Overlap Region Research Articles

Climate shifts orchestrated hominin interbreeding events across Eurasia.

When, where, and how often hominin interbreeding happened is largely unknown. We study the potential for Neanderthal-Denisovan admixture using species distribution models that integrate extensive fossil, archaeological, and genetic data with transient coupled general circulation model simulations of global climate and biomes. Our Pleistocene hindcast of past hominins' habitat suitability reveals pronounced climate-driven zonal shifts in the main overlap region of Denisovans and Neanderthals in central Eurasia. These shifts, which influenced the timing and intensity of potential interbreeding events, can be attributed to the response of climate and vegetation to past variations in atmospheric carbon dioxide and Northern Hemisphere ice-sheet volume. Therefore, glacial-interglacial climate swings likely played an important role in favoring gene flow between archaic humans.

Investigation of microstructural evolution in a hybrid additively manufactured steel bead

Abstract Motivated by the beneficial effects of friction stir processing (FSP) for microstructural grain refinement, equiaxed grain production, and minimizing metallurgical defects, additive bead (AB) produced by the gas metal arc welding-wire arc additive manufacturing (GMAW-WAAM) technique was subjected to FSP. This was because deposited additive bead often develops defects such as shrinkage, voids, solidification cracking, during liquid to solid transformation. In this study, a low carbon steel double pass additive bead with 32 % lateral overlap was fabricated by the GMAW-WAAM technique followed by hybridization through FSP in the overlapped region (OR). The peak temperature estimation during bead deposition and FSP on bead was done through modeling by using ABAQUS. The microstructural analysis was carried out by using optical microscopy, scanning electron microscopy, electron backscattered diffraction, and transmission electron microscopy. The microstructure of OR of deposited additive bead is dominated by a combination of ferrite and bainite while that of hybrid additive bead (HAB) is dominated by a combination of ferrite and martensite. Further, the analysis revealed the effects of FSP on the OR in the form of grain refinement from 5.56 µm to 3.50 µm and a decrease in the low angle grain boundaries from 35.4 % to 10.6 %. The continuous dynamic recrystallization is observed since the bainitic fraction in the overlapped region decreased along with an increase in the fraction of martensite in the friction stir processed zone. The kernel average misorientation is observed to decrease after FSP from 1.001 of AB to 0.608. The microhardness test reveals the decrease in the hardness after FSP.

GCMTN: Low-Overlap Point Cloud Registration Network Combining Dense Graph Convolution and Multilevel Interactive Transformer

A single receptive field limits the expression of multilevel receptive field features in point cloud registration, leading to the pseudo-matching of objects with similar geometric structures in low-overlap scenes, which causes a significant degradation in registration performance. To handle this problem, a point cloud registration network that incorporates dense graph convolution and a mutilevel interaction Transformer (GCMTN) in pursuit of better registration performance in low-overlap scenes is proposed in this paper. In GCMTN, a dense graph feature aggregation module is designed for expanding the receptive field of points and fusing graph features at multiple scales. To make pointwise features more discriminative, a multilevel interaction Transformer module combining Multihead Offset Attention and Multihead Cross Attention is proposed to refine the internal features of the point cloud and perform feature interaction. To filter out the undesirable effects of outliers, an overlap prediction module containing overlap factor and matching factor is also proposed for determining the match ability of points and predicting the overlap region. The final rigid transformation parameters are generated based on the distribution of the overlap region. The proposed GCMTN was extensively verified on publicly available ModelNet and ModelLoNet, 3DMatch and 3DLoMatch, and odometryKITTI datasets and compared with recent methods. The experimental results demonstrate that GCMTN significantly improves the capability of feature extraction and achieves competitive registration performance in low-overlap scenes. Meanwhile, GCMTN has value and potential for application in practical remote sensing tasks.

Mosaicing Technology for Airborne Wide Field-of-View Infrared Image

Multi-detector parallel scanning is derived from the traditional airborne panorama camera, and it has a great lateral field of view. A wide field-of-view camera can be used to obtain an area of remote sensing image by whisk broom mood during the flight. The adjacent image during acquisition should cover the overlap region according to the flight path, and then the regional image can be generated by image processing. Complexity and difficulty are increased during the regional image processing due to some interference factors of aircraft in flight. The overlap of the acquired regional image is constantly variable. Depending on the analysis of the imaging geometric principle of a wide field-of-view scanning camera, this paper proposes the rigorous geometric model of geoposition. The infrared image mosaic technology is proposed according to the features of regional images through the SIFT (Scale Invariant Feature Transform) operator to extract the two best-matching point pairs in the adjacent overlap region. We realize the coarse registration of adjacent images according to image translation, rotation, and a scale model of image geometric transformation, and then the local fine stitching is realized using the normalized cross-correlation matching strategy. The regional mosaic experiment of aerial multi-detector parallel scanning infrared image is processed to verify the feasibility and efficiency of the proposed algorithm.

Learning to concentrate: multi-tracer forecasts on local primordial non-Gaussianity with machine-learned bias

Local primordial non-Gaussianity (LPNG) is predicted by many non-minimal models of inflation, and creates a scale-dependent contribution to the power spectrum of large-scale structure (LSS) tracers, whose amplitude is characterized by bϕ .Knowledge of bϕ for the observed tracer population is therefore crucial for learning about inflation from LSS.Recently, it has been shown that the relationship between linear bias b1 and bϕ for simulated halos exhibits significant secondary dependence on halo concentration.We leverage this fact to forecast multi-tracer constraints on f loc NL.We train a machine learning model on observable properties of simulated IllustrisTNG galaxies to predict bϕ for samples constructed to approximate DESI emission line galaxies (ELGs) and luminous red galaxies (LRGs). We find σ(f loc NL) = 2.3, and σ(f loc NL = 3.7, respectively.These forecasted errors are roughly factors of 3, and 35% improvements over the single-tracer case for each sample, respectively.When considering both ELGs and LRGs in their overlap region, we forecast σ(f loc NL) = 1.5 is attainable with our learned model, more than a factor of 3 improvement over thesingle-tracer case,while the ideal split by bϕ could reach σ(f loc NL) < 1.We also perform multi-tracer forecasts for upcoming spectroscopic surveys targeting LPNG (MegaMapper, SPHEREx) and show that splitting tracer samples by bϕ can lead to an order-of-magnitude reduction in projected σ(f loc NL for these surveys.

High-fidelity numerical model of melt pool dynamics in selective multi-laser melting of Inconel 718 under different scanning strategies

The application of multi-laser scanning technology to additive manufacturing is one of the important means to improve its printing efficiency of additive manufacturing. Therefore, it is of great significance to study the evolution law of overlap region between multi-laser melt pools under different scanning strategies. Based on the discrete element-computational fluid dynamics method, the dynamic evolution of melt pools in the selective multi-laser melting (SMLM) is studied at the particle scale when two lasers scan the powder bed in the opposite (DL_O) or the same (DL_S) directions. The influence of laser spacing in SMLM with DL_O scanning on the melt pool dynamic behavior of the overlap region for Inconel 718 is especially investigated. The result shows that, in the SMLM process with DL_O scanning, when the laser spacing is 2–3 times the laser beam radius of 27 µm, the melt pools in the overlap region completely merge without obvious boundary lines, resulting in good surface quality and higher density of the product, which is consistent with that in DL_S scanning. Although the disordered flow may result in poor texture of the part manufactured by SMLM with DL_O, it can promote the melt pools to merge sufficiently in the overlap area to reduce the risk of inter-track defects. The thermal-mechanical finite element method at process-level is also used to examine the distribution of temperature and stress fields during multi-layer multi-track dual-laser printing under these two scanning strategies. The stress distribution is found to be significantly different under the DL_O and DL_S scanning strategies, so the residual stress in SMLM can be reduced by ingeniously using these two scanning methods in different zones and layers. Therefore, this work provides a clue on how to optimize the SMLM process.

Generating indistinguishability within identical particle systems: spatial deformations as quantum resource activators.

Identical quantum subsystems can possess a property which does not have any classical counterpart: indistinguishability. As a long-debated phenomenon, identical particles' indistinguishability has been shown to be at the heart of various fundamental physical results. When concerned with the spatial degree of freedom, identical constituents can be made indistinguishable by overlapping their spatial wave functions via appropriately defined spatial deformations. By the laws of quantum mechanics, any measurement designed to resolve a quantity which depends on the spatial degree of freedom only and performed on the regions of overlap is not able to assign the measured outcome to one specific particle within the system. The result is an entangled state where the measured property is shared between the identical constituents. In this work, we present a coherent formalization of the concept of deformation in a general [Formula: see text]-particle scenario, together with a suitable measure of the degree of indistinguishability. We highlight the basic differences with non-identical particles scenarios and discuss the inherent role of spatial deformations as entanglement activators within the spatially localized operations and classical communication operational framework. This article is part of the theme issue 'Identity, individuality and indistinguishability in physics and mathematics'.

Corrosion behaviour of hot-rolled 316L stainless steel-A6 carbon steel composite steel plate for marine environment

In this study, a composite steel plate for marine construction was fabricated using 316L stainless steel and A6 carbon steel through hot rolling. Neutral salt spray tests and electrochemical experiments were performed to analyse the corrosion behaviours of the cladding material, the carbon steel substrate, and the interface between stainless steel and carbon steel in a marine atmosphere and seawater. The results showed that an evident elemental overlap region was observed at the composite interface of the composite steel plate. After long salt spray test, the A6 carbon steel part showed significant accelerated corrosion along the interface, resulting in the interface specimens corroding at a faster rate than the carbon steel substrate. However, the composite interface showed better corrosion resistance than the carbon steel substrate in the electrochemical tests. A corrosion resistant layer with a width of 15 μm was found on the stainless-steel side of the composite interface.

A hybrid discrete exterior calculus and finite difference method for Boussinesq convection in spherical shells

We present a new hybrid discrete exterior calculus (DEC) and finite difference (FD) method to simulate fully three-dimensional Boussinesq convection in spherical shells subject to internal heating and basal heating, relevant in the planetary and stellar phenomenon. We employ DEC to compute the surface spherical flows, taking advantage of its unique features including coordinate system independence to preserve the spherical geometry, while we discretize the radial direction using FD method. The grid employed for this novel method is free of problems like the coordinate singularity, grid non-convergence near the poles, and the overlap regions. We have developed a parallel in-house code using the PETSc framework to verify the hybrid DEC-FD formulation and demonstrate convergence. We have performed a series of numerical tests which include quantification of the critical Rayleigh numbers for spherical shells characterized by aspect ratios ranging from 0.2 to 0.8, simulation of robust convective patterns in addition to stationary giant spiral roll covering all the spherical surface in moderately thin shells near the weakly nonlinear regime, and the quantification of Nusselt and Reynolds numbers for basally heated spherical shells.

Non-uniform Compact Schemes for Parallel Computing

Here, the performance of a sixth order accurate Non-Uniform Compact Scheme (NUCS6) in a parallel framework using the domain decomposition method is analyzed. Traditional compact schemes are used for uniform grids. However, study of flows involving complicated geometries requires transformation of computational domain onto a uniform grid. Compact schemes developed for physical plane computations eliminate the need for such grid transformations. The first successful implementation of uniform compact schemes on a parallelized framework with Schwartz domain decomposition demonstrated the effect of overlap points in eliminating spurious signals at inter-processor boundaries Sengupta et al. [Jour. Comp. Phy. 220 (2007)]. This paper presents the performance of a high order non-uniform compact scheme (NUCS6) in parallel computations with the domain decomposition method. The results of the benchmark problem of flow in a 2D square lid-driven cavity at post-Hopf bifurcation Reynolds number of 10000 is presented to show how the width of overlap region affects the growth and evolution of gyrating polygonal vortex at the centre of the cavity.

Integrating plan complexity and dosiomics features with deep learning in patient-specific quality assurance for volumetric modulated arc therapy

PurposeTo investigate the feasibility and performance of deep learning (DL) models combined with plan complexity (PC) and dosiomics features in the patient-specific quality assurance (PSQA) for patients underwent volumetric modulated arc therapy (VMAT).MethodsTotal of 201 VMAT plans with measured PSQA results were retrospectively enrolled and divided into training and testing sets randomly at 7:3. PC metrics were calculated using house-built algorithm based on Matlab. Dosiomics features were extracted and selected using Random Forest (RF) from planning target volume (PTV) and overlap regions with 3D dose distributions. The top 50 dosiomics and 5 PC features were selected based on feature importance screening. A DL DenseNet was adapted and trained for the PSQA prediction.ResultsThe measured average gamma passing rate (GPR) of these VMAT plans was 97.94% ± 1.87%, 94.33% ± 3.22%, and 87.27% ± 4.81% at the criteria of 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively. Models with PC features alone demonstrated the lowest area under curve (AUC). The AUC and sensitivity of PC and dosiomics (D) combined model at 2%/2 mm were 0.915 and 0.833, respectively. The AUCs of DL models were improved from 0.943, 0.849, 0.841 to 0.948, 0.890, 0.942 in the combined models (PC + D + DL) at 3%/3 mm, 3%/2 mm and 2%/2 mm, respectively. A best AUC of 0.942 with a sensitivity, specificity and accuracy of 100%, 81.8%, and 83.6% was achieved with combined model (PC + D + DL) at 2%/2 mm.ConclusionsIntegrating DL with dosiomics and PC metrics is promising in the prediction of GPRs in PSQA for patients underwent VMAT.

17q25.3 copy number changes: association with neurodevelopmental disorders and cardiac malformation

Copy number variants (CNVs) have been identified as common genomic variants that play a significant role in inter-individual variability. Conversely, rare recurrent CNVs have been found to be causal for many disorders with well-established genotype–phenotype relationships. However, the phenotypic implications of rare non-recurrent CNVs remain poorly understood. Herein, we re-investigated 18,542 cases reported from chromosomal microarray at Greenwood Genetic Center from 2010 to 2022 and identified 15 cases with CNVs involving the 17q25.3 region. We report the detailed clinical features of these subjects, and compare with the cases reported in the literature to determine genotype–phenotype correlations for a subset of genes in this region. The CNVs in the 17q25.3 region were found to be rare events, with a prevalence of 0.08% (15/18542) observed in our cohort. The CNVs were dispersed across the entire 17q25.3 region with variable breakpoints and no smallest region of overlap. The subjects presented with a wide range of clinical features, with neurodevelopmental disorders (autism spectrum disorder, intellectual disability, developmental delay) being the most common features (80%), then expressive language disorder (33%), and finally cardiovascular malformations (26%). The association of CNVs involving the critical gene-rich region of 17q25.3 with neurodevelopmental disorders and cardiac malformation, implicates several genes as plausible drivers for these events.

Description and phylogenetic analysis of the complete mitochondrial genome in Eulaelaps silvestris provides new insights into the molecular classification of the family Haemogamasidae.

In this study, the mitochondrial genome of Eulaelaps silvestris, which parasitizes Apodemus chevrieri, was sequenced and assembled to fill the gap in understanding the molecular evolution of the genus Eulaelaps. The E. silvestris mitochondrial genome is a double-stranded DNA molecule with a length of 14 882 bp, with a distinct AT preference for base composition and a notably higher AT content than GC content. The arrangement between genes is relatively compact, with a total of 10 gene intergenic regions and 12 gene overlap regions. All protein-coding genes had a typical ATN initiation codon, and only 2 protein-coding genes had an incomplete termination codon T. Out of the 13 protein-coding genes, the 5 most frequently used codons ended in A/U, with only 1 codon ending in G/C had an relative synonymous codon usage value >1. Except for trnS1 and trnS2, which lacked the D arm, all other tRNAs were able to form a typical cloverleaf structure; and there were a total of 38 mismatches in the folding process of tRNA genes. Unlike the gene arrangement order of the arthropod hypothetical ancestor, the E. silvestris mitochondrial genome underwent fewer rearrangements, mainly near tRNA genes and control regions. Both the maximum likelihood tree and the Bayesian tree showed that the family Haemogamasidae is most closely related to the family Dermanyssidae. The results not only provide a theoretical basis for studying the phylogenetic relationships of the genus Eulaelaps, but also provide molecular evidence that the family Haemogamasidae does not belong to the subfamily Laelapidae.

Evidence of Improved Thermal Stability via Nanoscale Contact Engineering in IGZO Source-Gated Thin-Film Transistors

Despite rapidly expanding interest in thin-film source-gated transistors (SGTs), the high-temperature dependence of drain current (TDDC) in devices comprising Schottky source barriers is delaying wide adoption. To reduce this effect, alternative source designs have been theorized. Specifically, introducing additional nanoscale layers at the source contact should facilitate the tunneling of charge carriers at the Fermi energy level with negligible TDDC. Here, we fabricate amorphous In <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{\text{2}}$</tex-math> </inline-formula> Ga <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{\text{2}}$</tex-math> </inline-formula> ZnO <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{\text{7}}$</tex-math> </inline-formula> tunnel-contact SGTs (TC-SGTs) with three times lower TDDC than polysilicon transistors with Schottky contacts. Numerical simulations help elucidate the control mechanisms. We show that the potential profile across the semiconductor in the bulk of the source-gate overlap region determines injection current, and the introduction of a thin interfacial layer at the contact reduces the role of the contact metal work function (WF) in current control and associated temperature effects. This device architecture adds improved thermal stability to the long list of SGT benefits, including low voltage saturation, power-efficient operation, high intrinsic gain, device-to-device uniformity, and robustness to mechanical and electrical stress.

Causal calibration: iteratively calibrating LiDAR and camera by considering causality and geometry

AbstractThe external calibration between 3D LiDAR and 2D camera is an extremely important step towards multimodal fusion for robot perception. However, its accuracy is still unsatisfactory. To improve the accuracy of calibration, we first analyze the interference factors that affect the performance of the calibration model under a causal inference framework in this study. Guided by the causality analysis, we present Iter-CalibNet (Iterative Calibration Convolutional Neural Network) to infer a 6 degrees of freedom (DoF) rigid body transformation between 3D LiDAR and 2D camera. By downscaling point clouds to obtain more overlapping region between 3D–2D data pair and applying iterative calibration manner, the interference of confounding bias in the calibration model is effectively eliminated. Moreover, our Iter-CalibNet adds non-local neural network after each convolution operation to capture the transformation relationship. We also combine the geometric loss and photometric loss obtained from the interframe constraints to optimize the calibration accuracy. Extensive experiments demonstrate that our Iter-CalibNet can achieve leading performance by comparison with other CNN based and traditional calibration methods.

&lt;span&gt;MOLECULAR CHARACTERISTICS OF NOROVIRUS IN ASIATIC HARD CLAM IN HANOI IN 2016&lt;/span&gt;

Aims: Norovirus (NoV) is a common foodborne virus in bivalve molluscs. This study aimed to identify genotypes of NoV genogroups I and II (GI and GII) in Asiatic hard clam (Meretrix meretrix) marketed in Hanoi, Viet Nam, in 2016. Methods: A total of 39 Asiatic hard clam samples positive for NoV GI and/or NoV GII was genotyped using nested RT-PCR targeting fragment spanning the ORF1/ORF2 overlap region. PCR products were sequenced using Sanger sequencing and phylogenetic analysis was carried out using MEGA 11 software. Results: NoV genotyping has been successfully performed for 23 samples. For NoV GI, four genotypes were detected: GI.2 (13.3%), GI.5 (46.7%), GI.6 (33.3%) and GI.8 (6.7%). We found five distinct genotypes of NoV GII, including GII.3 (61.1%), GII.4 (11.1%), GII.6 (11.1%), GII.13 (11.1%) and GII.17 (5.6%). Phylogenetic analysis revealed these NoV genotypes displayed high similarity with clinical strains circulating worldwide, especially strains from Asian countries. Conclusions: The contamination of NoV GI and NoV GII in Asiatic hard clams in Hanoi was complex with multiple genotypes. Two worldwide epidemic genotypes GII.4 and GII.17 were identified in the present study, however, the dominant NoV genotypes were GI.5 and GII.3.

Pixel-Wise Warping for Deep Image Stitching

Existing image stitching approaches based on global or local homography estimation are not free from the parallax problem and suffer from undesired artifacts. In this paper, instead of relying on the homography-based warp, we propose a novel deep image stitching framework exploiting the pixel-wise warp field to handle the large-parallax problem. The proposed deep image stitching framework consists of a Pixel-wise Warping Module (PWM) and a Stitched Image Generating Module (SIGMo). For PWM, we obtain pixel-wise warp in a similar manner as estimating an optical flow (OF). In the stitching scenario, the input images usually include non-overlap (NOV) regions of which warp cannot be directly estimated, unlike the overlap (OV) regions. To help the PWM predict a reasonable warp on the NOV region, we impose two geometrical constraints: an epipolar loss and a line-preservation loss. With the obtained warp field, we relocate the pixels of the target image using forward warping. Finally, the SIGMo is trained by the proposed multi-branch training framework to generate a stitched image from a reference image and a warped target image. For training and evaluating the proposed framework, we build and publish a novel dataset including image pairs with corresponding pixel-wise ground truth warp and stitched result images. We show that the results of the proposed framework are quantitatively and qualitatively superior to those of the conventional methods.

Dysphagia at 1 Year is Associated With Mean Dose to the Inferior Section of the Brain Stem

Dysphagia is a common toxicity after head and neck (HN) radiation therapy that negatively affects quality of life. We explored the relationship between radiation therapy dose to normal HN structures and dysphagia 1 year after treatment using image-based datamining (IBDM), a voxel-based analysis technique. We used data from 104 patients with oropharyngeal cancer treated with definitive (chemo)radiation therapy. Swallow function was assessed pretreatment and 1 year posttreatment using 3 validated measures: MD Anderson Dysphagia Inventory (MDADI), performance status scale for normalcy of diet (PSS-HN), and water swallowing test (WST). For IBDM, we spatially normalized all patients' planning dose matrices to 3 reference anatomies. Regions where the dose was associated with dysphagia measures at 1 year were found by performing voxel-wise statistics and permutation testing. Clinical factors, treatment variables, and pretreatment measures were used in multivariable analysis to predict each dysphagia measure at 1 year. Clinical baseline models were found using backward stepwise selection. Improvement in model discrimination after adding the mean dose to the identified region was quantified using the Akaike information criterion. We also compared the prediction performance of the identified region with a well-established association: mean doses to the pharyngeal constrictor muscles. IBDM revealed highly significant associations between dose to distinct regions and the 3 outcomes. These regions overlapped around the inferior section of the brain stem. All clinical models were significantly improved by including mean dose to the overlap region (P ≤ .006). Including pharyngeal dosimetry significantly improved WST (P=.04) but not PSS-HN or MDADI (P ≥ .06). In this hypothesis-generating study, we found that mean dose to the inferior section of the brain stem is strongly associated with dysphagia 1 year posttreatment. The identified region includes the swallowing centers in the medulla oblongata, providing a possible mechanistic explanation. Further work including validation in an independent cohort is required.

Measuring the X-ray luminosities of DESI groups from eROSITA Final Equatorial-Depth Survey – I. X-ray luminosity–halo mass scaling relation

ABSTRACT We use the eROSITA Final Equatorial-Depth Survey (eFEDS) to measure the rest-frame 0.1–2.4 keV band X-ray luminosities of ∼600 000 DESI groups using two different algorithms in the overlap region of the two observations. These groups span a large redshift range of 0.0 ≤ zg ≤ 1.0 and group mass range of $10^{10.76}\, h^{-1}\, \mathrm{M}_{\odot } \le M_h \le 10^{15.0}\, h^{-1}\, \mathrm{M}_{\odot }$. (1) Using the blind detection pipeline of eFEDS, we find that 10932 X-ray emission peaks can be cross-matched with our groups, ∼38 per cent of which have a signal-to-noise ratio $\rm {S}/\rm {N} \ge 3$ in X-ray detection. Comparing to the numbers reported in previous studies, this matched sample size is a factor of ∼6 larger. (2) By stacking X-ray maps around groups with similar masses and redshifts, we measure the average X-ray luminosity of groups as a function of halo mass in five redshift bins. We find that in a wide halo mass range, the X-ray luminosity, LX, is roughly linearly proportional to Mh and quite independent to the redshift of the groups. (3) We use a Poisson distribution to model the X-ray luminosities obtained using two different algorithms and obtain the best-fit $L_{\rm X}=10^{28.46\pm 0.03}M_{\rm h}^{1.024\pm 0.002}$ and $L_{\rm X}=10^{26.73 \pm 0.04}M_{\rm h}^{1.140 \pm 0.003}$ scaling relations, respectively. The best-fit slopes are flatter than the results previously obtained but closer to a self-similar prediction.

ICON-P - A double-blind evaluation of quality improvements with individualized CONstraints from low-cost knowledge-based radiation therapy planning in prostate cancer.

/Objective(S)A low-cost, prior knowledge-based individualized dose-constraint generator for organs-at-risk has been developed for prostate cancer radiation therapy (RT) planning. In this study, we aimed to evaluate the feasibility and improvements in organs-at-risk (OAR) doses in prostate cancer RT planning using this tool served on a web application. A set of previously treated prostate cancer cases planned and treated with generic constraints were replanned using individualized dose constraints derived from a library of cases with similar volumes of target, OAR, and overlap regions and served on the web-based application. The goal was to assess the reduction in mean dose, specified dose volumes (V59Gy, V56Gy, V53Gy, V47Gy, and V40Gy), and generalized equivalent uniform dose (gEUD) to the rectum and bladder. Planners and assessors were blinded to the initial achieved doses and penalties. Sample size estimation was based on improvement in V53Gy for the rectum and bladder with a paired evaluation. Twenty-four patients were replanned. All the plans had a PTV D95 of at least 97% of the prescribed dose. The individualized OAR constraints could be met for 87.5% of patients for all dose levels. The mean dose, V59Gy, V53Gy, and V47Gy for the bladder was reduced by 7.5Gy, 1.12%, 5.51%, and 10.53% respectively. Similarly for the rectum, the mean dose, V59Gy, V53Gy, V47Gy and was reduced by 5.5Gy, 4.34%, 6.97%, and 11.61% respectively. All dose reductions were statistically significant. The gEUD of the bladder was reduced by 2.47Gy (p<0.001) and the rectum by 3.21Gy (p<0.001). Treatment planning based on individualized dose constraints served on a web application is feasible and leads to improvement at clinically important dose volumes in prostate cancer RT planning. This application can be served publicly for improvements in RT plan quality.