科技金融驱动地区创新——基于“促进科技和金融结合试点”的自然实验

党的二十大报告强调,必须坚持科技是第一生产力,加快营造有利于实施创新驱动发展战略的良好环境。本文以2004-2019年城市为样本,检验“促进科技和金融结合”试点政策对城市创新水平的影响。研究发现,“促进科技和金融结合”试点政策显著提升了地区的创新水平。影响机制分析表明,“促进科技和金融结合”试点政策的实施加强了试点地区金融载体和创新载体两类载体的建设,进而提升了地区创新水平。进一步检验发现,“促进科技和金融结合”试点政策的创新促进效应主要存在于初始发展水平和人力资本水平更高的地区。研究结果还发现,“促进科技和金融结合”试点政策能够通过缓解企业融资约束提升企业的创新水平。本文的研究结果有助于为进一步推动科技和金融结合、加快实现我国高水平科技自立自强提供理论依据和政策参考。

A novel multi-channel porous structure facilitating mass transport towards highly efficient alkaline water electrolysis

An advantageous porous architecture of electrodes is pivotal in significantly enhancing alkaline water electrolysis(AWE)efficiency by optimizing the mass transport mechanisms.This effect becomes even more pronounced when aiming to achieve elevated current densities.Herein,we employed a rapid and scalable laser texturing process to craft novel multi-channel porous electrodes.Particularly,the obtained electrodes exhibit the lowest Tafel slope of 79 mV dec^(-1)(HER)and 49 mV dec^(-1)(OER).As anticipated,the alkaline electrolyzer(AEL)cell incorporating multi-channel porous electrodes(NP-LT30)exhibited a remarkable improvement in cell efficiency,with voltage drops(from 2.28 to 1.97 V)exceeding 300 mV under 1 A cm^(-1),compared to conventional perforated Ni plate electrodes.This enhancement mainly stemmed from the employed multi-channel porous structure,facilitating mass transport and bubble dynamics through an innovative convection mode,surpassing the traditional convection mode.Furthermore,the NP-LT30-based AEL cell demonstrated exceptional durability for 300 h under 1.0 A cm^(-2).This study underscores the capability of the novel multi-channel porous electrodes to expedite mass transport in practical AWE applications.

国有经济、市场化程度与中国经济稳增长

所有制结构与经济增长之间的逻辑关系,是我国经济发展过程中面临的重大问题。本文对此进行了理论与实证双重考察,发展出如下理论假说:政府所面临的经济增长压力是导致所有制结构调整的重要驱动因素,所有制结构调整有力地实现了稳增长。本文采用地级市城市、工业行业以及企业层面的多维数据对理论假说进行了验证,经济增长压力导致国有经济比重显著提高,国有经济比重提高在经济下行时期显著遏制了经济增长速度的下滑,实现了保增长和稳增长,即国有经济担当着经济增长的压舱石。本文还发现,国有经济的保增长和稳增长作用,在市场化程度发展充分的情况下更为显著,国有经济发展与市场体制建设具有互补作用。本文的研究在经济增长压力、所有制结构以及经济增长之间建立了一个统一的逻辑框架,拓展了中国特色社会主义经济理论中的政府和市场关系的内涵。

税收激励提升企业员工薪酬了吗?——来自2014年固定资产加速折旧政策的证据

企业员工薪酬增长不仅可以提高人民幸福感,对社会再生产过程的循环也有着重要作用。本文采用2009-2018年A股上市公司数据,基于2014年固定资产加速折旧政策这一“准自然实验”,运用倍差法考察了固定资产加速折旧政策对企业员工薪酬的影响。本文发现,固定资产加速折旧政策显著提高了企业员工薪酬。固定资产加速折旧政策有效提高企业经营效益,同时通过增加固定资产投入提高对高技能员工的需求,从而提高企业员工薪酬。进一步分析发现,该政策对非国有企业、劳动密集型企业、融资约束紧企业的员工薪酬具有更加明显的促进作用。本文研究有助于理解税收政策与企业员工薪酬之间关系的逻辑机理,对我国以税收激励政策调整促进经济结构转型升级具有一定的参考价值。

政府规划引领数字经济发展--来自五年规划的证据

当前,中国经济越来越呈现数字化特征,数字经济成为各级政府推动经济高质量发展的重要抓手。基于这一背景,本文从中国省级行政区五年规划文件入手,探究政府规划是否有利于数字经济产业的发展。使用改进的熵值法构造数字经济发展水平指数,用五年规划中相关行业描述的词语频率度量政府产业规划强度。通过固定效应方法和系统GMM方法估计发现,产业规划能够显著且稳健地促进数字经济产业发展。进一步分析表明,政府规划的政策效果具有地区异质性和行业异质性,中介组织和法律环境的发育有利于政府规划的引领作用;产业规划通过增强市场竞争程度这一机制提升数字经济发展水平。本文研究为政府规划的市场引领性作用提供了经验证据,为政府部门推动数字经济高质量发展、加快地区信息化智能化进程提供了科学依据。

营商环境与企业创新——基于商事制度改革的理论分析与实证检验

持续优化营商环境,最大限度释放创新创造活力,是实现高质量发展的重要战略举措。在发展中国家和地区,政府主导的营商环境变化对企业创新产生何种效应,是一个具有理论及实践双重价值的问题。本文在展开商事制度改革对企业创新影响理论分析的基础上,基于2011-2018年中国283个地级市的数据,运用双重差分法实证检验商事制度改革对企业创新的影响效应。研究发现,商事制度改革显著提升了企业创新水平。影响机制检验显示,商事制度改革降低了企业的制度性交易成本,改善了市场创新环境,进而提高了企业创新水平。此外,商事制度改革对企业创新的促进效应更多地表现在小规模企业、低融资约束企业以及法制环境较好地区的企业。本研究为持续优化营商环境、推进企业创新提供了理论支撑。

Power Allocation and Performance Analysis of the Collaborative NOMA Assisted Relaying Systems in 5G

Serving multiple cell-edge mobile terminals poses multifaceted challenges due to the increased transmission power and interferences, which could be overcome by relay communications. With the recent advancement of 5G technologies, non-orthogonal multiple access(NOMA) has been used at relay node to transmit multiple messages simultaneously to multiple cell-edge users. In this paper, a Collaborative NOMA Assisted Relaying(CNAR) system for 5G is proposed by enabling the collaboration of source-relay(S-R) and relay-destination(R-D) NOMA links. The relay node of the CNAR decodes the message for itself from S-R NOMA signal and transmits the remaining messages to the multiple cell-edge users in R-D link. A simplified-CNAR(S-CNAR) system is then developed to reduce the relay complexity. The outage probabilities for both systems are analyzed by considering outage behaviors in S-R and R-D links separately. To guarantee the data rate, the optimal power allocation among NOMA users is achieved by minimizing the outage probability. The ergodic sum capacity in high SNR regime is also approximated. Our mathematical analysis and simulation results show that CNAR system outperforms existing transmission strategies and S-CNAR reaches similar performance with much lower complexity.

An Adaptive Grouping Scheme in Ultra-Dense IEEE 802.11ax Network Using Buffer State Report Based Two-Stage Mechanism

IEEE 802.11ax,which is an emerging WLAN standard,aims at providing highly efficient communication in ultra-dense wireless networks.However,due to a large number of stations(STAs)in the ultra-dense device deployment scenarios,the potentially high packet collision rate significantly decreases the communication efficiency of WLAN.In this paper,we propose an adaptive STA grouping scheme to overcome this dense network challenge in IEEE 802.11ax by using Buffer State Report(BSR)based Two-stage Mechanism(BTM).In order to achieve the optimal efficiency of BSR delivery,we analyze the functional relationship between STA number in group and Resource Unit(RU)efficiency.Based on this analysis results,an adaptive STA grouping algorithm with variable group size is proposed to achieve efficient grouping in BTM.The numerical results demonstrate that the proposed adaptive BTM grouping algorithm significantly improves the BSR delivery efficiency and the throughput of overall system and each STA in the ultra-dense wireless network.

Deep Learning-Based Symbol Detection for Time-Varying Nonstationary Channels

The highly dynamic channel(HDC)in an extremely dynamic environment mainly has fast timevarying nonstationary characteristics.In this article,we focus on the most difficult HDC case,where the channel coherence time is less than the symbol period.To this end,we propose a symbol detector based on a long short-term memory(LSTM)neural network.Taking the sampling sequence of each received symbol as the LSTM unit's input data has the advantage of making full use of received information to obtain better performance.In addition,using the basic expansion model(BEM)as the preprocessing unit significantly reduces the number of neural network parameters.Finally,the simulation part uses the highly dynamic plasma sheath channel(HDPSC)data measured from shock tube experiments.The results show that the proposed BEM-LSTM-based detector has better performance and does not require channel estimation or channel model information.

Unique Characteristics of Vertical Carbon Nanotube Field-effect Transistors on Silicon

A vertical carbon nanotube field-effect transistor(CNTFET) based on silicon(Si) substrate has been proposed and simulated using a semi-classical theory. A single-walled carbon nanotube(SWNT) and an n-type Si nanowire in series construct the channel of the transistor. The CNTFET presents ambipolar characteristics at positive drain voltage(Vd) and n-type characteristics at negative Vd. The current is significantly influenced by the doping level of n-Si and the SWNT band gap. The n-branch current of the ambipolar characteristics increases with increasing doping level of the n-Si while the p-branch current decreases. The SWNT band gap has the same influence on the p-branch current at a positive Vd and n-type characteristics at negative Vd. The lower the SWNT band gap, the higher the current. However, it has no impact on the n-branch current in the ambipolar characteristics. Thick oxide is found to significantly degrade the current and the subthreshold slope of the CNTFETs.

Hybrid Reduced Graphene Oxide with Special Magnetoresistance for Wireless Magnetic Field Sensor

Very few materials show large magnetoresistance(MR)under a low magnetic field at room temperature,which causes the barrier to the development of magnetic field sensors for detecting low-level electromagnetic radiation in real-time.Here,a hybrid reduced graphene oxide(rGO)-based magnetic field sensor is produced by in situ deposition of FeCo nanoparticles(NPs)on reduced graphene oxide(rGO).Special quantum magnetoresistance(MR)of the hybrid rGO is observed,which unveils that Abrikosov's quantum model for layered materials can occur in hybrid rGO;meanwhile,the MR value can be tunable by adjusting the particle density of FeCo NPs on rGO nanosheets.Very high MR value up to 21.02±5.74%at 10 kOe at room temperature is achieved,and the average increasing rate of resistance per kOe is up to 0.9282ΩkOe^-1.In this paper,we demonstrate that the hybrid rGO-based magnetic field sensor can be embedded in a wireless system for real-time detection of low-level electromagnetic radiation caused by a working mobile phone.We believe that the two-dimensional nanomaterials with controllable MR can be integrated with a wireless system for the future connected society.

Angle-Based Beamforming in mmWave Massive MIMO Systems with Low Feedback Overhead Using Multi-Pattern Codebooks

The integration of millimeter-wave(mmWave)communications and massive multiple input multiple output(MIMO)techniques is a promising solution to dramatically increase the 5G network throughput.By using large antenna arrays,beamforming can be adopted to improve the 5G capacity by employing spatial domain resources.In a frequency division duplexing(FDD)based 5G mmWave MIMO system,beamforming operation requires timely downlink channel state information(CSI)feedback.However,the rapid channel variations caused by short wavelength of mmWave band,and the high-level feedback information required due to the large number of antennas in massive MIMO system lead to the significantly increased beamforming overhead.In this paper,by exploiting the higher angular stability of such channels,we propose an angle-based beamforming scheme to reduce the feedback frequency and the number of feedback bits.To facilitate this approach users are initially selected to reduce the intra-zone interference before beamforming.Besides,location related feedback,which is not affected by the number of antennas,is adopted to reduce overhead.The simulation results show that two proposed user selection algorithms can adapt to scenarios with diverse requirements,while the feedback overhead of proposed angle-based beamforming algorithm is sharply reduce compared with that of CSIbased beamforming algorithm.

A Multi-Layer Collaboration Framework for Industrial Parks with 5G Vehicle-to-Everything Networks

The fifth-generation(5G)wireless communication networks are expected to play an essential role in the transformation of vertical industries.Among many exciting applications to be enabled by 5G,logistics tasks in industry parks can be performed more efficiently via vehicle-to-everything(V2X)communications.In this paper,a multi-layer collaboration framework enabled by V2X is proposed for logistics management in industrial parks.The proposed framework includes three layers:a perception and execution layer,a logistics layer,and a configuration layer.In addition to the collaboration among these three layers,this study addresses the collaboration among devices,edge servers,and cloud services.For effective logistics in industrial parks,task collaboration is achieved through four functions:environmental perception and map construction,task allocation,path planning,and vehicle movement.To dynamically coordinate these functions,device–edge–cloud collaboration,which is supported by 5G slices and V2X communication technology,is applied.Then,the analytical target cascading method is adopted to configure and evaluate the collaboration schemes of industrial parks.Finally,a logistics analytical case study in industrial parks is employed to demonstrate the feasibility of the proposed collaboration framework.

商事制度改革与产业结构升级

深化商事制度改革、促进产业结构升级是新时代支撑经济高质量发展的重要抓手和环节。本文手工收集中国281个地级及以上城市2011—2015年的商事制度改革数据,从数量和质量两个维度,构建双重差分模型考察商事制度改革对产业结构升级的影响效应。结果显示,商事制度改革显著提升了产业结构升级的数量和质量。分产业检验发现,商事制度改革促进了服务业结构升级。究其机制,商事制度改革对产业结构升级的促进效应是通过激发创业、促进创新和提高风险投资来实现的。此外,异质性检验指出,商事制度改革对产业结构升级的促进效应在规模较大、金融发展程度较高和科教支出占比较高的城市更为显著。本文的发现为实现有效市场和有为政府的产业结构升级治理格局提供决策参考,也为实现营商环境优化的目标和路径提供借鉴。

A Hierarchical Game Model for Computation Sharing in Smart Buildings

Recently,initiatives to integrate Internet of Things(IoT)technologies into smart buildings have attracted extensive attention for improving the performance of buildings and the comfort of occupants.However,the amount of data generated by IoT devices remains a challenge to the building management systems(BMSs)in terms of intensity and complexity.Different from cloud computing and edge computing,we propose a computation sharing architecture in smart buildings to incentivize idle computing devices(ICDs,sellers)to offload computational tasks for the BMS(buyer).In this paper,we design a hierarchical game model,consisting of a Stackelberg game and a Cournot game,to achieve a dynamic increase in computational capacity for the BMS.To guarantee the utility of BMS and ICDs,the Stackelberg game model is built to analyze the interactions between BMS and ICDs.Then,the Cournot game model is presented to formulate the internal competition among multiple ICDs.Under the premise of the subgame perfect Nash equilibrium,the BMS can quote the optimal pricing strategy,and the ICDs can share the corresponding optimal amount of computing resources.Finally,the simulation results show that the BMS’s computational capacity is enhanced on-demand,and each participant in the game obtains maximal utility.

Converting LiNO_(3)additive to single nitrogenous component Li_(2)N_(2)O_(2)SEI layer on Li metal anode in carbonate-based electrolyte

With the increasing demand for high energy density energy storage device,Li metal has received intensive attention for its ultrahigh capacity and the lowest redox potential.LiNO_(3)is widely used as electrolyte additive for ether electrolyte,which can improve the cycle performance of Li metal anode.Compared to ethers,carbonates are more suitable for Li metal batteries with high voltage cathode because they have a wider electrochemical window.However,LiNO_(3)performs poor solubility in carbonate electrolyte,restricting its application in high voltage Li battery.Herein,we presented a facile method to introduce abundant LiNO_(3)additive to carbonate electrolyte system by introducing LiNO_(3)-PAN es as the interlayer of the cell.LiNO_(3)-PAN es is in sufficient contact with the electrolyte so that it can continuously releases LiNO_(3)to assist the formation of Li_(2)N_(2)O_(2)-rich single nitrogenous component SEI layer on Li surface.With the help of LiNO_(3)-PAN es,Li metal anode shows excellent cycle stability even at a high current density of 4mA/cm^(2),so that the cycle performance of the full cells was significantly improved,whether in the anode-free Cu||LFP cell or the Li||NCM622 cell.

政府创新目标激励企业创新了吗?——来自五年规划的经验证据

本文探讨了中国政府创新目标对企业创新的影响效应及其机制。本文基于中国地级市政府五年规划的创新目标数据及上市公司样本数据,使用多期双重差分法研究发现,地方政府提出创新目标后,辖区企业的专利申请量显著提高。进一步研究发现:创新目标的微观创新促进效应通过提高企业获得的财政补贴和外部投资资金等机制实现;创新目标提高了企业的发明专利申请量,但未提高企业的外观设计、实用新型专利申请量;创新目标的创新促进效应在大规模企业、非政治关联企业、高管具有较好教育背景的企业以及高新技术行业中更大。本文为理解国家经济社会发展规划的引领效应、进一步健全国家经济社会发展规划制度体系提供理论支撑。

经济增长压力与地区创新--来自经济增长目标设定的经验证据

本文结合增长目标管理与地方政府激励视角,理论阐述了经济增长压力对创新存在着先促进随后转为遏制的倒U形非线性影响效应。在实证上,采用政府工作报告中公布的经济增长速度目标与上一年实际经济增长速度的比值度量经济增长压力,基于2002-2016年全国281个地级市的面板数据,验证了理论假说。该非线性关系,在市场化程度较高的情况下更为突出。这一规律是微观市场主体对相关信息和政策进行理性反应的综合结果。

Green UAV communications for 6G: A survey

Unmanned Aerial Vehicles(UAVs) have received a wide range of attention for military and commercial applications. Enhanced with communication capability, UAVs are considered to play important roles in the Sixth Generation(6G) networks due to their low cost and flexible deployment. 6G is supposed to be an all-coverage network to provide ubiquitous connections for space, air, ground and underwater. UAVs are able to provide air-borne wireless coverage flexibly,serving as aerial base stations for ground users, as relays to connect isolated nodes, or as mobile users in cellular networks. However, the onboard energy of small UAVs is extremely limited. Thus,UAVs can be only deployed to establish wireless links temporarily. Prolonging the lifetime and developing green UAV communication with low power consumption becomes a critical challenge.In this article, a comprehensive survey on green UAV communications for 6G is carried out. Specifically, the typical UAVs and their energy consumption models are introduced. Then, the typical trends of green UAV communications are provided. In addition, the typical applications of UAVs and their green designs are discussed. Finally, several promising techniques and open research issues are also pointed out.

High sensitivity cascaded helical-core fiber SPR sensors

The distributed optical fiber surface plasmon resonance(SPR)sensors have attracted wide attention in biosensing and chemical sensing applications.However,due to the limitation of their sensing structure,it is difficult to adjust their res-onant wavelength and sensitivity.Here,novel and flexible cascaded helical-core fiber[HCF)SPR sensors are proposed theoretically and experimentally for distributed sensing applications.It is shown that the resonant wavelength and sensitivity of the sensors can be conveniently controlled by adjusting the twist pitch of the helical core.A high sensitivity of 11,180 nm/RIU for refractive-index measurement ranging from 1.355 to 1.365 is realized experimentally when the twist pitch of the helical core is 1.5 mm.It is worth noting that the sensitivity can be further improved by reducing the twist pitch.For example,the sensitivity of the sensor with a twist pitch of 1.4 mm can theoretically exceed 20,000 nm/RIU.This work opens up a new way to implement multi-parameter or distributed measurement,especially to establish sensing networks integrated in a single-core fiber or a multi-core fiber.