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Abstract Background The incidence of knee osteoarthritis after anterior cruciate ligament reconstruction (ACLR) is high to 57%, and the biomechanical abnormality during walking is one of the reasons. The purpose of this study was to investigate the effect of 12 weeks of knee extension constraint training on walking biomechanics during the stance phase of injured side after ACLR. Methods Forty-five patients were randomly assigned to three groups based on different brace conditions from 13 weeks to 24 weeks after ACLR: experimental (brace with knee extension constraint), placebo (brace without knee extension constraint), and control (no brace). Gait analysis was performed 3 and 6 months after ACLR. The peak for knee flexion angle (KFA), knee extension moment (KEM), and vertical ground reaction force (vGRF) were compared by 2 (time) x 3 (group) repeated-measures analysis of covariance (ANCOVA), and pairwise comparisons were conducted. . Results There was a significant time x group interaction for the peak KFA (p = 0.047), and there was no significant time x group interaction for the peak KEM and peak vGRF. The pairwise comparisons showed that there were no statistical differences among the groups both the pre-intervention and post-intervention in the peak KFA, peak KEM, and peak vGRF. Compared with pre-intervention, the peak vGRF in the experimental group was significantly greater (p = 0.009) and the peak KFA in the control group was significantly lower (p = 0.041) post-intervention. There were not significantly different in the placebo group between pre-intervention and post-intervention. Conclusion 12 weeks of knee extension constraint training can increase lower extremity loading on the injured side, may be a potential therapeutic adjunct to improve abnormal gait after ACLR.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by its aggressive nature and dismal prognosis, largely attributed to its unique tumor microenvironment. However, the molecular mechanisms by which tumor-associated macrophages (TAMs) promote PDAC progression, particularly the role of β-catenin signaling in regulating TAM phenotype and function, remain incompletely understood.Initially, we performed comprehensive analyses of RNA-seq and single-cell RNA-seq (scRNA-seq) datasets to investigate OSM and LOXL2 expression patterns in PDAC. Subsequently, the regulatory relationship between β-catenin and OSM in TAMs was examined using THP-1-derived macrophages. Furthermore, the functional impact of TAM-derived OSM on PDAC progression was evaluated through in vitro co-culture systems and an in vivo Panc02 lung metastasis model. Additionally, mechanistic studies employed pharmacological inhibitors and genetic approaches targeting β-catenin, OSM, and STAT3 signaling.Notably, elevated expression of OSM and LOXL2 in PDAC specimens significantly correlated with poor patient survival. Intriguingly, scRNA-seq analysis revealed that β-catenin signaling was uniquely activated in TAMs among immune cells, which consequently regulated both TAM polarization and OSM expression. These OSM-expressing TAMs exhibited a distinct hybrid M1/M2 phenotype. Besides, our transcriptional profiling of TAMs revealed concurrent activation of both pro- and anti-inflammatory programs, with enrichment in Wnt signaling pathways. RNA-seq analysis of PDAC cells exposed to TAM-derived factors demonstrated enhanced mesenchymal transition and stemness properties, with direct enrichment of OSM signaling and extracellular matrix remodeling pathways. Mechanistically, β-catenin activation directly regulated both TAM phenotype and OSM expression, while TAM-conditioned medium enhanced PDAC cell migration, invasion, and lung metastasis. Importantly, inhibition of β-catenin signaling simultaneously altered TAM polarization and reduced OSM expression, which substantially attenuated epithelial-mesenchymal transition (EMT) in co-cultured PDAC cells. Moreover, STAT3 inhibition abolished OSM-induced LOXL2 expression and subsequent EMT programming.Collectively, we identified a novel β-catenin/OSM-STAT3/LOXL2 signaling axis mediating TAM-induced PDAC progression. This pathway not only elucidates a previously unrecognized mechanism of β-catenin-mediated regulation of TAM function and phenotype but also presents potential therapeutic targets for intervention.

The optically pumped magnetometer (OPM) based magnetoencephalography (MEG) system offers advantages such as flexible layout and wearability. However, the position instability or jitter of OPM sensors can result in bad channels and segments, which significantly impede subsequent preprocessing and analysis. Most common methods directly reject or interpolate to repair these bad channels and segments. Direct rejection leads to data loss, and when the number of sensors is limited, interpolation using neighboring sensors can cause significant signal distortion and cannot repair bad segments present in all channels. Therefore, most existing methods are unsuitable for OPM-MEG systems with fewer channels. We introduce an automatic bad segments and bad channels repair method for OPM-MEG, called Repairbads. This method aims to repair all bad data and reduce signal distortion, especially capable of automatically repairing bad segments present in all channels simultaneously. Repairbads employs Riemannian Potato combined with joint decorrelation to project out artifact components, achieving automatic bad segment repair. Then, an adaptive algorithm is used to segment the signal into relatively stable noise data chunks, and the source-estimate-utilizing noise-discarding algorithm is applied to each chunk to achieve automatic bad channel repair. We compared the performance of Repairbads with the Autoreject method on both simulated and real auditory evoked data, using five evaluation metrics for quantitative assessment. The results demonstrate that Repairbads consistently outperforms across all five metrics. In both simulated and real OPM-MEG data, Repairbads shows better performance than current state-of-the-art methods, reliably repairing bad data with minimal distortion. The automation of this method significantly reduces the burden of manual inspection, promoting the automated processing and clinical application of OPM-MEG.

Abstract To examine the potential correlation between chemotherapy and the risk of individual of second primary endometrial cancer (SEC) in patients with rectal cancer (RC) and assess survival outcomes. The study employed the Surveillance, Epidemiology, and End Results database (SEER) as the primary data source, it encompasses a substantial cohort of patients diagnosed with RC between 1975 and 2018. This study involved a total of 30,847 individuals diagnosed with RC, of whom 168 individuals (5.45‰) experienced SEC. Among them, 107 patients (3.47‰) received chemotherapy treatment, while 61 patients (1.98‰) did not receive chemotherapy. The analysis of the overall occurrence of SEC revealed a significant association between SEC and chemotherapy treatment. Univariate and multivariate analyses confirmed a significant association between chemotherapy treatment and an increased risk of developing SEC in RC patients. Upon implementation of a dynamic analysis on the variables of relative risk and standardized incidence ratios, the results revealed that the likelihood of SEC escalated in tandem with advancing age. The examination of patients who developed SEC after receiving and not receiving chemotherapy revealed no substantial disparities in the 10-year overall survival (OS) and (cancer-specific survival) CSS rates. The results were the same after propensity score matching. Nevertheless, a notable discrepancy emerged when comparing the OS and CSS rates at 10 years between patients afflicted with SEC subsequent to chemotherapy and those afflicted with primary endometrial cancer, and the result was the same situation in the no-chemotherapy group. The use of chemotherapy in RC patients has been associated with an increased probability of developing specific SEC. Therefore, it is imperative to prioritize efforts aimed at reducing chemotherapy-related SEC occurrences and improving the prognosis of affected individuals.

IntroductionPrevious reviews have often concluded that open-skill sports are more effective at enhancing executive function (EF) than closed-skill sports. However, this conclusion may not hold for closed-skill sports with high cognitive demands, such as golf. This study aimed to compare the effects of football (open-skill) and golf (closed-skill) training on enhancing EF in university students.MethodUsing a quasi-experimental, pre-post test design, 63 male participants were assigned to three groups: football (n = 21), golf (n = 21), and a sedentary control group (n = 21). Over 16 weeks of training, the intervention groups engaged in four 90-min training sessions per week, while the control group attended one 80-min physical education class per week. Assessments were conducted before and after the intervention. EFs, including inhibition control and working memory, were assessed using the Flanker task and Corsi-block tapping task, respectively. Cardiovascular fitness (CRF) was measured by the multi-stage fitness test.ResultsThe golf group showed significant improvements in inhibition control from pre- to post-intervention (p = 0.02, d = 0.26), while the football and control groups did not exhibit significant changes. Post-intervention comparisons indicated no significant differences in EF performance between the golf and football groups; however, both outperformed the control group (golf, p = 0.002, d = 0.99; football, p = 0.01, d = 0.67). No significant improvement was observed in working memory for any group. Additionally, changes in CRF were not significantly correlated with EF performance.ConclusionThis study provides preliminary evidence that golf, a closed-skill sport with high cognitive demands, can effectively improve inhibitory control after 16 weeks of training. This improvement is comparable to that observed in football, an open-skill sport. The findings also suggest that the cognitive demands of the sports, rather than improvements in physical fitness, may be primarily responsible for the enhancements in EF.

BackgroundSplenic littoral cell angioma (LCA) is an exceptionally uncommon malignant potential vascular tumor with infrequent occurrences in pediatric patients. Due to its reliance on histopathological analysis for diagnosis, LCA may be mistakenly identified as other splenic tumors. Patients with LCA may experience anemia or thrombocytopenia, but peripheral blood pancytopenia is infrequent.Case reportA 14-year-old boy presented with peripheral blood pancytopenia, necessitating hospitalization after splenomegaly was identified during a physical examination. Following the exclusion of hematological disorders, a splenectomy was conducted; histopathological examination confirmed the diagnoses of LCA. No metastases or recurrences were observed during the 8-month follow-up. To the best of our knowledge, this case represents the first instance of LCA associated with pancytopenia in a pediatric patient.ConclusionLCA can lead to iron-deficiency anemia or thrombocytopenia, with rare occurrences of pancytopenia, potentially resulting in misdiagnosis as a hematological disorder. Surgical intervention remains an effective treatment for LCA.

This paper proposes a dual-band co-aperture antenna, which covers 2.09–11.61 GHz (9.52 GHz, 138.9%) and 21.6–29.6 GHz (8 GHz, 31%). The overall size of the proposed antenna is 0.76 × 0.76 × 0.37 λ03, where λ0 is the free space wavelength of the lowest operating frequency of 2.09 GHz. By removing the internal metal of the monopole antenna and adding a Vivaldi antenna at the bottom of the bowl monopole antenna, dual-band radiation characteristics can be achieved. A medium polarization converter is used to achieve circular polarization and improve the broadside gain in the high-frequency band. The simulation results show that the antenna has a stable omnidirectional radiation pattern in the low-frequency band and a directional radiation pattern in the high-frequency band.

This article reports the design and experiment of a novel air-assisted nozzle for pesticide application in orchard. A novel air-assisted nozzle was designed based on the transverse jet atomization pattern. This article conducted the performance and deposition experiments and established the mathematical model of volume median diameter (D50) and liquid flow rate with the nozzle design parameters. The D50 of this air-assisted nozzle ranged from 52.45 μm to 113.67 μm, and the liquid flow rate ranged from 142.6 ml/min to 1,607.8 ml/min within the designed conditions. These performances meet the low-volume and ultra-low-volume pesticide application in orchard. The droplet deposition experiment results demonstrated that the droplet coverage distribution in different layers and columns is relatively uniform, and the predicted value of spray penetration (SP) numbers SPiA, SPiB, and SPiC (i = 1, 2, and 3) are approximately 70%, 60%, and 70%, respectively. The droplet deposits on the foliage of the canopy (inside and outside) uniformly bring benefit for plant protection and pesticide saving. Compared with the traditional air-assisted nozzle that adopts a coaxial flow atomization pattern, the atomization efficiency of this air-assisted nozzle is higher. Moreover, the nozzle air pressure and liquid flow rate are considerably lower and greater than the traditional air-assisted nozzle, and these results proved that this air-assisted nozzle has great potential in orchard pesticide application. The relationship between the D50 and nozzle liquid pressure of this air-assisted nozzle differs from that of traditional air-assisted nozzles due to the atomization pattern and process. While this article provides an explanation for this relationship, further study about the atomization process and mechanism is needed so as to improve the performance.

Abstract Purpose Abnormal lower limb movement patterns have been observed during walking in individuals with limited ankle dorsiflexion. The purpose of this study was to investigate the relationships of peak ankle dorsiflexion angle during the stance phase of walking with the lower extremity biomechanics at the corresponding moment and to determine a cutoff value of functional limited ankle dorsiflexion during walking. Methods Kinematic and kinetic data of 70 healthy participants were measured during walking. Spearman's correlation coefficients were calculated to establish the association between peak ankle dorsiflexion and angle and moment of ankle, knee, and hip, ground reaction force, and pelvic movement at peak ankle dorsiflexion. All variables significantly related to peak ankle dorsiflexion were extracted as a common factor by factor analysis. Maximally selected Wilcoxon statistic was used to perform a cutoff value analysis. Results Peak ankle dorsiflexion positively correlated with ankle plantar flexion moment (r = 0.432; p = 0.001), ankle external rotation moment (r = 0.251; p = 0.036), hip extension angle (r = 0.281; p = 0.018), hip flexion moment (r = 0.341; p = 0.004), pelvic ipsilateral rotation angle (r = 0.284; p = 0.017), and medial, anterior, and vertical ground reaction force (r = 0.324; p = 0.006, r = 0.543; p = 0.001, r = 0.322; p = 0.007), negatively correlated with knee external rotation angle (r = −0.394; p = 0.001) and hip adduction angle (r = −0.256; p = 0.032). The cutoff baseline value for all 70 participants was 9.03°. Conclusions There is a correlation between the peak ankle dorsiflexion angle and the lower extremity biomechanics during walking. If the peak ankle dorsiflexion angle is less than 9.03°, the lower limb movement pattern will change significantly.

This is an essay in the field of ceramics and composites. To solve the problems of high-cost for cement cementitious material and low strength of cement filling body at the later stage in a lead-zinc mine, abundant slag solid waste resources were adopted and low-cost slag cementitious materials were developed in this paper to meet the quality requirement of mine fillings. After physical and chemical analysis of tailings, slag and cement clinker, the physical and chemical analysis of tailings, slag and cement clinker was carried out. Then, through the filler slurry slump test and the exploration test of the ratio of slag cementitious material, it is determined that the slurry concentration satisfying the fluidity is about 70%, and the ratio of slag to cement clinker is 2~4. The strength, bleeding rate and coagulation characteristics of filling body with different proportions of slag cementitious materials were investigated by comprehensive test. The results show that the ratio of slag cementitious material is 75%~80% slag and 20%~25% cement clinker, the filling body can meet the filling quality requirements of 0.5 ~3.5 MPa compressive strength and the filling slurry bleeding rate is less than 5%.

A rotary vibration-assisted polishing device (RVAPD) is designed to enhance polishing force by converting PZT’s linear motion into the rotary motion of a central platform via a flexible mechanism, improving material surface quality. The RVAPD is optimized, simulated, and tested to meet high-frequency and large-amplitude non-resonant vibration polishing requirements. Its structure, designed using theoretical models and finite element software, offers a wide range of polishing parameters. Performance parameters are validated through open-loop tests, confirming effectiveness in polishing experiments. The lever mechanism and Hoeckens connection enhance vibration parameters and motion efficiency, reducing surface flaws in SiC and improving uniformity. Adjusting the RVAPD structure and using the proposed method significantly improve SiC surface quality.

This study presents a comprehensive three-dimensional finite element modeling and parametric analysis of composite beam-to-column joints in steel–timber composite structures. The investigation encompassed a variety of shear connector configurations, end plate designs, and bolt dimensions, aiming to elucidate their respective influences on the structural performance and behavior of these joints. Through meticulous numerical simulation, this research sought to enhance the understanding of the interactions and load transfer mechanisms within composite connections, thereby contributing to the optimization of design practices in the field of structural engineering. The load–displacement relationship for timber–steel composite joints subjected to monotonic loading was investigated using ABAQUS 6.14 software. This study systematically analyzed the effects of various parameters, including different configurations of shear connectors, end plate thicknesses, and bolt dimensions, on the overall performance of the joints. Through this comprehensive numerical analysis, the research aimed to provide deeper insights into the mechanical behavior and structural integrity of these composite connections under the applied loading conditions. A non-linear finite element model of timber was developed and verified with the results of the experiment in this study. The findings are discussed in detail, highlighting the intricate relationships between the selected parameters and their respective effects on the performance and overall stability of the composite connections. This thorough evaluation aimed to enhance the understanding of how these variables interact within the context of composite joint design and behavior. Finally, design recommendations for composite structures, such as the dimensions of the bolt, end plate thickness, and different sizes of shear connectors are provided.

ObjectiveAnkle dorsiflexion during walking causes the tibia to roll forward relative to the foot to achieve body forward. Individuals with ankle dorsiflexion restriction may present altered movement patterns and cause a series of dysfunction. Therefore, the aim of this research was to clearly determine the effects of peak ankle dorsiflexion angle on lower extremity biomechanics and pelvic motion during walking and jogging.MethodThis study involved 51 subjects tested for both walking and jogging. The motion capture system and force measuring platforms were used to synchronously collect kinematics and kinetics parameters during these activities. Based on the peak ankle dorsiflexion angle during walking, the 51 subjects were divided into a restricted group (RADF group, angle 10°). Independent-Sample T-tests were performed to compare the pelvic and lower limb biomechanics parameters between the groups during walking and jogging test on this cross-sectional study.ResultsThe parameters that were significantly smaller in the RADF group than in the un-RADF group at the moment of peak ankle dorsiflexion in the walking test were: ankle plantar flexion moment (p

Summary: In natural and engineered environments, iron biocorrosion is an energy reservoir for growth of methanogens. However, how archaea accept electrons from metallic iron remains enigmatic. Here, we report that a Methanothrix-dominated methanogenic community from anaerobic granular sludge can reduce carbon dioxide (CO2) to methane (CH4) via electron uptake from zero-valent iron (ZVI). Through the batch experiments, a maximum CH4 yield of 40.8 ± 0.6 μeequiv/day and an electron recovery from ZVI oxidation to CH4 generation of 69.7% ± 6.1% are observed. Metagenome analysis and inhibition experiments indicate that electrons released by corrosive bacteria are utilized by Methanothrix for accomplishing CO2-to-CH4 conversion via potential intracellular and extracellular electron transfer. The results of activity tests of four electron donors (i.e., ZVI, stainless steel, H2, and acetate) suggest that the ZVI-dependent methanogenesis dominate the overall CH4 generation compared with hydrogenotrophic and acetoclastic methanogenesis, which provides a new insight into autotrophic metabolism of methanogens. Science for society: In natural and engineered environments, biocorrosion of iron is a critical energy reservoir for methanogens. With the increasing utilization of Fe0-containing materials in engineering field, Fe0-dependent methanogenesis is becoming a very important agent for CH4 generation. Generally, methanogens can consume H2 abiotically produced from the Fe0 corrosion. The direct electron uptake from Fe0 by methanogens might also be possible. Although the reliance of microbes on Fe0 has been recognized and known since the 19th century, the mechanisms are still widely debated and, in some cases, poorly understood. Hence, a comprehensive study of Fe0-dependent methanogenesis is expected to uncover the processes of metal corrosion, CH4 generation, and global carbon cycling.

To reduce the friction, wear, and temperature of the piston-cylinder liner friction pair, we designed and processed 27 kinds of bio-inspired textured pistons with cylindrical pits. Based on the experimental optimization design method, friction test, wear test, and thermal imaging test were carried out. Results show that the textured pistons can significantly reduce the friction. Various texture parameters have different effects on the mean friction force. The wear of the textured pistons is significantly less than that of the standard piston. The influence of the texture parameters on piston wear are analyzed through range analysis, regression equation, and 3D response surface method. The standard piston suffers from serious wear and tear. The cylindrical pit texture can supply lubrication and store abrasive particles, which can improve the wear condition of the textured piston surface to a certain extent. The friction heat of the textured pistons is small, which can reduce the average temperature of the friction pair.

The improvement of the steering performance of jet robots is challenging due to single inflexible jet aperture. Scallops provide a potential solution with hard shells and a double-hole jet propulsion, which are expected to achieve fast steering movement under water. Inspired by scallops, a bionic propulsion dynamic mesh is proposed in this article, and a three-dimensional computational model of scallops is established. We further calculated the scallop propulsion mechanism under the swing of shells with different shapes. The coupling of simultaneous swing of two shells and their coupling with velum are presented, revealing the unique movement mechanism of Bivalvia. Based on this, the advantages of the double-hole jet propulsion are applied to develop a scallop robot with excellent steering capabilities. Experiments are conducted to verify the steering performance of the scallop robot.

BackgroundCardiovascular disease (CVD) and cancer are the first and second causes of death in over 130 countries across the world. They are also among the top three causes in almost 180 countries worldwide. Cardiovascular complications are often noticed in cancer patients, with nearly 20% exhibiting cardiovascular comorbidities. Physical exercise may be helpful for cancer survivors and people living with cancer (PLWC), as it prevents relapses, CVD, and cardiotoxicity. Therefore, it is beneficial to recommend exercise as part of cardio-oncology preventive care.ObjectiveWith the progress of deep learning algorithms and the improvement of big data processing techniques, artificial intelligence (AI) has gradually become popular in the fields of medicine and healthcare. In the context of the shortage of medical resources in China, it is of great significance to adopt AI and machine learning methods for prescription recommendations. This study aims to develop an interpretable machine learning-based intelligent system of exercise prescription for cardio-oncology preventive care, and this paper presents the study protocol.MethodsThis will be a retrospective machine learning modeling cohort study with interventional methods (i.e., exercise prescription). We will recruit PLWC participants at baseline (from 1 January 2025 to 31 December 2026) and follow up over several years (from 1 January 2027 to 31 December 2028). Specifically, participants will be eligible if they are (1) PLWC in Stage I or cancer survivors from Stage I; (2) aged between 18 and 55 years; (3) interested in physical exercise for rehabilitation; (4) willing to wear smart sensors/watches; (5) assessed by doctors as suitable for exercise interventions. At baseline, clinical exercise physiologist certificated by the joint training program (from 1 January 2023 to 31 December 2024) of American College of Sports Medicine and Chinese Association of Sports Medicine will recommend exercise prescription to each participant. During the follow-up, effective exercise prescription will be determined by assessing the CVD status of the participants.Expected outcomesThis study aims to develop not only an interpretable machine learning model to recommend exercise prescription but also an intelligent system of exercise prescription for precision cardio-oncology preventive care.EthicsThis study is approved by Human Experimental Ethics Inspection of Guangzhou Sport University.Clinical trial registrationhttp://www.chictr.org.cn, identifier ChiCTR2300077887.

Abstract Background Patients receiving epidural or intrathecal opioids administration for neuraxial analgesia frequently suffer from an irritating itch. STING (stimulator of interferon genes), an innate immune modulator, is strongly implicated in pain pathogenesis via neuron-immune modulation. Given that pain and itch share some common neurocircuits, we evaluate the therapeutic potential of STING agonists in opioid-induced itch and chronic itch. Methods Opioids (morphine, fentanyl and sufentanil) were intrathecally injected to induce acute itch. Chronic itch was induced by dry skin and contact dermatitis. Opioids analgesic effect, itch-induced scratching behavior, spinal expression of STING, phosphorylation of TBK1 (tank-binding kinase 1), IRF3 (interferon regulatory factor-3) and ERK (extracellular signal-regulated kinase), as well as production of IFN-α and IFN-β were examined. STING agonists (DMXAA and ADU-S100), TBK1 inhibitor, recombinant IFN-α and IFN-β elucidated the mechanism and treatment of itch. Whole-brain functional connectivity was evaluated using resting-state fMRI. Results We report the primary expression of STING protein by the spinal dorsal horn neurons. Intraperitoneal injection of DMXAA dose-dependently reduces morphine-induced scratch bouts, without impairing morphine antinociception. Simultaneously, DMXAA alleviates fentanyl- and sufentanil-induced itching-like behavior, and chronic scratching behavior caused by dry skin and contact dermatitis. Furthermore, DMXAA drastically increases spinal phosphorylation of TBK1 and IRF3 following morphine exposure, dry skin and contact dermatitis. DMXAA-induced anti-pruritus effects and spinal productions of IFN-α and IFN-β are compensated by intrathecal delivery of the TBK1 inhibitor. Also, ADU-S100, recombinant IFN-α and IFN-β exhibits remarkable attenuation in scratching behaviors after morphine injection and dermatitis. Recombinant IFN-α inhibits morphine-induced spinal phosphorylation of ERK. Finally, DMXAA prevents dermatitis-induced the increase of cerebral functional connectivity between regions of interests such as primary somatosensory cortex, piriform cortex, retrosplenial cortex, colliculus and ventral thalamus. Conclusions STING activation confers protection against opioid-induced itch and chronic itch through spinal up-regulation of TBK1-IRF3-type I interferon cascades in mice, suggesting that STING agonists are promising candidates in translational development for pruritus relief.

ABSTRACTCulture is the core factor of corporate innovation, and board culture is the core embodiment of cultural factors in corporate governance. Board culture will have an important impact on corporate innovation, So what kind of board culture can Chinese boards build to better contribute to corporate innovation? Based on this core issue, this paper empirically explores the relationship between board authority culture, board cultural diversity and corporate innovation from the unique perspective of board culture. The results show that board authority culture is negatively related to corporate innovation; board cultural diversity can negatively regulate the relationship between board authority culture and corporate innovation, that is, the construction of diverse board culture of the Chinese board is more conducive to corporate innovation. The main reason why board authority culture inhibits corporate innovation is that board authority culture has obedience effect and inhibits corporate innovation through the path of increasing agency costs and weakening management risk preferences. Further research finds that the negative moderating effect of board culture diversity on the relationship between board authority culture and corporate innovation is more effective when the chairman has the highest authority directorship and has reputation authority but not political resource authority and organisation authority.

Endothelin receptors (ETAR and ETBR) are critical for vasoregulation and are targets for cardiovascular diseases treatment. Here, the authors offer a structural basis for peptide recognition selectivity and activation of both endothelin receptors.

The synergistic catalysis of dual metal sites is vital for selective activation of complicated chemical bonds in biomass compounds. The base-free selective oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-furandicarboxylic acid (FDCA) using air as oxidant and water as solvent is a highly sustainable upgrading process for cellulosic carbohydrates. In this work, a series of PtxRu-MgAlO (x = 0.5, 1, 2 and 3, in mole) nanocatalysts with controlled particle sizes (ca. 2 nm) were synthesized by a PVP-assisted adsorption method. The Pt2Ru-MgAlO catalyst showed 99% selectivity of FDCA with full conversion of HMF at only 100 °C under 0.2 MPa of air. In the meantime, an initial reaction rate of HMF of 2.8 mmol molM−1 s−1 and an intrinsic turnover frequency of 61.5 h−1 were attained, respectively. Besides, this catalyst exhibited superior stability during five consecutive reuses without metal leaching. It was disclosed that the Pt-Ru interaction played critical roles in determining the intrinsic activity and the CO bond activation of the prepared PtxRu-MgAlO catalysts. Kinetic experiments combined with in situ chemisorption techniques clearly unraveled adsorption and activation processes of CO bond on Pt0-Ru0 sites. To the best of our knowledge, this work firstly reported a PtRu bimetallic catalyst for aerobic oxidation of HMF and provided insight into synergistic catalysis.

Objective: The prediction of upcoming circular walking during linear walking is important for the usability and safety of the interaction between a lower limb assistive device and the wearer. This study aims to build a bilateral elimination rule-based finite class Bayesian inference system (BER-FC-BesIS) with the ability to predict the transition between circular walking and linear walking using inertial measurement units. Methods: Bilateral motion data of the human body were used to improve the recognition and prediction accuracy of BER-FC-BesIS. Results: The mean predicted time of BER-FC-BesIS in predicting the left and right lower limbs’ upcoming steady walking activities is 119.32 ± 9.71 ms and 113.75 ± 11.83 ms, respectively. The mean time differences between the predicted time and the real time of BER-FC-BesIS in the left and right lower limbs’ prediction are 14.22 ± 3.74 ms and 13.59 ± 4.92 ms, respectively. The prediction accuracy of BER-FC-BesIS is 93.98%. Conclusion: Upcoming steady walking activities (e.g., linear walking and circular walking) can be accurately predicted by BER-FC-BesIS innovatively. Significance: This study could be helpful and instructional to improve the lower limb assistive devices’ capabilities of walking activity prediction with emphasis on non-linear walking activities in daily living.

Temperature increasing heating combined with vacuum preloading is a new sludge dewatering and consolidation technology, and relevant field experimental research has not been carried out. The Baiyangdian sediments are taken as the research object in this study, an intermittent temperature mass phase change vaporizer combined with vacuum preloading is used to conduct field experimental research on sludge dewatering and consolidation. The technical principle of temperature increasing heating combined with vacuum preloading is expounded from the aspects of thermodynamics and osmotic consolidation theory, and the treatment effect is compared with conventional vacuum preloading. The results show that the technology of warming and heating combined with vacuum preloading can greatly improve the consolidation settlement of sediments. The volume compression rate is about 3 times that of the conventional vacuum preloading, the water content of the sediments is 34.59%, which is 18.6% lower than that of the conventional vacuum preloading, the strength of vane is about 2 times higher, and the degree of consolidation after 61 d of treatment is 83.3% to 85.4%. However, there is uneven settlement on the surface of sediments after treatment, showing that the farther away from the warming device on the plane, the smaller the settlement. According to the effective stress theory of saturated soil, the closer to the temperature increasing device, the faster the pore water pressure dissipates. When the temperature increasing heating stops, the pore water pressure has an obvious rebound phenomenon. The closer to the temperature increasing device, the greater the rebound, which is mainly related to the buried depth, loading time and temperature loading mode of the temperature increasing device. At the same time, according to the variation law of sediment moisture content and settlement, it is preliminarily determined that the effective radius of the temperature increasing device is 2 m to 3 m. The results may provide technical guidance for the engineering application of this technology.

This study proposes a parabolic off-axis reflective optical system design method to reduce the wave aberration of the optical system of a large aperture single star simulator and improve the optical system’s imaging quality. Firstly, we determined the design indexes of the optical system of the large aperture single star simulator by analyzing the technical indexes of the star sensitizer and the development status of the single star simulator; secondly, the initial structural parameters of the optical system were calculated based on the theory of primary aberration; then, we carried out the design optimization of the optical system, the image quality evaluation, and the tolerance analysis using Zemax software; finally, the study tested the wave aberration of the optical system by using the four-dimensional interferometer and the standard mirror together. The simulation results of the optical system are as follows: in the entire field of view, the aberration of the optical system is far less than 0.002%, the modulation transfer function (MTF) reaches the diffraction limit, and the maximum wave aberration is 0.0324 λ. The experimental results are as follows: the maximum wave aberration of the optical system is 0.0337 λ, which is less than 1/25 λ, and it meets the requirements of the index. The simulation and experimental results show that the optical system of the large aperture single star simulator designed by this method has good imaging quality and a simple system structure.

Silicon carbide particle-reinforced aluminum matrix composites (SiCp/Al) find diverse applications in engineering. Nevertheless, SiCp/Al exhibit limited machinability due to their special structure. A pulsed laser ultrasonic vibration assisted cutting (PLUVAC) method was proposed to enhance the machining characteristics of SiCp/Al and decrease surface defects. The finite element model was constructed, considering both the thermal effect of the pulsed laser and the location distribution of SiC particles. The model has been developed to analyze the damage forms of SiC particles and the formation mechanisms for the surface morphology. The influence of pulsed laser power on average cutting forces has also been analyzed. Research results indicate that PLUVAC accelerates the transition from the brittleness to the plastic of SiC particles, which helps to reduce surface scratching caused by fragmented SiC particles. Furthermore, the enhancement of surface quality is attributed to the decrease in surface cracks and the beneficial coating effect of the Al matrix. The accuracy of the simulation is verified by experiments, and the feasibility of PLUVAC method to enhance the surface quality of SiCp/Al is confirmed.

Deep learning for predicting the electronic-structure Hamiltonian of quantum systems necessitates satisfying the covariance laws, among which achieving SO(3)-equivariance without sacrificing the non-linear expressive capability of networks remains unsolved. To navigate the harmonization between SO(3)-equivariance and expressiveness, we propose HarmoSE, a deep learning method synergizing two distinct categories of neural mechanisms as a two-stage encoding and regression framework. The first stage corresponds to group theory-based neural mechanisms with inherent SO(3)-equivariant properties prior to the parameter learning process, while the second stage is characterized by a non-linear 3D graph Transformer network we propose, featuring high capability on non-linear expressiveness. Their combination lies in the point that, the first stage predicts baseline Hamiltonians with abundant SO(3)-equivariant features extracted, assisting the second stage in empirical learning of equivariance; and in turn, the second stage refines the first stage’s output as a fine-grained prediction of Hamiltonians using powerful non-linear neural mappings, compensating for the intrinsic weakness on non-linear expressiveness capability of mechanisms in the first stage. Our method enables precise, generalizable predictions while capturing SO(3)-equivariance under rotational transformations, and achieves state-of-the-art performance in Hamiltonian prediction tasks under multiple mean absolute error (MAE) metrics, such as the average MAE across all samples and matrix elements, the MAE for challenging samples, the MAE for different Hamiltonian blocks, and the MAE for the challenging blocks. It also demonstrates significant improvements in accuracy for downstream quantities, such as occupied orbital energy and the electronic wavefunction, as measured by MAE and cosine similarity, respectively.

A magnetically recoverable RuCo bimetallic catalyst was reported for the catalytic hydrogenation of furfural to furfuryl alcohol under ambient H2 pressure. The magnetic catalyst was prepared by H2 treatment of the RuCo composite precursor from a facile one-pot hydrolysis of Co and Ru salts by NaBH4 solution. This catalyst can totally convert furfural to 98–100% furfuryl alcohol at 120 °C under 1 bar H2 in isopropanol or water using only molecular H2 as hydrogen source. Moreover, the catalyst showed excellent stability during recycling test and can be easily and completely recovered by magnet from reaction solution. The influence of Ru/Co ratio and H2-treatment temperature was studied, which were shown to be important for the structural evolution and the metal interaction in RuCo active sites, based on the comprehensive characterizations including XRD, TGA, TEM, XPS, H2-TPR, CO adsorbed DRIFT-IR. It was demonstrated that the cooperative Ru0–Co0 bimetallic active sites in strong interaction can significantly promote activity and selectivity of the catalyst due to an enhanced adsorption and activation of furfural and H2, and simultaneously created a strong magnetism in the RuCo catalyst for simple physical separation.

Abstract Background More than one-third of the total world population is infected by Toxoplasma gondii (T. gondii). T. gondii has been linked to various diseases, such as cancer, mental disorders, type 2 diabetes mellitus (T2DM), etc. However, the effects of T. gondii infection on the risk of osteoporosis are unclear. Our study aimed to uncover evidence to determine whether patients exposed to T. gondii have an increased or decreased risk of osteoporosis in people with abnormal bone mineral density (BMD) by using case–control study. Methods A total of 729 patients, including 316 osteopenia and 413 osteoporosis patients of Han Chinese ancestry were selected in the study. Their blood samples were collected and the levels of specific IgG antibodies against T. gondii were measured using ELISA assay. We obtained some information about the patients from the medical record that included demographic indexes and clinical data. A logistic regression analysis was used to evaluate the effects of T. gondii infection on femur osteoporosis, lumbar osteoporosis and compound osteoporosis. Potential interaction was analyzed using multifactor dimensionality reduction software 1.0.0 (MDR 1.0.0). Results 113 positive patients with T. gondii infections have been detected, including 80 cases of osteoporosis and 33 cases of osteopenia, the infection rates of T. gondii were 19.37% (80/413) and 10.44% (33/316), respectively. The patients with T.gondii infections were at a 2.60 times higher risk of suffering from compound osteoporosis than those without T. gondii infections (OR = 2.60, 95% CI 1.54–4.39, P

IntroductionIncorporation of transversus abdominis plane (TAP) block into multimodal analgesia has been emphasized in Enhanced Recovery protocols (ERPs). However, benefit is limited in clinical practice. A potential explanation is the short duration of analgesia of standard local anesthetics. Herein, this randomized, double-blind, controlled trial evaluated whether TAPB with long-acting compound lidocaine hydrochloride injection reduces postoperative pain.Methods164 patients undergoing elective gynecological laparotomy under sevoflurane anesthesia randomly received ultrasound-guided TAP block with either saline, or ropivacaine, or compound lidocaine before anesthesia induction. The postoperative pain intensity (primary outcome) was evaluated by pain 11-point numerical rating scale. We also recorded sufentanil consumptions, time to first flatus, side-effects and hospital stay after surgery.ResultsWe reported that pain scores at rest at postoperative 3h in group 0.375% ropivacaine was lower than that in group saline [mean 2.4 (SD 1.2) vs. 3.0 (1.0), p = 0.036]. Compared with saline, 0.4% and 0.6% compound lidocaine caused lower pain scores at rest at postoperative 12h [2.8 (0.9) vs. 2.1 (0.9) and 2.0 (0.9), p = 0.016 and p = 0.006]. Sufentanil usage for the first postoperative 48h was lower in group 0.6% compound lidocaine than group saline [24.2 (5.4) vs. 45.6 (7.5) µg, p

Intraoperative remifentanil infusion may paradoxically induce post-surgical hyperalgesia. Dexmedetomidine reportedly reduces opioid-induced hyperalgesia. Nalmefene selectively reverses several side-effects of opioids without impairing analgesia. Herein, this randomized, double-blind controlled trial investigated whether nalmefene, dexmedetomidine, and both drugs combined prevent remifentanil-induced hyperalgesia. One hundred and fifty patients undergoing elective laparoscopic gynecological surgery under desflurane anesthesia randomly received either intraoperative sufentanil 0.20 μg kg−1 (Group S), or remifentanil 0.20 μg kg−1 min−1 (Group R), or remifentanil and pre-anesthesia nalmefene 0.20 μg kg−1 (Group N), or remifentanil and pre-anesthesia dexmedetomidine 0.50 μg kg−1 (Group D), or remifentanil and the combination of dexmedetomidine 0.25 μg kg−1 and nalmefene 0.10 μg kg−1 (Group DN). The threshold of postoperative mechanical hyperalgesia (primary outcome) was measured with von Frey filaments. We also recorded pain intensity, analgesic consumptions, hyperalgesic area, and side-effects for 24 h postoperatively. Compared with Group S, remifentanil reduced hyperalgesic threshold on the forearm [mean 89.4 (SD 13.7) vs. 62.2 (10.7) g, p < 0.001] at postoperative 24 h. Pain threshold on the forearm at postoperative 24 h was significantly lower in Group R than in Groups N, D and DN [62.2 (10.7) vs. 71.1 (12.3), 72.4 (12.9) and 78.0 (13.8) g]. Compared with Group R, Postoperative pain intensity, analgesic consumption and hyperalgesic area were lower likewise in Groups D and DN. However, the incidence of intraoperative bradycardia was lower and post-anesthesia recovery time was shorter in Group DN than Group D. Preoperative therapy of dexmedetomidine and nalmefene combined attenuates postoperative hyperalgesia in patients undergoing laparoscopic gynecological surgery under desflurane-remifentanil anesthesia.

To improve the friction and wear performance of the piston-cylinder liner friction pair, inspired by earthworms and leeches, 27 kinds of pistons with cylindrical pit arrays are designed and processed. Through a friction test, four superior textured pistons are optimized, and wear, life and thermal imaging tests are performed. Finite element analysis of the friction pair model is performed, and the friction and wear mechanisms are discussed. The results show that the pistons with cylindrical pit arrays have excellent friction and wear performance, less heat generation by friction, longer lives and less scratches on the cylinder liner. The temperature of the optimized textured pistons was reduced by around 5–10 °C. The wear amount of some textured pistons was reduced by over 50%, resulting in an improvement in their lifespan of at least 30% or more. The results of the finite element analysis indicate that the textured piston exhibited reduced deformation and favorable stress–strain distribution and satisfied the required contact pressure.

Brain function networks (BFN) are widely used in the diagnosis of electroencephalography (EEG)-based major depressive disorder (MDD). Typically, a BFN is constructed by calculating the functional connectivity (FC) between each pair of channels. However, it ignores high-order relationships (e.g., relationships among multiple channels), making it a low-order network. To address this issue, a novel classification framework, based on matrix variate normal distribution (MVND), is proposed in this study. The framework can simultaneously generate high-and low-order BFN and has a distinct mathematical interpretation. Specifically, the entire time series is first divided into multiple epochs. For each epoch, a BFN is constructed by calculating the phase lag index (PLI) between different EEG channels. The BFNs are then used as samples, maximizing the likelihood of MVND to simultaneously estimate its low-order BFN (Lo-BFN) and high-order BFN (Ho-BFN). In addition, to solve the problem of the excessively high dimensionality of Ho-BFN, Kronecker product decomposition is used for dimensionality reduction while retaining the original high-order information. The experimental results verified the effectiveness of Ho-BFN for MDD diagnosis in 24 patients and 24 normal controls. We further investigated the selected discriminative Lo-BFN and Ho-BFN features and revealed that those extracted from different networks can provide complementary information, which is beneficial for MDD diagnosis.

Aerodynamic heating of spinning flight vehicles have critical military applications such as flight testing, location tracking, stealth, and thermal protection. Based on the numerical method which is verified to be effective in the wind tunnel tests, this article discusses the aerodynamic thermal characteristics of a spinning winged projectile. Firstly, a 6-DOF trajectory model is established to demonstrate the motional behaviors. Partial flight data in supersonic, transonic, and subsonic regimes are separately defined as the inflow conditions. After that, thermo-fluid characteristics are compared between spin and non-spin. When the spin angular velocity is considered, a striking swirling flow phenomenon in the flow field, which result in the streamlines near the tail wings interfere with each other. Meanwhile, the impacts of the shear flow, trailing vortex and turbulent fluctuation are conspicuous. Besides, demonstrating the asymmetry of the temperature due to the flow deflection on the windward and leeward sides of the tail wings. Aerodynamic thermal differences on the surface of the tail wings are remarkable, especially at the tip of the wings. Therefore, the effects of spinning process on aerodynamic heating of winged vehicles cannot be ignored, particularly in supersonic flow at high Mach number.

Hybrid design is an effective approach to construct functional mechanical metamaterials. In this study, a periodic hybrid method for the TPMS (triply periodic minimal surface) structures is proposed, maintaining the original surface connectivity and structural strength. It is implemented by the combination of implicit function Ψ(x,y,z) and transition function ηx,y,z of the TPMS governing equation. Furthermore, three classical TPMS, i.e., P (Schwarz Primitive), IWP (Schoen I-WP) and FRD (Schoen F-RD), are represented to study the elastic properties of hybridizations using FE (Finite Element) computational method and experiments. Through the RVE-based (Representative Volume Element) homogenization method, it is demonstrated how hybridization of TPMS expands the designable range of elastic modulus. In addition, the elastic properties of the hybridizations, such as axial modulus, diagonal modulus and anisotropy, etc., can be quantificationally tailored by turning the formal parameters of TPMS. This study can be considered as a foundational contribution for the advancement of hybrid TPMS metamaterials.

BackgroundImmune checkpoint inhibitors (ICIs) have emerged as a promising treatment option for advanced non-small-cell lung cancer (NSCLC) patients, highlighting the need for biomarkers to identify responders and predict the outcome of ICIs. The purpose of this study was to evaluate the predictive value of baseline standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) derived from 18F-FDG-PET/CT in advanced NSCLC patients receiving ICIs.MethodsPubMed and Web of Science databases were searched from January 1st, 2011 to July 18th, 2022, utilizing the search terms “non-small-cell lung cancer”, “PET/CT”, “standardized uptake value”, “metabolic tumor volume”, “ total lesion glycolysis”, and “immune checkpoint inhibitors”. Studies that analyzed the association between PET/CT parameters and objective response, immune-related adverse events (irAEs) and prognosis of NSCLC patients treated with ICIs were included. We extracted the hazard ratio (HR) with a 95% confidence interval (CI) for progression-free survival (PFS) and overall survival (OS). We performed a meta-analysis of HR using Review Manager v.5.4.1.ResultsSixteen studies were included for review and thirteen for meta-analysis covering 770 patients. As for objective response and irAEs after ICIs, more studies with consistent assessment methods are needed to determine their relationship with MTV. In the meta-analysis, low SUVmax corresponded to poor PFS with a pooled HR of 0.74 (95% CI, 0.57-0.96, P=0.02). And a high level of baseline MTV level was related to shorter PFS (HR=1.45, 95% CI, 1.11-1.89, P

Chronic pain after bone fracture and orthopedic surgery is often refractory to most analgesics currently in use, thus emphasizing the urgent need for improved therapeutic medications. Chemokine-dependent neuroinflammation is critical for excitatory synaptic plasticity and central nociception sensitization. Recent studies have focused on the inhibition of inflammatory responses by artesunate, the first anti-malaria drug extracted from artemisinin. The present study investigated the analgesic effects and potential targets of artesunate in a mouse model of chronic pain induced by tibial fracture and orthopedic surgery. Three injections of artesunate were intrathecally administered on a daily basis from days 4 to 6 after fracture. We reported that repetitive exposure to artesunate (10 and 100 μg but not 1 μg) dose-dependently prevented fracture-induced mechanical and cold allodynia. Moreover, single intrathecal injection of artesunate (100 μg) alleviated the established chronic pain on day 14 after fracture surgery. Intraperitoneal artesunate (10 and 50 mg kg−1) therapy was effective against chronic fracture pain. Intriguingly, artesunate inhibited the upregulation of spinal chemokine CCL21, triggering receptor expressed on myeloid cells 2 (TREM2) and DNAX-activating protein of 12 kDa (DAP12) expressions and microglia activation in fracture mice. Furthermore, spinal CCL21 neutralization attenuated the severity of fracture-associated post-surgical pain. Exogenous CCL21-induced acute inflammatory pain was impaired by artesunate therapy. Additionally, the pharmacological blockage of TREM2 reduced recombinant CCL21-elicited behavioral hypernociception. The present findings demonstrate that artesunate therapy reduces the initiation and maintenance of fracture-associated chronic postoperative pain by inhibiting CCL21-dependent TREM2/DAP12 inflammatory signaling and microglia activation, thus suggesting that artesunate could emerge as a therapeutic strategy for fracture pain management.

AbstractPre-trained language representation models (PLMs) cannot well capture factual knowledge from text. In contrast, knowledge embedding (KE) methods can effectively represent the relational facts in knowledge graphs (KGs) with informative entity embeddings, but conventional KE models cannot take full advantage of the abundant textual information. In this paper, we propose a unified model for Knowledge Embedding and Pre-trained LanguagERepresentation (KEPLER), which can not only better integrate factual knowledge into PLMs but also produce effective text-enhanced KE with the strong PLMs. In KEPLER, we encode textual entity descriptions with a PLM as their embeddings, and then jointly optimize the KE and language modeling objectives. Experimental results show that KEPLER achieves state-of-the-art performances on various NLP tasks, and also works remarkably well as an inductive KE model on KG link prediction. Furthermore, for pre-training and evaluating KEPLER, we construct Wikidata5M1 , a large-scale KG dataset with aligned entity descriptions, and benchmark state-of-the-art KE methods on it. It shall serve as a new KE benchmark and facilitate the research on large KG, inductive KE, and KG with text. The source code can be obtained from https://github.com/THU-KEG/KEPLER.

Believing as a fundamental mental process influences other cognitive/affective processes and behavior. However, it is unclear whether believing engages distinct neurocognitive mechanisms in people with different cultural experiences. We addressed this issue by scanning Chinese and Danish adults using functional MRI during believing judgments on personality traits of oneself and a celebrity. Drift diffusion model analyses of behavioral performances revealed that speed/quality of information acquisition varied between believing judgments on positive and negative personality traits in Chinese but not in Danes. Chinese adopted a more conservative strategy of decision-making during celebrity- than self-believing judgments whereas an opposite pattern was observed in Danes. Non-decisional processes were longer for celebrity- than for self-believing in Danes but not in Chinese. Believing judgments activated the medial prefrontal cortex (mPFC) in both cultural groups but elicited stronger left anterior insular and ventral frontal activations in Chinese. Greater mPFC activity in Chinese was associated with longer duration of non-decision processes during believing-judgments, which predicted slower retrieval of self-related information in a memory test. Greater mPFC activity in Danes, however, was associated with a less degree of adopting a conservative strategy during believing judgments, which predicted faster retrieval of self-related information. Our findings highlight different neurocognitive processes engaged in believing between individuals from East Asian and Western cultures.

Small objects detection is a challenging task in computer vision due to the limited semantic information that can be extracted and the susceptibility to background interference. In this paper, we propose a decoupled multi-scale small object detection algorithm named DMS-YOLOv5. The algorithm incorporates a receptive field module into the feature extraction network for better focus on low-resolution small objects. The coordinate attention mechanism, which combines spatial and channel attention information, is introduced to reduce interference from background information and enhance the network’s attention to object information. A detection layer tailored to small-sized objects is added to compensate for the loss of small object information in multiple downsampling operations, greatly improving the detection capability of small objects. Next, The decoupled network is introduced into the detection head network for branch processing of classification and bounding box regression tasks. Finally, the bounding box loss function is improved to alleviate missed detection problems caused by the concentration of small objects and mutual occlusion between objects. The improved method achieved a mean average precision improvement of 12.1% on VisDrone2019-DET dataset compared to the original method. In comparison experiments with similar methods, our proposed method also demonstrated good performance, validating its effectiveness.

Electrocatalytic nitrate reduction into ammonia is promising for its restricted activity and selectivity in wastewater treatment, however, it remains challenging. In this work, Co3O4 nanosheet electrodes with rich oxygen vacancies (OVs) (Co3O4−x/NF) are prepared and then applied as efficient catalysts for selective electrocatalytic reduction of nitrate to ammonia. The resulting Co3O4−x/NF electrodes exhibit high NO3−-N removal efficiency and NH4+-N selectivity, at 93.7% and 85.4%, respectively. X-Ray photoelectron spectroscopy (XPS) and electron paramagnetic resonance spectra (EPR) results clearly reveal the formation of OVs in Co3O4−x/NF. The electrochemical characterization results confirm that OVs can effectively improve electron transfer as well as the electrochemically active area. The Co2+/Co3+ ratio of Co3O4−x/NF increases after the electrocatalytic reduction of nitrate, highlighting the crucial role played by Co2+ in mediating ammonia production via the Co2+/Co3+ cycle. These findings offer valuable guidelines for the development of more efficient and sustainable approaches for nitrate-contaminated wastewater treatment and ammonia synthesis.

Objectives: The objective of the study is to examine the relationship among physical literacy, mental health, and resilience in college students.Methods: The study is a cross-sectional study. Participants (N = 5,265; 46.6% males) completed perceived physical literacy instruments, mental health continuum short forms, and the 12-item child and youth resilience measures. Mediation models were applied to explore the association among three concepts.Results: Physical literacy, resilience, and mental health were significantly linked with each other. In the mediation model, the direct effect of physical literacy on mental health was 0.49. The indirect effect of physical literacy on mental health through the mediation of resilience was 0.97. The mediating effect of resilience accounts for 66.30% of the total effect, indicating the partial mediating effect of resilience in the relationship between physical literacy and mental health. In more detailed models, resilience was found to mediate the relationship between physical literacy and social and psychological wellbeing, accounting for 61.02% and 56.92% of the total effect, respectively. In addition, resilience acted as full mediator in the relationship between physical literacy and emotional wellbeing (>100%). These findings suggest that physical literacy increases mental health by improving resilience.Conclusions: This is the first time to connect physical literacy with mind factors. The mediating effect of resilience on the relationship between physical literacy and mental health was found. Our findings support the development of physical literacy in universities as part of a holistic approach to supporting the wellbeing and mental health of undergraduates. This study provides a new perspective for the development of large-scale interventions in the health of body and mind in college students.

Abstract Traditional network intrusion detection methods lack the ability of automatic feature extraction for encrypted network malicious traffic, and thus, the detection rates are low. Moreover, the means of this malicious traffic are concealed, and the key malicious features are usually hidden in many normal data packets, so fewer encrypted malicious traffic samples can be captured. This easily leads to insufficient system training, low detection rate, and high false alarm rate. This letter proposes an encrypted network malicious traffic detection model based on deep learning, in which automatic feature extraction is performed against encrypted network malicious traffic. The proposed model has self‐learning and self‐adaption abilities. Furthermore, a sample generation method of encrypted traffic based on deep Q‐networks and deep convolution generative adversarial networks is proposed, in which new samples are learned from the training samples of encrypted traffic and solves problems, such as insufficient original training samples and unbalanced samples. In a validation experiment, the proposed model could distinguish between normal and abnormal encrypted network traffic, and the accuracy rate reached 99.94%. Experimental results show that the proposed model in this letter can provide a new and better solution for an encrypted network malicious traffic detection system.

This study analyzes an office building located in Hangzhou, Zhejiang region, with a high assembly rate of 96.8%. Based on whole-process records and first-hand factory data, using an original method, we empirically investigate the carbon emissions associated to the assembly production and construction phase by comparing the results collected in the field with the calculation results for the simulated non-prefabricated building. The calculation results show that the production and construction stage of the prefabricated office building is characterized by a large reduction in carbon emissions, where the total measured carbon emissions of the subject building were 2265.73 tCO2e, which is 22 kgCO2e/m2 less than that under the non-prefabricated method. In the future development of China’s construction industry, taking Zhejiang Province as an example, the implementation of prefabricated office buildings with a PEC structure system can effectively reduce carbon emissions, which can help China to achieve the carbon peak as soon as possible.

Articular cartilage is a collagen-rich tissue that provides a smooth, lubricated surface for joints and is also responsible for load bearing during movements. The major components of cartilage are water, collagen, and proteoglycans. Osteoarthritis is a degenerative disease of articular cartilage, in which an early-stage indicator is the loss of proteoglycans from the collagen matrix. In this study, confocal Raman microspectroscopy was applied to study the degradation of articular cartilage, specifically focused on spatially mapping the loss of glycosaminoglycans (GAGs). Trypsin digestion was used as a model for cartilage degradation. Two different scanning geometries for confocal Raman mapping, cross-sectional and depth scans, were applied. The chondroitin sulfate coefficient maps derived from Raman spectra provide spatial distributions similar to histological staining for glycosaminoglycans. The depth scans, during which subsurface data were collected without sectioning the samples, can also generate spectra and GAG distributions consistent with Raman scans of the surface-to-bone cross sections. In native tissue, both scanning geometries demonstrated higher GAG content at the deeper zone beneath the articular surface and negligible GAG content after trypsin degradation. On partially digested samples, both scanning geometries detected an ∼100 μm layer of GAG depletion. Overall, this research provides a technique with high spatial resolution (25 μm pixel size) to measure cartilage degradation without tissue sections using confocal Raman microspectroscopy, laying a foundation for potential in vivo measurements and osteoarthritis diagnosis.

Epiphytic bacteria on the surfaces of submerged macrophytes play important roles in the growth of the host plant, nutrient cycling, and the conversion of pollutants in aquatic systems. A knowledge of the epiphytic bacterial community structure could help us to understand these roles. In this study, the abundance, diversity, and functions of the epiphytic bacterial community of Myriophyllum spicatum collected from Baiyangdian Lake in June, August, and October 2019 were studied using quantitative PCR (qPCR), high-throughput sequencing, and the prediction of functions. An analysis using qPCR showed that the epiphytic bacteria were the most abundant in October and the least abundant in August. High-throughput sequencing revealed that Proteobacteria, Gammaproteobacteria, and Aeromonas were the dominant phylum, class, and genus in all the samples. The common analyses of operational taxonomic units (OTUs), NMDS, and LDA showed that the epiphytic bacterial communities were clustered together based on the seasons. The results of a canonical correlation analysis (CCA) showed that the key water quality index that affected the changes of epiphytic bacterial community of M. spicatum was the total phosphorus (TP). The changes in abundance of Gammaproteobacteria negatively correlated with the TP. Predictive results from FAPROTAX showed that the predominant biogeochemical cycle functions of the epiphytic bacterial community were chemoheterotrophy, nitrate reduction, and fermentation. These results suggest that the epiphytic bacterial community of M. spicatum from Baiyangdian Lake varies substantially with the seasons and environmental conditions.

The prediction of water inflow during coal mining is an important issue. There are many factors that can affect the water inflow in mines. The intercoupling of these factors makes it difficult for current water inflow forecasting methods to meet the needs of real-time forecasting. Open channels are the main devices used for mine drainage, and their flow rate reflects the water inrush of a mine to some extent. This paper uses a hybrid neural network model combining attention mechanisms and a gated recurrent unit network to make real-time predictions of open channel flow. First, attention mechanisms are used to learn the interdependence between multisource hydrosensor data, and then, a gated recurrent unit network is employed to capture the dependencies on different time scales to improve the prediction accuracy of the neural network model. Finally, we design a series of comparative experiments to verify and analyse the performance of the hybrid neural network model. The experimental verification shows that the proposed model can learn the dependency relationships among multisource sensors, and the modelling of these dependencies can greatly improve the prediction accuracy of real-time flow in open channels.

Online social networks (OSNs) are generally susceptible to Sybil attack, which causes a series of cybersecurity problems and privacy violations. Malicious attackers can create massive Sybils and further utilize those fake identities to launch various Sybil attacks. Therefore, Sybil detection in OSNs has become an urgent security research problem for both academia and industries. The existing content-based methods to detect Sybils base on the combination of manual-design features and machine learning algorithms, which requires lots of professional experiences and human effort. These methods divide the Sybil detection problem into two piece-wise sub-problems, which prevents us from getting the optimal solution. In this work, we propose a novel content-based method to detect Sybils. The proposed method is an end-to-end classification model that extracts features directly from the input data, and then output the classification results in a unified framework. The proposed method includes three main parts: first, the self-normalizing convolutional neural network (CNN) is adopted to extract lower features from the multi-dimensional input data; second, the bidirectional self-normalizing LSTM network (bi-SN-LSTM) is developed to extract higher features from the compressed feature map sequence; third, the dense layer and softmax classifier are stacked to output the classification results. Unlike the traditional bidirectional long short-term memory network (bi-LSTM), the proposed bi-SN-LSTM network utilizes SELU as the activation function of its recurrent step, which provides unbounded changes to the state value. Through the case study of the real-world dataset, the comparison experiments demonstrate that our method significantly outperforms other state-of-the-art methods.

During the present study, a double groove texture was designed on the surface of a piston ring to improve the sealing performance between the piston ring and cylinder liner. The experimental design method was used to fabricate the test plan according to the groove width, depth, and spacing. By using the thermal–structural coupling analysis method, the finite element analysis of the standard piston ring and the textured piston ring was carried out to simulate the deformation state of the cylinder liner system of the piston ring group during the working stroke. The piston rings with different parameters designed by the test scheme were manufactured by wire electrical discharge machining, and the self-made experiment device carried out the sealing test. The results showed that the groove texture could improve the sealing performance of the piston ring, and the analyzed results demonstrated that the groove texture had little effect on the maximum deformation of the piston ring. Still, it could significantly reduce the minimum deformation of the piston ring group. A piston ring with groove texture would improve the sealing performance and reduce the deformation during the work stroke. During the test, the average deformation of the No.7 piston ring group, with a groove depth of 1 mm, a groove width of 0.5 mm, and a groove spacing of 0.1 mm, was the smallest, about 29.6% lower than that of the standard piston ring group. The sealing performance of the No.7 piston ring group was the best, and the reduction rate of the top gas leakage rate was 52.18%. During the present study, the sealing performance of the piston ring was improved by designing the grooved structure on the piston ring surface, thereby improving the fuel economy and power performance of the engine. The present study could provide a reference for the engineering field to design a piston ring with high sealing performance.

In this study, the reduction of the early-age strength of mortar caused by the traditional super absorbent polymer (SAP) was solved. Two types of alkanolamines (Alkanolamine-A and alkanolamine-B) and calcium nitrite were compounded with traditional SAP as early-age strength components and then were added into the mortar to evaluate effects on early-age strength and drying shrinkage. Results showed that adding two types of alkanolamines could significantly improve the early-age compressive strength of mortar. The addition of alkanolamines could refine the pore of cement paste and reduce the average pore size, which can be reflected by the increased strength and improved mortar drying shrinkage. Among them, the mortar with the composite of alkanolamine-A and alkanolamine-B added showed excellent performance. Its mechanical properties increased to 129% at day 3 and 139% at day 7 compared with the reference group; compressive strength can reach up to 31.8 MPa. The average pore size of the cement paste decreased by 27.8%, and the drying shrinkage was significantly smaller compared with the reference group.

In living bodies, pH values, which are precisely regulated and closely associated with diseased cells, can act as an efficient biologically intrinsic indicator for future intelligent biomedicine microsystems. In this work, we have developed flask-like carbonaceous nanomotors (FCNMs), via loading Fe3O4 nanoparticles (NPs) into a cavity, which exhibit a self-adaptive feature to a specific physiological pH by virtue of the pH-dependent dual enzyme-like activities of Fe3O4 NPs. Specifically, the peroxidase-like activity of Fe3O4 NPs in an acidic pH range, and the catalase-like activity in a near neutral and alkaline pH range, determine the products in the motion system (•OH, ions and O2), whose diffusions from the inner to the outside of the flask result in fluid movement providing the driving force for the movement of the FCNMs. Correspondingly, changes of the product concentrations and species in the physiological pH range (4.4–7.4) result, firstly, in velocity decrease and, then, with increase in pH, increase of the FCNMs occurs. Thanks to the non-linear velocity responsiveness, the FCNMs show intriguing pH taxis towards 6.8 (generally corresponding to the physiological pH in tumor microenvironments), where a maximum velocity appears. Furthermore, the superparamagnetic feature of the Fe3O4 NPs simultaneously endows the FCNMs with the abilities to be magnetic-oriented and easily separated. This work could significantly increase the possibility of nanomotors for targeted therapy of tumors and next-generation biotechnological applications.