Remote Sensing of Environmental Changes in Cold Regions

This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing

STFNets: Learning Sensing Signals from the Time-Frequency Perspective with Short-Time Fourier Neural Networks

Recent advances in deep learning motivate the use of deep neural networks in Internet-of-Things (IoT) applications. These networks are modelled after signal processing in the human brain, thereby leading to significant advantages at perceptual tasks such as vision and speech recognition. IoT applications, however, often measure physical phenomena, where the underlying physics (such as inertia, wireless signal propagation, or the natural frequency of oscillation) are fundamentally a function of signal frequencies, offering better features in the frequency domain. This observation leads to a fundamental question: For IoT applications, can one develop a new brand of neural network structures that synthesize features inspired not only by the biology of human perception but also by the fundamental nature of physics? Hence, in this paper, instead of using conventional building blocks (e.g., convolutional and recurrent layers), we propose a new foundational neural network building block, the Short-Time Fourier Neural Network (STFNet). It integrates a widely-used time-frequency analysis method, the Short-Time Fourier Transform, into data processing to learn features directly in the frequency domain, where the physics of underlying phenomena leave better foot-prints. STFNets bring additional flexibility to time-frequency analysis by offering novel nonlinear learnable operations that are spectral-compatible. Moreover, STFNets show that transforming signals to a domain that is more connected to the underlying physics greatly simplifies the learning process. We demonstrate the effectiveness of STFNets with extensive experiments. STFNets significantly outperform the state-of-the-art deep learning models in all experiments. A STFNet, therefore, demonstrates superior capability as the fundamental building block of deep neural networks for IoT applications for various sensor inputs

Association of serum uric acid with right cardiac chamber remodeling assessed by cardiovascular magnetic resonance feature tracking in patients with connective tissue disease

BackgroundRight cardiac chamber remodeling is widespread in patients with connective tissue disease (CTD). Serum uric acid (SUA) is considered a potential independent risk factor for cardiovascular disease, and elevated SUA levels are often observed in patients with CTD. The correlation between SUA levels and right cardiac chamber remodeling remains unclear. This study investigated the association of SUA with right cardiac chamber remodeling as assessed by cardiac magnetic resonance feature-tracking (CMR-FT) in CTD patients.Methods and resultsIn this cross-sectional study, a total of 104 CTD patients and 52 age- and sex-matched controls were consecutively recruited. All individuals underwent CMR imaging, and their SUA levels were recorded. The patients were divided into three subgroups based on the tertiles of SUA level in the present study. CMR-FT was used to evaluate the right atrial (RA) longitudinal strain and strain rate parameters as well as right ventricular (RV) global systolic peak strain and strain rate in longitudinal and circumferential directions for each subject. Univariable and multivariable linear regression analyses were used to explore the association of SUA with RV and RA strain parameters. Compared with the controls, the CTD patients showed significantly higher SUA levels but a lower RV global circumferential strain (GCS) and RA phasic strain parameters (all p < 0.05), except the RA booster strain rate. RV GCS remained impaired even in CTD patients with preserved RV ejection fraction. Among subgroups, the patients in the third tertile had significantly impaired RV longitudinal strain (GLS), RV GCS, and RA reservoir and conduit strain compared with those in the first tertile (all p < 0.05). The SUA levels were negatively correlated with RV GLS and RV GCS as well as with RA reservoir and conduit strain and strain rates (the absolute values of β were 0.250 to 0.293, all P < 0.05). In the multivariable linear regression analysis, the SUA level was still an independent determinant of RA conduit strain (β = -0.212, P = 0.035) and RV GCS (β = 0.207, P = 0.019).ConclusionSUA may be a potential risk factor of right cardiac chamber remodeling and is independently associated with impaired RA conduit strain and RV GCS in CTD patients

Optical-resolution photoacoustic microscopy of the metabolic rate of oxygen in a mouse renal tumor model

We propose using noninvasive longitudinal optical-resolution photoacoustic microscopy (L-ORPAM) to quantify blood flow flux, oxygen saturation (sO_2), and thereby the metabolic rate of oxygen (MRO_2), for a renal tumor model in the same mouse over weeks to months. Experiments showed that the sO2 difference between the artery and vein decreased greatly due to the arteriovenous shunting effect during tumor growth. Moreover, hypermetabolism was exhibited by an increase in MRO_2

Manipulations of phenylnorbornyl palladium species for multicomponent construction of a bridged polycyclic privileged scaffold

Hexahydromethanocarbazole is a privileged scaffold in the discovery of new drugs and photoactive organic materials due to its good balance between structural complexity and minimized entropy penalty upon receptor binding. To address the difficulty of synthesizing this highly desirable bridged polycyclic scaffold, we designed a convenient multicomponent reaction cascade as intercepted Heck addition/C-H activation/C-palladacycle formation/electrophilic attack of ANP/N-palladacycle formation/Buchwald amination. A distinguishing feature of this sophisticated strategy is the successive generation of two key phenylnorbornyl palladium species to control the reaction flow towards desired products. DFT calculations further reveal the crucial roles of Cs2CO3 and 5,6-diester substitutions on the norbornene reactant in preventing multiple side-reactions. This innovative method exhibits a broad scope with good yields, and therefore will enable the construction of natural-product-like compound libraries based on hexahydromethanocarbazole

STRESS ANALYSIS OF PLASTIC PIPE REINFORCED BY CROSS HELICALLY WOUND STEEL WIRES

ABSTRACT Polyethylene pipe reinforced by cross helically wound steel wires (PSP), which has excellent performance, is a new type of plastic-matrix steel composite pipe. PSP consists of three continuous layers, i.e., inner PE layer, composite layer and outer PE layer. Elastic parameters of the composite layer were obtained with series and parallel models. Solutions for elastic stresses and strains of the PSP under internal pressure, external pressure, and axial force were developed by using the three-dimensional (3-D) anisotropic elasticity. Good agreement between theoretical results and experimental data shows that the presented model can well predict stresses and strains of the PSP. KEYWORDS Composite materials, composite pipe, stress analysis, experimental investigation INTRODUCTION Plastic pipe reinforced by cross helically wound steel wires (PSP), a new type of plastic-matrix steel composite pipes developed in China, is extensively used in petroleum, chemical engineering, and municipal water supply, etc

Dynamic changes in marker components during the stir-frying of Pharbitidis Semen, and network analysis of its potential effects on nephritis

Introduction: Pharbitidis Semen (PS) has been widely used in traditional Chinese medicine to treat several diseases such as nephritis. PS is usually stir-fried to enhance its therapeutic efficacy before use in clinical practice. However, the changes in phenolic acids during stir-frying and the mechanisms of their therapeutic effects on nephritis are still unclear.Methods: Here, we studied the processing-induced chemical changes and elucidated the mechanism of PS in the treatment of nephritis. We determined the levels of the 7 phenolic acids in raw PS (RPS) and stir-fried PS (SPS) using high-performance liquid chromatography, analyzed the dynamic compositional changes during stir-frying, and used network analysis and molecular docking to predict and verify compound targets and pathways corresponding to nephritis.Results: The dynamic changes in the 7 phenolic acids in PS during stir-frying are suggestive of a transesterification reaction. Pathway analysis revealed that the targets of nephritis were mainly enriched in the AGE-RAGE, hypoxia-inducible factor-1, interleukin-17, and tumor necrosis factor signaling pathways among others. Molecular docking results showed that the 7 phenolic acids had good binding ability with the key nephritic targets.Discussion: The potential pharmaceutical basis, targets, and mechanisms of PS in treating nephritis were explored. Our findings provide a scientific basis for the clinical use of PS in treating nephritis