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Abstract The wearable exoskeleton system is a typical strongly coupled human–robotic system. Human–robotic is the environment for each other. The two support each other and compete with each other. Achieving high human–robotic compatibility is the most critical technology for wearable systems. Full structural compatibility can improve the intrinsic safety of the exoskeleton, and precise intention understanding and motion control can improve the comfort of the exoskeleton. This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closed-loop four-link knee joint. Secondly, an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed. The inner loop of the controller adopts the PID control algorithm, and the outer loop adopts the adaptive admittance control algorithm based on human–robot interaction force (HRI). The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human–robot system, thereby improving control compliance and the wearing comfort of the exoskeleton system. Finally, we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments. Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human–robotic joint motion tracking, effectively reducing human–machine interaction forces and improving the comfort and safety of the wearer. This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI, which provides a new method for the design and control of exoskeletons with high compatibility.

Abstract Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels. At the gene level, the maximal expression of hazardous genes (expression negatively associated with survival) but the minimal expression of protective genes (expression positively associated with survival) across different regions within a tumor were more prognostic than the average expression. Following that, we examined whether multiregional expression profiling can improve the performance of prognostic signatures. We investigated 11 gene signatures collected from previous publications and one signature developed in this study. For all of them, the prognostic prediction accuracy can be significantly improved by converting the regional expression of signature genes into sample-specific expression with a simple function—taking the maximal expression of hazardous genes and the minimal expression of protective genes. In the tumor microenvironment, we found a similar rule also seems applicable to immune ITH. We calculated the infiltration levels of major immune cell types in each region of a sample based on expression deconvolution. Prognostic analysis indicated that the region with the lowest infiltration level of protective or highest infiltration level of hazardous immune cells determined the prognosis of NSCLC patients. Our study highlighted the impact of RNA-ITH on the prognostication of NSCLC, which should be taken into consideration to optimize the design and application of expression-based prognostic biomarkers and models. Multiregional assays have the great potential to significantly improve their applications to prognostic stratification.

This study mainly explored the effects of teacher feedback, peer feedback and automated feedback on the use of metacognitive strategies in EFL writing. Ninety-seven participants were recruited and divided into three groups, who received two months of feedback from teachers, peers and an automatic writing evaluation system, respectively, and then completed English writing tasks. Metacognitive strategies in this study entail planning strategies (including language knowledge accumulation strategies and pre-planning strategies), monitoring strategies (including selective attention strategies and self-monitoring strategies), and self-evaluation strategies. By conducting repeated-measures ANOVA on three groups of participants' use of metacognitive strategies before and after receiving different feedbacks, it was found that there were statistically significant differences in the effects of teacher feedback, peer feedback, and automated feedback on the use of selective attention strategies, whereas there were no statistically significant differences in the impact of those aforementioned types of feedback on other metacognitive strategies. It was also found that automated feedback had a hindrance effect on the use of monitoring strategies, whereas teacher feedback and peer feedback had a promotive effect on the use of all metacognitive strategies.

Objective To evaluate the effectiveness of multimodal prehabilitation among patients with esophageal neoplasm through meta-analysis. Methods Randomized controlled trials （RCTs） reporting the effectiveness of multimodal prehabilitation in patients with esophageal neoplasm were searched from PubMed， Embase， Cochrane Library， Web of Science， CNKI， Wanfang， Chongqing VIP and CBM databases from the inception to October 1， 2023. Meta-analysis was performed by RevMan 5.4 software after quality evaluation. Results Ten RCTs consisting of 930 patients were included in this meta-analysis. The meta-analysis results showed that compared with conventional nursing， multimodal prehabilitation could lower the incidence of postoperative complications （relative risk （RR） =0.62， 95%CI 0.47-0.82）， and shorten the length of hospital stay （mean difference （MD） =-6.15 d， 95%CI -7.87--4.43 d），reduce hospital costs （MD=CNY-17 800， 95%CI -27 600--8 100）， prolong 6-minute walking distance （MD=93.35 m， 95%CI 36.19-150.51 m） and increase serum albumin levels （MD=6.18 g/L， 95%CI 4.08-8.28 g/L） and IgG levels （standardized mean difference （SMD）=1.21， 95%CI 1.01-1.42）， respectively. Conclusions Multimodal prehabilitation can accelerate postoperative recovery， decrease the incidence of postoperative complications， improve partial exercise， nutritional and immunological indexes， shorten the length of hospital stay and reduce hospitalization costs.

The vigorous development of wind power generation technology is the core path for the country to promote the low-carbon energy transformation and realize the "dual-carbon" (carbon peaking and carbon neutrality) goals. With the gradual saturation of the development of onshore and offshore wind power resources, wind power development from the near-shore to the distant deep sea is the inevitable trend of the future development of the wind power industry. The research and development and optimization of floating offshore wind turbine (FOWT) platforms is the key to promoting the development of offshore wind power in distant deep sea areas. Based on an analysis of the current development status of FOWT platforms at home and abroad, this paper further analyzes the current research status of aerodynamic loads, hydrodynamic loads, mooring systems, coupling analysis methods and commonly used numerical simulation tools in the design of FOWT platforms, and focuses on sorting out the key technological ideas and constitutive features of FOWT platforms that are driven by the enhancement of structural stability and the reduction of costs. By summarizing the current research status of FOWT platform optimization, we can forecast the problems and challenges in the design of FOWT platforms with a view to providing technical references for researchers in related fields.

Abstract Adenoid cystic carcinoma (ACC) is a rare, usually slow-growing yet aggressive head and neck malignancy. Despite its clinical significance, our understanding of the cellular evolution and microenvironment in ACC remains limited. We investigated the intratumoral microbiomes of 50 ACC tumor tissues and 33 adjacent normal tissues using 16S rRNA gene sequencing. This allowed us to characterize the bacterial communities within the ACC and explore potential associations between the bacterial community structure, patient clinical characteristics, and tumor molecular features obtained through RNA sequencing. The bacterial composition in the ACC was significantly different from that in adjacent normal salivary tissue, and the ACC exhibited diverse levels of species richness. We identified two main microbial subtypes within the ACC: oral-like and gut-like. Oral-like microbiomes, characterized by increased diversity and abundance of Neisseria, Leptotrichia, Actinomyces, Streptococcus, Rothia, and Veillonella (commonly found in healthy oral cavities), were associated with a less aggressive ACC-II molecular subtype and improved patient outcomes. Notably, we identified the same oral genera in oral cancer and head and neck squamous cell carcinomas. In both cancers, they were part of shared oral communities associated with a more diverse microbiome, less aggressive tumor phenotype, and better survival that reveal the genera as potential pancancer biomarkers for favorable microbiomes in ACC and other head and neck cancers. Conversely, gut-like intratumoral microbiomes, which feature low diversity and colonization by gut mucus layer-degrading species, such as Bacteroides, Akkermansia, Blautia, Bifidobacterium, and Enterococcus, were associated with poorer outcomes. Elevated levels of Bacteroides thetaiotaomicron were independently associated with significantly worse survival and positively correlated with tumor cell biosynthesis of glycan-based cell membrane components.

Abstract Background The Bric-a-Brac/Tramtrack/Broad Complex (BTB) gene family plays essential roles in various biological processes in plants. These genes encode proteins that contain a conserved BTB domain, which is involved in protein-protein interactions and regulation of gene expression. However, there is no systematic reports on the BTB gene family in G.max. Results In total, 122 soybean BTB genes were identified, which were classified into four groups based on the phylogenetic analysis. Gene structures analysis indicated that the number of exon–intron in GmBTBs ranges from 0 to18. Cis-element analysis revealed that most GmBTB genes contained cis-elements related to an abiotic stress response. In addition, qRT-PCR analyses indicated that most GmBTBs are significantly up-regulated under salinity, drought, and nitrate stresses. They suggested their potential for targeted improvement of soybean response to multiple abiotic stresses and nitrate availability. Conclusion These results provide valuable information for identifying the members of the GmBTB gene family in soybean and could provide a functional characterization of GmBTB genes in further research.

Abstract Light-emitting diodes (LEDs) based on perovskite semiconductor materials with tunable emission wavelength in visible light range as well as narrow linewidth are potential competitors among current light-emitting display technologies, but still suffer from severe instability driven by electric field. Here, we develop a stable, efficient and high-color purity hybrid LED with a tandem structure by combining the perovskite LED and the commercial organic LED technologies to accelerate the practical application of perovskites. Perovskite LED and organic LED with close photoluminescence peak are selected to maximize photon emission without photon reabsorption and to achieve the narrowed emission spectra. By designing an efficient interconnecting layer with p-type interface doping that provides good opto-electric coupling and reduces Joule heating, the resulting green emitting hybrid LED shows a narrow linewidth of around 30 nm, a peak luminance of over 176,000 cd m−2, a maximum external quantum efficiency of over 40%, and an operational half-lifetime of over 42,000 h.

Abstract N 6-methyladenosine (m6A) plays critical roles in regulating mRNA metabolism. However, comprehensive m6A methylomes in different plant tissues with single-base precision have yet to be reported. Here, we present transcriptome-wide m6A maps at single-base resolution in different tissues of rice and Arabidopsis using m6A-SAC-seq. Our analysis uncovers a total of 205,691 m6A sites distributed across 22,574 genes in rice, and 188,282 m6A sites across 19,984 genes in Arabidopsis. The evolutionarily conserved m6A sites in rice and Arabidopsis ortholog gene pairs are involved in controlling tissue development, photosynthesis and stress response. We observe an overall mRNA stabilization effect by 3’ UTR m6A sites in certain plant tissues. Like in mammals, a positive correlation between the m6A level and the length of internal exons is also observed in plant mRNA, except for the last exon. Our data suggest an active m6A deposition process occurring near the stop codon in plant mRNA. In addition, the MTA-installed plant mRNA m6A sites correlate with both translation promotion and translation suppression, depicting a more complicated regulatory picture. Our results therefore provide in-depth resources for relating single-base resolution m6A sites with functions in plants and uncover a suppression-activation model controlling m6A biogenesis across species.

Accurate identification of potato diseases is crucial for reducing yield losses. To address the issue of low recognition accuracy caused by the mismatch between target domain and source domain due to insufficient samples, the effectiveness of Multi-Source Unsupervised Domain Adaptation (MUDA) method in disease identification is explored. A Multi-Source Domain Feature Adaptation Network (MDFAN) is proposed, employing a two-stage alignment strategy. This method first aligns the distribution of each source-target domain pair within multiple specific feature spaces. In this process, multi-representation extraction and subdomain alignment techniques are utilized to further improve alignment performance. Secondly, classifier outputs are aligned by leveraging decision boundaries within specific domains. Taking into account variations in lighting during image acquisition, a dataset comprising field potato disease images with five distinct disease types is created, followed by comprehensive transfer experiments. In the corresponding transfer tasks, MDFAN achieves an average classification accuracy of 92.11% with two source domains and 93.02% with three source domains, outperforming all other methods. These results not only demonstrate the effectiveness of MUDA but also highlight the robustness of MDFAN to changes in lighting conditions.

Abstract Designing bifunctional catalysts to reduce the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) reaction barriers while accelerating the reaction kinetics is perceived to be a promising strategy to improve the performance of Zinc–air batteries. Unsymmetric configuration in single‐atom catalysts has attracted attention due to its unique advantages in regulating electron orbitals. In this work, a seesaw effect in unsymmetric Fe–Co bimetallic monoatomic configurations is proposed, which can effectively improve the OER/ORR bifunctional activity of the catalyst. Compared with the symmetrical model of Fe–Co, a strong charge polarization between Co and Fe atoms in the unsymmetric model is detected, in whom the spin‐down electrons around Co atoms are much higher than those spin‐up electrons. The seesaw effect occurred between Co atoms and Fe atoms, resulting in a negative shift of the d‐band center, which means that the adsorption of oxygen intermediates is weakened and more conducive to their dissociation. The optimized reaction kinetics of the catalyst leads to excellent performance in ZABs, with a peak power density of 215 mW cm−2 and stable cycling for >1300 h and >4000 cycles. Flexible Zinc–air batteries have also gained excellent performance to demonstrate their potential in the field of flexible wearables.

Deep networks play a crucial role in the recognition of agricultural diseases. However, these networks often come with numerous parameters and large sizes, posing a challenge for direct deployment on resource-limited edge computing devices for plant protection robots. To tackle this challenge for recognizing cotton diseases on the edge device, we adopt knowledge distillation to compress the big networks, aiming to reduce the number of parameters and the computational complexity of the networks. In order to get excellent performance, we conduct combined comparison experiments from three aspects: teacher network, student network and distillation algorithm. The teacher networks contain three classical convolutional neural networks, while the student networks include six lightweight networks in two categories of homogeneous and heterogeneous structures. In addition, we investigate nine distillation algorithms using spot-adaptive strategy. The results demonstrate that the combination of DenseNet40 as the teacher and ShuffleNetV2 as the student show best performance when using NST algorithm, yielding a recognition accuracy of 90.59% and reducing FLOPs from 0.29 G to 0.045 G. The proposed method can facilitate the lightweighting of the model for recognizing cotton diseases while maintaining high recognition accuracy and offer a practical solution for deploying deep models on edge computing devices.

Abstract Leveraging the ultra‐wideband advantages of the terahertz band, Integrated sensing and communication (ISAC) facilitates high‐precision sensing demands in human smart home applications. ISAC channel characteristics are the basis for ISAC system design. Currently, the ISAC channel is divided into target and background channels. Existing researches primarily focus on the attributes of human target itself, e.g. radar cross‐section and micro‐Doppler effect. However, the impact of human target on neither the pathloss characteristic of background channel nor the multipath propagation characteristic of target channel is considered. To address the gap, we conduct indoor channel measurements at 105 GHz to investigate the ISAC channel characteristics with the impact of human target. Firstly, by analysing the power angular delay profiles with and without human target, the changes in quantity and power of multipath components (MPCs) are observed. Then, a parameter called power control factor is proposed to evaluate the human target impact on pathloss, thereby modifying the existing pathloss model of background channel. Eventually, the MPCs belonging to target channel are extracted within target‐oriented power delay profile to count the power proportion of each bounce MPCs of the target‐Rx link, which supports the necessity of multi‐bounce (indirect) paths modelling in target channel.

Abstract Background Pleural fluid is one of the common complications of thoracic diseases, and tuberculous pleural effusion (TPE) is the most common cause of pleural effusion in TB-endemic areas and the most common type of exudative pleural effusion in China. In clinical practice, distinguishing TPE from pleural effusion caused by other reasons remains a relatively challenging issue. The objective of present study was to explore the clinical significance of the pleural fluid lactate dehydrogenase/adenosine deaminase ratio (pfLDH/pfADA) in the diagnosis of TPE. Methods The clinical data of 618 patients with pleural effusion were retrospectively collected, and the patients were divided into 3 groups: the TPE group (412 patients), the parapneumonic pleural effusion (PPE) group (106 patients), and the malignant pleural effusion (MPE) group (100 patients). The differences in the ratios of pleural effusion-related and serology-related indicators were compared among the three groups, and receiver operating characteristic curves were drawn to analyze the sensitivity and specificity of the parameter ratios of different indicators for the diagnosis of TPE. Results The median serum ADA level was higher in the TPE group (13 U/L) than in the PPE group (10 U/L, P

Abstract Neoantigens derived from somatic mutations in Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS), the most frequently mutated oncogene, represent promising targets for cancer immunotherapy. Recent research highlights the potential role of human leukocyte antigen (HLA) allele A*11:01 in presenting these altered KRAS variants to the immune system. In this study, we successfully generate and identify murine T-cell receptors (TCRs) that specifically recognize KRAS8–16 G12V from three predicted high affinity peptides. By determining the structure of the tumor-specific 4TCR2 bound to KRASG12V-HLA-A*11:01, we conduct structure-based design to create and evaluate TCR variants with markedly enhanced affinity, up to 15.8-fold. This high-affinity TCR mutant, which involved only two amino acid substitutions, display minimal conformational alterations while maintaining a high degree of specificity for the KRASG12V peptide. Our research unveils the molecular mechanisms governing TCR recognition towards KRASG12V neoantigen and yields a range of affinity-enhanced TCR mutants with significant potential for immunotherapy strategies targeting tumors harboring the KRASG12V mutation.

Abstract Background The COVID-19 pandemic have impacts on the prevalence of other pathogens and people’s social lifestyle. This study aimed to compare the pathogen, allergen and micronutrient characteristics of pediatric inpatients with pneumonia prior to and during the COVID-19 pandemic in a large tertiary hospital in Shanghai, China. Methods Patients with pneumonia admitted to the Department of Pediatric Pulmonology of Xinhua Hospital between March-August 2019 and March-August 2020 were recruited. And clinical characteristics of the patients in 2019 were compared with those in 2020. Results Hospitalizations for pneumonia decreased by 74% after the COVID-19 pandemic. For pathogens, virus, mycoplasma pneumoniae (MP) and mixed infection rates were all much lower in 2020 than those in 2019 (P

Abstract Background Hamartoma is a common benign tumor that usually occurs in the kidney, liver, lung, and pancreas. Large renal hamartomas may spontaneously rupture and hemorrhage, which is potentially life-threatening. Case presentation This report describes a 46-year-old Han Chinese female patient with multiple renal and hepatic hamartomas with rupture and hemorrhage of giant hamartoma in the left kidney. She underwent arterial embolization three times successively, and her condition was stable during the 2-year follow-up. This report includes a review of the relevant literature Conclusions the findings in this report and previous literature suggest that arterial embolization can not only rapidly treat hamartoma hemorrhage in the acute phase but can also effectively control multiple lesions in the long term after repeated multisite arterial embolization.

Abstract While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

[Introduction] Under the background of "carbon peak and neutrality" target and "ocean power" strategy, the integration of ocean renewable energy represented by offshore wind power and ocean resources represented by marine ranch is the new direction, new situation and new opportunity for the future development and utilization of ocean resources. The article reviews and analyzes the integrated development mode and key technical problems of offshore wind power and marine pasture, in order to provide technical references to the relevant research and engineering projects in China. [Method] Taking the integration of China's marine resources development needs as the guide, the global development trend of offshore wind power and marine ranch integration was analyzed, and the current situation and shortcomings of China's wind-fishery integration development were clarified. On this basis, the integration mode, equipment design, engineering cases and key technical problems of the integration development of offshore wind power and ocean ranch were analyzed in detail. Finally, a future outlook on the integration development of offshore wind power and ocean ranch in China was discussed. [Result] Through the analysis of the integrated development mode and key technical problems of the integration of offshore wind power and marine ranch development, the bottlenecks and technical challenges are clarified, and the key breakthrough directions are pointed out, providing scientific guidance and reference basis for the comprehensive development and utilization of offshore resources in China. [Conclusion] The article illustrates the necessity and feasibility of integrating the development of offshore wind power and marine ranch, and proposes a feasible way to integrate offshore wind power and marine ranch in China.

Jasmonic acid is a crucial phytohormone that plays a pivotal role, serving as a regulator to balancing plant development and resistance. However, there are analogous and distinctive characteristics exhibited in JA biosynthesis, perception, and signal transduction pathways in both herbaceous and woody plants. Moreover, the majority of research subjects have predominantly focused on the function of JA in model or herbaceous plants. Consequently, there is a significant paucity of studies investigating JA regulation networks in woody plants, particularly concerning post-transcriptional regulatory events such as alternative splicing (AS). This review article aims to conduct a comprehensive summary of advancements that JA signals regulate plant development across various woody species, comparing the analogous features and regulatory differences to herbaceous counterparts. In addition, we summarized the involvement of AS events including splicing factor (SF) and transcripts in the JA regulatory network, highlighting the effectiveness of high-throughput proteogenomic methods. A better understanding of the JA signaling pathway in woody plants has pivotal implications for forestry production, including optimizing plant management and enhancing secondary metabolite production.

Spikelet degeneration is a critical physiological issue that limits grain yield in rice (Oryza sativa L.), influenced by soil moisture conditions during meiosis. The study aimed to investigate the role and mechanism of moderate soil drying in spikelet degeneration and grain yield, as well as to establish a strategy and irrigation regime for suppressing spikelet degeneration to increase grain yield in rice. Field experiments were conducted involving two irrigation regimes: conventional well-watered (C-WW) and moderate soil drying (M-SD) during meiosis. Transgenic rice lines and chemical regulators were employed to elucidate the underlying partial biological mechanisms of this process. The results showed that M-SD regime effectively reduced spikelet degeneration rate and increased grain yield compared to C-WW. This improvement under M-SD regime was primarily attributed to the enhanced proline and aquaporin-mediated osmotic balance and redox homeostasis in young rice panicles, as well as the increased root activity during meiosis. The increased levels of brassinosteroids (BRs) and decreased levels of ethylene (ETH) in young panicles under the M-SD were closely associated with the enhanced proline and aquaporin-mediated osmotic balance and redox homeostasis, decreased oxidative damage, and reduced spikelet degeneration rate. The intrinsic relationship among key aquaporin genes expression and proline levels, osmotic balance and redox homeostasis, spikelet degeneration rate, as well as BRs and ETH levels, was further confirmed through the use of transgenic rice lines and chemical regulators. Collectively, an M-SD regime during meiosis can effectively suppress spikelet degeneration and thereby enhance grain yield, primarily through well-maintained osmotic balance and redox homeostasis in rice.

This paper establishes a high-fidelity and efficient Computational Fluid Dynamics (CFD) numerical method (AL-LDS-Ωnew) for wind turbine wake by combining the actuator line (AL), the localized dynamic Smagorinsky (LDS) sub-grid scale (SGS), and the new generation Ωnew vortex identification method under the framework of large eddy simulation. The model advantages are encouraging: 1) In terms of turbine modeling, the AL model is adopted to replace the traditional three-dimensional solid model, which avoids solving the boundary layer on the blade surface and improves computational efficiency; 2) In terms of wake simulation, the LDS SGS model is used to model turbulence, reducing vortex dissipation and further improving the refinement of turbine wake; 3) In terms of vortex identification, the new generation Ωnew vortex identification method avoids the difficult threshold selection in previous vortex identification and captures more refined vortex structures. The accuracy of the model is validated against published data of a NREL 5 MW wind turbine, and then extended to simulate the wake interference of tandem twin-rotor turbines by changing the pitch angle of the upstream wind turbine (WT1). The influence mechanisms between array wake interference and energy conversion efficiency under the pitch strategy are explored, demonstrating the AL-LDS-Ωnew coupling method is computationally accurate and efficient for simulating the complex wake interference. From analyses, the pitch strategy can effectively suppress the wake effect of the upstream turbine (WT1) and increase the power output of the downstream turbine (WT2), thus improving the overall output power of the array farm. Compared with the non-pitch condition (0 pitch angle), a pitch angle of (2°) maximizes the global energy conversion efficiency of the twin-rotor array: power augmentation by 0.29%, and thrust reduction by 5%. This optimal state reduces the fatigue load of the turbine and is more conducive to long-term operation. The findings, whilst preliminary, encourage the use of turbine pitch strategies in the wind farm planning and operation.

The response of Hypoxia Inducible Gene Domain (HIGD) proteins to hypoxia plays a crucial role in plant development. However, the research on this gene family in soybean has been lacking. In this study, we aimed to identify and comprehensively analyze soybean HIGD genes using the Glycine max genome database. As a result, six GmHIGD genes were successfully identified, and their phylogeny, gene structures, and putative conserved motifs were analyzed in comparison to Arabidopsis and rice. Collinearity analysis indicated that the HIGD gene family in soybean has expanded to some extent when compared to Arabidopsis. Additionally, the cis-elements in the promoter regions of GmHIGD and the transcription factors potentially binding to these regions were identified. All GmHIGD genes showed specific responsiveness to submergence and hypoxic stresses. Expression profiling through quantitative real-time PCR revealed that these genes were significantly induced by PEG treatment in root tissue. Co-expressed genes of GmHIGD were primarily associated with oxidoreductase and dioxygenase activities, as well as peroxisome function. Notably, one of GmHIGD genes, GmHIGD3 was found to be predominantly localized in mitochondria, and its overexpression in Arabidopsis led to a significantly reduction in catalase activity compared to wild-type plants. These results bring new insights into the functional role of GmHIGD in terms of subcellular localization and the regulation of oxidoreductase activity.

Background: Pediatric pneumonia presents a significant global health challenge, particularly in low- and middle-income countries. This study aimed to investigate the incidence of pneumonia in preschool children in Urumqi and its association with indoor environmental factors. Methods: This case-control study collected data from December 2018 to December 2019 on 1522 preschool children in Urumqi (779 boys and 743 girls) who were diagnosed with pneumonia by a physician. A control group of children who had never had pneumonia was matched in a 1:1 ratio based on gender, age, and ethnicity. Using questionnaires, data were collected on children's general characteristics, passive smoking, types of housing, flooring materials, and indoor dampness, analyzing potential factors associated with the incidence of pediatric pneumonia. Results: Multivariate analysis revealed that cesarean birth (odds ratio [OR] = 1.27; 95 % confidence interval [95%CI] = 1.08–1.48), being an only child (OR = 1.32; 95%CI = 1.13–1.55), antibiotic treatment during the first year of life (OR = 2.51; 95%CI = 1.98–3.19), passive smoking during the mother's pregnancy (OR = 1.62; 95%CI = 1.24–2.13), living in multi-family apartment housing (OR = 1.64; 95%CI = 1.28–2.10) and other types of housing (OR = 1.47; 95%CI = 1.09–1.99), laminate flooring (OR = 1.31; 95%CI = 1.01–1.72), and tile/stone/cement flooring flooring (OR = 1.31; 95%CI = 1.06–1.61), and dampness in dwelling (during first year of mother's pregnancy) (OR = 1.30; 95%CI = 1.04–1.63) were risk factors for pediatric pneumonia. The use of fresh air filtration systems in children's residences (OR = 0.66; 95%CI = 0.50–0.86) was identified as a protective factor. Conclusion: This study underscores the importance of indoor environmental factors in the prevention of pediatric pneumonia. Public health strategies should consider these factors to reduce the incidence of pneumonia in children. Future research needs to be conducted over a broader geographical range and consider a more comprehensive range of factors influencing pediatric pneumonia.

Abstract Background Lung cancer remains the foremost reason of cancer‐related mortality, with invasion and metastasis profoundly influencing patient prognosis. N‐acetyltransferase 10 (NAT10) catalyzes the exclusive N (4)‐acetylcytidine (ac4C) modification in eukaryotic RNA. NAT10 dysregulation is linked to various diseases, yet its role in non‐small cell lung cancer (NSCLC) invasion and metastasis remains unclear. Our study delves into the clinical significance and functional aspects of NAT10 in NSCLC. Methods We investigated NAT10's clinical relevance using The Cancer Genome Atlas (TCGA) and a group of 98 NSCLC patients. Employing WB, qRT‐PCR, and IHC analyses, we assessed NAT10 expression in NSCLC tissues, bronchial epithelial cells (BECs), NSCLC cell lines, and mouse xenografts. Further, knockdown and overexpression techniques (siRNA, shRNA, and plasmid) were employed to evaluate NAT10's effects. A series of assays were carried out, including CCK‐8, colony formation, wound healing, and transwell assays, to elucidate NAT10's role in proliferation, invasion, and metastasis. Additionally, we utilized lung cancer patient‐derived 3D organoids, mouse xenograft models, and Remodelin (NAT10 inhibitor) to corroborate these findings. Results Our investigations revealed high NAT10 expression in NSCLC tissues, cell lines and mouse xenograft models. High NAT10 level correlated with advanced T stage, lymph node metastasis and poor overall survive. NAT10 knockdown curtailed proliferation, invasion, and migration, whereas NAT10 overexpression yielded contrary effects. Furthermore, diminished NAT10 levels correlated with increased E‐cadherin level whereas decreased N‐cadherin and vimentin expressions, while heightened NAT10 expression displayed contrasting results. Notably, Remodelin efficiently attenuated NSCLC proliferation, invasion, and migration by inhibiting NAT10 through the epithelial‐mesenchymal transition (EMT) pathway. Conclusions Our data underscore NAT10 as a potential therapeutic target for NSCLC, presenting avenues for targeted intervention against lung cancer through NAT10 inhibition.

Cotton, a vital textile raw material, is intricately linked to people’s livelihoods. Throughout the cotton cultivation process, various diseases threaten cotton crops, significantly impacting both cotton quality and yield. Deep learning has emerged as a crucial tool for detecting these diseases. However, deep learning models with high accuracy often come with redundant parameters, making them challenging to deploy on resource-constrained devices. Existing detection models struggle to strike the right balance between accuracy and speed, limiting their utility in this context. This study introduces the CDDLite-YOLO model, an innovation based on the YOLOv8 model, designed for detecting cotton diseases in natural field conditions. The C2f-Faster module replaces the Bottleneck structure in the C2f module within the backbone network, using partial convolution. The neck network adopts Slim-neck structure by replacing the C2f module with the GSConv and VoVGSCSP modules, based on GSConv. In the head, we introduce the MPDIoU loss function, addressing limitations in existing loss functions. Additionally, we designed the PCDetect detection head, integrating the PCD module and replacing some CBS modules with PCDetect. Our experimental results demonstrate the effectiveness of the CDDLite-YOLO model, achieving a remarkable mean average precision (mAP) of 90.6%. With a mere 1.8M parameters, 3.6G FLOPS, and a rapid detection speed of 222.22 FPS, it outperforms other models, showcasing its superiority. It successfully strikes a harmonious balance between detection speed, accuracy, and model size, positioning it as a promising candidate for deployment on an embedded GPU chip without sacrificing performance. Our model serves as a pivotal technical advancement, facilitating timely cotton disease detection and providing valuable insights for the design of detection models for agricultural inspection robots and other resource-constrained agricultural devices.

BackgroundThe interplay between gut microbiota and metabolites in the early stages of sepsis-induced acute kidney injury (SA-AKI) is not yet clearly understood. This study explores the characteristics and interactions of gut microbiota, and blood and urinary metabolites in patients with SA-AKI.MethodsUtilizing a prospective observational approach, we conducted comparative analyses of gut microbiota and metabolites via metabolomics and metagenomics in individuals diagnosed with SA-AKI compared to those without AKI (NCT06197828). Pearson correlations were used to identify associations between microbiota, metabolites, and clinical indicators. The Comprehensive Antibiotic Resistance Database was employed to detect antibiotic resistance genes (ARGs), while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways informed on metabolic processes and microbial resistance patterns.ResultsOur study included analysis of four patients with SA-AKI and five without AKI. Significant disparities in bacterial composition were observed, illustrated by diversity indices (Shannon index: 2.0 ± 0.4 vs. 1.4 ± 0.6, P = 0.230; Simpson index: 0.8 ± 0.1 vs. 0.6 ± 0.2, P = 0.494) between the SA-AKI group and the non-AKI group. N6, N6, N6-Trimethyl-L-lysine was detected in both blood and urine metabolites, and also showed significant correlations with specific gut microbiota (Campylobacter hominis and Bacteroides caccae, R > 0, P < 0.05). Both blood and urine metabolites were enriched in the lysine degradation pathway. We also identified the citrate cycle (TCA cycle) as a KEGG pathway enriched in sets of differentially expressed ARGs in the gut microbiota, which exhibits an association with lysine degradation.ConclusionsSignificant differences in gut microbiota and metabolites were observed between the SA-AKI and non-AKI groups, uncovering potential biomarkers and metabolic changes linked to SA-AKI. The lysine degradation pathway may serve as a crucial link connecting gut microbiota and metabolites.

Abstract Noncontact humidity sensor overcomes the limitations of its contact sensing counterparts, including mechanical wear and cross infection, which becomes a promising candidate in healthcare and human-machine interface application. However, current humidity sensors still suffer the ubiquitous issue of uncomfortable wear and skin irritation hindering the long-term use. In this study, we report a skin-conformal and breathable humidity sensor assembled by anchoring MXenes-based composite into electrospun elastomer nanofibers coated with a patterned electrode. This composite is highly sensitive to the water molecules due to its large specific surface area and abundant water-absorbing hydroxyl groups, while the elastomeric nanofibers provide an ultrathin, highly flexible, and permeable substrate to support the functional materials and electrodes. This sensor presents not only excellent air permeability (0.078 g cm−2 d−1), high sensitivity (S = 704), and fast response/recovery (0.9 s/0.9 s), but also high skin conformability and biocompatibility. Furthermore, this humidity sensor is confirmed to realize the recognition of motional states and emotional modes, which provides a way for the advanced noncontact human-machine interface.

Abstract Objective Rheumatoid arthritis (RA) is a chronic, progressive autoimmune disease with a complex pathogenesis that has not yet been fully elucidated, and T-cell pyroptosis is an important pathogenetic factor in RA. This study aimed to investigate the role of endoplasmic reticulum aminopeptidase 2 (ERAP2) in the pyroptosis of CD4+ T cells in RA and the specific molecular mechanism. Methods Peripheral venous blood was collected from human subjects, and CD4+ T cells were isolated and activated to measure the level of pyroptosis and ERAP2 expression. Pyroptosis levels were assessed using immunofluorescence, flow cytometry, qRT-PCR, and Western blotting. Changes in pyroptosis levels were observed upon knockdown or overexpression of ERAP2. To detect activated Caspase-1 in tissues, chimeric mice were engrafted with human synovial tissue and reconstituted with human CD4+ T cells. CD4 + T cells were treated with GLI1 antagonists and SMO receptor agonists to detect changes in pyroptosis levels. Results CD4+ T cell levels undergoing pyroptosis were found to be elevated in the blood and synovium of RA patients. The gene and protein expression of ERAP2 were significantly higher in CD4+ T cells from RA patients. Deletion of ERAP2 suppressed pyroptosis of these cells, attenuated the activation of Caspase-1 in tissue T cells, and reduced tissue inflammatory responses. Reciprocally, overexpression of ERAP2 triggered inflammasome assembly, activated Caspase-1, and induced pyroptosis in CD4+ T cells. Mechanistically, ERAP2 inhibits the Hedgehog signaling pathway and upregulates the expression of nucleotide-binding oligomerization segment-like receptor family 3(NLRP3), cleaved Caspase-1, and Gasdermin D to promote pyroptosis in CD4+ T cells. Conclusions Taken together, our results identify a novel mechanism by which ERAP2 regulates RA development and document the effect of the ERAP2/Hedgehog signaling axis on pyroptosis of CD4+ T cells from RA patients.

This paper reports a performance optimized operational amplifier (OPAMP) using transconductance enhancement topology based on the amorphous indium- gallium-zinc-oxide (a-IGZO) thin-film transistors (TFTs). The performance of TFTs is enhanced by N2O plasma treatment that presents electrical characteristics suitable for accomplishing an OPAMP. The circuit consists of 19 TFTs with measured phase margin (PM) and unity-gain frequency (UGF) of 35.8° and 200 kHz, respectively. The DC power consumption (PDC) is 0.68 mW. Notably, it exhibits a high voltage gain (Av) of 32.67 dB and bandwidth (BW) of 15 kHz with 15 V DC supply voltage. Scarcely any work was reported with such a high gain while having a sufficient BW. The OPAMP demonstrates excellent performance among all a-IGZO literature and provides substantial support for the future development of TFT-based integrated circuits (ICs).

Al2O3, as one of the gate dielectric materials for thin film transistors (TFTs), has been extensively investigated because of its large bandgap, high breakdown field, and good thermal stability. However, the further development of Al2O3 thin films is limited by the presence of defects such as oxygen vacancies, self-interstitial atoms, or impurity elements. To overcome this obstacle, we have developed a novel method for fabricating Al2O3 thin films by using the atomic layer deposition (ALD) technique. This method replaces the conventional Trimethylaluminium (TMA)/H2O cycles with TMA/TMA/H2O/H2O cycles (referred to as ‘double cycles’), to deposit the Al2O3. The 5-nm ultrathin Al2O3 film showed a high areal capacitance of 660 nF/cm2 at 20 Hz, and a relatively low current density of 10−8 A/cm2 at 1 MV/cm. InGaZnO (IGZO) TFTs with ultrathin Al2O3 gate dielectric grown by double cycles exhibited outstanding performances, such as a near theoretical limit subthreshold swing (SS) of 70 mV/decade, a higher on/off current ratio $(I_{\mathrm{ on}} / I_{\mathrm{ off}}$ ) of 106, an increased field-effect mobility ( $\mu $ ) of 6.5 cm2/Vs, a lower threshold voltage $(V_{\mathrm{ th}})$ of 0.2 V, and a low operating voltage of 3 V. These results are superior to the IGZO TFTs with Al2O3 dielectrics deposited using the single TMA/H2O cycle. Therefore, the implementation of ‘double cycles’ in the fabrication of dielectrics through ALD demonstrates considerable potential for future application in low-power electronic devices.