The demand for separating and analysing rare target cells is increasing dramatically for vital applications such as cancer treatment and cell-based therapies. However, there remains a grand challenge for high-throughput and label-free segregation of lesion cells with similar sizes. Cancer cells with different invasiveness usually manifest distinct deformability. In this work, we employ a hydrogel microparticle system with similar sizes but varied stiffness to mimic cancer cells and examine in situ their deformation and focusing under microfluidic flow. We first demonstrate the similar focusing behaviour of hydrogel microparticles and cancer cells in confined flow that is dominated by deformability-induced lateral migration. The deformation, orientation and focusing position of hydrogel microparticles in microfluidic flow under different Reynolds numbers are then systematically observed and measured using a high-speed camera. Linear correlations of the Taylor deformation and tilt angle of hydrogel microparticles with the capillary number are revealed, consistent with theoretical predictions. Detailed analysis of the dependence of particle focusing on the flow rate and particle stiffness enables us to identify a linear scaling between the equilibrium focusing position and the major axis of the deformed microparticles, which is uniquely determined by the capillary number. Our findings provide insights into the focusing and dynamics of soft beads, such as cells and hydrogel microparticles, under confined flow, and pave the way for applications including the separation and identification of circulating tumour cells, drug delivery and controlled drug release.

Motion primitives play an important role in motion planning for autonomous vehicles, as they effectively address the sampling challenges inherent in nonholonomic motion planning. Employing motion primitives (MPs) is a widely accepted approach in nonholonomic motion planning based on sampling. This study specifically addresses the problem of learning from human-driving data to create human-like trajectories from predefined start-to-end states, which then serve as MP within the sampling-based nonholonomic motion planning framework. In this paper, we propose a deep learning-based method for generating MP that capture human-driving trajectory data features. By processing human-driving trajectory data, we create a Motion Primitive dataset that uniformly covers typical urban driving scenarios. Based on this dataset, a vehicle model long short-term memory neural network model is constructed to learn the features of the human-driving trajectory data. Finally, a framework for the generation of MP for practical applications is given based on this neural network. Our experiments, which focus on the dataset, the MMP generation network, and the generation process, demonstrate that our method significantly improves the training efficacy of the MP generation network. Additionally, the MP generated by our method exhibit higher accuracy compared to traditional methods.

The development of Maritime Autonomous Surface Ship (MASS) is progressing rapidly within the maritime industry. Degree Two of MASS (MASS-DoA2), balancing human oversight and autonomous efficiency, will likely gain regulatory approval and industry acceptance. MASS-DoA2 possesses different control modes to adapt to various scenarios. However, the control-switching mechanisms among operators at shore control centres, autonomous navigation systems and number of seafarers onboard remain ambiguous, which poses a new risk that may significantly influence navigation safety. This study focuses on MASS-DoA2 and carries out a systematic review of autonomous ship guidelines. A questionnaire was designed based on the review findings, and a survey was carried out among captains and researchers in related fields. The review identified 11 control-switching scenarios with suggested takeover agents and the switching process and outlined the priority relationship between various takeover agents. Finally, a control-switching framework for MASS – DoA2 is proposed. It can serve as a theoretical framework for research on MASS's dynamic degree of autonomy and provide a reference for maritime regulatory authorities in establishing MASS – DoA2 control-switching mechanisms.

Laser-driven inertial confinement fusion (ICF) diagnostics play a crucial role in understanding the complex physical processes governing ICF and enabling ignition. During the ICF process, the interaction between the high-power laser and ablation material leads to the formation of a plasma critical surface, which reflects a significant portion of the driving laser, reducing the efficiency of laser energy conversion into implosive kinetic energy. Effective diagnostic methods for the critical surface remain elusive. In this work, we propose a novel optical diagnostic approach to investigate the plasma critical surface. This method has been experimentally validated, providing new insights into the critical surface morphology and dynamics. This advancement represents a significant step forward in ICF diagnostic capabilities, with the potential to inform strategies for enhancing the uniformity of the driving laser and target surface, ultimately improving the efficiency of converting laser energy into implosion kinetic energy and enabling ignition.

In this paper, we propose a novel and highly effective variational Bayesian expectation maximization-maximization (VBEM-M) inference method for log-linear cognitive diagnostic model (CDM). In the implementation of the variational Bayesian approach for the saturated log-linear CDM, the conditional variational posteriors of the parameters that need to be derived are in the same distributional family as the priors, the VBEM-M algorithm overcomes this problem. Our algorithm can directly estimate the item parameters and the latent attribute-mastery pattern simultaneously. In contrast, Yamaguchi and Okada’s (2020a) variational Bayesian algorithm requires a transformation step to obtain the item parameters for the log-linear cognitive diagnostic model (LCDM). We conducted multiple simulation studies to assess the performance of the VBEM-M algorithm in terms of parameter recovery, execution time, and convergence rate. Furthermore, we conducted a series of comparative studies on the accuracy of parameter estimation for the DINA model and the saturated LCDM, focusing on the VBEM-M, VB, expectation-maximization, and Markov chain Monte Carlo algorithms. The results indicated that our method can obtain more stable and accurate estimates, especially for the small sample sizes. Finally, we demonstrated the utility of the proposed algorithm using two real datasets.

When latent variables are used as outcomes in regression analysis, a common approach that is used to solve the ignored measurement error issue is to take a multilevel perspective on item response modeling (IRT). Although recent computational advancement allows efficient and accurate estimation of multilevel IRT models, we argue that a two-stage divide-and-conquer strategy still has its unique advantages. Within the two-stage framework, three methods that take into account heteroscedastic measurement errors of the dependent variable in stage II analysis are introduced; they are the closed-form marginal MLE, the expectation maximization algorithm, and the moment estimation method. They are compared to the naïve two-stage estimation and the one-stage MCMC estimation. A simulation study is conducted to compare the five methods in terms of model parameter recovery and their standard error estimation. The pros and cons of each method are also discussed to provide guidelines for practitioners. Finally, a real data example is given to illustrate the applications of various methods using the National Educational Longitudinal Survey data (NELS 88).

The objective of this study was to investigate the genetic link between the age at first birth (AFB) and the occurrence of preterm labor and delivery, utilizing Mendelian randomization (MR) data alongside genomewide association analysis (GWAS). We obtained AFB-related GWAS summary data from the European Bioinformatics Institute database and preterm labor and delivery data was sourced from the FinnGen Consortium. The study considered AFB as exposure variables, with the incidence of preterm labor and delivery serving as the outcome variable. Several MR analysis methods, such as inverse-variance weighted (IVW), MR Egger, weighted median, simple, and weighted mode were utilized. Besides MR-Egger intercepts, Cochrane’s Q test evaluated heterogeneity in the MR data, while MR-PRESSO test checked for horizontal pleiotropy. To assess the association’s sensitivity, A leave-one-out approach was utilized to evaluate the sensitivity of the association. The IVW analysis validated that AFB is an independent risk factor for preterm labor and delivery (p < .001). Horizontal pleiotropy was unlikely to bias causality (p > .05). The likelihood of horizontal pleiotropy affecting causality was low (p > .05), and there was no indication of heterogeneity among the genetic variants (p > .05). Ultimately, a leave-one-out analysis confirmed the stability and reliability of this correlation. Our research indicated that AFB is a protective factor for preterm labor and delivery. Further research is required to clarify the possible mechanisms.

Direct numerical simulations are performed to explore the evolution behaviour of the turbulent/non-turbulent interface (TNTI) in a temporally evolving turbulent plane jet, using the evolution equation for the TNTI surface area. A novel algorithm is used to calculate the surface area of the TNTI and entrainment flux. It is shown that the surface area remains relatively constant, which leads to the mean entrainment velocity being inversely proportional to the square root of time. On average, the effects of the stretching and curvature/viscous terms on the TNTI area roughly counterbalance each other, while the curvature/inviscid term associated with vortex stretching is virtually zero. More specifically, the stretching term contributes to the production of the surface area, while the curvature/viscous term is associated with a destruction in the surface area. The local effect of the curvature/viscous term exhibits high spatial intermittency with small-scale extreme/intense events, whereas the effect of the large-scale stretching term is more continuous. To shed light on the contribution of curvature/viscous term to the evolution of the surface area, we decompose it into three components. The effect of the curvature/normal diffusion term (the curvature/viscous dissipation term) in the bulging regions (the valley regions) mainly contributes to the production of the area. The continuous decrease of the average mean curvature is associated with the production of the bulging regions and the destruction of the valley regions. Finally, although the entrainment velocity is mainly dominated by the normal diffusion effect, all three components related to the viscous effect are indispensable to the production and destruction of the TNTI area. This numerical study contributes to a better understanding of the evolution of the TNTI area.

Introduction: Agitation in Alzheimer’s dementia (AAD) confers significant humanistic and economic burden; however, factors, and relationships between them, which drive the extent of this burden are poorly understood. The Objectives of this study was to review and gather evidence on the burden of AAD in order to develop a conceptual framework capturing its effects on patients, their families, clinicians (i.e., care teams), and society, which can then be used to guide further research into how the burden of AAD might be reduced.

Methods: Evidence on the burden of AAD was identified via a targeted literature review. Data were classified into societal, patient/family/care team, and mitigating factors. A conceptual framework (i.e., a visual representation of variables and associations between them) was developed to map the relationships between factors and illustrate the precedents and downstream effects of agitated behaviors on patient and caregiver outcomes, including healthcare resource utilization (HCRU), costs, and admission to long term care(LTC).

Results: Agitated behaviors were found to directly impact caregiving demands in terms of the number of hours required to care for patients. Similarly, levels of caregiver stress (i.e., total caregiver burden, personal strain, role strain, and guilt) were found to be associated with the frequency and intensity of AAD. Burden also extended to care teams via increased HCRU (i.e., pharmacy, outpatient, inpatient, and emergency room visits), and consequently costs, relative to non-agitated patients. Indirectly, through caregiving demands, agitation also affected the rate of placement in formal care and LTC, both of which are associated with incremental costs. Evidence also indicated that mitigating factors such as pharmacological treatment could impact the frequency and intensity of agitated behaviors, potentially affecting downstream HCRU and costs. Limited evidence exists on the optimal means of employing such strategies to limit caregiver demands and stress.

Conclusions: This study demonstrated the complex interplay of factors which drive the burden of AAD and the need which exists for novel ways to improve outcomes for those impacted by the disease. Better insight into the mechanism by which agitated behaviors influence caregiver demands and stress could help improve mitigation strategies both within family units and the larger health system.

A high-energy picosecond 355 nm ultraviolet (UV) laser operating at 100 Hz was demonstrated. A 352 mJ, 69 ps, 1064 nm laser at 100 Hz was realized firstly by cascaded regenerative, laser diode end-pumped single-pass and side-pumped main amplifiers. The stimulated Raman scattering-based beam shaping technique, thermally induced birefringence compensation and 4f spatial filter-image relaying systems were used to maintain a relatively homogeneous beam intensity distribution during the amplification process. By using lithium triborate crystals for second- and third-harmonic generation (THG), a 172 mJ, approximately 56 ps, 355 nm UV laser was achieved with a THG conversion efficiency of 49%. To the best of our knowledge, it is the highest pulse energy of a picosecond 355 nm UV laser so far. The beam quality factor ${M}^2$ and pulse energy stability were ${M}_x^2$=3.92, ${M}_y^2$=3.71 and root mean square of 1.48%@3 hours. This laser system could play significant roles in applications including photoconductive switch excitation, laser drilling and laser micro-fabrication.

Accurately converting satellite instantaneous evapotranspiration (λETi) over time to daily evapotranspiration (λETd) is crucial for estimating regional evapotranspiration from remote sensing satellites, which plays an important role in effective water resource management. In this study, four upscaling methods based on the principle of energy balance, including the evaporative fraction method (Eva-f method), revised evaporative fraction method (R-Eva-f method), crop coefficient method (Kc-ET0 method) and direct canopy resistance method (Direct-rc method), were validated based on the measured data of the Bowen ratio energy balance system (BREB) in maize fields in northwestern (NW) and northeastern (NE) China (semi-arid and semi-humid continental climate regions) from 2021 to 2023. Results indicated that Eva-f and R-Eva-f methods were superior to Kc-ET0 and Direct-rc methods in both climatic regions and performed better between 10:00 and 11:00, with mean absolute errors (MAE) and coefficient of efficiency (ɛ) reaching <10 W/m2 and > 0.91, respectively. Comprehensive evaluation of the optimal upscaling time using global performance indicators (GPI) showed that the Eva-f method had the highest GPI of 0.59 at 12:00 for the NW, while the R-Eva-f method had the highest GPI of 1.18 at 11:00 for the NE. As a result, the Eva-f approach is recommended as the best way for upscaling evapotranspiration in NW, with 12:00 being the ideal upscaling time. The R-Eva-f method is the optimum upscaling method for the Northeast area, with an ideal upscaling time of 11:00. The comprehensive results of this study could be useful for converting λETi to λETd.

Weedy rice (Oryza sativa f. spontanea Auct. ex Backer) is a troublesome annual weed from the Gramineae family and infests rice (Oryza sativa L.) fields globally, with a notable presence in China. However, limited information is available regarding the effects of diverse environmental factors on its germination and emergence. A better understanding of the seed biology and ecology of weedy rice is crucial for developing effective weed management strategies. Experiments were conducted to evaluate the effects of temperature, light, soil burial depth, wheat (Triticum aestivum L.) crop residue amount, salt stress, osmotic stress, and radiant heat on the germination and seedling emergence of weedy rice. Weedy rice exhibited robust germination (>98%) when exposed to varying day/night temperatures (20/15 to 35/30 C) and remained unaffected by light conditions. Seedling emergence was not influenced within the top 5-cm soil layer, where 100% of the seedlings emerged. However, emergence decreased as the soil burial depth increased, eventually resulting in no emergence from a burial depth of 11 cm. The soil burial depth required for 50% of the maximum emergence was 8.3 cm. Seedling emergence ranged from 97% to 100% across different amounts of the wheat straw residue cover (0 to 10,000 kg ha−1). The sodium chloride concentration and osmotic potential required for 50% were 230.8 mM and −0.5 MPa, respectively. No germination was observed when weedy rice seeds were exposed to >110 C pretreatment (radiant heat for 5 min), indicating that residue burning could reduce infestation of weedy rice. The insights gained from this study contribute valuable knowledge to enhance the integrated management of weedy rice in China.

This study aimed to understand the potassium voltage-gated channel KQT-like subfamily, member 1 gene polymorphism in a rural elderly population in a county in Guangxi and to explore the possible relationship between its gene polymorphism and blood sugar. The 6 SNP loci of blood DNA samples from 4355 individuals were typed using the imLDRTM Multiple SNP Typing Kit from Shanghai Tianhao Biotechnology Co. The data combining epidemiological information (baseline questionnaire and physical examination results) and genotyping results were statistically analyzed using GMDR0.9 software and SPSS22.0 software. A total of 4355 elderly people aged 60 years and above were surveyed in this survey, and the total abnormal rate of glucose metabolism was 16·11 % (699/4355). Among them, male:female ratio was 1:1·48; the age group of 60–69 years old accounted for the highest proportion, with 2337 people, accounting for 53·66 % (2337/4355). The results of multivariate analysis showed that usually not doing farm work (OR 1·26; 95 % CI 1·06, 1·50), TAG ≥ 1·70 mmol/l (OR 1·19; 95 % CI 1·11, 1·27), hyperuricaemia (OR 1·034; 95 % CI 1·01, 1·66) and BMI ≥ 24 kg/m2 (OR 1·06; 95 % CI 1·03, 1·09) may be risk factors for abnormal glucose metabolism. Among all participants, rs151290 locus AA genotype, A allele carriers (AA+AC) were 0.70 times more likely (0.54 to 0.91) and 0.82 times more likely (0.70 to 0.97) to develop abnormal glucose metabolism than CC genotype carriers, respectively. Carriers of the T allele at the rs2237892 locus (CT+TT) were 0.85 times more likely to have abnormal glucose metabolism than carriers of the CC genotype (0.72 to 0.99); rs2237897 locus CT gene. The possibility of abnormal glucose metabolism in the carriers of CC genotype, TT genotype and T allele (CT + TT) is 0·79 times (0·67–0·94), 0·74 times (0·55–0·99) and 0·78 times (0·66, 0·92). The results of multifactor dimensionality reduction showed that the optimal interaction model was a three-factor model consisting of farm work, TAG and rs2237897. The best model dendrogram found that the interaction between TAG and rs2237897 had the strongest effect on fasting blood glucose in the elderly in rural areas, and they were mutually antagonistic. Environment–gene interaction is an important factor affecting abnormal glucose metabolism in the elderly of a county in Hechi City, Guangxi.

In a horizontally heated melting system, where a solid substance is subject to melting by a warmer liquid beneath, the presence of solute in the liquid introduces a complex interplay between temperature and concentration dynamics. Employing a recently developed sharp interface method (Xue et al., J. Comput. Phys., vol. 491, 2023), we conduct direct numerical simulations to investigate the transient behaviour of the system across a broad range of Rayleigh numbers and solute concentrations. Our observations reveal distinct flow regimes: at low concentrations, the system resembles a temperature-driven melting problem, characterized by vortex rolls beneath the melting interface. As the solute concentration increases, a stably stratified layer emerges beneath the interface, leading to the transition from thermal convection to penetrative convection, which resembles those flow characteristics observed in the double-diffusive convection. This shift results from the competition between the stabilizing effect induced by solute concentration gradient and the destabilizing effect caused by temperature gradient. Otherwise in the diffusion regime, characterized by very high solute concentrations, the flow becomes static due to the complete suppression of convection by the stably stratified layer. This regime further exhibits two distinct patterns: ‘melting’ and ‘dissolution’. Beyond characterizing diverse flow patterns, our study conducts a quantitative analysis, examining heat/mass transfer, melting rates, and the evolution of temperature and concentration at the interface. These insights contribute to a better understanding of the intricate interplay between temperature and solute concentration during phase change, with implications for accurately estimating melting rates in binary fluid systems.

A simplified configuration was developed to facilitate the mode transition process within an over-under Turbine-Based Combined Cycle (TBCC) inlet. Leveraging dynamic mesh technology, an unsteady numerical simulation of the mode transition was conducted, emphasising the flow characteristics of the mode transition and the impact of key similarity criteria numbers. The findings indicate that at an incoming Mach number of 2.0, the mode transition is paired with a continuous alteration in the capture mass flow of the high-speed duct. This continual change instigates the inlet unstarting, with subsequent flow characteristics being contingent on the historical effect, exhibiting a degree of hysteresis characteristics. When the scale effect is considered, it is observed that a larger model scale results in higher Reynolds (Re) and Strouhal (St) numbers. This directly contributes to a notable delay in the unstart moment, a decrease in the unstart interval, and an enlargement of the hysteresis loop. An examination of control variables reveals that the Re number marginally influences mode transition characteristics, while the St number’s effect constitutes approximately 90% of the scale effect. This conclusively demonstrates that the St number is the predominant similarity criterion number in the mode transition process.

This study investigated the impact of diallyl disulfide (DADS) on oxidative stress induced by hydrogen peroxide (H2O2) in ovine rumen epithelial cells (RECs). Initially, the effects of DADS were evaluated on cellular reactive oxygen species (ROS) levels, antioxidant capacity in RECs were estimated. Then, RNA-seq analysis was conducted in DADS-treated and untreated cells to analyze the differential gene expression, as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Finally, the effects of DADS on Kelch-like ECH associated protein 1/the nuclear factor erythroid 2-related factor 2 (Keap1/Nrf2) signaling pathway in RECs were evaluated. Results showed that DADS remarkably enhanced superoxide dismutase (SOD) activity and total antioxidant capacity (T-AOC) (P < 0.05) while reducing ROS and malonaldehyde production (P < 0.05) in H2O2-treated RECs. Transcriptomic analysis revealed that DADS might influence glutathione synthesis through cysteine and methionine metabolism, thereby affecting the transcription of genes involved in immunity and oxidative stress. The DADS treatment resulted in increased nuclear translocation of Nrf2 and upregulation of mRNA and protein levels of quinone oxidoreductase 1, heme oxygenase 1, and Nrf2. The Nrf2-specific inhibitor nullified the protective effects of DADS on malonaldehyde formation induced by H2O2 and decreased T-AOC and SOD activities. In conclusion, DADS demonstrated the ability to alleviate oxidative stress in RECs by promoting antioxidative capacity through the Keap1/Nrf2 signaling pathway.

This study examines the pursuit-evasion game involving unmanned aerial vehicles (UAVs), with a specific focus on the scenario of N-pursuers-one-escapee. The primary objective is to develop an optimal strategy for the escapee when the pursuers possess superior capabilities. To obtain this objective, we conduct the following study. Firstly, to enhance realism, a non-cooperative differential game model is formulated, incorporating multiple motion characteristics, including aerodynamics, overloading, and imposed constraints. Secondly, the end-value performance index is subsequently converted to an integral one, simplifying the solution process of the Hamilton-Jacobi-Bellman (HJB) equation. An iterative method is utilised to determine the covariates using the Cauchy initial value problem, and its convergence and uniqueness are established. The optimal avoidance strategy is subsequently derived from the covariates. Finally, the superiority of the proposed strategy is validated through simulation experiments and compared to three advanced optimal avoidance strategies. A total of 1,000 anti-jamming simulation experiments are conducted to verify the robustness of the proposed strategy.

Studies on obesity and risk factors from a life-course perspective among residents in the Tibet Plateau with recent economic growth and increasing obesity are important and urgently needed. The birth cohort in this area provides a unique opportunity to examine the association between maternal dietary practice and neonatal obesity. The study aims to detect the prevalence of obesity among neonates, associated with maternal diet and other factors, supporting life-course strategies for obesity control. A cohort of pregnant women was enrolled in Tibet Plateau and followed till childbirth. Dietary practice during pregnancy was assessed using the Chinese FFQ – Tibet Plateau version, food items and other variables were associated with the risk for obesity of neonates followed by logistic regression, classification and regression trees (CART) and random forest. Of the total 1226 mother–neonate pairs, 40·5 % were Tibetan and 5·4 % of neonates with obesity. Consuming fruits as a protective factor for obesity of neonates with OR (95 % CI) = 0·61 (0·43, 0·87) from logistic regression; as well as OR = 0·20 (0·12, 0·35) for consuming fruits (≥ weekly) from CART. Removing fruit consumption to avoid overshadowing effects of other factors, the following were influential from CART: maternal education (more than middle school, OR = 0·22 (0·13, 0·37)) and consumption of Tibetan food (daily, OR = 3·44 (2·08, 5·69). Obesity among neonates is prevalent in the study population. Promoting healthy diets during pregnancy and strengthening maternal education should be part of the life-course strategies for obesity control.