ICU患者置入Power PICC导管特殊异位原因分析

目的:探讨ICU患者置入Power PICC导管后头端反折向上至同侧和对侧锁骨下静脉、头臂静脉等特殊异位的相关因素。方法:回顾性分析2021年9月至2022年9月某三甲医院ICU 520例PICC置管患者,通过胸部X线确定PICC导管头端反折向上至对侧和同侧锁骨下静脉、头臂静脉的患者,分析其特殊异位发生因素。结果:胸部X线结果显示25例患者PICC管头端反折向上异位至对侧和同侧锁骨下静脉、头臂静脉或颈内静脉,异位发生率4.8%,不同静脉置管反折异位发生率相比差异无统计学意义,P>0.05。结论:ICU患者PICC置入发生导管头端反折向上至同侧和对侧锁骨下静脉、头臂静脉等特殊异位的发生因素较多,包括同时留置CVC或血透管、正在滴注或泵入多种药物、PICC管头端异位的隐匿性、导管材质、自身疾病及机械通气等危险因素。

基于调和概率语言术语集的Power平均算子

实践发现现存概率语言Power平均算子在应用中存在概率信息丢失、计算过于繁琐等问题,针对这些问题,提出一种基于调和概率语言术语集的Power平均算子。结合新的基本运算法则与新的支撑度,给出新的概率语言Power平均算子、概率语言Power几何平均算子、概率语言Power加权平均算子、概率语言Power加权几何平均算子,同时论证分析了这几类新型算子的性质。最后通过实验数据,将提出的算子与现存算子进行对比分析,验证了所提算子的有效性与可行性。

Carbon emission reduction:Contribution of photovoltaic power and practice in China

As a clean and renewable form of energy,photovoltaic(PV)power generation converts solar energy into electrical energy,reducing the consumption of fossil fuels and significantly lowering greenhouse gas emissions.Amidst the global transition towards cleaner forms of energy,countries all around the world are vigorously developing PV technology.

Highlights in recent wireless power IC research

Wireless power transfer(WPT)has been a popular topic in power integrated circuit(IC)designs in the past decade.As slogan"cutting the last wire"presented in ISSCC’15[1],WPT is poised to take over many wired power deliveries applica-tions today,just like what happened to wireless communica-tion nowadays.Over the years,WPT has become more mature and more wirelessly charged or powered products have become available on the market.This mini review intends to summarize recent breakthroughs in WPT inte-grated circuits(IC)research.

A Special Issue:“Key Technologies of Virtual Power Plant and Distributed Energy Resources”for Global Energy Interconnection

The increasing penetration of renewable and distributed energy resources(DERs)is transforming the power grid into a new type of clean and low-carbon power system.However,the uncertainty and volatility of DERs have also brought severe challenges to the secure and reliable operation of the power systems.In order to successfully integrate renewable DERs,virtual power plant(VPP)has emerged as a new technique for coordinating demand-side DERs,which has drawn significant attention from industry and academia.

Traction power systems for electrified railways:evolution,state of the art,and future trends

Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target.On the basis of sorting out the power supply structures of conventional AC and DC modes,this paper first reviews the characteristics of the existing TPSs,such as weak power supply flexibility and low-energy efficiency.Furthermore,the power supply structures of various TPSs for future electrified railways are described in detail,which satisfy longer distance,low-carbon,high-efficiency,high-reliability and high-quality power supply requirements.Meanwhile,the application prospects of different traction modes are discussed from both technical and economic aspects.Eventually,this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system,speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode,employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy.

Investigating Load Regulation Characteristics of a Wind-PV-Coal Storage Multi-Power Generation System

There is a growing need to explore the potential of coal-fired power plants(CFPPs)to enhance the utilization rate of wind power(wind)and photovoltaic power(PV)in the green energy field.This study developed a load regulation model for a multi-power generation system comprising wind,PV,and coal energy storage using realworld data.The power supply process was divided into eight fundamental load regulation scenarios,elucidating the influence of each scenario on load regulation.Within the framework of the multi-power generation system with the wind(50 MW)and PV(50 MW)alongside a CFPP(330 MW),a lithium-iron phosphate energy storage system(LIPBESS)was integrated to improve the system’s load regulation flexibility.The energy storage operation strategy was formulated based on the charging and discharging priority of the LIPBESS for each basic scenario and the charging and discharging load calculation method of LIPBESS auxiliary regulation.Through optimization using the particle swarm algorithm,the optimal capacity of LIPBESS was determined to be within the 5.24-4.88 MWh range.From an economic perspective,the LIPBESS operating with CFPP as the regulating power source was 49.1% lower in capacity compared to the renewable energy-based storage mode.

基于Power BI的DRGs数据分析方法

目的:探讨利用Power BI工具对DRGs数据进行有效分析,揭示潜在的数据特征和规律。方法:运用Power BI工具对2017年―2021年DRGs数据进行数据连接、数据清洗和处理等操作,提取和计算相关DRGs评价指标,最后通过可视化展示的方式对DRGs数据进行分析和呈现,从不同维度和角度深入研究DRGs数据特征和规律。结果:通过对2017年―2021年DRGs数据处理和可视化展示,能直观了解出院患者疾病构成、医疗资源利用、临床质量评估和医疗成本效益等总体情况,为提高医疗服务质量和资源利用效率等提供可行的解决方案。结论:基于Power BI的DRGs数据分析方法能够有效地帮助医院进行医疗费用控制和资源配置,并提高医疗服务的质量和效率。此方法为优化DRGs数据管理和医疗资源配置提供了重要的参考和借鉴价值。

Research on the MPPT of Photovoltaic Power Generation Based on Improved WOA and P&O under Partial Shading Conditions

Partial shading conditions(PSCs)caused by uneven illumination become one of the most common problems in photovoltaic(PV)systems,which can make the PV power-voltage(P-V)characteristics curve show multi-peaks.Traditional maximum power point tracking(MPPT)methods have shortcomings in tracking to the global maximum power point(GMPP),resulting in a dramatic decrease in output power.In order to solve the above problems,intelligent algorithms are used in MPPT.However,the existing intelligent algorithms have some disadvantages,such as slow convergence speed and large search oscillation.Therefore,an improved whale algorithm(IWOA)combined with the P&O(IWOA-P&O)is proposed for the MPPT of PV power generation in this paper.Firstly,IWOA is used to track the range interval of the GMPP,and then P&O is used to accurately find the MPP in that interval.Compared with other algorithms,simulation results show that this method has an average tracking efficiency of 99.79%and an average tracking time of 0.16 s when tracking GMPP.Finally,experimental verification is conducted,and the results show that the proposed algorithm has better MPPT performance compared to popular particle swarm optimization(PSO)and PSO-P&O algorithms.

Biodegradable and flexible i-carrageenan based RRAM with ultralow power consumption

Transient memories,which can physically disappear without leaving traceable remains over a period of normal operation,are attracting increasing attention for potential applications in the fields of data security and green electronics.Resistive random access memory(RRAM)is a promising candidate for next-generation memory.In this context,biocompatible l-carrageenan(l-car),extracted from natural seaweed,is introduced for the fabrication of RRAM devices(Ag/l-car/Pt).Taking advantage of the complexation processes between the functional groups(C–O–C,C–O–H,et al.)and Ag metal ions,a lower migration barrier of Ag ions and a high-speed switching(22.2 ns for SET operation/26 ns for RESET operation)were achieved,resulting in an ultralow power consumption of 56 fJ.And the prepared Ag/l-car/Pt RRAM devices also revealed the capacities of multilevel storage and flexibility.In addition,thanks to the hydrophilic groups of l-car molecule,the RRAM devices can be rapidly dissolved in deionized(DI)water within 13 minutes,showing excellent transient characteristics.This work demonstrates that l-car based RRAM devices have great potential for applications in secure storage applications,flexible electronics and transient electronics.

A Novel Multiple DBC-staked units Package to Parallel More Chips for SiC Power Module

Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple staked direct bonded copper(DBC) unit based power module packaging method to parallel more chips. This method utilizes mutual inductance cancellation effect to reduce parasitic inductance. Because the conduction area in the new package is doubled, the overall area of power module can be reduced. Entire power module is divided into smaller units to enhance manufacture yield, and improve design freedom. This paper provides a detailed design, analysis and fabrication procedure for the proposed package structure. Additionally, this paper offers several feasible solutions for the connection between power terminals and DBC untis. With the structure, 18dies were paralleled for each phase-leg in a econodual size power module. Both simulation and double pulse test results demonstrate that, compared to conventional layouts, the proposed package method has 74.8% smaller parasitic inductance and 34.9% lower footprint.

Increasing the Efficiency and Level of Environmental Safety of Pro-Environmental City Heat Supply Technologies by Low Power Nuclear Plants

In connection with the current prospect of decarbonization of coal energy through the use of small nuclear power plants (SNPPs) at existing TPPs as heat sources for heat supply to municipal heating networks, there is a technological need to improve heat supply schemes to increase their environmental friendliness and efficiency. The paper proves the feasibility of using the heat-feeding mode of ASHPs for urban heat supply by heating the network water with steam taken from the turbine. The ratio of electric and thermal power of a “nuclear” combined heat and power plant is given. The advantage of using a heat pump, which provides twice as much electrical power with the same heat output, is established. Taking into account that heat in these modes is supplied with different potential, the energy efficiency was used to compare these options. To increase the heat supply capacity, a scheme with the use of a high-pressure heater in the backpressure mode and with the heating of network water with hot steam was proposed. Heat supply from ASHPs is efficient and environmentally friendly even in the case of significant remoteness of heat consumers.

Broadband Dual-Input Doherty Power Amplifier Design Based on a Simple Adaptive Power Dividing Ratio Function

In this paper,a simple adaptive power dividing function for the design of a dual-input Doherty power amplifier(DPA)is presented.In the presented approaches,the signal separation function(SSF)at different frequency points can be characterized by a polynomial.And in the practical test,the coefficients of SSF can be determined by measuring a small number of data points of input power.Same as other dualinput DPAs,the proposed approach can also achieve high output power and back-off efficiency in a broadband operation band by adjusting the power distribution ratio flexibly.Finally,a 1.5-2.5 GHz highefficiency dual-input Doherty power amplifier is implemented according to this approach.The test results show that the peak power is 48.6-49.7d Bm,and the 6-d B back-off efficiency is 51.0-67.0%,and the saturation efficiency is 52.4-74.6%.The digital predistortion correction is carried out at the frequency points of 1.8/2.1GHz,and the adjacent channel power ratio is lower than-54.5d Bc.Simulation and experiment results can verify the effectiveness and correctness of the proposed method.

Safety-Constrained Multi-Agent Reinforcement Learning for Power Quality Control in Distributed Renewable Energy Networks

This paper examines the difficulties of managing distributed power systems,notably due to the increasing use of renewable energy sources,and focuses on voltage control challenges exacerbated by their variable nature in modern power grids.To tackle the unique challenges of voltage control in distributed renewable energy networks,researchers are increasingly turning towards multi-agent reinforcement learning(MARL).However,MARL raises safety concerns due to the unpredictability in agent actions during their exploration phase.This unpredictability can lead to unsafe control measures.To mitigate these safety concerns in MARL-based voltage control,our study introduces a novel approach:Safety-ConstrainedMulti-Agent Reinforcement Learning(SC-MARL).This approach incorporates a specialized safety constraint module specifically designed for voltage control within the MARL framework.This module ensures that the MARL agents carry out voltage control actions safely.The experiments demonstrate that,in the 33-buses,141-buses,and 322-buses power systems,employing SC-MARL for voltage control resulted in a reduction of the Voltage Out of Control Rate(%V.out)from0.43,0.24,and 2.95 to 0,0.01,and 0.03,respectively.Additionally,the Reactive Power Loss(Q loss)decreased from 0.095,0.547,and 0.017 to 0.062,0.452,and 0.016 in the corresponding systems.

Deep Learning-Based Secure Transmission Strategy with Sensor-Transmission-Computing Linkage for Power Internet of Things

The automatic collection of power grid situation information, along with real-time multimedia interaction between the front and back ends during the accident handling process, has generated a massive amount of power grid data. While wireless communication offers a convenient channel for grid terminal access and data transmission, it is important to note that the bandwidth of wireless communication is limited. Additionally, the broadcast nature of wireless transmission raises concerns about the potential for unauthorized eavesdropping during data transmission. To address these challenges and achieve reliable, secure, and real-time transmission of power grid data, an intelligent security transmission strategy with sensor-transmission-computing linkage is proposed in this paper. The primary objective of this strategy is to maximize the confidentiality capacity of the system. To tackle this, an optimization problem is formulated, taking into consideration interruption probability and interception probability as constraints. To efficiently solve this optimization problem, a low-complexity algorithm rooted in deep reinforcement learning is designed, which aims to derive a suboptimal solution for the problem at hand. Ultimately, through simulation results, the validity of the proposed strategy in guaranteed communication security, stability, and timeliness is substantiated. The results confirm that the proposed intelligent security transmission strategy significantly contributes to the safeguarding of communication integrity, system stability, and timely data delivery.

Power equipment vibration visualization using intelligent sensing method based on event-sensing principle

Vibration measurements can be used to evaluate the operation status of power equipment and are widely applied in equipment quality inspection and fault identification.Event-sensing technology can sense the change in surface light intensity caused by object vibration and provide a visual description of vibration behavior.Based on the analysis of the principle underlying the transformation of vibration behavior into event flow data by an event sensor,this paper proposes an algorithm to reconstruct event flow data into a relationship correlating vibration displacement and time to extract the amplitude-frequency characteristics of the vibration signal.A vibration measurement test platform is constructed,and feasibility and effectiveness tests are performed for the vibration motor and other power equipment.The results show that event-sensing technology can effectively perceive the surface vibration behavior of power and provide a wide dynamic range.Furthermore,the vibration measurement and visualization algorithm for power equipment constructed using this technology offers high measurement accuracy and efficiency.The results of this study provide a new noncontact and visual method for locating vibrations and performing amplitude-frequency analysis on power equipment.

Higher-order expansions of powered extremes of logarithmic general error distribution

In this paper,Let M_(n)denote the maximum of logarithmic general error distribution with parameter v≥1.Higher-order expansions for distributions of powered extremes M_(n)^(p)are derived under an optimal choice of normalizing constants.It is shown that M_(n)^(p),when v=1,converges to the Frechet extreme value distribution at the rate of 1/n,and if v>1 then M_(n)^(p)converges to the Gumbel extreme value distribution at the rate of(loglogn)^(2)=(log n)^(1-1/v).

Low-frequency oscillation of train-network system considering traction power supply mode

The low-frequency oscillation(LFO)has occurred in the train-network system due to the introduction of the power electronics of the trains.The modeling and analyzing method in current researches based on electrified railway unilateral power supply system are not suitable for the LFO analysis in a bilateral power supply system,where the trains are supplied by two traction substations.In this work,based on the single-input and single-output impedance model of China CRH5 trains,the node admittance matrices of the train-network system both in unilateral and bilateral power supply modes are established,including three-phase power grid,traction transformers and traction network.Then the modal analysis is used to study the oscillation modes and propagation characteristics of the unilateral and bilateral power supply systems.Moreover,the influence of the equivalent inductance of the power grid,the length of the transmission line,and the length of the traction network are analyzed on the critical oscillation mode of the bilateral power supply system.Finally,the theoretical analysis results are verified by the time-domain simulation model in MATLAB/Simulink.

Wireless Power Supply Based on MNG-MNZ Metamaterial for Cardiac Pacemakers

To solve the low power transfer efficiency and magnetic field leakage problems of cardiac pacemaker wireless powering, we proposed a wireless power supply system suitable for implanted cardiac pacemaker based on mu-negative(MNG) and mu-nearzero(MNZ) metamaterials. First, a hybrid metamaterial consisted of central MNG unit for magnetic field concentration and surrounding MNZ units for magnetic leakage shielding was established by theoretical calculation. Afterwards, the magnetic field distribution of wireless power supply system with MNG-MNZ metamaterial slab was acquired via finite element simulation and verified to be better than the distribution with conventional MNG slab deployed. Finally, an experimental platform of wireless power supply system was established with which power transfer experiment and system temperature rise experiment were conducted.Simulation and experimental results showed that the power transfer efficiency was improved from 44.44%,19.42%, 8.63% and 6.19% to 55.77%, 62.39%, 20.81%and 14.52% at 9.6 mm, 20 mm, 30 mm and 50 mm,respectively. The maximum SAR acquired by SAR simulation under human body environment was-7.14 dbm and maximum reduction of the magnetic field strength around the receiving coil was 2.82 A/m. The maximum temperature rise during 30min charging test was 3.85℃,and the safety requirements of human bodies were met.

Stackelberg Game for Wireless Powered and Backscattering Enabled Sensor Networks

This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.