Rapid Reconstruction Research Articles

Terahertz nondestructive layer thickness measurement and delamination characterization of GFRP laminates

Three-dimensional nondestructive location of defects, such as delaminations, in glass fiber-reinforced polymer (GFRP) laminates remains a challenge. Terahertz techniques have shown promise, but their success relies on advanced signal-processing techniques applied to the raw data. The current work presents an advance in the quantitative three-dimensional nondestructive location of delaminations in GFRP laminates. Namely, terahertz time-of-flight tomography, together with adaptive sparse deconvolution based on a two-step iterative shrinkage-thresholding algorithm, as well as the Canny edge-detection operator, are employed in nondestructive measurement of layer thicknesses and to extract the edges of delaminations in GFRP laminates. Compared with the commonly used frequency wavelet-domain deconvolution method or previous implementations of sparse deconvolution, the adaptive sparse deconvolution approach provides a clearer and rapid stratigraphic reconstruction of GFRP laminates while yielding accurate thickness information for each resin layer and low sensitivity to noise. In addition, the proposed edge-detection algorithm presents better performance in estimating the transverse size of delaminations, compared to the common −6 dB drop approach. Finally, our experiments verify the effectiveness of the proposed signal and image processing approaches for three-dimensional localization of delamination defects in GFRP laminates and the quantitative characterization of layer thickness.

Paired conditional generative adversarial network for highly accelerated liver 4D MRI

Purpose. 4D MRI with high spatiotemporal resolution is desired for image-guided liver radiotherapy. Acquiring densely sampling k-space data is time-consuming. Accelerated acquisition with sparse samples is desirable but often causes degraded image quality or long reconstruction time. We propose the Reconstruct Paired Conditional Generative Adversarial Network (Re-Con-GAN) to shorten the 4D MRI reconstruction time while maintaining the reconstruction quality. Methods. Patients who underwent free-breathing liver 4D MRI were included in the study. Fully- and retrospectively under-sampled data at 3, 6 and 10 times (3×, 6× and 10×) were first reconstructed using the nuFFT algorithm. Re-Con-GAN then trained input and output in pairs. Three types of networks, ResNet9, UNet and reconstruction swin transformer (RST), were explored as generators. PatchGAN was selected as the discriminator. Re-Con-GAN processed the data (3D + t) as temporal slices (2D + t). A total of 48 patients with 12 332 temporal slices were split into training (37 patients with 10 721 slices) and test (11 patients with 1611 slices). Compressed sensing (CS) reconstruction with spatiotemporal sparsity constraint was used as a benchmark. Reconstructed image quality was further evaluated with a liver gross tumor volume (GTV) localization task using Mask-RCNN trained from a separate 3D static liver MRI dataset (70 patients; 103 GTV contours). Results. Re-Con-GAN consistently achieved comparable/better PSNR, SSIM, and RMSE scores compared to CS/UNet models. The inference time of Re-Con-GAN, UNet and CS are 0.15, 0.16, and 120 s. The GTV detection task showed that Re-Con-GAN and CS, compared to UNet, better improved the dice score (3× Re-Con-GAN 80.98%; 3× CS 80.74%; 3× UNet 79.88%) of unprocessed under-sampled images (3× 69.61%). Conclusion. A generative network with adversarial training is proposed with promising and efficient reconstruction results demonstrated on an in-house dataset. The rapid and qualitative reconstruction of 4D liver MR has the potential to facilitate online adaptive MR-guided radiotherapy for liver cancer.

Lattice strain induced rapid structural reconstruction of NiCo hydroxide for efficient water oxidation

In the realm of catalysis, the efficiency of nickel-cobalt (NiCo) based catalysts is hampered by the sluggish kinetics of electrochemical reconstruction. The research herein proposes an innovative strategy centered on the induction of lattice strain to surmount this challenge. We successfully engineer lattice strain and distortion within nickel-cobalt hydroxide by the strategic incorporation of iridium. The X-ray absorption spectroscopy, charge density of elements simulation, ultraviolet photoelectron spectra combined with in-situ Raman results demonstrate that the electronic coupling between iridium and nickel-cobalt is enhanced by lattice strain, which narrows the band gap, and then boosts the electrochemical reconstruction of NiCo hydroxide. Furthermore, the in-situ EIS, methanol oxidation reaction, and DFT calculations collectively indicate that lattice strain can expedite the kinetic adsorption and desorption of intermediates during the OER process. The reconstructed voltage and overpotential are reduced by 50 mV and 77 mV after introducing lattice distortion, and a high stability for more than 500 h, respectively. This unique insight into lattice strain modification provides a way to optimize catalytic functions.

Improving the performance of speckle correlation imaging by using a speckle refinement method with self-calibrated homomorphic filtering

Scattering imaging based on speckle correlation is an attractive topic as it enables the rapid reconstruction of the object image through computational methods in a compact setup. However, this method typically relies on high-contrast speckle images obtained under narrowband light illumination in a darkroom environment, limiting its application scenarios. Here, we demonstrate a self-calibrated homomorphic filtering (SCHF) method that significantly enhances speckle contrast by modifying the distribution of components within the speckle image, thereby improving imaging performance. The experimental results reveal that our method leverages the physical mechanism of speckle correlation to obtain the optimal filtering solution under the guidance of a self-calibrated strategy. The integration of this method with current mainstream speckle correlation techniques showcases its scalability. Even in scenarios under ambient light interference or broadband light illumination, the SCHF is effective in improving imaging performance, demonstrating its practical application potential.

Automated geometric reconstruction and cable force inference for cable-net structures using 3D point clouds

Laser scanning provides an efficient solution to digital twin construction in civil engineering. The complexity and redundancy of large-scale point clouds substantially prolong the labor-intensive model reconstruction process. This paper presents an automated and high-precision geometric reconstruction approach for cable-net structures with a complete workflow from raw points to the extraction of cable shapes and forces. The strategy involves the extraction of coordinates of key cable regions through the characterization of cable geometry and local registration methods, followed by the computation of cable forces and shapes using segmented catenary theory and nonlinear optimization. The approach is validated with a single-curvature cable-net structure, with the accuracy of cable shapes within ±5 mm and errors in cable forces <5%. The method contributes to health monitoring and rapid reconstruction of cable-net structures. The precise geometry and forces will facilitate the creation of the mechanical models reflecting the physical authenticity of structures.

A Method for Full-Depth Sound Speed Profile Reconstruction Based on Average Sound Speed Extrapolation

The speed of sound in seawater plays a crucial role in determining the accuracy of multibeam bathymetric measurements. In deep-sea multibeam measurements, the challenge of inadequate longitudinal coverage of sound speed profiles arises from variations in seafloor topography, meteorological conditions, measurement equipment, and operational efficiency, resulting in diminished measurement precision. Building upon the EOF (Empirical Orthogonal Function), a method employed to analyze spatiotemporal data such as sound speeds, this paper addresses the limitations of the EOF method caused by the shallowest sampling depth of the sound speed profile samples. It proposes two methods for EOF reconstruction of measured sound speed profiles extended to full water depth by splicing measured sound speed profiles at non-full water depths with historical average sound speed profiles of the surveyed sea area. Specially, Method 2 introduces the latest metaheuristic optimization algorithm, CPO (Crested Porcupine Optimizer), which exhibited superior performance on multiple standard test functions in 2024. The study reconstructs randomly sampled measured sound speed profiles using the two proposed methods and commonly employed substitution and splicing methods, followed by a comparative analysis of the experimental outcomes. At a sampling depth of 200 m, Method 2 demonstrates performance superior to other methods, with RMSE, MAE, MAPE, and R2 values of 0.9511 m/s, 0.8492 m/s, 0.0566%, and 0.9963, respectively. Method 1 yields corresponding values of 0.9594 m/s, 0.8492 m/s, 0.0568%, and 0.9962, respectively. Despite its slightly inferior performance compared with Method 2, it offers substantial advantages over the substitution and splicing methods. Varying the sampling depth of measured sound speed profiles reveals that Methods 1 and 2 exhibit inferior reconstruction performance in shallow water compared with the substitution and splicing methods. Nevertheless, when the sampling depth surpasses the depth range of initial spatial modes with abrupt variations, both methods achieve notably higher reconstruction accuracy compared with the substitution and splicing methods, reaching a stabilized state. Sound ray tracing reveals that the reconstructed sound speed profiles from both methods meet the stringent accuracy standards for bathymetric measurements, achieving an effective beam ratio of 100%. The proposed methods not only provide rapid reconstruction of sound speed profiles, thereby improving the efficiency of multibeam bathymetric surveys, but also provide references for the reasonable determination of sampling depths of sound speed profiles to ensure reconstruction accuracy, demonstrating practical application value.

Rapid Surface Reconstruction of In2S3 Photoanode via Flame Treatment for Enhanced Photoelectrochemical Performance.

Surface reconstruction, reorganizing the surface atoms or structure, is a promising strategy to manipulate materials' electrical, electrochemical, and surface catalytic properties. Herein, a rapid surface reconstruction of indium sulfide (In2S3) is demonstrated via a high-temperature flame treatment to improve its charge collection properties. The flame process selectively transforms the In2S3 surface into a diffusionless In2O3 layer with high crystallinity. Additionally, it controllably generates bulk sulfur vacancies within a few seconds, leading to surface-reconstructed In2S3 (sr-In2S3). When using those sr-In2S3 as photoanode for photoelectrochemical water splitting devices, these dual functions of surface In2O3/bulk In2S3 reduce the charge recombination in the surface and bulk region, thus improving photocurrent density and stability. With optimized surface reconstruction, the sr-In2S3 photoanode demonstrates a significant photocurrent density of 8.5mA cm-2 at 1.23V versus a reversible hydrogen electrode (RHE), marking a 2.5-fold increase compared to pristine In2S3 (3.5mA cm-2). More importantly, the sr-In2S3 photoanode exhibits an impressive photocurrent density of 7.3mA cm-2 at 0.6V versus RHE for iodide oxidation reaction. A practical and scalable surface reconstruction is also showcased via flame treatment. This work provides new insights for surface reconstruction engineering in sulfide-based semiconductors, making a breakthrough in developing efficient solar-fuel energy devices.

A novel method for rapid estimation of active bone marrow dose for radiotherapy patients in epidemiological studies.

In a dedicated effort to improve the assessment of clonal hematopoiesis (CH) and study leukemia risk following radiotherapy, we are developing a large-scale cohort study among cancer patients who received radiation. To that end, it will be critical to analyze dosimetric parameters of red bone marrow (ABM) exposure in relation to CH and its progression to myeloid neoplasms, requiring reconstruction method for ABM doses of a large-scale patients rapidly and accurately. To support a large-scale cohort study on the assessment of clonal hematopoiesis and leukemia risk following radiotherapy, we present a new method for the rapid reconstruction of ABM doses of radiotherapy among cancer patients. The key idea of the presented method is to segment patient bones rapidly and automatically by matching a whole-body computational human phantom, in which the skeletal system is divided into 34 bone sites, to patient CT images via 3D skeletal registration. The automatic approach was used to segment site-specific bones for 40 radiotherapy patients. Also, we segmented the bones manually. The bones segmented both manually and automatically were then combined with the patient dose matrix calculated by the treatment planning system (TPS) to derive patient ABM dose. We evaluated the performance of the automatic method in geometric and dosimetric accuracy by comparison with the manual approach. The pelvis showed the best geometric performance [volume overlap fraction (VOF): 52% (mean) with 23% (σ) and average distance (AD): 0.8cm (mean) with 0.5cm (σ)]. The pelvis also showed the best dosimetry performance [absorbed dose difference (ADD): 0.7Gy (mean) with 1.0Gy (σ)]. Some bones showed unsatisfactory performances such as the cervical vertebrae [ADD: 5.2Gy (mean) with 10.8Gy (σ)]. This impact on the total ABM dose, however, was not significant. An excellent agreement for the total ABM dose was indeed observed [ADD: 0.4Gy (mean) with 0.4Gy (σ)]. The computation time required for dose calculation using our method was robust (about one minute per patient). We confirmed that our method estimates ABM doses across treatment sites accurately, while providing high computational efficiency. The method will be used to reconstruct patient-specific ABM doses for dose-response assessment in a large cohort study. The method can also be applied to prospective dose calculation within a clinical TPS to support clinical decision making at the point of care.

MDs-NP: a property prediction model construction procedure for naphtha based on molecular dynamics simulation

In the context of carbon neutrality and carbon peaking, molecular management has become a focus of the petrochemical industry. The key to achieving molecular management is molecular reconstruction, which relies on rapid and accurate calculation of oil properties. Focusing on naphtha, we proposed a novel property prediction model construction procedure (MDs-NP) employing molecular dynamics simulations for property collections and gamma distribution from real analytical data for calculating mole fractions of simulation mixtures. We calculated 348 sets of mixture properties data in the range of 273 K–300 K by molecular dynamics simulations. Molecular feature extraction was based on molecular descriptors. In addition to descriptors based on open-source toolkits (RDKit and Mordred), we designed 12 naphtha knowledge (NK) descriptors with a focus on naphtha. Three machine learning algorithms (support vector regression, extreme gradient boosting and artificial neural network) were applied and compared to establish models for the prediction of the density and viscosity of naphtha. Mordred and NK descriptors + support vector regression algorithm achieved the best performance for density. The selected RDKFp and NK descriptors + artificial neural network algorithm achieved the best performance for viscosity. Using ablation studies, T, P_w and CC(C)C are three effective descriptors in NK that can improve the performance of the property prediction models. MDs-NP has the potential to be extended to more properties as well as more-complex petroleum systems. The models from MDs-NP can be used for rapid molecular reconstruction to facilitate construction of data-driven models and intelligent transformation of petrochemical processes.

Electron Manipulation and Surface Reconstruction of Bimetallic Iron-Nickel Phosphide Nanotubes for Enhanced Alkaline Water Electrolysis.

Developing high-efficiency and stable bifunctional electrocatalysts for water splitting remains a great challenge. Herein, NiMoO4 nanowires as sacrificial templates to synthesize Mo-doped NiFe Prussian blue analogs are employed, which can be easily phosphorized to Mo-doped Fe2xNi2(1-x)P nanotubes (Mo-FeNiP NTs). This synthesis method enables the controlled etching of NiMoO4 nanowires that results in a unique hollow nanotube architecture. As a bifunctional catalyst, the Mo-FeNiP NTs present lower overpotential and Tafel slope of 151.3 (232.6) mV at 100 mA cm-2 and 76.2 (64.7) mV dec-1 for HER (OER), respectively. Additionally, it only requires an ultralow cell voltage of 1.47 V to achieve 10 mA cm-2 for overall water splitting and can steadily operate for 200 h at 100 mA cm-2. First-principles calculations demonstrate that Mo doping can effectively adjust the electron redistribution of the Ni hollow sites to optimize the hydrogen adsorption-free energy for HER. Besides, in situ Raman characterization reveals the dissolving of doped Mo can promote a rapid surface reconstruction on Mo-FeNiP NTs to dynamically stable (Fe)Ni-oxyhydroxide layers, serving as the actual active species for OER. The work proposes a rational approach addressed by electron manipulation and surface reconstruction of bimetallic phosphides to regulate both the HER and OER activity.

Prefabricated Fibula Flap vs Bone-Driven and Delayed Implant Installation for Jaw Reconstruction

Restoration of dental occlusion and oral rehabilitation is the ultimate goal of functional jaw reconstruction. To evaluate the prefabricated fibula flap (PFF) technique in occlusion-driven jaw reconstruction for benign or previously treated malignant disease. This cohort study was conducted from January 2000 to December 2019 at the University of Alberta Hospital and Institute of Reconstructive Sciences in Medicine in Edmonton, Alberta, Canada, among patients who underwent PFF or bone-driven and delayed osseointegrated implant installation (BDD). Patients were followed up for a minimum of 1 year after occlusal rehabilitation. Data were analyzed from July 2021 to June 2022. Patients underwent BDD or PFF, which consists of osseointegrated dental implant installation and skin grafting of the fibular bone 3 to 6 months before jaw tumor resection or defect reconstruction. The implant osseointegration is completed at the time of jaw reconstruction, allowing for full reconstruction, loading, and restoration of the dental occlusion in the immediate postoperative period. Safety, effectiveness, accuracy, timeliness of occlusal reconstruction, and aesthetic appeal were compared between PFF and BDD. Groups were compared for the following variables: postoperative complications, number of bony segments used, number of procedures needed, total operative time, time to occlusal rehabilitation, and number of implants installed, exposed, lost, and used (ie, exposed implants - lost implants). Aesthetic appeal was assessed using standardized full-face and profile digital photographs taken before and 6 to 12 months after the operation and analyzed by 3 naive raters. Among 9 patients receiving PFF (mean [SD] age, 43.3 [13.0] years; 7 men [77.8%]) and 12 patients receiving BDD (mean [SD] age, 41.9 [18.0] years; 8 men [66.7%]), the overall complication rate was similar (4 patients [44.4%] vs 3 patients [25.0%], respectively; relative risk, 1.78 [95% CI, 0.52 to 6.04]). The number of patients with implant loss was similar between PFF and BDD groups (0 patients vs 3 patients [25.0%], respectively; difference, -25.0 percentage points [95% CI, -48.4 to 9.7 percentage points]). PFF had a clinically meaningful faster mean (SD) occlusal rehabilitation compared with BDD (12.1 [1.9] months vs 60.4 [23.1] months; difference, -48.3 months [95% CI, -64.5 to -32.0 months]). The mean (SD) difference in preoperative to postoperative aesthetic score was similar between PFF and BDD groups (-0.8 [1.5] vs -0.2 [0.8]; difference, -0.6 [95% CI, -1.6 to 0.4]). This study found that PFF compared with BDD was a safe, effective, and aesthetic reconstructive option for patients with benign or previously treated jaw malignant tumors. This technique may provide rapid occlusal reconstruction and oral rehabilitation.

Intercalated and Surface-Adsorbed Phosphate Anions in NiFe Layered Double-Hydroxide Catalysts Synergistically Enhancing Oxygen Evolution Reaction Activity.

The oxygen evolution reaction (OER), a crucial semireaction in water electrolysis and rechargeable metal-air batteries, is vital for carbon neutrality. Hindered by a slow proton-coupled electron transfer, an efficient catalyst activating the formation of an O-H bond is essential. Here, we proposed a straightforward one-step hydrothermal procedure for fabricating PO43--modified NiFe layered double-hydroxide (NiFe LDH) catalysts and investigated the role of PO43- anions in enhancing OER. Phosphate amounts can efficiently regulate LDH morphology, crystallinity, composition, and electronic configuration. The optimized sample showed a low overpotential of 267 mV at 10 mA cm-2. Density functional theory calculations revealed that intercalated and surface-adsorbed PO43- anions in NiFe LDH reduced the Gibbs free energy in the rate-determining step of *OOH formation, balancing oxygen-containing intermediate adsorption/dissociation and promoting the OER. Intercalated phosphate ions accelerated precatalyst dehydrogenation kinetics, leading to a rapid reconstruction into active NiFe oxyhydroxide species. Surface-adsorbed PO43- interacted favorably with adsorbed *OOH on the active Ni sites, stabilizing *OOH. Overall, the synergistic effects of intercalated and surface-adsorbed PO43- anions significantly contributed to enhanced OER activity. Achieving optimal catalytic activity requires a delicate equilibrium between thermodynamic and kinetic factors by meticulously regulating the quantity of introduced PO43- ions. This endeavor will facilitate a deeper comprehension of the influence of anions in electrocatalysis for OER.

Study on trajectory optimization of satellite rapid orbit formation flying for space object

This paper proposes a method of collaborative trajectory planning that utilizes convex optimization and IFPSO to tackle the issue of rapid formation reconstruction by multiple satellites in a low Earth circular orbit. The trajectory optimisation in this study uses convex optimisation and takes into account thrust limitations and safety distance. The time optimal solution is replaced by the path optimal solution, resulting in a suboptimal solution. The time-suboptimal trajectory solving method for formation flying using the CVX software is designed. The IFPSO is used to allocate configurations and waypoints for formation reconstruction, with the aim of balancing fuel consumption across the fleet and reducing the overall fuel consumption of the satellite. The effectiveness of the proposed approach is confirmed by numerical simulation. Despite sacrificing some computational efficiency, the method offered can solve the issues of configuration allocation and trajectory optimization.

A real-time solution method for three-dimensional steady temperature field of transformer windings based on mechanism-embedded cascade network

To enhance the computation efficiency and accuracy of three-dimensional steady temperature field of transformer windings, we propose a new non-invasive Reduced Order Model (ROM) based on a mechanism-embedded cascade network. Initially, a snapshot matrix is formed from the Full Order Model (FOM) and then combined with Proper Orthogonal Decomposition (POD) to extract key modal features that characterize the temperature field. Subsequently, a cascade network architecture, integrating Multilayer Perceptron (MLP) and Radial Basis Function Neural Network (RBFNN), is devised to swiftly map working condition parameters to modal coefficients. Additionally, the cascade network is embedded with condition sensitivity and modal contribution mechanisms to further enhance prediction accuracy. Finally, by linearly weighting the modes with predicted modal coefficients, a rapid reconstruction of the steady temperature field in transformer windings is achieved. Validation against Fluent software simulations and experimental measurements demonstrate a close agreement, with computational errors of less than 4K and an impressive single solution time of only 0.0087 s, which is 48760 times faster compared to Fluent software.

Self-healing of active site in Co(OH)2/MXene electrocatalysts for hydrazine oxidation

The development of efficient hydrazine oxidation reaction (HzOR) catalysts is important for the construction of remarkable energy storage and conversion systems. However, after a period of electrochemical reaction, the active site of the catalyst will be irreversibly reduced or inactivated, and how to recover the active site is a major challenge. Here, we report 2D Co(OH)2/Ti3C2(OH)x MXene composites with rapid reconstruction and self-healing behaviors as efficient and stable electrocatalysts during HzOR process. Both experimental and theoretical results indicate that the introduction of Ti3C2(OH)x MXene can effectively reduce the dehydrogenation barrier of Co(OH)2, from 0.584 eV to 0.481 eV to form the real catalytic active center Co(OH)O. Subsequently, Co(OH)O/Ti3C2(OH)x MXene composites with metal-like conductivity not only present spontaneous adsorption capacity of N2H4, but also can modulated rate-determining step of dehydrogenation of *N2H4 to *N2H3 (0.54 eV) compared with Co(OH)O. Finally, the electrophilic oxygen of Co(OH)O/Ti3C2(OH)x can spontaneously obtain electrons and protons from N2H4, achieving the oxidation of N2H4 while reducing Co(OH)O to Co(OH)2, thus completing the self-healing of the efficient catalyst.

Lessons learned: overcoming common challenges in reconstructing the SARS-CoV-2 genome from short-read sequencing data via CoVpipe2

Background Accurate genome sequences form the basis for genomic surveillance programs, the added value of which was impressively demonstrated during the COVID-19 pandemic by tracing transmission chains, discovering new viral lineages and mutations, and assessing them for infectiousness and resistance to available treatments. Amplicon strategies employing Illumina sequencing have become widely established for variant detection and reference-based reconstruction of SARS-CoV-2 genomes, and are routine bioinformatics tasks. Yet, specific challenges arise when analyzing amplicon data, for example, when crucial and even lineage-determining mutations occur near primer sites. Methods We present CoVpipe2, a bioinformatics workflow developed at the Public Health Institute of Germany to reconstruct SARS-CoV-2 genomes based on short-read sequencing data accurately. The decisive factor here is the reliable, accurate, and rapid reconstruction of genomes, considering the specifics of the used sequencing protocol. Besides fundamental tasks like quality control, mapping, variant calling, and consensus generation, we also implemented additional features to ease the detection of mixed samples and recombinants. Results We highlight common pitfalls in primer clipping, detecting heterozygote variants, and dealing with low-coverage regions and deletions. We introduce CoVpipe2 to address the above challenges and have compared and successfully validated the pipeline against selected publicly available benchmark datasets. CoVpipe2 features high usability, reproducibility, and a modular design that specifically addresses the characteristics of short-read amplicon protocols but can also be used for whole-genome short-read sequencing data. Conclusions CoVpipe2 has seen multiple improvement cycles and is continuously maintained alongside frequently updated primer schemes and new developments in the scientific community. Our pipeline is easy to set up and use and can serve as a blueprint for other pathogens in the future due to its flexibility and modularity, providing a long-term perspective for continuous support. CoVpipe2 is written in Nextflow and is freely accessible from \href{https://github.com/rki-mf1/CoVpipe2}{github.com/rki-mf1/CoVpipe2} under the GPL3 license.

A Rapid Reconstruction Method of 3D Digital Rock with Strong Pore Connectivity

A Rapid Reconstruction Method of 3D Digital Rock with Strong Pore Connectivity

Reconquest, Reconstruction, Resumption: Churching Poland after the Second World War

Abstract This article examines how the Roman Catholic Church in Poland navigated the enormous increase in church buildings at its disposal at the end of the Second World War. This expansion was largely due to the mass acquisition of post-German churches in lands transferred from Germany to Poland. But rapid reconstruction of most of the churches destroyed during the war as well as the resumption of new construction also played a role. Although access to increased worship space might seem to have been a boon for Poland’s postwar Catholic Church, the appropriation, reconstruction and completion of thousands of church buildings presented the church with an array of challenges. Refounding local Polish religious life in post-German, and often post-Protestant, houses of worship raised difficult questions about how various constituencies in newly formed communities could be made to feel at home in their new surroundings. Trade-offs between the expectations and customs of divergent groups were exacerbated by the prominence within the postwar church of Catholics who were themselves post-German, having spent the war categorized as German before being recategorized as Polish after 1945. Close attention to how Polish Catholics encountered new sacred spaces and one another reveals the complex negotiations and balancing acts required to form an ostensibly homogeneous religious-national community.

Rapid three-dimensional reconstruction for micro-motion target based on the low-rank state-space

Rapid three-dimensional reconstruction for micro-motion target based on the low-rank state-space

Photo‐promoted rapid reconstruction induced alterations in active site of Ag@amorphous NiFe hydroxides for enhanced oxygen evolution reaction

AbstractThe dynamic surface self‐reconstruction behavior in local structure correlates with oxygen evolution reaction (OER) performance, which has become an effective strategy for constructing the catalytic active phase. However, it remains a challenge to understand the mechanisms of reconstruction and to accomplish it fast and deeply. Here, we reported a photo‐promoted rapid reconstruction (PRR) process on Ag nanoparticle‐loaded amorphous Ni‐Fe hydroxide nanosheets on carbon cloth for enhanced OER. The photogenerated holes generated by Ag in conjunction with the anodic potential contributed to a thorough reconstruction of the amorphous substrate. The valence state of unsaturated coordinated Fe atoms, which serve as active sites, is significantly increased, while the corresponding crystalline substrate shows little change. The different structural evolutions of amorphous and crystalline substrates during reconstruction lead to diverse pathways of OER. This PRR utilizing loaded noble metal nanoparticles can accelerate the generation of active species in the substrate and increase the electrical conductivity, which provides a new inspiration to develop efficient catalysts via reconstruction strategies.