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The ReaxFF can describe the properties of energetic materials (EMs) at equilibrium state, but does not work properly in simulating high-energy particle irradiation process because of its weak short-range interaction. In this paper, a modification was made for such a potential by connecting Ziegler-Biersack-Littmark (ZBL) potential to ReaxFF-lg through comparing to Density Functional Theory (DFT) results to accurately describe short-range interactions. After modification, the newly fitted ReaxFF-lg/ZBL potential predicts better the equation of state for EMs In displacement cascade simulations, comparing to results from ab initio molecular dynamics (AIMD), ReaxFF-lg/ZBL presented the similar transferred energy from a primary knock-on atom to surrounding atoms, better than the original ReaxFF-lg potential. Further large-scale displacement cascade simulations indicated ReaxFF-lg/ZBL could be applied for cascade simulations with PKA energy from less than 1 keV to high energy (e.g. 35 keV) cases, which is suitable for effectively simulating high-energy displacement cascades in EMs using molecular dynamics method.

Copper pillar bumps are widely utilized in advanced packaging technologies, representing a crucial foundation for 3D packaging. However, the mechanical properties of Sn3Ag bumps on copper columns often fall short of meeting increasingly demanding service conditions. Additionally, the loss of effectiveness due to excessive growth of intermetallic compounds at the interface needs to be addressed. To enhance the Sn₃Ag bumps and inhibit the excessive growth of intermetallic compounds, CoSn₃ nanocrystals were prepared, and Sn₃Ag–CoSn₃ composite copper pillar bumps were fabricated through composite electroplating. Upon reflowing, the CoSn3 nanocrystals decomposed, resulting in a significant formation of (Cu,Co)6Sn5 nanoparticles within the Sn3Ag matrix. The (Cu,Co)6Sn5 nanoparticles not only strengthen the solder joints by pinning, but also significantly reduced the excessive growth of interfacial intermetallic compounds, ultimately improving the service performance and reliability of the solder joints.

Abstract The toxicity of lunar dust (LD) to astronauts' health has been confirmed in the Apollo missions and subsequent biological experiments. Therefore, it is crucial to understand the biological toxicity of lunar dust for future human missions to the Moon. In this study, we exposed human lung epithelial cells (BEAS-2B) and peripheral blood B lymphocytes (AHH-1) to varying concentrations (0, 500, 1000, and 1500 μg/ml) of a lunar dust simulant (LDS) called CLDS-i for 24 and 48 h. The results provided the following key findings: (1) LDS induction of cell damage occurred through oxidative stress, with the levels of reactive oxygen species (ROS) in BEAS-2B cells being dependent on the duration of exposure. (2) Necrosis and early apoptosis were observed in BEAS-2B cells and AHH-1 cells, respectively. In addition, both cells showed lysosomal damage. (3) Genes CXCL1, SPP1, CSF2, MMP1, and POSTN are implicated in immune response and cytoskeletal arrangement regulation in BEAS-2B cells. Considering the similarities in composition and properties between CLDS-i and real lunar dust, our findings not only enhance the understanding of LDS toxicity, but also contribute to a better comprehension of the genomic alterations and molecular mechanisms underlying cellular toxicity induced by LD. These insights will contribute to the development of a biotoxicology framework aimed at safeguarding the health of astronauts and, consequently, facilitating future human missions to the Moon.

With the ongoing advancements and innovations of electronic device, the demand for low-melting-point solder is rising, especially for flexible printed electronics. The service environments of electronic device are complex and diverse, which have raised concerns regarding long-term service reliability in solder materials. In this work, a novel type of 30In33Sn25Bi4AgxZn low-melting-point alloy solder was proposed. The effects of Zn content on the corrosion resistance and electrochemical migration (ECM) resistance of the alloy system were investigated through electrochemical test and water drop test (WDT). The passivation film on the surface and the amorphous region of InSnBiAg8Zn alloys effectively inhibits the anodic dissolution of Zn atoms, improves the corrosion resistance of the alloy and delays the occurrence of electrochemical migration failure. The microscopic mechanism of ECM was revealed by conducting in-situ observations of the migration process of the alloy solder and analyzing the composition and morphology of the anode alloy and the migration products.

Abstract Aviation emergency management is playing a more and more important role in the aviation field. How to make effective use of massive heterogeneous and multi-source aviation accident knowledge has become a great challenge for aviation emergency management. Aiming at the problems such as too long physical length, mixed and composite entities, similar character of domain entity names, information difference between entities, separation of codes between entities, coding errors during transmission, etc., the construction method of knowledge map of civil aviation emergencies is studied. In previous research methods, entity link is always divided into two parts, that is, first detection and then disambiguation, which makes the mentioned entity and the candidate entity are encoded separately, and there is error transmission between the two parts, modules cannot communicate with each other, and the close association between entities cannot be well learned. In this paper, we proposed an end-to-end entity linking method based on two-layer BiLSTM model joint coding vectorize each word of civil aviation text information, and then concatenate feature vectors into two-layer BiLSTM model to obtain high-level context representation. Because the joint encoding of boundary information can reduce the error transmission, information is exchanged between candidate entities during the initial encoding to enhance the closeness between candidate entities and candidate entities. The experimental results show that compared with other sota models, the F1 value of the proposed model reaches 88.97%.

Background: Flavonoids are one of the most important metabolites with vast structural diversity and a plethora of potential pharmacological applications, which have drawn considerable attention in the laboratory. Nevertheless, it remains uncertain how many candidates were progressed to clinical application. Aim of Review: We carried out a critical review of natural and semi-synthetic flavonoid drugs and candidates undergoing different clinical phases worldwide by applying an adequate search method and conducted a brief cheminformatic and bioinformatic analysis. It was expected that the obtained results might narrow the screening scope and reduce the cost of drug research and development. Key scientific Concepts of Review: To our knowledge, this is the most systematic summarization of flavonoid-based drugs and clinical candidates to date. It was found that a total of 19 flavonoid-based drugs have been approved for the market, and of these, natural flavonoids accounted for 52.6%. Besides, a total of 36 flavonoid-based clinical candidates are undergoing or suspended in different phases, and of these, natural flavonoids account for 44.4%. Thus, natural flavonoids remain the best option for finding novel agents/active templates, and when investigated in conjunction with synthetic chemicals and biologicals, they offer the potential to discover novel structures that can lead to effective agents against a variety of human diseases. Additionally, flavonoid-based marketed drugs have been successful in cardiovascular treatment, and the related drugs account for more than 30% of marketed drugs. However, the use of flavonoids as antineoplastic and immunomodulating agents is not likely for approximately 50% of the candidates suspended in the clinical stage. Interestingly, the marketed drugs covered a broader range of chemical spaces based on size, polarity, and three-dimensional structure compared to the clinical candidates. In addition, flavonoid glycosides with poor oral bioavailability account for 36.8% of the marketed drugs, and thus, they could be thoroughly investigated.

The stability of the surrounding rock under high temperature is pivotal to the efficient and safe production of high-temperature fluidized mining engineering. To investigate the stability of rocks under high temperature, this paper takes the roof sandstone of Tongxin coal mine, examining changes in its physical parameters such as mass, dimensions, wave velocity, porosity, and permeability after treatment at various temperatures (20–700°C). The results showed that parameters like mass and wave velocity decreased with increasing temperature, while dimensions, porosity, fracture density, and permeability increased. The patterns of change in these physical properties with temperature exhibit a high degree of consistency. Additionally, composition analysis and thermal analysis were conducted to understand the physical and chemical changes occurred in sandstone. Scanning electron microscopy was used to observe microstructural changes in the sandstone. After analysis, the evolution of the internal structure of Tongxin sandstone with heat treatment is categorized into three stages. (1) stable change Stage (20–450°C, 650–700°C): Dominated by dehydration and thermal stress, where pore and fracture structures develop slowly; (2) rapid change stage (450–550°C, 600–650°C): Dominated by the kaolinite dehydroxylation, leading to increased porosity but decreased average pore size; (3) intense change stage (550–600°C): Dominated by the quartz phase transitions, where the thermal stress generated by quartz phase transitions causes dramatic alterations in the internal structure of the sandstone. Furthermore, a correlation model between wave velocity and permeability of sandstone at high temperatures was established based on the interrelationship of these physical properties, providing a new method for real-time monitoring of permeability under high-temperature conditions.

Energetic materials (EMs) are generally used in various conditions including under the neutron irradiation environment. To understand the radiation damages and related effects on mechanical property of EMs is important and necessary for their further applications under radiation conditions. In this paper, the displacement cascades are firstly simulated with molecular dynamics method in an octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) with the maximum energy of a primary knock-on atom (PKA) up to around 5 keV. The bond breaking, formation of free radicals, new gas molecules and interstitial and vacancy clusters, are all observed after displacement cascades, which can be used to explain the change of color and release of gas after irradiation as reported in experiments. Furthermore, the effect of above defect formation on mechanical property is calculated based on tensile stress simulations on damaged HMX. The results clearly show the appearance of strong stress gradient around defect formation region, resulting in lower external stress needed to deform the system. Thus, the radiation softening can be explored according to these results, same to experimental reports. Therefore, all these results indicate the radiation damages induced by energetic particles should be considered seriously for further application of energetic materials in nuclear conditions.

To address the demand for multilevel package, a low-melting-point high entropy alloy (HEA) solder was developed. It consists of 43In28Sn14Bi9Zn6Ag micro- and nano-particles with a melting point of about 62.80 °C. We obtained 43In28Sn14Bi9Zn6Ag nanoparticles by combining ultrasonic heating interaction with a ''hot shock'' process. Upon reflowing at 115 °C for 5 min, a Cu/Zn/Ag ternary intermetallic compound (IMC) formed at the interface between the solder and the copper substrate, leading to a shear strength of 40 MPa. The microstructure of this joint exhibits a complex composition with at least three phases, including Bi3In5 phase, Ag5Zn8 phase, and In0.2Sn0.8 solid solution. The stable Ag5Zn8 phase not only enhances the overall strength of the alloy matrix but also impedes the diffusion of In and Bi atoms, thereby preventing the segregation of the Bi3In5 phase. The high mixing entropy and pronounced lattice distortion in this high entropy alloy hinder the diffusion of elements within the solder matrix, mitigating the issue of excessive interfacial IMC growth. Consequently, the solder joints exhibit little degradation even after a high-temperature aging test. This high-entropy alloy solder has promising potential for multi-level chip stacking in 3D packaging.

This paper briefly summarizes the importance, current situation and existing problems of earthquake science popularization in primary and secondary schools, and focuses on the development path of earthquake science popularization based on STEAM education concept. On the basis of clarifying the main purpose, service target group of earthquake science popularization education, and effective popular science content and form, this paper applies the concept of STEAM education to propose the effective path of earthquake science popularization in primary and secondary schools. Taking the junior high school section as an example to make a specific case analysis, this paper suggests to build an earthquake science popularization ecosystem from the perspective of STEAM education. STEAM education is an interdisciplinary education concept that integrates science, technology, engineering, arts and mathematics, emphasizing the integration of disciplines. It is a new form of learning in which taking projects as the main line, teachers as the lead, and students as the main body. This study argues that STEAM education needs to be integrated into the earthquake science popularization, and a high-quality science education system should be constructed, covering both on- and off-campus educational activities and active learning ability, so as to create an ecosystem suitable for the development of science popularization education.

There are a series of engineering risks, such as ground subsidence, building tilt and cracking, in the process of shield tunnel driving through buildings, which have many adverse effects on urban residents and engineers. In particular, the differences in the effects of the interaction of two-lane tunnels on the building structure and ground deformation field are less often considered under different spatial effects such as construction sequences and tunnel spacings. As well as the problem of analyzing the building as a whole out of reality. To solve these problems, the spatial effect of the shield tunnel underpassing the shallow foundation building is simulated by Plaxis3D software to study the sensitivity analysis of surface settlement and the internal forces and deformation law of the building above in the process of tunneling underpassing with different depths of burial H and horizontal distance D of the double line tunnel. The engineering impact zoning method can investigate the safety of tunnels and buildings under different spatial effects when tunnels pass through buildings. The splitting of the building into plates and columns can reveal the forces and deformation laws of different structural parts. The results show that during the construction process of the double-line tunnel, the tunnel constructed first has a “blocking effect” on the tunnel constructed later, which affects the distribution of the disturbance area to a certain extent and changes the curve shape of the settlement trough. When the “blocking effect” occurs, the surface settlement and building deformation will be significantly reduced. In the internal forces of the building, the plate structure is mainly subjected to changes in axial forces, while the column structure is mainly affected by shear forces and bending moments. The factor of safety of tunnels decreases as the tunnel spacing decreases and as the building loads above increase.

Air traffic is exhibiting the characteristics of large flow, strong coupling, and high time variation. Therefore, the complex network of air traffic is more vulnerable to disturbances. When it is disturbed, the failure of some nodes spreads through dependency relationships in the network, resulting in cascade failure. In the event of a cascade failure, the network may quickly collapse until it is paralyzed, with widespread delays and flight cancellations. The current flow management and deployment methods still remain in the control-oriented stage, which is mainly completed by air traffic controls (ATCs), and lack of accurate flow adjustment and effective utilization of capacity. The whole air traffic system and its peripheral factors are intricate, so human and social factors must be integrated into the control and decision-making of the system. Considering engineering and social factors such as operation environment, social environment, personnel, rules, equipment, and information processing, we analyse the air traffic in a cyber-physical-social system (CPSS). To reflect the actual system behaviour rules, dynamic response, limit state, and so on, the corresponding computational experiment and comprehensive evaluation system are established. Based on neural networks and other technologies, a resource prediction scheme based on task demand is proposed for multi-dimensional resources such as airports, air routes, and ATC, to reduce the cost of system resource scheduling and improve resource utilization through resource prediction and adjustment. Finally, the accuracy of the proposed resource prediction algorithm is verified by theoretical analysis and simulation.

Bisphenol A (BPA) is a growing concern as an endocrine-disrupting chemical due to its adverse health effects. However, the association between BPA and sperm quality in adult human males remains unclear. The aim of this study was to assess the daily life exposure level of BPA and analyze its correlation with sperm quality in males. Patients who sought treatment in Chinese infertility clinics between May and October 2023 were selected as study subjects. We determined participants' serum BPA content using high-performance liquid chromatography. Sperm count and motility were assessed using a computer-aided sperm analysis system, while sperm morphology was analyzed using an improved Papanicolaou stain. A total of 405 participants, averaging 33.01 ± 5.44 years old, were included. We observed low semen quality among participants in infertility clinics. Principal component analysis was performed for each semen quality index, and three principal components reflecting sperm motility, count, and morphology were extracted. The participants' mean serum BPA level was 6.96 ng/mL. Negative correlations were observed between serum BPA content and total sperm count, sperm density, forward motility rate, and non-forward motility rate. A positive correlation was found between the non-motile sperm rate and the head deformity rate. Morphological abnormalities were the predominant adverse effects observed. Despite low daily life BPA exposure, long-term low-dose exposure in the general population may damage semen quality. This study provides a scientific basis for managing health risks associated with BPA exposure.

Alzheimer’s disease (AD) is the most common fatal neurodegenerative disease among the elderly worldwide, characterized by memory and cognitive impairment. The identification of biomarkers for AD is crucial and urgent to facilitate the diagnosis and intervention. The aim of this study was to evaluate the diagnostic value of acyl-Coenzyme A thioesterase 7 (ACOT7) as a serum biomarker for the prediction of AD. In our study, we observed a significant increase in ACOT7 expression in patients (n = 366) with AD and animal (n = 8–12) models of AD, compared to the control group. A significant negative correlation was found between ACOT7 levels and Mini-Mental State Examination (MMSE) scores (r = −0.85; p

Identified as the pathogenic genes of Alzheimer's disease (AD), APP, PSEN1, and PSEN2 mainly lead to early-onset AD, whose course is more aggressive, and atypical symptoms are more common than sporadic AD. Here, a novel missense mutation, APP E674Q (also named “Shanghai APP”), was detected in a Chinese index patient with typical late-onset AD (LOAD) who developed memory decline in his mid-70s. The results from neuroimaging were consistent with AD, where widespread amyloid β deposition was demonstrated in 18F-florbetapir Positron Emission Tomography (PET). APP E674Q is close to the β-secretase cleavage site and the well-studied Swedish APP mutation (KM670/671NL), which was predicted to be pathogenic in silico. Molecular dynamics simulation indicated that the E674Q mutation resulted in a rearrangement of the interaction mode between APP and BACE1 and that the E674Q mutation was more prone to cleavage by BACE1. The in vitro results suggested that the E674Q mutation was pathogenic by facilitating the BACE1-mediated processing of APP and the production of Aβ. Furthermore, we applied an adeno-associated virus (AAV)-mediated transfer of the human E674Q mutant APP gene to the hippocampi of two-month-old C57Bl/6 J mice. AAV-E674Q-injected mice exhibited impaired learning behavior and increased pathological burden in the brain, implying that the E674Q mutation had a pathogenicity that bore a comparison with the classical Swedish mutation. Collectively, we report a strong amyloidogenic effect of the E674Q substitution in AD. To our knowledge, E674Q is the only pathogenic mutation within the amyloid processing sequence causing LOAD.

Abstract Background The relationship between periodontitis and Alzheimer’s disease (AD) has attracted more attention recently, whereas profiles of subgingival microbiomes and gingival crevicular fluid (GCF) metabolic signatures in AD patients have rarely been characterized; thus, little evidence exists to support the oral-brain axis hypothesis. Therefore, our study aimed to characterize both the microbial community of subgingival plaque and the metabolomic profiles of GCF in patients with AD and amnestic mild cognitive impairment (aMCI) for the first time. Methods This was a cross-sectional study. Clinical examinations were performed on all participants. The microbial community of subgingival plaque and the metabolomic profiles of GCF were characterized using the 16S ribosomal RNA (rRNA) gene high-throughput sequencing and liquid chromatography linked to tandem mass spectrometry (LC–MS/MS) analysis, respectively. Results Thirty-two patients with AD, 32 patients with aMCI, and 32 cognitively normal people were enrolled. The severity of periodontitis was significantly increased in AD patients compared with aMCI patients and cognitively normal people. The 16S rRNA gene sequencing results showed that the relative abundances of 16 species in subgingival plaque were significantly correlated with cognitive function, and LC–MS/MS analysis identified a total of 165 differentially abundant metabolites in GCF. Moreover, multiomics Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO) analysis revealed that 19 differentially abundant metabolites were significantly correlated with Veillonella parvula, Dialister pneumosintes, Leptotrichia buccalis, Pseudoleptotrichia goodfellowii, and Actinomyces massiliensis, in which galactinol, sn-glycerol 3-phosphoethanolamine, D-mannitol, 1 h-indole-1-pentanoic acid, 3-(1-naphthalenylcarbonyl)- and L-iditol yielded satisfactory accuracy for the predictive diagnosis of AD progression. Conclusions This is the first combined subgingival microbiome and GCF metabolome study in patients with AD and aMCI, which revealed that periodontal microbial dysbiosis and metabolic disorders may be involved in the etiology and progression of AD, and the differential abundance of the microbiota and metabolites may be useful as potential markers for AD in the future.

Abstract The dried rhizomes of Coptis chinensis hold significance in Chinese medicine. Monocropping C. chinensis under the shade of a manmade scaffold, the primary planting mode, poses a threat to the ecological balance. In recent years, the practice of C. chinensis–Cunninghamia lanceolata understory cultivation has gained prevalence in southwest China. However, there is no evidence to suggest that understory cultivation enhances the viability, yield, or isoquinoline alkaloid content of C. chinensis. This study examined the physiological properties, yield indicators, and isoquinoline alkaloid content to investigate variations in C. chinensis in response to understory cultivation. Transcriptome analysis was conducted to elucidate potential mechanisms driving these alterations. The results indicate that understory cultivation significantly enhances the viability, yield, and levels of epiberberine, palmatine, and berberine in C. chinensis while reducing coptisine content. Transcriptomic analyses identified 2062 upregulated and 1853 downregulated genes in the understory cultivation system. Pathways such as “phenylpropanoid biosynthesis,” “zeatin biosynthesis,” “photosynthesis,” “tyrosine metabolism,” “isoquinoline alkaloid biosynthesis,” and “starch and sucrose metabolism” exhibited significant enrichment of differentially expressed genes (DEGs). DEGs involved in these pathways were thoroughly analyzed. INV, BGL-2, BGL-4, SPS-2, AMY-3, Psb B, Psb R, Psb S, Psa D, Psa E, Psa H, Psa O, Pet C, Pet H, deta, and b exhibited significant positive correlations with plant fresh weight, aboveground fresh weight, and underground fresh weight. 6-OMT-2 and COMT1-3 displayed significant positive correlations with coptisine content, but negative correlations with epiberberine, palmatine, and berberine content. ZOG-1, ZOG-3, TAT, PPO, POD-13 and UGT 73C5-1 showed noteworthy positive correlations with berberine content. Conversely, MIFH, POD-4, POD-5, and POD-8 displayed significant positive correlations with epiberberine, palmatine, and berberine content. POD-5, and POD-7 were significantly negatively correlated with coptisine content. Furthermore, gene expression levels determined by qRT–PCR aligned with the transcriptomic sequencing results, confirming the reliability of the transcriptomic findings. The results of this study contribute evidence elucidating potential mechanisms through which C. chinensis responds to understory cultivation. Graphical Abstract

Abstract In the realm of air combat, autonomous decision-making in regard to Unmanned Aerial Vehicle (UAV) has emerged as a critical force. However, prevailing autonomous decision-making algorithms in this domain predominantly rely on rule-based methods, proving challenging to design and implement optimal solutions in complex multi-UAV combat environments. This paper proposes a novel approach to multi-UAV air combat decision-making utilizing hierarchical reinforcement learning. First, a hierarchical decision-making network is designed based on tactical action types to streamline the complexity of the maneuver decision-making space. Second, the high-quality combat experience gained from training is decomposed, with the aim of augmenting the quantity of valuable experiences and alleviating the intricacies of strategy learning. Finally, the performance of the algorithm is validated using the advanced UAV simulation platform JSBSim. Through comparisons with various baseline algorithms, our experiments demonstrate the superior performance of the proposed method in both even and disadvantaged air combat environments.

Abstract Due to their high flexibility, low cost, and ease of handling, Unmanned Aerial Vehicles (UAVs) are often used to perform difficult tasks in complex environments. Stable and reliable path planning capability is the fundamental demand for UAVs to accomplish their flight tasks. Most researches on UAV path planning are carried out under the premise of known environmental information, and it is difficult to safely reach the target position in the face of unknown environment. Thus, an autonomous collision-free path planning algorithm for UAVs in unknown complex environments (APPA-3D) is proposed. An anti-collision control strategy is designed using the UAV collision safety envelope, which relies on the UAV's environmental awareness capability to continuously interact with external environmental information. A dynamic reward function of reinforcement learning combined with the actual flight environment is designed and an optimized reinforcement learning action exploration strategy based on the action selection probability is proposed. Then, an improved RL algorithm is used to simulate the UAV flight process in unknown environment, and the algorithm is trained by interacting with the environment, which finally realizes autonomous collision-free path planning for UAVs. The comparative experimental results in the same environment show that APPA-3D can effectively guide the UAV to plan a safe and collision-free path from the starting point to the target point in an unknown complex 3D environment.

Solid-state lithium batteries exhibit high-energy density and exceptional safety performance, thereby enabling an extended driving range for electric vehicles in the future. Solid-state electrolytes (SSEs) are the key materials in solid-state batteries that guarantee the safety performance of the battery. This review assesses the research progress on solid-state electrolytes, including polymers, inorganic compounds (oxides, sulfides, halides), and organic–inorganic composites, the challenges related to solid-state batteries in terms of their interfaces, and the status of industrialization research on solid-state electrolytes. For each kind of solid-state electrolytes, details on the preparation, properties, composition, ionic conductivity, ionic migration mechanism, and structure–activity relationship, are collected. For the challenges faced by solid-state batteries, the high interfacial resistance, the side reactions between solid-state electrolytes and electrodes, and interface instability, are mainly discussed. The current industrialization research status of various solid electrolytes is analyzed in regard to relevant enterprises from different countries. Finally, the potential development directions and prospects of high-energy density solid-state batteries are discussed. This review provides a comprehensive reference for SSE researchers and paves the way for innovative advancements in regard to solid-state lithium batteries.

Visible light communication (VLC) has been viewed as one promising candidate to mitigate the challenging spectrum crisis and radio frequency interference in future 6G mobile communications and networking. Due to the relatively limited baseband modulation bandwidth of VLC light sources—typically, light-emitting diodes—non-orthogonal multiple access (NOMA) techniques have been proposed and explored to enhance the spectral efficiency (SE) of VLC systems. However, almost all reported NOMA VLC schemes focus on well-discussed applications employing a Lambertian light beam configuration and ignore the potential applications with distinct non-Lambertian optical beam configurations. To address this issue, in this work, the performance of non-Lambertian optical beam configuration-based NOMA VLC is comparatively investigated for future 6G mobile networks. The numerical results demonstrate that, for a fundamental two-user application scenario with the far user located at the corner position, a maximum sum rate gain of about 15.6 Mbps could be provided by the investigated distinct non-Lambertian beam-based NOMA VLC, compared with the maximum sum rate of about 93.3 Mbps for the conventional Lambertian configuration with the same power splitting factor.

Cobalt has emerged as a vital material in 10 nm technology for localized interconnect layers, potentially offering a compelling alternative to Cu-based interconnects. In this study, we subjected the contamination arising from the presence of cobalt atoms in silicon to comprehensive investigation, employing electron transmission electron microscopy (TEM) observations in conjunction with first-principles calculations. The results show that a dense CoSi layer with a thickness of a few nanometers is formed at the interface of cobalt and Si. The CoSi layer blocks the diffusion of Co atoms into Si. This is due to the semiconducting nature of the covalent bond formed between Co and Si, leading to the emergence of a forbidden zone at the Co/CoSi interface. The diffusion of Co into CoSi is governed by the atomic exchange mechanism, however, the local distortion of the periodic atomic potential due to the presence of the forbidden zone at the Co/CoSi interface hinders the diffusion of Co into Si. Therefore, the deposition of a Co metal layer on a Si chip does not require an additional barrier layer.

In the process of building domain knowledge graph, the result of relationship extraction between entities is an important guarantee of the quality of the graph. Therefore, we propose a clustering method based on reinforcement learning for remote supervised relation extraction. For the relationship extraction of accident information in the aviation domain mapping, a clustering method combining local dense and global dissimilarity is proposed in combination with remote supervision, which can obtain a large amount of low-noise labeled data and reduce part of the wrong labeling and missing labeling due to the strong specialization in the aviation domain; meanwhile, reinforcement learning is introduced to denoise the negative instance noise in the positive sample data; Finally, we propose a two-attention segmentation (DAPCNN) relationship extraction model to mine deep semantic sentences. The experimental results show that in the civil aviation relationship extraction text constructed in this paper, the Micro_R, Micro_P and Micro_F1 values of the proposed relationship extraction method reach 83.41 %, 84.16 % and 83.96 %. In the open relationship extraction dataset DuIE, The Micro_R, Micro_P and Micro_F1 of the proposed method are up to 83.41 %, 93.58 % and 94.02 % respectively. Compared with the current advanced multi-instance and multi-label model, the proposed method can more accurately extract the relationship between aviation accident entities. At the same time, the performance of the open data set is also good, and has a certain universality.

Accurate segmentation of infected regions in lung computed tomography (CT) images is essential for the detection and diagnosis of coronavirus disease 2019 (COVID-19). However, lung lesion segmentation has some challenges, such as obscure boundaries, low contrast and scattered infection areas. In this paper, the dilated multiresidual boundary guidance network (Dmbg-Net) is proposed for COVID-19 infection segmentation in CT images of the lungs. This method focuses on semantic relationship modelling and boundary detail guidance. First, to effectively minimize the loss of significant features, a dilated residual block is substituted for a convolutional operation, and dilated convolutions are employed to expand the receptive field of the convolution kernel. Second, an edge-attention guidance preservation block is designed to incorporate boundary guidance of low-level features into feature integration, which is conducive to extracting the boundaries of the region of interest. Third, the various depths of features are used to generate the final prediction, and the utilization of a progressive multi-scale supervision strategy facilitates enhanced representations and highly accurate saliency maps. The proposed method is used to analyze COVID-19 datasets, and the experimental results reveal that the proposed method has a Dice similarity coefficient of 85.6% and a sensitivity of 84.2%. Extensive experimental results and ablation studies have shown the effectiveness of Dmbg-Net. Therefore, the proposed method has a potential application in the detection, labeling and segmentation of other lesion areas.

Abstract Plating Sn3Ag on copper substrates represents a crucial electronic packaging technique. In this study, we propose a novel composite plating approach, wherein CoSn 3 nanocrystals are deposited within the Sn3Ag coating. The resulting reflowed Sn3Ag joints exhibit a range of distinctive properties. Notably, CoSn 3 nanocrystals dissolve in Sn during the reflow process, thereby lowering the supercooling required for Sn nucleation. Consequently, Sn crystals grow in six-fold cyclic twins. Additionally, the dissolution of Co atoms in Sn leads to a reduced solubility of Cu atoms in Sn, consequently lowering the supercooling required for the nucleation of Cu6Sn5. Simultaneously, this phenomenon promotes the nucleation of Cu6Sn5, resulting in a considerable precipitation of Cu6Sn5 nanoparticles within the joints. Therefore, the mechanical properties of the joints are significantly enhanced, leading to a notable 20% increase in shear strength. Furthermore, the presence and distribution of Co elements within Sn induce changes in the growth pattern of interfacial Cu6Sn5. The growth process of Cu6Sn5 is dominated by the interfacial reaction, leading to its growth in a faceted shape. During the aging process, the dissolution of Co elements in Sn impedes the continuous growth of Cu6Sn5 at the interface, causing Cu6Sn5 to be distributed in the form of islands inside the joint. Remarkably, elemental Co acts as an inhibitor for the development of Cu3Sn and reduces the occurrence of Kirkendall voids.

Visible light communication (VLC) has emerged as one promising candidate technique to improve the throughput performance in future sixth-generation (6G) mobile communication networks. Due to the limited battery capacity of VLC systems, light energy harvesting has been proposed and incorporated for achieving the simultaneous lightwave information and power transfer (SLIPT) function and for improving the overall energy efficiency. Nevertheless, almost all reported works are limited to SLIPT scenarios adopting a basic and well-discussed Lambertian optical transmitter, which definitely cannot characterize the potential and essential scenarios employing distinctive non-Lambertian optical transmitters with various spatial beam characteristics. For addressing this issue, in this work, SLIPT based on a distinct non-Lambertian optical beam configuration is investigated, and for further enhancing the harvested energy and the achievable data rate, the relevant flexible optical beam configuration method is presented as well. The numerical results show that, for a typical receiver position, compared with about 1.14 mJ harvested energy and a 31.2 Mbps achievable data rate of the baseline Lambertian configuration, a harvested energy gain of up to 1.55 mJ and an achievable data rate gain of 21.1 Mbps can be achieved by the non-Lambertian SLIPT scheme explored here.

In the envisioned 6G internet of things (IoT), visible light communication (VLC) has emerged as one promising candidate to mitigate the frequency spectrum crisis. However, when working as the access point, VLC has to be connected with the backbone network via other wire communication solutions. Typically, power line communication (PLC) is viewed as an excellent match to VLC, which is capable of providing both a power supply and backbone network connection. Generally, the integration of PLC and VLC is taken into consideration for the above hybrid system for channel characteristics analysis. However, almost all current works focus on hybrid PLC and VLC, based on a conventional Lambertian optical beam configuration, and fail to address the applications of hybrid PLC and VLC based on distinct optical beam configurations. To address this issue, in this paper, the channel characteristics of hybrid PLC and VLC, based on distinct optical beam configurations, are explored and illustrated. Numerical results show that, for a central position of the receiver, compared with an achievable rate of about 194 Mbps for hybrid PLC and VLC with a baseline Lambertian optical beam configuration, the counterparts of a hybrid channel based on Rebel and NSPW optical beams are about 173.4 Mbps and 222.4 Mbps. Moreover, the effect of azimuth rotation is constructed and estimated for hybrid PLC and VLC, adopting a typical rotating asymmetric beam configuration.

BackgroundResistance training (RT) is recognized in clinical guidelines as a beneficial treatment for knee osteoarthritis (KOA), but the efficacy of different RT types is not well-established.ObjectiveThis network meta-analysis (NMA) aimed to compare the effects of different types of RT, namely, isometric muscle strengthening (IMMS), isokinetic muscle strengthening (IKMS) and isotonic muscle strengthening (ITMS), on pain, function and quadriceps muscle strength of patients with KOA.MethodsA systematic search was conducted up to September 2023 on databases, including PubMed, Cochrane Library, EMbase, Web of Science and China National Knowledge Infrastructure. The included studies comprised randomised controlled trials (RCTs) comparing RT with conventional rehabilitation and physiotherapy or other types of RT.ResultsCompared with the control group (CG) that received conventional physiotherapy, IKMS was optimal in terms of pain relief (MD = -1.33, 95% CI: -1.83 to -0.83), function (MD = -12.24, 95% CI: -17.29 to -7.19) and knee extension torque (SMD = -0.44, 95% CI: -0.74 to -0.14).ConclusionsCompared with conventional rehabilitation therapy, all three types of RT can improve pain and knee-joint function in KOA patients. IKMS demonstrated the best results among the different RT modalities.Prospero registrationPROSPERO registration number: CRD42023448579.

In the construction of the civil engineering infrastructure, the noise and vibration are affected by the geological conditions, adopting specific construction techniques based on the geological conditions is of great significance in suppressing the noise and vibration caused by the construction. To classify and evaluate the rock mass quality, the rock quality designation (RQD) is adopted widely in the geological and mining engineering. Traditionally, to obtain RQD, lengths of drilling core pieces are measured and RQD is calculated manually, which is labor-expensive and time-consuming. With the development of the computational power, the image treatment driven by the computer vision creates a potential approach to obtain RQD automatically. In the present work, the image treatment process with the aid of the object detection and the image segmentation is adopted to obtain RQD automatically, based on the similarity of features such as color and texture, the segment anything model is adopted to detect the rock cores in the image, then, the YOLOv8 algorithm is adopted to train the model, and the gap features of the rock chip segments are extracted for segmentation of different rock core segments. To test the performance of the proposed approach, 10 boreholes from Shapingba Railway Comprehensive Reconstruction Project are adopted to conduct the case study. Compared to the traditional manual approach, RQD obtained by the proposed approach is relatively accurate and obviously efficient, namely, the average error is less than 5% and the time consumed is less than 70%.

Abstract Background Osteosarcopenia is a syndrome with a concomitant presence of both sarcopenia and osteopenia/osteoporosis. It increases the risk of frailty, falls, fractures, hospitalization, and death. Not only does it burden the lives of older adults, but it also increases the economic burden on health systems around the world. This study aimed to review the prevalence and risk factors of osteosarcopenia to generate important references for clinical work in this area. Methods Pubmed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang, CBM, and VIP databases were searched from inception until April 24th, 2022. The quality of studies included in the review was evaluated using the NOS and AHRQ Scale. Pooled effects of the prevalence and associated factors were calculated using random or fixed effects models. Egger’s test, Begg’s test, and funnel plots were used to test the publication bias. Sensitivity analysis and subgroup analysis were conducted to identify the sources of heterogeneity. Statistical analysis was performed using Stata 14.0 and Review Manager 5.4. Results A total of 31 studies involving 15,062 patients were included in this meta-analysis. The prevalence of osteosarcopenia ranged from 1.5 to 65.7%, with an overall prevalence of 21% (95% CI: 0.16–0.26). The risk factors for osteosarcopenia were female (OR 5.10, 95% CI: 2.37–10.98), older age (OR 1.12, 95% CI: 1.03–1.21), and fracture (OR 2.92, 95% CI: 1.62–5.25). Conclusion The prevalence of osteosarcopenia was high. Females, advanced age, and history of fracture were independently associated with osteosarcopenia. It is necessary to adopt integrated multidisciplinary management.

White organic light-emitting diodes (WOLEDs) hold vast prospects in the fields of next-generation displays and solid-state lighting. Ultrathin emitting layers (UEMLs) have become a research hotspot because of their unique advantage. On the basis of simplifying the device structure and preparation process, they can achieve electroluminescent performance comparable to that of doped devices. In this review, we first discuss the working principles and advantages of WOLEDs based on UEML architecture, which can achieve low cost and more flexibility by simplifying the device structure and preparation process. Subsequently, the successful applications of doping and non-doping technologies in fluorescent, phosphorescent, and hybrid WOLEDs combined with UEMLs are discussed, and the operation mechanisms of these WOLEDs are emphasized briefly. We firmly believe that this article will bring new hope for the development of UEML-based WOLEDs in the future.

In medium- and short-range underwater application scenarios, thanks to the superior performance in transmission bandwidth, link latency, and security, underwater wireless optical communication (UWOC) is growing to be a promising complement to the mature underwater acoustic communication technique. In order to extend the future 6G Internet of Things (IOT) to various challenging and valuable underwater scenarios, the underwater spatial coverage and transmission performance has been actively discussed in typical seawater environments. However, almost all current works focus on underwater scenarios including light-emitting diode (LED) transmitters with well-known Lambertian optical beams and fail to characterize the scenarios adopting LED transmitters with distinctive non-Lambertian beam patterns. For addressing this limitation, in this article, the coverage performance of non-Lambertian UWOC for 6G is analyzed and illustrated. Furthermore, the switchable optical beam configuration scheme is proposed and estimated for UWOC. Numerical results illustrate that, compared with about 15.42 dB signal-to-noise ratio (SNR) fluctuation amplitude for UWOC with baseline Lambertian optical beam configuration, the corresponding SNR fluctuation amplitudes of UWOC based with two typical non-Lambertian optical beams are 8.71 dB and 24.60 dB. Furthermore, once the receiver depth is increased to 6.0 m, the SNR fluctuation amplitude for the above three UWOC coverage with distinct beam configuration could be reduced to 5.61 dB, 1.58 dB, and 10.33 dB, respectively.

Military information is gradually overloaded due to the diversity of sources and the exponential growth in quantity, which greatly affects the accuracy of intelligence personnel in extracting and analyzing military information. The modern warfare approach has also evolved from the traditional physical domain to the cognitive domain, and competing for advantages in the cognitive domain has become a key objective of combat. Therefore, constructing domain knowledge graphs and mining the relationships between data play an important role in cognitive domain analysis. In this paper, we propose a convolutional network recognition method based on improved two-layer bi-directional BiLSTM networks named the BERT-α BiLSTMs-RECNN-CRF (BDBRC) model. For the difficulties of military entities generally having long names and low extraction accuracy, as well as the existence of a large number of composite entities that are difficult to recognize, an improved two-layer BiLSTM model is devised first. In view of the fact that the BiLSTMs model always extracts features equally in long-distance text sequences without actually considering the different influences of different sentence contexts, contribution factor a is added to extract the contribution of the above and below to the target entity in different sentences respectively. Then, aiming at the strong problem of the domain of military news texts and the high level of inter-entity ambiguity, we propose a method that utilizes a modified convolutional network (RECNN) for partial feature extraction and jointly with a modified two-layer BiLSTM network for entity recognition. The experiment on the self-constructed dataset shows that the F1 value of the model proposed in this paper reaches 93.18%, and the F1 value, P, and H of our model are all better than the baseline model, which verifies the performance of the model. At the same time, we use public data sets MSRA and CLUB2020, and the experimental results show that the model proposed in this paper also has a good performance in the public data set, verifying the universality of the model. It can provide methodological support for the construction of the military knowledge graph.

With the growth of demand for air-space integrated transportation industry, the civil aviation transportation industry plays an increasingly important role in the national economy and transportation. The diversity and diversified development of civil aviation emergencies have greatly affected the decision-making efficiency for emergencies in civil aviation emergency management systems. Constructing a knowledge graph of civil aviation and improving the reliability and richness of the knowledge graph has become an urgent problem to be solved. There are some problems during the construction of a civil aviation domain knowledge graph such as long entity length, existing hybrid and composite entities, the similarity of the font features of domain entity names, a difference of information between entities, separated coding between entities, and error-prone in the transmission process of coding. So we research the construction method of knowledge graph for civil aviation emergencies to resolve these problems. (1) We propose a font pre-training model and incorporate a character feature layer into the embedding layer. (2) We propose a multi-attribute attention alignment method based on the Siamese network; entities with similar structures in the civil aviation knowledge base are input into the font layer for pre-training; the complete semantic information of entities and the importance of different attributes to entities are learned through two sub-networks respectively to improve the integrity of civil aviation knowledge graph. Experiments were carried out on the self-built aviation emergency and public data sets, respectively. The experimental results show that compared with other models, the F1 value of the proposed model can reach 96.97%, which verifies the feasibility of the model.

Background There have been no effective treatments for slowing or reversing Alzheimer’s disease (AD) until now. Growing preclinical evidence, including this study, suggests that mesenchymal stem cells-secreted exosomes (MSCs-Exos) have the potential to cure AD.Aims The first three-arm, drug-intervention, phase I/II clinical trial was conducted to explore the safety and efficacy of allogenic human adipose MSCs-Exos (ahaMSCs-Exos) in patients with mild to moderate AD.Methods The eligible subjects were assigned to one of three dosage groups, intranasally administrated with ahaMSCs-Exos two times per week for 12 weeks, and underwent follow-up visits at weeks 16, 24, 36 and 48.Results No adverse events were reported. In the medium-dose arm, Alzheimer’s Disease Assessment Scale–Cognitive section (ADAS-cog) scores decreased by 2.33 (1.19) and the basic version of Montreal Cognitive Assessment scores increased by 2.38 (0.58) at week 12 compared with baseline levels, indicating improved cognitive function. Moreover, the ADAS-cog scores in the medium-dose arm decreased continuously by 3.98 points until week 36. There were no significant differences in altered amyloid or tau deposition among the three arms, but hippocampal volume shrank less in the medium-dose arm to some extent.Conclusions Intranasal administration of ahaMSCs-Exos was safe and well tolerated, and a dose of at least 4×108 particles could be selected for further clinical trials.Trial registration number NCT04388982.

The rapid growth of the Internet of Things (IoT) market has made serial buses a universal transmission method for connecting various devices and carrying large amounts of heterogeneous data. Existing methods of processing heterogeneous serial bus data rely on programmable devices such as FPGAs and MCUs to solve the data heterogeneity problem by updating the system firmware functions. However, these methods are constrained by professional development knowledge, hardware platform compatibility, system reliability, and security, leading to the inflexibility and inefficiency of programmable devices to process serial bus heterogeneous data. In this paper, we propose a novel Software-defined Interaction (SDI) approach that enables the dynamic configuration of heterogeneous bus data and can process different data types by introducing a scripting language into a low-cost embedded device. Specifically, a Lightweight Data Distribution (L2D) mechanism is presented to address the strong dependency between data and protocols, which achieves efficient decoupling between data and processing methods. Additionally, a Multi-instance Hot-switching (MIHS) method is proposed to achieve dynamic switching among multiple instances. Finally, the effectiveness and real-time performance of the proposed method are verified through simulation and low-cost hardware deployment.

Abstract With the development of high-integration and high-power electronics, the lack of matching chip connecting materials that can withstand high temperatures has been a challenge. In this manuscript, a Cu@Cu6Sn5 core–shell bimetallic particles (approx. 1 μm in diameter) are successfully prepared and introduced as a new solder material for the packaging of power devices to obtain a Cu3Sn all-IMC solder joint. The joint consisted mainly of equiaxed Cu3Sn grains, and a small portion of columnar Cu3Sn grains. In columnar-type growth, Sn is the dominant diffusing species, which comes from the depletion of Sn in Cu6Sn5. The depleted Cu6Sn5 is transformed into columnar Cu3Sn. In equiaxed-type growth, Cu is the dominant diffusing species. Cu reacts with Cu6Sn5 to grow a Cu3Sn layer. This conclusion was confirmed by the orientation relationship. The equiaxed Cu3Sn grain nucleates at the Cu/Cu3Sn interface have an orientation relationship with the Cu substrate. Columnar Cu3Sn grains at the Cu6Sn5/Cu3Sn interface have an orientation relationship with Cu6Sn5.

Abstract Light harvesting, separation of charge carriers, and surface reactions are three fundamental steps that are essential for an efficient photocatalyst. Here we show that these steps in the TiO2 can be boosted simultaneously by disorder engineering. A solid-state reduction reaction between sodium and TiO2 forms a core-shell c-TiO2@a-TiO2-x(OH)y heterostructure, comprised of HO-Ti-[O]-Ti surface frustrated Lewis pairs (SFLPs) embedded in an amorphous shell surrounding a crystalline core, which enables a new genre of chemical reactivity. Specifically, these SFLPs heterolytically dissociate dihydrogen at room temperature to form charge-balancing protonated hydroxyl groups and hydrides at unsaturated titanium surface sites, which display high reactivity towards CO2 reduction. This crystalline-amorphous heterostructure also boosts light absorption, charge carrier separation and transfer to SFLPs, while prolonged carrier lifetimes and photothermal heat generation further enhance reactivity. The collective results of this study motivate a general approach for catalytically generating sustainable chemicals and fuels through engineered disorder in heterogeneous CO2 photocatalysts.

Abstract LncRNAs and tumor microenvironment (TME) exert an important effect in antitumor immunity. Nonetheless, the role of m6A-related lncRNA clustering patterns in prognosis, TME and immunotherapy of cervical cancer (CC) remains unknown. Here, based on 7 m6A-related prognostic lncRNAs obtained from TCGA-CC dataset, two m6AlncRNA clustering patterns were determined. m6AlncRNA clusterA was characterized by immune cell infiltrates and immune activation. m6AlncRNA clusterB was characterized by enrichment of immune evasion and tumorigenic activation pathways as well as survival and clinical stage disadvantage. Then, principal component analysis algorithms were used to construct m6AlncRNAscore based on prognostic differentially expressed genes between two m6AlncRNA clusters to quantify m6AlncRNA clustering patterns. m6AlncRNAscore was an independent prognostic protective factor. Higher Th2 and Treg cells and enrichment of immunosuppressive pathways were observed in the low-m6AlncRNAscore group, with poorer survival. High-m6AlncRNAscore was characterized by increased infiltration of activated CD8 T cell, enrichment of immune activation pathways, lower IL-10 and TGF-beta1 levels, and higher immunophenscore values, indicating inflamed TME and better anti-tumor immunotherapy efficacy. Quantitative Real-Time Polymerase Chain Reaction was used for detection of m6A-related prognostic lncRNAs. Collectively, we identified two m6AlncRNA clustering patterns which play a nonnegligible role in the prognosis, TME heterogeneity and immunotherapy of CC patients.

The purpose of this paper is to review the research progress in the realization of the organic–inorganic hybrid thin-film packaging of flexible organic electroluminescent devices using the PEALD (plasma-enhanced atomic layer deposition) and MLD (molecular layer deposition) techniques. Firstly, the importance and application prospect of organic electroluminescent devices in the field of flexible electronics are introduced. Subsequently, the principles, characteristics and applications of PEALD and MLD technologies in device packaging are described in detail. Then, the methods and process optimization strategies for the preparation of organic–inorganic hybrid thin-film encapsulation layers using PEALD and MLD technologies are reviewed. Further, the research results on the encapsulation effect, stability and reliability of organic–inorganic hybrid thin-film encapsulation layers in flexible organic electroluminescent devices are discussed. Finally, the current research progress is summarized, and the future research directions and development trends are prospected.

Nanoporous Cu foam is widely applied in many fields such as the packaging of electronic power devices. In this study, a sandwich-structured Cu-Zn eutectic alloy precursor composed of Cu0.53Zn0.47/Cu5Zn8/Cu0.53Zn0.47 is prepared through electroplating. The surface layer of the precursor, Cu0.53Zn0.47, has a flat surface with numerous grain boundaries, which effectively promotes its dealloying behavior. By contrast, Cu5Zn8 has a porous structure, which promotes the dealloying behavior at the center of the precursor. The dealloying of Cu0.53Zn0.47 is dominated by the coherent surface diffusion of Cu atoms, and the crystal lattice and orientation show no changes before and after dealloying. By contrast, the dealloying behavior of Cu5Zn8 requires the renucleation of Cu crystals; in this process, Cu atoms are transported to the surface of the layer by capillary forces to form clusters, which nucleate and grow.

Selecting the optimal spatiotemporal scale in fishing ground prediction models can maximize prediction accuracy. Current research on spatiotemporal scales shows that they are symmetrically distributed, which may not capture specific oceanographic features conducive to fishing ground formation. Recent studies have shown that deep learning is a promising research direction for addressing spatiotemporal scale issues. In the era of big data, deep learning outperforms traditional methods by more accurately and efficiently mining high-value, nonlinear information. In this study, taking Ommastrephes bartramii in the Northwest Pacific as an example, we used the U-Net model with sea surface temperature (SST) as the input factor and center fishing ground as the output factor. We constructed 80 different combinations of temporal scales and asymmetric spatial scales using data in 1998–2020. By comparing the results, we found that the optimal temporal scale for the deep learning fishing ground prediction model is 15 days, and the spatial scale is 0.25° × 0.25°. Larger time scales lead to higher model accuracy, and latitude has a greater impact on the model than longitude. It further enriches and refines the criteria for selecting spatiotemporal scales. This result deepens our understanding of the oceanographic characteristics of the Northwest Pacific environmental field and lays the foundation for future artificial intelligence-based fishery research. This study provides a scientific basis for the sustainable development of efficient fishery production.

In the electric vehicle wireless power transmission system, the high-frequency alternating magnetic field between the transmitter and receiver can have a certain impact on the health of living organisms and may even lead to lesions. In addition, metal foreign objects in an alternating magnetic field can cause their own heating or even cause fires due to the eddy current effect, so foreign object detection is an essential function in the wireless power transmission system of electric vehicles. In order to prevent metals and living organisms from entering the charging area and causing harm to the charging system and living organisms, this paper proposes a method for detecting living organisms and metal foreign objects. Firstly, the equivalent circuits for the detection systems of the living organism foreign objects and metal foreign objects are established, respectively, and the working theory of the detection system is analyzed by deriving equations. Secondly, the comb capacitor simulation model was constructed, and the comb capacitor electrode spacing, wire thickness, and capacitor spacing were designed based on the scale factor γ to explore the effects of the height and bottom area of the living organism’s foreign object on the comb capacitor. We constructed a simulation model of the detection coil and designed the inner diameter D, the number of turns N, and the wire spacing S of the detection coil according to the scale factor β. An arrayed detection coil and comb capacitor combination mode is proposed to realize the function of the simultaneous detection of metal and living organism foreign objects, and a compensation capacitor is introduced to keep the detection system in a resonant state. Lastly, a platform for foreign object detection experiments was set up to detect metal screws and beef chunks compared to the detection area without foreign objects. Metal screws entering the detection area cause a 20% voltage drop in the detection circuit resistor, and beef chunks entering the detection area cause a 30% voltage drop in the detection circuit resistor, so the detection method is effective in detecting both metals and living organisms. The feasibility of the combined mode of arrayed detection coils and comb capacitors was verified.

Intelligent lighting has attracted lots of research interests to investigate all the possible schemes to support this need as human has spent more and more time indoor. Semiconductor-based illumination network is an ideal bearer to carry on this mission. In this paper, we propose the concept of Internet of Light (IoL) and define its key functionalities by introducing the information and communication technologies to the illumination networks. Our latest research progress on high-speed transmission, resource optimization, and light stroboscopic irradiation experiment based on IoL platform show that IoL can not only provide value-added services such as positioning and information transmission but also act like a sensor network as part of Internet of Things infrastructure. It confirms that with sensors for different purposes integrated into the lamp, IoL helps people be aware of the environmental changes and make the adjustment accordingly, can provide cost-effective information service for Internet of Things applications, and supports the non-intrusive optical therapy in the future.

Abstract Sickle cell disease (SCD) is associated with altered plasma and erythrocyte lipid profiles. In a previous study, SCD mice with deficiency of proprotein convertase subtilisin/kexin type 9 (PCSK9) were observed to have more severe anemia and increased sickling compared to control SCD mice. Although PCSK9 affects circulating low density lipoprotein (LDL) by regulation of the LDL receptor, the effect of PCSK9 on anemia was independent of LDL receptor expression. In the current study, erythrocyte metabolomics were performed and revealed altered erythrocyte lipid species between SCD mice with and without PCSK9. Of particular interest, the late endosome-specific lipid bis(mono)acylglycerol phosphate (BMP) 44:12 was markedly decreased in erythrocytes from SCD mice deficient in PCSK9 mice relative to control SCD mice. Incubation of sickle erythrocytes with a neutralizing antibody to BMP increased erythrocyte sickling in vitro. In vitro treatment of SCD erythrocytes with amiodarone (1.5 μM) or medroxyprogesterone (6.75 μM), two pharmacologic compounds known to increase BMP, resulted in reduced erythrocyte sickling. Treatment of SCD mice with amiodarone (10 mg/kg) for 2 weeks resulted in increased BMP, improvement in anemia with reduced reticulocytosis, and decreased ex vivo sickling. In conclusion, severity of anemia in SCD is improved with amiodarone treatment, an effect which may be mediated through increased erythrocyte BMP.

BackgroundAlthough interleukin-2 (IL-2) has long been associated with cancer development, its roles in the development of cervical cancer remains unclear. Few studies examined the associations between IL-2 and high-risk human papillomavirus (HPV) with risk of cervical intraepithelial neoplasia (CIN).ObjectiveWe aimed to assess the association of IL-2 and high-risk HPV infection with risk of CIN as well as their interactions on the risk of CIN.DesignWe performed a cross-sectional analysis of screening data in 2285 women aged 19-65 years who participated in an ongoing community-based cohort of 40,000 women in Shanxi, China in 2014-2015. Both categorical and spline analyses were used to evaluation the association between IL-2 in the local vaginal fluids and prevalence of CIN. In addition, 1503 controls were followed up until January 31, 2019), the nested case-control study design was adopted to evaluate the association of vaginal lavage IL-2 levels and the risk of CIN progression.ResultsAfter adjusting for potential confounders, IL-2 levels were statistically inversely associated with prevalence of CIN (the 1st versus 4th quartile IL-2 levels: the respective odds ratio [OR] and 95% confidence intervals [CI] was: = 1.75 [1.37, 2.23] for CIN, 1.32 [1.01, 1.73] for CIN I, and 3.53 [2.26, 5.52] for CIN II/III). Increased IL-2 levels were inversely associated with prevalence of CIN (P-overall

Abstract Perovskite solar cells (PSCs) have the great potential for the next‐generation energy application, while the serious issue about longevity has still been a long‐standing concern. The rapid crystallization process would inevitably introduce defects, and the perovskite film decomposed rapidly when exposed to water/oxygen. Herein, the reduced l‐glutathione (GSH) is introduced into the perovskite precursor to tailor the crystallization process and passivate defects, thus relief the detrimental ion migration. Furthermore, GSH can effectively inhibit the formation of superoxide. As a result, the optimized PSCs demonstrate the champion power conversion efficiency of 22.89% and maintained 91% of its initial efficiency under ambient environment for 1000 h.

Monitoring and understanding the behavior of fishing vessels are important in facilitating effective management, preventing illegal fishing, informing fishing grounds and evaluating effects of harvests on fishery resources. In recent decades, a large quantity of real-time data of fishing vessels have become available with the development of vessel-tracking systems, making it possible to study the behavior of fishing vessels in high spatial and temporal resolutions. To effectively and efficiently deal with the large amount of data, algorithms from artificial intelligence (AI) are increasingly applied in the study of fishing vessel behavior. In this paper, we first introduce the various data sources for studying fishing vessel behavior and compare their pros and cons. Secondly, we review the AI methods that have been used to monitor and extract the behavior of fishing vessels from big data. Then, studies on the physical, ecological and social mechanisms affecting the behavior of fishing vessels were synthesized. Lastly, we review the applications of fishing vessel behavior in fishery science and management.

Visible light communications (VLC) techniques are viewed as promising candidates for the upcoming B5G&6G mobile wireless networks. Due to the broadcast nature of VLC channel, physical layer security (PLS) techniques have been considered and explored to improve the confidentiality of VLC transmission. Nevertheless, almost all current designs focus on application scenarios including sufficient transmitters and fail to match the scenarios with limited, even just two transmitters. For addressing this challenge, in this article, multiple optical beam switching scheme is proposed. Unlike conventional Lambertian beam based technique paradigm, the given scheme tentatively utilize two asymmetry non-Lambertian beams to configure each VLC transmitter. Numerical results show that, for the typical center legitimate receiver, compared with about 0.92 bps/Hz average secrecy capacity (SC) of the conventional Lambertian beam configuration, up to 5.55 bps/Hz average SC gain is acquired through the proposed beam switching scheme. Moreover, this potential gain will be enhanced to about 5.86 bps/Hz when three candidate non-Lambertian beams are available for each transmitter.