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Diarylethenes are an important class of photoswitches that usually exist in interconvertible parallel (photoinert) and antiparallel (photochromic) conformational states. Recent research afforded sterically congested diarylethenes that exist as stable and separable configurational atropisomers. Rational manipulation of stereochemistry is a robust strategy for regulating diarylethene photochemistry. Here, we present a brief account of the conformer/atropisomer-dependent photochromism of diarylethene photoswitches, and we discuss a recent advance at the interface of diarylethene photochemistry and polymer mechanochemistry: our group recently introduced a mechanical approach for converting a parallel diarylbenzothiadiazole into its antiparallel configurational diastereomers, thereby turning on its photochromic reactivity. After mechanical activation, UV light changes the converted diarylethene molecule into a colored ring-closed form by a 6π-electrocyclization reaction that permits the visualization of the mechanical activation event. Besides the fundamentally new mechanism of converting a molecule into its configurational diastereomers through force–stereochemistry coupling, the conversion of atropisomer stereochemistry is a noncovalent process and features high mechanical reactivity in comparison to conventional mechanophores, which require covalent bond scission. This new type of configurational mechanophore holds promise for various applications, such as high-sensitivity stress sensing, lithography, and information storage. 1 Diarylethene Conformers and Atropisomers 2 Polymer Mechanochemistry and Configurational Mechanophores 3 Regulating the Stereochemistry and Reactivity of a Diarylethene Atropisomer with Mechanical Force 4 Summary and Future Outlook [ABSTRACT FROM AUTHOR]

Pressure sensors provide significant information for monitoring and exploration of complex underwater environments. Current sensing technology of underwater pressure has certain limitations in the integration of individual sensors and decoupling of dynamic and static mechanical signals. In this paper, a polyester-based piezoelectric elastomer was synthesized and blended with modified nanocarbon fiber (DPBPE) to prepare a piezoelectric/capacitive composite, achieving integrated and synchronous identification of dynamic and static pressures. The incorporation of modified nanocarbon fiber into the piezoelectric elastomer ensures the piezoelectric and capacitive response of the composites and improves the relative capacitance change rate by 1.6 times compared to that of the neat elastomer. The prepared sensor shows a high sensitivity of 0.8 mV N−1 and 3.09 × 10−2 kPa−1 for dynamic and static pressure monitoring, respectively. Furthermore, the sensor showed good feedback for changes in water depth and underwater vibration without any mutual interference, indicating its great potential in fields such as ocean waves and underwater pressure monitoring. [ABSTRACT FROM AUTHOR]

In the pursuit of low‐dose flat‐panel X‐ray detection and imaging, controlling dark current is pivotal. Modulating the bandgap and resistivity of photosensitive materials is one of the methods to reduce dark current. The study introduces a novel approach by first demonstrating a non‐perovskite orthorhombic phase δ‐CsPbI2Br thick film, fabricated using an innovative elastic molecular‐assisted coating strategy. This technique results in a material with an optimized bandgap of 2.30 eV and a significantly elevated resistivity of 2.42 × 10¹⁰ Ω cm. Consequently, this leads to an ultralow dark current of 1.34 nA cm⁻2. Leveraging this advancement, the developed X‐ray detectors showcase a groundbreaking low detection limit of 53 nGyair s⁻¹, surpassing the performance of their cubic‐phase counterparts. Remarkably, the material exhibits excellent phase stability, maintaining its properties for up to 80 days. By integrating with a thin‐film transistor array, a flat‐panel X‐ray detector that delivers high‐quality 8‐bit imaging across a 64 × 64 matrix is successfully engineered. This work not only presents a transformative approach to substantially reduce dark current in low‐dose X‐ray detection but also sets a new benchmark in the field by combining enhanced imaging capability with robust long‐term stability. [ABSTRACT FROM AUTHOR]

Skeletal muscle loss is a common clinical disease, whose long treatment period and expensive treatment costs bring a heavy burden to patients. Currently, the use of piezoelectric materials to generate in situ and efficient electrical stimulation has been proven to significantly promote wound healing and other defects. However, skeletal muscle requires repaired materials with high elastic deformation to accompany its reciprocating movement during the healing process. Therefore, developing biocompatible materials that combine high piezoelectricity and stretchability is a great challenge. In the present work, a piezoelectric elastomer PPBE is prepared by copolymerization of bio‐based diacid and diol. PPBE has matching elastic modulus with the skeletal muscle to accompanied proceed stretching and recovery movements. Piezoelectrical charge from PPBE scaffold under ultrasound and mechanical stimuli could promote myogenic differentiation via Ca2+ signaling pathway and modulate cell functions, resulting in improved muscle morphology and functional performance of skeletal muscle. Thus, development of the degradable PPBE scaffold would provide new therapy strategy for volumetric muscle loss (VML) and present great potential in repairing of other tissues. [ABSTRACT FROM AUTHOR]

In the present study, poling−free PLLA/VB2 piezoelectric composites are fabricated to achieve synchronous sound recognition and energy harvesting. The addition of VB2 can interact with PLLA by intermolecular hydrogen bonding, inducing the dipole orientation of C=O in PLLA. Meanwhile, VB2 can promote crystallization of PLLA through heterogeneous nucleation. The combination of the two strategies significantly improves the piezoelectric performance of PLLA/VB2 composites. The PLLA/VB2 can detect the sound frequency with an accuracy of 0.1% in the range of 0–20 kHz to recognize characteristic sounds from a specific source. PLLA/VB2 can also convert sound into electrical energy synchronously with an energy density of 0.2 W/cm−3 to power up LEDs. Therefore, PLLA/VB2 shows great potential in the field of information and energy synchronous collection. [ABSTRACT FROM AUTHOR]

In this paper, a self‐powered piezoelectric sensor is developed for pressure monitoring. Though molecular design and processing optimum of piezoelectric materials, the the accuracy of pressure sensing was significantly improved, and the sphygmic signal of the human body can be detected. In particular, the prepared sensor is capable to be integrated under flexible OLED display to realize sphygmic signal detection. Thus, a new under‐screen flexible OLED health sensing device is realized. [ABSTRACT FROM AUTHOR]

Fully emulating the function of human skin through electronic skin depends on the simultaneous realization of both superficial and deep sensations. However, the majority of current research on electronic skin is limited to tactile-based bionics, focusing only on superficial sensation. In this study, a stretchable and self-healing elastomer based on 2,3-BDO (BBPE) is fabricated as electronic skin through molecular structure design with abundant dipoles and restricted crystallinity in the linear backbone. By realizing the piezoelectric and triboelectric output, our electronic skin (PBES) is capable of detecting various contact and contactless signals to realize not only superficial sensations of touch and stretch but also deep sensations of position and state. Furthermore, the PBES exhibits human-skin-like properties with elastic elongation higher than 300% even after 100 cycles and self-healing properties with a recovery of 77.34% of its electrical performance at 37 °C within 10 minutes. Moreover, the utilization of bio-based monomers ensures its biocompatibility and hydrophobicity similar to human skin. Considering its great potential in electronic bionics and human–computer interaction fields, PBES holds immense promise for future development. [ABSTRACT FROM AUTHOR]

Aspect-based sentiment analysis (ABSA) is a task of fine-grained sentiment analysis that aims to determine the sentiment of a given target. With the increased prevalence of smart devices and social media, diverse data modalities have become more abundant. This fuels interest in multimodal ABSA (MABSA). However, most existing methods for MABSA prioritize analyzing the relationship between aspect–text and aspect–image, overlooking the semantic gap between text and image representations. Moreover, they neglect the rich information in external knowledge, e.g., image captions. To address these limitations, in this paper, we propose a novel hierarchical framework for MABSA, known as HF-EKCL, which also offers perspectives on sensor development within the context of sentiment analysis. Specifically, we generate captions for images to supplement the textual and visual features. The multi-head cross-attention mechanism and graph attention neural network are utilized to capture the interactions between modalities. This enables the construction of multi-level aspect fusion features that incorporate element-level and structure-level information. Furthermore, for this paper, we integrated modality-based and label-based contrastive learning methods into our framework, making the model learn shared features that are relevant to the sentiment of corresponding words in multimodal data. The results, based on two Twitter datasets, demonstrate the effectiveness of our proposed model. [ABSTRACT FROM AUTHOR]

A cluster of vultures, artificially bred in a zoo in Shandong Province, China, displayed signs of emaciation and some even died, which raised the suspicion of an immunosuppressive pathogen. Upon conducting nucleic acid testing on the clinical samples, it was found that the CIAV was present in the tissue of dead vulture. In this study, samples of dead vulture tissue were used to isolate a chicken infectious anemia virus (CIAV) via the MDCC-MSB1 cell line, which was designated the SDTY2021-TJ strain. The full-length genomic sequence of SDTY2021-TJ was determined and analyzed in detail. The full genomic DNA of SDTY2021-TJ was found to be 2298 bp, with no omissions or additions in the coding region. The homology between the full-length genomic sequence of SDTY2021-TJ and the reference strain ranged from 95.5% (Del-Ros) to 98.7% (YN04). In comparison with the reference strain, the VP1 protein of SDTY2021-TJ contained a number of mutations. To assess the virulence of SDTY2021-TJ, one-day-old SPF chickens were inoculated with both high and low doses of the pathogen. The results demonstrated that SDTY2021-TJ had a considerable pathogenicity to SPF chickens, as the high-dose group caused a 50% mortality rate, and even the low-dose group caused a 30% mortality rate. The chickens infected with the disease exhibited paleness in the cockscomb and stunted growth, as well as a compromised response to NDV and AIV-H9 inactivated vaccine. Furthermore, histological observation revealed an atrophy and degeneration of the thymus. To the best of our knowledge, this is the first instance of CIAV being isolated from artificially bred Aegypius monachus, implying that wild birds may be involved in the transmission and spread of CIAV. [ABSTRACT FROM AUTHOR]

With the popularity of social networking services, people are increasingly inclined to share their opinions and feelings on social networks, leading to the rapid increase in multimodal posts on various platforms. Therefore, multimodal sentiment analysis has become a crucial research field for exploring users' emotions. The complex and complementary interactions between images and text greatly heighten the difficulty of sentiment analysis. Previous works conducted rough fusion operations and ignored the study for fine fusion features for the sentiment task, which did not obtain sufficient interactive information for sentiment analysis. This paper proposes a global local fusion neural network (GLFN), which comprehensively considers global and local fusion features, aggregating these features to analyze user sentiment. The model first extracts overall fusion features by attention modules as modality-based global features. Then, coarse-to-fine fusion learning is applied to build local fusion features effectively. Specifically, the cross-modal module is used for rough fusion, and fine-grained fusion is applied to capture the interaction information between objects and words. Finally, we integrate all features to achieve a more reliable prediction. Extensive experimental results, comparisons, and visualization of public datasets demonstrate the effectiveness of the proposed model for multimodal sentiment classification. [ABSTRACT FROM AUTHOR]

The highly miniaturized and integrated electronic devices have demanded contactless current sensors with scale miniaturization, structure flexibility, self‐powering and heat resistance. Herein, a novel magnetoelectric current sensor (MCS) based on polylactide/VB2 composites and FeCoV is prepared using in‐situ coating and poling‐free methods. The use of polylactide/VB2 composite makes the MCS self‐powered and heat resistant, and the use of FeCoV makes the MCS highly flexible. The in‐situ coating and poling‐free methods endow the polylactide/VB2 composite and FeCoV good interfacial coupling. As a result, the MCS possesses good linearity over 0.999 and high sensitivity of 0.64 mV/A to the external current, even at a high temperature of 120 °C. Besides, the MCS presents high durability after 200 000 cycles. The MCS with mini size, self‐powering, heat resistance, high flexibility and durability has great potential in safety monitoring of electronic devices fields. [ABSTRACT FROM AUTHOR]

Team creative processes of generating and elaborating ideas tend to be laden with emotional expressions and communication. Yet, there is a noticeable lack of theory on how differences in teams' management and support of affect expressions influence their ability to produce creative outcomes. We investigate why and when team authentic affect climates, which encourage members to share and respond to authentic affect, generate greater creativity compared with more constrained affect climates where members suppress or hide their genuine feelings. We propose that authentic affect climate enhances team creativity through greater information elaboration by the team and that these informational and creative benefits are more likely in functionally diverse teams. Results from three complementary studies—one multisource field study of management teams and two experiments—provide support for our predictions. In our experiments, we also examine the theorized affective mechanisms and find that authentic affect climate increases information elaboration and creativity through members' affect expressions (Study 2) and empathic responses to each other's expressed affect (Studies 2 and 3). We discuss the implications of our findings for the team creativity, diversity, and affect literatures. [ABSTRACT FROM AUTHOR]