Iterative Form Research Articles

Iterative or stative? New morphosemantic analyses of Latinlūgeō‘mourn’ anddoleō‘feel pain’

AbstractThis paper will start by focusing on the morphosemantics of a Latin verblūgeō‘mourn’, which represents an emotion felt by people mentally excruciated by their loved one’s death. Traditionally, it has been believed that the Proto-Indo-European verbal root *leu̯g- ‘break’ underlieslūgeō, but recently this etymology has been challenged. However, I will support the traditional ‘break’ hypothesis through a novel semantic comparison todoleō‘feel pain’, a verb also expressing a type of sensation humans often experience. Since its underlying root *delh1- means ‘hew, split’, similar to ‘break’, the semantic development ofdoleōwould provide a neat parallel forlūgeō. Having salvaged the connection with *leu̯g-, I will advocate a stative formation (with *-eh1-i̯é-) forlūgeōinstead of the more commonly presumed iterative reconstruction (with *-éi̯e-). The analysis conducted forlūgeōturns out to be useful fordoleō, too; I will propose that the latter verb’s wider semantic range is best explained as the result of the convergence of two formations, a stative form meaning ‘feel pain’ (with *-eh1-i̯é-) and an iterative form meaning ‘habitually give pain to’ (with *-éi̯e-, as previously assumed for this verb).

“[A]ltered that a litle which before I had written”: how Margaret Hoby wrote and rewrote her manuscript

AbstractThis essay conducts a paleographic study of Egerton Manuscript 2614, more commonly known as the “diary” of Margaret Hoby. To date, all scholarly studies of this document have been based on one of two print editions of the text. Unfortunately, these editions regularly mistranscribe and misrepresent the early modern manuscript and reduce its palimpsestic complexity. This is the first systematic study of this manuscript as a manuscript and what this textual artefact with all of its scratches, blots, strikethroughs, rewrites, and unfamiliar layout can tell us about how and why Hoby wrote it, and how and why she spent considerable time returning to and amending it. I argue that by looking at never before considered manuscriptal evidence we can conclude that Margaret Hoby produced her manuscript via a multistep process of rereading and revision, and that by approaching her revisionary marks as a form of tattoo, that is, as a form of writing over the self, we can better understand these marks as evidence of an iterative early modern form of self‐making through self‐writing and rewriting.

There’s a time and place: Navigating omni-temporality in the place branding process

This paper investigates how multiple stakeholders understand and navigate the interrelationship between past, present and future time-frames through what is termed omni-temporality. Despite an interest in the phenomenon within the corporate brand heritage literature, a limited understanding persists concerning how omni-temporality shapes stakeholders’ interactions with brands and with each other. These omissions are particularly pertinent in place branding where stakeholders are well-recognised as integral to the branding process. Through case studies of two city brands, our findings reveal tensions that arise when brand stakeholders prioritise the past or strive for a more contemporaneous and future-orientated framing. We identify the ways brand stakeholders navigate these tensions by utilising six (re)framing strategies that range from the reconciliatory to the destabilising. We show how facilitating stakeholders’ expressions of diversity and dissent can produce meaningful brand exchanges, ease the challenges associated with balancing continuity alongside change, and support an iterative form of temporal agency.

Plug‐and‐play algorithms for convex non‐convex regularization: Convergence analysis and applications

When the sparse regularizer is convex and its proximal operator has a closed‐form, first‐order iterative algorithms based on proximal operators can effectively solve the sparse optimization problems. Recently, plug‐and‐play (PnP) algorithms have achieved significant success by incorporating advanced denoisers to replace the proximal operators in iterative algorithms. However, convex sparse regularizers such as the ‐norm tend to underestimate the large values within the sparse solutions. In contrast, the convex non‐convex (CNC) sparse regularization enables the non‐convex regularizer while preserving the convexity of the objective function. In this paper, we propose several PnP algorithms for solving the CNC sparse regularization model and discuss their convergence properties. Specifically, we first derive the proximal operator for CNC sparse regularization in iterative form and subsequently integrate it with several first‐order algorithms to yield different PnP algorithms. Then, based on the monotone operator theory, we prove that the proposed PnP algorithms are convergent under the condition that the data‐fidelity term is strongly convex and the residuals of the denoisers are contractive. We also emphasized the significance of strong convexity in the data‐fidelity term for the CNC sparse regularization model. Additionally, we demonstrate the superiority of the proposed PnP algorithms through extensive image restoration tasks.

BP-SRM: A directly training algorithm for spiking neural network constructed by spike response model

Spiking neural networks (SNNs) have attracted widespread attention due to their unique bio-interpretability and low-power properties, but the non-differentiability of discrete spike sequences fired by spiking neurons brings difficulties to the learning of SNNs. Recently, surrogate gradient (SG) and back-propagation through time (BPTT) have provided an excellent idea for training SNNs constructed by leaky integrate-and-fire (LIF) neuron models. The LIF neuron model has been widely used in previous SNNs due to its simplicity and low computational cost, however, this also limits its simulation of biological neuron dynamics, reducing the biological interpretability of SNNs. In this paper, we generalize SG and BPTT to SNNs constructed by spike response model (SRM) and propose the BP-SRM algorithm. Specifically, we address why BPTT succeeded in LIF neurons-based SNNs but failed in SRM neurons-based SNNs in previous researches. Then we establish an iterative form of the SRM neuron model by selecting different state variables. Based on iterable SRM, we get the spatiotemporal dependencies between the state variables of SRM neurons-based SNNs, which allows us to derive the gradient and update weights in SNN by BP-SRM. Then we design temporal channel normalization for BP-SRM and verify the performance of the SNNs on static image dataset, dynamic image dataset and engineering dataset, including Fashion-MNIST, Weather Dataset, N-MNIST, American Sign Language Dataset and bearing fault diagnosis dataset. The experiment results indicate that BP-SRM achieves the state-of-the-art performance of SNNs.

Impact of inflation severity on retirement savings: A simulation analysis of projected accumulation and de-accumulation

Statistics have shown that by the age of 60, Malaysian life expectancy for males and females is expected to be 17.5 and 20.1 years, respectively. Thus, if not properly addressed by the authorities, the ageing population would contribute to a serious problem for the public by having an inadequacy of retirement wealth to sustain their lives. Considering all of these issues, the present study seeks to comprehensively examine the extent to which inflation adversely affects retirement savings. This investigation holds the potential to yield valuable insights into the accumulation of retirement wealth, thereby addressing the issue of insufficient retirement income, particularly among members of the Employees Provident Fund. Using a mathematical iteration formulation approach, the accumulation and de-accumulation of retirement wealth subject to inflation are formulated to examine the severe impact of this economic factor. Ironically, the disruptive effect of inflation on retirement savings is not severe. It is the power of compounding returns generated by dividend profits that absorbs the real impact. Despite the fact that this is a useful insight, people must plan well for their retirement savings to avoid having them eaten up by inflation. The results showed that inflation disruptions of varying degrees can negatively impact retirement funds. In order to effectively mitigate the potentially detrimental impact of inflation on retirement savings, it becomes imperative to adopt a strategic approach that encompasses various measures, like the exploration of investment opportunities that possess the potential to generate returns surpassing the prevailing inflation rate.

Annihilation-Net: Learned annihilation relation for dynamic MR imaging.

Deep learning methods driven by the low-rank regularization have achieved attractive performance in dynamic magnetic resonance (MR) imaging. The effectiveness of existing methods lies mainly in their ability to capture interframe relationships using network modules, which are lackinterpretability. This study aims to design an interpretable methodology for modeling interframe relationships using convolutiona networks, namely Annihilation-Net and use it for accelerating dynamicMRI. Based on the equivalence between Hankel matrix product and convolution, we utilize convolutional networks to learn the null space transform for characterizing low-rankness. We employ low-rankness to represent interframe correlations in dynamic MR imaging, while combining with sparse constraints in the compressed sensing framework. The corresponding optimization problem is solved in an iterative form with the semi-quadratic splitting method (HQS). The iterative steps are unrolled into a network, dubbed Annihilation-Net. All the regularization parameters and null space transforms are set as learnable in theAnnihilation-Net. Experiments on the cardiac cine dataset show that the proposed model outperforms other competing methods both quantitatively and qualitatively. The training set and test set have 800 and 118 images,respectively. The proposed Annihilation-Net improves the reconstruction quality of accelerated dynamic MRI with betterinterpretability.

The PANDAS/PANS disorders. Is it time for more allergist-immunologists to get involved?

Background: The pediatric autoimmune neurologic disorders associated with streptococcal infections (PANDAS) comprise a group of patients who, after infection with group A β-hemolytic streptococci (GAS), exhibit a spectrum of neuropsychiatric symptoms that include obsessive thoughts, compulsive behaviors, tics, hyperactivity, inattention, and mild choreiform movements. More recently, a group of patients with a symptom complex similar to PANDAS without evidence of streptococcal etiology was given the acronym pediatric acute-onset neuropsychiatric syndrome (PANS). Despite more than several decades of study and increasing numbers of patients being identified with PANDAS and PANS, there are ongoing controversies, which range from disagreements about specific pathogenetic mechanisms to whether these entities actually exist. Objective: The purpose of this report was to examine the current body of evidence that deals with the relationship(s) of immunologic host responses to infection and putative immunologic mechanisms involved in the pathogenesis of these disorders, to evaluate the effectiveness of anti-inflammatory and immunomodulatory therapies with intravenous immunoglobulin (IVIG), and to consider the extent to which allergist/immunologists might be involved in their management. Methods: An extensive literature review was conducted in medical literature data bases by applying terms such as PANDAS, PAN, autoimmune encephalitis, neuroinflammation, and autoimmune obsessive-compulsive disorders. Results: PANDAS and its later iterative form, PANS, continue to challenge clinicians, patients, and their families. Although the precise reason why these disorders develop remains unknown, both are considered to have an autoimmune basis related to the production of antibodies directed at antigens of the putative causative infectious disease agents that are cross-reactive with antigenic epitopes on selected brain nuclei, which lead to the neuroinflammatory sequelae responsible for the neuropsychiatric symptoms of these conditions, a phenomenon referred to as molecular mimicry. Conclusion: The PANDAS/PANS disorders are a continuing burden for growing numbers of patients, health-care providers, and the global health-care systems, and are a particular challenge for the allergist/immunologist who is increasingly being called upon for their management. Because of the importance of immunologic factors in the pathogenesis and treatment of these conditions with anti-inflammatory and immune-modulating treatments, the allergist/immunologist is well poised to offer consultative care.

CRITICAL BUCKLING LOAD SOLUTION OF THIN BEAM ON WINKLER FOUNDATION VIA POLYNOMIAL SHAPE FUNCTION IN STODOLA-VIANELLO ITERATION METHOD

The critical buckling load analysis of thin beam on Winkler foundation (BoWF) is crucial for BoWF subjected to in-plane compressive load. This paper presents the Stodola-Vianello method for the approximate solution of the governing ordinary differential equation (ODE). The Stodola-Vianello method expresses the ODE in iteration form after four successive integrations have been used in reformulating the equation. The problem then reduces to iteration in algebra. By deriving algebraic buckling shape functions that satisfy the boundary conditions, and substitution into the Stodola-Vianello iteration formula derived successive iterations of the buckling shape function would yield better approximations of the buckling shape. The existence condition for convergence which is the identity of the nth and (n +1) iterations are used to find the eigenvalue from which the buckling load is determined. The candidate problem solved is a BoWF with Dirichlet boundary conditions. It is found that one iteration yields sufficiently accurate buckling loads which differs from the exact solution by 0.129% for 0.0807% for and 0.0567% for where bl4 is a parameter measuring the beam structure – Winkler foundation interaction. The negligible difference in the critical buckling load found is because an approximate algebraic one-parameter shape function was used in the iteration. The paper has demonstrated the effectiveness of the Stodola-Vianello iteration for solving the stability of thin beam on Winkler foundation.

A generalized closed-form solution for 3D registration of two-point sets under isotropic and anisotropic scaling

Fitting of two-point sets under non-uniform scaling involves several applications, including ultrasound-guided surgery, where ultrasound images generally show anisotropy between its lateral and depth resolution. However, the current state-of-the-art only accomplishes the closed-form solution under the assumption of isotropic scaling, and only the iterative form of the solution is available for registration regardless of scaling type. A generalized closed-form solution, including anisotropic scaling, could robust the computation in the applications of multi-modality image fusion and surgical navigation based on ultrasound images. In this paper, a generalized closed-form solution (GCFS) that accounts for isotropic scaling and anisotropic scaling is proposed. GCFS finds the least-squares solution of rotation, translation, and scaling based on the singular value decomposition (SVD). The method was demonstrated to 1) register two 3D point sets under the effect of anisotropic scaling and 2) register two coplanar 3D point sets under the effect of anisotropic scaling. This study evaluates 3D registration between the preoperative model and intraoperative ultrasonic scanning of a femur and 2D registration of ultrasound images to the phantom for ultrasound calibration. In addition, the conditions that affect the transformation estimations like estimating reflection and noise degeneracy were also considered in the evaluation.

Comparison of different CFD-FEM coupling methods in advanced structural fire analysis

The research approach of multi-physical field coupling can be used to analyze the structural fire resistance problem. In the process of numerical simulation, multiple coupling interfaces are involved. Regarding fluid-thermal-solid coupling, most of the previous numerical studies on structural fire resistance have used the adiabatic surface temperature (AST) parameters in order to accurately describe complex boundary conditions in fire analysis. This approach belongs to the iterative coupling form, and the other type of direct coupling form is rarely used. In this paper, the specific scenario of a steel column surrounded by fire source is selected as a typical case to explore the thermodynamic phenomena of the steel column. Based on the computational fluid dynamics (CFD) method, the fire model analysis in the fluid domain was first implemented to investigate the distribution laws of the spatial velocity and temperature fields. Then the fluid-thermal-solid coupling was realized via iterative coupling (Adiabatic Surface Temperature method, AST method) and direct coupling (Full Conjugate Heat Transfer method, FCHT method) respectively to obtain the steel column temperatures. The accuracy of these two coupling methodologies was verified by comparing their results with the experimental data, and the accuracy of AST method depends on the reasonable sampling of fire analysis results. Following this, structural model analysis was completed using the solid temperature as the boundary condition to achieve the solid thermal-mechanical coupling. The yield strength degradation of the steel column after heating was explored. Finally, the non-necessity of fluid-mechanical-solid coupling in structural fire resistance was discussed.

The Parametric High-Fidelity-Generalized-Method-of-Cells with phase-field damage micromechanical model for heterogeneous composites

A new coupled micromechanical-damage formulation is presented by directly integrating the phase-field (PF) modeling approach for fracture and damage with the Parametric High-Fidelity-Generalized-Method-of-Cells (PHFGMC) micromechanical model. The combined PHFGMC-PF approach is proposed for progressive damage analysis of multi-phase heterogeneous composites with evolving microstructure subject to general multi-axial remote loading. New variational equations are introduced to couple the macro/micro deformation and PF variables of the discrete finite volumes (subcells). An iterative computational formulation is also presented for the numerical solution of the overall nonlinear equations. The proposed approach can accommodate various phase-field damage models and fracture energy approximations. Two PF damage laws, available in the literature, are implemented. The proposed PHFGMC-PF model verification is first accomplished by solving the single-edge crack problem under tension and shear and comparing the results to a finite element PF (FE-PF) analysis. Results of the presented case studies demonstrate a comparable ability of the PHFGMC-PF to solve similar FE-PF non-periodic problems. Applications are presented for progressive damage of carbon-fiber-reinforced (CRP) composites. The PHFGMC-PF in-situ elastic and fracture properties are calibrated for the carbon-reinforced polymer IM7/977-3 composite material system at the fiber–interface–matrix constituents. The micromechanics-PF model can capture the composite overall nonlinear mechanical and damage responses compared to experimental data.

Integrating computational thinking into primary mathematics: A case study of fraction lessons with Scratch programming activities

We presented a design-based study within the context of a four-session Scratch programming activity among 23 fourth-grade students in Hong Kong. Inspired by the computational thinking (CT) strategies and the 5E instructional model, we investigated students’ mathematical learning of fractions in a Scratch (block-based programming) environment. Students developed CT concepts, practices, and perspectives by building a “fraction magic calculator” in groups. This study analyzed the lesson design, students’ drawings, interviews, and work expressing their mathematical understanding of fractions in Scratch applications. The learning tasks were designed to support the students’ fraction learning and utilized computational abstractions in the form of variables, functions, and iterations to formulate mathematical models in a programming context. Students’ artifacts and feedback showed they were interested in learning fractions in a programming learning context, contributing to exercising and improving their fraction concepts and CT. Ultimately, we emphasized the benefits of CT integrated into mathematics education, promoting students’ understanding of fraction concepts, a set of CT abilities (concepts, practices, perspectives), and learning motivation. Moreover, we suggested a set of non-cognitive skills (e.g., socializing, expressing) to enrich the CT perspectives in the framework and show the importance of developing coding communities to co-create digital artifacts among learners. Overall, we highlighted that mathematics teachers should apply and create learning tasks that promote computational thinking to forge mathematical ideas and thinking.

Operationalizing crop model data assimilation for improved on-farm situational awareness

The ability of ‘digital agriculture’ to support on-farm decision making is predicated on the real-time combination of observations and prior knowledge into an integrated digital environment. The mathematical discipline that seeks to provide this integration is known as model data assimilation (DA), with demonstrated benefits including improved predictive reliability, and the capacity to identify unexpected changes in field conditions and potential measurement errors. Despite routine adoption in other fields, the delayed adoption of DA in agriculture is due to the need to express end-of-season outcomes such as yield, update forecasts of these outcomes throughout the growing season as data become available, and enhance forecast reliability. To overcome these challenges, three guiding principles are introduced, providing a means to operationalize crop model DA for robust on-farm decision support. We apply the guiding principles using a South Australian viticulture case study. Our case study involves application of an iterative form of a widely used DA algorithm (ensemble Kalman filter) to dynamically update both static parameters and states associated with a grapevine simulation model. Daily weather data as well as fortnightly ground-based leaf area index (LAI) data are used for assimilation. It is shown how crop model DA can lead to not only significant improvements in forecasts of LAI but also to forecasts of end-of-season yield. The guiding principles also enable observations of greatest value to be identified throughout the season. This study highlights the role that formal crop model DA can play in agricultural decision support through enhancing situational awareness in real time.

Development of low-cost, weight-adjustable clofazimine mini-tablets for treatment of tuberculosis in pediatrics

Clofazimine (CFZ) is an important component of the World Health Organization's (WHO) recommended all-oral drug regimen for treatment of multi-drug resistant tuberculosis (MDR-TB). However, the lack of a dividable oral dosage form has limited the use of the drug in pediatric populations, who may require lowering of the dose to reduce the likelihood of adverse drug events. In this study, pediatric-friendly CFZ mini-tablets were prepared from micronized powder via direct compression. Rapid disintegration and maximized dissolution in GI fluids was achieved using an iterative formulation design process. Pharmacokinetic (PK) parameters of the optimized mini-tablets were obtained in Sprague-Dawley rats and compared against an oral suspension of micronized CFZ particles to examine the effect of processing and formulation on the oral absorption of the drug. Differences in maximum concentration and area under the curve between the two formulations were non-significant at the highest dosing level tested. Variability between rats prevented bioequivalence from being determined according to guidelines outlined by the Food and Drug Administration (FDA). These studies provide an important proof-of-concept for an alternative, low-cost formulation and processing approach for the oral delivery of CFZ in manner that is suitable for children as young as 6 months of age.

Flexible Trip-Planning Queries

The current practice of users searching for different types of geo-resources in a geographic area and wishing to identify the most convenient routes for visiting the most relevant ones, requires the iterative formulation of several queries: first to identify the more interesting resources and then to select the best route to visit them. In order to simplify this process, in this paper a novel functionality for a geographic information retrieval (GIR) system is proposed, which retrieves and ranks several routes for visiting a number of relevant georeferenced resources as a result of a single query, named flexible trip-planning query. An original retrieval model is defined to identify the relevant resources and to rank the most convenient routes by taking into account personal user preferences. To this end, a graph-based algorithm is defined, exploiting prioritized aggregation to optimize the routes’ identification and ranking. The proposed algorithm is applied in the proof-of-concept of a Smart cOmmunity-based Geographic infoRmation rEtrievAl SysTem (SO-GREAT) designed to strengthen local communities: it collects and manages open data from regional authorities describing categories of authoritative territorial resources and services, such as schools, hospitals, etc., and from volunteered geographic services (VGSs) created by citizens to offer services in their neighbourhood.

Deterministic Beamforming for Unmanned Aerial Vehicle Array

This paper addresses the deterministic beamforming for unmanned aerial vehicle (UAV) array (UAVA), which is equipped with an antenna for each UAV. Unlike conventional array, the UAVA can obtain extra degrees-of-freedom for beamforming by flexibly controlling the topology of UAVs, which motivates us to consider an off-grid array layout to improve the beamformer. To effectively control the load of UAVs, we incorporate the dynamic range ratio (DRR) of weighting coefficients of UAVA. On these basis, we formulate a new optimization model aiming to minimize the maximum sidelobe level under the constraints of mainlobe ripple, DRR, layout spacing and array aperture. However, the resulting NP-hard problem is quite challenging due to the exponential form of layout vector and the non-convexity of mainlobe ripple and DRR. In this respect, we reformulate this multi-constrained problem into a new iteration form of combining alternating direction penalty method and majorization-minimization via introducing a series of auxiliary variables. In each iteration, the tractable and small-sized subproblems can almost globally be solved. Numerical results confirm that our method is more suitable for deterministic beamforming of UAVA than the state-of-the-art methods.

DESIGN SYSTEM INFORMATION CASHIER WEBSITE BASED SPIRAL METHOD SHOP VINNY KITCHEN MDO

Cashier system in shop business entities Vinny Kitchen Mdo is still using Sales services are still done manually, namely cashiers only use calculations manual with a calculator and data collection of goods is still manual and resulted very ineffective and efficient in doing transaction. Facility And service to cashier expected can given in a manner automatic so that No bother in transactions with customers, and if there is a cashier does not need to provide the same service in a manner manuals. Model implementation system cashier based web possible system used by cashiers and admins to automatically calculate orders for goods in transaction sale. Use system cashier based web This can see chart sales that are entered in the system so that store owners can monitor increases or a decrease in transactions. The method to be used is the Spiral Method that is, a software process model that incorporates the iterative form of the model prototyping aspect control And systematics. Design system information cashier sale product shop vinny kitchen mdo in do transaction, processing data, And Web-based automatic printing of reports when running will occur change system Which before manual be computerized.

A Contrastive Study of the Co-occurrence of the Augmented, Unaugmented and Iterative forms in -σκ- in Iliad 24

A Contrastive Study of the Co-occurrence of the Augmented, Unaugmented and Iterative forms in -σκ- in Iliad 24

A Tale of Two Rats: The Backstory of a Clever Cartoon.

A well-known cartoon among psychologists and behavior analysts depicts two rats in a Skinner box, leaning over a response lever as one says to the other, "Boy, do we have this guy conditioned, every time I press the bar down he drops a pellet in." Anyone who has ever conducted an experiment, worked with a client, or taught someone can relate to the cartoon's message of reciprocal control between subject and experimenter, client and therapist, and teacher and student. This is the tale of that cartoon and its impact. It begins mid-20th-century at Columbia University, then a hotbed of behavioral psychology, which bears an intimate connection to the cartoon's appearance. The tale expands from Columbia to follow the lives of its creators from their undergraduate days there to their deaths decades later. The infusion of the cartoon into American psychology begins with B. F. Skinner, but, over the years, it also has appeared in introductory psychology textbooks and in iterative form in mass media outlets such as the World Wide Web and magazines like The New Yorker. The heart of the tale, however, was stated in the second sentence of this abstract. The tale ends with a review of how reciprocal relations like those depicted by the cartoon's creators have influenced research and practice in behavioral psychology.