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Changes in heart structure and function after lung resection in patients with lung cancer are challenging to manage. Therefore, a non-invasive and reliable measurement tool to gauge such changes is critical. The purpose of the present study was to compare cardiological changes before and after lung resection using tissue Doppler imaging (TDI). A total of 43 patients (19 men and 24 women) with primary non-small cell lung cancer (n=37) and metastatic cancer in the lungs (n=6) were enrolled in the study.nTDI was used to determine the thickness of the ascending aorta, the open size of the ascending valve, the anterior-oposterior diameters of the left atrium and left ventricle, and the thickness of the ventricular septum and right ventricle before and after lung resection. Left ventricular (LV) ejection fraction (EF), pulmonary valve flow rate, tricuspid annular or mitral leaflet tip early (E) peak/late (A) diastolic blood flow velocities, tricuspid regurgitation flow, the lateral mitral annulus early (e') diastolic velocity and mitral E/e' ratio were used to determine LV filling pressure. Results revealed no significant differences between male and female patients in terms of the open size of the ascending valve, the anterior-posterior diameter of the left ventricle and the mitral E/e' ratio. Significant differences were found in the width of the ascending aorta, anterior-posterior diameter of the left atrium, width of the LV septum and right ventricular (RV) diameter before and after lung resection. Finally, there were significantchanges in EF and tricuspid pressure. The results indicated that TDI was useful as a non-invasive method for assessing left and right heart function following lung resection. The LV and RV dimensions were affected, but LV filling pressure was preserved after lobectomy. [ABSTRACT FROM AUTHOR]

We demonstrate an environmentally stable femtosecond laser for industrial application based on all polarization‐maintaining Yb‐doped laser and experimentally explore the effect of the net cavity dispersion (NCD) on output characteristics. The oscillator emits pulses with 5.1 ps and a 23 nm spectral bandwidth, then the pulse is compressed to 88 fs. The instabilities over 120 h gives 0.32% relative root mean square noise, indicating high stability of the pulse laser. With effective regulation of NCD, we obtained the maximum spectral bandwidth of 27 nm. Such broadband oscillator with compact all‐fiber configurations provide extremely high stability should be very attractive for long‐term industrial application. [ABSTRACT FROM AUTHOR]

Hydrogen embrittlement in hydrogen pipelines can cause severe economic losses and safety hazards, thus research on efficient hydrogen barrier coatings is of great importance. In this study, a more efficient and easily operable non-covalent modification method was employed to modify carboxymethyl chitosan (CMCS) onto graphene oxide (GO), resulting in a significant improvement in the dispersibility and uniform distribution of GO in waterborne epoxy resin. Subsequently, a hydrogen barrier coating was prepared by incorporating the modified GO into waterborne epoxy resin. The influence of different doping concentrations on the coating performance was investigated. The basic properties of the coatings were characterized using macroscopic analysis, SEM, contact angle measurements, adhesion tests and electrochemical techniques. The corrosion resistance and hydrogen barrier effect was evaluated through electrochemical hydrogen permeation experiments. Results showed that The modified graphene oxide has good compatibility with epoxy resin. When the content of CGO was 0.25 %, the dispersion was best. the CGO coatings has some corrosion resistance with approximately 10 MPa adhesive force and 105 Modular value at the beginning of immersion. The CGO coatings significantly improved the hydrogen resistance of ×80 steel. The lowest hydrogen permeation current density was observed at 0.25 wt% CGO concentration, which indicated optimal hydrogen permeation inhibition capability. • The graphene oxide (GO) has been modified to CGO by carboxymethyl chitosan. • 0.25%CGO was best dispersed in the epoxy resins. • The CGO complex coating has some corrosion resistance. • The 0.25%CGO coating has superior hydrogen resistance performance. [ABSTRACT FROM AUTHOR]

Travelers often change their behavior in reaction to adverse weather conditions. This paper seeks to conduct an empirical evaluation of both ordered and unordered discrete outcome frameworks for examining the adaptive behavior decisions of intercity travelers and investigate the varying effects of explanatory factors on different alternatives of adaptive behavior during adverse weather. The data from 754 respondents in the Beijing-Tianjin-Hebei urban agglomeration, China are collected by a two-phase survey instrument. To capture the unobserved heterogeneity more effectively, this paper develops three advanced models to investigate the variations in intercity travel behavior during adverse weather. Four alternative adaptive behaviors are determined as outcome variables: maintaining original travel plans, changing only the intercity mode, changing the departure date, and canceling the trip, while potential influencing factors including adverse weather conditions, trip-related characteristics, individual attributes and urban agglomeration attributes are statistically assessed. The results indicate that the unordered models consistently outperform their ordered counterparts, and the incorporation of multilayer heterogeneity enhances the model fit. Furthermore, significant factors and their coefficient values vary across the different adaptive behavior alternatives. Intercity travelers demonstrate a higher probability of changing departure dates or canceling trips during snowy and windy days compared to rainy and foggy days. Trains exhibit higher flexibility and reliability during adverse weather, and access attributes significantly affect intercity travel adaptive behavior. Additionally, the analysis of individual and urban agglomeration attributes uncovers variations in adaptive behavior among individuals and cities. These findings provide profound insights into the complexities and variations of intercity travel behavior during adverse weather, and propose practical strategies to mitigate the detrimental impacts of adverse weather on intercity travelers. • Adaptive behavior of intercity travelers during adverse weather is investigated. • Unordered framework outperforms ordered counterparts in adaptive behavior study. • Multilayer unobserved heterogeneity in the adaptive behavior is accounted for. • The varying effects of explanatory factors on different adaptive alternatives are examined. • Practical strategies are proposed to mitigate negative impacts of adverse weather. [ABSTRACT FROM AUTHOR]

Purpose: The impact of rolling on the performance of micro arc oxidation (MAO) coatings on ZM5 alloy has been underreported. The purpose of this study is to explore the correlation between rolling and the failure mechanism of MAO coatings in greater depth. Design/methodology/approach: The influence of rolling on the corrosion and wear properties of MAO coating was investigated by phase structure, bond strength test (initial bond strength and wet adhesion), electrochemical impedance spectroscopy and wear test. The change of the surface electrochemical properties was studied by first principles analysis. Findings: The results showed that the MAO coating on rolled alloy had better corrosion and wear resistance compared to cast alloy, although the structure and component content of two kinds of MAO coating are nearly identical. The difference in interface bonding between MAO coating and Mg substrate is the primary factor contributing to the disparity in performance between the two types of samples. Finally, the impact of the rolling process on MAO coating properties is explained through first-principle calculation. Originality/value: A comprehensive explanation of the impact of the rolling process on MAO coating properties will provide substantial support for enhancing the application of Mg alloy anticorrosion. [ABSTRACT FROM AUTHOR]

Latent fingerprints (LFPs) is one of the most important physical evidence in the criminal scene, playing an important role in forensic investigations. Therefore, developing highly sensitive and convenient materials for the visualization of LFPs is of great significance. We designed and synthesized an organic fluorescent molecule TP-PH with aggregation-induced enhanced emission (AIEE) activity. By simply soaking, blue fluorescent images with high contrast and resolution are readily developed on various surfaces including tinfoil, steel, glass and plastic. Remarkably, LFPs can be visualized within 5 min including the first-, second- and tertiary-level details. In addition, TP-PH exhibits interesting photoactivated fluorescence enhancement properties. Under irradiation of 365 nm UV light with a power density of 382 mW/cm2, the fluorescence quantum yield displays approximately 21.5-fold enhancement. Mechanism studies reveals that the photoactivated fluorescence is attributed to the irreversible cyclodehydrogenation reactions under UV irradiation. This work provides a guideline for the design of multifunctional AIEE fluorescent materials. [ABSTRACT FROM AUTHOR]

The causes analysis of road traffic accidents is often modelled based on high-dimensional small-sample data; however, such models often have low predictive accuracy and poor generalization performance. An analytical framework that considers both data augmentation and model optimization can enhance variable interpretation and predictive model performance, thereby improving the shortcomings of existing accident analysis methods. Our approach is as follows: 1) Starting with an analysis of the nature of road accidents, a symbolic operation is used to design a feature crosses algorithm. A random variable is added to construct a quantifiable feature selection algorithm, which can form a data augmentation method that conforms to the accident rules. 2) A highly reliable framework for analysing accident causes is constructed by using forward selection to optimize an ensemble learning model subset combined with feature crosses, feature selection and multiple-classification algorithms. A case study with accident data from a city in China shows that ensemble learning has the advantages of high predictive accuracy and strong generalization performance. It can accurately identify the key causes of accidents based on highly dimensional small-sample data. Driving behaviours such as lane changes and turns are the key causes of accidents. Giving drivers effective traffic environment information in a timely manner can significantly improve driving performance and reduce accident risk. This research provides a reference for the analysis of road accidents. [ABSTRACT FROM AUTHOR]

• Determinants of motorcyclists' injury severities are studied. • Methodological issues of scale and random heterogeneity are captured. • Mixed logit models considering generalized scale heterogeneity are estimated. • Random parameters logit model considering heterogeneity in means and vaeiances are also estimated. • Temporal instability warrants for estimation of separate year-specific models. • Significant differences in sources of heterogeneity over the years are observed. The presence of unobserved factors in the motorcycle involved two-vehicle crashes (MV) data could lead to heterogenous associations between observed factors and injury severity sustained by motorcyclists. Capturing such heterogeneities necessitates distinct methodological approaches, of which random and scale heterogeneity models are paramount. Herein, we undertake an empirical evaluation of random and scale heterogeneity models, exploring their efficacy in delineating the influence of external determinants on the degree of injury severity in crashes. Within the effects of scale heterogeneity, this study delves into two dominant models: the scaled multinomial logit model (S-MNL) and its generalized counterpart, the G-MNL, which encompasses both the S-MNL and the random parameters multinomial logit model (RPL). While the random heterogeneity domain is represented by the random parameters multinomial logit and an upgraded variant – the random parameters multinomial logit model with heterogeneity in means and variances (RPLHMV). Motorcycle involved two-vehicle crashes data were extracted from the UK STATS19 dataset from 2016 to 2020. Likelihood ratio tests are computed to assess the temporal variability of the significant factors. The test result demonstrates the temporal variations over a five-year study period. Some very important differences started to show up across the years based on the model estimation results: that the RPLHMV model statistically outperforms the G-MNL model in the 2016, 2018, and 2019 models, while the S-MNL model is statistically superior in the 2017 and 2020 years. These important findings suggest that the origin of heterogeneity in explaining factor weights can be captured by scale effects, not just random heterogeneity. In addition, the model results further show that motorcyclists' injury severities are significantly affected by motorcycle-related characteristics; there is the added factor of external influences, such as non-motorcycle drivers (males, young drivers, and elderly drivers) and vehicles (the moving status, age, and types of vehicles) that collide with motorcycles. The results of this paper are anticipated to help policymakers develop effective strategies to mitigate motorcycle involved two-vehicle crashes by implementing appropriate measures. [ABSTRACT FROM AUTHOR]

Roadside barriers have proven effective in preventing run-off-road accidents that occurred in mountainous areas. Nonetheless, the influence of variables impacting the severity of injuries resulting from collisions involving distinct types of roadside barriers may diverge. This study delves into the factors that influence the severity of driver's injuries in crashes encompassing three specific varieties of roadside barriers in mountainous regions, namely, W-beam barriers, flexible barriers, and roadside trees. The evolution of these factors over time is examined through the application of a random parameters logit modeling approach with heterogeneity in means and variances (RPLHMVs). By employing injury-severity data from 2016 to 2019 for the mountainous regions of a city in Southwest China, various potential influencing factors encompassing driver-, vehicle-, road-, and environment-specific characteristics are subjected to statistical analysis. The extent of the impact of identified statistically significant factors on driver's injury severity is assessed through the computation of pseudoelasticities. The findings reveal distinctions in the outcomes of driver's injury severity contingent upon the type of roadside barrier encountered during vehicle impacts. To illustrate, collisions involving W-beam barriers are more prone to result in severe injuries. Moreover, the influence of variables determining driver's injury severity displays noteworthy temporal shifts. Notably, the pseudoelasticities of numerous explanatory variables remain temporally consistent for incidents involving flexible or roadside barriers. In contrast, crashes involving W-beam barriers highlight that solely the speeding indicator demonstrates temporally stable pseudoelasticities. The insights garnered from this investigation offer the potential to contribute to the formulation of fresh guidelines for the design and selection of roadside barriers aimed at mitigating the severity of injuries incurred in crashes within mountainous regions. [ABSTRACT FROM AUTHOR]