag ligament is very similar to that of a single water or liquid paraffin ligament, and both approximately follow the Rayleigh Disintegration Mechanism, which provides a theoretical basis for analyzing the breakup process of the ligaments of different liquids as references for guiding the operation of centrifugal granulation of molten slag. [ABSTRACT FROM AUTHOR]

Microbial treatment of cyanide pollution is an effective, economical, and environmentally friendly method compared with physical or chemical approaches. A cyanide-degrading bacterium was isolated from electroplating sludge and identified as Aerococcus viridans (termed A. viridans T1) through an analysis of the biochemical reaction and 16 S rDNA gene sequence. A. viridans T1 showed a maximum resistance to 550 mg L−1 CN−. The effect of pH and temperature on cyanide degradation and bacterial growth was evaluated. The highest cyanide removal efficiency and bacterial growth occurred at pH 8 and pH7, respectively. The optimum temperature for cyanide degradation and bacterial growth was 34 °C. In addition, the carbon source and nitrogen source for cyanide degradation were optimized. The optimal carbon source and nitrogen source were glycerol and peptone, respectively. The cyanide degradation experiment indicated that A. viridans T1 was able to remove 84.1% of free cyanide at an initial concentration of 200 mg L−1 CN− within 72 h and 86.7% of free cyanide at an initial concentration of 150 mg L−1 CN− within 56 h. To improve the cyanide-degrading efficiency of A. viridans T1, eight process variables were further optimized using a response surface methodology. Three significant variables (soybean meal, corn flour, and L-cysteine) were identified using a Plackett–Burman design, and the variable levels were optimized using a central composite design. The optimal values of soybean meal, corn flour, and L-cysteine were 1.11%, 1.5%, and 1.2%, respectively. Under these optimal conditions, the confirmatory experiments showed that the actual degradation rate was 97.3%, which was similar to the predicted degradation rate of 98.87%. Its strong resistance to cyanide and cyanide-degrading activity may allow A. viridans T1 to be a candidate for the bioremediation of cyanide-contaminated environments. [ABSTRACT FROM AUTHOR]

Simple Summary: Guanine nucleotide-binding protein-like 3-like (GNL3L) is a novel GTP-binding nucleolar protein. In this study, we analyzed the expression, prognosis, and immune roles of GNL3L in pan-cancer from multiple omics analyses. The final results showed that GNL3L is differentially expressed in a variety of cancers, plays a prognostic role, and has good immune value. Moreover, GNL3L may affect the occurrence of cancer through processes such as ribonucleoprotein, ribosomal RNA processing, and cell proliferation. At the same time, we established an esophageal cancer (ESCA) prediction model with strong predictive ability and proved that GNL3L can significantly affect the proliferation ability of esophageal cancer cells through clone formation assays. In conclusion, GNL3L is an important biomarker. Guanine nucleotide-binding protein-like 3-like protein (GNL3L) is a novel, evolutionarily conserved, GTP-binding nucleolar protein. This study aimed to investigate the expression, prognosis, and immune value of GNL3L in pan-cancer from multiple omics analyses. Firstly, the expression and prognostic value of GNL3L in pan-cancer were discussed using the TIMER2 database, the GEPIA database, the cBioportal database, COX regression analysis, and enrichment analysis. The association of GNL3L with tumor mutational burden (TMB), tumor microsatellite instability (MSI), mismatch repair (MMR) genes, and immune cells was then analyzed. Finally, an esophageal cancer (ESCA) prediction model was established, and GNL3L clone formation assays were performed. The final results showed that GNL3L is differentially expressed in the vast majority of cancers, is associated with the prognosis of various cancers, and may affect cancer occurrence through processes such as ribonucleoprotein, ribosomal RNA processing, and cell proliferation. At the same time, it was found that the correlation between GNL3L and TMB, MSI, MMR, and various immune cells is significant. The established ESCA prediction model had a strong predictive ability, and GNL3L could significantly affect the proliferation of esophageal cancer cells. In conclusion, GNL3L may serve as an important prognostic biomarker and play an immunomodulatory role in tumors. [ABSTRACT FROM AUTHOR]

This paper researches the identification problem for the unknown parameters of the multivariate equation-error autoregressive systems. Firstly, the original identification model is decomposed into several sub-identification models according to the number of system outputs. Then, based on the characteristic that the information vector and the parameter vector are common among the sub-identification models, the coupling identification concept is used to propose a partially coupled generalized stochastic gradient algorithm. Furthermore, by expanding the scalar innovation of each subsystem model to the innovation vector, a partially coupled multi-innovation generalized stochastic gradient algorithm is proposed. Finally, the numerical simulations indicate that the proposed algorithms are effective and have good parameter estimation performances. [ABSTRACT FROM AUTHOR]

Global food production faces immense pressure, much of which can be attributed to climate change. A detailed evaluation of the impact of climate change on the yield of staple crops in Kazakhstan, a major food exporter, is required for more scientific planting management. In this study, the Mann–Kendall test and Theil–Sen Median slope were used to determine climate trends and staple food yields over the past 30 years; random forest was used to analyze the importance of monthly climatic factors; states were classified according to climatic factors through systematic clustering method; and lastly, the influence of climate on yield was analyzed using panel regression models. The upward trend in wind speed and potato yield throughout Kazakhstan was apparent. Furthermore, barley and wheat yields had increased in the southeast. We determined that for wheat, frostbite should be prevented after the warmer winters in the high-latitude areas. Except for July–August in the low-latitude areas, irrigation water should be provided in the other growth periods and regions. As similar effects were reported for barley, the same preventive measures would apply. For potatoes, tuber rot, caused by frost or excessive precipitation in May, should be prevented in high-latitude areas; soil dryness should be alleviated during the germination and seedling stages in low-latitude areas; and irrigation and cooling should be maintained during tuber formation and maturation. Furthermore, hot dry air in March and April could damage the crops. [ABSTRACT FROM AUTHOR]

Radio communication is a vital challenge during vehicle reentry into the Earth's atmosphere in practice, because the plasma covering the aerospace vehicle can block the communication as the spacecraft reenters the atmosphere. To investigate the potential of the terahertz wave, the transfer function method is first applied to study the wave propagation behavior in plasma, validated by the numerical and the experimental results. The comparison of all three results shows a decent agreement, with the average absolute difference around 1.1 dB for the power loss between the theoretical and numerical results for 100 GHz and 220 GHz and around 0.8 dB for the power loss between the simulation and measurement for 100 GHz and 220 GHz, which shows the validity of the transfer function method and the great potential of the numerical model for future study. Moreover, the results shows the possibility of the application of the THz wave to deal with the blackout problem. [ABSTRACT FROM AUTHOR]

In the context of sustainable development, agricultural production and environmental protection are inseparable, and environmental quality directly affects regional agricultural production safety. Kazakhstan is the largest food producer and exporter in Central Asia, and the quality of its agricultural environment is of great significance to international food security. This study focuses on the rationality of the entropy weight, factor weight, and CRITIC weight in the agricultural environmental evaluation within the common objective weight method, and comprehensively evaluates the coordination of environmental protection and agricultural production in Kazakhstan. The results show that (1) CRITIC weights are the most stable, followed by factor weights, while entropy weighting is the most unstable; objective weighting methods have their limitations and must be related to actual conditions and subjective experience. (2) The level of environmental protection and the degree of coordination are most problematic near the Aral Sea, followed by the remaining western region; the results reveal that these evaluation indexs are also insufficient at Kostany and Karagandy in the central region; this is caused by historical issues, climate change, natural conditions, and agricultural management patterns. Investment in environmental protection and agricultural production management should be coordinated in a targeted manner. (3) Except for the areas near the Aral Sea, the level of agricultural production in other states is very promising. This research serves as a reference for environmental assessment research, environmental governance investment, and agricultural production management in Kazakhstan. [ABSTRACT FROM AUTHOR]

Bath smelting technologies based on top submerged lance (TSL) injection have been widely used for pyrometallurgical metal production and solid waste treatment. In this work, a two-dimensional CFD simulation model of a pilot-scale 300 kg TSL furnace was established and applied to investigate the slag splashing phenomenon caused by submerged gas injection and combustion, with a special focus on the effect of submerged combustion on bubble formation, splash generation, splash distribution and heat transfer in the top space of the TSL furnace. The slag splash amount and distribution, and the temperature distribution characteristics inside the TSL furnace, especially under the influence of submerged combustion, were predicted, and influences of lance immersion depth and total injection gas flowrate on the splash behavior and heat transfer were investigated. As the lance immersion depth increases, more splashes are generated that distribute more evenly in the furnace top space and consequently heat transfer is enhanced. A larger injection gas flowrate generally increases the splash amount but the effect becomes weak when the injection gas flowrate exceeds a certain level, and there exists an appropriate range in injection gas flowrate for achieving the best heat transfer efficiency in TSL furnace. [ABSTRACT FROM AUTHOR]

In automotive technology, the proper use of thermal insulation materials helps improve the performance and life of internal equipment and reduce maintenance cost. In this study, plasma spraying and flame spraying are used to prepare and coat a new MgO-B2O3-SiO2-Zn powder on the SUS304 substrate. The resulting coating as thermal insulation layer formed a networked microstructure between the substrates to improve the thermal insulation performance of the material. By validation of thermal radiation experiments, the thermal insulation effects of various ceramic powders were compared, the high-temperature and low-temperature thermal insulation materials for about 300 and 100 °C were determined, and the thermal insulation performance of the constructed material coatings was verified by analysis. [ABSTRACT FROM AUTHOR]

The effective cryopreservation of mesenchymal stem cells (MSCs) is indispensable to the operation of basic research and clinical transplantation. The prevalent protocols for MSC cryopreservation utilize dimethyl sulfoxide (DMSO), which is easily permeable and able to protect MSCs from cryo-injuries, as a primary cryoprotectant (CPA). However, its intrinsic toxicity and adverse effects on cell function remain the bottleneck of MSC cryopreservation. In this work, we cryopreserved human umbilical cord mesenchymal stem cells (UCMSCs) using zwitterionic betaine combined with electroporation without any addition of DMSO. Betaine was characterized by excellent compatibility and cryoprotective properties to depress the freezing point of pure water and balance the cellular osmotic stress. Electroporation was introduced to achieve intracellular delivery of betaine, intending to further provide comprehensive cryoprotection on UCMSCs. Compared with DMSO cryopreservation, UCMSCs recovered from the protocol we developed maintained the normal viability and functions and reduced the level of reactive oxygen species (ROS) that are harmful to cell metabolism. Moreover, the in vivo distribution of thawed UCMSCs was consistent with that of fresh cells monitored by a bioluminescence imaging (BLI) system. This work opens a new window of opportunity for DMSO-free MSC cryopreservation using zwitterionic compounds like betaine combined with electroporation. [ABSTRACT FROM AUTHOR]

Simple Summary: Chicken meat has been proved to be a suspected source of extraintestinal pathogenic Escherichia coli (ExPEC), causing several diseases in humans, and bacteria in healthy chickens can contaminate chicken carcasses at the slaughter; however, reports about the prevalence and molecular characteristics of ExPEC in healthy chickens are still rare. In this study, among 926 E. coli isolates from healthy chickens in China, 22 (2.4%) were qualified as ExPEC and these ExPEC isolates were clonally unrelated. A total of six serogroups were identified in this study, with O78 being the most predominant type, and all the six serogroups had been frequently reported in human ExPEC isolates in many countries. All the 22 ExPEC isolates were multidrug-resistant and most isolates carried both blaCTX-M and fosA3 resistance genes. Notably, plasmid-borne colistin resistance gene mcr-1 was identified in six ExPEC isolates, among which two carried additional carbapenemase gene blaNDM, compromising both the efficacies of the two critically important drugs for humans, carbapenems and colistin. These results highlight that healthy chickens can serve as a potential reservoir for multidrug resistant ExPEC isolates, including mcr-1-containing ExPEC. Chicken products and chickens with colibacillosis are often reported to be a suspected source of extraintestinal pathogenic Escherichia coli (ExPEC) causing several diseases in humans. Such pathogens in healthy chickens can also contaminate chicken carcasses at the slaughter and then are transmitted to humans via food supply; however, reports about the ExPEC in healthy chickens are still rare. In this study, we determined the prevalence and characteristics of ExPEC isolates in healthy chickens in China. A total of 926 E. coli isolates from seven layer farms (371 isolates), one white-feather broiler farm (78 isolates) and 17 live poultry markets (477 isolates from yellow-feather broilers) in 10 cities in China, were isolated and analyzed for antibiotic resistance phenotypes and genotypes. The molecular detection of ExPEC among these healthy chicken E. coli isolates was performed by PCRs, and the serogroups and antibiotic resistance characteristics of ExPEC were also analyzed. Pulsed-field gel electrophoresis (PFGE) and Multilocus sequence typing (MLST) were used to analyze the genetic relatedness of these ExPEC isolates. We found that the resistance rate for each of the 15 antimicrobials tested among E. coli from white-feather broilers was significantly higher than that from brown-egg layers and that from yellow-feather broilers in live poultry markets (p < 0.05). A total of 22 of the 926 E. coli isolates (2.4%) from healthy chickens were qualified as ExPEC, and the detection rate (7.7%, 6/78) of ExPEC among white-feather broilers was significantly higher than that (1.6%, 6/371) from brown-egg layers and that (2.1%, 10/477) from yellow-feather broilers (p < 0.05). PFGE and MLST analysis indicated that clonal dissemination of these ExPEC isolates was unlikely. Serogroup O78 was the most predominant type among the six serogroups identified in this study, and all the six serogroups had been frequently reported in human ExPEC isolates in many countries. All the 22 ExPEC isolates were multidrug-resistant (MDR) and the resistance rates to ampicillin (100%) and sulfamethoxazole-trimethoprim (100%) were the highest, followed by tetracycline (95.5%) and doxycycline (90.9%). blaCTX-M was found in 15 of the 22 ExPEC isolates including 10 harboring additional fosfomycin resistance gene fosA3. Notably, plasmid-borne colistin resistance gene mcr-1 was identified in six ExPEC isolates in this study. Worryingly, two ExPEC isolates were found to carry both mcr-1 and blaNDM, compromising both the efficacies of carbapenems and colistin. The presence of ExPEC isolates in healthy chickens, especially those carrying mcr-1 and/or blaNDM, is alarming and will pose a threat to the health of consumers. To our knowledge, this is the first report of mcr-1-positive ExPEC isolates harboring blaNDM from healthy chickens. [ABSTRACT FROM AUTHOR]

The formation and growth kinetics of the reverted austenite during tempering in 13Cr supermartensitic stainless steel were investigated by a combination X-ray diffraction (XRD), transmission electron microscopy (TEM) and electron backscatter diffraction (EBSD) in a scanning electron microscope (SEM). The reverted austenite precipitated at the martensite blocks, sub-blocks, laths and grain boundaries. The growth kinetics was established by Johnson-Mehl-Avrami (JAM) kinetics equation according to the volume fraction of the equilibrium reverted austenite at room temperature. The Avrami exponent value is 0.5, and the activation energy was estimated to be 369 kJ/mol, the kinetic model indicates that the mechanism of reverted austenite is diffusion-controlled and the growth of reverted austenite closely relies on the diffusion of the nickel (Ni) element. The experimental measured orientations of the reverted austenite are in good agreement with the theoretical ones, implying that the reverted austenite has the same orientation with the surrounding martensite, which meets the Kurdjumov–Sachs (K-S) orientation relationship. The orientation relationships minimize the strain energy of the phase transformation by reducing the crystallographic mismatch between phases. [ABSTRACT FROM AUTHOR]

Scandium oxide (Sc2O3) thin films with different numbers of oxygen defects were prepared by ion-beam sputtering under different oxygen flow rates. The results showed that the oxygen defects heavily affected crystal phases, optical properties, laser-induced damage threshold (LIDT) and surface quality of Sc2O3 films. The thin film under 0 standard-state cubic centimeter per minute (sccm) oxygen flow rate had the largest number of oxygen defects, which resulted in the lowest transmittance, LIDT and the worst surface quality. In addition, the refractive index of 0 sccm Sc2O3 film could not be measured in the same way. When the oxygen flow rate was 15 sccm, the Sc2O3 film possessed the best transmittance, refractive index, LIDT and surface roughness due to the lowest number of oxygen defects. This work elucidated the relationship between oxygen defects and properties of Sc2O3 films. Controlling oxygen flow rate was an important step of limiting the number of oxygen defects, which is of great significance for industrial production. [ABSTRACT FROM AUTHOR]

Coastal wetland mapping plays an essential role in monitoring climate change, the hydrological cycle, and water resources. In this study, a novel classification framework based on the gravitational optimized multilayer perceptron classifier and extended multi-attribute profiles (EMAPs) is presented for coastal wetland mapping using Sentinel-2 multispectral instrument (MSI) imagery. In the proposed method, the morphological attribute profiles (APs) are firstly extracted using four attribute filters based on the characteristics of wetlands in each band from Sentinel-2 imagery. These APs form a set of EMAPs which comprehensively represent the irregular wetland objects in multiscale and multilevel. The EMAPs and original spectral features are then classified with a new multilayer perceptron (MLP) classifier whose parameters are optimized by a stability-constrained adaptive alpha for a gravitational search algorithm. The performance of the proposed method was investigated using Sentinel-2 MSI images of two coastal wetlands, i.e., the Jiaozhou Bay and the Yellow River Delta in Shandong province of eastern China. Comparisons with four other classifiers through visual inspection and quantitative evaluation verified the superiority of the proposed method. Furthermore, the effectiveness of different APs in EMAPs were also validated. By combining the developed EMAPs features and novel MLP classifier, complicated wetland types with high within-class variability and low between-class disparity were effectively discriminated. The superior performance of the proposed framework makes it available and preferable for the mapping of complicated coastal wetlands using Sentinel-2 data and other similar optical imagery. [ABSTRACT FROM AUTHOR]

High-definition mapping of 3D lane lines has been widely needed for the highway documentation and intelligent navigation of autonomous systems. A mobile mapping system (MMS) captures both accurate 3D LiDAR point clouds and high-resolution images of lane markings at highway driving speeds, providing an abundant data source for combined lane mapping. This paper aims to map lanes with an MMS. The main contributions of this paper include the following: (1) an intensity correction method was introduced to eliminate the reflectivity inconsistency of road-surface LiDAR points; (2) a self-adaptive thresholding method was developed to extract lane markings from their complicated surroundings; and (3) a LiDAR-guided textural saliency analysis of MMS images was proposed to improve the robustness of lane mapping. The proposed method was tested with a dataset acquired in Wuhan, Hubei, China, which contained straight roads, curved roads, and a roundabout with various pavement markings and a complex roadside environment. The experimental results achieved a recall of 96.4%, a precision of 97.6%, and an F-score of 97.0%, demonstrating that the proposed method has strong mapping ability for various urban roads. [ABSTRACT FROM AUTHOR]

Despite the growth in empirical research on neighborhood environmental characteristics and their influence on children's diets, physical activity, and obesity, much remains to be learned, as few have examined the relationship between neighborhood food availability on dietary behavior in children, specifically. This analysis utilized data from a community-based, cross-sectional sample of children ( n = 199) that was collected in New Orleans, Louisiana, in 2010. This dataset was linked to food environment data to assess the impact of neighborhood food access as well as household and parent factors on children's diets. We observed a negligible impact of the neighborhood food environment on children's diets, except with respect to fast food, with children who had access to fast food within 500 m around their home significantly less likely (OR = 0.35, 95% CI: 0.1, 0.8) to consume vegetables. Key parental and household factors did play a role in diet, including receipt of public assistance and cooking meals at home. Children receiving public assistance were 2.5 times (95% CI: 1.1, 5.4) more likely to consume fruit more than twice per day compared with children not receiving public assistance. Children whose family cooked dinner at home more than 5 times per week had significantly more consumption of fruit (64% vs. 58%) and vegetables (55% vs. 39%), but less soda (27% vs. 43%). Findings highlight the need for future research that focuses on the dynamic and complex relationships between built and social factors in the communities and homes of children that impact their diet in order to develop multilevel prevention approaches that address childhood obesity., Competing Interests: The authors declare no conflict of interest.

Cytomegalovirus (CMV) infection leads to notable morbidity and mortality in immunosuppressed patients. Current antiviral drugs are effective but seriously limited in their long-term use due to their relatively high toxicity. In the present study, we characterized the expression of murine CMV microRNAs (MCMV miRNAs) both in vitro and in vivo. Although 29 miRNAs were detectable during in vitro infection, only 11 miRNAs (classified as Group 1) were detectable during in vivo infection, and as many as 18 viral miRNAs (classified as Group 2) were less detectable (<50% of animals) in both the liver and lungs. In addition, viral miRNA profiles in the blood revealed unstable and reduced expression. We next explored the in vitro effects of viral miRNAs on MCMV replication. The inhibition of Group 1 viral miRNAs had little effect on virus production, but transfected cells overexpressing miR-m01-3-5p, miR-M23-1-5p, miR-M55-1, and miR-m107-1-5p in Group 2 showed statistically lower viral loads than those transfected with control miRNA (29%, 29%, 39%, and 43%, respectively, versus control). Finally, we performed hydrodynamic injection of viral miRNA agomirs and observed lower levels of MCMV recurrence in the livers of animals overexpressing the miR-m01-3-5p or mcmv-miR-M23-1-5p agomirs compared with those of animals transfected with control agomir, confirming the antiviral effects of viral miRNA manipulation in vivo. Therefore, the manipulation of viral miRNA expression shows great therapeutic potential and represents a novel antiviral strategy for the miRNA-based treatment of cytomegalovirus infection., Competing Interests: The authors declare no conflict of interest.

Human cytomegalovirus (HCMV) is a major risk factor in transplantation and AIDS patients, which induces high morbidity and mortality. These patients infected with HCMV experience an imbalance of redox homeostasis that cause accumulation of reactive oxygen species (ROS) at the cellular level. H2O2, the most common reactive oxygen species, is the main byproduct of oxidative metabolism. However, the function of H2O2 on HCMV infection is not yet fully understood and the effect and mechanism of N-acetylcysteine (NAC) on H2O2-stimulated HCMV replication is unclear. We, therefore, examined the effect of NAC on H2O2-induced HCMV production in human foreskin fibroblast cells. In the present study, we found that H2O2 enhanced HCMV lytic replication through promoting major immediate early (MIE) promoter activity and immediate early (IE) gene transcription. Conversely, NAC inhibited H2O2-upregulated viral IE gene expression and viral replication. The suppressive effect of NAC on CMV in an acute CMV-infected mouse model also showed a relationship between antioxidants and viral lytic replication. Intriguingly, the enhancement of HCMV replication via supplementation with H2O2 was accompanied with the activation of the p38 mitogen-activated protein kinase pathway. Similar to NAC, the p38 inhibitor SB203580 inhibited H2O2-induced p38 phosphorylation and HCMV upregulation, while upregulation of inducible ROS was unaffected. These results directly relate HCMV replication to H2O2, suggesting that treatment with antioxidants may be an attractive preventive and therapeutic strategy for HCMV.