Local Template Research Articles

Retrosynthesis Prediction with Local Template Retrieval

Retrosynthesis, which predicts the reactants of a given target molecule, is an essential task for drug discovery. In recent years, the machine learing based retrosynthesis methods have achieved promising results. In this work, we introduce RetroKNN, a local reaction template retrieval method to further boost the performance of template-based systems with non-parametric retrieval. We first build an atom-template store and a bond-template store that contains the local templates in the training data, then retrieve from these templates with a k-nearest-neighbor (KNN) search during inference. The retrieved templates are combined with neural network predictions as the final output. Furthermore, we propose a lightweight adapter to adjust the weights when combing neural network and KNN predictions conditioned on the hidden representation and the retrieved templates. We conduct comprehensive experiments on two widely used benchmarks, the USPTO-50K and USPTO-MIT. Especially for the top-1 accuracy, we improved 7.1% on the USPTO-50K dataset and 12.0% on the USPTO-MIT dataset.These results demonstrate the effectiveness of our method.

Wafer Surface Defect Detection Based on Background Subtraction and Faster R-CNN.

Concerning the problem that wafer surface defects are easily confused with the background and are difficult to detect, a new detection method for wafer surface defects based on background subtraction and Faster R-CNN is proposed. First, an improved spectral analysis method is proposed to measure the period of the image, and the substructure image can then be obtained on the basis of the period. Then, a local template matching method is adopted to position the substructure image, thereby reconstructing the background image. Then, the interference of the background can be eliminated by an image difference operation. Finally, the difference image is input into an improved Faster R-CNN network for detection. The proposed method has been validated on a self-developed wafer dataset and compared with other detectors. The experimental results show that compared with the original Faster R-CNN, the proposed method increases the mAP effectively by 5.2%, which can meet the requirements of intelligent manufacturing and high detection accuracy.

Crystal Structure Analysis of Sarcoplasmic-Calcium-Binding Protein: An Allergen in Scylla paramamosain.

The structure of allergenic proteins provides important information about the binding of allergens to antibodies. In this study, the crystal structure of Scy p 4 with a resolution of 1.60 Å was obtained by X-ray diffraction. Epitope mapping of Scy p 4 revealed that linear epitopes are located on the surface of Scy p 4. Also, conformational epitopes are mostly located in the structural conservative region. Further structural comparison, surface electrostatic potential, and hydrogen bond force analysis showed that mutation of Asp70 and Asp18/20/70 would lead to calcium-binding capacity being lost and destruction of allergenicity. Furthermore, a comparative analysis of structure showed that sarcoplasmic-calcium-binding protein (SCP) had high sequence, secondary, and spatial structural identity in crustaceans, which may be an important factor leading to cross-reactivity among crustaceans. The structure of Scy p 4 provides a template for epitope evaluation and localization of SCPs, which will help to reveal cross-reactivity among species.

Three-dimensional printing template for intraoperative localization of pulmonary nodules in the pleural cavity.

Localization of pulmonary nodules is challenging. However, traditional localization methods have high radiation doses and a high risk of complications. We developed a noninvasive 3-dimensional printing navigational template for intraoperative localization. It can reduce puncture-related complications and simplify the localization process. This study will verify the feasibility of this method. Patients with peripheral pulmonary nodules were included in this study. The computed tomography scan sequences were obtained to design a digital template model, which was then imported into a 3-dimensional printer to produce a physical navigational template. Finally, the navigational template is placed into the patient's pleural cavity for intraoperative localization. The precision of the nodule localization and associated complications were evaluated. Twelve patients were finally included in this study. Intraoperative navigational template localization was used in all patients. The success rate of intraoperative nodule localization was 100%, and the median time of localization was 19.5minutes (range, 16-23.5minutes). The deviation median of the navigational template was 2.1mm (range, 1.1-2.7mm). Among the included patients, no significant complications occurred during intraoperative localization. The 3-dimensional printing template for intraoperative localization is feasible, will cause no trauma to the patient, and has acceptable accuracy for application in nodules localization. This navigational template greatly simplifies the localization process and may potentially break the dependence of percutaneouslocalization on computed tomography scanning.

Research on the Visual Guidance System of Zoning Casting Grinding Based on Feature Points

Compared to traditional rough casting grinding (RCG), the individualization of castings is very different, which makes it difficult to realize the automation of casting grinding. At this stage, the primary method is manual grinding. In this study, the regional casting grinding system based on feature points is adopted to achieve the personalized grinding of castings and improve the grinding efficiency and the automation level of the manufacturing process. After preprocessing the point cloud, the fast point feature histogram (FPFH) descriptor is used to describe the features of each region and construct the local template. The position of the local region is obtained by template matching. The random sample consensus (RANSAC) algorithm is used to calculate the plane and fit the point cloud to obtain the contact point trajectory of the grinding head. Then, according to different polishing methods, different polishing poses are generated. The simulation experimental results show that the system has good adaptability, and the consistency of finished products is good.

Thousands of human mutation clusters are explained by short-range template switching.

Variation within human genomes is unevenly distributed, and variants show spatial clustering. DNA replication-related template switching is a poorly known mutational mechanism capable of causing major chromosomal rearrangements as well as creating short inverted sequence copies that appear as local mutation clusters in sequence comparisons. In this study, haplotype-resolved genome assemblies representing 25 human populations and multinucleotide variants aggregated from 140,000 human sequencing experiments were reanalyzed. Local template switching could explain thousands of complex mutation clusters across the human genome, the loci segregating within and between populations. During the study, computational tools were developed for identification of template switch events using both short-read sequencing data and genotype data, and for genotyping candidate loci using short-read data. The characteristics of template-switch mutations complicate their detection, and widely used analysis pipelines for short-read sequencing data, normally capable of identifying single nucleotide changes, were found to miss template-switch mutations of tens of base pairs, potentially invalidating medical genetic studies searching for a causative allele behind genetic diseases. Combined with the massive sequencing data now available for humans, the novel tools described here enable building catalogs of affected loci and studying the cellular mechanisms behind template switching in both healthy organisms and disease.

Non-Gaussianity in DHOST inflation

DHOST inflation models where deviations from a pure de Sitter background are induced by an axion-like potential can lead to large non-Gaussianities. We investigate the nature of non-Gaussianities in these models and compare to the results given by the Planck experiment. The overlap between the DHOST non-Gaussianities and the equilateral, orthogonal and local templates can be rendered arbitrarily small. On the other hand, this does not preclude DHOST models from showing large non-Gaussianities as exemplified by their reduced bispectrum. As a result, they could be probed by future experiments and also by a more thorough analysis of the existing Planck data.

Joint Local and Nonlocal Progressive Prediction for Versatile Video Coding.

In the latest video coding standard, namely Versatile Video Coding (VVC), more directional intra modes and reference lines have been utilized to improve prediction efficiency. However, complex content still cannot be predicted well with only the adjacent reference samples. Although nonlocal prediction has been proposed to further improve the prediction efficiency in existing algorithms, explicit signalling or matching error potentially limits the coding efficiency. To address these issues, we propose a joint local and nonlocal progressive prediction scheme, targeting at improving nonlocal prediction accuracy without additional signalling. Specifically, template matching based prediction (TMP) is conducted firstly to derive an initial nonlocal predictor. Based on the first prediction and previously decoded reconstruction information, a local template, including inner textures and neighboring reconstruction, is carefully designed. With the local template involved in nonlocal matching process, a more accurate nonlocal predictor can be found progressively in the second prediction. Finally, the coefficients from the two predictions are fused and transmitted in bitstreams. In this way, more accurate nonlocal predictor can be derived implicitly with local information instead of being explicitly signalled. Experimental results on the reference software VTM-9.0 of VVC show that the method achieves 1.02% BD-Rate reduction for natural sequences and 2.31% BD-Rate reduction for screen content videos under all intra (AI) configuration.

Far-Infrared Line Diagnostics: Improving N/O Abundance Estimates for Dusty Galaxies

Abstract The nitrogen-to-oxygen (N/O) abundance ratio is an important diagnostic of galaxy evolution because the ratio is closely tied to the growth of metallicity and the star formation history in galaxies. Estimates for the N/O are traditionally made with optical lines that could suffer from extinction and excitation effects, so the N/O is arguably measured better through far-infrared (far-IR) fine-structure lines. Here we show that the [N iii]57 μm/[O iii]52 μm line ratio, denoted N3O3, is a physically robust probe of N/O. This parameter is insensitive to gas temperature and only weakly dependent on electron density. Although it has a dependence on the hardness of the ionizing radiation field, we show that it is well corrected when the [Ne iii]15.5 μm/[Ne ii]12.8 μm line ratio is included. We verify the method, and characterize its intrinsic uncertainties by comparing the results to photoionization models. We then apply our method to a sample of nearby galaxies using new observations obtained with SOFIA/FIFI-LS in combination with available Herschel/PACS data, and the results are compared with optical N/O estimates. We find evidence for a systematic offset between the far-IR and optically derived N/O. We argue that the likely reason is that our far-IR method is biased toward younger and denser H ii regions, while the optical methods are biased toward older H ii regions as well as diffuse ionized gas. This work provides a local template for studies of the abundance of interstellar medium in the early Universe.

Benchmarking GPCR homology model templateselection in combination with de novo loop generation.

G protein-coupled receptors (GPCR) comprise the largest family of membrane proteins and are of considerable interest as targets for drug development. However, many GPCR structures remain unsolved. To address the structural ambiguity of these receptors, computational tools such as homology modeling and loop modeling are often employed to generate predictive receptor structures. Here we combined both methods to benchmark a protocol incorporating homology modeling based on a locally selected template and extracellular loop modeling that additionally evaluates the presence of template ligands during these modeling steps. Ligands were also docked using three docking methods and two pose selection methods to elucidate an optimal ligand pose selection method. Results suggest that local template-based homology models followed by loop modeling produce more accurate and predictive receptor models than models produced without loop modeling, with decreases in average receptor and ligand RMSD of 0.54Å and 2.91Å, respectively. Ligand docking results showcased the ability of MOE induced fit docking to produce ligand poses with atom root-mean-square deviation (RMSD) values at least 0.20Å lower (on average) than the other two methods benchmarked in this study. In addition, pose selection methods (software-based scoring, ligand complementation) selected lower RMSD poses with MOE induced fit docking than either of the other methods (averaging at least 1.57Å lower), indicating that MOE induced fit docking is most suited for docking into GPCR homology models in our hands. In addition, target receptor models produced with a template ligand present throughout the modeling process most often produced target ligand poses with RMSD values ≤ 4.5Å and Tanimoto coefficients > 0.6 after selection based on ligand complementation than target receptor models produced in the absence of template ligands. Overall, the findings produced by this study support the use of local template homology modeling in combination with de novo ECL2 modeling in the presence of a ligand from the template crystal structure to generate GPCR models intended to study ligand binding interactions.

Inhomogeneous Template Adaptation of Temporal Quasi-Periodic Three-Dimensional Signals

We propose a novel framework for performing inhomogeneous template adaptation on temporal three-dimensional data. Templates of interest are first globally translated, scaled and rotated using statistical methods in the form of Procrustes analysis. In this globally adapted form, the data is parameterized to a minimum bounding rectangular prism using a parameterization method known as free-form deformation. The parameterized model is then reduced to a linear least squares problem, which subsequently allows for a robust local template adaptation scheme utilizing a non-parametric formulation. To account for complex noise behaviour encountered in quasi-periodic signals, we ensue to complete the framework with an adaptive noise model. We demonstrate the power of the proposed framework using three applications: firstly, we quantify the ability of the proposed framework to track geometric features of heart disease on a synthetic dataset containing three-dimensional electrocardiogram signals. Next we track these features on a publicly available real dataset (PTB database) to demonstrate its potential in heart disease diagnostics. Lastly, we apply the proposed framework to map three-dimensional velocity profiles using the publicly available Complex Upper-Limb Movements database.

A Machine Vision System for Stacked Substrates Counting With a Robust Stripe Detection Algorithm

Batch measurement of sheet-like product quantity is very common in manufacturing and commercial areas. Particularly, to satisfy the growing requirement of automatic and nondestructive detection, a machine vision system for stacked substrates counting is proposed in this paper. With a brief description of the system architecture and imaging module, the challenges for real data analysis are investigated. Our main contribution is to develop a robust stripe detection algorithm by combining the merits of local template matching and global frequency domain filtering. Besides the peak-valley feature across the stack profile, the collinear prior shape along the substrates is also utilized in a morphological scheme to purify the obtained ridge-line or stripe images, which, finally, benefits the statistical counting output. It is verified in experiments using a diversity of substrate media that our developed system can achieve a high counting accuracy with the detection error not more than 0.01% as the sample thickness varies between 0.05 mm and 0.5 mm. Moreover, the proposed algorithm performs much robustly with various kinds of abnormalities and interferences like irregular piling, media distortion, and foreign contamination.

IA-OPD: An Optimized Orthogonal Pulse Design Scheme for Waveform Division Multiple Access UWB Systems

A new design scheme of orthogonal pulses is proposed for waveform division multiple access ultra-wideband (WDMA-UWB) systems. In order to achieve WDMA and to improve user capacity, the proposed method, termed as interference alignment based orthogonal pulse design (IA-OPD), employs combined orthogonal wavelet functions in the pulse design. The combination coefficients are optimized by using interference alignment. Due to the reciprocity between transmitted and local template signals, the iterative process based on maximum signal to interference plus noise ratio (Max-SINR) criterion can be used to solve the optimization problem in interference alignment. Numerical results demonstrate that the optimized orthogonal pulses provide excellent performances in terms of multiple access interference suppression, user capacity and near-far resistance without using any multiuser detection techniques. Thus, the IA-OPD scheme can be used to efficiently design a large number of orthogonal pulses for multiuser WDMA-UWB systems with low computational complexity and simple transceiver structure.

UAV target detection and parameter estimation in non‐homogeneous clutter

Aiming at the problem of UAV target detection and parameter estimation in non-homogeneous clutter with STLFMCW radar, a SK-CFAR detector is proposed based on the local spectrum refinement. By using zoom-FFT, the two-dimensional spectrum of the received signal is extracted for local template matching. Subsequently, the two-dimensional SK-CFAR detector and CLEAN technique are applied to decide whether there exist some targets in the region of interest. Compared with Radon–Fourier transform (RFT) and moving target detection (MTD), the proposed estimator based on local speed compensation is a good choice for the trade-off of high performance and low computational load even though the input signal-to-clutter ratio approaches to −24 dB.

A pattern-matching method for flow model calibration under training image constraint

Modern geostatistical modeling techniques are developed to simulate complex geologic connectivity patterns (e.g., curvilinear fluvial systems) at the grid-level using a training image (TI) that encodes multiple-point statistical (MPS) information. A challenging aspect of using MPS methods is conditioning the resulting models on nonlinear flow data. We develop a pattern-matching method for calibration of MPS-based facies models subject to the TI constraint. Since the exact statistical information in the TI can only be expressed empirically, flow data conditioning and pattern matching are carried out in two iterative steps, using an alternating-direction algorithm. Flow data integration is formulated through a regularized least-squares by taking advantage of learned k-SVD sparse parametrization and l1-norm sparsity-promoting regularization methods. The TI constraint is enforced through a MPS-based pattern-matching algorithm that uses the identified model calibration solution to generate a corresponding facies model that is consistent with the TI. The pattern-matching algorithm uses a local search template to scan the TI to find facies patterns with smallest distances from the corresponding local patterns in the parameterized approximate solution. The identified patterns for each location in the model are stored and used to estimate local conditional probabilities for assigning the facies types to each grid cell. The resulting solution is passed to the flow data conditioning step as a regularization term to perform the next iteration. The process is repeated until the MPS facies model provides an acceptable match to the data. Numerical experiments are presented to evaluate the performance of the pattern-matching method for calibration of complex facies models.

Three-Dimensionally Printed Template for Percutaneous Localization of Multiple Lung Nodules

When multiple target lung nodules exist, the computed tomography (CT)-guided percutaneous localization procedure becomes complicated. In this study, a three-dimensional (3D)-printed template was designed that could guide hook wire localization of multiple lung nodules. The pilot study aimed for preliminary validation of the feasibility of template-guided localization for multiple lesions. Patients with multiple lung nodules (<2 cm) and who were scheduled for surgical resection were recruited for participation in this study. After securing their preadmission CT images, the study investigators reconstructed a 3D thorax model from which they designed a digital model as a navigational template. A physical template was then printed for guiding the percutaneous localization of lung nodules. The localization accuracy was evaluated on the basis of the deviation between the localizer and the nodule. From April 2018 to November 2018, the study enrolled 16 patients with 34 lung nodules. All noduleswere successfully localized under template guidance, with a median procedural time of 10.0minutes(interquartile range [IQR], 8.5-12.6 minutes) anda median radiation exposure of 235 mGy • cm(IQR, 195-254 mGy • cm). The median deviation fromthe hookwires and nodule centers was 9.0 mm (IQR, 6.2-11.8 mm). Except for2 cases of pneumothorax without needfor furtherintervention, no complications occurred. Navigational templates built using 3D printing may serve as an effective approach for facilitating localization of multiple lung nodules.

A Dehazing Algorithm Based on Local Adaptive Template for Transmission Estimation and Refinement

Outdoor images are vulnerable to environment and may suffer various distortions. Therefore, preprocessing for images captured in bad weather is particularly important for computer vision system. One of the most common conditions is haze. Image dehazing, especially single image dehazing is a challenging topic since it’s an ill-posed problem and needs to rely on extra information or prior. In this paper, we discussed the shortcomings of existing algorithms and proposed a novel step called Local Adaptive Template. The template is used in transmission estimation and transmission refinement. Starting from the target pixel, the template is extracted under the guidance of the similarity function and only contains pixels related to the center point, thus avoids the influence of adjacent objects, even those with blur edges. We then used the template to improve the Dark Channel Prior(DCP) and the Guided Filter(GF) respectively, and effectively avoided the block effect in DCP and the blur in GF. The obtained transmission map is much more accurate, and free from the halo effect. The dehazing result is much clearer and still looks natural without haze residual. Experiments on natural images and synthetic images show that our method achieves better dehazing results than several state-of-art algorithms and can adapt to different situations.

Velocity profiles of [CII], [CI], CO, and [OI] and physical conditions in four star-forming regions in the Large Magellanic Cloud

Aims. The aim of our study is to investigate the physical properties of the star-forming interstellar medium (ISM) in the Large Magellanic Cloud (LMC) by separating the origin of the emission lines spatially and spectrally. The LMC provides a unique local template to bridge studies in the Galaxy and high redshift galaxies because of its low metallicity and proximity, enabling us to study the detailed physics of the ISM in spatially resolved individual star-forming regions. Following Okada et al. (Okada, Y., Requena-Torres, M. A., Güsten, R., et al. 2015, A&amp;A, 580, A54), we investigate different phases of the ISM traced by carbon-bearing species in four star-forming regions in the LMC, and model the physical properties using the KOSMA-τ PDR model. Methods. We mapped 3–13 arcmin2 areas in 30 Dor, N158, N160, and N159 along the molecular ridge of the LMC in [C II] 158 μm with GREAT on board SOFIA. We also observed the same area with CO(2-1) to (6-5), 13CO(2-1) and (3-2), [C I] 3P1–3P0 and 3P2–3P1 with APEX. For selected positions in N159 and 30 Dor, we observed [O I] 145 μm and [O I] 63 μm with upGREAT. All spectra are velocity resolved. Results. In all four star-forming regions, the line profiles of CO, 13CO, and [C I] emission are similar, being reproduced by a combination of Gaussian profiles defined by CO(3-2), whereas [C II] typically shows wider line profiles or an additional velocity component. At several positions in N159 and 30 Dor, we observed the velocity-resolved [O I] 145 and 63 μm lines for the first time. At some positions, the [O I] line profiles match those of CO, at other positions they are more similar to the [C II] profiles. We interpret the different line profiles of CO, [C II] and [O I] as contributions from spatially separated clouds and/or clouds in different physical phases, which give different line ratios depending on their physical properties. We modeled the emission from the CO, [C I], [C II], and [O I] lines and the far-infrared continuum emission using the latest KOSMA-τ PDR model, which treats the dust-related physics consistently and computes the dust continuum SED together with the line emission of the chemical species. We find that the line and continuum emissions are not well-reproduced by a single clump ensemble. Toward the CO peak at N159 W, we propose a scenario that the CO, [C II], and [O I] 63 μm emission are weaker than expected because of mutual shielding among clumps.

Accuracy of a 3-Dimensionally Printed Navigational Template for Localizing Small Pulmonary Nodules

Localization of small lung nodules are challenging because of the difficulty of nodule recognition during video-assisted thoracoscopic surgery. Using 3-dimensional (3-D) printing technology, a navigational template was recently created to assist percutaneous lung nodule localization; however, the efficacy and safety of this template have not yet been evaluated. To assess the noninferiority of the efficacy and safety of a 3-D-printed navigational template guide for localizing small peripheral lung nodules. This noninferiority randomized clinical trial conducted between October 2016 and October 2017 at Shanghai Pulmonary Hospital, Shanghai, China, compared the safety and precision of lung nodule localization using a template-guided approach vs the conventional computed tomography (CT)-guided approach. In total, 213 surgical candidates with small peripheral lung nodules (<2 cm) were recruited to undergo either CT- or template-guided lung nodule localization. An intention-to-treat analysis was conducted. Percutaneous lung nodule localization. The primary outcome was the accuracy of lung nodule localization (localizer deviation), and secondary outcomes were procedural duration, radiation dosage, and complication rate. Of the 200 patients randomized at a ratio of 1:1 to the template- and CT-guided groups, most were women (147 vs 53), body mass index ranged from 15.4 to 37.3, the mean (SD) nodule size was 9.7 (2.9) mm, and the mean distance between the outer edge of target nodule and the pleura was 7.8 (range, 0.0-43.9) mm. In total, 190 patients underwent either CT- or template-guided lung nodule localization and subsequent surgery. Among these patients, localizer deviation did not significantly differ between the template- and CT-guided groups (mean [SD], 8.7 [6.9] vs 9.6 [5.8] mm; P = .36). The mean (SD) procedural durations were 7.4 (3.2) minutes for the template-guided group and 9.5 (3.6) minutes for the CT-guided group (P < .001). The mean (SD) radiation dose was 229 (65) mGy × cm in the template-guided group and 313 (84) mGy × cm in CT-guided group (P < .001). The use of the 3-D-printed navigational template for localization of small peripheral lung nodules showed efficacy and safety that were not substantially worse than those for the CT-guided approach while significantly simplifying the localization procedure and decreasing patient radiation exposure. ClinicalTrials.gov identifier: NCT02952261.

The Far-infrared Emission of the First Massive Galaxies

Abstract Massive Population II galaxies undergoing the first phase of vigorous star formation after the initial Population III stage should have high energy densities and silicate-rich interstellar dust. We have modeled the resulting far-infrared spectral energy distributions (SEDs), demonstrating that they are shifted substantially to bluer (“warmer”) wavelengths relative to the best fitting ones at z ≈ 3, and with strong outputs in the 10–40 μm range. When combined with a low level of emission by carbon dust, their SEDs match that of Haro 11, a local moderately low-metallicity galaxy undergoing a very young and vigorous starburst that is likely to approximate the relevant conditions in young Population II galaxies. We expect to see similar SEDs at high redshifts (z ≳ 5) given the youth of galaxies at this epoch. In fact, we find a progression with redshift in observed galaxy SEDs, from those resembling local ones at 2 ≲ z &lt; 4 to a closer resemblance with Haro 11 at 5 ≲ z &lt; 7. In addition to the insight on conditions in high-redshift galaxies, this result implies that estimates of the total infrared luminosities at z ∼ 6 based on measurements near λ ∼ 1 mm can vary by factors of 2–4, depending on the SED template used. Currently popular modified blackbodies or local templates can result in significant underestimates compared with the preferred template based on the SED of Haro 11.