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The sluggish kinetics of BiVO4 limits its applications in solar-to-hydrogen energy conversion. In this work, the zeolitic imidazolate framework ZIF-67 as a cocatalyst was immobilized on a BiVO4 nanocone via a solution-based photo-deposition method for photoelectrochemical water oxidation. Under the assistance of the nano-tip effect induced by the BiVO4 tip, nanoflower-like ZIF-67 was selectively grown at the vertex of the BiVO4 nanocone. The constructed BiVO4/ZIF-67 composite photoelectrode yielded a photocurrent of 0.92 mA cm−2 at ∼1.23 VRHE, which is about 3.5-fold that of pure BiVO4. In addition, surface/bulk charge separation efficiencies (ηsurf and ηbulk) were elevated when compared to those of the BiVO4 photoelectrode. Photoelectrochemical impedance spectroscopy (PEIS) and intensity modulated photocurrent spectroscopy (IMPS) measurements were further investigated to reveal the critical role of the modification of ZIF-67 in suppressing charge recombination and improving the photoelectrochemical activity of BiVO4. This research presents a feasible way to design a BiVO4/MOF composite photoanode induced by the nano-tip effect for enhanced photoelectrochemical water splitting performance. [ABSTRACT FROM AUTHOR]

Most current point cloud super-resolution reconstruction requires huge calculations and has low accuracy when facing large outdoor scenes; a Dense Feature Pyramid Network (DenseFPNet) is proposed for the feature-level fusion of images with low-resolution point clouds to generate higher-resolution point clouds, which can be utilized to solve the problem of the super-resolution reconstruction of 3D point clouds by turning it into a 2D depth map complementation problem, which can reduce the time and complexity of obtaining high-resolution point clouds only by LiDAR. The network first utilizes an image-guided feature extraction network based on RGBD-DenseNet as an encoder to extract multi-scale features, followed by an upsampling block as a decoder to gradually recover the size and details of the feature map. Additionally, the network connects the corresponding layers of the encoder and decoder through pyramid connections. Finally, experiments are conducted on the KITTI deep complementation dataset, and the network performs well in various metrics compared to other networks. It improves the RMSE by 17.71%, 16.60%, 7.11%, and 4.68% compared to the CSPD, Spade-RGBsD, Sparse-to-Dense, and GAENET. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to propose a hybrid force/position controller based on the adaptive variable impedance. Design/methodology/approach: First, the working space is divided into a force control subspace and a position subspace, the force control subspace adopts the position impedance control strategy. At the same time, the contact force model between the robot and the surface is analyzed in this space. Second, based on the traditional position impedance, the model reference adaptive control is introduced to provide an accurate reference position for the impedance controller. Then, the BP neural network is used to adjust the impedance parameters online. Findings: The experimental results show that compared with the traditional PI control method, the proposed method has a higher flexibility, the dynamic response accommodation time is reduced by 7.688 s and the steady-state error is reduced by 30.531%. The overshoot of the contact force between the end of robot and the workpiece is reduced by 34.325% comparing with the fixed impedance control method. Practical implications: The proposed control method compares with a hybrid force/position based on PI control method and a position fixed impedance control method by simulation and experiment. Originality/value: The adaptive variable impedance control method improves accuracy of force tracking and solves the problem of the large surfaces with robot grinding often over-polished at the protrusion and under-polished at the concave. [ABSTRACT FROM AUTHOR]

Background: Due to its unique anatomical characteristics, supracondylar fractures of the humerus are often difficult to achieve firm fixation with internal fixation equipment, resulting in delayed functional exercise, often leaving cubitus varus deformity, elbow stiffness, contractures, and other complications. Here, we report an adult patient with a supracondylar fracture of the humerus who underwent internal fixation through an anterior median incision in the humerus with our self-developed anterior anatomical locking plate of the distal humerus. Case presentation: A 29-year-old male patient of Chinese ethnicity with trauma-induced right supracondylar fracture of the humerus and multiple soft tissue contusions, without nerve damage, blood vessel damage, or other injuries, underwent an internal incision in our hospital using a new anatomical locking plate for the anterior distal humerus fixed treatment. During the 16-month follow-up period, the patient's elbow range of motion was almost completely restored, functional scores were excellent, and there were no minor or major postoperative complications. Conclusion: In this study, we propose a surgical reconstruction strategy for adult patients with supracondylar humeral fractures. Through the anterior median incision of the humerus, open reduction and internal fixation were performed with an anatomic locking plate on the anterior side of the distal humerus to restore and fix the structure of the distal humerus, and satisfactory clinical results were achieved in our case. [ABSTRACT FROM AUTHOR]

MnO2@PCs (porous carbons) exhibiting high energy and power density are utilized as supercapacitor electrodes and prepared by impregnating porous carbons (PCs) derived from coal tar pitch (CTP) with KMnO4 as the manganese source. This study systematically investigates the impact of MnO2 loading on the microstructure and electrochemical performance in sample. It is found that the specific surface areas (SSA) of all MnO2@PCs significantly reduced compared to that of the PCs 2789 m2 g−1. The suggested mechanism might be a combination of the energy storage mechanism of dual layer capacitors with pseudo‐capacitance due to redox reactions of MnO2. Notably, MnO2@PCs‐0.0075 exhibits a maximum SSA of 1454.62 m2 g−1. Its specific capacitance reached 561 F g−1 at 0.5 A g−1, while the capacitance of the PCs increased by 81.5% to 309 F g−1. Remarkably, the Coulombic efficiency remained at 100%. The power density and energy density are determined in a two‐electrode test system to be 0.5 kW kg−1 and 58.01 Wh kg−1, respectively, at 0.5 A g−1. Concluding from these results and related literature, the MnO2 content significantly influences the electrochemical performance, suggesting that MnO2@PCs‐0.0075 could be a promising supercapacitor (SC) electrode material, provided its capacitance retention is enhanced. [ABSTRACT FROM AUTHOR]

This paper proposed a three-loop physical parameter identification method considering physical feasibility and nonlinear friction model. The full physical parameters can be obtained with physical feasibility by constructing an optimization problem. And the nonlinear friction model which considered Stribeck effect is employed to improve identification accuracy. In the first loop, the physical parameters are identified with a regression model. In the second loop, the nonlinear friction model is identified with a nonlinear optimization method. And in the third loop, the obtained friction parameters are updated and the identification results are to be further optimized. Different from traditional methods like the least squares (LS), weight least squares (WLS) and other optimization methods which can only get base parameters and do not consider Stribeck effect, the proposed scheme can get physical parameters with physical constraints. It is useful in many robotic applications, like model-based control. The Stribeck effect is also employed to improve identification accuracy. The experimental results verified the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Nonlinear optical rectification (NOR) coefficients in symmetric double-graded quantum wells with different geometrical configurations under non-resonant laser field in the presence of electric and magnetic fields are theoretically investigated. The quantum states under the applied external fields are obtained under effective mass approximation and using diagonalization method. Our calculated results indicate that the above-mentioned external fields play a significant role in manipulating the resonant peak values and peak positions of nonlinear optical rectification coefficients of the quantum system dynamically. Considerable NOR coefficient can be achieved, not only by choosing appropriate laser dressing parameter as well as the electric and magnetic fields, but also by choosing appropriate well and barrier widths. Our results show great advantages in dynamically tuning NOR coefficient of symmetric double-graded quantum wells using multi-physic fields, paving the way for possible application for tunable infrared detector and signal processing based on symmetric double-graded quantum wells. [ABSTRACT FROM AUTHOR]

This paper proposes a point-by-point weighted fusion algorithm based on an improved random sample consensus (RANSAC) and inverse distance weighting to address the issue of low-resolution point cloud data obtained from light detection and ranging (LiDAR) sensors and single technologies. By fusing low-resolution point clouds with higher-resolution point clouds at the data level, the algorithm generates high-resolution point clouds, achieving the super-resolution reconstruction of lidar point clouds. This method effectively reduces noise in the higher-resolution point clouds while preserving the structure of the low-resolution point clouds, ensuring that the semantic information of the generated high-resolution point clouds remains consistent with that of the low-resolution point clouds. Specifically, the algorithm constructs a K-d tree using the low-resolution point cloud to perform a nearest neighbor search, establishing the correspondence between the low-resolution and higher-resolution point clouds. Next, the improved RANSAC algorithm is employed for point cloud alignment, and inverse distance weighting is used for point-by-point weighted fusion, ultimately yielding the high-resolution point cloud. The experimental results demonstrate that the proposed point cloud super-resolution reconstruction method outperforms other methods across various metrics. Notably, it reduces the Chamfer Distance (CD) metric by 0.49 and 0.29 and improves the Precision metric by 7.75% and 4.47%, respectively, compared to two other methods. [ABSTRACT FROM AUTHOR]

Soil moisture content is one of the most important soil indices for agriculture production. With the increasing food requirement and limited irrigation water sources, it is of great significance to accurately and quickly measure the soil moisture content for precision irrigation, especially in deficient agricultural areas, such as North China Plain. To achieve this goal, more attention was paid to the application of unmanned aerial vehicle multispectral reflectance technology. However, it was urgent to enhance the regression models between spectral data and soil realistic moisture content, and there were limited studies about the regression research on deep soil layers. Thus, the farmland of winter wheat–summer maize double cropping at Yongnian District, Hebei, North China, was selected as the study area. A six-band multispectral camera mounted on a low-altitude unmanned aerial vehicle (UAV) was used to obtain the field spectral reflectance with bands from 470~810 nm, and meanwhile, soil moisture content at different depths (10, 20, 30, 40, 50, and 60 cm) was measured after maize sowing. Unary linear regression (ULR), multivariate linear regression (MLR), ridge regression (RR), and an artificial neural network (ANN) were employed to establish regression models. The results demonstrated that the sensitive bands of spectral reflectance were 690 nm, 470 nm, and 810 nm. Those models all established significant regression at the depths of 0–20 cm and 40–60 cm, particularly at 10, 50, and 60 cm soil layers. However, for a depth of 20–40 cm, the prediction accuracy was generally lower. Among MLR, RR, and BP models, the MLR exhibited the highest identification accuracy, which was most recommended for the application. The findings of this study provide technical guidance and effective regression for the multispectral reflectance on the farmland of North China Plain, especially for deep soil layer moisture prediction. [ABSTRACT FROM AUTHOR]

The lotus seed and lily bulb beverage (LLB) has a problem with solid particle sedimentation. To address this issue, LLB was homogenised twice at different pressures (0~100 MPa) using a homogeniser. This study aims to investigate the changes in the particle size distribution (PSD), microstructure, rheological behaviour, sedimentation index (IS), turbidity, physicochemical properties, and sensory quality of LLBs after homogenisation treatments. The results regarding PSD and microstructure showed that the suspended particles were decomposed at high pressure with increasing homogenisation pressure, forming small particles of cellular material, cell wall fragments, fibre fractions, and polymers. The LLB showed shear-thinning behaviour and weak gelation characteristics (G′ > G″) and rheological properties. Among all homogenisation pressures, the 60 MPa sample showed the lowest sedimentation rate and the highest turbidity. When the pressure was increased from 0 to 100 MPa, the total soluble solid (TSS) content showed an upward trend, while the ascorbic acid content (AAC) gradually decreased. The highest sensory evaluation was observed in the 60 MPa sample in terms of overall acceptability. [ABSTRACT FROM AUTHOR]

Hot dip galvanized products are widely used in various aspects of production and life due to their excellent corrosion resistance. Some studies have added a fourth trace alloying element to the zinc aluminum magnesium coating to form a quaternary alloy for better performance. This article prepared two different types of Zn−Al−Mg alloy ingots with trace amounts of Si added by induction melting, consisting of Zn1Al1Mg0.01Si and Zn1Al1Mg0.05Si, and solidified them in a heating furnace with argon gas protection atmosphere. The precipitation process of Zn1Al1Mg(0.01,0.05)Si alloy components under non equilibrium and equilibrium solidification conditions was calculated. The initial crystalline phase of the alloy and the initial solidification temperature were predicted through phase diagram calculations. The microstructure and phase types of the alloy were analyzed using scanning electron microscopy (SEM) and field emission scanning electron microscopy (FE-SEM). The electrochemical Tafel curves of Zn1Al1Mg(0.01,0.05)Si with different Si contents showed that the Zn1Al1Mg0.05Si has the highest corrosion potential and Zn1Al1Mg0.01Si has the lowest corrosion current which means the 1Al1Mg0.01Si alloy possesses the highest corrosion resistance. The Nyqust curves and bode curves also showed that the practical impedance of 1Al1Mg0.01Si alloy is higher than that of 1Al1Mg0.05Si. Moreover, electron probe X-ray micro-analyzer(EPMA) reveals the distribution of Si elements in the Zn1Al1Mg(0.01,0.05)Si. At present, there is little research on the microstructure and properties of quaternary alloys containing silicon. Therefore, studying the influence of silicon content on the microstructure and properties of alloys is of great significance. [ABSTRACT FROM AUTHOR]

Acoustic emission (AE) technology provides a novel approach for studying the damage and fracture behavior of wood‐plastic composites (WPCs) during their application process. This method allows rapid and precise analysis of the mechanical properties of materials, which is a significant advancement for the emerging WPC industry. Hence, a blend of waste floor sanding powder (FSP) and rice husk (RH) reinforced recycled high‐density polyethylene (Re‐HDPE) was prepared by the extrusion method. The AE technique, scanning electron microscopy, and finite element method (FEM) were used to analyze the damage and fracture behavior of the composite materials under a three‐point bending test. The results indicated that the bearing capacity of RH/Re‐HDPE composites was slightly higher than that of FSP/Re‐HDPE composites. The AE technique can better illustrate the damage evolution and fracture process of composites and determine the damage degree and mode. Matrix cracking and deformation were more pronounced in the FSP/Re‐HDPE composites. Fiber breakage and delamination were more prominent in the RH/Re‐HDPE composites. In addition, repeated loading caused irreversible damage to the composite. The increase in temperature led to the attenuation of the AE signal and a decrease in matrix strength. However, when the temperature reached a certain point, the cumulative AE ringing count increased again because the higher temperature improved the fiber–matrix interface strength, which partially canceled out the negative effect. In addition, Abaqus was used for simulation analysis, and the running results coincided with the experimental value. Highlights: RH/Re‐HDPE and FSP/Re‐HDPE are sustainability and low‐cost composites.AE can determine the degree and mode of damage of WPC at different temperatures.The AE curves of RH/Re‐HDPE and FSP/Re‐HDPE all pass through four stages.Heating reduced the matrix strength and improved the interface strength of WPC.The results of FEM were consistent with the experimental results. [ABSTRACT FROM AUTHOR]

With the rapid development of social industrialization, environmental problems seriously threaten people's health, especially water pollution. Therefore, there is an urgent need to construct a multifunctional nanoplatform for different scenarios. Two-dimensional MXene@AgAu@PDA nanosheets loaded with AgAu bimetallic nanocages have been prepared by a one-step method. First, the in situ generated MXene@Ag is used as an auxiliary template, and then HAuCl4 and dopamine are added for in situ redox-oxidizing polymerization reactions to obtain AgAu catalytic nanocages and the protective polydopamine (PDA) layer which can improve the stability and biocompatibility. MXene and PDA have excellent photothermal conversion ability while hollow AgAu nanocages have strong absorption in the near-infrared region and a local surface plasmonic resonance effect. In comparison to the catalytic reaction rates under dark and room temperature conditions, the catalytic kinetic rate of MXene@AgAu@PDA nanosheets under near-infrared irradiation increases from 0.13 to 0.69 min−1 mg−1. Density functional theory (DFT) is used to study the electron transfer behavior between AgAu nanocages and MXene nanosheets, and the mechanism of the enhanced catalytic reaction rate is analyzed. Besides, due to its Ag ions and photothermal coupling antibacterial properties, 40 μg mL−1 MXene@AgAu@PDA nanosheets inactivates nearly all E. coli and S. aureus after irradiation with near-infrared light for 6 min. [ABSTRACT FROM AUTHOR]

The regular admittance controller cannot be easily transferred to the physical human–robot interaction scenario because of the dynamic stiffness of the human arm. The dynamic interaction of humans can cause high frequency and unsafe oscillation of the robot arm. Based on the adaptive control scheme, this paper presents an online sensory-based analytical approach to recognize and quantify the “stability index" named as a robust haptic observer. The observer performs the Fast Fourier Transform on the interaction force signal within a sliding window and quickly detects system oscillation through a simple mathematical transformation. Compared with the existing methods, it can calculate a normalized system stability index more accurately and faster. This quantified index is employed in a linearized adaptive law to tune the parameters of the admittance controller. Experimental validation of the proposed strategy is performed and compared with state-of-the-art work in a task of human-guided drawing. The results show that our proposed approach can effectively detect oscillation, and the drawing time is shortened by 15% with the same tracking accuracy. In addition, the energy consumption is 44.4% less on average. [ABSTRACT FROM AUTHOR]

Heart rate recovery (HRR), a noninvasive assessment of autonomic nervous function, is widely studied in adults with hypertension or prehypertension. This study aimed to evaluate whether HRR was independently associated with prehypertension in obese children. A total of 326 obese children aged 7 to 16 years were divided into 2 groups: prehypertension group and normal blood pressure (BP) group (control group). Anthropometric indexes, physical activity (PA) information, biochemical parameters, and HRR were collected. Multiple logistic regression analysis showed that body mass index (BMI) (odds ratio [OR] = 1.116; P <.05), waist-to-hip ratio (WHR) (OR = 1.258; P <.05), homeostasis model assessment (HOMA-IR) (OR = 1.087; P <.01), diastolic blood pressure (DBP) (OR = 1.304; P <.01), and HRR values (OR = 0.892; P <.05) were independent risk factors of prehypertension in obese children. Our findings demonstrated decreased HRR was closely associated with prehypertension in obese children, which indicated studying the role of sympathetic/parasympathetic imbalance might be helpful to explore the underlying mechanism. [ABSTRACT FROM AUTHOR]

The 3 μm wavelength band laser is located on the strong absorption peak of water and the atmospheric transmission window. The 3 μm laser with high single pulse energy is used in medical treatment for cutting soft tissues and bones during surgery. It is used as a pump source for optical parametric oscillators, and Fe lasers can realize 3~5 μm or 8~14 μm laser output, which has an irreplaceable role in certain areas (e.g., optoelectronic countermeasures, LIDAR, atmospheric monitoring, etc.). Commercial semiconductor-pumped Er lasers are capable of achieving 3 μm laser output of 600 mJ with the maturation of a 970 nm semiconductor laser. The conversion efficiency is significantly improved. However, the energy is lower than a flash-lamp-pumped Er laser. There are still serious crystal thermal effects and an inefficient conversion process. In this paper, the energy-level systems of 3 μm Er-doped lasers are discussed. A summary of the current state of research on Er lasers using different matrices and the commercialization of Er-doped lasers with wavelengths ranging from 2.7 μm to 3 μm is also provided. Several technical means are given to enhance laser performance. Furthermore, the development of Er-doped solid-state lasers with wavelengths between 2.7 and 3 μm is envisaged in the near future. [ABSTRACT FROM AUTHOR]

Background: Plasmodium berghei has been used as a preferred model for studying human malaria, but only a limited number of disease-associated genes of P. berghei have been reported to date. Identification of new disease-related genes as many as possible will provide a landscape for better understanding the pathogenesis of P. berghei. Methods: Network module analysis method was developed and applied to identify disease-related genes in P. berghei genome. Sequence feature identification, gene ontology annotation, and T-cell epitope analysis were performed on these genes to illustrate their functions in the pathogenesis of P. berghei. Results: 33,314 genes were classified into 4,693 clusters. 4,127 genes shared by six malaria parasites were identified and are involved in many aspects of biological processes. Most of the known essential genes belong to shared genes. A total of 63 clusters consisting of 405 P. berghei genes were enriched in rodent malaria parasites. These genes participate in various stages of parasites such as liver stage development and immune evasion. Combination of these genes might be responsible for P. berghei infecting mice. Comparing with P. chabaudi, none of the clusters were specific to P. berghei. P. berghei lacks some proteins belonging to P. chabaudi and possesses some specific T-cell epitopes binding by class-I MHC, which might together contribute to the occurrence of experimental cerebral malaria (ECM). Conclusions: We successfully identified disease-associated P. berghei genes by network module analysis. These results will deepen understanding of the pathogenesis of P. berghei and provide candidate parasite genes for further ECM investigation. [ABSTRACT FROM AUTHOR]

The article titled "The Opposite Role of Alternatively Spliced Isoforms of LINC00477 in Gastric Cancer" has been retracted by the journal Cancer Management & Research. The retraction was made due to concerns regarding the use of non-verifiable cell lines in the study. These cell lines were found to be contaminated, wrongly identified, improperly indexed, and unavailable through external cell line repositories. The corresponding author did not respond to queries or provide original data, raising doubts about the validity of the findings. The retracted article will remain online but will be marked as "Retracted." [Extracted from the article]

The purpose of this paper is to re-examine the impact of exchange rate changes on the trade balance of China and its major trading partners. In the past, many studies have been focussed on the linear effect of exchange rate change, but in this paper, a non-linear Autoregressive Distribution Lag (NARDL) model is proposed. Empirical results show that there are nonlinear and asymmetric effects on the trade balance of exchange rate. In particular, the effect of exchange rate appreciation on Sino-US trade balance is more significant than that of depreciation. A genuine devaluation of the domestic currency would improve the balance of the domestic trade. However, the opposite effect is found in the case of Sino-Japan and the Euro, and the depreciation of the currency will make the trade balance worse. These results provide a solid basis for understanding the relation of exchange rate variation and trade balance. In terms of economic reality, it is also a useful reference for adjusting exchange rate and commercial policy. [ABSTRACT FROM AUTHOR]

Thermal discomfort body language has been shown to be a psychological representation of personnel's particular thermal comfort. Individual thermal comfort differences are ignored in public building settings with random personnel flow. To solve this issue, we suggested a Bayesian group thermal dissatisfaction rate prediction model based on thermal discomfort body language expression and subsequently implemented intelligent indoor temperature and humidity control. The PMV-PPD model was utilized to represent the group's overall thermal comfort and to create a prior distribution of thermal dissatisfaction rate. To acquire the dynamic distribution of temperature discomfort body language, data on thermal discomfort body language expression were collected in a real-world office setting experiment. Based on Bayesian theory, we used personalized thermal discomfort body language expressions to modify the group's universal thermal comfort and realized the assessment of the thermal dissatisfaction rate by combining commonality and personalization. Finally, a deep reinforcement learning system was employed to achieve intelligent indoor temperature and humidity control. The results show that when commonality and personalized thermal comfort differences are combined, real-time prediction of thermal dissatisfaction rate has high prediction accuracy and good model performance, and the prediction model provides a reference basis for reasonable indoor temperature and humidity settings. [ABSTRACT FROM AUTHOR]

This paper theoretically and experimentally analyzes the influence of different sensor array schemes and optical collimation structures on fingerprint recognition. Considering the process yield, cost and the quality of fingerprint image, we find the appropriate size ranges of microlenses and sensors are 20~30 μm and 35~50 μm respectively, and the bonding process between the optical collimating film and the sensor substrate has little damage to the sensor, which is conducive to mass production. [ABSTRACT FROM AUTHOR]

Strong coupling between plasmons and multiple different exciton states (MESs) enables the creation of multiple hybrid polariton states under ambient conditions. These hybrid states possess unique optical properties different from those of their separate identities, making them ideal candidates for exploiting room-temperature multimode hybridization and multiqubit operation. In this study, we revealed the static spectral response properties of plasmon-MES strong coupling via a fully quantum mechanics approach. These theoretical predictions were experimentally demonstrated in plasmonic nanocavities containing two and three different exciton species. Additionally, the dynamical absorption processes of such strong coupling systems were investigated, and results indicated that the damping of the hybrid polariton states induced by the strong coupling could be markedly modulated by the acoustic oscillations from the plasmonic nanocavities. Our findings contribute a theoretical approach for accurately describing the plasmon-MES interactions and a platform for developing the high-speed active plasmonic devices based on multiqubit strong coupling. [ABSTRACT FROM AUTHOR]

An appropriate technical overhaul strategy is very important for the development of enterprises. Most enterprises pay attention to the design life of the equipment, that is, the point when the equipment can no longer be used as stipulated by the manufacturer. However, in the later stage of the equipment, the operation and maintenance costs may be higher than the benefit of the equipment. Therefore, only the design life of the equipment may cause a waste of funds, so as to avoid the waste of funds, the enterprise's strategy of technical reform and overhaul are optimized. This paper studies the optimal decommissioning life of the equipment (taking into account both the safety and economic life of the equipment), and selects the data of a 35 kV voltage transformer in a powerful enterprise. The enterprise may have problems with the data due to recording errors or loose classification. In order to analyze the decommissioning life of the equipment more accurately, it is necessary to first use t-distributed stochastic neighbor embedding (t-SNE) to reduce the data dimension and judge the data distribution. Then, density-based spatial clustering of applications with noise (DBSCAND) is used to screen the outliers of the data and mark the filtered abnormal data as a vacancy value. Then, random forest is used to fill the vacancy values of the data. Then, an Elman neural network is used for random simulation, and finally, the Fisher orderly segmentation is used to obtain the optimal retirement life interval of the equipment. The overall results show that the optimal decommissioning life range of the 35 kV voltage transformer of the enterprise is 31 to 41 years. In this paper, the decommissioning life range of equipment is scientifically calculated for enterprises, which makes up for the shortage of economic life. Moreover, considering the "economy" and "safety" of equipment comprehensively will be conducive to the formulation of technical reform and overhaul strategy. [ABSTRACT FROM AUTHOR]

The development of novel polymer dielectrics with enhanced dielectric performance is a great challenge for application of film capacitors in modern electronics and electrical systems. Herein, an innovative approach of chemical vapor deposition polymerization technology is proposed to prepare the all‐organic sandwich structured parylene/polyimide/parylene (Py/PI/Py) composite films by employing poly(chloro‐para‐xylylene) (parylene C) as the outer layers and polyimide (PI) as the inner layer. The Py/PI/Py composites exhibit superior thermal resistance and outstanding mechanical properties. Moreover, thanks to the interfacial effect which contributes to reinforcing the dielectric response and the thickness effect which facilitates improving the breakdown strength, the dielectric performance of Py/PI/Py composites has been enhanced significantly. Accordingly, dielectric constant of 4.52–5.09, dissipation factor of 0.21–1.01%, and breakdown strength of 307–460 MV m−1 are achieved. Besides, notable energy storage performance is also obtained in Py/PI/Py composite dielectrics. Consequently, this novel application of chemical vapor deposition polymerization method in preparing all‐organic multilayered polymer composite films with sandwich structure shows promising potential in film capacitor applications in harsh conditions. [ABSTRACT FROM AUTHOR]

New-onset refractory status epilepticus (NORSE) is rare but intractable. Anti-N-methyl-d-aspartate receptor (NMDAR) encephalitis and cryptogenic etiologies are the two major causes of NORSE with distinct clinical features. To elucidate the underlying mechanisms, 6 patients with anti-NMDAR encephalitis NORSE and 5 with cryptogenic NORSE (C-NORSE) were enrolled. Five patients of cerebrovascular disorders were used as controls. Quantitative proteomic analysis of the cerebrospinal fluid (CSF) samples of the patients revealed 101 and 56 proteins were changed, respectively. The average fold-change of the upregulated proteins, namely up-proteomic score in this study, was positively correlated with the severity and prognosis of the diseases, including ICU stay (r = 0.9308, P = 0.0035 in NMDAR group; r = 0.8977, P = 0.0193 in C-NORSE group), mRS score at discharge (r = 0.9710, P = 0.0111 in NMDAR group; r = 0.7071, P = 0.2000 in C-NORSE group), and time taken for patients awaking from a coma (r = 0.8823, P = 0.0100 in NMDAR group; r = 0.7906, P = 0.2000 in C-NORSE group). Pathways involved in humoral immune response, wound healing, and epigenetic regulation of transcription were upregulated in anti-NMDAR encephalitis NORSE. Pathways of innate and lymphocyte mediated immune response, synaptic functions, ubiquitination, and cell apoptosis were up-regulated in C-NORSE, which was consistent with a mouse model of status epilepticus. Fc receptor and B cell mediated immunity signaling pathways were downregulated in C-NORSE. Immunome microarray analysis demonstrated high autoantibody targeting 48 proteins in CSF samples of anti-NMDAR encephalitis NORSE. While the reaction was kept at a very low level in C-NORSE. There is no significant difference in inflammatory cytokine level between each group. The level of IL-4 (r = 0.7435, P = 0.0451), IL-13 (r = 0.7643, P = 0.0384), IFN-γ (r = 0.7973, P = 0.0287) and TNF-α (r = 0.8598, P = 0.0141) in NMDAR group, and IL-6 (r = 0.8479, P = 0.0348), IL-8 (r = 0.9076, P = 0.0166) in C-NORSE group were positively correlated with the up-proteomic score. The present study suggests that the up-proteomic score of CSF could be a promising indicator for assessment of the severity of anti-NMDAR encephalitis NORSE and C-NORSE. The distinct CSF proteomes imply different pathogenic mechanisms of the two diseases, and immunotherapy strategies as well. [ABSTRACT FROM AUTHOR]

The paper proposes a method to effectively fuse multi-exposure inputs and generate high-quality high dynamic range (HDR) images with unpaired datasets. Deep learning-based HDR image generation methods rely heavily on paired datasets. The ground truth images play a leading role in generating reasonable HDR images. Datasets without ground truth are hard to be applied to train deep neural networks. Recently, Generative Adversarial Networks (GAN) have demonstrated their potentials of translating images from source domain $X$ to target domain $Y$ in the absence of paired examples. In this paper, we propose a GAN-based network for solving such problems while generating enjoyable HDR results, named UPHDR-GAN. The proposed method relaxes the constraint of the paired dataset and learns the mapping from the LDR domain to the HDR domain. Although the pair data are missing, UPHDR-GAN can properly handle the ghosting artifacts caused by moving objects or misalignments with the help of the modified GAN loss, the improved discriminator network and the useful initialization phase. The proposed method preserves the details of important regions and improves the total image perceptual quality. Qualitative and quantitative comparisons against the representative methods demonstrate the superiority of the proposed UPHDR-GAN. [ABSTRACT FROM AUTHOR]

Objectives: Mesoderm, derived from a new layer between epiblast and hypoblast during gastrulation, can differentiate into various tissues, including muscles, bones, kidneys, blood, and the urogenital system. However, systematic elucidation of mesoderm characteristics and specific markers remains a challenge. This study aims to screen and identify candidate genes important for mesoderm development. Materials and Methods: Cells originating from the three germ layers were obtained by laser capture microdissection, followed by microcellular RNA sequencing. Mesoderm‐specific differentially expressed genes (DEGs) were identified by using a combination of three bioinformatics pipelines. Candidate mesoderm‐specific genes expression were verified by real‐time quantitative polymerase chain reaction analysis and immunohistochemistry. Functional analyses were verified by ESCs‐EBs differentiation and colony‐forming units (CFUs) assay. Results: A total of 1962 differentially expressed mesoderm genes were found, out of which 50 were candidate mesoderm‐specific DEGs which mainly participate in somite development, formation of the primary germ layer, segmentation, mesoderm development, and pattern specification process by GO analysis. Representative genes Cdh2, Cdh11, Jag1, T, Fn‐1, and Pcdh7 were specifically expressed in mesoderm among the three germ layers. Pcdh7 as membrane‐associated gene has hematopoietic‐relevant functions identified by ESCs‐EBs differentiation and CFUs assay. Conclusions: Spatial transcriptomic profiling with multi‐method analysis and confirmation revealed candidate mesoderm progenitors. This approach appears to be efficient and reliable and can be extended to screen and validate candidate genes in various cellular systems. [ABSTRACT FROM AUTHOR]

A 6-DOF cooperative manipulator is used for human spinal deformity detection. In order to ensure the scanning quality of spinal deformity and improve the solution rate and speed of inverse motion solution of the manipulator, an inverse kinematics analytical method based on spherical geometry is proposed in this paper. We take the AUBO-i5 collaborative manipulator as the research object, which combines the rapidity of analytical solution with the flexibility of spherical solution. In the Robot Operating System, the simulation experiment solves the inverse kinematics of 10 000 sets of randomly generated postures. The success rate and time-consuming of the solution are calculated. Compared with the two commonly used inverse kinematics solving algorithms, TRAC-IK and KDL, this method has obvious advantages in terms of success rate and average time-consuming. [ABSTRACT FROM AUTHOR]

We developed a large area and low cost optical fingerprint recognition product based on LTPS (low temperature poly silicon) process. A high efficient a‐Si pin sensor is introduced, the quantum efficiency under white light is 70% and the dark state current density is E‐10 A / mm2. The "one‐to‐one" and "one to multiple" structures of sensor and micro lens are compared, and the "one‐to‐one" optical path structure is systematically analyzed and evaluated. The optical path focal length is about 100 μm. The fingerprint recognition effect is significantly improved by adding a BM shading layer, and this scheme can effectively avoid the screen burning problem caused by the high luminous intensity of pixels in the fingerprint unlocking area. [ABSTRACT FROM AUTHOR]

The extraction of rivers in cold and arid regions is of great significance for applications such as ecological environment monitoring, agricultural planning, and disaster warning. However, there are few related studies on river extraction in cold and arid regions, and it is still in its infancy. The accuracy of river extraction is low, and the details are blurred. The rapid development of deep learning has provided us with new ideas, but with lack of corresponding professional datasets, the accuracy of the current semantic segmentation network is not high. This study mainly presents the following. (1) According to the characteristics of cold and arid regions, a professional dataset was made to support the extraction of rivers from remote sensing images in these regions. (2) Combine transfer learning and deep learning, migrate the ResNet-101 network to the LinkNet network, and introduce the attention mechanism to obtain the AR-LinkNet network, which is used to improve the recognition accuracy of the network. (3) A channel attention module and a spatial attention module with residual structure are proposed to strengthen the effective features and improve the segmentation accuracy. (4) Combining dense atrous spatial pyramid pooling (DenseASPP) with AR-LinkNet network expands the network receptive field, which can extract more detailed information and increase the coherence of extracted rivers. (5) For the first time, the binary cross-entropy loss function combined with the Dice loss function is applied to river extraction as a new loss function, which accelerates the network convergence and improves the image quality. Validation on the dataset shows that, compared with typical semantic segmentation networks, the method performs better on evaluation metrics such as recall, intersection ratio, precision, and F 1 score, and the extracted rivers are clearer and more coherent. [ABSTRACT FROM AUTHOR]

The solidification and corrosion behavior of the Ti/B added Zn-Al-Mg alloys were experimentally investigated by means of microstructure characterization and electrochemical test. The basic calculations were carried out to predict the characteristics of the Ti-added Zn-Al-Mg alloys. The Zn-Al-Mg ingots with minor doping of Ti/B were prepared and solidified under different cooling rate, including air cooling, water quenching and furnace cooling. The scanning electron microscopy (SEM) and the X-ray diffraction method (XRD) were used to determine the microstructures and phase types of the alloy samples. It could be discovered that trace TiAl3 particles were dispersed in the Ti/B added alloy samples which provide the heterogeneous nucleation sites to refine the size of the dendrites and the eutectic microstructures. More fined microstructures with the addition of both Ti and B were obtained compared with those with the merely addition of Ti, and the water cooled alloys presented the finest microstructures due to the fastest cooling rate. It could also be noticed that with the increasing solidification rate, the percentage of the MgZn2 phase turned out to be higher because of the Mg2Zn11↔MgZn2 transition, which is in consistent with the results in the actual hot-dip galvanizing process. Electrochemical experiments in the previous work included methods the of the Tafel polarization test and the electrochemical impedance spectroscopy test (EIS). Results show that the quenched Zn-Al-Mg alloy with the addition of both Ti and B takes on best corrosion resistance. Consequently, the addition of certain amount of Ti/B elements and the appropriate elevation of the cooling rate will be the practicable approaches to optimize the microstructure and the corrosion resistance of the Zn-Al-Mg coatings in the actual galvanizing process. [ABSTRACT FROM AUTHOR]

Summary: Automatic crack detection on concrete surfaces has become increasingly important for the health diagnosis of concrete structures to prevent possible malfunctions or accidents. In this paper, a concrete crack segmentation network based on convolution–deconvolution feature fusion with holistically nested networks is proposed. The proposed network adopts an encoder–decoder structure and uses VGG‐16 as the basic feature extraction network. First, considering the problem that the VGG‐16 network can extract redundant features in the encoding stage, based on the channel attention mechanism, the channel spatial correlation and global information are used to emphasize crack features to remove redundant features. Second, through the convolution–deconvolution feature fusion module, the deep semantic information of the deconvolution is effectively fused with the shallow features of convolution, which effectively improves the semantic crack feature information extracted at each stage of the VGG‐16 network. Finally, based on a multiscale supervised learning mechanism, holistically nested networks are used to fuse the prediction results from different scales, which enhances the network's ability to express linear topological structures and improves the accuracy of crack segmentation. Through a large number of experiments on the Bridge_Crack_Image_Data dataset and CFD dataset, we demonstrate that compared with other deep networks, the proposed network not only achieves better segmentation results for cracks of different widths but is also more robust. [ABSTRACT FROM AUTHOR]

Faster-than-Nyquist signaling (FTNS) has already been shown to increase the communication capacity on certain channels such as additive white Gaussian noise and block flat multiple-input multiple-output (MIMO) Rayleigh fading channels. The following issues, however, remain unresolved: 1) whether FTNS enables a capacity increase in generalized MIMO Rayleigh fading channels that are selective in time, frequency, and space; and 2) how channel selectivities affect the capacity and if present, the FTN capacity gain. To address the issues, this paper firstly investigates the ergodic capacity of MIMO-FTN transmission over triply-selective fading channels. We derive a low-complexity approximate capacity formula and also show how it degenerates in other channel models, such as doubly-selective single-input single-output fading channels, which can be considered as the special cases of triply-selective fading channels. The capacity evaluation results obtained under different channel conditions show that: 1) MIMO-FTN outperforms MIMO-Nyquist in terms of capacity; 2) the FTN gains are nearly consistent, while the FTN gains obtained in the frequency-selective fading channels are slightly higher than those obtained in the flat fading channels. [ABSTRACT FROM AUTHOR]

Parametric interpolation has been widely used in robot control because of its advantages over traditional linear or circular interpolation. The NURBS interpolation based on S-shaped feedrate scheduling can realize the smooth continuous motion of robots, but it also faces two challenges. One challenge is that when the NURBS curve is split into multiple blocks, if one or more blocks are too short, the final feedrate profile is often discontinuous. The other challenge is that the NURBS curve cannot be obtained entirely due to calculation errors. In this paper, a high-precision NURBS interpolator based on S-shaped feedrate scheduling is proposed. In this interpolator, a bidirectional velocity scanning scheme is developed to effectively handle the too short split blocks of the NURBS curve. Meanwhile, an optimization algorithm is proposed to ensure the precision of NURBS curves. The feasibility and advantages of the proposed method are verified through case studies. [ABSTRACT FROM AUTHOR]

Background: The true diploid frog, Xenopus tropicalis (X. tropicalis) is an excellent genetic model organism. To date, the CRISPR/Cas-mediated genome editing methods established in this species are mostly based on SpCas9 that requires the stringent NGG protospacer-adjacent motif (PAM) for target recognition, which limits its genome editing scope. Thus, it is highly desirable to circumvent this limitation. Results: Through one-cell stage injection of Cas/gRNAs into X. tropicalis embryos, we evaluated the mutagenic efficiency of 8 different Cas variants using T7EI assay, Sanger DNA sequencing, or deep sequencing. Our data indicate that SaCas9 and KKH SaCas9 are highly effective in frogs, which could be used for direct phenotyping in G0 embryos. In contrast, VQR Cas9, xCas9 3.7, SpG Cas9, and SpRY Cas9 were ineffective in X. tropicalis embryos and no activity was detected for iSpyMac Cas9. We also found that LbCas12a/crRNA RNP complexes with paired crRNAs efficiently induced small fragment deletions in X. tropicalis embryos. Conclusion: SaCas9 and KKH SaCas9 are robust genome editing tools in X. tropicalis embryos. LbCas12a/crRNA RNP complexes are useful for inducing DNA fragment deletions in frog embryos. These tools expand the CRISPR/Cas genome editing scope in X. tropicalis and increase the flexibility for various genome editing applications in frogs. [ABSTRACT FROM AUTHOR]

To solve the inherent brittleness of magnesium phosphate cement (MPC)-based composites, we incorporated polyvinyl alcohol (PVA) fibers to develop tensile strain hardening fiber reinforced magnesium phosphate cement composites (SHFRMC). The effects of fly ash (FA) content, PVA fiber volume fractions (Vf), the sand to binder mass ratio (S/B), and the water to solid mass ratio (W/S) on the workability, compressive strength, and tensile properties of the SHFRMC were studied. Lastly, the micromorphology of PVA fibers and their bonding with the matrix was examined by the optical microscope test. Generally, when the FA content is 30%, the SHFRMC can achieve relatively high strength and strain capacity while maintaining good workability; the SHFRMC can achieve relatively high workability, strength, and strain capacity when the Vf is 1.8%; when the S/B is 0, the workability, strength, and strain capacity of the SHFRM are the highest; and when the W/S is 0.13 or 0.16, the SHFRMC can achieve relatively high strength and strain capacity while maintaining good workability. The results revealed that a trade-off was needed among the workability, compressive strength, direct tensile stress, and tensile strain. The optical microscopy test showed that PVA fiber connects well with the matrix and plays an important bridging role in the tensile process to bear stress and restrain crack development, resulting in multicracking. [ABSTRACT FROM AUTHOR]

The paper proposes a solution based on Generative Adversarial Network (GAN) for solving jigsaw puzzles. The problem assumes that an image is divided into equal square pieces, and asks to recover the image according to information provided by the pieces. Conventional jigsaw puzzle solvers often determine the relationships based on the boundaries of pieces, which ignore the important semantic information. In this paper, we propose JigsawGAN, a GAN-based auxiliary learning method for solving jigsaw puzzles with unpaired images (with no prior knowledge of the initial images). We design a multi-task pipeline that includes, (1) a classification branch to classify jigsaw permutations, and (2) a GAN branch to recover features to images in correct orders. The classification branch is constrained by the pseudo-labels generated according to the shuffled pieces. The GAN branch concentrates on the image semantic information, where the generator produces the natural images to fool the discriminator, while the discriminator distinguishes whether a given image belongs to the synthesized or the real target domain. These two branches are connected by a flow-based warp module that is applied to warp features to correct the order according to the classification results. The proposed method can solve jigsaw puzzles more efficiently by utilizing both semantic information and boundary information simultaneously. Qualitative and quantitative comparisons against several representative jigsaw puzzle solvers demonstrate the superiority of our method. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel integrated light‐dependent sensor which can be used to detect the illuminance and color temperature of the ambient light. Based on the low temperature polysilimn (LTPS) thin film transistor (TFT) process and photosensitivity qf PIN photodiode, the sensor can realize 0–100K lux of the monitor range and an accuracy of 0.5 lux/step. Meanwhile, it can identify the color temperature from 2000 K to 8000 K with an accuracy of ± 250 K. The LCD panel with this optical sensor could adjust brightness and color temperature adaptively according to the ambient light. It saves more space for terminal product which will also facilitates the full screen display. [ABSTRACT FROM AUTHOR]

Adiponectin (APN) is reported to be correlated closely with autonomic nervous function in different clinical settings. Heart rate recovery (HRR) is a noninvasive and readily obtainable indicator, which reflects the coordinated interplay between parasympathetic reactivation and sympathetic withdrawal. This study aimed to investigate the relationship between serum APN and HRR in polycystic ovarian syndrome (PCOS) women. Eighty-nine PCOS women were enrolled and divided into two groups. Women with HRR values slower than 12 beats were defined as Blunted HRR Group. APN levels were compared between Blunted HRR Group and Normal HRR Group. Multivariate logistic regression analysis and multiple linear regression analysis were performed to determine which clinical variables were independently associated with HRR and APN levels, respectively. Twenty-three women were categorized into Blunted HRR Group, in which APN level was significantly lower than Normal HRR Group. Age, body mass index, hypertension, and APN were independent factors of attenuated HRR in PCOS women. Meanwhile, multiple linear regression analysis showed age, dyslipidemia, and homeostasis model assessment-insulin resistance (HOMA-IR) were closely associated with APN levels in PCOS women. Our findings suggested that decreased APN concentration was closely associated with HRR blunt in PCOS women. Further studies are needed to explore the underlying interactions between APN and autonomic nervous function. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a novel point-to-surface representation for 3D point cloud learning. Unlike the previous methods that mainly adopt voxel, mesh, or point coordinates, we propose to tackle this problem from a new perspective: learn a set of quadratic terms based static and global reference surfaces to describe 3D shapes, such that the coordinates of a 3D point (x, y, z) can be extended to quadratic terms (xy, xz, yz, $\ldots $) and transformed to the relationship between the local point and the global reference surfaces. Then, the static surfaces are changed into dynamic surfaces by adaptive contribution weighting to improve the descriptive capability. Towards this end, we propose our point-to-surface representation, a new representation for 3D point cloud learning that has not been attempted before, which can assemble local and global geometric information effectively by building connections between the point cloud and the learned reference surfaces. Given 3D points, we show how the reference surfaces are constructed, and how they are inserted into the 3D learning pipeline for different tasks. The experimental results confirm the effectiveness of our new representation, which has outperformed the state-of-the-art methods on the tasks of 3D classification and segmentation. [ABSTRACT FROM AUTHOR]

We propose a general formalism beyond Weisskopf–Wigner approximation to efficiently calculate the coupling matrix element, evolution spectrum and population evolution of two quantum emitters in arbitrary metallic nanostructures. We demonstrate this formalism to investigate the radiative coupling and decay dynamics of two quantum emitters embedded in the two hot spots of three silver nano-spheroids. The vacuum Rabi oscillation in population evolution and the anti-crossing behavior in evolution spectrum show strong radiative coupling is realized in this metallic nanostructure despite its strong plasmon damping. Our formalism can serve as a flexible and efficient calculation tool to investigate the distant coherent interaction in a large variety of metallic nanostructures, and may be further developed to handle the cases for multiple quantum emitters and arbitrary dielectric–metallic hybrid nanostructures. [ABSTRACT FROM AUTHOR]

Background and Purpose: An increasing number of autoimmune encephalitis (AE)-associated autoantibodies have been successfully characterized. However, many cases of AE remain unexplained on account of unknown antibodies. The aim of the present study was to identify a novel antibody against collapsin response mediator protein 2 (CRMP2) in suspected AE patients. Methods: A patient's serum and cerebrospinal fluid samples tested negative for known AE antibodies; however, strong immunolabel signals were observed in the neuronal cytoplasm of the cortex, hippocampus, and Purkinje cells on rat brain sections. Immunoprecipitation from the rat brain protein lysate, followed by mass spectrometry analysis, was used to identify the targeting antigen. Western blotting and cell-based assay with antigen-overexpressing HEK293T cells were used for antibody specificity, epitope, IgG subtype determination, and retrospective study. Results: An antibody against CRMP2, a synaptic protein involved in axon guidance, was identified. The immunostains of the patient's samples on rat brain sections were eliminated by pre-absorption with HEK293T cells overexpressing CRMP2. The samples specifically immunoreacted with CRMP2, but not with CRMP1, CRMP3, CRMP4, and CRMP5. The C-terminus of CRMP2 with 536 amino acids contained the epitope for antibody binding. The subtype analysis showed that the anti-CRMP2 antibody was IgG4. Furthermore, a screening of 46 patients with neurological disoders and neuro-cytoplasm immunostainings on rat brain sections resulted in the identification of anti-CRMP2 antibodies in a case of encephalomyelitis. The two patients responded well to immunotherapies. Conclusions: This study discovered that a novel anti-CRMP2 antibody was associated with suspected AE and thus should be included in the testing list for AE. [ABSTRACT FROM AUTHOR]

Faster-than-Nyquist signaling (FTNS) has emerged as a promising technique to increase communication capacity in bandwidth-limited channels. However, the presence of FTN-induced inter-symbol interference (FTN-ISI) in the received observations, is detrimental to channel estimation (CE) and data detection in terms of computational complexity and performance. This paper copes with these problems by incorporating linear pre-equalization (LPE) and composite precoding formed by linear spectral precoding and Tomlinson-Harashima precoding (THP), into the FTNS. Specifically, LPE completely pre-equalizes the FTN-ISI, while spectral precoding resolves the LPE-caused signal spectral broadening by introducing proper artificial ISI, which is pre-equalized by THP. Channel-induced ISI, as the only ISI component in the observations, is estimated and equalized using the classical frequency-domain low-complexity schemes. We show that there are four advantages of the LPE-aided CE over the CE designed for the FTN transmissions without FTN-ISI pre-equalization, namely lower pilot overhead, simpler yet optimal pilot sequence design, lower mean-squared error of CE, and more robust against the FTN-ISI. Simulation results show that our scheme improves the performance of CE and detection, compared to existing FTN frequency-domain CE and equalization schemes. [ABSTRACT FROM AUTHOR]

Accurate intensity estimation of tropical cyclone (TC) is important and challenging. Currently, no standardized method is available for estimating the TC intensity, usually in terms of the maximum surface wind speed, using satellite remote sensing data. This article proposes a multifeature distribution learning (MFDL) model that uses satellite microwave brightness temperatures to estimate the TC intensity. The MFDL model uses the brightness temperatures of Advanced Technology Microwave Sounder (ATMS) to generate the synthetic temperature anomaly fields of TCs at different pressure levels. These 3-D temperature anomaly data are trained by MFDL to establish the relationship between anomaly fields and TC intensity. MFDL treats the TC intensity estimation as a probability distribution of wind speed, instead of as a regression problem as in the conventional TC intensity estimation methods. In this study, 964 TCs occurred in North Atlantic (NA) and North Pacific (NP) from 2012 to 2019 are used for training and testing. The simulation results suggest that estimation accuracy is greatly improved using the preprocessed 3-D TC anomaly data. The MFDL network achieves the average mean absolute errors (MAEs) of 4.37 m/s for NA TCs and 4.92 m/s for NP TCs in the years 2018 and 2019. The results show that the MFDL network and ATMS temperature-based anomaly can be a promising means for TC intensity estimation in operational weather forecast. [ABSTRACT FROM AUTHOR]

Background: Retinopathy of prematurity (ROP) remains a leading cause of childhood blindness worldwide. This study aimed to investigate whether supplementation of n-3 polyunsaturated fatty acids (n-3 PUFAs) in parenteral nutrition may have beneficial effects on ROP in preterm infants.Methods: A total of 89 preterm infants, admitted to Neonatal Intensive Care Unit (NICU) in Anhui Provincial Children's Hospital from September 2017 to August 2020, were recruited in the study. Based on the medical documents, the subjects were categorised into two groups: administration of the fish oil emulsion (n=43) containing soy oil, medium-chain-triglycerides (MCT), olive oil and fish oil (6g/dL, 6g/dL, 5g/dL and 3g/dL respectively), and the soy oil emulsion (n=46) containing 10g/dL of soy oil and MCT each. At 4 weeks of hospitalization, ROP was screened and diagnosed. Fatty acids in erythrocytes were determined using gas chromatography.Results: The averaged birth weight and gestational age were 1594±296 g and 31.9±2.3 wk, 1596±263 g and 31.6±2.3 wk respectively for preterm infants in the fish oil group and soy oil group. After 4 to 6 weeks of hospitalization, among all the preterm infants, 52 developed ROP (all stages) indicating an incidence of ROP at 58.43%. Although the incidence of ROP with any stages showed no differences between the two groups, the severe ROP incidence in the group with fish oil emulsions (2.33%) was significantly lower than that in the group with soy oil emulsions (23.91%) (P<0.05). After 14 days of nutrition support, the preterm infants administered fish oil emulsions had an increase in erythrocyte DHA content, with a reduction in ratio of arachidonic acid (AA) to DHA and an increase of n-3 index.Conclusion: Supplementation of n-3 PUFAs through parenteral fish oil containing lipid emulsions resulted in an increase in erythrocyte DHA, and this might have beneficial effects on prevention of severe ROP in preterm infants. [ABSTRACT FROM AUTHOR]

We propose a cascaded impedance control algorithm based on a virtual dynamics model (VDM) to achieve robust and effective mechanical impedance for a robot interacting with unknown environments. This cascaded controller consists of an internal loop of virtual impedance control based on a VDM and an external loop of impedance reference control. The VDM-based virtual impedance control can achieve the same effect as the conventional admittance control; its intermediate output of force/torque serves as the input for the external loop reference impedance control. Therefore, this cascaded controller shows superior performance by combining the advantages of admittance control and impedance control. We evaluate the controller in multiple-contact experiments on a six-degrees of freedom (6-DOF) industrial robot manipulator. The result shows that under various contact situations such as soft and rigid surfaces and free space, the proposed method can rapidly track the target and effectively maintain stability. In the experiments conducted on the robot in contact with various environments, the proposed control method reduced the steady-state error by more than 20% compared with the conventional admittance control. [ABSTRACT FROM AUTHOR]