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For improving the actuation performance at low electric fields of dielectric elastomers, achieving high dielectric constant (ɛr) and low modulus (Y) simultaneously has been targeted in the past decades, but there are few ways to accomplish both. In contrast to the classical strategies such as incorporating plasticizers or ceramic to prepare the silicon-based dielectric elastomers, here, blending an amino-complexed hybrid (polyethyleneimine (PEI)-Ag) with polydimethylsiloxane (PDMS) elastomer is reported as an alternative strategy to tailor the ɛr and Y. PEI-Ag not only exhibits excellent dielectric enhancement properties but also minimizes the PDMS crosslinking through amino-complexed reaction between PEI and Pt catalysts. The prepared dielectric elastomers have a ɛr of 7.2 @ 103 ​Hz and Y of 1.14 ​MPa, leading to an actuation strain of 22.27 ​% at 35 ​V/μm. Hence, incorporating such novel hybrids based on dual amino-complexed effect on both matrix and particles sufficiently promotes the actuated performance of dielectric elastomers.

As an endogenous signaling molecule, carbon monoxide (CO) has emerged as an increasingly promising option regarding as gas therapy due to its positive pharmacological effects in various diseases. Owing to the gaseous nature and potential toxicity, it is particularly important to modulate the CO release dosages and targeted locations to elucidate the biological mechanisms of CO and facilitate its clinical applications. Based on these, diverse CO-releasing molecules (CORMs) have been developed for controlled release of CO in biological systems. However, practical applications of these CORMs are limited by several disadvantages including low stability, poor solubility, weak releasing controllability, random diffusion, and potential toxicity. In light of rapid developments and diverse advantages of nanomedicine, abundant nanomaterials releasing CO in controlled ways have been developed for therapeutic purposes across various diseases. Due to their nanoscale sizes, diversified compositions and modified surfaces, vast CO-releasing nanomaterials (CORNMs) have been constructed and exhibited controlled CO release in specific locations under various stimuli with better pharmacokinetics and pharmacodynamics. In this review, we present the recent progress in CORNMs according to their compositions. Following a concise introduction to CO therapy, CORMs and CORNMs, the representative research progress of CORNMs constructed from organic nanostructures, hybrid nanomaterials, inorganic nanomaterials, and nanocomposites is elaborated. The basic properties of these CORNMs, such as active components, CO releasing mechanisms, detection methods, and therapeutic applications, are discussed in detail and listed in a table. Finally, we explore and discuss the prospects and challenges associated with utilizing nanomaterials for biological CO release.

Fluoroquinolones (FQ) are essential for the treatment of multidrug-resistant tuberculosis (MDR-TB). The FQ resistance (FQ-R) rate in MDR-TB in China and its risk factors remain poorly understood. We conducted a retrospective, population-based genomic epidemiology study of MDR-TB patients in Shanghai, China, from 2009 to 2018. A genomic cluster was defined as strains with genetic distances ≤ 12 single nucleotide polymorphisms. The transmitted FQ-R was defined as the same FQ resistance-conferring mutations shared by ≥ 2 strains in a genomic cluster. We used multivariable logistic regression analysis to identify the risk factors for drug resistance. Among the total 850 MDR-TB patients included in the study, 72.8% (619/850) were male, the median age was 39 (interquartile range 28, 55) years, 52.7% (448/850) were migrants, and 34.5% (293/850) were previously treated patients. Most of the MDR-TB strains belong to the Beijing lineage (91.7%, 779/850). Overall, the genotypic resistance rate of FQ was 34.7% (295/850), and 47.1% (139/295) FQ-R patients were in genomic clusters, of which 98 (33.2%, 98/295) were presumed as transmitted FQ-R. Patients with treatment-naïve (aOR = 1.84; 95% CI: 1.09, 3.16), diagnosed in a district-level hospital (aOR = 2.69; 95% CI: 1.56, 4.75), and streptomycin resistance (aOR = 3.69; 95% CI: 1.65, 9.42) were significantly associated with the transmission of FQ-R. In summary, the prevalence of FQ-R among MDR-TB patients was high in Shanghai, and at least one-third were transmitted. Enforced interventions including surveillance of FQ drug susceptibility testing and screening among MDR-TB before initiation of treatment were urgently needed.

Abstract Digital dental technology covers oral cone-beam computed tomography (CBCT) image processing and low-dose CBCT dental applications. A low-dose CBCT image enhancement method based on image fusion is proposed to address the need for subzygomatic small screw insertion. Specifically, firstly, a sharpening correction module is proposed, where the CBCT image is sharpened to compensate for the loss of details in the underexposed/over-exposed region. Secondly, a visibility restoration module based on type II fuzzy sets is designed, and a contrast enhancement module using curve transformation is designed. In addition to this, we propose a perceptual fusion module that fuses visibility and contrast of oral CBCT images. As a result, the problems of overexposure/underexposure, low visibility, and low contrast that occur in oral CBCT images can be effectively addressed with consistent interpretability. The proposed algorithm was analyzed in comparison experiments with a variety of algorithms, as well as ablation experiments. After analysis, compared with advanced enhancement algorithms, this algorithm achieved excellent results in low-dose CBCT enhancement and effective observation of subzygomatic small screw implantation. Compared with the best performing method, the evaluation metric is 0.07–2 higher on both datasets. The project can be found at: https://github.com/sunpeipei2024/low-dose-CBCT .

Genetic mutations in the β-globin gene lead to a decrease or removal of the β-globin chain, causing the build-up of unstable alpha-hemoglobin. This condition is referred to as beta-thalassemia (BT). The present treatment strategies primarily target the correction of defective erythropoiesis, with a particular emphasis on gene therapy and hematopoietic stem cell transplantation. However, the presence of inefficient erythropoiesis in BT bone marrow (BM) is likely to disturb the previously functioning BM microenvironment. This includes accumulation of various macromolecules, damage to hematopoietic function, destruction of bone cell production and damage to osteoblast(OBs), and so on. In addition, the changes of BT BM microenvironment may have a certain correlation with the occurrence of hematological malignancies. Correction of the microenvironment can be achieved through treatments such as iron chelation, antioxidants, hypoglycemia, and biologics. Hence, This review describes damage in the BT BM microenvironment and some potential remedies.

Abstract This study assessed muscle activity (root mean square, RMS, and median frequency, MDF) to evaluate the acute response to blood flow restriction (BFR) resistance exercise (RE) and conventional moderate intensity (MI) RE. We also performed exploratory analyses of differences based on sex and exercise‐induced hypoalgesia (EIH). Fourteen asymptomatic individuals performed four sets of unilateral leg press with their dominant leg to volitional fatigue under two exercise conditions: BFR RE and MI RE. Dominant side rectus femoris (RF) and vastus lateralis (VL) muscle activity were measured using surface electromyography (sEMG) through exercise. RMS and MDF were calculated and compared between conditions and timepoints using a linear mixed model. Pressure pain thresholds (PPT) were tested before and immediately after exercise and used to quantify EIH. Participants were then divided into EIH responders and nonresponders, and the differences on RMS and MDF were compared between the two groups using Hedges' g. RMS significantly increased over time (RF: p = 0.0039; VL: p = 0.001) but not between conditions (RF: p = 0.4; VL: p = 0.67). MDF decreased over time (RF: p = 0.042; VL: p

Context and backgroundMicroplastics (MPs) and heavy metals (HMs) coexist in the farmland of China.MotivationIt still remains unclear the extent of their exposure and distribution in sweet potato fields.HypothesisPolyethylene (PE) or polyamide (PA) is the main MP pollutant in contaminated sweet potato sites, and the MP abundance in low-latitude and eastern areas is highest. Methods: In this study, saturated NaCl solution, a stereo microscope, a Fourier transform infrared spectrometer, and an electrothermal digester are used for the extraction, observation, identification of MPs, and analysis of Cd elements in soil, respectively.MethodsIn this study, saturated NaCl solution, a stereo microscope, a Fourier transform infrared spectrometer, and an electrothermal digester are used for the extraction, observation, identification of MPs, and analysis of Cd elements in soil, respectively.ResultsHere, we found an average MP level of 112,400 items/kg in 30 sweet potato field sites based on the items in 5 g soil and the magnification (200x), and the maximum abundance was 197,153 items/kg in Laiyang city, Shandong province, by field survey. The distribution characteristics of MPs are middle-latitude areas < low-latitude areas, and eastern areas > central areas. Most MPs are of the fragment and film shape, which account for 47.96 and 40.22%, respectively. In order to detect MP polymers in three cities named “Liancheng,” “Huanggang,” and “Laiyang” with different degrees of development, a laser infrared imaging system was used as a novel instrument to explore the MPs larger than 10 μm.ConclusionThe results showed that PA is the main MP pollutant in contaminated sweet potato sites, and soil texture, planting time, and urbanization processes may be the main factors affecting MP distribution. The average cadmium (Cd) concentration in 215 field sites is 0.15 mg/kg, and the local Cd pollution is existing, but the overall pollution is low. In addition, Cd concentration was negatively correlated with MP abundance. This study reveals the status of MP and also Cd pollution in sweet potato fields, which provides a theoretical basis for the safe production and utilization of sweet potato fields.

Substation inspection robots often encounter complex environments, making the rapid identification of accessible paths crucial. Traditional global path planning methods for substation inspection robots are often characterized by shortcomings, such as prolonged execution times and substantial memory consumption. To address these issues, this paper introduces a novel strategy that integrates an improved jump point search (JPS) algorithm with the dynamic window algorithm (DWA). To mitigate the slow search speed of the traditional JPS algorithm, this study first proposes a bidirectional jump-point search technique. Additionally, an adaptive end-search mechanism is introduced to address the potential issue of non-overlapping jump points during the bidirectional search process. Second, to further enhance the reliability of the jump-point search algorithm, the search range is expanded from the original 8 domains to 16 domains. Additionally, a novel obstacle avoidance strategy and a revised cost function are proposed. Finally, the DWA algorithm is integrated to ensure that the planned path aligns more closely with the robot’ s actual trajectory. Experimental results demonstrate that the proposed algorithm maximally reduces the search time by 55.9% and the path length by 5.61% compared with traditional JPS algorithm, and shows superior overall performance in larger and more complex map environments.

In recent years, deep-learning-based classification methods have been widely used for hyperspectral images (HSIs). However, in the existing transformer-based HSI classification methods, how to effectively and comprehensively utilize the rich information still has room for improvement, for example, when utilizing multiple-image information, the comprehensive interaction between information has insufficient consideration. To address the above issues, cross-attention interaction, class token and patch token information, and multiscale spatial information are addressed in a unified framework, and a cross-attention-based multi-information fusion transformer (CAMFT) for HSI classification was proposed, which includes the multiscale patch embedding module, the residual connection-based DeepViT (RCD) module, and the double-branch cross-attention (DBCA) module. First, the multiscale patch embedding module is formed for multi-information preprocessing, accompanied by the built of different scale processing branches and the addition of learnable class tokens. Second, the RCD module is designed to utilize rich information from different layers; this module includes reattention and residual connection. Third, a DBCA module is constructed to obtain more representative multi-information fusion features; this module not only integrates multiscale patch information but also effectively utilizes complementary information between class tokens and patch tokens in the interaction of two branches. Moreover, numerous experiments demonstrate that, compared with other state-of-the-art classification methods, the proposed CAMFT method achieves the optimal classification performance, especially with a small training sample size, but it still has excellent performance.

Tunneling under existing underground buildings has become a common issue in densely populated urban areas. The current elastic analysis for ground displacement from new tunnel construction focuses on circular tunnels. However, theoretical analysis for non-circular chamber excavations is lacking. This paper aims to develop an elastic analysis for ground deformation from non-circular chamber excavations using the ‘equivalent radius’ theory, Verruijt’s formula, and Park’s model. It adjusts the ellipticization parameter δ and uniform radial displacement ε in Verruijt’s formula. Additionally, equivalent stiffness values for diverse existing hollow structures are considered using various approaches. A comparison of the theoretical results from field measurements and simulations shows the modified equations predict ground deformation well. Finally, parametric analysis explores the impacts of non-circular cavern excavations on existing structures under different factors.

Intelligent mobile robots have been gradually used in various fields, including logistics, healthcare, service, and maintenance. Path planning is a crucial aspect of intelligent mobile robot research, which aims to empower robots to create optimal trajectories within complex and dynamic environments autonomously. This study introduces an improved A* algorithm to address the challenges faced by the preliminary A* pathfinding algorithm, which include limited efficiency, inadequate robustness, and excessive node traversal. Firstly, the node storage structure is optimized using a minimum heap to decrease node traversal time. In addition, the heuristic function is improved by adding an adaptive weight function and a turn penalty function. The original 8-neighbor is expanded to a 16-neighbor within the search strategy, followed by the elimination of invalid search neighbor to refine it into a new 8-neighbor according to the principle of symmetry, thereby enhancing the directionality of the A* algorithm and improving search efficiency. Furthermore, a bidirectional search mechanism is implemented to further reduce search time. Finally, trajectory optimization is performed on the planned paths using path node elimination and cubic Bezier curves, which aligns the optimized paths more closely with the kinematic constraints of the robot derivable trajectories. In simulation experiments on grid maps of different sizes, it was demonstrated that the proposed improved A* algorithm outperforms the preliminary A* Algorithm in various metrics, such as search efficiency, node traversal count, path length, and inflection points. The improved algorithm provides substantial value for practical applications by efficiently planning optimal paths in complex environments and ensuring robot drivability.

As shield tunnels increase, managing shield muck strains construction and the environment. To mitigate this problem, shield muck replaced bentonite in silty clay to improve synchronous grouting slurry. Initially, the physical attributes and microstructural composition of shield muck were obtained, alongside an analysis of the effects of the muck content, particle size, and general influencing factors on the slurry properties through standardized tests and regression models. Subsequently, leveraging three-dimensional response surface methodology, admixture interactions and multiple factor impacts on the slurry were explored. Finally, utilizing the SQP optimization technique, an optimal slurry blend ratio tailored for actual project needs was derived for improved muck slurry. The findings reveal with the decreasing bleeding rates as the muck content rises, the particle size diminishes. An inverse relationship exists between the muck content and slurry fluidity. At soil–binder ratios below 0.6, a decrease in the soil–binder ratio intensifies the influence of the water–binder ratio on the slurry density, bleeding rate, and setting time. The fly flash–cement ratio inversely correlates with the slurry bleeding rate, while the ratio greater than 0.6 is positively correlated. For muck particle sizes under 0.2 mm, the fly flash–cement ratio inversely impacts the density, while over 0.2 mm, it correlates positively. The optimal proportion for silty clay stratum synchronous grouting slurry, substituting muck for bentonite, includes a water–binder ratio of 0.559, binder–sand ratio of 0.684, fly flash–cement ratio of 2.080, soil–binder ratio of 0.253, particle size under 0.075 mm, and water-reducing admixture of 0.06.

The identification of genome-wide selection signatures can reveal the potential genetic mechanisms involved in the generation of new breeds through natural or artificial selection. In this study, we screened the genome-wide selection signatures of prolific Suffolk sheep, a new strain of multiparous mutton sheep, to identify candidate genes for reproduction traits and unravel the germplasm characteristics and population genetic evolution of this new strain of Suffolk sheep. Whole-genome resequencing was performed at an effective sequencing depth of 20× for genomic diversity and population structure analysis. Additionally, selection signatures were investigated in prolific Suffolk sheep, Suffolk sheep, and Hu sheep using fixation index (FST) and heterozygosity H) analysis. A total of 5,236.338 Gb of high-quality genomic data and 28,767,952 SNPs were obtained for prolific Suffolk sheep. Moreover, 99 selection signals spanning candidate genes were identified. Twenty-three genes were significantly associated with KEGG pathway and Gene Ontology terms related to reproduction, growth, immunity, and metabolism. Through selective signal analysis, genes such as ARHGEF4, CATIP, and CCDC115 were found to be significantly correlated with reproductive traits in prolific Suffolk sheep and were highly associated with the mTOR signaling pathway, the melanogenic pathway, and the Hippo signaling pathways, among others. These results contribute to the understanding of the evolution of artificial selection in prolific Suffolk sheep and provide candidate reproduction-related genes that may be beneficial for the establishment of new sheep breeds.

【Objective】CIPK23 plays an important role in the development and mineral absorption in many plants, however, there are no relevant reports on CIPK23 gene and its function in flowering Chinese cabbage. The research will provide some theoretical references for further study of the function of BcCIPK23 in the growth and development and nitrogen metabolism in flowering Chinese cabbage.【Method】The full-length cDNA sequence of BcCIPK23 was obtained by homologous cloning method from flowering Chinese cabbage variety 'Youlv 501'. The encoded BcCIPK23 protein were analyzed by bioinformatics, and the expression characteristics of BcCIPK23 in different tissues and its response to different nitrogen sources of flowering Chinese cabbage were analyzed.【Result】The CDS full length of BcCIPK23 gene in flowering Chinese cabbage was 1 450 bp, encoding 482 amino acids, with a molecular weight of 53.41 kD, and a theoretical isoelectric point of 9.28. The BcCIPK23 sequence contained the domains of STKc-SnRK3 and CIPK-C, which were the conserved domains of CIPK family. The phylogenetic analysis showed that BcCIPK23 from flowering Chinese cabbage was antigenically closely related to BrCIPK23 from Brassica rapa. The qRT-PCR results showed that BcCIPK23 was expressed in leaves, petioles, stalks, roots, flowers and other tissues of flowering Chinese cabbage, but was mainly expressed in leaves, petioles and stalks. The expression level of BcCIPK23 was significantly affected by different sources and concentrations of nitrogen, decreased significantly with the increase of NO3- or NH4+ concentration. It was predicted that BcCIPK23 may play a key role in the growth and development of leaves and stalks, and the absorption and utilization of nitrogen in flowering Chinese cabbage.【Conclusion】BcCIPK23 is a member of the CIPK gene family, which is highly expressed in leaves and other active organs. It can respond to changes in nitrogen sources and nitrogen concentrations, and is involved in plant growth and development and nitrogen metabolic processes.

As a high-performance polymer, Polyether ether ketone (PEEK) and its injection-molded products are widely used as an ideal metal replacement. The production of ideal PEEK injection molded products, including microcellular injection molded, requires the support of high mold temperatures that can be maintained. Given this, a rapid mold temperature rising technology based on induction heating was designed to take advantage of the ultra-high heating rate of induction heating, which effectively met rapid increase and maintenance of high mold temperatures for PEEK injection molding. Both finite element analysis and experimental results showed, compared to the electric heating method, the induction heating method increased the efficiency to 5600% when the mold temperature rise from 150 to 180 °C compared to electric heating. All heating methods were used for the validation tests of injection molding PEEK, microporous injection molding PEEK, and micro-open microporous injection molding PEEK. The experimental results showed that the surface quality of PEEK samples molded by induction heating was 9.8%–61.2% higher than that of the oil heater heating, while the mechanical properties were more than 18%. Besides, the adaptability to longer holding times for micro-open microcellular injection molding suggested it can effectively broaden the possibilities of developing higher-performance PEEK foam products. The pioneering design and analysis of heating methods in this work had important guidance for promoting high-performance polymer injection molding and the lightweight of its foamed products.

Abstract Coxsackievirus A16 (CV-A16) is still an important pathogen that causes hand, foot and mouth disease (HFMD) in young children and infants worldwide. Previous studies indicated that CV-A16 infection is usually mild or self-limiting, but it was also found that CV-A16 infection can trigger severe neurological complications and even death. However, there are currently no vaccines or antiviral compounds available to either prevent or treat CV-A16 infection. Therefore, investigation of the virus‒host interaction and identification of host proteins that play a crucial regulatory role in the pathogenesis of CV-A16 infection may provide a novel strategy to develop antiviral drugs. Here, to increase our understanding of the interaction of CV-A16 with the host cell, we analyzed changes in the proteome of 16HBE cells in response to CV-A16 using tandem mass tag (TMT) in combination with LC‒MS/MS. There were 6615 proteins quantified, and 172 proteins showed a significant alteration during CV-A16 infection. These differentially regulated proteins were involved in fundamental biological processes and signaling pathways, including metabolic processes, cytokine‒cytokine receptor interactions, B-cell receptor signaling pathways, and neuroactive ligand‒receptor interactions. Further bioinformatics analysis revealed the characteristics of the protein domains and subcellular localization of these differentially expressed proteins. Then, to validate the proteomics data, 3 randomly selected proteins exhibited consistent changes in protein expression with the TMT results using Western blotting and immunofluorescence methods. Finally, among these differentially regulated proteins, we primarily focused on HMGB1 based on its potential effects on viral replication and virus infection-induced inflammatory responses. It was demonstrated that overexpression of HMGB1 could decrease viral replication and upregulate the release of inflammatory cytokines, but deletion of HMGB1 increased viral replication and downregulated the release of inflammatory cytokines. In conclusion, the results from this study have helped further elucidate the potential molecular pathogenesis of CV-A16 based on numerous protein changes and the functions of HMGB1 Found to be involved in the processes of viral replication and inflammatory response, which may facilitate the development of new antiviral therapies as well as innovative diagnostic methods.

Three species of spider genus Sinopoda Jäger, 1999 are reported from southern China. Two of them are described as new to science: S. guiyang Zhang, Yu & Zhong, sp. nov. and S. xishui Zhang, Yu & Zhong, sp. nov., both from Guizhou Province. The male of S. horizontalis Zhong, Cao & Liu, 2017 is described for the first time based on new material from the type locality, Wuyishan National Nature Reserve, Fujian Province, China. Detailed descriptions, diagnoses, photographs and a distribution map of the three species are provided.

In this study, a post-treatment method was carried out to increase the tensile strength of poly ether ketone (PEEK) fibers, with a maximum increase of 69%. The effects of the post-treatment process parameters on the diameter shrinkage ratio, mechanical properties of PEEK fibers, and the aggregated state structure were also quantitatively investigated by optical measurements, uniaxial tensile tests, differential scanning calorimetry, and two-dimensional-wide angle X-ray diffraction. These studies revealed that the enhanced orientation of PEEK fibers with increasing post-treatment temperature and constant tensile force is the major reason for the significant increase in uniaxial tensile strength. The diameter shrinkage ratio can be used as an indicator of the degree of fiber orientation. More critically, this study also presented mathematical models that described the high linearity of the increase in diameter shrinkage ratio and uniaxial tensile strength of fibers with post-treatment temperature and constant tensile force, respectively. That also revealed the equivalence of temperature and constant tensile force in the post-treatment process and obtained the conversion factor. These in-depth understandings provided positive guidance for improving the strength of PEEK fibers and achieving controllable morphology and mechanical properties in PEEK fiber production.

The rapid mutation of SARS-CoV-2 has led to multiple rounds of large-scale breakthrough infection and reinfection worldwide. However, the dynamic changes of humoral and cellular immunity responses to several subvariants after infection remain unclear. In our study, a 6-month longitudinal immune response evaluation was conducted on 118 sera and 50 PBMC samples from 49 healthy individuals who experienced BA.5/BF.7/XBB breakthrough infection or BA.5/BF.7-XBB reinfection. By studying antibody response, memory B cell, and IFN-γ secreting CD4+/CD8+ T cell response to several SARS-CoV-2 variants, we observed that each component of immune response exhibited distinct kinetics. Either BA.5/BF.7/XBB breakthrough infection or BA.5/BF.7-XBB reinfection induces relatively high level of binding and neutralizing antibody titers against Omicron subvariants at an early time point, which rapidly decreases over time. Most of the individuals at 6 months post-breakthrough infection completely lost their neutralizing activities against BQ.1.1, CH.1.1, BA.2.86, JN.1 and XBB subvariants. Individuals with BA.5/BF.7-XBB reinfection exhibit immune imprinting shifting and recall pre-existing BA.5/BF.7 neutralization antibodies. In the BA.5 breakthrough infection group, the frequency of BA.5 and XBB.1.16-RBD specific memory B cells, resting memory B cells, and intermediate memory B cells gradually increased over time. On the other hand, the frequency of IFN-γ secreting CD4+/CD8+ T cells induced by WT/BA.5/XBB.1.16 spike trimer remains stable over time. Overall, our research indicates that individuals with breakthrough infection have rapidly declining antibody levels but have a relatively stable cellular immunity that can provide some degree of protection from future exposure to new antigens.

A chemical investigation of the arils of Torreya grandis led to the isolation of seven abietane-type diterpenoids (compounds 1–7) including three previously undescribed compounds, one unreported natural product, and three known analogs. The structures of these compounds were determined by means of spectroscopy, single-crystal X-ray diffraction, and ECD spectra. An antibacterial activity assay showed that compounds 5 and 6 had significant inhibitory effects on methicillin-resistant Staphylococcus aureus, with MIC values of 100 μM. Moreover, compounds 1, 3, 4, and 7 exhibited anti-neuroinflammatory activity in LPS-stimulated BV-2 microglia cells, with the IC50 values ranging from 38.4 to 67.9 μM.

The shales of the Taiyuan Formation and Shanxi Formation in the North China Basin have good prospects for shale gas exploration and development. In this study, Well KP1 at the northern margin of the North China Basin was used as the research object for rock mineral, organic geochemical, and elemental geochemical analyses. The results show that brittle minerals in the shales of the Taiyuan Formation and Shanxi Formation are relatively rare (50%). The average TOC content is 3.68%. The organic matter is mainly mixed and sapropelic. The source rocks of the Taiyuan Formation and Shanxi Formation are mainly felsic, and the tectonic background lies in the continental island arc area. The primary variables that influenced the enrichment of organic materials during the sedimentary stage of the Taiyuan Formation were paleosalinity and paleoproductivity. Paleosalinity acted as the primary regulator of organic matter enrichment during the sedimentary stage of the Shanxi Formation.

Soil moisture (SM) plays a critical role in various fields such as agriculture, hydrology, and land-atmosphere interactions. This study aims to evaluate the performance of the categorical boosting algorithm (CatBoost) in comparison to other multiple-boosting algorithms for SM prediction. Appropriate feature selection is vital for achieving accurate predictions, and this study focuses on identifying relevant features and assessing CatBoost's suitability for the task. The study incorporates several boosting algorithms including Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and CatBoost to estimate SM. Results indicate that radar backscatter coefficient, soil roughness, and digital elevation model (DEM) are crucial features for SM retrieval. Comparatively, CatBoost outperforms GBDT, XGBoost, and LightGBM in various feature combinations. The most favorable results are obtained when utilizing all features as inputs for the algorithm. These optimal results yield a mean absolute error (MAE) of 2.40 vol.%, mean relative error (MRE) of 0.16 vol.%, root mean square error (RMSE) of 3.26 vol.%, and Pearson correlation coefficient of 0.73. Additionally, the study analyzes the inversion results for different ranges of SM and Normalized Difference Vegetation Index (NDVI). Within the range of SM from 0 to 25 vol.% and NDVI from 0 to 0.7, utilizing all features yields the most accurate results. Using CatBoost, this approach achieves an MAE of 1.52 vol.%, MRE of 0.12 vol.%, RMSE of 2.11 vol.%, and R of 0.81. The study suggests that applying boosting algorithms, especially CatBoost, holds promise in accurately estimating surface SM.

Functional muscle network analysis has attracted a great deal of interest in recent years, promising high sensitivity to changes of intermuscular synchronicity, studied mostly for healthy subjects and recently for patients living with neurological conditions (e.g., those caused by stroke). Despite the promising results, the between- and within-session reliability of the functional muscle network measures are yet to be established. Here, for the first time, we question and evaluate the test-retest reliability of non-parametric lower-limb functional muscle networks for controlled and lightly-controlled tasks, i.e., sit-to-stand, and over-the-ground walking, respectively, in healthy subjects. Fifteen subjects (eight females) were included over two sessions on two different days. The muscle activity was recorded using 14 surface electromyography (sEMG) sensors. The intraclass correlation coefficient (ICC) of the within-session and between-session trials was quantified for the various network metrics, including degree and weighted clustering coefficient. In order to compare with common classical sEMG measures, the reliabilities of the root mean square (RMS) of sEMG and the median frequency (MDF) of sEMG were also calculated. The ICC analysis revealed superior between-session reliability for muscle networks, with statistically significant differences when compared to classic measures. This paper proposed that the topographical metrics generated from functional muscle network can be reliably used for multi-session observations securing high reliability for quantifying the distribution of synergistic intermuscular synchronicities of both controlled and lightly controlled lower limb tasks. In addition, the low number of sessions required by the topographical network metrics to reach reliable measurements indicates the potential as biomarkers during rehabilitation.

Summary: Combination therapy using effective drug molecules and functional genes such as small interfering RNA (siRNA) has been suggested as a powerful strategy against multiple drug resistance. Here, we present a protocol for preparing a delivery system by developing dynamic covalent macrocycles using a dithiol monomer to co-deliver doxorubicin and siRNA. We describe steps for preparing the dithiol monomer, followed by co-delivery to form nanoparticles. We then detail procedures for cell uptake and assessing enhanced anti-cancer efficacy in vitro.For complete details on the use and execution of this protocol, please refer to Lyu et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

In hyperspectral image (HSI) classification scenarios, deep learning-based methods have achieved excellent classification performance, but often rely on large-scale training datasets to ensure accuracy. However, in practical applications, the acquisition of hyperspectral labeled samples is time consuming, labor intensive and costly, which leads to a scarcity of obtained labeled samples. Suffering from insufficient training samples, few-shot sample conditions limit model training and ultimately affect HSI classification performance. To solve the above issues, an active learning (AL)-based multipath residual involution Siamese network for few-shot HSI classification (AL-MRIS) is proposed. First, an AL-based Siamese network framework is constructed. The Siamese network, which has relatively low demand for sample data, is adopted for classification, and the AL strategy is integrated to select more representative samples to improve the model’s discriminative ability and reduce the costs of labeling samples in practice. Then, the multipath residual involution (MRIN) module is designed for the Siamese subnetwork to obtain the comprehensive features of the HSI. The involution operation was used to capture the fine-grained features and effectively aggregate the contextual semantic information of the HSI through dynamic weights. The MRIN module comprehensively considers the local features, dynamic features and global features through multipath residual connections, which improves the representation ability of HSIs. Moreover, a cosine distance-based contrastive loss is proposed for the Siamese network. By utilizing the directional similarity of high-dimensional HSI data, the discriminability of the Siamese classification network is improved. A large number of experimental results show that the proposed AL-MRIS method can achieve excellent classification performance with few-shot training samples, and compared with several state-of-the-art classification methods, the AL-MRIS method obtains the highest classification accuracy.

ABSTRACT: Objectives: To evaluate the performance of nucleotide matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in predicting the drug resistance of Mycobacterium tuberculosis. Methods: A total of 115 rifampin-resistant and 53 rifampin-susceptible tuberculosis (TB) clinical isolates were randomly selected from TB strains stored at -80℃ in the clinical laboratory of Shanghai Pulmonary Hospital. Nucleotide MALDI-TOF-MS was performed to predict the drug resistance using phenotypic susceptibility as the gold standard. Results: The overall assay sensitivities and specificities of nucleotide MALDI-TOF-MS were 92.2% and 100.0% for rifampin, 90.9% and 98.6% for isoniazid, 71.4% and 81.2% for ethambutol, 85.1% and 93.1% for streptomycin, 94.0% and 100.0% for amikacin, 77.8% and 99.3% for kanamycin, 75.0% and 93.3% for ofloxacin, and 75.0% and 93.3% for moxifloxacin. The concordances between nucleotide MALDI-TOF-MS antimicrobial susceptibility testing (AST) and phenotypic AST were 94.6% (rifampin), 90.1% (isoniazid), 79.2% (ethambutol), 89.9% (streptomycin), 99.4% (amikacin), 97.0% (kanamycin), 88.1% (ofloxacin), and 88.0% (moxifloxacin). Conclusion: Nucleotide MALDI-TOF-MS could be a promising tool for rapid detection of Mycobacterium tuberculosis drug sensitivity to rifampin, isoniazid, ethambutol, streptomycin, amikacin, kanamycin, ofloxacin, and moxifloxacin.

Polyether-ether-ketone (PEEK) is an excellent engineering polymer with numerous advantages. Processing by microcellular injection molding (MIM) can reduce product weight and save energy consumption. However, conventional MIM is plagued with limited weight-reduction and poor surface quality, so there have been few reports on microcellular PEEK with high weight-reduction based on injection molding. In this study, microcellular PEEK with weight reduction of 49.6% was prepared by mold-opening microcellular injection molding (MOMIM). The effects of holding time, holding pressure and mold-opening distance on microcellular PEEK were studied. Results show that incremental holding time and holding pressure could increase PEEK's density, promote the formation of dense cells and improve mechanical properties. Meanwhile, larger mold-opening distance reduced product's density, raised cell size and cell density, and lowered tensile properties, while the flexural properties increased first and then decreased when the mold-opening distance became larger. In addition, the surface qualities of microcellular PEEK prepared by MIM and MOMIM were compared, and it was found that MOMIM could significantly improve the surface quality. These microcellular PEEK prepared by MOMIM with tunable properties can further promote the lightweight application of PEEK.

Abstract Objective To explore the appropriate dosage of levothyroxine treatment for congenital hypothyroidism patients with different thyroid stimulating hormone (TSH) levels. Methods A total of 116 patients, who were regularly followed-up in our endocrine clinic from January 2010 to December 2020, were divided into four groups based on their thyroid function (group A: TSH ≥ 100 mIU/L, group B: TSH ≥ 20, and 4.6 mIU/L and 4.6 mIU/L and 6.6 pmol/L). The initial dosage of levothyroxine was individualized for each patient based on their TSH level and then adjusted according to their thyroid function at every follow-up time point. The levothyroxine dosage at each time point was compared between the groups, and thyroid function and physical and neurological development after treatment were also compared. Results After individualized dosage adjustment, all patients achieved normal thyroid function. Although there were statistical differences in neurological development between the four groups (p

Abstract Background Bronchopulmonary dysplasia (BPD) is one of the most common adverse consequence of premature delivery and the most common chronic lung disease in infants. BPD is associated with long-term lung diseases and neurodevelopmental disorders that can persist into the adulthood. The adverse consequences caused by severe BPD are more serious. However, there were few studies on the risk factors for severe BPD. Methods This is a retrospective study of preterm infants born less than 32-week gestational age (GA) and diagnosed with BPD. Results A total of 250 preterm infants with a diagnosis of BPD and GA

Deep learning has been demonstrated to be a powerful nonlinear modeling method with end-to-end optimization capabilities for hyperspectral Images (HSIs). However, in real classification cases, obtaining labeled samples is often time-consuming and labor-intensive, resulting in few-shot training samples. Based on this issue, a multipath and multiscale Siamese network based on spatial-spectral features for few-shot hyperspectral image classification (MMSN) is proposed. To conduct classification with few-shot training samples, a Siamese network framework with low dependence on sample information is adopted. In one subnetwork, a spatial attention module (DCAM), which combines dilated convolution and cosine similarity to comprehensively consider spatial-spectral weights, is designed first. Then, we propose a residual-dense hybrid module (RDHM), which merges three-path features, including grouped convolution-based local residual features, global residual features and global dense features. The RDHM can effectively propagate and utilize different layers of features and enhance the expression ability of these features. Finally, we construct a multikernel depth feature extraction module (MDFE) that performs multiscale convolutions with multikernel and hierarchical skip connections on the feature scales to improve the ability of the network to capture details. Extensive experimental evidence shows that the proposed MMSN method exhibits a superior performance on few-shot training samples, and its classification results are better than those of other state-of-the-art classification methods.

We performed a prospective study to evaluate the diagnostic accuracy of nucleotide matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) in identifying nontuberculous mycobacterium (NTM) from clinical respiratory samples. A total of 175 eligible patients were prospectively enrolled, including 108 patients diagnosed with NTM pulmonary disease (NTM-PD) and 67 control patients with other diseases. All specimens were subjected to acid-fast staining, liquid culture combined with MPT64 antigen detection, and a nucleotide MALDI-TOF MS assay. NTM cultures were also subjected to the MeltPro Myco assay for species identification. Altogether, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of nucleotide MALDI-TOF MS were 77.8% (95% CI: 68.6–85.0%), 92.5% (82.8–97.2%), 94.4% (86.8–97.9%), and 72.1% (61.2–81.0%), respectively; these results were not statistically different from the results of culture + MPT64 antigen testing (75.0% [65.6–82.6%], 95.5% [86.6–98.8%], 96.4% [89.2–99.1%], and 70.3% [59.7–79.2%], respectively). In the identification of NTM species, of the 84 nucleotide MALDI-TOF MS positive samples, 77 samples (91.7%) were identified at the species level. Using culture + MeltPro Myco assay as the reference standard, nucleotide MALDI-TOF MS correctly identified 77.8% (63/81) of NTM species. Our results demonstrated that the nucleotide MALDI-TOF MS assay was a rapid single-step method that provided the reliable detection of NTM and identification of NTM species. This new method had the same sensitivity and specificity as the culture + MPT64 antigen method, but was much more rapid.

Abstract Background To verify the efficacy and safety of an inexpensive standardized regimen for multidrug-resistant tuberculosis (MDR-TB) with low resistance to isoniazid (INH), a multicenter prospective study was conducted in eastern China. Methods Patients diagnosed as MDR-TB with low concentration INH resistance and rifampicin resistance, second-line/injectable agents sensitive were prospectively enrolled, given the regimen of Amikacin (Ak)–Fluoroquinolones (FQs)–Cycloserine (Cs)–Protionamide (Pto)–PasiniaZid (Pa)–Pyrazinamide (Z) for 6 months followed by 12 months of FQs–Cs–Pto–Pa–Z, and then followed up for treatment outcomes and adverse events (AEs). Results A total of 114 patients were enrolled into the study. The overall favorable treatment rate was 79.8% (91/114). Among 91 cases with favorable treatment, 75.4% (86/114) were cured and 4.4% (5/114) were completed treatment. Regarding to unfavorable outcomes, among 23 cases, 8.8% (10/114) had failures, 8.8% (10/114) losing follow up, 0.9% (1/114) had treatment terminated due to intolerance to drugs and 1.8% (2/114) died. Treatment favorable rate was significantly higher in newly treated MDR-TB (91.7%, 33/36) than that in retreated MDR-TB (74.4%, 58/78, p 0.03). The investigators recorded 42 AEs occurrences in 30 of 114 patients (26.3%). Clinicians rated most AEs as mild or moderate (95.24%, 40/42). Conclusions The regimen was proved to be effective, safe and inexpensive. It is suitable for specific drug resistant population, especially for newly-treated patients, which could be expected to be developed into a short-course regimen. Clinical trials registration China Clinical Trial Registry ChiCTR-OPC-16009380

Background: Enterovirus A71 (EVA71) is one of the main pathogens causing hand, foot and mouth disease (HFMD). In China, the proportion of cases of HFMD caused by EVA71 is known to be significantly lower following EVA71 vaccination; however, infection with EVA71 can still occur after vaccination. Methods: The complete genomic sequences of EVA71-KM18A and KM18B (from two rare cases of EVA71 infection following vaccination) were obtained. Phylogenetic analysis, nucleotide mutation analysis, recombinant analysis and comparative analysis of amino acid mutations were performed. Results: Phylogenetic analysis determined that the EVA71 strains belonged to the C4a subgenotype. The KM18A and KM18B strains were highly similar to the vaccine strains. For the KM18B strain, there were some obvious homologous recombination signals in the 5’non-coding region, region 2A, region 2C and region 3D. Amino acid mutations were observed in the SP55 (position 729) and 71-6 (position 500) conformational neutralizing epitopes of the KM18A and KM18B strains. Conclusions: These amino acid mutations may affect the SP55 and 71-6 conformational neutralizing epitopes and change their spatial conformation, thereby weakening vaccine effectiveness.

This study focuses on the problem of multitarget tracking. To address the existing problems of current tracking algorithms, as manifested by the time consumption of subgroup separation and the uneven group size of unmanned aerial vehicles (UAVs) for target tracking, a multitarget tracking control algorithm under local information selection interaction is proposed. First, on the basis of location, number, and perceived target information of neighboring UAVs, a temporary leader selection strategy is designed to realize the local follow-up movement of UAVs when the UAVs cannot fully perceive the target. Second, in combination with the basic rules of cluster movement and target information perception factors, distributed control equations are designed to achieve a rapid gathering of UAVs and consistent tracking of multiple targets. Lastly, the simulation experiments are conducted in two- and three-dimensional spaces. Under a certain number of UAVs, clustering speed of the proposed algorithm is less than 3 s, and the equal probability of the UAV subgroup size after group separation is over 78%.

Optical frequency combs can provide phase-coherent links between optical frequencies and microwaves, allowing for precise optical frequency generation; however current technologies require external optical references or multiple power-intensive peripherals that make them less suitable for on-chip applications. Here, the authors present phase stabilization of a frequency microcomb without nonlinear processes nor external optical reference signals.

ABSTRACT Our objective was to evaluate the performance of whole-genome sequencing (WGS) from early positive liquid cultures for predicting Mycobacterium tuberculosis complex (MTBC) drug resistance. Clinical isolates were obtained from tuberculosis patients at Shanghai Pulmonary Hospital (SPH). Antimicrobial susceptibility testing (AST) was performed, and WGS from early Bactec mycobacterial growth indicator tube (MGIT) 960-positive liquid cultures was performed to predict the drug resistance using the TB-Profiler informatics platform. A total of 182 clinical isolates were enrolled in this study. Using phenotypic AST as the gold standard, the overall sensitivity and specificity for WGS were, respectively, 97.1% (89.8 to 99.6%) and 90.4% (83.4 to 95.1%) for rifampin, 91.0% (82.4 to 96.3%) and 95.2% (89.1 to 98.4%) for isoniazid, 100.0% (89.4 to 100.0%) and 87.3% (80.8 to 92.1%) for ethambutol, 96.6% (88.3 to 99.6%) and 61.8% (52.6 to 70.4%) for streptomycin, 86.8% (71.9 to 95.6%) and 95.8% (91.2 to 98.5%) for moxifloxacin, 86.5% (71.2 to 91.5%) and 95.2% (90.3 to 98.0%) for ofloxacin, 100.0% (54.1 to 100.0%) and 67.6% (60.2 to 74.5%) for amikacin, 100.0% (63.1 to 100.0%) and 67.2% (59.7 to 74.2%) for kanamycin, 62.5% (24.5 to 91.5%) and 88.5% (82.8 to 92.8%) for ethionamide, 33.3% (4.3 to 77.7%) and 98.3% (95.1 to 99.7%) for para-aminosalicylic acid, and 0.0% (0.0 to 12.3%) and 100.0% (97.6 to 100.0%) for cycloserine. The concordances of WGS-based AST and phenotypic AST were as follows: rifampin (92.9%), isoniazid (93.4%), ethambutol (89.6%), streptomycin (73.1%), moxifloxacin (94.0%), ofloxacin (93.4%), amikacin (68.7%), kanamycin (68.7%), ethionamide (87.4%), para-aminosalicylic acid (96.2%) and cycloserine (84.6%). We conclude that WGS could be a promising approach to predict MTBC resistance from early positive liquid cultures. IMPORTANCE In this study, we used whole-genome sequencing (WGS) from early positive liquid (MGIT) cultures instead of solid cultures to predict drug resistance of 182 Mycobacterium tuberculosis complex (MTBC) clinical isolates to predict drug resistance using the TB-Profiler informatics platform. Our study indicates that WGS may be a promising method for predicting MTBC resistance using early positive liquid cultures.

IntroductionFear of missed serious bacterial infections (SBIs) results in many febrile young infants receiving antibiotics. We aimed to compare the time to antibiotics between infants with SBIs and those without.Materials and MethodsWe recruited febrile infants ≤ 90 days old seen in the emergency department (ED) between December 2017 and April 2021. SBI was defined as (1) urinary tract infection, (2) bacteremia or (3) bacterial meningitis. We compared the total time (median with interquartile range, IQR) from ED arrival to infusion of antibiotics, divided into (i) time from triage to decision for antibiotics and (ii) time from decision for antibiotics to administration of antibiotics.ResultsWe analyzed 81 and 266 infants with and without SBIs. Median age of those with and without SBIs were 44 (IQR 19–72) and 29 (IQR 7–56) days, respectively (p = 0.002). All infants with SBIs and 168/266 (63.2%) infants without SBIs received antibiotics. Among 249 infants who received antibiotics, the median total time from ED arrival to infusion of antibiotics was 277.0 (IQR 236.0–385.0) mins for infants with SBIs and 304.5 (IQR 238.5–404.0) mins for those without (p = 0.561). The median time to decision for antibiotics was 156.0 (IQR 115.0–255.0) mins and 144.0 (IQR 105.5–211.0) mins, respectively (p = 0.175). Following decision for antibiotics, infants with SBIs received antibiotics much faster compared to those without [107.0 (IQR 83.0–168.0) vs. 141.0 (94.0–209.5) mins, p = 0.017].ConclusionThere was no difference in total time taken to antibiotics between infants with SBIs and without SBIs. Both recognition and administration delays were observed. While all infants with SBIs were adequately treated, more than half of the infants without SBIs received unnecessary antibiotics. This highlights the challenge in managing young febrile infants at initial presentation, and demonstrates the need to examine various aspects of care to improve the overall timeliness to antibiotics.

Objective: To evaluate the performance of whole-genome sequencing (WGS) for predicting Mycobacterium tuberculosis (MTB) drug resistance. Methods: 276 rifampin-resistance tuberculosis (RR-TB) and 30 rifampicin-sensitive clinical isolates were randomly selected from patients with tuberculosis in Shanghai Pulmonary Hospital (SPH). Phenotypic drug susceptibility testing (DST) against six anti-TB drugs was performed, and WGS was used to predict the drug resistance using an online ‘TB-Profiler’ tool. Results: Using phenotypic susceptibility as the gold standard, the overall sensitivities and specificities for WGS were 94.53% and 92.00% for isoniazid, 97.10% and 100.00% for rifampicin, 97.46% and 64.36% for ethambutol, 97.14% and 95.83% or streptomycin, 93.02% and 98.87% for ofloxacin, and 75.00% and 100.00% for amikacin, respectively. The concordances of WGS-based DST and phenotypic DST were: isoniazid (94.12%), rifampicin (97.39%), ethambutol (77.12%), streptomycin (96.73%), ofloxacin (96.41%) and amikacin (97.06%). Conclusions: WGS could be a promising approach to predict resistance to isoniazid, rifampicin, ethambutol, streptomycin, ofloxacin, and amikacin.

Objectives: To report the cost-effectiveness of Xpert in detecting Mycobacterium tuberculosis (MTB) through a comprehensive systematic review. Methods: Specialized bibliographic databases were searched. Study quality was evaluated by commonly-used industry standards. Due to heterogeneity, evidences were synthesized narratively. Results: Four studies from intermediate-to-low tuberculosis (TB)-burdern areas and 17 studies from high-TB-burden areas were included. Smear microscopy, clinical diagnosis and chest radiography were mostly used for comparison. Cost elements varied considerably depending on the perspectives. Cost-effectiveness and cost-utility analyses were used by seven and fourteen studies, respectively. All studies were of high quality (CHEERS score of 78.4 and QHES score of 86.9). Average cost per test was 29.8 US$ for Xpert compared with 3.83 US$ for smear microscopy. Cost-effectiveness analyses mostly supported application of Xpert into areas under varying TB burdens. Conclusions: Xpert seems cost-effective under respective willingness-to-pay thresholds in nations with differences in socioeconomy, HIV stress and geographical distribution. Nevertheless, policymakers will benefit from localized studies since regional economic/financial statuses and health-care system should also be considered apart from the reports of cost-effectiveness.

ABSTRACT Mycobacterium kansasii, an important opportunistic pathogen of humans, causes serious pulmonary disease. Sixty M. kansasii isolates were collected for investigating the clinical characteristics of patients with M. kansasii infections as well as drug susceptibility and genotypes of M. kansasii. More than 90% of the patients infected with M. kansasii were from eastern China. According to the internal transcribed spacers (ITS), rpoB, hsp65, and tuf, all M. kansasii isolates were classified as molecular type I, irrespective of the disease manifestation. Sixty M. kansasii isolates from China were diverse and separated into four branches. Pairwise average nucleotide identity (ANI) values for M. kansasii isolates affiliated with different genotypes were more than 85%. The earliest isolate was isolated from Jiangsu in 1983. Of the isolates, 78.3% (47/60) were isolated since 1999. All isolates were sensitive to rifabutin. All but one isolate was sensitive to clarithromycin. Sensitivity rates to rifampin, amikacin, moxifloxacin, and linezolid were 80.0%, 90.0%, 88.3%, and 91.7%, respectively. A high rate of resistance was noted for ciprofloxacin (44 isolates, 73.3%) and ethambutol (46 isolates, 76.7%). Compared with M. tuberculosis H37Rv, 12 mutations of embCA were observed in all M. kansasii isolates. All these 60 M. kansasii isolates shared identical sequences of rpoB, inhA, katG, rrl, rrs, rpsL, gyrA, and gyrB. In conclusion, M. kansasii isolates are exhibiting greater genetic diversity globally. The resistance mechanism of M. kansasii is not necessarily related to gene mutation. IMPORTANCE M. kansasii type I is the main genotype spreading worldwide. The molecular history of the global spread of type I isolates remains largely unclear. We conducted a detailed analysis of genomic evolution of global M. kansasii isolates. Our results suggest that M. kansasii isolates exhibit greater genetic diversity globally.

Dissipative Kerr solitons (DKSs) in microresonators have boosted the development of the chip-scale ultrastable microcomb sources, and thrived in both fundamental physics and a wide range of applications. Among various DKS states, single DKS, double DKS, and a perfect soliton crystal could be identified simply based on the optical spectrum. Especially, the double DKS state, due to its two-pulse-interference nature, has recently found its own application in microwave photonics, such as reconfigurable rf filters. However, the traditional method to generate double DKS usually yields stochastically relative positions of the DKS in the cavity, which limits the versatility of the application. Here a method to deterministically generate double DKSs with fixed relative positions assisted by the dual-pump driven scheme in a 97-GHz Si_{3}N_{4} microresonator is demonstrated. Via the dual-pump scheme, not only has the single soliton been repeatably generated, double DKS with deterministic relative positions has also been realized through backward tuning. The effects of pump wavelength tuning and pump power on the relative positions are investigated. A direct bridge between the relative positions and the avoided mode crossing induced modulated cw background is established. This work not only provides insight to DKS dynamics in a dual-pump scheme, but also improves the versatility of double-DKS based applications in microwave photonics.

A compact wideband optical switch assisted by graphene nanosheet heater is demonstrated by shifting the bandedge of the photonic crystal waveguides (PhCWG) through current-induced heating. The high heating efficiency of graphene and the high light-matter interactions in slow-light PhCWG are combined to enhance the heating efficiency and extinction ratio. The extinction ratio is increased from 15 dB to 22 dB and the tuning bandwidth is up to 20 nm with only 28 K temperature change. Our measurements match well with simulation results, suggesting an effective way for CMOS compatible chip-scale integrated graphene microheater switch.

Research on product distribution channels has mainly focused on channel cost, risk aversion, consumer fairness preference, price decision, channel coordination, and channel selection while paying less attention to the product experience. Compared with offline channels, the online channel is at a disadvantage with regards to the product experience. For experience products, consumers cannot accurately access the value of the products through online channels because of its virtuality. In contrast, offline channels can attract more consumers with real product experience. However, the application of virtual reality technology has become increasingly more extensive in recent years. Virtual reality technology enhances the interaction level between online consumers and experience products, and it can help consumers assess product value more accurately, which has a greater impact on consumers' purchase decisions. Manufacturers can make full use of virtual reality technology to expand online sales. To maximize the manufacturers' revenue, this paper uses consumer utility theory and game theory to design four experience products' distribution channel models and analyzes the relationship between the manufacturers' revenue in different distribution channel models and virtual reality technology. The results show when the interaction level of virtual reality technology is low, manufacturers tend to choose a dual distribution channel, but when the interaction level of virtual reality technology is high, a single online distribution channel is the best choice for manufacturers.

Motor systems are becoming more and more vital in modern manufacturing and bearings play an important role in the performance of a motor system. Many problems that arise in motor operation are related to bearing faults. In many cases, the accuracy of the devices for monitoring or controlling a motor system highly depends on the dynamic properties of motor bearings. Thus, fault diagnosis of a motor system is inseparably related to the diagnosis of the bearing assembly. The fault diagnosis of rolling bearings is substantially a classification problem. The traditional application of random forest (RF) to fault diagnosis methods is based on balanced data. However, in a practical situation, it is difficult to collect the fault data that are usually unbalanced. In order to solve this problem, in the first step, we propose a two-step (TS) clustering algorithm to enhance the original synthetic minority oversampling technique (SMOTE) algorithm for the unbalanced data classification. Then, based on the improvement of the SMOTE algorithm, we propose the principal component analysis (PCA) and apply it in the field of high-dimensional unbalanced fault diagnosis data. In this paper, we apply this new method to the fault diagnosis of rolling bearings, and the experiments conducted in the end show that the improved algorithm has a better classification performance.

In satellite scheduling system, one of the most important issues is task scheduling. Most of the existing algorithms focused on the scenario of normal tasks with fixed priority and don’t consider emergency tasks. However, emergency tasks in satellite scheduling system have the independent arrival time and execution deadline. To deal with this challenge, we propose the task scheduling model, task priority model, and task scheduling algorithms based on rolling-horizon optimization (RHO) strategy to manage the tasks. In task scheduling model, we construct a scheduling model with multiple constraint conditions. In task priority model, we decompose task priority into four parts, including target priority, imaging task priority, TT&C (track, telemetry, control) requirement priority, and data transmission requirement priority, and describe the factors corresponding to each priority based on the actual engineering. The RHO strategy is designed with a periodical triggering mode, and scheduling process is decomposed into a series of static scheduling intervals, the dynamic scheduling of emergency tasks is realized by optimizing the scheduling schemes in each interval. Meanwhile, task scheduling algorithms, including heuristic algorithm, genetic algorithm, and NSGA-II algorithm, are designed to solve the proposed task scheduling model. Our simulation results show that the proposed task priority model and RHO strategy are effective, which can significantly improve the number of overall tasks and emergency tasks. Meanwhile, each task scheduling algorithm has different performances in the processing time and optimal objectives.

In recent years, deep-learning-based hyperspectral image (HSI) classification networks have become one of the most dominant implementations in HSI classification tasks. Among these networks, convolutional neural networks (CNNs) and attention-based networks have prevailed over other HSI classification networks. While convolutional neural networks with perceptual fields can effectively extract local features in the spatial dimension of HSI, they are poor at capturing the global and sequential features of spectral–spatial information; networks based on attention mechanisms, for example, Transformer, usually have better ability to capture global features, but are relatively weak in discriminating local features. This paper proposes a fusion network of convolution and Transformer for HSI classification, known as FusionNet, in which convolution and Transformer are fused in both serial and parallel mechanisms to achieve the full utilization of HSI features. Experimental results demonstrate that the proposed network has superior classification results compared to previous similar networks, and performs relatively well even on a small amount of training data.

Porous nanomaterials have attracted much attention in the field of electrochemiluminescence (ECL) analysis research because of their large specific surface area, high porosity, possession of multiple functional groups, and ease of modification. Porous nanomaterials can not only serve as good carriers for loading ECL luminophores to prepare nanomaterials with excellent luminescence properties, but they also have a good electrical conductivity to facilitate charge transfer and substance exchange between electrode surfaces and solutions. In particular, some porous nanomaterials with special functional groups or centered on metals even possess excellent catalytic properties that can enhance the ECL response of the system. ECL composites prepared based on porous nanomaterials have a wide range of applications in the field of ECL biosensors due to their extraordinary ECL response. In this paper, we reviewed recent research advances in various porous nanomaterials commonly used to fabricate ECL biosensors, such as ordered mesoporous silica (OMS), metal–organic frameworks (MOFs), covalent organic frameworks (COFs) and metal–polydopamine frameworks (MPFs). Their applications in the detection of heavy metal ions, small molecules, proteins and nucleic acids are also summarized. The challenges and prospects of constructing ECL biosensors based on porous nanomaterials are further discussed. We hope that this review will provide the reader with a comprehensive understanding of the development of porous nanomaterial-based ECL systems in analytical biosensors and materials science.

Background: Phenotypes have been identified within heterogeneous disease, such as acute respiratory distress syndrome and sepsis, which are associated with important prognostic and therapeutic implications. The present study sought to assess whether phenotypes can be derived from intensive care patients with coronavirus disease 2019 (COVID-19), to assess the correlation with prognosis, and to develop a parsimonious model for phenotype identification.Methods: Adult patients with COVID-19 from Tongji hospital between January 2020 and March 2020 were included. The consensus k means clustering and latent class analysis (LCA) were applied to identify phenotypes using 26 clinical variables. We then employed machine learning algorithms to select a maximum of five important classifier variables, which were further used to establish a nested logistic regression model for phenotype identification.Results: Both consensus k means clustering and LCA showed that a two-phenotype model was the best fit for the present cohort (N = 504). A total of 182 patients (36.1%) were classified as hyperactive phenotype, who exhibited a higher 28-day mortality and higher rates of organ dysfunction than did those in hypoactive phenotype. The top five variables used to assign phenotypes were neutrophil-to-lymphocyte ratio (NLR), ratio of pulse oxygen saturation to the fractional concentration of oxygen in inspired air (Spo2/Fio2) ratio, lactate dehydrogenase (LDH), tumor necrosis factor α (TNF-α), and urea nitrogen. From the nested logistic models, three-variable (NLR, Spo2/Fio2 ratio, and LDH) and four-variable (three-variable plus TNF-α) models were adjudicated to be the best performing, with the area under the curve of 0.95 [95% confidence interval (CI) = 0.94–0.97] and 0.97 (95% CI = 0.96–0.98), respectively.Conclusion: We identified two phenotypes within COVID-19, with different host responses and outcomes. The phenotypes can be accurately identified with parsimonious classifier models using three or four variables.

Abstract Ultrafast optical switch based on plasmonic nanostructures has large application potentials in optical logic circuits and optical communication systems. Integration of plasmonic optical switching devices with optical fibers is a breakthrough for realizing practical applications in long‐range optical data transmission or communication techniques. Here, the incorporation of plasmonic optical switch devices onto the end facets of optical fibers is reported, so that the switched optical signals are generated by interaction between femtosecond laser pulses and plasmonic nanostructures on one end of the fiber, and are delivered via the fiber waveguide to the other end for detection or decoding. “Quenching” of localized surface plasmon in the gold nanowires by its interaction with band‐edge modulation in gold through strong optical excitation is the responsible photophysics. This work accomplishes for the first time the implementation of ultrafast plasmonic optical switch device on optical fiber tips for logic data transmission.