Piecewise Approach Research Articles

Surgical resection is associated with improved long-term survival of patients with resectable pancreatic head cancer compared to multiagent chemotherapy.

Standard of care for resectable pancreatic cancer is a combination of surgical resection (SR) and multiagent chemotherapy (MCT). We aim to determine whether SR or MCT is associated with superior survival for patients receiving only single-modality therapy. Patients with stage I-IIb pancreatic head adenocarcinoma who received either MCT or SR were identified in the NCDB (2013-2015). Following a piecewise approach to estimating hazards over the course of follow-up, conditional overall survival (OS) at 30, 60, and 90 days after treatment initiation was estimated using landmark analyses. 3103 patients received MCT alone (60.3%) and 2043 underwent SR alone (39.7%). SR had an OS disadvantage at 30 (HR 3.99, 95% CI 3.12-5.11) and 60 days (HR 1.85, 95% CI 1.4-2.45), but an OS advantage after 90 days (HR 0.59, 95% CI 0.55-0.64). In a landmark analysis conditioned on 90 days survival post treatment initiation, median OS was improved for SR (17.0 vs. 12.2 months, p<0.0001); SR improved 3-year OS by 21.3% (p<0.05), despite patients being older (median 72 vs. 67 years, p<0.0001) with higher Charlson-Deyo comorbidity scores (≥2: 11.2 vs. 8.6%, p=0.006). For patients with resectable pancreatic cancer, SR is associated with superior long-term survival compared to MCT.

EE111 Adoption of Piecewise Modelling: A Review of Nice Health Technology Appraisals in Oncology

10 years ago, NICE DSU Technical Support Document 14 noted the underutilization of piecewise models as an alternative to fully parametric models for survival extrapolations and recommended their consideration where more flexible survival models are required. This study aimed to review the adoption of the piecewise approach in recent assessments of oncology drugs submitted to the National Institute for Health and Care Excellence (NICE).

Analysis of Huanglongbing disease model with a novel fractional piecewise approach

Huanglongbing (yellow dragon disease), often known as citrus greening, is one of the world's most destructive citrus illnesses. It is caused by Candidatus Liberibacter asiaticus, a bacterial disease that spreads through the tree canopy, causing the tree to degrade and eventually die. The aim of this paper is to study the dynamics of the Huanglongbing disease model using the novel piecewise derivative approach in the sense of singular and non-singular kernels. The singular kernel operator is in the sense of Caputo, while the non-singular kernel is the Atangana-Baleanu Caputo operator. The existence and uniqueness of the solution with piecewise derivatives are examined for the aforementioned problem. The suggested problem's approximate solution is obtained using the piecewise numerical iterative scheme based on the Newton polynomial approach. The numerical simulation for the piecewise derivable problem under consideration is presented using the data for various fractional orders. From the simulations, it is observed that when the vaccination rate is high then the number of exposed and infected citrus trees is small as compared to the lower vaccination rates.

Development of a Strain-Based Model to Predict Eviscerated Thoracic Response From Dynamic Individual Rib Tests.

The objective of this study was to develop an analytical model using strain-force relationships from individual rib and eviscerated thorax impacts to predict bony thoracic response. Experimental eviscerated thorax forces were assumed to have two distinct responses: an initial inertial response and subsequently, the main response. A second-order mass-spring-damper model was used to characterize the initial inertial response of eviscerated thorax force using impactor kinematics. For the main response, equivalent strains in rib levels 4-7 were mapped at each time point and a strain-based summed force model was constructed using individual rib tests and the same ribs in the eviscerated thorax test. A piecewise approach was developed to join the two components of the curve and solve for mass, damping, stiffness parameters in the initial response, transition point, and scale factor of the strain-based summed force model. The final piecewise model was compared to the overall experimental eviscerated thorax forces for each postmortem human subjects (PMHS) (n = 5) and resulted in R2 values of 0.87-0.96. A bootstrapping approach was utilized to validate the model. Final model predictions for the validation subjects were compared with the corridors constructed for the eviscerated thorax tests. Biofidelity ranking system score (BRSS) values were approximately 0.71 indicating that this approach can predict eviscerated responses within one standard deviation from the mean response. This model can be expanded to other tissue states by quantifying soft tissue and visceral contributions, therefore successfully establishing a link between individual rib tests and whole thoracic response.

Valuing water purification services of forests: a production function approach using panel data from China's Sichuan province

AbstractThe water purification functions of forests represent one of the most frequently invoked examples of nonmarket ecosystem services that are economically valuable. This study quantifies the monetary value of forests' water purification services in the form of the ensuing cost savings of municipal drinking water treatment, using a rich panel dataset from China's Sichuan province. Moreover, this study has undertaken a novel spatial piecewise approach to investigate the spatial patterns of such cost savings delivered by forests at different distances from the water intake point. The estimation results find that forests within a 2 km radius upstream from the water intake point have the most sizeable and statistically significant cost saving effect. For forests within a 3 km radius, this effect becomes somewhat smaller but remains statistically significant. Beyond a 4 km radius, this effect becomes notably smaller and statistically equal to zero. Our analysis facilitates the optimal spatial targeting of forest conservation.

A novel piece-wise approach to modeling interactions in a food web model

New definitions always have more capabilities in describing phenomena than the more classic and well-known concepts because they usually appear to fill the gaps in existing concepts. In this paper, we employ a new stochastic fractional system that models interactions in a mutualism–parasitism food web. The main idea of piece-wise differential and integral operators is to separate the time under study into separate time domains in which the model behaves different behaviors. The idea was recently proposed by Atangana et al., and is gradually being used to solve a variety of application models. In order to demonstrate the valuable capabilities of this approach, many numerical simulations are provided in this paper. These results are mainly obtained from studying the role of the parameters in the model on its overall behavior. The results confirm that the piece-wise approach to the problem is a wise idea with more effectiveness rather than considering the whole situation is studied by a single operator. It is recommended to use these modified operators in modeling other applied problems with similar features.

Fans deactivation for minimisation of airborne pathogen transmission: During Malaysians congregational prayer gathering in mosque

This research investigated the possibility of minimising airborne pathogen transmission in a mosque during congregational prayer by reducing air flow circulation within the space using the Computational Fluid Dynamics (CFD) simulation method. A three-dimensional model representing an internal mosque building and prayers congregation was created and meshed, using a numerical computational method. In contrast, an individual airborne pathogen transmission was modelled using a discrete particle model (DPM) to represent the particle flow characteristics. The model was validated using a piecewise approach, and the results were in good agreement with the experimental results. This demonstrated that fan deactivation could reduce pathogen transmission by 24.62%. The reason for this significant reduction is that droplets expelled by assailants during a prayer session lack the propagational energy required to cause infection of other members of the congregation due to disengagement of the fans. This research equally revealed that understanding the characteristics of particles adherence to surfaces and their directions of propagation can serve as a guide in epidemic prevention and transmission and control of infectious diseases.

Exploring the relationship between mobility and COVID\u2212\u200919 infection rates for the second peak in the United States using phase-wise association

Human mobility plays an important role in the dynamics of infectious disease spread. Evidence from the initial nationwide lockdowns for COVID− 19 indicates that restricting human mobility is an effective strategy to contain the spread. While a direct correlation was observed early on, it is not known how mobility impacted COVID− 19 infection growth rates once lockdowns are lifted, primarily due to modulation by other factors such as face masks, social distancing, and the non-linear patterns of both mobility and infection growth. This paper introduces a piece-wise approach to better explore the phase-wise association between state-level COVID− 19 incidence data and anonymized mobile phone data for various states in the United States. Prior literature analyzed the linear correlation between mobility and the number of cases during the early stages of the pandemic. However, it is important to capture the non-linear dynamics of case growth and mobility to be usable for both tracking and forecasting COVID− 19 infections, which is accomplished by the piece-wise approach. The associations between mobility and case growth rate varied widely for various phases of the epidemic curve when the stay-at-home orders were lifted. The mobility growth patterns had a strong positive association of 0.7 with the growth in the number of cases, with a lag of 5 to 7 weeks, for the fast-growth phase of the pandemic, for only 20 states that had a peak between July 1st and September 30, 2020. Overall though, mobility cannot be used to predict the rise in the number of cases after initial lockdowns have been lifted. Our analysis explores the gradual diminishing value of mobility associations in the later stage of the outbreak. Our analysis indicates that the relationship between mobility and the increase in the number of cases, once lockdowns have been lifted, is tenuous at best and there is no strong relationship between these signals. But we identify the remnants of the last associations in specific phases of the growth curve.

Automatic Feature Selection for Improved Interpretability on Whole Slide Imaging

Deep learning methods are widely used for medical applications to assist medical doctors in their daily routine. While performances reach expert’s level, interpretability (highlighting how and what a trained model learned and why it makes a specific decision) is the next important challenge that deep learning methods need to answer to be fully integrated in the medical field. In this paper, we address the question of interpretability in the context of whole slide images (WSI) classification with the formalization of the design of WSI classification architectures and propose a piece-wise interpretability approach, relying on gradient-based methods, feature visualization and multiple instance learning context. After training two WSI classification architectures on Camelyon-16 WSI dataset, highlighting discriminative features learned, and validating our approach with pathologists, we propose a novel manner of computing interpretability slide-level heat-maps, based on the extracted features, that improves tile-level classification performances. We measure the improvement using the tile-level AUC that we called Localization AUC, and show an improvement of more than 0.2. We also validate our results with a RemOve And Retrain (ROAR) measure. Then, after studying the impact of the number of features used for heat-map computation, we propose a corrective approach, relying on activation colocalization of selected features, that improves the performances and the stability of our proposed method.

Piecewise All-Atom SMD Simulations Reveal Key Secondary Structures in Luciferase Unfolding Pathway

Although the folding of single-domain proteins is well characterized theoretically and experimentally, the folding of large multidomain proteins is less well known. Firefly luciferase, a 550 residue three-domain protein, has been commonly used as a substrate to study chaperone reactions and as a model system for the study of folding of long polypeptide chains, including related phenomena such as cotranslational folding. Despite being characterized by various experimental techniques, the atomic-level contributions of various secondary structures of luciferase to its fold’s mechanical stability remain unknown. Here, we developed a piecewise approach for all-atom steered molecular dynamics simulations to examine specific secondary structures that resist mechanical unfolding while minimizing the amount of computational resources required by the large water box of standard all-atom steered molecular dynamics simulations. We validated the robustness of this approach with a small NI3C protein and used our approach to elucidate the specific secondary structures that provide the largest contributions to luciferase mechanostability. In doing so, we show that piecewise all-atom steered molecular dynamics simulations can provide novel atomic resolution details regarding mechanostability and can serve as a platform for novel mutagenesis studies as well as a point for comparison with high-resolution force spectroscopy experiments.

Availability Modeling in Power Converters Considering Components Aging

Power electronic converters are increasingly used in power systems. However, they are vulnerable components and prone to aging failures, thus affecting overall system reliability. Therefore, their availability modeling especially in large-scale power electronic-based power systems is of paramount importance. This letter introduces four different approaches for converter availability modeling considering aging failures under different maintenance strategies. The accuracy and calculation burden of these approaches are illustrated by numerical analysis. It is shown that the method of device of stages and piece-wise approach are the most applicable methods in the case of corrective and preventive maintenance strategies respectively.

Simulation of the asphalt concrete stiffness degradation using simplified viscoelastic continuum damage model

A procedure based on the simplified viscoelastic continuum damage model is developed to simulate asphalt concrete stiffness degradation caused by the application of cyclic loads. Several tests are performed to characterize the linear viscoelastic and fatigue damage properties of four asphalt mixtures. It was found that the piecewise approach proposed to simulate the stiffness evolution successfully describes the damage growth under loads applications. It was also found that the exponential model used to fit the characteristic curves best describes the stiffness evolution for the entire load history. Finally, stiffness evolution simulations showed higher fatigue resistance for polymer-modified mixtures.

Analysis of load mismatch effect compensation in Doherty power amplifier

AbstractThis paper presents a theoretical and experimental analysis of the capabilities of the dual-input Doherty power amplifier (DPA) architecture to mitigate efficiency and output power degradations when used in a mismatched load environment. Following a simplified linear piecewise approach, an analytical demonstration is proposed to derive optimal radio frequency drives applied to the Auxiliary path of the DPA to restore power performances while avoiding large signal voltage clipping of active cells. The proposed analytical study is corroborated with harmonic balance simulated results of a C-band, 20-W GaN DPA prototype. The fabricated dual-input DPA prototype has been measured under 1.5-VSWR mismatch configurations to validate the proposed analysis.

Technical Note: Rapid multiexponential curve fitting algorithm for voxel-based targeted radionuclide dosimetry.

Dosimetry in nuclear medicine often relies on estimating pharmacokinetics based on sparse temporal data. As analysis methods move toward image-based three-dimensional computation, it becomes important to interpolate and extrapolate these data without requiring manual intervention; that is, in a manner that is highly efficient and reproducible. Iterative least-squares solvers are poorly suited to this task because of the computational overhead and potential to optimize to local minima without applying tight constraints at the outset. This work describes a fully analytical method for solving three-phase exponential time-activity curves based on three measured time points in a manner that may be readily employed by image-based dosimetry tools. The methodology uses a series of conditional statements and a piecewise approach for solving exponential slope directly through measured values in most instances. The proposed algorithm is tested against a purpose-designed iterative fitting technique and linear piecewise method followed by single exponential in a cohort of ten patients receiving 177 Lu-DOTA-Octreotate therapy. Tri-exponential time-integrated values are shown to be comparable to previously published methods with an average difference between organs when computed at the voxel level of 9.8±14.2% and -3.6±10.4% compared to iterative and interpolated methods, respectively. Of the three methods, the proposed tri-exponential algorithm was most consistent when regional time-integrated activity was evaluated at both voxel- and whole-organ levels. For whole-body SPECT imaging, it is possible to compute 3D time-integrated activity maps in <5min processing time. Furthermore, the technique is able to predictably and reproducibly handle artefactual measurements due to noise or spatial misalignment over multiple image times. An efficient, analytical algorithm for solving multiphase exponential pharmacokinetics is reported. The method may be readily incorporated into voxel-dose routines by combining with widely available image registration and radiation transport tools.

PCN194 COST-EFFECTIVENESS ANALYSIS OF PEMBROLIZUMAB IN COMBINATION WITH CARBOPLATIN AND PACLITAXEL FOR PREVIOUSLY UNTREATED PATIENTS WITH METASTATIC SQUAMOUS NON-SMALL CELL LUNG CANCER IN ENGLAND

To assess cost-effectiveness of pembrolizumab with carboplatin and paclitaxel (pembrolizumab combination) versus carboplatin plus paclitaxel (chemotherapy) or pembrolizumab monotherapy (in PDL1 ≥50% expressors) in previously untreated metastatic squamous non-small cell lung cancer (NSCLC). A three-state partitioned survival model was developed with a 30-year time horizon. The KEYNOTE-407(data cut off: April, 2018) trial informed the efficacy and adverse event parameters of pembrolizumab combination and chemotherapy. Overall survival (OS) was extrapolated using a piece-wise approach, utilising trial Kaplan-Meier data until week 52, and extrapolating overall survival beyond the trial using mortality risks for the chemotherapy group derived from an external real-world database (SEER) for the remainder of the time horizon, with a relative risk applied for pembrolizumab combination based on within-trial treatment efficacy. An indirect treatment comparison provided comparative effectiveness estimates of pembrolizumab combination versus pembrolizumab in PDL1 ≥50% expressors. Quality-adjusted life years (QALYs) were estimated using utilities derived from trial EQ-5D data. Resource use and unit costs were applied from an NHS perspective. The model demonstrated that pembrolizumab combination increases the life expectancy of patients from 1.76 to 3.29 discounted years, and from 1.27 to 2.42 discounted QALYs relative to chemotherapy use. The base case incremental cost-effectiveness ratio (ICER) versus paclitaxel plus carboplatin is £33,075, with a dominant result observed versus pembrolizumab monotherapy in PDL1 ≥50% expressors. The latter result should be interpreted with caution, as the hazard ratio for mortality is not statistically different between comparators and incremental QALYs are close to zero. Model results are most sensitive to assumptions around the extrapolation of overall survival data. The results of this cost-effectiveness analysis demonstrated that pembrolizumab combination is a cost-effective choice compared to standard of care therapies in the UK when considering a willingness to pay threshold of £50,000 per QALY, as per NICE end-of-life criteria.

Development of an Advanced Force Field for Water Using Variational Energy Decomposition Analysis.

Given the piecewise approach to modeling intermolecular interactions for force fields, they can be difficult to parametrize since they are fit to data like total energies that only indirectly connect to their separable functional forms. Furthermore, by neglecting certain types of molecular interactions such as charge penetration and charge transfer, most classical force fields must rely on, but do not always demonstrate, how cancellation of errors occurs among the remaining molecular interactions accounted for such as exchange repulsion, electrostatics, and polarization. In this work we present the first generation of the (many-body) MB-UCB force field that explicitly accounts for the decomposed molecular interactions commensurate with a variational energy decomposition analysis, including charge transfer, with force field design choices that reduce the computational expense of the MB-UCB potential while remaining accurate. We optimize parameters using only a single water molecule and water cluster data up through pentamers, with no fitting to condensed phase data, and we demonstrate that high accuracy is maintained when the force field is subsequently validated against conformational energies of larger water cluster data sets, radial distribution functions of the liquid phase, and the temperature dependence of thermodynamic and transport water properties. We conclude that MB-UCB is comparable in performance to MB-Pol but is less expensive and more transferable by eliminating the need to represent short-ranged interactions through large parameter fits to high order polynomials.

Satellite Stereo Image Processing for 3D Topographic Mapping

Abstract. The large scale topographic map generation is mostly carried out using the aerial images while the high resolution satellite data are gaining popularity because of its large swath width that enables the efficient and economic mapping even over inaccessible areas. To use the satellite data for the 3D topographic mapping, the data should be acquired in the stereo mode and they requires to be aligned for the epipolar geometry. The accurate epipolar image resampling aligns stereo images to enable a stereo display on the computer monitor where human operators can easily identify and extract 3D features, such as points of interest, contours, building layers, and roads. The pushbroom type camera, which is used by most high-resolution satellites, has quite different epipolar geometry than the frame type of aerial or terrestrial cameras. Therefore, the piecewise approach should be used instead of the fundamental matrix approach that is the standard method for the frame type cameras. Regarding the sensor model, most high-resolution satellite data use RPCs (Rational Polynomial Coefficients) of RFM (Rational Function Model) while the frame type camera use the collinearity equation. But RPCs from the satellite image providers have not been accurate enough such that GCPs (Ground Control Points) are often required for improving the RPCs accuracy. The GCPs acquisition is not an easy task over the inaccessible areas and the positional accuracy of the old geospatial data such as orthoimages and traditional maps is relatively low. Fortunately, the positional accuracy of RPCs increases than the past such as up to several meters. The major problem to achieve high accuracy of stereo geometry is to ensure that the consistency between the stereo data is less than one-pixel level. Therefore, in this study, we first utilized the relative orientation method to improve the precision between the stereo data without using any GCP. The tie points are extracted using the robust stereo matching and they are used to generate quasi-GCPs by the space intersection based on the RPCs. The quasi-GCPs are projected back to the stereo data to model and remove the inconsistency in the image space. The improved RPCs were used to accurately align the stereo data for map production.

A comparison of the time homogeneous and time non-homogeneous markov models for monitoring HIV/AIDS disease progression: Results from patients on ART.

Background: Markov models are widely used in studying progression of chronic diseases using the time homogeneity approach. Relatively few studies use the time non-homogeneous approach to model the progression of HIV/AIDS based particularly in the use of viral load monitoring mainly due to fact that that viral load is expensive to measure frequently hence not readily available in the format required. Non-homogeneous models reveal the interval in which viral rebound occurs. Methods: This study compares the time-homogeneous Markov approach to the time nonhomogeneous approach in predicting HIV/AIDS progression. A piece-wise constant approach to non-homogeneous modelling is used. Results: This study reveals that a piece-wise constant Markov approach to non-homogeneous modelling which allows variation in transition rates within intervals [0,0.5) years and [0.5,∞) years is better for predicting HIV/AIDS progression compared to the time-homogeneous approach. Failure to combination antiretroviral therapy (cART) increases significantly the rate of viral rebound and deaths 6 months post treatment initiation. Conclusion: Hence, there is need to closely monitor the uptake of antiretroviral drugs in the first six months of treatment to increase the chances of survival for HIV/AIDS patients.

High accuracy least-squares solutions of nonlinear differential equations.

This study shows how to obtain least-squares solutions to initial and boundary value problems of ordinary nonlinear differential equations. The proposed method begins using an approximate solution obtained by any existing integrator. Then, a least-squares fitting of this approximate solution is obtained using a constrained expression, derived from Theory of Connections. In this expression, the differential equation constraints are embedded and are always satisfied. The resulting constrained expression is then used as an initial guess in a Newton iterative process that increases the solution accuracy to machine error level in no more than two iterations for most of the problems considered. An analysis of speed and accuracy has been conducted for this method using two nonlinear differential equations. For non-smooth solutions or for long integration times, a piecewise approach is proposed. The highly accurate value estimated at the final time is then used as the new initial guess for the next time range, and this process is repeated for subsequent time ranges. This approach has been applied and validated solving the Duffing oscillator obtaining a final solution error on the order of 10-12. To complete the study, a final numerical test is provided for a boundary value problem with a known solution.

PRM162 - A PIECEWISE APPROACH TO THE EXTRAPOLATION OF INVASIVE DISEASE-FREE SURVIVAL (IDFS) IN THE ADJUVANT TREATMENT OF HER2+ BREAST CANCER

Cost-effectiveness analyses often necessitate the extrapolation of survival data beyond the observation period of a trial. In adjuvant breast cancer, risk of recurrence is high immediately following surgery but decreases over time. An extrapolation reliant solely on observed trial data may lead to estimated survival outcomes that are not reflective of survival rates observed at later timepoints. This study outlines a piecewise approach to survival extrapolation. Outcomes from this piecewise approach are then compared to standard extrapolation and observed values in the long-term follow-up of trials evaluating trastuzumab + chemotherapy (TC) in the adjuvant treatment of HER2+ breast cancer. The adjusted extrapolation was segmented into three separate “phases”. During phase one (time zero to year 4), a log-logistic extrapolation is fitted to invasive disease-free survival (IDFS) data from a Phase III randomised controlled trial, APHINITY. From years four to 10 (time period 2), the initial parametric extrapolation is augmented using a “cure” model. Implementation of the ‘cure’ model assumes that the proportion of patients being “cured” (no longer at risk of recurrence and only subject to background mortality) linearly increases with time from 0% at 48 months to 95% at 120 months. In phase three (year 10 onwards), 95% of event-free patients are assumed to be no longer at risk of recurrence and are susceptible to background mortality only. The unadjusted extrapolation, vastly underestimates expected DFS at later timepoints. The piecewise approach produced similar hazard rates to those observed in the long-term follow-up of older adjuvant trials. IDFS/EFS values at 10 years are 75.23% and 70.00% for the adjusted extrapolation and the BCIRG-006 trial, respectively. The adjustment appears to be beneficial and serves to improve the real-world accuracy of the extrapolation.