Actin polymerization powers key cellular processes, including motility, morphogenesis, and endocytosis. The actin turnover cycle depends critically on "re-charging" of ADP-actin monomers with ATP, ...but whether this reaction requires dedicated proteins in cells, and the underlying mechanism, have remained elusive. Here we report that nucleotide exchange catalyzed by the ubiquitous cytoskeletal regulator cyclase-associated protein (CAP) is critical for actin-based processes in vivo. We determine the structure of the CAP-actin complex, which reveals that nucleotide exchange occurs in a compact, sandwich-like complex formed between the dimeric actin-binding domain of CAP and two ADP-actin monomers. In the crystal structure, the C-terminal tail of CAP associates with the nucleotide-sensing region of actin, and this interaction is required for rapid re-charging of actin by both yeast and mammalian CAPs. These data uncover the conserved structural basis and biological role of protein-catalyzed re-charging of actin monomers.
Glacier inventories are fundamental in understanding glacier dynamics and glacier-related environmental processes. High-resolution mapping of glacier outlines is lacking, although high-resolution ...satellite images have become available in recent decades. Challenges in development of glacier inventories have always included accurate delineation of boundaries of debris-covered glaciers, which is particularly true for high-resolution satellite images due to their limited spectral bands. To address this issue, we introduced an automated, high-precision method in this study for mapping debris-covered glaciers based on 1 m resolution Gaofen-2 (GF-2) imagery. By integrating GF-2 reflectance, topographic features, and land surface temperature (LST), we used an attention mechanism to improve the performance of several deep learning network models (the U-Net network, a fully convolutional neural network (FCNN), and DeepLabV3+). The trained models were then applied to map the outlines of debris-covered glaciers, at 1 m resolution, in the central Karakoram regions. The results indicated that the U-Net model enhanced with the Convolutional Block Attention Module (CBAM) outperforms other deep learning models (e.g., FCNN, DeepLabV3+, and U-Net model without CBAM) in terms of precision for supraglacial debris identification. On the testing dataset, the CBAM-enhanced U-Net model achieved notable performance metrics, with its accuracy, F1 score, mean intersection over union (MIoU), and kappa coefficient reaching 0.93, 0.74, 0.79, and 0.88. When applied at the regional scale, the model even exhibits heightened precision (accuracies = 0.94, F1 = 0.94, MIoU = 0.86, kappa = 0.91) in mapping debris-covered glaciers. The experimental glacier outlines were accurately extracted, enabling the distinction of supraglacial debris, clean ice, and other features on glaciers in central Karakoram using this trained model. The results for our method revealed differences of 0.14% for bare ice and 10.36% against the manually interpreted glacier boundary for supraglacial debris. Comparison with previous glacier inventories revealed raised precisions of 8.74% and 4.78% in extracting clean ice and with supraglacial debris, respectively. Additionally, our model demonstrates exceptionally high exclusion for bare rock outside glaciers and could reduce the influence of non-glacial snow on glacier delineation, showing substantial promise in mapping debris-covered glaciers.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Formation and turnover of branched actin networks underlies cell migration and other essential force-driven processes. Type I nucleation-promoting factors (NPFs) such as WASP recruit actin monomers ...to Arp2/3 complex to stimulate nucleation. In contrast, mechanisms of type II NPFs such as Abp1 (also known as HIP55 and Drebrin-like protein) are less well understood. Here, we use single-molecule analysis to investigate yeast Abp1 effects on Arp2/3 complex, and find that Abp1 strongly enhances Arp2/3-dependent branch nucleation by stabilizing Arp2/3 on sides of mother filaments. Abp1 binds dynamically to filament sides, with sub-second lifetimes, yet associates stably with branch junctions. Further, we uncover a role for Abp1 in protecting filament junctions from GMF-induced debranching by competing with GMF for Arp2/3 binding. These data, combined with EM structures of Abp1 dimers bound to Arp2/3 complex in two different conformations, expand our mechanistic understanding of type II NPFs.
Aiming to understand group behaviors and dynamics of neural networks, we have previously proposed the Josephson junction neuron (JJ neuron) as a fast analog model that mimics a biological neuron ...using superconducting Josephson junctions. In this study, we further analyze the dynamics of the JJ neuron numerically by coupling one JJ neuron to another. In this coupled system we observe a phase-flip bifurcation, where the neurons synchronize out-of-phase at weak coupling and in-phase at strong coupling. We verify this by simulation of the circuit equations and construct a bifurcation diagram for varying coupling strength using the phase response curve and spike phase difference map. The phase-flip bifurcation could be observed experimentally using standard digital superconducting circuitry.
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In this study, the Mo0.5NbTiZrTax (x = 0.3, 0.5, 0.7) HEAs obtained by arc melting were controlled by the change of Ta content. The microstructure, the wear properties, and the corrosion resistance ...of the alloys were studied systematically. The results revealed that the alloys have the BCC (major) phase + BCC (minor) phase structure. At the same time, the increase in Ta content promotes the refinement of grains and the formation of sub-grains with gradually random orientation at grain boundaries but suppresses the randomization of crystal orientation. This also enriched the defect structure inside the alloys, further induced the formation of Zr-rich second phase particles, high-density stacking fault structures, and disordered Zr-rich BCC phases. The increase in Ta content significantly improved the wear properties of the alloys, which is mainly ascribed to the presence of the tough BCC phase and the combined effects of solid solution strengthening, second phase strengthening, fine grain strengthening, lattice distortion effect, and stacking fault strengthening. The electrochemical measurements confirm that the overall corrosion resistance of the alloys shows a trend of first increasing and then decreasing with the increase of Ta content due to the formation of micro batteries between the second phase rich in Zr as the anode and dendrites.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Vessel trajectory prediction using AIS data plays an important role in maritime navigation warning and safety. A key aspect of trajectory prediction is multimodal because of the uncertainty of vessel ...behavior. However, complex trajectory modes are difficult to be learned from low-dimensional AIS data with noise. In this paper, we propose a new method for multimodal vessel trajectory prediction, called Multimodal Vessel Trajectory Prediction via Modes Distribution Modeling (VT-MDM). This approach addresses the above challenges by introducing additional hiding regimes to characterize complex trajectory modes independently. Specifically, we introduce an additional latent vector as the encoding of the trajectory modes, which is randomly sampled from a multivariate Gaussian distribution to generate multiple predicted trajectories. To enable this Gaussian distribution for capturing the vessel trajectory modes, we use adversarial learning to enforce all its realizations to generate realistic predicted trajectories. Furthermore, we also encourage the mapping between the latent vectors of the modes and the predicted trajectories to be invertible and smooth, which prompts VT-MDM to produce truly and gradually multimodal predicted trajectories. Experiments on the real AIS dataset show that our method is capable of multimodal trajectory prediction with high accuracy.
•Multimodal prediction by directly modeling the vessel trajectory modes’ distribution.•Continuous trajectory modes space.•Larger trajectory modes’ distribution.•Gradual transition between different predicted modes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this paper, a CH
NH
(MA)PbBr
/Si heterojunction photodetector (PD) is prepared, and a simple method is proposed to improve the performance by introducing an ITO conductive layer and modulating ...thickness of the MAPbBr
layer. The results indicate that the MAPbBr
/Si heterojunction PD exhibits an ultra-broadband photoresponse ranging from 405 to 1064 nm, and excellent performances with the responsivity (R) of 0.394 mA/W, detectivity (D) of 0.11×10
Jones, and response times of ∼2176/∼257 ms. When adding the ITO layer, the R and D are greatly improved to 0.426 A/W and 5.17×10
Jones, which gets an increment of 1.08×10
% and 4.7×10
%, respectively. Meanwhile, the response times are reduced to ∼130/∼125 ms, and a good environmental stability is obtained. Moreover, it is found that the photoresponse is strongly dependent on the thickness of the MAPbBr
layer. By modulating the MAPbBr
layer thickness from ∼85 to ∼590 nm, the performances are further improved with the best R of ∼0.87 A/W, D of ∼1.92×10
Jones, and response times of ∼129/∼130 ms achieved in the ∼215 nm-thick PD.
CdS, with a noncentrosymmetric structure, is thought as an important electron transport layer (ETL) in perovskite-based devices, but its pyroelectric effect, which can efficiently modulate the ...optoelectronic processes, is not well explored. In this work, a MAPbI3 heterojunction of CdS/MAPbI3/Spiro-OMeTAD with a c-axis preferred oxygen-doped CdS ETL is developed as a high-performance photodetector (PD). This PD exhibits a stable self-powered property in the spectral range of ∼360–780 nm due to its excellent photovoltaic effect. Moreover, the light-induced pyroelectric potential in the CdS ETL is demonstrated to be an efficient approach for improving the photoresponses, and different effects are observed for different laser irradiations, which can be well understood from their working mechanisms. Upon 450 nm laser irradiation, the photovoltage responsivity (R) is greatly improved from 596.9 to 6383.6 V/W with an increment of 1069.54%. In addition, the response spectrum is also extended outside the bandgap restriction of the MAPbI3 to 1550 nm due to both the pyroelectric and photothermoelectric effects, which is a big breakthrough for the perovskite heterojunction PD. Through turning the external bias voltage and ambient temperature, the coupling mechanisms of the pyroelectric and photovoltaic effects are further analyzed. This work provides an important understanding of designing the CdS ETL-based perovskite heterojunction for broadband high-performance photoelectric devices by introducing the pyroelectric effect.
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An electron transport layer (ETL) with a suitable gradient energy level can enhance electron transfer, suppress carrier recombination, and effectively improve the photoresponse of photodetectors ...(PDs). In this letter, a series of ITO/ZnO/CdS/MAPbI3/Spiro-OMeTAD heterojunction PDs were prepared by incorporating a ZnO layer at the CdS/ITO interface upon varying the thickness from 0 to 95 nm. The optimized band arrangement in the PD results in an excellent self-powering ability and improved photoresponse. Moreover, both the photovoltaic and pyroelectric responses strongly correlate with the thickness of the ZnO layer. The PD with an optimal ZnO thin film thickness of 50 nm achieves a huge responsivity (R) of 1.19 × 104 V/W and detectivity (D) of 2.22 × 109 Jones, primarily due to the strengthened pyro-phototronic effects enabled by the dual ETL layers. In addition, the enhanced pyroelectric effect broadens the spectral range of the PD to 360–1550 nm, largely surpassing the band gap of the heterojunction.
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