Cybernetic basis and system practice of remote sensing and spatial information science

Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level

Orbital Origin of Extremely Anisotropic Superconducting Gap in Nematic Phase of FeSe Superconductor

The iron-based superconductors are characterized by multiple-orbital physics where all the five Fe 3$d$ orbitals get involved. The multiple-orbital nature gives rise to various novel phenomena like orbital-selective Mott transition, nematicity and orbital fluctuation that provide a new route for realizing superconductivity. The complexity of multiple-orbital also asks to disentangle the relationship between orbital, spin and nematicity, and to identify dominant orbital ingredients that dictate superconductivity. The bulk FeSe superconductor provides an ideal platform to address these issues because of its simple crystal structure and unique coexistence of superconductivity and nematicity. However, the orbital nature of the low energy electronic excitations and its relation to the superconducting gap remain controversial. Here we report direct observation of highly anisotropic Fermi surface and extremely anisotropic superconducting gap in the nematic state of FeSe superconductor by high resolution laser-based angle-resolved photoemission measurements. We find that the low energy excitations of the entire hole pocket at the Brillouin zone center are dominated by the single $d_{xz}$ orbital. The superconducting gap exhibits an anti-correlation relation with the $d_{xz}$ spectral weight near the Fermi level, i.e., the gap size minimum (maximum) corresponds to the maximum (minimum) of the $d_{xz}$ spectral weight along the Fermi surface. These observations provide new insights in understanding the orbital origin of the extremely anisotropic superconducting gap in FeSe superconductor and the relation between nematicity and superconductivity in the iron-based superconductors.Comment: 19 pages, 4 figure

SARS-CoV-2 antibodies protect against reinfection for at least 6 months in a multicentre seroepidemiological workplace cohort

Identifying the potential for Severe Acute Respiratory Syndrome : Coronavirus 2 (SARS-CoV-2) reinfection is crucial for understanding possible long-term epidemic dynamics. We analysed longitudinal PCR and serological testing data from a prospective cohort of 4,411 United States employees in 4 states between April 2020 and February 2021. We conducted a multivariable logistic regression investigating the association between baseline serological status and subsequent PCR test result in order to calculate an odds ratio for reinfection. We estimated an odds ratio for reinfection ranging from 0.14 (95% CI: 0.019 to 0.63) to 0.28 (95% CI: 0.05 to 1.1), implying that the presence of SARS-CoV-2 antibodies at baseline is associated with around 72% to 86% reduced odds of a subsequent PCR positive test based on our point estimates. This suggests that primary infection with SARS-CoV-2 provides protection against reinfection in the majority of individuals, at least over a 6-month time period. We also highlight 2 major sources of bias and uncertainty to be considered when estimating the relative risk of reinfection, confounders, and the choice of baseline time point and show how to account for both in reinfection analysis

Moving Away or Fitting In? Understanding Shyness in Chinese Children

This paper reports on three studies of shy behavior in Mainland Chinese children. In Study 1 (N = 107, M age = 10.05), a Chinese Shyness Scale (CSS) was developed based on Chinese teachers’ open-ended descriptions of children’s shy behavior. In Study 2 (N = 388, M age = 10.80) and Study 3 (N = 198, M age = 10.20), the construct validity of the two forms of shyness that emerged in Study 1 (i.e., anxious shyness and regulated shyness) were examined in relation to children’s social preference, temperament, and psychosocial adjustment. A distinct pattern of results was found for anxious shyness and regulated shyness. The findings highlight the role of culture in shaping expression of children’s shy behavior

Thermal sensing using micro-ring resonators in optical network-on-chip

In this paper, we for the first time utilize the micro-ring resonators (MRs) in optical networks-on-chip (ONoCs) to implement thermal sensing without requiring additional hardware or chip area. The challenges in accuracy and reliability that arise from fabrication-induced process variations (PVs) and device-level wavelength tuning mechanism are resolved. We quantitatively model the intrinsic thermal sensitivity of MRs with finegrained consideration of wavelength tuning mechanism. Based on it, a novel PV-tolerant thermal sensor design is proposed. By exploiting the hidden `redundancy' in wavelength division multiplexing (WDM) technique, our sensor achieves accurate and efficient temperature measurement with the capability of PV tolerance. Evaluation results based on professional photonic component and circuit simulations show an average of 86.49% improvement in measurement accuracy compared to the state-of-the-art on-chip thermal sensing approach using MRs. Our thermal sensor achieves stable performance in the ONoCs employing dense WDM with an inaccuracy of only 0.8650 K.Published versionThis work is partially supported by NAP M4082282 and SUG M4082087 from Nanyang Technological University, HP-NTU Digital Manufacturing Corporate Lab, Singapore, and NSFC 61772094, China

Three‐dimensional chromatin landscapes in somatotroph tumour

Abstract Background The three‐dimensional (3D) genome architecture plays a critical role inregulating gene expression. However, the specific alterations in thisarchitecture within somatotroph tumors and their implications for gene expression remain largely unexplored. Methods We employed Hi‐C and RNA‐seq analyses to compare the 3D genomic structures of somatotroph tumors with normal pituitary tissue. This comprehensive approachenabled the characterization of A/B compartments, topologically associateddomains (TADs), and chromatin loops, integrating these with gene expression patterns. Results We observed a decrease in both the frequency of chromosomal interactions andthe size of TADs in tumor tissue compared to normal tissue. Conversely, the number of TADs and chromatin loops was found to be increased in tumors. Integrated analysis of Hi‐C and RNA‐seq data demonstrated that changes inhigher‐order chromat in structure were associated with alterations in gene expression. Specifically, genes in A compartments showed higher density and increased expression relative to those in B compartments. Moreover, the weakand enhanced insulation boundaries were identified, and the associated genes were enriched in the Wnt/β‐Catenin signaling pathway. We identified the gainedand lost loops in tumor and integrated these differences with transcriptional changes to examine the functional relevance of the identified loops. Notably, we observed an enhanced insulation boundary and a greater number of loops in the TCF7L2 gene region within tumors, which was accompanied by an upregulation of TCF7L2 expression. Subsequently, TCF7L2 expression was confirmed through qRT‐PCR, and upregulated TCF7L2 prompted cell proliferation and growth hormone (GH) secretion in vitro. Conclusion Our results provide comprehensive 3D chromatin architecture maps of somatotroph tumors and offer a valuable resource for furthering the understanding of the underlying biology and mechanisms of gene expression regulation

An adaptive multi‐mode switching control strategy to improve the stability of virtual synchronous generator with wide power grid strengths variation

Abstract With the increasing proportion of renewable power generations in the power system, the power grid impedance may fluctuate greatly, and it is difficult for the virtual synchronous generator (VSG) with a single control structure to meet the stability requirements. Thus, the control principles of the two types of VSGs are compared to conclude that there are similarities in the control structure of the two VSGs. And the small signal models of the two types of VSGs are established to analyze the stability boundaries, coming to the conclusion that the stability region is complementary. Based on the conclusions, the paper puts forward the idea of switching operation modes: switch to the U‐VSG mode when the grid strength weakens and switch to the PQ‐VSG mode when greater, so that the inverter can keep stable in a wider range of grid strength. Therefore, the characterization method of the switching boundary with hysteresis properties is proposed. Then the improved recursive least squares (RLS) algorithm is introduced to identify the power grid impedance online without additional injected disturbance, based on which the adaptive multi‐mode smooth switching control strategy is proposed. Finally, the effectiveness of the analysis and the control strategy are verified by simulations

GPM-Based Multitemporal Weighted Precipitation Analysis Using GPM_IMERGDF Product and ASTER DEM in EDBF Algorithm

To obtain the high-resolution multitemporal precipitation using spatial downscaling technique on a precipitation dataset may provide a better representation of the spatial variability of precipitation to be used for different purposes. In this research, a new downscaling methodology such as the global precipitation mission (GPM)-based multitemporal weighted precipitation analysis (GMWPA) at 0.05° resolution is developed and applied in the humid region of Mainland China by employing the GPM dataset at 0.1° and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m DEM-based geospatial predictors, i.e., elevation, longitude, and latitude in empirical distribution-based framework (EDBF) algorithm. The proposed methodology is a two-stepped process in which a scale-dependent regression analysis between each individual precipitation variable and the EDBF-based weighted precipitation with geospatial predictor(s), and to downscale the predicted multitemporal weighted precipitation at a refined scale is developed for the downscaling of GMWPA. While comparing results, it shows that the weighted precipitation outperformed all precipitation variables in terms of the coefficient of determination (R2) value, whereas they outperformed the annual precipitation variables and underperformed as compared to the seasonal and the monthly variables in terms of the calculated root mean square error (RMSE) value. Based on the achieved results, the weighted precipitation at the low-resolution (e.g., at 0.75° resolution) along-with the original resolution (e.g., at 0.1° resolution) is employed in the downscaling process to predict the average multitemporal precipitation, the annual total precipitation for the year 2001 and 2004, and the average annual precipitation (2001–2015) at 0.05° resolution, respectively. The downscaling approach resulting through proposed methodology captured the spatial patterns with greater accuracy at higher spatial resolution. This work showed that it is feasible to increase the spatial resolution of a precipitation variable(s) with greater accuracy on an annual basis or as an average from the multitemporal precipitation dataset using a geospatial predictor as the proxy of precipitation through the weighted precipitation in EDBF environment

Correction: Disruption of FGF5 in Cashmere Goats Using CRISPR/Cas9 Results in More Secondary Hair Follicles and Longer Fibers.

[This corrects the article DOI: 10.1371/journal.pone.0164640.]

Multi-Constrained Optimization Method of Line Segment Extraction Based on Multi-Scale Image Space

Image-based line segment extraction plays an important role in a wide range of applications. Traditional line segment extraction algorithms focus on the accuracy and efficiency, without considering the integrity. Serious line segmentation fracture problems caused by image quality will result in poor subsequent applications. To solve this problem, a multi-constrained line segment extraction method, based on multi-scale image space, is presented. Firstly, using Gaussian down-sampling with a classical line segment detection method, a multi-scale image space is constructed to extract line segments in each image scale and all line segments are projected onto the original image. Then, a new line segment optimization and purification strategy is proposed with the horizontal and vertical distances and angle geometric constraint relationships between line segments to merge fracture line segments and delete redundant line segments. Finally, line segments with adjacent positions are optimized using the grayscale constraint relationship, based on normalized cross-correlation similarity criterion for realizing the second optimization of fracture line segments. Compared with mainstream line segment detector and edge drawing lines methods, experimental results (i.e., indoor, outdoor, and aerial images) indicate the validity and superiority of our proposed methods which can extract longer and more complete line segments