Retrograde intrarenal surgery for lower pole stones utilizing stone displacement technique yields excellent results

Objective:To evaluate the long-term stone-free rate(SFR)of retrograde intrarenal surgery(RIRS)in the treatment of lower pole renal calculi using only basket relocation and identify independent predictors of stone-free status.Methods:All consecutive patients undergoing RIRS lower pole renal calculi at a single highvolume tertiary center were analyzed retrospectively.Lower pole stones were relocated to the upper pole,where laser lithotripsy was performed.All patients were followed up in the clinic following the surgery and yearly thereafter.The stone-free status was assessed with a combination of an abdominal ultrasound and abdominal X-ray,or an abdominal non-contrast computed tomography if the stones were known to be radiolucent.Results:A total of 480 consecutive patients who underwent RIRS for treatment of lower pole renal calculi,between January 2012 and December 2018,were analyzed from a prospectively maintained database of 3000 ureteroscopies.With a median follow-up time of 18.6 months,the mean SFR was 94.8%.The procedures were unsuccessful in 26(5.4%)patients due to unreachable stones.The median stone size of the unreachable stones was 12 mm(range 10e30 mm).Multivariable logistic regression analysis revealed two predictors of SFR for lower pole stones:a small cumulative stone burden(odds ratio[OR]:0.903,95%confidence interval[CI]:0.867e0.941,p<0.0001)and preoperative ureteral stent insertion(OR:0.515,95%CI:0.318e0.835,pZ0.007).Conclusion:The long-term SFR of RIRS for the treatment of lower pole stones with basket displacement with appropriate patient selection is high.

Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources.However,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud computing.An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing costs.This approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of applications.In this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing cost.We consider four cost-types for application deployment:Computation,communication,energy consumption,and violations.The proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the system.An extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art approaches.The results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.

Layered Coded Cache Placement and Cooperative Delivery with Sharing Links in Satellite-Terrestrial Integrated Networks

Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.

Characteristics of proppant transport and placement within rough hydraulic fractures

A three-dimensional reconstruction of rough fracture surfaces of hydraulically fractured rock outcrops is carried out by casting process,a large-scale experimental setup for visualizing rough fractures is built to perform proppant transport experiments.The typical characteristics of proppant transport and placement in rough fractures and its intrinsic mechanisms are investigated,and the influences of fracture inclination,fracture width and fracturing fluid viscosity on proppant transport and placement in rough fractures are analyzed.The results show that the rough fractures cause variations in the shape of the flow channel and the fluid flow pattern,resulting in the bridging buildup during proppant transport to form unfilled zone,the emergence of multiple complex flow patterns such as channeling,reverse flow and bypassing of sand-carrying fluid,and the influence on the stability of the sand dune.The proppant has a higher placement rate in inclined rough fractures,with a maximum increase of 22.16 percentage points in the experiments compared to vertical fractures,but exhibits poor stability of the sand dune.Reduced fracture width aggravates the bridging of proppant and induces higher pumping pressure.Increasing the viscosity of the fracturing fluid can weaken the proppant bridging phenomenon caused by the rough fractures.

Efficient Digital Twin Placement for Blockchain-Empowered Wireless Computing Power Network

As an open network architecture,Wireless Computing PowerNetworks(WCPN)pose newchallenges for achieving efficient and secure resource management in networks,because of issues such as insecure communication channels and untrusted device terminals.Blockchain,as a shared,immutable distributed ledger,provides a secure resource management solution for WCPN.However,integrating blockchain into WCPN faces challenges like device heterogeneity,monitoring communication states,and dynamic network nature.Whereas Digital Twins(DT)can accurately maintain digital models of physical entities through real-time data updates and self-learning,enabling continuous optimization of WCPN,improving synchronization performance,ensuring real-time accuracy,and supporting smooth operation of WCPN services.In this paper,we propose a DT for blockchain-empowered WCPN architecture that guarantees real-time data transmission between physical entities and digital models.We adopt an enumeration-based optimal placement algorithm(EOPA)and an improved simulated annealing-based near-optimal placement algorithm(ISAPA)to achieve minimum average DT synchronization latency under the constraint of DT error.Numerical results show that the proposed solution in this paper outperforms benchmarks in terms of average synchronization latency.

Analysis of the Application Effect of Tracheal Stent Placement in the Nutritional Support Treatment of Tracheoesophageal Fistula

Objective:To evaluate and analyze the application effect of tracheal stent placement in nutritional support therapy for tracheoesophageal fistula.Methods:Clinical data of 32 patients who underwent nutritional support therapy for tracheoesophageal fistula in our hospital from September 2021 to September 2022 were collected,and all patients underwent tracheal silicone stenting,comparing dyspnea classification and Karnofsky score before and after stenting,and conducting post-treatment follow-up.Results:In 32 patients with tracheoesophageal fistula,dyspnea grading improved from grades III and IV to grades 0 to II.Before treatment,10 patients(31.06%)were in grade IV,17 patients(53.12%)were in grade III,and five patients(15.62)were in grade II;after treatment,13 patients(40.63%)were in grade I,12 patients(37.50%)were in grade I,and seven patients(21.87%)were in grade 0(P<0.05);Karnofsky score(37.52±4.86 before treatment)improved significantly to 71.39±8.24 one week after treatment(P<0.05).Nine patients with tracheoesophageal fistula were placed with silicone Y14-10-10 stent,11 with silicone 18-14-14 stent,three with silicone Y15-12-12,and seven with silicone stent 16-13-13.Conclusion:Silicone tracheobronchial stent placement for the treatment of tracheoesophageal fistula is technically feasible,simple,and safe,with reliable near-term efficacy,and is worthy of popularization and application.

Clinical Study on Improving Articulation Clarity in Spastic Cerebral Palsy with 120 Cases of Oral-Facial Acupressure Combined with Oral Placement Therapy

Objective:To observe the efficacy of oral-facial acupressure combined with oral placement therapy(OPT)in improving articulation clarity in 120 children with spastic cerebral palsy,and to explore effective therapeutic solutions for speech disorders associated with spastic cerebral palsy.Methods:A total of 120 children with spastic cerebral palsy and speech disorders,meeting the inclusion criteria,were randomly assigned into two groups:60 cases in the treatment group and 60 cases in the control group.The treatment group received orofacial acupressure combined with OPT,while the control group received only OPT.The Oral Motor Function Assessment Scale(OMFAS),developed by the China Rehabilitation Research Centre(CRRC),was used to evaluate the treatment outcomes before and after the intervention.Results:After the treatment,both the treatment and control groups showed improved mobility of the mandible,lips,and tongue.However,the treatment group exhibited significantly better improvement than the control group,with the difference between the two groups being statistically significant(P<0.05).Conclusion:Oral-facial acupressure combined with OPT can effectively improve articulation clarity in children with spastic cerebral palsy.This combined therapy is recommended for clinical promotion and application.

Pole placement method of controlling chaos in DC-DC buck converters

Based on the mechanism for the generation of chaos in a buck converter, a pole placement method is proposed and applied to controlling the chaos in a circuit. The control circuit is designed and tested. Numerical calculation and circuit implementation demonstrate the validity of this chaos control method.

Control strategy for pneumatic rotary position servo systems based on feed forward compensation pole-placement self-tuning method

The pneumatic rotary position system, in which an electro-pneumatic proportional flow valve controled a rotary cylinder, was studied, and its mathematical model was built. The model indicated that the controlled pneumatic system had disadvantages such as inherent non-linearity and variations of system parameters with working points. In order to improve the dynamic performance of the system, feed forward compensation self-tuning pole-placement strategy was adopted to place the poles of the system in a desired position in real time, and a recursive least square method with fixed forgetting factors was also used in the parameter estimation. Experimental results show that the steady state error of the pneumatic rotary position system is within 3% and the identified system parameters can be converged in 5 s. Under different loads, the controlled system has an excellent tracking performance and robustness of anti-disturbance.

Erratum to“A note on overshoot estimation in pole placements”

There is a mild flaw in the statement of Proposition 2.1 in the above paper （cf. [1] ）. We restate it as follows.

An Improvement on Data-Driven Pole Placement for State Feedback Control and Model Identification

The recently proposed data-driven pole placement method is able to make use of measurement data to simultaneously identify a state space model and derive pole placement state feedback gain. It can achieve this precisely for systems that are linear time-invariant and for which noiseless measurement datasets are available. However, for nonlinear systems, and/or when the only noisy measurement datasets available contain noise, this approach is unable to yield satisfactory results. In this study, we investigated the effect on data-driven pole placement performance of introducing a prefilter to reduce the noise present in datasets. Using numerical simulations of a self-balancing robot, we demonstrated the important role that prefiltering can play in reducing the interference caused by noise.

NN adaptive pole placement method for sintering finish point control

A neural network model with a special structure, which is divided into linearand nonlinear parts, was proposed for identification of a nonlinear system. In this model, thenonlinear part of the object is treated as a measured disturbance, and is compensated by a feedforward method; an adaptive pole placement algorithm is used to control the linear part of theobject. The simulation results show that the identification efficiency and accuracy are improvedwhen the new controller is applied to sintering finish point control.

POLE PLACEMENT CONTROLLERS FOR LINEAR TIME-DELAY SYSTEMS WITH COMMENSURATE POINT DELAYS

This paper investigates the exact and approximate spectrum assignment properties associated with realizable output-feedback pole-placement type controllers for single-input single-output linear time-invariant time-delay systems with commensurate point delays. The controller synthesis problem is discussed through the solvability of a set of coupled diophantine equations of polynomials. An extra complexity is incorporated to the above design to cancel extra unsuitable dynamics being generated when solving the above diophantine equations. Thus, the complete controller tracks any arbitrary prefixed (either finite or delay-dependent) closed-loop spectrum. However, if the controller is simplified by deleting the above mentioned extra complexity, then the robust stability and approximated spectrum assignment are still achievable for a certain sufficiently small amount of delayed dynamics. Finally, the approximate spectrum assignment and robust stability problems are revisited under plant disturbances if the nominal controller is maintained. In the current approach, the finite spectrum assignment is only considered as a particular case to the designer's choice of a (delay-dependent) arbitrary spectrum assignment objective.

CONTINUOUS-TIME GENERALIZED PREDICTIVECONTROL WITH POLE-PLACEMENT

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AN ALGEBRAIC METHOD FOR POLE PLACEMENT IN MULTIVARIABLE SYSTEMS

This paper considers the pole placement in multivariable systems involving known delays by using dynamic controllers subject to multirate sampling. The controller parameterizations are calculated from algebraic equations which are solved by using the Kronecker product of matrices. It is pointed out that the sampling periods can be selected in a convenient way for the solvability of such equations under rather weak conditions provided that the continuous plant is spectrally controllable. Some overview about the use of nonuniform sampling is also given in order to improve the system's performance.

Enhancement of Ride Quality of Quarter Vehicle Model by Using Mixed H2/H with Pole-Placement

The aim of the present work is to illustrate the application of mixed H2/H∞ control theory with Pole-Placement in de- signing controller for semi-active suspension system. It is well known that the ride comfort is improved by reducing vehicle body acceleration generated by road disturbance. In order to study this phenomenon, Two Degrees of Freedom (DOF) in state space vehicle model was built in. However, the role of H is to minimize the disturbance effect on the output while H2 is used to improve the input of controller. Linear Matrix Inequality (LMI) technique is used to calculate the dynamic controller parameters. The simulation results show that the H2 and H techniques can effectively control the vibration of vehicle system where the reduction of suspension working space, dynamic tire load and body acceleration. Moreover, the simulation results show that the (RMS) of suspension working space was reduced by 44.5%, body acceleration and dynamic tire load are reduced by 18.5% and 20% respectively.

Neuromorphic Continuous-Time State Space Pole Placement Adaptive Control

A neuromorphic continuous-time state space pole assignment adaptive controller is proposed, which is particularlyappropriate for controlling a large-scale time-variant state-space model due to the parallely distributed nature ofneurocomputing. In our approach, Hopfield neural network is exploited to identify the parameters of a continuous-timestate-space model, and a dedicated recurrent neural network is designed to compute pole placement feedback control law inreal time. Thus the identification and the control computation are incorporated in the closed-loop, adaptive, real-timecontrol system. The merit of this approach is that the neural networks converge to their solutions very quickly andsimultaneously.

Sea Turtle Foraging Optimization-Based Controller Placement with Blockchain-Assisted Intrusion Detection in Software-Defined Networks

Software-defined networking(SDN)algorithms are gaining increas-ing interest and are making networks flexible and agile.The basic idea of SDN is to move the control planes to more than one server’s named controllers and limit the data planes to numerous sending network components,enabling flexible and dynamic network management.A distinctive characteristic of SDN is that it can logically centralize the control plane by utilizing many physical controllers.The deployment of the controller—that is,the controller placement problem(CPP)—becomes a vital model challenge.Through the advancements of blockchain technology,data integrity between nodes can be enhanced with no requirement for a trusted third party.Using the lat-est developments in blockchain technology,this article designs a novel sea turtle foraging optimization algorithm for the controller placement problem(STFOA-CPP)with blockchain-based intrusion detection in an SDN environ-ment.The major intention of the STFOA-CPP technique is the maximization of lifetime,network connectivity,and load balancing with the minimization of latency.In addition,the STFOA-CPP technique is based on the sea turtles’food-searching characteristics of tracking the odour path of dimethyl sulphide(DMS)released from food sources.Moreover,the presented STFOA-CPP technique can adapt with the controller’s count mandated and the shift to controller mapping to variable network traffic.Finally,the blockchain can inspect the data integrity,determine significantly malicious input,and improve the robust nature of developing a trust relationship between sev-eral nodes in the SDN.To demonstrate the improved performance of the STFOA-CPP algorithm,a wide-ranging experimental analysis was carried out.The extensive comparison study highlighted the improved outcomes of the STFOA-CPP technique over other recent approaches.

Multi-Layer Fog-Cloud Architecture for Optimizing the Placement of IoT Applications in Smart Cities

In the smart city paradigm, the deployment of Internet of Things(IoT) services and solutions requires extensive communication and computingresources to place and process IoT applications in real time, which consumesa lot of energy and increases operational costs. Usually, IoT applications areplaced in the cloud to provide high-quality services and scalable resources.However, the existing cloud-based approach should consider the above constraintsto efficiently place and process IoT applications. In this paper, anefficient optimization approach for placing IoT applications in a multi-layerfog-cloud environment is proposed using a mathematical model (Mixed-Integer Linear Programming (MILP)). This approach takes into accountIoT application requirements, available resource capacities, and geographicallocations of servers, which would help optimize IoT application placementdecisions, considering multiple objectives such as data transmission, powerconsumption, and cost. Simulation experiments were conducted with variousIoT applications (e.g., augmented reality, infotainment, healthcare, andcompute-intensive) to simulate realistic scenarios. The results showed thatthe proposed approach outperformed the existing cloud-based approach interms of reducing data transmission by 64% and the associated processingand networking power consumption costs by up to 78%. Finally, a heuristicapproach was developed to validate and imitate the presented approach. Itshowed comparable outcomes to the proposed model, with the gap betweenthem reach to a maximum of 5.4% of the total power consumption.

Improved Harris Hawks Optimization Algorithm Based Data Placement Strategy for Integrated Cloud and Edge Computing

Cloud computing is considered to facilitate a more cost-effective way to deploy scientific workflows.The individual tasks of a scientific work-flow necessitate a diversified number of large states that are spatially located in different datacenters,thereby resulting in huge delays during data transmis-sion.Edge computing minimizes the delays in data transmission and supports the fixed storage strategy for scientific workflow private datasets.Therefore,this fixed storage strategy creates huge amount of bottleneck in its storage capacity.At this juncture,integrating the merits of cloud computing and edge computing during the process of rationalizing the data placement of scientific workflows and optimizing the energy and time incurred in data transmission across different datacentres remains a challenge.In this paper,Adaptive Cooperative Foraging and Dispersed Foraging Strategies-Improved Harris Hawks Optimization Algorithm(ACF-DFS-HHOA)is proposed for optimizing the energy and data transmission time in the event of placing data for a specific scientific workflow.This ACF-DFS-HHOA considered the factors influencing transmission delay and energy consumption of data centers into account during the process of rationalizing the data placement of scientific workflows.The adaptive cooperative and dispersed foraging strategy is included in HHOA to guide the position updates that improve population diversity and effectively prevent the algorithm from being trapped into local optimality points.The experimental results of ACF-DFS-HHOA confirmed its predominance in minimizing energy and data transmission time incurred during workflow execution.