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The low-aluminum and low-magnesium Zn1.5Al1.1Mg hot-based Zn-Al-Mg alloy coated plate was employed as research object, the initial corrosion mechanism of the cut edges of low aluminum, low magnesium Zn-Al-Mg alloy coated plates was clarified by SEM, EDS, XRD and other methods. Moreover, through SEM and XRD method, the types and morphology of corrosion products at the cut edges of the specimens after immersion and cyclic corrosion experiments were analyzed for evaluating the protective performance of Zn-Al-Mg alloy coatings on their cut edges. Results showed that the cut edge of the Zn-Al-Mg alloy coating was composed of three microstructures: pure Zn phase, Zn-MgZn2 binary eutectic and Zn-MgZn2-Al ternary eutectic. In general, the ternary eutectic and binary eutectic containing MgZn2 phase served as corrosion initiation points during the initial corrosion stage of Zn-Al-Mg alloy cut edges, and then extended to the entire coating. During the long-term corrosion process of cutting edges in Zn-Al-Mg alloy coatings, the Zn element played a major protective role. Specifically, free Zn2+ accumulated at the cutting edge of the coating by forming basic zinc carbonate [Zn5(OH)6(CO3)2] and basic zinc chloride [Zn5(OH)8Cl2·H2O], hindering the longitudinal expansion of the corrosive medium. Nevertheless, when these precipitates transformed into porous ZnO, the protective capabilities of the coating failed, and the cut edge was damaged.

Background: Cytomegalovirus (CMV) can cause infection and critical diseases in hematopoietic stem cell transplantation (HSCT) recipients. This study aimed to explore the cumulative incidence and risk factors for CMV infection and disease among HSCT recipients in Taiwan. Methods: This retrospective cohort study using the Taiwan Blood and Marrow Transplantation Registry (TBMTR) included HSCT recipients between 2009 and 2018 in Taiwan. The primary outcome was cumulative incidence of CMV infection or disease at day 100 after HSCT. Secondary outcomes included day 180 cumulative incidence of CMV infection or disease, infection sites, risk factors for CMV infection or disease, survival analysis, and overall survival after CMV infection and disease. Results: There were 4394 HSCT recipients included in the study (2044 auto-HSCT and 2350 allo-HSCT). The cumulative incidence of CMV infection and disease was significantly higher in allo-HSCT than in auto-HSCT patients at day 100 (53.7% vs. 6.0%, P

More highway built in the mountains in recent years, the driving risk in the tunnel group is becoming a new issue. This paper analyzed the driving risk in the mountain highway tunnel group from the perspective of visual load. Based on vehicle test in the Pengshui-Xiantang tunnel group in China, the evolution characteristics of MTPA were quantitatively analyzed, and the random forest model was constructed to discuss the effect factors of the maximum transient velocity value of the pupil area (MTPA) in different sections. The results are as follows: (1) The MTPA frequently presents a tendency of steep rise and fall in the tunnel group. MTPA in the second tunnel is significantly higher than the first tunnel. (2) The mountain tunnel group can be divided into nine sections; the velocity, design luminance, measured luminance, and location have different effects on MTPA in each section. Due to the complex terrain conditions, the location has a more significant impact on MTPA in the second tunnel. (3) The first tunnel entrance, the first tunnel exit to the second tunnel entrance, and the second tunnel exit are the areas with more significant pressure on drivers in the tunnel group. The visual load of drivers in the exit section of the last tunnel is the greatest. The driving risk reduction recommendations include improving the transition lighting design of the second tunnel, clarifying the tunnel group identification, and adding safety features at the tunnel connection section, in order to clarify the driver's expectations and reduce the fear of the unknown mountain environment., Author(s): Hao Lu [1]; Tongtong Shang [2]; Ting Shang (corresponding author) [3] 1. Introduction Highway tunnels are a crucial component of the transportation network [1]. Road safety in highway tunnels [...]

Abstract This study aims to model a hybrid power system that can continuously generate power by switching between two possible thermal sources: solar radiation and combustion energy from synthesis gases. The system comprised a hybrid energy receiver, solar dish, Stirling generator, fluidized‐bed gasifier, boiler, and water tank. The solar dish was a dual‐reflection solar collector that used two mirrors, namely the main and subordinate concentrators, to concentrate a broad expanse of solar radiation onto a hybrid energy receiver. The fluidized‐bed gasifier was employed for the production of synthesis gases. The synthesis gases were combusted to provide an auxiliary heat source for the Stirling generator when solar radiation was insufficient. Solar radiation or combustion energy was alternatively introduced into the hybrid energy receiver and converted to power by a 1‐kW‐scale beta‐type Stirling engine. In this manner, the Stirling generator could serve as a base‐load power plant regardless of solar conditions. In this study, a complete quantitative model was developed for a demonstration plant by incorporating thermodynamic and dynamic models of the beta‐type Stirling engine, a ray‐tracing model for the dual‐reflection solar dish, an energy model of the hybrid energy receiver, and experimental data for the fluidized‐bed gasifier. The performance response of the system during switching between solar radiation and combustion energy was predicted. The modeling results indicated that switching can result in a continuous power output ranging from 600 to 1200 W. With synthesis gas combustion as the auxiliary heat source, the hybrid Stirling power system can be operated continuously, and the overall power output is increased by 109.82% compared to a conventional concentrated solar power system that only uses solar radiation.

Background: Personalized nutrition risk assessment is crucial in addressing the association between healthy dietary habits across the life course and the development of disease, functional capacity, and healthy aging, as specific dietary pattern recommendations may not be suitable for diverse food cultures. Objective: To develop a data-driven, personalized nutrition risk assessment algorithm linked to incident hypertension, diabetes, and all-cause mortality utilizing the food frequency questionnaire among middle-aged and older individuals. Methods: A retrospective, population-based cohort study conducted between 1999 and 2015 utilized the nationally representative Taiwan Longitudinal Study on Aging (TLSA) survey to examine personalized dietary risk clusters and their associations with health outcomes. Latent class analysis was performed to derive the dietary diversity clusters among community-dwelling middle-aged and older individuals. Outcomes were defined as new-onset hypertension, diabetes mellitus and all-cause mortality at 4-, 8-, 12- and 16-year follow-ups. Results: Data from 1,811 participants (58.14% males, 43.90% aged 50−64 years) showed that around one-third of participants reported being illiterate, 21.98% widowed, and 51.46% engaging in regular physical exercise. Four dietary diversity clusters were identified: “least diverse”, “fish and meat”, “dairy, fruit, and vegetable”, and “most diverse”. The “most diverse” cluster was characterized by a high consumption of protein-rich foods, while the “dairy, fruit, and vegetable” cluster had the highest consumption of dairy products and beans/legumes. The “least diverse” cluster had the lowest intake of protein-rich foods, and dark-colored vegetables and fruits. The “most diverse” cluster had a significantly lower risk of hypertension development at the 4-year (aOR 0.58; p < 0.02) and 8-year (aOR 0.57; p < 0.01) follow-up and diabetes at the 4-year (aOR 0.44; p < 0.03) follow-up. Participants in the “most diverse” clusters exhibited lower risks of 8-year, 12-year, and 16-year mortality than those in the “least diverse” cluster (aOR 0.67, p < 0.05; 0.67, p < 0.03; and 0.50, p < 0.01, respectively). Conclusion: The personalized nutrition risk assessment algorithm from the food frequency questionnaire can effectively stratify personal health risks among diverse middle-aged and older individuals, making it a valuable tool in lifestyle modification and intervention studies.

This paper proposes a new control system by integrating integral state feedback control and sliding mode control to eliminate the influences from the reference input change, external load, and parameter variations. For most control systems, integral action is used to overcome the reference input change and external load. However, its control performance cannot be guaranteed. State feedback control is used to dominate the pole location of the closed-loop control system. However, the system parameters determine their pole locations and may change due to uncertainties. Thus, the characteristics of the closed-loop control system are changed. Sliding mode control is used to compensate for the effect of the parameter variations and make the system invariant. The resulting system combines linear state feedback and sliding mode control to guarantee the desired performance. This shows that the proposed system can be easily applied and designed. A servo control system is used to demonstrate the performance, and simulations and experiments are carried out to evaluate the newly defined structure. They show that the strategies and control design can reach robust performance even with uncertainties or external load, and the chattering of the sliding mode control can be minimized.

Abstract Free oligosaccharides are abundant macronutrients in milk and involved in prebiotic functions and antiadhesive binding of viruses and pathogenic bacteria to colonocytes. Despite the importance of these oligosaccharides, structural determination of oligosaccharides is challenging, and milk oligosaccharide biosynthetic pathways remain unclear. Oligosaccharide structures are conventionally determined using a combination of chemical reactions, exoglycosidase digestion, nuclear magnetic resonance spectroscopy, and mass spectrometry. Most reported free oligosaccharides are highly abundant and have lactose at the reducing end, and current oligosaccharide biosynthetic pathways in human milk are proposed based on these oligosaccharides. In this study, a new mass spectrometry technique, which can identify linkages, anomericities, and stereoisomers, was applied to determine the structures of free oligosaccharides in human, bovine, and caprine milk. Oligosaccharides that do not follow the current biosynthetic pathways and are not synthesized by any discovered enzymes were found, indicating the existence of undiscovered biosynthetic pathways and enzymes.

Mass spectrometry can be used for structural determination of N-glycans, but commonly requires prior derivatisation or comparison to a library of standards. Here logically-derived sequence tandem mass spectrometry allows for assignment of native N-glycans by analysis of successive fragmentation patterns without derivatisation and standards.

[Purpose/significance] Summarizing and exploring the path of open government data empowerment and value enhancement can enrich the theoretical basis in this field, and open up channels for the integration and utilization of open government data to value enhancement, and provide reference for the current stage of open government data resource construction and social environment construction . [Methods/process] Based on the analysis of the data usage and related policy releases of the open government data platform website, this paper explored the basic path of open government data empowerment and value enhancement from the three aspects of data, policy and market drive, and proposed future development strategies . [Results/conclusions] The basic internal and external driving paths of open government data empowerment and value enhancement can be divided into the following three types: data appreciation, policy release, and market promotion. And specific strategies that can be implemented at the emergence stage are proposed, that is, to release the value of open government data, increase the utilization efficiency of open government data, and build a open government data value enhancement strategy system that can be used for three purposes.

Improving the driving safety of mountainous highway tunnels has become an urgent problem in China, while the existing literature pays more attention to the safety of urban tunnels. From the perspective of visual load, this paper built a GA-SVR model to analyze the influences of speed, design brightness, measured brightness, and position in the Gaogu long tunnel. The results show the following: firstly, the changes of MTPA in the long mountainous highway tunnels can be divided into five stages, which is different from the three-stage division of urban tunnels; secondly, the influencing degree of factors was varied in different stages: the position factor mattered most in stages 1, 2, 4, and 5, while the design brightness had the greatest impact in stage 3; thirdly, the driver's psychological pressure was greatest on the entrance and exit section of the tunnel; lastly, the increased length of mountainous highway tunnels and the long-term enclosed driving environment made the psychological load of drivers intensified. Therefore, it was necessary for the mountainous highway tunnels to consider more accurate gradual lighting design in the 200-m sections after the entrance and before the exit, meanwhile enhancing traffic safety management and protections in the middle of the tunnel., Author(s): Hao Lu [1]; Ting Shang (corresponding author) [2]; Jie Bao [1]; Ye Liang [2] 1. Introduction In compliance with the national strategy for west China development, more and more [...]

Gramicidin A (gA) is a linear antimicrobial peptide that can form a channel and specifically conduct monovalent cations such as H+ across the lipid membrane. The antimicrobial activity of gA is associated with the formation of hydroxyl free radicals and the imbalance of NADH metabolism, possibly a consequence caused by the conductance of cations. The ion conductivity of gramicidin A can be blocked by Ca2+ ions. However, the effect of Ca2+ ions on the antimicrobial activity of gA is unclear. To unveil the role of Ca2+ ions, we examined the effect of Ca2+ ions on the antimicrobial activity of gramicidin A against Staphylococcus aureus (S. aureus). Results showed that the antimicrobial mechanism of gA and antimicrobial activity by Ca2+ ions are concentration-dependent. At the low gA concentration (≤1 μM), the antimicrobial mechanism of gA is mainly associated with the hydroxyl free radical formation and NADH metabolic imbalance. Under this mode, Ca2+ ions can significantly inhibit the hydroxyl free radical formation and NADH metabolic imbalance. On the other hand, at high gA concentration (≥5 μM), gramicidin A acts more likely as a detergent. Gramicidin A not only causes an increase in hydroxyl free radical levels and NAD+/NADH ratios but also induces the destruction of the lipid membrane composition. At this condition, Ca2+ ions can no longer reduce the gA antimicrobial activity but rather enhance the bacterial killing ability of gramicidin A.

Due to topography, geology, and other factors, small spacing sections are common between tunnels and interchange exits. There is mandatory lane-changing behavior for vehicles that need to leave the main line and drive inside the road before leaving the tunnel. Affected by the 'white hole' of a tunnel, the lane-changing behavior of off-ramp vehicles differs significantly from that of original roadbed sections. To study the mandatory lane-changing duration (MLCD) of off-ramp vehicles in small spacing sections of the tunnel to interchange in mountainous areas, their time and trajectory data were collected based on a driving simulator. According to the characteristics of the data, the survival analysis method was used to analyze the influence on the MLCD of off-ramp vehicles of the spacing section between the tunnel and interchange, vehicle types, tunnel types, ramp types, highway service level, and whether to set exit advance guide signs in the tunnel and the Cox proportional hazards model of the MLCD was established. The results showed that the spacing of the tunnel interchange, the road service level, and whether to set exit advance guide signs in the tunnel had significant effects on the MLCD of vehicles, while the vehicle, the tunnel, and the ramp types did not. When the spacing section of the tunnel interchange was less than 500m, the off-ramp vehicle had continuous mandatory lane-changing behavior, and when the distance decreased from 400m to 300m, the risk rate of lane changing increased by 5.68 times. Survival function curve estimation provided the 75% quantile of MLCD of off-ramp vehicles under different conditions, which could provide a theoretical reference for setting the minimum distance between a tunnel and interchange exit., Author(s): Ting Shang [1]; Guan Lian (corresponding author) [2]; Yingci Zhao [3]; Xingliang Liu [1]; Weijun Wang [4] 1. Introduction With the development of mountainous highways in China, limited by [...]

BACKGROUND: Dental health issues are on the rise, necessitating prompt and precise diagnosis. Automated dental condition classification can support this need. OBJECTIVE: The study aims to evaluate the effectiveness of deep learning methods and multimodal feature fusion techniques in advancing the field of automated dental condition classification. METHODS AND MATERIALS: A dataset of 11,653 clinically sourced images representing six prevalent dental conditions—caries, calculus, gingivitis, tooth discoloration, ulcers, and hypodontia—was utilized. Features were extracted using five Convolutional Neural Network (CNN) models, then fused into a matrix. Classification models were constructed using Support Vector Machines (SVM) and Naive Bayes classifiers. Evaluation metrics included accuracy, recall rate, precision, and Kappa index. RESULTS: The SVM classifier integrated with feature fusion demonstrated superior performance with a Kappa index of 0.909 and accuracy of 0.925. This significantly surpassed individual CNN models such as EfficientNetB0, which achieved a Kappa of 0.814 and accuracy of 0.847. CONCLUSIONS: The amalgamation of feature fusion with advanced machine learning algorithms can significantly bolster the precision and robustness of dental condition classification systems. Such a method presents a valuable tool for dental professionals, facilitating enhanced diagnostic accuracy and subsequently improved patient outcomes. [ABSTRACT FROM AUTHOR]

Noise from elevated railway bridges in urban areas has been causing severe environmental issues. To find the peak frequency of sound energy and thus develop targeted countermeasures for noise mitigation, policymakers need a better understanding of the noise characteristics of urban railway bridges during train passage. This study approaches this issue by combining transient dynamic analyses and acoustic finite element simulation. Our frequency characteristic analysis focused on two primary noise sources: wheel-rail noise and bridge-borne noise. We built a spatial noise model that predicts the radiated noise of urban railway bridges in both the active and planning stages. The results show that the wheel-rail noise peaked at 800 Hz, 1600 Hz, and 3150 Hz, while the bridge-borne noise peaked at 40 Hz, 50 Hz, 80 Hz, and 125 Hz. The validation results demonstrated that the developed noise spatial prediction model extended well to similar urban railway bridges. [ABSTRACT FROM AUTHOR]