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Abstract We study a millicharged co-interacting dark matter scenario, where the primary dark matter constituent is the dark photon A′ and the secondary component is the fermion χ. In this model, χ interacts with A′ via a U(1)′ interaction while being millicharged with respect to normal photons. Our investigation focuses on the oscillation of A′ dark matter into photons within the background of χ particles, revealing that the A′ − χ scattering rate benefits from a Bose enhancement of the A′ final state. As the oscillation production rate is directly linked to the scattering rate, the conversion of A′ dark matter into monochromatic photons experiences significant amplification owing to this Bose enhancement, especially when the scattering rate Γsca approaches the dark photon mass m A ′ $$ {m}_{A^{\prime }} $$ . These converted monochromatic photons are detectable through radio telescopes and can induce distortions in the Cosmic Microwave Background (CMB) spectrum. We find that the sensitivity of radio telescopes and the constraints imposed by CMB distortion on the kinetic mixing parameter are notably heightened compared to scenarios without the subdominant millicharged dark matter.

Background The reaserch of artificial intelligence (AI) model for predicting spinal refracture is limited to bone mineral density, X‐ray and some conventional laboratory indicators, which has its own limitations. Besides, it lacks specific indicators related to osteoporosis and imaging factors that can better reflect bone quality, such as computed tomography (CT). Objective To construct a novel predicting model based on bone turn‐over markers and CT to identify patients who were more inclined to suffer spine refracture. Methods CT images and clinical information of 383 patients (training set = 240 cases of osteoporotic vertebral compression fractures (OVCF), validation set = 63, test set = 80) were retrospectively collected from January 2015 to October 2022 at three medical centers. The U‐net model was adopted to automatically segment ROI. Three‐dimensional (3D) cropping of all spine regions was used to achieve the final ROI regions including 3D_Full and 3D_RoiOnly. We used the Densenet 121‐3D model to model the cropped region and simultaneously build a T‐NIPT prediction model. Diagnostics of deep learning models were assessed by constructing ROC curves. We generated calibration curves to assess the calibration performance. Additionally, decision curve analysis (DCA) was used to assess the clinical utility of the predictive models. Results The performance of the test model is comparable to its performance on the training set (dice coefficients of 0.798, an mIOU of 0.755, an SA of 0.767, and an OS of 0.017). Univariable and multivariable analysis indicate that T_P1NT was an independent risk factor for refracture. The performance of predicting refractures in different ROI regions showed that 3D_Full model exhibits the highest calibration performance, with a Hosmer–Lemeshow goodness‐of‐fit (HL) test statistic exceeding 0.05. The analysis of the training and test sets showed that the 3D_Full model, which integrates clinical and deep learning results, demonstrated superior performance with significant improvement (p‐value

Background: Renzhu Jianwei Granula (RJG) is a traditional Chinese medicine compound initially formulated to address precancerous lesions for gastric cancer. The aim of this study was to assess RJG's efficacy in treating precancerous lesions of gastric cancer through a comprehensive meta-analysis of randomized clinical trials. Methods: Two authors separately conducted an exhaustive search across three databases (PubMed, CNKI and Wanfang) without imposing any restrictions on publication year or language. Eligible studies, spanning from the inception of databases to July 18th, 2024, were included. Valid data were summarized and those with a group size of 3 or more were preserved. R software and Cochrane collaboration tools were employed for sensitivity analysis and assessing the quality of the included studies. The data from selected studies were transformed into risk ratios (RRs) and subjected to meta-analysis. This study was prospectively registered in PROSPERO. Results: Data from 9 studies encompassing 912 participants revealed that the RJG group exhibited superior clinical efficacy compared to the control group, with an RR of 0.36 (95 % confidence interval (CI): 0.25 to 0.52). RJG demonstrated enhanced efficacy over the control group in both comprehensive efficacy (RR: 0.42, 95 % CI: 0.31 to 0.55) and gastroscopy efficacy (RR: 0.56, 95 % CI: 0.46 to 0.69). Moreover, significant improvements in pathological features such as atrophy (RR: 0.58, 95 % CI: 0.45 to 0.73), dysplasia (RR: 0.41, 95 % CI: 0.27 to 0.61), and intestinal metaplasia (RR: 0.54, 95 % CI: 0.43 to 0.69) in precancerous lesions of gastric cancer were observed following RJG administration. Conclusion: This study's synthesized data provide compelling evidence of RJG's substantial therapeutic impact in ameliorating symptoms associated with precancerous lesions of gastric cancer. Trial registration number: The study protocol was registered at PROSPERO (CRD42024572606)

Objective: Dementia is an important disease burden among the elderly, and its occurrence may be profoundly affected by environmental factors. Evidence of the relationship between air pollution and dementia is emerging, but the extent to which this can be offset by lifestyle factors remains ambiguous. Methods: This study comprised 155,828 elder adults aged 60 years and above in the UK Biobank who were dementia-free at baseline. Cox proportional hazard models were conducted to examine the associations of annual average levels of air pollutants in 2010, including nitrogen dioxide (NO2), nitrogen oxides (NOX), particulate matter (PM2.5, PM10, and PMcoarse) and lifestyle factors recorded at baseline [physical activity (PA), sleep patterns, or smoking status] with incident risk of dementia, and their interactions on both multiplicative and additive scales. Results: During a 12-year period of follow-up, 4,389 incidents of all-cause dementia were identified. For each standard deviation increase in ambient NO2, NOX or PM2.5, all-cause dementia risk increases by 1.07-fold [hazard ratio (HR) and 95 % confidence interval (CI) = 1.07 (1.04, 1.10)], 1.05-fold (95 % CI: 1.02, 1.08) and 1.07-fold (95 % CI: 1.04, 1.10), whereas low levels of PA, poor sleep patterns, and smoking are associated with an elevated risk of dementia [HR (95 % CI) = 1.17 (1.09, 1.26), 1.13 (1.00, 1.27), and 1.14 (1.07, 1.21), respectively]. Furthermore, these air pollutants show joint effects with low PA, poor sleep patterns, and smoking on the onset of dementia. The moderate to high levels of PA could significantly or marginally significantly modify the associations between NO2, NOX or PM2.5 (P-int = 0.067, 0.036, and 0.067, respectively) and Alzheimer’s disease (AD), but no significant modification effects are found for sleep patterns or smoking status. Conclusion: The increased exposures of NO2, NOX, or PM2.5 are associated with elevated risk of dementia among elderly UK Biobank population. These air pollutants take joint effects with low PA, poor sleep patterns, and smoking on the development of dementia. In addition, moderate to high levels of PA could attenuate the incident risk of AD caused by air pollution. Further prospective researches among other cohort populations are warranted to validate these findings.

Purpose: This study aims to identify the key factors influencing health-related quality of life (HRQoL) of pediatric acute myeloid leukemia (AML) patients following their initial diagnosis and examine their impact on the five-year survival prognosis. Methods: A chart review and follow-up were conducted for children with AML who participated in a prospective cohort study between 2017 and 2020. We identified factors influencing HRQoL through Pediatric Quality of Life Inventory™ (PedsQL™ 4.0), PedsQL™ Cancer Module 3.0 (CM 3.0) and PedsQL™ Family Impact Module 2.0 (FIM 2.0), as well as assessed the impact of impaired HRQoL on the overall outcomes of patients. Results: Sixty-four subjects enrolled in the study had complete HRQoL outcome data, and 61 of them completed the 5-year follow-up. In CM 3.0, age was positively associated with parental proxy reports (p = 0.040), whereas divorced families were negatively associated with child self-reports (p = 0.045). A positive medical history correlates with FIM 2.0 (p = 0.025). Residence (p = 0.046), the occupation of caregivers (p = 0.014), disease severity (p = 0.024), and the only child (p = 0.029) exhibited statistically significant associations with the impairment of HRQoL. Impaired HRQoL scores shown by the PedsQL™4.0 parent proxy report (p = 0.013) and FIM 2.0 (p = 0.011) were associated with a reduced 5-year survival rate. Conclusions: This study demonstrated that early impairment of HRQoL in pediatric acute myeloid leukemia patients has predictive value for long-term prognosis. Once validated, these findings may provide some guidance to clinicians treating children with AML.

Although Federated Deep Learning (FDL) enables distributed machine learning in the Internet of Vehicles (IoV), it requires multiple clients to upload model parameters, thus still existing unavoidable communication overhead and data privacy risks. The recently proposed Swarm Learning (SL) provides a decentralized machine learning approach for unit edge computing and blockchain-based coordination. A Swarm-Federated Deep Learning framework in the IoV system (IoV-SFDL) that integrates SL into the FDL framework is proposed in this paper. The IoV-SFDL organizes vehicles to generate local SL models with adjacent vehicles based on the blockchain empowered SL, then aggregates the global FDL model among different SL groups with a credibility weights prediction algorithm. Extensive experimental results show that compared with the baseline frameworks, the proposed IoV-SFDL framework reduces the overhead of client-to-server communication by 16.72%, while the model performance improves by about 5.02% for the same training iterations.

Abstract Pyroptosis, an inflammatory caspase-dependent programmed cell death, plays a vital role in maintaining tissue homeostasis and activating inflammatory responses. Orthodontic tooth movement (OTM) is an aseptic force-induced inflammatory bone remodeling process mediated by the activation of periodontal ligament (PDL) progenitor cells. However, whether and how force induces PDL progenitor cell pyroptosis, thereby influencing OTM and alveolar bone remodeling remains unknown. In this study, we found that mechanical force induced the expression of pyroptosis-related markers in rat OTM and alveolar bone remodeling process. Blocking or enhancing pyroptosis level could suppress or promote OTM and alveolar bone remodeling respectively. Using Caspase-1 −/− mice, we further demonstrated that the functional role of the force-induced pyroptosis in PDL progenitor cells depended on Caspase-1. Moreover, mechanical force could also induce pyroptosis in human ex-vivo force-treated PDL progenitor cells and in compressive force-loaded PDL progenitor cells in vitro, which influenced osteoclastogenesis. Mechanistically, transient receptor potential subfamily V member 4 signaling was involved in force-induced Caspase-1-dependent pyroptosis in PDL progenitor cells. Overall, this study suggested a novel mechanism contributing to the modulation of osteoclastogenesis and alveolar bone remodeling under mechanical stimuli, indicating a promising approach to accelerate OTM by targeting Caspase-1.

Abstract This study was to develop a computer vision evaluation method to automatically measure the degree of scoliosis based on the machine learning algorithm. For the X-ray images of 204 patients with idiopathic scoliosis who underwent full-spine radiography, histogram equalization of original image was performed before a flipping method was used to magnify asymmetric elements, search for the global maximum pixel value in each line, and scan local maximal pixel value, with the intersection set of two point sets being regarded as candidate anchor points. All fine anchors were fitted with cubic spline algorithm to obtain the approximate curve of the spine, and the degree of scoliosis was measured by the standardized integral area. All measured data were analyzed. In manual measurement, the Cobb angle was 11.70–25.00 (20.15 ± 3.60), 25.20–44.70 (33.89 ± 5.41), and 45.10–49.40 (46.98 ± 1.25) in the mild, moderate and severe scoliosis group, respectively, whereas the value for the standardized integral area algorithm was 0.072–0.298 (0.185 ± 0.040), 0.100–0.399 (0.245 ± 0.050), and 0.246–0.901 (0.349 ± 0.181) in the mild, moderate and severe scoliosis group, respectively. Correlation analysis between the manual measurement of the Cobb angle and the evaluation of the standardized integral area algorithm demonstrated the Spearman correlation coefficient r = 0.643 (P

Abstract Infected bone defects are a major challenge in orthopedic treatment. Native bone tissue possesses an endogenous electroactive interface that induces stem cell differentiation and inhibits bacterial adhesion and activity. However, traditional bone substitutes have difficulty in reconstructing the electrical environment of bone. In this study, we develop a self-promoted electroactive mineralized scaffold (sp-EMS) that generates weak currents via spontaneous electrochemical reactions to activate voltage-gated Ca2+ channels, enhance adenosine triphosphate-induced actin remodeling, and ultimately achieve osteogenic differentiation of mesenchymal stem cells by activating the BMP2/Smad5 pathway. Furthermore, we show that the electroactive interface provided by the sp-EMS inhibits bacterial adhesion and activity via electrochemical products and concomitantly generated reactive oxygen species. We find that the osteogenic and antibacterial dual functions of the sp-EMS depend on its self-promoting electrical stimulation. We demonstrate that in vivo, the sp-EMS achieves complete or nearly complete in situ infected bone healing, from a rat calvarial defect model with single bacterial infection, to a rabbit open alveolar bone defect model and a beagle dog vertical bone defect model with the complex oral bacterial microenvironment. This translational study demonstrates that the electroactive bone graft presents a promising therapeutic platform for complex defect repair.

Abstract Adult tendon stem/progenitor cells (TSPCs) are essential for tendon maintenance, regeneration, and repair, yet they become susceptible to senescence with age, impairing the self-healing capacity of tendons. In this study, we employ a recently developed deep-learning-based efficacy prediction system to screen potential stemness-promoting and senescence-inhibiting drugs from natural products using the transcriptional signatures of stemness. The top-ranked candidate, prim-O-glucosylcimifugin (POG), a saposhnikovia root extract, could ameliorate TPSC senescent phenotypes caused by long-term passage and natural aging in rats and humans, as well as restore the self-renewal and proliferative capacities and tenogenic potential of aged TSPCs. In vivo, the systematic administration of POG or the local delivery of POG nanoparticles functionally rescued endogenous tendon regeneration and repair in aged rats to levels similar to those of normal animals. Mechanistically, POG protects TSPCs against functional impairment during both passage-induced and natural aging by simultaneously suppressing nuclear factor-κB and decreasing mTOR signaling with the induction of autophagy. Thus, the strategy of pharmacological intervention with the deep learning-predicted compound POG could rejuvenate aged TSPCs and improve the regenerative capacity of aged tendons.

In recent decades, cyanobacterial blooms have intensified in many lakes in China. Algal blooms are closely linked to the predation pressure on phytoplankton, but the changes in the relationship between phytoplankton and their primary predators, zooplankton, remain unclear. To investigate the changing patterns and driving factors of the relationship between plankton, the historical data of plankton from 14 typical freshwater lakes around the Yangtze River were collected from multiple databases. By comparing the structure of plankton communities in typical lakes between the 1990s and the 2010s, it was found that the phytoplankton density was elevated in 79% of all the lakes; on average, it had increased to 3156 times higher than it had been. In contrast, the zooplankton density was elevated in only 57% of these lakes, and this value was only two times higher than it had been. In 11 out of the 14 lakes, the zooplankton density growth rate was lower than that of the phytoplankton. The percentage of cyanobacteria in these lakes increased from 53% to 62%, and the changes in cyanobacteria were significantly negatively correlated with the changes in zooplankton. Eutrophication caused this significant increase in phytoplankton, especially cyanobacteria. Cyanobacterialization, changes in fish community structures, biological invasion, and river–lake relationships impede zooplankton survival. This combination of factors hinders plankton coupling in many lakes. This study attempts to provide new insights for lake ecological management.

Camera arrays can enhance the signal-to-noise ratio (SNR) between dim targets and backgrounds through multi-view synthesis. This is crucial for the detection of dim targets. To this end, we design and develop an infrared camera array system with a large baseline. The multi-view synthesis of camera arrays relies heavily on the calibration accuracy of relative poses in the sub-cameras. However, the sub-cameras within a camera array lack strict geometric constraints. Therefore, most current calibration methods still consider the camera array as multiple pinhole cameras for calibration. Moreover, when detecting distant targets, the camera array usually needs to adjust the focal length to maintain a larger depth of field (DoF), so that the distant targets are located on the camera’s focal plane. This means that the calibration scene should be selected within this DoF range to obtain clear images. Nevertheless, the small parallax between the distant sub-aperture views limits the calibration. To address these issues, we propose a calibration model for camera arrays in distant scenes. In this model, we first extend the parallax by employing dual-array frames (i.e., recording a scene at two spatial locations). Secondly, we investigate the linear constraints between the dual-array frames, to maintain the minimum degrees of freedom of the model. We develop a real-world light field dataset called NUDT-Dual-Array using an infrared camera array to evaluate our method. Experimental results on our self-developed datasets demonstrate the effectiveness of our method. Using the calibrated model, we improve the SNR of distant dim targets, which ultimately enhances the detection and perception of dim targets.

Epidemiologic studies have reported the positive relationship of benzo[a]pyrene (BaP) exposure with the risk of lung cancer. However, the mechanisms underlying the relationship is still unclear. Plasma microRNA (miRNA) is a typical epigenetic biomarker that was linked to environment exposure and lung cancer development. We aimed to reveal the mediation effect of plasma miRNAs on BaP-related lung cancer. We designed a lung cancer case-control study including 136 lung cancer patients and 136 controls, and measured the adducts of benzo[a]pyrene diol epoxide-albumin (BPDE-Alb) and sequenced miRNA profiles in plasma. The relationships between BPDE-Alb adducts, normalized miRNA levels and the risk of lung cancer were assessed by linear regression models. The mediation effects of miRNAs on BaP-related lung cancer were investigated. A total of 190 plasma miRNAs were significantly related to lung cancer status at Bonferroni adjusted P 2 between plasma samples before and after tumor resection surgery at Bonferroni adjusted P

Accurate identification of small tea buds is a key technology for tea harvesting robots, which directly affects tea quality and yield. However, due to the complexity of the tea plantation environment and the diversity of tea buds, accurate identification remains an enormous challenge. Current methods based on traditional image processing and machine learning fail to effectively extract subtle features and morphology of small tea buds, resulting in low accuracy and robustness. To achieve accurate identification, this paper proposes a small object detection algorithm called STF-YOLO (Small Target Detection with Swin Transformer and Focused YOLO), which integrates the Swin Transformer module and the YOLOv8 network to improve the detection ability of small objects. The Swin Transformer module extracts visual features based on a self-attention mechanism, which captures global and local context information of small objects to enhance feature representation. The YOLOv8 network is an object detector based on deep convolutional neural networks, offering high speed and precision. Based on the YOLOv8 network, modules including Focus and Depthwise Convolution are introduced to reduce computation and parameters, increase receptive field and feature channels, and improve feature fusion and transmission. Additionally, the Wise Intersection over Union loss is utilized to optimize the network. Experiments conducted on a self-created dataset of tea buds demonstrate that the STF-YOLO model achieves outstanding results, with an accuracy of 91.5% and a mean Average Precision of 89.4%. These results are significantly better than other detectors. Results show that, compared to mainstream algorithms (YOLOv8, YOLOv7, YOLOv5, and YOLOx), the model improves accuracy and F1 score by 5-20.22 percentage points and 0.03-0.13, respectively, proving its effectiveness in enhancing small object detection performance. This research provides technical means for the accurate identification of small tea buds in complex environments and offers insights into small object detection. Future research can further optimize model structures and parameters for more scenarios and tasks, as well as explore data augmentation and model fusion methods to improve generalization ability and robustness.

Abstract Macrophages are involved mainly in the balance between inflammation and tenogenesis during the healing process of tendinopathy. However, etiological therapeutic strategies to efficiently treat tendinopathy by modulating macrophage state are still lacking. In this study, we find that a small molecule compound Parishin-A (PA) isolated from Gastrodia elata could promote anti-inflammatory M2 macrophage polarization by inhibiting gene transcription and protein phosphorylation of signal transducers and activators of transcription 1. Local injection or sustained delivery of PA by mesoporous silica nanoparticles (MSNs) could almost recover the native tendon’s dense parallel-aligned collagen matrix in collagenase-induced tendinopathy by modulating macrophage-mediated immune microenvironment and preventing heterotopic ossification. Especially, MSNs decrease doses of PA, frequency of injection and yield preferable therapeutic effects. Mechanistically, intervention with PA could indirectly inhibit activation of mammalian target of rapamycin to repress chondrogenic and osteogenic differentiation of tendon stem/progenitor cells by influencing macrophage inflammatory cytokine secretion. Together, pharmacological intervention with a natural small-molecule compound to modulate macrophage status appears to be a promising strategy for tendinopathy treatment.

Measurement principle of axis straightness error of cylindrical parts was introduced based on their roundness profiles. The evaluation models of the center coordinates of four kinds of the reference circles were built, and the evaluation models of the axis straightness errors were established by using the least-square and minimum zone criteria. The roundness profiles of eight simulated cylinders, eight holes, and eight shafts were extracted, and their axis straightness errors were evaluated based on the different reference circles and evaluation criteria. The “minimax” issues in the evaluation process of axis straightness errors were be solved by using Equilibrium Optimizer, and its implementation flows were given. Their evaluation results were analyzed under the used reference circles and evaluation criteria. The analysis results showed that both reference circles and evaluation criteria have much influence on the evaluation results, and that among the evaluation results based on the centers’ coordinates of four reference circles and two evaluation criteria, the axis straightness errors evaluated based on the center coordinates of least-square reference circle and the minimum zone criteria is the least one for most of cylindrical parts, the roundness profiles of which may have no singularities, and the differences among the axis straightness errors evaluated on the basis of different reference circles and different evaluation criteria are very large sometimes, which should be noted in checking whether the axis straightness errors of parts are qualified.

Abstract Lead-free tin perovskite solar cells (PSCs) have undergone rapid development in recent years and are regarded as a promising eco-friendly photovoltaic technology. However, a strategy to suppress charge recombination via a built-in electric field inside a tin perovskite crystal is still lacking. In the present study, a formamidinium tin iodide (FASnI3) perovskite absorber with a vertical Sn2+ gradient was fabricated using a Lewis base-assisted recrystallization method to enhance the built-in electric field and minimize the bulk recombination loss inside the tin perovskites. Depth-dependent X-ray photoelectron spectroscopy revealed that the Fermi level upshifts with an increase in Sn2+ content from the bottom to the top in this heterogeneous FASnI3 film, which generates an additional electric field to prevent the trapping of photo-induced electrons and holes. Consequently, the Sn2+-gradient FASnI3 absorber exhibits a promising efficiency of 13.82% for inverted tin PSCs with an open-circuit voltage increase of 130 mV, and the optimized cell maintains over 13% efficiency after continuous operation under 1-sun illumination for 1,000 h.

Abstract Background White matter hyperintensity (WMH) is one of the typical neuroimaging manifestations of cerebral small vessel disease (CSVD), and the WMH correlates closely to cognitive impairment (CI). CSVD patients with WMH own altered topological properties of brain functional network, which is a possible mechanism that leads to CI. This study aims to identify differences in the characteristics of some brain functional network among patients with different grades of WMH and estimates the correlations between these different brain functional network characteristics and cognitive assessment scores. Methods 110 CSVD patients underwent 3.0 T Magnetic resonance imaging scans and neuropsychological cognitive assessments. WMH of each participant was graded on the basis of Fazekas grade scale and was divided into two groups: (A) WMH score of 1–2 points (n = 64), (B) WMH score of 3–6 points (n = 46). Topological indexes of brain functional network were analyzed using graph-theoretical method. T-test and Mann–Whitney U test was used to compare the differences in topological properties of brain functional network between groups. Partial correlation analysis was applied to explore the relationship between different topological properties of brain functional networks and overall cognitive function. Results Patients with high WMH scores exhibited decreased clustering coefficient values, global and local network efficiency along with increased shortest path length on whole brain level as well as decreased nodal efficiency in some brain regions on nodal level (p 0.05). Conclusion Therefore, we come to conclusions that patients with high WMH scores showed less optimized small-world networks compared to patients with low WMH scores. Global and local network efficiency on the whole-brain level, as well as nodal efficiency in certain brain regions on the nodal level, can be viewed as markers to reflect the course of WMH.

Abstract Background All birds reproduce via internal fertilization, but only ~3% of male birds possess the external genitalia that allows for intromission. Waterfowl (e.g., duck and goose) are representatives of them, and the external genitalia development of male geese is directly related to mating ability. Notably, some male geese show abnormal external genitalia development during ontogenesis. However, until now little is known about the molecular mechanisms of the external genitalia development in goose. In the present study, comparative transcriptomic analyses were performed on the hypothalamus, pituitary gland, testis, and external genitalia isolated from the 245-day-old male Tianfu meat geese showing normal (NEGG, n = 3) and abnormal (AEGG, n = 3) external genitals in order to provide a better understanding of the mechanisms controlling the development of the external genitalia in aquatic bird species. Results There were 107, 284, 2192, and 1005 differentially expressed genes (DEGs) identified in the hypothalamus, pituitary gland, testis and external genitalia between NEGG and AEGG. Functional enrichment analysis indicated that the DEGs identified in the hypothalamus were mainly enriched in the ECM-receptor interaction pathway. The ECM-receptor interaction, focal adhesion, and neuroactive ligand-receptor interaction pathways were significantly enriched by the DEGs in the pituitary gland. In the testis, the DEGs were enriched in the neuroactive ligand-receptor interaction, cell cycle, oocyte meiosis, and purine metabolism. In the external genitalia, the DEGs were enriched in the metabolic, neuroactive ligand-receptor interaction, and WNT signaling pathways. Furthermore, through integrated analysis of protein-protein interaction (PPI) network and co-expression network, fifteen genes involved in the neuroactive ligand-receptor interaction and WNT signaling pathways were identified, including KNG1, LPAR2, LPAR3, NPY, PLCB1, AVPR1B, GHSR, GRM3, HTR5A, FSHB, FSHR, WNT11, WNT5A, WIF1, and WNT7B, which could play crucial roles in the development of goose external genitalia. Conclusions This study is the first systematically comparing the hypothalamus, pituitary gland, testis, and external genitalia transcriptomes of male geese exhibiting normal and abnormal external genitals. Both bioinformatic analysis and validation experiments indicated that the neuroactive ligand-receptor interaction pathway could regulate the WNT signaling pathway through PLCB1 to control male goose external genitalia development.

ABSTRACT: Egg weight is an important indicator of egg phenotypic traits, which directly affects the economic benefits of the poultry industry. In the present research, laying ducks were classified into high egg weight (HEW) and light egg weight (LEW) groups. To reveal the underlying mechanism that may be responsible for the egg weight difference, the integrated analysis of transcriptomes and serum metabolomics was performed between the two groups. The results showed extremely significant differences (P < 0.01) in the total egg weight at 300 d, and average egg weight between the HEW and LEW groups. 733, 591, 82, and 74 differentially expressed genes (DEGs) were identified in the liver, magnum, F1, and F5 (hierarchical follicles) follicle membrane, respectively. The candidate genes were screened further from the perspective of forming an egg. In terms of egg yolk formation, the functional analysis revealed fatty acid metabolism-related pathways account for 36% of the liver's top pathways, including fatty acid biosynthesis, folate biosynthesis, fatty acid metabolism, and glycerol lipid metabolism pathways. FASN gene was identified as the key candidate gene by comprehensive analysis of gene expression and protein-protein interaction (PPI) network. In the follicle membrane, the DEGs were mainly enriched in protein processing in the endoplasmic reticulum, and MAPK signaling pathway, and HSPA2, HSPA8, BAG3 genes were identified as crucial candidate genes. In terms of egg white formation, the functional analysis revealed protein metabolism-related pathways account for 40% of the magnum's top pathways, which includes protein processing in the endoplasmic reticulum pathway. HSP90AA1 and HSPA8 genes were identified as key candidate genes. In addition, the integrated transcriptomic and metabolomic analysis showed that arginine and proline metabolism pathways could contribute to differences in egg weight. Thus, we speculated that the potential candidate genes, regulatory pathways, and metabolic biomarkers mentioned above might be responsible for the egg weight difference. These findings might provide a theoretical basis for improving the egg weight of ducks.

Abstract Lithium‐rich layered oxides (LLOs) with high energy density and low cost are regarded as promising candidates for the next‐generation cathode materials for lithium‐ion batteries (LIBs). However, there are still some drawbacks of LLOs such as oxygen instability and irreversible structure reconstruction, which seriously limit their electrochemical performance and practical applications. Herein, the high‐valence Ta doping is proposed to adjust the electronic structures of transition metals, which form strong Ta‐O bonds and reduce the covalency of Ni‐O bonds, thereby stabilizing the lattice oxygen and enhancing the structural/thermal stabilities of LLOs during electrochemical cycling. As a result, the optimized Ta‐doped LLO can deliver a capacity retention of 80% and voltage decay of 0.34 mV cycle−1 after 650 cycles at 1C. This study enriches the fundamental understanding of the electronic structure adjustment of LLOs and contributes to the optimization of LLOs for high‐energy LIBs.

With the completion of Chinese BeiDou Navigation Satellite System (BDS), the world has begun to enjoy the Positioning, Navigation, and Timing (PNT) services of four Global Navigation Satellite Systems (GNSS). In order to improve the GNSS performance and expand its applications, Low Earth Orbit (LEO) Enhanced Global Navigation Satellite System (LeGNSS) is being vigorously advocated. Combined with high-, medium-, and low- earth orbit satellites, it can improve GNSS performance in terms of orbit determination, Precise Point Positioning (PPP) convergence time, etc. This paper comprehensively reviews the current status of LeGNSS, focusing on analyzing its advantages and challenges for precise orbit and clock determination, PPP convergence, earth rotation parameter estimation, and global ionosphere modeling. Thanks to the fast geometric change brought by LEO satellites, LeGNSS is expected to fundamentally solve the problem of the long convergence time of PPP without any augmentation. The convergence time can be shortened within 1 minute if appropriate LEO constellations are deployed. However, there are still some issues to overcome, such as the optimization of LEO constellation as well as the real time LEO precise orbit and clock determination.

A knowledge graph (KG), a special form of semantic network, integrates fragmentary data into a graph to support knowledge processing and reasoning. KG quality control is important to the utility of KGs. It is essential to investigate KG quality and the parameters influencing KG quality to better understand its quality control. Although many works have been conducted to evaluate the dimensions of KG quality, quality control of the construction process, and enhancement methods for quality, a comprehensive literature review has not been presented on this topic. This paper intends to fill this research gap by presenting a comprehensive survey on the quality control of KGs. First, this paper defines six main evaluation dimensions of KG quality and investigates their correlations and differences. Second, quality control treatments during KG construction are introduced from the perspective of these dimensions of KG quality. Third, the quality enhancement of a constructed KG is described from various dimensions. This paper ultimately aims to promote the research and applications of KGs.

Transition metal nitride (TMN) films with excellent hardness and lubricating performance are versatile low dimension materials, which are widely used in various fields including industries, transportation, aerospace, and so on. This paper introduces one film design strategy and provides a review of the mechanisms for strengthening and lubricating nitride films. The design strategy refers to two aspects which determine the structures, the performance, the components, and the chemical constitutions of nitride films The strengthening mechanisms of nitride films are then illuminated in detail, including the solid solution effect, the grain size effect, the secondary phase effect, the stress or stress field effect, the template effect, and the valence electron concentration effect. Five lubricating mechanisms are next summarized, including the easy-shear nature, the tribo-chemical reactions, the lubricious fluorides, the textured contact surface, and the synergistic effect. This paper aims to give a comprehensive introduction for understanding the mechanisms of strengthening and lubrication of nitride films for students and researchers, as well as to understand the current research progress in nitride films for exploring research gaps.

In this paper, combined with the improved artificial potential field (IAPF) method and the nonlinear model predictive control (NMPC) algorithm, a collision avoidance decision-making support scheme considering ship maneuverability and the International Regulations for Preventing Collisions at Sea (COLREGs) is proposed. First, to comply with the requirements of COLREGs, an improved repulsive potential field is presented for different encounter scenarios when the ship detects the risk of collision, and the coordinated ship domain is applied to provide safety criteria for collision avoidance. Then, by transforming the MMG model to a discrete-time nonlinear system, the NMPC is utilized to predict the future state of the ship according to the current state, and the IAPF method is incorporated to calculate the potential field in each future state as the objective function. Following this approach, the action taken to avoid collision is more effective, the ship motion in avoiding collision is more accurate, and the collision avoidance decision making is more reasonable. Finally, two simulation examples of multi-ship encounter scenarios are applied to illustrate the merits and effectiveness of the proposed collision avoidance decision-making support scheme.

Abstract Perovskite solar cells (PSCs) emerging as a promising photovoltaic technology with high efficiency and low manufacturing cost have attracted the attention from all over the world. Both the efficiency and stability of PSCs have increased steadily in recent years, and the research on reducing lead leakage and developing eco-friendly lead-free perovskites pushes forward the commercialization of PSCs step by step. This review summarizes the main progress of PSCs in 2020 and 2021 from the aspects of efficiency, stability, perovskite-based tandem devices, and lead-free PSCs. Moreover, a brief discussion on the development of PSC modules and its challenges toward practical application is provided.

The preparation of lanthanide-transition metal clusters containing multiple lanthanide atoms remains challenging. Here, the authors present the controlled on-surface formation of ligand-stabilized heterometallic Ce/Au clusters containing two, three and four Ce atoms bridged by Au adatoms.

Abstract The interaction between the voltage source converter (VSC) and weak grid causes a negatively damped or diverging oscillation (DVO). The diverging oscillation generally evolves into a sustained oscillation (STO) when governed by the nonlinearities in the VSC's control system, such as the saturation of pulse width modulation (PWM). The conventional small‐signal impedance/admittance modelling (SSIM/SSAM) and stability analysis methods are not suitable for the characteristic analysis of STO. This paper presents a large‐signal impedance/admittance model (LSIM/LSAM)‐based quantitative analysis method to better understand the mechanism, characteristics, and occurrence conditions of STO. The LSAM extends the SSAM by incorporating the nonlinearity of PWM saturation using the describing function method. First, a unique time‐varying characteristic of the oscillation associated with nonlinearity is investigated. Then, two LSIM/LSAM‐based occurrence criteria for STO are established based on an equivalent RLC circuit model of the system. Three critical pieces of information, including the occurrence condition, frequency, and magnitude, associated with STO are revealed by the criteria. Finally, the LSAM‐based analysis method is applied to investigate the time‐varying admittance of the VSC and to assess the magnitude and frequency of STO. Both the criteria and LSAM‐based analysis results have been verified through time‐domain simulations on a typical grid‐connected VSC.

Many aquatic ecosystems are seriously threatened by cyanobacteria blooms; gas vesicles enable cyanobacteria to form harmful cyanobacterial blooms rapidly. Many lake managers try to control cyanobacterial blooms by collapsing gas vesicle, but it is still unclear whether gas vesicle recovery will cause this method to fail. Through the culture experiments of three cyanobacteria, it was found that all cyanobacteria with collapsed gas vesicles can rapidly regain buoyancy in a few days under nutrient-sufficient environments, and average gas vesicle content was even 9% higher than initially. In contrast, buoyancy recovery of all cyanobacteria under nutrient-limited environments was significantly worse. After culture experiments, the average gas vesicle content of all cyanobacteria in phosphorus-limited environments only reach 49% of the initial value. The gas vesicle content of two non-nitrogen-fixing cyanobacteria in nitrogen-limited environments only reached 38% of initial value. The buoyancy of cyanobacteria in different tropic levels was similar to the gas vesicle content. These results indicate that collapsing gas vesicles can only control cyanobacterial blooms in the short-term. To control cyanobacterial blooms in the long-term, in deep lakes, lake managers should discharge gas vesicles’ collapsed cyanobacteria into deep water. In shallow lakes, the disruption of gas vesicles must be combined with nutrient control measures to effectively control cyanobacteria blooms.

Safety is a core concern in human–robot collaboration (HRC), which highly relies on multi‐information collected from its environment by various sensors. Current passive solution is to isolate the robot from human by fences or cages, which is invalid for a real collaborative robot, especially for the domestic and rehabilitation robots. Herein, a capacitive and piezoresistive hybrid sensor for long‐distance proximity and wide‐range force detection in HRC is reported. The sensor composes a pair of interdigital copper foil worked as the electrode for both coplanar capacitors and resistors, while a carbon black in polymer matrix works as the piezoresistive material. As‐prepared hybrid sensor can detect the object approaching as far as 100 mm, while a contact force covers from 0 to 450 N. The maximum sensitivity is 0.65 mm−1 for object proximity, and 17.73 N−1 for contact force. Significantly, the proposed hybrid sensor is feasible and scalable integration for the electronic‐skins (e‐skins) with superior stability, mechanical flexibility and deformability, which can withstand large compression, bending and torsion in applications. Finally, the e‐skins are used for safety control in two types of commercial robots, which exhibits the long‐distance proximity and large‐range force detection capabilities, illustrating its potential usage in complex, precise, and safe requirement conditions.

With the development of intelligent transportation system,the vehicles will no longer be controlled by the traditional traffic light when they enter or leave the intersection.Instead,they will interact with the local server (LS) near the intersection and accept the regulation of LS.The basic of the security vehicle communication at intersections is authentication of network node.Based on this,an anonymous vehicle authentication scheme based on blockchain technology was proposed.The scheme employed a hybrid cryptography based on identity and hash message authentication code,and recorded the authentication results in blockchains.According to simulation testing and result analysis,the scheme ensures the anonymity and privacy-preserving,with less communication overhead compared to other methods.

Autonomous vehicles have been extensively researched and developed rapidly in recent years.However,these vehicles may be not able to avoid collision with vehicles that appear suddenly.To solve this problem,a cooperative trajectory prediction system for intelligent and automated connected convoy based on blockchain was proposed.In the proposed system,each node in the intelligent and automated connected convoy and roadside infrastructure predict the trajectory of vehicles around them with the LSTM model,and they share the information they get.Using blockchain,the intelligent and automated connected convoy and roadside infrastructure rate the received messages.The summarized rating will be stored as a block in the blockchain that stores the trust values.Vehicles in the intelligent and automated connected convoy are able to judge whether the other nodes in the Conroy are credible according to their trust value,and messages from the low trust value sender will be ignored,thus achieving cooperative driving.Experiment shows that the proposed system plays a significant role in improving driving safety of the intelligent connected platoon.

Tin based perovskite solar cells could be promising replacements for lead based counterparts due to their lower toxicity, but their efficiencies are much lower. Here, Liu et al. report stable tin based perovskite solar cells with efficiency over 10% by designing amorphous-polycrystalline nanostructures.

Objectives: To investigate the association of gender, ethnicity, living region, and socioeconomic status (SES) with health literacy and attitudes toward nevi and melanoma in Chinese adolescents and to examine whether health literacy mediates the association of SES with attitudes.Study Design: A multicenter cross-sectional study was conducted among newly enrolled college students. First-year students were recruited from five universities in different regions of China in 2018 using the cluster sampling method. The observers were blinded to the participants.Methods: Health literacy and attitudes were measured using a previously validated tool (Nevus and Melanoma Health Literacy and attitudes Test). SES was measured by annual family income and parental highest educational level. Nonparametric test was used to examine the association of participants' characteristics with health literacy and attitudes. Two-level generalized linear model with logarithm link function and Gamma distribution was used individually for SES. The mediation effect model was used to examine the mediation effect of health literacy.Results: A total of 21,086 questionnaires were completed by college students with a mean age of 18.0 ± 0.8 years. The mean scores of health literacy and attitudes were 9.83 ± 7.46 (maximum score: 28) and 16.98 ± 2.92 (maximum score: 20), respectively. Female, Han nationality, annual family income, and parental educational levels were positively associated with health literacy and attitudes. Regional differences showed different effects on health literacy and attitudes. A mediation model showed that literacy mediated the association of SES with attitudes toward nevi and melanoma. Health literacy mediated ~30–50% of the association of SES with attitudes.Conclusions: Melanoma-related health literacy among Chinese college students is generally insufficient and needs to be improved. Targeted and personalized health education for improving health literacy related to nevi and melanoma may improve the general population's attitudes and further promote health-related behavior to prevent and identify early-stage melanoma.

Hybrid electrical vehicle (HEV) is a popular transport solution to reducing carbon dioxide emissions. Switched reluctance motors (SRMs) are one of the most promising motors for such applications. In SRM-based series-type HEV, there are three energy components, i.e., generator, battery bank, and SRM. A tri-port converter is needed to combine the three energy components in one power converter. The tri-port converter has a modular and concise structure, which meets the requirements for HEV applications. The proposed tri-port converter supports five working modes, including generator to SRM, battery bank to SRM, generator and battery bank to SRM, generator to SRM and battery bank, and battery bank to SRM and generator under driving conditions; under standstill conditions, generator to battery bank and battery bank to generator energy flow can also be realized without requiring extra converters. The corresponding control strategies are also developed to cooperate with different working modes. Moreover, the fault tolerance characteristics of the tri-port converter are investigated to expand its feasibility under harsh HEV application conditions. The simulation and experiments are undertaken with a 750W prototype to evaluate the performance of the proposed tri-port converter for HEV applications.

This paper presents a review of the electrical and electronic technologies investigated in more-electric aircraft (MEA). In order to change the current situation of low power efficiency, serious pollution, and high operating cost in conventional aircraft, the concept of MEA is proposed. By converting some hydraulic, mechanical, and pneumatic power sources into electrical ones, the overall power efficiency is greatly increased, and more flexible power regulation is achieved. The main components in an MEA power system are electrical machines and power electronics devices. The design and control methods for electrical machines and various topologies and control strategies for power electronic converters have been widely researched. Besides, several studies are carried out regarding energy management strategies that intend to optimize the operation of MEA power distribution systems. Furthermore, it is necessary to investigate the system stability and reliability issues in an MEA, since they are directly related to the safety of passengers. In terms of machine technologies, power electronics techniques, energy management strategies, and the system stability and reliability, a review is carried out for the contributions in the literature to MEA.

In this study, by analyzing the relationship between hybrid combinations and parental lines, we found that the eating quality traits of hybrid combinations were determined by both parents. The sterile lines determined the overall eating quality characteristics of the hybrid combinations. For the same sterile line, there were some correlations between the hybrid combinations and restorer lines in terms of taste value, rapid visco analyzer breakdown and setback values, apparent amylose content, and cooked rice hardness and stickiness. Analysis of the starch fine structure between hybrid combinations and their restorer lines demonstrated positive correlations between them in terms of short-branch amylopectin chains and amylose. Moreover, different allelic combinations of the Wx gene showed different genetic effects on the eating quality traits of hybrid rice. Overall, this study provides a framework for the development of hybrid rice with superior eating quality.

The thermal catalytic conversion of biomass is currently a prevalent method for producing activated carbon with superb textural properties and excellent adsorption performance. However, activated carbon suffers severely from its poor thermal stability, which can easily result in spontaneous burning. In contrast, silica material is famed for its easy accessibility, high specific surface area, and remarkable thermal stability; however, its broader applications are restricted by its strong hydrophilicity. Based on this, the present review summarizes the recent progress made in carbon-silica composite materials, including the various preparation methods using diverse carbon (including biomass resources) and silica precursors, their corresponding structure–function relationship, and their applications in adsorption, insulation, batteries, and sensors. Through their combination, the drawbacks of the individual materials are circumvented while their original advantages are maintained. Finally, several bottlenecks existing in the field of carbon-silica composites, from synthesis to applications, are discussed in this paper, and possible solutions are given accordingly.

Environmental quality is a great concern to everyone, in order to realize the collection, upload, management, and visualization of parameters of atmospheric environment in real time. We propose a cheap, low-power, and fast deployment wireless sensor node for environmental monitoring, consisting of STM32 MCU, ESP8266, light sensor, rain sensor, UV sensor, seven-in-one sensor (including temperature, humidity, PM2.5, PM10, CO2, formaldehyde, and TVOC), and solar automatic tracking module. A customized μC/OS-III runs on the node, which controls the transmission of environment parameters collected by each sensor to the cloud server through the wireless network, and then the server receives, stores, and visualizes the data. In actual test, the node collects data once an hour, and the running power of the node is low and stable. Experimental results show that the node could achieve accurate collection and transmission and display the environmental data, and solar automatic tracking module could meet long-term running of the node in the night and continuous rainy days.

Abstract Background Anterior knee pain is one of the most common musculoskeletal complaints of young patients. We notice that some patients had normal femoral trochlear, medial and lateral patellar retinaculum, and special patellar morphology, which resulted in a series of symptoms in the flexion of the knee due to the impingement of the lateral articular surface of the patella with the femur. We firstly termed this pathologic process as lateral patellar impingement syndrome (LPIS). This ambispective cohort study was to explore the curative effect of arthroscopic lateral patelloplasty for early LPIS. Methods Thirty-five early LPIS patients which underwent arthroscopic lateral patelloplasty were enrolled in our study. Evaluations consisted of pre- and postoperative symptoms, physical examinations, radiographs, and questionnaires. The Lysholm score, patellar suitable angle, patellar tilt angle, and patellar lateral shift were measured with the CT scan and Merchant X-ray film. The efficacy was graded as excellent, good, fair, and poor according to the patient’s subjective evaluation. Results The patients were followed up for an average of 41.1 ± 18.6 months. The efficacy results were excellent in 6, good in 26, fair in 2, and poor in 1. There were statistical differences in pre- and postoperative Lysholm scores (80.66 ± 5.51 vs 81.91 ± 6.21) (P