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Abstract Background Prefabricated myofunctional appliance can guide tooth eruption, improve dentition alignment, correct myofunctional disorders and harmful oral habits. However, its application to skeletal discrepancy may result in unsatisfactory tooth inclination. This study aimed to construct a novel appliance with overjet design to avoid this side effect and investigated its shape and mechanical changes under occlusion using three-dimensional finite element method. Methods We established three samples of prefabricated myofunctional appliances. The first one was edge to edge without overjet, and the outer shield of both jaws were flattened. The second one was 3 mm overjet with stepped the outer shield. The last one was 3 mm overjet, and the outer shield of both jaws were flatted, which meant the front wall of lower jaw was strengthened with bumper, termed as lower bumper. A complete dentition model was applied to the study. 150 N occlusal force was applied to each type of appliance and the deformation displacement and the changes in stress was recorded. Results The deformation was significant in the incisors regions, especially in the vertical and lateral dimensions. The maximum displacements of 3 mm overjet with step shield group were 7.08 mm (vertical), 3.99 mm (lateral), and 2.90 mm (sagittal), while it decreased to 3.92 mm(vertical), 1.94 mm (lateral), and 1.55 mm (sagittal) in overjet with bumper group. Moreover, the upper molar regions exhibited higher vertical and sagittal displacement in 3 mm overjet with step shield group, which were 3.03 mm (vertical) and 1.99 mm (sagittal), and the bumper design could decrease the maximum displacement to 1.72 mm (vertical) and 0.72 mm (sagittal). In addition, the Von Mises stress of appliances was analyzed, and results indicated that 3 mm overjet with step shield generated higher stress than other groups, with the maximum Von Mises stress was 0.9387 MP, which were 0.5858 and 0.5657 MP in edge to edge group and 3 mm overjet with lower bumper group, respectively. Conclusion The prefabricated myofunctional appliances may cause deformation during occlusion. Compared to step shield group, the application of lower bumper exhibited better resistance to occlusal force.

A new type of rotary reducer is urgently needed in engineering to improve the low efficiency of single point drive operation for flat single axis photovoltaic tracking brackets, in order to adapt to complex environments and reduce costs. For this purpose, a cylindrical worm helical gear toroidal worm multi-point drive rotary reducer is designed, and performance testing and analysis are conducted. Firstly, analyze and compare the installation position and transmission mechanism of the multi-point drive rotary reducer with that of the single point drive. Secondly, the performance of the rotary reducer under rated output torque and overturning torque is numerically simulated using Romax software, and a comprehensive performance testing platform for the rotary reducer is built to test the transmission performance of the prototype under rated output torque and overturning torque. The results show that multi-point drive can withstand larger loads compared to single point drive, and the overall stability of the tracking bracket is stronger; the larger the rated output torque value, the greater the stress value of the worm gear; the overall stress value and deformation of the secondary transmission mechanism under the overturning torque meet the actual working condition requirements; the experimental test does not cause significant damage inside the reducer, and the simulation and experimental results are in good agreement. The design of the rotary reducer meets the practical working characteristics of the flat single axis photovoltaic tracking bracket under harsh working conditions, and can provide theoretical reference and support for improving the photovoltaic conversion efficiency construction of photovoltaic power stations.

In order to solve the problems of eccentric load of planetary gear train and large impact of gear teeth meshing caused by torsional deformation of double planetary gear shafts under load, a topological modification method considering torsional deformation of double planetary gear shaft is proposed. The causes of torsional deformation of the double planetary gear shaft and its influence on the load sharing performance of the gear train are analyzed. Based on the multi body gear bearing contact analysis (PLTCA) and the gear bearing contact analysis (LTCA), the bearing transmission error and the tooth surface load distribution coefficient under the deformation are solved; the optimization intelligent algorithm is used to solve the optimal solution of the modification parameters under the condition of the maximum modification amount of the tooth surface; the simulation results show that the proposed method can effectively reduce the unit length load of the tooth surface and the amplitude of the transmission error. The unit length load of the first and second planetary tooth surfaces is reduced by 33.58% and 21.35% respectively, and the amplitude of the transmission error is reduced by 77.74%; the experimental verification is carried out on the reducer load test-bed, and the experimental results are consistent with the simulation results. The wear condition of the planetary gear surface is greatly improved, the problem of eccentric load of NGWN planetary gear train is better solved, and the transmission accuracy and service life of the equipment are improved.

The abnormal concentration of stress in the structure area of the working face is closely related to the rock burst. Based on the good correlation between the wave velocity and stress of the coal and rock mass, the seismic wave CT detection technology is widely used in the evaluation and warning of the risk of rock burst. However, the existing researches are mainly focused on simple conditions or single structure area. The composite structure area formed by multiple geological structures has not been discussed. Taking the 2305 fully mechanized working face of a mine in Shandong as an example, in the context of the concentration of microseismic events in the composite structure area and the occurrence of rock bursts, the seismic wave CT detection technology is used to obtain the stress distribution of coal and rock mass in the structure area and the characteristic index c including speed and speed gradient of seismic wave is introduced to analyze the stress distribution characteristics and the risk of rock burst. The research results show that: ① The concentration of microseismic events is related to adjacent structures. The concentrated areas can be divided into single or composite areas according to the number of structures, and can be divided into strongly or weakly disturbed areas according to the degree of disturbance. ② The strongly disturbed area composite structure area has the highest static stress concentration, and the weakly disturbed single structure area has the lowest stress concentration. The stress increase level of the fault single structure area is positively correlated with the degree of disturbance. The syncline in the weakly disturbed composite structure area has a significantly higher stress than the fault area. ③ The static stress concentration of the surrounding rock in the structure area is the main cause of intense surrounding rock activity. Based on the static load of surrounding rock and the dynamic load increment under the influence of mining, the risk of rock burst in the concentrated area of different microseismic events can be obtained.

The number of cars on roadways around the world continues to increase year over year. However, the imbalance between traffic supply and demand has not only brought traffic congestion but also caused serious safety problems. To reduce travel risk, this study proposes a driver route planning method based on accident risk cost prediction for connected and automated vehicles. According to the entropy weight method and an improved algorithm of K shortest paths, a route planning model with accident risk as the main optimization objective was established. Firstly, an accident risk evaluation system was built based on traffic accident data, and a quantitative prediction model of accident risk cost based on driver-, vehicle-, road-, and environment-related factors was constructed. Secondly, the entropy weight method was used to calculate the weights of each indicator to determine accident risk considering the aforementioned factors. Then, the route planning model was established, and the solution algorithm based on K shortest paths was designed to solve the optimal route by comprehensively considering accident risk cost and travel time. The accident risk index of each road section in the example road network was assigned, and the risk of the road section was quantified according to the accident risk cost model. Three candidate paths were calculated by using the path planning algorithm proposed in this study; the total risk cost is 6.19, 6.26, and 6.39, respectively; and the total travel time is 29, 29, and 31, respectively. After comparison, the optimal path and two alternative paths are obtained. The results show that the accident risk cost prediction model based on historical accident data can be used to quantify driving risk. The proposed method can help drivers in the connected and automated environment choose the optimal travel route with the lowest risk and shortest travel time and improve overall traffic safety and efficiency., Author(s): Xiaoleng Liao [1]; Tong Zhou [1]; Xu Wang (corresponding author) [1]; Rongjian Dai [1]; Xuehui Chen [2]; Xiangmin Zhu [2] 1. Introduction With the rapid development of the global [...]

The working device of an excavator in construction machinery is prone to damage and wear under ordinary working conditions. Based on a model of an excavator under typical working conditions, the dynamic load-bearing situation of the three main joint friction subsets of the working device is simulated by using the virtual prototype technology; the location of the functional device with high stress is identified based on finite element analysis, and the correctness of the simulation results is verified by designing strain gauges. Based on this, the dynamic contact stress variation law of the contact surface of the end-face friction subsets was explored, and the end-face wear depth was calculated by combining Archard wear theory and finite element wear simulation technology; the specimens were worn on the end-face wear tester, and the surface wear was observed under the scanning electron microscope to summarize the wear mechanism and analyze the element content changes of the worn surface. The results show that the three main joints of the working device produce large dynamic fluctuations and are prone to wear, and the destructive degree is more prominent; the wear process is accompanied by higher temperatures, fatigue wear, and abrasive wear on the wear surface, and the wear depth value of the right end face is significantly larger than that of the left end face. This method has a significant reference value for reliability analysis and optimization improvement when using construction machinery's main joint friction pairs. [ABSTRACT FROM AUTHOR]

Diabetic foot ulcers (DFUs) pose significant clinical challenges, representing severe complications in diabetes mellitus patients and contributing to non‐traumatic amputations. Identifying reliable biomarkers can optimize early diagnosis and improve therapeutic outcomes. This study focused on evaluating the association between serum levels of 25‐hydroxyvitamin D [25‐(OH)D], Serum Retinol Binding Protein (RBP), and Cyclooxygenase‐2 (COX‐2) in elderly DFU patients. A retrospective study involving 240 participants, from March 2020 to March 2023. The participants were segmented into three cohorts: 80 with DFUs, 80 diabetic patients without DFUs, and 80 healthy controls. Serum concentrations of the three biomarkers were assayed using methods like enzyme‐linked immunosorbent assay (ELISA), chemiluminescence immunoassay, and an automated biochemistry analyser. Comparisons were made both between groups and within the DFU group based on disease severity. Statistical analysis revealed significant differences in biomarker levels across the groups (p < 0.05). COX‐2 and RBP concentrations were highest in the DFU group, followed by the non‐DFU diabetic group, and lowest in the control group. Conversely, 25(OH)D levels were highest in the control group, followed by the non‐DFU diabetic group, and lowest in the DFU group. Within the DFU group, RBP and COX‐2 levels increased with disease severity, while 25(OH)D levels decreased. These variations were especially pronounced in patients with the most severe Wagner grading. A significant positive correlation was observed between disease severity and levels of RBP (r = 0.651, p < 0.05) and COX‐2 (r = 0.356, p < 0.05). Conversely, a significant negative correlation was identified between disease severity and 25(OH)D levels (r = −0.658, p < 0.05). Assessing 25(OH)D, RBP, and COX‐2 serum levels offers a promising tool for evaluating the severity and progression of DFUs. Monitoring these biomarkers can enrich our understanding of the metabolic and inflammatory pathways of the disease and potentially refine therapeutic strategies. [ABSTRACT FROM AUTHOR]

Initiation of T cell receptor (TCR) signaling involves the activation of the tyrosine kinase LCK; however, it is currently unclear how LCK is recruited and activated. Here, we have identified the membrane protein CD146 as an essential member of the TCR network for LCK activation. CD146 deficiency in T cells substantially impaired thymocyte development and peripheral activation, both of which depend on TCR signaling. CD146 was found to directly interact with the SH3 domain of coreceptor-free LCK via its cytoplasmic domain. Interestingly, we found CD146 to be present in both monomeric and dimeric forms in T cells, with the dimerized form increasing after TCR ligation. Increased dimerized CD146 recruited LCK and promoted LCK autophosphorylation. In tumor models, CD146 deficiency dramatically impaired the antitumor response of T cells. Together, our data reveal an LCK activation mechanism for TCR initiation. We also underscore a rational intervention based on CD146 for tumor immunotherapy., Introduction T cell activation undergoes an orderly and complex process that critically relies on T cell receptor (TCR) signaling, which requires an orchestrated interplay of receptors, receptor-associated factors, kinases, and [...]

Object detection in low-light scenarios has been widely acknowledged as a significant research area in the field of computer vision, presenting a challenging task. Aiming at the low detection accuracy of mainstream single-stage object detection models in low-light scenarios, this paper proposes a detection model called DK_YOLOv5 based on YOLOv5, specifically designed for such scenarios. First, a low-light image enhancement algorithm with better results is selected to generate enhanced images that achieve relatively better visual effects and amplify target features. Second, the SPPF layer is improved to an R-SPPF module with faster inference speed and stronger feature expression ability. Next, we replace the C3 module with the C2f module and incorporate an attention mechanism to develop the C2f_SKA module, enabling richer gradient information flow and reducing the impact of noise features. Finally, the model detection head is replaced with a decoupled head suitable for the object detection task in this scenario to improve model performance. Additionally, we expand the Exdark dataset to include low-light data of underground mine scenario targets, named Mine_Exdark. Experimental results demonstrate that the proposed DK_YOLOv5 model achieves higher detection accuracy than other models in low-light scenarios, with an mAP0.5 of 71.9% on the Mine_Exdark dataset, which is 4.4% higher than that of YOLOv5. [ABSTRACT FROM AUTHOR]

Understanding equity and travelers' behavior plays a key role in creating suitable strategies to promote the development of the expressway. Especially, finding clusters of expressway users could help managers provide targeted policies in order to enhance service quality. However, it is challenging to identify expressway travel behaviors, such as traffic flow distribution and users' classification. Electronic toll collection (ETC) has been widely applied to improve expressway management, because it can record the origin–destination information of users. This paper proposes a framework to analyze the equity and travel behavior of expressway users with a large amount of ETC data. In the first stage, the Gini coefficient is adopted to analyze expressway equity. In the second stage, 12 kinds of indicators are extracted, including number of trips, car type, mean distance, etc. In the third stage, kmeans algorithm is adopted to cluster the users, based on the introduced indicators. Finally, we analyze the traffic flow distribution of each group by constructing a traffic flow network. The results show that the Gini coefficient is 0.4193, which demonstrates evident inequity in the expressway service. Moreover, statistical analysis shows that expressway flow is complicated and 70.77% of travelers do not make repeat trips. It is demonstrated that expressway users can be divided into six groups, and the flow networks of cluster 2 and cluster 3 are connected more closely and evenly than other clusters are. [ABSTRACT FROM AUTHOR]