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Abstract Background Lead dislodgements, tricuspid valve failure, and wound infections are prominent issues addressed by leadless pacemakers (LPM). These devises have emerged as viable alternatives to conventional transvenous pacemakers. LPMs offer minimized complications and effective pacing, particularly beneficial for elderly patients with a low body mass index (BMI) who are at heightened infection of risk. The Micra AV leadless pacemaker was released in the US in 2020, featuring a VDD pacing mode akin to conventional pacemakers. It senses atrial activity to pace ventricular beats while maintaining the natural atrioventricular activation sequence. Micra AV achieves atrioventricular synchronization through mechanical sensing principles. Ongoing research aims to assess its efficacy, implantation feasibility, and clinical safety. Case presentation An 83-year-old man with a history of syncope was the focus of this case study. An implantable cardiac monitor (ICM) recorded occasional high-degree atrioventricular block in the patient. Subsequently, the Micra AV was implanted via the left femoral vein, and its settings were adjusted in accordance with data obtained from the ICM. No significant issues regarding pacing threshold or impedance were found during the follow-up examinations post-surgery. Importantly, the patient experienced a noticeable reduction in symptoms compared to before the implantation. Discussion This case underscores the significance of ICM monitoring in elucidating cardiac events leading to syncope and guiding appropriate treatment. It also highlights the successful outcomes and reliable implantation of the Micra AV for managing high-degree atrioventricular block. This study contributes to the growing body of evidence supporting the adoption of leadless pacemakers as a viable option for patients requiring cardiac pacing, particularly those vulnerable to complications associated with traditional pacemakers. It provides real-world evidence of Micra AV’s efficacy and safety, further validating its role in clinical practice.

Abstract Aiming at the problem that traditional methods are difficult to fully utilize the rich spectral information in hyperspectral images (HSI) and fail to capture the complex higher‐order relations in hyperspectral data, which leads to limited classification performance extreme learning machine and fails to further improve the classification accuracy of HSIs, the authors propose the hypergraph convolutional extreme learning machine (HGCELM) method. The method not only inherits all the advantages of extreme learning machine (ELM), but also embeds hypergraph convolution for feature selection, which is capable of handling higher‐order relations. This enables HGCELM to capture more complex relationships between nodes and provide richer representation capabilities. At the same time, the training speed advantage of ELM is retained, thus speeding up the model training process. Experimental results show that the proposed algorithm achieves better accuracy compared to other clustering algorithms.

Non-flow aqueous zinc-bromine batteries without auxiliary components (e.g., pumps, pipes, storage tanks) and ion-selective membranes represent a cost-effective and promising technology for large-scale energy storage. Unfortunately, they generally suffer from serious diffusion and shuttle of polybromide (Br−, Br3−) due to the weak physical adsorption between soluble polybromide and host carbon materials, which results in low energy efficiency and poor cycling stability. Here, we develop a novel self-capture organic bromine material (1,1′-bis [3-(trimethylammonio)propyl]-4,4′-bipyridinium bromine, NVBr4) to successfully realize reversible solid complexation of bromide components for stable non-flow zinc-bromine battery applications. The quaternary ammonium groups (NV4+ ions) can effectively capture the soluble polybromide species based on strong chemical interaction and realize reversible solid complexation confined within the porous electrodes, which transforms the conventional “liquid–liquid” conversion of soluble bromide components into “liquid–solid” model and effectively suppresses the shuttle effect. Thereby, the developed non-flow zinc-bromide battery provides an outstanding voltage platform at 1.7 V with a notable specific capacity of 325 mAh g−1NVBr4 (1 A g−1), excellent rate capability (200 mAh g−1NVBr4 at 20 A g−1), outstanding energy density of 469.6 Wh kg−1 and super-stable cycle life (20,000 cycles with 100% Coulombic efficiency), which outperforms most of reported zinc-halogen batteries. Further mechanism analysis and DFT calculations demonstrate that the chemical interaction of quaternary ammonium groups and bromide species is the main reason for suppressing the shuttle effect. The developed strategy can be extended to other halogen batteries to obtain stable charge storage.

The excessive utilization of petroleum-based plastic products has led to a pervasive environmental and human health threat. In response, the adoption of bioplastics derived from biomass has emerged as the foremost alternative to conventional plastics, owing to their inherent biodegradability and sustainability. The present study demonstrates the preparation of a biodegradable and cost-effective lignocellulosic bioplastic by utilizing dissolving bamboo leaf powder with deep eutectic solvents (DES) and regenerating lignin in situ. The DES was synthesized through a one-step heating and stirring method using choline chloride (ChCl) and anhydrous oxalic acid. The crystallinity of the bioplastics is enhanced by DES pretreatment, thereby improving the internal structural order of the material. Moreover, lignin regeneration reduces the pore size within the bioplastics and contributes to a more compact internal structure. The prepared lignocellulosic bioplastics exhibit remarkable mechanical strength, with a tensile strength of 113 MPa. Additionally, they demonstrate good water stability, as evidenced by a contact angle of 55.52°. Moreover, these bioplastics possess an exceptional biodegradability with a degradation rate exceeding 98% after 60 days. This study presents an innovative approach for the high-value utilization of bamboo leaf resources.

ABSTRACT Loquat (Eriobotrya japonica Lindl.) is a kind of subtropical fruit cultivated in many countries. This study aimed to evaluate the changes in the content of total phenol, total flavonoid, and 1,1-Diphenyl-2-picrylhydrazyl (DPPH), scavenging activity during the seven developmental stages and to determine the optimum harvesting time of loquat fruits by using chlorophyll fluorescence and Red Green Blue (RGB) intensity detection. Our results revealed a high correlation between chlorophyll fluorescence parameters and the internal chemical parameters (total phenol, total flavonoid, and DPPH scavenging activity) in loquat. The best prediction model from ST1 to ST5 for total flavonoid with variable fluorescence (Fv) and Fv / maximum fluorescence (Fm), R 2 = 0.79, and for DPPH scavenging activity with Fm, Fv, and Fv/Fm, R 2 = 0.92 was achieved, respectively. Total phenol correlated with minimum fluorescence (Fo) and Fv from ST4 to ST7, with R 2 = 0.99. Red Green Blue (RGB) intensity is also highly correlated with the internal chemical parameters. Both total phenol and DPPH radical scavenging activities had the best correlations with the B intensity value (R 2 = 0.998, R 2 = 0.970) in the ST1-ST4 period, respectively. Total phenols and total flavonoids had the best correlation with the G intensity value (R 2 = 0.909, R 2 = 0.986) in the ST5-ST7 period, respectively. In conclusion, developmental stage ST5 is the optimum harvesting time for loquat fruit, and chlorophyll fluorescence and RGB intensity are both noninvasive measurements for quality assessment during the loquat development period and for the prediction of the optimal time for harvesting loquat fruit.

Peanut (Arachis hypogaea L.) is a globally important oil crop. Web blotch is one of the most important foliar diseases affecting peanut, which results in serious yield losses worldwide. Breeding web blotch-resistant peanut varieties is the most effective and economically viable method for minimizing yield losses due to web blotch. In the current study, a bulked segregant analysis with next-generation sequencing was used to analyze an F2:3 segregating population and identify candidate loci related to web blotch resistance. Based on the fine-mapping of the candidate genomic interval using kompetitive allele-specific PCR (KASP) markers, we identified a novel web blotch resistance-related locus spanning approximately 169 kb on chromosome 16. This region included four annotated genes, of which only Arahy.35VVQ3 had a non-synonymous single nucleotide polymorphism in the coding region between the two parents. Two markers (Chr.16.12872635 and Chr.16.12966357) linked to this gene were shown to be co-segregated with the resistance of peanut web blotch by 72 randomly selected recombinant inbred lines (RIL), which could be used in marker-assisted breeding of resistant peanut varieties.

Abstract Background Bacterial wilt caused by Ralstonia solanacearum severely affects peanut (Arachis hypogaea L.) yields. The breeding of resistant cultivars is an efficient means of controlling plant diseases. Therefore, identification of resistance genes effective against bacterial wilt is a matter of urgency. The lack of a reference genome for a resistant genotype severely hinders the process of identification of resistance genes in peanut. In addition, limited information is available on disease resistance-related pathways in peanut. Results Full-length transcriptome data were used to generate wilt-resistant and -susceptible transcript pools. In total, 253,869 transcripts were retained to form a reference transcriptome for RNA-sequencing data analysis. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of differentially expressed genes revealed the plant-pathogen interaction pathway to be the main resistance-related pathway for peanut to prevent bacterial invasion and calcium plays an important role in this pathway. Glutathione metabolism was enriched in wilt-susceptible genotypes, which would promote glutathione synthesis in the early stages of pathogen invasion. Based on our previous quantitative trait locus (QTL) mapping results, the genes arahy.V6I7WA and arahy.MXY2PU, which encode nucleotide-binding site-leucine-rich repeat receptor proteins, were indicated to be associated with resistance to bacterial wilt. Conclusions This study identified several pathways associated with resistance to bacterial wilt and identified candidate genes for bacterial wilt resistance in a major QTL region. These findings lay a foundation for investigation of the mechanism of resistance to bacterial wilt in peanut.

Post-weld heat treatment and rolling deformation are used to improve the mechanical properties of 2195-O Al–Li alloy friction stir welding (FSW) joints, and the effects on the grain structure, precipitation behaviors, hardness distribution, and tensile performance are discussed. Microstructural characterization was conducted using scanning electron microscopy (SEM), electron backscattered diffraction (EBSD), and transmission electron microscopy (TEM). Mechanical properties were measured by hardness test and tensile test. Results show that coarse precipitates are subjected to various degrees of dissolution after FSW. Solution treatment following artificial aging (SAA) and 40% rolling deformation + SAA treatment (R40-SAA) enables the dissolution of coarse precipitates completely and precipitation of strengthening phases (T1 and θ′) in the nugget zone (NZ), thermo-mechanically affected zone and heat-affected zone (HAZ). These strengthening precipitates have little difference in precipitation behavior after SAA and R40-SAA treatment and remain consistent across all regions, resulting in joint hardness change a little between these two joints with a homogeneous distribution. The change in precipitates leads to an increase in hardness and enhances both the SAA joint strength and the R40-SAA joint strength to 503 MPa and 528 MPa (superior to the original joints by 309 MPa and 334 MPa, respectively), respectively. The SAA joints fracture in the NZ resulting from the development of AGG, and develop an intergranular fracture morphology with an elongation of 4.2%. The R40-SAA joints have an elongation of 7.2% due to the generation of uniformly fine grains in the NZ, and fail in the HAZ exhibiting a brittle fracture mechanism.

The study aimed to evaluate the gel properties of mung bean protein (MP)/sodium caseinate (NaCas) hybrid yogurt at various mixing ratios, such as rheology, texture, water holding capacity, microstructure, and formation mechanism. The gel hardness, storage modulus (G′) and water holding capacity of MP/NaCas yogurt increased and subsequently decreased as the NaCas level increased, maximum at a MP/NaCas ratio of 70:30. Meanwhile, as the MP/NaCas ratio was 70:30, the hybrid yogurt gel formed tighter and finer network structure. Moreover, the MP/NaCas hybrid yogurt slowed down the acidification rate with increasing NaCas ratio. Especially when NaCas was added at 50 %, the blend sample presented the longest fermentation time (280 min). Results showed that the optimal physicochemical characteristics of the yogurt gel were obtained when MP/NaCas ratio was mixed at 70:30. The results of the intermolecular forces indicated that hydrophobic interactions were the main factor causing yogurt gel formation.

Egg quality traits are economically important in the poultry industry. To explore the genetic architecture and identify potential candidate genes, a genome-wide association study (GWAS) was performed for 13 egg quality traits using data from whole-genome sequencing of 299 Longyan Shan-ma female ducks, including 12 quantitative traits and one qualitative trait, eggshell color (ESC; white, light green, green). From estimation of pedigree genetic parameters, heritability (h2) ranged from 0.022 to 0.996 for the 12 quantitative traits, with the highest h2 (0.996) for eggshell color a* value (ESCA) and the lowest h2 (0.022) for egg yolk percentage relative to EW. A total of 8,874 single nucleotide polymorphism (SNP)-based significant associations (1.0 × 10−6) and 247 insertion-deletion (indel)-based significant associations (1.00 × 10−5) were identified, including 5,980 SNPs and 159 indel markers. From 5,924 SNPs and 143 indels associated with ESC traits, 181 potential candidate genes were identified, and most significant SNPs and indels (P < 1.0 × 10−20) were located at 1.86 Mb (44.29−46.15 Mb) on chromosome 4. The top SNP (chr4:45325309:C>A; P = 7.97 × 10−43) and the top indel (chr4:45299595:delTTCCACTCCAC; P = 4.20 × 10−36) for the ESC a* value were within two known ESC candidate genes; ATP-binding cassette subfamily G member 2 (ABCG2) and protein kinase cGMP-dependent 2 (PRKG2). Of 56 SNPs and 16 indels associated with other egg quality traits, 46 potential candidate genes were identified including synapse differentiation-inducing 1-like (SYNDIG1L) for EW, and core histone macro-H2A.1 (LOC101795967) and neurogenin 1 (NEUROG1) for egg shape index; and four genes including collagen type VI alpha 3 chain (COL6A3), lysine demethylase 7A (KDM7A), LOC101802169, and sperm-associated antigen 16 (SPAG16) for egg yolk weight and the percentage of yolk to total egg weight. Of the 46 genes, the molecular functions of 22 are related to protein binding, indicating important roles in the formation of egg quality traits. Our findings provide new insight into the genetic basis of egg quality traits in ducks.

Abstract Practical aqueous zinc‐ion batteries require low‐cost thin zinc anodes with long‐term reversible stripping/depositing. However, thin zinc anodes encounter more severe issues than thick zinc, such as dendrites and uneven stripping, resulting in subpar performance and limited lifetimes. Here, this work proposes a three‐in‐one zinc anode obtained by a large‐scale two‐step method to address the above issues. In a three‐in‐one zinc anode, the copper foil as an inactive current collector solves the gradual reduction of the active area when only the pure zinc as an active current collector. This work develops an automatic electroplating device that can continuously deposit a zinc layer on a conducting foil to meet the demand for zinc‐coated copper foils. The sodium carboxymethylcellulose (CMC)‐zinc fluoride (ZnF2) protective layer prevents direct contact between zinc and separator, and provides a uniform and sufficient supply of zinc ions. The CMC‐ZnF2‐coated copper foil performs up to 3000 reversible zinc deposition/stripping cycles with a cumulative capacity of 6 Ah cm−2 and an average Coulombic efficiency of 99.94%. The Zn||ZnVO cell using the three‐in‐one anode achieved a high capacity retention of over 70% after 15 000 cycles. The proposed three‐in‐one anode and the automatic electroplating device will facilitate industrialization of practical thin zinc anodes.

ABSTRACT: Avian feather color is a fascinating trait, and the genetic mechanism of duck plumage formation is still in the preliminary stage. In this study, feather color of Liancheng White ducks was analyzed by determination of melanin content and RNA-seq analysis. In this research, 9 ducks from Mallards (n = 3), Liancheng White (n = 3) and Pekin ducks (n = 3) were used by high performance liquid chromatography (HPLC) and Masson-Fontana staining to reveal the difference of feather melanin content. RNA-seq from 11 hair follicle tissues (1- and 8-wk-old) of Liancheng White ducks (n = 5) and Pekin ducks (n = 7) was used to analyze the candidate genes for the feather melanin synthesis, and Immunofluorescence experiment was used to show the protein expression in 6 black- and white-feathered ducks. Pectorale, skin, liver, fat, brain, heart, kidney, lung, spleen of an 8-wk-old black-feathered Mallard were collected for candidate gene expression. The results showed that the contents of feathers, beak, web melanin in Liancheng White ducks were higher than in Pekin ducks (p < 0.05). Melanin within hair follicles was located in the barb ridge and hair matrix of black feather duck, also we found that TYRP1, TYR, SOX10 genes were differentially expressed between Liancheng White and Pekin ducks (p < 0.05), and these genes were mainly expressed showed in duck skin tissues. This study revealed the unique feather color phenotype of Liancheng White duck shedding light on the transcriptome that underlies it.

Introduction: The Euchromatic Histone Methyl Transferase Protein 2 (EHMT2), also known as G9a, deposits transcriptionally repressive chromatin marks that play pivotal roles in the maturation and homeostasis of multiple organs. Recently, we have shown that Ehmt2 inactivation in the mouse pancreas alters growth and immune gene expression networks, antagonizing Kras-mediated pancreatic cancer initiation and promotion. Here, we elucidate the essential role of Ehmt2 in maintaining a transcriptional landscape that protects organs from inflammation.Methods: Comparative RNA-seq studies between normal postnatal and young adult pancreatic tissue from Ehmt2 conditional knockout animals (Ehmt2fl/fl) targeted to the exocrine pancreatic epithelial cells (Pdx1-Cre and P48Cre/+), reveal alterations in gene expression networks in the whole organ related to injury-inflammation-repair, suggesting an increased predisposition to damage. Thus, we induced an inflammation repair response in the Ehmt2fl/fl pancreas and used a data science-based approach to integrate RNA-seq-derived pathways and networks, deconvolution digital cytology, and spatial transcriptomics. We also analyzed the tissue response to damage at the morphological, biochemical, and molecular pathology levels.Results and discussion: The Ehmt2fl/fl pancreas displays an enhanced injury-inflammation-repair response, offering insights into fundamental molecular and cellular mechanisms involved in this process. More importantly, these data show that conditional Ehmt2 inactivation in exocrine cells reprograms the local environment to recruit mesenchymal and immunological cells needed to mount an increased inflammatory response. Mechanistically, this response is an enhanced injury-inflammation-repair reaction with a small contribution of specific Ehmt2-regulated transcripts. Thus, this new knowledge extends the mechanisms underlying the role of the Ehmt2-mediated pathway in suppressing pancreatic cancer initiation and modulating inflammatory pancreatic diseases.

Summary: The prediction of drug-target interactions (DTIs) is a critical phase in the sustainable drug development process, especially when the research focus is to capitalize on the repositioning of existing drugs. Computational approaches to predicting DTIs can provide important insights into drug mechanisms of action. However, current methods for predicting DTIs based on the structural information of the knowledge graph may suffer from the sparseness and incompleteness of the knowledge graph and neglect the latent type information of the knowledge graph. In this paper, we propose TTModel, a knowledge graph embedding model for DTI prediction. By exploiting biomedical text and type information, TTModel can learn latent text semantics and type information to improve the performance of representation learning. Comprehensive experiments on two public datasets demonstrate that our model outperforms the state-of-the-art methods significantly on the task of DTI prediction.

Curcumin (CUR) is a compound extracted from turmeric that has a variety of functions including antioxidant and anti-inflammatory. As an estrogen-like mycotoxin, zearalenone (ZEN) not only attacks the reproductive system, but also has toxic effects on the liver. However, whether CUR can alleviate ZEN-induced liver injury remains unclear. This paper aims to investigate the protective effect of CUR against ZEN-induced liver injury in mice and explore the molecular mechanism involved. BALB/c mice were randomly divided into control (CON) group, CUR group (200 mg/kg b. w. CUR), ZEN group (40 mg/kg b. w. ZEN) and CUR+ZEN group (200 mg/kg b. w. CUR+40 mg/kg b. w. ZEN). 28 d after ZEN exposure and CUR treatment, blood and liver samples were collected for subsequent testing. The results showed that CUR reversed ZEN-induced hepatocyte swelling and necrosis in mice. It significantly reduced the serum alkaline phosphatase (ALP), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels in mice (p < 0.05). In addition, CUR significantly reduced hepatic ROS, malondialdehyde, hydrogen peroxide and apoptosis levels in mice (p < 0.05). Quantitative RT-PCR and Western blot results showed that CUR significantly reduced the expression of Bax and Caspase3, and reversed the increase of Nrf2, HO-1 and NQO1 expression in the liver of mice induced by ZEN (p < 0.05). In conclusion, CUR alleviated ZEN-induced liver injury in mice by scavenging ROS and inhibiting the mitochondrial apoptotic pathway.

Abstract Background To determine the prognostic value of cumulative calcification score of coronary artery calcification (CAC), thoracic aortic calcification (TAC) and aortic valve calcification (AVC) in acute ST segment elevation myocardial infarction (STEMI) patients. Methods This was a retrospective, single-center cohort study. A total of 332 STEMI patients who received primary percutaneous coronary intervention (PPCI) were enrolled in this study between January 2010 to October 2018. We assessed the calcification in the left anterior descending branch (LAD), left circumflex branch (LCX), right coronary artery (RCA), thoracic aorta, and aortic valve. Calcification of each part was counted as 1 point, and the cumulative calcification score was calculated as the sum of all points. The primary endpoint was all-cause mortality. Multivariate Cox proportional hazards models were used to determine association of cumulative calcification score with end points. The performance of the score was evaluated by receiver operating characteristic (ROC) curve analysis and absolute net reclassification improvement (NRI), compared with the Global Registry of Acute Coronary Events (GRACE) risk score. Results The overall population’s calcification score was 2.0 ± 1.6. During a mean follow-up time of 69.8 ± 29.3 months, the all-cause mortality rate was 12.1%. Kaplan-Meier curve showed that the score was significantly associated with mortality (log-rank p

Reinforcement learning algorithms can cooperate with trajectory planning idea to improve the training efficiency in the field of autonomous driving for the fixed geometric constraints of the road and limited dynamics. In this study, we propose a Dynamic Waypoint Proximal Policy Optimization (DW-PPO) framework for the merging into a platoon scenario, in which the target location is constantly changing as the platoon travels. Specifically, we set up a waypoint generator based on Bezier curve to aid in the composition of the state space and reward calculation. Moreover, we refine the waypoint tracking reward in terms of both distance and direction and add an additional merging reward to complete the merging task. We test our model on three dimensions: learning performance, control performance, and generalization performance and compare with baseline model. Experimental results show that our proposed method has better training efficiency, control stability and generalization ability.

To address the problem of autonomous lane-changing maneuvers for automated vehicle platoons on highways, a novel platoon lane-changing (PLC) tracking control framework based on the multi-agent Deep Deterministic Policy Gradient (MA-DDPG) and adaptive model predictive control (AMPC) is presented. Currently, the classic platoon cooperative control method is complex in structure and necessitates the establishment of an accurate vehicle dynamics model, so a fully decentralized MA-DDPG algorithm is proposed to realize the longitudinal following control, handling nonlinear systems and continuous state space. The agents associated with each following vehicle stay in communication via the predecessor-leader following (PLF) or predecessor following (PF) communication topology, training locally. Secondly, the traditional MPC is prone to large fluctuations in the early stage of solving and its tracking performance deteriorates with varied longitudinal speed. Therefore, an AMPC controller whose prediction time domain changes with the longitudinal speed is combined with the quintic polynomial curve to complete the lateral control, and a fuzzy controller is introduced for compensation of front wheel steering angles. The results of the joint Carsim/Simulink simulation demonstrate that the AMPC controller can achieve lateral tracking control under working conditions of 50 km/h, 100 km/h, and variable speed, and the front wheel steering angles are also stable. The MA-DDPG algorithm can achieve effective following control when the longitudinal expected speed is 25 m/s. The framework proposed in this study can both track effectively and smooth the longitudinal velocity profile compared with algorithm combinations 1: CACC with AMPC and 2: CACC with PID.

Nonwoven fabric defect detection is an essential part of the production process, and it is important to realize fast and accurate nonwoven fabric defect detection to improve production efficiency. Aiming at the problems of nonwoven fabric defect detection in which most defect targets are small and traditional industrial cameras are unable to recognize foreign impurities of the same color, a nonwoven fabric defect detection method based on hyperspectral imaging and improved YOLOv5 is proposed. Specifically, hyperspectral imaging technology is used to replace traditional vision and solve the problem of homochromatic foreign matter impurities from the dimension of spectrum. In addition, the LSK attention module is introduced into the YOLOv5 backbone network, which enables the network to learn the key feature information and enhance the detection of small targets. Finally, an improved light repetitive group frequency permutation network (Light-RepGFPN) is proposed in the neck structure, by which the feature fusion capability of the model is enhanced, so that the high-level semantic information and the low-level spatial information are fully fused to improve the detection accuracy. Combined with the LSK and Light-RepGFPN modules, we propose an improved YOLOv5 (LL-YOLOv5) defect detection network. It is experimentally proved that LL-YOLOv5 can achieve an average accuracy mean 90.3% in the nonwoven fabric hyperspectral image defects dataset, which is 2.2% higher than that of the original model, respectively.

Sarcasm is a sophisticated speech act that is intended to express contempt or ridicule on social communities such as Twitter. In recent years, the prevalence of sarcasm on the social media has become highly disruptive to sentiment analysis systems due to not only its tendency of polarity flipping but also usage of figurative language. It is observed that sarcastic texts often convey a humorous effect. Thus, determining the humor in texts can be pertinent to the successful detection of sarcasm, and vice versa. However, current works always regard sarcasm detection and humor identification as separate tasks. In this paper, we argue that these tasks should be treated as a joint, collaborative, effort, considering the semantic connections between sarcasm and humor expressed in texts. Enlightened by the multi-task learning strategy, we present a joint architecture that settles two highly pertinent tasks, sarcasm detection and humor identification. As the basic of deep neural networks, we learn both tasks jointly exploring weight sharing to capture the task-specific features for each task and task-cross features between the two tasks. Extensive experiments on real-world datasets demonstrate that our presented model consistently enhances both sarcasm detection and humor identification tasks consistently with the help of the strong semantic relationships, achieving much better performance than state-of-the-art baselines.

Abstract Developing atomically synergistic bifunctional catalysts relies on the creation of colocalized active atoms to facilitate distinct elementary steps in catalytic cycles. Herein, we show that the atomically-synergistic binuclear-site catalyst (ABC) consisting of $${{{{{\rm{Zn}}}}}}^{\delta+}$$ Zn δ + -O-Cr6+ on zeolite SSZ-13 displays unique catalytic properties for iso-stoichiometric co-conversion of ethane and CO2. Ethylene selectivity and utilization of converted CO2 can reach 100 % and 99.0% under 500 °C at ethane conversion of 9.6%, respectively. In-situ/ex-situ spectroscopic studies and DFT calculations reveal atomic synergies between acidic Zn and redox Cr sites. $${{{{{\rm{Zn}}}}}}^{\delta+}$$ Zn δ + ( $$0 \, < \, \delta \, < \, 2$$ 0 < δ < 2 ) sites facilitate β-C-H bond cleavage in ethane and the formation of Zn-H δ- hydride, thereby the enhanced basicity promotes CO2 adsorption/activation and prevents ethane C-C bond scission. The redox Cr site accelerates CO2 dissociation by replenishing lattice oxygen and facilitates H2O formation/desorption. This study presents the advantages of the ABC concept, paving the way for the rational design of novel advanced catalysts.

Abstract Background Pod shell thickness (PST) is an important agronomic trait of peanut because it affects the ability of shells to resist pest infestations and pathogen attacks, while also influencing the peanut shelling process. However, very few studies have explored the genetic basis of PST. Results An F2 segregating population derived from a cross between the thick-shelled cultivar Yueyou 18 (YY18) and the thin-shelled cultivar Weihua 8 (WH8) was used to identify the quantitative trait loci (QTLs) for PST. On the basis of a bulked segregant analysis sequencing (BSA-seq), four QTLs were preliminarily mapped to chromosomes 3, 8, 13, and 18. Using the genome resequencing data of YY18 and WH8, 22 kompetitive allele-specific PCR (KASP) markers were designed for the genotyping of the F2 population. Two major QTLs (qPSTA08 and qPSTA18) were identified and finely mapped, with qPSTA08 detected on chromosome 8 (0.69-Mb physical genomic region) and qPSTA18 detected on chromosome 18 (0.15-Mb physical genomic region). Moreover, qPSTA08 and qPSTA18 explained 31.1–32.3% and 16.7–16.8% of the phenotypic variation, respectively. Fifteen genes were detected in the two candidate regions, including three genes with nonsynonymous mutations in the exon region. Two molecular markers (Tif2_A08_31713024 and Tif2_A18_7198124) that were developed for the two major QTL regions effectively distinguished between thick-shelled and thin-shelled materials. Subsequently, the two markers were validated in four F2:3 lines selected. Conclusions The QTLs identified and molecular markers developed in this study may lay the foundation for breeding cultivars with a shell thickness suitable for mechanized peanut shelling.

Abstract Objective To analyse the efficacy of the therapeutic use of low-level laser therapy (LLLT) on the tissue repair process of allogeneic scleral grafts in patients with contracted sockets by analysing the speed of graft vascularisation and fornice depth of contraction percentage. Methods A retrospective chart review was performed from April 2015 to April 2021 including 39patients with socket contraction. Allogeneic scleral grafts were used to repair the sockets in all patients. They were randomly enrolled into two groups. The laser group included 18 patients treated with LLLT after the surgery, whereas the control group included 21 patients without LLLT after the surgery who healed naturally. The LLLT equipment used in the research had a wavelength of 650 nm, 10 mW power, and 3.8 J/cm2 dosimetry, and the procedure was performed once daily for 5 min over 7 days, beginning 1 week postoperatively. All patients were followed up over 6 months to examine the changes in the size of the area of the non-vascularised graft and upper and inferior fornice depth. Results The laser group presented a significantly increased speed of conjunctival vascularisation compared with the control group (P = 0.003). The fornice depth of contraction percentage was more apparent in the control group than that in the laser group (P = 0.000). Conclusion LLLT accelerates conjunctival vascularisation, stimulates conjunctival incision healing within a short period, shortens the tissue repair process, reduces the local inflammatory response, and causes no significant shrinkage of the conjunctival sac.

The evaluation of the focal field of Cassegrain antennas is crucial for the design and optimization of the complex feeds in quasi-optical systems. However, employing traditional physical optics methods generates high computational complexity and is inefficient. An accurate and efficient calculation method of Cassegrain antennas’ focal fields that involves a range of incidence angles is proposed, which integrates ray tracing and vector diffraction integration (RT-VDI) theories. It can calculate the focal field in any given or predefined incident direction, not limited to the case of axial incidence. In addition, the use of the equivalent parabolic theory greatly simplifies the process of integral calculation. Moreover, ray tracing and integration operations are executed upon the calculation of the reflector to further improve efficiency. Numerical examples are presented to demonstrate the accuracy and efficiency of the proposed method.

Background and aimSymptomatic intracranial hemorrhage (sICH) was the most serious complication associated with alteplase intravenous thrombolysis (IVT) in acute ischemic stroke (AIS) patients. However, the relationship between serum sodium levels and post-thrombolysis symptomatic intracranial hemorrhage has not been investigated. Therefore, the aim of this study was to investigate the relationship between pre-thrombolysis serum sodium levels and sICH after IVT, as well as to explore the optimal pre-thrombolysis serum sodium levels for lowering the risk of sICH following IVT.MethodsFrom July 1, 2017 to April 30, 2023, out-of-hospital AIS patients who received IVT in the emergency department were enrolled in this study. Serum sodium levels were measured at admission prior to IVT, and National Institutes of Health Stroke Scale scores were continuously assessed during and after thrombolysis. Routine follow-up neuroimaging was performed between 22 to 36 h after IVT. Initially, three logistic regression models and restricted cubic splines (RCS) were established to investigate the relationship between serum sodium levels and post-thrombolysis sICH. Furthermore, to evaluate the predictive value of serum sodium for post-thrombolysis sICH, we compared area under the receiver operating characteristic curve (AUROC) and net reclassification improvement (NRI) before and after incorporating serum sodium into traditional models. Finally, subgroup analysis was conducted to explore interactions between serum sodium levels and other variables.ResultsA total of 784 AIS patients who underwent IVT were enrolled, among whom 47 (6.0%) experienced sICH. The median serum sodium concentration for all patients was 139.10 [interquartile ranges (IQR): 137.40–141.00] mmol/L. Patients who developed sICH had lower serum sodium levels than those without sICH [138.20(IQR:136.00–140.20) vs. 139.20(IQR:137.40–141.00), p = 0.031]. Logistic regression analysis (model 3) revealed a 14% reduction in the risk of post-thrombolysis sICH for every 1 mmol/L increase in serum sodium levels after adjusting for confounding variables (p

At the crucial period of addressing climate change, especially to the carbonization of land use change, it is vital that relevant actions are taken to enable two ambitious dual-carbon goals, namely, ensuring that carbon emissions peak before 2030 and achieving carbon neutrality before 2060. This research investigates the impacts of land use changes on carbon emissions using a novel approach that integrates Light Detection and Ranging (LiDAR) with Geographic Information System (GIS). This approach is innovative due to its high quality three-dimensional representation to quantified exact carbon stock and forest emissions occurring due to specific land-use change. Therefore, through actual LiDAR, this research helps demarcate the pattern emitting different land-use measures, including deforestation, urban programs, agricultural differences, and forest and land changes, over historical change records and verified carbonization formulas. Similar qualitative levels between LiDAR and GIS analysis help determine the varying degrees of carbonization occurring due to enhanced deforestation, urban additions, and agricultural contributions while reporting the possible procedural carbons acquired during reforestation and other measurements. The results helped clarify that the most distinct level of land utilization shows the least level of carbon sent into the air. Therefore, the implication is that strategic land use measures and better working conditions can curb carbon indications. These signals support land-use policy and preparedness goals in a low carbon level. This study creates valuable records for the land utilization and cartograph, created through the power of LiDAR and GIS analysis.

The drill-blasting method is a commonly used mining technique in open-pit mines, and the peak particle velocity (PPV) caused by blasting vibrations is an important indicator for evaluating the rationality of blasting mining design parameters. To develop an effective PPV prediction model, a parameter self-optimizing RUN-XGBoost prediction model is implemented using the Runge-Kutta optimization algorithm (RUN) combined with extreme gradient boosting (XGBoost). The factors affecting the prediction of PPV, including maximum explosive (ME), total explosive (TE), blast center distance (BCD), blast hole depth (BHD), and height difference between the measurement location and the blast location (DH), are selected as the influencing indicators. 188 pieces of blasting operation data were measured at the RK open pit copper-cobalt mine. Then, the RUN-XGBoost prediction model for PPV is studied and compared with the Sadovsky empirical formula, traditional XGBoost model, PSO-XGBoost model, and some traditional machine learning models (Ridge, LASSO, SVM, and SVR) using R2, RMSE, VAF, MAE, and MBE as evaluation indicators for model prediction results. Finally, the Shapley Additive Explanations (SHAP) method is used to evaluate the contribution of different influencing indicators to the PPV prediction results. The results show that the RUN-XGBoost prediction model is significantly better than other machine learning models and the Sadovsky empirical formula in the prediction of PPV, further demonstrating that the RUN-XGBoost prediction model can handle the nonlinear features of multiple factors and provide a reliable, simple, and effective PPV prediction model, forming a rapid prediction and evaluation method for blasting vibrations in open-pit mining.

ABSTRACTLineage-wise physiological activities of plankton communities in the ocean are important but challenging to characterize. Here, we conducted whole-assemblage metatranscriptomic profiling at continental shelf and slope sites in the South China Sea to investigate carbon fixation potential in different lineages. RuBisCO expression, the proxy of Calvin carbon fixation (CCF) potential, was mainly contributed by Bacillariophyta, Chlorophyta, Cyanobacteria, and Haptophyta, which was differentially affected by environmental factors among lineages. CCF potential exhibited positive or negative correlations with phagotrophy gene expression, suggesting phagotrophy possibly enhances or complements CCF. Our data also reveal significant non-Calvin carbon fixation (NCF) potential, as indicated by the active expression of genes in all five currently recognized NCF pathways, mainly contributed by Flavobacteriales, Alteromonadales, and Oceanospirillales. Furthermore, in Flavobacteriales, Alteromonadales, Pelagibacterales, and Rhodobacterales, NCF potential was positively correlated with proton-pump rhodopsin (PPR) expression, suggesting that NCF might be energetically supported by PPR. The novel insights into the lineage-differential potential of carbon fixation, widespread mixotrophy, and PPR as an energy source for NCF lay a methodological and informational foundation for further research to understand carbon fixation and the trophic landscape in the ocean.IMPORTANCEMarine plankton plays an important role in global carbon cycling and climate regulation. Phytoplankton and cyanobacteria fix CO2 to produce organic compounds using solar energy and mainly by the Calvin cycle, whereas autotrophic bacteria and archaea may fix CO2 by non-Calvin cycle carbon fixation pathways. How active individual lineages are in carbon fixation and mixotrophy, and what energy source bacteria may employ in non-Calvin carbon fixation, in a natural plankton assemblage are poorly understood and underexplored. Using metatranscriptomics, we studied carbon fixation in marine plankton with lineage resolution in tropical marginal shelf and slope areas. Based on the sequencing results, we characterized the carbon fixation potential of different lineages and assessed Calvin- and non-Calvin- carbon fixation activities and energy sources. Data revealed a high number of unigenes (4.4 million), lineage-dependent differential potentials of Calvin carbon fixation and responses to environmental conditions, major contributors of non-Calvin carbon fixation, and their potential energy source.

Due to excellent thermal and mechanical properties, biodegradable poly(ethylene succinate) (PES) is a promising polyester in various practical fields. In this research, three novel poly(ethylene succinate-co-2-methyl succinate) (PESMS) copolyesters were synthesized from ethylene glycol, succinic acid, and 2-methyl succinic acid as the monomers, which showed the same main chain structure as PES except the presence of methyl between −OCCH2CH2CO− groups. The influence of ethylene 2-methyl succinate unit content on the crystal structure, thermal property, crystallization behavior, spherulitic morphology and crystal growth, as well as mechanical property of PESMS copolyesters was extensively investigated. The introduction of methyl significantly increased the toughness of PESMS copolyesters. For a better understanding of the structure and properties relationship, the influence of the location of methyl between −OCH2CH2O− groups introduced from diol or between −OCCH2CH2CO− groups introduced from diacid on the thermal and mechanical properties of PES based copolyesters was also compared and discussed.

[0.94(Bi0.5Na0.5)TiO3-0.06BaTiO3]0.98-(LiNbO3)0.02 (BNBTLN) piezoelectric ceramic coating was fabricated by thermal spray process on stainless steel substrates with thermal barrier coating (TBC) as an intermediary layer. The morphology, structure, and electrical properties of the thermal-sprayed BNBTLN coatings after furnace heat treatment (F-HT) and plasma torch heat treatment (P-HT) were studied, respectively. The BNBTLN coatings after F-HT and P-HT both had the coexisting rhombohedral and tetragonal perovskite phases and exhibited excellent electrical properties, with an effective piezoelectric coefficient d33 of 68 p.m./V and 40 p.m./V, respectively. These results reveal that high quality piezoelectric coatings can be achieved by the P-HT method, which is promising for scaling up the fabrication of piezoelectric ceramic coatings.

Fe–Mn–xAl–C steel ingots have been fabricated by vacuum melting with Al compositions varied from x = 0 to 3 and 5 wt.%, respectively. After properly hot-forging and hot-rolling as well as solution heat treatments, impact toughness tests were carried out at 77 K using a standard full-size of Charpy impact V-notch configuration. It was found that the addition of Al element is more conducive to enhance the cryogenic toughness. The relationship between the cryogenic toughness and the Al composition has been revealed through detailed microstructural studies by electron back scatter diffraction and transmission-electron microscopy. The stack fault energy (SFE) increases with the increase of Al content at various temperature. The plastic deformation is dominated by deformation bands which are dominated by deformation twins (DTs) and ε-martensite at x = 0 and DTs at x = 3 and 5%, respectively. The DTs near fracture the notch-tip area increased in the order of the 0Al, 3Al, and 5Al steel. The DTs with high density, together with their contented dislocations, significantly contributed to the high cryogenic toughness of the studied high manganese steel with higher Al content. Banded ε-martensite will deterioration cryogenic toughness due to its large size compared to DTs at 0Al steel.

Abstract The premetastatic niches (PMN) formed by primary tumor‐derived molecules regulate distant organs and tissues to further favor tumor colonization. Targeted PMN therapy may prevent tumor metastasis in the early stages, which is becoming increasingly important. At present, there is a lack of in‐depth understanding of the cellular and molecular characteristics of the PMN. Here, we summarize current research advances on the cellular and molecular characteristics of the PMN. We emphasize that PMN intervention is a potential therapeutic strategy for early prevention of tumor metastasis, which provides a promising basis for future research and clinical application.

Abstract Aqueous copper-based batteries have many favourable properties and have thus attracted considerable attention, but their application is limited by their low operating voltage originating from the high potential of copper negative electrode (0.34 V vs. standard hydrogen electrode). Herein, we propose a coordination strategy for reducing the intrinsic negative electrode redox potential in aqueous copper-based batteries and thus improving their operating voltage. This is achieved by establishing an appropriate coordination environment through the electrolyte tailoring via Cl− ions. When coordinated with chlorine, the intermediate Cu+ ions in aqueous electrolytes are successfully stabilized and the electrochemical process is decoupled into two separate redox reactions involving Cu2+/Cu+ and Cu+/Cu0; Cu+/Cu0 results in a redox potential approximately 0.3 V lower than that for Cu2+/Cu0. Compared to the coordination with water, the coordination with chlorine also results in higher copper utilization, more rapid redox kinetics, and superior cycle stability. An aqueous copper-chlorine battery, harnessing Cl−/Cl0 redox reaction at the positive electrode, is discovered to have a high discharge voltage of 1.3 V, and retains 77.4% of initial capacity after 10,000 cycles. This work may open up an avenue to boosting the voltage and energy of aqueous copper batteries.

Abstract Objective This retrospective study analyzed breathing patterns and age subgroups effect on cortical bone quality of the mandible in growing subjects, aiming to explore the application value of facial skeletal pattern combined with cortical bone density detection in early screening diagnosis of mouth breathing. Methods One hundred twenty-six participants were divided into four groups: mouth breathing group (7–9, 10–12 years old) and nasal breathing group (7–9, 10–12 years old). The mandibular anterior, middle, and posterior cortical bone mineral density (CBMD), cortical bone width (MCW), ANB, and FMA values were measured. Independent T-test and Mann–Whitney U test were used to compare the measured values. Binary logistic regression was employed to analyze the correlation between measured variables and the children’s breathing patterns. ROC analysis was used to determine the ability of the cortical bone density measurements in early screening diagnosis of MB. Results Mouth breathing had a negative impact on CBMD and MCW of the pre-mandibular (Pog) in subjects aged 7–9 years and also impacted the development of (Pog) and submandibular (Me) sites in subjects aged 10–12 years. Older children in the nasal breathing group have higher CBMD, MCW, and SNB values and lower FMA values. Single-factor and multiple-factor logistic binary regression analysis showed that FMA, MSPogCBMD, MSPogMCW, and ANB are correlated factors for children at risk of mouth breathing. Conclusion Mouth breathing pattern is closely associated with decreased mandibular CBMD and MCW values in children aged 7–12, where the anterior (Pog) and inferior (Me) sites of anterior mandible are more significantly affected. Furthermore, in combination with facial skeletal pattern, it provides a basis for the early warning diagnosis of mouth breathing.

Ultrafast laser technology has moved from ultrafast to ultra-strong due to the development of chirped pulse amplification technology. Ultrafast laser technology, such as femtosecond lasers and picosecond lasers, has quickly become a flexible tool for processing brittle and hard materials and complex micro-components, which are widely used in and developed for medical, aerospace, semiconductor applications and so on. However, the mechanisms of the interaction between an ultrafast laser and brittle and hard materials are still unclear. Meanwhile, the ultrafast laser processing of these materials is still a challenge. Additionally, highly efficient and high-precision manufacturing using ultrafast lasers needs to be developed. This review is focused on the common challenges and current status of the ultrafast laser processing of brittle and hard materials, such as nickel-based superalloys, thermal barrier ceramics, diamond, silicon dioxide, and silicon carbide composites. Firstly, different materials are distinguished according to their bandgap width, thermal conductivity and other characteristics in order to reveal the absorption mechanism of the laser energy during the ultrafast laser processing of brittle and hard materials. Secondly, the mechanism of laser energy transfer and transformation is investigated by analyzing the interaction between the photons and the electrons and ions in laser-induced plasma, as well as the interaction with the continuum of the materials. Thirdly, the relationship between key parameters and ultrafast laser processing quality is discussed. Finally, the methods for achieving highly efficient and high-precision manufacturing of complex three-dimensional micro-components are explored in detail.

The rice waterlogging stress test was conducted at the experimental base of the College of Agriculture, Yangtze University, using Yangxian You 418 as the test subject, in order to investigate the impact of waterlogging on rice growth during the period from July to August each year. Six waterlogging stress tests with different waterlogging depth (1/4 plant height (1/4PH), 2/4 PH, and 3/4 PH) and duration (5 d and 7 d) were set up at the jointing–booting stage of rice (T1: 1/4 PH, 7 d; T2: 2/4 PH, 7 d; T3: 3/4 PH, 7 d; T4: 1/4 PH, 5 d; T5: 2/4 PH, 5 d; T6: 3/4 PH, 5 d;) with shallow water irrigation (CK) as control. The plant height, population leaf area, above-ground dry matter, and the yield of rice were measured. The correlation between the waterlogging depth and rice yield reduction was analyzed, and the flood disaster threshold index of rice was established. The results showed that at the end of stress, the plant height of all waterlogged treatments exceeded CK, and the plant height of T3 and T6 treatments significantly increased by 31.90% and 15.93%, respectively. The leaf area of rice treated with T1, T3, T4, and T5 was higher than CK (p < 0.05), and the above-ground dry matter of rice treated with T2, T3, T4, T5, and T6 was higher than CK (p < 0.05). When normal irrigation was restored to the maturity stage, the plant height of all rice treated with waterlogging was still higher than CK (p < 0.05). However, as the degree of waterlogging increased, rice yield decreased significantly, with a notable reduction of 31.68% observed in the T3 treatment compared to CK. Assuming a drainage index based on a 20% decrease in rice yield, it is imperative that the ratio of flooded depth to plant height remains below 37% when waterlogging persists for 7 days in rice cultivation. These research findings offer crucial scientific insights for implementing effective drainage management measures during flood disasters in rice paddies.

Micro-hole aerostatic bearings are important components in micro-low-gravity simulation of aerospace equipment, and the accuracy of micro-low-gravity simulation tests is affected by them. In order to eliminate the influence of air resistance on the attitude control accuracy of remote sensing satellites and achieve high fidelity of micro-low-gravity simulation tests, in this study, a design and parameter optimization method was proposed for micro-hole aerostatic bearings for a vacuum environment. Firstly, the theoretical analysis was conducted to investigate the impact of various bearing parameters and external conditions on the bearing load capacity and mass flow. Subsequently, a function model describing the variation in bearing load capacity and mass flow with bearing parameters was obtained utilizing a BP neural network. The parameters of aerostatic bearings in a vacuum environment were optimized using the non-dominated sorting genetic algorithm (NSGA-II) with the objectives of maximizing the load capacity and minimizing the mass flow. Subsequently, experimental tests were conducted on the optimized bearings in both atmospheric and vacuum conditions to evaluate their load capacity and mass flow. The results show that in a vacuum environment, the load capacity and mass flow of aerostatic bearings are increased compared to those in standard atmospheric conditions. Furthermore, it has been determined that the optimal solution for the bearing’s load capacity and mass flow occurs when the bearing has an orifice aperture of 0.1 mm, 36 holes, and an orifice distribution diameter of 38.83 mm. The corresponding load capacity and mass flow are 460.644 N and 11.816 L/min, respectively. The experimental and simulated errors are within 10%; thus, the accuracy of the simulation is verified.

A flash tempering process has been demonstrated for low-carbon low-alloy lath martensite, which includes heating the sample to 750 °C (Ac1: 752 °C), dwelling at 750 °C for 2 s, and quenching directly to room temperature. The high temperature accelerated the spread of the supersaturated carbon atoms in the lath martensite, activated the dislocation migrations and thus their combining and annihilation, and promoted the mass recrystallisation. The reduced dwelling time inhibited the coarsening of the martensitic laths and suppressed the growth of the recrystallized structures. The combination of higher temperature and the shorter dwelling period, so-called flash tempering, gives rise to the same microstructure and mechanical properties as those obtained by the conventional tempering process (i.e., dwelling at 600 °C for 1 h). The high efficient flash tempering, possessing significantly reduced energy and time consumptions, may have important consequence in industrialization of tempering process.

Abstract Background Home confinement during the epidemic has a significant impact on the lifestyle and behavior of school-aged children, who have exhibited an increase in the prevalence and development of myopia. Our research will look at if home confinement will affect school-aged children on myopia control with orthokeratology. Method Data on axial length was gathered from school-aged children who had received OK lenses treatment. The entire data was separated into subgroups based on gender, age, and initial refraction, and the AL changes for each period were calculated using the formula defined in our study. Finally, the acquired data will be examined using various statistical approaches, and the ideas of slow, moderate, and rapid myopia progression will be applied to our study. Result A total of 258 study subjects met the requirements to be included in the study. We discovered that the percentage of rapid myopia growth increased during the epidemic. In addition, the AL changes before and during the epidemic were found to be statistically significant in 171 subjects in the overall data. (P = 0.041) In the high age group, the AL changes before and during the epidemic、(P = 0.033) before and after the epidemic (P = 0.023) were found to be statistically significant. The AL changes before and during the epidemic (P = 0.035) were shown to be statistically significant in the moderate myopia group. Finally, we did not find statistically significant results for other groups. Conclusion We cannot conclude that home confinement did have a negative impact on myopia control with orthokeratology in school-aged children. But we found there was an increase in the percentage of patients with OK treatment that had fast myopia progression during the confinement. We also observed that older children with higher initial refraction were more likely to be affected by home confinement.

Abstract Aqueous iron batteries are appealing candidates for large-scale energy storage due to their safety and low-cost aspects. However, the development of aqueous Fe batteries is hindered by their inadequate long-term cycling stability. Here, we propose the synthesis and application as positive electrode active material of cross-linked polyaniline (C-PANI). We use melamine as the crosslinker to improve the electronical conductivity and electrochemical stability of the C-PANI. Indeed, when the C-PANI is tested in combination with a Fe metal negative electrode and 1 M iron trifluoromethanesulfonate (Fe(TOF)2) electrolyte solution, the coin cell can deliver a specific capacity of about 110 mAh g−1 and an average discharge voltage of 0.55 V after 39,000 cycles at 25 A g−1 with a test temperature of 28 °C ± 1 °C. Furthermore, mechanistic studies suggest that Fe2+ ions are bonded to TOF− anions to form positively charged complexes Fe(TOF)+, which are stored with protons in the C-PANI electrode structures. Finally, we also demonstrate the use of C-PANI in combination with a polymeric hydrogel electrolyte to produce a flexible reflective electrochromic lab-scale iron battery prototype.

Abstract Background Gas hydrate-bearing subseafloor sediments harbor a large number of microorganisms. Within these sediments, organic matter and upward-migrating methane are important carbon and energy sources fueling a light-independent biosphere. However, the type of metabolism that dominates the deep subseafloor of the gas hydrate zone is poorly constrained. Here we studied the microbial communities in gas hydrate-rich sediments up to 49 m below the seafloor recovered by drilling in the South China Sea. We focused on distinct geochemical conditions and performed metagenomic and metatranscriptomic analyses to characterize microbial communities and their role in carbon mineralization. Results Comparative microbial community analysis revealed that samples above and in sulfate-methane interface (SMI) zones were clearly distinguished from those below the SMI. Chloroflexota were most abundant above the SMI, whereas Caldatribacteriota dominated below the SMI. Verrucomicrobiota, Bathyarchaeia, and Hadarchaeota were similarly present in both types of sediment. The genomic inventory and transcriptional activity suggest an important role in the fermentation of macromolecules. In contrast, sulfate reducers and methanogens that catalyze the consumption or production of commonly observed chemical compounds in sediments are rare. Methanotrophs and alkanotrophs that anaerobically grow on alkanes were also identified to be at low abundances. The ANME-1 group actively thrived in or slightly below the current SMI. Members from Heimdallarchaeia were found to encode the potential for anaerobic oxidation of short-chain hydrocarbons. Conclusions These findings indicate that the fermentation of macromolecules is the predominant energy source for microorganisms in deep subseafloor sediments that are experiencing upward methane fluxes. Video Abstract

Task assignment is of paramount importance in multi-AUV systems, particularly in applications such as bridge inspection where task execution is direction-specific. In such scenarios, the underactuation of AUVs is a critical factor that cannot be ignored. Therefore, it is essential to consider the AUV’s kinematic model comprehensively to ensure minimal energy consumption during task execution. In this paper, we introduce an improved Reeds–Shepp algorithm in conjunction with a distributed auction approach. We treat AUVs as car-like models in our approach, paying meticulous attention to their operational characteristics during path planning. Importantly, we effectively utilize their backward driving capabilities. Our analysis reveals that this model successfully fulfills the directional requirements of detection tasks. Furthermore, the distributed auction approach optimizes the overall task distribution in the multi-AUV system. We support our method with simulation results that underscore its effectiveness.

The classifiers based on the convolutional neural network (CNN) and graph convolutional network (GCN) have demonstrated their effectiveness in hyperspectral image (HSI) classification. However, their performance is limited by the high time complexity of CNN, spatial complexity of GCN, and insufficient labeled samples. To ease these limitations, the spectral–spatial graph convolutional network with dynamic-synchronized multiscale features is proposed for few-shot HSI classification. Firstly, multiscale patches are generated to enrich training samples in the feature space. A weighted spectral optimization module is explored to evaluate the discriminate information among different bands of patches. Then, the adaptive dynamic graph convolutional module is proposed to extract local and long-range spatial–spectral features of patches at each scale. Considering that features of different scales can be regarded as sequential data due to intrinsic correlations, the bidirectional LSTM is adopted to synchronously extract the spectral–spatial characteristics from all scales. Finally, auxiliary classifiers are utilized to predict labels of samples at each scale and enhance the training stability. Label smoothing is introduced into the classification loss to reduce the influence of misclassified samples and imbalance of classes. Extensive experiments demonstrate the superiority of the proposed method over other state-of-the-art methods, obtaining overall accuracies of 87.25%, 92.72%, and 93.36% on the Indian Pines, Pavia University, and Salinas datasets, respectively.

Decades of studies on thermoelectric materials have enabled the design of high‐performance materials based on basic materials properties, such as bandgap engineering. In general, bandgap energies correspond to the temperature at which the peak thermoelectric performance occurs. For instance, CuGaTe2 with a relatively wide bandgap of 1.2 eV has its peak zT > 1 at > 900 K. On the other hand, the zT is usually very low (

Gas hydrates possess significant potential as an energy resource and exert a notable influence on global climate change. The Shenhu Area is one of the globally recognized focal points for gas hydrate research, and additional investigation is required to fully comprehend its gas migration mechanism. By utilizing the most recent core-log-seismic data and gas geochemical data, a comprehensive analysis was conducted to determine the influence of gas migration pathways on gas hydrate accumulation in the study area. This study investigated the various types of gas migration pathways, employing integrated geological models that incorporate faults and gas chimneys to understand their respective contributions to the accumulation of gas hydrates. Based on these findings and drilling constraints, a three-gas combined production model was subsequently proposed. Thermogenic gas, secondary microbial gas, and in situ microbial gas are all potential sources of the gas responsible for hydrate formation. Thermogenic gas plays a significant role in the gas hydrate system, as evidenced by distinct features of late-mature thermogenic gas observed in gas samples extracted from hydrates in Well W18. In the study area, the primary conduits for gas migration encompass deep faults, branch faults, and gas chimneys. Among these, deep faults act as the most crucial pathways of thermogenic gas migration. The integration of geological models that incorporating deep faults and gas chimneys has profoundly impacted the accumulation of gas hydrates in the Shenhu Area, consequently influencing the distribution of shallow gas and gas hydrate. Furthermore, the proposed three-gas combined production model, which involves the simultaneous extraction of deep gas reservoirs, shallow gas reservoirs, and gas hydrates, holds significant implications for exploring and developing deep-water natural gas resources. However, its successful implementation necessitates interdisciplinary collaboration among scientists.

Herein, a real‐time, fast, tightly coupled simultaneous localization and mapping (SLAM) system is proposed. The deep neural network is used to segment the point cloud semantically to construct the point cloud semantic map descriptor, and the global navigation satellite system real‐time kinematic position is used to detect the loop closure. Finally, a factor‐graph model is used for global optimization. The working principle of the SLAM system is introduced in detail, including the construction of the factor graph, the generation of the point cloud semantic graph descriptor, the generation of the ring graph, the loop‐closure detection process, and the global optimization. Indoor and outdoor experiments are conducted to validate the performance of overall trajectory estimation and loop‐closure detection. Compared to traditional methods, the proposed method offers improved accuracy and real‐time performance in trajectory estimation. It effectively addresses issues such as limited feature constraints, large computational consumption, and subpar real‐time performance, allowing for quick and accurate loop‐closure detection. Moreover, the method demonstrates a time consumption reduction of two‐thirds compared to traditional approaches while exhibiting superior overall loop‐closure detection performance.

BackgroundThyroid associated ophthalmopathy (TAO) is an organ-specific autoimmune disease that has a significant impact on individuals and society. The etiology of TAO is complicated and poorly understood. Thus, the goal of this study was to use bioinformatics to look into the pathogenesis of TAO and to identify the optimum feature genes (OFGs) and immune infiltration patterns of TAO.MethodsFirstly, the GSE58331 microarray data set was utilized to find 366 differentially expressed genes (DEGs). To find important modular genes, the dataset was evaluated using weighted gene coexpression network analysis (WGCNA). Then, the overlap genes of major module genes and DEGs were further assessed by applying three machine learning techniques to find the OFGs. The CIBERSORT approach was utilized to examine immune cell infiltration in normal and TAO samples, as well as the link between optimum characteristic genes and immune cells. Finally, the related pathways of the OFGs were predicted using single gene set enrichment analysis (ssGSEA).ResultsKLB, TBC1D2B, LINC01140, SGCG, TMEM37, and LINC01697 were the six best feature genes that were employed to create a nomogram with high predictive performance. The immune cell infiltration investigation revealed that the development of TAO may include memory B cells, T cell follicular helper cells, resting NK cells, macrophages of type M0, macrophages of type M1, resting dendritic cells, active mast cells, and neutrophils. In addition, ssGSEA results found that these characteristic genes were closely associated with lipid metabolism pathways.ConclusionIn this research, we found that KLB, TBC1D2B, LINC01140, SGCG, TMEM37, and LINC01697 are intimately associated with the development and progression of TAO, as well as with lipid metabolism pathways.

Background The purpose of this study was to evaluate the effectiveness of His-Purkinje system pacing (HPSP) in the management of patients with pace-induced cardiomyopathy (PICM). Methods PubMed, Embase, Web of Science, and the Cochrane Library were searched comprehensively to collect related studies published from the inception of databases to June 1, 2022. R 4.04 software, including the Metafor package, matrix package, and the Meta package, was utilized to conduct the singe-arm meta-analysis. The methodology index for non-randomized studies (MINORS) was used to assess the methodological quality of the included studies. Results A total of seven studies were included, involving 164 PICM patients. The meta-analysis showed that HPSP ameliorated the left ventricular ejection fraction (LVEF) by 13.41% (95% CI [11.21–15.61]), improved the New York Heart Association (NYHA) classification by 1.02 (95% CI [−1.41 to −0.63]), and shortened the QRS duration (QRSd) by 60.85 ms (95% CI [−63.94 to −57.75]), resulting in improved cardiac functions in PICM patients. Besides, HPSP reversed the ventricular remodeling, with a 32.46 ml (95% CI [−53.18 to −11.75]) decrease in left ventricular end systolic volume (LVESV) and a 5.93 mm (95% CI [−7.68 to −4.19]) decrease in left ventricular end-diastolic dimension (LVEDD). HPSP also showed stable electrical parameters of pacemakers, with a 0.07 V (95% CI [0.01–0.13]) increase in pacing threshold, a 0.02 mV (95% CI [−0.85 to 0.90]) increase in sensed R-wave amplitude, and a 31.12 Ω reduction in impedance (95% CI [−69.62 to 7.39]). Compared with LBBP, HBP improved LVEF by 13.28% (95% CI [−11.64 to 14.92]) vs 14.43% (95% CI [−13.01 to 15.85]), ameliorated NHYA classification by 1.18 (95% CI [−1.97 to −0.39]) vs 0.95 (95% CI [−1.33 to −0.58]), shortened QRSd by 63.16 ms (95% CI [−67.00 to −59.32]) vs 57.98 ms (95% CI [−62.52 to −53.25]), and decreased LVEDD by 4.12 mm (95% CI [−5.79 to −2.45]) vs 6.26 mm (95% CI [−62.52 to −53.25]). The electrical parameters of the pacemaker were stable in both groups. Conclusions This meta-analysis showed that HPSP could significantly improve cardiac function, promote reverse remodeling, and provide stable electrical parameters of pacemakers for PICM patients.