Full Iteration Research Articles

Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review

AbstractPeer review is a key component of the publishing process in most fields of science. Increasing submission rates put a strain on reviewing quality and efficiency, motivating the development of applications to support the reviewing and editorial work. While existing NLP studies focus on the analysis of individual texts, editorial assistance often requires modeling interactions between pairs of texts—yet general frameworks and datasets to support this scenario are missing. Relationships between texts are the core object of the intertextuality theory—a family of approaches in literary studies not yet operationalized in NLP. Inspired by prior theoretical work, we propose the first intertextual model of text-based collaboration, which encompasses three major phenomena that make up a full iteration of the review–revise–and–resubmit cycle: pragmatic tagging, linking, and long-document version alignment. While peer review is used across the fields of science and publication formats, existing datasets solely focus on conference-style review in computer science. Addressing this, we instantiate our proposed model in the first annotated multidomain corpus in journal-style post-publication open peer review, and provide detailed insights into the practical aspects of intertextual annotation. Our resource is a major step toward multidomain, fine-grained applications of NLP in editorial support for peer review, and our intertextual framework paves the path for general-purpose modeling of text-based collaboration. We make our corpus, detailed annotation guidelines, and accompanying code publicly available.1

Confronting Potential Cultural Barriers in Translated Works

Confronting Potential Cultural Barriers in Translated Works reflects upon the stylistic choices of Maxine Hong Kingston and Sandra Cisneros in their respective works, "No Name Woman" and “Woman Hollering Creek.” Both strategically include either moments of or full iterations of translation culturally and linguistically. When incorporating translation at any degree, a potential barrier could arise: a barrier from comprehension, a barrier from translation, a barrier between author and reader, or a barrier between cultures. Throughout this essay, I will be discerning the stylistic choices of Cisneros and Kingston concerning their inclusion of translation but also their overarching storylines to evaluate whether their work disrupts the presented cultural barrier or whether the presented cultural barrier disrupts their work.

Dynamic asynchronous iterations

Many problems can be solved by iteration by multiple participants (processors, servers, routers etc.). Previous mathematical models for such asynchronous iterations assume a single function being iterated by a fixed set of participants. We will call such iterations static since the system's configuration does not change. However in several real-world examples, such as inter-domain routing, both the function being iterated and the set of participants change frequently while the system continues to function. In this paper we extend Üresin and Dubois's work on static iterations to develop a model for this class of dynamic or always on asynchronous iterations. We explore what it means for such an iteration to be implemented correctly, and then prove two different conditions on the set of iterated functions that guarantee the full asynchronous iteration satisfies this new definition of correctness. These results have been formalised in Agda and the resulting library is publicly available.

Integrating advances in population and evolutionary ecology with conservation strategy through long-term studies of red-billed choughs.

Conceptual and methodological advances in population and evolutionary ecology are often pursued with the ambition that they will help identify demographic, ecological and genetic constraints on population growth rate (λ), and ultimately facilitate evidence-based conservation. However, such advances are often decoupled from conservation practice, impeding translation of scientific understanding into effective conservation and of conservation-motivated research into wider conceptual understanding. We summarise key outcomes from long-term studies of a red-billed chough Pyrrhocorax pyrrhocorax population of conservation concern, where we proactively aimed to achieve the dual and interacting objectives of advancing population and evolutionary ecology and advancing effective conservation. Estimation of means, variances and covariances in key vital rates from individual-based demographic data identified temporal and spatial variation in subadult survival as key constraints on λ, and simultaneously provided new insights into how vital rates can vary as functions of demographic structure, natal conditions and parental life history. Targeted analyses showed that first-year survival increased with prey abundance, implying that food limitation may constrain λ. First-year survival then decreased dramatically, threatening population viability and prompting emergency supplementary feeding interventions. Detailed evaluations suggested that the interventions successfully increased first-year survival in some years and additionally increased adult survival and successful reproduction, thereby feeding back to inform intervention refinements and understanding of complex ecological constraints on λ. Genetic analyses revealed novel evidence of expression of a lethal recessive allele, and demonstrated how critically small effective population size can arise, thereby increasing inbreeding and loss of genetic variation. Population viability analyses parameterised with all available demographic and genetic data showed how ecological and genetic constraints can interact to limit population viability, and identified ecological management as of primacy over genetic management to ensure short-term persistence of the focal population. This case study demonstrates a full iteration through the sequence of primary science, evidence-based intervention, quantitative evaluation and feedback that is advocated in conservation science but still infrequently achieved. It thereby illustrates how pure science advances informed conservation actions to ensure the (short-term) stability of the target population, and how conservation-motivated analyses fed back to advance fundamental understanding of population processes.

Diagnostic Value of Chest CT Images Based on Full Model Iterative Reconstruction Algorithm for Lung Cancer Patients

Objective. To evaluate the value of low-dose CT scanning and full model iteration recombinant technology peripheral lung cancer in the paper using whole model iterative reconstruction algorithm and compare iterative model-wide restructuring, reorganization part of an iterative algorithm, affecting filtered back projection image quality. Method. Fifty-two patients with peripheral lung cancer, all of whom were diagnosed by pathological biopsy, were selected for the study. All patients received three scans of low-dose chest CT, next-low-dose, and low-dose, after which the raw data of three different doses were reconstructed using filtered back-projection, iterative partial algorithm reconstitution, and reconstructed full-model iteration, respectively, and the effect of each algorithm on the processing of chest CT images of peripheral lung cancer at different doses and the diagnosis of the disease were compared after the reconstitution was completed. Results. The average effective radiation dose for the low-dose group was (0.3±0.02) mSv At each dose level, image noise objective recombinant whole iterative model < part of the reorganization of the iterative algorithm < filtered back projection, the difference was significant. In the case of lung lesions, the full-model iterative algorithm has similar evaluation power to the LD-partial iterative algorithm. When a patient’s body mass index (BMI) > 25 kg/m2, the whole model iteration reorganization image quality is reduced, but the lesions-to-noise ratio (SNR) is unaffected. Conclusion. The combination of a very low dose of recombinant iterative model as compared to full-dose low-dose chest CT dose can be reduced to 88% but does not reduce the overall image quality and can show good radiological signs of peripheral lung cancer and not affect BMI patients.

A Simple and Fast Bi-Objective Search Algorithm

Many interesting search problems can be formulated as bi-objective search problems; for example, transportation problems where both travel distance and time need to be minimized. Multi-objective best-first search algorithms need to maintain the set of undominated paths from the start state to each state to compute a set of paths from a given start state to a given goal state (the Pareto-optimal solutions) such that no path in the set is dominated by another path in the set. Each time they find a new path to a state n, they perform a dominance check to determine whether such a path dominates any of the previously found paths to n. Existing algorithms do not perform these checks efficiently, requiring at least a full iteration over the Open list per check. In this paper, we present the first multi-objective algorithm that performs these checks efficiently. Indeed, Bi-Objective A* (BOA*)—our algorithm—requires constant time to check for dominance. Our experimental evaluation shows that BOA*is orders-of-magnitude faster than state-of-the-art search algorithms, such as NAMOA*, Bi-Objective Dijkstra, and Bidirectional Bi-Objective Dijkstra.

Multiscale phase inversion for vertical transverse isotropic media

ABSTRACTInanisotropy full waveform inversion, the pseudo‐acoustic approximation is widely used to reduce the computation cost. However, artefacts and inaccurate predictions of amplitudes by the pseudo‐acoustic approximation often result in slow convergence in the full waveform inversion iterations and inaccurate tomograms. To solve this problem, multiscale phase inversion methodology is extended to vertical transverse isotropic media. In multiscale phase inversion, the amplitude spectra of the predicted data are replaced by those of the recorded data to mitigate the amplitude mismatch problem. Moreover, multiscale phase inversion tends to avoid the local minimum problem of full waveform inversion by temporally integrating the traces several times. Numerical tests on synthetic data and field data demonstrate the superiority of this method compared to conventional multiscale full waveform inversion for vertical transverse isotropic media.

Modelling and analysis of vibration on power electronic module structure and application of model order reduction

Modelling and analysis of vibration of an IGBT power electronic module (PEM) structure were undertaken. PEM structure considered in this study was without molding compound and wirebonds. The most critical resonant frequency was identified by modal analysis. At the critical frequency of 1345 Hz, for the vertical displacement of the base excitation, subsequent stress distribution on the PEM structure was analysed. Concurrent vibration and thermo-mechanical fatigue loads on the reliability of PEM structure solder interconnects were also estimated by widely used linear damage superposition approach. It was concluded that the at critical resonant frequency the vibration induced damage is more severe than the thermo-mechanical fatigue loading. In addition, a quarter car model (QCM) was used to mimic the dynamic interaction between the rough road surface and an electric vehicle (EV) in order to analyse the road surface roughness induced excitation on the PEM structure in the engine compartment. Stress and strain distribution on the PEM structure due to road surface roughness were analysed. Furthermore, three Krylov subspace based model order reduction (MOR) techniques were applied to the resulting dynamic system in vibration analysis. Due to the limits on computing resources, a submodel was utilized for MOR analysis. Within the three MOR techniques, Passive Reduced order Interconnect Macromodeling Algorithm (PRIMA) MOR technique performs better than the other techniques. Computational time ratio between reduced system iteration and the full system iteration is 1: 53.

Design of a Crashworthy Cable-Driven Four-Bar Link Robotic Landing Gear System

In this work a novel crashworthy cable-driven four-bar link mechanism is designed, manufactured, and tested for the development of robotic landing gear for rotorcraft. The paper will demonstrate how combining two such mechanisms through a common driving cable leads to unique advantages in the kinematics of the system and reduced loads applied to the actuators driving the system. The results on the kinematics and static force distributions are presented for such a configuration and show that, for the rotorcraft class under consideration (220–440 lb, 100–200 kg), the leg mechanism can conform to ground slopes up to . A novel design, manufacturing, and a drop testing workflow that allows for rapid design and iteration of robotic landing gear are further developed. The workflow includes the design, simulation, rapid manufacturing, and crash-survivability testing through drop testing with a two week turnaround time for a full design iteration. With regard to rapid manufacturing, this work demonstrates the use of three-dimensionally printed acrylonitrile butadiene styrene mandrels for the production of fully functional carbon fiber polymer reinforced components. This paper concludes with actuation experiments to show practical performance capabilities of the final crashworthy robotic landing gear system designed.

General efficient class of Steffensen type methods with memory for solving systems of nonlinear equations

There are a very small number of high quality derivative free methods with memory for solving a system of nonlinear equations numerically. Motivated and inspired by the fact, we propose a more efficient general class of Steffensen type multipoint methods with memory. This proposed class requires one divided difference and inverse of only one matrix per full iteration. We also demonstrate their applicability and illustrate that these methods produce approximations of greater accuracy and remarkably reduce the computational time for solving systems of nonlinear equations numerically. For quantitative comparison, we have also computed total number of convergent points and convergent percentage along with basins of attractions on a number of test problems to recommend the best quality algorithm.

Review: Not Quite Architecture: Writing around Alison and Peter Smithson, by M. Christine Boyer

M. Christine Boyer Not Quite Architecture: Writing around Alison and Peter Smithson Cambridge, Mass.: MIT Press, 2017, 483 pp., 25 color and 80 b/w illus. $44.95 (cloth), ISBN 9780262035514 Robin Hood Gardens (1972), the London housing estate that realized the urban principles of Peter and Alison Smithson, is now in the process of being literally and figuratively deconstructed. As would suit a pair of architects whose professional careers began with musings over the “as found” rubble of postwar London, the Victoria and Albert Museum has stepped in to salvage a three-story section of the structure from the demolition site. The segment, despite the curatorial conservation of its fittings and cabinetry, is no arbitrarily, or even programmatically, determined fragment: it represents a full iteration of the repeated graphic sequence that once formed the building's facade. This pattern of prefabricated parts preserves the centrality of the representational method that was as fundamental to the Smithsons' practice as were off-the-shelf materials. The graphology of this reliquary also encapsulates the spirit of the disproportionate quantity of historical research into the Smithsons and their work that has been conducted over the past few decades. Much has been made of the Smithsons' commentary on the compilation of advertisements, as well as their affection for raw industrial materiality. Scholars, myself included, have deployed interactions of the couple with the politics of the discipline at home and abroad to preserve a portrait of an era that is both peculiarly British and central to the devolution of mainstream modernism. The universality of the particular was a strong theoretical suit of the Smithsons …

Nested Plant/Controller Codesign Using G-Optimal Design and Continuous Time Adaptation Laws: Theoretical Framework and Application to an Airborne Wind Energy System

This paper presents a nested codesign (combined plant and controller design) formulation that uses optimal design of experiments (DoE) techniques at the upper level to globally explore the plant design space, with continuous-time control parameter adaptation laws used at the lower level. The global design space exploration made possible through optimal DoE techniques makes the proposed methodology appealing for complex, nonconvex optimization problems for which legacy approaches are not effective. Furthermore, the use of continuous-time adaptation laws for control parameter optimization allows for the extension of the proposed optimization framework to the experimental realm, where control parameters can be optimized during experiments. At each full iteration, optimal DoE are used to generate a batch of plant designs within a prescribed design space. Each plant design is tested in either a simulation or experiment, during which an adaptation law is used for control parameter optimization. Two techniques are proposed for control parameter optimization at each iteration: extremum seeking (ES) and continuous-time DoE. The design space is reduced at the end of each full iteration, based on a response surface characterization and quality of fit estimate. The effectiveness of the approach is demonstrated for an airborne wind energy (AWE) system, where the plant parameters are the center of mass location and stabilizer area, and the control parameter is the trim pitch angle.

Quality Function Deployment and operational design decisions – a healthcare infrastructure development case study

The purpose of this paper is to demonstrate how QFD can enhance a healthcare organisation’s strategic operational alignment, by synchronising the infrastructure design with the service intention. In this empirical paper, a case study of a £15 million infrastructure development has been used as the unique context to assess and test the experimental findings. QFD was utilised in order to capture and transform the requirements of decision-makers, providers, patients and local communities into both service and building design for Project K, a healthcare infrastructure, in the U.K. Two full iterations of the QFD results are presented. Using QFD generated effectiveness and efficiency by creating an information exchange platform and providing the stakeholders with a framework to optimise the decision-making. This paper makes a practical contribution by empirically testing the QFD modelling and providing evidence of its implementation within the complex, dynamic and evolving nature of the healthcare built environment sector.

Quantile regression and variable selection for single-index varying-coefficient models

ABSTRACTIn this article, a new efficient iteration procedure based on quantile regression is developed for single-index varying-coefficient models. The proposed estimation scheme is an extension of the full iteration procedure proposed by Carroll et al., which is different with the method adopted by Wu et al. for single-index models that a double-weighted summation is used therein. This distinguish not only be the reason that undersmoothing should be a necessary condition in our proposed procedure, but also may reduce the computational burden especially for large-sample size. The resulting estimators are shown to be robust with regardless of outliers as well as varying errors. Moreover, to achieve sparsity when there exist irrelevant variables in the index parameters, a variable selection procedure combined with adaptive LASSO penalty is developed to simultaneously select and estimate significant parameters. Theoretical properties of the obtained estimators are established under some regular conditions, and some simulation studies with various distributed errors are conducted to assess the finite sample performance of our proposed method.

Ce 3p hard x-ray photoelectron spectroscopy study of the topological Kondo insulator CeRu4Sn6

Bulk sensitive hard x-ray photoelectron spectroscopy data of the Ce 3p core level of CeRu4Sn6 are presented. Using a combination of full multiplet and configuration iteration model we were able to obtain an accurate lineshape analysis of the data, thereby taking into account correlations for the strong plasmon intensities. We conclude that CeRu4Sn6 is a moderately mixed valence compound with a weight of 8% for the Ce f0 configuration in the ground state.

Improved Chebyshev–Halley family of methods with seventh and eighth order of convergence for simple roots

The principle aim of this manuscript is to introduce a new highly efficient improved modification of Chebyshev–Halley family with increasing order of convergence. The idea is based on the schemes proposed by Li et al. (Appl Math Comput 235:221–225, 2014) and Sharma (Appl Math Comput 256:119–124, 2015). The proposed scheme has at least seventh-order of convergence and also posses an optimal eighth-order of convergence for a particular value of the disposable parameter. Each member of the proposed scheme is free from second-order derivative and requires only four functional evaluations (viz. three evaluations of function f and one of first-order derivative $$f'$$ ) per full iteration. A variety of concrete numerical examples demonstrates that our proposed scheme performs better than the existing schemes proposed by Li et al. (Appl Math Comput 235:221–225, 2014) and Sharma (Appl Math Comput 256:119–124, 2015). Dynamical study of our methods also confirms the above conclusions to a great extent. Moreover, the local convergence of these methods is given using hypotheses only on the first derivative and Lipschitz constants.

Cyclic Coordinate-Update Algorithms for Fixed-Point Problems: Analysis and Applications

Many problems reduce to the fixed-point problem of solving $x=T(x)$, where $T$ is a mapping from a Hilbert space to itself. To this problem we apply the coordinate-update algorithms, which update only one or a few components of $x$ at each step. When each step is cheap, these algorithms are faster than the full fixed-point iteration (which updates all the components). In this paper, we focus on cyclic coordinate selection rules, where the ordering of coordinates in each cycle is arbitrary. The corresponding algorithms are fast, but their convergence is unknown in the fixed-point setting. When $T$ is a nonexpansive operator and has a fixed point, we show that the sequence of coordinate-update iterates converges to a fixed point under proper step sizes. This result applies to the primal-dual coordinate-update algorithms, which have wide applications to optimization problems with nonseparable nonsmooth objectives, and/or global linear constraints. Numerically, we apply coordinate-update algorithms with cycli...

Siltumvadīšanas uzdevuma risinājums anizotropā 3D vidē un tā pilnveidošanas iespējas

Nowadays there are high speed improvements in processors frequencies and processors amount on a single map. So these opportunities have to be used in such fields as modeling and simulation, prediction models and simulations. One of these fields is strictly connected with the article's subject (heat conduction). Heat conduction calculation in 3D space is quite a problem for 3D space calculations because the time spent on calculation for usual approaches is quite long. It is possible to separate full iteration of heat conduction calculation into several portions. These portions of calculation could contain separate calculation blocks. It is possible to implement using ADI (Alternating Direction Implicit) principles in dividing full iteration of heat conduction calculation into 3 parts. Each of these parts ignores one of the directions of coordinate axes, but allows to calculate only three diagonal matrix using Thomas algorithm. It means that additional effort on difference scheme construction has the payback of calculation time reducing because of separated calculable blocks. Another boost of calculation speed is dynamic time step implementation by taking into account the prediction matrix of next iteration heat transfer calculations. This approach has no strict impact on time step calculations for each next iteration, but it can be bordered between the possible minimal and maximal time step defined values. Provided solutions allow to manage algorithm calculation time by applying as many computers as many times as needed to reduce the calculation time.

Another Newton-type method with (k+2) order convergence for solving quadratic equations

In this paper we define another Newton-type method for finding simple root of quadratic equations. It is proved that the new one-point method has the convergence order of k  2 requiring only three function evaluations per full iteration,where k is the number of terms in the generating series. The Kung and Traub conjecture states that the multipoint iteration methods, without memory based on n function evaluations, could achieve maximum convergence order 1 2nï€ ­but, the new method produces convergence order of nine, which is better than the expected maximum convergence order. Finally, we have demonstrated that our present method is very competitive with the similar methods.

The Buckley–James Estimator and Induced Smoothing

SummaryThe Buckley–James (BJ) estimator is known to be consistent and efficient for a linear regression model with censored data. However, its application in practice is handicapped by the lack of a reliable numerical algorithm for finding the solution. For a given data set, the iterative approach may yield multiple solutions, or no solution at all. To alleviate this problem, we modify the induced smoothing approach originally proposed in 2005 by Brown & Wang. The resulting estimating functions become smooth, thus eliminating the tendency of the iterative procedure to oscillate between different parameter values. In addition to facilitating point estimation the smoothing approach enables easy evaluation of the projection matrix, thus providing a means of calculating standard errors. Extensive simulation studies were carried out to evaluate the performance of different estimators. In general, smoothing greatly alleviates numerical issues that arise in the estimation process. In particular, the one‐step smoothing estimator eliminates non‐convergence problems and performs similarly to full iteration until convergence. The proposed estimation procedure is illustrated using a dataset from a multiple myeloma study.