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Abstract Near-infrared transparent films demonstrate important applications in many fields, but how to eliminate light interference from ultraviolet-visible region and how to tackle the trade-off effect between film thickness and transmittance remain as challenges. Herein, we report a near-infrared transparent film that achieves high-efficient combination of thin thickness (16 μm), suitable cut-off wavelength (890 nm), and ideal transmittance (TNIR > 90%, TVis

Abstract Obesity, a growing global health concern, is closely linked to depression. However, the neural mechanism of association between obesity and depression remains poorly understood. In this study, neural‐specific WFS1 deficiency exacerbates the vicious cycle of obesity and depression in mice fed a high‐fat diet (HFD), positioning WFS1 as a crucial factor in this cycle. Through human pluripotent stem cells (hESCs) neural differentiation, it is demonstrated that WFS1 regulates Zn2+ homeostasis and the apoptosis of neural progenitor cells (NPCs) and cerebral organoids by inhibiting the zinc transporter ZnT3 under the situation of dysregulated lipid metabolism. Notably, riluzole regulates ZnT3 expression to maintain zinc homeostasis and protect NPCs from lipotoxicity‐induced cell death. Importantly, riluzole, a therapeutic molecule targeting the nervous system, in vivo administration prevents HFD‐induced obesity and associated depression. Thus, a WFS1‐ZnT3‐Zn2+ axis critical is demonstrated for the vicious cycle of obesity and depression and that riluzole may have the potential to reverse this process against obesity and depression.

Osteosarcoma, a prevalent primary malignant bone tumor, often presents with lung metastases, severely impacting patient survival rates. Extracellular vesicles, particularly exosomes, play a pivotal role in the formation and progression of osteosarcoma-related pulmonary lesions. However, the communication between primary osteosarcoma and exosome-mediated pulmonary lesions remains obscure, with the potential impact of pulmonary metastatic foci on osteosarcoma progression largely unknown. This study unveils an innovative mechanism by which exosomes originating from osteosarcoma pulmonary metastatic sites transport the miR-194/215 cluster to the primary tumor site. This transportation enhances lung metastatic capability by downregulating myristoylated alanine-rich C-kinase substrate (MARCKS) expression. Addressing this phenomenon, in this study we employ cationic bovine serum albumin (CBSA) to form nanoparticles (CBSA-anta-194/215) via electrostatic interaction with antagomir-miR-194/215. These nanoparticles are loaded into nucleic acid-depleted exosomal membrane vesicles (anta-194/215@Exo) targeting osteosarcoma lung metastatic sites. Intervention with bioengineered exosome mimetics (anta-194/215@Exo) not only impedes osteosarcoma progression but also significantly prolongs the lifespan of tumor-bearing mice. These findings suggest that pulmonary metastatic foci-derived exosomes initiate primary osteosarcoma lung metastasis by transferring the miR-194/215 cluster targeting MARCKS, making the miR-194/215 cluster a promising therapeutic target for inhibiting the progression of patients with osteosarcoma lung metastases.

Abstract Zinc bromine flow batteries (ZBFBs) are well suited for stationary energy storage due to their attractive features of high energy density and low cost. Nevertheless, the ZBFBs suffer from low power density and limited efficiency owing to the relatively severe polarization of the Br2/Br− redox couple. Herein, a three‐dimensional (3D) hierarchical composite electrode based on core‐shell Ni/NiO heterostructures anchored on graphite felt (Ni/NiO@GF) is designed to promote the kinetics of the Br2/Br− couple, so as to improve the power density and efficiency of the ZBFB. In this design, the highly conductive carbon felt and Ni cores provide a composite electrode with a 3D electron transporting framework to guarantee excellent electronic conductivity, while the NiO shells possess great absorption ability to Br2 and brilliant catalytic activity for the Br2/Br− redox reaction to reduce the electrochemical polarization. As a result, an enhanced ZBFB with Ni/NiO@GF electrode shows an outstanding energy efficiency of 86% at 20 mA cm−2 and can be operated at a current density of up to 160 mA cm−2 with a respectable energy efficiency of 67%. These results exhibit a promising strategy to fabricate catalytic electrodes for high‐performance ZBFBs.

Abstract Background Anti-vascular endothelial growth factor (anti-VEGF) therapy is used for myopic choroidal neovascularization (mCNV). Patchy chorioretinal atrophy (pCRA) enlargement has been reported in mCNV cases associated with vision loss. Our aim was to compare the long-term effectiveness of anti-VEGF therapy alone versus anti-VEGF followed by posterior scleral reinforcement (PSR) in controlling myopic maculopathy in mCNV eyes. Methods We performed a retrospective review of the medical records of 95 high myopia patients (refractive error ≥ 6.00 diopters, axial length ≥ 26.0 mm) with mCNV. Patients were treated with anti-VEGF alone (group A) or anti-VEGF followed by PSR (group B). The following data were collected: refractive error, best corrected visual acuity (BCVA), ophthalmic fundus examination, ocular coherence tomography and ocular biometry at 12 and 24 months pre- and postoperatively. The primary outcomes were changes in pCRA and BCVA. Results In 26 eyes of 24 patients, the mean pCRA size significantly increased from baseline (0.88 ± 1.69 mm2) to 12 months (1.57 ± 2.32 mm2, t = 3.249, P = 0.003) and 24 months (2.17 ± 2.79 mm2, t = 3.965, P = 0.001) postoperatively. The increase in perilesional pCRA in group B (n = 12) was 98.2% and 94.2% smaller than that in group A (n = 14) at 12 and 24 months (Beta 0.57 [95% CI 0.01, 191 1.13], P = 0.048). In group B, 7 eyes (58.3%) gained more than 2 lines of BCVA compared with only 4 eyes (28.6%) in group A at 24 months. Conclusion Anti-VEGF therapy followed by PSR achieved better outcomes than anti-VEGF therapy alone in controlling the development of myopic maculopathy in mCNV and may constitute a better treatment option by securing a better long-term VA outcome.

The atmosphere is a complex nonlinear system, with the information of its temperature, water vapor, pressure, and cloud being crucial aspects of remote-sensing data analysis. There exist intricate interactions among these internal components, such as convection, radiation, and humidity exchange. Atmospheric phenomena span multiple spatial and temporal scales, from small-scale thunderstorms to large-scale events like El Niño. The dynamic interactions across different scales, along with external disturbances to the atmospheric system, such as variations in solar radiation and Earth surface conditions, contribute to the chaotic nature of the atmosphere, making long-term predictions challenging. Grasping the intrinsic chaotic dynamics is essential for advancing atmospheric analysis, which holds profound implications for enhancing meteorological forecasts, mitigating disaster risks, and safeguarding ecological systems. To validate the chaotic nature of the atmosphere, this paper reviewed the definitions and main features of chaotic systems, elucidated the method of phase space reconstruction centered on Takens’ theorem, and categorized the qualitative and quantitative methods for determining the chaotic nature of time series data. Among quantitative methods, the Wolf method is used to calculate the Largest Lyapunov Exponents, while the G–P method is used to calculate the correlation dimensions. A new method named Improved Saturated Correlation Dimension method was proposed to address the subjectivity and noise sensitivity inherent in the traditional G–P method. Subsequently, the Largest Lyapunov Exponents and saturated correlation dimensions were utilized to conduct a quantitative analysis of FY-4A and Himawari-8 remote-sensing infrared observation data, and ERA5 reanalysis data. For both short-term remote-sensing data and long-term reanalysis data, the results showed that more than 99.91% of the regional points have corresponding sequences with positive Largest Lyapunov exponents and all the regional points have correlation dimensions that tended to saturate at values greater than 1 with increasing embedding dimensions, thereby proving that the atmospheric system exhibits chaotic properties on both short and long temporal scales, with extreme sensitivity to initial conditions. This conclusion provided a theoretical foundation for the short-term prediction of atmospheric infrared radiation field variables and the detection of weak, time-sensitive signals in complex atmospheric environments.

The development of appropriate and effective periodate (PI) activation technology is currently a popular research area. This study presents a novel efficient photocatalytic activation approach of PI for pollutant degradation based on carbon nitride (g-C3N4) and visible light (Vis). The results show that the system can remove 92.3% of acid orange 7 (AO7) within 60 min under the g-C3N4/PI/Vis reaction system. The degradation rate constant (kobs) reached 4.08 × 10−2 min−1, which is 4.21, 5.16 times, and 51.3 times higher than that of the g-C3N4/Vis system (9.7 × 10−3 min−1), PI/Vis system (7.9 × 10−3 min−1) and the g-C3N4/PI system (7.96 × 10−4 min−1), respectively. Clearly, the addition of PI significantly enhances the degradation efficiency of AO7 in the system. Additionally, under the same reaction conditions, the presence of PI showed excellent oxidation capacity in the photoactivation process compared with other common oxidants, such as peroxymonosulfate, peroxydisulfate, and H2O2. Moreover, the g-C3N4/PI/Vis system showed excellent removal of AO7 across a wide range of pH levels and in the presence of various anions. Electron paramagnetic resonance (EPR) and quenching experiments suggested that the superoxide anions (•O2−) and singlet oxygen (1O2) dominated in the oxidation of pollutants in the g-C3N4/PI/Vis system. In addition, the catalyst showed relative stability during cyclic testing, although a slight reduction in degradation efficiency was observed. In brief, the g-C3N4/PI/Vis system is highly efficient and environmentally friendly, with significant application potential in wastewater treatment.

Hemostatic materials that allow fast and convenient hemostasis are urgently needed. However, obtaining an ideal hemostatic agent that exhibits biocompatibility, biodegradability, and hemostatic efficacy remains challenging. Recent studies demonstrate that morphological characteristics of hemostatic materials impact their efficacy. This study reports on the importance of morphological modification of traditional Chinese medicine plant polysaccharides. The hemostatic properties of Three-leaf Qing polysaccharides, optimized in particle (SYQ-P) and sponge (SYQ-S) forms, were investigated in vitro and in vivo. SYQ-S and SYQ-P exhibit excellent biodegradability and biocompatibility, thereby improving fibroblast cell proliferation. The hemostatic mechanism involves stable blood clot formation through intrinsic coagulation pathways. In a lethal mouse liver defect bleeding model, blood loss and clotting time were lower with polysaccharides use than with commercial hemostatic drugs. SYQ-S demonstrates instant water-triggered expansion and high absorption capacity, while the sponge-like morphological characteristics effectively improve blood component concentrations. With efficient hemostasis and excellent biocompatibility, SYQ-S dramatically accelerated wound healing in a full-thickness skin defect model in vivo. Thus, SYQ-S effectively promotes the formation of granulation tissue, collagen deposition, and angiogenesis, which ultimately accelerates wound healing. Our work highlights the design of natural Chinese medicine polysaccharides and presents a promising hemostatic agent for widespread clinical application.

Abstract Background Diabetic kidney disease (DKD) is the most frequent complication in patients with type 2 diabetes mellitus (T2DM). It causes a chronic and progressive decline in kidney function, and ultimately patients require renal replacement therapy. To date, an increasing number of clinical studies have been conducted to explore the potential and novel biomarkers, which can advance the diagnosis, estimate the prognosis, and optimize the therapeutic strategies at the early stage of DKD. In the current study, we sought to investigate the association of plasma myoglobin with DKD. Methods A total of 355 T2DM patients with DKD and 710 T2DM patients without DKD were enrolled in this study. Laboratory parameters including blood cell count, hemoglobin A1c, biochemical parameters, and plasma myoglobin were recorded. Patients were classified on admission according to the tertile of myoglobin and clinical parameters were compared between the groups. Pearson correlation analysis, linear regression, logistic regression, receiver operating characteristics (ROC) analysis, and spline regression were performed. Results Plasma myoglobin significantly increased in patients with DKD and was associated with renal function and inflammatory parameters. Plasma myoglobin was an independent risk factor for the development of DKD. The area under ROC curve of myoglobin was 0.831. Spline regression showed that there was a significant linear association between DKD incidence and a high level of plasma myoglobin when it exceeded 36.4 mg/mL. Conclusions This study shows that elevated plasma myoglobin level is closely associated with the development of kidney injury in patients with T2DM.

Satellite signals of opportunity positioning (SSOOP) attempts to work out a navigation solution with many non-global navigation satellite systems (GNSS) satellite signals, when GNSS signals are not available. It is promising in addressing GNSS vulnerability by using an overwhelming quantity of satellites with diverse signal formats, multiple radio bands, and global availability. How to figure out an applicable receiver position from the signals transmitted by anonymous satellites with unknown emission time? Toward massive SSOOP, this work contributes (a) a summary of the fundamental challenges by reviewing the mathematical formulations of SSOOP problem; (b) a set of proposed methods for SSOOP, including orbit predication, signal processing, and different modes of user positioning; (c) an analysis on the orbit prediction precision of two-line elements (TLEs) at different geographic locations on Earth and its impact on positioning performance, based on the orbit data obtained from our experimental (international ID: 40136) satellite that has a similar orbit height as the IRIDIUM satellites; and (d) the design and test result of an IRIDIUM SSOOP receiver prototype for verifying the proposed methods and corroborating the analysis, which showed a CEP ≈892 m (circular error probable) in standalone mode tests and a CEP ≈40 m in differential mode tests.

Disulfidptosis, a newly revealed form of cell death, regulated by numerous genes that has been recently identified. The exact role of disulfidptosis in lung adenocarcinoma (LUAD) still uncertain. Objective of this study was to explore potential prognostic markers among disulfidptosis genes in LUAD. By combining transcriptomic information from Gene Expression Omnibus databases and The Cancer Genome Atlas, we identified differentially expressed and prognostic disulfidptosis genes. By conducting least absolute shrinkage and selection operator with multivariate Cox regression, four disulfidptosis genes were selected to create the prognostic signature. The implementation of the signature separated the training and validation cohorts into groups with high- and low-risk. Subsequently, the model was verified by conducting an independent analysis of receiver operating characteristic (ROC) curves. Further comparisons were made between the two risk-divided groups with regards the tumor microenvironment, immune cell infiltration, immunotherapy response, and drug sensitivity. The signature was constructed using four disulfidptosis-related genes: SLC7A11, SLC3A2, NCKAP1, and GYS1. According to ROC curves, the signature was effective for predicting LUAD prognosis. In addition, the prognostic signature correlated with sensitivity to chemotherapeutic agents and the efficacy of immunotherapy in LUAD. Finally, through external validation, we showed that NCKAP1 are correlated with tumor migration, proliferation, and invasion of LUAD cells. GYS1 affects immune cell, especially M2 macrophage infiltration in the tumor microenvironment. The disulfidptosis four-gene model can reliably predict the prognosis of patients diagnosed with LUAD, thereby providing valuable information for clinical applications and immunotherapy.

Abstract Assembly is a critical step in the manufacturing process. Robotic assembly technology in automatic production lines has greatly improved the production efficiency. However, in assembly process, dynamic disturbances such as processing time change and advance delivery may occur, which cause the scheduling deviation. Traditional scheduling methods are not sufficient to meet the real-time and adaptive requirements in smart manufacturing. Digital twin (DT) has the characteristics of virtual-reality interaction and real-time mapping. In this paper, we propose a DT-based framework of task rescheduling for robotic assembly line (RAL) and its key methodologies, thus to realize the timely and dynamic adjustment of scheduling plan under uncertain interferences. First, a DT model of RAL task rescheduling composed of physical entity (PE), virtual entity (VE), and virtual-reality interaction mechanism is proposed. Then, a mathematical model is established. By analyzing the adaptive objective thresholds from the perspectives of event trigger and user demand trigger, a DT-driven multi-level (production unit level and line level) rescheduling strategy is proposed. Taking both the computing time and solution quality into consideration, the precedence graph is introduced to propose a rescheduling approach based on an improved discrete fireworks algorithm. Finally, the effectiveness of the proposed model and approach are verified by task scheduling experiments of RAL.

In this study, numerous triaxial hydraulic fracturing experiments are performed in continental shale outcrop samples and artificial samples with similar properties to investigate the HF propagation behavior under single-cluster and multi-cluster fracturing treatments. The single-cluster fracturing experimental results show that the interlayer interface (IF) has a significant effect on the HF height containment, which tends to shear slip under conditions of low IF bonded strength, low vertical stress difference, low wellbore traversing layer strength and low q⋅μ value (the product of injection rate and fracturing fluid viscosity), resulting in the arrest of HF by the IF, and the vertical propagation of HF is hindered. Seven types of HF geometries were observed under the interference of multiple IFs, which could be classified into three categories in the vertical plane based on degree of connection with IFs, namely, simple fracture, small-scale fishbone-like fracture, and large-scale fishbone-like fracture. The multi-cluster fracturing experimental results indicate that the vertical propagation law of HF under multi-cluster fracturing is similar to single-cluster fracturing. Under the conditions of small cluster spacing and large number of perforation clusters, it is difficult for each perforation cluster to initiate HF evenly, and the middle perforation cluster is more difficult than outers. In addition, injection-pressure curves in theory can provide some useful information for HF geometries identification. But it is difficult to judge whether the HFs initiate evenly and develop uniformly at multiple perforation clusters by observing the injection fracturing curves because the evolution law of the injection-pressure curves under the simultaneous propagation of multiple HFs and the propagation of a single HF are similar.

Abstract The molecular mechanisms underlying uric acid (UA)‐induced mitochondrial dysfunction and apoptosis have not yet been elucidated. Herein, we investigated underlying mechanisms of UA in the development of mitochondrial dysfunction and apoptosis. We analyzed blood samples of individuals with normal UA levels and patients with hyperuricemia. Results showed that patients with hyperuricemia had significantly elevated levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels, which may indicate liver or mitochondrial damage in patients with hyperuricemia. Subsequently, lipidomic analysis of mouse liver tissue mitochondria and human liver L02 cell mitochondria was performed. Compared with control group levels, high UA increased mitochondrial phosphatidylserine (PS) and decreased mitochondrial phosphatidylethanolamine (PE) levels, whereas the expression of mitochondrial phosphatidylserine decarboxylase (PISD) that mediates PS and PE conversion was downregulated. High UA levels also inhibited signal transducer and activator of transcription 3 （STAT3） phosphorylation as well as mitochondrial respiration, while inducing apoptosis both in vivo and in vitro. Treatment with allopurinol, overexpression of PISD, and lyso‐PE (LPE) administration significantly attenuated the three above‐described effects in vitro. In conclusion, UA may induce mitochondrial dysfunction and apoptosis through mitochondrial PISD downregulation. This study provides a new perspective on liver damage caused by hyperuricemia.

To address the issue of ineffective injection resulting from the consistent channeling of injected water through highly permeable channels in ultra-deep, high-temperature, high-salinity, and strongly heterogeneous reservoirs during the production process, a gel particle profile control agent suitable for high-temperature and high-salinity conditions was chosen. With the help of the glass etching visual microscopic model and the heterogeneous long core model, the formation mechanism of a water flooding channeling path and the distribution law of the remaining oil were explored, the microscopic profile control mechanism of the different parameters was clarified, and the profile control effect of macroscopic core displacement was analyzed. The research shows that the formation mechanism of a water flooding channeling path is dominated by the distribution law of the permeability section and the connection mode between different penetration zones. The remaining oil types after water flooding are mainly contiguous block, parallel throats, and multi-branch clusters. The profile control effect of gel particles on reservoir vertical heterogeneity is better than that of reservoir lateral heterogeneity. It was found that 10 wt% submicron particles with a median diameter of 600 nm play a good role in profiling and plugging pores of 5–20 μm. In addition, 10 wt% micron-sized particles with a median diameter of 2.63 μm mainly play a strong plugging role in the pores of 20–30 μm, and 5 wt% micron-sized particles with a median diameter of 2.63 μm mainly form a weak plugging effect on the pores of 10–20 μm. The overall profile control effect of 10 wt% submicro particles is the best, and changes in concentration parameters have a more significant effect on the profile control effect. In the macroscopic core profile control, enhanced oil recovery (EOR) can reach 16%, and the gel particles show plugging, deformation migration, and re-plugging. The research results provide theoretical guidance for tapping the potential of the remaining oil in strong heterogeneous reservoirs. To date, the gel particles have been applied in the Tahe oilfield and have produced an obvious profile control effect; the oil production has risen to the highest value of 26.4 t/d, and the comprehensive water content has fallen to the lowest percentage of 32.1%.

In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.

Abstract Background Yunnan is rich in fungal diversity and cultural diversity, but there are few researches on ethnomycology. In addition, extensive utilization of wild edible fungi (WEF), especially the ectomycorrhizal fungi, threatens the fungal diversity. Hence, this study aims to contribute to the ethnomycological knowledge in Pu’er Prefecture, Yunnan, China, including information on the fungal taxa presented in markets and natural habitats, with emphasis in ectomycorrhizal fungi (EMF). Methods Semi-structured interviews with mushroom vendors in markets and with mushroom collectors in natural habitats were conducted. Information related to local names, habitat, fruiting time, species identification, price, cooking methods and preservation methods of wild edible mushrooms were recorded. Wild edible fungi were collected from forests, and morphological and molecular techniques were used to identify fungal species. Results A total of 11 markets were visited during this study. The 101 species collected in the markets belonged to 22 families and 39 genera, and about 76% of them were EMF. A wealth of ethnomycological knowledge was recorded, and we found that participants in the 45–65 age group were able to judge mushroom species more accurately. Additionally, men usually had a deepest mushroom knowledge than women. A total of 283 species, varieties and undescribed species were collected from natural habitats, and about 70% of them were EMF. Mushroom species and recorded amounts showed correspondence between markets and the natural habitats on different months. Conclusion The present study shows that Pu’er Prefecture is rich in local mycological knowledge and fungal diversity. However, it is necessary to continue the research of ethnomycological studies and to design and conduct dissemination of local knowledge in order to preserve it, since it currently remains mainly among the elderly population.

Immature function and fragility hinder application of hESC-derived β cells (SC-β cell) for diabetes cell therapy. Here, the authors identify ZnT8 as a gene editing target to enhance the insulin secretion and cell survival under metabolic stress by abolishing zinc transport in SC-β cells.

Liver function indicators are often impaired in patients with type 2 diabetes mellitus (T2DM), who present higher concentrations of aspartate aminotransferase, alanine aminotransferase, and gamma-glutamyl transferase than individuals without diabetes. However, the mechanism of liver injury in patients with T2DM has not been clearly elucidated. In this study, we performed a lipidomics analysis on the liver of T2DM mice, and we found that phosphatidylethanolamine (PE) levels were low in T2DM, along with an increase in diglyceride, which may be due to a decrease in the levels of phosphoethanolamine cytidylyltransferase (Pcyt2), thus likely affecting the de novo synthesis of PE. The phosphatidylserine decarboxylase pathway did not change significantly in the T2DM model, although both pathways are critical sources of PE. Supplementation with CDP-ethanolamine (CDP-etn) to increase the production of PE from the CDP-etn pathway reversed high glucose and FFA (HG&FFA)-induced mitochondrial damage including increased apoptosis, decreased ATP synthesis, decreased mitochondrial membrane potential, and increased reactive oxygen species, whereas supplementation with lysophosphatidylethanolamine, which can increase PE production in the phosphatidylserine decarboxylase pathway, did not. Additionally, we found that overexpression of PCYT2 significantly ameliorated ATP synthesis and abnormal mitochondrial morphology induced by HG&FFA. Finally, the BAX/Bcl-2/caspase3 apoptosis pathway was activated in hepatocytes of the T2DM model, which could also be reversed by CDP-etn supplements and PCYT2 overexpression. In summary, in the liver of T2DM mice, Pcyt2 reduction may lead to a decrease in the levels of PE, whereas CDP-etn supplementation and PCYT2 overexpression ameliorate partial mitochondrial function and apoptosis in HG&FFA-stimulated L02 cells.

Abstract Disassembly is an important step in remanufacturing products. Robotic disassembly helps to improve disassembly efficiency. However, the end‐of‐life products often have the parts with uncertain quality, which is manifested as wear, fracture, deformation, corrosion, and other failure features. The parts failure features always have impacts on disassembly process. First, the evaluation method of parts failure features is researched, and the quantitative model of parts failure features is constructed using fuzzy models. Then, the disassembly information model is established by considering the influence of different failure degrees on the robotic disassembly process. Afterwards, to generate the optimal disassembly solution, deep reinforcement learning (DRL) is used to solve robotic disassembly sequence planning problem which considers parts failure features. Considering the influence of parts failure features on robotic disassembly time, the states, actions and rewards and environment are designed in DRL. Finally, a case study of the double shaft coupling as a waste product is carried out, and the proposed method is compared with the other methods to verify the effectiveness.

Aiming at the further acceleration of the aging speed in China， and considering the lack of effective exercise for the elderly， their shoulders， elbows and wrist joints often suffer from soreness， pain， and other problems. Thus， a new type of arm joint training instrument with multi-posture and multi-motion forms for family use is developed. Through theoretical design and calculation， and based on NX， a forward kinematic analysis and comparison of the four-bar mechanism without rapid return is conducted， 3 sets of rod length parameters (corresponding to 2 attitudes， 3 different motion forms， 9 different motion parameters respectively) are determined as a design scheme， and the force balance and load change analysis of the arm joint training equipment are carried out by the design scheme. Finally， according to the theoretical design calculation and the dynamic simulation analysis data of the NX virtual prototype， the performance of the physical prototype of the training instrument is trial-produced and tested. The test results show that the training instrument is safe， reliable and comfortable， and the human shoulders， elbows， wrists and waist joints can be better trained.

The number of resident space objects (RSOs) has been steadily increasing over time, posing significant risks to the safe operation of on-orbit assets. The accurate prediction of potential collision events and implementation of effective and nonredundant avoidance maneuvers require the precise estimation of the orbit positions of objects of interest and propagation of their associated uncertainties. Previous research mainly focuses on striking a balance between accurate propagation and efficient computation. A recently proposed approach that integrates uncertainty propagation with different coordinate representations has the potential to achieve such a balance. This paper proposes combining the generalized equinoctial orbital elements (GEqOE) representation with an adaptive Gaussian mixture model (GMM) for uncertainty propagation. Specifically, we implement a reformulation for the orbital dynamics so that the underlying state and the moment feature of the GMM are propagated under the GEqOE coordinates. Starting from an initial Gaussian probability distribution function (PDF), the algorithm iteratively propagates the uncertainty distribution using a detection-splitting module. A differential entropy-based nonlinear detector and a splitting library are utilized to adjust the number of GMM components dynamically. Component splitting is triggered when a predefined threshold of differential entropy is violated, generating several GMM components. The final probability density function (PDF) is obtained by a weighted summation of the component distributions at the target time. Benefiting from the nonlinearity reduction caused by the GEqOE representation, the number of triggered events largely decreases, causing the necessary number of components to maintain uncertainty realism also to decrease, which enables the proposed approach to achieve good performance with much more efficiency. As demonstrated by the results of propagation in three scenarios with different degrees of complexity, compared with the Cartesian-based approach, the proposed approach achieves comparable accuracy to the Monte Carlo method while largely reducing the number of components generated during propagation. Our results confirm that a judicious choice of coordinate representation can significantly improve the performance of uncertainty propagation methods in terms of accuracy and computational efficiency.

It is vital for the annotation of uncharacterized proteins by protein function prediction. At present, Deep Neural Network based protein function prediction is mainly carried out for dataset of small scale proteins or Gene Ontology, and usually explore the relationships between single protein feature and function tags. The practical methods for large-scale multi-features protein prediction still need to be studied in depth. This paper proposes a DNN based protein function prediction approach IGP-DNN. This method uses Grasshopper Optimization Algorithm (GOA) and Intuitionistic Fuzzy c-Means clustering (IFCM) based protein function modules extracting algorithm to extract the features of protein modules, utilizing Kernel Principal Component Analysis (KPCA) method to reduce the dimensionality of the protein attribute information, and integrating module features and attribute features. Inputting integrated data into DNN through multiple hidden layers to classify proteins and predict protein functions. In the experiments, the F-measure value of IGP-DNN on the DIP dataset reaches 0.4436, which shows better performance.

The sixth generation (6G) mobile networks will reshape the world by offering instant, efficient, and intelligent hyper-connectivity, as envisioned by the previously proposed Ubiquitous-X 6G networks. Such hyper-massive and global connectivity will introduce tremendous challenges into the operation and management of 6G networks, calling for revolutionary theories and technological innovations. To this end, we propose a new route to boost network capabilities toward a wisdom-evolutionary and primitive-concise network (WePCN) vision for the Ubiquitous-X 6G network. In particular, we aim to concretize the evolution path toward the WePCN by first conceiving a new semantic representation framework, namely semantic base, and then establishing an intelligent and efficient semantic communication (IE-SC) network architecture. In the IE-SC architecture, a semantic intelligence plane is employed to interconnect the semantic-empowered physical-bearing layer, network protocol layer, and application-intent layer via semantic information flows. The proposed architecture integrates artificial intelligence and network technologies to enable intelligent interactions among various communication objects in 6G. It features a lower bandwidth requirement, less redundancy, and more accurate intent identification. We also present a brief review of recent advances in semantic communications and highlight potential use cases, complemented by a range of open challenges for 6G.

Recovery from gastrointestinal (GI) surgery is often interrupted by the unpredictable occurrence of postoperative complications, including infections, anastomotic leak, GI dysmotility, malabsorption, cancer development, and cancer recurrence, in which the implication of gut microbiota is beginning to emerge. Gut microbiota can be imbalanced before surgery due to the underlying disease and its treatment. The immediate preparations for GI surgery, including fasting, mechanical bowel cleaning, and antibiotic intervention, disrupt gut microbiota. Surgical removal of GI segments also perturbs gut microbiota due to GI tract reconstruction and epithelial barrier destruction. In return, the altered gut microbiota contributes to the occurrence of postoperative complications. Therefore, understanding how to balance the gut microbiota during the perioperative period is important for surgeons. We aim to overview the current knowledge to investigate the role of gut microbiota in recovery from GI surgery, focusing on the crosstalk between gut microbiota and host in the pathogenesis of postoperative complications. A comprehensive understanding of the postoperative response of the GI tract to the altered gut microbiota provides valuable cues for surgeons to preserve the beneficial functions and suppress the adverse effects of gut microbiota, which will help to enhance recovery from GI surgery.

Abstract Background Nitrogen-fixing prokaryotes (diazotrophs) contribute substantially to nitrogen input in mangrove sediments, and their structure and nitrogen fixation rate (NFR) are significantly controlled by environmental conditions. Despite the well-known studies on diazotrophs in surficial sediments, the diversity, structure, and ecological functions of diazotrophic communities along environmental gradients of mangrove sediment across different depths are largely unknown. Here, we investigated how biological nitrogen fixation varied with the depth of mangrove sediments from the perspectives of both NFR and diazotrophic communities. Results Through acetylene reduction assay, nifH gene amplicon and metagenomic sequencing, we found that the NFR increased but the diversity of diazotrophic communities decreased with the depth of mangrove sediments. The structure of diazotrophic communities at different depths was largely driven by salinity and exhibited a clear divergence at the partitioning depth of 50 cm. Among diazotrophic genera correlated with NFR, Agrobacterium and Azotobacter were specifically enriched at 50–100 cm sediments, while Anaeromyxobacter, Rubrivivax, Methylocystis, Dickeya, and Methylomonas were more abundant at 0–50 cm. Consistent with the higher NFR, metagenomic analysis demonstrated the elevated abundance of nitrogen fixation genes (nifH/D/K) in deep sediments, where nitrification genes (amoA/B/C) and denitrification genes (nirK and norB) became less abundant. Three metagenome-assembled genomes (MAGs) of diazotrophs from deep mangrove sediments indicated their facultatively anaerobic and mixotrophic lifestyles as they contained genes for low-oxygen-dependent metabolism, hydrogenotrophic respiration, carbon fixation, and pyruvate fermentation. Conclusions This study demonstrates the depth-dependent variability of biological nitrogen fixation in terms of NFR and diazotrophic communities, which to a certain extent relieves the degree of nitrogen limitation in deep mangrove sediments. Video Abstract

Abstract Cancer is one of the major diseases that endanger human health. Current treatment options have low patient tolerance, poor prognosis, and strong side effects. Pulsed electromagnetic therapy can selectively kill cancer cells by taking advantage of their own electromagnetic sensitivity specificity. Pulsed electric fields (PEFs), pulsed electromagnetic fields (PEMFs), and cold atmospheric plasma (CAP) are three main means that have promising application in cancer therapy. Pulsed electromagnetic therapy showed significant anticancer ability in vitro and in vivo. In this paper, we summarize the basic principles, methods, and state of art research of PEFs, PEMFs, and PEMFs for cancer therapy. Based on cancer pro‐oxidation therapy, we propose a combination therapy of electromagnetic field‐enhanced CAP for cancer therapy.

Portunus trituberculatus (swimming crab) is an important breeding crab in China. The current breeding mode of swimming crab is still the traditional “spring seedling and winter harvest” breeding mode. In recent years, researchers have begun to explore a new off-season breeding mode through autumn seedling. In this study, the rate of embryonic development, embryo antioxidant ability and hatching rate of swimming crab in different water temperatures in an off-season breeding mode (breeding in early autumn) and digestive enzyme activity of newly hatched larvae were compared. The results showed that the duration of each development stage of swimming crab embryos was gradually reduced with increasing water temperature. The total development time was 9.43 d at 27°C and only 6.88 d at 33°C. These effects were accompanied by an increase in the development rate from 0.11 d-1 to 0.15 d-1. The total effective accumulated temperature under the 4 temperature conditions was basically maintained at about 150°C·d (147.08 ∼ 153.62°C·d), and there was no significant difference between different groups. The development of embryos at 27°C and 29°C was very synchronous, and no abnormal embryos were observed. Conversely, at 31°C, the later stage of development exhibited asynchrony, and diapause and death were noted in some embryos. At 33°C, more embryos died. The embryo hatching rate was approximately 70% at 27°C and 29°C, and the rate was significantly reduced at 31°C and 33°C. Specifically, the rate was only 13.89% at 33°C. As the water temperature increased, the activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-PX) as well as the total antioxidant capacity (T-AOC) and malondialdehyde (MDA) levels of embryos increased first and then decreased, reaching the highest value at 31°C. Catalase (CAT) activity exhibited the opposite trend which was the lowest at 29 °C with a value of only 0.17 U/mg prot and the highest at 33°C with a value of up to 0.51 U/mg prot. At temperatures of 27°C, 29°C and 31°C, the differences in various digestive enzymes of newly hatched larvae primarily manifested as the high activities of pepsin (PEP) and α-amylase (AMS) at 31°C, and other differences were not obvious. At 33°C during embryonic development, the activities of various digestive enzymes were relatively low, especially the activities of trypsin (TPS) and cellulase (CL), which were significantly lower than those of the other three temperature groups. Therefore, judging from the antioxidant index of embryos and the digestive enzyme activity of newly hatched larvae, the embryonic development was still good when the water temperature was 31°C, accompanied by water temperatures above 31°C that seriously affected enzyme activity. Overall, a temperature below 31°C represents the appropriate temperature for embryonic development in autumn in swimming crabs.

To explore the influence of different densities of Sinonovacula constricta on the composition of easily degradable organic matter and related functional bacteria, four experimental ecosystems were established: three polyculture systems (PMB1, PMB2, and PMB3) of Portunus trituberculatus and Marsupenaeus japonicus with different stocking densities of S. constricta (11.6, 23.1, and 34.7×104 ind./hm2, respectively) and a polyculture system with only P. trituberculatus and M. japonicus (PM). Among the easily degradable organic components in all aquaculture systems, protein content was the highest (0.74%~0.86%), followed by carbohydrates (0.16%~0.21%) and lipids (0.06%~0.13%). In the high-density (34.7×104 ind./hm2) S. constricta mixed culture system, the contents of carbohydrates, lipids, and proteins in the sediment were significantly lower than those of the other polyculture systems. The number of cellulose-decomposing bacteria in PMB3 was 3.79×106 cfu/g, which was significantly higher than that in the other systems. The number of starch-degrading bacteria and glutin-degrading bacteria was the lowest in PMB3, 1.26×104 cfu/g, and 160.00 cfu/g, respectively. The number of lipid-degrading bacteria in PMB3 was 0.77×104 cfu/g, which was significantly lower than that in the other systems. The easily degradable organics content in sediment was significantly positively correlated with the corresponding functional bacteria. The results showed that mixed culture of S. constricta could reduce the content of easily degradable organics in the sediment of mariculture ponds and change the number of functional bacteria in the sediment and the availability of degradable organic sediments may determine the abundance of corresponding degradable bacteria.

Based on the existing research, special plastic baskets were used as anti-injury shelters to explore the hidden behavior and molting growth of Portunus trituberculatus (Swimming crab) different initial body weights (Group A: 5.74 ± 0.11 g, Group B: 12.06 ± 0.15 g, Group C: 24.82 ± 0.41 g, Group D: 49.55 ± 1.12 g and Group E: 94.32 ± 1.19 g). The results showed that the shelter occupancy rate (SOR) during the daytime with all different body weights were significantly higher than that at night (P < 0.05), and the SOR was proportional to the crab’s body weight, among them, SOR in group E was as high as 71.52%. Meanwhile, the territorial consciousness of smaller body weight crabs (Groups A, B and C) was poor, and there was a phenomenon in which multiple individuals occupied the same shelter at the same time, while the individuals with the body weight of approximately 50 g and above (Groups D and E) had strong territorial consciousness, and most of them occupied one shelter alone. In all groups, more individuals chose to molt in the shelter on condition that there existed shelter, and the rate of molting in group B was high up to 81.15% and that in other groups was about 60%. Although the existence of shelter had no significant influence on the molting interphase (MI) of swimming crab in each group, the body weight growth rate (WGR) and carapace width growth rate (WGRC) after molting were increased by shelter compared with those without shelter. In addition, shelter could improve the survival rate (SR) in each group, and the effect of shelter on individuals with large body weight was relatively more obvious, in which the SR in Group D was significantly improved (P < 0.05). In general, the shelter can play a positive role in the whole growth of swimming crab. Therefore, it is necessary to set up the shelter in advance before the seedlings are put into production, which is helpful to increase the yield of swimming crab.

Abstract Background The study of protein complexes and protein functional modules has become an important method to further understand the mechanism and organization of life activities. The clustering algorithms used to analyze the information contained in protein-protein interaction network are effective ways to explore the characteristics of protein functional modules. Results This paper conducts an intensive study on the problems of low recognition efficiency and noise in the overlapping structure of protein functional modules, based on topological characteristics of PPI network. Developing a protein function module recognition method ECTG based on Topological Features and Gene expression data for Protein Complex Identification. Conclusions The algorithm can effectively remove the noise data reflected by calculating the topological structure characteristic values in the PPI network through the similarity of gene expression patterns, and also properly use the information hidden in the gene expression data. The experimental results show that the ECTG algorithm can detect protein functional modules better.

Roots assist plants in absorbing water and nutrients from soil. Thus, they are vital to the survival of nearly all land plants, considering that plants cannot move to seek optimal environmental conditions. Crop species with optimal root system are essential for future food security and key to improving agricultural productivity and sustainability. Root systems can be improved and bred to acquire soil resources efficiently and effectively. This can also reduce adverse environmental impacts by decreasing the need for fertilization and fresh water. Therefore, there is a need to improve and breed crop cultivars with favorable root system. However, the lack of high-throughput root phenotyping tools for characterizing root traits in situ is a barrier to breeding for root system improvement. In recent years, many breakthroughs in the measurement and analysis of roots in a root system have been made. Here, we describe the major advances in root image acquisition and analysis technologies and summarize the advantages and disadvantages of each method. Furthermore, we look forward to the future development direction and trend of root phenotyping methods. This review aims to aid researchers in choosing a more appropriate method for improving the root system.

In this work, we used the Direct Laser Writing Grayscale Photolithography technology to fabricate a normally-off p-GaN gate high-electron-mobility transistor with the air-bridge source-connection. The air-bridge source-connection was formed using the Direct Laser Writing Grayscale Photolithography, and it directly connected the two adjacent sources and spanned the gate and drain of the multi-finger p-GaN gate device, which featured the advantages of stable self-support and large-span capabilities. Verified by the experiments, the fabricated air-bridge p-GaN gate devices utilizing the Direct Laser Writing Grayscale Photolithography presented an on-resistance of 36 Ω∙mm, a threshold voltage of 1.8 V, a maximum drain current of 240 mA/mm, and a breakdown voltage of 715 V. The results provide beneficial design guidance for realizing large gate-width p-GaN gate high-electron-mobility transistor devices.

In pen + touch interfaces, two-handed pointing tasks are quite basic. We focus on two-handed pointing tasks on a stationary touchable tablet under asynchronous conditions, in which another target will not appear until one target is touched and dwelled. Fitts' law cannot accurately model such pointing tasks based on the results of our pilot study. This paper seeks to establish an ergonomics model for bimanual pointing tasks under asynchronous interaction. We designed and implemented three experiments with bimanual pointing tasks varying the target widths and distances. A series of bimanual pointing tasks with ten different IDs (Index of Difficulty) were carried out by 18 participants. The movement time (MT) and errors were collected and analyzed. Through experiments, we found that the index of difficulty of pointing tasks has a significant impact on MT (F9,170 = 6.276, p 2 = 0.973, while the Fitts' law model only achieves a fit of R2 = 0.623. The experimental results show that our model has a strong effectiveness and applicability for bimanual pointing tasks in pen + touch interfaces.

This paper proposed an improved full-order sliding-mode observer (IFSMO), applied to a sensorless control system of surface-mounted permanent magnet synchronous motor (SPMSM), to obtain a high-precision rotor speed and position. First, the IFSMO method, which combines the new sliding-mode function with the variable boundary layer function, is presented to suppress the chattering and accelerate the convergence speed of the system. Meanwhile, since the observer has the characteristics of a second-order low-pass filter, the high-frequency noise contained in the estimated back EMF signal can be effectively filtered out without an additional low-pass filter. Then, the proposed PLL is designed to obtain rotor position and speed. Finally, simulations and experiments of the SPMSM system based on the IFSMO method under different working conditions are implemented, which demonstrates the effectiveness of the proposed algorithm.

As one of the key technologies in 5th generation mobile networks, device-to-device (D2D) communication technology can significantly improve spectrum utilization, throughput and energy efficiency as well as reduce congestion in the networks. However, due to the spectrum sharing between D2D users (DUs) and cellular users (CUs), it may also cause serious interferences. In this paper, we adopt appropriate stochastic geometric tools to model and analyze the mutual interferences, based on which the coverage probabilities of different users are derived to evaluate the network performance. Specifically, we model the locations of CUs as a Poisson point process (PPP), while the locations of DUs are modelled as a Poisson hole process (PHP), which is driven by the PPP of CUs' locations due to the exclusion between the positions of CUs and DUs. Furthermore, the approximated expressions of user coverage probabilities are obtained by two methods, which are consistent with the simulation results. The first method is to dissolve the hole, and the second method is to approximate the PHP through a thinned PPP. In addition, the user ergodic data rates and the sum data rate of the networks are also derived through the second approach. The impacts of key parameters (such as the density of DUs and the size of the warning radius) on the ergodic rates and sum data rate are analyzed.

Moving shadow elimination plays an important role in the field of moving object detection. However, the accuracy of shadow elimination is an open question, due to illumination and complex texture. Furthermore, the problem of misclassification of moving object caused by shadow has also become increasingly serious. To address this problem, this paper presents a moving shadow elimination algorithm based on the fusion of multi-feature pattern, which can enhance the accuracy of moving object detection system. In this approach, a dual-channel HSV color space feature and a uniform extended scale invariant local ternary pattern (UESILTP) texture feature are synthesized to elimination shadow. It greatly overcomes the misjudgment of dark object by color feature and the false detection caused by inconspicuous texture characteristics of moving object. Meantime, a method of region growth is adopted to fill the existing cavities in the color space. Finally, qualitative and quantitative comparisons with state-of-the-art methods show that the algorithm is effective.

Energy harvesting cognitive radio network (EH-CRN) is a promising approach to address the shortage of spectrum resources and the increase of energy consumption simultaneously in wireless networks. In this article, we propose a novel machine learning (ML)-based energy-spectrum two-dimensional (2D) cognition technology to improve the sensing accuracy as well as the network throughput in EH-CRNs, which consists of sensing, prediction and decision modules. More specifically, we first study the 2D sensing module which is achieved by a carefully constructed dynamic Bayesian network (DBN) to effectively exploit the coupling between spectrum usage and energy harvesting in EH-CRNs. Then we propose a deep neural network (DNN) based 2D transmission decision module to optimize the transmission energy of secondary users (SUs). With our proposed novel 2D cognition scheme, SUs can characterize the energy-spectrum correlation and transmit data with optimal transmission energy. The proposed ML-based 2D cognition is evaluated via extensive simulations in terms of sensing accuracy, prediction accuracy, and network throughput, and simulation results indicate that our proposed scheme significantly outperforms the conventional one-dimensional (1D) cognition scheme working in spectrum or energy dimension only.

Razor clams (Sinonovacula constricta) are one of the major polyculture species in mariculture ponds, along with swimming crabs (Portunus trituberculatus), in the coastal zones of China, and their effect on CO2 fluxes are poorly studied. CO2 fluxes from mariculture ponds with swimming crabs, kuruma shrimp (Marsupenaeus japonicus) (CS) and mariculture ponds with swimming crabs, kuruma shrimp and razor clams (with different clam densities from low to high, CSB1, CSB2, CSB3, respectively) were measured during the farming season. The CO2 fluxes of CS, CSB1, CSB2, and CSB3 were −25.37, −30.23, −28.81 and −12.18 mg m−2 h−1, respectively. All the ponds acted as CO2 sinks across the water-air interface. Our results showed that water pH was a good indicator of the CO2 flux, and a pH value of 8.24 was the critical value dividing the dataset into influxes or effluxes in the mariculture ponds. Net primary production was also significantly correlated with the CO2 flux and is considered a key driver regulating the CO2 flux. Our findings indicate that the low clam stocking density used in this study could enhance the CO2 sink across the water-air interface by promoting phytoplankton biomass and net primary production, whereas the CO2 sink may be weakened with an increase in clam density due to a decline in phytoplankton biomass and net primary production.

In this study, the mating behavior of Portunus trituberculatus under indoor conditions and the role of shelters in its mating process were systematically studied by using behavioral observation methods. The results showed that the mating behavior of P. trituberculatus was divided into four stages: courtship and pre-copulatory guarding, reproductive moulting, copulation, and post-copulatory guarding. P. trituberculatus in the no shelter group (NSG) usually preferred to gather at the edges or corners of the cement tank, while P. trituberculatus in the shelter group (SG) preferred to hide in the shelters. During the whole experiment, the shelter occupancy rate of P. trituberculatus during the day (57.40%) was significantly higher than that at night (38.08%) (P

Under the too short arc scenario, the evolutionary-based algorithm has more potential than traditional methods in initial orbit determination. However, the underlying multimodal phenomenon in initial orbit determination is ignored by current works. In this paper, we propose a new enhanced differential evolution (DE) algorithm with multimodal property to study the angle-only IOD problem. Specifically, a coarse-to-fine convergence detector is implemented, based on the Boltzmann Entropy, to determine the evolutionary phase of the population, which lays the basis of the balance between the exploration and exploitation ability. A two-layer niching technique clusters the individuals to form promising niches after each convergence detected. The candidate optima from resulting niches are saved as supporting individuals into an external archive for diversifying the population, and a local search within the archive is performed to refine the solutions. In terms of performance validation, the proposed multimodal differential evolution algorithm is evaluated on the CEC2013 multimodal benchmark problems, and it achieved competitive results compared to 11 state-of-the-art algorithms, which present its capability of multimodal optimization. Moreover, several IOD experiments and analyses are carried out on three simulated scenarios of space-based observation. The findings show that, compared to traditional IOD approaches and EA-based IOD algorithms, the proposed algorithm is more successful at finding plausible solutions while improving IOD accuracy.

Ectomycorrhizal fungi establish a mutualistic symbiosis in roots of most woody plants. The molecular underpinning of ectomycorrhizal development was only explored in a few lineages. Here, we characterized the symbiotic transcriptomes of several milkcap species (Lactarius, Russulales) in association with different pine hosts. A time-course study of changes in gene expression during the development of L. deliciosus–Pinus taeda symbiosis identified 6 to 594 differentially expressed fungal genes at various developmental stages. Up- or down-regulated genes are involved in signaling pathways, nutrient transport, cell wall modifications, and plant defenses. A high number of genes coding for secreted proteases, especially sedolisins, were induced during root colonization. In contrast, only a few genes encoding mycorrhiza-induced small secreted proteins were identified. This feature was confirmed in several other Lactarius species in association with various pines. Further comparison among all these species revealed that each Lactarius species encodes a highly specific symbiotic gene repertoire, a feature possibly related to their host-specificity. This study provides insights on the genetic basis of symbiosis in an ectomycorrhizal order, the Russulales, which was not investigated so far.

With plentiful spectrum resources, millimeter-wave (mmWave) band has been the forefront candidate to enable the requirements of lower latency and faster data rate for future automotive systems. However, the incorporation of mmWave directional transmission and diversely vehicular mobility triggers frequent beam realignment, thus largely increasing the beamforming overhead and leaving less time for data transmission. In this paper, an energy-angle domain access and transmission frame structure is investigated for mmWave vehicle-to-everything communications, which consists of two phases, initial access and data transmission. Considering the transmission interruption issue caused by blockage, we propose an energy-angle domain initial access scheme, by which the signals are labeled by different directions with multi-power level. Several performance metrics are subsequently obtained to evaluate the proposed scheme. Next, we formulate the access time-throughput tradeoff problem mathematically and prove that there indeed exists the optimal access time which yields the highest throughput for data transmission. Moreover, a binary-decision beam tracking scheme is designed to maintain the directional link connection in the data transmission phase. Numerical evaluations and simulations have been conducted to verify the correctness of our point of view and the superiority of our proposed methods.

Wireless powered communication networks are promising in the next generation wireless communication systems since they can prolong the communication time of users. However, the wireless powered performance is limited due to the low energy harvesting efficiency caused by channel fading. In order to tackle this issue, rotary-wing unmanned aerial vehicle (UAV) enabled wireless powered communication network (WPCN) is first proposed to provide energy harvesting and information transmission to multiple ground users. Then, the energy consumption minimization problem for the UAV-enabled WPCN is formulated subject to the speed, initial and final positions of the UAV, the energy harvesting causality and user scheduling constraints. Finally, an efficient algorithm by employing the path discretization and successive convex approximation techniques is proposed to solve the challenging non-convex problem. Simulation results show that our proposed scheme can efficiently balance the energy harvesting phase and transmission phase based on the optimal trajectory design, moreover, it outperforms other benchmark schemes in terms of the energy consumption.

In this paper, we investigate the air-to-ground multi-traffic backhaul enabled by unmanned aerial vehicle (UAV) equipped with multiple radio access networks (RANs). Faced with the challenging traffic designation problem over diverse RANs, an efficient packet delivery scheme based on multi-priority batch arrival queuing theory is proposed to match various traffics with multiple RANs. Specifically, our contributions are three-fold: 1) The average queuing time of UAV-enabled multi-RAN access is theoretically derived according to multi-priority batch arrival queuing theory. 2) The priority factor and z-type utility function are well tailored by leveraging the derived queuing time. 3) A multiple traffic backhaul strategy is further proposed by exploiting the priority factor and z-type utility function to optimize the packet delivery, i.e., maximizing the delay utility via joint network selection and power allocation for diverse RANs. The simulation results show that the average delay of delay-sensitive packets is reduced by 15%, and the overall packet delivery quality is improved considerably.

Microsatellites have stringent demands for thermal dissipation systems with high efficiency but low weight, which is a difficult combination to obtain using current technologies. The design method of a new cooling system consisting of hollow metallic microlattice material filled with liquid is developed and proposed, and its heat dissipation performance is analyzed through experimental tests and numerical simulations. Through the analysis results of the influences of the microstructures of the hollow microlattice material, it is found that the effective coefficient (the number of channels taking part in convection) has the highest influence on the heat dissipation performance. Numerical simulation results illustrated that the heating surface temperature can be reduced to 301.7 K through special design, which can meet the heat dissipation requirement of most microsatellites. The new microlattice cooling system in this study improves heat dissipation performance while having very low structural weight, thus providing a feasible substitute for thermal control systems in microsatellites.

In this paper, to enhance the spectrum utilization in cognitive unmanned aerial vehicle networks (CUAVNs), we propose a cooperative spectrum sensing scheme based on a continuous hidden Markov model (CHMM) with a novel signal-to-noise ratio (SNR) estimation method. First, to exploit the Markov property in the spectrum state, we model the spectrum states and the corresponding fusion values as a hidden Markov model. A spectrum prediction is obtained by combining the parameters of CHMM and a preliminary sensing result (obtained from a clustered heterogeneous two-stage-fusion scheme), and this prediction can further guide the sensing detection procedure. Then, we analyze the detection performance of the proposed scheme by deriving its closed-formed expressions. Furthermore, considering imperfect SNR estimation in practical applications, we design a novel SNR estimation scheme which is inspired by the reconstruction of the signal on graphs to enhance the proposed CHMM-based sensing scheme with practical SNR estimation. Simulation results demonstrate the proposed CHMM-based cooperative spectrum sensing scheme outperforms the ones without CHMM, and the CHMM-based sensing scheme with the proposed SNR estimator can outperform the existing algorithm considerably.

Recently, electrides have received increasing attention due to their multifunctional properties as superconducting, catalytic, insulating, and electrode materials, with potential to offer other performance and possess novel physical states. This work uncovers that Li _5 N as an electride possess four novel physical states simultaneously: electride state, super-coordinated state, superconducting state, and superionic state. By obtaining high-pressure phase diagrams of the Li–N system at 150–350 GPa using a crystal structure search algorithm, we find that Li _5 N can remain stable as P 6/ mmm structure and has a 14-fold super-coordination number, as verified by Bader charge and electron localization function analysis. Its superconducting transition temperature reaches the highest at 150 GPa ( T _c = 48.97 K). Besides, Li _5 N exhibits the superionic state at 3000 K, in which N atoms act like solid, while some Li atoms flow like liquid. The above results are further verified at a macroscopic level by using deep learning potential molecular dynamics simulations.

In the above article [1], the ordinate unit of Figure 9 was labeled incorrectly.

Iridoviruses are an important pathogen of ectothermic vertebrates and are considered a significant threat to aquacultural fish production. Recently, one of the most economically important marine species in China, the large yellow croaker (Larimichthys crocea), has been increasingly reported to be the victim of iridovirus disease. In this study, we isolated and identified a novel iridovirus, LYCIV-ZS-2020, from cage-cultured large yellow croaker farms in Zhoushan island, China. Genome sequencing and subsequent phylogenetic analyses showed that LYCIV-ZS-2020 belongs to the genus Megalocytivirus and is closely related to the Pompano iridoviruses isolated in the Dominican Republic. LYCIV-ZS-2020 enriched from selected tissues of naturally infected large yellow croaker was used in an artificial infection trial and the results proved its pathogenicity in large yellow croaker. This is the first systematic research on the genetic and pathogenic characterization of iridovirus in large yellow croakers, which expanded our knowledge of the iridovirus.