Process Simulation and Optimization of Fluid Catalytic Cracking Unit’s Rich Gas Compression System and Absorption Stabilization System

In a fuel-based refinery, rich gas in the fluid catalytic cracking (FCC) unit is further processed to separate dry gas and refinery products (i.e., stabilized gasoline and liquified petroleum gas). The process is utility-intensive and costly and includes a two-stage compressor, pumps, an absorber, a stripper, a stabilizer, and a re-absorber. The optimization was conducted with respect to the compressor outlet pressure from the gas compression system (GCS) and the flow rate of absorbent and supplementary absorbent from the Absorption-stabilization System (ASS) using the process simulation software Aspen Plus. Compared to the base case of a 725 kt/a rich gas FCC unit, a refinery can save 2.42% of utility costs under optimal operation. Through optimized operation, medium-pressure steam consumption has been reduced by 2.4% compared to the base case, resulting in a significant improvement in total operational cost. The optimization strategy can provide insightful guidance for the practical operation of GCS and ASS.</p

Link Prediction via Sparse Gaussian Graphical Model

Link prediction is an important task in complex network analysis. Traditional link prediction methods are limited by network topology and lack of node property information, which makes predicting links challenging. In this study, we address link prediction using a sparse Gaussian graphical model and demonstrate its theoretical and practical effectiveness. In theory, link prediction is executed by estimating the inverse covariance matrix of samples to overcome information limits. The proposed method was evaluated with four small and four large real-world datasets. The experimental results show that the area under the curve (AUC) value obtained by the proposed method improved by an average of 3% and 12.5% compared to 13 mainstream similarity methods, respectively. This method outperforms the baseline method, and the prediction accuracy is superior to mainstream methods when using only 80% of the training set. The method also provides significantly higher AUC values when using only 60% in Dolphin and Taro datasets. Furthermore, the error rate of the proposed method demonstrates superior performance with all datasets compared to mainstream methods

Deep Learning Methods for Underwater Target Feature Extraction and Recognition

The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network. An underwater target recognition classifier is based on extreme learning machine. Although convolution neural networks can execute both feature extraction and classification, their function mainly relies on a full connection layer, which is trained by gradient descent-based; the generalization ability is limited and suboptimal, so an extreme learning machine (ELM) was used in classification stage. Firstly, CNN learns deep and robust features, followed by the removing of the fully connected layers. Then ELM fed with the CNN features is used as the classifier to conduct an excellent classification. Experiments on the actual data set of civil ships obtained 93.04% recognition rate; compared to the traditional Mel frequency cepstral coefficients and Hilbert-Huang feature, recognition rate greatly improved

Captive breeding of wildlife resources-China's revised supply-side approach to conservation

The conservation and utilization of wild animals in China often raises public concerns. Thus, the Chinese government is increasingly exploring sustainable development of wildlife resources, and has implemented a series of measures, such as the modification of the Wildlife Protection Law (WPL), implementation of captive breeding licenses, an animal marking system, forest certification, and other actions to regulate captive breeding and utilization of wildlife. At the same time, the government tries to meet the Chinese traditional demand for wildlife products. We first introduce wildlife utilization as an internationally accepted conservation tool, and describe market‐based wildlife farming as a legal substitute for wild‐hunted animals. Second, we highlight the importance of wildlife products in Chinese culture and economy and review some successful examples of wildlife utilization in China, showing that the supply‐side approach is a viable alternative to classical conservation. Subsequently, we outline benefits of, and drawbacks to, China's ‘conservation through utilization’ approach, resulting in the implementation of China's new, revised WPL. We discuss merits and shortcomings of China's revised WPL and respond to recent national and international criticism on China's supply‐side approach to conservation. We strongly propose that captive breeding is a feasible approach to China's wildlife conservation–utilization dilemma, and much work is needed to promote the progress, such as legislation restructure, government attention, duties clarification, and so on. © 2019 The Wildlife Society

Mechanisms and Therapeutic Targets of Depression After Intracerebral Hemorrhage

The relationship between depression and intracerebral hemorrhage (ICH) is complicated. One of the most common neuropsychiatric comorbidities of hemorrhagic stroke is Post-ICH depression. Depression, as a neuropsychiatric symptom, also negatively impacts the outcome of ICH by enhancing morbidity, disability, and mortality. However, the ICH outcome can be improved by antidepressants such as the frequently-used selective serotonin reuptake inhibitors. This review therefore presents the mechanisms of post-ICH depression, we grouped the mechanisms according to inflammation, oxidative stress (OS), apoptosis and autophagy, and explained them through their several associated signaling pathways. Inflammation is mainly related to Toll-like receptors (TLRs), the NF-kB mediated signal pathway, the PPAR-γ-dependent pathway, as well as other signaling pathways. OS is associated to nuclear factor erythroid-2 related factor 2 (Nrf2), the PI3K/Akt pathway and the MAPK/P38 pathway. Moreover, autophagy is associated with the mTOR signaling cascade and the NF-kB mediated signal pathway, while apoptosis is correlated with the death receptor-mediated apoptosis pathway, mitochondrial apoptosis pathway, caspase-independent pathways and others. Furthermore, we found that neuroinflammation, oxidative stress, autophagy, and apoptosis experience interactions with one another. Additionally, it may provide several potential therapeutic targets for patients that might suffer from depression after ICH

Coexistence of multiuser entanglement distribution and classical light in optical fiber network with a semiconductor chip

Building communication links among multiple users in a scalable and robust way is a key objective in achieving large-scale quantum networks. In realistic scenario, noise from the coexisting classical light is inevitable and can ultimately disrupt the entanglement. The previous significant fully connected multiuser entanglement distribution experiments are conducted using dark fiber links and there is no explicit relation between the entanglement degradations induced by classical noise and its error rate. Here we fabricate a semiconductor chip with a high figure-of-merit modal overlap to directly generate broadband polarization entanglement. Our monolithic source maintains polarization entanglement fidelity above 96% for 42 nm bandwidth with a brightness of 1.2*10^7 Hz/mW. We perform a continuously working quantum entanglement distribution among three users coexisting with classical light. Under finite-key analysis, we establish secure keys and enable images encryption as well as quantum secret sharing between users. Our work paves the way for practical multiparty quantum communication with integrated photonic architecture compatible with real-world fiber optical communication network

The Role of lncRNAs in the Distant Metastasis of Breast Cancer

Breast cancer (BC) remains the most frequently diagnosed cancer worldwide. Among breast cancer patients, distant metastasis and invasion is the leading cause of BC related death. Recently, long non-coding RNAs (lncRNAs), which used to be considered a genetic byproduct (owing to their unknown biological function), have been reported to be highly implicated in the development and progression of BC. In this review, we produce a summary of the functions and mechanisms of lncRNAs implicated in the different distant metastases of BC. The functions of lncRNAs have been divided into two types: oncogenic type and tumor suppressor. Furthermore, the majority of them exert their roles through the regulation of invasion, migration, epithelial—mesenchymal transition (EMT), and the metastasis process. In the final part, we briefly addressed future research prospects of lncRNAs, especially the testing methods through which to detect lncRNAs in the clinical work, and introduced several different tools with which to detect lncRNAs more conveniently. Although lncRNA research is still in the initial stages, it is a promising prognosticator and a novel therapeutic target for BC metastasis, which requires more research in the future

The Ginger-shaped Asteroid 4179 Toutatis: New Observations from a Successful Flyby of Chang'e-2

On 13 December 2012, Chang'e-2 conducted a successful flyby of the near-Earth asteroid 4179 Toutatis at a closest distance of 770 $\pm$ 120 meters from the asteroid's surface. The highest-resolution image, with a resolution of better than 3 meters, reveals new discoveries on the asteroid, e.g., a giant basin at the big end, a sharply perpendicular silhouette near the neck region, and direct evidence of boulders and regolith, which suggests that Toutatis may bear a rubble-pile structure. Toutatis' maximum physical length and width are (4.75 $\times$ 1.95 km) $\pm$10$\%$, respectively, and the direction of the +$z$ axis is estimated to be (250$\pm$5$^\circ$, 63$\pm$5$^\circ$) with respect to the J2000 ecliptic coordinate system. The bifurcated configuration is indicative of a contact binary origin for Toutatis, which is composed of two lobes (head and body). Chang'e-2 observations have significantly improved our understanding of the characteristics, formation, and evolution of asteroids in general.Comment: 21 pages, 3 figures, 1 tabl

Spatial distribution characteristics of splashing rainfall caused by nappe flow impingement on a plunge pool

Splashing is the main atomization source for a jet impinging on a liquid layer. Increased understanding of splashing rainfall characteristics can help to reduce the hazard of flood discharge atomization in hydraulic engineering. In this study, the spatial distribution of splashing rainfall caused by a nappe flow impinging on a downstream water cushion was experimentally investigated. Effects of the main hydraulic factors of impingement velocity, unit discharge, and water-cushion depth on splashing were investigated. The shape of splashing rainfall contours was approximately elliptical in horizontal planes. Maximum rainfall intensity was in the surrounding impingement region, and rainfall intensity decreased with an increase in the distance between the impingement center point and measurement points. Splashing rainfall intensity increased with increases in impingement velocity and unit discharge, whereas the opposite was observed with an increase in plunge pool depth. A gamma distribution described rainfall intensity distribution in the longitudinal and vertical direction, whereas a Gaussian distribution described intensity in the transverse direction. A series of empirical relations were proposed