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Abstract Copper iodide (CuI) has garnered considerable attention as a promising alternative to p‐type transparent conducting oxides owing to its low cation vacancy formation energy, shallow acceptor level, and readily modifiable conductivity via doping. Although sulfur (S) doping through liquid iodination has exhibited high efficacy in enhancing the conductivity with record high figure of merit (FOM) of 630 00 MΩ−1, solution‐processed S‐doped CuI (CuI:S) for low‐cost large area fabrication has yet to be explored. Here, a highly conducting CuI:S thin‐film for p‐type transparent conducting electrode (TCE) is reported using low temperature solution‐processing with thiourea derivatives. The optimization of thiourea dopant is determined through a comprehensive acid‐base study, considering the effects of steric hindrance. The modification of active groups of thioureas facilitated a varying carrier concentration range of 9 × 1018–2.52 × 1020 cm−3 and conductivities of 4.4–390.7 S cm−1. Consequently, N‐ethylthiourea‐doped CuI:S exhibited a FOM value of 7 600 MΩ−1, which is the highest value among solution‐processed p‐type TCEs to date. Moreover, the formulation of CuI:S solution for highly conductive p‐type TCEs can be extended to CuI:S inks, facilitating high‐throughput solution‐processes such as inkjet printing and spray coating.

Abstract Developing transparent p‐type semiconductors and conductors has attracted significant interest in both academia and industry because metal oxides only show efficient n‐type characteristics at room temperature. Among the different candidates, copper iodide (CuI) is one of the most promising p‐type materials because of its widely adjustable conductivity from transparent electrodes to semiconducting layers in transistors. CuI can form thin films with high transparency in the visible light region using various low‐temperature deposition techniques. This progress report aims to provide a basic understanding of CuI‐based materials and recent progress in the development of various devices. The first section provides a brief introduction to CuI with respect to electronic structure, defect states, charge transport physics, and overviews the CuI film deposition methods. The material design concepts through doping/alloying approaches to adjust the optoelectrical properties are also discussed in the first section. The following section presents recent advances in state‐of‐the‐art CuI‐based devices, including transparent electrodes, thermoelectric devices, p–n diodes, p‐channel transistors, light emitting diodes, and solar cells. In conclusion, current challenges and perspective opportunities are highlighted.

Dye-sensitized solid-state solar cells (DSSCs) replacing the liquid electrolyte with a p-type semiconductor have been extensively examined to solve the practical problems associated with wet-type solar cells. Here, we report the fabrication of a solid-state solar cell using copper iodide (CuI) as the hole conductor and alkyl-functionalized carbazole dye (MK-2) as the sensitizer. A DSSC sensitized with MK-2 showed a solar-to-electrical power conversion efficiency of 3.33% with a Voc of 496 mV and a Jsc of 16.14 mA cm-2 under AM 1.5 simulated sunlight. The long alkyl chains act as a barrier for charge recombination, and the strong accepting and donating abilities of the cyanoacrylic and carbazole groups, respectively, enhance the absorption of light at a longer wavelength, increasing the short-circuit current density. The efficiency recorded in this work is higher than similar DSSCs based on other hole collectors.

Abstract C6F12O is proposed to be one potential eco‐friendly insulation gas to replace SF6. However, the assessment of its decomposition properties and the compatibility with metal electrodes in discharge faults is still challenging, which greatly hinders the development of its insulation and arc‐extinction applications. Herein, a theoretical method is proposed to reasonably address the discharge effects on C6F12O decomposition over typical Cu and Al electrodes at atomic scale. The results show that both the external electric field and the excess electrons could affect the activation of C6F12O by changing the electron acceptance of C6F12O and the orbital hybridisation during the surface bonding. On metal surfaces, the C‐F single bond in adsorbed C6F12O is the weakest position to decompose, and its cleavage could be promoted by the discharge effects. After the C‐F breaking, the C‐C cleavage remains unfavourable on Cu (111), but it is significantly promoted on Al (111), indicating a higher corrosion risk on the Al surface via continuous C6F12O decompositions. The proposed method as a valid supplement to the experiment reveals the discharge effects and the decomposition tendency of C6F12O on metal electrodes in discharge faults, which broadens the means for insulation gas evaluation.

Abstract Spread of parking difficulty can be regarded as a special cascading failure process of urban parking systems. A comprehensive understanding of this process can be greatly helpful to build a more robust parking system. Parking network, a specified complex network, is proposed to model, simulate, and analyse the failure process of urban parking systems in this paper. This model is applied to the analysis of parking systems in an abstract city grid and the downtown area of Luohu, Shenzhen. The results demonstrate that the parking network can capture subtle variations among various parking cruising behaviours or strategies from a network perspective. To enhance the utility of the parking network, an auxiliary indicator named “Parking Difficulty Index” is introduced to help assess the failure degree of urban parking system, estimate the optimal timing for parking guidance intervention, and evaluate the effectiveness of various guidance strategies in mitigating parking difficulties.

Abstract Image‐text retrieval is a fundamental yet challenging task, which aims to bridge a semantic gap between heterogeneous data to achieve precise measurements of semantic similarity. The technique of fine‐grained alignment between cross‐modal features plays a key role in various successful methods that have been proposed. Nevertheless, existing methods cannot effectively utilise intra‐modal information to enhance feature representation and lack powerful similarity reasoning to get a precise similarity score. Intending to tackle these issues, a context‐aware Relation Enhancement and Similarity Reasoning model, called RESR, is proposed, which conducts both intra‐modal relation enhancement and inter‐modal similarity reasoning while considering the global‐context information. For intra‐modal relation enhancement, a novel context‐aware graph convolutional network is introduced to enhance local feature representations by utilising relation and global‐context information. For inter‐modal similarity reasoning, local and global similarity features are exploited by the bidirectional alignment of image and text, and the similarity reasoning is implemented among multi‐granularity similarity features. Finally, refined local and global similarity features are adaptively fused to get a precise similarity score. The experimental results show that our effective model outperforms some state‐of‐the‐art approaches, achieving average improvements of 2.5% and 6.3% in R@sum on the Flickr30K and MS‐COCO dataset.

Abstract Telomere length is closely linked to biological aging, oxidative stress, and the development of cardiovascular diseases. This study aimed to assess the association between dietary selenium intake and telomere length in individuals with hypertension. Data on dietary selenium intake were captured through the National Health and Nutrition Examination Survey (NHANES) computer‐assisted dietary interview system (CADI). Telomere length determination entailed selecting blood samples from all participants in the NHANES database. The analysis was performed using Analysis System software, with Empower stats utilized for data analysis. Results showed that there was a significant association between dietary selenium intake and telomere length in hypertension, particularly within the female group. In female hypertension cases, a 1 mcg increase in dietary selenium intake corresponded to a telomere length increase of 1.19 bp, even after adjusting for age, race, BMI, marital status, physical activity, energy intake, and stroke history. The relationship between dietary selenium intake and telomere length exhibited a linear pattern in female hypertension patients. This study identified a positive association between dietary selenium intake and telomere length in hypertension, particularly within the female group.

Abstract Aims The utility of growth differentiation factor‐15 (GDF‐15) in predicting long‐term adverse outcomes in heart failure (HF) patients is not well established. This study explored the relationship between GDF‐15 levels and adverse outcomes in HF patients across various ejection fraction (EF) phenotypes associated with coronary heart disease (CHD) and evaluated the added prognostic value of incorporating GDF‐15 into the Meta‐Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score‐based model. Methods and results This single‐centre cohort study included 823 HF patients, categorized into 230 (27.9%) reduced EF (HFrEF), 271 (32.9%) mid‐range EF (HFmrEF), and 322 (39.1%) preserved EF (HFpEF) groups. The median age was 68.0 years (range: 56.0–77.0), and 245 (29.8%) were females. Compared with the HFrEF and HFmrEF groups, the HFpEF group had a higher GDF‐15 concentration (P = 0.002) and a higher MAGGIC risk score (P

Abstract Remaining useful fatigue life monitoring of wind turbine drivetrains is important. However, the implementation of real‐time monitoring often faces efficiency and accuracy challenges. In order to resolve this, this paper proposes a vibration‐based damage monitoring digital twin (VBDM‐DT) that enables the online intelligent evaluation of wind turbine gearboxes, using gear tooth surface durability as an example fatigue mode. The VBDM‐DT integrates a random wind load model, a high‐fidelity dynamics model, and a fatigue damage model. The random wind load model takes the wind speed from the supervisory control and data acquisition (SCADA) as input to estimate the input torque of the drivetrain in real time. Simultaneously, VBDM‐DT uses the vibration signals from the condition monitoring system (CMS) to intelligently calibrate the dynamics model, allowing it to be continuously adjusted and optimized in response to actual vibrations. The fatigue damage model takes the real‐time dynamic loads estimated by the high‐fidelity dynamic model as input to achieve real‐time fatigue damage monitoring of key components in the wind turbine gearbox. Applying the VBDM‐DT model to a 2 MW wind turbine gearbox, the results indicate that the model provides satisfactory accuracy in estimating input loads and good adaptability in intelligent calibration of the dynamic model. Based on this model, the fatigue life estimation for gears and bearings is more credible and reliable.

Abstract Objective We performed a post hoc exploratory analysis of Remote Ischemic Conditioning for Acute Moderate Ischemic Stroke (RICAMIS) to determine whether hypertension history and baseline systolic blood pressure (SBP) affect the efficacy of remote ischemic conditioning (RIC). Methods Based on the full analysis set of RICAMIS, patients were divided into hypertension versus non‐hypertension group, or