Template Parameters Research Articles

Gravitational waves from first-order phase transitions in LISA: reconstruction pipeline and physics interpretation

We develop a tool for the analysis of stochastic gravitational wave backgrounds from cosmological first-order phase transitions with LISA: we initiate a template databank for these signals, prototype their searches, and forecast their reconstruction.The templates encompass the gravitational wave signals sourced by bubble collisions, sound waves and turbulence. Accounting for Galactic and extra-Galactic foregrounds, we forecast the region of the parameter space that LISA will reconstruct with better than ∼ 10% accuracy, if certain experimental and theoretical uncertainties are solved by the time LISA flies.We illustrate the accuracy with which LISA can reconstruct the parameters on a few benchmark signals, both in terms of the template parameters and the phase transition ones.To show the impact of the forecasts on physics beyond the Standard Model, we map the reconstructed benchmark measurements into the parameter spaces of the singlet extension of the Standard Model and of the classically conformal invariant U(1) B-L model.

Benchmarking AlphaFold-Generated Structures of Chemokine-Chemokine Receptor Complexes.

AlphaFold and AlphaFold-Multimer have become two essential tools for the modeling of unknown structures of proteins and protein complexes. In this work, we extensively benchmarked the quality of chemokine-chemokine receptor structures generated by AlphaFold-Multimer against experimentally determined structures. Our analysis considered both the global quality of the model, as well as key structural features for chemokine recognition. To study the effects of template and multiple sequence alignment parameters on the results, a new prediction pipeline called LIT-AlphaFold (https://github.com/LIT-CCM-lab/LIT-AlphaFold) was developed, allowing extensive input customization. AlphaFold-Multimer correctly predicted differences in chemokine binding orientation and accurately reproduced the unique binding orientation of the CXCL12-ACKR3 complex. Further, the predictions of the full receptor N-terminus provided insights into a putative chemokine recognition site 0.5. The accuracy of chemokine N-terminus binding mode prediction varied between complexes, but the confidence score permitted the distinguishing of residues that were very likely well positioned. Finally, we generated a high-confidence model of the unsolved CXCL12-CXCR4 complex, which agreed with experimental mutagenesis and cross-linking data.

Complex Dynamical Characteristics of the Fractional-Order Cellular Neural Network and Its DSP Implementation

A new fractional-order cellular neural network (CNN) system is solved using the Adomian decomposition method (ADM) with the hyperbolic tangent activation function in this paper. The equilibrium point is analyzed in this CNN system. The dynamical behaviors are studied as well, using a phase diagram, bifurcation diagram, Lyapunov Exponent spectrum (LEs), and spectral entropy (SE) complexity algorithm. Changing the template parameters and the order values has an impact on the dynamical behaviors. The results indicate that rich dynamical properties exist in the system, such as hyperchaotic attractors, chaotic attractors, asymptotic periodic loops, complex coexisting attractors, and interesting state transition phenomena. In addition, the digital circuit implementation of this fractional-order CNN system is completed on a digital signal processing (DSP) platform, which proves the accuracy of ADM and the physical feasibility of the CNN system. The study in this paper offers a fundamental theory for the fractional-order CNN system as it applies to secure communication and image encryption.

High-performance flexible pressure sensor based on ordered double-level nanopillar array films: Design, development, and modeling

To improve the sensitivity and broaden the range of flexible pressure sensors, we proposed a high-performance flexible pressure sensor based on ordered double-level nanopillar array films. In this work, polypyrrole/multi-walled carbon nanotube/polyurethane (PPy/MWCNT/PU) conductive films with double-level nanopillar array microstructures were prepared by continuously adjusting the oxidation and pore expansion parameters of a porous anodic alumina template (AAO), where the high pillar height was 1243.0 ± 7.0 nm, and the low pillar height was 868.0 ± 4.70 nm. We studied the influence of the structural characteristics of ordered double-level nanopillar array conductive films and a flexible pressure sensor on the sensing performance using finite element simulations, the establishment of sensing mechanism, and sensor performance measurements. The results showed that the pressure was positively correlated with the change rate of strain and the surface microstructure contact area of the ordered double-level nanopillar array films. The sensor sensitivity reached 208.353 kPa−1, and its range was extended by 267%. In addition, the sensor, which could monitor vocalization, drinking pulse and finger movements, could be used in a wide range of applications, including wearable medical monitoring and smart sign language textiles.

Kinetically controlled composition of III-V ternary nanostructures

Controlling the composition of ternary III-V and III-nitride nanomaterials such as vertical nanowires, horizontal nanowires, nanosheets, and nanomembranes grown by different epitaxy techniques is essential for band gap engineering and fabrication of nanoheterostructures with tunable properties. Herein, we investigate the diffusion-induced growth process of III-V ternary materials in different geometries including planar layers, nanomembranes, and horizontal and vertical nanowires grown by selective area epitaxy or with a catalyst droplet on top and derive a rather general equation connecting the composition of ternary solid with the composition of vapor. The form of this vapor-solid distribution remains identical for a wide range of geometries, while the coefficients entering the equation contain thermodynamic factors, kinetic constants of the material transport, and geometrical parameters of the growth template. General properties of the vapor-solid distribution are investigated with respect to material constants, growth condition, and geometry, including the interplay of thermodynamics and growth kinetics leading to the suppression of the miscibility gaps in InGaAs and InGaN systems. A good correlation of the model with the data on the compositions of InGaAs, InGaP, and AlGaAs materials grown by different methods is demonstrated. Overall, these results give a simple analytical tool for understanding the compositional trends and compositional tuning of III-V ternary nanostructures, which should work equally well for Si-Ge and II-VI material systems.

Reconstructing physical parameters from template gravitational wave spectra at LISA: first order phase transitions

A gravitational wave background from a first order phase transition in the early universe may be observable at millihertz gravitational wave (GW) detectors such as the Laser Interferometer Space Antenna (LISA). In this paper we introduce and test a method for investigating LISA's sensitivity to gravitational waves from a first order phase transition using parametrised templates as an approximation to a more complete physical model. The motivation for developing the method is to provide a less computationally intensive way to perform Markov Chain Monte Carlo (MCMC) inference on the thermodynamic parameters of a first order phase transition, or on generally computationally intensive models. Starting from a map between the physical parameters and the parameters of an empirical template, we first construct a prior on the empirical parameters that contains the necessary information about the physical parameters; we then use the inverse mapping to reconstruct approximate posteriors on the physical parameters from a fast MCMC on the empirical template. We test the method on a double broken power law approximation to spectra in the sound shell model. The reconstruction method substantially reduces the proposal evaluation time, and despite requiring some precomputing of the mapping, this method is still cost-effective overall. In two test cases, with signal-to-noise ∼ 40, the method recovers the physical parameters and the spectrum of the injected gravitational wave power spectrum to 95% confidence. In previous Fisher matrix analysis we found the phase boundary speed v w was expected to be the best constrained of the thermodynamic parameters. In this work, for an injected phase transition GW power spectrum with v w = 0.55, with a direct sample on the thermodynamic parameters we recover 0.630+0.17 -0.059 and for our reconstructed sample 0.646+0.098 -0.075.

Controlled assembly of gold nanoparticles in resonant gold nanoapertures for SERS applications

The controlled assembly of plasmonic nanoparticles is vital for realizing low-cost, high efficiency plasmonic substrates with tunable resonances. Here, we present a strategy to assemble gold nanoparticles (AuNPs) in resonant gold nanoapertures (NAs) to enable coupling-mediated near-field enhancement. The NAs templates are fabricated using shadow sphere lithography on polyelectrolyte (PE) coated substrates. Subsequently, AuNPs are assembled in the resonant NA templates via a simple immersion step. The PE layer, AuNP concentration, NaCl concentration, incubation time, and template thickness are used to control the particle number per aperture and the interparticle distance of the AuNP assemblies. The fabricated AuNP-NA substrates are evaluated for their SERS potential using 4-Mercaptobenzoic acid (MBA) as a Raman reporter molecule. The SERS intensity of the AuNP-NA templates can be enhanced by ten times by controlling the AuNP and NA template parameters as compared to the bare NA templates. Numerical simulations show that the coupling between the various plasmonic modes is crucial for this SERS enhancement. The proposed strategy can be used to fabricate hybrid AuNP-NA based SERS substrates with improved sensitivity.

Particle Number Measurement and Its Numerical Simulation of the Airborne Particle Counter by ‘Post-Collection-Check’

The measurement results of the light-scattering airborne particle counter can effectively evaluate the concentration of airborne particles in the clean environment and confined space, and the accuracy improvement of the calibration measurement results has attracted more and more attention. This paper introduces the ‘post-collection-check’ way of the airborne particle concentration measurement method of the OPC (Optical Particle Counter), based on FESEM (Field Emission Scanning Electron Microscopy) and AAO (Anodic Aluminum Oxide) template, the probability distribution of the collected PSL (Polystyrene Latex) particles on the surface of AAO template, and the pressure parameters of AAO template under the different particle over current areas are both simulated. The numerical simulation results will help to improve the accuracy of the inference statistics of the collected PSL particle number on the membrane filter, and to give guidance on the optimal design of the PSL particle collection tube and the membrane filter, in order to provide an important reference for further improving the OPC particle concentration calibration and traceability method based on statistical theory.

Tailoring Ordered Wrinkle Arrays for Tunable Surface Performances by Template-Modulated Gradient Films.

Complex wrinkled microstructures are ubiquitous in natural systems and living bodies. Although homogeneous wrinkles in film-substrate bilayers have been extensively investigated in the past 2 decades, tailoring heterogeneous wrinkles by a facile method is still a challenge. Here, we report on the controllable heterogeneous wrinkles in template-modulated thickness-gradient metal films sputter-deposited on polydimethylsiloxane substrates. It is found that the stress of the gradient film is strongly position-dependent and the wrinkles are always restricted in thinner film regions. The morphological characteristic and formation mechanism of the heterogeneous wrinkles are analyzed and discussed in detail based on the stress theory. Ordered wrinkle arrays are achieved by adjusting the deposition time, copper grid period, template shape, and lifting height. The surface performances (e.g., the friction property) are well controlled by the wrinkle arrays. This work could promote better understanding of the spontaneously heterogeneous wrinkles in template-modulated gradient films and controllable fabrication of various wrinkle arrays by independently tuning film deposition conditions and template parameters.

UML Templates Distilled

UML templates are possibly the most neglected and misused piece of knowledge in UML modelling. This subject has been disregarded in the research and practice literature and even by modelling tools providers. This paper suggests that such oblivion results from a general misunderstanding that UML templates are just graphical representations of genericity like it is found in programming languages, and from the insufficient support from the modelling tools, with a consequence of poor usage of UML templates in practice. Indeed, the capabilities and potential of UML templates are far-reaching. Increasing awareness around them could bring significant benefits for UML users, namely, higher-level abstraction and reuse. Therefore, this paper provides a distilling tutorial on UML templates to highlight their flexibility and advantages. That presentation follows a tutorial style and is supported by several illustrative examples, varying from simpler to more complex ones. This tutorial reviews the Template construct’s core concepts and terminology, presents constraining classifiers and shows how to define properties and operations as template parameters. Then, it presents and discusses advanced aspects such as operation templates, parameter defaults, the relationship between binding and generalization, and the specific semantics of package templates. Furthermore, the paper discusses the related work and uncovers some of the UML templates’ limitations and opportunities for improvement.

Initial Clinical Evaluation of Fast-kV Dual Energy Imaging for Markerless Tumor Tracking of Lung Tumors in Stereotactic Body Radiation Therapy (SBRT)

Dual energy (DE) fluoroscopy is being considered for markerless tumor tracking (MTT) of lung tumors. The principal advantage of this technique is that it can be used to remove overlaying bony anatomy, and hence improve the tracking accuracy vs. single energy (SE) fluoroscopy. Previous studies using phantoms have demonstrated the superiority of DE vs. SE imaging for MTT. The goal of this study is to clinically evaluate MTT with fast-kV switching DE imaging on a cohort of SBRT lung cancer patients using the on-board imager (OBI) of a commercial linear accelerator.In this Institutional Review Board (IRB)-approved prospective study, DE images were acquired for 10 SBRT lung cancer patients. For each patient, DE images were obtained over 180o arc using fast-kV switching implemented on the OBI of a commercial linear accelerator. This fast-kV switching technique produced x-ray pulses that alternate between programmed tube voltages (i.e., 120 and 60 kVp) at a rate of 15 Hz. Weighted logarithmic subtraction was performed offline on consecutive high-low energy projections to produce soft tissue images. For comparison, SE image sequences were obtained by using the 120 kVp images. Separately, a template was derived from the contoured gross tumor volume (GTV) on the CT simulation scan. A template-based matching algorithm was then used to track target motion on both DE and SE image sequences. Successful matching was defined as any instance in which the algorithm matched the template on the respective fluoroscopic image. Ground truth positions were estimated from both the DE and SE images using Bayesian inference.A total of 2278 SE and DE image frames were analyzed. DE imaging resulted in significantly improved tracking vs. SE on 884/2278 (38.8%) of image frames. In those frames, the average tracking error was 1.78 +/- 2.02 mm vs. 2.21 +/- 2.38 mm, for DE vs. SE imaging, respectively (P < 0.001). For 4/10 patients, the average reduction in tracking error with DE vs. SE tracking was > 0.7 mm. No correlation was observed between tumor volume/location and improved tracking accuracy with DE imaging. Additionally, the fraction of images that could not be tracked with SE was 91/2278 (4.0%). The addition of DE imaging decreased this number to 33/2278 (1.4%) (P < 0.001).This is the first prospective study to evaluate fast-kV switching DE imaging for MTT in a cohort of SBRT lung cancer patients. This study has demonstrated that by removal of overlapping bony anatomy, DE imaging increases tracking accuracy and decreases the number of images where tracking fails. Future work includes optimization of template parameters to further improve DE tracking accuracy.

Influence of α-Al2O3 Template and Process Parameters on Atomic Layer Deposition and Properties of Thin Films Containing High-Density TiO2 Phases

High-density phases of TiO2, such as rutile and high-pressure TiO2-II, have attracted interest as materials with high dielectric constant and refractive index values, while combinations of TiO2-II with anatase and rutile have been considered promising materials for catalytic applications. In this work, the atomic layer deposition of TiO2 on α-Al2O3 (0 0 0 1) (c-sapphire) was used to grow thin films containing different combinations of TiO2-II, anatase, and rutile, and to investigate the properties of the films. The results obtained demonstrate that in a temperature range of 300–400 °C, where transition from anatase to TiO2-II and rutile growth occurs in the films deposited on c-sapphire, the phase composition and other properties of a film depend significantly on the film thickness and ALD process time parameters. The changes in the phase composition, related to formation of the TiO2-II phase, caused an increase in the density and refractive index, minor narrowing of the optical bandgap, and an increase in the hardness of the films deposited on c-sapphire at TG ≥ 400 °C. These properties, together with high catalytic efficiency of mixed TiO2-II and anatase phases, as reported earlier, make the films promising for application in various functional coatings.

Smart surgical template models for customized knee joint replacements

Abstract The paper introduces a method for the automated generation of patient-specific instruments (PSI), here in particular templates, for the implantation of customized implants. The basis is the derivation of data from the morphology of the bony situation and the medical planning. A developed methodological approach based on an Active Shape Model (ASM) is used for the morphological measurement. Determined geometric dimensions are placed on this ASM and automatically adjusted in each case. In addition, specially developed software tools for the planning and design of medical devices will be presented. This includes, among other things, the intuitive control of template parameters by the user when manual adjustments are necessary. The determined data is bundled and applied to previously methodically thought-out and categorized master CAD (Computer Aided Design) models of surgical templates. These master models are fully configurable and designed to be adjusted within defined ranges of values. The templates are printed from the biocompatible material PA12 using selective laser sintering (SLS).

Research on Data Mining Method of TCM Prescription Based on Machine Learning

This paper uses conditional random field model to mine TCM data. In order to identify the information of prescriptions in ancient Chinese medicine books, the model firstly cleaned and segmented the original text data, then, labels are added according to the selection of TCM characteristics to mark part of the corpus, and according to the demand divided into two parts, the training corpus was used to adjust the parameters of the custom CRF feature template, and the model was generated after adjusting the parameters. The accuracy of the model for entity recognition was verified by using the test corpus. In the end, the feasibility of the conditional random field model in the identification of TCM prescriptions was verified experimentally.

Accelerating linear solvers for Stokes problems with C++ metaprogramming

The efficient solution of large sparse saddle point systems is very important in computational fluid mechanics. The discontinuous Galerkin finite element methods have become increasingly popular for incompressible flow problems but their application is limited due to high computational cost. We describe C++ programming techniques that may help to accelerate linear solvers for such problems. The approach is based on the policy-based design pattern and partial template specialization, and is implemented in the open source AMGCL library. The efficiency is demonstrated with the example of accelerating an iterative solver of a discontinuous Galerkin finite element method for the Stokes problem. The implementation allows selecting algorithmic components of the solver by adjusting template parameters without any changes to the codebase. It is possible to switch the system matrix to use small statically sized blocks to store the nonzero values, or use a mixed precision solution, which results in up to 4 times speedup, and reduces the memory footprint of the algorithm by about 40%. We evaluate both monolithic and composite preconditioning strategies for 3 benchmark problems. The performance of the proposed solution is compared with a multithreaded direct Pardiso solver and a parallel iterative PETSc solver.

Siamese Regression Tracking With Reinforced Template Updating.

Siamese networks are prevalent in visual tracking because of the efficient localization. The networks take both a search patch and a target template as inputs where the target template is usually from the initial frame. Meanwhile, Siamese trackers do not update network parameters online for real-time efficiency. The fixed target template and CNN parameters make Siamese trackers not effective to capture target appearance variations. In this paper, we propose a template updating method via reinforcement learning for Siamese regression trackers. We collect a series of templates and learn to maintain them based on an actor-critic framework. Among this framework, the actor network that is trained by deep reinforcement learning effectively updates the templates based on the tracking result on each frame. Besides the target template, we update the Siamese regression tracker online to adapt to target appearance variations. The experimental results on the standard benchmarks show the effectiveness of both template and network updating. The proposed tracker SiamRTU performs favorably against state-of-the-art approaches.

Development and validation of an MRI-based radiomic nomogram to distinguish between good and poor responders in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapy.

In the clinical management of patients with locally advanced rectal cancer (LARC), the early identification of poor and good responders after neoadjuvant chemoradiotherapy (N-CRT) is essential. Therefore, we developed and validated predictive models including MRI findings from the structured report template, clinical and radiomics parameters to differentiate between poor and good responders in patients with locally advanced rectal cancer who underwent neoadjuvant chemoradiotherapy. Preoperative multiparametric MRI from 183 patients with locally advanced rectal cancer (122 in the training cohort, 61 in the validation cohort) was included in this retrospective study. After preprocessing, radiomic features were extracted and two methods of feature selection was applied to reduce the number of radiomics features. Logistic regression (LR) and random forest (RF) machine learning classifiers were trained to identify good responders from poor responders. Multivariable logistic regression analysis was used to incorporate the radiomic signature and clinical risk factors into a nomogram. Classifier performance was evaluated using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). For the differentiation of poor and good responders, the radiomics model with an LR classifier achieved AUCs of 0.869 and 0.842 for the training and validation cohorts, respectively. The nomogram showed the highest reproducibility and prognostic ability in the training and validation cohorts, with AUCs of 0.923 (95% confidence interval, 0.872-0.975) and 0.898 (0.819-0.978), respectively. Additionally, the nomogram achieved significant risk stratification of patients in respect to progression free survival (PFS). The nomogram accurately differentiated good and poor responders in patients with LARC undergoing N-CRT, and showed significant performance for predicting PFS.

Dosimetric comparison of dynamic conformal arc integrated with segment shape optimization and variable dose rate versus volumetric modulated arc therapy for liver SBRT.

The aim is a dosimetric comparison of dynamic conformal arc integrated with the segment shape optimization and variable dose rate (DCA_SSO_VDR) versus VMAT for liver SBRT and interaction of various treatment plan quality indices with PTV and degree of modulation (DoM) for both techniques. Twenty-five patients of liver SBRT treated using the VMAT technique were selected. DCA_SSO_VDR treatment plans were also generated for all patients in Monaco TPS using the same objective constraint template and treatment planning parameters as used for the VMAT technique. For comparison purpose, organs at risk (OARs) doses and treatment plans quality indices, such as maximum dose of PTV (Dmax%), mean dose of PTV (Dmean%), maximum dose at 2 cm in any direction from the PTV (D2cm%), total monitor units (MU's), gradient index R50%, degree of modulation (DoM), conformity index (CI), homogeneity index (HI), and healthy tissue mean dose (HTMD), were compared. Significant dosimetric differences were observed in several OARs doses and lowered in VMAT plans. The D2cm%, R50%, CI, HI and HTMD are dosimetrically inferior in DCA_SSO_VDR plans. The higher DoM results in poor dose gradient and better dose gradient for DCA_SSO_VDR and VMAT treatment plans, respectively. For liver SBRT, DCA_SSO_VDR treatment plans are neither dosimetrically superior nor better alternative to the VMAT delivery technique. A reduction of 69.75% MU was observed in DCA_SSO_VDR treatment plans. For the large size of PTV and high DoM, DCA_SSO_VDR treatment plans result in poorer quality.

Predicting poor response to neoadjuvant chemoradiotherapy for locally advanced rectal cancer: Model constructed using pre-treatment MRI features of structured report template

PurposeTo develop a predictive model with pre-treatment magnetic resonance imaging (MRI) findings of the structured report template and clinical parameters for poor responses prediction after neoadjuvant chemoradiotherapy (neoCRT) in locally advanced rectal cancers (LARC) patients. MethodPatients with clinicopathologically confirmed LARC (training and validation datasets, n = 100 and 71, respectively) were enrolled. Patients’ clinical data were retrospectively collected. MRI findings of the structured report template were analysed. The tumour regression grade (TRG) system as proposed by Mandard et al was used. Poor response was defined as TRG 3–5. Univariate logistic regression analysis and a lasso regression model were performed to select the significant predictive features from the training set. A nomogram was constructed based on a multivariable logistic regression analysis. Calibration, discrimination, and clinical usefulness of the nomogram were assessed. The calibrative and discriminative ability of our model were compared with those of models including the tumour-node-metastasis (TNM) stage and clinical factors. ResultsThe MRI-reported T4b stage, MRI-reported extramural venous invasion (EMVI) positivity, MRI-detected number of positive mesorectal lymph nodes (LNs) > 0, and preoperative oxaliplatin and capecitabine (CAPOX) chemotherapy regimen were incorporated into our nomogram. The nomogram showed good discrimination, with areas under the receiver operating characteristic (ROC) curves of 0·823 and 0·820 in the training and test sets, respectively, and good calibration in both datasets. The decision curve analysis confirmed that the nomogram was clinically useful. The calibrative and discriminative ability of our model were better than those models including the TNM stage and clinical factors. ConclusionA nomogram based on pre-treatment MRI features of the structured report template and clinical risk factors has potential for use as a non-invasive tool to preoperatively predict poor responses in LARC patients after neoCRT.

The dosimetry comparison study between 3D print template and free-hand guided of precision (125)I seeds implantation on superficial metastatic carcinoma

Objective: To compare the dose difference of (125)I seeds implantation on superficial metastatic carcinoma between 3D print template guided operation and traditional implantation. To investigate the accuracy of seeds implantation according preplan guided by 3D print template. Methods: A total of 21 cases of patient with 27 lesions underwent (125)I seeds implantation from January 2015 to May 2018 in Hebei General Hospital were analyzed retrospectively. In which, ten lesions underwent seeds implantation guided by 3D print template (template group) and 17 lesions underwent free-hand traditional implantation (traditional group). All patients had been fixed as the position of operation and then performed CT scan. After preplan was designed, the 3D templates were printed in template group. Postplan was performed after the operation.The dose volume histogram, D90 was calculated. The D90 pre and post operation were collected and compared in each group. The difference of D90 and the percentage difference of D90 between pre and post operation were calculated by the formula D90d=D90post-D90pre, D90d%=(D90post-D90pre)/D90pre×100%, and compared the difference between two groups. Results: The mean D90 pre and post operation in template group were (92±26) and (93±27) Gy respectively, t=-0.749, P=0.473. The mean D90 pre and post operation in traditional group were (104±29) and (104±26) Gy respectively, t=-0.139, P=0.891. The difference of D90 in two groups were (3.1±2.4) and (10.0±8.7) Gy, Z=-2.5, P=0.012. The percentage difference of D90 in two groups were 3.1%±1.9% and 9.5%±7.9%, Compared with the traditional group, the template group had smaller fluctuations, and the difference was statistically significant (Z=-2.7, P=0.006) (all P<0.05). Conclusions: The dose parameters of 3D template guided seeds implantation between postplan and preplan are nearly consistent.3D template has good repeatability, which provides a theoretical basis for the popularization of 3D printing technology.