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Abstract Aims Compared to primary breast sarcoma (BSs), radiotherapy-induced sarcoma (RIS) is a less frequent type of secondary breast sarcoma. Undifferentiated pleomorphic sarcoma (UPS) is an even rarer occurrence within the RIS category. This study aimed to present the clinicopathologic and molecular features of breast radiotherapy-induced UPS. Methods A retrospective study was conducted at the Third Affiliated Hospital of Soochow University to analyze three patients with radiation-induced undifferentiated pleomorphic sarcoma (UPS) following breast cancer, spanning from 2006 to 2023. The clinical and pathological variables were extracted from the medical records, while immunohistochemistry was employed to analyze the immunophenotypes of these tumors. Genomic characteristics were assessed through DNA and RNA sequencing techniques. Another 15 cases from the literature were also reviewed to better characterize the tumor. Results The affected areas encompass the chest wall and breasts, with an incubation period ranging from 6 to 17 years. The tumor cells exhibit pleomorphism and demonstrate a high degree of pathological mitosis. Notably, two cases displayed an accelerated disease progression, characterized by recurrent tumors and metastases occurring within short intervals of 48 and 7 months respectively subsequent to the initial diagnosis. The two prevailing identified genes were TP53 (2/3, 66.7%) and RB1 (1/3, 33.3%). Through analysis of somatic copy number variation (CNV), it was discovered that two oncogenes, MCL1 (1/3, 33.3%) and MYC (1/3, 33.3%), had experienced gains in CNV. The Tumor Mutational Burden (TMB) values for case 1, case 2, and case 3 were 5.9 mut/Mb, 1.0 mut/Mb, and 3.0 mut/Mb, respectively. Moreover, the analysis of RNA-NGS (next-generation sequencing) revealed the presence of a novel gene fusion, named COL3A1-GULP1, in case 2. Conclusions Based on our thorough analysis of research findings and previous reports, it is evident that radiotherapy-induced UPS exhibits a highly diverse and frequently severe clinical and biological behavior. Identifying tumor formation using genome sequencing can help understand its biological behavior and determine personalized treatments.

Abstract Background Investigating immune cell infiltration in the brain post-ischemia-reperfusion (I/R) injury is crucial for understanding and managing the resultant inflammatory responses. This study aims to unravel the role of the RPS27A-mediated PSMD12/NF-κB axis in controlling immune cell infiltration in the context of cerebral I/R injury. Methods To identify genes associated with cerebral I/R injury, high-throughput sequencing was employed. The potential downstream genes were further analyzed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) analyses. For experimental models, primary microglia and neurons were extracted from the cortical tissues of mouse brains. An in vitro cerebral I/R injury model was established in microglia using the oxygen-glucose deprivation/reoxygenation (OGD/R) technique. In vivo models involved inducing cerebral I/R injury in mice through the middle cerebral artery occlusion (MCAO) method. These models were used to assess neurological function, immune cell infiltration, and inflammatory factor release. Results The study identified RPS27A as a key player in cerebral I/R injury, with PSMD12 likely acting as its downstream regulator. Silencing RPS27A in OGD/R-induced microglia decreased the release of inflammatory factors and reduced neuron apoptosis. Additionally, RPS27A silencing in cerebral cortex tissues mediated the PSMD12/NF-κB axis, resulting in decreased inflammatory factor release, reduced neutrophil infiltration, and improved cerebral injury outcomes in I/R-injured mice. Conclusion RPS27A regulates the expression of the PSMD12/NF-κB signaling axis, leading to the induction of inflammatory factors in microglial cells, promoting immune cell infiltration in brain tissue, and exacerbating brain damage in I/R mice. This study introduces novel insights and theoretical foundations for the treatment of nerve damage caused by I/R, suggesting that targeting the RPS27A and downstream PSMD12/NF-κB signaling axis for drug development could represent a new direction in I/R therapy.

Because the deformation parameters (temperature, strain rate) in the actual manufacturing process are non-constant. We investigate meta-dynamic recrystallization behavior under the transient mutation state. First, based on a single-pass thermal deformation experiment and electron backscatter diffraction (EBSD) technique, this study establishes a quantitative calculation method for the volume fraction of meta-dynamic recrystallization under different deformation conditions, and find the GOS threshold basis for judging the occurrence of meta-dynamic recrystallization. Comparing the experimental results with the numerical simulation results, it is found that the MDRX behavior of the material could be accurately described. The meta-dynamic recrystallization evolution law of the material in the thermal deformation insulation stage under the variable strain rate state is investigated by continuous variable rate thermal deformation experiment and numerical simulation. It is observed that an increase of the average strain rate in the continuous variable strain rate state would promote the meta-dynamic recrystallization softening behavior of the material in comparison with the steady state deformation stage, and vice versa.

Abstract We study properties of the innermost photonsphere in the regular compact star background. We take the traceless energy–momentum tensor and dominant energy conditions. In the regular compact star background, we analytically obtain an upper bound on the radius of the innermost photonsphere as $$r_{\gamma }^{in}\leqslant \frac{12}{5}M,$$ r γ in ⩽ 12 5 M , where $$r_{\gamma }^{in}$$ r γ in is the radius of the innermost photonsphere and M is the total ADM mass of the asymptotically flat compact star spacetime.

Abstract Background White clover (Trifolium repens L.) is an excellent leguminous cool-season forage with a high protein content and strong nitrogen-fixing ability. Despite these advantages, its growth and development are markedly sensitive to environmental factors. Indole-3-acetic acid (IAA) is the major growth hormone in plants, regulating plant growth, development, and response to adversity. Nevertheless, the specific regulatory functions of Aux/IAA genes in response to abiotic stresses in white clover remain largely unexplored. Results In this study, we identified 47 Aux/IAA genes in the white clover genome, which were categorized into five groups based on phylogenetic analysis. The TrIAAs promoter region co-existed with different cis-regulatory elements involved in developmental and hormonal regulation, and stress responses, which may be closely related to their diverse regulatory roles. Collinearity analysis showed that the amplification of the TrIAA gene family was mainly carried out by segmental duplication. White clover Aux/IAA genes showed different expression patterns in different tissues and under different stress treatments. In addition, we performed a yeast two-hybrid analysis to investigate the interaction between white clover Aux/IAA and ARF proteins. Heterologous expression indicated that TrIAA18 could enhance stress tolerance in both yeast and transgenic Arabidopsis thaliana. Conclusion These findings provide new scientific insights into the molecular mechanisms of growth hormone signaling in white clover and its functional characteristics in response to environmental stress.

Abstract The molecular fingerprint sensing technology based on metasurface has unique attraction in the biomedical field. However, in the terahertz (THz) band, existing metasurface designs based on multi-pixel or angle multiplexing usually require more analyte amount or possess a narrower tuning bandwidth. Here, we propose a novel single-pixel graphene metasurface. Based on the synchronous voltage tuning, this metasurface enables ultra-wideband ( $$\sim$$ ∼ 1.5 THz) fingerprint enhancement sensing of trace analytes, including chiral optical isomers, with a limit of detection (LoD) ≤ 0.64 μg/mm2. The enhancement of the fingerprint signal ( $$\sim$$ ∼ 17.4 dB) originates from the electromagnetically induced transparency (EIT) effect excited by the metasurface, and the ideal overlap between the light field constrained by single-layer graphene (SLG) and ultra-thin analyte. Meanwhile, due to the unique nonlinear enhancement mechanism in graphene tuning, the absorption envelope distortion is inevitable. To solve this problem, a universal fingerprint spectrum inversion model is developed for the first time, and the restoration of standard fingerprints reaches Rmax 2 ≥ 0.99. In addition, the asynchronous voltage tuning of the metasurface provides an opportunity for realizing the dynamic reconfiguration of EIT resonance and the slow light modulation in the broadband range. This work builds a bridge for ultra-wideband THz fingerprint sensing of trace analytes, and has potential applications in active spatial light modulators, slow light devices and dynamic imaging equipments.

Objective To investigate the treatment methods and efficacy of acute pulmonary embolism. Methods The diagnosis and treatment information of 8 patients with APE secondary to pelvic vein thrombosis admitted by the Changsha First Hospital from 2020 to 2021 were recorded and analyzed. All patients treated with temporary inferior vena cava filter combined with catheter contact thrombolysis. The prognosis was analyzed after the 3-month follow-up. Results After treatment, Arterial partial pressure of oxygen increased from （52.83±4.18） mmHg to （92.34±6.12） mmHg （t=33.221, P＜0.01）, and blood oxygen saturation increased from (80.83±5.34)% to (96.12±4.11)% （t=13.853, P＜0.01）. The shock index and Miller's score significantly decreased. All patients recovered and were discharged, with an average hospital stay of 17.5 days. The recovery rate of the temporary inferior vena cava filter was 100%, with an average recovery time of 3.38 weeks. After 3 months, pulmonary artery CTA showed a 100% patency rate of the pulmonary artery tunk. Conclusion The combination of temporary inferior vena cava filter and catheter contact thrombolysis is a safe and effective treatment for acute pulmonary embolism secondary to pelvic vein thrombosis.

Abstract Mental disorders are the leading contributors to the globally nonfatal burden of disease. This study was aimed to estimate the burden of mental disorders in Asian countries. Based on GBD 2019, the prevalence and disability-adjusted life of years (DALYs) rates with 95% uncertainty intervals (UI) were estimated in Asian countries. Predictions for the future burden of 8 selected countries, ranks of the burden of mental disorders and correlations with Sociodemographic Index (SDI) were also estimated. During the past 3 decades, while the number of DALYs of mental disorders increased from 43.9 million (95% UI: 32.5–57.2) to 69.0 million (95% UI: 51.0–89.7), the age-standardized rates of DALYs of mental disorders remained largely consistent from 1452.2 (95% UI: 1080.16–1888.53) per 100,000 population in 1990 to 1434.82 (95% UI: 1065.02–1867.27) per 100,000 population in 2019, ranked as the eighth most significant disease burden in Asia in 2019. Depressive disorders (37.2%) were the leading contributors to the age-standardized DALY rates of mental disorders in Asia, followed by anxiety disorders (21.5%). The age-standardized DALY rates in females were higher than their male counterparts, both peaked at 30-34 years. The age-standardized DALY rates were predicted to remain stable, with the number of DALYs presented an upward trend in the future. There was no significant correlation between the burden of mental disorders and SDI. All mental disorders ranked higher in 2019, compared in 1990. To reduce this burden, urgent measures for prevention, treatment, and rehabilitation for mental disorders need to be taken by Asian governments.

Asymmetric rolling is beneficial for grain refinement and properties improvement through mass production of metals. This study introduces a novel asymmetric rolling technology, known as dynamic offsets and shear force adjustment (DS) rolling. DS rolling not only achieves roll offset and differential speed/diameter, but maintains a constant offset angle in multiple passes. And rolling mechanics model, finite element model, and rolling experiment is established. The results indicate the advantages of DS rolling in reducing the vertical rolling force with increasing offset angles. Moreover, it is observed that the vertical rolling force initially decreases and subsequently increases as the roll-to-diameter ratio increases. DS rolling enhances both average strain and core strain compared to symmetrical rolling, consequently promoting uniformity in strain distribution and permeability into the core region. The shear stress is the primary factor contributing to the increase in equivalent strain during DS rolling. The adjustment of roller diameter ratio and offset angle allows for control over the shear stress level. DS rolling enhances mechanical properties and refines the grain structure. Notably, at an offset angle of 9°, DS rolling results in a substantial increase in microhardness on the upper surface, center, and lower surface of Cu by 3.31 %, 8.40 %, and 8.19 %, respectively, when compared to symmetrical rolling. Furthermore, DS rolling exhibits an enhanced tensile strength and elongation, yielding improvements of 5.12 % and 38.9 % compared to symmetrical rolling, respectively. Additionally, DS rolling leads to a reduction in grain size by 5.77 %, 17.3 %, and 21.7 % on the upper surface, center, and lower surface, respectively.

Abstract Centromere protein A (CENP‐A), a centromere‐specific histone H3 variant, is crucial for kinetochore positioning and chromosome segregation. However, its regulatory mechanism in human cells remains incompletely understood. A structure‐activity relationship (SAR) study of the cell‐cycle‐arresting indole terpenoid mimic JP18 leads to the discovery of two more potent analogs, (+)‐6‐Br‐JP18 and (+)‐6‐Cl‐JP18. Tubulin is identified as a potential cellular target of these halogenated analogs by using the drug affinity responsive target stability (DARTS) based method. X‐ray crystallography analysis reveals that both molecules bind to the colchicine‐binding site of β‐tubulin. Treatment of human cells with microtubule‐targeting agents (MTAs), including these two compounds, results in CENP‐A accumulation by destabilizing Cdh1, a co‐activator of the anaphase‐promoting complex/cyclosome (APC/C) E3 ubiquitin ligase. This study establishes a link between microtubule dynamics and CENP‐A accumulation using small‐molecule tools and highlights the role of Cdh1 in CENP‐A proteolysis.

Abstract is missing (Short communication)

In this paper, we introduce a novel two-degree-of-freedom piezoelectric stack hybrid energy harvester including a piezoelectric stack and a set of piezoelectric layers. By incorporating a mechanical stopper and bending leaf springs to achieve frequency up-conversion, we significantly enhance the voltage response of the system. We compare the output performance of prototypes with different spring stiffness. The experimental results show that, at a frequency of 7.8 Hz and an acceleration of 0.8 g, the piezoelectric layers on the lower beam of bending leaf springs generate a peak voltage of 18.92 V, and its instantaneous output power is 32 mW. Meanwhile, the piezoelectric stack produces a peak voltage of 28.56 V, with an instantaneous output power of 3.83 W. Moreover, an increase in the stiffness of the bending leaf spring leads to a decrease in voltage response and power output. This research can facilitate the development of hybrid piezoelectric self-powered applications.

An event schema provides a formal language for representing events and modeling knowledge about the world. Existing event schema induction methods often only applies text features to the cluster, restricting its cluster capabilities. This article presents a Graph-Based Event Schema Induction model to extract structural features from our constructed graph. Inspired by in-context learning, we propose a way to conceptualize clusters to generate event schemas. We evaluated the clustering experiment using the Adjusted Rand Index (ARI), normalized mutual information (NMI), accuracy (ACC), and BCubed-F1 metrics and generated event schemas based on overlap ratio and acceptable ratio. The experimental results show that our method has shown improvement in terms of clustering effectiveness, and the generated event schemas achieved highly acceptable ratio.

Backgrounds: In order to detect early gastric cancer (EGC), this research sought to assess the diagnostic utility of magnifying endoscopy (ME) as well as the significance of mucin phenotype and microvessel features. Methods: 402 individuals with an EGC diagnosis underwent endoscopic submucosal dissection (ESD) at the Department of ME between 2012 and 2020. After adjusting for image distortion, high-magnification endoscopic pictures were taken and examined to find microvessels in the area of interest. The microvessel density was measured as counts per square millimeter (counts/mm2) after segmentation, and the vascular bed's size was computed as a percentage of the area of interest. To identify certain properties of the microvessels, such as end-points, crossing points, branching sites, and connection points, further processing was done using skeletonized pixels. Results: According to the research, undifferentiated tumors often lacked the MS pattern and showed an oval and tubular microsurface (MS) pattern, but differentiated EGC tumors usually lacked the MS pattern and presented a corkscrew MV pattern. Submucosal invasion was shown to be more strongly associated with the destructive MS pattern in differentiated tumors as opposed to undifferentiated tumors. While lesions with a corkscrew MV pattern and an antrum or body MS pattern revealed greater MUC5AC expression, lesions with a loop MV pattern indicated higher MUC2 expression. Furthermore, CD10 expression was higher in lesions with a papillary pattern and an antrum or body MS pattern. Conclusion: These results imply that evaluating mucin phenotype and microvessel features in conjunction with magnifying endoscopy (ME) may be a useful diagnostic strategy for early gastric cancer (EGC) detection. Nevertheless, further investigation is required to confirm these findings and identify the best course of action for EGC diagnosis.

As a crucial exploration technique for unconventional reservoirs, hydraulic fracturing enables the formation of complex fracture networks, thereby facilitating the flow of oil and gas. The closure of natural fractures decreases stimulation performance. Microparticle proppants are used to fill natural fractures and effectively increase the stimulation area. The 100-mesh proppant conventionally used in field operations may be insufficiently small to effectively access natural fractures. In order to effectively overcome natural fractures closure, microparticle proppants (i.e., proppants with a diameter of 75 μm (200-mesh) or less) are required. The particle size threshold test of microparticle proppants placement is conducted to determine the size threshold of proppants flowing into natural fractures. The microparticle proppants placement experiment in multi-branch fractures is conducted to investigate the volume difference of proppants in different fractures. Numerical simulations are performed to model proppant transport within fractures of actual dimensions to facilitating the optimization of stimulation parameters. The main conclusions are as follows: (1) Effective inflow of microparticle proppants requires a size threshold of proppants. For the 200-mesh proppants, the size should be less than half of natural fractures width when microparticle proppants effectively flow into natural fractures. (2) Sand concentration affects the size threshold of microparticle proppants. The size threshold should appropriately increase to ensure the inflow of proppant. (3) Difference of multi-branch fracture width has a significant effect on volume of microparticle proppants inside fractures. When the width ratio of multi-branch fractures exceeds 2, this effect becomes obvious. (4) Particle size has an effect on proppant placement. 200-mesh proppants can obtain uniform distribution of proppants among natural fractures. 140-mesh proppants can obtain maximum proppant volume among natural fractures. Sand concentration significantly affects proppant placement performance. The optimal sand concentration is 60kg/m3. The pumping rate for a single cluster fracture should not be excessively low. The pumping rate should be larger than 0.5m3/min and the optimal pumping rate 2m3/min. In this paper, the particle size and concentration of particulate proppant are optimized and the geometric characteristics of fractures are considered. These conclusions provide important practical guidance and scientific basis for the optimization and application of hydraulic fracturing technology.

In the quest for large-scale photovoltaic (PV) panel extraction, substantial data volumes are essential, given the demand for sub-meter rooftop PV resolution. This requires the concept of Latent Photovoltaic Locations (LPL) to reduce the scope of the amount of subsequent processing. In order to minimize manual annotation, a pioneering weakly-supervised framework is proposed, which is capable of generating pixel-level annotations for segmentation based on image-level annotations and provides the two datasets required for the classification-then-segmentation strategy without more annotations. The strong noise-resistance of the Segment Anything Model (SAM) is discovered in the extremely difficult rough coarse pseudo-label refinement, which, after integrating a probability updating mechanism, achieves a seamless transition from scene classification to semantic segmentation. The resulting national LPL distribution map, rendered at a 2 m resolution, showcases a commendable 92 % accuracy and a F1-score of 91 %, and the advantages of the framework in terms of efficiency and accuracy have been verified through a large number of experiments. This process explores how to use fundamental large models to accelerate the remote sensing information extraction process, which is crucial in the current trajectory of deep learning in remote sensing. The relevant code is available at https://github.com/Github-YRQ/LPL.

Abstract Background The adaptive mechanisms of agricultural pests are the key to understanding the evolution of the pests and to developing new control strategies. However, there are few studies on the genetic basis of adaptations of agricultural pests. The turnip moth, Agrotis segetum (Lepidoptera: Noctuidae) is an important underground pest that affects a wide range of host plants and has a strong capacity to adapt to new environments. It is thus a good model for studying the adaptive evolution of pest species. Results We assembled a high-quality reference genome of A. segetum using PacBio reads. Then, we constructed a variation map of A. segetum by resequencing 98 individuals collected from six natural populations in China. The analysis of the population structure showed that all individuals were divided into four well-differentiated populations, corresponding to their geographical distribution. Selective sweep analysis and environmental association studies showed that candidate genes associated with local adaptation were functionally correlated with detoxification metabolism and glucose metabolism. Conclusions Our study of A. segetum has provided insights into the genetic mechanisms of local adaptation and evolution; it has also produced genetic resources for developing new pest management strategies.

In recent years, the movement analysis is commonly used to track the risk of injury and strengthen the efficiency of athlete performance. However, most of these devices are costly, found mainly in experimental settings, which analyze a few samples of each movement. In this paper, a new ambulatory movement analysis system with wearable sensors for the precise measurement of all athleteꞌs movements in an actual training scenario is introduced. Initially, an adaptive method categorizes a broad variety of training behaviors by the Differential Finite element Transformation method (DFET) along with a Random Forest Classification (DFET- RF) method. Secondly, the measurement of the absolute identities of the wearable sensor devices placed on the knee bone and pelvic bone is performed with a discrete gradient descent (DGD) algorithm, which calculates a range of motion-extension between the knee and hip angle. Finally, the edge computing is used to process data in real-time and reduce the latency of the system. The next version of wearable technology will know the person's identity, individually - not just physically and actively in a much more significant way; a wearable device that tells the world about the identity of the person and the connected devices. The knee flexion is greater at the terminal swing period (85%) and hip flexion (68%). The development of future device capabilities is based on verification. Once a wearable can validate the wearer's identity, several other things about their activities can be regulated. Such angles are automatically extracted for each movement during jogging at the acceleration of the sacrum effect. Besides, standard data has developed and is used to decide whether the movement methodology for a person varied from the standard data to classify potential instances due to injury. This is done by a gradient-shift recording technique for the joint-related angle details. For precise and automated assessment of athletic movements, effective activity measurement in various uncontrolled conditions for both injuries processing performance progress, the suggested system has been discussed in this paper.

Abstract Background Cementoblasts on the tooth-root surface are responsible for cementum formation (cementogenesis) and sensitive to Porphyromonas gingivalis stimulation. We have previously proved transcription factor CXXC-type zinc finger protein 5 (CXXC5) participates in cementogenesis. Here, we aimed to elucidate the mechanism in which CXXC5 regulates P. gingivalis-inhibited cementogenesis from the perspective of mitochondrial biogenesis. Methods In vivo, periapical lesions were induced in mouse mandibular first molars by pulp exposure, and P. gingivalis was applied into the root canals. In vitro, a cementoblast cell line (OCCM-30) was induced cementogenesis and submitted for RNA sequencing. These cells were co-cultured with P. gingivalis and examined for osteogenic ability and mitochondrial biogenesis. Cells with stable CXXC5 overexpression were constructed by lentivirus transduction, and PGC-1α (central inducer of mitochondrial biogenesis) was down-regulated by siRNA transfection. Results Periapical lesions were enlarged, and PGC-1α expression was reduced by P. gingivalis treatment. Upon apical inflammation, Cxxc5 expression decreased with Il-6 upregulation. RNA sequencing showed enhanced expression of osteogenic markers, Cxxc5, and mitochondrial biogenesis markers during cementogenesis. P. gingivalis suppressed osteogenic capacities, mitochondrial biogenesis markers, mitochondrial (mt)DNA copy number, and cellular ATP content of cementoblasts, whereas CXXC5 overexpression rescued these effects. PGC-1α knockdown dramatically impaired cementoblast differentiation, confirming the role of mitochondrial biogenesis on cementogenesis. Conclusions CXXC5 is a P. gingivalis-sensitive transcription factor that positively regulates cementogenesis by influencing PGC-1α-dependent mitochondrial biogenesis. Video Abstract

Purpose: To evaluate the myopia risk in school-aged children one year after lifting a pandemic-related lockdown and develop a tool to identify high-risk groups. Methods: In total, 38,079 children without myopia from 38 schools were included. The outcomes were myopia incidence and progression in 1 year after the COVID-19 lockdown was lifted, both obtained by the spherical equivalent refraction (SER). We separated the population into an exploratory (75%) and a validation sample (25%) to construct the risk score model. Results: In total, 9811 (29.57%) students became myopic, and the overall myopia progression was 0.22 ± 0.62 D. Even less myopia progression was noted in the pre-myopia group at baseline (All: P = 0.045, Boy: P = 0.005). The risk score model included seven predictors: gender, grade, SER at baseline, residence, parental myopia, eye discomfort symptoms, and online courses. The model had a score range of 0–46 and an optimal cutoff of 34. The area under the receiver operating curve of the model was 0.726 (0.719–0.732) for the exploratory sample and 0.731 (0.720–0.742) for the validation sample. Conclusions: The risk score can serve as a practical tool for classifying the risk of myopia in school-aged children.

Abstract The pink stem borer, Sesamia inferens (Walker), is a significant polyphagous pest historically restricted to regions south of N34° latitude. However, with changes in global climate and farming practices, the distribution of this moth has progressively exceeded its traditional limit of 34° N and encompassed most regions in North China. The genetic adaptations of S. inferens remain incompletely understood due to the lack of high-quality genome resources. Here, we sequenced the genome of S. inferens using PacBio and Hi-C technology, yielding a genome assembly of 865.04 Mb with contig N50 of 1.23 Mb. BUSCO analysis demonstrated this genome assembly has a high-level completeness of 96.1% gene coverage. In total, 459.72 Mb repeat sequences (53.14% of the assembled genome) and 20858 protein-coding genes were identified. We used the Hi-C technique to anchor 1135 contigs to 31 chromosomes, yielding a chromosome-level genome assembly with a scaffold N50 of 29.99 Mb. In conclusion, our high-quality genome assembly provided valuable resource that exploring the genetic characteristics of local adaptation and developing an efficient control strategy.

Abstract Small cell transformation was one mechanism by which EGFR-mutation NSCLC acquired resistance after tyrosine kinase inhibitors (TKIs) treatment. A few reports of small cell transformation occurred in other oncogene-driven lung cancers. We found the first case of transformation of a RET-rearranged lung adenocarcinoma to SCLC after selpercatinib, a novel highly selective RET TKIs. Whole-exome sequencing (WES) was used to explore alteration in gene expression in tumor tissue at initial diagnosis and after transformation into small cell carcinoma. We found that transformed into SCLC tumor tissue had inactivation of RB1 and TP53, with RET fusion was still present. In addition, the APOBEC family of cytidine deaminases appeared amplification. Although RET rearrangement still existed, using another RET TKIs was ineffective, and etoposide plus platinum might be an effective rescue treatment.

Abstract We investigate distributions of matter fields outside spherically symmetric ultra-compact objects with null circular orbits in the asymptotically flat background. Based on the dominant energy and the non-negative trace conditions, we prove the existence of effective radius of matter field hairs outside horizonless ultra-compact objects. We also analytically find a no long hair behavior, which states that the effective radius of matter field hairs cannot extend beyond the outermost null circular orbit of horizonless ultra-compact objects.

The interaction between an atmospheric pressure plasma jet (APPJ) and an aqueous solution has great application prospects in biomedicine and many other fields. Reactive species adjacent to a water surface is critical to the activation of APPJ-treated water, which is affected by both the water evaporation and the admixture of ambient air. In this paper, taking He APPJ as an example, a two-dimensional (2D) cylindrically symmetric fluid model is developed to obtain the spatial distributions of gas components before discharging, and a series of global models are developed for the discharge in the boundary gas layer adjacent to the water surface. The interfacial distributions of reactive species and their fluxes onto the water surface are quantified. It is found that the electron density is 1016–1017 m−3 and it shows an annular distribution in the boundary gas layer. The density distributions of most reactive species there reveal ring-like shapes as well. The dominant cation and anion in such a boundary layer are H3O+ and OH−, respectively. The most abundant metastable is O2(a1Δ), the most abundant reactive oxygen species are H2O2 and OH, and the most abundant reactive nitrogen species are NO and HNO2. The species of H2O2, OH, HO2, and HNO2 are reportedly to have significant biological effects, and in our simulation, their fluxes onto the water surface are remarkable, higher than 1017 m−2 s−1. In addition, the effects of radial gas velocity and water evaporation on the particle flux distributions are also revealed.

Excessive aluminum (Al) in acidic soils is a primary factor that hinders plant growth. The objective of the present study was to investigate the effect and physiological mechanism of exogenous silicon (Si) in alleviating aluminum toxicity. Under hydroponic conditions, 4 mM Al significantly impeded the growth of white clover; however, pretreatments with 1 mM Si mitigated this inhibition, as evidenced by notable changes in growth indicators and physiological parameters. Exogenous silicon notably increased both shoot and root length of white clover and significantly decreased electrolyte leakage (EL) and malondialdehyde (MDA) content compared to aluminum treatments. This positive effect was particularly evident in the roots. Further analysis involving hematoxylin staining, scanning electron microscopy (SEM), and examination of organic acids (OAs) demonstrated that silicon relieved the accumulation of bioactive aluminum and ameliorated damage to root tissues in aluminum-stressed plants. Additionally, energy-dispersive X-ray (EDX) analysis revealed that additional silicon was primarily distributed in the root epidermal and cortical layers, effectively reducing the transport of aluminum and maintaining the balance of exchangeable cations absorption. These findings suggest that gradual silicon deposition in root tissues effectively prevents the absorption of biologically active aluminum, thereby reducing the risk of mineral nutrient deficiencies induced by aluminum stress, promoting organic acids exudation, and compartmentalizing aluminum in the outer layer of root tissues. This mechanism helps white clover alleviate the damage caused by aluminum toxicity.

IntroductionChina has experienced unprecedented transformations unseen in a century and is gradually progressing toward an emerging superpower. The epidemiological trends of digestive diseases in the United States (the US) have significant prescient effects on China.MethodsWe extracted data on 18 digestive diseases from the Global Burden of Diseases 2019 Data Resource. Linear regression analysis conducted by the JoinPoint software assessed the average annual percentage change of the burden. We performed subgroup analyses based on sex and age group.ResultsIn 2019, there were 836.01 and 180.91 million new cases of digestive diseases in China and the US, causing 1558.01 and 339.54 thousand deaths. The age-standardized incidence rates of digestive diseases in China and the US were 58417.87/100,000 and 55018.65/100,000 respectively, resulting in age-standardized mortality rates of 81.52/100,000 and 60.88/100,000. The rates in China annually decreased by 2.149% for mortality and 2.611% for disability-adjusted life of year (DALY). The mortality and DALY rates of the US, respectively, had average annual percentage changes of −0.219 and −0.251. Enteric infections and cirrhosis and other chronic liver diseases accounted for the highest incidence and prevalence in both counties, respectively. The burden of multiple digestive diseases exhibited notable sex disparities. The middle-old persons had higher age-standardized prevalence rates.ConclusionChina bore a greater burden of digestive diseases, and the evolving patterns were more noticeable. Targeted interventions and urgent measures should be taken in both countries to address the specific burden of digestive diseases based on their different epidemic degree.

Intracranial aneurysm is a high-risk disease, with imaging playing a crucial role in their diagnosis and treatment. The rapid advancement of artificial intelligence in imaging technology holds promise for the development of AI-based radiomics predictive models. These models could potentially enable the automatic detection and diagnosis of intracranial aneurysms, assess their status, and predict outcomes, thereby assisting in the creation of personalized treatment plans. In addition, these techniques could improve diagnostic efficiency for physicians and patient prognoses. This article aims to review the progress of artificial intelligence radiomics in the study of intracranial aneurysms, addressing the challenges faced and future prospects, in hopes of introducing new ideas for the precise diagnosis and treatment of intracranial aneurysms.

Predicting the production amounts has great significance for exploitation of oil and gas resources. The flow–geomechanical coupling effect plays an important role in predicting production. Shale rocks and the stress-dependent permeability model are critical for representing this coupling effect. The pore network of shale rock is not abundant like that of coal rock, and the matrix blocks of shale rock are not completely separated by the pore network. There is stress concentration around the pores when shale rock is deformed. Based on previous studies, the stress-dependent permeability model considering the impact of stress concentration is used in this study to build a numerical simulation model for flow–geomechanical coupling in a shale gas reservoir and validation using field data. Sensitivity studies are conducted to discuss the difference in production prediction between the new and common models. The main conclusions of this study are as follows: 1) The new model can fit both the field and experimental data well; the average error in daily production rate between the numerical solution and field data is 8%, which indicates that the new model can be used to predict shale gas production. 2) Under the geomechanical condition of a real reservoir, the difference in predicted production between models with and without stress concentration can be large and increase with the ratio of a to b. If this ratio is less than 50, the impact of stress concentration is not significant. Otherwise, the impact of stress concentration on production increases sharply and can exceed 20%. 3) The adsorption-induced strain enhances the impact of stress concentration on production. When the Langmuir pressure exceeds 1 MPa and Langmuir strain exceeds 0.01, the impact magnitude of stress concentration can exceed 10%.

Lewis Fry Richardson proposed his famous picture of turbulent flows in 1922, where the kinetic energy is transferred from large-scale to small-scale structures until the viscosity converts it into heat. This cascade idea, also known as the forward energy cascade, is now widely accepted and is treated as the cornerstone of not only turbulent modeling, but also global circulation models of the ocean and atmosphere. In this work, the Filter-Space-Technique is applied to the oceanic flow field provided by the CMEMS reanalysis model to quantify the scale-to-scale energy flux. A rich dynamical pattern associated with different scales is observed. More precisely, either positive or negative fluxes are observed, indicating the direction of the energy cascade, where the energy is transferred from large-scale structures to small-scale ones or vice versa. High-intensity energy exchange is found mainly in the Western Boundary Current Systems and Equatorial Counter Currents. For the latter case, a wavelike pattern is observed on the westward travel. Moreover, strong seasonal variation is evident for some scales and regions. These results confirm the existence of forward and inverse cascades and rich regional dynamics.

Abstract The yellow peach moth, Conogethes punctiferalis, is a highly polyphagous pest widespread in eastern and southern Asia. It demonstrates a unique ability to adapt to rotten host fruits and displays resistance to pathogenic microorganisms, including fungi. However, the lack of available genomic resources presents a challenge in comprehensively understanding the evolution of its innate immune genes. Here, we report a high-quality chromosome-level reference genome for C. punctiferalis utilizing PacBio HiFi sequencing and Hi-C technology. The genome assembly was 494 Mb in length with a contig N50 of 3.25 Mb. We successfully anchored 1,226 contigs to 31 pseudochromosomes. Our BUSCO analysis further demonstrated a gene coverage completeness of 96.3% in the genome assembly. Approximately 43% repeat sequences and 21,663 protein-coding genes were identified. In addition, we resequenced 110 C. punctiferalis individuals from east China, achieving an average coverage of 18.4 × and identifying 5.8 million high-quality SNPs. This work provides a crucial resource for understanding the evolutionary mechanism of C. punctiferalis’ innate immune system and will help in developing new antibacterial drugs.

Advanced high strength steels (AHSS) are typically loaded in a multiaxial stress state during forming process and service. However, the deformation mechanism under multiaxial loading is not clarified, which limits the optimization of sheet metal forming. In particular, due to instability, biaxial compression loading of single thin plate has not been reported, which results in unclear evolution of the yield surfaces in the second, third and fourth quadrants of σ11-σ22 space and corresponding deformation mechanisms. Therefore, the deformation mechanism of AHSS thin plates under biaxial loading was systematically investigated in the complete σ11-σ22 space using a specially designed cruciform specimen and buckling prevention fixture in the current work. The mechanical properties of dual-phase (DP780) steel under different loading paths were studied by uniaxial tension, uniaxial compression, and biaxial loading tests. There is an obvious yield strength difference between the first quadrant and the third quadrant in the σ11-σ22 space. In the second and fourth quadrants of σ11-σ22 space, the compression part makes a greater effect on the yield behavior of the material than the tension part. More specifically, dislocation slip is activated earlier at the boundary under compression loading, resulting in earlier yielding of the material. Based on the analysis of the Taylor factor, the activation of slip systems of DP780 steel before and after deformation is clarified. In addition, a detailed analysis of the microstructure and texture evolution in DP780 steel after deformation is conducted, and a correlation between texture evolution and loading paths is established. It is found that the compression part under biaxial loading results in more grains with low Taylor factor and promotes the transformation of the initial texture to copper or rotated copper texture in DP780 steel.

Introduction: The simultaneous improvement of fiber quality and yield for cotton is strongly limited by the narrow genetic backgrounds of Gossypium hirsutum (Gh) and the negative genetic correlations among traits. An effective way to overcome the bottlenecks is to introgress the favorable alleles of Gossypium barbadense (Gb) for fiber quality into Gh with high yield. Objectives: This study was to identify superior loci for the improvement of fiber quality and yield. Methods: Two sets of chromosome segment substitution lines (CSSLs) were generated by crossing Hai1 (Gb, donor-parent) with cultivar CCRI36 (Gh) and CCRI45 (Gh) as genetic backgrounds, and cultivated in 6 and 8 environments, respectively. The kmer genotyping strategy was improved and applied to the population genetic analysis of 743 genomic sequencing data. A progeny segregating population was constructed to validate genetic effects of the candidate loci. Results: A total of 68,912 and 83,352 genome-wide introgressed kmers were identified in the CCRI36 and CCRI45 populations, respectively. Over 90 % introgressions were homologous exchanges and about 21 % were reverse insertions. In total, 291 major introgressed segments were identified with stable genetic effects, of which 66(22.98 %), 64(21.99 %), 35(12.03 %), 31(10.65 %) and 18(6.19 %) were beneficial for the improvement of fiber length (FL), strength (FS), micronaire, lint-percentage (LP) and boll-weight, respectively. Thirty-nine introgression segments were detected with stable favorable additive effects for simultaneous improvement of 2 or more traits in Gh genetic background, including 6 could increase FL/FS and LP. The pyramiding effects of 3 pleiotropic segments (A07:C45Clu-081, D06:C45Clu-218, D02:C45Clu-193) were further validated in the segregating population. Conclusion: The combining of genome-wide introgressions and kmer genotyping strategy showed significant advantages in exploring genetic resources. Through the genome-wide comprehensive mining, a total of 11 clusters (segments) were discovered for the stable simultaneous improvement of FL/FS and LP, which should be paid more attention in the future.

Abstract Background Integrins are closely related to mechanical conduction and play a crucial role in the osteogenesis of human mesenchymal stem cells. Here we wondered whether tensile stress could influence cell differentiation through integrin αVβ3. Methods We inhibited the function of integrin αVβ3 of human mesenchymal stem cells by treating with c(RGDyk). Using cytochalasin D and verteporfin to inhibit polymerization of microfilament and function of nuclear Yes-associated protein (YAP), respectively. For each application, mesenchymal stem cells were loaded by cyclic tensile stress of 10% at 0.5 Hz for 2 h daily. Mesenchymal stem cells were harvested on day 7 post-treatment. Western blotting and quantitative RT-PCR were used to detect the expression of alkaline phosphatase (ALP), RUNX2, β-actin, integrin αVβ3, talin-1, vinculin, FAK, and nuclear YAP. Immunofluorescence staining detected vinculin, actin filaments, and YAP nuclear localization. Results Cyclic tensile stress could increase the expression of ALP and RUNX2. Inhibition of integrin αVβ3 activation led to rearrangement of actin filaments and downregulated the expression of ALP, RUNX2 and promoted YAP nuclear localization. When microfilament polymerization was inhibited, ALP, RUNX2, and nuclear YAP nuclear localization decreased. Inhibition of YAP nuclear localization could reduce the expression of ALP and RUNX2. Conclusions Cyclic tensile stress promotes early osteogenesis of human mesenchymal stem cells via the integrin αVβ3-actin filaments axis. YAP nuclear localization participates in this process of human mesenchymal stem cells. Video Abstract

Abstract The rapid evolution of resistance in agricultural pest poses a serious threat to global food security. However, the mechanisms of resistance through metabolic regulation are largely unknown. Here, we found that a GST gene cluster was strongly selected in North China (NTC) population, and it was significantly genetically-linked to lambda-cyhalothrin resistance. Knockout of the GST cluster using CRISPR/Cas9 significantly increased the sensitivity of the knockout strain to lambda-cyhalothrin. Haplotype analysis revealed no non-synonymous mutations or structural variations in the GST cluster, whereas GST_119 and GST_121 were significantly overexpressed in the NTC population. Silencing of GST_119 or co-silencing of GST_119 and GST_121 with RNAi significantly increased larval sensitivity to lambda-cyhalothrin. We also identified additional GATAe transcription factor binding sites in the promoter of NTC_GST_119. Transient expression of GATAe in Hi5 cells activated NTC_GST_119 and Xinjiang (XJ)_GST_119 transcription, but the transcriptional activity of NTC_GST_119 was significantly higher than that of XJ_GST_119. These results demonstrate that variations in the regulatory region result in complex expression changes in the GST cluster, which enhances lambda-cyhalothrin resistance in field-populations. This study deepens our knowledge of the evolutionary mechanism of pest adaptation under environmental stress and provides potential targets for monitoring pest resistance and integrated management.

Abstract Bridge steel has been widely used in recent years for its excellent performance. Understanding the high-temperature Dynamic Recrystallization (DRX) behavior of high-performance bridge steel plays an important role in guiding the thermomechanical processing process. In the present study, the hot deformation behavior of Q370qE bridge steel was investigated by hot compression tests conducted on a Gleeble 3800-GTC thermal-mechanical physical simulation system at temperatures ranging from 900 ℃ to 1100 ℃ and strain rates ranging from 0.01 s−1 to 10 s−1. The obtained results were used to plot the true stress-strain and work-hardening rate curves of the experimental steel, with the latter curves used to determine the critical strains for the initiation of DRX. The Zener-Hollomon equation was subsequently applied to establish the correspondence between temperature and strain rate during the high-temperature plastic deformation of bridge steel. In terms of the DRX volume fraction solution, a new method for establishing DRX volume fraction was proposed based on two theoretical models. The good weathering and corrosion resistance of bridge steel lead to difficulties in microstructure etching. To solve this, the MTEX technology was used to further develop EBSD data to characterize the original microstructure of Q370qE bridge steel. This paper lays the theoretical foundation for studying the DRX behavior of Q370qE bridge steel.

The increasing integration of wind power in power systems necessitates the probabilistic assessment of various uncertain factors. In operational planning, modeling short-term scale uncertainties, i.e., wind power forecast errors, plays an important role. In this paper, according to the different forecast values, the corresponding probability distributions of wind power forecast errors are developed using a data-driven manner. Then, the polynomial chaos expansion surrogate is developed to facilitate the probabilistic load margin assessment considering wind power forecast errors. The effectiveness of the forecast error model is verified using the historical data of realistic wind power plants. The results show that the probability distributions of forecast errors vary with the level of forecast values. Moreover, the performance of the polynomial chaos expansion surrogate in estimating probabilistic load margin is validated in the IEEE 30-bus system. The results demonstrate that the versatile forecast error distributions significantly impact the characteristics of load margin. Moreover, the polynomial chaos expansion surrogate can accelerate the load margin assessment compared to the Monter Carlo simulation while retaining the same accuracy.

Flexible rolling is important for increasing rolling production capacity. Since the wear rolls withdrawn and new rolls launched into the rolling process causing thermal deformation parameters variation, such as deformation temperature, strain rate, and strain. This paper studies the coupling behavior of static recrystallization (SRX), metadynamic recrystallization (MDRX), and thermal deformation parameters based on the double-pass thermal simulation experiments, analyzes the flow stress curves and reveals the variation law of recrystallization with thermal deformation parameters. The result shows that the second-pass flow stress of SRX is significantly dependent on the inter-pass time, deformation temperature and strain rate, Compared to MDRX, SRX requires time to nucleus of conception and is more influenced by initial strain. Considering the recovery effect and the multi-pass static softening solution algorithm of materials, the kinetic models of SRX and MDRX are established, and the predicted values of the models are in good agreement with the experimental values. The EBSD microstructure characterization technique is used to characterize the morphology of SRX and MDRX. The result shows that increasing inter-pass time, deformation temperature and strain rate can promote the SRX and MDRX process and improve static softening effect. Under the condition of constant deformation temperature and strain rate, increasing the initial strain can increase the SRX volume fraction. However, deformation temperature and strain rate have a more significant effect on the static softening than the initial strain. This paper provides a theoretical basis for designing and optimizing recrystallization behavior of flexible rolling gaps.

Probabilistic power flow is one of the fundamental tools for assessing the impacts of uncertainties on the operating states of power systems. However, this analysis requires sufficient historical data to obtain precise probability distributions of input variables, which may not be met in practical engineering problems. In this paper, input variables with insufficient data are represented by parametric probability boxes (p-boxes), i.e., probability distributions with imprecise parameters. In order to facilitate the uncertain power flow calculation with p-boxes, a polynomial chaos expansion-based method is developed. Moreover, the interval-valued Borgonovo index is proposed for global sensitivity analysis and to identify the input variables that have critical impacts on systems. The simulations in IEEE 14-bus and 118-bus systems verify the accuracy and efficiency of the proposed method by comparing it with the conventional double-loop sampling method.

Spermidine is well known to accumulate in plants exposed to drought, but the regulatory network associated with its biosynthesis and accumulation and the underlying molecular mechanisms remain unclear. Here, we demonstrated that the Trifolium repens TrMYB33 relayed the ABA signal to modulate drought-induced spermidine production by directly regulating the expression of TrSAMS1, which encodes an S-adenosylmethionine synthase. This gene was identified by transcriptome and expression analysis in T. repens. TrSAMS1 overexpression and its pTRV-VIGS-mediated silencing demonstrated that TrSAMS1 is a positive regulator of spermidine synthesis and drought tolerance. TrMYB33 was identified as an interacting candidate through yeast one-hybrid library screening with the TrSAMS1 promoter region as the bait. TrMYB33 was confirmed to bind directly to the predicted TAACCACTAACCA (the TAACCA MYB binding site is repeated twice in tandem) within the TrSAMS1 promoter and to act as a transcriptional activator. Additionally, TrMYB33 contributed to drought tolerance by regulating TrSAMS1 expression and modulating spermidine synthesis. Additionally, we found that spermidine accumulation under drought stress depended on ABA and that TrMYB33 coordinated ABA-mediated upregulation of TrSAMS1 and spermidine accumulation. This study elucidated the role of a T. repens MYB33 homolog in modulating spermidine biosynthesis. The further exploitation and functional characterization of the TrMYB33–TrSAMS1 regulatory module can enhance our understanding of the molecular mechanisms responsible for spermidine accumulation during drought stress.

Creeping bentgrass (Agrostis stolonifera) is an excellent cool-season turfgrass that is widely used in urban gardening, landscaping, and golf turf. Triennial field experiments from 2017 to 2019 were conducted to investigate effects of the foliar application of chitosan (CTS), γ-aminobutyric acid (GABA), or sodium chloride (NaCl) on mitigating summer bentgrass decline (SBD) and exploring the CTS, GABA, or NaCl regulatory mechanism of tolerance to summer heat stress associated with changes in chlorophyll (Chl) loss and photosynthetic capacity, osmotic adjustment (OA), oxidative damage, and cell membrane stability. The findings demonstrated that persistent ambient high temperatures above 30 °C during the summer months of 2017, 2018, and 2019 significantly reduced the turf quality (TQ), Chl content, photochemical efficiency of PSII (Fv/Fm and PIABS), leaf relative water content, and osmotic potential (OP) but significantly increased electrolyte leakage (EL) and the accumulations of free proline, water-soluble carbohydrate (WSC), hydrogen peroxide (H2O2), and malondialdehyde (MDA). The foliar application of CTS, GABA, or NaCl could significantly alleviate SBD, as reflected by improved TQ and delayed Chl loss during hot summer months. Heat-induced declines in Fv/Fm, PIABS, the net photosynthetic rate (Pn), the transpiration rate (Tr), and water use efficiency (WUE) could be significantly mitigated by the exogenous application of CTS, GABA, or NaCl. In addition, the foliar application of CTS, GABA, or NaCl also significantly improved the accumulations of free proline and WSC but reduced the EL, OP, and H2O2 content and the MDA content in leaves of creeping bentgrass in favor of water and redox homeostasis in summer. Based on the comprehensive evaluation of the subordinate function value analysis (SFVA), the CTS had the best effect on the mitigation of SBD, followed by GABA and NaCl in 2017, 2018, and 2019. The current study indicates that the foliar application of an appropriate dose of GABA, CTS, or NaCl provides a cost-effective strategy for mitigating SBD.

Objectives This study aimed to assess the internal law and time trend of hospitalisation for oesophagogastric variceal bleeding (EGVB) in cirrhosis and develop an effective model to predict the trend of hospitalisation time.Design We used a time series covering 72 months to analyse the hospitalisation for EGVB in cirrhosis. The number of inpatients in the first 60 months was used as the training set to establish the autoregressive integrated moving average (ARIMA) model, and the number over the next 12 months was used as the test set to predict and observe their fitting effect.Setting and data Case data of patients with EGVB between January 2014 and December 2019 were collected from the Affiliated Hospital of Southwest Medical University.Outcome measures The number of monthly hospitalised patients with EGVB in our hospital.Results A total of 877 patients were included in the analysis. The proportion of EGVB in patients with cirrhosis was 73% among men and 27% among women. The peak age at hospitalisation was 40–60 years. The incidence of EGVB varied seasonally with two peaks from January to February and October to November, while the lowest number was observed between April and August. Time-series analysis showed that the number of inpatients with EGVB in our hospital increased annually. The sequence after the first-order difference was a stationary series (augmented Dickey-Fuller test p=0.02). ARIMA (0,1,0) (0,1,1)12 with a minimum Akaike Information Criterion value of 260.18 could fit the time trend of EGVB inpatients and had a good short-term prediction effect. The root mean square error and mean absolute error were 2.4347 and 1.9017, respectively.Conclusions The number of hospitalised patients with EGVB at our hospital is increasing annually, with seasonal changes. The ARIMA model has a good prediction effect on the number of hospitalised patients with EGVB in cirrhosis.

As humans, we can naturally break down a task into individual steps in our daily lives and we are able to provide feedback or dynamically adjust the plan when encountering obstacles. Similarly, our aim is to facilitate agents in comprehending and carrying out natural language instructions in a more efficient and cost-effective manner. For example, in Vision–Language Navigation (VLN) tasks, the agent needs to understand instructions such as “go to the table by the fridge”. This understanding allows the agent to navigate to the table and infer that the destination is likely to be in the kitchen. The traditional VLN approach mainly involves training models using a large number of labeled datasets for task planning in unseen environments. However, manual labeling incurs a high cost for this approach. Considering that large language models (LLMs) already possess extensive commonsense knowledge during pre-training, some researchers have started using LLMs as decision modules in embodied tasks, although this approach shows the LLMs’ reasoning ability to plan a logical sequence of subtasks based on global information. However, executing subtasks often encounters issues, such as obstacles that hinder progress and alterations in the state of the target object. Even one mistake can cause the subsequent tasks to fail, which makes it challenging to complete the instructions through a single plan. Therefore, we propose a new approach—C (Correction) and P (Planning) with M (Memory) I (Integration)—that centered on an LLM for embodied tasks. In more detail, the auxiliary modules of the CPMI facilitate dynamic planning by the LLM-centric planner. These modules provide the agent with memory and generalized experience mechanisms to fully utilize the LLM capabilities, allowing it to improve its performance during execution. Finally, the experimental results on public datasets demonstrate that we achieve the best performance in the few-shot scenario, improving the efficiency of the successive task while increasing the success rate.

Monocular 3D object detection plays a pivotal role in autonomous driving, presenting a formidable challenge by requiring the precise localization of 3D objects within a single image, devoid of depth information. Most existing methods in this domain fall short of harnessing the limited information available in monocular 3D detection tasks. They typically provide only a single detection outcome, omitting essential uncertainty analysis and result post-processing during model inference, thus limiting overall model performance. In this paper, we propose a comprehensive framework that maximizes information extraction from monocular images while encompassing diverse depth estimation and incorporating uncertainty analysis. Specifically, we mine additional information intrinsic to the monocular 3D detection task to augment supervision, thereby addressing the information scarcity challenge. Moreover, our framework handles depth estimation by recovering multiple sets of depth values from calculated visual heights. The final depth estimate and 3D confidence are determined through an uncertainty fusion process, effectively reducing inference errors. Furthermore, to address task weight allocation in multi-task training, we present a versatile training strategy tailored to monocular 3D detection. This approach leverages measurement indicators to monitor task progress, adaptively adjusting loss weights for different tasks. Experimental results on the KITTI and Waymo dataset confirm the effectiveness of our approach. The proposed method consistently provides enhanced performance across various difficulty levels compared to the original framework while maintaining real-time efficiency.

The fusion of millimeter-wave radar and camera modalities is crucial for improving the accuracy and completeness of 3-dimensional (3D) object detection. Most existing methods extract features from each modality separately and conduct fusion with specifically designed modules, potentially resulting in information loss during modality transformation. To address this issue, we propose a novel framework for 3D object detection that iteratively updates radar and camera features through an interaction module. This module serves a dual purpose by facilitating the fusion of multi-modal data while preserving the original features. Specifically, radar and image features are sampled and aggregated with a set of sparse 3D object queries, while retaining the integrity of the original radar features to prevent information loss. Additionally, an innovative radar augmentation technique named Radar Gaussian Expansion is proposed. This module allocates radar measurements within each voxel to neighboring ones as a Gaussian distribution, reducing association errors during projection and enhancing detection accuracy. Our proposed framework offers a comprehensive solution to the fusion of radar and camera data, ultimately leading to heightened accuracy and completeness in 3D object detection processes. On the nuScenes test benchmark, our camera–radar fusion method achieves state-of-the-art 3D object detection results with a 41.6% mean average precision and 52.5% nuScenes detection score.

Generalizing policies learned by agents in known environments to unseen domains is an essential challenge in advancing the development of reinforcement learning. Lately, language-conditioned policies have underscored the pivotal role of linguistic information in the context of cross-environments. Integrating both environmental and textual information into the observation space enables agents to accomplish similar tasks across different scenarios. However, for entities with varying forms of motion but the same name present in observations (e.g., immovable mage and fleeing mage), existing methods are unable to learn the motion information the entities possess well. They face the problem of ambiguity caused by motion. In order to tackle this challenge, we propose the entity mapper with multi-modal attention based on behavior prediction (EMMA-BBP) framework, comprising modules for predicting motion behavior and text matching. The behavioral prediction module is used to determine the motion information of the entities present in the environment to eliminate the semantic ambiguity of the motion information. The role of the text-matching module is to match the text given in the environment with the information about the entity’s behavior under observation, thus eliminating false textual information. EMMA-BBP has been tested in the demanding environment of MESSENGER, doubling the generalization ability of EMMA.

ObjectiveThe objective of this study is to develop a model to predicts the postoperative Hunt-Hess grade in patients with intracranial aneurysms by integrating radiomics and deep learning technologies, using preoperative CTA imaging data. Thereby assisting clinical decision-making and improving the assessment and prognosis of postoperative neurological function.MethodsThis retrospective study encompassed 101 patients who underwent aneurysm embolization surgery. 851 radiomic features were extracted from CTA images. 512 deep learning features are extracted from last layer of ResNet50 deep convolutional neural network model. The feature screening process pipeline encompassed intraclass correlation coefficient analysis, principal component analysis, U test, spearman correlation analysis, minimum redundancy maximum relevance algorithm and Lasso regression, to identify features most correlated with postoperative Hunt-Hess grading. In the model construction phase, three distinct models were constructed: radiomics feature-based model (RSM), deep learning feature-based model (DLM), and deep learning-radiomics feature fusion model (DLRSCM). The study also calculated the radiomics score and combined it with clinical data to construct a Nomogram for predictive modeling. DLM, RSM and DLRSCM model was constructed by 9 base algorithms and 1 ensemble learning algorithm – Stacking ensemble model. Model performance was evaluated based on the area under the Receiver Operating Characteristic (ROC) curve (AUC), Matthews Correlation Coefficient (MCC), calibration curves, and decision curves analysis.Results5 significant radiomic feature and 4 significant deep learning features were obtained through the feature selection process. These features were utilized for model construction. Bootstrap resampling method was used for internal validation of the models. In terms of model evaluation, the DLM model, the stacking ensemble algorithm results achieved an AUC of 0.959 and MCC of 0.815. In the RSM model, the stacking ensemble model AUC was 0.935 and MCC was 0.793. The stacking ensemble model in DLRSCM outperformed others, with an AUC of 0.968 and MCC of 0.820. Results indicated that the ANN performed optimally among all base models, while the stacked ensemble learning model exhibited the highest predictive performance.ConclusionThis study demonstrates that the combination of radiomics and deep learning is an effective approach to predict the postoperative Hunt-Hess grade in patients with intracranial aneurysms. This holds significant value in the early identification of postoperative neurological complications and in enhancing clinical decision-making.

ObjectivesThe study aims to analyze factors that affect the postoperative health-related quality of life (HRQOL) of degenerative lumbar scoliosis (DLS) patients and explore the appropriate pelvic incidence minus lumbar lordosis (PI-LL) value for Chinese DLS patients.MethodsDLS patients who met the inclusion and exclusion criteria were included in this study. General information, spino-pelvic parameters, and HRQOL were collected. Correlation analysis was used to explore the spino-pelvic parameters that affect the postoperative HRQOL. Thresholds of each parameter were obtained using the receiver operating characteristic (ROC) curve. Regardless of the effect of age, DLS patients were classified into three groups according to the SRS-Schwab classification: group 0 means PI-LL 20°. Postoperative HRQOL was analyzed using variance methods. The ROC curve was used to measure the appropriate PI-LL threshold. When considering the effect of age, the patients with Oswestry Disability Index (ODI) 0.8, postoperative sagittal vertical axis (SVA) ≤ 5 cm, postoperative T1 pelvic angle (TPA) ≤ 16° and postoperative global tilt (GT) ≤ 22°, respectively. Regardless of the effect of age, there was a statistical difference in postoperative HRQOL between group 0 and group ++. The PI-LL threshold derived from the ROC curve was 14.4°. Compared with the PI-LL > 14° group, the PI-LL ≤ 14° group achieved a lower postoperative ODI score and a higher postoperative SRS-22 score. Considering the influence of age, the equation for ideal PI-LL was PI-LL = 0.52age + 0.38PI-39.4 (R = 0.509, p = 0.001).ConclusionsPI-LL was an important parameter that affects the postoperative HRQOL of DLS patients. Sufficient LL should be restored during the operation (LL ≥ PI-14°). The appropriate PI-LL value was affected by age. Smaller LL needed to be restored as the age increased.

Electrochemical micromachining is an emerging technology in the machining field. This method offers several advantages such as exceptional surface quality, minimal cathode depletion, and a high elimination rate. Often, an ultrashort pulse power supply is employed in electrochemical micromachining to address over-machining in non-processing areas. While reducing the pulse duration can enhance processing accuracy, its high cost and impracticality for regular production limit its development. This paper presents the use of a Two-tone sinusoidal signal as an alternative to ultrashort pulse in electrochemical micromachining. We investigated the mechanism behind the reduced machining gap with this signal. By drilling micro-holes in the nickel sheet to optimize parameters such as voltage, fundamental frequency, and harmonic order. Using the Taguchi optimization method, we studied the impact of these control variables on the micromachining process during micro-hole drilling. The study also focused on fabricating micro-structures using the best processing parameters. Our results showed that using the optimized parameters greatly enhanced processing accuracy. Moreover, we found that high machining accuracy could be achieved when working on hard-to-cut super alloy plates.