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A computational fluid dynamics (CFD) trimming method based on wind tunnel and flight test data is proposed. Aerodynamic coefficients obtained for a helicopter rotor using this method were compared with both experimental data from a test report and CFD results based on the control parameters that were reported in the same document. The method applies small disturbances to the collective pitch angle, the lateral cyclic pitch angle and the longitudinal cyclic pitch angle of the helicopter’s main rotor during forward flight to analyze the effects of each disturbance on the thrust coefficient, the pitching moment coefficient and the rolling moment coefficient of the rotor. Then, by solving a system of linear equations, the collective pitch angle, the lateral cyclic pitch angle and the longitudinal cyclic pitch angle of the main rotor in the CFD trim state are obtained. The AH-1G rotor is used in this paper. NASA has conducted a comprehensive flight test program on this model and has published detailed test reports. Using this method, the pitch moment and the roll moment can be corrected to almost zero and the calculated thrust coefficient is more consistent with the test data when compared with results from direct CFD simulations.

Dust aerosols can influence climate change, the ecological environment, human health, etc. and are one of the most important factors causing global change. The specific contributions of dust events, gusts, and dust devils to dust emission remain unclear in many regions. In this study, we quantified dust emissions generated by dust events, gusts, and dust devils in the center of the Taklimakan Desert of northwestern China and investigated their respective contributions to atmospheric dust aerosols. The results illustrated that monthly dust emissions and the dust emission time for dust events, gusts, and dust devils peaked in July, August, and June, respectively, and the average monthly contributions to dust emissions were 48.2, 10.6, and 41.2% and those to emission time were 60.5, 25.5, and 14.0%, respectively. Although the dust emissions for the dust event were comparable to the sum of gusts and dust devils, the average value of AOD corresponding to the dust event was roughly 2.5 times higher than that of a non-dust day. The results presented in this study not only highlight the undeniable contribution of gusts and dust devils to dust emissions but also indicate that the specific contributions to atmospheric dust aerosols from gusts and dust devils remain uncertain.

The encoder–decoder paradigm has emerged as the prevailing framework in medical image segmentation, and recent studies within this paradigm have demonstrated its remarkable effectiveness for lesion delineation. However, because the encoder compresses high-dimensional inputs and the decoder must reconstruct the target from the encoder’s limited latent representation, a fixed encoder–decoder pipeline inevitably introduces a semantic gap between the two stages. To bridge this gap, we present MAFormer, a novel U-shaped network tailored for medical image segmentation. Specifically, we design a Multi-scale Dependency Feature Construction (MDFC) module that refines the skip-connection pathway to fuse semantic information across hierarchical levels. In addition, we propose an Attention Representation Reinforcement Module (ARRM) that strengthens encoder–decoder semantic alignment via bidimensional similarity computation and a hierarchical masking strategy. Extensive experiments on GlaS, Synapse and ISIC2018 datasets confirm that MAFormer consistently surpasses state-of-the-art encoder–decoder methods on both large and small scale datasets. In particular, it achieves higher Dice scores, underscoring the effectiveness of MAFormer in improving overall segmentation accuracy.

This study investigated the dust storm observation data from the Taklimakan Desert in 2018, focusing on analyzing horizontal dust flux (Q), vertical dust flux (F), their relationships with aerosol optical depth (AOD), and the relationship between HYSPLIT backward trajectories and dust storm dispersion direction. Key findings include: (1) at the Xiaotang (XT) station, Q values at low heights (1–10 m) exceeded those at higher altitudes, highlighting the role of flat terrain in dust accumulation, while Q values at the Tazhong (TZ) station remained relatively stable, suggesting dust redistribution influenced by undulating topography; (2) vertical dust flux (F) decreased with height, with significant seasonal variations in spring linked to frequent dust events; (3) at station XT, the contribution of F at 5 m height is relatively strong to AOD and its peak precedes AOD by 24–72 h, although the direct correlation is weak; and (4) dust dispersion directions aligned with HYSPLIT trajectories and high Q values corresponded with remotely derived dust dispersion patterns.

In the post-Moore era, as the energy consumption of micro-nano electronic devices rapidly increases, near-field radiative heat transfer (NFRHT) with super-Planckian phenomena has gradually shown great potential for applications in efficient and ultrafast thermal modulation and energy conversion. Recently, hyperbolic materials, an important class of anisotropic materials with hyperbolic isofrequency contours, have been intensively investigated. As an exotic optical platform, hyperbolic materials bring tremendous new opportunities for NFRHT from theoretical advances to experimental designs. To date, there have been considerable achievements in NFRHT for hyperbolic materials, which range from the establishment of different unprecedented heat transport phenomena to various potential applications. This review concisely introduces the basic physics of NFRHT for hyperbolic materials, lays out the theoretical methods to address NFRHT for hyperbolic materials, and highlights unique behaviors as realized in different hyperbolic materials and the resulting applications. Finally, key challenges and opportunities of the NFRHT for hyperbolic materials in terms of fundamental physics, experimental validations, and potential applications are outlined and discussed.

Emerging evidence implicates gut microbiota dysbiosis as a key modulator for the pathogenesis of Alzheimer's disease (AD) via the gut-brain axis. To investigate the causal role of microbial communities in AD progression, we performed fecal microbiota transplantation (FMT) in APP/PS1 transgenic mice using donor microbiota from healthy wild-type mice or dextran sulfate sodium (DSS)-induced colitis mice. Cognitive function, amyloid-beta (Aβ) pathology, and pro-inflammatory cytokine levels were assessed in mice. 16S ribosomal RNA sequencing of gut microbiota and bioinformatic functional analyses were applied to identify the specific microbial communities potentially involved in AD progression. FMT-WT mice (fecal microbiota transplantation from healthy wild-type mice) exhibited significant improvements in spatial memory (Morris Water Maze), exploratory behavior (Y-maze), and locomotor activity (Open Field Test), alongside reduced Aβ plaque burden and normalized expression of pro-inflammatory cytokines (IL-6, IL-1β, TNF-α) in both gut and brain tissues. Conversely, FMT-DSS mice (fecal microbiota transplantation from DSS-treated donors) displayed exacerbated cognitive deficits, heightened Aβ deposition, and elevated pro-inflammatory cytokine levels. Microbial profiling revealed stark contrasts: FMT-WT mice harbored beneficial taxa ( , ) linked to anti-inflammatory products like short-chain fatty acid, while FMT-DSS mice showed blooms of pathogenic genera ( , ) associated with neurotoxic metabolites. Functional analyses predicted enrichment of neuroprotective pathways (e.g., lysine metabolism) in FMT-WT and pro-inflammatory pathways (e.g., carbon metabolism) in FMT-DSS. Crucially, neuroinflammation occurred independently of gut barrier disruption, implicating circulating microbial metabolites as key mediators. Our findings demonstrate that gut microbiota composition bidirectionally influences AD progression, with FMT from healthy donors attenuating neuroinflammation and pathology, while colitis-associated dysbiosis exacerbates disease hallmarks. Our study positions microbiota-targeted therapies as a promising strategy to modulate AD progression through the gut-brain axis.

Dust direct radiative effect (DDRE) can modify the near‐surface air temperature, which can in turn influence dust emission. However, the feedback mechanism of DDRE on dust emission is poorly understood. In this study, the influence of DDRE on dust emission in Taklimakan Desert (TD) was investigated using comprehensive ground‐based observations. The results show that the near‐surface air temperature significantly decreased as a result of DDRE, corresponding to dust emission enhanced. Statistically, the contributions of DDRE to dust emission during light, moderate, and heavy dusty episodes were 5.0% (3.6%), 5.2% (2.8%), and 6.1% (3.3%) in spring (summer), respectively. From the perspective of mechanism, DDRE can induce an increase in air density by cooling the near‐surface, causing an enhancement of aerodynamic drag, promoting dust emission in TD. Such positive feedback of DDRE on dust emission may be a potential contributor to improving the dust emission scheme of numerical modeling in the future. Plain Language Summary Taklimakan Desert (TD) is a significant dust source in China and East Asia, providing abundant dust aerosols that are suspended in the atmosphere over Tarim Basin. Currently, the feedback mechanism of the radiative effect of suspended dust on dust emission is poorly understood. By combining comprehensive ground‐based observations with reanalysis data, we investigated the influence of dust direct radiative effect (DDRE) on dust emission in TD. Due to the DDRE, the near‐surface air temperature during light, moderate and heavy dust pollution episodes decreased by 7.01 (4.38), 7.28 (3.51), and 8.50 K (4.06 K) in spring (summer), respectively. Such a distinct cooling effect decreased the threshold wind speed, leading to dust emission enhanced in TD. The contributions of DDRE to dust emission were 5.0%–6.1% (2.8%–3.6%) in spring (summer). According to the physical mechanism of sand movement, the near‐surface cooling effect caused by DDER induced an increase in air density, leading to the enhancement of aerodynamic drag, which resulted in more dust particles leaving from the surface. Therefore, DDER is responsible for the promotion of dust emissions in TD. The results are beneficial for improving dust emission schemes in future modeling. Key Points Dust direct radiative effect (DDRE) and air pressure are presented as quadratic functions Contributions of DDRE to dust emission are 5.0%–6.1% (2.8%–3.6%) in spring (summer) Enhancement of aerodynamic drag is the primary cause of dust emission increased

A growing number of studies have indicated that extracellular vesicles (EVs), such as exosomes, are involved in the development of neurodegenerative diseases. Components of EVs with biological effects like proteins, nucleic acids, or other molecules can be delivered to recipient cells to mediate physio-/pathological processes. For instance, some aggregate-prone proteins, such as β-amyloid and α-synuclein, had been found to propagate through exosomes. Therefore, either an increase of detrimental molecules or a decrease of beneficial molecules enwrapped in EVs may fully or partly indicate disease progression. Numerous studies have demonstrated that dysbiosis of the gut microbiota and neurodegeneration are tightly correlated, well-known as the “gut–brain axis”. Accumulating evidence has revealed that the gut bacteria-derived EVs play a pivotal role in mediating microbe–host interactions and affect the function of the “gut–brain axis”, which subsequently contributes to the pathogenesis of neurodegenerative diseases. In this review, we first briefly discuss the role of EVs from mammalian cells and microbes in mediating the progression of neurodegenerative diseases, and then propose a novel strategy that employs EVs of plants (plant cell-derived exosome-like nanoparticles) for treating neurodegeneration.

Observation data of the meteorology and dust devil over the desert transition zone at the northern margin of the Taklimakan Desert were combined estimation models for dust emission amounts (DEAs) by dusty weather and dust devil. The aim of the study was to quantitatively determine the contributions of the two weather conditions to the DEAs of the study area. The results indicated that the total DEAs in spring, summer, autumn, and winter were 8.07, 23.62, 1.38, and 0.014 t/km2, respectively, accounting for 24.39, 71.40, 4.17, and 0.04% of the annual total DEAs. The DEAs by dusty weather in the four seasons were 6.55, 10.89, 0.27, and 0.011 t/km2, respectively, accounting for 36.96, 61.45, 1.52, and 0.07% of the annual value, while the DEAs by dust devil in the four seasons were 1.52, 12.73, 1.11, and 0.0033 t/km2, respectively. And the contribution rates of dusty weather and dust devil to the total DEAs were 53.5 and 46.5%, respectively.

This paper designs a ratio consistency algorithm based on event triggering mechanism aiming at the frequency recovery deviation caused by traditional droop control in microgrid. It achieves secondary frequency modulation in microgrid by adjusting the active power setting value. The max-min consistency algorithm is proposed to realize asymptotic consistency of distributed power supply in a finite time. Communication delay is added to ensure the accuracy of frequency update and verifies the robustness of the algorithm against itself. Meanwhile, the validity of event triggering conditions is verified. Finally, the simulation examples are carried out to prove the correctness and superiority of the proposed finite-time control strategy.