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To any projective pair (X , B) equipped with an ample ℚ -line bundle L (or even any ample numerical class), we attach a new invariant β ⁢ (μ) ∈ ℝ , defined on convex combinations μ of divisorial valuations on X, viewed as point masses on the Berkovich analytification of X. The construction is based on non-Archimedean pluripotential theory, and extends the Dervan–Legendre invariant for a single valuation – itself specializing to Li and Fujita's valuative invariant in the Fano case, which detects K-stability. Using our β-invariant, we define divisorial (semi)stability, and show that divisorial semistability implies (X , B) is sublc (i.e. its log discrepancy function is non-negative), and that divisorial stability is an open condition with respect to the polarization L. We also show that divisorial stability implies uniform K-stability in the usual sense of (ample) test configurations, and that it is equivalent to uniform K-stability with respect to all norms/filtrations on the section ring of (X , L) , as considered by Chi Li. [ABSTRACT FROM AUTHOR]

Purpose This study aimed to evaluate the ability of ultrafast power Doppler (PD) to assess disease activity in rheumatoid arthritis (RA) by examining the correlations between variables from ultrafast PD perfusion imaging and clinical measures of disease activity. Methods Thirty-three RA patients underwent clinical assessments of disease activity and ultrasound scans of bilateral wrists using both ultrafast and conventional PD systems. A spatial singular value decomposition filter was applied to the ultrafast PD imaging. Singular vectors representing perfusion and fast flows were selected to produce perfusion images. All images were quantitatively analyzed with computer assistance and scored semiquantitatively (0-3) by a physician for synovial vascularity. The Pearson correlation coefficients between image variables and clinical indices were calculated. Results The correlation coefficients ranged from weakly to moderately positive between ultrafast PD variables and clinical indices (r=0.221-0.374, all P

Abstract Understanding and controlling the ground stress in deep coalfield mining is crucial for ensuring mine safety and efficiency. This study aims to address two unresolved scientific issues in ground stress research: the selection of optimal excavation plans and the large-scale rapid acquisition of ground stress data. A novel computational model is proposed for key rock layer control under different crustal stress conditions. The model considers the complexity and uncertainty of ground stress distribution by simplifying the key rock strata into a fixed-fixed beam model and calculating their safety through mechanical methods. Introducing an innovative approach for acquiring large-scale stress fields using GPS data. By inverting large-scale strain fields in the coalfield area, combined with World Stress Map (WSM) and measured data, accurate stress fields are obtained. The proposed optimal excavation plan can be applied to various coalfield locations worldwide, providing a scientific basis for safe and efficient mining operations. Additionally, the innovative use of GPS data in obtaining large-scale stress fields offers a valuable tool for assessing ground stress variation.

Overheating and the resultant tube failures of boiler high temperature heating surfaces such as waterwall is one of the sore major problems affecting the safe operation of coal-fired power generating units. Boiler tube overheating generally occurs at some localized areas of boiler heating surfaces. To alleviate tube overheating and avoid the resultant tube failures, it’s necessary to monitor the tube temperature distribution in real-time to make preventive boiler operation adjustment. Due to the limitation of measurement method and the huge time cost of numerical method, currently there are still lack of methods that can realize the real-time prediction of waterwall tube temperature distribution during boiler operation. Therefore, this paper integrated the coupled heat transfer model with neural network and established a typical database of a 350 MW supercritical boiler using the coupled model, which contains 220 different typical boiler operating cases generated by adjusting 46 key operating parameters. Then, 4 400 expansion cases were derived at extremely time cost by the quick expansion method proposed in this paper. The deep neural network model was then constructed with 46 boiler operating parameters and waterwall coordinates as the model input and the tube temperature at the corresponding locations as the output. The DNN model was trained based on the comprehensive database containing 220 typical cases and 4 400 expansion cases. The MSE of the DNN model on validation set was only 0.005 3, the AUC5 was 0.988 and the calculation time was within 0.1 s. It illustrates that the data-driven model realized the real-time prediction of the waterwall tube temperature distribution over the entire boiler operating conditions by means of generalizing the numerical simulation results of finite cases. In addition, a quick database expansion method was proposed to address the problem that the heat transfer deterioration is difficult to be accurately predicted due to the insufficient data of the heat deterioration, and the prediction accuracy of the heat deterioration problem was significantly improved. Both the accuracy and the response speed of the model meet the demand of coal-fired plants for a real-time monitoring of tube temperature distribution.

Abstract Van der Waals integration of freestanding perovskite-oxide membranes with two-dimensional semiconductors has emerged as a promising strategy for developing high-performance electronics, such as field-effect transistors. In these innovative field-effect transistors, the oxide membranes have primarily functioned as dielectric layers, yet their great potential for structural tunability remains largely untapped. Free of epitaxial constraints by the substrate, these freestanding membranes exhibit remarkable structural tunability, providing a unique material system to achieve huge strain gradients and pronounced flexoelectric effects. Here, by harnessing the excellent structural tunability of PbTiO3 membranes and modulating the underlying substrate’s elasticity, we demonstrate the tip-pressure-induced polarization switching with an ultralow pressure (down to 0.06 GPa). Moreover, as an application demonstration, we develop a prototype non-volatile ferroelectric field-effect transistor integrated on silicon that can be operated mechanically and electrically. Our findings underscore the great potential of oxide membranes for utilization in advanced non-volatile electronics and highly sensitive pressure sensors.

Abstract Objectives This study aimed to establish the exposure-lag-response effect between daily maximum temperature and stroke-related emergency department visits and to project heat-induced stroke impacts under global warming levels (GWL) of 2 °C and 4 °C. Methods Stroke-related emergency department visits in Taiwan from 2001 to 2020 were identified using the National Health Insurance Research Database (NHIRD). The study population consisted of 1,100,074 initial stroke cases matched with 2,200,148 non-stroke controls. We employed Distributed Lag Nonlinear Models (DLNM) in a case-crossover study to investigate the association between temperature and stroke. Generalized Estimating Equations (GEE) models with a Poisson function were used to correlate high-temperature exposure with annual stroke incidence rates. Projections were made under two global warming scenarios, GWL 2.0 °C and 4.0 °C, using Coupled General Circulation Model (GCMs). Baseline data from 1995 to 2014 were transformed for spatial distribution at the township level. Geographic Information System (GIS) spatial analysis was performed using Quantum GIS 3.2.0 software. Results DLNM exposure-lag-response effect revealed that daily maximum temperature exceeding 34 °C significantly increased the risk of stroke-related emergency department visits, particularly for ischemic stroke. Under the 2 °C GWL scenario, the frequency of days with temperatures surpassing 34 °C is projected to rise substantially by the median year of 2042, with a further increase to 92.6 ± 18.0 days/year by 2065 under the 4 °C GWL scenario. Ischemic stroke showed the highest increase in temperature-related incidence rates, notably rising from 7.80% under the GWL 2 °C to 36.06% under the GWL 4 °C. Specifically, the annual temperature-related incidence rate for ischemic stroke is expected to increase significantly by 2065. Regions such as Taichung, Hsinchu, Yilan, and Taitung demonstrated pronounced changes in heat-related ischemic stroke incidence under the GWL 4 °C. Conclusions The findings emphasize the importance of addressing temperature-related stroke risks, particularly in regions projected to experience significant temperature increases. Effective mitigation strategies are crucial to reduce the impact of rising temperatures on stroke incidence and safeguard public health.

Abstract Background The stiffness of the tumor microenvironment (TME) directly influences cellular behaviors. Radiotherapy (RT) is a common treatment for solid tumors, but the TME can impact its efficacy. In the case of liver cancer, clinical observations have shown that tumors within a cirrhotic, stiffer background respond less to RT, suggesting that the extracellular matrix (ECM) stiffness plays a critical role in the development of radioresistance. Methods This study explored the effects of ECM stiffness and the inhibition of lysyl oxidase (LOX) isoenzymes on the radiation response of liver cancer in a millimeter-sized three-dimensional (3D) culture. We constructed a cube-shaped ECM-based millimeter-sized hydrogel containing Huh7 human liver cancer cells. By modulating the collagen concentration, we produced two groups of samples with different ECM stiffnesses to mimic the clinical scenarios of normal and cirrhotic livers. We used a single-transducer system for shear-wave-based elasticity measurement, to derive Young’s modulus of the 3D cell culture to investigate how the ECM stiffness affects radiosensitivity. This is the first demonstration of a workflow for assessing radiation-induced response in a millimeter-sized 3D culture. Results Increased ECM stiffness was associated with a decreased radiation response. Moreover, sonoporation-assisted LOX inhibition with BAPN (β-aminopropionitrile monofumarate) significantly decreased the initial ECM stiffness and increased RT-induced cell death. Inhibition of LOX was particularly effective in reducing ECM stiffness in stiffer matrices. Combining LOX inhibition with RT markedly increased radiation-induced DNA damage in cirrhotic liver cancer cells, enhancing their response to radiation. Furthermore, LOX inhibition can be combined with sonoporation to overcome stiffness-related radioresistance, potentially leading to better treatment outcomes for patients with liver cancer. Conclusions The findings underscore the significant influence of ECM stiffness on liver cancer’s response to radiation. Sonoporation-aided LOX inhibition emerges as a promising strategy to mitigate stiffness-related resistance, offering potential improvements in liver cancer treatment outcomes.

Mentre imperversa la guerra in Ucraina, il personale di soccorso di tutta Europa lavora per sostenere i milioni di profughi costretti ad abbandonare le proprie case. Eventi così stressanti e continuativi richiedono risposte utili a prevenire e promuovere la salute emotiva di tutte le vittime. In tale ambito l’EMDR risulta essere la terapia elettiva per il trattamento e la rielaborazione delle esperienze traumatiche vissute sia dai rifugiati sia da chi si occupa di loro. Nell’articolo l’autore, dopo una breve introduzione teorica circa le fasi del trauma e il processo del lutto, illustrerà le modalità di intervento di primo soccorso con EMDR più efficaci per sostenere i rifugiati e chi si occupa di loro. In questo tipo di emergenze infatti, data la continua sollecitazione cui sono sottoposti, i soccorritori si trovano a rischio di sviluppare una traumatizzazione vicaria. È dunque fondamentale pensare ad un intervento di supporto mirato anche per loro al fine di aumentare la resilienza. Mentre imperversa la guerra in Ucraina, il personale di soccorso di tutta Europa lavora per sostenere i milioni di profughi costretti ad abbandonare le proprie case. Eventi così stressanti e continuativi richiedono risposte utili a prevenire e promuovere la salute emotiva di tutte le vittime. In tale ambito l’EMDR risulta essere la terapia elettiva per il trattamento e la rielaborazione delle esperienze traumatiche vissute sia dai rifugiati sia da chi si occupa di loro. Nell’articolo l’autore, dopo una breve introduzione teorica circa le fasi del trauma e il processo del lutto, illustrerà le modalità di intervento di primo soccorso con EMDR più efficaci per sostenere i rifugiati e chi si occupa di loro. In questo tipo di emergenze infatti, data la continua sollecitazione cui sono sottoposti, i soccorritori si trovano a rischio di sviluppare una traumatizzazione vicaria. È dunque fondamentale pensare ad un intervento di supporto mirato anche per loro al fine di aumentare la resilienza. [ABSTRACT FROM AUTHOR]

Background: Real-world vaccine effectiveness following the third dose of vaccination against SARS-CoV-2 remains less investigated among people with HIV (PWH). Methods: PWH receiving the third dose of BNT162b2 and mRNA-1273 (either 50- or 100-μg) were enrolled. Participants were followed for 180 days until the fourth dose of COVID-19 vaccination, SARS-CoV-2 infection, seroconversion of anti-nucleocapsid IgG, death, or loss to follow-up. Anti-spike IgG was determined every 1–3 months. Results: Of 1427 participants undergoing the third-dose COVID-19 vaccination, 632 (44.3%) received 100-μg mRNA-1273, 467 (32.8%) 50-μg mRNA-1273, and 328 (23.0%) BNT162b2 vaccine and the respective rate of SARS-CoV-2 infection or seroconversion of anti-nucleocapsid IgG was 246.1, 280.8 and 245.2 per 1000 person-months of follow-up (log-rank test, p = 0.28). Factors associated with achieving anti-S IgG titers >1047 BAU/mL included CD4 count 200 copies/mL (aOR, 0.27; 95% CI, 0.09–0.80), having achieved anti-spike IgG >141 BAU/mL within 3 months after primary vaccination (aOR, 3.69; 95% CI, 2.68–5.07), receiving BNT162b2 vaccine as the third dose (aOR, 0.20; 95% CI, 0.10–0.41; reference, 100-μg mRNA-1273), and having previously received two doses of mRNA vaccine in primary vaccination (aOR, 2.46; 95% CI, 1,75-3.45; reference, no exposure to mRNA vaccine). Conclusions: PWH receiving different types of the third dose of COVID-19 vaccine showed similar vaccine effectiveness against SARS-CoV-2 infection. An additional dose with 100-μg mRNA-1273 could generate a higher antibody response than with 50-μg mRNA-1273 and BNT162b2 vaccine.

Abstract Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, and the expression and function of an uncharacterized protein RNF214 in HCC are still unknown. Phase separation has recently been observed to participate in the progression of HCC. In this study, we investigated the expression, function, and phase separation of RNF214 in HCC. We found that RNF214 was highly expressed in HCC and associated with poor prognosis. RNF214 functioned as an oncogene to promote the proliferation, migration, and metastasis of HCC. Mechanically, RNF214 underwent phase separation, and the coiled-coil (CC) domain of RNF214 mediated its phase separation. Furthermore, the CC domain was necessary for the oncogenic function of RNF214 in HCC. Taken together, our data favored that phase separation of RNF214 promoted the progression of HCC. RNF214 may be a potential biomarker and therapeutic target for HCC.

Phenolic acid decarboxylase (PAD) (lyase, EC 4.1.1.102) catalyzes the conversion of phenolic acids such as coumaric acid, ferulic acid, caffeic acid, and glucosic acid that are widely distributed in plants into 4-vinyl derivatives. 4-Vinyl derivatives are not only high-grade fragrances, but also key precursors for the synthesis of other spices such as vanillin. Food spices are mainly chemically synthesized in the current market. By contrast, the biosynthesis method, which is characterized by single precursor substances, mild conditions and environmental friendliness, has broad application prospects, and biosynthesized spices are regarded as being equivalent to natural products. Therefore, using PAD for the biosynthesis of 4-vinyl derivatives is of great significance to supplementing the production pathway of this type of fragrance. In this article, PAD derived from microorganisms are summarized from five aspects: origins, molecular structure, catalytic mechanism and structure-function correlation, catalytic properties, and techniques to improve the catalytic efficiency.

Background: The RECOVERY trial demonstrated that the use of dexamethasone is associated with a 36% lower 28-day mortality in hospitalized patients with COVID-19 on invasive mechanical ventilation. Nevertheless, the optimal timing to start dexamethasone remains uncertain. Methods: We conducted a quasi-experimental study at National Taiwan University Hospital (Taipei, Taiwan) using propensity score matching to simulate a randomized controlled trial to receive or not to receive early dexamethasone (6 mg/day) during the first 7 days following the onset of symptoms. Treatment was standard protocol-based, except for the timing to start dexamethasone, which was left to physicians’ decision. The primary outcome is 28-day mortality. Secondary outcomes include secondary infection within 60 days and fulfilling the criteria of de-isolation within 20 days. Results: A total of 377 patients with COVID-19 were enrolled. Early dexamethasone did not decrease 28-day mortality in all patients (adjusted odds ratio [aOR], 1.03; 95% confidence interval [CI], 0.97–1.10) or in patients who required O2 for severe/critical disease at admission (aOR, 1.05; 95%CI, 0.94–1.18); but is associated with a 24% increase in superinfection in all patients (aOR, 1.24; 95% CI, 1.12–1.37) and a 23% increase in superinfection in patients of O2 for several/critical disease at admission (aOR, 1.23; 95% CI, 1.02–1.47). Moreover, early dexamethasone is associated with a 42% increase in likelihood of delayed clearance of SARS-CoV-2 virus (adjusted hazard ratio, 1.42; 95% CI, 1.01–1.98). Conclusion: An early start of dexamethasone (within 7 days after the onset of symptoms) could be harmful to hospitalized patients with COVID-19.

Abstract Global modeling of aerosol‐particle number and size is important for understanding aerosol effects on Earth's climate and air quality. Fine‐resolution global models are desirable for representing nonlinear aerosol‐microphysical processes, their nonlinear interactions with dynamics and chemistry, and spatial heterogeneity. However, aerosol‐microphysical simulations are computationally demanding, which can limit the achievable global horizontal resolution. Here, we present the first coupling of the TwO‐Moment Aerosol Sectional (TOMAS) microphysics scheme with the High‐Performance configuration of the GEOS‐Chem model of atmospheric composition (GCHP), a coupling termed GCHP‐TOMAS. GCHP's architecture allows massively parallel GCHP‐TOMAS simulations including on the cloud, using hundreds of computing cores, faster runtimes, more memory, and finer global horizontal resolution (e.g., 25 km × 25 km, 7.8 × 105 model columns) versus the previous single‐node capability of GEOS‐Chem‐TOMAS (tens of cores, 200 km × 250 km, 1.3 × 104 model columns). GCHP‐TOMAS runtimes have near‐ideal scalability with computing‐core number. Simulated global‐mean number concentrations increase (dominated by free‐tropospheric over‐ocean sub‐10‐nm‐diameter particles) toward finer GCHP‐TOMAS horizontal resolution. Increasing the horizontal resolution from 200 km × 200–50 km × 50 km increases the global monthly mean free‐tropospheric total particle number by 18.5%, and over‐ocean sub‐10‐nm‐diameter particles by 39.8% at 4‐km altitude. With a cascade of contributing factors, free‐tropospheric particle‐precursor concentrations increase (32.6% at 4‐km altitude) with resolution, promoting new‐particle formation and growth that outweigh coagulation changes. These nonlinear effects have the potential to revise current understanding of processes controlling global aerosol number and aerosol impacts on Earth's climate and air quality.

Abstract Many chemical transport models treat mineral dust as spherical. Solar backscatter retrievals of trace gases (e.g., OMI and TROPOMI) implicitly treat mineral dust as spherical. The impact of the morphology of mineral dust particles is studied to assess its implications for global chemical transport model (GEOS‐Chem) simulations and solar backscatter trace gas retrievals at ultraviolet and visible (UV‐Vis) wavelengths. We investigate how the morphology of mineral dust particles affects the simulated dust aerosol optical depth; surface area, reaction, and diffusion parameters for heterogeneous chemistry; phase function, and scattering weights for air mass factor (AMF) calculations used in solar backscatter retrievals. We use a mixture of various aspect ratios of spheroids to model the dust optical properties and a combination of shape and porosity to model the surface area, reaction, and diffusion parameters. We find that assuming spherical particles can introduce size‐dependent and wavelength‐dependent errors of up to 14% in simulated dust extinction efficiency with corresponding error in simulated dust optical depth typically within 5%. We find that use of spheroids rather than spheres increases forward scattered radiance and decreases backward scattering that in turn decrease the sensitivity of solar backscatter retrievals of NO2 to aerosols by factors of 2.0–2.5. We develop and apply a theoretical framework based on porosity and surface fractal dimension with corresponding increase in the reactive uptake coefficient driven by increased surface area and species reactivity. Differences are large enough to warrant consideration of dust non‐sphericity for chemical transport models and UV‐Vis trace gas retrievals.

IntroductionPrimary dysmenorrhea (PDM), characterized by cyclic pain, may involve pain modulation within the reward system (RS). The Catechol-O-methyltransferase (COMT) Val158Met polymorphism, which significantly influences dopamine activity, is linked to the regulation of both acute and chronic pain. This study examines the differential neurodynamic modulation in the RS associated with COMT Val158Met polymorphisms during menstrual pain among PDM subjects.MethodNinety-one PDM subjects underwent resting-state fMRI during menstruation and were genotyped for COMT Val158Met polymorphisms. The amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) analyses were used to assess the RS response. Psychological evaluations included the McGill Pain Questionnaire, Pain Catastrophizing Scale, Beck Anxiety Inventory, and Beck Depression Inventory.ResultVal/Val homozygotes (n = 50) and Met carriers (n = 41) showed no significant differences in McGill Pain Questionnaire, Beck Anxiety Inventory, and Beck Depression Inventory. However, Met carriers exhibited lower scores on the Pain Catastrophizing Scale. Distinct FC patterns was observed between Val/Val homozygotes and Met carriers, specifically between the nucleus accumbens (NAc) and prefrontal cortex, NAc and inferior parietal lobe, ventral tegmental area (VTA) and prefrontal cortex, VTA and precentral gyrus, and VTA and superior parietal lobe. Only Met carriers showed significant correlations between ALFF and FC values of the NAc and VTA with pain-related metrics (McGill Pain Questionnaire and Pain Catastrophizing Scale scores). NAc ALFF and NAc-prefrontal cortex FC values positively correlated with pain-related metrics, while VTA ALFF and VTA-prefrontal cortex and VTA-superior parietal lobe FC values negatively correlated with pain-related metrics.DiscussionThis study reveals that the COMT Val158Met polymorphism results in genotype-specific functional changes in the brain’s RS during menstrual pain. In Met carriers, engagement of these regions is potentially linked to motivational reward-seeking and top-down modulation. This polymorphism likely influences the RS’s responses, significantly contributing to individual differences in pain regulation.

summary: Purpose: Stroke survivors and their informal family caregivers may share the impact of the disease, which may affect family functioning and quality of life (QoL) for both. This study compared the perceptions of stroke survivors and informal family caregivers regarding family functioning and QoL and examined the QoL of those reporting effective versus ineffective family functioning. Methods: A cross-sectional study design and convenience sampling were used. Stroke survivor–informal family caregiver dyads were recruited from a medical university hospital. We assessed participants’ demographic and clinical variables, including disease severity, family functioning, and QoL. Independent t-test, paired t-test, Wilcoxon signed-rank test, and Mann–Whitney U test were used to analyze the data. Results: Seventy-one stroke survivor–informal family caregiver dyads participated in the current study. Most stroke survivors and informal family caregivers reported effective family functioning, with no significant differences. However, significant differences existed in the seven domains (physical functioning, role-physical, bodily pain, general health, vitality, social functioning, and role-emotional) of QoL, except emotional health. Stroke survivors reporting ineffective family functioning had a significantly lower mental component summary score, unlike informal family caregivers. Conclusions: Our findings suggest that family functioning is crucial to ensure stroke survivors’ QoL, particularly regarding their mental health. Health professionals should prioritize mental health assessments and provide appropriate care interventions for stroke survivors in the first 1–6 months after stroke onset.

Abstract Non-Intrusive Load Monitoring (NILM) is a valuable technique for breaking down overall power consumption into the energy usage of individual appliances. Understanding power usage patterns through NILM plays an important role in reducing energy costs and achieving carbon reduction goals. However, privacy concerns often deter consumers from sharing their electricity consumption data. To address these privacy concerns, Federated Learning (FL) has been introduced in NILM, which enables the training of NILM models while keeping power consumers’ data locally. However, FL’s reliance on a single global model leads to poor performance on clients with unique power consumption patterns. In response to this challenge, we present a Personalized Federated Learning NILM algorithm (PerFedNILM), a practical personalized FL approach for NILM. PerFedNILM limits the local update bias across clients and trains personalized models for individual clients to improve load-monitoring performance. In addition, it mitigates the negative impact of client dropout, which is a common issue in practice. Our experiments on using real-world energy data demonstrate that PerFedNILM outperforms previous FL-based NILM methods, especially in client dropout scenarios.

Abstract Solid state single-photon sources with high brightness and long coherence time are promising qubit candidates for modern quantum technology. To prevent decoherence processes and preserve the integrity of the qubits, decoupling the emitters from their surrounding environment is essential. To this end, interfacing single photon emitters (SPEs) with high-finesse cavities is required, especially in the strong coupling regime, when the interaction between emitters can be mediated by cavity fields. However, achieving strong coupling at elevated temperatures is challenging due to competing incoherent processes. Here, we address this long-standing problem by using a quantum system, which comprises a class of SPEs in hexagonal boron nitride and a dielectric cavity based on bound states in the continuum (BIC). We experimentally demonstrate, at room temperature, strong coupling of the system with a large Rabi splitting of ~4 meV thanks to the combination of the narrow linewidth and large oscillator strength of the emitters and the efficient photon trapping of the BIC cavity. Our findings unveil opportunities to advance the fundamental understanding of quantum dynamical system in strong coupling regime and to realise scalable quantum devices capable of operating at room temperature.

Abstract Van der Waals (vdW) materials, including hexagonal boron nitride (hBN), are layered crystalline solids with appealing properties for investigating light-matter interactions at the nanoscale. hBN has emerged as a versatile building block for nanophotonic structures, and the recent identification of native optically addressable spin defects has opened up exciting possibilities in quantum technologies. However, these defects exhibit relatively low quantum efficiencies and a broad emission spectrum, limiting potential applications. Optical metasurfaces present a novel approach to boost light emission efficiency, offering remarkable control over light-matter coupling at the sub-wavelength regime. Here, we propose and realise a monolithic scalable integration between intrinsic spin defects in hBN metasurfaces and high quality (Q) factor resonances, exceeding 102, leveraging quasi-bound states in the continuum (qBICs). Coupling between defect ensembles and qBIC resonances delivers a 25-fold increase in photoluminescence intensity, accompanied by spectral narrowing to below 4 nm linewidth and increased narrowband spin-readout efficiency. Our findings demonstrate a new class of metasurfaces for spin-defect-based technologies and pave the way towards vdW-based nanophotonic devices with enhanced efficiency and sensitivity for quantum applications in imaging, sensing, and light emission.

Background: Our objective was to investigate the prevalence of plasmid-mediated quinolone resistance (PMQR) genes in fluoroquinolone-nonsusceptible Klebsiella pneumoniae (FQNSKP) in Taiwan, 1999–2022. Methods: A total of 938 FQNSKP isolates were identified from 1966 isolates. The presence of PMQR and virulence genes, antimicrobial susceptibility, capsular types, and PMQR-plasmid transferability were determined. Results: An increasing number of PMQR-containing FQNSKP isolates were observed over the study period. Our results showed that 69.0% (647 isolates) of FQNSKP isolates contained at least one PMQR gene, and 40.6%, 37.0%, and 33.9% of FQNSKP carried aac(6′)-Ib-cr, qnrB, and qnrS, respectively. None of FQNSKP carried qepA and qnrC. The most common combination of PMQR genes was aac(6′)-Ib-cr and qnrB (12.3%). The presence of PMQR genes is strongly related to resistance to aminoglycoside, cephalosporin, tetracycline, and sulfamethoxazole/trimethoprim in FQNSKP. The capsular serotype K64 is the most common serotype we tested in both the non-PMQR and PMQR FQNSKP isolates, while K20 showed a higher prevalence in PMQR isolates. The magA and peg-344 genes showed a significantly higher prevalence rate in non-PMQR isolates than in PMQR isolates. Eleven isolates that carried the PMQR and carbapenemase genes were identified; however, three successful transconjugants showed that the PMQR and carbapenemase genes were not located on the same plasmid. Conclusions: Our results indicated an increasing prevalence of PMQR genes, especially qnrB and qnrS, in FQNSKP in Taiwan. Moreover, the distribution of PMQR genes was associated with capsular serotypes and antimicrobial resistance gene and virulence gene distribution in FQNSKP.

Less research has been conducted on the association between camellia oil’s (CO) phenolic composition and antioxidant capability. In this study, the phenolic profile of CO and its connection to antioxidant capacity were examined utilizing a combination of widely-targeted phenolic metabolomics and multivariate statistical analysis. A total of 751 phenolics were discovered. The WGCNA was used to link phenols to antioxidants, yielding 161 antioxidant-related phenols from the blue module. In response to several antioxidant assays, 59 (FRAP), 59 (DPPH), and 53 (ABTS) phenolics were identified as differential phenolic markers (DPMs). Further stepwise multiple linear regression revealed six DPMs that substantially influenced the antioxidant capacities. Nine metabolic pathways and their associated network mechanisms for the most significant phenolics were developed. This study sheds light on the phenolic content of CO, elucidates their role in antioxidant activity, and lays the groundwork for improving extraction techniques and generating improved product.

As a type of transmission actuator commonly used in mechanical structures, high-speed rotary mechanisms are widely used in the machinery, energy, civil engineering, and military industries. The main working part of the mechanism is the end face, and the vibration characteristics of the end face directly affect the accuracy and completeness of the whole mechanism. In terms of performance, the end face vibration characteristics reflect the degree of change in the machine’s end face displacement. The traditional end face displacement test method uses a single contact sensor for measurement, but the degree of error in the system is large. It is also difficult to adapt this method to the current high-precision working conditions under the requirements for accurate vibration prediction and control technology. Therefore, this work proposes a test method based on multi-sensor acquisition and data fusion, using different sensors to form a sensor test network. It seeks to address the limitations of the conventional test method that relies on a single-frequency domain, using high-frequency domain impact signals, medium-frequency domain vibration signals, and low-frequency domain rotational speed signals for multi-sensor data fusion to achieve a complete high-speed rotating mechanism with a particular focus on full-area coverage. In order to better obtain the test data, the sensor layout network is optimized through the optimization design method, and the optimal sensor installation scheme is proposed. Finally, the data fusion algorithm and sensor layout scheme are experimentally verified with a typical high-speed rotating mechanism.

IntroductionPercussionists stand out for their expertise in rhythm, with the network for musical rhythm (NMR) serving a vital neurological function in their improvisation, which is deeply rooted in comprehensive musical knowledge. Our research examines the central representations of various improvisation tactics used by percussionists and investigates the interactions between the NMR and other relevant neural networks.MethodsTwenty-five percussionists participated in functional magnetic resonance imaging (fMRI) sessions, which included two cognitive strategies of improvisation. Structural improvisation (SIMP) emphasized rhythmic patterns, while free improvisation (FIMP) focused on musical spontaneity. Sight-reading scenario served as the reference condition. Paired t-tests were utilized for comparative analyses.ResultsThe findings revealed a dynamic interplay characterized by increased activity in the executive control network and NMR, along with decreased activity in the default mode network during SIMP. During FIMP, heightened activity was observed in the executive control network, NMR, limbic, and memory systems. In both SIMP vs. sight-reading and FIMP vs. sight-reading comparisons, the visual network’s activity decreased, a trend also observed in the comparative analysis of FIMP vs. SIMP.DiscussionIn SIMP, percussionists leverage external rhythmic signals, resulting in heightened NMR and ECN activity and reduced DMN activity. In contrast, FIMP is characterized by a rise in activity within the NMR, ECN, limbic system, memory system, and reward system, underscoring the vital roles of motivation and memory in the rapid production of spontaneous musical ideas within set frameworks. The diminished activity in the visual network during FIMP compared to SIMP suggests less reliance on visual stimuli in FIMP. These findings suggest that various improvisational tactics may engage different neural pathways.

Background: Long COVID, an emerging public health issue, is characterized by persistent symptoms following SARS-CoV-2 infection. This study aims to explore the relationship between post-COVID-19 symptomatology and patient distress employing Latent Class Analysis to uncover symptom co-occurrence patterns and their association with distress. Methods: A cross-sectional study was conducted using an online survey among 240 participants from a university and affiliated hospital of southern Taiwan. The survey quantified distress due to persistent symptoms and assessed the prevalence of Long COVID, symptom co-occurrence, and latent symptom classes. Latent Class Analysis (LCA) identified distinct symptom patterns, and multiple regression models evaluated associations between symptom patterns, distress, and demographic factors. Results: The study found that 80 % of participants experienced Long COVID, with symptoms persisting for over three months. Individuals with multiple COVID-19 infections showed a significant increase in general (β = 1.79), cardiovascular (β = 0.61), and neuropsychological symptoms (β = 2.18), and higher total distress scores (β = 6.35). Three distinct symptomatology classes were identified: ''Diverse'', ''Mild'', and ''Severe'' symptomatology. The ''Mild Symptomatology'' class was associated with lower distress (−10.61), while the ''Severe Symptomatology'' class showed a significantly higher distress due to symptoms (13.32). Conclusion: The study highlights the significant impact of Long COVID on individuals, with distinct patterns of symptomatology and associated distress. It emphasizes the cumulative effect of multiple COVID-19 infections on symptom severity and the importance of tailored care strategies.

Academic engagement in recent years has become the focus of determining student learning and achievement. However,despite this growing awareness that has revolutionized academic policies and educational approaches, literature on engagement in the academic context is still in its infancy. This study seeks to remedy this through the confirmation of the Utrecht Work Engagement Scale for Students' (UWES-S) promising psychometric properties and by providing empirical evidence on the relationship between academic engagement, personality traits, and social media addiction, a determinant that has yet to be explored. Our findings indicate that of the five personality traits analyzed, agreeableness had the strongest negative correlation with academic engagement, and perhaps equally as striking is the positive, albeit insignificant, association between social media and academic engagement. Furthermore, the most informative and least informative items for academic engagement were identified using IRT analysis. Finally, this study also addresses several gaps in the literature by determining that the one-factor construct of the UWES-S is an adequate measure of academic engagement compared to its three-factor counterpart and by demonstrating the measurement invariance of the UWES-S across gender, class year, and academic major in our sample of Taiwanese undergraduates., Author(s): Li-Chiu Chi [sup.1] , Tseng-Chung Tang [sup.2] , Eugene Tang [sup.3] Author Affiliations: (1) https://ror.org/00q523p52, grid.412054.6, 0000 0004 0639 3562, College of Applied Arts and Sciences, National Formosa University, [...]

Perovskite solar cells (PSCs) have garnered significant attention in the photovoltaic field owing to their exceptional photoelectric properties, including high light absorption, extensive carrier diffusion distance, and an adjustable band gap. Temperature is a crucial factor influencing both the preparation and performance of perovskite solar cells. The annealing temperature exerts a pronounced impact on the device structure, while the operational temperature influences carrier transport, perovskite band gap, and interface properties. This paper provides a comprehensive review of the influence of varied annealing temperatures on the hole transport layer, electron transport layer, and perovskite layer. Additionally, we present an overview of innovative annealing methods applied to perovskite materials. The effects of diverse working temperatures on the overall performance of perovskite cells are thoroughly examined and discussed in this review. In the end, different temperature conditions under ISOS testing conditions are summarized.

Background: Candidemia is associated with a high mortality rate. This study aimed to evaluate the clinical impact of a diagnostic intervention and antifungal stewardship in adults with candidemia, including effectiveness in facilitating appropriate antifungals and improving patient outcomes. Methods: A pre-post quasi-experimental study was conducted to analyze the impact of the integrated workflow of rapid species identification and antifungal stewardship intervention provided by infectious disease specialists for adults with candidemia at a medical center in southern Taiwan from March 1st, 2014 to February 29th, 2016. The primary endpoint was 30-day crude mortality, and secondary outcomes included the time to species identification, time to initial antifungal modification, and length of hospital stay. Results: Total 303 patients with candidemia were included, including 152 adults in the pre-intervention period (Mar. 1st, 2014–Feb. 28th, 2015; control group) and 151 in the intervention period (Mar. 1st, 2015–Feb. 29th, 2016; case group). Demographic and clinical characteristics of patients in two groups were similar. The case group had a shorter time to species identification (72 vs. 96 h, P