Impact of Vehicle Steering Strategy on the Severity of Pedestrian Head Injury.

In response to the sudden violation of pedestrians crossing the road, intelligent vehicles take into account factors such as the road conditions in the accident zone, traffic rules, and surrounding vehicles' driving status to make emergency evasive decisions. Thus, the collision simulation models for pedestrians and three types of vehicles, i.e., sedans, Sport Utility Vehicles (SUVs), and Multi-Purpose Vehicle (MPVs), are built to investigate the impact of vehicle types, vehicle steering angles, collision speeds, collision positions, and pedestrian orientations on head injuries of pedestrians. The results indicate that the Head Injury Criterion (HIC) value of the head increases with the increase in collision speed. Regarding the steering angles, when a vehicle's steering direction aligns with a pedestrian's position, the pedestrian remains on top of the vehicle's hood for a longer period and moves together with the vehicle after the collision. This effectively reduces head injuries to pedestrians. However, when the vehicle's steering direction is opposite to the pedestrian's position, the pedestrian directly collides with the ground, resulting in higher head injuries. Among them, MPVs cause the most severe injuries, followed by SUVs, and sedans have the least impact. Overall, intelligent vehicles have great potential to reduce head injuries of pedestrians in the event of sudden pedestrian-vehicle collisions by combining with Automatic Emergency Steering (AES) measures. In the future, efforts need to be made to establish an optimized steering strategy and optimize the handling of situations where steering is ineffective or even harmful.

FusionOpt-Net: A Transformer-Based Compressive Sensing Reconstruction Algorithm.

Compressive sensing (CS) is a notable technique in signal processing, especially in multimedia, as it allows for simultaneous signal acquisition and dimensionality reduction. Recent advancements in deep learning (DL) have led to the creation of deep unfolding architectures, which overcome the inefficiency and subpar quality of traditional CS reconstruction methods. In this paper, we introduce a novel CS image reconstruction algorithm that leverages the strengths of the fast iterative shrinkage-thresholding algorithm (FISTA) and modern Transformer networks. To enhance computational efficiency, we employ a block-based sampling approach in the sampling module. By mapping FISTA's iterative process onto neural networks in the reconstruction module, we address the hyperparameter challenges of traditional algorithms, thereby improving reconstruction efficiency. Moreover, the robust feature extraction capabilities of Transformer networks significantly enhance image reconstruction quality. Experimental results show that the FusionOpt-Net model surpasses other advanced methods on various public benchmark datasets.

Clarifying the impact of engine operating parameters of heavy-duty diesel vehicles on NOx and CO2 emissions using multimodal fusion methods.

The issue of air pollution from transportation sources remains a major concern, particularly the emissions from heavy-duty diesel vehicles, which pose serious threats to ecosystems and human health. China VI emission standards mandate On-Board Diagnostics (OBD) systems in heavy-duty diesel vehicles for real-time data transmission, yet the current data quality, especially concerning crucial parameters like NOx output, remains inadequate for effective regulation. To address this, a novel approach integrating Multimodal Feature Fusion with Particle Swarm Optimization (OBD-PSOMFF) is proposed. This network employs Long Short-Term Memory (LSTM) networks to extract features from OBD indicators, capturing temporal dependencies. PSO optimizes feature weights, enhancing prediction accuracy. Testing on 23 heavy-duty vehicles demonstrates significant improvements in predicting NOx and CO2 mass emission rates, with mean squared errors reduced by 65.205 % and 70.936 % respectively compared to basic LSTM models. This innovative multimodal fusion method offers a robust framework for emission prediction, crucial for effective vehicle emission regulation and environmental preservation.

NLRP3 blockade by MCC950 suppressed osteoclastogenesis via NF-κB/c-Fos/NFATc1 signal pathway and alleviated bone loss in diabetes mellitus.

Obesity and type 2 diabetes mellitus (T2DM) are linked to osteoporosis development, with obesity being a significant risk factor for T2DM. T2DM patients with obesity exhibit a higher fracture rate and often have a poor prognosis post-fracture. To address the urgent need for understanding the mechanisms of diabetic osteoporosis (DOP), research is ongoing to explore how obesity and T2DM impact bone metabolism. The NLRP3 inflammasome has been implicated in the pathogenesis of osteoporosis, and MCC950, an NLRP3 inflammasome inhibitor, has shown promise in various diseases but its role in osteoporosis remains unexplored. In this study, BMMs and BMSCs were isolated and cultured to investigate the effects of MCC950 on bone metabolism, and DOP model was used to evaluate the efficacy of MCC950 in vivo. The study demonstrated that MCC950 treatment inhibited osteoclast differentiation, reduced bone resorption capacity in BMMs without suppression for osteoblast differentiation from BMSCs. Additionally, MCC950 suppressed the activation of the NF-κB signaling pathway and downregulated key factors associated with osteoclast differentiation. Additionally, MCC950 alleviated bone loss in DOP mouse. These findings suggest that MCC950, by targeting the NLRP3 inflammasome, may have a protective role in preventing osteoporosis induced by T2DM with obesity. The study highlights the potential therapeutic implications of MCC950 in managing diabetic osteoporosis and calls for further research to explore its clinical application in high-risk patient populations.

The effects of foot orthoses on radiological parameters and pain in children with flexible flat feet: a systematic review and meta-analysis.

Objective: This study aimed to investigate the impact of foot orthoses on foot radiological parameters and pain in children diagnosed with flexible flatfoot. Methods: A comprehensive search was conducted across several databases, including PubMed, Web of Science, EMBASE, Cochrane Library, and EBSCO, covering publications from the inception of each database up to 8 June 2024. The study focused on randomized controlled trials investigating the use of foot orthoses for treating flexible flat feet in children. Four researchers independently reviewed the identified literature, extracted relevant data, assessed the quality of the studies, and performed statistical analyses using RevMan 5.4 software. Results: Six studies involving 297 participants were included. The methodological quality of the included literature ranged from moderate to high. Radiological parameters of the foot improved significantly in older children with flexible flat feet following foot orthotic intervention compared to controls, particularly in the lateral talar-first metatarsal angle [mean difference (MD) = -2.76, 95% confidence interval (95% CI) -4.30 to -1.21, p = 0.0005], lateral talo-heel angle (MD = -5.14, 95% CI -7.76 to -2.52, p = 0.0001) and calcaneal pitch angle (MD = 1.79, 95% CI 0.88-2.69, p = 0.0001). These differences were statistically significant. Additionally, foot orthoses significantly improved the ankle internal rotation angle and reduced foot pain in children with symptomatic flexible flatfoot (MD = -2.51, 95% CI -4.94 to -0.07, p = 0.04). Conclusion: The use of foot orthoses positively impacts the improvement of radiological parameters of the foot and reduces pain in older children with flexible flat feet. However, in younger children with flexible flat feet, the improvement from foot orthoses was not significant, likely due to challenges in radiological measurements caused by the underdevelopment of the ossification centers in the foot. Further studies are needed. Consequently, the results of this meta-analysis support the implementation of an early intervention strategy using foot orthoses for the management of symptomatic flat feet in older children. Systematic Review Registration: https://www.crd.york.ac.uk/, PROSPERO [CRD42023441229].

Single-pulse three-dimensional parallel recording in glass using a feedback system.

High-quality three-dimensional computer-generated holograms (3D-CGHs) are crucial for programmable 3D femtosecond laser parallel recording (3D-FLPR). In this study, we introduced an innovative feedback approach for the rapid optimization of 3D-CGHs by incorporating the superposition of the calculated lens phases (CLPs) onto the 3D-CGHs within a feedback system. This feedback system, governed by coordinated control of a spatial light modulator (SLM) and a camera, served to avoid the poor quality of the ordinary CGH system. As a result, we successfully demonstrated coaxial 3D-FLPR in Ag-doped phosphate glass solely using a single fs laser pulse. Additionally, we regulated the energy distribution of the generated 3D multi-focus (3D-MF) to compensate the laser energy losses inside the glass. The presented single-pulse 3D parallel recording indicated the significant advancement facilitated by our method, particularly in enhancing the writing efficiency of optical storage.

Inhibition of Tumoral VISTA to Overcome TKI Resistance via Downregulation of the AKT/mTOR and JAK2/STAT5 Pathways in Chronic Myeloid Leukemia.

Tyrosine kinase inhibitors (TKIs) have revolutionized the treatment landscape for chronic myeloid leukemia (CML). However, TKI resistance poses a significant challenge, leading to treatment failure and disease progression. Resistance mechanisms include both BCR::ABL1-dependent and BCR::ABL1-independent pathways. The mechanisms underlying BCR::ABL1 independence remain incompletely understood, with CML cells potentially activating alternative signaling pathways, including the AKT/mTOR and JAK2/STAT5 pathways, to compensate for the loss of BCR::ABL1 kinase activity. This study explored tumoral VISTA (encoded by VSIR) as a contributing factor to TKI resistance in CML patients and identified elevated tumoral VISTA levels as a marker of resistance and poor survival. Through in vitro and in vivo analyses, we demonstrated that VSIR knockdown and the application of NSC-622608, a novel VISTA inhibitor, significantly impeded CML cell proliferation and induced apoptosis by attenuating the AKT/ mTOR and JAK2/STAT5 pathways, which are crucial for CML cell survival independent of BCR::ABL1 kinase activity. Moreover, VSIR overexpression promoted TKI resistance in CML cells. Importantly, the synergistic effect of NSC-622608 with TKIs offers a potent therapeutic avenue against both imatinib-sensitive and imatinib-resistant CML cells, including those harboring the challenging T315I mutation. Our findings highlight the role of tumoral VISTA in mediating TKI resistance in CML, suggesting that inhibition of VISTA, particularly in combination with TKIs, is an innovative approach to enhancing treatment outcomes in CML patients, irrespective of BCR::ABL1 mutation status. This study not only identified a new pathway contributing to TKI resistance but also revealed the possibility of targeting tumoral VISTA as a means of overcoming this significant clinical challenge.

Scaling-law mechanical marker for liver fibrosis diagnosis and drug screening through machine learning.

Studies of cell and tissue mechanics have shown that significant changes in cell and tissue mechanics during lesions and cancers are observed, which provides new mechanical markers for disease diagnosis based on machine learning. However, due to the lack of effective mechanic markers, only elastic modulus and iconographic features are currently used as markers, which greatly limits the application of cell and tissue mechanics in disease diagnosis. Here, we develop a liver pathological state classifier through a support vector machine method, based on high dimensional viscoelastic mechanical data. Accurate diagnosis and grading of hepatic fibrosis facilitates early detection and treatment and may provide an assessment tool for drug development. To this end, we used the viscoelastic parameters obtained from the analysis of creep responses of liver tissues by a self-similar hierarchical model and built a liver state classifier based on machine learning. Using this classifier, we implemented a fast classification of healthy, diseased, and mesenchymal stem cells (MSCs)-treated fibrotic live tissues, and our results showed that the classification accuracy of healthy and diseased livers can reach 0.99, and the classification accuracy of the three liver tissues mixed also reached 0.82. Finally, we provide screening methods for markers in the context of massive data as well as high-dimensional viscoelastic variables based on feature ablation for drug development and accurate grading of liver fibrosis. We propose a novel classifier that uses the dynamical mechanical variables as input markers, which can identify healthy, diseased, and post-treatment liver tissues.

Insulin receptor isoform B is required for efficient proinsulin processing in pancreatic ß cells.

The insulin receptor (INSR, IR) has two isoforms, IRA and IRB, through alternative splicing. However, their distinct functions in vivo remain unclear. Here we generated ß cell-specific IRB knockout (KO) mice (ßIRBKO). The KO mice displayed worsened hyperinsulinemia and hyperproinsulinemia in diet-induced obesity due to impaired proinsulin processing in ß cells. Mechanistically, loss of IRB suppresses eukaryotic translation initiation factor 4G1 (eIF4G1) by stabilizing the transcriptional receptor sterol-regulatory element binding protein 1 (SREBP1). Moreover, excessive autocrine proinsulin in ßIRBKO mice enhances the activity of extracellular signal-regulated kinase (ERK) through the remaining IRA to further stabilize nuclear SREBP1, forming a feedback loop. Collectively, our study paves the way to dissecting the isoform-specific function of IR in vivo and highlights the important roles of IRB in insulin processing and protecting ß cells from lipotoxicity in obesity.

Clinical knowledge-based ECG abnormalities detection using dual-view CNN-Transformer and external attention mechanism.

BACKGROUND: Automatic abnormalities detection based on Electrocardiogram (ECG) contributes greatly to early prevention, computer aided diagnosis, and dynamic analysis of cardiovascular diseases. In order to achieve cardiologist-level performance, deep neural networks have been widely utilized to extract abstract feature representations. However, the mechanical stacking of numerous computationally intensive operations makes traditional deep neural networks suffer from inadequate learning, poor interpretability, and high complexity. METHOD: To address these limitations, a clinical knowledge-based ECG abnormalities detection model using dual-view CNN-Transformer and external attention mechanism is proposed by mimicking the diagnosis of the clinicians. Considering the clinical knowledge that both the detailed waveform changes within a single heartbeat and the global changes throughout the entire recording have complementary roles in abnormalities detection, we presented a dual-view CNN-Transformer to extract and fuse spatial-temporal features from different views. In addition, the locations of the ECG where abnormalities occur provide more information than other areas. Therefore, two external attention mechanisms are designed and added to the corresponding views to help the network learn efficiently. RESULTS: Experiment results on the 9-class dataset show that the proposed model achieves an average F1-score of 0.854±0.01 with a higher interpretability and a lower complexity, outperforming the state-of-the-art model. CONCLUSIONS: Combining all these excellent features, this study provides a credible solution for automatic ECG abnormalities detection.

A Parameter Reduction-Based Decision-Making Method with Interval-Valued Neutrosophic Soft Sets for the Selection of Bionic Thin-Wall Structures.

Bio-inspired thin-wall structures with excellent mechanical properties, high-energy absorption capabilities, and a desirable lightweight level have been extensively applied to the passive safety protection of transportation and aerospace. Collaboration matching and the selection of optional structures with different bionic principles considering the multiple attribute evaluation index and engineering preference information have become an urgent problem. This paper proposes a parameter reduction-based indifference threshold-based attribute ratio analysis method under an interval-valued neutrosophic soft set (IVNS-SOFT) to obtain the weight vector of an evaluation indicator system for the selection of bionic thin-wall structures, which can avoid the problem of an inadequate subjective evaluation and reduce redundant parameters. An IVNS-SOFT-based multi-attributive border approximation area comparison (MABAC) method is proposed to obtain an optimal alternative, which can quantify uncertainty explicitly and handle the uncertain and inconsistent information prevalent in the expert system. Subsequently, an application of five bio-inspired thin-wall structures is applied to demonstrate that this proposed method is valid and practical. Comparative analysis, sensitivity analysis, and discussion are conducted in this research. The results show that this study provides an effective tool for the selection of bionic thin-wall structures.

Comparison of initial percutaneous balloon compression versus radiofrequency thermocoagulation followed by percutaneous balloon compression in the treatment of trigeminal neuralgia. / 首次经皮球囊压迫术与射频热凝术后再行经皮球囊压迫术治疗三叉神经痛的比较.

OBJECTIVES: There are a variety of minimally invasive interventional treatments for trigeminal neuralgia, and the efficacy evaluation is different. The preferred treatment scheme is still controversial. This study aims to investigate the differences in treatment effects between patients with primary trigeminal neuralgia (PTN) treated with percutaneous balloon compression (PBC) for the first intervention and patients with pain recurrence after radiofrequency thermocoagulation (RT) who then received PBC for PTN, and to offer clinicians and patients more scientifically grounded and precise treatment alternatives. METHODS: We retrospectively analyzed 103 patients with PTN admitted to the Department of Pain Management of the Second Affiliated Hospital of Guangxi Medical University from January 2020 to December 2021, including 49 patients who received PBC for the first time (PBC group) and 54 patients who received PBC for pain recurrence after RT (RT+PBC group). General information, preoperative pain score, intraoperative oval foramen morphology, oval foramen area, balloon volume, duration of compression, and postoperative pain scores and pain recurrence at each time point on day 1 (T1), day 7 (T2), day 14 (T3), 1 month (T4), 3 months (T5), and 1 year (T6) were collected and recorded for both groups. The differences in treatment effect, complications and recurrence between the 2 groups were compared, and the related influencing factors were analyzed. RESULTS: The differences of general information, preoperative pain scores, foramen ovale morphology, foramen ovale area, T1 to T3 pain scores between the 2 groups were not statistically different (all P>0.05). The balloon filling volume in the PBC group was smaller than that in the RT+PBC group, the pain scores at T4 to T6 and pain recurrence were better than those in the RT+PBC group (all P<0.05). Pain recurrence was positively correlated with pain scores of T2 to T6 (r=0.306, 0.482, 0.831, 0.876, 0.887, respectively; all P<0.01). CONCLUSIONS: The choice of PBC for the first intervention in PTN patients is superior to the choice of PBC after pain recurrence after RT treatment in terms of treatment outcome and pain recurrence.

Targeting PARP14 with lomitapide suppresses drug resistance through the activation of DRP1-induced mitophagy in multiple myeloma.

Multiple myeloma (MM) is a hematological malignancy that remains incurable, primarily due to the high likelihood of relapse or development of resistance to current treatments. To explore and discover new medications capable of overcoming drug resistance in MM, we conducted cell viability inhibition screens of 1504 FDA-approved drugs. Lomitapide, a cholesterol-lowering agent, was found to exhibit effective inhibition on bortezomib-resistant MM cells in vitro and in vivo. Our data also indicated that lomitapide decreases the permeability of the mitochondrial outer membrane and induces mitochondrial dysfunction in MM cells. Next, lomitapide treatment upregulated DRP1 and PINK1 expression levels, coupled with the mitochondrial translocation of Parkin, leading to MM cell mitophagy. Excessive mitophagy caused mitochondrial damage and dysfunction induced by lomitapide. Meanwhile, PARP14 was identified as a direct target of lomitapide by SPR-HPLC-MS, and we showed that DRP1-induced mitophagy was crucial in the anti-MM activity mediated by PARP14. Furthermore, PARP14 is overexpressed in MM patients, implying that it is a novel therapeutic target in MM. Collectively, our results demonstrate that DRP1-mediated mitophagy induced by PARP14 may be the cause for mitochondrial dysfunction and damage in response to lomitapide treatment.

CLPs-miR-103a-2-5p inhibits proliferation and promotes cell apoptosis in AML cells by targeting LILRB3 and Nrf2/HO-1 axis, regulating CD8 + T cell response.

BACKGROUND: LILRB3, a member of the leukocyte immunoglobulin-like receptor B (LILRB) family, has immunosuppressive functions and directly regulates cancer development, which indicates that LILRB3 is an attractive target for cancer diagnosis and therapy. Novel therapeutic treatments for acute myeloid leukemia (AML) are urgent and important, and RNA therapeutics including microRNAs (miRNAs) could be an effective option. Here, we investigate the role of dysregulated miRNA targeting LILRB3 in the AML microenvironment. METHODS: Potential miRNAs binding to the 3'-untranslated region (3'-UTR) of the LILRB3 mRNA were predicted by bioinformatics websites. Then, we screened miRNAs targeting LILRB3 by quantitative real-time PCR, and the dual luciferase reporter assay. The expression of LILRB3 and microRNA (miR)-103a-2-5p in AML were determined and then their interactions were also analyzed. In vitro, the effects of miR-103a-2-5p were determined by CCK8, colony formation assay, and transwell assay, while cell apoptosis and cell cycle were analyzed by flow cytometry. Cationic liposomes (CLPs) were used for the delivery of miR-103a-2-5p in the AML mouse model, which was to validate the potential roles of miR-103a-2-5p in vivo. RESULTS: LILRB3 was upregulated in AML cells while miR-103a-2-5p was dramatically downregulated. Thus, a negative correlation was found between them. MiR-103a-2-5p directly targeted LILRB3 in AML cells. Overexpressed miR-103a-2-5p significantly suppressed the mRNA and protein levels of LILRB3, thereby inhibiting AML cell growth and reducing CD8 + T cell apoptosis. In addition, overexpressed miR-103a-2-5p reduced both the relative expression of Nrf2/HO-1 pathway-related proteins and the ratio of GSH/ROS, leading to the excessive intracellular ROS that may promote AML cell apoptosis. In the mouse model, the delivery of miR-103a-2-5p through CLPs could inhibit tumor growth. CONCLUSIONS: MiR-103a-2-5p serves as a tumor suppressor that could inhibit AML cell proliferation and promote their apoptosis by downregulating LILRB3 expression, suppressing the Nrf2/HO-1 axis, and reducing the ratio of GSH/ROS. Besides, our findings indicate that miR-103a-2-5p may enhance the CD8 + T cell response by inhibiting LILRB3 expression. Therefore, the delivery of miR-103a-2-5p through CLPs could be useful for the treatment of AML.

A Hierarchical Prediction Method for Pedestrian Head Injury in Intelligent Vehicle with Combined Active and Passive Safety System.

With the development of intelligent vehicle technology, the probability of road traffic accidents occurring has been effectively reduced to a certain extent. However, there is still insufficient research on head injuries in human vehicle collisions, making it impossible to effectively predict pedestrian head injuries in accidents. To study the efficacy of a combined active and passive safety system on pedestrian head protection through the combined effect of the exterior airbag and the braking control systems of an intelligent vehicle, a "vehicle-pedestrian" interaction system is constructed in this study and is verified by real collision cases. On this basis, a combined active and passive system database is developed to analyze the cross-influence of the engine hood airbag and the vehicle braking curve parameters on pedestrian HIC (head injury criterion). Meanwhile, a hierarchy design strategy for a combined active and passive system is proposed, and a rapid prediction of HIC is achieved via the establishment of a fitting equation for each grading. The results show that the exterior airbag can effectively protect the pedestrian's head, prevent the collision between the pedestrian's head and the vehicle front structure, and reduce the HIC. The braking parameter H2 is significantly correlated with head injury, and when H2 is less than 1.8, the HIC value is less than 1000 in nearly 90% of cases. The hierarchy design strategy and HIC prediction method of the combined active and passive system proposed in this paper can provide a theoretical basis for rapid selection and parameter design.

Interception of Transient Allyl Radicals with Low-Valent Allylpalladium Chemistry: Tandem Pd(0/II/I)-Pd(0/II/I/II) Cycles in Photoredox/Pd Dual-Catalytic Enantioselective C(sp3)-C(sp3) Homocoupling.

We present comprehensive computational and experimental studies on the mechanism of an asymmetric photoredox/Pd dual-catalytic reductive C(sp3)-C(sp3) homocoupling of allylic electrophiles. In stark contrast to the canonical assumption that photoredox promotes bond formation via facile reductive elimination from high-valent metal-organic species, our computational analysis revealed an intriguing low-valent allylpalladium pathway that features tandem operation of Pd(0/II/I)-Pd(0/II/I/II) cycles. Specifically, we propose that (i) the photoredox/Pd system enables the in situ generation of allyl radicals from low-valent Pd(I)-allyl species, and (ii) effective interception of the fleeting allyl radical by the chiral Pd(I)-allyl species results in the formation of an enantioenriched product. Notably, the cooperation of the two pathways highlights the bifunctional role of Pd(I)-allyl species in the generation and interception of transient allyl radicals. Moreover, the mechanism implies divergent substrate-activation modes in this homocoupling reaction, suggesting a theoretical possibility for cross-coupling. Combined, the current study offers a novel mechanistic hypothesis for photoredox/Pd dual catalysis and highlights the use of low-valent allylpalladium as a means to efficiently intercept radicals for selective asymmetric bond constructions.

A high altitude respiration and SpO2 dataset for assessing the human response to hypoxia.

This report presents the Harespod dataset, an open dataset for high altitude hypoxia research, which includes respiration and SpO2 data. The dataset was collected from 15 college students aged 23-31 in a hypobaric oxygen chamber, during simulated altitude changes and induced hypoxia. Real-time physiological data, such as oxygen saturation waveforms, oxygen saturation, respiratory waveforms, heart rate, and pulse rate, were obtained at 100 Hz. Approximately 12 hours of valid data were collected from all participants. Researchers can easily identify the altitude corresponding to physiological signals based on their inherent patterns. Time markers were also recorded during altitude changes to facilitate realistic annotation of physiological signals and analysis of time-difference-of-arrival between various physiological signals for the same altitude change event. In high altitude scenarios, this dataset can be used to enhance the detection of human hypoxia states, predict respiratory waveforms, and develop related hardware devices. It will serve as a valuable and standardized resource for researchers in the field of high altitude hypoxia research, enabling comprehensive analysis and comparison.

Catalytic Asymmetric Synthesis of Atropisomers Bearing Multiple Chiral Elements: An Emerging Field.

With the rapid development of asymmetric catalysis, the demand for the enantioselective synthesis of complex and diverse molecules with different chiral elements is increasing. Owing to the unique features of atropisomerism, the catalytic asymmetric synthesis of atropisomers has attracted a considerable interest from the chemical science community. In particular, introducing additional chiral elements, such as carbon centered chirality, heteroatomic chirality, planar chirality, and helical chirality, into atropisomers provides an opportunity to incorporate new properties into axially chiral compounds, thus expanding the potential applications of atropisomers. Thus, it is important to perform catalytic asymmetric transformations to synthesize atropisomers bearing multiple chiral elements. In spite of challenges in such transformations, in recent years, chemists have devised powerful strategies under asymmetric organocatalysis or metal catalysis, synthesizing a wide range of enantioenriched atropisomers bearing multiple chiral elements. Therefore, the catalytic asymmetric synthesis of atropisomers bearing multiple chiral elements has become an emerging field. This review summarizes the rapid progress in this field and indicates challenges, thereby promoting this field to a new horizon.

Study on High-Velocity Impact Perforation Performance of CFRP Laminates for Rail Vehicles: Experiment and Simulation.

To study the perforation performance of CFRP laminates for rail vehicles under high-velocity impact from foreign objects, impact tests on CFRP laminates at a velocity of 163 m/s were carried out, and a corresponding finite element model was established using ABAQUS and verified. The user-defined material subroutine combined the material strain rate hardening effect and the 3D-Hashin damage criterion. The effects of impact velocity, impact object shape, and oblique angle on the perforation performance of CFRP laminates are discussed. Results show that impact velocity positively correlates with impact peak force and residual velocity. Laminates can be perforated by projectiles with a velocity above 120 m/s, and impact velocity greatly influences delamination below 140 m/s. Three shapes of projectile impacting laminates are considered: spherical, cylindrical, and conical. The conical projectile penetrates the laminate most easily, with the largest delamination area. The cylindrical projectile with a flat end suffers the most resistance, and the delaminated area is between the impact conditions of the conical and spherical projectiles. Increasing the angle of inclination increases the impacted area of the laminate and the extent of damage, thus dissipating more energy. The projectile fails to penetrate the laminate when the oblique angle reaches 60°. CFRP composite structures penetrated by high-speed impacts pose a significant threat to the safety of train operations, providing an opportunity for the application of bio-inspired composite structures.