Lanthanide ions doped upconversion system with dual luminescence centers has attracted much interest in fields of display and temperature sensing. Herein, XNbO4:Yb3+,Er3+ (X = Lu, Gd, Y) are synthesized by solid state method. LuNbO4:Yb3+,Er3+ exhibits optimal upconversion luminescence under the same excitation conditions. Meanwhile, the appropriate combination of dual luminescence centers for Er3+ and Tm3+ can easily achieve color-tunable emission including white emission by adjusting the content of doped ions upon 980 nm excitation. The improving proportion of red emission with increasing Tm3+ is assigned to the effective energy transfer between Er3+ and Tm3+. Furthermore, UC luminescence thermometric performances are systematically investigated. Using non-thermally coupled levels of F-4(9/2) (Er3+) and F-3(2,3) (Tm3+) based on dual luminescence centers can obtain higher sensitivity performance (maximum absolute and relative sensitivity of 69.1 x 10(-3) K-1 and 4.0 % K-1) compared to thermally coupled levels of H-2(11/2) and S-4(3/2). The above results indicate that LuNbO4:Yb3+,Er3+,Tm3+ is a promising upconversion luminescence material for solid-state displays and optical thermometry.

BACKGROUND:Although ICU delirium is recognised as a significant independent predictor of long-term cognitive decline and mortality, its clinical management often remains fragmented. As frontline providers, ICU nurses play a pivotal role in early interventions; however, the psychological and professional determinants that underpin their clinical practice require clearer delineation. AIM:The aim of this study was to assess the knowledge-attitude-practice (KAP) landscape regarding delirium among ICU nurses and to model the mediating role of professional attitudes in translating theoretical knowledge into clinical behaviours. STUDY DESIGN:A cross-sectional survey was conducted in March 2025. Using convenience sampling, a validated KAP questionnaire was administered to ICU nurses via an online platform. The instrument evaluated three domains: Knowledge (10 items, total score range 10-40), Attitudes (10 items, total score range 10-40) and Practice (18 items, total score range 18-72), with higher scores indicating greater proficiency or more favourable orientations. Data were analysed using descriptive statistics, Pearson correlation and multiple linear regression, with mediation effects tested via path analysis. RESULTS:Among 617 valid responses, the mean scores for knowledge, attitudes and practice were 2.58 ± 0.63, 3.42 ± 0.44 and 3.11 ± 0.51, respectively. Significant positive correlations were observed between all KAP dimensions (all p < 0.001). Regression analysis identified hospital grade and prior delirium training as key predictors of knowledge levels (p < 0.05). Both knowledge (β = 0.37) and attitudes (β = 0.36) were significantly associated with practice scores (p < 0.001). Mediation analysis confirmed that attitudes partially mediated the relationship between knowledge and practice (indirect effect = 0.06), accounting for 10.91% of the total effect. CONCLUSIONS:ICU nurses demonstrate generally positive attitudes towards delirium management but exhibit notable knowledge deficits, particularly regarding delirium subtypes. Knowledge serves as the primary driver of practice, whereas professional attitudes function as a significant mediator that facilitates the translation of knowledge into action. Future interventions should transcend basic procedural instruction, prioritising tiered educational programmes and the cultivation of professional values to ensure sustained clinical improvements. RELEVANCE TO CLINICAL PRACTICE:To enhance delirium care, multifaceted strategies are warranted: implementing systematic, tiered training to address specific knowledge gaps (e.g., hypoactive delirium); enhancing professional self-efficacy by emphasising the clinical impact of accurate assessment; and fostering a supportive unit culture that promotes evidence-based discussions and proactive intervention.

Photon upconversion (UC), while promising for infrared photonics, is fundamentally constrained by limited spectral response range, low efficiency, and slow response speeds. Here, we present a machine learning-guided single-photon UC strategy based on cascade pumping that implements a "LEGO-inspired photon stacking" mechanism, in which intermediate state of lanthanide ions (Ln3+) becomes a "virtual ground state" for direct single-photon pumping to target energy levels. As a proof-of-concept, the NaYS2:Ho3+ UC emissions are selectively enhanced by 2-3 orders of magnitude via precise population control. This mechanism extends efficient UC response to ~2100 nm and reduces response time from 30 ms to 54 μs. The approach generalizes to other Ln3+ (Tm3+/Pr3+/Er3+), and energy-transfer optimization in Ho3+-sensitized systems yields near-pure RGB emission. We further demonstrate the high-sensitivity and rapid-response UC narrowband photodetection, enabling low-threshold CO2 sensing with a sensitivity of 6.4×10-4 ppm-1. Our work offers strategy for developing single-photon UC and infrared photodetection technologies.

Lanthanide-doped nanocrystals capable of color-tunable upconversion luminescence have attracted significant attention. However, current research primarily focuses on complex multi-layered core-shell architectures, making the structural design simplification for achieving tunable upconversion emission a persistent challenge. Here, leveraging the superior optical properties of double perovskites, we propose a simplified core-shell model (Cs2NaYF6:Er3+@Cs2NaYF6) to achieve orthogonal upconversion luminescence of Er3+ under different excitation wavelengths. Red-green switchable upconversion luminescence can be realized under dual-channel selective NIR wavelength (980 nm and 1550 nm) excitation, which is attributed to the distinct cross-relaxation rates of Er3+ under different excitation modes. Moreover, the coating of an inert shell further enhances the emission intensity (similar to 220-fold) by suppressing energy migration to surface quenching centers. This excitation-wavelength-gated upconversion luminescence modulation is successfully applied in information encoding and decoding based on the optical logic gate. These findings provide valuable insights for simplifying the design of tunable upconversion in core-shell nanostructures, offering significant potential for advanced information security applications.

Lanthanide ions (Ln3+) doped upconversion originates from their diverse 4f electron transitions. However, the direct manipulation of excited-state electron populations for dynamic emission modulation remains challenging. In this study, a cross-relaxation control paradigm, enabled by dual-wavelength cooperative excitation, is developed for dynamic upconversion engineering. The Er3+-Ln3+ (Ln3+ = Tm3+, Ho3+, Yb3+) doped NaYS2 platform precisely populates the dual-target energy levels via cross-relaxation pathways under cooperative excitation. This approach enables dynamic green-to-red luminescence switching while amplifying the red emission (∼20-fold) by accelerating the cross-relaxation kinetics; Er3+ acts as the photon harvester, and Ln3+ serves as the cross-relaxation mediator to redirect population fluxes. The experimental and theoretical results demonstrate that this phenomenon originates from the unique properties of the low phonon energy, unique layered structure with a large interionic spacing, and high refractive index of the NaYS2 host. Finally, programmable upconversion logic gate arrays are implemented to develop a dynamic- random-visual encryption system for optical information security. This study establishes a novel paradigm for upconversion manipulation with unprecedented capabilities for advanced information technologies.

Rotator cuff tear is one of the most common diseases in sports medicine, and arthroscopic anchor suture and knotting are the main treatment. However, poor tendon-bone healing or retear after surgery remains the main challenge in rotator cuff repair. Herein, we describe a technique for arthroscopic repair of rotator cuff tear: "cable-bridge" suture. This is a rotator cuff repair technique based on the biomechanical concept of the rotator cuff cable and on the principle of bridge suture. First, different knots of medial row anchors are locked with each other to form a main cable similar to the rotator cuff structure. The sutures are cross-linked and fixed with the lateral row anchors to form a "crossed-bridge" cable structure. The medial row suture locking plus lateral row bridge fixation enables all sutures to form a single overall structure like a cable bridge, achieving an optimized mechanical distribution at the tendon-bone interface, forming a continuous compression band at the tendon-bone interface, evenly distributing the tension, reducing single-point stress concentration, and converting linear tension into circular pressure, which is similar to the principle of the cable bridge, with improved surgical reliability.

Thermally enhanced upconversion luminescence demonstrates distinct advantages for optical thermometry in complex scenarios. In this work, NaYS2:Tm3+ phosphors are synthesized via a solid-gas reaction method, followed by systematic investigation of the upconversion luminescence characteristic. The abundant energy level structure of Tm3+ enables its dual functionality as both sensitizer and activator, achieving self-sensitized upconversion luminescence. Under both 808 and 1208 nm excitation, significant thermal enhancement of emission is observed with elevating temperature, which can be attributed to activated phonon-assisted thermal population effect. The temperature-dependent luminescence of NaYS2:Tm3+ is thoroughly analyzed by LIR technique, focusing on the thermally coupled energy levels of 1G4(1)/1G4(2) and 3F2/3F3. Remarkably, the developed Tm3+ single-doped thermometer based on the luminescence thermal enhancement exhibits excellent temperature sensing performance under multi-wavelength excitation of 808 and 1208 nm, exhibiting promising potential for thermometry with wide temperature range and high sensitivity. These findings not only provide a viable strategy for achieving high performance thermometry but also deepen the understanding of thermal enhancement mechanisms in upconversion materials.

Background Catheter-associated urinary tract infection (CAUTI) is a significant threat to patient safety in intensive care units (ICU). Although evidence-based guidelines for CAUTI prevention, adherence remains suboptimal, particularly among ICU nurses in China. Objective To evaluate the effect of a preventive management intervention based on the Management by Objectives (MBO) theory on CAUTI prevention in an ICU setting. Methods A quasi-experimental study with a historical control group was conducted. Patients admitted between January and December 2021 constituted the control group and received routine care. Patients admitted between January 2022 and December 2023 constituted the intervention group and received the MBO-based preventive management in addition to routine care. We compared the two groups on the health outcomes: the incidence of CAUTI, urinary catheter indwelling rate, catheter indwelling days, compliance with bundle measures, hand hygiene compliance, antibiotic use, ICU length of stay, and clinical outcomes. Results A total of 1606 patients were included. The overall urinary catheter indwelling rate was 77.59%, and only 5 CAUTI cases occurred. The CAUTI incidence was 0.41% in the control group (2021). During the intervention period, the incidence was 0.32% in the first year (2022) and 0.19% in the second year (2023), respectively. The difference in CAUTI incidence between the control and intervention groups was not statistically significant (P > 0.05). However, the catheter indwelling rate in the second intervention year was significantly lower than in the control year (P < 0.05). Furthermore, the ICU length of stay and clinical outcomes in the second intervention year showed significant improvement compared to both the control group and the first intervention year (P < 0.05). Conclusion The MBO-based preventive management intervention was associated with a significant reduction in catheter indwelling rates and ICU length of stay. This demonstrates that the intervention can improve nursing practices regarding catheter management and enhance patient outcomes in the ICU.

Massive irreparable rotator cuff tears (MIRCTs) are not uncommon in clinical practice, significantly impacting shoulder function and daily activities. Extensive tear size, tendon contracture, and fat infiltration within the rotator cuff pose significant challenges for both patients and clinicians. This type of tear is a key area of interest and a challenge in research and treatments. Current treatment options include conservative management, debridement, partial repair, superior capsule reconstruction (SCR), tendon transfers, and reverse total shoulder arthroplasty (RTSA). However, clinical outcomes vary widely. The rotator cable (RC) exhibits a perpendicular orientation with respect to the superior rotator cuffs, thereby forming an arc-shaped attachment to the proximal humerus, and it plays an essential role in maintaining the rotator cuff's force couple. The attachments of both anterior and posterior RC play a crucial role in facilitating overhead movements. When complete tension-free coverage of the footprint cannot be attained, whole rotator cable reconstruction (WRCR) presents as an alternative approach for MIRCTs. We utilized autologous tendon harvested from the proximal biceps tendon for arthroscopic WRCR. The proposed technique offers distinct advantages: autologous tissue utilization eliminates immunogenicity; simplified harvesting reduces operative complexity; and minimized anchor usage enhances cost-effectiveness. In this study, 12 patients underwent WRCR, with significant improvements in shoulder function and pain relief observed during a 1 year follow-up.

Upconversion luminescent materials exhibit significant potential for optical storage and anti-counterfeiting applications. However, conventional upconversion-encoded materials lack dynamic control over optical states and color modulation, particularly in both visible and NIR modes. Herein, we propose that combining an excellent upconversion luminescent material with photochromic materials provides an efficient strategy for developing a wider variety of photochromic luminescent systems. Novel NaYF4: Yb, Er @N-TiO2 core-shell structures were designed to integrate upconversion luminescence and photochromic properties. The core-shell structures exhibit distinct photochromic behavior, demonstrating reversible color changes from white to dark blue under 365 nm irradiation. Using reversible photochromism, the upconversion luminescence intensity can be modulated reversibly with a maximum luminescence modulation rate of 83.4 %. We demonstrated the utility of dual-field stimulus-responsive anti-counterfeiting labels and light-printing applications, where both color and luminescence intensity are recovered via laser thermal treatment. This work establishes a new strategy for designing advanced functional materials for high-security anti-counterfeiting and dynamic information display technologies.

Foreign Function Interfaces (FFIs) are essential for enabling interoperability between programming languages, yet existing FFI solutions are ill-suited for the dynamic, interactive workflows prevalent in modern notebook environments such as Jupyter. Current approaches require extensive manual configuration, introduce significant boilerplate, and often lack support for recursive calls and object-oriented programming (OOP) constructs-features critical for productive, multi-language development. We present Kernel-FFI, a transparent, language-agnostic framework that enables seamless cross-language function calls and object manipulation within interactive notebooks. Kernel-FFI employs source-level transformation to automatically rewrite cross-language invocations, eliminating the need for manual bindings or boilerplate. Kernel-FFI provides robust support for OOP by enabling foreign object referencing and automatic resource management across language boundaries. Furthermore, to address the blocking nature of Jupyter kernels and support recursive and asynchronous foreign calls, we introduce a novel side-channel communication mechanism. Our tool will be open-sourced and available at https://codepod.io/docs/kernel-ffi

A series of YNbO4:Er3+,Yb3+,Tm3+ is prepared by the solid-state reaction method. No significant structure changes are found in prepared samples by X-ray diffraction characterization. Blue, green and red emissions of (1)G(4)-> H-3(6) for Tm3+, and H-2(11/2)/S-4(3/2) -> I-4(15/2), F-4(9/2) -> I-4(15/2) for Er3+ can be obtained in Er3+,Yb3+,Tm3+ co-doped system under 808 nm excitation, and the upconversion mechanism are investigated in detail. Complex energy transfer and cross relaxation make it difficult for Er3+,Tm3+ system to bring Tm3+ blue emission of (1)G(4)-> H-3(6), whereas the Yb3+ mediated effect plays a key role in the population of blue emitting level for Tm3+. Moreover, YNbO4:Er3+,Yb3+,Tm3+ can realize thermometry with high sensitivity performance of 7.7 x 10(-3) K-1 for S-A and 1.2 % K-1 for S-R. The tri-doped system showing excellent color tunability can achieve multi-color upconversion luminescence including white light emission, which has the potential to be applied in solid-state displays, optical thermometry and light-emitting diodes.

The design of color-tunable upconversion luminescence for expand the application of optical fields has been a hot research topic. Herein, Yb3+, Ho3+ co-doped YNb1-xVxO4 (x = 0, 0.25, 0.5, 0.75, 1) are synthesized by solid state method. The color tunability of UC luminescence from green to red is achieved by varying the component ratio of Nb5+ and V 5+ in the mixed compositions. The continuous introduction of V 5+ component strengthens the vibrational band of the mixed host, thus promoting the non-radiative relaxation of 5 I 6 -> 5 I 7 in activator Ho3+, which becomes the key to obtain the color-tunable UC luminescence. Besides, the Ho3+ activated system exhibits strong temperature dependent variation in UC luminescence intensity of 5F4/5S2 -> 5I8 and 5 F 5 -> 5 I 8 . The optimal sensitivity parameters can be obtained as 35.64 x 10-3 K- 1 for SA-max and 3.78 % for SR-max in YVO4:Yb3+,Ho3+ thermometer. Benefit by the luminescence color tunability and excellent thermometry performance, phosphors with host dependent upconversion of Ho3+ activated system are expected to achieve optical applications in various fields of anti-counterfeiting, display, and temperature sensing.

Before full achieving automation, Autonomous Vehicle(AV) must undergo a transitional phase of human-machine collaborative driving. Therefore, designing appropriate Human-Machine Interface (HMI) modes of collaboration is key to ensuring both driving safety and user experience. However, existing research has rarely considered the design of human-machine collaboration modes under different Hazard Visibility scenarios. In this study, we conducted a simulated driving experiment (N = 28) to explore the effects of three HMI-based collaboration modes (HMI1, HMI2, and HMI3) on driving behavior and subjective perception under two hazard visibility scenarios (visible and invisible hazard). The designs of the three collaboration modes were primarily based on varying levels of explainability and control. The results show that in the invisible hazard scenario, drivers exhibited significantly lower situation awareness and preference compared to the visible hazard scenario. The design of HMI in different collaboration modes significantly influences drivers' situation awareness, cognitive workload, trust, and attention distribution, with the highest satisfaction reported for HMI2 (high explainability, AV-led decision-making). Particularly in the invisible hazard scenario, HMI2 significantly improved drivers' situation awareness and attention while minimizing cognitive workload. The study also indicates that during autonomous driving, drivers require a certain sense of control, though this does not necessarily mean they need to directly participate in decision-making. Instead, a sense of control can be fostered by augmenting the explainability of the HMI. These findings provide valuable insights for the design of human-machine interfaces in AV to enhance driving safety.

The amount of scientific data is currently growing at an unprecedented pace, with tensors being a common form of data that display high-order, high-dimensional, and sparse features. While tensor-based analysis methods are effective, the vast increase in data size has made processing the original tensor infeasible. Tensor decomposition offers a solution by decomposing the tensor into multiple low-rank matrices or tensors that can be efficiently utilized by tensor-based analysis methods. One such algorithm is the Tucker decomposition, which decomposes an N -order tensor into N low-rank factor matrices and a low-rank core tensor. However, many Tucker decomposition techniques generate large intermediate variables and require significant computational resources, rendering them inadequate for processing high-order and high-dimensional tensors. This article introduces FasterTucker decomposition, a novel approach to tensor decomposition that builds on the FastTucker decomposition, a variant of the Tucker decomposition. We propose an efficient parallel FasterTucker decomposition algorithm, called cuFasterTucker, designed to run on a GPU platform. Our algorithm has low storage and computational requirements and provides an effective solution for high-order and high-dimensional sparse tensor decomposition. Compared to state-of-the-art algorithms, our approach achieves a speedup of approximately 7 to 23 times.

Herein, a series of Er3+ 3+ self-sensitized NaYS2 2 phosphors are synthesized by the solid-gas reaction method for a novel upconversion luminescence thermometer. Er3+ 3+ possesses abundant excited state energy levels in the near- infrared region, enabling efficient upconversion luminescence by absorbing different near-infrared wavelength light. Compared to 980 nm excitation, the emission intensity is enhanced by nearly an order of magnitude under 1532 nm excitation, which can be attributed to the larger absorption cross-section of 4I13/2 I 13/2 and stronger absorption efficiency for Er3+. 3+ . Based on the luminescence intensity ratio technique, the optical thermometry behaviors of NaYS2:Er3+ 2 :Er 3+ under different wavelength excitation are evaluated by employing the thermally coupled energy levels of 2H11/2/4S3/2. H 11/2 / 4 S 3/2 . It can be deduced that the excitation wavelength has no significant effect on the temperature sensing parameters. Compared to other typical upconversion luminescence thermometers, NaYS2: 2 : Er3+ 3+ thermometer exhibits not only excellent sensitivity performance but also high upconversion luminescence efficiency, which is expected to be applied in wide-temperature-range and highly-sensitive temperature sensing.

Multimodal Sentiment Analysis (MSA) technology, prevalent in consumer applications and mobile edge computing (MEC), enables sentiment examination through user data collected by smart devices. Despite the focus on representation learning in MSA, current methods often prioritize recognition performance through modality interaction and fusion. However, they struggle to capture multi-view sentiment cues across different interaction states, limiting multimodal sentiment representations' expressiveness. This paper develops an innovative MSA framework, MVIR, learning multi-view interactive representations in diverse interaction states. Multilple meticulously designed sentiment tasks and an introduced self-supervised label generation algorithm (SSLGM) enable a comprehensive understanding of multi-view sentiment tendencies. The dual-view attention weighted fusion (DVAWF) module is designed to facilitate inter-modality information exchange in different interaction states. Extensive experiments on three MSA datasets affirm the efficacy and superiority of MVIR, showcasing its ability to capture sentiment information from multimodal data across various interaction states.

Herein, Na3Y(VO4)2:Nd3+,Yb3+,Ho3+/Er3+/Tm3+ are synthesized through the solid-state reaction method. By utilizing Yb3+-mediated energy transfer in Nd3+-sensitized various activators (Ho3+/Er3+/Tm3+) system, 808 nm excited multi -color upconversion luminescence is realized. Yb3+ plays an important role in energy transfer bridging, and the introduction of Yb3+ in Nd3+-sensitized system can significantly improve emission of activators by nearly two orders of magnitude. The main luminescence mechanism of Nd3+-> Yb3+-> Activators (Ho3+/Er3+/ Tm3+) is proved via measuring the emission characteristics and luminescence decay curves. With efficient upconversion luminescence, the optical thermometry behaviors for Na3Y(VO4)2:Nd3+,Yb3+,Ho3+/Er3+/Tm3+ are investigated. The maximum relative and absolute sensitivities are 1.08 % K-1 and 7.82 x 10-3 K-1 for Na3Y (VO4)2:Nd3+,Yb3+,Er3+; 1.01 % K-1 and 4.22 x 10-3 K-1 for Na3Y(VO4)2:Nd3+,Yb3+,Tm3+; and 1.08 % K-1 and 22 x 10-3 K-1 for Na3Y(VO4)2:Nd3+,Yb3+,Ho3+, respectively. Based on the multi -color upconversion luminescence and high sensitivity thermometry performance, the Na3Y(VO4)2:Nd3+,Yb3+,Ho3+/Er3+/Tm3+ phosphors have potential applications in fields of solid-state display and safety sign of high -temperature.

The integration of Autonomous Vehicles (AVs) into existing human-driven traffic systems poses considerable challenges, especially within environments where human and machine interactions are frequent and complex, such as at unsignalized intersections. To deal with these challenges, we introduce a novel framework predicated on dynamic and socially-aware decision-making game theory to augment the social decision-making prowess of AVs in mixed driving environments. This comprehensive framework is delineated into three primary modules: Interaction Orientation Identification, Mixed-Strategy Game Modeling, and Expert Mode Learning. We introduce 'Interaction Orientation' as a metric to evaluate the social decision-making tendencies of various agents, incorporating both environmental factors and trajectory characteristics. The mixed-strategy game model developed as part of this framework considers the evolution of future traffic scenarios and includes a utility function that balances safety, operational efficiency, and the unpredictability of environmental conditions. To adapt to real-world driving complexities, our framework utilizes a dynamic optimization framework for assimilating and learning from expert human driving strategies. These strategies are compiled into a comprehensive strategy library, serving as a reference for future decision-making processes. The proposed approach is validated through extensive driving datasets and human-in-loop driving experiments, and the results demonstrate marked enhancements in decision timing and precision.

One of the key factors determining whether autonomous vehicles (AVs) can be seamlessly integrated into existing traffic systems is their ability to interact smoothly and efficiently with human drivers and communicate their intentions. While many studies have focused on enhancing AVs' human-like interaction and communication capabilities at the behavioral decision-making level, a significant gap remains between the actual motion trajectories of AVs and the psychological expectations of human drivers. This discrepancy can seriously affect the safety and efficiency of AV-HV (Autonomous Vehicle-Human Vehicle) interactions. To address these challenges, we propose a motion planning method for AVs that incorporates implicit intention expression. First, we construct a trajectory space constraint based on human implicit intention priors, compressing and pruning the trajectory space to generate candidate motion trajectories that consider intention expression. We then apply maximum entropy inverse reinforcement learning to learn and estimate human trajectory preferences, constructing a reward function that represents the cognitive characteristics of drivers. Finally, using a Boltzmann distribution, we establish a probabilistic distribution of candidate trajectories based on the reward obtained, selecting human-like trajectory actions. We validated our approach on a real trajectory dataset and compared it with several baseline methods. The results demonstrate that our method excels in human-likeness, intention expression capability, and computational efficiency.