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Ovarian cancer is the leading cause of death among all gynecological malignancies, and drug resistance renders the current chemotherapy agents ineffective for patients with advanced metastatic tumors. We report an effective treatment strategy for targeting metastatic ovarian cancer involving a nanoformulation (Bola/IM)─bola-amphiphilic dendrimer (Bola)-encapsulated imatinib (IM)─to target the critical mediator of ovarian cancer stem cells (CSCs) CD117 (c-Kit). Bola/IM offered significantly more effective targeting of CSCs compared to IM alone, through a novel and tumor-specific β-catenin/HRP2 axis, allowing potent inhibition of cancer cell survival, stemness, and metastasis in metastatic and drug-resistant ovarian cancer cells. Promising results were also obtained in clinically relevant patient-derived ascites and organoids alongside high tumor-oriented accumulation and favorable pharmacokinetic properties in mouse models. Furthermore, Bola/IM displayed synergistic anticancer activity when combined with the first-line chemotherapeutic drug cisplatin in patient-derived xenograft mouse models without any adverse effects. Our findings support the use of Bola/IM as a nanoformulation to empower IM, providing targeted and potent treatment of metastatic ovarian cancer. Our study thus represents a significant advancement toward addressing the unmet medical need for improved therapies targeting this challenging disease.

Dipeptidyl peptidase IV (DPPIV, EC 3.4.14.5) is an exopeptidase widely expressed on various cell surfaces that selectively cleaves N-terminal dipeptides from diverse substrates. In recent years, DPPIV inhibitors have been extensively utilized in the treatment of hepatitis mellitus (DM). In this study, we designed a far-red fluorescent probe, DBX-AP, through molecular docking simulations and by leveraging the functional characteristics of DPPIV. This probe enables rapid, highly selective, and real-time monitoring of DPPIV activity both in vitro and in vivo. Using DBX-AP, we developed a visual high-throughput screening technique for the detection of DPPIV inhibitors. From a library of 4828 compounds, three inhibitors (K784-2660, 6484-0066, and E699-0153) were identified for their strong inhibitory effects on DPPIV. These inhibitors not only suppressed DPPIV activity in the ileum of mice, thereby reducing GLP-1 degradation, but also effectively inhibited DPPIV activity in gut microbiota. The successful application of DBX-APin visual detection technology highlights its potential for evaluating DPPIV activity and identifying novel DPPIV inhibitors for diabetes mellitus treatment.

How the size of the Pt-cluster over Nb2O5affects the catalytic performance for the hydrodehydration of 2,5-furandicarboxylic acid (FDCA) is not yet clear at the molecular level. We rationally designed the Pt1/Nb2O5([Pt1]) and Pt3/Nb2O5([Pt3]) catalyst models. Over them, the catalytic mechanism for the hydrodehydration of FDCA to adipic acid (AA) has been theoretically investigated in aqueous solution at the GGA-PBE/DNP level together with its side reactions. The hydrodehydration of FDCA to AA is associated with the ring-opening of furan as the rate-determining step, whereas the decarboxylation of FDCA to furan is related to the cleavage of the C–C bond as the rate-determining step. For the conversion of FDCA, [Pt3] shows higher catalytic activity than [Pt1], because of the less positive charge of Pt1–Pt2 dual-sites over [Pt3] than that of the Pt1 single-site over [Pt1]. Here, the Pt1–Pt2 dual-sites over [Pt3] have a more important synergistic effect on the cleavage of both C5–O3 and C5–C6 bonds compared with the Pt single-site over [Pt1]. Furthermore, [Pt3] selectively favors the FDCA-to-AA hydrodehydration, whereas [Pt1] selectively promotes the FDCA-to-furan decarboxylation. The current research results should provide some theoretical clues for designing novel supported cluster metal oxide catalysts for the hydrogenation of biomass.

Herein, we report a method for enantioselective vinylogous addition of enones to alkoxyallenes enabled by synergistic borane/palladium catalysis. The inductive effect provided by borane coordination to the ketone was essential for closing the gap between the conditions needed for the generation of a dienolate and those needed for initiation of the palladium catalytic cycle by protonation of the metal catalyst. Furthermore, we accomplished the first example of stereodivergent synthesis with chiral borane/transition-metal catalysts.

In the process of the dynamic wireless charging (DWC) of an electric vehicle (EV), the relative position of the coupling coil changes, causing the problem of constant fluctuations of the charging power, which affects the service life of the battery and bring safety problems. Therefore, a power fluctuation suppression method based on the particle swarm optimization (PSO) algorithm is proposed in this paper. First, based on the LCC-S compensation topology, the transmission characteristics of an EV DWC system are analyzed. Then, a DC–DC conversion circuit is added to the rectifier and voltage regulation part of the receiver, and the double closed-loop control parameters are optimized by the PSO algorithm to achieve stable charging power for EV. Finally, the effectiveness of the proposed method is verified by simulations, and compared with the coupling mechanism design and other control strategies to solve the power fluctuation problem of EV dynamic wireless charging. Moreover, experimental results show that the double closed-loop control optimized by the PSO algorithm in this paper can restore balance within 0.08 s, and the fluctuation range is controlled to within ± 1% when the coupling coefficient changes continuously.

Multisource remote sensing images (RSIs) can capture the complementary information of ground objects for use in semantic segmentation. However, there can be inconsistency and interference noise among the multimodal data from different sensors. Therefore, it is a challenge to effectively reduce the differences and noise between the different modalities and fully utilize their complementary features. In this article, we propose a universal cross-fusion transformer framework (CFFormer) for the semantic segmentation of multisource RSIs, adopting a parallel dual-stream structure to extract features separately from the different modalities. We introduce a feature correction module (FCM) that corrects the features of the current modality by combining features from the other modalities in both the spatial and channel dimensions. In the feature fusion module (FFM), we employ a multihead cross-attention mechanism to interact globally and fuse features from the different modalities, enabling the comprehensive utilization of the complementary information in multisource RSIs. Finally, comparative experiments demonstrate that the proposed CFFormer framework not only achieves state-of-the-art (SOTA) accuracy but also exhibits outstanding robustness when compared to the current advanced networks for semantic segmentation of multisource RSIs. Specifically, CFFormer achieves a mean intersection over union (mIoU) of 58% and an overall accuracy (OA) of 85.35% on the WHU-OPT-SAR dataset, outperforming the second-ranked network by 4.71% and 1.74%, respectively. On the Vaihingen and Potsdam datasets, CFFormer also achieves the best results, with mIoU and OA values of 84.31%/91.88% and 88.62%/92.64%, respectively. The source code is available at https://github.com/masurq/CFFormer.

The waste heat boiler in a sulfur-burning sulfuric acid plant experienced failures, specifically furnace tube bursting and tube sheet leakage. Samples were extracted from the front tube sheet and the tubes that had failed, located where the waste heat boiler had developed leaks. The compositions, microstructures, mechanical properties, and crack morphology of the tube sheet and the tubes were analyzed. There were many small cracks in the tube-sheet joints, and Na was detected in the cracks. Na was also found in the expanded connection area between the tubes and the tube sheet. The inner wall of the tubes near the tube burst area was severely corroded. The amount of S on the inner walls of the tubes near the tube burst area was significantly higher than that on the outer walls of the tubes. Through relevant analyses, the following conclusions were obtained: the alkali stress corrosion cracks widely appeared in the tube-sheet joint. The sulfuric acid formed by the mixture of leaked water and high-temperature flue gas flowed into the tubes, and relevant tubes were seriously corroded and eventually burst. The erosion of solid particles formed by the shedding of refractory materials promoted the thinning of tube walls.

Friction is a considerable boundary condition in aluminum alloy hot extrusion. In this study, ball-on-disc friction tests at temperatures of 25–500 °C were performed to equivalently simulate the interface tribological behaviors between Al–Mg–Si–Cu alloy and die steel in hot extrusion. The wear tracks and wear debris on disc samples were observed by means of ultradepth 3D microscopy, field-emission scanning microscope and energy dispersive spectroscopy. The change trends of wear depth, width and wear rate of aluminium disc with temperature and wear cycles were investigated. The evolutions of wear mechanism and friction coefficient with temperature were revealed. A mechanical analytical model for identifying adhesion and ploughing friction components during friction was established. The results show that as temperature rises, wear rate of aluminum disc increases gradually, while the average friction coefficient increases first rapidly and then decreases, which is associated with the changes of friction and wear mechanisms. The adhesion friction force constitutes the majority of total friction force, while ploughing friction force accounts for less than 3 %. Compared with the large variation of adhesion friction coefficient during friction, shear friction stress can tend to be stable and is not affected by the change of contact area, which may can better characterize the adhesion frictional behavior of die interface in aluminum alloy hot extrusion. The quantitative relationship between temperature and steady shear friction stress was described by an inverse polynomial peak function.

In this paper, a series of insensitive smokeless nitrocellulose (NC)-based propellants were prepared through the absorption rolling method. Their thermal stability was rigorously assessed via vacuum stability test (VST), and their thermal reactivity of the propellant was comprehensively investigated and compared using the thermogravimetric analysis (TG)/differential scanning calorimetry (DSC) technique. Additionally, the combustion characteristics were meticulously analyzed by a constant-volume combustion diagnosis system. The experimental results showed that the thermal stability of the propellant was significantly enhanced when N-butyl-N-nitratoethyl nitramine (Bu-NENA) was used to partially or fully replace nitroglycerin (NG). However, an increase in Bu-NENA content corresponded with a decrease in the burning rate of the propellant. The catalytic effects observed in propellants varied markedly, influencing the composition of the products formed during thermal decomposition. Specifically, substituting 50 and 100% of NG with Bu-NENA resulted in reductions in the decomposition heat release of 96.2 and 258 J·g–1, respectively. Furthermore, the introduction of the catalyst significantly increased the burning rate under low-pressure conditions. For instance, at 2 MPa, the burning rate of Bu-0503 increased from 1.78 to 5.23 mm·s–1. A lower content of Bu-NENA was associated with a more luminous flame, while substituting 50 and 100% of NG with Bu-NENA led to decreases in flame temperature by 222 and 535 °C, respectively. The observed decrease in the flame temperature is attributed to the heat absorption during the volatilization of Bu-NENA, leading to a reduction in the thermal feedback of the flame.

The Jahn–Teller (JT) effect, as a spontaneous symmetry-breaking mechanism arising from the coupling between electronic and nuclear degrees of freedom, is a widespread phenomenon in molecular and condensed matter systems. Here, we investigate the influence of the JT effect on the photodissociation dynamics of CF3I molecules. Based on ab initio calculation, we obtain the three-dimensional potential energy surfaces for 3Q0+and 1Q1states and establish a diabatic Hamiltonian model to study the wavepacket dynamics in the CF3I photodissociation process. Using the wave function of the final state after dissociation, we calculate the rotational density matrix of the CF3fragment and analyze its rotational excitation under the JT effect, as well as its partial coherence property and selection rules. Our work paves the way to the experimental observation and quantification of the JT effect in molecular dissociation dynamics beyond the classical ball-and-stick model.

Accurately predicting mutations in G protein-coupled receptors (GPCRs) is critical for advancing disease diagnosis and drug discovery. In response to this imperative, GPTrans has emerged as a highly accurate predictor of disease-related mutations in GPCRs. The core innovation of GPTrans resides in the design of a novel feature extraction network, that is capable of integrating features from both wildtype and mutant protein variant sites, utilizing multifeature connections within a transformer framework to ensure comprehensive feature extraction. A key aspect of GPTrans’s effectiveness is our introduction of an innovative deep feature integration strategy, which merges embeddings and class tokens from multiple protein language models, including evolutionary scale modeling and ProtTrans, thus shedding light on the biochemical properties of proteins. Leveraging transformer components and a self-attention mechanism, GPTrans captures higher-level representations of protein features. Employing both wildtype and mutation site information for feature fusion not only enriches the predictive feature set but also avoids the common issue of overestimation associated with sequence-based predictions. This approach distinguishes GPTrans, enabling it to significantly outperform existing methods. Our evaluations across diverse GPCR data sets, including ClinVar and MutHTP, demonstrate GPTrans’s superior performance, with average AUC values of 0.874 and 0.590 in 10-fold cross-validation. Notably, compared to the AlphaMissense method, GPTrans exhibited a remarkable 38.03% improvement in accuracy when predicting disease-associated mutations in the MutHTP data set. A thorough analysis of the predicted results further validates the model’s effectiveness. The source code, data sets, and prediction results for GPTrans are available for academic use at https://github.com/EduardWang/GPTrans.

AbstractDanzhi-xiaoyao-San (DZXYS), a Traditional Chinese Medicine, plays an essential role in the clinical treatment of depression, but its mechanisms in humans remain unclear. To investigate its pharmacological effects and mechanisms as an add-on therapy for depression, we conducted a double-blind, placebo-controlled trial with depressed patients receiving selective serotonin reuptake inhibitors (SSRIs). Serum and fecal samples were collected for metabolomic and microbiome analysis using UHPLC-QTRAP-MS/MS and 16S rRNA gene sequencing technologies, respectively. Depression symptoms were assessed using the 24-item Hamilton Depression Scale. We employed network pharmacology, metabolomics, and molecular docking to identify potential targets associated with DZXYS. We also examined the correlation between gut microbes and metabolites to understand how DZXYS affects the microbiota-gut-brain axis. The results showed that DZXYS combined with SSRIs was more effective than SSRIs alone in improving depression. We identified 39 differential metabolites associated with DZXYS treatment and found seven upregulated metabolic pathways. The active ingredients quercetin and luteolin were docked to targets (AVPR2, EGFR, F2, and CDK6) associated with the enriched pathways ‘pancreatic cancer’ and ‘phospholipase D signaling pathway’, which included the metabolite lysophosphatidic acid [LPA(0:0/16:0)]. Additionally, we identified 32 differential gut microbiota species related to DZXYS treatment, with Bacteroides coprophilusand Ruminococcus gnavusshowing negative correlations with specific metabolites such as L-2-aminobutyric acid and LPA(0:0/16:0). Our findings indicate that DZXYS's antidepressant mechanisms involve multiple targets, pathways, and the regulation of LPA and the microbiota-gut-brain axis. These insights from our systems pharmacology analysis contribute to a better understanding of DZXYS's potential pharmacological mechanisms in depression treatment.Communicated by Ramaswamy H. Sarma

Bamboo materials are known for their excellent toughness and seismic performance, which makes them a promising option for advancing their application in the field of structural engineering to enhance the seismic resilience of engineering structures. This study focused on mechanical behavior of bolted steel‐neosinocalamus affinis‐based bamboo scrimber and steel connections, and conducted shear test research and analysis on 54 specimens divided into 18 groups, aiming to promote the application of bamboo scrimber in the field of structural engineering. The study indicates that connections with thin steel plates (t= 0.5d, t= 1d) predominantly exhibit a single‐hinge yield mode, while those with thick steel plates (t= 2d) are inclined towards a double‐hinged yield mode. The yield and ultimate load‐carrying capacities of a connection are enhanced with the increase in bolt diameter. However, the influence of the steel plate's strength grade on these capacities is minimal. The yield load‐carrying capacity of connections with thick steel plates has a significant increase compared with the connection with thin steel plates. The thickness of the steel plate does not significantly affect the connection ultimate load‐carrying capacity. The initial stiffness of a connection is positively correlated with the bolt diameter, yet it remains unaffected by variations in the steel plate's thickness. The stiffness of a connection is categorized into two distinct types based on the steel plate strength grade. Connections using steel plates with a strength grade above Q235 exhibit similar stiffness levels, which are consistently higher than those using Q235‐grade steel plates. The angle between the load direction and the grain direction has an effect on the connection ductility. The ductility coefficient across various connections predominantly centers around 2.5. The research also validates that the Foschi theoretical model, traditionally applied to wood structures with bolted, nailed, and similar dowel‐type connections, accurately delineates the nonlinear load–displacement behavior of bolted steel–bamboo scrimber and steel connections for the entire duration of the process. When comparing the same configurations, connections utilizing neosinocalamus affinis‐based bamboo scrimber demonstrate a higher load‐carrying capacity than those using phyllostachys pubescens‐based bamboo scrimber, with a maximum enhancement in load‐carrying capacity of 18%. The design carrying capacity meets the test load requirements for the given end distances of 7d. This research can provide theoretical support for the engineering application of neosinocalamus affinis‐based bamboo scrimber. The results demonstrate that for thick steel plates (t= 2d) in bolted steel‐based bamboo scrimber and steel connections, a double‐hinge failure mode near each shear plane alongside the local carrying yield of the bamboo indicates Yield Mode IV. In contrast, connections with relatively thinner steel plates (0.5d− 1d) exhibited a single hinge and local carrying yield. This aligns with Johansen findings in timber structures, though distinctions in steel plate thickness between Yield Modes III and IV differ. Specifically, a steel plate thickness of 1ddoes not mark the boundary between thin and thick plates, suggesting a critical point between 1dand 2d. Despite adherence to Eurocode 5 design requirements for end, spacing, and edge distances, all connections avoided failure in Yield Mode I, with no definitive preyield deformation in steel plates observed before bolt deformation. Previous studies and literature also confirm that connections meeting the thickness requirements of GB50005 and Eurocode 5 (a≥ 4d) fail in Mode III or IV, not Mode I. This indicates that, under certain construction standards, bolted steel‐based bamboo scrimber and steel connections effectively utilize the mechanical properties of their components, particularly the bending capacity of bolts.

Graph clustering, which learns the node representations for effective cluster assignments, is a fundamental yet challenging task in data analysis and has received considerable attention accompanied by graph neural networks (GNNs) in recent years. However, most existing methods overlook the inherent relational information among the nonindependent and nonidentically distributed nodes in a graph. Due to the lack of exploration of relational attributes, the semantic information of the graph-structured data fails to be fully exploited which leads to poor clustering performance. In this article, we propose a novel self-supervised deep graph clustering method named relational redundancy-free graph clustering (R2FGC) to tackle the problem. It extracts the attribute- and structure-level relational information from both global and local views based on an autoencoder (AE) and a graph AE (GAE). To obtain effective representations of the semantic information, we preserve the consistent relationship among augmented nodes, whereas the redundant relationship is further reduced for learning discriminative embeddings. In addition, a simple yet valid strategy is used to alleviate the oversmoothing issue. Extensive experiments are performed on widely used benchmark datasets to validate the superiority of our R2FGC over state-of-the-art baselines. Our codes are available at https://github.com/yisiyu95/R2FGC.

Source-free domain adaptation is a crucial machine learning topic, as it contains numerous applications in the real world, particularly with respect to data privacy. Existing approaches predominantly focus on euclidean data, such as images and videos, while the exploration of non-euclidean graph data remains scarce. Recent graph neural network (GNN) approaches can suffer from serious performance decline due to domain shift and label scarcity in source-free adaptation scenarios. In this study, we propose a novel method named Graph Diffusion-based Alignment with Jigsaw (GALA), tailored for source-free graph domain adaptation. To achieve domain alignment, GALA employs a graph diffusion model to reconstruct source-style graphs from target data. Specifically, a score-based graph diffusion model is trained using source graphs to learn the generative source styles. Then, we introduce perturbations to target graphs via a stochastic differential equation instead of sampling from a prior, followed by the reverse process to reconstruct source-style graphs. We feed the source-style graphs into an off-the-shelf GNN and introduce class-specific thresholds with curriculum learning, which can generate accurate and unbiased pseudo-labels for target graphs. Moreover, we develop a simple yet effective graph-mixing strategy named graph jigsaw to combine confident graphs and unconfident graphs, which can enhance generalization capabilities and robustness via consistency learning. Extensive experiments on benchmark datasets validate the effectiveness of GALA.

China's residence permit system is the focus of the nation's household registration system reform and a crucial aspect of promoting the new people-centered urbanization. Based on the China Migrants Dynamic Survey, this study uses the probit regression model to investigate the impact of the residence permit system on the floating population's willingness to settle in cities and examines the moderating effect of local government's financial resources. The results show that the residence permit system has a significant promoting effect on the migrants’ willingness to settle. And local government financial resources can strengthen the effect of the residence permit system on the willingness to settle. Additional exploration shows that the residence permit system can enhance the willingness of floating populations to settle in urban areas by increasing their income and consumption levels. Heterogeneity analysis shows that for non-agricultural household registration, high-education, high-income, and interprovincial migrating groups, the incentive effect of the residence permit system is more stronger. Based on the findings, while improving the residence permit system and expanding its coverage groups, transfer payments from the central government to local governments should be increased to effectively improve the value of residence permits, promote the floating population's settlement in cities, and advance China's new urbanization.

A conjugated polymer P-M2with carbazole units as impendent sidechains is used as the electropolymerization (EP) precursor to prepare EP film and realize the coupling reaction between conjugated polymers. Further, the EP film is used as the fluorescent film probe to Fe3+, whose limit of detection (LOD) is calculated to be 1.4×10−7mol/L. Compared with that of the EP film prepared by small molecule precursor M2, the LOD is enhanced ten times. The results are due to both the long conjugation length of P-M2and the inherent highly cross-linking network microstructures of P-M2EP film. Hereby, this work realizes not only the reaction between conjugated polymers but also a new precursor for the EP method and a promising fluorescent film sensor candidate.

Proteolytic targeting chimera (PROTAC) represent an advanced strategy for targeting undruggable proteins, and the molecular warheads targeting E3 ligases play a crucial role. Recently, we explored an alkenyl oxindole warhead targeting the E3 ligase DCAF11 and sought to validate its potential. In this study, we synthesized a range of BRD4 PROTACs (8a–8o, 14a–14f, 22a–22m) with modified alkenyl oxindole warheads and developed a high-throughput screening system based on high-content imaging. We identified L134(22a) as a potent BRD4 degrader, achieving BRD4 degradation (Dmax> 98%, DC50= 7.36 nM) and demonstrating antitumor activity. Mechanically, BRD4 degradation by L134was mediated through the ubiquitin-proteasome system in a DCAF11-dependent manner. Therefore, this study provides a rapid screening method for effective PROTACs and highlights the PROTAC L134based on alkenyl oxindole-DCAF11 pair as a promising candidate for treating BRD4-driven cancers.

•aMCD belongs to HHV-8–negative MCD, which might be a potential early stage of iMCD.•Patients with aMCD do not need immediate treatment but should be closely monitored.

Impaired extravillous trophoblast (EVT) invasion and resulted poor placentation play a vital role in the development of preeclampsia (PE). However, the underlying mechanisms of dysregulated EVTs remain unclear. This study aimed to explore the role of poly (C)-binding protein 2 (PCBP2), a multifunctional RNA-binding protein, in the pathogenesis of PE and to investigate the detailed signaling pathway. Using qRT-PCR, western blot, and immunohistochemistry, we confirmed that the expression of PCBP2 significantly decreased in placentas from 18 early-onset PE and 30 late-onset PE in comparison to those from 30 normotensive pregnancies. Besides, more significant suppression of PCBP2 was observed in the early-onset type. After transfection of HTR-8/SVneo with small-interfering RNA specific to PCBP2, the cellular biological behaviors including vitality, immigration, invasiveness, and apoptosis were evaluated by CCK-8 assay, wound-healing assay, transwell assay, and flow cytometry respectively. RNA-seq was applied to screen differentially expressed genes in HTR-8/SVneo upon PCBP2silencing. GO and KEGG analysis indicated that WNT signaling pathway and the related processes such as extracellular matrix remodeling and cell adhesion were among the most enriched pathways or processes. Meanwhile, the alternative splicing of WNT5A regulated by PCBP2 was also identified by RIP-seq. Based on HTR-8/SVneo and villous explant, the regulatory roles of PCBP2 on trophoblast were confirmed to be mediated by WNT5A. Besides, it revealed that ROR2/JNK/MMP2/9 pathway was a vital pathway downstream WNT5A in trophoblast cells. In conclusion, this study suggests that down-regulated PCBP2 impaired the functions of EVTs via suppression of WNT5A-mediating ROR2/JNK/MMPs pathway, which may eventually contribute to the development of PE.Graphical Abstract

New electron-donating materials are crucial for developing efficient exciplex emitters and host matrices in simplified phosphorescent organic light-emitting diodes (PhOLEDs) with low driving voltage, high efficiency, and minimal efficiency roll-off. Herein, a spiro backbone with a highly sterically rigid structure and orthogonal configuration was attached to the commonly used 9H-carbazole (Cz) via para-linking, resulting in a new electron-donating material 9-(9, $9'$ -spirobi[fluoren]-2-yl)- 9H-Cz (SBF-Cz). The influence of the donor strength on the photophysical, electrochemical, and electroluminescent performances was studied. SBF-Cz exhibits a high T1 level, a shallow highest occupied molecular orbital (HOMO) level, and excellent thermal properties. Utilizing these properties, a simplified blue organic light-emitting diode (OLED) using SBF-Cz:2,4,6-Tris[3-(diphenylphosphinyl)phenyl]-1,3,5-triazine (PO-T2T) as the emitter achieves an EL emission peak at 476 nm and a maximum external quantum efficiency (EQEmax) of 11.2%. Furthermore, the spiro-type exciplex as a universal host was systematically investigated in blue, green, and red PhOLEDs. Notably, the EQEmax of blue, green, and red PhOLEDs using the spiro-type exciplex as host improved by 6.8%, 23.8%, and 11.1%, respectively, compared to the conventional host mCP. Additionally, the blue, green, and red PhOLEDs exhibit lower EQE roll-off of 8.7%, 8.1%, and 1.2% at a brightness of 1000 cd $\cdot $ m-2 compared to the reference devices. This work underscores the significance of the spiro-type donor in developing new blue exciplexes and host matrices for OLEDs.

The Turkey–Syria earthquakes that occurred on February 6, 2023, have caused significant human casualties and economic damage. Emergency services require quick and accurate assessments of widespread building damage in affected areas. This can be facilitated by using remote sensing methods, specifically all-day and all-weather Synthetic Aperture Radar (SAR). In this study, we aimed to improve the detection of building anomalies in earthquake-affected areas using SAR images. To achieve this, we employed Recurrent Neural Network (RNN) to train coherence time series and predict co-seismic coherence. This approach allowed us to generate a Damage Proxy Map (DPM) for building damage assessment. The results of our study indicated that the estimated proportion of building damage in Kahramanmaras was approximately 24.08%. These findings were consistent with the actual damage observed in the field. Moreover, when utilizing the mean and standard deviation of coherence time series, our method achieved higher accuracy (0.761) and a lower false alarm rate (0.136) compared to directly using coherence with only two views of SAR data. Overall, our study demonstrates that this method provides an accurate and reliable approach for post-earthquake building damage assessment.