One-degree-of-freedom flow-induced vibration (FIV) and energy harvesting through FIV of an elastically mounted circular cylinder with mechanically coupled rotation were investigated numerically for low Reynolds number 100, mass ratio 8 and a wide range of reduced velocities. The aims of this study are to investigate the effect of the flow direction angle $\beta$ on the vibration and energy harvesting through FIV. Two types of lock-in are found: vortex-induced vibration (VIV) and galloping. The response amplitude increases with the increase of $\beta$ in both regimes. Both VIV response and galloping regimes are found for $\beta$ = 45° to $\beta$ = 90°. For $\beta$ = −90° to $\beta$ = 0°, only VIV response regimes are found. The fluid force and fluid torque play different roles in exciting/damping the vibration. In the high-amplitude gallop regime, the fluid force excites the vibration, and the torque damps the vibration. Energy harvesting at flow direction angle 90° is investigated as this flow direction has the maximum galloping amplitude. The energy harvesting is achieved by a linear electric damping coefficient in the numerical model. The maximum harvestable power in the galloping regime is significantly greater than that in the VIV regime, and it increases with the increase of the reduced velocity. When the reduced velocity is 20, the harvested power is over 20 times that in the VIV regime, and can further increase if reduced velocity further increases. The maximum efficiency over all simulated parameters is 0.424, occurring when the reduced velocity is 20, and electric damping factor is 0.04.

This study employs a direct numerical simulation method to investigate the wake pattern evolutions of flows past an insulated spheroid and provides expressions of force and torque coefficients influenced by a streamwise magnetic field in an incompressible, conducting, viscous fluid. A total of 1150 cases are examined covering a parameter range of Reynolds number $50 \leqslant \textit{Re} \leqslant 250$, aspect ratio $1.5 \leqslant \beta \leqslant 6$, inclination angle $0^\circ \leqslant \theta \leqslant 90^\circ$, and interaction parameter $0 \leqslant N \leqslant 10$, where $\beta$ and $N$, respectively, reflect the anisotropy of the spheroid and the strength of magnetic field. Nine wake patterns are classified based on wake structure features and summarised in three maps of regimes according to the inclination angle. The transition mechanisms among these wake patterns are also investigated under the influence of a streamwise magnetic field. Furthermore, expressions for drag, lift and torque coefficients are derived with the help of three fundamental physical criteria. Results indicate that the force and torque expressions give a good prediction within the present parameter space $\{\textit{Re}, \beta , \theta , N\}$.

Some cadres receive promotions, whereas others do not. This study explores the Chinese Communist Party’s (CCP) personnel control over the central state-owned enterprise (SOE) leaders from the Hu era to the Xi era. An analysis of the résumés and careers of SOE leaders reveals that the CCP has established a dual-track system to manage enterprises with different functions. This system employs two types of incentives: promotion incentives for leaders of eldest-son enterprises associated with national security, and salary incentives for leaders of other enterprises. Through the dual-track system, the CCP aims to influence the career trajectories of SOE leaders and address conflicts of interest in the principal-agent relationship. This study also investigates the individual characteristics of SOE leaders, including their political qualifications, professional qualifications and ages. The results indicate a tendency towards specialization and institutionalization in central-enterprise leaders, even during the Xi era.

Persistent malnutrition is associated with poor clinical outcomes in cancer. However, assessing its reversibility can be challenging. The present study aimed to utilise machine learning (ML) to predict reversible malnutrition (RM) in patients with cancer. A multicentre cohort study including hospitalised oncology patients. Malnutrition was diagnosed using an international consensus. RM was defined as a positive diagnosis of malnutrition upon patient admission which turned negative one month later. Time-series data on body weight and skeletal muscle were modelled using a long short-term memory architecture to predict RM. The model was named as WAL-net, and its performance, explainability, clinical relevance and generalisability were evaluated. We investigated 4254 patients with cancer-associated malnutrition (discovery set = 2977, test set = 1277). There were 2783 men and 1471 women (median age = 61 years). RM was identified in 754 (17·7 %) patients. RM/non-RM groups showed distinct patterns of weight and muscle dynamics, and RM was negatively correlated to the progressive stages of cancer cachexia (r = –0·340, P < 0·001). WAL-net was the state-of-the-art model among all ML algorithms evaluated, demonstrating favourable performance to predict RM in the test set (AUC = 0·924, 95 % CI = 0·904, 0·944) and an external validation set (n 798, AUC = 0·909, 95 % CI = 0·876, 0·943). Model-predicted RM using baseline information was associated with lower future risks of underweight, sarcopenia, performance status decline and progression of malnutrition (all P < 0·05). This study presents an explainable deep learning model, the WAL-net, for early identification of RM in patients with cancer. These findings might help the management of cancer-associated malnutrition to optimise patient outcomes in multidisciplinary cancer care.

Schistosomiasis is a parasitic disease that imposes a significant burden on society. The eggs are the primary pathogenic factor in schistosomiasis, and their accumulation in liver could lead to the formation of granulomas and liver fibrosis. However, the metabolic changes in liver resulting from schistosomiasis remain poorly understood. We established a mouse model of schistosomiasis japonica, where the eggs accumulate in the liver and form egg granulomas. We used mass spectrometry imaging to analyze the differences in metabolites among various liver regions, including the liver tissue from normal mice, the liver area outside the granulomas in schistosomiasis mice, and the granuloma region in schistosomiasis mice. There were significant differences in metabolites between different liver regions, which enriched in metabolic pathways such as the biosynthesis of unsaturated fatty acids, taurine and hypotaurine metabolism, glycerophospholipid metabolism, glycolysis/gluconeogenesis, purine metabolism, arachidonic acid metabolism, and bile secretion. In normal liver tissue, higher concentrations of oleic acid (FA (18:1)), eicosapentaenoic acid (FA (20:5)), and L-glutamine were observed. In liver regions outside the granulomas, D-glucose and pyruvic acid were elevated compared to those in normal mice. Taurine increased in the liver of schistosomiasis. Meanwhile, there were elevated uric acid and spermidine in the egg granulomas. We employed mass spectrometry imaging technology to investigate metabolic reprogramming in liver of Schistosoma japonicum-infected mice. We explored the spatial distribution of differential metabolites in liver of schistosomiasis including unsaturated fatty acids, taurine, glutamine, spermidine, and uric acid. Our research provides valuable insights for further elucidating metabolic reprogramming in schistosomiasis.

Vaccines have revolutionised the field of medicine, eradicating and controlling many diseases. Recent pandemic vaccine successes have highlighted the accelerated pace of vaccine development and deployment. Leveraging this momentum, attention has shifted to cancer vaccines and personalised cancer vaccines, aimed at targeting individual tumour-specific abnormalities. The UK, now regarded for its vaccine capabilities, is an ideal nation for pioneering cancer vaccine trials. This article convened experts to share insights and approaches to navigate the challenges of cancer vaccine development with personalised or precision cancer vaccines, as well as fixed vaccines. Emphasising partnership and proactive strategies, this article outlines the ambition to harness national and local system capabilities in the UK; to work in collaboration with potential pharmaceutic partners; and to seize the opportunity to deliver the pace for rapid advances in cancer vaccine technology.

Computerized assessment provides rich multidimensional data including trial-by-trial accuracy and response time (RT) measures. A key question in modeling this type of data is how to incorporate RT data, for example, in aid of ability estimation in item response theory (IRT) models. To address this, we propose a joint model consisting of a two-parameter IRT model for the dichotomous item response data, a log-normal model for the continuous RT data, and a normal model for corresponding paper-and-pencil scores. Then, we reformulate and reparameterize the model to capture the relationship between the model parameters, to facilitate the prior specification, and to make the Bayesian computation more efficient. Further, we propose several new model assessment criteria based on the decomposition of deviance information criterion (DIC) the logarithm of the pseudo-marginal likelihood (LPML). The proposed criteria can quantify the improvement in the fit of one part of the multidimensional data given the other parts. Finally, we have conducted several simulation studies to examine the empirical performance of the proposed model assessment criteria and have illustrated the application of these criteria using a real dataset from a computerized educational assessment program.

Objectives: Depression is the second most prevalent mental illness among the elderly. Nonetheless, treatment- resistant depression (TRD) is prevalent among the elderly; one-third of elderly patients with major depressive disorder (MDD) who received antidepressant treatment failed to achieve remission. Although there have been several studies regarding the associations between MDD and increased mortality and suicidal risk, studies between TRD and mortality/suicidal risk in the elderly still remains limited. In this national cohort study, we examined the association between TRD, non-TRD MDD, and non-depression with all-cause mortality, accident mortality, and suicide mortality.

Methods: For this retrospective longitudinal analysis on the entire population, the National Health Insurance Research Database of Taiwan, which comprises claims data from a lifetime insurance program and provided comprehensive medical inpatient and outpatient information categorized by ICD-9-CM and ICD-10. The National Mortality Registry offered information regarding mortality resulting from all causes, natural causes, suicide, and accidents. A cohort of ≥60-year-old patients, including both those with and without MDD, was observed between January 2003 and December 2017. Individuals were classified as TRD if they had undergone aminimum of two distinct antidepressant trials within the current episode’s two-year duration and dose, as documented in the prescribing records. Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) were calculated for mortality risk utilizing Cox regression models.

Results: Among those >60 years old, after adjusting with sex and comorbidities, TRD was associated with increased risk of suicide (aHR 7.4, 95% CI [5.6-9.8]; MDD without TRD 4.4 [4.1- 4.6], compared with non-MDD group). Simliar risk of accident mortality was observed among three groups (TRD aHR 1.3 [0.9-1.9]; MDD without TRD 0.9 [0.9-1.0], compared with non-MDD group). Surprisely, TRD might presented lower mortality risk of natural mortality than the non- MDD group (TRD aHR 0.8 [0.7-0.8]; MDD without TRD 0.9 [0.8-0.9], compared with non- MDD group).

Conclusions: The suicide mortality among elderly patients with TRD is higher in comparison to non-MDD patients; nevertheless, accident mortality does not appear to have increased and the natural mortality rate is reduced. The lower mortality may reflect patient selection, and the contributing factors need further evaluation.

Developing a model to describe the shock-accelerated cylindrical fluid layer with arbitrary Atwood numbers is essential for uncovering the effect of Atwood numbers on the perturbation growth. The recent model (J. Fluid Mech., vol. 969, 2023, p. A6) reveals several contributions to the instability evolution of a shock-accelerated cylindrical fluid layer but its applicability is limited to cases with an absolute value of Atwood numbers close to $1$, due to the employment of the thin-shell correction and interface coupling effect of the fluid layer in vacuum. By employing the linear stability analysis on a cylindrical fluid layer in which two interfaces separate three arbitrary-density fluids, the present work generalizes the thin-shell correction and interface coupling effect, and thus, extends the recent model to cases with arbitrary Atwood numbers. The accuracy of this extended model in describing the instability evolution of the shock-accelerated fluid layer before reshock is confirmed via direct numerical simulations. In the verification simulations, three fluid-layer configurations are considered, where the outer and intermediate fluids remain fixed and the density of the inner fluid is reduced. Moreover, the mechanisms underlying the effect of the Atwood number at the inner interface on the perturbation growth are mainly elucidated by employing the model to analyse each contribution. As the Atwood number decreases, the dominant contribution of the Richtmyer–Meshkov instability is enhanced due to the stronger waves reverberated inside the layer, leading to weakened perturbation growth at initial in-phase interfaces and enhanced perturbation growth at initial anti-phase interfaces.

Caryocaridids are a unique representative of pelagic arthropods from the Ordovician period. They are typically found as flattened carapaces in mudstones and shales. This study reports on a species of caryocaridids, Soomicaris cedarbergensis, discovered in the Lower Ordovician of northwestern Xinjiang, NW China. The species shows the rare enrolled carapaces with a preserved cuticular ultrastructure. These specimens of caryocaridids from Xinjiang are the first reported in the Yili Block, and provide the substantial evidence that the paleogeographic distribution of caryocaridid phyllocarids could extend to the Central Asian Orogenic Belt. This species existed from the late Tremadocian until the end of the Ordovician (Hirnantian), making it the longest-ranging known species of caryocaridids. The carapace cuticle of S. cedarbergensis is composed of carbonate-fluorapatite and can be divided into three mineralized lamellae: outer, middle, and inner. The outer and inner lamellae each consist of three layers that correspond to the epicuticle, exocuticle, and endocuticle of extant crustacean carapaces. Moreover, the polygonal reticulation structure of the carapace in archaeostracans appears to be similar in shape and size to the hemolymph sinuses of leptostracans. This unique ultrastructure of the carapace cuticle in caryocaridids is believed to be better suited for a pelagic lifestyle.

The global challenge of methane emissions from enteric fermentation is critical, as it contributes significantly to atmospheric greenhouse gases and represents a loss of energy that could otherwise be utilized by ruminants. With the increasing demand for dairy and meat products, finding effective methods to reduce methane production is essential. This review explores the use of advanced meta-omics techniques – including metagenomics, metatranscriptomics, metaproteomics, and metabolomics – to deepen our understanding of ruminal methane production and identify potential strategies for its mitigation. These high-throughput technologies provide comprehensive insights into the rumen microbial communities and their metabolic functions by analyzing DNA, RNA, proteins, and metabolites directly from environmental samples. Metagenomics and metatranscriptomics offer a detailed view of microbial diversity and gene expression, while metaproteomics can identify specific enzymes and proteins directly involved in methane production pathways, revealing potential targets for mitigation strategies. Integrating these meta-omics approaches allows for a holistic understanding of the microbial processes that drive methane emissions, enabling the development of more precise interventions, such as tailored dietary modifications and the use of specific inhibitors. This review underscores the importance of a multi-omics strategy in characterizing microbial roles and interactions within the rumen, which is crucial for devising effective and sustainable methods to reduce methane emissions without compromising livestock productivity.

The evolution of the water-entry cavity affects the impact load and the motion of the body. This paper adopts the Eulerian finite element method for multiphase flow for simulations of the high-speed water-entry process. The accuracy and convergence of the numerical method are verified by comparing it with the experimental data and the results of the transient cavity dynamics theory. Based on the results, the representative characteristics of the cavity are discussed from the perspective of the cavity cross-section. It is found that the asymmetry of the cavity expansion and contraction durations is related to the motion of the free surface and the closure of the cavity. The uplift of the free surface suppresses cavity expansion, while the jet generated from free surface closure accelerates cavity contraction. The duration of the contraction of the cavity near the free surface is shorter than the expansion duration due to the change in the velocity distribution caused by the free surface motion. The necking phenomenon during deep closure leads to an increase in the internal pressure of the cavity, prolonging cavity contraction near the deep closure area. This work provides new insights into the cavity dynamics in high-speed water entry.