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Volume reflex produces sympatho-inhibition that is mediated by the hypothalamic paraventricular nucleus (PVN). However, the mechanisms for the sympatho-inhibitory role of the PVN and the neurochemical factors involved remain to be identified. In this study, we proposed C-type natriuretic peptide (CNP) as a potential mediator of this sympatho-inhibition within the PVN. Microinjection of CNP (1.0 μg) into the PVN significantly decreased renal sympathetic nerve activity (RSNA) (−25.8% ± 1.8% vs. −3.6% ± 1.5%), mean arterial pressure (−15.0 ± 1.9 vs. −0.1 ± 0.9 mmHg) and heart rate (−23.6 ± 3.5 vs. −0.3 ± 0.9 beats/min) compared with microinjection of vehicle. Picoinjection of CNP significantly decreased the basal discharge of extracellular single-unit recordings in 5/6 (83%) rostral ventrolateral medulla (RVLM)-projecting PVN neurons and in 6/13 (46%) of the neurons that were not antidromically activated from the RVLM. We also observed that natriuretic peptide receptor type C (NPR-C) was present on the RVLM projecting PVN neurons detected by dual-labeling with retrograde tracer. Prior NPR-C siRNA microinjection into the PVN significantly blunted the decrease in RSNA to CNP microinjections into the PVN. Volume expansion-mediated reduction in RSNA was significantly blunted by prior administration of NPR-C siRNA into the PVN. These results suggest a potential role for CNP within the PVN in regulating RSNA, specifically under physiological conditions of alterations in fluid balance.

Experimental data and numerical simulation codes for a manuscript titled"Proximate deconfined quantum critical point in SrCu2(BO3)2".

Experimental data and numerical simulation codes for a manuscript titled"Proximate deconfined quantum critical point in SrCu2(BO3)2".

In order to improve the reliability of the acquisition/output link in the PLC control system, the design principle of the redundant system is analyzed, combined with the field application environment and actual needs, a distributed I/O redundancy method based on domestic PLC is developed. The article introduces the digital input/output and analog input/output redundancy schemes respectively for the type of data collected. This method takes the self-diagnosis results of the self-diagnosis periodically during operation as the basis for redundant diagnosis, combined with the user-configured redundancy scheme to improve accuracy of collecting/outputting data. It can be known from experiments and on-site base application that this method improves the reliability of the PLC control system and can ensure that the PLC system operates stably, efficiently and safely for a long time.

Aiming at the requirements of the design parameters temperature, humidity and air volume of the fairing air conditioner in a launch site, the implementation plan of the traditional fairing air conditioning system was investigated. In this paper, from the aspects of information security and reliability, a redundant automatic control system for air conditioning with fairing based on domestic PLC was proposed. In this regard, the article introduces the functions of domestic super Yu PLC components, redundant unit system scheme, and builds the system architecture and control scheme from the hardware and software aspects. Through on-site experimental debugging, the feasibility and stability of the fairing air conditioning control system are verified, and it has obvious advantages such as safety and reliability. It solves the problem of zero application of domestic PLC in the fairing air conditioning system and is a high reliability fairing air conditioning system design plan.

Supplemental Digital Content is available in the text., Central infusion of Ang II (angiotensin II) has been associated with increased sympathetic outflow resulting in neurogenic hypertension. In the present study, we appraised whether the chronic increase in central Ang II activates the paraventricular nucleus of the hypothalamus (PVN) resulting in elevated sympathetic tone and altered baro- and chemoreflexes. Further, we evaluated the contribution of HIF-1α (hypoxia-inducible factor-1α), a transcription factor involved in enhancing the expression of N-methyl-D-aspartate receptors and thus glutamatergic-mediated sympathetic tone from the PVN. Ang II infusion (20 ng/minute, intracerebroventricular, 14 days) increased mean arterial pressure (126±9 versus 84±4 mm Hg), cardiac sympathetic tone (96±7 versus 75±6 bpm), and decreased cardiac parasympathetic tone (16±2 versus 36±3 versus bpm) compared with saline-infused controls in conscious rats. The Ang II-infused group also showed an impaired baroreflex control of heart rate (−1.50±0.1 versus −2.50±0.3 bpm/mm Hg), potentiation of the chemoreflex pressor response (53±7 versus 30±7 mm Hg) and increased number of FosB-labeled cells (53±3 versus 19±4) in the PVN. Concomitant with the activation of the PVN, there was an increased expression of HIF-1α and N-Methyl-D-Aspartate-type1 receptors in the PVN. Further, Ang II-infusion showed increased renal sympathetic nerve activity (20.5±2.3% versus 6.4±1.9% of Max) and 3-fold enhanced renal sympathetic nerve activity responses to microinjection of N-methyl-D-aspartate (200 pmol) into the PVN of anesthetized rats. Further, silencing of HIF-1α in NG108 cells abrogated the expression of N-methyl-D-aspartate-N-methyl-D-aspartate-type1 induced by Ang II. Taken together, our studies suggest a novel Ang II-HIF-1α-N-methyl-D-aspartate receptor-mediated activation of preautonomic neurons in the PVN, resulting in increased sympathetic outflow and alterations in baro- and chemoreflexes.

The autoregressive (AR) models, such as attention-based encoder-decoder models and RNN-Transducer, have achieved great success in speech recognition. They predict the output sequence conditioned on the previous tokens and acoustic encoded states, which is inefficient on GPUs. The non-autoregressive (NAR) models can get rid of the temporal dependency between the output tokens and predict the entire output tokens in at least one step. However, the NAR model still faces two major problems. On the one hand, there is still a great gap in performance between the NAR models and the advanced AR models. On the other hand, it's difficult for most of the NAR models to train and converge. To address these two problems, we propose a new model named the two-step non-autoregressive transformer(TSNAT), which improves the performance and accelerating the convergence of the NAR model by learning prior knowledge from a parameters-sharing AR model. Furthermore, we introduce the two-stage method into the inference process, which improves the model performance greatly. All the experiments are conducted on a public Chinese mandarin dataset ASIEHLL-1. The results show that the TSNAT can achieve a competitive performance with the AR model and outperform many complicated NAR models., Submitted to Interspeech2021

In this paper, we propose an end-to-end post-filter method with deep attention fusion features for monaural speaker-independent speech separation. At first, a time-frequency domain speech separation method is applied as the pre-separation stage. The aim of pre-separation stage is to separate the mixture preliminarily. Although this stage can separate the mixture, it still contains the residual interference. In order to enhance the pre-separated speech and improve the separation performance further, the end-to-end post-filter (E2EPF) with deep attention fusion features is proposed. The E2EPF can make full use of the prior knowledge of the pre-separated speech, which contributes to speech separation. It is a fully convolutional speech separation network and uses the waveform as the input features. Firstly, the 1-D convolutional layer is utilized to extract the deep representation features for the mixture and pre-separated signals in the time domain. Secondly, to pay more attention to the outputs of the pre-separation stage, an attention module is applied to acquire deep attention fusion features, which are extracted by computing the similarity between the mixture and the pre-separated speech. These deep attention fusion features are conducive to reduce the interference and enhance the pre-separated speech. Finally, these features are sent to the post-filter to estimate each target signals. Experimental results on the WSJ0-2mix dataset show that the proposed method outperforms the state-of-the-art speech separation method. Compared with the pre-separation method, our proposed method can acquire 64.1%, 60.2%, 25.6% and 7.5% relative improvements in scale-invariant source-to-noise ratio (SI-SNR), the signal-to-distortion ratio (SDR), the perceptual evaluation of speech quality (PESQ) and the short-time objective intelligibility (STOI) measures, respectively., ACCEPTED by IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP)

Reservoirs and dams are vital human-built infrastructures that play essential roles in flood control, hydroelectric power generation, water supply, navigation, and other functions. The realization of those functions requires efficient reservoir operation, and the effective controls on the outflow from a reservoir or dam. Over the last decade, artificial intelligence (AI) techniques have become increasingly popular in the field of streamflow forecasts, reservoir operation planning and scheduling approaches. In this study, three AI models, namely, the backpropagation (BP) neural network, support vector regression (SVR) technique, and long short-term memory (LSTM) model, are employed to simulate reservoir operation at monthly, daily, and hourly time scales, using approximately 30 years of historical reservoir operation records. This study aims to summarize the influence of the parameter settings on model performance and to explore the applicability of the LSTM model to reservoir operation simulation. The results show the following: (1) for the BP neural network and LSTM model, the effects of the number of maximum iterations on model performance should be prioritized; for the SVR model, the simulation performance is directly related to the selection of the kernel function, and sigmoid and RBF kernel functions should be prioritized; (2) the BP neural network and SVR are suitable for the model to learn the operation rules of a reservoir from a small amount of data; and (3) the LSTM model is able to effectively reduce the time consumption and memory storage required by other AI models, and demonstrate good capability in simulating low-flow conditions and the outflow curve for the peak operation period.

In recent years, dual-arm robots have been favored in various industries due to their excellent coordinated operability. One of the focused areas of study on dual-arm robots is obstacle avoidance, namely path planning. Among the existing path planning methods, the artificial potential field (APF) algorithm is widely applied in obstacle avoidance for its simplicity, practicability, and good real-time performance over other planning methods. However, APF is firstly proposed to solve the obstacle avoidance problem of mobile robot in plane, and thus has some limitations such as being prone to fall into local minimum, not being applicable when dynamic obstacles are encountered. Therefore, an obstacle avoidance strategy for a dual-arm robot based on speed field with improved artificial potential field algorithm is proposed. In our method, the APF algorithm is used to establish the attraction and repulsion functions of the robotic manipulator, and then the concepts of attraction and repulsion speed are introduced. The attraction and repulsion functions are converted into the attraction and repulsion speed functions, which mapped to the joint space. By using the Jacobian matrix and its inverse to establish the differential velocity function of joint motion, as well as comparing it with the set collision distance threshold between two robotic manipulators of robot, the collision avoidance can be solved. Meanwhile, after introducing a new repulsion function and adding virtual constraint points to eliminate existing limitations, APF is also improved. The correctness and effectiveness of the proposed method in the self-collision avoidance problem of a dual-arm robot are validated in MATLAB and Adams simulation environment.

The mechanical properties especially the high temperature mechanical properties of cutting tool materials have significant effects on the cutting performance. A new kind of Al 2 O 3 -based ceramic tool material (AW20P5) synergistically toughened by SiC whiskers and nanoparticles was fabricated with good mechanical properties at room temperature, and then the high temperature mechanical properties and their evolution mechanisms from 700 °C to 1200 °C of AW20P5 were investigated compared with the room temperature mechanical properties. The results showed that the flexural strength firstly increased and subsequently decreased with the increasing of the testing temperature. The maximum flexural strength was 673 MPa at the testing temperature of 850 °C. With the increasing of the testing temperature, the fracture toughness of the AW20P5 tool material firstly decreased continuously from 700 °C to 1100 °C but subsequently increased at 1200 °C accompanied with the obvious plasticity. Combining the scanning electron microscope (SEM) and X-ray diffractometer (XRD) analysis, it was concluded that the degradation of the mechanical properties at elevated temperatures was ascribed to the oxidation of SiC and the decrease of its elasticity modulus, the improvement of the mechanical properties at elevated temperatures was ascribed to the healing of the micro cracks and defects as well as the decrease of the interfacial bonding strength.

To improve the efficiencies and benefits of distribution network investments, a investment allocation method of distribution network based on big data is proposed in this paper. Firstly, considering the corporate responsibility, user perception and power grid development demands, the index systems for power grid development level and investment direction are established, and then the coupling relationship between these two index systems is calculated based on big data. Considering the differences in the current power grid development level, planning objectives and indexes of different regions, a correcting coefficient is proposed to modify the above model and the priorities of power grid investment directions are achieved eventually. The above model is further verified by the actual data of a region in Hebei province.

How to express the designer's creative intent in a simple and intuitive way is the main problem in 3d modeling, especially for novice designers. This paper presents a free shape 3d modeling system for creative design based on modified Catmull-Clark subdivision. The system contains a series of easy but novel operations which can be used to change the topology of models, such as creating holes and handles. In order to create sharp features, feature marking operations are provided to specify where the sharp feature is. This system also provides surface conversion function to make the modeling results be compatible with the traditional CAD systems. Firstly, a simple but efficient quad domain division scheme is adopted to generate quad sub-meshes. In order to improve the smoothness at the regular vertices, long boundary curves which across multiple sub-meshes are used to be the boundary constraints while fitting. In this way, the smoothness at regular vertex can be C2 continuous. We perform experiments for both skilled and novice designers. Results show that our system is easy to operate and can be used to construct complex models with less time.

Based on the concept of life cycle and the conditions of 220kV station, the technology and economy of GIS, HGIS and AIS of 220kV and 110kV sides are compared, the main cost of 30 years’ construction from putting the equipment into operation to decommissioning are analyzed, and the cost from 2049 to 2019 according to the discount rate are calculated. Based on the life cycle cost objective function, the optimal solution is obtained, and the lowest cost distribution device selection scheme is obtained.

With the continuous development of energy Internet technology, its requirements for communication systems are getting higher and higher. As for the energy Internet, it is based on the concept of the Internet and the existing smart grid. Its communication system also needs to rely on the existing power communication system. In the energy Internet, the use of block chain and intelligent contract technology to meet credible and automatic point-to-point energy transactions can improve the overall operating efficiency of the system, reduce management costs, and make the energy Internet a self-organizing and self-regulating structure. In essence, energy Internet and block chain technology must be built on the Internet of Things, a common intelligent device. This paper takes the power line communication technology of the Internet in the current power system as the research object, analyzes the main challenges and problems in the construction of energy Internet based on blockchain, and then provides the corresponding research basis for the future heterogeneous network integration.

As an effective way to solve energy problems and achieve sustainable development, electric vehicles (EV s) present broad application prospects. Without the help of effective distribution network planning and design methods, the development of EVs is impossible. However, due to the massive access of EV s, the planning and design of distribution network is quite different from the traditional power system. This paper presents the key steps of smart distribution network planning converging high penetration level of EV s on the technique side, reviews latest developments in the field of modelling methods, solving algorithms and evaluation methods, and emphatically discusses the coupling between the EVs charging behavior and the planning of distribution network, as well as the main comprehensive evaluation methods. The future research direction of smart distribution network with high-penetration level of EV s is proposed.

The core-shell structure Fe3O4@C magnetic nanoparticles were synthesized with superparamagnetic Fe3O4 nanosphere as a magnetic core, glucose, phenolic and soluble starch resin as carbon source via a solvothermal method. The structure of Fe3O4@C magnetic nanoparticles was characterizes using TEM, XRD and VSM. The effects of preparation conditions in the structure of the Fe3O4@C magnetic nanoparticles were taken out. The results indicate: Fe3O4@Cg magnetic nano particle with glucose as carbon source has 250 nm diameter and 8-10 nm thickness of carbon shell; Fe3O4@Cp has 160 nm diameter and 6-8 nm carbon shell with phenolic as carbon source; when the carbon source changes to soluble starch, the magnetic nano particle prepared with 150 nm diameter and 15-20 nm carbon shell. Through XRD, the magnetic nano particles Fe3O4@C synthesized with three kinds of carbon sources have amorphous carbon diffraction peak except for all the characteristic peaks of Fe3O4. The magnetism of Fe3O4@Cg, Fe3O4@Cp and Fe3O4@Cs are 74.1 emu/g, 48.7 emu/g and 41.3 emu/g, respectively.

A series of magnetically recyclable Pd/Fe 3 O 4 @γ-Al 2 O 3 catalysts were synthesized using the superparamagnetic Fe 3 O 4 @γ-Al 2 O 3 core–shell microspheres as the supporter and nano-Pd particles assembled on γ-Al 2 O 3 shell as the active catalytic component. The structure of the catalysts was characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), N 2 adsorption–desorption and vibrating sample magnetometer (VSM). The catalytic activity and the recyclability properties of the catalysts for the Heck coupling reaction with aryl bromides and the olefins were investigated. The results show that the microspheres of the magnetic Pd/Fe 3 O 4 @γ-Al 2 O 3 catalysts were about 400 nm and the nano-Pd particles assembled on γ-Al 2 O 3 shell were about 3–4 nm in size. The saturation magnetization (MS) of the magnetic catalysts was sufficiently high to allow magnetic separations. In the Heck coupling reactions, the magnetic Pd/Fe 3 O 4 @γ-Al 2 O 3 catalysts exhibited good catalytic activity and recyclability. With Pd/Fe 3 O 4 @γ-Al 2 O 3 (0.021 mol%) catalyst, the bromobenzene conversion and product yield reached about 96.8% and 91.2%, respectively, at 120 °C and in 14 h. After being recycled for six times, the conversion of bromobenzene and the recovery of the catalyst were about 80% and 90%, respectively. The nano-Pd particles were kept well dispersed in the used Pd/Fe 3 O 4 @γ-Al 2 O 3 catalysts.

Novel nanotube-like conjugated microporous polymer (CMP) with a large surface area was prepared by one-step chemical synthesis via cross-coupling of 1,4-diethynylbenzene and 2,4,6-tribromophenol. Due to its unique surface hydrophobicity and porous feature, we prepared CMP nanotube-based hydrophobic sponges by filling the CMP nanotubes into melamine sponges to afford a bulk absorbent via the method similar to “ship-in-bottle”. The CMP treated sponges exhibit excellent absorption capacity and recyclability for separation of organics from water. Moreover, the absorbates can be re-collected simply by squeezing the treated sponge. This work provides a simple and efficient method to prepare hydrophobic, oleophilic sponge materials, which is of technological significance for potential use, especially for oil-spill cleanups or removal of organic pollutants from water.

Novel magnetically recyclable Pd/γ-AlOOH@Fe3O4 catalysts were prepared using γ-AlOOH@Fe3O4 as a magnetic supporter and nano-Pd particles as the active catalytic component. The structure of the catalysts was characterized by XRD (X-ray diffraction), TEM (transmission electron microscopy), N2 adsorption-desorption, and a VSM (vibration sample magnetometer). The catalytic activity and recyclability for the Heck coupling reaction were investigated. Results showed that the magnetic γ-AlOOH@Fe3O4 possessed a core-shell structure, as well as that the nano-Pd particles were 6–8 nm and had been well dispersed in the γ-AlOOH shell. In the Heck coupling reactions, the magnetic Pd/γ-AlOOH@Fe3O4 catalysts exhibited good catalytic activity and recyclability. For the (0.021 mol%)Pd/γ-AlOOH@Fe3O4 catalyst, the bromobenzene conversion and product yield reached about 100% and 96.3%, respectively, under a 120°C reaction temperature and 12 h reaction time. After being recycled 8 times, the conversion of bromobenzene and the recovery of the catalyst were about 90% and 93%, respectively. The nano-Pd particles were kept well dispersed in the used Pd/γ-AlOOH@Fe3O4 catalyst.

The reservoir is an important hydraulic engineering measure for human utilization and management of water resources. Additionally, a reasonable and effective reservoir operating plan is essential for realizing reservoir function. To explore the application of a deep learning algorithm on the field of reservoir operations, a recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU) are employed to predict outflows for the Xiluodu (XLD) reservoir. Meanwhile, this paper summarized the law of the effect of parameter setting on model performance compared to the simulation performance of three models, and analyzed the main factors that affect reservoir operation to provide the reference for future model of application research. Results show (1) the number of iterations and hidden nodes mainly influence the model precision, and the former has more effect than the latter, and the batch size mainly affects the calculated speed, (2) all three models can predict the reservoir outflow accurately and efficiently, (3) the operating decision generated by three models can implement the flood control and power generation goal of the reservoir and meet the operating regulation, and (4) under different hydrological periods, the influence factors of reservoir operation and their importance are different.

Five strains of plant growth-promoting rhizobacteria (PGPR) with 1-aminocyclopropane-1-carboxylate (ACC) deaminase activity were isolated from carnation soil and roots using ACC as the sole nitrogen source. Based on their growth morphological, microscopic cell properties and 16S rRNA sequence analysis, the results showed that three strains were identified as Enterobacter section and one as Erwinia among four strains from the soil, and one from carnation roots wAS identified as Acinetobacter; there are some differences in ACC deaminase activities among all isolated strains in this study. It is suggested that ACC deaminase-containing PGPR could be a cost-effective, environment-friendly and promising potential strategy to promote plant growth, alleviate biotic and abiotic stresses and ensure sustainable agriculture, especially for ethylene-sensitive flowers production. Key words: 1-Aminocyclopropane-1-carboxylate (ACC), deaminase, plant growth-promoting rizobacteria, carnation, salinity stress.

Renal denervation (RDN) has been postulated to reduce sympathetic drive during heart failure (HF), but the central mechanisms are not completely understood. The purpose of the present study was to assess the contribution of neuronal nitric oxide synthase (nNOS) within the paraventricular nucleus (PVN) in modulating sympathetic outflow in rats with HF that underwent RDN. HF was induced in rats by ligation of the left coronary artery. Four weeks after surgery, bilateral RDN was performed. Rats with HF had an increase in FosB-positive cells in the PVN with a concomitant increase in urinary excretion of norepinephrine, and both of these parameters were ameliorated after RDN. nNOS-positive cells immunostaining, diaphorase staining, and nNOS protein expression were significantly decreased in the PVN of HF rats, findings that were ameliorated by RDN. Microinjection of nNOS inhibitor N(G)-monomethyl l-arginine into the PVN resulted in a blunted increase in lumbar sympathetic nerve activity (11±2% versus 24±2%) in HF than in sham group. This response was normalized after RDN. Stimulation of afferent renal nerves produced a greater activation of PVN neurons in rats with HF. Afferent renal nerve stimulation elicited a greater increase in lumbar sympathetic nerve activity in rats with HF than in sham rats (45±5% versus 22±2%). These results suggest that intact renal nerves contribute to the reduction of nNOS in the PVN, resulting in the activation of the neurons in the PVN of rats with HF. RDN restores nNOS and thus attenuates the sympathoexcitation commonly observed in HF.

The optimisation of submerged hollow fibre MBRs was achieved through a series of numerical simulations ranging from meso-scale simulations of the membrane module and filtration zone, to micro-scale simulations of the inhomogeneous distribution of filtration flux, and the effects of fibre displacement on surface shear and flux. A meso-scale Computational Fluid Dynamics model, coupled with sludge rheology models to account for the behaviour of mixed liquor and porous media models to represent the resistance of membranes to the fluid field, was developed and used to estimate shear stress in the filtration zone of a 1250 L pilot scale membrane bioreactor. These simulations indicated that the addition of iron salts altered the rheology of activated sludge and reduced the uneven distribution of shear stress, particularly in the lower zone of the membrane module. For the filtration zone design, the highest shear stress was predicted to occur for vertically oriented membranes aligned in parallel with air diffuser nozzles generating 10 mm diameter bubbles constrained to travel in the filtration zone by solid baffles encasing the membrane module. Micro-scale CFD modelling of flux as a function of fibre length, diameter, permeate collection modes (bottom-out, top-out and two-end out) was conducted on a single hollow fibre membrane. Results suggested that the local flux at the bottom was 43.8% lower than that at the top for a 2 m long hollow fibre operated in a top-out permeation mode, indicating an uneven flux distribution along fibre length. This can be improved by increasing fibre diameter or using two-side out permeation mode. Pressure profiles from meso-scale models of two-phase (liquid-air) flow were imported to the micro-scale models to account for the impact of aeration on flux. Under aerated conditions, a more even flux distribution was observed for the fibre with a bottom-out permeate collection mode than the one operated with a top-out permeate collection mode with the ratio of flux at the base to flux at the outlet of 12.2% compared to 23.3%. Fibre movement induced membrane surface shear was evaluated with microscale Fluid Structure Interaction (FSI) modelling. Surface shear was found to be 130% high for a moving fibre compared with a fixed fibre under the same aeration intensity. The average shear stress on a moving fibre could be increased by decreasing the Young’s modulus (more flexible fibre), increasing the fibre looseness and using fibre with larger diameter. In addition, the average shear around a bundle of 7 fibres with high packing density (666 m2/m3) was found to be 3.6 times greater than the bundle with lower packing density (172 m2/m3) moved at identical amplitude and frequency.

Since the reform and opening up policy, China’s commercial development has made an unprecedented achievement both in speed and in scale in recent years, thus it becomes a dazzling light in the world’s economic development. However, in the construction of commercial outlets in recent years, there are some phenomenons such as layout of the chaos, the same function of the formats, business facilities redundant construction, resources waste, and excessive competition because of a lack of unified planning, which will have a negative impact to the sustainable development of commercial economy and prosperity of our country. Under the background of economic globalization, this article makes an exploration about Zhuozhou’s business sustainable development in the perspective of the trend of global commerce development field of vision, which will guide the practice of the commercial development of our country in a new scientific concept of development strategy and will ensure our business developing safe and healthy in the fierce international competition. Keywords-economic globalization; sustainable development; business I. THE COMMERCIAL DEVELOPMENT OF ECONOMIC

Under arbitrary masses, in this paper, we discuss the existence of new families of spatial central configurations for the N + N + 2-body problem, $N\ge 2$ . We study some necessary conditions and sufficient conditions for a families of spatial double pyramidical central configurations (d.p.c.c.), where 2N bodies are at the vertices of a nested regular N-gons ${\Gamma }_{1}\cup {\Gamma }_{2}$ , and the other two bodies are symmetrically located on the straight line that is perpendicular to the plane that contains ${\Gamma }_{1}\cup {\Gamma }_{2}$ and passes through the geometric center of ${\Gamma }_{1}\cup {\Gamma }_{2}$ . We prove that if the bodies are in a d.p.c.c., then the masses on each N-gon are equal, and the other two are also equal. And also we prove the existence and uniqueness of the central configurations for any given ratios of masses.