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Abstract Coherent dispersive wave emission, as an important phenomenon of soliton dynamics, manifests itself in multiple platforms of nonlinear optics from fibre waveguides to integrated photonics. Limited by its resonance nature, efficient generation of coherent dispersive wave with ultra-broad bandwidth has, however, proved difficult to realize. Here, we unveil a new regime of soliton dynamics in which the dispersive wave emission process strongly couples with the splitting dynamics of the driving pulse. High-order dispersion and self-steepening effects, accumulated over soliton self-compression, break the system symmetry, giving rise to high-efficiency generation of coherent dispersive wave in the ultraviolet region. Simultaneously, asymmetric soliton splitting results in the appearance of a temporally-delayed ultrashort pulse with high intensity, overlapping and copropagating with the dispersive wave pulse. Intense cross-phase modulations lead to octave-wide broadening of the dispersive wave spectrum, covering 200–400 nm wavelengths. The highly-coherent, octave-wide ultraviolet spectrum, generated from the simple capillary fibre set-up, is in great demand for time-resolved spectroscopy, ultrafast electron microscopy and frequency metrology applications, and the critical role of the secondary pulse in this process reveals some new opportunities for all-optical control of versatile soliton dynamics.

Abstract Background Monitoring hand hygiene compliance (HHC) of healthcare providers (HCPs) in healthcare facilities is critical for hand hygiene (HH) promotion. However, less is known about the cost and effectiveness of different HHC monitoring tools. In this study, we aimed to compare various health economic indicators corresponding to electronic system-based monitoring (ESM) and manual paper-based monitoring (MPM) for HHC to provide evidence-based advice for HHC monitoring measures targeted selecting. Methods A before and after study in 40 clinical departments with 4,524 healthcare providers was conducted from December 2022 to January 2023 (MPM implementation phase) and March 2023 to May 2023 (ESM implementation phase). The cost-effectiveness, cost-efficiency, the extent of the Hawthorne effect, and indirect cost-benefit of the two monitoring methods were compared. Results The total cost spent on ESM for the 40 departments (17,702.92 CNY) was 4,123.76 CNY lower than that of MPM (21,826.68 CNY). The HHC of MPM (80.16%) was higher than that of ESM (69.82%) (p

Abstract Background Past research has focused on the analysis of the association between sugar-sweetened beverages consumption and screen time, respectively, and an indicator of physical fitness in adolescents. However, no studies have analyzed the interaction between sugar-sweetened beverage consumption and screen time on physical fitness index. Methods Demographic information, lifestyle, sugar-sweetened beverage consumption and screen time were investigated and physical fitness indicators were tested in 8136 adolescents aged 13–18 years from six geographic regions of China using stage-stratified whole population sampling. The chi-square test and one-way ANOVA were used to compare the covariates. The Kruskal-Wallis test was used to compare physical fitness index between different sugar-sweetened beverage consumption and screen time groups. Generalized linear model ordered logistic regression analysis was used to analyze the interaction between sugar-sweetened beverage consumption and ST on physical fitness index. Results The differences in physical fitness index among different sugar-sweetened beverage consumers in child adolescents were all statistically significant in boys, girls, and in total (H-value of 72.415, 16.859, and 78.544, P 120 min/d (OR = 2.27, 95% CI:1.78, 2.89) had the the highest risk of reduced physical fitness index (P

The pyrolysis behavior of biomass is critical for industrial process design, yet the complexity of pyrolysis models makes this task challenging. This paper introduces an innovative hybrid model to quantify the pyrolysis potential of pine needles, predicting the entire process of their pyrolysis behavior. Through experimental analyses and kinetic parameter calculations of pine needle pyrolysis, the study employs a kinetic model with a chemical reaction mechanism. Additionally, it introduces an improved dung beetle optimization algorithm to accurately capture the primary trends in pine needle pyrolysis. The developed artificial neural network model incorporates meta-heuristic algorithms to address process error factors. Validation is based on experimental data from TG at three different heating rates. The results demonstrate that the hybrid model exhibits strong predictive performance compared to the standalone model, with coefficients of determination (R²) of 0.9999 and 0.999 for predicting the conversion degree and conversion rate of untrained data, respectively. Additionally, the standard errors of prediction (SEP) are 0.249% and 0.449% for predicting the conversion degree and conversion rate of untrained data, respectively.

Abstract Background Ice and snow sports, which are inherently high risk due to their physically demanding nature, pose significant challenges in terms of participant safety. These activities increase the likelihood of injuries, largely due to reduced bodily agility and responsiveness in cold, often unpredictable winter environments. The critical need for effective injury prevention in these sports is emphasized by the considerable impact injuries have on the health of participants, alongside the economic and social costs associated with medical and rehabilitative care. In the context of ice and snow sports environments, applying the E principles of injury prevention to evaluate intervention measures can guide the implementation of future sports safety and other health promotion intervention measures in this field. When well executed, this approach can substantially reduce both the frequency and severity of injuries, thereby significantly enhancing the safety and long-term viability of these challenging sports. Objective The objective of this study was to rigorously assess and statistically substantiate the efficacy of diverse injury prevention strategies in ice and snow sports, aiming to bolster future safety measures with solid empirical evidence. Design Systematic review and meta-analysis. Methods The overarching aim of this research was to meticulously aggregate and scrutinize a broad spectrum of scholarly literature, focusing on the quantifiable efficacy of diverse, multicomponent intervention strategies in mitigating the incidence of injuries within the realm of ice and snow sports. This endeavour entailed an exhaustive extraction of data from esteemed academic databases, encompassing publications up to September 30, 2023. In pursuit of methodological excellence and analytical rigor, the study employed advanced bias assessment methodologies, notably the AMSTAR 2 and GRADE approaches, alongside sophisticated random-effects statistical modelling. This comprehensive approach was designed to ensure the utmost validity, reliability, and scholarly integrity of the study’s findings. Results Fifteen papers, including 9 randomized controlled trials, 3 case‒control studies, and 3 cohort studies with 26,123 participants and 4,382 injuries, were analysed. The findings showed a significant reduction in injury rates through various interventions: overall injury prevention (RR = 0.50, 95% CI 0.42–0.63), educational training (RR = 0.50, 95% CI 0.34–0.73), educational videos (RR = 0.53, 95% CI 0.34–0.81), protective equipment (RR = 0.64, 95% CI 0.46–0.87), and policy changes (RR = 0.28, 95% CI 0.16–0.49). Subgroup analysis revealed potential heterogeneity in compliance (p = 0.347). Compared to controls, multicomponent interventions effectively reduced injury rates. Conclusion This systematic review and meta-analysis demonstrated that multicomponent interventions significantly prevent injuries in ice and snow sports. By applying the E principles of injury prevention and constructing a framework for practical injury prevention research in ice and snow sports, we can gradually shift towards a systemic paradigm for a better understanding of the development and prevention of sports injuries. Moreover, sports injury prevention is a complex and dynamic process. Therefore, high-quality experiments in different scenarios are needed in future research to provide more reliable evidence, offer valuable and relevant prevention information for practitioners and participants, and help formulate more effective preventive measures in practice.

We demonstrate that by using a cascaded configuration of five solid-core photonic crystal fiber (PCF) samples with progressively decreasing core diameters, ultraviolet light with wavelengths as short as ∼300 nm can be generated in a supercontinuum (SC) set-up. With a nanosecond laser as the pump light, the modulation instability effect leads to the generation of multiple optical solitons in the first PCF sample which has a close-to-zero dispersion value at the pump wavelength (∼1064 nm). The following PCF samples with decreasing core diameters enhance the waveguide nonlinearity, and at the same time provide continuously-shorter phase-matching wavelengths for dispersive-wave emission, thereby pushing the short-wavelength edge of the SC spectrum into the deep ultraviolet spectral region. While the PCF splicing technique ensures the compactness of this SC set-up, the generated SC spectrum, spanning ∼350 nm to ∼2000 nm with a flat spectral profile, may be applied in fluorescence microscopy and biochemical imaging.

Brillouin fiber laser with the non-resonance pumping configuration, has compact set-up, good wavelength tunability and high-power single-frequency-emission capability, being regarded as an important technique for highly-coherent light generation. Such Brillouin fiber lasers, using single-mode fiber (SMF) as the Brillouin gain medium, generally have high lasing thresholds and mode-hopping instabilities, resulting from the relatively-low Brillouin gain coefficient of the conventional SMF. Here, we report a compact, non-resonance-pumping Brillouin photonic crystal fiber laser that can generate kHz-level-linewidth single-frequency lasing with tens-of-mW lasing threshold. Mode-hopping instability of this laser is largely suppressed thanks to the short (∼20 m) cavity length, which gives rise to a free-spectral-range (FSR) value of ∼10 MHz properly matching the tens-of-MHz Brillouin gain bandwidth. Experimental results of both self-heterodyne and frequency-noise measurements indicate a laser linewidth of ∼1.4 kHz, corresponding to high linewidth-narrowing ratio of ∼18. No lasing line of high-order Stokes was observed in experiments as the laser pump power was gradually increased to ∼200 mW, giving a nearly-linear lasing slope.

An improved YOLOv8 detection method is proposed for detecting distracted driving behavior and driver’s emotion. Unlike the commonly used YOLOv8 method, an attention mechanism named MHSA and a CNN module are synthesized to ensure improved performance in terms of accuracy and convergence, where MHSA is used to detect distracted driving behavior and CNN is used to detect driver’s emotion. The FER2013 dataset and collected dataset are used to train the improved YOLOv8. The training results show that the proposed YOLOv8 demonstrates improved performance compared with the commonly used YOLO based methods. Finally, the validity of the proposed YOLOv8 method is illustrated through implementations in Jetson Nano platform, where the TensorRT and DeepStream methods in the Jetson Nano device are used to optimize the volume and operational speed of the proposed YOLOv8 method, respectively. Test results show that the proposed YOLOv8 method can yield better real-time and accuracy properties.

Cubic press is the primary equipment for diamond production in China. Its key component, the hinge beam, bears continuous alternating loads in the working environment and is prone to failure and breakage. In this paper, a method combining response surface method (RSM) and multi-objective genetic algorithms (MOGA) is proposed to optimize the hinge beam of the new hexagon top press. Firstly, a parametric model of the hinge beam is established. The dimensions of key parts are treated as design parameters, while the maximum stress and displacement serve as objective functions. There is also a constraint on the maximum mass. Then, the optimal space-filling design (OSF) is used as the design of experiments (DOE) to obtain the design experimental points. The proxy model is obtained by the response surface method. Afterward, the global optimum solution is searched using the MOGA method, and the optimal result of the hinge beam is evaluated. The results show that the optimized hinge beam effectively improves stiffness and strength with a slight increase in weight. Stress concentration is also significantly reduced, providing a valuable reference for the design and development of the press.

Laser assistance and the use of a diamond tool with a negative rake angle are promising methods for machining hard and brittle materials. In this paper, a cutting force model and a smoothed particle hydrodynamics (SPH) model were constructed to investigate the ductile removal mechanism of fused silica. Subsequently, in-situ laser assisted diamond cutting (LADC) experiments were performed to demonstrate the critical depth of cut (DOC), cutting force, and surface quality. As expected, the developed theoretical model demonstrated satisfactory accuracy in predicting the cutting force, with an error rate confined to 12%. Results indicated that the ductile machinability was enhanced with laser assistance due to a decrease in hardness, and the initiation of brittle fracture was reduced by high hydrostatic compressive stress when using a tool with a negative rake angle. A smooth and homogenous surface of fused silica with a surface roughness (Sa) of 13.8 nm was achieved for the application of a diamond tool with a rake angle of −65°.

Abstract Background Mechanical forces have an important role in the initiation and progression of orthopedic surgical incisions complications. To avoid incision complications with the reduction of dermal tension, surgeons may choose a buried continuous suture technique other than the traditional interrupted vertical mattress suture. Absorbable barbed sutures are widely used in orthopedics due to their convenience and reducing wound tension. The aim of this research is to compare and explain the advantages of running subcuticular suturing technique with absorbable barbed sutures for orthopedic surgical incisions closure. Methods Finite element models of layered skin and two different suture techniques, running subcuticular suture and intradermal buried vertical mattress suture, ware constructed. The mechanical property difference between standard sutures and barbed sutures was modelled using different contact friction coefficient. Pulling the skin wound was simulated, and the sutures’ pressure on the skin tissue was determined. Results Compared with traditional smooth sutures, the barbed sutures effectively increased the contact force for subepidermal layers, which led the less force variation between different layers. The results also suggested that subcuticular suture caused less stress concentration compared with intradermal buried vertical mattress suture. Conclusions In conclusion, our study indicated that running subcuticular suturing technique with absorbable barbed sutures for orthopedic surgical incisions closure results in more uniform stress distribution in the dermis. We recommend this combination as the preferred method of skin closure in orthopedic surgery unless contraindicated.

Chromosomal karyotype is important to determine whether a newborn has a genetic disorder. There are two main categories of chromosomal abnormalities: structural abnormalities, in which the chromosome structure is altered, and chromosome number abnormalities. Manual karyotyping is complex and takes a lot of time because it requires a high degree of domain expertise. Based on this investigation, we propose a new method of chromosome defect detection based on deep learning with 20,299 chromosome images from Dongguan Kanghua Hospital as data that integrates the diversity of chromosome features and trains a classifier model based on feature fusion for chromosome abnormality detection. We put forward a feature fusion classifier with dynamic weights (FFCDW) for chromosomal abnormality detection, after data augmentation with three deep learning networks, ResNet, SENet, and VGG19, the three trained models are combined using a dynamic weighting approach. Experiments prove the FFCDW method outperforms these mainstream models of ResNet, SENet, and VGG19. The proposed method based on FFCDW achieves a precision of 0.8902 and an F1-score of 0.8805 with a small standard deviation (0.00903 and 0.00892, respectively). In addition, the algorithm can automatically assign weights based on the results of a single model, and the strategy with dynamic weights outperforms the strategy with fixed weights in the proposed feature fusion classifier.

Neuroinflammation is the common pathological feature of neuropsychiatric diseases. Chrysin, a kind of natural flavonoid compound, was reported to exert antidepressant effects, however the direct targets of chrysin remain unclear. Currently studies showed chrysin alleviated CUMS-induced depressive-like behaviors in mice. We found chrysin inhibited CUMS-induced microglia activation in mice. We further found that chrysin inhibited the activation of Fyn and NF-κB pathway, and decreased the expression of iNOS, COX2 and NLRP3. Furthermore, our data showed that chrysin can bind to Fyn using pull-down assay. Transfection siRNA-Fyn abolished the inhibitory effect of chrysin on activation of NF-κB pathway. This study revealed that targeting inhibition of Fyn by chrysin to alleviate CUMS-induced neuroinflammation and depressive-like behaviors via inhibiting the expression of iNOS, COX2 and NLRP3 mediated by inhibition of NF-κB pathway. Thus, this study has revealed, for the first time, Fyn was the direct target of chrysin against neuroinflammation and neuroinflammation-related depression.

Abnormal tool wear is a significant problem encountered in machining. MoS2 has the function of friction reduction; thus, to mitigate friction, two Ni-based coatings, Ni60 and Ni60 + 15 wt.% Ni/MoS2, were obtained on tungsten steel using supersonic plasma technology. The microstructure, phase structure, microhardness, fatigue properties, and friction and wear properties of the two coatings were characterized. The results show that the two plasma-sprayed Ni-based coatings have desirable structures. The addition of Ni-coated MoS2 can effectively improve the hardness of the coatings, with values reaching as high as 735 HV. The speed of rotation of the friction ball was set as 200 r/min, and the cutting force was 201.6 N. The fatigue performance as well as the friction and wear performance of the coating are simulated using ANSYS. The fatigue performance is improved by 12.6 % after adding 15 wt.% Ni/MoS2, and the friction system of the coating becomes stable after 25 min of contact. The addition of 15 wt.% Ni/MoS2 can effectively improve the performance of the tool material.

Introduction: Tracing the genetic causes for male infertility due to asthenoteratozoospermia has revealed at least 40 causative genes, which provides valuable reference for the genetic testing of asthenoteratozoospermia in clinical practice. To identify deleterious variants in the human tetratricopeptide repeat domain 12 (TTC12) gene in a large cohort of infertile Chinese males with asthenoteratozoospermia.Methods: A total of 314 unrelated asthenoteratozoospermia-affected men were recruited for whole exome sequencing. The effects of the identified variants were evaluated by in silico analysis, and confirmed by in vitro experiments. Intracytoplasmic sperm injection (ICSI) was used to evaluate the efficiency of assisted reproduction technique therapy.Results and Discussion: Novel homozygous TTC12 variants (c.1467_1467delG (p.Asp490Thrfs*14), c.1139_1139delA (p.His380Profs*4), and c.1117G>A (p.Gly373Arg)) were identified in three (0.96%) of the 314 cases. Three mutants were indicated to be damaging using in silico prediction tools, and were further confirmed by in vitro functional analysis. Hematoxylin and eosin staining and ultrastructural observation of the spermatozoa revealed multiple morphological abnormalities of flagella, with the absence of outer and inner dynein arms. Notably, significant mitochondrial sheath malformations were also observed in the sperm flagella. Immunostaining assays indicated that TTC12 is present throughout the flagella, and was strongly concentrated in the mid-piece in control spermatozoa. However, spermatozoa from TTC12-mutated individuals exhibited almost no staining intensity of TTC12 and outer and inner dynein arms components. The three men accepted ICSI treatment using their ejaculated spermatozoa, and two female partners successfully delivered healthy babies. Our findings provide direct genetic evidence that homozygous variants in TTC12 cause male infertility with asthenoteratozoospermia by causing dynein arm complex defects and mitochondrial sheath malformations in the flagellar. We also demonstrated that TTC12 deficiency-mediated infertility could be overcome by ICSI technology.

Microglia are the only resident innate immune cells derived from the mesoderm in the nerve tissue. They play a role in the development and maturation of the central nervous system (CNS). Microglia mediate the repair of CNS injury and participate in endogenous immune response induced by various diseases by exerting neuroprotective or neurotoxic effects. Traditionally, microglia are considered to be in a resting state, the M0 type, under physiological conditions. In this state, they perform immune surveillance by constantly monitoring pathological responses in the CNS. In the pathological state, microglia undergo a series of morphological and functional changes from the M0 state and eventually polarize into classically activated microglia (M1) and alternatively activated microglia (M2). M1 microglia release inflammatory factors and toxic substances to inhibit pathogens, while M2 microglia exert neuroprotective effects by promoting nerve repair and regeneration. However, in recent years, the view regarding M1/M2 polarization of microglia has gradually changed. According to some researchers, the phenomenon of microglia polarization is not yet confirmed. The M1/M2 polarization term is used for a simplified description of its phenotype and function. Other researchers believe that the microglia polarization process is rich and diverse, and consequently, the classification method of M1/M2 has limitations. This conflict hinders the academic community from establishing more meaningful microglia polarization pathways and terms, and therefore, a careful revision of the concept of microglia polarization is required. The present article briefly reviews the current consensus and controversy regarding microglial polarization typing to provide supporting materials for a more objective understanding of the functional phenotype of microglia.

Abstract Background Relapsed childhood polymicrobial osteomyelitis associated with dermatophytosis has not been reported in the literature. Case presentation Here we report on a case of a 45-year-old man who had left tibial osteomyelitis for 29 years, accompanied by skin fungal infection of the ipsilateral heel for 20 years, and underwent a second operation due to recurrence of polymicrobial infection 6 years ago. The patient had a history of injury from a rusty object, which penetrated the anterior skin of the left tibia middle segment causing subsequent bone infection, but was asymptomatic after receiving treatments in 1983. The patient was physically normal until dermatophytosis occurred on the ipsilateral heel skin in 1998. The patient complained that the dermatophytosis was gradually getting worse, and the tibial wound site became itchy, red, and swollen. The left tibial infection resurged in May 2012, leading to the patient receiving debridement and antibiotic treatment. H&E and Gram-stained histology was performed on biopsy specimens of sequestrum and surrounding inflammatory tissue. Tissue culture and microbiology examination confirmed polymicrobial infection with Staphylococcus aureus (S. aureus) and Corynebacterium and a fungus. Additionally, the patient also received potassium permanganate for dermatophytosis when he was admitted into the hospital. Conclusions Together with longitudinal follow-up of medical history, surgical findings, histopathological and microbiology culture evidence, we conclude that boyhood tibia polymicrobial osteomyelitis with S. aureus and Corynebacterium occurred in this patient, and the fungal activation of dermatophytosis may have led to osteomyelitis relapse.

In recent years, carbon nanotubes(CNTs) have begun to attract attention in the fields of field emission, nanoelectronic devices, nano machines and composite reinforced materials. But the traditional processing methods for cutting these increase tool wear. However, non-traditional processing can be used to machine materials of any hardness and strength. In this paper, the research trends of non-traditional processing of CNTs are critically reviewed. First, this study introduces the application of CNTs and their development history. Second, the surface morphology, purification and growth effects of laser-processed CNTs are summarised, these are analysed and discussed. Subsequently, the effects of ultrasonic parameters and other external parameters on the diormance of ultrasonically processed CNTs are analysed. Next, the effects of electrical and non-electrical parameters on the surface morphology of CNTs processed by micro-electro-discharge machining(μEDM) are compared, and a summary analysis is presented. In addition, the research on the improvement of the performance of CNTs by electrochemical machining(ECM) is reviewed and prospected. Simultaneously, different non-traditional processing of CNTs is discussed. Finally, the most recent progress in non-traditional processing of CNTs is described, and the future trends, which may potentially guide subsequent research studies, are predicted.

In recent years, with the rapid development of artificial intelligence, machine vision technology has been widely used in various fields. Traditional cancer detection methods are time-consuming, labor-intensive, and highly dependent on the experience of pathologists; therefore, these methods cannot meet the needs of modern medical treatment. Machine vision overcomes the disadvantages of traditional detection methods in cancer detection and can help pathologists improve the detection accuracy. According to the requirements of medical detection, this review summarizes the applications of machine vision in the detection of cancer cells in histopathological images and analyzes the advantages and disadvantages of existing methods in image preprocessing, segmentation, feature extraction and recognition. Finally, research on the detection methods of histopathological cancer cells is reviewed and prospected, and future development trends are predicted to provide guidance for follow-up research.

The present study envisaged the preparation of four kinds of coatings on 45# steel substrate by using the Supersonic plasma spraying (SPS) technology. The structure and morphology of the four coatings were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM), and the hardness, wear resistance and corrosion resistance of the coatings were studied. The results show that there was an increase in the ceramic particles. The wear resistance and corrosion performance of the coatings was improved to some extent. The hardness of N6WA decreased with an increase in the coating distance, but it showed good wear resistance. The wear mechanism was found to involve mainly the abrasive wear. A series of electrochemical tests were carried out in 3.5 wt.% NaCl solution, and the corrosion behavior and corrosion resistance mechanism were studied.

Purpose: The study aimed to report a rare case of a patient with Alport syndrome, which was manifested as unilateral non-infectious uveitis after bilateral cataract surgery.Methods: A case report.Results: A 2-year-old boy was diagnosed with unilateral panuveitis based on the clinical and multimodal imaging findings. Intraocular fluid samples for metagenomic next-generation sequencing (mNGS) and microbial culture were negative. However, urine tests found proteinuria and microscopic hematuria. Pathologic findings of the kidney revealed a thickened membrane, and a diagnosis of Alport syndrome was considered. Gene analysis found deletions in exon 1 of COL4A5 and exons 1 and 2 of COL4A6. The uveitis resolved gradually, following the administration of oral steroids.Conclusion: Uveitis may be an ocular manifestation of Alport syndrome.

Accurately and efficiently predicting the fuel consumption of vehicles is the key to improving their fuel economy. This paper provides a comprehensive review of data-driven fuel consumption prediction models. Firstly, by classifying and summarizing relevant data that affect fuel consumption, it was pointed out that commonly used data currently involve three aspects: vehicle performance, driving behavior, and driving environment. Then, from the model structure, the predictive energy and the characteristics of the traditional machine learning model (support vector machine, random forest), the neural network model (artificial neural network and deep neural network), and this paper point out that: (1) the prediction model of fuel consumption based on neural networks has a higher data processing ability, higher training speed, and stable prediction ability; (2) by combining the advantages of different models to build a hybrid model for fuel consumption prediction, the prediction accuracy of fuel consumption can be greatly improved; (3) when comparing the relevant indicts, both the neural network method and the hybrid model consistently exhibit a coefficient of determination above 0.90 and a root mean square error below 0.40. Finally, the summary and prospect analysis are given based on various models’ predictive performance and application status.

In order to improve the prefabrication level of highway mountain tunnels, improve the quality of the project, and shorten the construction period, a new type of prefabricated concrete curb member was developed based on an actual project. The production process, construction technical points, and on-site assembly technology are discussed. In addition, a method to calculate the anti-collision performance of the curb components is proposed, that is, the collision force of 850 kN was calculated by the pseudo-static method, and then finite element simulation analysis was used to obtain the stress of the concrete structure and reinforcement. The results show that the reinforcement will not fail, which will ensure the curb component will not undergo brittle fracture. This study provides a reference to improve the prefabrication level of highway tunnels.

Purpose: Expanded carrier screening (ECS) is an effective method to identify at-risk couples (ARCs) and avoid birth defects. This study aimed to reveal the carrier spectrum in the Chinese population and to delineate an expanded carrier gene panel suitable in China.Methods: Medical exome sequencing (MES), including 4,158 disease-causing genes, was offered to couples at two reproductive centers. It was initially used as a diagnostic yield for potential patients and then used for ECS. Clinical information and ECS results were retrospectively collected.Results: A total of 2,234 couples, representing 4,468 individuals, underwent MES. In total, 254 individuals showed genetic disease symptoms, and 56 of them were diagnosed with genetic diseases by MES. Overall, 94.5% of them were carriers of at least one disease-causing variant. The most prevalent genes were GJB2 for autosomal recessive disorders and G6PD for X-linked diseases. The ARC rate was 9.80%, and couples were inclined to undergo preimplantation genetic testing when diseases were classified as “profound” or “severe.”Conclusion: This study provided insight to establish a suitable ECS gene panel for the Chinese population. Disease severity significantly influenced reproductive decision-making. The results highlighted the importance of conducting ECS for couples before undergoing assisted reproductive technology.

Neural attention-based encoders, which effectively attend sentence tokens to their associated context without being restricted by long-term distance or dependency, have demonstrated outstanding performance in embedding sentences into meaningful representations (embeddings). The Universal Sentence Encoder (USE) is one of the most well-recognized deep neural network (DNN) based solutions, which is facilitated with an attention-driven transformer architecture and has been pre-trained on a large number of sentences from the Internet. Besides the fact that USE has been widely used in many downstream applications, including information retrieval (IR), interpreting its complicated internal working mechanism remains challenging. In this work, we present a visual analytics solution towards addressing this challenge. Specifically, focused on semantics and syntactics (concepts and relations) that are critical to domain clinical IR, we designed and developed a visual analytics system, i.e., USEVis. The system investigates the power of USE in effectively extracting sentences’ semantics and syntactics through exploring and interpreting how linguistic properties are captured by attentions. Furthermore, by thoroughly examining and comparing the inherent patterns of these attentions, we are able to exploit attentions to retrieve sentences/documents that have similar semantics or are closely related to a given clinical problem in IR. By collaborating with domain experts, we demonstrate use cases with inspiring findings to validate the contribution of our work and the effectiveness of our system.

On-demand synthesis and dissociation of soliton molecules are controlled to occur simultaneously in massively parallel trapping potentials in an optomechanical lattice, unfolding the stochastic multi-soliton dynamics and enabling statistical insights.

Abstract In this paper, molecular dynamics simulations are carried out to investigate the cutting mechanism during the hybrid machining process combined the thermal and vibration assistants. A modified cutting model is applied to study the material removal behavior and subsurface damage formation in one vibration cycle. The results indicate that during the hybrid machining process, the dominant material removal mechanism could transform from extrusion to shearing in a single vibration cycle. With an increase of the cutting temperature, the generation and propagation of cracks are effectively suppressed while the swelling appears when the dominant material removal mechanism becomes shearing. The formation mechanism of the subsurface damage in one vibration cycle can be distinct according to the stress distribution. Moreover, the generation of the vacancies in workpiece becomes apparent with increasing temperature, which is an important phenomenon in hybrid machining process.

As UAV technology has been leaping forward, small consumer-grade UAVs equipped with optical sensors are capable of easily acquiring high-resolution images, which show bright prospects in a wide variety of terrains and different fields. First, the crater rim landscape of the Dinosaur Valley ring formation located on the central Yunnan Plateau served as the object of the surface change detection experiment, and two repetitive UAV ground observations of the study area were performed at the same altitude of 180 m with DJI Phantom 4 RTK in the rainy season (P1) and the dry season (P2). Subsequently, the UAV-SfM digital three-dimensional (3D) modeling method was adopted to build digital models of the study area at two points in time, which comprised the Digital Surface Model (DSM), Digital Orthomosaic Model (DOM), and Dense Image Matching (DIM) point cloud. Lastly, a quantitative analysis of the surface changes at the pit edge was performed using the point-surface-body surface morphological characterization method based on the digital model. As indicated by the results, (1) the elevation detection of the corresponding check points of the two DSM periods yielded a maximum positive difference of 0.2650 m and a maximum negative value of −0.2279 m in the first period, as well as a maximum positive difference of 0.2470 m and a maximum negative value of −0.2589 m in the second period. (2) In the change detection of the two DOM periods, the vegetation was 9.99% higher in the wet season than in the dry season in terms of coverage, whereas the bare soil was 10.54% more covered than the wet season. (3) In general, the M3C2-PM distances of the P1 point cloud and the P2 point cloud were concentrated in the interval (−0.2,0.2), whereas the percentage of the interval (−0.1,0) accounted for 26.69% of all intervals. The numerical model of UAV-SfM was employed for comprehensive change detection analysis. As revealed by the result of the point elevation difference in the constant area, the technique can conform to the requirements of earth observation with certain accuracy. The change area suggested that the test area can be affected by natural conditions to a certain extent, such that the multi-source data can be integrated to conduct more comprehensive detection analysis.

Based on the raindrop spectrum data observed in Xi'an, Shaanxi Province from 2013 to 2014, and combined with the observation data of the weather radar, the mean raindrop distribution, the microphysical characteristic quantity and Z-R relationship of 43 precipitation events of the mixed convective-stratiform clouds were statistically analyzed. The results show that the mean raindrop spectrum of the precipitation display a single peak, and the fitting of the Gamma distribution to the large precipitation particles is obviously better than that of the M-P distribution. The drop size corresponding to the peak value of raindrop number concentration and having the greatest contribution to rainfall intensity appeared at less than 1 mm in diameter in the raindrop spectrum. A Z-R relationship Z=168R1.43 has been established by the least square method for the mixed convective-stratiform clouds in Xi'an area. When the echo intensity calculated from raindrop spectrum data is less than (greater than) 30 dBz, the radar observation can overestimate the echo intensity. With echo intensity decreasing, the radar echo intensity is obviously overestimated (underestimated). A 5-grade revised scheme for the radar echo is proposed. The Z-R relationship Z=168R1.43 was used to estimate the rainfall during the precipitation events of the mixed convective-stratiform clouds in Xi'an area. The estimated amount of precipitation is closer to the actually measured rainfall. The relative error of the estimated rainfall was reduced from 51.3% to 25.4%.

We propose a deep learning approach to collectively compare two or multiple ensembles, each of which is a collection of simulation outputs. The purpose of collective comparison is to help scientists understand differences between simulation models by comparing their ensemble simulation outputs. However, the collective comparison is non-trivial because the spatiotemporal distributions of ensemble simulation outputs reside in a very high dimensional space. To this end, we choose to train a deep discriminative neural network to measure the dissimilarity between two given ensembles, and to identify when and where the two ensembles are different. We also design and develop a visualization system to help users understand the collective comparison results based on the discriminative network. We demonstrate the effectiveness of our approach with two real-world applications, including the ensemble comparison of the community atmosphere model (CAM) and the rapid radiative transfer model for general circulation models (RRTMG) for climate research, and the comparison of computational fluid dynamics (CFD) ensembles with different spatial resolutions.

Ultrasonic-assisted wire–arc additive manufacturing (WAAM) can refine microstructures, enhancing performance and improving stress concentration and anisotropy. It has important application prospects in aerospace, weaponry, energy, transportation, and other frontier fields. However, the process parameters of ultrasonic treatment as an auxiliary technology in the WAAM process still have an important impact on product performance indicators, such as the amplitude of the ultrasonic tool, the distance between the points of action of the product, and the scanning speed. The number of ultrasonic impacts influences the performance indexes. Therefore, these parameters must be optimized. This paper describes the advantages and the defects of WAAM components, as well as the principle and development status of ultrasonic treatment technology. Subsequently, this paper also briefly describes how ultrasonic-assisted technology can refine the crystal and improve the mechanical properties of WAAM components. Finally, we review the influence of process parameters (such as ultrasonic amplitude, application direction, and impact times) on the product materials. In this paper, a comprehensive optimization method for ultrasonic parameters is proposed to improve the mechanical properties of WAAM components.

Driver identification is very important to realizing customized service for drivers and road traffic safety for electric vehicles and has become a research hotspot in the field of modern automobile development and intelligent transportation. This paper presents a comprehensive review of driver identification methods. The basic process of driver identification task is proposed as four steps, the advantages and disadvantages of different data sources for driver identification are analyzed, driver identification models are divided into three categories, and the characteristics and research progress of driver identification models are summarized, which can provide a reference for further research on driver identification. It is concluded that on-board sensor data in the natural driving state is objective and accurate and could be the main data source for driver identification. Emerging technologies such as big data, artificial intelligence, and the internet of things have contributed to building a deep learning hybrid model with high accuracy and robustness and representing an important gradual development trend of driver identification methods. Developing a driver identification method with high accuracy, real-time performance, and robustness is an important development goal in the future.

Weak target detection is a great challenging in radar field. To detect weak targets via radar communication integrated signal, a method for constructed step-LFM (CStep-LFM) signal is proposed based on quadrature amplitude modulation-orthogonal frequency division multiplexing (QAM-OFDM) echoes. First, a QAM-OFDM and CStep-LFM model is established, and then a bandpass filters bank is used to transform the QAM-OFDM echo into a Step-LFM signal. Finally, compared with several existing integrated signals, the analyses and the simulation results show that CStep-LFM signal not only improves the detection performance of weak targets but also has a better communication performance. [ABSTRACT FROM AUTHOR]

To prevent the possible accident of a large passenger plane due to rapid decompression, transient load analysis is of vital importance in the assessment of structure strength and also an important clause of airworthiness standard. A 0-D isentropic model and a 1-D model based on the characteristic line are developed to simulate the rapid decompression process of the cockpit-cabin model due to a cracked windshield. The accuracy of these models is presented by comparing them with experiments and 3-D CFD simulations. Then, the 1-D model is applied to study the influence of cabin and cockpit volume, windshield and decompression panel area, compartments, and environment pressure on the decompression load. The non-dimensional decompression time and the non-dimensional decompression load are developed to evaluate the decompression characteristics, and the correlation equations are established. The relative deviation between the results of the correlation equation fit and the results of the one-dimensional simulation is less than 3%. This work provides a new engineering method for structure strength design and decompression load analysis with high accuracy and low resource consumption.

Background: Empty follicle syndrome (EFS) is defined as the complete failure to retrieve oocytes after ovarian stimulation. Although several mutations in ZP1, ZP2, ZP3, and LHCGR have been identified as genetic causes of EFS, its pathogenesis is still not well-understood.Methods: Whole-exome sequencing (WES) was employed to identify the candidate pathogenic mutations, which were then verified by Sanger sequencing. A study in CHO-K1 cells was performed to analyze the effect of the mutation on protein expression. Additionally, immunohistochemistry (IHC) staining was used to examine follicular development and zona pellucida (ZP) assembly in the ovary of an EFS patient.Results: A novel heterozygous deletion in ZP3 (c.565_579del[p.Thr189_Gly193del]) was identified in the EFS patient. It was inherited dominantly and resulted in significant degradation of the ZP3 protein. Oocytes with degenerated cytoplasm and abnormal ZP assembly were observed in follicles up to the secondary stage, and many empty follicle-like structures were present.Conclusion: We identified a novel ZP3 mutation that expands the mutational spectrum associated with human EFS. We also showed the abnormal follicular development and ZP assembly of the EFS patient with the heterozygous ZP3 mutation, which provides new insights into the pathogenesis of EFS.

As the most important element in improving the service life of a mechanical system, surface coating materials are of key importance in the development of high-end equipment. To improve the comprehensive properties of the surface coating, the common core-shell structure/Ni60 coating was prepared on the surface of #45 steel by supersonic plasma spraying. The results show that the Ni60 has no layer structure, pores, cracks, and other defects on the surface of the coating. The nanohardness of the NNA(Ni60/Ni (Al) mixture powder), NNM(Ni60/Ni (MoS2) mixture powder), and NNC(Ni60/Ni (C) mixture powder) coatings is 6815 μN, 5750 μN, and 2000 μN. The results show that the wear resistance of the NNA coating is better. In the friction and wear test, the NNA coating mainly shows adhesive wear and abrasive wear, while the NNM and NNC coatings mainly show abrasive wear.

Transparent nano-ceramics have an important high-transmittance, material-integrating structure and function and a variety of potential applications, such as use in infrared windows, optical isolators, composite armors, intelligent terminal screens, and key materials of solid-state lasers. Transparent ceramics were originally developed to replace single crystals because of their low fabricating cost, controllable shape, and variable composition. Therefore, this study reviews and summarizes the development trends in transparent nano-ceramics and their potential applications. First, we review the research progress and application of laser nano-ceramic materials, focusing on the influence of controllable doping of rare earth ions on thermal conductivity and the realization of large-scale fabrication technology. Second, the latest research progress on magneto-optical transparent nano-ceramics, mainly including terbium gallium garnet (Tb3Ga5O12, TGG) ceramics and terbium aluminum garnet (Tb3Al5O12, TAG) ceramics, are summarized, and their performance is compared. Third, the research progress of transparent armor nano-ceramic materials, represented by MgAl2O3 and Aluminum oxynitride (AlON), are reviewed. Lastly, the progress in electro-optical transparent nano-ceramics and scintillation transparent nano-ceramics is reported, and the influence of the material-fabrication process on electro-optic effect or luminous intensity is compared. Moreover, the effect of particle diameter on fabrication, the relationship between nano powder and performance, and different sintering methods are discussed. In summary, this study provides a meaningful reference for low-cost and sustainable production in the future.

The metal-intermetallic laminate composite Ti/Al 3 Ti can be used as protective armor in aerospace and military applications, due to its low density, high strength, and superior impact-resistant performance. The ballistic performance of the laminate composite was studied by ballistic testing and finite element technology. The failure modes, such as radical cracks, layer delamination, and plastic deformation, have been found after the ballistic test, and the specific energy absorption was used to evaluate the ballistic capacity of the material. The finite element model of the Ti/Al 3 Ti impacted by the projectile was established by considering the interface, which was simulated by the solid elements with zero thickness. The simulation results demonstrate the failure process of the interface during penetration. The interfacial failure allowed for layer detachment with its labor layers. The simulation results agree well with that of the experiment, and the practicality and credibility of the model is verified.

Abstract Background Small supernumerary marker chromosomes (sSMCs) are common structurally abnormal chromosomes that occur in 0.288% of cases of mental retardation. Isodicentric 15 (idic(15)) is common in sSMCs and usually leads to a rare chromosome disorder with distinctive clinical phenotypes, including early central hypotonia, developmental delay, epilepsy, and autistic behavior. It was previously shown that the partial tetrasomy 15q and partial hexasomy 15q syndromes are usually caused by one and two extra idic(15), respectively. Karyotypes containing a mosaic partial octosomy 15q resulting from three extra idic(15) have rarely been reported. Case presentation Two patients with profound intellectual impairment, development delay and hyperpigmentation were recruited for this study. The phenotype was relatively more severe in patient 1 than in patient 2. Conventional cytogenetic analysis of peripheral blood obtained from patients 1 and 2 revealed rare mosaic karyotypes containing sSMCs, i.e., mos 49,XX,+mar × 3[83]/48,XX,+mar × 2[7]/46,XX[10] and mos 48,XX,+mar × 2[72]/47,XX,+mar[28], respectively. The results of analyses of copy number variation (CNV) and fluorescence in situ hybridization (FISH) analyses, showed that the sSMCs were found to be idic(15) involving the Prader-Willi/Angelman Syndrome Critical Region (PWACR) genes and the P gene, with duplication sizes of 6.3 Mb and 9.7 Mb, respectively. DNA fingerprinting analysis of patient 1 showed a maternal origin for the idic(15). Both patients had mosaic idic(15) karyotypes: patient 1 had cells with a 15q partial octosomy (83%), and patient 2 had cells with a 15q partial hexasomy (72%). Conclusions We detected two rare mosaic idic(15) karyotypes that were associated with congenital abnormalities, including a rare mosaic octosomy of 15q11-q13. Our cases further validate the notion that the phenotypic severity is correlated with the level of mosaicism and the dosage effect of related genes in the proximal 15q.

In order to deepen the understanding of rotating effects on internal cooling, the flow and heat transfer characteristics of 2-pass rotating rectangular smooth/ribbed channels are investigated by Reynolds-Averaged Navier-Stokes (RANS) simulation. Three rotating numbers (Ro = 0.10, 0.25, and 0.40) are simulated, and the maximum buoyancy parameter (Bo) reaches 5.0. The results show that the rotating buoyancy has significant effects on the flow and heat transfer under high Bo conditions. When Bo > 1.0, rotating buoyancy inducts flow separation near the leading edge (LE) in the first passage, while the air flow in the second passage shows a double-peak profile. With increased Bo, the heat transfer in the first passage is greatly increased, and the maximum growth rate occurs at Bo = 0.6~1.0. However, the heat transfer in the second passage has no obvious changes due to a strong turn effect. In the ribbed channel, rotating effects are much weaker than those in the smooth channel. This research helps to improve the understanding of the internal cooling heat transfer mechanism in land-based gas turbines under typical operating conditions.

The traditional acoustic-based diagnosis (ABD) technique based on single-channel testing has a significant engineering value. Since its diagnosis robustness is sensitive to sound signal acquisition location, it develops slowly. To solve this problem, the 2-dimensional (2D) sound field variation near the machine is adopted for diagnosis by the near-field acoustic holography (NAH)- based fault diagnosis method with array measurement. However, its performance is limited due to the neglect of the sound field normal change information. To dig the sound field fault information further, a 2.5-dimensional (2.5D) acoustic field diagnosis method is presented in this paper and its performance compared with the 2D technology is verified by the bearing diagnostic test. Different from the 2D technique with only one source image, the 2.5D acoustic field model consists of source image, holographic sound image, and the differences between them, and its effective feature model is constructed by Gabor wavelet feature extraction and random forest feature reduction algorithm. The diagnostic effect of the 2.5D technique compared with the 2D technique increases more than 11% in the bearing diagnostic test. It provides new ideas for the development of the NAH-based fault diagnosis method, and further improves the ABD technique-based array measurement.