Developing a consistent near-wall turbulence model remains an unsolved problem. The machine learning method has the potential to become the workhorse for turbulence modelling. However, the learned model suffers from limited generalisability, especially for flows without similarity laws (e.g. separated flows). In this work, we propose a knowledge-integrated additive (KIA) learning approach for learning wall models in large-eddy simulations. The proposed approach integrates the knowledge in the simplified thin-boundary-layer equation with a data-driven forcing term for the non-equilibrium effects induced by pressure gradients and flow separations. The capability learned from each flow dataset is encapsulated using basis functions with the corresponding weights approximated using neural networks. The fusion of capabilities learned from various datasets is enabled using a distance function, in a way that the learned capability is preserved and the generalisability to other cases is allowed. The additive learning capability is demonstrated via training the model sequentially using the data of the flow with pressure gradient but no separation, and the separated flow data. The capability of the learned model to preserve previously learned capabilities is tested using turbulent channel flow cases. The periodic hill and the 2-D Gaussian bump cases showcase the generalisability of the model to flows with different surface curvatures and different Reynolds numbers. Good agreements with the references are obtained for all the test cases.

We introduce the exponentially preferential recursive tree and study some properties related to the degree profile of nodes in the tree. The definition of the tree involves a radix $a\gt 0$. In a tree of size $n$ (nodes), the nodes are labeled with the numbers $1,2, \ldots ,n$. The node labeled $i$ attracts the future entrant $n+1$ with probability proportional to $a^i$.

We dedicate an early section for algorithms to generate and visualize the trees in different regimes. We study the asymptotic distribution of the outdegree of node $i$, as $n\to \infty$, and find three regimes according to whether $0 \lt a \lt 1$ (subcritical regime), $a=1$ (critical regime), or $a\gt 1$ (supercritical regime). Within any regime, there are also phases depending on a delicate interplay between $i$ and $n$, ramifying the asymptotic distribution within the regime into “early,” “intermediate” and “late” phases. In certain phases of certain regimes, we find asymptotic Gaussian laws. In certain phases of some other regimes, small oscillations in the asymototic laws are detected by the Poisson approximation techniques.

This study examined global trends in influenza-associated lower respiratory infections (LRIs) deaths from 1990 to 2019 using data from the GBD 2019. The annual percentage change (APC) and average annual percentage change (AAPC) were used to analyze age-standardized death rates (ASDR). Globally, the ASDR of influenza-associated LRIs was 3.29/100,000 in 2019, which was higher in the African region (6.57/100,000) and among adults aged 70 years and older (29.88/100,000). The ASDR of influenza-associated LRIs decreased significantly from 1990 to 2019 (AAPC = −1.88%, P < 0.05). However, it was significantly increased among adults aged 70 years and older during 2017–2019 (APC = 2.31%, P < 0.05), especially in Western Pacific Region and South-East Asia Regions. The ratio of death rates between adults aged 70 years and older and children aged under 5 years increased globally from 1.63 in 1990 to 5.34 in 2019, and the Western Pacific Region experienced the most substantial increase, with the ratio soaring from 1.83 in 1990 to 12.98 in 2019. Despite a decline in the global ASDR of influenza-associated LRIs, it continues to impose a significant burden, particularly in the African, Western Pacific regions and among the elderly population.

This study investigates the effects of fat emulsion-based early parenteral nutrition in patients following hemihepatectomy, addressing a critical gap in clinical knowledge regarding parenteral nutrition after hemihepatectomy. We retrospectively analysed clinical data from 274 patients who received non-fat emulsion-based parenteral nutrition (non-fatty nutrition group) and 297 patients who received fat emulsion-based parenteral nutrition (fatty nutrition group) after hemihepatectomy. Fat emulsion-based early parenteral nutrition significantly reduced levels of post-operative aspartate aminotransferase, total bilirubin and direct bilirubin, while minor decreases in red blood cell and platelet counts were observed in the fatty nutrition group. Importantly, fat emulsion-based early parenteral nutrition shortened lengths of post-operative hospital stay and fasting duration, but did not affect the incidence of short-term post-operative complications. Subgroup analyses revealed that the supplement of n-3 fish oil emulsions was significantly associated with a reduced inflammatory response and risk of post-operative infections. These findings indicate that fat emulsion-based early parenteral nutrition enhances short-term post-operative recovery in patients undergoing hemihepatectomy.

This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.

This paper investigates the long-run nexus between wealth inequality and aggregate output using a DSGE model in which wealth inequality endogenously affects individual entrepreneurship incentives, thereby influencing aggregate output. Our model passes the indirect inference test against the UK data from 1870 to 2015. We find that shocks to aggregate TFP, entrepreneurial barriers, government grant support and general government spending played significant roles in shaping historical inequality dynamics in the UK. Directly removing entrepreneurial barriers or indirectly providing government grant support to the private sector such as through inclusive loan subsidies are effective means of reducing inequality and stimulating output growth.

The ubiquitous marine radiocarbon reservoir effect (MRE) constrains the construction of reliable chronologies for marine sediments and the further comparison of paleoclimate records. Different reference values were suggested from various archives. However, it remains unclear how climate and MREs interact. Here we studied two pre-bomb corals from the Hainan Island and Xisha Island in the northern South China Sea (SCS), to examine the relationship between MRE and regional climate change. We find that the MRE from east of Hainan Island is mainly modulated by the Southern Asian Summer Monsoon-induced precipitation (with 11.4% contributed to seawater), rather than wind induced upwelling. In contrast, in the relatively open seawater of Xisha Island, the MRE is dominated by the East Asian Winter Monsoon, with relatively more negative (lower) ΔR values associated with high wind speeds, implying horizontal transport of seawater. The average SCS ΔR value relative to the Marine20 curve is –161±39 14C years. Our finding highlights the essential role of monsoon in regulating the MRE in the northern SCS, in particularly the tight bond between east Asian winter monsoon and regional MRE.

Multiple osteoarticular tuberculosis (MOT) represents an uncommon yet severe form of tuberculosis, characterized by a lack of systematic analysis and comprehension. Our objective was to delineate MOT’s epidemiological characteristics and establish a scientific foundation for prevention and treatment. We conducted searches across eight databases to identify relevant articles. Pearson’s chi-square test (Fisher’s exact test) and Bonferroni method were employed to assess osteoarticular involvement among patients of varying age and gender (α = 0.05). The study comprised 98 articles, encompassing 151 cases from 22 countries, with China and India collectively contributing 67.55% of cases. MOT predominantly affected individuals aged 0–30 years (58.94%). Pulmonary tuberculosis was evident in 16.55% of cases, with spinal involvement prevalent (57.62%). Significant differences were noted in trunk, spine, thoracic, and lumbar vertebrae involvement, as well as type I lesions across age groups, increasing with age. Moreover, significant differences were observed in upper limb bone involvement and type II lesions across age groups, decreasing with age. Gender differences were not significant. MOT primarily manifests in China and India, predominantly among younger individuals, indicating age-related variations in osteoarticular involvement. Enhanced clinical awareness is crucial for accurate MOT diagnosis, mitigating missed diagnoses and misdiagnoses.

Developing large-eddy simulation (LES) wall models for separated flows is challenging. We propose to leverage the significance of separated flow data, for which existing theories are not applicable, and the existing knowledge of wall-bounded flows (such as the law of the wall) along with embedded learning to address this issue. The proposed so-called features-embedded-learning (FEL) wall model comprises two submodels: one for predicting the wall shear stress and another for calculating the eddy viscosity at the first off-wall grid nodes. We train the former using the wall-resolved LES (WRLES) data of the periodic hill flow and the law of the wall. For the latter, we propose a modified mixing length model, with the model coefficient trained using the ensemble Kalman method. The proposed FEL model is assessed using the separated flows with different flow configurations, grid resolutions and Reynolds numbers. Overall good a posteriori performance is observed for predicting the statistics of the recirculation bubble, wall stresses and turbulence characteristics. The statistics of the modelled subgrid-scale (SGS) stresses at the first off-wall grids are compared with those calculated using the WRLES data. The comparison shows that the amplitude and distribution of the SGS stresses and energy transfer obtained using the proposed model agree better with the reference data when compared with the conventional SGS model.

This study demonstrates a kilowatt-level, spectrum-programmable, multi-wavelength fiber laser (MWFL) with wavelength, interval and intensity tunability. The central wavelength tuning range is 1060–1095 nm and the tunable number is controllable from 1 to 5. The wavelength interval can be tuned from 6 to 32 nm and the intensity of each channel can be adjusted independently. Maximum output power up to approximately 1100 W has been achieved by master oscillator power amplifier structures. We also investigate the wavelength evolution experimentally considering the difference of gain competition, which may give a primary reference for kW-level high-power MWFL spectral manipulation. To the best of our knowledge, this is the highest output power ever reported for a programmable MWFL. Benefiting from its high power and flexible spectral manipulability, the proposed MWFL has great potential in versatile applications such as nonlinear frequency conversion and spectroscopy.

Fiber Bragg grating-based Raman oscillators are capable of achieving targeted frequency conversion and brightness enhancement through the provision of gain via stimulated Raman scattering across a broad gain spectrum. This capability renders them an exemplary solution for the acquisition of high-brightness, specialized-wavelength lasers. Nonetheless, the output power of all-fiber Raman oscillators is typically limited to several hundred watts, primarily due to limitations in injectable pump power and the influence of higher-order Raman effects, which is inadequate for certain application demands. In this study, we introduce an innovative approach by employing a graded-index fiber with a core diameter of up to 150 μm as the Raman gain medium. This strategy not only enhances the injectable pump power but also mitigates higher-order Raman effects. Consequently, we have successfully attained an output power of 1780 W for the all-fiber Raman laser at 1130 nm, representing the highest output power in Raman fiber oscillators with any configuration reported to date.

Glycosylation modifications of proteins and glycan hydrolysis are critical for protein function in biological processes. Aberrations in glycosylation enzymes are linked to lysosomal storage disorders (LSDs), immune interactions, congenital disorders and tumour progression. Mannosidase alpha class 2B member 1 (MAN2B1) is a lysosomal hydrolase from the α-mannosidase family. Dysfunction of MAN2B1 has been implicated as causative factors in mannosidosis, a lysosomal storage disorder characterised by cognitive impairment, hearing loss and immune system and skeletal anomalies. Despite decades of research, its role in pathogenic infections, autoimmune conditions, cancers and neurodegenerative pathologies is highly ambiguous. Future studies are required to shed more light on the intricate functioning of MAN2B1. To this end, we review the biological functions, expression patterns, enzymatic roles and potential implications of MAN2B1 across various cell types and disease contexts. Additionally, the novel insights presented in this review may aid in understanding the role of MAN2B1 in immune cells, thereby paving the way for targeted therapeutic interventions in immune-related disorders.

Predicting epidemic trends of coronavirus disease 2019 (COVID-19) remains a key public health concern globally today. However, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection rate in previous studies of the transmission dynamics model was mostly a fixed value. Therefore, we proposed a meta-Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) model by adding a time-varying SARS-CoV-2 reinfection rate to the transmission dynamics model to more accurately characterize the changes in the number of infected persons. The time-varying reinfection rate was estimated using random-effect multivariate meta-regression based on published literature reports of SARS-CoV-2 reinfection rates. The meta-SEIRS model was constructed to predict the epidemic trend of COVID-19 from February to December 2023 in Sichuan province. Finally, according to the online questionnaire survey, the SARS-CoV-2 infection rate at the end of December 2022 in Sichuan province was 82.45%. The time-varying effective reproduction number in Sichuan province had two peaks from July to December 2022, with a maximum peak value of about 15. The prediction results based on the meta-SEIRS model showed that the highest peak of the second wave of COVID-19 in Sichuan province would be in late May 2023. The number of new infections per day at the peak would be up to 2.6 million. We constructed a meta-SEIRS model to predict the epidemic trend of COVID-19 in Sichuan province, which was consistent with the trend of SARS-CoV-2 positivity in China. Therefore, a meta-SEIRS model parameterized based on evidence-based data can be more relevant to the actual situation and thus more accurately predict future trends in the number of infections.