Reconstruction Theory Research Articles

Social Reconstruction as an Effort to Restorate the Concept of Educational Management

Social reconstruction theory in the world of education emphasizes that education must act as a tool for social transformation that encourages students to think critically, understand social problems, and contribute to creating a more just and inclusive society. This article aims to explore more deeply the concept of social reconstruction theory in its urgency in the field of education management. This research uses a normative approach. The results of the study show that social reconstruction and educational management are interrelated in an effort to create an education system that is responsive to social change, where educational management functions as a tool for implementing strategies that support social transformation through inclusive and relevant learning.

When and Why Do Supervisors’ Evaluations Overweight Subordinates’ Performance Outcomes? Evidence from a Team Setting in the Field

ABSTRACT To better understand supervisors’ outcome bias, I use a regression discontinuity design that compares coaches’ performance assessments of professional football players involved in narrow wins and losses. I document that supervisors over-react to negative outcomes, sharply lowering performance ratings and tripling subordinate turnover. I find that supervisors’ evaluations that subjectively incorporate information from more incomplete objective performance measures are more prone to outcome bias than those that draw on less incomplete objective measures. I also document that supervisors’ evaluations of high-performing team members are more prone to outcome bias than supervisors’ evaluations of low performers. Finally, I find that outcomes affect supervisors’ ex post information collection. My findings, consistent with predictions that I derive from the theory of cognitive reconstruction, shed light on supervisors’ outcome bias in team settings and how effectively firms’ use of objective performance measures, direct monitoring, and information gathering can mitigate this bias. JEL Classifications: M50; D91; Z20.

Accuracy and completeness of autobiographical memory: evidence from a wearable camera study

ABSTRACT A small wearable camera, SenseCam, passively captured pictures from everyday experience that were later used to evaluate the accuracy and completeness of autobiographical memory. Nine undergraduates wore SenseCams that took pictures every 10 s for two days. After one week and one month, participants first recalled their experiences from specific time periods (timeslices), then reviewed the corresponding pictures to make corrections and report information omitted from initial recall. Results demonstrated the utility of wearable cameras as research tools, and illustrated several characteristics of everyday memory. Recall contents reflected the structure of undergraduate lives. Three different types of omissions were reported: neglected, reminded, and forgotten. Pictures stimulated memory, even for non-visual information (e.g., feelings, thoughts), increasing recall by 23%. The mean completeness of initial recall was 79% (upper bound), with at least 21% forgetting. Accuracy was self-scored by participants (M = 89%), and the mean error rate (11%) provided evidence against strong reconstructive and copy theories of memory. The characteristics of errors shed light on the cognitive processes underlying them. Ratings of recall (confidence, reliving, knowledge, and frequency) supported the episodic/semantic distinction, the dual-process theory of repetition, and reconstructive imagery. Metamemory measures showed a positive correlation between confidence and accuracy.

Time-dependent theory of reconstruction of attosecond harmonic beating by interference of multiphoton transitions

Time-dependent theory of reconstruction of attosecond harmonic beating by interference of multiphoton transitions

Refined composite multivariate multiscale fuzzy dispersion entropy: Theoretical analysis and applications

Multivariate multiscale sample entropy (mvMSE) is a popular method to quantify the irregularity of multi-channel time series. However, mvMSE generates either undefined or unreliable results for short-length signals and has a high computational cost. To address these issues, multivariate multiscale dispersion entropy (mvMDE) was recently developed, but it depends on its parameters and overlooks some data information. To address these limitations, we herein propose an extension of fuzzy dispersion entropy (FDE) by incorporating fuzzy set theory, multidimensional embedding reconstruction theory, and dispersion patterns. This leads to the multivariate multiscale FDE (mvMFDE) and refined composite mvMFDE (RCmvMFDE) measures. (RC)mvMFDE is the first multivariate analysis based on Shannon entropy that uses the fuzzification concept. Some sets of time series have been synthesized and analyzed using several concepts in multivariate signal processing to evaluate the advantages of our introduced mvMFDE and RCmvMFDE. The results indicated that the proposed methods are less sensitive to their parameters, signal length, and noise, providing more stable results compared to the existing approaches mvMSE and mvMDE. On multi-channel noise signals and bivariate autoregressive processes, mvMSE, mvMDE, and mvMFDE produced similar finding although mvMFDE exhibited superior discriminative capabilities. When applied to one physiological dataset and two mechanical datasets, RCmvMFDE distinguished the diverse dynamics of multichannel signals exceptionally well.

Experimental study and multi‐scale refinement model of high damping acrylic polymer matrix VEDs for civil structural seismic retrofit

AbstractThe viscoelastic dampers (VEDs), which can provide both stiffness and damping, have been recently introduced into the field of structural vibration control for seismic enhancement of civil engineering structures. In this study, a kind of high damping acrylic polymer matrix VEDs (HDPVED) is developed independently, and this innovative HDPVED can solve the significant problem of service performance under medium‐high temperature environments, as well as low‐frequency vibration control under earthquake actions for civil engineering structures. To systematically investigate the influencing rules of frequency, temperature, and displacement amplitude on the mechanical properties and damping dissipation performance of HDPVEDs, a series of dynamic mechanical performance tests of the developed HDPVEDs are carried out at different frequencies, temperatures, and displacement amplitudes. The research results show that HDPVED exhibits excellent damping dissipation capability and adaptability under medium‐high temperature environments and low‐frequency excitations. The mechanical properties and energy dissipation performance present a strong correlation with frequency, temperature and displacement amplitude, and there is an obvious coupling effect between the three influencing factors. Based on the macroscopic mechanical property research of HDPVED, the microscopic damping mechanism and microscopic mechanical properties of HDPVED are then investigated. High‐order fractional derivative fraction Voigt and Maxwell model in parallel (FVMP) models are preferred to characterize the combined hyper‐elasticity and viscoelasticity owned by networked molecular chains and free molecular chains. The breaking and reconstruction theory of microphysical bonds is used to assess the effect of packing particles, and the time‐temperature equivalence principle is introduced to assess the effect of temperature. The multi‐scale refinement model is proposed, and the validity and accuracy of this model are verified by testing data of HDPVED. The study results show that the proposed model can accurately describe the effects of frequency, temperature, displacement amplitude, and microstructure on the multi‐scale mechanical properties of HDPVED. It provides a theoretical basis for the multi‐scale design and development of high damping VEDs.

Ozone as an environmental driver of influenza

Under long-standing threat of seasonal influenza outbreaks, it remains imperative to understand the drivers of influenza dynamics which can guide mitigation measures. While the role of absolute humidity and temperature is extensively studied, the possibility of ambient ozone (O3) as an environmental driver of influenza has received scant attention. Here, using state-level data in the USA during 2010–2015, we examined such research hypothesis. For rigorous causal inference by evidence triangulation, we applied 3 distinct methods for data analysis: Convergent Cross Mapping from state-space reconstruction theory, Peter-Clark-momentary-conditional-independence plus as graphical modeling algorithms, and regression-based Generalised Linear Model. The negative impact of ambient O3 on influenza activity at 1-week lag is consistently demonstrated by those 3 methods. With O3 commonly known as air pollutant, the novel findings here on the inhibition effect of O3 on influenza activity warrant further investigations to inform environmental management and public health protection.

Ultrasparse Ultrasonic Synthetic Aperture Focus Imaging by Passive Sensing.

Ultrasonic synthetic aperture focus techniques (SAFTs) using less than the total number of available array elements to transmit ("sparse" transmissions) have been recently used in both medical imaging and industrial nondestructive testing (NDT) imaging to increase test speed and simplify multiplexer hardware. The challenge of sparse arrays is to obtain a reasonable image quality given the reduced transmitter-receiver combinations available to the beamforming process. This article proposes a "ultrasparse" SAFT method that employs a minimum number of transmitter elements (from one to four elements only) to obtain an entire full-matrix capture (FMC) set of waveforms. Specifically, a "virtual" FMC is obtained from normalized cross-power spectra between each array element pair in an implementation of "passive" ultrasonic sensing. In order to maintain high image quality without sacrificing imaging speed (e.g., applying a minimal initial time delay and keeping a short time recording window), several key steps have to be taken in this "passive" imaging mode, specifically: 1) the use of carefully designed segment-averaged normalized cross-power spectrum (NCPS) for robust passive reconstruction of the ultrasonic impulse response function (IRF) between two receivers; 2) the use of both the causal and acausal portions of the passively reconstructed IRFs; and 3) the compounding of multiple wave modes in the beamforming process. These steps also ensure the elimination of the near-field blind zone hence potentially enabling near-field imaging. The article first reviews the theory of passive IRF reconstruction between two receivers, comparing time-averaged cross correlation versus segment-averaged NCPS, and then demonstrates the application to ultrasparse SAFT FMC imaging of drilled holes in an aluminum block using a linear transducer array where only one to four elements are used in transmission.

Chaotic characterization and chaotic prediction modelling of HFSWR ionospheric echoes excited by typhoon

ABSTRACT This research explores the intricate-coupling relationship between typhoons and the ionosphere by the high-frequency surface wave radar’s (HFSWR) over-the-horizon capabilities. This letter describes the gravity wave features in travelling ionospheric disturbances (TIDs) and ionospheric drift information. Further discussion is raised on the chaotic properties of gravity wave features using the Lyapunov exponents and chaotic attractors, particularly as they are influenced by typhoon. To predict these gravity wave features more accurately, a new model is developed by synergizing phase space reconstruction theory and statistical learning theory, a chaotic prediction model for gravity wave features constructed on a third-order Volterra filter. The experimental findings confirm that the gravity waves features detected via HFSWR present the hyperchaotic behaviour. More importantly, the innovative gravity wave prediction model based on chaotic attractor can capture the dynamics of the original chaotic system. Notably, the model’s prediction accuracy has been improved by 98.6% after the introduction of phase space reconstruction modelling.

Research progress of femoral bone tunnel positioning in anterior cruciate ligament reconstruction

To review the concept and methods of femoral bone tunnel positioning in anterior cruciate ligament (ACL) reconstruction, in order to provide a reference for clinical treatment. The relevant literature on the concept and methods of femoral bone tunnel positioning in ACL reconstruction in domestic and international research was extensively reviewed. The position of the femoral bone tunnel is a key factor in determining the prognosis of ACL reconstruction. The concept of femoral bone tunnel positioning in ACL reconstruction has experienced isometric reconstruction, anatomical reconstruction, Ribbon-like theory, I.D.E.A.L. theory, and nearly isometric reconstruction theory. The femoral bone tunnel positioning technique is also changing with the in-depth study of the anatomy and biomechanics of the ACL, and each bone tunnel positioning technique has its own advantages and disadvantages. Over-The-Top technique is now mainly used for ACL revision; the clock-face positioning method is basically no longer applicable due to the large error, poor stability, and low retrievability; the bone landmarks positioning method (the lateral condyle of the femur's Resident's ridge and bifurcation ridge, and the the apex of the deep cartilage), which is now mostly used clinically due to the more constant anatomical landmarks. The quadrant method under X-ray fluoroscopy is more cumbersome to implement intraoperatively, so it is mainly used for academic research; computer navigation-assisted positioning has gradually become popular in recent years, which is highly accurate, avoids the influence of human factors on the positioning of the bone tunnel, and has a very good prospect of application; three-dimensional printing-assisted positioning technology, which is accurate in positioning, with a high degree of reproducibility and a short learning curve. The concept of femoral bone tunnel positioning for ACL reconstruction has undergone several evolutions, reflecting the deepening of the understanding of ACL and the improvement of the clinical results of reconstruction. The precision, personalization, and intelligence of positioning techniques are the focus of current and future development.

Starting from Scratch: Experiences from Developing the First Vascular Anastomotic Training Program in North Macedonia Using the Porcine Thigh as a Simulation Model

AbstractMicrosurgical reconstruction constitutes a fundamental part of plastic and reconstructive surgery. It demands high dexterity and intricate technical skills. Its steep learning curve benefits from thorough training throughout residency, where using realistic simulation models in the appropriate sequence of complexity progression is essential in ensuring patient safety prior to progressing to a clinical setting. Commencing training on microvascular-like small diameter vessels could prove unsuitable and ineffective for inexperienced surgeons, however, the larger diameter neurovascular structures in the porcine thigh can provide excellent anastomotic training without compromising the animal tissue training sought after by residents. We present the results from implementing the first vascular anastomotic course in our country, where reconstructive theory was combined with simulated anastomotic training on the porcine thigh. Junior plastic surgery residents described acquiring comprehensive knowledge of reconstructive techniques and could successfully complete anastomoses, despite none to minimal previous experience. Using the porcine thigh should be encouraged as a start-up vascular anastomotic training tool as it provides realistic conditions and tissue handling training, and could improve quality of further training on microvascular structures.

An estimation method for sensor faults based on observer in interconnected systems.

In this research, a class of nonlinear interconnected systems with sensor faults were investigated and an estimation method was proposed for system sensor faults based on the theory of system state reconstruction. Considering sensor fault vectors in nonlinear interconnected systems, this method constructed a generalized nonlinear interconnected system, whose state was designed by augmenting the original system state and fault vectors, which provides a foundation for fault estimation of nonlinear interconnected systems. An augmented observer was developed by equivalent transformation of generalized interconnected system, so as to realize robust estimations of sensor faults in interconnected systems. This estimation method took into account the effect of external disturbance of the system on fault estimation and estimated the convergence speed of error system; the developed method also considered the convenience of solving the gain matrix of the augmented observer, which was beneficial to the realization of sensor fault estimation in interconnected system. The sensor estimation method proposed in the paper has the advantages of robustness in fault estimation,rapidity in error convergence, and convenience in solving the gain matrix. Finally, the state and sensor fault estimation errors of two interconnected systems can both approach 0 within 10 seconds, thus achieving the purpose of fault estimation. Two simulation experiments verified the effectiveness of the proposed fault estimation method and provided a reference for the fault estimation method of nonlinear interconnected systems with disturbance.

Meaning Reconstruction After Suicide Loss

Suicide loss is an example of traumatic loss, as suicide loss survivors face unique challenges in processing the loss. Consequently, in this conceptual paper, meaning reconstruction will be defined as a theoretical paradigm beneficial for clients navigating suicide loss. The aim of this manuscript is to provide a general overview of meaning reconstruction theory and to offer concrete suggestions on implementation of the meaning reconstruction theory as it relates to suicide loss. Further, the authors will utilize a hypothetical case study to illuminate the integration of meaning reconstruction for suicide loss survivors.

An Information Theoretic Condition for Perfect Reconstruction.

A new information theoretic condition is presented for reconstructing a discrete random variable X based on the knowledge of a set of discrete functions of X. The reconstruction condition is derived from Shannon's 1953 lattice theory with two entropic metrics of Shannon and Rajski. Because such a theoretical material is relatively unknown and appears quite dispersed in different references, we first provide a synthetic description (with complete proofs) of its concepts, such as total, common, and complementary information. The definitions and properties of the two entropic metrics are also fully detailed and shown to be compatible with the lattice structure. A new geometric interpretation of such a lattice structure is then investigated, which leads to a necessary (and sometimes sufficient) condition for reconstructing the discrete random variable X given a set {X1,…,Xn} of elements in the lattice generated by X. Intuitively, the components X1,…,Xn of the original source of information X should not be globally "too far away" from X in the entropic distance in order that X is reconstructable. In other words, these components should not overall have too low of a dependence on X; otherwise, reconstruction is impossible. These geometric considerations constitute a starting point for a possible novel "perfect reconstruction theory", which needs to be further investigated and improved along these lines. Finally, this condition is illustrated in five specific examples of perfect reconstruction problems: the reconstruction of a symmetric random variable from the knowledge of its sign and absolute value, the reconstruction of a word from a set of linear combinations, the reconstruction of an integer from its prime signature (fundamental theorem of arithmetic) and from its remainders modulo a set of coprime integers (Chinese remainder theorem), and the reconstruction of the sorting permutation of a list from a minimal set of pairwise comparisons.

Detecting shifts in nonlinear dynamics using Empirical Dynamic Modeling with Nested-Library Analysis.

Abrupt changes in system states and dynamical behaviors are often observed in natural systems; such phenomena, named regime shifts, are explained as transitions between alternative steady states (more generally, attractors). Various methods have been proposed to detect regime shifts from time series data, but a generic detection method with theoretical linkage to underlying dynamics is lacking. Here, we provide a novel method named Nested-Library Analysis (NLA) to retrospectively detect regime shifts using empirical dynamic modeling (EDM) rooted in theory of attractor reconstruction. Specifically, NLA determines the time of regime shift as the cutting point at which sequential reduction of the library set (i.e., the time series data used to reconstruct the attractor for forecasting) optimizes the forecast skill of EDM. We illustrate this method on a chaotic model of which changing parameters present a critical transition. Our analysis shows that NLA detects the change point in the model system and outperforms existing approaches based on statistical characteristics. In addition, NLA empirically detected a real-world regime shift event revealing an abrupt change of Pacific Decadal Oscillation index around the mid-1970s. Importantly, our method can be easily generalized to various systems because NLA is equation-free and requires only a single time series.

A Metaphoric Exploration of Objective Constructivism

The dichotomy between constructive and objective accounts of the epistemic process is a persistent problem. This paper describes the theory of reconstruction in quantum physics that may give a metaphor for the possible compatibility of constructivist and realist accounts. The argument works by analog reasoning and suggests that local subjective and global objective descriptions may converge.

Industrial computed tomography for three-dimensional cultural relic model reconstruction based on L1-αL2+TV norm minimization

Industrial computed tomography (ICT) has emerged as a valuable tool for the conservation of cultural relics since it enables the extraction of information about the internal structure of artifacts without causing any damage. However, sparse and finite angle projection computed tomography (CT) often generates images with a large number of artifacts caused by insufficient data. This paper introduces a new cone-beam CT hybrid model based on compressed sensing (CS) theory and total variance (TV) denoising using the Split Bregman algorithm to address this problem, for the first time using compressed sensing theory for CT reconstruction of cultural relics. The model combines the L1 and L2 norms and optimizes the total variance of the image as the objective function. To enhance the reconstruction of L1-L2, the paper employs the continuation strategy of α and proposes a new combination function to update α. Consequently, the reconstruction results are compared with those of traditional common methods, and the effect of different α update functions is observed on the reconstruction results. The results from the model and real CT images demonstrate that the proposed L1-αL2 + TV method yields superior reconstruction results compared to ART + TV, SART, and L1/L2 algorithms based on objective evaluation indexes such as RMSE, SSIM, and PSNR, the proposed L1-αL2 + TV method achieves SSIM improvement of at least 15.2 %. Moreover, the newly proposed combined function is better at preserving the grain of the image, resulting in a much-improved reconstruction of the contours, making it highly beneficial for subsequent conservation and restoration of heritage. Overall, this proposed L1-αL2 + TV mixture model provides low-noise and high-quality reconstruction results, while maintaining the grain of the original image, making it a great boon for heritage conservation and restoration.

Meaning reconstruction 70 years later: Processing older adults' unfinished business in a drama therapy group.

Unfinished business (UB), when individuals appraise their relationship with others or themselves as incomplete or unresolved, entails difficult emotions such as regret, remorse, and guilt. UB is often associated with bereavement and is considered to be a predictor of complicated grief. Here we report two case studies describing the processing of the sudden death of a significant other in the context of a randomized controlled study of 12-week drama therapy groups for older adults. The intervention followed the format of Playback Theater, an improvised form of theater based on personal stories, and a life review paradigm. A mixed-methods approach explored the course of individual therapy within the group and potential mechanisms of change. The participants completed mental health questionnaires in a pre-post-follow-up design. The qualitative data included video recordings and postintervention interviews. One participant reported a clinically significant (CS) change in depressive symptoms and psychological well-being on the post and follow-up measurement indices. The second reported a CS change in self-esteem and relationship satisfaction at the end of the intervention, but not at follow-up. The findings suggest that the drama therapy contributed to the resolution of UB through restorative work in the three domains defined in meaning reconstruction theory: the "event story" of the loss, the "back story" of the relationship with the deceased, and the "personal story" of self. The results point to the need for additional research on meaning reconstruction in the context of drama therapy and encourage the broader application of performative techniques to treat complicated bereavement. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Towards effective information content assessment: Analytical derivation of information loss in the reconstruction of random fields with model uncertainty

Structures are abundant in both natural and human-made environments and usually studied in the form of images or scattering patterns. To characterize structures a huge variety of descriptors is available spanning from porosity to radial and correlation functions. In addition to morphological structural analysis, such descriptors are necessary for stochastic reconstructions, stationarity and representativity analysis. The most important characteristic of any such descriptor is its information content — or its ability to describe the structure at hand. For example, from crystallography it is well known that experimentally measurable S2 correlation function lacks necessary information content to describe majority of structures. The information content of this function can be assessed using Monte-Carlo methods only for very small 2D images due to computational expenses. Some indirect quantitative approaches for this and other correlation function were also proposed. Yet, to date no methodology to obtain information content for arbitrary 2/3D image is available. In this work, we make a step towards developing a general framework to perform such computations analytically. We show, that one can assess the entropy of a perturbed random field and that stochastic perturbation of fields’ correlation function decreases its information content. In addition to analytical expression, we demonstrate that different regions of correlation function are in different extent informative and sensitive for perturbation. Proposed model bridges the gap between descriptor-based heterogeneous media reconstruction and information theory and opens way for computationally effective way to compute information content of any descriptor as applied to arbitrary structure.

Combining Adaptive Mathematical Morphology and Visual Reconstruction Theory for Animation Creation

Abstract This paper first discusses the use of traditional elements in animation creation and analyzes the linear narrative and artistic expression involved in its creation. Secondly, in order to carry out the image design of animation creation, the color adaptive mathematical morphology is used to carry out the image edge calculation, and the ICP algorithm in the visual reconstruction theory is introduced to carry out the point cloud alignment and fusion. Finally, the effectiveness of this paper’s method is evaluated by comparing algorithms and examples. According to the findings, the loss rate of expansion and corrosion details using the color adaptive mathematical morphology operator is 0.05% and 5.69%, respectively. The overall evaluation of the visual reconstruction presentation is 94.93% at grade C or above. This shows that using the method of this paper can accurately realize the image design of animation creation, enhance the audience’s perception of animation with a clearer view, and then promote the prosperity of the animation industry.