The Impact of Optimizing Details in the Operating Room on the Level of Knowledge, Attitude, and Practice of Hospital Infection Prevention and Control by Surgeons, as Well as the Effectiveness of Infection Control

Objective: This paper aims to explore the impact of optimizing details in the operating room on the level of knowledge, attitude, and practice of hospital infection prevention and control by surgeons, as well as the effectiveness of infection control. Methods: From January 2022 to June 2023, a total of 120 patients were screened and randomly divided into a control group (routine care and hospital infection management) and a study group (optimizing details in the operating room). Results: Significant differences were found between the two groups in the data of surgeons’ level of knowledge, attitude, and practice in hospital infection prevention and control, infection rates, and nursing satisfaction, with the study group showing better results (P Conclusion: The use of optimizing details in the operating room among surgeons can effectively improve surgeons’ level of knowledge, attitude, and practice in hospital infection prevention and control, reduce infection occurrence, and is worth promoting.

Based on the water source heat pump system operation control and energy consumption optimization

The contradiction between the increasing material demand and resource,is the country has faced problems,to better solve the material demand and the contradiction between the environment and resources,is applied to the development of new energy,new energy,not only can alleviate people and resources,environment and resources,the contradiction between people and the environment,also can promote the sustainable development of world economy,HVAC technology has emerged a new generation of energysaving technology,HVAC has the characteristics of low consumption,low pollution,is a development of technology,to be promoted for environmentfriendly,resource-conserving society has an important role in promoting.This paper focuses on the HVAC technology,water source heat pump system operation control and energy consumption optimization,for the relevant personnel reference.

Operation optimization of plugged screen cleanup by rotary water jetting

The rotary water jetting is one of the most important techniques for horizontal well cleanup.The jet flow is used to remove plugging particles from sand control screens to recover their permeability.Currently,the operation optimization of this technique depends mainly on experience due to absence of applicable evaluation and design models for removing plugging materials.This paper presents an experimental setup to simulate the cleanup process of plugged screens by rotary water jetting on the surface and to evaluate the performance of a jetting tool.Using real plugged screens pulled from damaged wells,a series of tests were performed,and the qualitative relationships between the cleanup efficiency and various operational parameters,such as the type of fluids used,flow rate,mode of tool movement,etc.,were obtained.The test results indicated that the cleanup performance was much better when the rotary jetting tool moved and stopped periodically for a certain time than that when it reciprocated at a constant speed.To be exact,it was desirable for the rotary jetting tool to move for 1.5-2 m and stop for 2-4 min,which was called the ＂move-stop-move＂ mode.Good cleanup performance could be obtained at high flow rates,and the flow rate was recommended to be no lower than 550-600 L/min.The test results also indicated that complex mud acid was better than clean water in terms of cleanup performance.Good cleanup efficiency and high screen permeability recovery could be achieved for severely plugged screens.Rotary jetting is preferred for the cleanup of horizontal wells with severely plugged screens,and the screen permeability recovery ratio may reach 20％ if optimized operation parameters were used.

A mathematical model for optimized operation and controlin a CDQ-Boiler system

Based on analyzing the thermal process of a CDQ （coke dry quenching）-Boiler system, the mathematical model for opti-mized operation and control in the CDQ-Boiler system was developed. It includes a mathematical model for heat transferring process in the CDQ unit, a mathematical model for heat transferring process in the boiler and a combustion model for circulating gas in the CDQ-Boiler system. The model was verified by field data, then a series of simulations under several typical operating conditions of CDQ-Boiler were carried on, and in turn, the online relation formulas between the productivity and the optimal circulating gas, and the one between the productivity and the optimal second air, were achieved respectively. These relation equations have been success- fully used in a CDQ-Boiler computer control system in the Baosteel, to realize online optimized guide and control, and meanwhile high efficiency in the CDQ-Boiler system has been achieved.

A train timetable rescheduling approach based on multi-train tracking optimization of high-speed railways

Purpose–This paper aims to propose a train timetable rescheduling(TTR)approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.Design/methodology/approach–Firstly,a single-train trajectory optimization(STTO)model is constructed based on train dynamics and operating conditions.The train kinematics parameters,including acceleration,speed and time at each position,are calculated to predict the arrival times in the train timetable.A STTO algorithm is developed to optimize a single-train time-efficient driving strategy.Then,a TTR approach based on multi-train tracking optimization(TTR-MTTO)is proposed with mutual information.The constraints of temporary speed restriction(TSR)and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train.The multi-train trajectories at each position are optimized to generate a timeefficient train timetable.Findings–The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF.The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay(TTD).As for the TSR scenario,the proposed TTR-MTTO can reduce TTD by 60.60%compared with the traditional TTR approach with dispatchers’experience.Moreover,TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.Originality/value–With the cooperative relationship and mutual information between train rescheduling and control,the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.

Output neighboring-extremal and NCO tracking control in the optimal operation of CSTR

A new optimizing framework of process operation is proposed to deal with optimizing op- eration of continuous stirred tank reactor （CSTR）. The optimization framework includes two layers： the first layer, necessary condition of optimally （NCO） tracking controller, calculates the optimal set-point of the process; and the second layer, output neighboring-extremal controller, calculates the input values of the controlled plant. The algorithm design and convergent analysis of output neighboring-extremal controller are discussed emphatically, and in the case of existing parametric uncertainty, the approach is shown to converge to the optimum atmost in two iterations. At last the approach is illustrated by simulation results for a dynamic CSTR.

Time-Optimal Control Problem for <i>n</i>×<i>n</i>Co-Operative Parabolic Systems with Control in Initial Conditions

In this paper, time-optimal control problem for a liner n× n co-operative parabolic system involving Laplace operator is considered. This problem is, steering an initial state y(0)=u?, with control u?so that an observation y(t) hitting a given target set in minimum time. First, the existence and uniqueness of solutions of such system under conditions on the coefficients are proved. Afterwards necessary and sufficient conditions of optimality are obtained. Finally a scaler case is given.

Analytic optimal pose tracking control in close-range proximity operations with a non-cooperative target

This paper investigates an analytical optimal pose tracking control problem for chaser spacecraft during the close-range proximity operations with a non-cooperative space target subject to attitude tumbling and unknown orbital maneuvering.Firstly,the relative translational motion between the orbital target and the chaser spacecraft is described in the Line-of-Sight(LOS)coordinate frame along with attitude quaternion dynamics.Then,based on the coupled 6-Degree of Freedom(DOF)pose dynamic model,an analytical optimal control action consisting of constrained optimal control value,application time and its duration are proposed via exploring the iterative sequential action control algorithm.Meanwhile,the global closed-loop asymptotic stability of the proposed predictive control action is presented and discussed.Compared with traditional proximity control schemes,the highlighting advantages are that the application time and duration of the devised controller is applied discretely in light of the influence of the instantaneous pose configuration on the pose tracking performance with less energy consumptions rather than at each sample time.Finally,three groups of illustrative examples are organized to validate the effectiveness of the proposed analytical optimal pose tracking control scheme.

A Predator-prey Particle Swarm Optimization Approach to Multiple UCAV Air Combat Modeled by Dynamic Game Theory

Dynamic game theory has received considerable attention as a promising technique for formulating control actions for agents in an extended complex enterprise that involves an adversary. At each decision making step, each side seeks the best scheme with the purpose of maximizing its own objective function. In this paper, a game theoretic approach based on predatorprey particle swarm optimization(PP-PSO) is presented, and the dynamic task assignment problem for multiple unmanned combat aerial vehicles(UCAVs) in military operation is decomposed and modeled as a two-player game at each decision stage. The optimal assignment scheme of each stage is regarded as a mixed Nash equilibrium, which can be solved by using the PP-PSO. The effectiveness of our proposed methodology is verified by a typical example of an air military operation that involves two opposing forces: the attacking force Red and the defense force Blue.

Solving chemical dynamic optimization problems with ranking-based differential evolution algorithms

Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-differentiable or explicit mathematical descriptions do not exist. Recently, evolutionary algorithms are gaining popularity for DOPs as they can be used as robust alternatives when the deterministic techniques are invalid. In this article, a technology named ranking-based mutation operator(RMO) is presented to enhance the previous differential evolution(DE) algorithms to solve DOPs using control vector parameterization. In the RMO, better individuals have higher probabilities to produce offspring, which is helpful for the performance enhancement of DE algorithms. Three DE-RMO algorithms are designed by incorporating the RMO. The three DE-RMO algorithms and their three original DE algorithms are applied to solve four constrained DOPs from the literature. Our simulation results indicate that DE-RMO algorithms exhibit better performance than previous non-ranking DE algorithms and other four evolutionary algorithms.

Optimal control of quadratic functionals for affine nonlinear systems

In this paper we analyze the optimal control problem for a class of afflne nonlinear systems under the assumption that the associated Lie algebra is nilpotent. The Lie brackets generated by the vector fields which define the nonlinear system represent a remarkable mathematical instrument for the control of affine systems. We determine the optimal control which corresponds to the nilpotent operator of the first order. In particular, we obtain the control that minimizes the energy of the given nonlinear system. Applications of this control to bilinear systems with first order nilpotent operator are considered.

Computing Open-Loop Optimal Control of the q-Profile in Ramp-Up Tokamak Plasmas Using the Minimal-Surface Theory

The q-profile control problem in the ramp-up phase of plasma discharges is consid- ered in this work. The magnetic diffusion partial differential equation （PDE） models the dynamics of the poloidal magnetic flux profile, which is used in this work to formulate a PDE-constrained op-timization problem under a quasi-static assumption. The minimum surface theory and constrained numeric optimization are then applied to achieve suboptimal solutions. Since the transient dy- namics is pre-given by the minimum surface theory, then this method can dramatically accelerate the solution process. In order to be robust under external uncertainties in real implementations, PID （proportional-integral-derivative） controllers are used to force the actuators to follow the computational input trajectories. It has the potential to implement in real-time for long time discharges by combining this method with the magnetic equilibrium update.

Existence and Uniqueness of the Optimal Control in Hilbert Spaces for a Class of Linear Systems

We analyze the existence and uniqueness of the optimal control for a class of exactly controllable linear systems. We are interested in the minimization of time, energy and final manifold in transfer problems. The state variables space X and, respectively, the control variables space U, are considered to be Hilbert spaces. The linear operator T(t) which defines the solution of the linear control system is a strong semigroup. Our analysis is based on some results from the theory of linear operators and functional analysis. The results obtained in this paper are based on the properties of linear operators and on some theorems from functional analysis.

The performance analysis and calculation for variable frequency speed control motors with the rotor structure optimized

In the paper, the method to optimize the rotor structure in variable frequency speed control motors is introduced. The saturation and the skin effect are considered and 2D no-load and load electromagnetic field is calculated in finite elements for a variable frequency speed control motor before and after optimization. Finally, no-load current and operation performance before and after optimization are obtained and the two results are contrasted.

机力通风冷却塔风机自寻优群控方法研究

机力通风冷却塔以占地面积小的显著优点,在中小型基建工程中得到广泛应用。为提升中小型基建工程外冷系统的节能性和可靠性、改进传统多风机控制方法,创新性地提出了一种基于累计运行时间的机力通风冷却塔风机自寻优群控方法。将多风机整体化控制改进为顺序化联动控制,可有效降低风机启动门槛出力、消除整体化控制固有缺陷,满足非线性、时变性、大滞后系统控制的节能、可靠需求。经工程验证:该方法是一种契合纯变频电机配置冷却塔系统的多风机控制方法。该方法风机出力柔和、控制线性度好、系统易镇定、稳态偏差小;能够通过累计运行时间参数比对,实现风机自动交互运行,运行可靠性高。该方法的提出与实际应用可对配置机力通风冷却塔的中小型基建工程的安全节能运行提供借鉴。

4DI110型空压机的技术改造与操作优化

文章通过介绍新引进的4DI110型离心式空压机(以下简称“空压机”)试运行阶段开始以来的运行情况和气温变化对空压机出口流量造成的影响,分析空压机出口流量随气温变化而变化的规律,指出空压机防喘阀V3004阀不能自动调节出口压力,影响空分装置工况的稳定。为实现空压机出口压力的稳定,对其防喘阀V3004阀采取增设自动旁路阀V3008阀的技术改造,同时优化和完善相关逻辑控制并阐述了空压机经技术改造后的操作优化和取得的实际效果。

混合能源直流微电网能源优化管控策略研究

混合能源直流微电网在快速跟踪负载方面具有较大优势,弥补了固体氧化物燃料电池(solidoxidefuelcell,SOFC)直流微电网功率跟踪缓慢的问题。现有能源管控策略重点关注能源分配,对系统效率、运行安全性和燃料亏空方面缺乏相关研究和成熟策略。为此,提出了一种混合能源直流微型电网能源优化管控策略。首先,搭建了混合SOFC直流微电网模型。其次,采用最优操作点(optimal operating points,OOPs)实现最大效率,然后采用平均电流控制模式保证稳定的电力供应。最后,设计了基于SOFC电流的时滞控制算法来避免燃料亏空。实验结果表明,所提出的能源优化管控策略具有时间响应迅速、输出效率高和热特性良好等优势。

复合干扰作用下基于干扰观测器的系统运行优化控制

为了优化实际工业系统性能,降低损耗,针对不同类型干扰同时作用的系统,提出一种改进的两层运行优化控制算法来解决干扰对控制系统带来的影响。首先,采取传统两层运行优化控制框架结构,在底层设计PID控制器来保证控制系统的跟踪性能,使得系统的输出能尽可能地跟踪设定值;其次,根据作用于系统的复合噪声类型,结合H_(∞)方法在上层设计干扰观测器以及补偿控制器进行干扰抑制,以使系统的输出能够跟踪最优设定值;最后,通过数值仿真验证该方法的有效性。

考虑制氢效率优化的氢-储-风直流微网功率协调控制

利用风电等新能源制氢是提高新能源消纳能力的一种有效技术手段。为适应风电及负荷功率的波动性并确保制氢电解槽高效运行,提出一种考虑制氢效率优化运行需求的氢-储-风直流微网功率协调控制方法。根据制氢电解槽优化运行区间和直流母线电压波动范围,将直流微网划分为正常运行模式(即制氢电解槽优化运行)和极端运行模式(即制氢电解槽非优化运行)。在正常运行模式下,通过电解槽的自适应下垂控制和电池储能含虚拟电容的变系数下垂控制,将电解槽运行点维持在优化运行区间内,保证电解槽高效安全运行;在极端运行模式下,通过氢/储控制策略灵活切换以确保直流微网电压安全。所提协调控制方法不但可快速抑制风电及负荷功率波动所引发的直流母线电压波动,而且可维持制氢效率处于较高水平。最后,通过PSCAD/EMTDC的仿真算例分析验证了所提方法的有效性和优越性。