With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of ...low efficiency and poor accuracy, when handling big data. In this study, the research object was the asynchronous motor in the drivetrain diagnostics simulator system. The vibration signals of different fault motors were collected. The raw signal was pretreated using short time Fourier transform （STFT） to obtain the corresponding time-frequency map. Then, the feature of the time-frequency map was adap- tively extracted by using a convolutional neural network （CNN）. The effects of the pretreatment method, and the hyper parameters of network diagnostic accuracy, were investigated experimentally. The experimental results showed that the influence of the preprocessing method is small, and that the batch-size is the main factor affecting accuracy and training efficiency. By investigating feature visualization, it was shown that, in the case of big data, the extracted CNN features can represent complex mapping relationships between signal and health status, and can also overcome the prior knowledge and engineering experience requirement for feature extraction, which is used by tra- ditional diagnosis methods. This paper proposes a new method, based on STFT and CNN, which can complete motor fault diagnosis tasks more intelligently and accurately.
Vertical cavity surface-emitting lasers (VCSELs) have made indispensable contributions to the development of modern optoelectronic technologies. However, arbitrary beam shaping of VCSELs within a ...compact system has remained inaccessible until now. The emerging ultra-thin flat optical structures, namely metasurfaces, offer a powerful technique to manipulate electromagnetic fields with subwavelength spatial resolution. Here, we show that the monolithic integration of dielectric metasurfaces with VCSELs enables remarkable arbitrary control of the laser beam profiles, including self-collimation, Bessel and Vortex lasers, with high efficiency. Such wafer-level integration of metasurface through VCSEL-compatible technology simplifies the assembling process and preserves the high performance of the VCSELs. We envision that our approach can be implemented in various wide-field applications, such as optical fibre communications, laser printing, smartphones, optical sensing, face recognition, directional displays and ultra-compact light detection and ranging (LiDAR).
•We assessed the economic impacts of renewable energy (RE) development in China.•Using a CGE model with novel improvement in investment behavior of power sector.•Large-scale RE development by 2050 ...would not incur a significant macroeconomic cost.•Developing RE benefits the upstream industry and have environmental cobenefits.
This study assesses the economic impacts and environmental co-benefits of large-scale development of renewable energy (RE) in China toward 2050 using a dynamic computable general equilibrium (CGE) model with distinguished improvements in the power sector. Two scenarios are constructed: a reference scenario assuming conventional development of RE and an REmax scenario assuming large-scale RE development by tapping China’s RE potential. The results show that large-scale RE development would not incur a significant macroeconomic cost. On the contrary, it would have significant green growth effects that benefit the growth of upstream industries, reshape the energy structure, and bring substantial environmental co-benefits. If the share of RE reaches 56% in the total primary energy in 2050, then non-fossil power sectors will become a mainstay industry with value added accounting for 3.4% of the GDP, a share comparable to other sectors such as agriculture (2.5%), iron and steel (3.3%), and construction (2.1%). In RE max scenario, the large scale RE development will stimulate the output worth of $1.18 trillion from other RE related upstream industries and create 4.12 million jobs in 2050. In addition to economic benefits, it could substantially reduce the emissions of CO2 and air pollutants such as NOx, SO2.
Zika virus (ZIKV) has evolved into a global health threat because of its unexpected causal link to microcephaly. Phylogenetic analysis reveals that contemporary epidemic strains have accumulated ...multiple substitutions from their Asian ancestor. Here we show that a single serine-to-asparagine substitution Ser139→Asn139 (S139N) in the viral polyprotein substantially increased ZIKV infectivity in both human and mouse neural progenitor cells (NPCs) and led to more severe microcephaly in the mouse fetus, as well as higher mortality rates in neonatal mice. Evolutionary analysis indicates that the S139N substitution arose before the 2013 outbreak in French Polynesia and has been stably maintained during subsequent spread to the Americas. This functional adaption makes ZIKV more virulent to human NPCs, thus contributing to the increased incidence of microcephaly in recent ZIKV epidemics.
The cytosolic sulfotransferases (SULTs) are phase II conjugating enzymes that catalyze the transfer of a sulfonate group from the universal sulfate donor 3'-phosphoadenosine-5'-phosphosulfate to a ...nucleophilic group of their substrates to generate hydrophilic products. Sulfation has a major effect on the chemical and functional homeostasis of substrate chemicals. SULTs are widely expressed in metabolically active or hormonally responsive tissues, including the liver and many extrahepatic tissues. The expression of SULTs exhibits isoform-, tissue-, sex-, and development-specific regulations. SULTs display a broad range of substrates including xenobiotics and endobiotics. The expression of SULTs has been shown to be transcriptionally regulated by members of the nuclear receptor superfamily, such as the peroxisome proliferator-activated receptors, pregnane X receptor, constitutive androstane receptor, vitamin D receptor, liver X receptors, farnesoid X receptor, retinoid-related orphan receptors, estrogen-related receptors, and hepatocyte nuclear factor 4α These nuclear receptors can be activated by numerous xenobiotics and endobiotics, such as fatty acids, bile acids, and oxysterols, many of which are substrates of SULTs. Due to their metabolism of xenobiotics and endobiotics, SULTs and their regulations are implicated in the pathogenesis of many diseases. This review is aimed to summarize the central role of major SULTs, including the SULT1 and SULT2 subfamilies, in the pathophysiology of liver and liver-related diseases. SIGNIFICANCE STATEMENT: Sulfotransferases (SULTs) are indispensable in the homeostasis of xenobiotics and endobiotics. Knowing SULTs and their regulations are implicated in human diseases, it is hoped that genetic or pharmacological manipulations of the expression and/or activity of SULTs can be used to affect the clinical outcome of diseases.The cytosolic sulfotransferases (SULTs) are phase II conjugating enzymes that catalyze the transfer of a sulfonate group from the universal sulfate donor 3'-phosphoadenosine-5'-phosphosulfate to a nucleophilic group of their substrates to generate hydrophilic products. Sulfation has a major effect on the chemical and functional homeostasis of substrate chemicals. SULTs are widely expressed in metabolically active or hormonally responsive tissues, including the liver and many extrahepatic tissues. The expression of SULTs exhibits isoform-, tissue-, sex-, and development-specific regulations. SULTs display a broad range of substrates including xenobiotics and endobiotics. The expression of SULTs has been shown to be transcriptionally regulated by members of the nuclear receptor superfamily, such as the peroxisome proliferator-activated receptors, pregnane X receptor, constitutive androstane receptor, vitamin D receptor, liver X receptors, farnesoid X receptor, retinoid-related orphan receptors, estrogen-related receptors, and hepatocyte nuclear factor 4α These nuclear receptors can be activated by numerous xenobiotics and endobiotics, such as fatty acids, bile acids, and oxysterols, many of which are substrates of SULTs. Due to their metabolism of xenobiotics and endobiotics, SULTs and their regulations are implicated in the pathogenesis of many diseases. This review is aimed to summarize the central role of major SULTs, including the SULT1 and SULT2 subfamilies, in the pathophysiology of liver and liver-related diseases. SIGNIFICANCE STATEMENT: Sulfotransferases (SULTs) are indispensable in the homeostasis of xenobiotics and endobiotics. Knowing SULTs and their regulations are implicated in human diseases, it is hoped that genetic or pharmacological manipulations of the expression and/or activity of SULTs can be used to affect the clinical outcome of diseases.
Creating atomic defects in nanomaterials is an effective approach to promote the catalytic performance of a catalyst, but the defective catalysts are often prone to mechanical collapse if not ...properly synthesized. The uncontrollably formed defects also make it difficult to systematically investigate their effects on the catalytic performance. Herein, we report an efficient method of ionic reductive complexation extraction (IRCE) to fabricate atomic vacancies in a transition metal based nanomaterial without damaging its nanostructure, turning the otherwise catalytically inactive material to an advanced catalyst towards water oxidation in alkaline electrolyte. Here nickel based layered double hydroxide mixed with Cu(
ii
) is used to demonstrate the concept. With a tunable content and uniform dispersion of Cu(
ii
) on the brucite layer of the LDH, a suitable complexing agent could specifically combine with and remove the target Cu(
ii
), thereby creating the desired vacancies. The resulting vacancy rich TM LDH is found to be an excellent OER electrocatalyst with a low overpotential and small Tafel slope, due to the purposely modulated geometric and electronic structures of the active sites, and the greatly decreased charge transfer resistance.
NiCu LDH with atomic vacancies created
via
a facile IRCE method shows advanced electrocatalytic performance towards water oxidation.
In this letter, we propose a convolutional neural network (CNN) based predictor for reversible data hiding (RDH). Firstly, a new image division strategy is presented, which can divide the cover image ...into four independent parts. Via using it, any pixel in each part can be predicted by all its 8-neighbor pixels to generate the preprocessed images. Then, the preprocessed image is fed into a carefully designed CNN-based prediction model to output the predicted image, which is used to build the prediction-error histogram for RDH. Experimental results demonstrate that a sharply distributed prediction-error histogram (i.e., small prediction errors) can be easily obtained by our proposed CNN-based predictor. Furthermore, combining with the classical prediction-error expansion (PEE) embedding strategy, a series of new RDH algorithms with higher visual quality can be formed in contrast to the state-of-the-art RDH schemes.
This study evaluates the PM2.5 pollution-related health impacts on the national and provincial economy of China using a computable general equilibrium (CGE) model and the latest nonlinear ...exposure–response functions. Results show that the health and economic impacts may be substantial in provinces with a high PM2.5 concentration. In the WoPol scenario without PM2.5 pollution control policy, we estimate that China experiences a 2.00% GDP loss and 25.2 billion USD in health expenditure from PM2.5 pollution in 2030. In contrast, with control policy in the WPol scenario, a control investment of 101.8 billion USD (0.79% of GDP) and a gain of 1.17% of China’s GDP from improving PM2.5 pollution are projected. At the provincial level, GDP loss in 2030 in the WoPol scenario is high in Tianjin (3.08%), Shanghai (2.98%), Henan (2.32%), Beijing (2.75%), and Hebei (2.60%) and the top five provinces with the highest additional health expenditure are Henan, Sichuan, Shandong, Hebei, and Jiangsu. Controlling PM2.5 pollution could bring positive benefits in two-thirds of provinces. Tianjin, Shanghai, Beijing, Henan, Jiangsu, and Hebei experience most benefits from PM2.5 pollution control as a result of a higher PM2.5 pollution and dense population distribution. Conversely, the control investment is higher than GDP gain in some underdeveloped provinces, such as Ningxia, Guizhou, Shanxi, Gansu, and Yunnan.
Logic locking is a technique that has been proposed to thwart IC counterfeiting and overproduction by untrusted foundry. Recently, the security of logic locking is threatened by a new attack called ...SAT attack, which can effectively decipher the correct key of most logic locking techniques. In this paper, we propose a new technique called delay locking to enhance the security of existing logic locking techniques. For delay locking, the key into a locked circuit not only determines its functionality, but also its timing profile. A functionality-correct but timing-incorrect key will result in timing violations and thus making the circuit malfunction.
Neural Trojans Yuntao Liu; Yang Xie; Srivastava, Ankur
2017 IEEE International Conference on Computer Design (ICCD),
2017-Nov.
Conference Proceeding
While neural networks demonstrate stronger capabilities in pattern recognition nowadays, they are also becoming larger and deeper. As a result, the effort needed to train a network also increases ...dramatically. In many cases, it is more practical to use a neural network intellectual property (IP) that an IP vendor has already trained. As we do not know about the training process, there can be security threats in the neural IP: the IP vendor (attacker) may embed hidden malicious functionality, i.e neural Trojans, into the neural IP. We show that this is an effective attack and provide three mitigation techniques: input anomaly detection, re-training, and input preprocessing. All the techniques are proven effective. The input anomaly detection approach is able to detect 99.8% of Trojan triggers although with 12.2% false positive. The re-training approach is able to prevent 94.1% of Trojan triggers from triggering the Trojan although it requires that the neural IP be reconfigurable. In the input preprocessing approach, 90.2% of Trojan triggers are rendered ineffective and no assumption about the neural IP is needed.
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