Reconstruction Phase Research Articles

Escenarios de realidad virtual gamificada y su incidencia en el fomento de la motivación del aprendizaje de la escritura en el contexto universitario

This research focused on determining the impact of using gamified virtual reality environments on writing skills development in university settings. The aim was to implement new teaching methods that promote meaningful learning based on digital competencies and motivation. Methodologically, the study employed Pedagogical Action Research, which involved deconstruction, reconstruction, and validation phases. The population consisted of 278 first-year students enrolled in the Language and Communication course at a private university in southern Lima. The results demonstrated the effectiveness of the implemented strategies in enhancing student motivation, primarily due to the activation of dopamine, a neurotransmitter responsible for driving action towards efficiently solving challenges. A significant finding was the promotion of autonomous learning, as the prior review of resources facilitated the resolution of challenges. Consequently, Flipped Learning effectively prepared students for hybrid classes and encouraged active apprentices. The study concludes that the use of gamified virtual reality environments positively impacts the development of students' writing skills. Motivated students showed greater willingness to practice and refine their abilities, which in turn led to an improvement in the quality of their writing.

Forensic sex classification by convolutional neural network approach by VGG16 model: accuracy, precision and sensitivity.

In the reconstructive phase of medico-legal human identification, the sex estimation is crucial in the reconstruction of the biological profile and can be applied both in identifying victims of mass disasters and in the autopsy room. Due to the inherent subjectivity associated with traditional methods, artificial intelligence, specifically, convolutional neural networks (CNN) may present a competitive option. This study evaluates the reliability of VGG16 model as an accurate forensic sex prediction algorithm and its performance using orthopantomography (OPGs). This study included 1050 OPGs from patients at the Santa Maria Local Health Unit Stomatology Department. Using Python, the OPGs were pre-processed, resized and similar copies were created using data augmentation methods. The model was evaluated for precision, sensitivity, F1-score and accuracy, and heatmaps were created. The training revealed a discrepancy between the validation and training loss values. In the general test, the model showed a general balance between sexes, with F1-scores of 0.89. In the test by age group, contrary to expectations, the model was most accurate in the 16-20 age group (90%). Apart from the mandibular symphysis, analysis of the heatmaps showed that the model did not focus on anatomically relevant areas, possibly due to the lack of application of image extraction techniques. The results indicate that CNNs are accurate in classifying human remains based on the generic factor sex for medico-legal identification, achieving an overall accuracy of 89%. However, further research is necessary to enhance the models' performance.

A Reconstruction of the Shrine of the Prophet Nahum: An Analysis of 3D Documentation Methods and Data Transfer Technology for Virtual and Augmented Realities

This article focuses on modern methods of documentation and visualization for a historic object. Digital photogrammetry and terrestrial laser scanning (TLS), which are essential tools for documenting cultural heritage in view of their rapid development in recent years, were used, compared, and analyzed. Furthermore, the use of available 3D computer graphics technologies for visualization is described and an optimal procedure for converting the object into VR and AR is proposed and implemented. The technologies presented in this article were tested within the context of a project on the reconstruction of the shrine of the Prophet Nahum in the city of Alqosh in northern Iraq, taking the shrine as a case study. Funded by ARCH Int. and provided by GemaArt Int., the restoration project started in 2018 and was completed in 2021. The ongoing documentation was prepared by the CTU and it used the materials for research purposes. Accurate documentation using photogrammetry, drones, and TLS was key to the restoration. Leica BLK360, Faro Focus S150, and GeoSlam laser scanners were used, as well as photogrammetric methods. In particular, the documentation process involved the creation of 3D textured models from the photogrammetry, which were compared to the TLS data to ensure accuracy. These models were necessary to track changes during the reconstruction phases and to calculate the volumes of rubble removed and materials added. Our data analysis revealed significant differences between the construction logs and the analysis of the accurate 3D models; the results showed an underestimation of the displaced material statements by 13.4% for removed material and 4.6% for added material. The use of heat maps and volumetric analyses helped to identify areas of significant change that guided the reconstruction and documented significant changes to the building for the investor. These findings are important for use in the construction industry with respect to historic sites as well as for further research focused on visualization using VR (virtual reality) and AR (augmented reality). The conversion of existing 3D models into VR and AR is rapidly evolving and significant progress was made during this project. The Unreal Engine (UE) game engine was used. Despite the significantly improved performance of the new UE 5 version, the data for conversion to VR and AR needs to be decimated to reduce the amount—in our case, this was by up to 90%. The quality appearance of the objects is then ensured by textures. An important outcome of this part of the research was the debugged workflow developed to optimize the 3D models for VR, which was essential for creating a virtual museum that shows the restoration process.

Reconstructive Phase Transition Enables Abnormal Negative Thermal Quenching of Photoluminescence in a 1D Hybrid Perovskite.

Organic-inorganic hybrid perovskites (OIHPs) have attracted enormous attention owing to their intriguing structural tunability and diverse functional properties. Reconstructive phase transitions, involving the breaking and reconstruction of chemical bonds, have rarely been found in such materials; however, these features may induce many intriguing physical properties in optics, ferroelectrics, ferromagnetics, and so forth. Here, we utilized the weak and switchable coordination bonds of HETMA-MnCl3 (HETMA = (2-hydroxyethyl) trimethylammonium) to construct a 1D hybrid perovskite employing a neutral framework. As expected, this compound undergoes a reconstructive phase transition with a high phase transition temperature of 421 K. HETMA-MnCl3 shows remarkable red fluorescence, a wide emission spectrum, and a long luminous lifetime. Impressively, the reconstructive phase transition of HETMA-MnCl3 dominates the excellent PL coexistence of negative thermal quenching and thermal quenching behavior. To the best of our knowledge, such a phenomenon has rarely been found in the realm of multifunctional optoelectronic materials. This work provides possibilities to explore new classes of perovskite materials with reconstructive phase transitions and contributes to further developments.

Prosedur Pemeriksaan MSCT Cardiac pada Klinis Heart Failure dengan Disertai Atrial Fibrilasi di Instalasi Radiologi RS Universitas Sebelas Maret

Background:Cardiac MSCT is a CT scan examination that can show the structure of the heart chamber and blood vessels. The cardiac MSCT examination procedure in clinical heart failure accompanied by atrial fibrillation at the Radiology Installation of Sebelas Maret University Hospital uses a pitch parameter setting of 0.2 and selection of the contrast scanning reconstruction phase interval based on the results of the calcium score phase interval. This study aims to describe the cardiac MSCT examination procedure and the reasons for using the pitch parameter of 0.2 and determining the contrast scanning phase interval based on the results of the calcium score phase interval in clinical heart failure accompanied by atrial fibrillation. Method:This type of research is qualitative research with a case study approach. Data collection is carried out using observation, interview and documentation methods, then the data obtained is analyzed using an interactive data model, namely data collection, data reduction, data presentation and drawing conclusions. Results:Cardiac MSCT examination procedure in clinical heart failure accompanied by atrial fibrillation at the Sebelas Maret University Radiology Installation, the patient was not given betablocker drugs due to arrhythmia abnormalities. The protocol for this examination is topogram, calcium scoring and contrast cardiac scanning. Topogram parameters at 100 kV, and 60mA as high as the sternal notch to the diaphragm. Calcium scoring parameters at 80-90 kV, slice thickness 3mm with prospective ECG gatting method, scanning area for calcium scoring from the aortic arch to the cardiac basal. Cardiac contrast scanning parameters at 70-90 kV, slice thickness 0.8, tube rotation 0.33 and pitch 0.2 with an area from the aortic arch to the cardiac basal. Triggering scan is placed on the descending aorta as high as the main pulmonary artery. The use of a pitch of 0.2 can provide a longer ECG RR interval range in unstable patient pulses, thereby minimizing interpolation artifacts and facilitating the selection of contrast scanning reconstruction phase intervals. The use of calcium scorring phase interval results for selecting the contrast scanning reconstruction phase interval can facilitate the determination of the appropriate phase so that no artifacts are found due to errors in selecting the reconstruction phase interval, because in patients with atrial fibrillation, wave irregularities will result in differences in location between phase intervals. Conclusions:The use of pitch 0.2 aims to obtain a wider range of ECG RR intervals, thus minimizing the occurrence of interpolation artifacts in unstable patient heart rates. The use of calcium scorring reconstruction phase interval results as a guideline for setting the reconstruction phase interval in contrast scanning can facilitate the placement of appropriate and precise interval locations, so that no artifacts are found.

A Timeline-Based Study of the Early Reconstruction Phases in Ishikawa Prefecture Following the 2024 Noto Peninsula Earthquake

An earthquake and tsunami on 1 January 2024, caused extensive damage across Ishikawa Prefecture, Japan. This study systematically examined the recovery process. It aimed to analyze the initial stages of recovery and highlight the lessons learned from these efforts. By collecting data from Ishikawa’s post-disaster records, including government reports, reconstruction plans, local news, and observational records, we compiled the first “Early Reconstruction Timeline for Ishikawa”. This timeline divided the recovery process into four phases: disaster occurrence and emergency response (January), reconstruction preparation (February–April), the beginning of early reconstruction (May–September), and the beginning of mid-reconstruction to the present (October–Present). Analysis of this timeline revealed several significant findings. First, Ishikawa’s reconstruction efforts were structured into three key phases: ‘Post-Disaster Relief and Emergency Response’, ‘Post-Disaster Reconstruction Preparation Period’, and ‘Infrastructure Reconstruction and Emergency Housing Construction Period’. This phased approach highlights an efficient and organized recovery process, distinguishing Ishikawa from other disaster-affected regions. Additionally, the housing reconstruction model showcased an innovative balance between emergency housing as a public resource and the specific needs of displaced residents. These findings not only establish a timeline-based framework for Ishikawa’s reconstruction but also provide practical insights for guiding early post-disaster recovery efforts in various disaster-affected contexts worldwide.

Beyond the curtain: the impact of political non alignment on the urban reconstruction of Skopje

ABSTRACT This paper explores the reconstruction of Skopje following the 1963 earthquake, focusing on the interplay between productive conditions and temporal factors that shaped the city's transformation. The research examines how the earthquake, a critical juncture in Skopje's history, catalyzed profound urban and institutional changes, influenced by the Cold War's geopolitical landscape. The idea of ‘nonaligned modernism’ facilitated a convergence of international expertise, as demonstrated by the involvement of prominent teams like Doxiadis Associates and Polservice, and the strategic decisions of the International Board of Consultants (IBC). The paper reveals that the reconstruction process was not just a physical effort but a complex negotiation of institutional, cultural, and geopolitical factors. It highlights how the timing, sequencing of decisions, and the availability of global resources and expertise were crucial to the project's execution. Through a detailed analysis of the reconstruction phases, the strategic decisions made, and the international collaboration involved, this research underscores the significance of aligning productive conditions with temporal factors in shaping the outcomes of urban reconstruction efforts. The Skopje case exemplifies how crises can drive transformative change and set precedents for future international collaborations in urban planning.

Method to characterize phase transformation kinetics at high temperature

AbstractA new method is described to characterize the transformation kinetics of reconstructive systems at high temperatures using synchrotron X‐ray radiation, a quadrupole lamp furnace, and a detector capable of collecting a diffraction pattern of sufficient range in a minimal amount of time. Using this method, the activation energy for a reconstructive phase transformation in Dy2TiO5 was determined to be 149 kJ/mol. This value is more reasonable when compared with the uncertain values determined using conventional methods such as differential scanning calorimetry. In addition, the new method also provides higher quality data with improved time resolution, leading to better determination of fitted kinetic parameters.

Bi-directional Projection Framework for Fast Single Image Super Resolution

Background:: Collaborative Representation (CR) has been widely used in Single Image Super Resolution (SISR) with the assumption that Low-resolution (LR) and high-resolution (HR) features can be linearly represented by neighborhoods and share consistent CR coefficients. Numerous patents and journal papers have been published. However, this CR consistency does not hold in the reconstruction phase, which leads to degraded performance. Methods:: To fulfill this gap, we propose a novel bi-directional projection model (BDPM) to establish a bi-directional mapping between LR and HR features without any consistency constraint. The multiple projection matrices are offline computed to reduce reconstruction time greatly. We further develop several strategies to extract features and group neighborhoods such that local structures can be preserved better. Results:: Compared to the learning-based methods, BDPM is about 2 to 10 times faster and compared to the reconstruction-based methods, it is about 500 to 2,000 times faster. Conclusion:: The empirical studies verify the effectiveness of BDPM and extensive experimental results demonstrate that BDPM achieves better SISR performance than many state-of-the-arts.

FPGA Accelerated Implementation of 3D Mesh Secret Sharing Based on Symmetric Similarity of Model

Secret sharing is particularly important in the field of information security, which allows for the reconstruction of secret information from secure shares. However, due to the large amount of data and non-integer data type of 3D (three-dimensional) models, it is less efficient to perform sharing compared to the 2D(two-dimensional) digital images. In order to enable efficient sharing of 3D models as well, this article designs different circuit modules to parallelize the process of sharing 3D models. The proposed structure exploits the vertex extension to perform a complete reconstruction of the 3D model. In the sharing phase, the symmetric similarity of 3D model is exploited to realize the sharing in parallel, which improves the efficiency of sharing. In the reconstruction phase, the Strassen algorithm is used to optimize matrix multiplication, which saves circuit resources. Simulation results show that the structure performs more than 100 times faster than software. The utilization of circuit resources and the size of the share are both optimized. The validity of the designed hardware architecture is confirmed after analyzing the data from experiments performed on several 3D models.

3D augmented reality-guided robotic partial nephrectomy

The present study aims to provide a contemporary overview of the use of augmented reality (AR) in robotic renal surgery from the renal pedicle management to the demolition and reconstructive phases thanks also to the preoperative planning obtained with three-dimensional virtual models (3DVMs). Recently, the increasing use of the robotic approach extends the indication to partial nephrectomy also in cases of complex or large renal masses and maximizing functional and surgical outcomes. With this goal, new imaging technologies have increased in popularity, especially for laparoscopic and robotic approaches. In this scenario, hyper-accuracy 3DVMs of the kidney and tumor, based on computed tomography (CT) scans, have been developed as a new tool for preoperative planning and intraoperative surgical navigation via AR technology. However, a standardized production process of 3DVMs and dedicated guidelines on their use and application are still needed. A recent systematic review and metanalysis has shed light on the impact of 3D models on minimally-invasive nephron-sparing surgery (NSS). Specifically, lower rates of global ischemia and collecting system violation were observed within AR-robot-assisted partial nephrectomy (RAPN). However, these rates did not translate into significant improvements in terms of oncological or functional outcomes. This review provides a contemporary overview of the use of AR in robotic renal surgery from the renal pedicle management to the demolition and reconstructive phases thanks also to the preoperative planning obtained with 3DVMs.

SGRR: A two-stage method for removing raindrops from ground-based sky maps

The ground-based sky map provides real-time meteorological information for photovoltaic power stations and optimizes power generation efficiency by capturing changes in sky clouds. In order to effectively remove raindrops from the ground sky map and obtain a more accurate ground sky map, this paper proposes a new method called “Semantic Segmentation Generative Adversarial Raindrop Removal” (SGRR), which is divided into two stages: raindrop region segmentation and reconstruction. First, the ground-based sky map raindrop region segmentation dataset (GSRRS Dataset) and the ground-based sky map raindrop region reconstruction dataset (GSRRR Dataset) were constructed. During the segmentation stage, the U-shaped network was used in combination with the Depthwise Separable Receptive Field Pyramid module and Convolutional Block Attention Modules. The experimental results showed that the mean pixel accuracy, mean intersection over union, F1 score, and frames per second (FPS) on the GSRRS dataset reached 92.547%, 88.212%, 89.741%, and 120.7, respectively. In the reconstruction phase, a bidirectional interpolation filling module was proposed and combined with the optimization results of efficient channel attention mechanism. The peak signal-to-noise ratio, structural similarity, and FPS on the GSRRR dataset reached 30.23, 0.8751, and 77.6, respectively. The experiment shows that SGRR technology can accurately remove raindrops from ground-based sky images and generate images without obvious artifacts and has excellent performance.

Clivus Chordoma: Case Report and Current Considerations on Endoscopic Endonasal Trans-Sphenoid Surgery with Neurosurgeon-Otolaryngologist Collaboration

Chordomas, infrequent malignancies primarily located along the craniospinal axis, showcase gradual growth and localized bone destruction, with the clival region involved in approximately 25-35% of cases. Headaches accompanied by neurological deficits are the typical clinical presentations. Complete surgical resection is the mainstay, with recent collaborative efforts between otorhinolaryngologists and neurosurgeons leading to a positive shift from traditional craniotomic procedures to endoscopic endonasal approaches, fostering minimally invasive techniques and utilizing endoscopy for primary visualization across the neuraxis. Furthermore, the concept of team surgery has been introduced, involving simultaneous contributions from ENT surgeons and Neurosurgeons at all stages of the procedure, including the approach, resection, and reconstruction phases. This report presents a series of two successful cases of clival chordomas managed using the endoscopic endonasal approach at Siloam Hospital Lippo Village This indicates its potential as a viable surgical choice, particularly within medical centers that possess the necessary specialties. Successful implementation is notably enhanced through collaborative efforts between otolaryngologists and neurosurgeons, underscoring the significance of interdisciplinary teamwork.

Single-crystal elastic moduli, anisotropy, and the B1–B2 phase transition of NaCl at high pressures

Pressure dependences of the highest and lowest possible longitudinal sound velocities in single crystals of the B1 and B2 phases of NaCl were extracted from examination of their polycrystalline samples using the technique of time-domain Brillouin scattering. Based on the data collected up to 41 GPa, we largely extended the pressure range where single-crystal elastic moduli, Cij(P), and elastic anisotropy of the two cubic phases are measured, especially the experimental data for the B2 phase formed upon the reconstructive phase transition. The B1 phase of NaCl exhibits strong and growing anisotropy with increasing pressure, while that of the B2 phase is much weaker. Comparing with the previous experimental Cij(P) of other compounds exhibiting or expected to exhibit the B1–B2 phase transition, such as CaO, MgO, and (Mg1−x, Fex)O, we concluded that the transition is initiated by the shear instability due to violation of the Born stability criterion [C44(P)–P] > 0 and predicted the presently-not-verified transition pressures for MgO and (Mg1−x, Fex)O.

Towards attributed graph clustering using enhanced graph and reconstructed graph structure

Attributed graph clustering, leveraging both structural and attribute information, is crucial in various real-world applications. However, current approaches face challenges stemming from the sparsity of graphs and sensitivity to noise in Graph Convolutional Networks (GCNs). Moreover, GCN-based methods are often designed based on the assumption of homophilic graph and ignore heterophilic graph. To address these, we propose a graph clustering method that consists of four phases: graph enhance, graph reconstruction, graph refine, and dual-guidance supervisor module. An enhanced graph module is defined by an auxiliary graph to consider distant relationships in the topology structure to alleviate the limitations of sparse graphs. The graph reconstruction phase includes the creation and integration of homophily and heterophily graphs to achieve graph-agnostic. In graph refine, the auxiliary graph is iteratively improved to enhance the generalization of the representation. In this phase, a subspace clustering module is applied to convert attribute-based embeddings into relationship-based representations. Finally, the extracted graphs are fed to a dual-guidance supervisor module to obtain the final clustering result. Experimental validation on several benchmark datasets demonstrates the efficiency of our model. Meanwhile, the findings offer significant advancements in attributed graph clustering, promising improved applicability in various domains.

Reconstructive metal–semiconductor phase transition between nonlayered and layered tungsten dinitride

Reconstructive phase transitions are characterized by significant changes in the crystal structure of a material, typically accompanied by dramatic changes in its physical properties. In this Letter, via first-principles calculations, we report a reconstructive phase transition between nonlayered and layered tungsten dinitride (WN2) with kinetic energy barriers of 0.19 and 0.61 eV per formula unit depending on the transition direction. The nonlayered-to-layered transition can be triggered when an in-plane biaxial strain reaches 9.3%, while the layered-to-nonlayered transition happens at 53.5% of an out-of-plane uniaxial strain. The nonlayered and layered WN2 phases exhibit distinct structural, bonding, and electronic characteristics. Another intrinsic advantage of the reconstructive transition between layered and nonlayered phases is that it can be easily extended to two-dimensional (2D) nanoscale regions. Our results predict a rich phase diagram for 2D WN2 under strains, appealing for advanced nanoelectronics applications such as phase-change electronics or pressure sensors.

MODELLING GROWTH STRATEGIES OF TRANSPORT ENTERPRISES IN THE CONDITIONS OF CONTEXT UNCERTAINTY

Modern military conditions and tasks of post-war reconstruction require the development of effective strategies for the activity of transport enterprises of Ukraine to ensure the continuity of supplies of military and humanitarian goods. The purpose of the research was to create a model for the selection of optimal strategies for the development of transport enterprises of Ukraine in the conditions of uncertainty caused by the simultaneous influence of military aggression and the deepening of transport integration of Ukraine with the EU. The Saaty's method was selected for the study, which is based on the construction of fuzzy functions and is the most relevant in the context of the influence of a significant number of unstable exogenous and endogenous factors on the functioning of enterprises. In consideration of the evolving landscape of transportation in the European Union and Ukraine, the authors have distilled the overarching objectives of sustainable transportation development (economic, social, and environmental) into eighteen sub-objectives pertaining to the advancement of enterprises. These objectives are then subjected to expert evaluation. The article presents the findings of this expert ranking exercise, delineating the priorities for transportation enterprises in Ukraine across two distinct periods: the current state of martial law and the subsequent phase of post-war reconstruction. The authors have built a model for selecting optimal strategies for the development of a transport enterprise on the basis of a multi-level hierarchy of priority growth goals in two periods. As strategic alternatives, the authors have chosen the "strategy of limited growth"; "strategy of concentrated growth"; "strategy of diversified growth"; "strategy of integrated growth"; and "combined strategy". The paper determines that the appropriate growth strategies for transport enterprises during the period of martial law would be: a strategy of limited growth (rank 1.827) and a combined strategy (rank 2.0980). In the period of post-war reconstruction, the following growth strategies will be appropriate for implementation: concentrated growth (rank 3.0151) and integrated growth (rank 2.6783). The publication proposes a set of possible options for practical management actions in various functional areas of the transport enterprise (financial, organisational, marketing, social, technological, environmental) in accordance with the defined development strategies under martial law and post-war reconstruction. The practical application of the methodological approach to strategic management of transport enterprises in the context of economic uncertainty developed in the article will help to preserve domestic transport companies in the conditions of war and increase their competitiveness in the post-war period. The comprehensive implementation of the identified strategies will contribute to the development of innovative technologies, as well as European social and environmental transport standards in Ukraine.

Malicious Participants and Fake Task Detection Incorporating Gaussian Bias

Mobile crowdsensing (MCS) is a combination of crowdsourcing ideas and mobile sensing devices, designed to enable rational allocation of resources at scale. However, the MCS platform is highly vulnerable to injection attacks from malicious participants and fake tasks that interfere with platform service capabilities and sensing activities. To this end, the participant and task submission process is modeled as a multivariate time series, and a detection model for malicious participants and fake tasks (MP-FTD) with a Gaussian prior on the attentional mechanism and a two-stage adversarial training process is proposed. The attention mechanism was corrected using Gaussian bias, and then the corrected attention mechanism was used to obtain the correlation discrepancies between the data. Using the adversarial training method of Generative Adversarial Networks (GAN), the output of the correlation discrepancy reconstruction phase is transformed into a focus score, to amplify the reconstruction error in the output of the focus score reconstruction phase, and to improve the differentiation between the injected data and normal data of malicious attackers. The detection of these malicious attackers will effectively improve the robustness of the sensing platform. Experiments on six real-world datasets showed that the average F1-score reached 93.44%, outperforming the current baseline method, and resulting in an average 12.07% improvement in participant assignment accuracy and an average 12.25% improvement in task assignment accuracy in task assignment experiments.

Challenges in Pediatric Liver Retransplantation: A Technical Perspective.

Liver retransplantation (reLT) is the only option for pediatric patients experiencing graft loss. Despite recent advancements in surgical techniques and perioperative management, it remains a high-risk procedure. Our aim is to describe our experience in pediatric reLT, focusing on the technical aspects and surgical challenges. We systematically analyzed surgical reports from pediatric reLT performed at our center between 2006 and 2023 to identify recurrent intraoperative findings and specific surgical techniques. We focused on challenges encountered during different phases of reLT, including hepatectomy, vascular, and biliary reconstruction. Additionally, we compared patient and graft survival rates among different groups. During the study period, 23 children underwent 25 reLT procedures at our center. Major surgical challenges included complex hepatectomy and vascular reconstructions, necessitating tailored approaches. Our analysis shows that patient and graft survival were significantly lower for reLT compared to primary transplantation (p = 0.002). Early reLT had a significantly lower graft survival compared to late reLT (p = 0.002), although patient survival was comparable (p = 0.278). Patient and graft survival rates were comparable between the first and second reLT (p = 0.300, p = 0.597). Patient survival tended to be higher after living-donor liver transplantation (LDLT) compared to deceased-donor liver transplantation (DDLT), although the difference was not statistically significant (p = 0.511). Pediatric reLT involves significant technical challenges and lower survival rates. Advances in perioperative management are crucial for improving outcomes. Further research is needed to optimize surgical strategies and evaluate the long-term benefits of LDLT in pediatric reLT.

A Novel Approach to Automatically Digitize Analog Seismograms

Abstract Before the widespread adoption of the digital seismographs, seismic records were stored in analog form on paper and manually read by analysts. These analog seismograms contained various useful information and were crucial for seismic research. To meet the demands of the modern computational analysis, researchers must digitize historical analog seismograms and extract information. In this article, we present a novel approach to automatically digitize analog seismograms. Initially, Otsu threshold segmentation was applied to the analog seismograms to remove underlying noise and improve their clarity. Subsequently, a novel dynamic distributed seismic waveform onset-point-search algorithm was implemented, which automatically locates the onset point of each seismic waveform baseline in analog seismograms and accurately determines the total number of seismic waveform curves. To address the complexity and diversity of seismic waveforms, we implemented an innovative seismic waveform classification algorithm that can distinguish between complex waveforms and smooth waveforms, and further implemented a new smooth waveform removal method to eliminate interference from smooth waveforms during complex waveform extraction. Then, we used a YOLOv9s-based model to identify time markers within the seismic waveforms for removal. In addition, in the seismic waveform digitization extraction and reconstruction phase, we implemented a novel method for extracting significant seismic waveform features and geometric restoration for peak and trough feature extraction and geometric restoration, as well as vertical feature extraction of seismic waveforms. Finally, we implemented a new waveform sequence integration and time mapping model, which can effectively reconstruct seismic waveform data based on the extracted features and map arrival times to each waveform point. Experiments have verified the significant superiority and stability of the methods implemented in this article for digitizing analog seismograms.