In this retrospective study examining the treatment of low-risk AmpC-producing Enterobacterales bacteremia during two periods with different microbiology reporting strategies, reporting of ceftriaxone susceptibility was associated with a statistically significant decrease in carbapenem use as definitive therapy compared to when susceptibility was suppressed (21 vs 50%, p < 0.0001).

Observers were randomized to time and location across two different Neonatal Intensive Care Units (NICUs) to count hand hygiene opportunities (HHOs). Mean hourly HHO was lower at night and during use of precautions, and higher in shared rooms. HHO benchmarks can support implementation of group electronic monitoring systems in NICUs.

This study explored the relationship between multifaceted multilingualism and cognitive shifting through a task-switching paradigm using fMRI. Multilingualism was modeled from both convergent (i.e., integrated multilingual index) and divergent (i.e., L2 proficiency, interpreting training, language entropy) perspectives. Participants identified letters or numbers based on task cues, with Repeat trials maintaining the same task and Switch trials requiring a different task. Switch cost (Switch–Repeat) was used to reflect shifting demands. Better task-switching performance was associated with a higher integrated multilingual index and interpreting training. Neuroimaging indicated that multilinguals predominantly engaged left-hemisphere regions for switching, with extensive multilingual experience requiring fewer neural resources for switch cost (i.e., more efficient processing for cognitive control). During task switching, brain connectivity was regulated locally by L2 proficiency, and globally by interpreting training. These findings underscore the importance of considering multifaceted multilingual experience to understand its impact on cognitive function and brain activity.

The safety of human-collaborative operations with robots depends on monitoring the external torque of the robot, in which there are toque sensor-based and torque sensor-free methods. Economically, the classic method for estimating joint external torque is the first-order momentum observer (MOB) based on a physic model without torque sensors. However, uncertainties in the dynamic model, which encompasses parameters identification error and joint friction, affect the torque estimation accuracy. To address this issue, this paper proposes using the backpropagation neural network (BPNN) method to estimate joint external torque without the delicate physical model by utilizing the powerful machine learning ability to handle the uncertainties of the MOB method and improve the accuracy of torque estimation. Using data obtained from the torque sensor to train the BPNN to build up a digital torque model, the trained BPNN can perceive force in practical applications without relying on the torque sensor. In the end, by contrast to the classic first-order MOB, the result demonstrates that BPNN achieves higher estimation accuracy compared to the MOB.

Substantial changes resulting from the interaction of environmental and dietary factors contribute to an increased risk of obesity, while their specific associations with obesity remain unclear. Identify inflammation-related dietary patterns (DPs) and explore their associations with obesity among urbanized Tibetan adults under significant environmental and dietary changes.Totally, 1826 subjects from the suburbs of Golmud City were enrolled in an open cohort study, of which 514 were followed up. Height, weight, and waist circumference were used to define overweight and obesity. DPs were derived using reduced rank regression with 41 food groups as predictors and hs-CRP and prognostic nutritional index as inflammatory response variables. Altitude was classified as high or ultra-high. Two DPs were extracted. DP-1 was characterized by having high consumptions of sugar-sweetened beverages, savory snacks, and poultry, and a low intake of tsamba. DP-2 had high intakes of poultry, pork, animal offal, and fruits, and a low intake of butter tea. Participants in the highest tertiles (T3) of DPs had increased risks of overweight and obesity (DP-1: OR=1.37, 95% CI: 1.07, 1.77; DP-2: OR=1.48, 95% CI: 1.18, 1.85) than those in the lowest tertiles (T1). Participants in T3 of DP-2 had an increased risk of central obesity (OR=2.25, 95% CI: 1.49, 3.39) than those in T1. The positive association of DP-1 with overweight and obesity was only significant at high altitudes, while no similar effect was observed for DP-2. Inflammation-related DPs were associated with increased risks of overweight and/or obesity.

In this work, the shape of a bluff body is optimized to mitigate velocity fluctuations of turbulent wake flows based on large-eddy simulations (LES). The Reynolds-averaged Navier–Stokes method fails to capture velocity fluctuations, while direct numerical simulations are computationally prohibitive. This necessitates using the LES method for shape optimization given its scale-resolving capability and relatively affordable computational cost. However, using LES for optimization faces challenges in sensitivity estimation as the chaotic nature of turbulent flows can lead to the blowup of the conventional adjoint-based gradient. Here, we propose using the regularized ensemble Kalman method for the LES-based optimization. The method is a statistical optimization approach that uses the sample covariance between geometric parameters and LES predictions to estimate the model gradient, circumventing the blowup issue of the adjoint method for chaotic systems. Moreover, the method allows for the imposition of smoothness constraints with one additional regularization step. The ensemble-based gradient is first evaluated for the Lorenz system, demonstrating its accuracy in the gradient calculation of the chaotic problem. Further, with the proposed method, the cylinder is optimized to be an asymmetric oval, which significantly reduces turbulent kinetic energy and meander amplitudes in the wake flows. The spectral analysis methods are used to characterize the flow field around the optimized shape, identifying large-scale flow structures responsible for the reduction in velocity fluctuations. Furthermore, it is found that the velocity difference in the shear layer is decreased with the shape change, which alleviates the Kelvin–Helmholtz instability and the wake meandering.

In this article, we study the following Schrödinger equation

\begin{align*}\begin{cases}-\Delta u -\frac{\mu}{|x|^2} u+\lambda u =f(u), &\text{in}~ \mathbb{R}^N\backslash\{0\},\\\int_{\mathbb{R}^{N}}|u|^{2}\mathrm{d} x=a, & u\in H^1(\mathbb{R}^{N}),\end{cases}\end{align*}

where $N\geq 3$, a > 0, and $\mu \lt \frac{(N-2)^2}{4}$. Here $\frac{1}{|x|^2} $ represents the Hardy potential (or ‘inverse-square potential’), λ is a Lagrange multiplier, and the nonlinearity function f satisfies the general Sobolev critical growth condition. Our main goal is to demonstrate the existence of normalized ground state solutions for this equation when $0 \lt \mu \lt \frac{(N-2)^2}{4}$. We also analyse the behaviour of solutions as $\mu\to0^+$ and derive the existence of normalized ground state solutions for the limiting case where µ = 0. Finally, we investigate the existence of normalized solutions when µ < 0 and analyse the asymptotic behaviour of solutions as $\mu\to 0^-$.

The simulation of rarefied gas flow based on the Boltzmann equation is challenging, especially when the gas mixtures have disparate molecular masses. In this paper, a computationally tractable kinetic model is proposed for monatomic gas mixtures, to mimic the Boltzmann collision operator as closely as possible. The intra- and inter-collisions are modelled separately using relaxation approximations, to correctly recover the relaxation time scales that could span several orders of magnitude. The proposed kinetic model preserves the accuracy of the Boltzmann equation in the continuum regime by recovering four critical transport properties of a gas mixture: the shear viscosity, the thermal conductivity, the coefficients of diffusion and the thermal diffusion. While in the rarefied flow regimes, the kinetic model is found to be accurate when comparing its solutions with those from the direct simulation Monte Carlo method in several representative cases (e.g. one-dimensional normal shock wave, Fourier flow and Couette flow, two-dimensional supersonic flow passing a cylinder and nozzle flow into a vacuum), for binary mixtures with a wide range of mass ratios, species concentrations and different intermolecular potentials. Pronounced separations in species properties have been observed, and the flow characteristics of gas mixtures in shock waves are found to change as the molecular mass ratio increases from 10 to 1000.

Foodborne diseases are ongoing and significant public health concerns. This study analysed data obtained from the Foodborne Outbreaks Surveillance System of Wenzhou to comprehensively summarise the characteristics of foodborne outbreaks from 2012 to 2022. A total of 198 outbreaks were reported, resulting in 2,216 cases, 208 hospitalisations, and eight deaths over 11 years. The findings suggested that foodborne outbreaks were more prevalent in the third quarter, with most cases occurring in households (30.8%). Outbreaks were primarily associated with aquatic products (17.7%) as sources of contamination. The primary transmission pathways were accidental ingestion (20.2%) and multi-pathway transmission (12.1%). Microbiological aetiologies (46.0%), including Vibrio parahaemolyticus, Salmonella ssp., and Staphylococcus aureus, were identified as the main causes of foodborne outbreaks. Furthermore, mushroom toxins (75.0%), poisonous animals (12.5%), and poisonous plants (12.5%) were responsible for deaths from accidental ingestion. This study identified crucial settings and aetiologies that require the attention of both individuals and governments, thereby enabling the development of effective preventive measures to mitigate foodborne outbreaks, particularly in coastal cities.

In response to the complex and challenging task of long-distance inspection of small-diameter and variable-diameter mine holes, this paper presents a design for an adaptive small-sized mine hole robot. First, focusing on the environment of small-diameter mine holes, the paper analyzes the robot’s functions and overall structural framework. A two-wheeled wall-pressing robot with good mobility, arranged in a straight line, is designed. Furthermore, an adaptive variable-diameter method is devised, which involves constructing an adaptive variable-diameter model and proposing a control method based on position and force estimators, enabling the robot to perceive external forces. Lastly, to verify the feasibility of the structural design and adaptive variable-diameter method, performance tests and analyses are conducted on the robot’s mobility and adaptive variable-diameter capabilities. Experimental results demonstrate that the robot can move within small-diameter mine holes at any inclination angle, with a maximum horizontal crawling speed of 3.96 m/min. By employing the adaptive variable-diameter method, the robot can smoothly navigate convex platform obstacles and slope obstacles in mine holes with diameters ranging from 70 mm to 100 mm, achieving the function of adaptive variable-diameter within 2 s. Thus, it can meet the requirements of moving inside mine holes under complex conditions such as steep slopes and small and variable diameters.

This study aims to evaluate the impact of low-carbohydrate diet, balanced dietary guidance and pharmacotherapy on weight loss among individuals with overweight or obesity over a period of 3 months. The study involves 339 individuals with overweight or obesity and received weight loss treatment at the Department of Clinical Nutrition at the Second Affiliated Hospital of Zhejiang University, School of Medicine, between 1 January 2020 and 31 December 2023. The primary outcome is the percentage weight loss. Among the studied patients, the majority chose low-carbohydrate diet as their primary treatment (168 (49·56 %)), followed by balanced dietary guidance (139 (41·00 %)) and pharmacotherapy (32 (9·44 %)). The total percentage weight loss for patients who were followed up for 1 month, 2 months and 3 months was 4·98 (3·04, 6·29) %, 7·93 (5·42, 7·93) % and 10·71 (7·74, 13·83) %, respectively. Multivariable logistic regression analysis identified low-carbohydrate diet as an independent factor associated with percentage weight loss of ≥ 3 % and ≥ 5 % at 1 month (OR = 0·461, P < 0·05; OR = 0·349, P < 0·001). The results showed that a low-carbohydrate diet was an effective weight loss strategy in the short term. However, its long-term effects were comparable to those observed with balanced dietary guidance and pharmacotherapy.

The AIMTB rapid test assay is an emerging test, which adopted a fluorescence immunochromatographic assay to measure interferon-γ (IFN-γ) production following stimulation of effector memory T cells in whole blood by mycobacterial proteins. The aim of this article was to explore the ability of AIMTB rapid test assay in detecting Mycobacterium tuberculosis (MTB) infection compared with the widely applied QuantiFERON-TB Gold Plus (QFT-Plus) test among rural doctors in China. In total, 511 participants were included in the survey. The concordance between the QFT-Plus test and the AIMTB rapid test assay was 94.47% with a Cohen’s kappa coefficient (κ) of 0.84 (95% CI, 0.79–0.90). Improved concordance between the two tests was observed in males and in participants with 26 or more years of service as rural doctors. The quantitative values of the QFT-Plus test was higher in individuals with a result of QFT-Plus-/AIMTB+ as compared to those with a result of QFT-Plus-/AIMTB- (p < 0.001). Overall, our study found that there was an excellent consistency between the AIMTB rapid test assay and the QFT-Plus test in a Chinese population. As the AIMTB rapid test assay is fast and easy to operate, it has the potential to improve latent tuberculosis infection testing and treatment at the community level in resource-limited settings.

Flying insects exhibit remarkable capabilities in coordinating their olfactory sensory system and flapping wings during odour plume-tracking flights. While observations have indicated that their flapping wing motion can ‘sniff’ up the incoming plumes for better odour sampling range, how flapping motion impacts the odour concentration field around the antennae is unknown. Here, we reconstruct the body and wing kinematics of a forwards-flying butterfly based on high-speed images. Using an in-house computational fluid dynamics solver, we simulate the unsteady flow field and odourant transport process by solving the Navier–Stokes and odourant advection-diffusion equations. Our results show that, during flapping flight, the interaction between wing leading-edge vortices and antenna vortices strengthens the circulation of antenna vortices by over two-fold compared with cases without flapping motion, leading to a significant increase in odour intensity fluctuation along the antennae. Specifically, the interaction between the wings and antennae amplifies odour intensity fluctuations on the antennae by up to 8.4 fold. This enhancement is critical in preventing odour fatigue during odour-tracking flights. Further analysis reveals that this interaction is influenced by the inter-antennal angle. Adjusting this angle allows insects to balance between resistance to odour fatigue and the breadth of odour sampling. Narrower inter-antennal angles enhance fatigue resistance, while wider angles extend the sampling range but reduce resistance. Additionally, our findings suggest that while the flexibility of the wings and the thorax's pitching motion in butterflies do influence odour fluctuation, their impact is relatively secondary to that of the wing–antenna interaction.

The flexible flat cable (FFC) assembly task is a prime challenge in electronic manufacturing. Its characteristics of being prone to deformation under external force, tiny assembly tolerance, and fragility impede the application of robotic assembly in this field. To achieve reliable and stable robotic automation assembly of FFC, an efficient assembly skill acquisition strategy is presented by combining a parallel robot skill learning algorithm with adaptive impedance control. The parallel robot skill learning algorithm is proposed to enhance the efficiency of FFC assembly skill acquisition, which reduces the risk of damaging FFC and tackles the uncertain influence resulting from deformation during the assembly process. Moreover, FFC assembly is also a complex contact-rich manipulation task. An adaptive impedance controller is designed to implement force tracking during the assembly process without precise environment information, and the stability is also analyzed based on the Lyapunov function. Experiments of FFC assembly are conducted to illustrate the efficiency of the proposed method. The experimental results demonstrate that the proposed method is robust and efficient.