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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 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.

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.

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.

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.

Abstract Here we retrieve global daily 1 km gapless PM2.5 concentrations via machine learning and big data, revealing its spatiotemporal variability at an exceptionally detailed level everywhere every day from 2017 to 2022, valuable for air quality monitoring, climate change, and public health studies. We find that 96%, 82%, and 53% of Earth’s populated areas are exposed to unhealthy air for at least one day, one week, and one month in 2022, respectively. Strong disparities in exposure risks and duration are exhibited between developed and developing countries, urban and rural areas, and different parts of cities. Wave-like dramatic changes in air quality are clearly seen around the world before, during, and after the COVID-19 lockdowns, as is the mortality burden linked to fluctuating air pollution events. Encouragingly, only approximately one-third of all countries return to pre-pandemic pollution levels. Many nature-induced air pollution episodes are also revealed, such as biomass burning.

Background: Existing prognostic scoring systems for intensive care unit (ICU) trauma patients require extensive data collection. The Geriatric Trauma Outcome Score (GTOS), which is based on age, injury severity, and transfusion need, has been validated for predicting mortality in elderly patients with trauma; however, its utility in the general ICU trauma population remains unexplored. Methods: This retrospective study included 2952 adult ICU trauma patients admitted between 2016 and 2021. The GTOS was calculated as follows: age + (Injury Severity Score × 2.5) + 22 (if transfused within 24 h). The area under the receiver operating characteristic curve (AUROC) was used to assess GTOS’s ability to predict mortality. The optimal GTOS cutoff was determined using Youden’s index. Mortality rates were compared between the high and low GTOS groups, including a propensity score-matched analysis adjusted for baseline characteristics. Results: This study included 2952 ICU trauma patients, with an overall mortality rate of 11.0% (n = 325). GTOS demonstrated good predictive accuracy for mortality (AUROC 0.80). The optimal cutoff was 121.8 (sensitivity, 0.791; specificity, 0.685). Despite adjustments, patients with GTOS ≥ 121.8 had significantly higher mortality (17.4% vs. 6.2%, p < 0.001) and longer hospital stays (20.3 vs. 15.3 days, p < 0.001) compared to GTOS < 121.8. Conclusions: GTOS showed a reasonable ability to predict mortality in ICU trauma patients across all ages, although not as accurately as more complex ICU-specific models. With its simplicity, the GTOS may serve as a rapid screening tool for risk stratification in acute ICU trauma settings when combined with other data.

BackgroundPrevious studies have indicated a potential link between the gut microbiota and lymphoma. However, the exact causal interplay between the two remains an area of ambiguity.MethodsWe performed a two-sample Mendelian randomization (MR) analysis to elucidate the causal relationship between gut microbiota and five types of lymphoma. The research drew upon microbiome data from a research project of 14,306 participants and lymphoma data encompassing 324,650 cases. Single-nucleotide polymorphisms were meticulously chosen as instrumental variables according to multiple stringent criteria. Five MR methodologies, including the inverse variance weighted approach, were utilized to assess the direct causal impact between the microbial exposures and lymphoma outcomes. Moreover, sensitivity analyses were carried out to robustly scrutinize and validate the potential presence of heterogeneity and pleiotropy, thereby ensuring the reliability and accuracy.ResultsWe discerned 38 potential causal associations linking genetic predispositions within the gut microbiome to the development of lymphoma. A few of the more significant results are as follows: Genus Coprobacter (OR = 0.619, 95% CI 0.438–0.873, P = 0.006) demonstrated a potentially protective effect against Hodgkin’s lymphoma (HL). Genus Alistipes (OR = 0.473, 95% CI 0.278–0.807, P = 0.006) was a protective factor for diffuse large B-cell lymphoma. Genus Ruminococcaceae (OR = 0.541, 95% CI 0.341–0.857, P = 0.009) exhibited suggestive protective effects against follicular lymphoma. Genus LachnospiraceaeUCG001 (OR = 0.354, 95% CI 0.198–0.631, P = 0.0004) showed protective properties against T/NK cell lymphoma. The Q test indicated an absence of heterogeneity, and the MR-Egger test did not show significant horizontal polytropy. Furthermore, the leave-one-out analysis failed to identify any SNP that exerted a substantial influence on the overall results.ConclusionOur study elucidates a definitive causal link between gut microbiota and lymphoma development, pinpointing specific microbial taxa with potential causative roles in lymphomagenesis, as well as identifying probiotic candidates that may impact disease progression, which provide new ideas for possible therapeutic approaches to lymphoma and clues to the pathogenesis of lymphoma.

Abstract Ambient fine particulate matter (PM2.5) is the world’s leading environmental health risk factor. Quantification is needed of regional contributions to changes in global PM2.5 exposure. Here we interpret satellite-derived PM2.5 estimates over 1998-2019 and find a reversal of previous growth in global PM2.5 air pollution, which is quantitatively attributed to contributions from 13 regions. Global population-weighted (PW) PM2.5 exposure, related to both pollution levels and population size, increased from 1998 (28.3 μg/m3) to a peak in 2011 (38.9 μg/m3) and decreased steadily afterwards (34.7 μg/m3 in 2019). Post-2011 change was related to exposure reduction in China and slowed exposure growth in other regions (especially South Asia, the Middle East and Africa). The post-2011 exposure reduction contributes to stagnation of growth in global PM2.5-attributable mortality and increasing health benefits per µg/m3 marginal reduction in exposure, implying increasing urgency and benefits of PM2.5 mitigation with aging population and cleaner air.

Abstract A see-through augmented reality prototype has been developed based on an ultrathin nanoimprint metalens array, opening up a full-colour, video-rate, and low-cost 3D near-eye display.

Abstract KD is an acute systemic vasculitis that most commonly affects children under 5 years old. Sepsis is a systemic inflammatory response syndrome caused by infection. The main clinical manifestations of both are fever, and laboratory tests include elevated WBC count, C-reactive protein, and procalcitonin. However, the two treatments are very different. Therefore, it is necessary to establish a dynamic nomogram based on clinical data to help clinicians make timely diagnoses and decision-making. In this study, we analyzed 299 KD patients and 309 sepsis patients. We collected patients' age, sex, height, weight, BMI, and 33 biological parameters of a routine blood test. After dividing the patients into a training set and validation set, the least absolute shrinkage and selection operator method, support vector machine and receiver operating characteristic curve were used to select significant factors and construct the nomogram. The performance of the nomogram was evaluated by discrimination and calibration. The decision curve analysis was used to assess the clinical usefulness of the nomogram. This nomogram shows that height, WBC, monocyte, eosinophil, lymphocyte to monocyte count ratio (LMR), PA, GGT and platelet are independent predictors of the KD diagnostic model. The c-index of the nomogram in the training set and validation is 0.926 and 0.878, which describes good discrimination. The nomogram is well calibrated. The decision curve analysis showed that the nomogram has better clinical application value and decision-making assistance ability. The nomogram has good performance of distinguishing KD from sepsis and is helpful for clinical pediatricians to make early clinical decisions.

Abstract Paraoxonase 2 (PON2) is a multifunctional intracellular enzyme that has received growing attention for its ability to modulate various aspects of normal and malignant cellular physiology. Recent research has revealed that PON2 is upregulated in tissues from patients with various types of solid tumors and hematologic cancers, likely due to its ability to suppress oxidative stress and evade apoptosis. However, the effects of PON2 on pulmonary oncogenesis are unknown. Here, we conducted studies to investigate how PON2 influences lung cancer cell proliferation in vitro and lung tumorigenesis in vivo using a variety of cellular and animal models. It was found that PON2 expression deficiency hampered the proliferation of cultured lung cancer cells with concomitant cell cycle arrest at the G1 phase. In addition, the loss of endogenous PON2 expression impaired key aspects of oxidative metabolism in lung adenocarcinoma cells. Moreover, we investigated how the interplay between PON2 expression in lung tumors and host mice influences lung tumor initiation and progression. PON2 status in both transplanted tumor cells and mice failed to influence the development of subcutaneously grafted Lewis lung carcinoma (LLC) tumors, orthotopically implanted LLC tumors, and oncogenic Kras-driven primary lung adenocarcinoma tumors. Importantly, the frequencies of tumor-infiltrating myeloid subsets that include myeloid-derived suppressor cells (MDSCs) and tumor-associated macrophages were not impacted by PON2 expression in LLC tumor-bearing mice. Overall, our studies indicate that PON2 plays a limited role in murine lung tumorigenesis.

The case presented involves a 6-year-old boy admitted to the Department of Infectious Diseases with symptoms of fever, cough, and rash, ultimately diagnosed with Mycoplasma pneumoniae -induced rash and mucositis (MIRM). The patient exhibited typical MIRM rashes, characterized by severe damage to the oral mucosa and scattered rashes on his limbs and trunk.

Abstract The cornea is the outmost ocular tissue and plays an important role in protecting the eye from environmental insults. Corneal epithelial wounding provokes pain and fear and contributes to the most ocular trauma emergency assessments worldwide. ZEB1 is an essential transcription factor in development; but its roles in adult tissues are not clear. We identify Zeb1 is an intrinsic factor that facilitates corneal epithelial wound healing. In this study, we demonstrate that monoallelic deletion of Zeb1 significantly expedites corneal cell death and inhibits corneal epithelial EMT-related cell migration upon an epithelial debridement. We provide evidence that Zeb1-regulation of corneal epithelial wound healing is through the repression of genes required for Tnfa-induced epithelial cell death and the induction of genes beneficial for epithelial cell migration. We suggest utilizing TNF-α antagonists would reduce TNF/TNFR1-induced cell death in the corneal epithelium and inflammation in the corneal stroma to help corneal wound healing.

Field emission is an important work mode for electron sources, and carbon nanotubes (CNTs) have been extensively studied for their good emission properties. It is well known that the parameters of the grid deeply influence the field emission performance of CNTs, a relationship that requires further elucidation. Therefore, in this study, the relationship between the grid aperture ratio and electron transmittance was studied through simulations and experiments. This study’s results indicate that the electron transmittance improved as the grid aperture ratio increased. Meanwhile, electron beam spot simulations and imaging experiments indicate that an increased grid aperture ratio will expand the cathode electron divergence, leading to a larger electron beam spot size. These results demonstrate that there is a trade-off in maintaining the grid aperture ratio between high electron transmittance and relatively small electron beam spot size, and the optimum grid aperture ratio is between 75% and 85%. These results will provide a reference for the design and optimization of X-ray tubes and other electron sources.

An enhanced fault diagnosis approach for rolling bearings with composite faults using an optimized Squeeze and Excitation ResNet (SE-ResNet) model is proposed. This method integrates grid search (GS), support vector regression (SVR), ensemble empirical mode decomposition (EEMD), and low-rank multimodal fusion (LMF) to effectively handle the signals of acoustic–vibration fusion. By combining these techniques, the aim is to improve the accuracy and reliability of rolling bearing fault diagnosis. Firstly, improved EEMD combined with GS-SVR and a window function is used for rolling bearing vibration signal decomposition. Singular value methods are used to filter and reconstruct the results. Secondly, Markov transition fields (MTFs) are used to encode vibration signals into 2D images. LMF is used for the fusion of vibration and sound signals. An improved Squeeze and Excitation ResNet50 network is proposed for feature identification and classification of rolling bearing composite fault data. Finally, the method undergoes rigorous testing and evaluation using rolling bearing data. The experimental outcomes demonstrate that, in comparison to traditional neural networks, the enhanced SE-ResNet, integrated with GS-SVR-EEMD and LMF, attains superior diagnostic accuracy. Additionally, the proposed approach can be effectively utilized for diagnosing rolling bearing composite faults.

Here, we present a case with genetically confirmed SCN. The main symptom of the child was recurring fever. The combination of antibiotics combined with G-CSF injection was proved to be insufficient, and the patient developed ''solid'' liver abscess. After undergoing surgical anatomical hepatic lobectomy, the child's infection symptoms showed improvement. The postoperative culture of the purulent material from the liver infection lesion revealed an infection with Staphylococcus aureus. Our case raises the possibility of pathogen sources and routes of infection, clinical characteristics, and effective treatment for SCN patients with concomitant liver abscess.

Abstract Studies using machine learning (ML) approaches have reported high diagnostic accuracies for glaucoma detection. However, none assessed model performance across ethnicities. The aim of the study is to externally validate ML models for glaucoma detection from optical coherence tomography (OCT) data. We performed a prospective, cross-sectional study, where 514 Asians (257 glaucoma/257 controls) were enrolled to construct ML models for glaucoma detection, which was then tested on 356 Asians (183 glaucoma/173 controls) and 138 Caucasians (57 glaucoma/81 controls). We used the retinal nerve fibre layer (RNFL) thickness values produced by the compensation model, which is a multiple regression model fitted on healthy subjects that corrects the RNFL profile for anatomical factors and the original OCT data (measured) to build two classifiers, respectively. Both the ML models (area under the receiver operating [AUC] = 0.96 and accuracy = 92%) outperformed the measured data (AUC = 0.93; P

Background Social media can be used to engage consumers in hospital service design and quality improvement (QI) activities, however its uptake may be limited by a lack of guidance to support implementation. This article presents the perceived barriers and enablers in using social media for consumer engagement derived from an interview study with public hospital stakeholders.Methods Semi-structured interviews with 26 Australian hospital service providers and consumer representatives. Data were analysed using a deductive content analysis method.Results Data were collected between October 2019 and April 2020. Facebook was the platform most commonly used for consumer engagement activities. Barriers and enablers to social media-based consumer engagement were identified. The barrier themes were (1) fears and concerns; (2) lack of skills and resources for social media engagement; (3) lack of organisational processes and support; and (4) problems with social media platforms and the changing social media landscape. The enabler themes were: (1) hospitals facilitating access and use; (2) making discussions safe; (3) cultivating a social media community; and (4) building on success.Conclusion Using social media to facilitate consumer engagement in hospital service design and QI activities is feasible and acceptable to service providers and consumers. Hospitals and their executives can create a supportive environment for social media-based engagement activities through developing clear governance systems and providing training and support to all users. Consumers need to be involved in co-designing social media-based activities and determining which forms of engagement are accessible and acceptable. For some consumers and service providers, barriers such as a lack of resources and distrust of social media companies might mean that social media-based engagement will be less acceptable for them. Because of this it is important that hospitals provide complementary methods of engagement (eg, face-to-face) alongside social media-based methods.

Abstract Deep‐learning‐based 3D place recognition has received more attention since the data‐driven fashion is widely used for the 3D point cloud applications. Most of the existing deep‐learning‐based 3D place recognition methods only utilise a single scene for place recognition. However, a single scene may have measurement noise or observable dynamic object differences, which may lead to a reduction in recognition accuracy. To improve the performance of 3D place recognition, a sequence matching based rearrangement method is proposed. Our sequence matching method is based on an assignment algorithm and guides the candidate rearrangement in searching for a similar place. The global descriptor extraction adapts the effective sparse tensor representation and a simple pooling layer to obtain the global descriptor. A new loss function combination is employed to train the network. The proposed approach is evaluated on the popular 3D place recognition benchmarks, which proves the effectiveness of the proposed approach.

Optical imaging systems have greatly extended human visual capabilities, enabling the observation and understanding of diverse phenomena. Imaging technologies span a broad spectrum of wavelengths from x-ray to radio frequencies and impact research activities and our daily lives. Traditional glass lenses are fabricated through a series of complex processes, while polymers offer versatility and ease of production. However, modern applications often require complex lens assemblies, driving the need for miniaturization and advanced designs with micro- and nanoscale features to surpass the capabilities of traditional fabrication methods. Three-dimensional (3D) printing, or additive manufacturing, presents a solution to these challenges with benefits of rapid prototyping, customized geometries, and efficient production, particularly suited for miniaturized optical imaging devices. Various 3D printing methods have demonstrated advantages over traditional counterparts, yet challenges remain in achieving nanoscale resolutions. Two-photon polymerization lithography (TPL), a nanoscale 3D printing technique, enables the fabrication of intricate structures beyond the optical diffraction limit via the nonlinear process of two-photon absorption within liquid resin. It offers unprecedented abilities, e.g. alignment-free fabrication, micro- and nanoscale capabilities, and rapid prototyping of almost arbitrary complex 3D nanostructures. In this review, we emphasize the importance of the criteria for optical performance evaluation of imaging devices, discuss material properties relevant to TPL, fabrication techniques, and highlight the application of TPL in optical imaging. As the first panoramic review on this topic, it will equip researchers with foundational knowledge and recent advancements of TPL for imaging optics, promoting a deeper understanding of the field. By leveraging on its high-resolution capability, extensive material range, and true 3D processing, alongside advances in materials, fabrication, and design, we envisage disruptive solutions to current challenges and a promising incorporation of TPL in future optical imaging applications.

In recent years, with the intensification of global warming, extreme weather has become more frequent, intensifying the uncertainty of new energy output and load power, and seriously affecting the safe operation of power systems. Scene generation is an effective method to solve the uncertainty problem of stochastic planning of integrated systems of new energy generation. Therefore, this paper proposes a scenario generation and scenario reduction model of photovoltaic (PV) output and electric vehicle (EV) load power under extreme weather based on the copula function. Firstly, the non-parametric kernel density estimation method is used to fit a large number of sample data. The kernel density estimation expressions of PV and EV powers under extreme weather conditions are obtained and the corresponding goodness of fit tests are carried out. Then, a variety of joint distribution models based on the copula function are established to judge the goodness of fit of each model, and the optimal copula function is selected as the joint probability distribution function by combining the Kendall and Spearman correlation coefficients of each model. Finally, the optimal copula joint probability distribution is used to generate PV and EV power scenarios. The data of extremely hot weather in a certain province were selected for an example analysis. The results show that the output scenario obtained conforms to the correlation under this extreme weather, and has higher accuracy in reflecting the actual PV output and load power in this province under this extreme weather, which can provide a reference for reliability analyses of power systems and power grid planning.

Abstract A surge of interest has been brought to all‐solid‐state batteries (ASSBs) as they show great prospects for enabling higher energy density and improved safety compared to conventional liquid batteries. Na Super Ionic CONductors (NaSICONs) proposed by Goodenough and Hong in 1976 are the most promising materials class for Na‐based ASSBs owing to their excellent ion conductivity (>1 mS cm−1), high thermal and chemical/electrochemical stability, as well as good chemical/electrochemical compatibility with electrode materials. The major challenge facing NaSICON‐type electrolytes is the generally high interfacial resistance and thus sluggish charge transfer kinetics across the NaSICON/cathode interface. Great endeavors in the past few years have led to progress in the improvement of the ion‐conducting property, and a dramatic decrease in the NaSICON/electrode interface resistance. Excellent cycling performance and rate capability have been achieved through interface engineering. In this review article, we summarize the state‐of‐the‐art findings for various derivatives of NaSICON structured solid electrolytes, with the aim of providing a deeper understanding of the underlying mechanism for the improvement of ion conductivity, and the intrinsic reasons for the enhanced interface charge transfer kinetics. These strategies can be readily extended to other solid electrolytes. We hope this review will inspire more work on NaSICON‐type solid electrolytes and solid‐state batteries.

The image depicts a schematic illustration of a van der Waals heterostructure used to electrically activate quantum emitters in hexagonal boron nitride.

Abstract Background Diagnostic performance of optical coherence tomography (OCT) to detect Alzheimer’s disease (AD) and mild cognitive impairment (MCI) remains limited. We assessed whether compensating the circumpapillary retinal nerve fiber layer (cpRNFL) thickness for multiple demographic and anatomical factors as well as the combination of macular layers improves the detection of MCI and AD. Methods This cross-sectional study of 62 AD (n = 92 eyes), 108 MCI (n = 158 eyes), and 55 cognitively normal control (n = 86 eyes) participants. Macular ganglion cell complex (mGCC) thickness was extracted. Circumpapillary retinal nerve fiber layer (cpRNFL) measurement was compensated for several ocular factors. Thickness measurements and their corresponding areas under the receiver operating characteristic curves (AUCs) were compared between the groups. The main outcome measure was OCT thickness measurements. Results Participants with MCI/AD showed significantly thinner measured and compensated cpRNFL, mGCC, and altered retinal vessel density (p

Graphene plasmons hold potential for infrared optoelectronic devices, but the interaction with the substrate often degrades their quality. Here, the authors report the characterization of plasmons in suspended graphene with tunable suspension height, showing enhanced quality factors and propagation lengths at room temperature.

Background: The subtypes of circulating white blood cells undergo relative changes under systemic inflammation; thus, the derived ratio may reflect patients' immunoinflammatory status. Under the hypothesis that change in segmented neutrophil-to-monocyte (SeMo) ratio, delta-SeMo ratio, may reflect the host's immunoinflammatory response against illness, this study aims to investigate the effectiveness of using delta-SeMo ratio to assess the mortality risk of patients with trauma and critical illness. Materials and Methods: A total of 1476 adult patients with trauma admitted to the intensive care unit (ICU) between January 1, 2009, and December 31, 2020, were enrolled in this study. Delta-SeMo ratio was defined using the following formula: SeMo ratio at day 3 (72–96 h after admission into ICU) – SeMo ratio at admission (at admission into ICU). The primary outcome was inhospital mortality. Results: There was no significant difference in the SeMo ratio at admission between death and survival patients (18.7 ± 11.0 vs. 18.7 ± 18.4, P = 0.974); however, SeMo ratio at day 3 (20.3 ± 15.5 vs. 15.7 ± 16.0, P = 0.002) and delta-SeMo ratio (1.6 ± 19.5 vs.–3.0 ± 24.2, P = 0.034) of the patients who died were significantly higher than those of the patients who survived. The patients with delta-SeMo ratio ≥1.038, an estimated cutoff value for best predicting mortality by the plotted receiver operating characteristic curve, sustained an approximately 2-fold adjusted mortality (adjusted odds ratio [AOR]: 1.84, 95% confidence interval [CI]: 1.27–2.66, P = 0.001) than those with a delta-SeMo ratio

Abstract Background There are still few studies on the clinical characteristics and related risk factors of schizophrenia patients with intestinal obstruction. Our aim is to explore the clinical characteristics and related risk factors of schizophrenia patients with intestinal obstruction. Methods This study focused on schizophrenia patients with intestinal obstruction who were hospitalized in the psychiatric department of a hospital in Wuhan from January 2007 to December 2020 as the main research object. We intend to retrospectively analyze the clinical characteristics and related risk factors of schizophrenia patients with intestinal obstruction. Results In the 1937 persons with schizophrenia included in this study, 97 patients were complicated with intestinal obstruction, and the incidence was 5.01%.The results of the study showed that patients with age ≥ 60 years old, visiting time ≥ 24 h, hospital stay ≥ 90 days, history of abdominal surgery, course of disease ≥ 5 years, male, and patients with cardiovascular and cerebrovascular diseases are prone to intestinal obstruction; Logistic multiple regression analysis showed that the related risk factors of schizophrenia patients with intestinal obstruction mainly included the patient's age, visiting time, length of hospital stay, history of abdominal surgery, course of disease and gender. Conclusion The older the age, the longer the hospital stay, the longer the course of the disease, the history of previous surgery, and the male schizophrenia who do not see a doctor within 24 h of the onset, the risk of intestinal obstruction is higher, and it is easy to be misdiagnosed and even life-threatening.

The electrochemical CO2 reduction reaction (CO2RR) on Cu catalyst holds great promise for converting CO2 into valuable multicarbon (C2+) compounds, but still suffers poor selectivity due to the sluggish kinetics of forming carbon–carbon (C–C) bonds. Here we reported a perovskite oxide-derived Cu catalyst with abundant grain boundaries for efficient C–C coupling. These grain boundaries are readily created from the structural reconstruction induced by CO2-assisted La leaching. Using this defective catalyst, we achieved a maximum C2+ Faradaic efficiency of 80.3% with partial current density over 400 mA cm−2 in neutral electrolyte in a flow-cell electrolyzer. By combining the structural and spectroscopic investigations, we uncovered that the in-situ generated defective sites trapped by grain boundaries enable favorable CO adsorption and thus promote C–C coupling kinetics for C2+ products formation. This work showcases the great potential of perovskite materials for efficient production of valuable multicarbon compounds via CO2RR electrochemistry.

ABSTRACT The objective of this study was to compare the performances of BioFire Respiratory Panel 2 (RP2) plus, quantitative real-time PCR (qPCR), and culture for the detection of Bordetella pertussis in nasopharyngeal swab (NPS) specimens. Consecutive NPS specimens were collected from patients with clinically suspected pertussis from 1 March 1 to 31 July 2018 in Shenzhen Children’s Hospital. All the specimens were tested in parallel by RP2 plus, qPCR, and culture methods. A total of 464 children were enrolled in this study. The positive pertussis rates of culture, RP2 plus, and qPCR were 23.1%, 39.0%, and 38.4%, respectively. Compared to the combined reference standard, the sensitivity, specificity, positive predictive value, and negative predictive values were, respectively, 56.6% (95% confidence interval [CI], 49.2 to 63.7%), 100% (98.3 to 100%), 100% (95.7 to 100%), and 77.0% (72.2 to 81.2%) for culture, 89.9% (84.5 to 93.7%), 96.0% (92.8 to 97.9%), 93.9% (89.1 to 96.8%), and 93.3% (89.5 to 95.8%) for RP2 plus, and 86.8% (80.9 to 91.1%), 94.9% (91.4 to 97.1%), 92.1% (86.9 to 95.5%), and 91.3% (87.2 to 94.2%) for qPCR. The most prevalent codetected pathogen was human rhinovirus/enterovirus (n = 99, 52.4%), followed by parainfluenza virus (n =32, 16.9%) and respiratory syncytial virus (n = 29, 15.3%), in children with B. pertussis present, which was consistent with the top three pathogens previously found in children with B. pertussis absent. Turnaround times for RP2 plus, qPCR, and culture were 2 h, 8 h, and 120 h, respectively. RP2 plus quickly and accurately detected B. pertussis, providing valuable information for an early clinical diagnosis and optimal choice of therapy. IMPORTANCE In recent years, there have been some epidemic or local outbreaks of pertussis in countries with high vaccination rates. One of the crucial factors in controlling pertussis is early diagnosis, which is based on specific laboratory measurements, including culture, serological tests, and PCR assays. Compared to culture and serological tests, PCR is more suitable for clinical application, with a fast detection speed of several hours independent of the disease stage and individual vaccination status. BioFire Respiratory Panel 2 plus, a multiplex PCR assay for simultaneously detecting 22 respiratory pathogens, facilitates the quick detection of Bordetella pertussis and coinfecting respiratory pathogens. It also provides valuable information for an early clinical diagnosis and optimal choice of therapy for children with clinically suspected pertussis.

ABSTRACT Verticillium dahliae is a soilborne plant fungal pathogen that causes Verticillium wilt, a disease that reduces the yields of many economically important crops. Despite its worldwide distribution and harmful impacts, much remains unknown regarding how the numerous effectors of V. dahliae modulate plant immunity. Here, we identified the intracellular effector VdCE11 that induces cell death and defense responses in Nicotiana benthamiana to counter leaf pathogens such as Sclerotinia sclerotiorum and Botrytis cinerea. VdCE11 also contributes to the virulence of V. dahliae in cotton and Arabidopsis. Yeast two-hybrid library screening and immunoprecipitation revealed that VdCE11 interacts physically with the cotton aspartic protease GhAP1. GhAP1 and its Arabidopsis homolog AtAP1 are negative regulators of plant immunity, since disruption of either increased the resistance of cotton or Arabidopsis to V. dahliae. Further, VdCE11 plays a role in promoting the accumulation of the AP1 proteins and increasing its hydrolase activity. Taken together, these results indicate a novel mechanism regulating virulence whereby the secreted effector VdCE11 increases cotton susceptibility to V. dahliae by promoting the accumulation and activity of GhAP1. IMPORTANCE Verticclium dahliae is a plant fungal pathogen that causes a destructive vascular disease on a large number of plant hosts, resulting in great threat to agricultural production. In this study, we identified a V. dahliae effector VdCE11 that induces cell death and defense responses in Nicotiana benthamiana. Meanwhile, VdCE11 contributes to the virulence of V. dahliae in cotton and Arabidopsis. Yeast two-hybrid library screening and immunoprecipitation revealed that VdCE11 interacts physically with the cotton aspartic protease GhAP1. GhAP1 and its Arabidopsis homolog AtAP1 are negative regulators of plant immunity since disruption of either increased the resistance of cotton or Arabidopsis to V. dahliae. Further research showed that VdCE11 plays a role in promoting the accumulation of the AP1 proteins and increasing its hydrolase activity. These results suggested that a novel mechanism regulating virulence whereby VdCE11 increases susceptibility to V. dahliae by promoting the accumulation and activity of GhAP1 in the host.

The emergence of multimodal medical imaging technology greatly increases the accuracy of clinical diagnosis and etiological analysis. Nevertheless, each medical imaging modal unavoidably has its own limitations, so the fusion of multimodal medical images may become an effective solution. In this paper, a novel fusion method on the multimodal medical images exploiting convolutional neural network (CNN) and extreme learning machine (ELM) is proposed. As a typical representative in deep learning, CNN has been gaining more and more popularity in the field of image processing. However, CNN often suffers from several drawbacks, such as high computational costs and intensive human interventions. To this end, the model of convolutional extreme learning machine (CELM) is constructed by incorporating ELM into the traditional CNN model. CELM serves as an important tool to extract and capture the features of the source images from a variety of different angles. The final fused image can be obtained by integrating the significant features together. Experimental results indicate that, the proposed method is not only helpful to enhance the accuracy of the lesion detection and localization, but also superior to the current state-of-the-art ones in terms of both subjective visual performance and objective criteria.

There has been interest in using social media for consumer engagement in hospitals, particularly for service design and quality improvement, but services have identified a need for guidance. This article outlines the methods used to involve stakeholders in the development of a guide for the use of social media as a consumer engagement tool for Australian public hospitals, and describes the changes to the guide and implementation findings that resulted from stakeholder involvement. The development of the guide involved cycles of two interrelated methods – (1) small group co-creation involving three hospital consumer representatives, three service provider representatives and three academics gathering and analysing data, and integrating findings into the development of the guide; and (2) a consultation with eighteen hospital stakeholders who provided feedback on versions of the guide throughout its development. Participants were encouraged to use their experience as service providers and consumers to reflect broadly on how the content and design of the guide could support social media-based consumer engagement within their particular setting. The co-creation and consultation methods led to four main feedback themes: (1) Enhancing usability is critical for guidance resources ; (2) Executive support and teamwork are essential for implementation ; (3) Start small and build experience and knowledge over time ; and (4) Thinking about new methods brings up questions around existing practice . Involving stakeholders in the design process through co-creation and consultation methods led to critical changes to the guide, enhancing its usability and creating a focus in the guide on building organisational and individual capacity around service design and improvement. Involving stakeholders in the development of the guide also allowed us to translate existing research knowledge into practical implementation strategies and tools, and may increase the likelihood of the guide being used by hospitals, providers and consumers.

With continuous improvements in integration, totalization and automation, remaining useful life predictions of mechanical equipment have become a key feature of technology and core element of equipment prediction and health management. The traditional method based on degradation mechanisms is not fully capable of predicting remaining useful life, especially for special power plants that use industrial transmissions, barrel launchers, etc. The expected service requirements are higher for condition monitoring and remaining service life prediction. The effective prediction of the remaining useful life of such special power plants is a major challenge and technical bottleneck in the industrial field and national defense equipment construction. This paper analyzes and expands on the research on the remaining life prediction methods for special power plants and analyzes the remaining life prediction methods of existing dynamic models, as well as data-driven and data–model fusion drives, and specific ideas for future research and development in four aspects, including remaining useful life prediction tests supplemented with soft measurements. Additionally, future research directions for the remaining life prediction of special power plants are provided.

Abstract Background Engaging consumers - patients, families, carers and community members who are current or potential service users - in the planning, design, delivery, and improvement of health services is a requirement of public hospital accreditation in Australia. There is evidence of social media being used for consumer engagement in hospitals internationally, but in Australia this use is uncommon and stakeholders’ experiences have not been investigated. The aim of the study was to explore the experiences and beliefs of key Australian public hospital stakeholders around using social media as a consumer engagement tool. This article focuses on the study findings relating to methods, risks, and benefits of social media use. Methods Semi-structured interviews were conducted with Australian public hospital stakeholders in consumer representative, consumer engagement/patient experience, communications or quality improvement roles. Qualitative data were analysed using a deductive content analysis method. An advisory committee of consumer and service provider stakeholders provided input into the design and conduct of this study. Results Twenty-six Australian public hospital service providers and consumers were interviewed. Participants described social media being used to: recruit consumers for service design and quality improvement activities; as an online space to conduct consultations or co-design; and, to gather feedback and patient experience data. The risks and benefits discussed by interview participants were grouped into five themes: 1) overcoming barriers to engagement, 2) consumer-initiated engagement; 3) breadth vs depth of engagement, 4) organisational transparency vs control and 5) users causing harm. Conclusions Social media can be used to facilitate consumer engagement in hospital service design and quality improvement. However, social media alone is unlikely to solve broader issues commonly experienced within health consumer engagement activities, such as tokenistic engagement methods, and lack of clear processes for integrating consumer and patient feedback into quality improvement activities.

Developing a new and efficient catalytic route for the production of alkanes by upgrading the aqueous phenolic biofuels still remains a challenge. Here, we designed and synthesized a bifunctional catalyst that uses natural montmorillonite (MMT) as support and combines metal active sites and Brӧnsted acid sites in the MMT via ion exchange and reduction roasting process. The catalytic activity of the as-synthesized Pd-MMT (H+) was evaluated by the hydrodeoxygenation (HDO) of a series of lignin-derived phenolic compounds in water. Our model reaction study reveals that the HDO of phenol undergoes an initial hydrogenation of aromatic rings to produce cyclohexanol and cyclohexanone, followed by the dehydration of cyclohexanol to provide intermediate cyclohexene and a final hydrogenation of cyclohexene to create a cyclohexane product. The combination of high metal catalytic activity and Brӧnsted acidity in Pd-MMT (H+) synergistically accelerated the HDO of phenol. Furthermore, good catalytic activity and recycling ability were also observed for other lignin-derived phenolic compounds.

Objective Pediatric patients can be significantly impacted emotionally by exposure to acute trauma which may negatively impact long-term functioning and lead to an increase in overall distress. This study reports on the incidence of acute stress disorder among pediatric trauma patients in a hospital setting in the southeastern region of the USA.Methods Pediatric patient mental health assessments were conducted using the Childhood Stress Disorders Checklist- Short Form (CSDC-SF) as part of a new integrated behavioral health standard of care within the Trauma Services Division of a level 1 pediatric hospital. Mental health consultations occurred at bedside on inpatient hospital admission into trauma services, or at the outpatient hospital clinic after discharge for injuries treated in the emergency department.Results Associations among type of trauma, child age, and sex were explored in a sample of 617 children (58.9% male) aged 2–18 years (Mage=10.27). The sample was primarily ethnic minorities (56.1% black/African-American, 5% Hispanic/Latinx). Fifteen per cent or more of trauma reports were for burns (26%), motor vehicle accident (22.7%), and recreational sports or leisure activity-related injury (17.5%). Sixty-four per cent of children scored ≥1 on the CSDC-SF, indicating symptoms consistent with acute stress disorder. Higher scores were associated with female sex, age, and injury type.Level of evidence Level IV study provides evidence of the link between traumatic injury and mental health symptoms in a pediatric population. Findings highlight the critical need for mental health screening and provision of integrated mental health counseling services at time of acute pediatric trauma.

There has been no consensus on the neural dissociation between emotion-label and emotion-laden words, which remains one of the major concerns in affective neurolinguistics. The current study adopted dot-probe tasks to investigate the valence effect on attentional bias toward Chinese emotion-label and emotion-laden words. Behavioral data showed that emotional word type and valence interacted in attentional bias scores with an attentional bias toward positive emotion-laden words rather than positive emotion-label words and that this bias was derived from the disengagement difficulty in positive emotion-laden words. In addition, an attentional bias toward negative emotion-label words relative to positive emotion-label words was observed. The event-related potential (ERP) data demonstrated an interaction between emotional word type, valence, and hemisphere. A significant hemisphere effect was observed during the processing of positive emotion-laden word pairs rather than positive emotion-label, negative emotion-label, and negative emotion-laden word pairs, with positive emotion-laden word pairs eliciting an enhanced P1 in the right hemisphere as compared to the left hemisphere. Our results found a dynamic attentional bias toward positive emotion-laden words; individuals allocated more attention to positive emotion-laden words in the early processing stage and had difficulty disengaging attention from them in the late processing stage.

Phosphorus (P) accumulation in rice–wheat rotation fields around the Yangtze River delta have been enriched during the last decades. To protect the environment and save P resources, we conducted field experiments to optimize the P application scheme. First, one field experiment was designed as a series of P fertilizer application doses of 0–100 kg P2O5 hm−2. Grain yield and P uptake by crops were analyzed to calculate P surplus and P use efficiency. Soil P fractions were extracted and tested. According to the P balance, we optimized fertilization by reducing the chemical P amount, which was used by local farmers; furthermore, we substituted chemical P with organic fertilizer. To verify these management strategies, another field experiment was conducted with five treatments: no N, P, or K fertilizer (CK); only no P fertilizer (NK); farmers’ fertilization of P (90 kg P2O5 hm−2) (FFP); reducing 20% P (FFP-20%P); and reducing 20% P and replacing 20% P by manure (FFPM-36%P). The grain yield was enhanced by increased P fertilizer and reached a constant level after 75 kg P2O5 hm−2. Moreover, the annual P surplus was balanced around the input of 150 kg P2O5 hm−2. Accordingly, by optimizing fertilization (FFP-20%P) and further replacing manure (FFPM-36%P), we also achieved crop yield equivalent to that of FFP treatment (90 kg P2O5 hm−2). Thus, the 72–75 kg P2O5 hm−2 application rate is a threshold for the production of rice and wheat and P balance. Total P content in soil was enhanced by increased input of P fertilizer and mainly divided into labile Pi and middle stable Pi fractions. Soil Olsen-P content increased by P fertilization accordingly, while the content of organic P and stable P content was relatively constant. Reducing P fertilizer by 20% had similar results for soil P fractions when compared with farmers’ P fertilization treatment. Therefore, reducing at least 20% current input of P by farmers (annual 180 kg P2O5 hm−2) according to the balance of P surplus in rice and wheat rotation systems is an imperative measure to guarantee crop production with enhanced P use efficiency, and meanwhile, it can alleviate environmental risk.

In this paper, we present a novel and unified model for studying the vibration of cylindrical shells based on the three-dimensional (3D) elastic theory and the Carrera Unified Formulation. Our approach represents a significant advancement in the field, as it enables us to accurately predict the vibrational behavior of cylindrical shells under arbitrary boundary conditions. To accomplish this, we expand the axial, circumferential, and radial displacements of the shell using Chebyshev polynomials and Taylor series, thereby reducing the dimensionality of the expansion and ensuring the precision and rigor of our results. In addition, we introduce three groups of artificial boundary surface springs to simulate the general end boundary conditions of the cylindrical shell and coupling springs to strongly couple the two surfaces of the cylindrical shell φ = 0 and φ = 2π to ensure continuity of displacements on these faces. Using the energy function of the entire cylindrical shell model, we obtain the characteristic equation of the system by finding the partial derivatives of the unknown coefficients of displacement in the energy function. By solving this equation, we can directly obtain the vibration characteristics of the cylindrical shell. We demonstrate the convergence, accuracy, and reliability of our approach by comparing our computational results with existing results in the literature and finite element results. Finally, we present simulation results of the frequency features of cylindrical shells with various geometrical and boundary parameters in the form of tables and figures. Overall, we believe that our novel approach has the potential to greatly enhance our understanding of cylindrical shells and pave the way for further advancements in the field of structural engineering. Our comprehensive model and simulation results contribute to the ongoing efforts to develop efficient and reliable techniques for analyzing the vibrational behavior of cylindrical shells.

This study proposed an all-fiber Fabry–Perot interferometer (FPI) strain sensor with two miniature bubble cavities. The device was fabricated by writing two axial, mutually close short-line structures via femtosecond laser pulse illumination to induce a refractive index modified area in the core of a single-mode fiber (SMF). Subsequently, the gap between the two short lines was discharged with a fusion splicer, resulting in the formation of two adjacent bubbles simultaneously in a standard SMF. When measured directly, the strain sensitivity of dual air cavities is 2.4 pm/με, the same as that of a single bubble. The measurement range for a single bubble is 802.14 µε, while the measurement range for a double bubble is 1734.15 µε. Analysis of the envelope shows that the device possesses a strain sensitivity of up to 32.3 pm/με, which is 13.5 times higher than that of a single air cavity. Moreover, with a maximum temperature sensitivity of only 0.91 pm/°C, the temperature cross sensitivity could be neglected. As the device is based on the internal structure inside the optical fiber, its robustness could be guarantee. The device is simple to prepare, highly sensitive, and has wide application prospects in the field of strain measurement.

This study proposes a high-efficiency method using a co-prime circular microphone array (CPCMA) for the bearing fault diagnosis, and discusses the acoustic characteristics of three fault-type signals at different rotation speeds. Due to the close positions of various bearing components, radiation sounds are seriously mixed, and it is challenging to separate the fault features. Direction-of-arrival (DOA) estimation can be used to suppress noise and directionally enhance sound sources of interest; however, classical array configurations usually require a large number of microphones to achieve high accuracy. To address this, a CPCMA is introduced to raise the array’s degrees of freedom in order to reduce the dependence on the microphone numbers and computation complexity. The estimation of signal parameters via rotational invariance techniques (ESPRIT) applied to a CPCMA can quickly figure out the DOA estimation without any prior knowledge. By using the techniques above, a sound source motion-tracking diagnosis method is proposed according to the movement characteristics of impact sound sources for each fault type. Additionally, more precise frequency spectra are obtained, which are used in combination to determine the fault types and locations.

Abstract We examined the choriocapillaris microvasculature using a non-invasive swept-source optical coherence tomography angiography (SS-OCTA) in 41 healthy controls and 71 hypertensive patients and determined possible correlations with BP and renal parameters. BP levels, serum creatinine and urine microalbumin/creatinine ratio (MCR) specimens were collected. The estimated glomerular filtration rate (eGFR) was calculated based on CKD-EPI Creatinine Equation. The main outcome was choriocapillaris flow deficits (CFD) metrics (density, size and numbers). The CFD occupied a larger area and were fewer in number in the hypertensive patients with poor BP control (407 ± 10 µm2; 3260 ± 61) compared to the hypertensives with good BP control (369 ± 5 µm2; 3551 ± 41) and healthy controls (365 ± 11 µm2; 3581 ± 84). Higher systolic BP (β = 9.90, 95% CI, 2.86–16.93), lower eGFR (β = − 0.85; 95% CI, − 1.58 to − 0.13) and higher urine MCR (β = 1.53, 95% CI, 0.32–2.78) were associated with larger areas of CFD. Similar significant associations with systolic BP, eGFR and urine MCR were found with number of CFD. These findings highlight the potential role of choriocapillaris imaging using SS-OCTA as an indicator of systemic microvascular abnormalities secondary to hypertensive disease.

Background: The geriatric nutritional risk index (GNRI) calculated as 1.489 × albumin (g/dL) +41.7× (current body weight/ideal body weight) is useful in identifying high-risk for malnutrition in elderly patients with subacute or chronic diseases. Given that trauma patients have sustained injuries in an acute condition, this study is designed to explore the association between GNRI on admission and outcomes in elderly and young adult patients with trauma. Materials and Methods: From January 01, 2009, to December 31, 2019, a total of 1772 elderly and 2194 young adult trauma patients were categorized into four nutritional risk groups according to GNRI: high-risk group (GNRI 98). Propensity score-matched patient cohorts were created in different nutritional risk groups against the no-risk group to minimize the confounding effects of sex, age, pre-existing comorbidities, Glasgow Coma Scale score, and Injury Severity Score on outcome measurements. Primary outcome was in-hospital mortality, and secondary outcome was the length of hospital stay. Results: Young adult patients with trauma were comparable in pattern of mortality outcomes and hospital stays to that in elderly patients. Analysis of the selected propensity score-matched patient cohorts revealed that both elderly and young adult patients in the high-risk group had significantly higher odds of mortality (elderly, odds ratio [OR], 6.5; 95% confidence interval [CI], 3.00-14.03; P < 0.009; young adult, OR, 2.7; 95% CI, 1.45-5.11; P = 0.001) and longer hospital stay (elderly, 21.5 days vs. 12.4 days, respectively, P < 0.001; young adults, 22.5 days vs. 14.1 days, respectively, P < 0.001) than those of the no-risk group. Conclusion: This study demonstrated that the GNRI could serve as a useful screening method to identify high-risk malnutrition in acutely injured trauma patients, including not only the elderly trauma patients but also the young adult trauma patients.

Abstract Background Cemented vertebrae frequently re-fracture after vertebroplasty to treat osteoporotic vertebral compression fractures (OVCFs) with large clefts. We compared the efficacy of planned and central-clefted puncture, both followed by a second puncture, as treatments for OVCFs with large clefts. Methods We retrospectively studied 38 patients. 18 of whom underwent planned puncture (group A) and 20 central-clefted puncture (group B). A second puncture was performed when the initially injected cement was restricted to the cleft. We recorded a visual analog scale (VAS) pain scores, vertebral kyphotic angles (KAs), and compression ratios (CRs) preoperatively and at 2 days and 6 months postoperatively. We recorded the cement dispersion patterns and complications. Results Second punctures succeeded in 15/18 and 7/20 patients of groups A and B, respectively. At 2 days postoperatively, the VAS score, KA, and CR were significantly better than the preoperative values (P < 0.01); no significant difference was found between the two groups (P > 0.05). At the 6-month follow-up, all scores were poorer than at 2 days postoperatively (all P < 0.05), significantly more so in group B than group A (P < 0.05). Significant differences in terms of the cement dispersion patterns, and the cemented vertebral re-fracture and cement leakage rates, were observed between the two groups (all P < 0.05). Conclusion The two-puncture techniques were initially effective when treating large-clefted OVCFs. However, compared to the central-clefted puncture, the planned puncture improved the success rate of the second puncture, allowed better cement dispersion, and reduced the incidence of vertebral re-fracture during follow-up.