Reconstruction Process Research Articles

The Reconstruction of Bi2Te4O11 Nanorods for Efficient and pH-universal Electrochemical CO2 Reduction.

The electrochemical CO2 reduction reaction (CO2RR) to generate chemical fuels such as formate presents a promising route to a carbon-neutral future. However, its practical application is hindered by the competing CO production and hydrogen evolution reaction (HER), as well as the lack of pH-universal catalysts. Here, Te-modified Bi nanorods (Te-Bi NRs) were synthesized through in situ reconstruction of Bi2Te4O11 NRs under the CO2RR condition. Our study illustrates that the complex reconstruction process of Bi2Te4O11 NRs during CO2RR could be decoupled into three distinct steps, i.e., the destruction of Bi2Te4O11, the formation of Te/Bi phases, and the dissolution of Te. The thus-obtained Te-Bi NRs exhibit remarkably high performance in CO2RR towards formate production, showing high activity, selectivity, and stability across all pH conditions (acidic, neutral, and alkaline). In a flow cell reactor under neutral, alkaline, or acidic conditions, the catalysts achieved HCOOH Faradaic efficiencies of up to 94.3 %, 96.4 %, and 91.0 %, respectively, at a high current density of 300 mA cm-2. Density functional theory calculations, along with operando spectral measurements, reveal that Te manipulates the Bi sites to an electron-deficient state, enhancing the adsorption strength of the *OCHO intermediate, and significantly suppressing the competing HER and CO production. This study highlights the substantial influence of catalyst reconstruction under operational conditions and offers insights into designing highly active and stable electrocatalysts towards CO2RR.

The Reconstruction of Bi2Te4O11 Nanorods for Efficient and pH‐universal Electrochemical CO2 Reduction

AbstractThe electrochemical CO2 reduction reaction (CO2RR) to generate chemical fuels such as formate presents a promising route to a carbon‐neutral future. However, its practical application is hindered by the competing CO production and hydrogen evolution reaction (HER), as well as the lack of pH‐universal catalysts. Here, Te‐modified Bi nanorods (Te−Bi NRs) were synthesized through in situ reconstruction of Bi2Te4O11 NRs under the CO2RR condition. Our study illustrates that the complex reconstruction process of Bi2Te4O11 NRs during CO2RR could be decoupled into three distinct steps, i.e., the destruction of Bi2Te4O11, the formation of Te/Bi phases, and the dissolution of Te. The thus‐obtained Te−Bi NRs exhibit remarkably high performance in CO2RR towards formate production, showing high activity, selectivity, and stability across all pH conditions (acidic, neutral, and alkaline). In a flow cell reactor under neutral, alkaline, or acidic conditions, the catalysts achieved HCOOH Faradaic efficiencies of up to 94.3 %, 96.4 %, and 91.0 %, respectively, at a high current density of 300 mA cm−2. Density functional theory calculations, along with operando spectral measurements, reveal that Te manipulates the Bi sites to an electron‐deficient state, enhancing the adsorption strength of the *OCHO intermediate, and significantly suppressing the competing HER and CO production. This study highlights the substantial influence of catalyst reconstruction under operational conditions and offers insights into designing highly active and stable electrocatalysts towards CO2RR.

Target Fitting Method for Spherical Point Clouds Based on Projection Filtering and K-Means Clustered Voxelization.

Industrial computed tomography (CT) is widely used in the measurement field owing to its advantages such as non-contact and high precision. To obtain accurate size parameters, fitting parameters can be obtained rapidly by processing volume data in the form of point clouds. However, due to factors such as artifacts in the CT reconstruction process, many abnormal interference points exist in the point clouds obtained after segmentation. The classic least squares algorithm is easily affected by these points, resulting in significant deviation of the solution of linear equations from the normal value and poor robustness, while the random sample consensus (RANSAC) approach has insufficient fitting accuracy within a limited timeframe and the number of iterations. To address these shortcomings, we propose a spherical point cloud fitting algorithm based on projection filtering and K-Means clustering (PK-RANSAC), which strategically integrates and enhances these two methods to achieve excellent accuracy and robustness. The proposed method first uses RANSAC for rough parameter estimation, then corrects the deviation of the spherical center coordinates through two-dimensional projection, and finally obtains the spherical center point set by sampling and performing K-Means clustering. The largest cluster is weighted to obtain accurate fitting parameters. We conducted a comparative experiment using a three-dimensional ball-plate standard. The sphere center fitting deviation of PK-RANSAC was 1.91 μm, which is significantly better than RANSAC's value of 25.41 μm. The experimental results demonstrate that PK-RANSAC has higher accuracy and stronger robustness for fitting geometric parameters.

Arsitektur Sistem Informasi Rehabilitasi dan Rekonstruksi Rumah Terkena Dampak Gempa Menggunakan Framework Togaf

The study focuses on the impact of the 2018 earthquake in the Province of West Nusa Tenggara, particularly the extensive damage to hundreds of thousands of houses. It aims to assess the initial phase of post-earthquake housing rehabilitation and reconstruction activities and seeks to enhance their efficiency and effectiveness. One of the main issues identified is the absence of an integrated information system to facilitate data management and coordination among relevant agencies, often leading to errors and delays in implementing activities. To address this, the research utilizes the TOGAF ADM Framework as an architectural design method, providing detailed guidelines for creating a flexible and adaptable information system architecture. Data is collected through in-terviews, document studies, and literature reviews. The research delves into the vision and mis-sion, regulations, and guidelines pertaining to the rehabilitation and reconstruction process, as well as an analysis of the current business processes and assets owned by the BPBD of the Province of West Nusa Tenggara. The expected outcome is the development of an information system ar-chitecture that can overcome obstacles in rehabilitation and reconstruction activities, resulting in a more effective and efficient process. Moreover, it aims to enhance coordination and resource uti-lization. Ultimately, the study concludes that implementing a TOGAF ADM-based information system architecture can offer a comprehensive solution to the challenges encountered in post-earthquake housing rehabilitation and reconstruction. This resulting integrated and opti-mized system is expected to serve as a valuable reference for relevant agencies in other provinces facing similar situations in the future.

Surface Reconstruction Regulation of Co3N Through Heterostructure Engineering Toward Efficient Oxygen Evolution Reaction.

Oxygen evolution reaction (OER) electrocatalysts generally experience structural and electronic modifications during electrocatalysis. This phenomenon, referred to as surface reconstruction, results in the formation of catalytically active species that act as real OER sites. Controlling surface reconstruction therefore is vital for enhancing the OER performance of electrocatalysts. In this study, a new approach is introduced of heterostructure engineering to facilitate the surface reconstruction of target catalysts. Using MnCo carbonate hydroxide (MnCo─CH)@Co3N as a demonstration, it is discovered that the surface reconstruction occurs more readily and rapidly on MnCo─CH@Co3N than on Co3N. More interestingly, during the reconstruction process, Mn species migrate to the surface, enabling the in situ formation of highly active Mn-doped CoOOH. Consequently, the MnCo─CH@Co3N catalyst after reconstruction exhibits a low overpotential of 257mV at 10mAcm-2, compared to 379mV of individual Co3N. This work offers fresh perspectives on understanding the enhanced OER performance of heterostructure electrocatalysts and the role of heterostructure in promoting surface reconstruction.

Identifying the dynamic behaviors in complete reconstruction of Co-based complex precatalysts during electrocatalytic oxygen evolution

Transition metal-based nanomaterials have emerged as promising electrocatalysts for oxygen evolution reaction (OER). Considerable research efforts have shown that self-reconstruction occurs on these nanomaterials under operating conditions of OER process. However, most of them undergo incomplete reconstruction with limited thickness of reconstruction layer, leading to low component utilization and arduous exploration of real catalytic mechanism. Herein, we identify the dynamic behaviors in complete reconstruction of Co-based complexes during OER. The hollow phytic acid (PA) cross-linked CoFe-based complex nanoboxes with porous nanowalls are designed because of their good electrolyte penetration and mass transport ability, in favor of the fast and complete reconstruction. A series of experiment characterizations demonstrate that the reconstruction process includes the fast substitution of PA by OH− to form Co(Fe)(OH)x and subsequent potential-driven oxidation to Co(Fe)OOH. The obtained CoFeOOH delivers a low overpotential of 290 mV at a current density of 10 mA cm−2 and a long-term stability. The experiment results together with theory calculations reveal that the Fe incorporation can result in the electron rearrangement of reconstructed CoFeOOH and optimization of their electronic structure, accounting for the enhanced OER activity. The work provides new insights into complete reconstruction of metal-based complexes during OER and offers guidelines for rational design of high-performance electrocatalysts.

The Keystone Flap: A Game Changer That Promises New Horizons in Reconstructive Surgery.

Since its first description emerged in 2003, the keystone flap has garnered the attention of the international scientific community due to its high safety profile and the suitably low complication rate associated with the reconstructive process. In this study, data were obtained from the performance of 72 keystone flaps to cover soft-tissue defects after the excision of neoplastic processes, excisions, and injuries occurring in polytrauma. The study was conducted in the Department of Plastic Surgery, "Bagdasar-Arseni" Emergency Hospital, Bucharest, and two plastic surgeons in the department performed the surgical procedures. The statistical analysis revealed a remarkably low complication rate (3.22%), excellent functional and esthetic results, and a short hospitalization time. No intraoperative complications were identified during this study. The degree of satisfaction obtained after reconstructive surgery was exceptionally high, with a score of 9.47 on a 10-point rating scale (0 = poor results, 10 = excellent results) from the patient's perspective and 9.51 out of 10 for the surgical team. The keystone flap is the optimal solution for reconstructing soft-tissue defects of variable sizes and shapes. It is associated with a low length of hospitalization, a low complication rate, and high patient satisfaction.

Ligand-tuning of coordination compound for improved oxygen evolution

Controllable regulation of the reconstruction process for the pre-catalysts towards oxygen evolution remains as a great challenge. In this study, we report a bi-ligand strategy to facilitate the structural transformation of coordination compounds to metal oxyhydroxides during oxygen evolution with enhanced activity. A coordination compound consisting of 1,1′-ferrocene acid (Fc) and Ni2+ was synthesized, in which terephthalic acid was introduced. The second ligand of terephthalic acid facilitates the reconstruction process, inducing an enhanced catalytic activity. In 1 mol·L−1 KOH aqueous solution, the optimized catalyst can drive a current density of 10 mA·cm–2 under a lower overpotential of 220 mV. Using this catalyst, zinc-air batteries can be prepared. The obtained zinc-air battery presents a large specific capacity of 718 mA·h·g−1 with excellent cycling stability for over 100 h far exceeding that of Pt/C+RuO2 battery fabricated with commercial catalysts. The excellent performance and low cost of this catalyst will open up broad prospects for the development of advanced systems for water electrolysis and zinc air batteries.

Recent advances and applications of artificial intelligence in 3D bioprinting.

3D bioprinting techniques enable the precise deposition of living cells, biomaterials, and biomolecules, emerging as a promising approach for engineering functional tissues and organs. Meanwhile, recent advances in 3D bioprinting enable researchers to build in vitro models with finely controlled and complex micro-architecture for drug screening and disease modeling. Recently, artificial intelligence (AI) has been applied to different stages of 3D bioprinting, including medical image reconstruction, bioink selection, and printing process, with both classical AI and machine learning approaches. The ability of AI to handle complex datasets, make complex computations, learn from past experiences, and optimize processes dynamically makes it an invaluable tool in advancing 3D bioprinting. The review highlights the current integration of AI in 3D bioprinting and discusses future approaches to harness the synergistic capabilities of 3D bioprinting and AI for developing personalized tissues and organs.

Possibilities to evaluate the vehicle pre-collision travel velocity in the case of a frontal impact with a fixed object, through numerical modelling

Abstract The present paper evaluates, from a physical-mathematical perspective, the pre-collision travel speed of a vehicle, in the case of a frontal impact with a rigid, fixed pole-type obstacle. The evaluation considers both energy methods and deformation coefficients, taking into account the parameters resulting from the primary investigation of the accident site. The reconstruction of such road accidents aims to determine the kinematic parameters that influence the behavior of the involved vehicle, and to allow the analysis of avoidance possibilities of such events. The developed working algorithm can be applied to solve a large number of road accident cases by changing the input data and to obtain the necessary kinematic and dynamic parameters for the accident reconstruction process. Thus, it is possible to establish the dynamics of such road traffic events, which facilitates the assessment and comparison of different conditions under study. The validation of the fore-mentioned reconstruction algorithm is performed by comparing the results obtained through numerical modelling with those determined experimentally. The relative error between the two is, as well, assessed.

Reconstructive evolutionary morphology: Tracing the historical process of modifications of complex systems driven by natural selection through changing ecological conditions.

There is general consensus among evolutionary biologists that natural selection drives phenotypic modifications within populations over generational time. How to reconstruct this historical process, however, has been discussed mostly in theoretical terms, and recommendations and explanations on how to translate such theoretical insights into practice are needed. The present study aims at providing a theory-supported practical guide on how to reconstruct historical evolutionary processes by applying a morphology-centered approach through a series of interdependent steps of descriptive morphology, functional analysis, ecological observation, integration of paleoecological data, and evolutionary synthesis. Special attention is given to the development of tests regarding the accuracy, closeness to reality, and plausibility of the hypotheses at every level of the reconstructive process. This morphology-centered approach had its beginnings in the wake of the evolutionary synthesis and is part of the scientifically necessary process of reciprocal testing of hypotheses generated by different methods and data for the reconstruction of evolutionary history.

Epistemologies from the North of Brazil: the counterhegemony of Epistemologies from the Southeast

The North and the global South are separated not only by the Equator, but also by an abyssal thinking, as emphasized by the author Portuguese Boaventura de Sousa Santos, which presents the Modern Western Thought as responsible for making invisible, non existent, the knowledge produced and practiced by humans in the global South, while the North is global hegemonic in its being, being and doing in the world. However, the South epistemologies exist and can help you understand how to practice co-presence, until now denied by abyssal thinking that makes the hegemonic global North. So, open up possibilities for exploring parallel understanding epistemologies North of Brazil, located in the global South, since the existence of abyssal thinking global instigates us to also discuss the hypothesis of a thought abysmal environmental Brazil, definer a line; 'this side of the line' is the Southeast and 'across the line' is the North of Brazil, in which context the North represents all other regions, except the Southeast. Epistemologies of southeastern Brazil are assumed hegemonic, but need to be deconstructed to the revelations engendered research on the epistemologies of the North Country, thereby reconstruct a Brazilian thought, where North, South, Southeast, Northeast and Midwest recognize physical geography and politics of Brazil, without forgetting that the human being in any geographical locations and under different political contexts are diverse, complex, and this has to be knowledge and expertise, and must take up counter-hegemonic, while there is no hegemony . The beginning of the reconstruction process is understanding how the sociology of absences makes this all that was made invisible by the logic and methods of production of non existence and presents the ecology of knowledge as an antidote to the production of absences, because that will represent the ecology superstructure built this new thinking replacement of abyssal thinking of Southeastern Brazil hegemonic. The purpose of this article, therefore, is to explore the possibilities of epistemologies of Northern Brazil for the construction of Brazilian thought.

Deep unfolding network with spatial alignment for multi-modal MRI reconstruction

Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic information, but some modalities are limited by the long scanning time. To accelerate the whole acquisition process, MRI reconstruction of one modality from highly under-sampled k-space data with another fully-sampled reference modality is an efficient solution. However, the misalignment between modalities, which is common in clinic practice, can negatively affect reconstruction quality. Existing deep learning-based methods that account for inter-modality misalignment perform better, but still share two main common limitations: (1) The spatial alignment task is not adaptively integrated with the reconstruction process, resulting in insufficient complementarity between the two tasks; (2) the entire framework has weak interpretability. In this paper, we construct a novel Deep Unfolding Network with Spatial Alignment, termed DUN-SA, to appropriately embed the spatial alignment task into the reconstruction process. Concretely, we derive a novel joint alignment-reconstruction model with a specially designed aligned cross-modal prior term. By relaxing the model into cross-modal spatial alignment and multi-modal reconstruction tasks, we propose an effective algorithm to solve this model alternatively. Then, we unfold the iterative stages of the proposed algorithm and design corresponding network modules to build DUN-SA with interpretability. Through end-to-end training, we effectively compensate for spatial misalignment using only reconstruction loss, and utilize the progressively aligned reference modality to provide inter-modality prior to improve the reconstruction of the target modality. Comprehensive experiments on four real datasets demonstrate that our method exhibits superior reconstruction performance compared to state-of-the-art methods.

어린이집 교사의 일과운영 재구성 과정 탐구 - 민간어린이집 1개소를 중심으로

This study explored the process of reconstructing to healthy and orderly routine for both infants and toddlers and teachers based on the routine management that teachers experience in daycare center. To this end, we conducted action research with five teachers at a daycare center from April to May 2024, conducting four group interviews at one-week intervals and conducting non-participant observation four times for each teacher. The collected data are transcription data, observation journals and other data and the results were derived after analyzing according to the inductive analysis procedure of Lee Dong Sung and Kim Young Chun(2014). The process of reconstruction of teachers' routine management was in the following order: perceive reality, attempt to change, and waking up. Teachers recognize the problems and need for change in routine management and daily life habits guidance strategies, and daily life habits guidance strategies and role division among teachers and so on were changed, and routine managements were reorganized. In the process, teachers realized the need for method of guidance for the voluntary participation of infants and toddlers and the formation of order in their lives and need for effective cooperation between teachers. In addition, teachers became able to raise a problem themselves and make a plan to reconstruction their routine management. Based on the results of the study, improve to the process-oriented daycare center evaluation system, strengthening teacher education on daily life habits guidance and transition time management, plan and evaluation of daily life operations for autonomous participation of infants and toddlers, daycare center' management system change for systematic cooperation among teachers were suggested.

Single-stage management of Charcot neuroarthropathy and osteomyelitis in diabetic patients

Objective: Describe our experience treating Charcot neuroarthropathy (CN) coexisting with concurrent bone infection in a single step, treated with external fixation, and report the mid-term radiographic and functional outcomes. Methods: Retrospective case series of patients diagnosed with CN and osteomyelitis treated with a single-step approach consisting of necrotic bone debridement and fusion extended over the affected joints using a circular external fixator with a minimum of 18 months of follow-up. Results: Six patients were evaluated, and three patients achieved excellent results and were able to walk outside their homes. One of them required a below-the-knee amputation due to persistent infection. Two patients had good results according to the Pinzur proposed evaluation scheme. All patients agreed that they would choose the reconstruction process for their deformity over an infrapatellar amputation. Conclusion: We believe the results from our case series apply to the previously published literature on this therapeutic modality. Level of evidence IV; Case series.

A LiDAR-driven three-dimensional simulation model for far-red solar-induced chlorophyll fluorescence in forests

Solar-induced chlorophyll fluorescence (SIF) is a subtle but informative probe of plant photosynthesis. Quantifying the three-dimensional (3D) distribution of SIF benefits a better understanding of photosynthesis variations over heterogeneous canopies. Although radiative transfer models (RTMs) provide a solid theoretical basis for simulating the 3D SIF distribution, most RTMs use virtual scenes with complex reconstruction processes. This study aims to develop a 3D SIF simulation model (FluorLiDAR) directly driven by terrestrial light detection and ranging (LiDAR) data using leaf and canopy RTMs, including a 3D PAR (photosynthetically active radiation) simulation model, the Fluspect model, the atmosphere radiative transfer module in SCOPE, and the multiple scattering coefficients of sunlit and shaded leaves from the 4-scale model. The results show that (1) the simulated and measured SIF patterns were consistent, with R2 (RMSE) values of 0.73 (0.17 mW/nm/m2/sr) and 0.76 (0.12 mW/nm/m2/sr) for 1-min sampling and 10-min averages, respectively. Moreover, the R2 between FluorLiDAR and the DART simulation reached 0.94. The R2 of FluorLiDAR and DART were both higher than 1D mSCOPE using every 10-min sampling data. (2) Point density, denoted by average NPD (nearest point distance), influenced the performance of our model mainly when it was smaller than 0.1 m. Chlorophyll content had less influence on the model accuracy (R2 and rRMSE), and the bias between simulation and measurement decreased as chlorophyll content increased. (3) The simulated 3D SIF distribution pattern closely resembled PAR within the canopy. Besides, FluorLiDAR can simulate the hot spot effect like DART and mSCOPE though the effect was not as obvious as the other two models. This study highlights the potential of a LiDAR-driven SIF model for 3D SIF simulation over a heterogeneous canopy, which may benefit the understanding of the structural impacts on forest photosynthesis in real forest scenes.

The effects of multielement basicity on niobium-bearing phase reconstruction in low grade niobium rougher concentrate

The beneficiation and recovery of ores with complex nature, low abundance have become the main direction for the development of niobium resources. The niobium resources with large reserves in Bayan Obo have not been effectively developed due to their fine particles, low grade, and complex nature. A new method for the phase reconstruction of minerals through a reconstruction process was proposed. The reconstruction of Bayan Obo niobium-bearing rougher concentrate was realized by a high-temperature melting-cooling crystallization process. The impacts of multielement basicity on the reconstruction of niobium-bearing minerals were investigated by adjusting the composition of the slag in this study. The loparite ((Ca,Ce,Na)(Nb,Ti)O3) phase is formed in slag with a higher basicity. On the contrary, the calciobetafite (Ca2(Nb,Ti)2O7) is generated in slag with a lower basicity. Besides, the combined mass fractions of valuable TiO2, Nb2O5, and rare earth oxide (REO) in calciobetafite reaches 71.94% (only 56.83% in loparite). The formation mechanism of niobium-bearing phases under different basicities was also discussed. The results of this study can provide theoretical guidance for transforming the niobium-bearing phase and enriching valuable elements in the process of phase reconstruction.

Accelerated structural transformation of metal-organic frameworks via interfacial engineering for efficient oxygen evolution reaction

Most metal-organic frameworks (MOFs) undergo structural transformations during the oxygen evolution reaction (OER), prompting the development of more catalytically active metal oxyhydroxides. However, one of the biggest challenges still is managing the MOF reconstruction process. Here, we present an interface engineering strategy to encourage MOFs to structurally change into metal oxyhydroxides, which are more active in the OER process. By meticulous design, the NiSe/CoFc′ (CoFc-MOF, Fc′ = 1,1′-ferrocenecarboxylic acid) heterojunction was successfully constructed, exhibiting remarkable interface coupling effects. This characteristic not only facilitates efficient electron transfer from CoFc′ to NiSe, and accelerates the structural transformation process of CoFc′, but also activates more catalytic active sites. Compared to pure CoFc′, NiSe/CoFc′ exhibits enhanced structural transformation capability, occurring in a shorter time and at a lower voltage, with more catalytic sites being activated. Furthermore, the transformed NiSe/CoFc′ displays suprior catalytic activity with an overpotential of 227 mV at a current density of 100 mA cm−2, surpassing the single-component CoFc′. And the Faradaic efficiency of NiSe/CoFc′ is near to 99.6%. This approach offers a noval avenue for the levelheaded plan of non-precious metal electrocatalysts for water electrolysis, enabling the control of structural conversion through interface engineering.

A modified capacitance tomography image reconstruction approach based on iterative shrinkage-thresholding algorithm combined with deep networks

Abstract Due to the ‘soft-field’ effect and the challenges posed by ill-posed and ill-conditioned inverse problems, it is difficult to obtain high quality images from an electrical capacitance tomography (ECT) system. To achieve both high-quality images and fast imaging speed with limited measurement data, an image reconstruction algorithm, which was initially proposed for compressive sensing, is adapted for ECT image reconstruction to optimize the ill-posed nature of its inverse problem. The proposed algorithm leverages deep learning networks inspired by the iterative shrinkage-thresholding algorithm (ISTA), thereby creating a model that is both mathematically interpretable and endowed with trainable parameters. Building upon this foundation, the conventional Landweber iteration is integrated with the ISTA-Net to refine the optimization process for ECT image reconstruction. In order to propose an effective model adapting to the actual multiphase flow characteristics and complex flow pattern changes, the training and test process is driven by a comprehensive dataset generated from dynamic simulations, rather than artificial samples of multiphase distributions. This numerical methodology simulates the dynamic measurement process of a virtual ECT sensor by coupling the gas–liquid two-phase flow field and the ECT electrostatic field. The results of the testing phase indicate that the proposed algorithm outperforms traditional ECT image reconstruction methods. Compared with the linear back projection algorithm, the average image error and gas fraction error have been reduced by 20.44% and 16.74%, respectively, while maintaining a computational speed comparable to that of the Landweber iteration. The accuracy of the new algorithm in reconstructing the two-phase interface and estimating the gas fraction has been validated by static experimental tests, showing its potential for practical application in online gas–liquid two-phase flow measurement scenarios.

Anisotropic sparse transformation for spectral CT image reconstruction

AbstractPhoton‐counting detector‐based computed tomography (PCD‐CT) is an advanced realization of spectral CT, the multi‐energy projection data is captured from the same object, hence, CT images can provide additional spectral resolution, making it possible to perform material decomposition. However, multiple projections may have a low signal‐to‐noise ratio (SNR), such that CT images suffer from noise. To handle this problem, a spectral CT image reconstruction method based on anisotropic sparse transformation (AST) is proposed. To increase the quality of reconstruction, AST through an anisotropic guided filter (AGF) and quasi norm is proposed. Then, as a new regularization, AST is introduced into an iterative reconstruction process, generating an AST‐based method. Moreover, to utilize the correlation among projection data, the average image serves as the guidance image of AGF, it varies with the iterative index, resulting in a technique of dynamic average image (DAI). The AST‐based model involves quasi norm minimization, hence an effective strategy is employed to solve the corresponding problem. A series of experiments were performed. The experiment showed that, compared to other listed methods, the result of the AST‐based method can achieve better visualization and higher quantitative indexes, hence it has application potential in the medical imaging field.