Evaluation of Effectiveness of Integrated Intervention Program in Improving Drug Addicts' Psychological Health

Objective To investigate the social mental state of drug addicts in a compulsive drug abuse treatment center; evaluate the effectiveness of integrated program for the prevention of abuse relapse and improvement of drug addicts＇ psychological health. Methods The study subjects were addicts from the Wuhan Compulsive Drug Abuse Treatment Center between October 2003 and June 2004, who satisfied the inclusion criteria. A non-randomized control-intervention study design was adopted. Volunteers willing to take part in intervention were put into the intervention group with their full awareness and willingness to prevent drug abuse relapse. The control group was composed of the addicts who were willing to prevent relapse and to be followed up after their discharge. Results The effectiveness of the integrated intervention program in promoting addicts＇ psychological health： before the intervention, the scores of Self-Rating Anxiety Scale （SAS）, the positive and negative dimensionalities of Simple Coping Style Questionnaire （SCSQ） and Chinese Perceived Stress Scales （CPSS） had no significant differences between the intervention group and the control group. After the intervention, except that the SCSQ＇s positive dimensionality in the intervention group was significantly higher than that in the control group, other indices in the intervention group were lower. Before and after the intervention, the psychological health level in both the groups was lower than that in the normal population; there were significant differences between addicts and normal subjects in regards with all of the indices above. Conclusion Drug abuse was associated closely with addicts＇ social mental factors. The integrated intervention program can alleviate anxiety and stress, reduce co-morbid mental disorders and effectively improve their coping style. In conclusion, the program can promote addicts＇ psychological health significantly.

An integrated pest management program for managing fusarium head blight disease in cereals

Fusarium head blight(FHB)is a worldwide devastating disease of small grain cereals and Fusarium graminearum species complex(FGSC)is the major pathogen causing the disease.The epidemics of FHB lead to the reduction of grain yield and economic losses.Additionally,mycotoxins produced by the FHB pathogens are hazardous to the health of human and livestock.In this review,we summarize the epidemiology of FHB,and introduce effects of this disease on economy,environment and food safety.We focus on the integrated management approaches for controlling FHB including agronomic practices,resistant cultivars,chemical control,and biocontrol.In addition,we also discuss the potential novel management strategies against FHB and mycotoxin.

Novel integrated optimization algorithm for trajectory planning of robot manipulators based on integrated evolutionary programming

Optimal trajectory planning for robot manipulators plays an important role in implementing the high productivity for robots. The performance indexes used in optimal trajectory planning are classified into two main categories: optimum traveling time and optimum mechanical energy of the actuators. The current trajectory planning algorithms are designed based on one of the above two performance indexes. So far, there have been few planning algorithms designed to satisfy two performance indexes simultaneously. On the other hand, some deficiencies arise in the existing integrated optimi2ation algorithms of trajectory planning. In order to overcome those deficiencies, the integrated optimization algorithms of trajectory planning are presented based on the complete analysis for trajectory planning of robot manipulators. In the algorithm, two object functions are designed based on the specific weight coefficient method and ' ideal point strategy. Moreover, based on the features of optimization problem, the intensified evolutionary programming is proposed to solve the corresponding optimization model. Especially, for the Stanford Robot,the high-quality solutions are found at a lower cost.

Joint Active and Passive Beamforming Design for Hybrid RIS-Aided Integrated Sensing and Communication

Integrated sensing and communication(ISAC) is considered an effective technique to solve spectrum congestion in the future. In this paper, we consider a hybrid reconfigurable intelligent surface(RIS)-assisted downlink ISAC system that simultaneously serves multiple single-antenna communication users and senses multiple targets. Hybrid RIS differs from fully passive RIS in that it is composed of both active and passive elements, with the active elements having the effect of amplifying the signal in addition to phase-shifting. We maximize the achievable sum rate of communication users by collaboratively improving the beamforming matrix at the dual function base station(DFBS) and the phase-shifting matrix of the hybrid RIS, subject to the transmit power constraint at the DFBS, the signal-to-interference-plus-noise-ratio(SINR) constraint of the radar echo signal and the RIS constraint are satisfied at the same time. The builtin RIS-assisted ISAC design problem model is significantly non-convex due to the fractional objective function of this optimization problem and the coupling of the optimization variables in the objective function and constraints. As a result, we provide an effective alternating optimization approach based on fractional programming(FP) with block coordinate descent(BCD)to solve the optimization variables. Results from simulations show that the hybrid RIS-assisted ISAC system outperforms the other benchmark solutions.

Enhancing Data Analysis and Automation: Integrating Python with Microsoft Excel for Non-Programmers

Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision-making across diverse domains. Conversely, Python is indispensable for professional programming due to its versatility, readability, extensive libraries, and robust community support. It enables efficient development, advanced data analysis, data mining, and automation, catering to diverse industries and applications. However, one primary issue when using Microsoft Excel with Python libraries is compatibility and interoperability. While Excel is a widely used tool for data storage and analysis, it may not seamlessly integrate with Python libraries, leading to challenges in reading and writing data, especially in complex or large datasets. Additionally, manipulating Excel files with Python may not always preserve formatting or formulas accurately, potentially affecting data integrity. Moreover, dependency on Excel’s graphical user interface (GUI) for automation can limit scalability and reproducibility compared to Python’s scripting capabilities. This paper covers the integration solution of empowering non-programmers to leverage Python’s capabilities within the familiar Excel environment. This enables users to perform advanced data analysis and automation tasks without requiring extensive programming knowledge. Based on Soliciting feedback from non-programmers who have tested the integration solution, the case study shows how the solution evaluates the ease of implementation, performance, and compatibility of Python with Excel versions.

APPLICATION OF HYBRID AERO-ENGINE MODEL FOR INTEGRATED FLIGHT/PROPULSION OPTIMAL CONTROL

The real-time capability of integrated flight/propulsion optimal control （IFPOC） is studied. An appli- cation is proposed for IFPOC by combining the onboard hybrid aero-engine model with sequential quadratic pro- gramming （SQP）. Firstly, a steady-state hybrid aero-engine model is designed in the whole flight envelope with a dramatic enhancement of real-time capability. Secondly, the aero-engine performance seeking control including the maximum thrust mode and the minimum fuel-consumption mode is performed by SQP. Finally, digital simu- lations for cruise and accelerating flight are carried out. Results show that the proposed method improves real- time capability considerably with satisfactory effectiveness of optimization.

A COMBINED PARAMETRIC QUADRATIC PROGRAMMING AND PRECISE INTEGRATION METHOD BASED DYNAMIC ANALYSIS OF ELASTIC-PLASTIC HARDENING/SOFTENING PROBLEMS

The objective of the paper is to develop a new algorithm for numerical solution of dynamic elastic-plastic strain hardening/softening problems. The gradient dependent model is adopted in the numerical model to overcome the result mesh-sensitivity problem in the dynamic strain softening or strain localization analysis. The equations for the dynamic elastic-plastic problems are derived in terms of the parametric variational principle, which is valid for associated, non-associated and strain softening plastic constitutive models in the finite element analysis. The precise integration method, which has been widely used for discretization in time domain of the linear problems, is introduced for the solution of dynamic nonlinear equations. The new algorithm proposed is based on the combination of the parametric quadratic programming method and the precise integration method and has all the advantages in both of the algorithms. Results of numerical examples demonstrate not only the validity, but also the advantages of the algorithm proposed for the numerical solution of nonlinear dynamic problems.

Integrated reliability of travel time and capacity of urban road network under ice and snowfall conditions

In order to evaluate and integrate travel time reliability and capacity reliability of a road network subjected to ice and snowfall conditions,the conceptions of travel time reliability and capacity reliability were defined under special conditions.The link travel time model(ice and snowfall based-bureau public road,ISB-BPR) and the path choice decision model(elastic demand user equilibrium,EDUE) were proposed.The integrated reliability was defined and the model was set up.Monte Carlo simulation was used to calculate the model and a numerical example was provided to demonstrate the application of the model and efficiency of the solution algorithm.The results show that the intensity of ice and snowfall,the traffic demand and supply,and the requirements for level of service(LOS) have great influence on the reliability of a road network.For example,the reliability drops from 65% to 5% when the traffic demand increases by 30%.The comprehensive performance index may be used for network planning,design and maintenance.

Key technologies for the novel distributed numerical control integrated system

A novel distributed numerical control (DNC) integrated system based on plug-in software technology is proposed. It connects new or old numerical control (NC) machine tools which have inhomogeneous numerical control systems with CAD/CAM system by CANbus network. A DNC computer is able to control 15 sets of NC machine tools reliably at the same time. The novel DNC system increases the efficiency of machine tools and improve the production management level by realizing non-paper production, agile manufacturing, networked manufacturing and so on in the near future. Key technologies to construct the novel DNC integrated system include the integration of inhomogeneous numerical control systems, NC program restart, and algorithm for communication competition. Such system has demonstrated successful applications in some corporations that have acquired good economic benefits and social effects.

A stable implicit nodal integration-based particle finite element method(N-PFEM)for modelling saturated soil dynamics

In this study,we present a novel nodal integration-based particle finite element method(N-PFEM)designed for the dynamic analysis of saturated soils.Our approach incorporates the nodal integration technique into a generalised Hellinger-Reissner(HR)variational principle,creating an implicit PFEM formulation.To mitigate the volumetric locking issue in low-order elements,we employ a node-based strain smoothing technique.By discretising field variables at the centre of smoothing cells,we achieve nodal integration over cells,eliminating the need for sophisticated mapping operations after re-meshing in the PFEM.We express the discretised governing equations as a min-max optimisation problem,which is further reformulated as a standard second-order cone programming(SOCP)problem.Stresses,pore water pressure,and displacements are simultaneously determined using the advanced primal-dual interior point method.Consequently,our numerical model offers improved accuracy for stresses and pore water pressure compared to the displacement-based PFEM formulation.Numerical experiments demonstrate that the N-PFEM efficiently captures both transient and long-term hydro-mechanical behaviour of saturated soils with high accuracy,obviating the need for stabilisation or regularisation techniques commonly employed in other nodal integration-based PFEM approaches.This work holds significant implications for the development of robust and accurate numerical tools for studying saturated soil dynamics.

Three-scale integrated optimization model of furnace simulation,cyclic scheduling,and supply chain of ethylene plants

In order to explore the potential of profit margin improvement,a novel three-scale integrated optimization model of furnace simulation,cyclic scheduling,and supply chain of ethylene plants is proposed and evaluated.A decoupling strategy is proposed for the solution of the three-scale model,which uses our previously proposed reactor scale model for operation optimization and then transfers the obtained results as a parameter table in the joint MILP optimization of plant-supply chain scale for cyclic scheduling.This optimization framework simplifies the fundamental mixed-integer nonlinear programming(MINLP)into several sub-models,and improves the interpretability and extendibility.In the evaluation of an industrial case,a profit increase at a percentage of 3.25%is attained in optimization compared to the practical operations.Further sensitivity analysis is carried out for strategy evolving study when price policy,supply chain,and production requirement parameters are varied.These results could provide useful suggestions for petrochemical enterprises on thermal cracking production.

Recent Progresses on Optimal Design of Heat Integrated Water Allocation Network

Energy integration and mass integration are important approaches to achieve energy saving and emission reduction in the process industry.Generally,the methods can be classified into two groups,viz.:conceptual design methods and mathematical programming methods.The former includes mainly graphical methods based on pinch technology that is operated easily.A feasible solution can be quickly obtained.Conceptual design methods are sequential in nature including two steps,namely:targeting and designing.The latter is based on superstructure optimization,and corresponding algorithm is adopted to solve the model.The trade-offs and connections among the entire network can be established and explored.Multiple factors can be considered and optimized simultaneously by mathematical programming methods.This paper describes the synthesis of heat integrated water allocation networks(HIWAN)based on both conceptual design methods and mathematical programming methods systematically.In addition,the characteristics and shortcomings of the existing research methods are summarized,and the future research direction is prospected.

An Exploratory Practice of Integration of Industry and Education in High-level Programming Language Course in the Background of New Engineering

This paper analyzes some problems of the current teaching situation in the course High-level Programming Language,such as the lagging content of the course compared with technology development,the emphasis on theory rather than on practice,the low enthusiasm of students for learning,and the weak practical ability of students.In response to the needs of enterprises for talents under the background of New Engineering,especially the cultivation of students’adaptability and practical abilities towards future industries to improve students’knowledge and problemsolving abilities to keep up with the modern technology,this paper proposes the ways and methods to reform and explore the teaching content and teaching methods by integrating industry and education,assisting teaching according to industrial demands,and lowering technology barriers of new technology.The practical effect is evaluated through a survey in class and the follow-up questionnaire after class,and the results show that the effect of the practice is effective.

An Empirical Application of User-Guided Program Analysis

Although static program analysis methods are frequently employed to enhance software quality,their efficiency in commercial settings is limited by their high false positive rate.The EUGENE tool can effectively lower the false positive rate.However,in continuous integration(CI)environments,the code is always changing,and user feedback from one version of the software cannot be applied to a subsequent version.Additionally,people find it difficult to distinguish between true positives and false positives in the analytical output.In this study,we developed the EUGENE-CI technique to address the CI problem and the EUGENE-rank lightweight heuristic algorithm to rate the reports of the analysis output in accordance with the likelihood that they are true positives.On the three projects ethereum,go-cloud,and kubernetes,we assessed our methodologies.According to the trial findings,EUGENE-CI may drastically reduce false positives while EUGENE-rank can make it much easier for users to identify the real positives among a vast number of reports.We paired our techniques with GoInsight~1 and discovered a vulnerability.We also offered a patch to the community.

Optimization of Training Program for Land Resource Management Major under the Background of Urban and Rural Integration

With constant deepening of development outlook of urban and rural integration,education circle starts to attach great importance to reform of personnel training program.Since scarcity of land resource and key role of land management in urban and rural integration,it is urgent to optimize the personnel training program for land resource management major.From aspects of optimum objectives,principles,program and implementation effect,this paper discusses training program for land resource management major under the background of urban and rural integration.It is expected to provide reference for cultivating land resource management personnel suitable for development of urban and rural integration.

Real-time Risk-averse Dispatch of an Integrated Electricity and Natural Gas System via Condi-tional Value-at-risk-based Lookup-table Ap-proximate Dynamic Programming

The real-time risk-averse dispatch problem of an integrated electricity and natural gas system(IEGS)is studied in this paper.It is formulated as a real-time conditional value-at-risk(CVaR)-based risk-averse dis-patch model in the Markov decision process framework.Because of its stochasticity,nonconvexity and nonlinearity,the model is difficult to analyze by traditional algorithms in an acceptable time.To address this non-deterministic polynomial-hard problem,a CVaR-based lookup-table approximate dynamic programming(CVaR-ADP)algo-rithm is proposed,and the risk-averse dispatch problem is decoupled into a series of tractable subproblems.The line pack is used as the state variable to describe the impact of one period’s decision on the future.This facilitates the reduction of load shedding and wind power curtailment.Through the proposed method,real-time decisions can be made according to the current information,while the value functions can be used to overview the whole opti-mization horizon to balance the current cost and future risk loss.Numerical simulations indicate that the pro-posed method can effectively measure and control the risk costs in extreme scenarios.Moreover,the decisions can be made within 10 s,which meets the requirement of the real-time dispatch of an IEGS.Index Terms—Integrated electricity and natural gas system,approximate dynamic programming,real-time dispatch,risk-averse,conditional value-at-risk.

Wire Bonding Using Offline Programming Method

Manual process of creating bonding diagram is known to be time consuming and error prone. In comparison, offline programming (OLP) provides a much more viable option to reduce the wire bonding creation time and error. OLP is available in two versions, i.e., vendor specific OLP and direct integration offline pro- gramming (Di-OLP). Both versions utilize the bonding diagram and computer aided design data to speed up bonding program creation. However, the newly proposed Di-OLP is more flexible as it can be used to create bonding program for multiple machine platforms in microelectronics industry. Some special features of Di-OLP method are presented. The application of generic OLP however, is applicable to machines that recognize ASCII text file. The user needs to know the data format accepted by machine and convert the data accordingly to suit its application for different machine platforms. Di-OLP is also a practical method to replace the time consuming manual method in production line.

STOCHASTIC OPTIMAL CONTROL FOR THE RESPONSE OF QUASI NON-INTEGRABLE HAMILTONIAN SYSTEMS

A strategy is proposed based on the stochastic averaging method for quasi non- integrable Hamiltonian systems and the stochastic dynamical programming principle.The pro- posed strategy can be used to design nonlinear stochastic optimal control to minimize the response of quasi non-integrable Hamiltonian systems subject to Gaussian white noise excitation.By using the stochastic averaging method for quasi non-integrable Hamiltonian systems the equations of motion of a controlled quasi non-integrable Hamiltonian system is reduced to a one-dimensional av- eraged It stochastic differential equation.By using the stochastic dynamical programming princi- ple the dynamical programming equation for minimizing the response of the system is formulated. The optimal control law is derived from the dynamical programming equation and the bounded control constraints.The response of optimally controlled systems is predicted through solving the FPK equation associated with It stochastic differential equation.An example is worked out in detail to illustrate the application of the control strategy proposed.

Computer Program Calculation for Distortion of Wide-Band Track and Hold Amplifier

Tow different computer calculation methods for distortion of the wide-band diode bridge track and hold amplifier (THA) are presented based on a high frequency Schottky diode model. One of the computer programs calculates the distortion of weekly nonlinear THA based on the KCL and the nonlinear-current method. The other calculates the weekly nonlinear distortion by using a Volterra series method and a nodal formulation. Comparative calculation results for the diode bridge THA have shown good agreement with these two computer program calculation methods, whereas the overall computational efficiency of the nonlinear-current method is better than that of the nodal formulation method in a special evaluation.

A New Approach for a Class of Optimal Control Problems of Volterra Integral Equations

In this paper, we propose a new approach for a class of optimal control problems governed by Volterra integral equations which is based on linear combination property of intervals. We convert the nonlinear terms in constraints of problem to the corresponding linear terms. Discretization method is also applied to convert the new problems to the discrete-time problem. In addition, some numerical examples are presented to illustrate the effectiveness of the proposed approach.