Termination Criterion Research Articles

Revisiting IRKA: Connections with Pole Placement and Backward Stability

The iterative rational Krylov algorithm (IRKA) is a popular approach for producing locally optimal reduced-order ${\mathscr{H}}_{2}$ -approximations to linear time-invariant (LTI) dynamical systems. Overall, IRKA has seen significant practical success in computing high fidelity (locally) optimal reduced models and has been successfully applied in a variety of large-scale settings. Moreover, IRKA has provided a foundation for recent extensions to the systematic model reduction of bilinear and nonlinear dynamical systems. Convergence of the basic IRKA iteration is generally observed to be rapid—but not always; and despite the simplicity of the iteration, its convergence behavior is remarkably complex and not well understood aside from a few special cases. The overall effectiveness and computational robustness of the basic IRKA iteration is surprising since its algorithmic goals are very similar to a pole assignment problem, which can be notoriously ill-conditioned. We investigate this connection here and discuss a variety of nice properties of the IRKA iteration that are revealed when the iteration is framed with respect to a primitive basis. We find that the connection with pole assignment suggests refinements to the basic algorithm that can improve convergence behavior, leading also to new choices for termination criteria that assure backward stability.

Feasibility Study of Beam Angle Optimization for Proton Treatment Planning Using a Genetic Algorithm

This study describes a method that uses a genetic algorithm to select optimal beam angles in proton therapy and evaluates the effectiveness of the proposed algorithm in actual patients. In the use of the genetic algorithm to select the optimal angle, a gene represents the angle of each field and a chromosome represents the combination of beam angles. The fitness of the genetic algorithm, which represents the suitability of the chromosome to the solution, was quantified by using the dose distribution. The weighting factors of the organs used for fitness were obtained from clinical data through logistic regression, reflecting the dose characteristics of actual patients. Genetic operations, such as selection, crossover, mutation, and replacement, were used to modify the population and were repeated until an evaluation based on fitness reached the termination criterion. The proposed genetic algorithm was tested by assessing its ability to select optimal beam angles in three patients with liver cancer. The optimal results for fitness, planning target volume (PTV), normal liver, and skin in the population were compared with the clinical treatment plans, a process that took an average of 36.8 minutes. The dose-volume histograms (DVHs) and the fitness of the genetic algorithm plans did not differ significantly from the actual treatment plans. These findings indicate that the proposed genetic algorithm can automatically generate proton treatment plans with the same quality as actual clinical treatment plans.

Recommendations for respiratory rehabilitation in adults with coronavirus disease 2019.

Coronavirus disease-2019 (COVID-19) is a highly infectious respiratory disease that leads to respiratory, physical, and psychological dysfunction in patients. Respiratory rehabilitation is an important intervention as well as cure for clinical patients. With increased understanding of COVID-19 and the accumulation of clinical experience, we proposed recommendations for respiratory rehabilitation in adults with COVID-19 based on the opinions of frontline clinical experts involved in the management of this epidemic and a review of the relevant literature and evidence. Our recommendations are as follows: 1. for inpatients with COVID-19, respiratory rehabilitation would relieve the symptoms of dyspnea, anxiety, and depression and eventually improve physical functions and the quality of life; 2. for severe/critical inpatients, early respiratory rehabilitation is not suggested; 3. for patients in isolation, respiratory rehabilitation guidance should be conducted through educational videos, instruction manuals, or remote consultation; 4. assessment and monitoring should be performed throughout the respiratory rehabilitation process; 5. proper grade protection should be used following the present guidelines. These recommendations can guide clinical practice and form the basis for respiratory rehabilitation in COVID-19 patients.

Utilization of the Moore-Penrose inverse in the modeling of overconstrained mechanisms with frictionless and frictional joints

The indeterminate equations that describe overconstrained mechanisms are often solved using the Moore-Penrose inverse. Some limitations of this approach are investigated here. Firstly, frictionless systems are considered. The problem of solvability of accelerations and joint reactions is studied—the non-uniqueness of reactions and uniqueness of accelerations is discussed. Next, the dependence of the results on the selection of the physical units is examined. It is checked which elements of the solution are physically non-equivalent after changing the units; relationships between different solutions are derived. Secondly, frictional systems are considered. Joint friction dependent and independent on normal load is studied. Fixed point iterations and Newton's method are applied to solve nonlinear equations of motion. The Moore-Penrose inverse is employed to conduct calculations. The null space solution components are considered, and necessary amendments in the iterative processes termination criteria are discussed. The origins of non-uniqueness of accelerations and Lagrange multipliers are analyzed. The unit-sensitivity of frictional system models is addressed. Finally, an illustrative example is given, and conclusions are drawn—limitations and possible improvements of the Moore-Penrose inverse approach are discussed.

Terminal Invariance of Jump Diffusions

Terminal invariance sufficient conditions for nonlinear dynamical stochastic controllable systems of diffusion-jump type are proposed. These conditions have no analogues in the world literature. Both perturbation invariance conditions (for a fixed initial point) and absolute invariance conditions (ensuring that the terminal criterion takes a constant value for any initial data) are formulated.

Determining An Appropriate Cardiopulmonary Exercise Testing Protocol For Individuals With Neuromuscular Disease

PURPOSE: To review published standards and recommendations for people with neuromuscular disease and establish a graded ramp-up protocol to assess exercise tolerance for individuals who have moderate to severe muscle weakness. METHODS: A review of literature for muscular dystrophy or neuromuscular disease and exercise testing was performed to assess different methodologies in Cardiopulmonary Exercise Testing (CPET) using cycle ergometry CPET. A progressive ramp-up protocol was developed and administered with patients who attend Stanford’s multidisciplinary clinic to determine feasibility and test termination criteria that may limit the ability to achieve maximum oxygen consumption. RESULTS: Literature search resulted in 43 research studies. The study breakdown included Myopathies and McArdle disease =20; Pompe=5; FSHD; SMA, Metabolic Myopathies=3; DMD/BMD=2, Myotonic Dystrophy=2; CMT=1; IBM=1. Studies greatly ranged in mode of testing. Most study participants were ambulatory. Most protocols used a graded 1-2 minute progressive ramping protocol up to the point of exhaustion indicated by a Visual Analog Scale and heart rate. Early termination resulted from participants voluntarily stopping due to muscle weakness. We developed a progressive ramp up protocol with 1-minute increment increase in workload at 5-watt intervals to avoid early termination from large increases in workload. We tested 3 individuals with neuromuscular disease and 2 controls. Only 2 participants (1 with NMD and 1 control) were able to reach an RER of 1.1 of maximal oxygen uptake (VO2max). Reasons for early termination were consistent with the published literature including heart rate, voluntary stop and muscle weakness. CONCLUSIONS: With promising treatments on the horizon for neuromuscular diseases, physical therapists are asked to determine appropriate exercise prescriptions for individuals with a range of functional abilities and muscle weakness. Currently, CPET protocol methodology varies for weaker individuals. Our results will contribute to developing a proposed submaximal clinical exercise tolerance test protocol to establish safe exercise prescriptions and determine treatment intervention benefits for patients with neuromuscular disease.

Prediction of ocean import shipment lead time using machine learning methods

This paper focuses on developing a predictive model for estimating the shipment lead time using machine learning methods for ocean import freight considering interests of different stakeholders such as shipper, carrier, freight forwarder, and consignee. Two different terminal criteria for calculating shipment lead time are defined considering different milestones: one with empty container return and the other with delivery confirmation at the destination. Real data obtained from an industry partner are used for implementation, and multinomial logistic regression is identified as the best classifier with the highest accuracy in each binning method, which is followed by a decision tree method. Additionally, commonly used classifiers such as multinomial logistic regression, decision tree, K-nearest neighbors, and support vector machine perform better than Naïve Bayes when the categorical variables are binarized, and vice versa when the categorical variables are converted into ordinal values. The proposed model has the significant potential to benefit different parties in the supply chain by providing improved visibility and predictability for shipment lead times.

Multiobjective planning for spacecraft reorientation under complex pointing constraints

The spacecraft is required to optimize some performance indexes during the attitude maneuver in many space missions. Moreover, the presence of the bounded and pointing constraints will greatly reduce the feasible attitude space. It is difficult to solve the optimal spacecraft reorientation under complex multiple constraints. The notion of the rotational-path geometric-reasonableness is proposed to evaluate the quality of the maneuver path in terms of its geometric characteristics, which involve the path length and path unwinding in this paper. Considering the rotational-path geometric-reasonableness and energy consumption, this paper addresses the multiobjective spacecraft reorientation planning problem with constraints and proposes a new dynamic-iteration-based multiobjective planning (DIMP) method. Through the iterative quadratic programming approach with the dynamic termination criteria, the proposed method first generates a multiobjective suboptimal solution that does not consider the pointing constraints. Then the final solution under the keep-in and keep-out constraints is yielded via multiple rotational-path decomposition and iterative planning. Simulation results demonstrate the high efficiency of the proposed method, which can obtain a high-quality and low-energy solution.

Real-Time Principal Component Analysis

We propose a variant of Principal Component Analysis (PCA) that is suited for real-time applications. In the real-time version of the PCA problem, we maintain a window over the most recent data and project every incoming row of data into a lower-dimensional subspace, which we generate as the output of the model. The goal is to reduce the reconstruction error of the output from the input and to retain major components pertaining to previous distributions of the data. We use the reconstruction error as the termination criteria to update the eigenspace as new data arrives. We then propose two variants of this algorithm that are progressively more time efficient. To verify whether our proposed model can capture the essence of the changing distribution of large datasets in real time, we have implemented the algorithms and compared performance against carefully designed simulations that change distributions of data sources over time in a controllable manner. Furthermore, we have demonstrated that proposed algorithms can capture the changing distributions of real-life datasets by running simulations on datasets from a variety of real-time applications, e.g., localization, activity recognition, customer expenditure, and so forth. Results show that straightforward modifications to convert PCA to use a sliding window of datasets do not work because of the difficulties associated with determination of optimal window size. Instead, we propose algorithmic enhancements that rely on spectral analysis to improve dimensionality reduction. Results show that our methods can successfully capture the changing distribution of data in a real-time scenario, thus enabling real-time PCA.

On the application of shooting method for determining semicontinuous distillation limit cycles

Semicontinuous distillation is a new separation technology for distilling multicomponent mixtures. This process was designed using design methodologies with heuristic components that evolved over 20 years. However, the fundamental philosophy of these design methodologies, which involves guessing, checking and then using a black-box optimization procedure to find the values of the design variables to meet some performance criteria, has not changed. Mainly, to address the problem of having a heuristic simulation termination criterion in the black-box optimization phase, the single shooting method for semicontinuous distillation design was proposed in this study. We envision that this is a first step in the transformation of the semicontinuous distillation design process for obtaining optimal designs. We demonstrate the application of this method using two case studies, which involve the separation of hexane, heptane and octane.

Joint moment trade-offs across the upper extremity and trunk during repetitive work

Individuals can coordinate small kinematic changes at several degrees of freedom simultaneously in the presence of fatigue, leaving it unclear how overall biomechanical demands at each joint are altered. The purpose of this study was to evaluate trade-offs in joint moments between the trunk, shoulder, and elbow during repetitive upper extremity work. Participants performed four simulated workplace tasks cyclically until meeting fatigue termination criteria. Emergent fatigue-induced adaptations to repetitive work resulted in task-dependent trade-offs in joint moments. In general, reduced shoulder moments were compensated for by increased elbow and trunk joint moment contributions. Although mean joint moment changes were modest (range: 1–3 Nm) across participants, a wide distribution of responses was observed, with standard deviations exceeding 10 Nm. Re-distributing biomechanical demands across joints may alleviate constant tissue loads and facilitate continued task performance with fatigue but may be at the expense of increasing demands at adjacent joints.

Formalizing the dependency pair criterion for innermost termination

• Dependency pairs criterion and verification of termination of rewriting systems. • Automating termination of rewriting and functional programs. • Formalization of termination of first-order term rewriting systems. • Innermost reduction and termination of rewriting. • Formally proving the soundness of rewriting with the PVS proof assistant. Rewriting is a framework for reasoning about functional programming. The dependency pair criterion is a well-known mechanism to analyze termination of term rewriting systems. Functional specifications with an operational semantics based on evaluation are related, in the rewriting framework, to the innermost reduction relation. This paper presents a PVS formalization of the dependency pair criterion for the innermost reduction relation: a term rewriting system is innermost terminating if and only if it is terminating by the dependency pair criterion. The paper also discusses the application of this criterion to check termination of functional specifications.

Prehospital Disposition and Patient Outcomes in Cardiac Arrest AFTER Resuscitation Termination Protocol Change in an Urban Setting.

Out-of-hospital cardiac arrest (OHCA) is a leading cause of death in the United States, and efforts have been made to develop termination of resuscitation protocols utilizing clinical criteria predictive of successful resuscitation and survival to discharge. A termination of resuscitation protocol utilizing longer resuscitation time and end-tidal carbon dioxide (EtCO2) monitoring criteria for termination was implemented for Emergency Medical Service (EMS) providers in an urban prehospital system in 2017. This study examines the effect the modified termination of resuscitation protocol had on rates of patient transport to a hospital, return of spontaneous circulation (ROSC), and survival to discharge. A retrospective analysis was performed utilizing data from the Cardiac Arrest Registry to Enhance Survival (CARES) database. A total of 1,005 prehospital cardiac arrest patients 18 years and older from 2016 through 2017 were included in the analysis. Patients with traumatic cardiac arrest or had valid do-not-resuscitate orders were excluded. Unadjusted analysis using chi-square statistics was performed, including an analysis stratified by Utstein style reporting. Adjusted analysis was also performed using logistic regression with multiple imputation for missing values. Unadjusted analysis showed a significant decrease in ROSC on emergency department (ED) arrival (30% versus 13%; P <.001) following the change in protocol. There was no significant difference in patient transport rate (62%) and a statistically non-significant decrease in overall survival (15% versus 11%). When stratified by Utstein style analysis, statistically significant decreases in ED arrival with ROSC were seen for unwitnessed asystolic, as well as bystander witnessed asystolic, pulseless electrical activity (PEA), and shockable OHCA. Adjusted analysis showed a decreased likelihood of ROSC with the protocol change (0.337; 95% CI, 0.235-0.482). The modification of termination of resuscitation protocol was not associated with a statistically significant change in transport rate or survival. A significant decrease in rate of arrivals to the ED with ROSC was seen, particularly for bystander witnessed OHCA.

Adaptive beam alignment method for millimeter-wave massive MIMO communication systems

To compensate the severe path loss of millimeter-wave channel, large-scale antenna arrays are required to provide beamforming gains for millimeter wave communication systems. Since the millimeter wave (mmWave) MIMO channel has strong directional selectivity, it is necessary for transmitter and receiver to perform beam alignment for obtaining maximum beamforming gains. In this paper, we first propose an adaptive beam alignment scheme. Based on the proposed scheme, adaptive hierarchical traversal beam search algorithm and adaptive hierarchical iterative beam search algorithm are proposed for beam alignment. Both of the algorithms adjust the training time adaptively by exploiting the beam detection algorithm to improve the success rate of beam alignment and reduce beam training overhead. Furthermore, in order to improve the transmission data rate and the beam alignment reliability of the system, maximum transmission data rate is adopted as the termination criterion of beam training. Simulation results show that the proposed algorithms have higher transmission data rate and beam alignment success rate compared with the existing beam search algorithms under both line-of-sight (LOS) and non-line-of-sight (NLOS) channels. Moreover, the proposed algorithms are more reliable to dynamic scenarios, especially the short distance between transmitter and receiver.

Results of treatment of bilateral destructive pulmonary tuberculosis patients using mini-invasive surgical interventions.

There were analyzed case-histories of patients operated on bilateral destructive pulmonary tuberculosis who underwent treatment at pulmonary-surgical unit of CI “DRCCTPA” Phthisiatria” from 2010 to 2018. Case histories of 259 patients’ were included in the study, in complex treatment of which, surgical stage of treatment was used. Analyzing direct results in 2 months after surgery, the estimation based on clinical, roentgenologic and laboratory studies by criteria of destruction cavities closure, bacterioexcretion termination and clinical stabilization of the tuberculosis process was used. In carrying out a research patients were divided into 2 groups: the main group consisted of 129 patients who underwent mini-invasive methods of surgical treatment with mini-access under the control of video-thoracoscopy (single-step or staging bilateral video-assisted lung resection – 58 patients, collapse-surgical video-assisted single-step or staging interventions – 53, staging mini-invasive pleuropneumonectomy – 18). The comparison group included 130 patients operated according to standard approaches with conventional methods. Comparison groups did not differ reliably (p&gt;0,05) by the gender and the age, by tuberculosis forms, by disease duration, by functional parameters, by main prevalence and severity of tuberculosis. A biggest number of complications in both groups was noted after pleuropneumo­nectomies, lobectomies and thoracoplasty. In the comparison group postoperative complications were observed in 32 (24.6%) patients, that is 2.2 more often (p=0.002). In the main group, bronchopleural complications occurred in 8 cases (6.2%), and in the comparison group – in 16 (12.3%), that is 2 times less frequently, exacerbation of tuberculosis process was noted 3.8 times more often in patients of comparison group. Performed analysis of the nature of postoperative complications in both groups confirms the effect of traumatism of access not only on the course of the wound process, but also on the frequency of pleural, pulmonary and functional complications. A complete clinical effect in the patients of comparison group was achieved in 82 cases (63%), that is by 1.4 times less than in the main group (p&lt;0.001). Abacillation, while maintaining destruction in one of the lungs, occurred at the time of discharge from the hospital in 12 (9.3%) patients of the main group and in 21 (16.5%) – of the comparison one. There were 3 (2.3%) patients discharging bacteria in the main group and 20 (15.4%) patients in the comparison group.

Addition of Dialysis to Ex-Vivo Lung Perfusion Maintains Homeostasis and Stability of Donor Lungs: A Pilot Study

Ex-vivo lung perfusion (EVLP) maintains marginal donor lungs at body temperature with ventilation and circulating perfusate, allowing for functional assessment prior to transplantation. Prolonged EVLP would allow for advanced time-dependent therapies for donor lung repair and reconditioning. We hypothesized that the addition of a dialysis machine to the EVLP circuit would maintain homeostasis of the donor lung and prolong EVLP duration. Porcine donor lungs (n=3) were extracted and placed on the EVLP platform for 36 hours or until termination criteria (dynamic compliance < 15ml/cmH2O) was reached. Lungs were perfused with an acellular solution and closed atrium, according to the Toronto protocol. A dialysis machine was incorporated into the EVLP circuit with a custom-designed dialysate to continuously dialyze perfusate using continuous venovenous hemodialysis (Fig1A). Physiological function, electrolytes and inflammatory mediators in EVLP perfusate were measured hourly. In this pilot study, dialysis cases were compared to historical controls with similar protocol (n=6). Dialysis successfully prevented an increase in electrolyte levels (Fig 1C) and maintained glucose and lactate levels at baseline (1C). EVLP was prolonged in the dialysis group with a mean duration of EVLP reaching 32±6.93 h in the E+D group compared to 18.67±3.27 h in the historical control group (Fig 1D). Percent lung survival at 24h of perfusion was 100% in the E+D group, while only 20% was seen in historical controls (Fig 1B). Both lungs which survived to 36h of EVLP presented excellent lung function based on assessment by EVLP. Dialysis may preserve lung function and length of EVLP by maintaining homeostasis of the lung. Following the results of this encouraging pilot study, a formal blinded experiment is being performed and is underway.

Comparison of eight filter-based feature selection methods for monthly streamflow forecasting – Three case studies on CAMELS data sets

Recently, there has been an increased emphasis on employing data-driven models to forecast streamflow. However, in these data-driven models used for forecasting monthly streamflow, the performances of filter-based feature selection (FFS) methods have not been studied in detail. In this study, we investigated the effectiveness of eight common FFS methods, namely, linear Pearson correlation, partial linear Pearson correlation (PCI), mutual information (MI), conditional MI, partial MI, maximal relevance minimal redundancy Pearson correlation, maximal relevance minimal redundancy MI and gamma test methods, on three regression models, namely multiple linear regression (MLR), ensemble extreme learning machine (enELM) and k-nearest neighbor (KNN) regression, for real-world one-month-ahead streamflow forecasting. The study was conducted on three cases from the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) data sets. Furthermore, two termination criterion (TC) methods, the Hampel test and resampling, were comparatively analyzed. The results of this study highlight three important findings. First, there was no dominant FFS method that coupled with enELM or KNN. Second, when resampling was applied to select a final model in the candidate combinations of the eight FFS methods and three regression models, PCI was the most favorable FFS method for the final model. Finally, the Hampel test TC was superior to the resampling TC in terms of stability and anti-overfitting. These findings have significant practical reference value for real-world monthly streamflow forecasting.

ORCA study: real-world versus reading centre assessment of disease activity of neovascular age-related macular degeneration (nAMD)

Background/aimsThe prospective, non-interventional ORCA module of the OCEAN study (Observation of Treatment Patterns with Lucentis in Approved Indications) evaluated the qualiy of spectral domain-optical coherence tomography (SD-OCT) image interpretation and...

Penentuan Rute Terpendek Pendistribusian Tabung Gas Lpg 3 Kg Pt. Fega Gas Palu Pratama Menggunakan Algoritma Tabu Search

ABSTRACTDistribution is one of the important tools in the company business activities. The problem that is often occurred indistribution is the determination of the shortest route. The purpose of this study is optimitation distribution route of3 kg LPG gas cylinders which is carried out by PT. Fega Gas Palu Pratama in Palu City, considering that thiscompany has not used a particular method in determining the distribution route of 3 kg LPG gas cylinders. Themethod used in this study is the Tabu Search algorithm. The algorithm of the Tabu Search method are of follows,first by determine the initial solution using the closest Nearest Neighbor, determine alternatives by exchange 2points in the solution, evaluate alternative solutions, determine a new optimum solution, update the Tabu List, thenwhen the termination criteria are obtained then the Tabu Search algorithm will stop otherwise it will revert toexchanging 2 points evaluation. The process of calculating the Tabu Search algorithm is conducted manually andbuilt using MATLAB. Based on the research that has been done, it is obtained that the shortest, more efficient routeis 21.91 km which has reduction of 7.26 km from the initial route 29.17 km.Keywords : Algorithm Tabu Search, Distribution, Shortest Route.

Integrating Advanced Harmony Search with Fuzzy Logic for Solving Buffer Allocation Problems

This paper introduces a new fuzzy advanced harmony search algorithm for solving single-objective buffer allocation problems (BAPs). The proposed algorithm represents the first attempt at solving BAPs using a fuzzy logic system, by tuning the advanced harmony search control parameters. The main steps of the proposed algorithm included parameter initialisation, harmony memory initialisation and evaluation, improvisation, harmony memory update, AHS parameter update, and termination criterion check. The aim of this approach is to achieve a better convergence rate and avoid the stacking of local optima. The performance of the proposed algorithm was compared with other methods used in solving BAPs. The proposed approach has shown a higher capability in finding optimal solutions compared to previous methods used for two benchmark problems. Improvement of up to 94.75% in the overall throughput is reported for the 3-stage problem, while for the 12-stage problem, a slight improvement (up to 7.58%) is also reported in the overall throughput. The results achieved indicate that the proposed algorithm is an efficient and promising tool in solving BAPs.