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The boom in bike-sharing is receiving growing attention as societies become more aware of the importance of active non-motorized traffic modes. However, the low usage of this transport mode in China raises concerns. The primary objective of this study is to explore factors affecting bike-sharing usage and satisfaction degree of bike-sharing among the bike-sharing user population in China. Data were collected by a questionnaire survey in Ningbo. A bivariate ordered probit (BOP) model was developed to examine simultaneously those factors associated with both bike-sharing usage and satisfaction degree of bike-sharing among users. Marginal effects for contributory factors were calculated to quantify their impacts on the outcomes. The results showed that the BOP model can account for commonly shared unobserved characteristics within usage and satisfaction of bike-sharing. The BOP model results showed that the usage of bike-sharing was affected by gender, household bicycle/e-bike ownership, trip model, travel time, bike-sharing stations location, and users' perception of bike-sharing. The satisfaction degree of bike-sharing was affected by household income, bike-sharing stations location, and users' perception of bike-sharing. It is also found that bike-sharing usage and satisfaction degree are strongly correlated and positive in direction. The results can enhance our comprehension of the factors that affect usage and satisfaction degree of bike-sharing. Based on the results, some suggestions regarding planning, engineering, and public advocacy were discussed to increase the usage of bike-sharing in Ningbo, China.

The rapid advancement of nanomedicine and nanoparticle (NP) materials presents novel solutions potentially capable of revolutionizing health care by improving efficacy, bioavailability, drug targeting, and safety. NPs are intriguing when considering medical applications because of their essential and unique qualities, including a significantly higher surface to mass ratio, quantum properties, and the potential to adsorb and transport drugs and other compounds. However, NPs must overcome or navigate several biological barriers of the human body to successfully deliver drugs at precise locations. Engineering the drug carrier biointerface can help overcome the main biological barriers and optimize the drug delivery in a more personalized manner. This review discusses the significant heterogeneous biological delivery barriers and how biointerface engineering can promote drug carriers to prevail over hurdles and navigate in a more personalized manner, thus ushering in the era of Precision Medicine. We also summarize the nanomedicines' current advantages and disadvantages in drug administration, from natural/synthetic sources to clinical applications. Additionally, we explore the innovative NP designs used in both non-personalized and customized applications as well as how they can attain a precise therapeutic strategy.

A bstract To provide reliable quantitative predictions for hot and dense QCD matter, a holographic model must be calibrated to match first-principles lattice results at vanishing baryon chemical potential. The equation of state from two leading lattice groups, HotQCD and the Wuppertal-Budapest (WB) collaboration, exhibits notable differences at high temperatures. We revisit the Einstein-Maxwell-dilaton (EMD) holographic model for hot QCD with 2+1 flavors and physical quark masses, fitting the lattice QCD data from the WB collaboration. In particular, using the parameterization for the scalar potential and gauge coupling from our previous work [Phys. Rev. D 106 (2022) L121902], we achieve quantitative agreement between the equation of state, chiral condensates, and state-of-the-art lattice results. Furthermore, higher-order baryon number susceptibilities are consistent with those for 2+1+1 flavor QCD. In particular, the critical endpoint (CEP) obtained from the WB collaboration data closely matches that from the combination of HotQCD and WB datasets, highlighting the robustness of the CEP location. Our holographic prediction for the location of the CEP also aligns with recent Bayesian analysis of multiple EMD models and an effective potential approach to QCD from gap equations.

Firstly we qualitatively analyze the formation of the dip and peak structures of the kurtosis \\[\\kappa \\sigma ^2\\] of net baryon number fluctuation along imagined freeze-out lines and discuss the signature of the existence of the QCD critical end point (CEP) in the Nambu–Jona-Lasinio (NJL) model, Polyakov-NJL (PNJL) model as well as \\[\\mu \\]-dependent PNJL(\\[\\mu \\] PNJL) model with different parameter sets, and then we apply a realistic PNJL model with parameters fixed by lattice data at zero chemical potential, and quantitatively investigate its \\[\\kappa \\sigma ^2\\] along the real freeze-out line extracted from experiments. The important contribution from gluodynamics to the baryon number fluctuations is discussed. The peak structure of \\[\\kappa \\sigma ^2\\] along the freeze-out line is solely determined by the existence of the CEP mountain and can be used as a clean signature for the existence of CEP. The formation of the dip structure is sensitive to the relation between the freeze-out line and the phase boundary, and the freeze-out line starts from the back-ridge of the phase boundary is required. To our surprise, the kurtosis \\[\\kappa \\sigma ^2\\] produced from the realistic PNJL model along the experimental freeze-out line agrees with BES-I data well, which indicates that equilibrium result can explain the experimental data. It is worth to point out that the extracted freeze-out temperatures from beam energy scan measurement are indeed higher than the critical temperatures at small chemical potentials, which supports our qualitative analysis.

A bstract We study the rotation effects of the hot and dense QCD matter in a non-perturbative regime by the gauge/gravity duality. We use the gravitational model that is designated to match the state-of-the-art lattice data on the thermal properties of (2+1)-flavor QCD and predict the location of the critical endpoint and the first-order phase transition line at large baryon chemical potential without rotation. After introducing the angular velocity via a local Lorentz boost, we investigate the thermodynamic quantities for the system under rotation in a self-consistent way. We find that the critical temperature and baryon chemical potential associated with the QCD phase transition decrease as the angular velocity increases. Moreover, some interesting phenomena are observed near the critical endpoint. We then construct the 3-dimensional phase diagram of the QCD matter in terms of temperature, baryon chemical potential, and angular velocity. As a parallel investigation, we also consider the gravitational model of SU(3) pure gluon system, for which the 2-dimensional phase diagram associated with temperature and angular velocity has been predicted. The corresponding thermodynamic quantities with rotation are investigated.

To improve robotic positioning accuracy and enhance overall manufacturing precision, this paper proposes an adaptive momentum Levenberg–Marquardt cascaded B-spline interpolation particle swarm optimization (AMLM-BIPSO) algorithm for calibrating robotic geometric errors. Initially, a momentum term is incorporated into the traditional Levenberg–Marquardt algorithm to suppress overshooting and oscillation, thereby improving the preliminary estimation of geometric parameters. Subsequently, inspired by the concept of Knowledge-based artificial Neural Networks, B-spline interpolation is embedded into the standard particle swarm optimization framework to refine the final calibration. By cascading these two enhanced techniques, the proposed method achieves higher accuracy in parameter identification. Experimental validation on an industrial robot confirms that the AMLM-BIPSO algorithm yields substantial improvements in positioning accuracy and calibration reliability.

Background Gastric cancer (GC) is one of the most pernicious tumors that seriously harm human healthcare. GC metastasis is one of the prime cause of failed cancer treatment, but correlation between N6-methyladenosine (m6A) and GC metastasis was less reported. Methods Methylated RNA immunoprecipitation sequencing (MeRIP-seq) of GC tissues was conducted. Quantitative real-time PCR (qRT-PCR), western blotting and immunohistochemistry (IHC) were taken to determine the expression of ALKBH5 in GC tissues and cell lines. RNA-seq together with MeRIP-qRT-PCR was used to screen the target gene of ALKBH5. RNA pulldown, mass spectrometry and RNA immunoprecipitation (RIP) were used to search the “reader” protein of target gene. The mechanism was also validated via a tail vein injection method for lung metastasis model. Results Decreased expression of ALKBH5 was detected in GC samples, and it was correlated with clinical tumor distal metastasis and lymph node metastasis. ALKBH5 interference promoted metastasis of GC cells and this effect was closely related to the demethylase activity of ALKBH5. PKMYT1, as a downstream target of ALKBH5, promoted invasion and migration in GC. Caused by ALKBH5 knockdown or its demethylase activity mutation, upregulated expression of PKMYT1 indicated that ALKBH5 modulates expression of PKMYT1 in an m6A-dependent manner. IGF2BP3 helped stabilize the mRNA stability of PKMYT1 via its m6A modification site. Conclusions This study established an ALKBH5-PKMYT1-IGF2BP3 regulation system in metastasis, representing a new therapeutic target for GC metastasis.

Photothermal therapy (PTT) offers many advantages such as high efficiency and minimal invasiveness, but clinical adoption of PTT nanoagents have been stifled by unresolved concerns such as the biodegradability as well as long-term toxicity. Herein, poly (lactic-co-glycolic acid) (PLGA) loaded with black phosphorus quantum dots (BPQDs) is processed by an emulsion method to produce biodegradable BPQDs/PLGA nanospheres. The hydrophobic PLGA not only isolates the interior BPQDs from oxygen and water to enhance the photothermal stability, but also control the degradation rate of the BPQDs. The in vitro and in vivo experiments demonstrate that the BPQDs/PLGA nanospheres have inappreciable toxicity and good biocompatibility, and possess excellent PTT efficiency and tumour targeting ability as evidenced by highly efficient tumour ablation under near infrared (NIR) laser illumination. These BP-based nanospheres combine biodegradability and biocompatibility with high PTT efficiency, thus promising high clinical potential. Black phosphorus is a biodegradable 2D material that has attracted growing interest in biomedicine. Here, the authors carry out in vitro and in vivo experiments to demonstrate that nanospheres loaded with black-phosphorus quantum dots perform as promising phothermal cancer therapy agents.

In the advanced helicopter gear transmission system, the elastic web gear structure is a new type of vibration reduction structure. Its vibration reduction mechanism, parameter value and control strategy are all scientific problems to be solved urgently. This paper establishes the nonlinear dynamic equation of elastic web herringbone gear transmission system under multi-factor coupling. The influence of four potentially applicable elastic materials on the system dynamic load sharing performance is explored. Then the effects of these two materials on the system nonlinear vibration characteristics under different working conditions are analyzed. Finally, the variation of dynamic load coefficient (DLC) and load sharing coefficient (LSC) with input/output torque excitation and system structure size under the action of two materials is analyzed. The results show that compared with elastic web without consideration, when the web is made of beryllium copper, Ni40Cr20Co20Mo, spring steel and silicon rubber, the DLCs of the left and right sides of gear pair are different by 21.68%, 7.64%, 21.55% and 3.5%, so the load sharing performance of silicon rubber is better. When the input speed changes, when the silicone rubber is used than the superalloy, the periodic motion area of the system is relatively large, which is beneficial to improve the system stability. With the change of input power, silicone rubber is more beneficial to periodic motion than superalloy. The research results can guide the design, optimization and control of the new generation of helicopter and ship elastic web gear system.

Most of the current variable speed limit (VSL) strategies are designed to alleviate congestion in relatively short freeway segments with a single bottleneck. However, in reality, consecutive bottlenecks can occur simultaneously due to the merging flow from multiple ramps. In such situations, the existing strategies use multiple VSL controllers that operate independently, without considering the traffic flow interactions and speed limit differences. In this research, we introduced a multiagent reinforcement learning-based VSL (MARL-VSL) approach to enhance collaboration among VSL controllers. The MARL-VSL approach employed a centralized training with decentralized execution structure to achieve a joint optimal solution for a series of VSL controllers. The consecutive bottleneck scenarios were simulated in the modified cell transmission model to validate the effectiveness of the proposed strategy. An independent single-agent reinforcement learning-based VSL (ISARL-VSL) and a feedback-based VSL (feedback-VSL) were also applied for comparison. Time-varying heterogeneous traffic flow stemming from the mainline and ramps was loaded into the freeway network. The results demonstrated that the proposed MARL-VSL achieved superior performance compared to the baseline methods. The proposed approach reduced the total time spent by the vehicles by 18.01% and 17.07% in static and dynamic traffic scenarios, respectively. The control actions of the MARL-VSL were more appropriate in maintaining a smooth freeway traffic flow due to its superior collaboration performance. More specifically, the MARL-VSL significantly improved the average driving speed and speed homogeneity across the entire freeway.