Yiyang Dahegu rice (YyDHG) is an important agricultural specialty of Yiyang County, Jiangxi Province, and it is also a significant component of the local cultural and economic development. In this experiment, 89 samples of Dahegu rice (DHG) were collected from Jiangxi Province, including 52 samples of YyDHG and 37 samples of DHG from other regions within Jiangxi Province (oDHG). Comprehensive analysis was conducted using polyacrylamide gel electrophoresis, field phenotypic observation, population structure analysis and quality analysis. The results of variety identification indicated that the 89 samples actually comprised 52 distinct varieties, including 19 varieties of YyDHG. Population analysis has revealed rich genetic diversity among DHG varieties within Jiangxi Province, yet no significant subpopulation differentiation was observed between YyDHG and oDHG. Quality experiments demonstrated that YyDHG exhibits significant differences in appearance quality from oDHG, but no notable differences in milling quality or cooked taste and flavour. This suggests that the competitiveness of YyDHG in the market may not entirely depend on its unique quality characteristics, but rather more on its cultural value and brand effect. This experiment conducted a comprehensive analysis of the variety characteristics, genetic diversity and quality traits of YyDHG. Not only does it provide a scientific basis for the breeding and germplasm resource conservation of YyDHG, but it also holds positive implications for promoting the development of its industry.

Nutrition intervention is an effective way to improve flesh qualities of fish. The effect of feed supplementation with glutamate (Glu) on flesh quality of gibel carp (Carassius gibelio) was investigated. In trial 1, the fish (initial weight: 37.49 ± 0.08 g) were fed two practical diets with 0 and 2% Glu supplementation. In trial 2, the fish (37.26 ± 0.04 g) were fed two purified diets with 0 and 3% Glu supplementation. The results after feeding trials showed that dietary Glu supplementation increased the hardness and springiness of muscle, whether using practical or purified diets. Glu-supplemented diets increased the thickness and density of myofibres and collagen content between myofibres. Furthermore, Glu promoted muscle protein deposition by regulating the IGF-1-AKT-mTOR signalling pathway, and enhanced the myofibre hypertrophy by upregulating genes related to myofibre growth and development (mef2a, mef2d, myod, myf5, mlc, tpi and pax7α). The protein deposition and myofibre hypertrophy in turn improved the flesh texture. In addition, IMP content in flesh increased when supplementing Glu whether to practical or to purified diet. Metabolomics confirmed that Glu promoted the deposition of muscle-flavoured substances and purine metabolic pathway most functioned, echoed by the upregulation of key genes (ampd, ppat and adsl) in purine metabolism. The sensory test also clarified that dietary Glu improved the flesh quality by enhancing the muscle texture and flavour. Conclusively, dietary Glu supplementation can improve the flesh quality in this fish, which can further support evidence from other studies more generally that improve flesh quality of cultured fish.

Assemblies of slender structures forming brushes are common in daily life from sweepers to pastry brushes and paintbrushes. These types of porous objects can easily trap liquid in their interstices when removed from a liquid bath. This property is exploited to transport liquids in many applications, ranging from painting, dip-coating and brush-coating to the capture of nectar by bees, bats and honeyeaters. Rationalising the viscous entrainment flow beyond simple scaling laws is complex due to the multiscale structure and the multidirectional flow. Here, we provide an analytical model, together with precision experiments with ideal rigid brushes, to fully characterise the flow through this anisotropic porous medium as it is withdrawn from a liquid bath. We show that the amount of liquid entrained by a brush varies non-monotonically during the withdrawal at low speed, is highly sensitive to the different parameters at play and is very well described by the model without any fitting parameter. Finally, an optimal brush geometry maximising the amount of liquid captured at a given retraction speed is derived from the model and experimentally validated. These optimal designs open routes towards efficient liquid-manipulating devices.

Against the proliferation of large language model (LLM) based Artificial Intelligence (AI) products such as ChatGPT and Gemini, and their increasing use in professional communication training, researchers, including applied linguists, have cautioned that these products (re)produce cultural stereotypes due to their training data. However, there is a limited understanding of how humans navigate the assumptions and biases present in the responses of these LLM-powered systems and the role humans play in perpetuating stereotypes during interactions with LLMs. In this article, we use Sequential-Categorial Analysis, which combines Conversation Analysis and Membership Categorization Analysis, to analyze simulated interactions between a human physiotherapist and three LLM-powered chatbot patients of Chinese, Australian, and Indian cultural backgrounds. Coupled with analysis of information elicited from LLM chatbots and the human physiotherapist after each interaction, we demonstrate that users of LLM-powered systems are highly susceptible to becoming interactionally entrenched in culturally essentialized narratives. We use the concepts of interactional instinct and interactional entrenchment to argue that whilst human–AI interaction may be instinctively prosocial, LLM users need to develop Critical Interactional Competence for human–AI interaction through appropriate and targeted training and intervention, especially when LLM-powered tools are used in professional communication training programs.

Antimicrobial prescribing differences between physicians and nurse practitioners (NPs) remain poorly characterized. We compared prescribing practices at a safety-net hospital. NPs adhered more to pneumonia guidelines, while physicians had better adherence for abdominal and urinary infections. Ineffective therapy was more common for NPs. These gaps highlight important stewardship opportunities.

The phenomenon of bulge evolution under the action of gravity on shallow water is prevalent both in natural occurrences and engineering industries. However, despite its ubiquity, its physical process remains largely unexplored. The evolution of bulge contains two fundamental physical processes: collapse and propagation. The collapse process can be further divided into two sub-processes: squeezing process and diffusion process. Based on the weakly nonlinear shallow water assumption with the classical perturbation method, the governing equations controlling the surface elevations in the diffusion process and the propagation process have been theoretically derived, where a bulge-induced surface pressure is modeled for the propagation process. Moreover, their scaling laws for the decay of wave height are also established, which have been validated by direct numerical simulation results. The derived scaling laws for wave height attenuation of bulge evolution provide profound insights, which hold the potential to applications in the engineering industry.

An actively controllable cascaded proton acceleration driven by a separate 0.8 picosecond (ps) laser is demonstrated in proof-of-principle experiments. MeV protons, initially driven by a femtosecond laser, are further accelerated and focused into a dot structure by an electromagnetic pulse (EMP) on the solenoid, which can be tuned into a ring structure by increasing the ps laser energy. An electrodynamics model is carried out to explain the experimental results and show that the dot-structured proton beam is formed when the outer part of the incident proton beam is optimally focused by the EMP force on the solenoid; otherwise, it is overfocused into a ring structure by a larger EMP. Such a separately controlled mechanism allows precise tuning of the proton beam structures for various applications, such as edge-enhanced proton radiography, proton therapy and pre-injection in traditional accelerators.

The selection of random sampling points is crucial for the path quality generated by probabilistic roadmap (PRM) algorithm. Increasing the number of sampling points can enhance path quality. However, it may also lead to extended convergence time and reduced computational efficiency. Therefore, an improved probabilistic roadmap algorithm (TL-PRM) is proposed based on topological discrimination and lazy collision. TL-PRM algorithm first generates a circular grid area among start and goal points. Then, it constructs topological nodes. Subsequently, elliptical sampling areas are created between each pair of adjacent topological nodes. Random sampling points are generated within these areas. These sampling points are interconnected using a layer connection strategy. An initial path is generated using a delayed collision strategy. The path is then adjusted by modifying the nodes on the convex outer edges to avoid obstacles. Finally, a reconnection strategy is employed to optimize the path. This reduces the number of path waypoints. In dynamic environments, TL-PRM algorithm employs pose adjustment strategies for semi-static and dynamic obstacles. It can use either the same or opposite pose adjustments to avoid dynamic obstacles. Experimental results indicate that TL-PRM algorithm reduces the average number of generated sampling points by 70.9% and average computation time by 62.1% compared with PRM* and PRM-Astar algorithms. In winding and narrow passage maps, TL-PRM algorithm significantly decreases the number of sampling points and shortens convergence time. In dynamic environments, the algorithm can adjust its pose orientation in real time. This allows it to safely reach the goal point. TL-PRM algorithm provides an effective solution for reducing the generation of sampling points in PRM algorithm.

A generalised multiparameter model for linear modal stability and sensitivity analysis is developed. The stability and sensitivity equations are derived from a generalised vector-form governing equation comprised of multiple dimensionless parameters that represent different physical forces affecting the system’s stability. By introducing adjoint variables and constructing the Lagrangian identity, a differential relationship between the eigenvalue of the perturbation mode and dimensionless parameters is determined and defined as the global sensitivity gradient. It provides the constraint that must be satisfied for changes in different dimensionless parameters along the isoeigenvalue curve, which aids in the fast computation of the neutral curve. Moreover, the global sensitivity gradient can directly and intuitively evaluate the competitive relationship among the influences of various parameters on system instability. Based on the global sensitivity gradient, an optimal stability control strategy for transitioning from an unstable state to a stable state is discussed. Additionally, the relative sensitivity function is also introduced to investigate the influence of relative parameter variations on instability. To demonstrate the effectiveness of this method, three applications are presented: two-dimensional flow around a circular cylinder with a single dimensionless parameter Re; three-dimensional axisymmetric magnetohydrodynamic (MHD) flow around a sphere with two parameters Re and $N$; and two-dimensional MHD mixed convection with three parameters Re, ${\textit{Gr}}$ and $\textit{Ha}$.

This study employs volume-of-fluid-based computational fluid dynamics modelling to investigate the coupled effects of surface wettability and inflow vapour velocity on R134a ($p/p_{cri}=0.25$) condensation heat transfer in horizontal tubes. The results demonstrate that both the condensation heat transfer coefficient (HTC) and Nusselt number consistently increase with rising vapour velocity, indicating enhanced convective heat transfer at higher flow rates. Within this overall trend, the influence of surface wettability varies significantly across different velocity regimes. At moderate inlet velocities (10 m s−1), surface wettability demonstrates maximum impact, with the HTC enhancement exceeding 19.1% between peak and minimum values, optimising at contact angles of 120$^\circ$–140$^\circ$. As velocity increases to 20 m s−1, while surface wettability effects persist with $\gt$11.7 % enhancement, convective heat transfer becomes increasingly dominant, showing $\gt$38.8 % improvement in the maximum HTC compared with the 10 m s−1 case. At higher velocities (40 m s−1), the influence of surface wettability diminishes substantially, with the HTC variation reducing to $\gt$1.04 %. At extreme velocities (80 m s−1), surface tension effects become negligible compared with vapour shear forces, resulting in minimal (0.53 %) variation across different contact angles. The equivalent Reynolds number peaks at 20 m s−1, indicating optimal conditions for condensate formation and flow characteristics. These findings provide crucial insights for condensation system design, suggesting that while increasing velocity generally enhances heat transfer performance, surface wettability modifications are most effective at moderate velocities, while high-velocity applications should prioritise flow dynamics and system geometry optimisation.

This study presents a novel investigation into the vortex dynamics of flow around a near-wall rectangular cylinder based on direct numerical simulation at $Re=1000$, marking the first in-depth exploration of these phenomena. By varying aspect ratios ($L/D = 5$, $10$, $15$) and gap ratios ($G/D = 0.1$, $0.3$, $0.9$), the study reveals the vortex dynamics influenced by the near-wall effect, considering the incoming laminar boundary layer flow. Both $L/D$ and $G/D$ significantly influence vortex dynamics, leading to behaviours not observed in previous bluff body flows. As $G/D$ increases, the streamwise scale of the upper leading edge (ULE) recirculation grows, delaying flow reattachment. At smaller $G/D$, lower leading edge (LLE) recirculation is suppressed, with upper Kelvin–Helmholtz vortices merging to form the ULE vortex, followed by instability, differing from conventional flow dynamics. Larger $G/D$ promotes the formation of an LLE shear layer. An intriguing finding at $L/D = 5$ and $G/D = 0.1$ is the backward flow of fluid from the downstream region to the upper side of the cylinder. At $G/D = 0.3$, double-trailing-edge vortices emerge for larger $L/D$, with two distinct flow behaviours associated with two interactions between gap flow and wall recirculation. These interactions lead to different multiple flow separations. For $G/D = 0.9$, the secondary vortex (SV) from the plate wall induces the formation of a tertiary vortex from the lower side of the cylinder. Double-SVs are observed at $L/D = 5$. Frequency locking is observed in most cases, but is suppressed at $L/D = 10$ and $G/D = 0.9$, where competing shedding modes lead to two distinct evolutions of the SV.

Seoul – Patients in hospital gowns crowded in with their IV poles. Visitors pressed against glass doors to watch. The crew hovered with lights, camera and microphone.

“Ready … cue,” the director barked, then filmed the scene of a young widow undergoing tests to give a kidney to her mother, who had abandoned her as a child.

Although active flow control based on deep reinforcement learning (DRL) has been demonstrated extensively in numerical environments, practical implementation of real-time DRL control in experiments remains challenging, largely because of the critical time requirement imposed on data acquisition and neural-network computation. In this study, a high-speed field-programmable gate array (FPGA) -based experimental DRL (FeDRL) control framework is developed, capable of achieving a control frequency of 1–10 kHz, two orders higher than that of the existing CPU-based framework (10 Hz). The feasibility of the FeDRL framework is tested in a rather challenging case of supersonic backward-facing step flow at Mach 2, with an array of plasma synthetic jets and a hot-wire acting as the actuator and sensor, respectively. The closed-loop control law is represented by a radial basis function network and optimised by a classical value-based algorithm (i.e. deep Q-network). Results show that, with only ten seconds of training, the agent is able to find a satisfying control law that increases the mixing in the shear layer by 21.2 %. Such a high training efficiency has never been reported in previous experiments (typical time cost: hours).

Objectives/Goals: Recognizing a critical need for sustained education and community beyond formalized training periods at Columbia University’s NCATS-CTSA, we created the TRANSFORM (TRaining And Nurturing Scholars FOr Research that is Multidisciplinary) Evolution program to preserve the networks cultivated during the KL2 program. Methods/Study Population: We will provide an overview of the genesis, expansion, key components, and programming for the TRANSFORM Evolution program. The program is designed for current and alumni of the KL2 program and late junior faculty that receive our CTSA’s Irving Scholar Award. TRANSFORM Evolution is a faculty and alumni network offering a platform to support the next generation of clinical and translational researchers while fostering a lasting community of collaboration and educational activities throughout a scholar’s career lifespan. Results/Anticipated Results: Salient components include the opportunities for social interaction, such as social/happy hours and member led education/career development sessions pertaining to topics that support thriving in an academic career. The program operates with financial resources and the support of a program manager. Evolution adopts a holistic, long-term approach, focusing on the entire professional lifespan by encouraging the development of enduring opportunities for our alumni. The program is intentionally structured to meet the evolving needs of its participants, through the beginning to more established phases in their professional careers. This continuity underscores the program’s capacity to adapt and remain relevant, informing and supporting sustained career progression and scholarly productivity. Discussion/Significance of Impact: The program has been an instrumental adjuvant in facilitating the transition to each career stage. By cultivating a community rooted in a common foundation – the KL2 and Irving Scholars programs, the program has created a robust support system that is crucial for the career development of clinician-scientists.

Using National Healthcare Safety Network data, an interrupted time series of intravenous antimicrobial starts (IVAS) among hemodialysis patients was performed. Annual adjusted rates decreased by 6.64% (January 2012–March 2020) and then further decreased by 8.91% until December 2021. IVAS incidence trends have decreased since 2012, including during the early COVID-19 pandemic.

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.