Composite Match Index with Application of Interior Deformation Field Measurement from Magnetic Resonance Volumetric Images of Human Tissues

Whereas a variety of different feature-point matching approaches have been reported in computer vision, few feature-point matching approaches employed in images from nonrigid, nonuniform human tissues have been reported. The present work is concerned with interior deformation field measurement of complex human tissues from three-dimensional magnetic resonance (MR) volumetric images. To improve the reliability of matching results, this paper proposes composite match index (CMI) as the foundation of multimethod fusion methods to increase the reliability of these various methods. Thereinto, we discuss the definition, components, and weight determination of CMI. To test the validity of the proposed approach, it is applied to actual MR volumetric images obtained from a volunteer’s calf. The main result is consistent with the actual condition

Automatic Object-Oriented, Spectral-Spatial Feature Extraction Driven by Tobler’s First Law of Geography for Very High Resolution Aerial Imagery Classification

(This article belongs to the Special Issue Recent Trends in UAV Remote Sensing)Aerial image classification has become popular and has attracted extensive research efforts in recent decades. The main challenge lies in its very high spatial resolution but relatively insufficient spectral information. To this end, spatial-spectral feature extraction is a popular strategy for classification. However, parameter determination for that feature extraction is usually time-consuming and depends excessively on experience. In this paper, an automatic spatial feature extraction approach based on image raster and segmental vector data cross-analysis is proposed for the classification of very high spatial resolution (VHSR) aerial imagery. First, multi-resolution segmentation is used to generate strongly homogeneous image objects and extract corresponding vectors. Then, to automatically explore the region of a ground target, two rules, which are derived from Tobler’s First Law of Geography (TFL) and a topological relationship of vector data, are integrated to constrain the extension of a region around a central object. Third, the shape and size of the extended region are described. A final classification map is achieved through a supervised classifier using shape, size, and spectral features. Experiments on three real aerial images of VHSR (0.1 to 0.32 m) are done to evaluate effectiveness and robustness of the proposed approach. Comparisons to state-of-the-art methods demonstrate the superiority of the proposed method in VHSR image classification.Peer Reviewe

Dynamical Behaviors of Stochastic Hopfield Neural Networks with Both Time-Varying and Continuously Distributed Delays

This paper investigates dynamical behaviors of stochastic Hopfield neural networks with both time-varying and continuously distributed delays. By employing the Lyapunov functional theory and linear matrix inequality, some novel criteria on asymptotic stability, ultimate boundedness, and weak attractor are derived. Finally, an example is given to illustrate the correctness and effectiveness of our theoretical results

Plan4MC: Skill Reinforcement Learning and Planning for Open-World Minecraft Tasks

We study building a multi-task agent in Minecraft. Without human demonstrations, solving long-horizon tasks in this open-ended environment with reinforcement learning (RL) is extremely sample inefficient. To tackle the challenge, we decompose solving Minecraft tasks into learning basic skills and planning over the skills. We propose three types of fine-grained basic skills in Minecraft, and use RL with intrinsic rewards to accomplish basic skills with high success rates. For skill planning, we use Large Language Models to find the relationships between skills and build a skill graph in advance. When the agent is solving a task, our skill search algorithm walks on the skill graph and generates the proper skill plans for the agent. In experiments, our method accomplishes 24 diverse Minecraft tasks, where many tasks require sequentially executing for more than 10 skills. Our method outperforms baselines in most tasks by a large margin. The project's website and code can be found at https://sites.google.com/view/plan4mc.Comment: 19 page

Structured sonic tube with carbon nanotube like topological edge states

A single-wall carbon nanotube can be viewed as a one-dimensional material created by rolling up a sheet of graphene. Its electronic band structure depends on the chirality, i.e., how the sheet has been rolled up, yet synthesizing the symmetry at will is rather challenging. We structure an artificial honeycomb lattice in both a zigzag and an armchair tube and explore their topological features for sound. Our findings reveal how armchair tubes remain gapless, whereas the zigzag counterparts host nontrivial edge states of non-zero quantized Zak phase, which are dictated by the circumferential number of units. Unlike man-made planar lattices whose underling symmetry must be broken to harvest quantum Hall and pseudospin phases, interestingly, the structured tubular lattice symmetry remains intact, while its nontrivial phase alone is governed by the chirality and the tube diameter. We foresee that our results, not only for sound, but also in photonics, mechanics and electronics will broaden future avenues for fundamental and applied sciencesThis work was supported by the National Basic Research Program of China (2017YFA0303702), NSFC (12074183, 11922407, 11834008, 11874215, 12104226, and 12225408), and the Fundamental Research Funds for the Central Universities (020414380181). Z.Z. acknowledges the support from the China National Postdoctoral Program for Innovative Talents (BX20200165), the China Postdoctoral Science Foundation (2020M681541), Jiangsu Planned Projects for Postdoctoral Research Funds (2021K054A), and Funds for Zijin Scholars of Nanjing University. J.C. acknowledges the support from the European Research Council (ERC) through the Starting Grant 714577 PHONOMETA and from the MINECO through a Ramón y Cajal grant (Grant No. RYC-2015-17156)

Theory of non-Hermitian topological whispering gallery

Topological insulators have taken the condensed matter physics scenery by storm and captivated the interest among scientists and materials engineers alike. Surprisingly, this arena which was initially established and profoundly studied in electronic systems and crystals, has sparked a drive among classical physicists to pursue a wave-based analogy for sound, light and vibrations. In the latest efforts combining valley-contrasting topological sound with non-Hermitian ingredients, B. Hu et al. [Nature 597, 655 (2021)] employed thermoacoustic coupling in sonic lattices whose elementary building blocks are coated with electrically biased carbon nanotube films. In this contribution, we take a theoretical and numerical route towards understanding the complex acoustic interplay between geometry and added acoustic gain as inspired by the aforesaid publication. Besides complex bulk and edge states predictions and computations of mode-split resonances using whispering gallery configurations, we also predict an acoustic amplitude saturation in dependence on the activated coated elements. We foresee that our computational advances may assist future efforts in exploring thermoacoustic topological properties.We acknowledge the support from the European Research Council (ERC) through the Starting Grant No. 714577 PHONOMETA. R.P.S. acknowledges support from the CONEX-Plus programme funded by Universidad Carlos III de Madrid and the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 801538. Z.Z., Y.C., and X.L. acknowledge the support from the National Natural Science Foundation of China (Nos. 12074183, 11922407, 11834008, 12225408, and 12104226) and the Fundamental Research Funds for the Central Universities (No. 020414380181)

Land Cover Change Detection Based on Adaptive Contextual Information Using Bi-Temporal Remote Sensing Images

Land cover change detection (LCCD) based on bi-temporal remote sensing images plays an important role in the inventory of land cover change. Due to the benefit of having spatial dependency properties within the image space while using remote sensing images for detecting land cover change, many contextual information-based change detection methods have been proposed in past decades. However, there is still a space for improvement in accuracies and usability of LCCD. In this paper, a LCCD method based on adaptive contextual information is proposed. First, an adaptive region is constructed by gradually detecting the spectral similarity surrounding a central pixel. Second, the Euclidean distance between pairwise extended regions is calculated to measure the change magnitude between the pairwise central pixels of bi-temporal images. All the bi-temporal images are scanned pixel by pixel so the change magnitude image (CMI) can be generated. Then, the Otsu or a manual threshold is employed to acquire the binary change detection map (BCDM). The detection accuracies of the proposed approach are investigated by three land cover change cases with Landsat bi-temporal remote sensing images and aerial images with very high spatial resolution (0.5 m/pixel). In comparison to several widely used change detection methods, the proposed approach can produce a land cover change inventory map with a competitive accuracyThis work was supported by the National Science Foundation China (61701396), the Natural Science Foundation of Shaan Xi Province (2017JQ4006), Engineering Research Center of Geospatial Information and Digital Technology, NASG (SIDT20171003), The National Key Research and Development Program of China(018YFF0215006), Natural Science Foundation of Jiangsu Province, China (BK20150835), and Tibet Natural Science Foundation-The study of Tibet crop condition monitoring based on crop growth model and multi-source remote sensing data (2016-ZR-15-18).Peer Reviewe

Association between dietary inflammatory index and risk of endometriosis: A population-based analysis

Background and aimsChronic inflammation plays a significant role in the etiology of endometriosis, which might be affected by dietary intake. This study aimed to investigate the association between dietary inflammatory index (DII) and the risk of endometriosis.MethodsA cross-sectional analysis using data from the National Health and Nutrition Examination Survey (1999–2006) was conducted on 3,410 American participants, among whom 265 reported a diagnosis of endometriosis. DII scores were calculated based on the dietary questionnaire. The association of DII scores with endometriosis was evaluated by adjusted multivariate logistic regression analyzes, which were further investigated in the subgroups.ResultsIn the fully adjusted models, the odds ratio (OR) for endometriosis participants in the highest and middle tertiles of DII scores were 1.57 [95% confidence interval (CI): 1.14–2.17] and 1.18 (95% CI: 0.84–1.65), compared to the lowest tertile (Ptrend = 0.007). In subgroup analyzes, the significant positive association between DII scores and the endometriosis risk was also observed in non-obese women (ORtertile3vs1: 1.69, 95% CI: 1.12–2.55; Ptrend = 0.012), women without diabetes (ORtertile3vs1: 1.62, 95% CI: 1.16–2.27; Ptrend = 0.005), women with hypertension (ORtertile3vs1: 2.25, 95% CI: 1.31–3.87; Ptrend = 0.003), parous women (ORtertile3vs1: 1.55, 95% CI: 1.11–2.17; Ptrend = 0.011), and women using oral contraceptives (ORtertile3vs1: 1.63, 95% CI: 1.15–2.30; Ptrend = 0.006).ConclusionThis nationally representative study found that increased intake of the pro-inflammatory diet, as a higher DII score, was positively associated with endometriosis risk among American adults. Our results suggested anti-inflammatory dietary interventions may be promising in the prevention of endometriosis. Further prospective studies are necessary to confirm these findings

cGMP-independent nitric oxide signaling and regulation of the cell cycle

BACKGROUND: Regulatory functions of nitric oxide (NO(•)) that bypass the second messenger cGMP are incompletely understood. Here, cGMP-independent effects of NO(• )on gene expression were globally examined in U937 cells, a human monoblastoid line that constitutively lacks soluble guanylate cyclase. Differentiated U937 cells (>80% in G0/G1) were exposed to S-nitrosoglutathione, a NO(• )donor, or glutathione alone (control) for 6 h without or with dibutyryl-cAMP (Bt(2)cAMP), and then harvested to extract total RNA for microarray analysis. Bt(2)cAMP was used to block signaling attributable to NO(•)-induced decreases in cAMP. RESULTS: NO(• )regulated 110 transcripts that annotated disproportionately to the cell cycle and cell proliferation (47/110, 43%) and more frequently than expected contained AU-rich, post-transcriptional regulatory elements (ARE). Bt(2)cAMP regulated 106 genes; cell cycle gene enrichment did not reach significance. Like NO(•), Bt(2)cAMP was associated with ARE-containing transcripts. A comparison of NO(• )and Bt(2)cAMP effects showed that NO(• )regulation of cell cycle genes was independent of its ability to interfere with cAMP signaling. Cell cycle genes induced by NO(• )annotated to G1/S (7/8) and included E2F1 and p21/Waf1/Cip1; 6 of these 7 were E2F target genes involved in G1/S transition. Repressed genes were G2/M associated (24/27); 8 of 27 were known targets of p21. E2F1 mRNA and protein were increased by NO(•), as was E2F1 binding to E2F promoter elements. NO(• )activated p38 MAPK, stabilizing p21 mRNA (an ARE-containing transcript) and increasing p21 protein; this increased protein binding to CDE/CHR promoter sites of p21 target genes, repressing key G2/M phase genes, and increasing the proportion of cells in G2/M. CONCLUSION: NO(• )coordinates a highly integrated program of cell cycle arrest that regulates a large number of genes, but does not require signaling through cGMP. In humans, antiproliferative effects of NO(• )may rely substantially on cGMP-independent mechanisms. Stress kinase signaling and alterations in mRNA stability appear to be major pathways by which NO(• )regulates the transcriptome

Reduced anthropogenic aerosol radiative forcing caused by biogenic new particle formation

The magnitude of aerosol radiative forcing caused by anthropogenic emissions depends on the baseline state of the atmosphere under pristine preindustrial conditions. Measurements show that particle formation in atmospheric conditions can occur solely from biogenic vapors. Here, we evaluate the potential effect of this source of particles on preindustrial cloud condensation nuclei (CCN) concentrations and aerosol-cloud radiative forcing over the industrial period. Model simulations show that the pure biogenic particle formation mechanism has a much larger relative effect on CCN concentrations in the preindustrial atmosphere than in the present atmosphere because of the lower aerosol concentrations. Consequently, preindustrial cloud albedo is increased more than under present day conditions, and therefore the cooling forcing of anthropogenic aerosols is reduced. The mechanism increases CCN concentrations by 20-100% over a large fraction of the preindustrial lower atmosphere, and the magnitude of annual global mean radiative forcing caused by changes of cloud albedo since 1750 is reduced by 0.22 W m-2 (27%) to -0.60 W m-2. Model uncertainties, relatively slow formation rates, and limited available ambient measurements make it difficult to establish the significance of a mechanism that has its dominant effect under preindustrial conditions. Our simulations predict more particle formation in the Amazon than is observed. However, the first observation of pure organic nucleation has now been reported for the free troposphere. Given the potentially significant effect on anthropogenic forcing, effort should be made to better understand such naturally driven aerosol processes