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Controlling reaction outcomes through external influences is a central goal in chemistry. Vibrational coupling between molecular vibrations and cavity modes is rapidly emerging as a distinct strategy compared with conventional thermochemical and photochemical methods; however, insight into the fundamental mechanisms remains limited. Here we investigate how vibrational weak and strong coupling in plasmonic nanocavities modifies the thermal dehydration of copper sulfate pentahydrate. We demonstrate that light–matter coupling reduces the onset temperature for dehydration by up to 14 °C, and we attribute this effect to enhanced radiative energy transport that is mediated by resonant electromagnetic modes, eliminating temperature gradients in the coupled system. Our findings provide direct evidence of localized energy transfer leading to modified chemical behaviour in specific regions of high optical density of states. This work establishes a mechanism for modifying thermally driven chemical processes using optical cavities, with implications for the development of catalytic systems that exploit these tailored interactions to achieve targeted reaction control.

Artificial intelligence (AI) literacy is a global strategic objective in education. However, little is known about how AI should be taught. In this paper, 46 studies in academic conferences and journals are reviewed to investigate pedagogical strategies, learning tools, assessment methods in AI literacy education in K-12 contexts, and students’ learning outcomes. The investigation reveals that the promotion of AI literacy education has seen significant progress in the past two decades. This highlights that intelligent agents, including Google’s Teachable Machine, Learning ML, and Machine Learning for Kids, are age-appropriate tools for AI literacy education in K-12 contexts. Kindergarten students can benefit from learning tools such as PopBots, while software devices, such as Scratch and Python, which help to develop the computational thinking of AI algorithms, can be introduced to both primary and secondary schools. The research shows that project-based, human–computer collaborative learning and play- and game-based approaches, with constructivist methodologies, have been applied frequently in AI literacy education. Cognitive, affective, and behavioral learning outcomes, course satisfaction and soft skills acquisition have been reported. The paper informs educators of appropriate learning tools, pedagogical strategies, assessment methodologies in AI literacy education, and students’ learning outcomes. Research implications and future research directions within the K-12 context are also discussed.

In this study, we devised an innovative cartridge-type modular photodetector designed to boost the photoresponse of two-dimensional (2D) materials by utilizing up-conversion particles (UCPs) in selective infrared (IR) regions beyond the bandgap. The merit of this structure is that the incident near-infrared or short wave infrared (SWIR) light, after passing through the 2D SnSe channel layer, is converted into visible light via the up-conversion effect and then reabsorbed by SnSe. To further optimize the photoresponse improvement in the SWIR region, we fine-tuned the dopant material and its concentration for the UCPs, attaining a 3.28-fold enhancement in the up-conversion efficiency. Using these approaches, we accomplished a 9.74-fold enhancement in the selective photoresponse within the SWIR region of 2D SnSe. We extended this approach to a 2D MoS2/UCP system to demonstrate the broad applicability of a cartridge-type modular photodetector design using 2D materials and UCPs for broadband photodetection. Additionally, we demonstrated a method for reusing a cartridge-type modular photodetector by recovering the UCP and quartz framework and removing the device components for repeated use.

Herein, we present a significant advancement in long-term cryopreservation techniques for microalgae Stichococcusspecies using a combination of linear polyglycerol (linPG) and dimethyl sulfoxide (DMSO). The technique was tested on three Stichococcusspecies: Stichococcus bacillaris, Stichococcus deasonii, and Stichococcus minor, which showed long-term viability and recovery rates superior to those when treated with a traditional cryoprotectant only. While DMSO alone enabled high cell recovery rates for all species after 1 week of cryopreservation, the rates for some of them dropped below 50% after 26 weeks of cryopreservation. Treating the cells with a combination of linPG and DMSO raised the recovery rates for all three Stichococcusspecies to above 92% after long-term cryopreservation. Our findings indicate that linPG in combination with DMSO offers a synergistic and effective solution for maintaining cell integrity and functionality during long-term cryopreservation of microalgae.

Low astringency in table grapes, a trait favored by consumers, is influenced by condensed tannins in the skins and seeds, regulated by complex enzymatic activities and gene expression during berry development. To facilitate the selection of less astringent table grape genotypes, this study investigated total polymeric tannin content (PTC) and transcriptomic changes in the berry skins of two cultivars, ‘Tano Red’ (non-astringent) and ‘Ruby Seedless’ (astringent), across four developmental stages. The methylcellulose precipitation assay showed consistently higher total PTC in ‘Ruby Seedless’, peaking at two weeks after full bloom (2 WAFB) and declining thereafter, a trend replicated in hybrid progeny and other cultivars. Transcriptome analysis revealed that tannin biosynthesis-related genes were most highly expressed at 2 WAFB in ‘Ruby Seedless’ compared to ‘Tano Red’, with these genes exhibiting strong co-expression network correlations. qPCR analysis further confirmed early and elevated expression of genes involved in flavan-3-ol monomer synthesis (ANR and LAR) and its galloylation (SCPL-AT) at 2 WAFB in astringent table grape cultivars. These findings demonstrate that tannin accumulation and the expression of tannin pathway genes in the berry skin peak during the early stages of berry development in astringent table grapes. The observed correlation between total PTC and the expression levels of ANR, LAR, and SCPL-AT suggests that combining total PTC measurements with the expression levels of these marker genes in the berry skin could serve as an effective tool for breeding less astringent grape cultivars.

AbstractThe term “fashion activism” is now used to describe various activist practices related to fashion, dress, or clothing-making, despite their distinct natures. Although there has been extensive discourse on fashion activism, these distinctions are largely overlooked. This terminological confusion, combined with the complex dynamics of diverse cases of fashion activism, has made the concept daunting for many fashion practitioners, both professionals and students, potentially discouraging their participation. Therefore, our goal is to gain a clearer understanding of fashion activism through a comprehensive typology. We examined a wide range of activist practices broadly labeled as fashion activism, along with the varying critiques surrounding them. From this research, we categorized these instances into four distinct types, primarily based on their motivations, objectives, and methods: “Activism Uses Dress,” “Fashion Uses Activism,” “Activism Uses Fashion,” and “Activism Against Fashion.” Ultimately, through this typology, we aim to critically analyze and articulate the distinct characteristics of these four types of fashion activism, including their interests in profit-making, the limitations of their methods, their stances on the existing fashion system, and their final objectives. Furthermore, this work emphasizes the need to acknowledge and bridge the gap between fashion activism theory and practice, particularly to foster more prolific and productive collaborations between the two fields. In this vein, we present this typology as a terminological and structural framework to make fashion activism more accessible, while also highlighting the potential of activist design projects to create counter-narratives and catalyze fundamental shifts in the status quo.

Despite their growing popularity, swarms of robots remain limited by the operating time of each individual. We present algorithms that allow a human to sculpt a swarm of robots into a shape that persists in space perpetually, independent of onboard energy constraints, such as batteries. Robots generate a path through a shape such that robots cycle in and out of the shape. Robots inside the shape react to human initiated changes and adapt the path through the shape accordingly. Robots outside the shape recharge and return to the shape so that the shape can persist indefinitely. The presented algorithms communicate shape changes throughout the swarm using message passing and robot motion. These algorithms enable the swarm to persist through any arbitrary changes to the shape. We describe these algorithms in detail and present their performance in simulation and on a swarm of mobile robots. The result is a swarm behavior more suitable for extended duration, dynamic shape-based tasks in applications, such as entertainment, agriculture, and emergency response.

[Display omitted] • p -Toluenesulfinate (PTSL) is used as a coating material to clog the pores of PI. • PTSL-coated PI separators exhibit improved thermal and physical stabilities. • PTSL coating layer can act as an artificial CEI layer at the NCM cathodes. • PTSL-coated PI consequently affords improved cycling retention over 100 cycles. Increasing the energy density of lithium-ion batteries enhances their applicability; however, ensuring their safety remains a critical issue in the energy society. Herein, we report the development of a lithium p -toluenesulfinate (PTSL)-coated polyimide (PI) separator with improved safety and electrochemical performance during cycling. It is anticipated that integrating PTSL particles into the PI separator will mitigate the risk of internal short circuits by clogging the porous structure of the PI separator and enhance the interfacial stability of the electrode materials. The PTSL is expected to act as an effective component of protective layers, physically separating the cathode from direct contact with electrolytes. The PTSL-embedded PI separator regulated the porous structure inherent to the PI separator, thereby enhancing its physical and thermal properties, such as improved wetting characteristics (evidenced by higher ionic conductivities and lithium-ion transference numbers) and thermal behaviors (reduced shrinkage and more stable thermal decomposition behaviors). During cycling, the cells with the PTSL-coated PI separator demonstrated increased cycling retention compared to the cells with graphite/NCM811 electrodes because the additional PTSL-based protective layers mitigated the electrolyte decomposition upon cycling. [ABSTRACT FROM AUTHOR]

[Display omitted] • SC-CO 2 extraction process with various cosolvents (NMP, DMAc, DMF, DMSO). • Phase behavior data in CO 2 + PVDF+cosolvent (NMP, DMAc, DMF, DMSO) system. • The highest extraction efficiency of 98.8% achieved with DMF cosolvent. • PVDF recovered with DMSO cosolvent had comparable cell performances to raw PVDF. In this study, a polyvinylidene fluoride (PVDF) binder material for secondary batteries was removed using a supercritical CO 2 extraction process instead of conventional extraction processes such as leaching and pyrolysis. To determine the optimal process conditions, the phase behavior of the binder in CO 2 was studied by measuring the pressure and temperature before the supercritical CO 2 extraction. To design an effective extraction process, the extraction time, temperature, and pressure were studied under various experimental conditions using a supercritical extraction system. Various organic cosolvents were used in the experiment to improve the extraction efficiency. According to the experimental result, the optimal extraction conditions were determined to 353.2 K, 10 MPa, and 20 min with dimethylformamide (DMF) cosolvent. Under these process conditions, the removal rate of the binder was 98.8 %. However, there was a significant difference in cell performance such as initial discharge capacity and cycling stability depending on the extraction solvent. Specifically, cycling stability improved in the order of using DMF, NMP, DMSO, and DMAc. The extracted binder material was analyzed by differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscope (SEM) to compare the raw and processed materials and evaluate the reusability of the binder material. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) literacy education for young students is gaining traction among researchers and educators. Researchers are developing courses and attempting to teach AI literacy to younger students, using age‐appropriate AI educational learning tools. Although teachers play a crucial role in AI literacy education, their perceptions and attitudes have received little attention. This study explores the perceptions of 60 teachers regarding the use of AI educational learning tools, and examines the factors influencing their attitudes in relation to implementing AI literacy education. The technological acceptance model and the technological, pedagogical, and content knowledge (CK) (TPACK) framework inform the research design, and a mixed method, combining the statistical package for Social Science and thematic analysis, is employed for data analysis. The study reveals that teachers have positive perceptions regarding the usefulness and ease of use of AI educational learning tools in their AI literacy teaching. This paper also reveals that teachers embrace an arts‐based approach to teaching AI literacy. The qualitative data reveal that teachers face challenges such as insufficient CK and experience with AI; and knowledge of TPACK. The five factors affecting their acceptance of AI educational learning tools are: (a) teachers' perceptions of their AI CK and experience in teaching AI literacy (technological content knowledge); (b) technical challenges and stakeholder acceptance; (c) the attributes of AI educational learning tools; (d) school infrastructure and budget constraints; and (e) potential for distraction and negative emotional responses. This study offers insights for policymakers regarding professional development initiatives and technical support mechanisms, thereby facilitating more effective AI literacy implementation.

ABSTRACTIntroductionTargeted protein degradation (TPD) has emerged as an innovative therapeutic strategy through selective degradation of specific proteins by harnessing the cellular ubiquitin-proteasome system (UPS), which involves over 600 E3 ubiquitin ligases. Recent proteome profiling reported tumor-specific E3 ligases in human. Development of those tumor-specific E3 ligase ligands would provide a solution for tumor-specific TPD for effective cancer treatment.Areas coveredThis review provides a comprehensive list of E3 ligases found only in specific types of tumor from public databases and highlights examples of their ligands discovered through fragment-based approaches. It details their discovery process and potential applications for precise TPD and effective cancer treatments.Expert opinionCurrent TPD strategies using proteolysis-targeting chimeras (PROTACs) primarily utilize general E3 ligases, such as CRBN and VHL. Since these E3 ligases demonstrate effective protein degradation activity in most human cell types, CRBN and VHL-based PROTACs can exhibit undesired TPD in off-target tissues, which often leads to the side effects. Therefore, developing tumor-specific E3 ligase ligands can be crucial for effective cancer treatments. Fragment-based ligand discovery (FBLD) approaches would accelerate the identification of these tumor-specific E3 ligase ligands and associated PROTACs, thereby advancing the field of targeted cancer therapies.

•The CCL2/CCR2 axis is elevated by MYC and BCL2 via nuclear factor κB p65 in DE-DLBCL.•CCL2/CCR2 axis promotes M2 polarization of macrophage and immunosuppressive environment, being a potential therapeutic target in DE-DLBCL.

The metabolic profile of dendritic cells (DCs) shapes their phenotype and functions. The carboxylesterase 1 (CES1) enzyme is highly expressed in mononuclear myeloid cells; however, its exact role in DCs is elusive. We used a CES1 inhibitor (WWL113) and genetic overexpression to explore the role of CES1 in DC differentiation in inflammatory models. CES1expression was analyzed during CD14+monocytes differentiation to DCs (MoDCs) using quantitative polymerase chain reaction. A CES1 inhibitor (WWL113) was applied during MoDC differentiation. Surface markers, secreted cytokines, lactic acid production, and phagocytic and T cell polarization capacity were analyzed. The transcriptomic and metabolic profiles were assessed with RNA sequencing and mass spectrometry, respectively. Cellular respiration was assessed using seahorse respirometry. Transgenic mice were used to assess the effect of CES1 overexpression in DCs in inflammatory models. CES1expression peaked early during MoDC differentiation. Pharmacological inhibition of CES1 led to higher expression of CD209, CD86 and MHCII. WWL113 treated MoDCs secreted higher quantities of interleukin (IL)-6, IL-8, tumor necrosis factor, and IL-10 and demonstrated stronger phagocytic ability and a higher capacity to polarize T helper 17 differentiation in an autologous DC-T cell coculture model. Transcriptomic profiling revealed enrichment of multiple inflammatory and metabolic pathways. Functional metabolic analysis showed impaired maximal mitochondrial respiration capacity, increased lactate production, and decreased intracellular amino acids and tricarboxylic acid cycle intermediates. Transgenic human CES1overexpression in murine DCs generated a less inflammatory phenotype and increased resistance to T cell–mediated colitis. In conclusion, CES1 inhibition directs DC differentiation toward a more inflammatory phenotype that shows a stronger phagocytic capacity and supports T helper 17 skewing. This is associated with a disrupted mitochondrial respiration and amino acid depletion.Blocking carboxylesterase 1 induces dendritic cells to adopt a more inflammatory phenotype, with concurrent metabolic adaptations. Conversely, carboxylesterase 1 overexpression in dendritic cells results in a less inflammatory profile both in vitro and in vivo.

This work examines the effects of temperature (100–150 °C), pressure (1–25 bar), and UV illumination on gas-phase photocatalytic CO2methanation over Ru/TiO2. Irradiating the catalyst enables an ∼20% decrease in operating pressure to maintain the same production rate. Furthermore, the relative light enhancement is greater at 100 °C than 150 °C─a phenomenon attributed to increased carrier recombination rates at higher temperatures. Arrhenius experiments indicate that the global activation energy (Ea) of the reaction is similar in the dark and light, suggesting that rate enhancements are determined by changes in surface coverage. To test this hypothesis, the CO2reduction mechanism is probed using in situdiffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). The spectra show an increase in the relative surface coverage of the intermediate formyl group under irradiation. These findings illustrate that, within the experimental conditions explored in this study, the photoexcitation of charge carriers in the semiconductor primarily influences the surface coverage of intermediates to drive enhanced methane formation at low temperatures.

Modern graphics processing units (GPUs) provide an unprecedented level of computing power. In this study, we present a high-performance, multi-GPU implementation of the analytical nuclear gradient for Kohn–Sham time-dependent density functional theory (TDDFT), employing the Tamm–Dancoff approximation (TDA) and Gaussian-type atomic orbitals as basis functions. We discuss GPU-efficient algorithms for the derivatives of electron repulsion integrals and exchange–correlation functionals within the range-separated scheme. As an illustrative example, we calculate the TDA-TDDFT gradient of the S1state of a full-scale green fluorescent protein with explicit water solvent molecules, totaling 4353 atoms, at the ωB97X/def2-SVP level of theory. Our algorithm demonstrates favorable parallel efficiencies on a high-speed distributed system equipped with 256 Nvidia A100 GPUs, achieving >70% with up to 64 GPUs and 31% with 256 GPUs, effectively leveraging the capabilities of modern high-performance computing systems.

Successful integration of point-of-care testing (POCT) into clinical settings requires improved assay sensitivity and precision to match laboratory standards. Here, we show how innovations in amplified biosensing, imaging, and data processing, coupled with deep learning, can help improve POCT. To demonstrate the performance of our approach, we present a rapid and cost-effective paper-based high-sensitivity vertical flow assay (hs-VFA) for quantitative measurement of cardiac troponin I (cTnI), a biomarker widely used for measuring acute cardiac damage and assessing cardiovascular risk. The hs-VFA includes a colorimetric paper-based sensor, a portable reader with time-lapse imaging, and computational algorithms for digital assay validation and outlier detection. Operating at the level of a rapid at-home test, the hs-VFA enabled the accurate quantification of cTnI using 50 μL of serum within 15 min per test and achieved a detection limit of 0.2 pg/mL, enabled by gold ion amplification chemistry and time-lapse imaging. It also achieved high precision with a coefficient of variation of <7% and a very large dynamic range, covering cTnI concentrations over 6 orders of magnitude, up to 100 ng/mL, satisfying clinical requirements. In blinded testing, this computational hs-VFA platform accurately quantified cTnI levels in patient samples and showed a strong correlation with the ground truth values obtained by a benchtop clinical analyzer. This nanoparticle amplification-based computational hs-VFA platform can democratize access to high-sensitivity point-of-care diagnostics and provide a cost-effective alternative to laboratory-based biomarker testing.

ABSTRACTThis study investigated whether mobile payment (MP) adopters in China extend their MP usage during their travel abroad, through the lens of continuity theory. The findings from in-depth interviews articulated six major concerns while using MP at home, namely perceived risks, costs, incompatibility, complexity, customer support, and social influence. Three major concerns for not using MP when travelling abroad include perceived security risk, costs, and incompatibility. Discontinuity of usage include past experiences and concerns about using MP in the home country, together with their negative evaluation of the MP service environment of the travel destinations. This study answers why some Chinese tourists abandon MP when they travel. Practical implications are offered to service providers to enhance users’ experiences.

Facilitated transport membranes provide a low-cost means of separating hydrocarbon mixtures. However, the application of such membranes is currently limited to gas-phase mixtures. In this study, a pervaporation membrane that can separate high concentrations of linear alpha olefins (e.g., 1-hexene and 1-octene) from liquid-phase hydrocarbon mixtures was developed. The pervaporation membrane was fabricated by coating a known olefin gas separation membrane material, poly(vinylpyrrolidone), onto a microporous support. Silver nanoparticles (Ag NPs) were incorporated into the polymer matrix and activated by the electron-accepting polarizer 7,7,8,8-tetracyanoquinodimethane to induce a partial positive charge on their surface. They acted as olefin carriers for facilitated transport, resulting in the extremely high pervaporative separation of a 1-hexene/n-hexane mixture over a long period. A 1-hexene concentration of more than 99% in the permeate was achieved at a feed concentration of 25%, resulting in a separation factor higher than 100 under stable operation for at least 100 h. Additionally, when the permeate pressure increased to 500 mbar, the 1-hexene flux sharply increased because of facilitated transport by the carrier action of the surface-charged Ag NPs, whereas the n-hexane flux remained nearly unchanged. These results demonstrate that facilitated transport membranes are highly effective in the pervaporative separation of liquid-phase mixtures and thus may provide a future direction for the development of high-performance membrane materials.

This paper introduces a media service model that exploits artificial intelligence (AI) video generators at the receive end. This proposal deviates from the traditional multimedia ecosystem, completely relying on in-house production, by shifting part of the content creation onto the receiver. We bring a semantic process into the framework, allowing the distribution network to provide service elements that prompt the content generator rather than distributing encoded data of fully finished programs. The service elements include fine-tailored text descriptions, lightweight image data of some objects, or application programming interfaces, comprehensively referred to as semantic sources, and the user terminal translates the received semantic data into video frames. Empowered by the random nature of generative AI, users can experience super-personalized services accordingly. The proposed idea incorporates situations in which the user receives different service providers’ element packages, either in a sequence over time or multiple packages at the same time. Given promised in-context coherence and content integrity, the combinatory dynamics will amplify the service diversity, allowing the users to always chance upon new experiences. This work particularly aims at short-form videos and advertisements, which the users would easily feel fatigued by seeing the same frame sequence every time. In those use cases, the content provider’s role will be recast as scripting semantic sources, transformed from a thorough producer. Overall, this work explores a new form of media ecosystem facilitated by receiver-embedded generative models, featuring both random content dynamics and enhanced delivery efficiency simultaneously.

Visual signals that integrate situation awareness (SA) information can improve drivers’ performance when assuming control of a partially automated vehicle from a non-driving task. By incorporating information that follows the levels of model of SA, these signals enable drivers to more quickly attain higher levels of SA, potentially bypassing traditional sequential processing stages. We evaluated the effectiveness of such SA-enhanced signals (displayed in the instrument cluster) in a simulated driving study by measuring takeover times and collision occurrences. The results indicate that incorporating SA information about the environment significantly reduces the time needed for drivers to take control of the vehicle and results in fewer collisions. Considering these performance differences suggests insights on optimizing visual cues to quickly restore SA among drivers as they transition from non-driving activities to manual control in partially automated vehicles.

The clinical course of nontuberculous mycobacterial pulmonary disease (NTM-PD) is varied, and a watchful waiting management strategy is appropriate for a subset of patients. Understanding disease progression and risk factors for progression is essential for deciding on an appropriate follow-up strategy.

In the aftermath of the COVID-19 pandemic, opportunities to modulate biological pathways common to the lifecycles of viruses need to be carefully considered. N-linked glycosylation in humans is mediated exclusively by the oligosaccharyltransferase complex and is frequently hijacked by viruses to facilitate infection. As such, STT3A/B, the catalytic domain of the OST complex, became an intriguing drug target with broad-spectrum antiviral potential. However, due to the critical role N-linked glycosylation plays in a number of fundamental human processes, the toxicological ramifications of STT3A/B inhibition required attention commensurate to that given to antiviral efficacy. Herein, we describe how known STT3A/B inhibitor NGI-1 inspired the discovery of superior tool compounds which were evaluated in in vitroefficacy and translational safety (e.g., CNS, cardiovascular, liver) studies. The described learnings will appeal to those interested in the therapeutic utility of modulating N-linked glycosylation as well as the broader scientific community.

Using scanning tunneling microscopy (STM), we investigate the spatial distribution of the bridging hydroxyl (OHb) bound excess electrons on the rutile TiO2(110) surface and its temperature dependence. By performing simultaneously recorded empty and filled state imaging on single OHbs at different temperatures in STM, we determine that the spatial distribution of the OHbbound excess electrons retains a symmetric four-lobe structure around the OHbat both 78 and 7 K. This indicates that OHbs are much weaker charge traps compared to bridging O vacancies (Ob-vac). In addition, by sequentially removing the capping H of each OHbusing voltage pulses, we find that the annihilation of each OHbis accompanied by the disappearance of some lobes in the filled state STM, thus verifying the direct correlation between OHbs and their excess electrons.

Purpose: Maintaining hemodynamic stability during cardiac ablation under general anesthesia is challenging. Remimazolam, a novel ultrashort-acting benzodiazepine, is characterized by maintaining comparatively stable blood pressure and does not influence the cardiac conduction system, which renders it a reasonable choice for general anesthesia for cardiac ablation. We aimed to evaluate whether remimazolam is associated with a decreased incidence of intraoperative hypotension compared with desflurane. Methods: In this single-centre, parallel-group, prospective, single-blind, randomized clinical trial, we randomized patients (1:1) into a remimazolam group (remimazolam-based total intravenous anesthesia) or desflurane group (propofol-induced and desflurane-maintained inhalational anesthesia) during cardiac ablation procedures for arrhythmia. The primary outcome was the incidence of intraoperative hypotensive events, defined as mean arterial pressure of &lt; 60 mm Hg at any period. Results: Overall, we enrolled 96 patients between 2 August 2022 and 19 May 2023 (47 and 49 patients in the remimazolam and desflurane groups, respectively). The remimazolam group showed a significantly lower incidence of hypotensive events (14/47, 30%) than the desflurane group (29/49, 59%; relative risk [RR], 0.5; 95% confidence interval [CI], 0.31 to 0.83; P= 0.004). Remimazolam was associated with a lower requirement for bolus or continuous vasopressor infusion than desflurane was (23/47, 49% vs43/49, 88%; RR, 0.56; 95% CI, 0.41 to 0.76; P&lt; 0.001). No between-group differences existed in the incidence of perioperative complications such as nausea, vomiting, oxygen desaturation, delayed emergence, or pain. Conclusions: Remimazolam was a viable option for general anesthesia for cardiac ablation. Remimazolam-based total intravenous anesthesia was associated with significantly fewer hypotensive events and vasopressor requirements than desflurane-based inhalational anesthesia was, without significantly more complications. Study registration: ClinicalTrials.gov (NCT05486377); first submitted 1 August 2022.

Understanding the dynamics of “hot”, highly energetic electrons resulting from nonradiative plasmon decay is crucial for optimizing applications in photocatalysis and energy conversion. This study presents an analysis of electron kinetics within plasmonic metals, focusing on the steady-state behavior during continuous-wave (CW) illumination. Using an inelastic spectroscopy technique, we quantify the temperature and lifetimes of distinct carrier populations during excitation. A significant finding is the monotonic increase in hot electron lifetime with decreases in electronic temperature. We also observe a 1.22× increase in hot electron temperature during intraband excitation compared to interband excitation and a corresponding 2.34× increase in carrier lifetime. The shorter lifetimes during interband excitation are hypothesized to result from direct recombination of nonthermal holes and hot electrons, highlighting steady-state kinetics. Our results help bridge the knowledge gap between ultrafast and steady-state spectroscopies, offering critical insights for optimizing plasmonic applications.