•Motive power for development of smart petrochemical factory.•Connotation of smart factory in petrochemical industry.•Technology system of smart factory.•Key technologies of smart factory in ...petrochemical industry.•Guarantee measures for smart factory in petrochemical industry.
Opportunities and challenges in the petrochemical industry and the emergence of massive disruptive technologies have triggered a new revolution that has the power to fundamentally change industrial processes including manufacturing, engineering, materials, supply chains, lifecycle management. Recently, the newly arisen smart factory adopted a disruptive manufacturing methodology and has become a key part of the petrochemical industry. The smart factory, which is different from the original production systems used in the petrochemical industry, needs to assess and position its future research agenda including its definition, intension, framework, and technology. Systems thinking and systems problem solving for the smart factory must be prioritized. Based on an analysis of the driving force for smart factory development, this paper proposes a lifecycle blueprint and consensus-based operating and technology roadmap. The definition and features of a smart factory in the petrochemical industry are presented. Furthermore, a summary of the technical systems and future-proof research field of the smart petrochemical factory from an academic and industrial viewpoint is presented.
Network function virtualization (NFV) brings great conveniences and benefits for the enterprises to outsource their network functions to the cloud datacenter. In this paper, we address the virtual ...network function (VNF) placement problem in cloud datacenter considering users' service function chain requests (SFCRs). To optimize the resource utilization, we take two less-considered factors into consideration, which are the time-varying workloads, and the basic resource consumptions (BRCs) when instantiating VNFs in physical machines (PMs). Then the VNF placement problem is formulated as an integer linear programming (ILP) model with the aim of minimizing the number of used PMs. Afterwards, a Two-StAge heurisTic solution (T-SAT) is designed to solve the ILP. T-SAT consists of a correlation-based greedy algorithm for SFCR mapping (first stage) and a further adjustment algorithm for virtual network function requests (VNFRs) in each SFCR (second stage). Finally, we evaluate T-SAT with the artificial data we compose with Gaussian function and trace data derived from Google's datacenters. The simulation results demonstrate that the number of used PMs derived by T-SAT is near to the optimal results and much smaller than the benchmarks. Besides, it improves the network resource utilization significantly.
Network function virtualization (NFV) and edge computing (EC) are two promising and innovative technologies to accelerate 5G networks. However, placing the service function chains (SFC), each of ...which consists of a series of ordered virtual network functions (VNFs), into the EC enabled networks is an intractable issue and some new challenges shall arise. Firstly, EC is a hierarchical and geo-distributed structure, which will influence the form of SFCs and make the VNF placement location-related. Secondly, the data processing in EC is hierarchical too, which incurs different latency requirements. In this paper, we study the VNF placement problem considering users’ SFC requests (SFCr) in NFV and EC enabled networks. Apart from the above new challenges, the implementation method and chaining of VNFs are also considered, which will raise the need of tradeoff between node resource consumption and bandwidth consumption when placing VNFs. Then the above problem is formulated as an integer linear programming (ILP) model mathematically aiming to minimize the total resource consumption, which is proven to be NP-hard. We get the optimal results when the number of SFCrs is small taking advantage of optimization solver and propose a polynomial time heuristic when the problem scale is large. Simulation results show that the resource consumption derived by our heuristic solution is near to the optimal solution and its performance is very much superior to the contrastive schemes.
The reactive oxygen species (ROS) and phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway play critical roles in the pathogenesis of prostate cancer by modulating cell ...proliferation. Picropodophyllin (PPP), an inhibitor of the insulin-like growth factor 1 receptor (IGF-1R), exerts significant antitumor effects via the PI3K/AKT signaling pathway. However, the effects of PPP on prostate cancer via ROS production and the PI3K/AKT signaling pathway remain elusive. Herein, we focused on examining the antitumor effects of PPP on DU145 and LNCaP human prostate cancer cells to determine the possible molecular mechanism. Our data indicated that the inhibitory effect of PPP on the proliferation of DU145 and LNCaP human prostate cancer cells was mediated by apoptosis induction and cell cycle blockade. Furthermore, PPP significantly influenced the expression of apoptosis-related, cell cycle, ROS production, and PI3K/AKT signaling proteins. These findings suggest that PPP can induce cell cycle arrest and apoptosis via the production of ROS and inhibition of PI3K/AKT signaling pathway, thereby suppressing the proliferation of prostate cancer cells.
Owing to the Network Function Virtualization (NFV) and Software-Defined Networks (SDN), Service Function Chain (SFC) has become a popular service in SDN and NFV-enabled network. However, as the ...Virtual Network Function (VNF) of each type is generally multi-instance and flows with SFC requests must traverse a series of specified VNFs in predefined orders, it is a challenge for dynamic SFC formation to optimally select VNF instances and construct paths. Moreover, the load balancing and end-to-end delay need to be paid attention to, when routing flows with SFC requests. Additionally, fine-grained scheduling for traffic at flow level needs differentiated routing which should take flow features into consideration. Unfortunately, traditional algorithms cannot fulfill all these requirements. In this paper, we study the Differentiated Routing Problem considering SFC (DRP-SFC) in SDN and NFV-enabled network. We formulate the DRP-SFC as a Binary Integer Programming (BIP) model aiming to minimize the resource consumption costs of flows with SFC requests. Then a novel routing algorithm, Resource Aware Routing Algorithm (RA-RA), is proposed to solve the DRP-SFC. Performance evaluation shows that RA-RA can efficiently solve the DRP-SFC and surpass the performance of other existing algorithms in acceptance rate, throughput, hop count and load balancing.
Conventional discriminant locality preserving projection (DLPP) is a dimensionality reduction technique based on manifold learning, which has demonstrated good performance in pattern recognition. ...However, because its objective function is based on the distance criterion using L2-norm, conventional DLPP is not robust to outliers which are present in many applications. This paper proposes an effective and robust DLPP version based on L1-norm maximization, which learns a set of local optimal projection vectors by maximizing the ratio of the L1-norm-based locality preserving between-class dispersion and the L1-norm-based locality preserving within-class dispersion. The proposed method is proven to be feasible and also robust to outliers while overcoming the small sample size problem. The experimental results on artificial datasets, Binary Alphadigits dataset, FERET face dataset and PolyU palmprint dataset have demonstrated the effectiveness of the proposed method.
Clinical data show that the incidence and mortality rates of cancer are rising continuously, and cancer has become an ongoing public health challenge worldwide. Excitingly, the extensive clinical ...application of traditional Chinese medicine may suggest a new direction to combat cancer, and the therapeutic effects of active ingredients from Chinese herbal medicine on cancer are now being widely studied in the medical community. As a traditional anticancer Chinese medicine, ChanSu has been clinically applied since the 1980s and has achieved excellent antitumor efficacy. Meanwhile, the ChanSu active components (e.g., telocinobufagin, bufotalin, bufalin, cinobufotalin, and cinobufagin) exert great antitumor activity in many cancers, such as breast cancer, colorectal cancer, hepatocellular carcinoma and esophageal squamous cell carcinoma. Many pharmaceutical scientists have investigated the anticancer mechanisms of ChanSu or the ChanSu active components and obtained certain research progress. This article reviews the research progress and antitumor mechanisms of ChanSu active components and proposes that multiple active components of ChanSu may be potential anticancer drugs.
Paclitaxel (PTX) is among the most commonly used first-line drugs for cancer chemotherapy. However, its poor water solubility and indiscriminate distribution in normal tissues remain clinical ...challenges. Here we design and synthesize a highly water-soluble nucleolin aptamer-paclitaxel conjugate (NucA-PTX) that selectively delivers PTX to the tumor site. By connecting a tumor-targeting nucleolin aptamer (NucA) to the active hydroxyl group at 2' position of PTX via a cathepsin B sensitive dipeptide bond, NucA-PTX remains stable and inactive in the circulation. NucA facilitates the uptake of the conjugated PTX specifically in tumor cells. Once inside cells, the dipeptide bond linker of NucA-PTX is cleaved by cathepsin B and then the conjugated PTX is released for action. The NucA modification assists the selective accumulation of the conjugated PTX in ovarian tumor tissue rather than normal tissues, and subsequently resulting in notably improved antitumor activity and reduced toxicity.
With the advances of Software-Defined Networks (SDN) and Network Function Virtualization (NFV), Service Function Chain (SFC) has been becoming a popular paradigm to carry and complete network ...services. Such new computing and networking paradigm enables Virtual Network Functions (VNFs) to be placed in software entities/virtual machines over a network of physical equipments in elastic and flexible way with low capital and operation expenses. VNFs are chained together to steer traffic as needed. However, most of the existing traffic steering and routing path computation algorithms for SFC are complex, unscalable, and low time-efficiency. In this paper, we study the VNF Selection and Chaining Problem (VNF-SCP) in SDN/NFV-enabled networks. We formulate VNF-SCP as a Binary Integer Programming (BIP) model in order to compute routing path for each SFC Request (SFCR) with the minimum end-to-end delay. Then, a novel Deep Learning-based Two-Phase Algorithm (DL-TPA) is introduced, where VNF selection network and VNF chaining network are designed to achieve intelligent and efficient VNF selection and chaining for SFCRs. Performance evaluation shows that DL-TPA can achieve high prediction accuracy and time efficiency of routing path computation, and the overall network performance can be improved significantly.
Emerging evidence indicates that osteoclasts direct osteoblastic bone formation. MicroRNAs (miRNAs) have a crucial role in regulating osteoclast and osteoblast function. However, whether miRNAs ...mediate osteoclast-directed osteoblastic bone formation is mostly unknown. Here, we show that increased osteoclastic miR-214-3p associates with both elevated serum exosomal miR-214-3p and reduced bone formation in elderly women with fractures and in ovariectomized (OVX) mice. Osteoclast-specific miR-214-3p knock-in mice have elevated serum exosomal miR-214-3p and reduced bone formation that is rescued by osteoclast-targeted antagomir-214-3p treatment. We further demonstrate that osteoclast-derived exosomal miR-214-3p is transferred to osteoblasts to inhibit osteoblast activity in vitro and reduce bone formation in vivo. Moreover, osteoclast-targeted miR-214-3p inhibition promotes bone formation in ageing OVX mice. Collectively, our results suggest that osteoclast-derived exosomal miR-214-3p transfers to osteoblasts to inhibit bone formation. Inhibition of miR-214-3p in osteoclasts may be a strategy for treating skeletal disorders involving a reduction in bone formation.
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