Search

The design of effective civil aircraft man-machine interactive airworthiness verification scenarios is the basis for the implementation of crew workload verification. In accordance with the 1523 clauses of CCAR25 of the Civil Aviation Regulations of China and the airworthiness verification requirements in Appendix D,through the interpretation of the airworthiness verification regulations of the transport aircraft crew workload,the workload verification man-machine interactive airworthiness content and verification process is established. Then,the design principles for the crew workload airworthiness verification scenarios of civil aircraft man-machine interaction is established,and the verification scenarios is designed from the four dimensions of test crew,operating process,operating environment and operating status,and then the typical crew workload airworthiness verification scenarios is captured. Finally,the airworthiness verification method of crew workload is proposed combined with crew workload evaluation strategies compared with the measurement methods. The results show that the constructed civil aircraft man-machine interactive airworthiness verification scenarios and airworthiness verification methods are applicable and effective,and can provide a reference for airworthiness verification of civil aircraft crew workload.

Bacteria and fungi drive decomposition, a fundamental process in the carbon cycle, yet the importance of microbial community composition for decomposition remains elusive. Here, we used an 18-month reciprocal transplant experiment along a climate gradient in Southern California to disentangle the effects of the microbial community versus the environment on decomposition. Specifically, we tested whether the decomposition response to climate change depends on the microbial community. We inoculated microbial decomposers from each site onto a common, irradiated leaf litter within "microbial cages" that prevent microbial exchange with the environment. We characterized fungal and bacterial composition and abundance over time and investigated the functional consequences through litter mass loss and chemistry. After 12 months, microbial communities altered both decomposition rate and litter chemistry. Further, the functional measurements depended on an interaction between the community and its climate in a manner not predicted by current theory. Moreover, microbial ecologists have traditionally considered fungi to be the primary agents of decomposition and for bacteria to play a minor role. Our results indicate that not only does climate change and transplantation have differential legacy effects among bacteria and fungi, but also that bacterial communities might be less functionally redundant than fungi with regards to decomposition. Thus, it may be time to reevaluate both the role of microbial community composition in its decomposition response to climate and the relative roles of bacterial and fungal communities in decomposition.

The high diversity of soil bacteria is attributed to the spatial complexity of soil systems, where habitat heterogeneity promotes niche partitioning among bacterial taxa. This premise remains challenging to test, however, as it requires quantifying the traits of closely related soil bacteria and relating these traits to bacterial abundances and geographic distributions. Here, we sought to investigate whether the widespread soil taxon Curtobacterium consists of multiple coexisting ecotypes with differential geographic distributions. We isolated Curtobacterium strains from six sites along a climate gradient and assayed four functional traits that may contribute to niche partitioning in leaf litter, the top layer of soil. Our results revealed that cultured isolates separated into fine-scale genetic clusters that reflected distinct suites of phenotypic traits, denoting the existence of multiple ecotypes. We then quantified the distribution of Curtobacterium by analysing metagenomic data collected across the gradient over 18 months. Six abundant ecotypes were observed with differential abundances along the gradient, suggesting fine-scale niche partitioning. However, we could not clearly explain observed geographic distributions of ecotypes by relating their traits to environmental variables. Thus, while we can resolve soil bacterial ecotypes, the traits delineating their distinct niches in the environment remain unclear.

Magnesium metal batteries (MMBs), recognized as promising contenders for post‐lithium battery technologies, face challenges such as uneven magnesium (Mg) plating and stripping behaviors, leading to uncontrollable dendrite growth and irreversible structural damage. Herein, we have developed a Mg foil featuring prominently exposed (002) facets and an architecture of nanosheet arrays (termed (002)‐Mg), created through a one‐step acid etching method. Specifically, the prominent exposure of Mg (002) facets, known for their inherently low surface and adsorption energies with Mg atoms, not only facilitates smooth nucleation and dense deposition but also significantly mitigates side reactions on the Mg anode. Moreover, the nanosheet arrays on the surface evenly distribute the electric field and Mg ion flux, enhancing Mg ion transfer kinetics. As a result, the fabricated (002)‐Mg electrodes exhibit unprecedented long‐cycle performance, lasting over 6000 h (>8 months) at a current density of 3 mA cm−2 for a capacity of 3 mAh cm−2. Furthermore, the corresponding pouch cells equipped with various electrolytes and cathodes demonstrate remarkable capacity and cycling stability, highlighting the superior electrochemical compatibility of the (002)‐Mg electrode. This study provides new insights into the advancement of durable MMBs by modifying the crystal structure and morphology of Mg. [ABSTRACT FROM AUTHOR]

To study the impact of faults on the enrichment and mobility of shale oil in the Gulong area, representative rock samples were selected in this paper. Based on geochemical data and chemical kinetics methods, coupled with shale oil enrichment and mobility analysis techniques, the shale oil generation quantity and in situ oil content were evaluated from the perspectives of shale oil generation and micro migration, and the mobility of shale oil was revealed. At the same time, the hydrocarbon expulsion efficiency (HEE) of shale was qualitatively and quantitatively characterized, combined with the development of faults. The research results indicate that the study area mainly develops organic-rich felsic (ORF)/organic-containing felsic (OCF) shale, their proportion in both wells exceeds 65%, and the resource amount is the largest in this type of lithofacies. The development of a fault controls the enrichment of shale oil, and the in situ oil content and oil saturation index (OSI) of the shale in well Y58, which is close to the fault, are significantly worse than those in well S2. Well Y58 has 9.52 mg/g and 424.83 mg/g TOC respectively, while well S2 has 11.34 mg/g and 488.73 mg/g TOC respectively. The fault enhanced the migration of shale oil, increasing the efficiency of oil expulsion. As a result, the components with weak polarity or small molecules, such as saturated hydrocarbons and low carbon number n-alkanes, are prone to migration, reducing the mobility of shale oil. [ABSTRACT FROM AUTHOR]

Aiming at the consumption problems caused by the high proportion of renewable energy being connected to the distribution network, it also aims to improve the power supply reliability of the power system and reduce the operating costs of the power system. This paper proposes a two-stage planning method for distributed generation and energy storage systems that considers the hierarchical partitioning of source-storage-load. Firstly, an electrical distance structural index that comprehensively considers active power output and reactive power output is proposed to divide the distributed generation voltage regulation domain and determine the access location and number of distributed power sources. Secondly, a two-stage planning is carried out based on the zoning results. In the phase 1 distribution network-zoning optimization layer, the network loss is minimized so that the node voltage in the area does not exceed the limit, and the distributed generation configuration results are initially determined; in phase 2, the partition-node optimization layer is planned with the goal of economic optimization, and the distance-based improved ant lion algorithm is used to solve the problem to obtain the optimal distributed generation and energy storage system configuration. Finally, the IEEE33 node system was used for simulation. The results showed that the voltage quality was significantly improved after optimization, and the overall revenue increased by about 20.6%, verifying the effectiveness of the two-stage planning. [ABSTRACT FROM AUTHOR]

After the integration of large-scale Distributed Generation (DG) into the distribution network, the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network, exacerbating the phenomenon of wind and solar power wastage. As a novel power system model, the fundamental concept of Regional Autonomous Power Grids (RAPGs) is to achieve localized management and energy autonomy, thereby facilitating the effective consumption of DGs. Therefore, this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for autonomy. First, a regional Energy Storage (ES) configuration strategy is proposed. This strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load and DG output to maximize the elimination of source load deviations in the region as the upper limit constraint of ES capacity. Then, a control strategy for regional ES is proposed, the charging and discharging reference line of ES is set, and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio, the proportion of power supply matching hours, new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy capabilities. The final simulation results show that in the real regional grid example, the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9% and 4.8% on average, and the power imbalance of the tie line decreased by 7.8% on average. The proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluctuation of power exchange between the regional grid and the higher-level grid. This presents a rational and effective planning solution for the regional grid, facilitating the coordinated development between the region and the distribution network. Graphic Abstract [ABSTRACT FROM AUTHOR]

Pancreatic ductal adenocarcinoma (PDAC) has quickly risen to become the third leading cause of cancer-related death in the United States. This is in part because of its fibrotic tumor microenvironment (TME) that contributes to poor vascularization and immune infiltration and subsequent chemo- and immunotherapy failure. Here, we investigated an immunotherapy approach combining delivery of stimulator of interferon genes (STING) and Toll-like receptor 4 (TLR4) innate immune agonists by lipid-based nanoparticle (NP) coencapsulation with senescence-inducing RAS-targeted therapies, which can remodel the immune suppressive PDAC TME through the senescence-associated secretory phenotype. Treatment of transplanted and autochthonous PDAC mouse models with these regimens led to enhanced uptake of NPs by multiple cell types in the PDAC TME, induction of type I interferon and other proinflammatory signaling pathways, increased antigen presentation by tumor cells and antigen-presenting cells, and subsequent activation of both innate and adaptive immune responses. This two-pronged approach produced potent T cell–driven and type I interferon–mediated tumor regression and long-term survival in preclinical PDAC models dependent on both tumor and host STING activation. STING and TLR4-mediated type I interferon signaling was also associated with enhanced natural killer and CD8+ T cell immunity in human PDAC samples. Thus, combining localized immune agonist delivery with systemic tumor-targeted therapy can orchestrate a coordinated type I interferon–driven innate and adaptive immune response with durable antitumor efficacy against PDAC. Editor's summary: Unlike other tumor types, existing immunotherapies have not proven very successful for pancreatic ductal adenocarcinoma (PDAC), necessitating the development of additional approaches. Here, Chibaya et al. developed a combination therapy approach that included nanoparticle delivery of STING and TLR4 agonists, which stimulate the immune response, in combination with the MEK inhibitor trametinib and CDK4/6 inhibitor palbociclib, which promote senescence of tumor cells. The combination therapy induced robust antitumor immune responses that controlled tumor burden in implanted and autochthonous PDAC mouse models. These data support further development of this potent combination therapy for PDAC. —Courtney Malo [ABSTRACT FROM AUTHOR]

Hydrothermal activity is widespread in sedimentary basins, but its dual effects (chemistry and temperature) on shale reservoirs are rarely discussed. In this research, we systematically collected 33 well core samples from Q1 to Q9 units in Gulong Sag, Songliao Basin, and analyzed them using a variety of analytical techniques, including a field emission scanning electron microscopy (FE-SEM), an energy-dispersive spectrometer (EDS), X-ray diffraction (XRD), and stable C-O isotopes. Combined with the collected vitrinite reflectance (Ro), total organic carbon (TOC), and soluble hydrocarbon content data, which is the sum of free oil (pyrolysis S1) and sorb oil content (pyrolysis S2), the results show that (1) Q4 and Q8 units have large amounts of hydrothermal minerals, and its C-O isotope obviously shifts to negative, which implied those units are the main hydrothermal fluid influence area; (2) the hydrothermal activity occurred in the late depositional period of Q1–Q9 units such that its geochemistry has little effect on the proliferation of algae blooms, but its high temperature calculated by δ18O temperature formulas (around 208 °C) promoted the organic matter maturation process around Q4 and Q8; and (3) the overpressure caused by hydrothermal activity protected the shale reservoir and minimized the decrease in mineral reservoir brittleness index caused by hydrothermal fluid influence. We suggest that the shale reservoir affected by hydrothermal fluid will become a good geology "dessert", and its upper and/or lower bounds can form an engineering "dessert" due to the precipitation of large amounts of brittle carbonate minerals. [ABSTRACT FROM AUTHOR]

Truncated singular value decomposition (TSVD) is a popular recovery algorithm for multimode fiber single-pixel imaging (MMF-SPI), and it uses truncation thresholds to suppress noise influences. However, due to the sensitivity of MMF relative to stochastic disturbances, the threshold requires frequent re-determination as noise levels dynamically fluctuate. In response, we design an adaptive truncation threshold determination (ATTD) method for TSVD-based MMF-SPI in disturbed environments. Simulations and experiments reveal that ATTD approaches the performance of ideal clairvoyant benchmarks, and it corresponds to the best possible image recovery under certain noise levels and surpasses both traditional truncation threshold determination methods with less computation—fixed threshold and Stein's unbiased risk estimator (SURE)—specifically under high noise levels. Moreover, target insensitivity is demonstrated via numerical simulations, and the robustness of the self-contained parameters is explored. Finally, we also compare and discuss the performance of TSVD-based MMF-SPI, which uses ATTD, and machine learning-based MMF-SPI, which uses diffusion models, to provide a comprehensive understanding of ATTD. [ABSTRACT FROM AUTHOR]

In recent years, deep neural networks have achieved significant success in 3D point cloud recognition tasks. However, these models still demonstrate substantial performance challenges in the presence of data corruption. It is crucial to improve the robustness and generalization ability of the model. In this work, we propose a novel framework that combines GPT and CLIP models to enhance the robustness of existing point cloud classification models, which has two main modules: the Text-Image Fusion Module, which includes a GPT-Driven TextGen Processor and FocalView Projection, and the Dual-Path Intelligent Adapter Module. First, the GPT-Driven TextGen Processor leverages GPT-4’s capabilities to generate detailed textual descriptions tailored to point cloud intricacies. FocalView Projection dynamically selects viewpoints based on attention maps, enhancing two-dimensional representations of three-dimensional point clouds. Secondly, the Dual-Path Intelligent Adapter Module achieves fine-tuning and feature adaptation by combining internal and external adapters. Additionally, during the fine-tuning process, we employ a variant of Projected Gradient Descent (PGD) adversarial training, named VPGD, to increase the model’s resilience to adversarial perturbations. Our approach has achieved state-of-the-art results on robust 3D points cloud recognition datasets such as ModelNet40-C and ScanObjectNN-C. [ABSTRACT FROM AUTHOR]

Rationale: Gas chromatography–mass spectrometry (GC–MS) combines chromatography and MS, providing full play to the advantages of high separation efficiency of GC, strong qualitative ability of MS, and high sensitivity of detector. In GC–MS data processing, determining the experimental compounds is one of the most important analytical steps, which is usually realized by one‐to‐one similarity calculations between the experimental mass spectrum and the standard mass spectrum library. Although the accuracy of the algorithm has been improved in recent years, it is still difficult to distinguish structurally similar mass spectra, especially isomers. At the same time, the library capacity is very large and increasing every year, and the algorithm needs to perform large numbers of calculations with irrelevant compounds in the library to recognize unknown compounds, which leads to a significant reduction in efficiency. Methods: This work proposed to exclude a large number of irrelevant mass spectra by presearching, perform preliminary similarity calculations using similarity algorithms, and finally improve the accuracy of similarity calculations using deep classification models. The replica library of NIST17 is used as the query data, and the master library is used as the reference database. Results: Compared with the traditional recognition algorithm, the preprocessing algorithm has reduced the time by 4.2 h, and by adding the deep learning models 1 and 2 as the final determination, the recognition accuracy has been improved by 1.9% and 6.5%, respectively, based on the original algorithm. Conclusions: This method improves the recognition efficiency compared to conventional algorithms and at the same time has better recognition accuracy for structurally similar mass spectra and isomers. [ABSTRACT FROM AUTHOR]

AbstractThis retrospective analysis evaluated the use of anti-thymocyte globulin (ATG) with or without post-transplantation cyclophosphamide (PTCy) for graft-versus-host disease (GvHD) prophylaxis in children with acute leukemia undergoing hematopoietic stem cell transplantation (HSCT). The study included 57 children, with 35 in the ATG-PTCy group and 22 in the ATG group. While overall incidence of acute and chronic GvHD did not differ significantly between groups, the ATG-PTCy group had lower rates of grade II-IV acute GvHD (p = 0.013) and moderate-to-severe chronic GvHD (p = 0.001) compared to the ATG group. Importantly, ATG-PTCy significantly improved GvHD/relapse-free survival (GRFS) compared to ATG (65.71% vs. 36.63%; p = 0.003). There were no differences in engraftment, infection rates, immune reconstitution, overall survival, leukemia-free survival, relapse rate, or non-relapse mortality between the two groups. Combining ATG with PTCy may reduce moderate-to-severe GvHD and improve GRFS in children undergoing HSCT for acute leukemia. [ABSTRACT FROM AUTHOR]

Peak detection is an important step in mass spectrometry as accurately identifying characteristic peaks is key to data analysis. In order to address the issue of false peak detection, while simultaneously ensuring accurate detection of weak and overlapped peaks, this paper introduces an improved algorithm for mass spectrometry integrating weighted continuous wavelet transform with particle swarm optimization-based Otsu (WWTPO). The algorithm applies the weighted continuous wavelet transform (WCWT) to compress the frequency spectrum signal into a smaller scale range, which allows for the acquisition of more distinct and informative peak information. Moreover, the algorithm employs the particle swarm optimization (PSO) algorithm to iteratively evaluate the optimal image segmentation threshold, which addresses the challenge of inaccurate Otsu image segmentation. The method was applied to detect simulated peaks as well as matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) datasets. The performance evaluation was conducted using receiver operating characteristic (ROC) curves, F1 measure and F-scores. Through comparison with continuous wavelet transform (CWT) and genetic algorithm-based threshold segmentation (WSTGA), multi-scale peak detection (MSPD) and CWT and image segmentation (CWT-IS), the results demonstrate that WWTPO exhibits excellent performance in peak detection. The determination of 4-isopropyltoluene also demonstrates that WWTPO has excellent practical application. This method not only maintains a low false peak identification rate but also detects more weak peaks and overlapping peaks, further improving the accuracy and efficiency of peak detection in mass spectrometry. [ABSTRACT FROM AUTHOR]