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The study on the absorber of flexural waves based on time-domine model coupling theory is not applicable to all models，and has complex design process，which is difficult for widespread application in industrial engineering. Therefore，a research method for elastic absorbers based on the acoustic impedance matching theory is proposed. The absorption curve of absorbers is verified with theoretical calculations，numerical simulations and experiment. The results show that the proposed method can quickly and easily realize the structural design of elastic absorbers，bringing new possibilities for the research on flexural waves absorption and vibration reduction design. The theoretical method and absorption structure proposed in this paper do not need additional damping materials，which is more conducive to meet the requirements of lightweight structures in aeronautical engineering. At the same time， it brings new possibilities for the field of vibration wave absorption，especially the design of efficient absorption and vibration reduction of curved waves.

Mode converters (MCs) play an essential role in mode-division multiplexing (MDM) systems. Numerous schemes have been developed on the silicon-on-insulator (SOI) platform, yet most of them focus solely on the conversion of fundamental mode to one or two specific higher-order modes. In this study, we introduce a hybrid shape optimization (HSO) method that combines particle swarm optimization (PSO) with adjoint methods to optimize the shape of the S-bend waveguide, facilitating the design of arbitrary-order MCs featuring compactness and high performance. Our approach was validated by designing a series of 13 μm-long MCs, enabling efficient conversion between various TE modes, ranging from TE0 to TE3. These devices can be fabricated in a single lithography step and exhibit robust fabrication tolerances. Experiment results indicate that these converters achieve low insertion losses under 1 dB and crosstalks below −15 dB across bandwidths of 80 nm (TE0–TE1), 62 nm (TE0–TE2), 70 nm (TE0–TE3), 80 nm (TE1–TE2), 55 nm (TE1–TE3), and 75 nm (TE2–TE3). This advancement paves the way for flexible mode conversion, significantly enhancing the versatility of on-chip MDM technologies.

Oolong tea was highly favored by consumers for its rich aroma. However, there was significant loss of fragrance in Oolong tea products during processing and storage, urgently necessitating the development of corresponding technologies to stabilize aroma molecules. Addressing this, this study investigated the stabilization of aroma compounds in Rougui Oolong tea. Employing spinning cone column distillation, volatile organic compounds (VOCs) were extracted from the tea. The effect of hydroxypropyl-β-cyclodextrin on inhibiting the aromatic loss of these extracted VOCs during storage was assessed using gas chromatography-ion mobility spectrometry. Results showed that after 7, 21, and 42 days of storage at room temperature (25 ℃), the samples treated with hydroxypropyl-β-cyclodextrin (experimental group) consistently contained significantly higher quantities of VOCs compared to the untreated controls (P

In modern ship degaussing systems, degaussing windings are mainly distributed based on the shape of ship bulkhead, which is difficult to ensure the degaussing effect of magnetic induction intensity of unit winding of each degaussing winding. In order to solve this problem, this paper introduces a tilted correlation screening in high-dimensional variable filter, which splits and recombines the original coils, and re-divides the original degaussing sections, so as to improve the degaussing efficiency of each coil. Aiming at the problem of sparse parameter vectors and multiple collinearity in the calculation of degaussing current after winding restructuring, this paper proposes a slant correlation screening and partial ridge regression algorithm. Through simulation, when the threshold is 0.73 and 0.91, the algorithm reduces 10.08% and 17.59% respectively compared with the least square method, while the residual root mean square error decreases by 10.45% and 12.17%. The simulation results show that the degaussing effect is significantly improved after the algorithm is adopted.

Standardization is one of the key steps to analyze locomotive overhaul data with a focus on reliability-centered maintenance (RCM). However, traditional manual methods encounter challenges such as small sample sizes, non-standardized data formats, analytical complexities, and high labour costs, hindering the achievement of data standardization. Large language models (LLM), featuring powerful performance in natural language processing comprehension and handling complex tasks, have made great academic and industrial progress in recent years. This study initially investigated the application performance of LLMs in information extraction from locomotive overhaul data, with the following three reveals, as the universal information extraction (UIE) LLM is suitable for information extraction in the field of locomotive overhaul; expanding the size of locomotive data helps improve the UIE performance in information extraction from locomotive overhaul data; balancing the types of fault labels does not notably help improve this performance. Subsequent explorations concentrated on difficulties in data annotation. The script writing method was utilized for automated annotation of data, and ChatGLM was leveraged to standardize locomotive overhaul data, yielding Bleu-4, Rouge-1, Rouge-2, and Rouge-L metrics of 86.87%, 89.60%, 87.54%, and 94.26%, respectively, in alignment with the requirements of engineering applications. Further developments introduced an auxiliary data standardization pre-processing tool to streamline the standardization process by encapsulating the LLM.

In this study, in order to establish an electrochemical method for the rapid and sensitive determination of benzo[a]pyrene (BaP) in barbecued meat products, a Fe3O4/multi-walled carbon nanotubes (MWCNTs)-COOH/Nafion/glassy carbon electrode (GCE) electrochemical sensor was prepared using magnetic ferric oxide (Fe3O4), MWCNTs-COOH and Nafion as composite modifying materials and a GCE as carrier. The optimal conditions were determined as follows: disodium hydrogen phosphate-potassium dihydrogen phosphate solution at pH 2.5 as electrolyte solution, 0.5% Nafion as dispersant, 6 µL of modifying solution (2 mg/mL), and enrichment time 15 min. Under these conditions, there was a good linear relationship between BaP concentration in the range of 0–100 nmol/L and peak current, with a determination coefficient (R2) of 0.997 0. The detection limit of this method was 3.12 × 10–10 mol/L, and the spiked recoveries ranged from 86.65% to 96.97%. In conclusion, the electrochemical sensor has good stability and reproducibility and is suitable for the rapid detection of BaP in barbecued meat products.

Abstract Background Adolescent malignant-bone tumor patients' fear of cancer recurrence is a significant psychological issue, and exploring the influencing factors associated with fear of cancer recurrence in this population is important for developing effective interventions. This study is to investigate the current status and factors influencing fear of cancer recurrence (FCR) related to malignant bone-tumors in adolescent patients, providing evidence for future targeted mental health support and interventions. Design A cross-sectional survey. Methods In total, 269 adolescent malignant-bone tumor cases were treated at two hospitals in Zhejiang Province, China from January 2023 to December 2023. Patients completed a General Information Questionnaire, Fear of Progression Questionnaire-Short Form (FoP-Q-SF), Family Hardiness Index (FHI), and a Simple Coping Style Questionnaire (SCSQ). Univariate and multivariable logistic regressions analysis were used to assess fear of cancer recurrence. Results A total of 122 (45.4%) patients experienced FCR (FoP-Q-SF ≥ 34). Logistic regression analysis analyses showed that per capita-monthly family income, tumor stage, communication between the treating physician and the patient, patient's family relationships, family hardiness a positive coping score, and a negative coping score were the main factors influencing FCR in these patients (P

Hemerocallis citrina Borani is a traditional folk food used to promote the lactation of postpartum mothers in China; however, the active ingredients and corresponding mechanisms are still unknown. In this study, the lactogenic effect of alcoholic and aqueous extracts of H. citrina was primarily evaluated, and the aqueous extract (1,000 and 2,000 mg/kg) displayed significant lactation-promoting effects. Three eluates of the aqueous extract (0%, 30%, and 50%HCW) were further evaluated for their lactogenic effect, and 30% and 50% HCW showed significant lactation-promoting activity. Nineteen ingredients, including those with a high content of rutin and isoquercetin, were then identified from 30% and 50%HCW using the ultra-performance liquid chromatography-quadrupole-time-of-flight-mass spectrometry (UPLC-Q-TOF-MS) method. Finally, the lactogenic effect of rutin and isoquercetin was evaluated, and both compounds displayed significant lactation-promoting activity. The mechanisms relative to the lactation-promoting active ingredients for H. citrina extracts and compounds are to stimulate the release of prolactin (PRL) and progesterone (P), as well as to induce the expression of prolactin receptor (PRLR) and improve the morphology of mammary tissue. This study first clarified the lactation-promoting active ingredients of H. citrina and the corresponding mechanisms, which provide a new insight into the new lactation-promoting drug and promote the high-value utilization of H. citrina resources.

Background: The gut microbiome is central to human health, but the potential impact of ozone (O3) exposure on its establishment in early life has not been thoroughly examined. Therefore, this study aimed to investigate the relationship between prenatal O3 exposure and the variations of the human gut microbiome during the first two years of life. Design: A cohort study design was used. Pregnant women in the third trimester were recruited from an obstetric clinic, and long-term follow-ups were conducted after delivery. The gut microbiome was analyzed using the 16 S rRNA V3-V4 gene regions. Functional pathway analyses of gut microbial communities in neonates were performed using Tax4fun. The average concentrations of ambient O3 and other air pollutants from pregnancy to delivery were calculated using the China High Air Pollutants (CHAP) dataset, based on the permanent residential addresses of participants. Multiple linear regression and mixed linear models were utilized to investigate the associations between prenatal O3 exposure and gut microbiome features. Results: Prenatal O3 exposure did not significantly affect the gut microbial alpha diversity of mothers and neonates. However, it was found to be positively associated with the gut microbial alpha diversity in 24-month-old infants. Prenatal O3 exposure explained 13.1 % of the variation in neonatal gut microbial composition. After controlling for potential covariates, prenatal O3 exposure was associated with neonatal-specific gut microbial taxa and functional pathways. Furthermore, the mixed linear models showed that prenatal O3 exposure was negatively associated with variations of Streptococcus (p-value = 0.001, q-value = 0.005), Enterococcus (p-value = 0.001, q-value = 0.005), Escherichia-Shigella (p-value = 0.010, q-value = 0.025), and Bifidobacterium (p-value = 0.003, q-value = 0.010). Conclusions: This study is the first to examine the effects of prenatal O3 exposure on gut microbial homeostasis and variations. It demonstrates that prenatal O3 exposure is associated with variations in certain aspects of the gut microbiome. These findings provide novel insights into the dynamics and establishment of the human microbiome during the first two years of life.

Abstract Background The gonadotropin hormone-releasing hormone agonists (GnRH-a) have been widely used for controlled ovarian stimulation in assisted reproductive technology (ART). The early-follicular long-acting GnRH-a long protocol (EFL) and the luteal phase short-acting GnRH-a long protocol (LPS) are commonly used GnRH agonist protocols. We conducted a retrospective analysis to assess and compare the rates of congenital abnormalities and safety profiles in offspring born from the EFL and LPS protocols. Methods We conducted a retrospective cohort study to analyze and compare neonatal data from patients who using EFL or LPS protocols at our center between January 1, 2014, and June 30, 2017. The study ultimately included 1810 neonates from 1401 cycles using the EFL protocol and 2700 neonates from 2129 cycles using the LPS protocol.The main outcome measures are gestational age at delivery, birth weight, and congenital anomaly rate.To assess the influence of various factors on congenital abnormalities, a random-effects logistic regression model was employed. Results The EFL and LPS protocols led to similar congenital anomaly rates (1.64% vs. 2.35%, P = 0.149). No significant differences were found between the two groups regarding birth weight and its categories, newborn gender and congenital anomaly rate. The results of the multivariate logistic regression model indicated no association between congenital anomaly and BMI, duration of infertility, treatment protocol, fertilization method, or embryo transfer stage. Compared with singleton pregnancies, the probability of congenital defects in multiple pregnancies was 2.64 times higher (OR: 2.64, 95% CI: 1.72–4.05, P

Direct-to-handset satellite service is one of the important applications for low earth orbiting (LEO) satellite constellation systems. The overview on the main technology routes, application scenarios, and business types of satellite communication service for direct-to-handset was provided. The construction cost, capacity and operating income of LEO satellite constellation system were analyzed. The main applications of direct-to-handset satellite in China should focus on wide coverage and massive connections. Furthermore, there was a risk of commercial closed-loop in high traffic and broadband satellite applications. Finally, the technology trend was discussed associated with application requirements.

BackgroundErythrocyte dysfunction is a characteristic of diabetes mellitus (DM). However, erythrocyte-associated biomarkers do not adequately explain the high prevalence of DM. Here, we describe red blood cell distribution width to albumin ratio (RAR) as a novel inflammatory biomarker for evaluating an association with DM prevalence and prognosis of all-cause mortality.MethodsData analyzed in this study were extracted from the National Health and Nutrition Examination Survey (NHANES) 1999−2020. A total of 40,558 participants (non-DM and DM) were enrolled in the study; RAR quartiles were calibrated at Q1 [2.02,2.82] mL/g, Q2 (2.82,3.05] mL/g, Q3 (3.05,3.38] mL/g, and Q4 (3.38,12.08] mL/g. A total of 8,482 DM patients were followed (for a median of 84 months), of whom 2,411 died and 6,071 survived. The prevalence and prognosis associated with RAR and DM were analyzed; age and sex were stratified to analyze the prevalence of RAR in DM and the sensitivity of long-term prognosis.ResultsAmong non-DM (n=30,404) and DM (n=10,154) volunteers, DM prevalence in RAR quartiles was 8.23%, 15.20%, 23.92%, and 36.39%. The multivariable odds ratio (OR) was significant for RAR regarding DM, at 1.68 (95% CI 1.42, 1.98). Considering Q1 as a foundation, the Q4 OR was 2.57 (95% CI 2.11, 3.13). The percentages of DM morbidity varied across RAR quartiles for dead (n=2,411) and surviving (n=6,071) DM patients. Specifically, RAR quartile mortality ratios were 20.31%, 24.24%, 22.65%, and 29.99% (P3.22 mL/g suffered shorter survival and higher mortality as compared to those with RAR ≤3.22 mL/g. OR and HR RAR values were much higher than those of regular red blood cell distribution width.ConclusionsThe predictive value of RAR is more accurate than that of RDW for projecting DM prevalence, while RAR, a DM risk factor, has long-term prognostic power for the condition. Survival time was found to be reduced as RAR increased for those aged ≤60 years among female DM patients.

The accurate and fast localization of key components on high-speed railways in operation serves is one of the foundations for fault diagnosis of high-speed railways. However, utilizing ordinary industrial cameras for data collection on operational high-speed railways often results in motion blur or misses key components. On the other hand, training object detection models with data collected by ultra-high-speed spike cameras encounters challenges, such as difficulties in data annotation and model training. To this end, this paper proposes a detection method for key components on high-speed railways that leverages reconstruction based on spike data. Firstly, based on the principle of spike triggering, the light intensity was restored at different points following the inter-spike interval. Then, local adjustments to light intensity were made through global light intensity calculations. The adjusted results were further filtered and locally enhanced to reconstruct high-resolution grayscale images. Subsequently, after data cleaning and annotation based on the reconstructed images, the annotated data were used to train the detection model for key components on high-speed railways. Finally, the trained model was accelerated using TensorRT. Experimental results showed that the accelerated model achieved an accuracy of 98.7% and a single-frame inference rate of 3.5 ms both on average. The study findings lay a foundation for the engineering applications of the proposed algorithm .

[Objective] Metal Magnetic Memory(MMM) stress detection technology, facilitating non-contact and on-line detection, has demonstrated significant potential for application in stress damage detection on ferromagnetic materials, particularly steel pipelines used for oil and gas transmission. However, existing research lacks a comprehensive analysis of the magneto-mechanical relationship. Therefore, this study seeks to establish a comprehensive magneto-mechanical relationship system and clarify the correspondence between MMM detection signals and stress concentration during both the elastic and plastic stages. [Methods] In this study, numerical models were developed to represent the relationship between magnetization and strain in pipelines, using the J-A theory as the basis. Computational analysis was conducted to investigate the characteristics of MMM detection signals at various stages of pipeline deformation and to examine the impact of shape parameters of hysteresis-free magnetization curves and pinning coefficients on MMM signals under stress influence. To verify the obtained relationship between strain and magnetic signals, a full-scale hydrostatic experiment was conducted. [Results] The experimental results revealed a gradual increase in strain with the applied stress in the pipeline. During the elastic deformation stage, the magnetization curve exhibited its first reversal near the yield point, and this reversal occurred earlier with higher shape parameters of hysteresis-free magnetization curves. In the plastic deformation stage, the presence of dislocations caused alternations in the magnetic characteristics of the pipeline material, leading to the second reversal on the magnetization curve near the yield point, which was significantly influenced by pinning coefficients. Specifically, higher pinning coefficients resulted in delayed reversals. The strain values corresponding to the reversals decreased quadratically, and the two reversals occurred in opposite directions. [Conclusion] By incorporating phase contrast analysis between MMM signal reversals and calibration results obtained from the same material as the pipelines, this model, which utilizes the aforementioned characteristics, has been proven effective in identifying plastic strain occurrence in stress concentration zones of steel oil and gas pipelines and offers a practical solution for rapid qualitative detection of stress concentration in pipelines.

This study is devoted to exploring the strategy of automatic sketch generation and optimization of industrial design based on deep learning. By combining the Generative Adversarial Network (GAN) with the optimization algorithm, this paper proposes an innovative method to realize the automatic generation of high-quality and diverse industrial design sketches. In the experiment, this paper selects SketchyCAD and other public data sets, trains them through deep learning model, and introduces genetic algorithm(GA) and differential evolution algorithm to optimize the parameters. In terms of experimental results, we observed that the quality of generated sketches was significantly improved, and the design sketches generated by the mode (GAN+GA) were more realistic and innovative. The introduction of optimization strategy further improves the generation effect and intelligently adjusts the model parameters to adapt to different design styles. In this paper, the influence of hyperparameter tuning is analyzed in detail, and it is found that the adjustment of learning rate plays a key role in generating quality and diversity. However, the experiment also revealed some challenges and room for improvement. We noticed that the generated results may have the risk of over-fitting in the training process, and with the increase of training times, the diversity gradually decreased. This suggests that more complex model structure and richer data sets are needed to improve the generalization performance. Generally speaking, this study provides new ideas and methods for the integration of deep learning and industrial design. By innovatively combining generation model and optimization algorithm, this research has contributed beneficial research results to the development of industrial design automation. This research is of great significance to promote the intelligence and innovation in the field of industrial design.

Grain boundary optimization of Al-Mg-Sc-Zr alloy was carried out by multi-directional forging and annealing treatment, and the effects of mixed grain boundary structures on the anisotropic behavior of mechanical properties of alloy sheets were investigated. The results show that the homogenized alloy which mainly possesses high angle grain boundaries tends to form rolled shear bands and high intensity Brass, Copper and S textures after rolling deformation, resulting in obvious mechanical properties anisotropy of rolled sheet. The IPAYS of yield strength and IPAUTS of ultimate tensile strength are 6.68% and 5.85%, respectively. After multi-directional forging and annealing treatment, the matrix of the alloy is a mixed crystal structure with high/low angle grain boundary structures. After rolling deformation, the shear band density and texture intensity decrease obviously, resulting in the obvious improvement of the anisotropy of the alloy rolled sheet.

Congenital insensitivity to pain with anhidrosis (CIPA) is associated with Charcot arthropathy and is a rare clinical syndrome, with limited treatment options. Through a decade-long follow-up of a single case, we aim to provide new insights for clinicians regarding the choice of surgical strategies and postoperative complications. The diagnosed patient exhibited congenital insensitivity to pain and anhidrosis, accompanied by severe Charcot arthropathy affecting the spine. Multiple postoperative complications, including implant displacement, adjacent segment pathology, and pedicle screw loosening, occurred after surgical intervention, leading to five subsequent revision surgeries. Considering the limited experience in managing CIPA-related Charcot spinal arthropathy in the literature, surgical correction remains the preferred treatment. Among the 16 cases reviewed, common postoperative complications included implant displacement, adjacent segment pathology, and pedicle screw loosening. Based on current experience, we do not recommend extensive resection and reconstruction after removing the affected vertebral body, as this may increase the risk of implant displacement. Instead, a 360° long-segment fusion may help reduce the risk of adjacent segment degeneration. Additionally, we discuss potential reasons for revision surgery after Charcot spinal arthropathy surgery and perioperative management strategies for such cases. Meticulous care, appropriate rehabilitation exercises, and metabolic therapy for bone mineralization are crucial components of the treatment for this condition.

With the improvement of the requirements for the safe operation of distribution network lines, the harmonics injected by distributed power generation make the existing line selection methods ineffective, and the fault line selection method with a single criterion becomes more and more difficult to meet the line selection work after the single-phase ground fault occurs in the complex distribution network system. Therefore, a single-phase grounding fault joint line selection for resonant grounding system considering the injection harmonics of distributed power sources is proposed. In view of the characteristics of different phases and periodic changes of transient zero-sequence current of fault lines and sound lines after a single-phase grounding fault occurs in the resonant grounding system, the transient zero-sequence current is calculated by multi-scale cross-sample entropy according to the difference in low-frequency period. Then, according to the high-frequency phase difference, the weighted transient energy method and the synchronous squeeze wavelet transform are used to calculate the reconstruction error of the high-frequency transient zero-sequence current. In addition, the weighted transient energy method is used to control the calculation amount and determine the fault line through three criteria: multi-scale cross-sample entropy, weighted transient energy and reconstruction error. The experimental results show that the joint line selection method is less affected by different fault conditions and this method has high accuracy and strong anti-interference.

A DBSCAN (density-based spatial clustering of applications with noise) cluster of lightning data is proposed as the substitute for radar products to solve the problem of beam blockage in radar observation and the delay of radar products in service operations. Two lightning data, BJTLS (Beijing Total Lightning System) and upgraded National Lightning Positioning Network (DDW1), are used and the 2σ lightning jump algorithm is applied to perform severe weather nowcasting on 4 June and 12 June in 2022. The nowcasting effects of the strong convective cell identification method and the DBSCAN clustering method are further compared and analyzed. Based on a determined search radius (R) for neighboring lightning data and a determined minimum number of location results (number of minimum points) in R, the DBSCAN's clustering effect on lightning location data corresponds well with the strong convective radar echo. The ideal parameter combinations for BJTLS, R is 0.05, number of minimum points is 5; and for DDW1 data R is 0.22 and number of minimum points is 3. The results show that both methods and two kinds of data could effectively be used in severe weather nowcast. For BJTLS data, the effects of two methods are equivalent. The probability of detection, false alarm rate, critical success index and lead time of two methods are 100% and 100%, 11.9% and 13.3%, 88.1% and 86.7%, 38.9 min and 42.8 min, respectively. The 2σ lightning jump algorithm can be applied for nowcasting with lightning data, reducing the dependence on radar products. For DDW1 lightning data, compared with the identification method, the start time of the clustering method delays, leading to missing alarms. Since the flash rate of the DDW1 lightning data is low, there will be more missed cases if the flash rate threshold is set to trigger the lightning jump. But without the threshold, there will be more false alarms in operation. Therefore, BJTLS data is more suitable than DDW1 data for applying the 2σ lightning jump algorithm in the service operation. The detection efficiency of BJTLS in Beijing is high and it is necessary to further improve the detection efficiency of DDW1. In conclusion, the DBSCAN clustering method provides a new idea for the service operation of the 2σ lightning jump algorithm.

Moulding the flow of phononic waves in three-dimensional (3D) space plays a critical role in controlling the sound and thermal properties of matter. To this end, 3D phononic crystals (PnCs) have been considered the gold standard because their complete phononic bandgap (PnBG) enables omnidirectional inhibition of phononic wave propagation. Nevertheless, achieving a complete PnBG in the high-frequency regime is still challenging, as attaining the correspondingly demanded mesoscale 3D crystals consisting of continuous frame networks with conventional fabrications is difficult. Here, we report that a DNA origami-designed-3D crystal can serve as a hypersonic 3D PnC exhibiting the widest complete PnBG. DNA origami crystallization can unprecedentedly provide 3D crystals such that continuous frame 3D crystals at the mesoscale are realizable. Furthermore, their lattice symmetry can be molecularly programmed to be at the highest level in a hierarchy of symmetry groups and numbers, which can facilitate the widening of the PnBG. More importantly, conformal silicification can render DNA origami-3D crystals rigid. Overall, we predict that the widest hypersonic PnBG can be achieved with DNA origami-designed 3D crystals with optimal lattice geometry and silica fraction; our work can provide a blueprint for the design and fabrication of mesoscale 3D PnCs with a champion PnBG.

In the field of gear fault diagnosis, it is of great significance to effectively diagnose early wear faults of gears. However, early wear fault has weak characteristics and is difficult to diagnose. Thus, a gear early wear fault diagnosis model based on the sparse attention mechanism is proposed to solve this problem. This model uses a new sparse attention mechanism combined with a convolution neural network to improve the traditional sectional attention mechanism and locate the specific fault frequency. The gearbox fault simulation test data is used for test verification. Compared with other diagnosis methods, this new method can achieve a more accurate and comprehensive diagnosis, reduce analysis cost and obtain sensitive fault characteristic frequency under the same sample condition and calculation cost. The conclusion of this method can provide data support for gear maintenance.

The increasing need for human-robot interaction requires not only robots to understand how humans think, but also humans to understand robots. Interestingly, little attention has been given to how humans interpret robots’ behaviors. In this study, we adopted a social mental rotation task and investigated whether socially engaging behaviors could influence how people take a robot’s perspectives. In a real lab, two android robots with neutral appearance sat opposite each other by a table with conflicting perspectives. Before the participant started the experiment, one of the robots behaved more interactively than the other by showing more socially engaging behaviors. Then the participant was required to identify rotated normal or mirrored digits presented inbetween the two robots. Results revealed a significant interactive effect between the digits type (normal; mirrored) and robot type (interactive; noninteractive). When digits were oriented to the interactive robot, we found a larger RT difference between normal and mirrored digits. In general, these findings suggested that robots’ interactive behaviors could influence how people spontaneously consider the robot’s perspective. Future studies may further consider how interactive behaviors can shape human-robot relationships and facilitate human-robot interaction.

The transpalatal arch (TPA) is widely used in clinical orthodontics for various purposes. This article reviews the versatile clinical uses and mechanics of TPAs for clinical reference. Traditionally, TPA is conceived as an anchorage reinforcement device. However, the literature does not support the sole use of TPA for anchorage control. TPA, combined with other conventional anchorage means, can only provide sufficient anchorage in certain cases. As an adjunct to fixed appliance treatment, TPA can be applied for arch width maintenance, tooth alignment and habit braking to improve treatment efficiency and reduce side effects. Meanwhile, TPA can be used to provide active orthodontic forces for maxillary molars to move or rotate bilaterally and unilaterally in all three planes of space, especially on occasions where molar rotation and transverse discrepancy exist. A two-couple system is formed with a TPA connecting bilateral maxillary first molars, the mechanical analysis of which can improve the understanding of treatment mechanics and make tooth movement more predictable. In recent years, TPA has also been used in combination with temporary anchorage devices for maxillary molar intrusion and full arch mesialization or distalization. The combined use of TPA with TADs and maxillary skeletal expanders could be further investigated in the future.

Objective This study aimed to investigate the clinical significance of exostosin 1 (EXT1) in confirmed and suspected lupus membranous nephropathy (LMN).Methods EXT1 was detected in 67 renal tissues of M-type phospholipase A2 receptor (PLA2R)-negative and ANA-positive membranous nephropathy by immunohistochemistry, and cases were divided into confirmed LMN and suspected LMN. The clinicopathological data were compared among the above groups, as well as EXT1-positive group and EXT1-negative group.Results Twenty-two cases (73.3%) of confirmed LMN and six cases (16.2%) of suspected LMN exhibited EXT1 expression on the glomerular basement membrane and/or mesangium area, showing a significant difference (p

Polarized holographic properties play an important role in the holographic data storage of traditional organic recording materials. In this study, reduced graphene oxide (RGO) was introduced into a phenanthraquinone-doped polymethylmethacrylate (PQ/PMMA) photopolymer to effectively improve the orthogonal polarization holographic properties of the material. Importantly, the lateral size of RGO nanosheets has an important influence on the polymerization of MMA monomers. To some extent, a larger RGO diameter is more conducive to promoting the polymerization of MMA monomers and can induce more PMMA polymers to be grafted on its surface, thus obtaining a higher PMMA molecular weight. However, too large of a RGO will lead to too much grafting of the PMMA chain to shorten the length of a single PMMA chain, which will lead to the degradation of PQ/PMMA holographic performance. Compared with the original PQ/PMMA, the diffraction efficiency of the RGO-doped PQ/PMMA photopolymer can reach more than 11.4% (more than 3.5 times higher than the original PQ/PMMA), and its photosensitivity is significantly improved by 4.6 times. This study successfully synthesized RGO-doped PQ/PMMA high-performance photopolymer functional materials for multi-dimensional holographic storage by introducing RGO nanoparticles. Furthermore, the polarization holographic properties of PQ/PMMA photopolymer materials can be further accurately improved to a new level.

Abstract Purpose This study aimed to analyze the distribution of IgG subclass in diabetic nephropathy (DN) and its association with clinicopathological features. Methods This is a single-center retrospective study enrolling 108 patients with biopsy-proven DN. Immunofluorescence and immunohistochemistry staining were applied, and clinicopathological features and renal outcomes were compared between patients with different patterns or categories of IgG subclass deposition. Results Both IgG and its subclasses colocalized with collagen IV α5 on glomerular basement membrane (GBM) and some of tubular basement membrane (TBM). IgG1 and the Mixed type were two predominant types of deposition, no matter on GBM or TBM, and IgG1 showed a much higher deposition rate on GBM than that on TBM (P = 0.004). IgG subclass deposit on multi-location was more associated with a shorter duration of nephropathy and severer tubular interstitial injury (P

The ancient Chinese remedy BuyangHuanwu Decoction (BHD) is used to treat qi deficit and blood stasis conditions. This work investigated the effect of BHD on cerebral vasospasm (CVS) caused by subarachnoid hemorrhage (SAH). Rats were randomly assigned into four groups: control group, SAH group, SAH + BHD [13 g/(kg day)] group, and SAH + BHD [26 g/(kg day)] group. The Garcia neurological scoring scale was used to assess neurological dysfunction. Hematoxylin and eosin stains were used to determine the extent of vasospasm by measuring the diameter of the basilar artery. Western blot was used to measure the concentrations of phosphoinositide 3-kinase (PI3K), AKT, and phospho-AKT expression levels. RT-PCR was used to determine PI3K and AKT RNA expressions. Immunohistochemistry and enzyme-linked immunosorbent assay were used to measure levels of endothelial nitric oxide synthase (eNOS) and nitric oxide (NO), respectively, in cerebrospinal fluid. BHD treatment ameliorated CVS and mitigated neurological dysfunction after SAH. Furthermore, the findings suggest that NO concentration was increased through the activation of classical PI3K/AKT signaling and the eNOS pathway. Thus, BHD showed multifaceted roles in preventing damage via decreasing vasospasm and improving neurological impairments caused by CVS after SAH.

Abstract Aim The aim of this study was to investigate the renoprotective effects of exosomes derived from rat bone marrow mesenchymal stem cells (rBMSCs) in a rat model of 5/6 nephrectomy (Nx)-induced chronic kidney disease (CKD). Methods A rat model of 5/6 Nx-induced CKD was established using conventional method. rBMSC-derived exosomes were isolated using ultracentrifugation and characterized. The exosomes were injected into 5/6 Nx rats through the caudal vein. After 12 weeks, 24 h proteinuria, serum creatinine (SCr), and blood urea nitrogen (BUN) levels were evaluated, and renal pathology was analyzed by H&E and Masson staining, and transmission electron microscopy. The expression of klotho was analyzed and the activity of the klotho promoter was evaluated using a luciferase reporter assay. Results The isolated exosomes showed typical morphological features. Exosomes transplantation reduced 24 h urinary protein excretion, and SCr and BUN levels in 5/6 Nx-induced CKD rats. Furthermore, renal pathology was improved in the exosome-treated 5/6 Nx rats. Mechanistically, the exosomes significantly upregulated the activity of klotho promoter and its expression. Conclusions Transplantation of rBMSC-derived exosomes may protect against kidney injury, probably by regulating klotho activity and expression. Our results provide a theoretical basis for the application of rBMSC-derived exosomes in CKD therapy.

Stereochemical control of acyclic carbon radical intermediates remains a challenge, due to the difficulty in differentiation between the two faces of the planar species. Here the authors show diastereodivergent hydrogen atom transfer to acyclic carbon radicals via control of N-heterocyclic carbene–borane reagents with either a thiol catalyst or a Lewis acid.

The currently developed remote fault diagnosis systems for fully mechanized mining equipment are mostly for single-machine equipment such as coal shearers, scraper conveyors and belt conveyors, and for expert remote guidance and maintenance systems based on video or virtual reality. However, there is few research on equipment group fault diagnosis systems that integrates cloud platform, remote fault diagnosis and expert remote guidance and maintenance. In order to solve the above problem, a remote fault diagnosis system of fully mechanized mining equipment group based on cloud platform is designed. Firstly, the method collects the state monitoring information of shearer, hydraulic support, scraper conveyor, transfer machine, emulsion pump station, belt conveyor and power supply system of fully mechanized working face through sensors. Secondly, the state monitoring information of fully mechanized mining equipment group is transmitted to the ground server through the underground ring network of the coal mine. The ground server performs intelligent fault diagnosis analysis, data storage, and alarm query on the received information. Finally, the state monitoring information of fully mechanized mining equipment group of the ground server is transmitted to the cloud server in a unified format through the MQTT protocol for data processing and format conversion. And the converted data is transmitted to the mobile terminal by 4G/5G network and transmitted to the PC terminal by the MQTT protocol. Therefore, the method can realize the visualization, fault query, fault alarm and timely push of fault warning information of the state monitoring of fully mechanized mining equipment group. With visual video monitoring as the medium, when the fully mechanized mining equipment fails, the video information can be transferred to the corresponding expert in real time. The expert can remotely guide the coal workers for remote maintenance through the video information. The system has been tested in the fully mechanized working face of Huangling Coal Mine in Shaanxi. The results show that the system realizes the remote fault diagnosis of fully mechanized mining equipment group. The system realizes the real-time push of the state monitoring and fault warning information of fully mechanized mining equipment group through the mobile phone platform. Moreover, the system reduces the fault rate and the number of unplanned shutdowns of fully mechanized mining equipment group and improves the production efficiency by about 30%.

Photonic computation has garnered huge attention due to its great potential to accelerate artificial neural network tasks at much higher clock rate to digital electronic alternatives. Especially, reconfigurable photonic processor consisting of Mach–Zehnder interferometer (MZI) mesh is promising for photonic matrix multiplier. It is desired to implement high-radix MZI mesh to boost the computation capability. Conventionally, three cascaded MZI meshes (two universal N × N unitary MZI mesh and one diagonal MZI mesh) are needed to express N × N weight matrix with O(N 2) MZIs requirements, which limits scalability seriously. Here, we propose a photonic matrix architecture using the real-part of one nonuniversal N × N unitary MZI mesh to represent the real-value matrix. In the applications like photonic neural network, it probable reduces the required MZIs to O(Nlog2 N) level while pay low cost on learning capability loss. Experimentally, we implement a 4 × 4 photonic neural chip and benchmark its performance in convolutional neural network for handwriting recognition task. Low learning-capability-loss is observed in our 4 × 4 chip compared to its counterpart based on conventional architecture using O(N 2) MZIs. While regarding the optical loss, chip size, power consumption, encoding error, our architecture exhibits all-round superiority.

The current automatic coal mining technology with memory cutting as the core technology cannot perceive the changes of geological conditions of the working face autonomously, and the shearer can hardly realize automatic height adjustment control according to the changes of coal seam thickness. And it is only a preliminary exploration for precision mining. In order to solve the above problems, a digital coal seam-based precision mining system for fully mechanized working face is developed. Firstly, the system establishes the initial 3D digital coal seam model by using coal mine geological data, working face cutting data and geological realistic data of the working face transportation and return air roadways and the cubic spline interpolation method. Secondly, through the fully mechanized mining equipment inertial navigation system, odometer, radar, angle sensor, the model dynamically senses the actual walking trajectory and cutting trajectory of the shearer, and dynamically corrects the established initial 3D digital coal seam model and generates the straightness detection curve of the scraper conveyor. Finally, according to the revised 3D digital coal seam model, the cutting trajectory curve of the shearer is dynamically planned and sent to the shearer control system to instruct the shearer to automatically adjust the height according to the change of coal seam thickness. Through the scraper conveyor straightness detection curve and hydraulic support travel information comprehensive analysis, the model calculates the displacement deviation of each hydraulic support for the next cut. And the displacement deviation of each hydraulic support for the next cut is sent to the hydraulic support control system of the fully mechanized working face to realize the hydraulic support automatic straightening. The test results show that the system realizes dynamic planning of cutting trajectory of the shearer, automatic tracking control of the height adjustment trajectory and automatic straightening of hydraulic support. The cutting trajectory of the shearer planning knife can be obtained through the CT slice of 3D digital coal seam model. The planned cutting trajectory error is less than 02 m. Without human intervention, the automatic cutting time is about 1 h for 250 m long working face, and the automatic cutting time for triangular coal is about 30 min.

As a localization and map construction method,SLAM(Simultaneous Localization and Mapping) is widely used in the field of robots.SLAM algorithm enables the robot to perceive environmental information and establish environmental map through sensors carried by the robot itself in an unfamiliar environment,and calculate its own posture.In this way,the robot can move in an unknown environment.With the in-depth study of SLAM,the research results in the field of SLAM have been very rich.However,the discussion on indoor SLAM is not comprehensive enough.Through the summary and comparison of the exis-ting development results of the SLAM method,a comprehensive statement is shown.In this paper,the technical status of SLAM and the classification problem of SLAM under different sensors in indoor scenes are firstly introduced.Secondly,the classic framework of SLAM is revealed.Thirdly,the principles of SLAM algorithms with different sensors are described according to the different types of related sensors.Fourthly,the limitations of the traditional indoor SLAM algorithms are discussed and two research directions-SLAM based on multi-sensor fusion technology and SLAM based on deep learning technology are led out.Finally,the future development trend and application field of SLAM are suggested

Hemerocallis citrina Baroni [Asphodelaceae], which is traditional herbal medicine, has been widely used for treating depressive disorders in Eastern-Asia countries. However, the active compounds and corresponding mechanism of anti-depression are not yet completely clarified. In this study, the anti-depressive activities of six H. citrina extracts were primarily evaluated. The results showed that the water extract of H. citrina flowers (HCW) displays significant anti-depressive activity. A total of 32 metabolites were identified from HCW by high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS) and nuclear magnetic resonance (NMR). And then, the anti-depressive activity of the high-level compound (rutin) in HCW was also estimated. The results indicated that rutin displayed significant anti-depressive activity and was one of the main active ingredients. Finally, the anti-depressive mechanisms of HCW and rutin were investigated based on the intestinal microorganisms. The results showed that HCW and rutin increase the diversity and richness of the intestinal flora and regulate the specific intestinal microorganisms such as Bacteroides and Desulfovibrio genera in depressed mice. This work marks the first comprehensive study of the active components, anti-depressive activities and corresponding mechanisms of different H. citrina extracts, which provide a potential possibility for developing new antidepressants.

Based on S-band Doppler weather radar raw data, the total lightning location data of Beijing Lightning Network (BLNET) and hailfall reports from Beijing Meteorological Service, two lightning jump algorithms, Gatlin algorithm and σ algorithm, with different configurations are compared and analyzed for early warning performance of 177 hailfall events in Beijing from 2015 to 2018. The results show that, the early warnings of different multiples of σ algorithm are quite different, 2σ (in this situation, the current changing rate of total flash exceeds two times of the standard deviation of total flash rate in previous time) has the best performance in the σ algorithm. That is to say, 2σ algorithm has the highest probability of detection (POD) and critical success index (CSI), as well as the lowest false alarm rate (FAR), comparing with σ, 3σ and 4σ algorithms. The early warnings of Gatlin algorithm under different N (which is the amount of samples before current time used to calculate the mean and standard deviation) configurations have little difference, and the early warning efficiency is best when N=6, comparing with N=7, 8, 9 and 10. The POD, FAR and CSI of 2σ algorithm are 80.2%, 41.6%, and 51.1%, respectively. The corresponding results of the Gatlin algorithm with N=6 are 82.5%, 62.0%, and 35.2%, respectively. In addition, the applications of these two algorithms to a multi-cell thunderstorm process and a squall line process are analyzed in detail. The results also show that Gatlin algorithm with N=6 has a slightly higher POD than 2σ algorithm, but its FAR is much higher and its CSI is lower. Considering the evaluation of hail nowcast results by Gatlin algorithm and 2σ algorithm, 2σ lightning jump algorithm is more suitable for hail nowcasting in Beijing. And it is beneficial to improving the application of lightning data to hail nowcasting in Beijing

Real-world nonhomogeneous haze brings challenges to image restoration. More efforts are needed to remove dense haze and thin haze simultaneously and efficiently. However, most existing dehazing methods do not pay attention to the complex distributions of haze and usually suffer from a low runtime speed. To tackle such problems, we present an efficient re-parameterization residual attention network (RRA-Net), whose design has three key aspects. Firstly, we propose a training-time multi-branch residual attention block (MRAB), where multi-scale convolutions in different branches cope with the nonuniformity of haze and are converted into a single-path convolution during inference. It also features local residual learning with improved spatial attention and channel attention, allowing dense and thin haze to be attended to differently. Secondly, our lightweight network structure cascades six MRABs followed by a long skip connection with attention and a fusion tail. Overall, our RRA-Net only has about 0.3M parameters. Thirdly, two new loss functions, namely the Laplace pyramid loss and the color attenuation loss, help train the network to recover details and colors. The experimental results show that the proposed RRA-Net performs favorably against state-of-the-art dehazing methods on real-world image datasets, including both nonhomogeneous haze and dense homogeneous haze. A runtime comparison under the same hardware setup also demonstrates the superior efficiency of the proposed network.