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With the development of the Internet of Things (IoT), most communication systems are difficult to implement on a large scale due to their high complexity. Multiple-input multiple-output (MIMO) precoding is a generally used technique for improving the reliability of free-space optical (FSO) communications, which is a key technology in the 6G era. However, traditional MIMO precoding schemes are typically designed based on the assumption of additive white Gaussian noise (AWGN). In this paper, we present a novel MIMO precoding method based on reinforcement learning (RL) that is specifically designed for the Poisson shot noise model. Unlike traditional MIMO precoding schemes, our proposed scheme takes into account the unique statistical characteristics of Poisson shot noise. Our approach achieves significant performance gains compared to existing MIMO precoding schemes. The proposed scheme can achieve the bit error rate (BER) of 10−5 in a strong turbulence channel and exhibits superior robustness against imperfect channel state information (CSI).

A scientific review is a type of article that summarizes the current state of a specific field, which is crucial for promoting the advancement of our science community. Authors need to read hundreds of research articles to prepare the data and insights for a comprehensive review, which is time-consuming and labor-intensive. In this work, we present an algorithm that can automatically extract keywords from the meta-information of each article and generate the basic data for review articles. Two different fields—communication engineering, and lab on a chip technology—were analyzed as examples. We first built an article library by downloading all the articles from the target journal using a python-based crawler. Second, the rapid automatic keyword extraction algorithm was implemented on the title and abstract of each article. Finally, we classified all extracted keywords into class by calculating the Levenshtein distance between each of them. The results demonstrated its capability of not only finding out how communication engineering and lab on a chip were evolved in the past decades but also summarizing the analytical outcomes after data mining of the extracted keywords. Our algorithm is more than a useful tool for researchers during the preparation of a review article, it can also be applied to quantitatively analyze the past, present and help authors predict the future trend of a specific research field.

A M3.1 earthquake occurred in Qingpu District of Shanghai at 1:39 on June 15，2023. The Shanghai Earthquake Early Warning Network successfully received the earthquake early warning information released by the China Earthquake Early Warning Network，and the locally deployed Fujian Early Warning System EEW also successfully processed and produced the earthquake early warning results. In this paper，the results of 7 earthquake early warnings produced by Shanghai Earthquake Early Warning System and the earthquake early warning information released by China Earthquake Early Warning Network are compared and analyzed. The epicenter of the earthquake is located in the Shanghai Earthquake Early Warning Network. The first early warning information was released at 6.8 s after the earthquake. All 7 early warning processing results were produced within 15 s after the earthquake. Compared with the official earthquake catalogue，the first early warning processing result has an epicentral position deviation of 5 km and a magnitude deviation of −0.1. With the increase of the number of early warning stations involved in the calculation，the epicenter position is finally consistent with the official catalogue，and the magnitude deviation is also maintained at 0.5. The results of this earthquake early warning show that although Shanghai and its surrounding areas belong to the general early warning area with small and micro earthquakes as the main seismic activities，due to the large density of early warning stations，more accurate early warning processing results can also be produced in a short time after the earthquake，which is of great reference significance for the ongoing integration of monitoring and early warning business in the Yangtze River Delta.

In light of rapid economic and urban growth, the proliferation of structures including transmission towers, signal poles, and wind generators has become evident. Consequently, precise object detection of these structures emerges as a pivotal approach to enhance infrastructure management. This technique establishes a robust foundation for achieving elevated efficiency, precision, optimized energy management, and heightened safety monitoring. This article introduces a novel model for detecting structure based on channel and large-scale selective kernel (CLSK) model using high-resolution images. The method is rooted in a two-stage target detection network, enabling simultaneous identification of both primary structures and their associated shadows. The incorporation of deformable convolutions augments the model's ability to extract intricate features. Moreover, the introduction of the innovative LSK attention module, along with the CLSK attention module, enhances the optimization of features gleaned from the network's core architecture. Simultaneously, the complete intersection over union loss function refines the network's focus by considering parameters such as center point distance and aspect ratio in addition to the conventional overlapping area. This comprehensive approach facilitates improved feedback on detection outcomes. Empirical evaluation of the proposed network underscores its superior performance when juxtaposed with both conventional network models and the rotating detection box network.

The effects of plant protein sources (PPSs) on the health of the liver and intestine of the largemouth bass, Micropterus salmoides, were compared to verify the potential damaging effects of dietary fiber (DF). A diet containing 55% fish meal (FM) was used as the control. The test diets contained 25% soybean meal (SBM), rapeseed meal (RSM), cottonseed meal, or peanut meal, and the FM content was decreased to 30%. The protein and lipid contents of these five diets were balanced by casein and oil. Fish were raised for 8 weeks. The fish fed the diet containing PPS showed a trend of decreasing growth and apparent digestibility coefficients. The contents of total bile acid, lipid, and collagen in the liver were increased, and the mRNA expression levels of genes encoding inflammatory factors and enzymes involved in de novo fatty acid synthesis and bile acid synthesis were upregulated. Both the lipid and collagen contents in the liver were positively correlated with the DF content in the diet significantly. Morphology and histology showed reduced liver size, hepatic steatosis, and fibrosis in fish fed diets containing PPS. The lowest hepatosomatic index was observed in fish fed the SBM diet, and the most severe damage was observed in fish fed the RSM diet. No obvious histological abnormalities were observed in the hindgut. The bile acid profile in the liver could be used to distinguish the types of PPS very well by Fisher discriminant analysis. These results indicated that 25% of each of the four PPSs in the diet exceeded the tolerance range of largemouth bass and caused liver damage, which might be mediated by bile acid. DF in PPS might be an important agent contributing to liver damage.

To solve the problem that the number of sequences in the complete complementary sequence set is limited, periodic quasi-complementary sequence set was constructed.Firstly, based on the circular Florentine array, the near optimal periodic quasi-complementary sequence set was constructed by using the mapping function on .The obtained periodic quasi-complementary sequence sets had new subsequence lengths.Secondly, based on the one-coincidence frequency-hopping sequence set, the asymptotically optimal periodic quasi-complementary sequence set was constructed by defining the mapping function from to .The comparison results show that compared with the existing periodic quasi-complementary sequence sets, the proposed method contains more sequences with the same subsequence length, and can support more users in multi-carrier communication system.

Refined lithology identification is an essential task, often constrained by the subjectivity and low efficiency of classical methods. Computer-aided automatic identification, while useful, has seldom been specifically geared toward refined lithology identification. In this study, we introduce Rock-ViT, an innovative machine learning approach. Its architecture, enhanced with supervised contrastive loss and rooted in visual Transformer principles, markedly improves accuracy in identifying complex lithological patterns. To this end, we have collected public datasets and implemented data augmentation, aiming to validate our method using sandstone as a focal point. The results demonstrate that Rock-ViT achieves superior accuracy and effectiveness in the refined lithology identification of sandstone. Rock-ViT presents a new perspective and a feasible approach for detailed lithological analysis, offering fresh insights and innovative solutions in geological analysis.

ABSTRACT Pollination services provided by wild insect pollinators are critical to natural ecosystems and crops around the world. There is an increasing appreciation that the gut microbiota of these insects influences their health and consequently their services. However, pollinator gut microbiota studies have focused on well-described social bees, but rarely include other, more phylogenetically divergent insect pollinators. To expand our understanding, we explored the insect pollinator microbiomes across three insect orders through two DNA sequencing approaches. First, in an exploratory 16S amplicon sequencing analysis of taxonomic community assemblages, we found lineage-specific divergences of dominant microbial genera and microbiota community composition across divergent insect pollinator genera. However, we found no evidence for a strong broad-scale phylogenetic signal, which we see for community relatedness at finer scales. Subsequently, we utilized metagenomic shotgun sequencing to obtain metagenome-assembled genomes and assess the functionality of the microbiota from pollinating flies and social wasps. We uncover a novel gut microbe from pollinating flies in the family Orbaceae that is closely related to Gilliamella spp. from social bees but with divergent functions. We propose this novel species be named Candidatus Gilliamella eristali. Further metagenomes of dominant fly and wasp microbiome members suggest that they are largely not host-insect adapted and instead may be environmentally derived. Overall, this study suggests selective processes involving ecology or physiology, or neutral processes determining microbe colonization may predominate in the turnover of lineages in insect pollinators broadly, while evolution with hosts may occur only under certain circumstances and on smaller phylogenetic scales. IMPORTANCE Wild insect pollinators provide many key ecosystem services, and the microbes associated with these insect pollinators may influence their health. Therefore, understanding the diversity in microbiota structure and function, along with the potential mechanisms shaping the microbiota across diverse insect pollinators, is critical. Our study expands beyond existing knowledge of well-studied social bees, like honey bees, including members from other bee, wasp, butterfly, and fly pollinators. We infer ecological and evolutionary factors that may influence microbiome structure across diverse insect pollinator hosts and the functions that microbiota members may play. We highlight significant differentiation of microbiomes among diverse pollinators. Closer analysis suggests that dominant members may show varying levels of host association and functions, even in a comparison of closely related microbes found in bees and flies. This work suggests varied importance of ecological, physiological, and non-evolutionary filters in determining structure and function across largely divergent wild insect pollinator microbiomes.

The purpose of this experiment was to study the antibacterial effect of saponins from different sources on common food-borne pathogens, and to develop the application of saponins in the field of food. The size of inhibition zone, minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of saponins from three different sources (Gleditsia sinensis shell, green tea and Camellia oleifera seed) were determined by Oxford cup method and double dilution method, respectively. The results showed that the three saponins from different sources all had antibacterial effect on four common food-borne pathogenic bacteria, namely Bacillus subtilis, Staphylococcus aureus, Salmonella sp. and Escherichia coli. Among them, the saponins derived from Gleditsia sinensis shell had the best antibacterial effect. The double dilution method showed that their MICs for the two Gram-positive bacteria Bacillus subtilis and Staphylococcus aureus were both 4 mg/mL, and the MBCs were 16 mg/mL and 8 mg/mL respectively; The MIC of Salmonella and E.coli of two Gram-negative bacteria were 4 mg/mL and 8 mg/mL, and MBC were 8 mg/mL and 16 mg/mL respectively. The results provide devidence for the research and development of safe, high effective and natural plant food preservatives.

Abstract Background Despite the well-studied effects of gestational weight gain (GWG) on offspring health, little is known about the association of trimester-specific GWG with offspring birth weight among underweight pregnant women. This study aimed to explore the association of trimester-specific GWG rate with small for gestational age (SGA) in underweight women. Methods The GWG rate of underweight pregnant women (pre-pregnancy body mass index [BMI] lower than 18.5 kg/m2) of the Born in Guangzhou Cohort Study was calculated as the weight gain during a specific trimester divided by the corresponding duration of week. Total GWG was calculated as the weight difference between pre-pregnancy and delivery, and was categorized into inadequate, adequate, and excessive weight gain based on the 2009 Institute of Medicine (IOM) weight gain recommendation. The INTERGROWTH-21st standards were used to define SGA. Logistic regression models were used to examine the associations of total GWG and trimester-specific GWG rates with SGA. Associations between trimester-specific GWG rates and SGA were also analyzed separately based on different total GWG categories (i.e. inadequate and adequate/excessive GWG). Results Of the 3839 participants, SGA births occurred in 397 (10.3%), and mean GWG was 14.9 kg (SD 3.9). A lower risk of SGA was observed among women with higher GWG rate (per 0.5 kg/week increase) during the first (adjusted OR [aOR] 0.74, 95%CI 0.57, 0.96) and second (adjusted OR [aOR] 0.40, 95%CI 0.30, 0.55) but not third trimester. Similar association between higher GWG rate during the second trimester and a decreased risk of SGA were observed among women with inadequate (

Battery energy storage systems (BESSs) are one of the main countermeasures to promote the accommodation and utilization of large-scale grid-connected renewable energy sources. With the rapid increase in the installed capacity of BESSs, the security problem and economic problem of BESSs are gradually exposed. On the one hand, fire accidents happen on occasion; on the other hand, the operation efficiencies and battery utilizations of BESSs are not high, resulting in considerable economic losses. In this paper, the relationship between the construction scheme of a BESS and the power conversion system (PCS) is analyzed. The structures, control methods, and grid-connected/islanding control strategies of PCSs are categorized, evaluated, and compared in detail. And the design schemes of high capacity BESSs as well as relevant considerations are systematically discussed. The test waveforms of a 10-kV BESS based on a cascaded H-bridge high-voltage straight hanging PCS are shown to prove the feasibility of this advanced transformerless BESS scheme. Finally, the future development directions of high-capacity BESSs and PCSs are prospected.

The precise segmentation of the optic cup (OC) and the optic disc (OD) is important for glaucoma screening. In recent years, medical image segmentation based on convolutional neural networks (CNN) has achieved remarkable results. However, many traditional CNN methods do not consider the cross-domain problem, i.e., generalization on datasets of different domains. In this paper, we propose a novel unsupervised domain-adaptive segmentation architecture called CAE-BMAL. Firstly, we enhance the source domain with a convolutional autoencoder to improve the generalization ability of the model. Then, we introduce an adversarial learning-based boundary discrimination branch to reduce the impact of the complex environment during segmentation. Finally, we evaluate the proposed method on three datasets, Drishti-GS, RIM-ONE-r3, and REFUGE. The experimental evaluations outperform most state-of-the-art methods in accuracy and generalization. We further evaluate the cup-to-disk ratio performance in OD and OC segmentation, which indicates the effectiveness of glaucoma discrimination.

As a matter of experience, people always take it for granted that ambient light should be eliminated for the research and application of storage phosphors. Such an empirical viewpoint has hindered the development of storage phosphors in a lighting environment. Herein, we introduce a glow-in-the-daylight phenomenon, which is essentially photostimulated luminescence of ultraviolet phosphor upon stimulation by polychromatic daylight. As a proof of concept, imaging and spectral experiments are carried out using an x-ray-charged LuPO_{4}:Pr^{3+} phosphor to demonstrate the glow performance. The charged phosphor exhibits solar-blind ultraviolet (200–280 nm) emission under sunlight, while its persistent luminescence is nearly absent in a dark environment, revealing the role of sunlight in releasing the stored energy of the phosphor. Moreover, inspired by the case of LuPO_{4}:Pr^{3+}, we expect to revisit other ultraviolet phosphors that do not exhibit persistent luminescence in the dark, enabling more glow-in-the-daylight materials to be developed.

ABSTRACTThe Zika virus (ZIKV) is a mosquito-borne flavivirus that causes neonatal abnormalities and other disorders. Antibodies to the ZIKV envelope (E) protein can block infection. In this study, next-generation sequencing (NGS) of immunoglobulin heavy chain (IgH) mRNA transcripts was combined with single-cell PCR cloning of E-binding monoclonal antibodies for analysing antibody response in a patient from the early stages of infection to more than one year after the clearance of the virus. The patient's IgH repertoire 14 and 64 days after symptom onset showed dramatic dominant clonal expansion but low clonal diversity. IgH repertoire 6 months after disease-free status had few dominant clones but increased diversity. E-binding antibodies appeared abundantly in the repertoire during the early stages of infection but quickly declined after clearance of the virus. Certain VH genes such as VH5-10-1 and VH4-39 appeared to be preferentially enlisted for a rapid antibody response to ZIKV infection. Most of these antibodies require relatively few somatic hypermutations to acquire the ability to bind to the E protein, pointing to a possible mechanism for rapid defence against ZIKV infection. This study provides a unique and holistic view of the dynamic changes and characteristics of the antibody response to ZIKV infection.

Terahertz polarization converter has drawn great attention for its properties of wavefront control in recent years. However, the low transmission efficiency of these converters remains a major obstruction to be resolved. A promising solution is the all-dielectric metasurface, based on which, this study proposes a high-efficiency transmissive terahertz linear-to-circular polarization converter. The simulations show the transmission efficiency of the converter is beyond 88% with an ellipticity

The concentration of butyric acid in the intestine increased with the increase in the content of fermentable dietary fibre; however, the potential physiological impact of a high dose of butyric acid on fish has not been sufficiently studied. The aim of this study was to investigate the effect of two dosages of butyric acid on the growth and health of the liver and intestine of the largemouth bass (Micropterus salmoides). Sodium butyrate (SB) was added to the diet at 0 g/kg (CON), 2 g/kg (SB2), and 20 g/kg (SB20), and the juvenile largemouth bass were fed to apparent satiation for 56 days. No significant difference was observed in the specific growth rate or hepatosomatic index among the groups (P>0.05). The concentration of β-hydroxybutyric acid in the liver, the activities of alanine aminotransferase, aspartate aminotransferase, and alkaline phosphatase, and the concentrations of triglyceride and total cholesterol in serum increased significantly in the SB20 group compared to the CON group (P

The pathological mechanisms of neural tube defects (NTDs) are not yet fully understood. Although the dysregulation of histone modification in NTDs is recognized, it remains to be fully elucidated on a genome-wide level. We profiled genome-wide H3K27me3 and H3K27ac occupancy by CUT&Tag in neural tissues from ICR mouse embryos with benzo[a]pyrene (BaP)-induced NTDs (250 mg kg−1) at E9.5. Furthermore, we performed RNA sequencing (RNA-seq) to investigate the regulation of histone modifications on gene expressions. Gene ontology and KEGG analysis were conducted to predict pathways involved in the development of NTDs. Our analysis of histone 3 lysine 27 modification in BaP-NTD neural tissues compared to BaP-nonNTD revealed 6045 differentially trimethylated regions and 3104 acetylated regions throughout the genome, respectively. The functional analysis identified a number of pathways uniquely enriched for BaP-NTD embryos, including known neurodevelopment related pathways such as anterior/posterior pattern specification, ephrin receptor signaling pathway, neuron migration and neuron differentiation. RNA-seq identified 423 differentially expressed genes (DEGs) between BaP-NTD and BaP-nonNTD group. The combination analysis of CUT&Tag and RNA-seq found that 55 DEGs were modified by H3K27me3 and 25 by H3K27ac in BaP-NTD, respectively. In the transcriptional regulatory network, transcriptional factors including Srsf1, Ume6, Zbtb7b, and Cad were predicated to be involved in gene expression regulation. In conclusion, our results provide an overview of histone modifications during neural tube closure and demonstrate a key role of genome-wide alterations in H3K27me3 and H3K27ac in NTDs corresponding with changes in transcription profiles.

The bias stability performance of accelerometers is essential for an inertial navigation system. The traditional pendulous accelerometer usually has a flexible connection structure, which could limit the long-term bias stability. Here, based on the main technologies employed in previous space missions of our group, we developed a terrestrial triaxial navigation-compatible accelerometer. Because there is no mechanical connection between the inertial test mass and the frame, the bias performance relies on the stability of the equivalent electrostatic spring, where further sources are analyzed to get the optimal electrostatic force scheme. To investigate the bias stability under different ranges, the vertical and horizontal measurement ranges are designed at 5 g and ±10 mg, respectively. A low-noise high-voltage levitation scheme is adopted to extend the vertical measurement range from sub-mg to more than earth’s 1-g gravity. Finally, the experimental validation results show that the 24-h bias stability of vertical and two horizontal directions come to 13.8 μg, 0.84 μg, and 0.77 μg, respectively.

The inner constituents of lithium-ion batteries (LIBs) are easy to deform during charging and discharging processes, and the accumulation of these deformations would result in physical fractures, poor safety performances, and short lifespan of LIBs. Recent studies indicate that the introduction of self-healing (SH) materials into electrodes or electrolytes can bring about great enhancements in their mechanical strength, thus optimizing the cycle stability of the batteries. Due to the self-healing property of these special functional materials, the fractures/cracks generated during repeated cycles could be spontaneously cured. This review systematically summarizes the mechanisms of self-healing strategies and introduces the applications of SH materials in LIBs, especially from the aspects of electrodes and electrolytes. Finally, the challenges and the opportunities of the future research as well as the potential of applications are presented to promote the research of this field.

The antibody repertoire is a critical component of the adaptive immune system and is believed to reflect an individual’s immune history and current immune status. Delineating the antibody repertoire has advanced our understanding of humoral immunity, facilitated antibody discovery, and showed great potential for improving the diagnosis and treatment of disease. However, no tool to date has effectively integrated big Rep-seq data and prior knowledge of functional antibodies to elucidate the remarkably diverse antibody repertoire. We developed a Rep-seq dataset Analysis Platform with an Integrated antibody Database (RAPID; https://rapid.zzhlab.org/), a free and web-based tool that allows researchers to process and analyse Rep-seq datasets. RAPID consolidates 521 WHO-recognized therapeutic antibodies, 88,059 antigen- or disease-specific antibodies, and 306 million clones extracted from 2,449 human IGH Rep-seq datasets generated from individuals with 29 different health conditions. RAPID also integrates a standardized Rep-seq dataset analysis pipeline to enable users to upload and analyse their datasets. In the process, users can also select set of existing repertoires for comparison. RAPID automatically annotates clones based on integrated therapeutic and known antibodies, and users can easily query antibodies or repertoires based on sequence or optional keywords. With its powerful analysis functions and rich set of antibody and antibody repertoire information, RAPID will benefit researchers in adaptive immune studies.

The key to fine-grained aircraft recognition is discovering the subtle traits that can distinguish different subcategories. Early approaches leverage part annotations of fine-grained objects to derive rich representations. However, manual labeling part information is cumbersome. In response to this issue, previous CNN-based methods reuse the backbone network to extract part-discrimination features, the inference process of which consumes much time. Therefore, we introduce generalized multiple instance learning (MIL) into fine-grained recognition. In generalized MIL, an aircraft is assumed to consist of multiple instances (such as head, tail, and body). Firstly, instance-level representations are obtained by the feature extractor and instance conversion component. Secondly, the obtained instance features are scored by an MIL classifier, which can yield high-level part semantics. Finally, a fine-grained object label is inferred by a MIL pooling function that aggregates multiple instance scores. The proposed approach is trained end-to-end without part annotations and complex location networks. Experimental evidence is conducted to prove the feasibility and effectiveness of our approach on combined aircraft images (CAIs).

As part of concepts for chemical energy storage of excess chemical energy produced from renewable sources, we investigated the performance of CuO/ZnO catalysts supported on mesoporous carbon to convert CO2 hydrogenation to methanol. In this work, mesoporous carbon was used as the catalyst support for CuO-ZnO catalysts. Four catalysts with different precipitated precursors were synthesized and analyzed by N2-physisorption, X-ray diffraction (XRD), thermogravimetric analysis (TG-DTG), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The results show that catalyst CZ-in situ had the highest turnover frequency (TOF) (2.8 × 10−3 s−1) and methanol production rate (0.8 mmol g−1·h−1). The catalysts for co-precipitation of copper and zinc on carbon precursors are more active. Cu/ZnO domains that are accessible to the reactant gas are another reason for the catalysts being active. The Cu-ZnO interface is crucial to methanol catalyst activity.

Ultra-sensitive inertial sensors are one of the key components in satellite Earth’s gravity field recovery missions and space gravitational wave detection missions. Low-noise capacitive position transducers are crucial to these missions to achieve the scientific goal. However, in actual engineering applications, the sensor head and electronics unit usually place separately in the satellite platform where a connecting cable is needed. In this paper, we focus on the stray-capacitance influences of coaxial cables which are used to connect the mechanical core and the electronics. Specially, for the capacitive transducer with a differential transformer bridge structure usually used in high-precision space inertial sensors, a connecting method of a coaxial cable between the transformer’s secondary winding and front-end circuit’s preamplifier is proposed to transmit the AC modulated analog voltage signal. The measurement and noise models including the stray-capacitance of the coaxial cable under this configuration is analyzed. A prototype system is set up to investigate the influences of the cables experimentally. Three different types and lengths of coaxial cables are chosen in our experiments to compare their performances. The analysis shows that the stray-capacitance will alter the circuit’s resonant frequency which could be adjusted by additional tuning capacitance, then under the optimal resonant condition, the output voltage noises of the preamplifier are measured and the sensitivity coefficients are also calibrated. Meanwhile, the stray-capacitance of the cables is estimated. Finally, the experimental results show that the noise level of this circuit with the selected cables could all achieve 1–2 × 10−7 pF/Hz1/2 at 0.1 Hz.