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Scientific user facilities present a unique set of challenges for image processing due to the large volume of data generated from experiments and simulations. Furthermore, developing and implementing algorithms for real-time processing and analysis while correcting for any artifacts or distortions in images remains a complex task, given the computational requirements of the processing algorithms. In a collaborative effort across multiple Department of Energy national laboratories, the MLExchange project is focused on addressing these challenges. MLExchange is a Machine Learning framework deploying interactive web interfaces to enhance and accelerate data analysis. The platform allows users to easily upload, visualize, label, and train networks. The resulting models can be deployed on real data while both results and models could be shared with the scientists. The MLExchange web-based application for image segmentation allows for training, testing, and evaluating multiple machine learning models on hand-labeled tomography data. This environment provides users with an intuitive interface for segmenting images using a variety of machine learning algorithms and deep-learning neural networks. Additionally, these tools have the potential to overcome limitations in traditional image segmentation techniques, particularly for complex and low-contrast images.

The Li-S battery is a promising next-generation technology due to its high theoretical energy density (2600 Wh kg-1) and low active material cost. However, poor cycling stability and coulombic efficiency caused by polysulfide dissolution have proven to be major obstacles for a practical Li-S battery implementation. In this work, we develop a novel strategy to suppress polysulfide dissolution using hydrofluoroethers (HFEs) with bi-functional, amphiphlic surfactant-like design: a polar lithiophilic "head" attached to a fluorinated lithiophobic "tail." A unique solvation mechanism is proposed for these solvents whereby dissociated lithium ions are readily coordinated with lithiophilic "head" to induce self-assembly into micelle-like complex structures. Complex formation is verified experimentally by changing the additive structure and concentration using small angle X-ray scattering (SAXS). These HFE-based electrolytes are found to prevent polysulfide dissolution and to have excellent chemical compatibility with lithium metal: Li||Cu stripping/plating tests reveal high coulombic efficiency (>99.5%), modest polarization, and smooth surface morphology of the uniformly deposited lithium. Li-S cells are demonstrated with 1395 mAh g-1 initial capacity and 71.9% retention over 100 cycles at >99.5% efficiency-evidence that the micelle structure of the amphiphilic additives in HFEs can prohibit polysulfide dissolution while enabling facile Li+ transport and anode passivation.

Although used in in vitro culture to boost secondary metabolite production, UV‐B radiation can seriously affect plant growth if not properly dosed. Rosemary callus can be used as an important source of effective ingredients in the food and medicine industry. To balance the positive and negative effects of UV‐B on rosmary callus, this study investigated the effects of melatonin on rosemary callus under UV‐B radiation. The results showed that melatonin improved rosemary callus growth, with fresh weight and dry weight increased by 15.81% and 8.30%, respectively. The addition of 100 μM melatonin increased antioxidant enzyme activity and NO content in rosemary callus. At the same time, melatonin also significantly reduced membrane lipid damage and H2O2 accumulation in rosemary callus under UV‐B stress, with malondialdehyde (MDA) and H2O2 contents reduced by 13.03% and 14.55%, respectively. In addition, melatonin increased the total phenol and rosmarinic acid contents in rosemary callus by 19% and 54%, respectively. Melatonin significantly improved the antioxidant activity of the extracts from rosemary callus. These results suggest that exogenous melatonin can alleviate the adverse effects of UV‐B stress on rosemary callus by promoting NO accumulation while further enhancing phenolic accumulation and biological activity. [ABSTRACT FROM AUTHOR]

To achieve CFD numerical simulation of the intake difference between cylinders in the two- stroke ignition intake pipe EFI kerosene engine, Fluent builds a one-dimensional simulation model and a three-dimensional simulation model of the prototype by GT-power. By setting up the crankcase agitation area and the cylinder scavenging area, this paper analyzes the gas flow process in the flow field of the two parts. The results show the fresh charge and kerosene mass entering the left cylinder scavenging channel reach 102.27 mg and 16.59 mg respectively whereas the fresh charge and kerosene mass entering the right cylinder scavenging channel stand at 107.03 mg and 21.01 mg respectively. The unevenness of crankcase distribution is 2.27%, of air intake of the whole machine is 1.48% while the diiference of cylinder scavenging is 1.6%. In conclusion, the crankshaft agitation causes larger mixture mass and concentration into the right cylinder and therefore the uneven distribution of the crankcase is largely responsible for affecting the uneven intake of the whole machine. It is also found that the smaller-sized injection particles not only improve the scavenging efficiency, but also optimize the diiference between the two cylinders. [ABSTRACT FROM AUTHOR]

China experiences severe particulate matter pollution associated with rapid economic growth and accelerated urbanization. In this study, concentrations of PM 2.5 (fine particulate matter with an aerodynamic diameter ≤ 2.5 μm) throughout China, and specifically in nine typical urban agglomerations and one economic region, were statistically analyzed using high-resolution ground-based PM 2.5 observations from June 2014 to May 2018. The spatial variation of PM 2.5 was also explored via spatial autocorrelation analysis. High annual mean PM 2.5 concentrations were predominantly concentrated in the Beijing-Tianjin-Hebei, Central Plain, Northern Slope of Tianshan Mountain, and Cheng-Yu urban agglomerations, as well as the Huaihai Economic Region. The proportion of air quality nationwide monitoring sites where annual average PM 2.5 concentrations exceeded the Chinese Ambient Air Quality Standards (CAAQS) Grade II annual standard were 82.8%, 77.1%, and 70.8% in 2015, 2016, and 2017, respectively. Moreover, the frequency of PM 2.5 concentrations meeting the CAAQS Grade I 24-h standard increased in five national-level urban agglomerations, and the average annual PM 2.5 decreased from 2015 to 2017 with a reduction rate of over 20%. The southern Beijing-Tianjin-Hebei agglomeration and surrounding areas revealed the highest PM 2.5 pollution in four seasons. Monthly mean PM 2.5 typically exhibited a characteristic "U" shape. Diurnal mean PM 2.5 concentrations were generally consistent with typical urban agglomerations, with maximum and minimum PM 2.5 values occurring at approximately 08:00-12:00 and 15:00-17:00, respectively, except for the Northern Slope of Tianshan Mountain urban agglomeration (NSTM-UA) (14:00 and 08:00, respectively). A positive spatial autocorrelation of PM 2.5 concentrations was observed in all urban agglomerations (except NSTM-UA); high-high agglomeration centers of PM 2.5 pollution were located far inland with a circular distribution, and low-low agglomeration centers formed at the periphery of the high-high agglomeration region. This study is key for understanding the difference in PM 2.5 concentrations among urban agglomerations and region-oriented air pollution control strategies are highly suggested., (Copyright © 2018 Elsevier B.V. All rights reserved.)