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A large number of epidemiological studies have confirmed that arteriosclerosis (AS) is a risk factor for abdominal aortic aneurysm (AAA). However, the relationship between AS and AAA remains controversial. The objective of this work is to better understand the association between the two diseases by identifying the co-differentially expressed genes under both pathological conditions, so as to identify potential genetic biomarkers and treatment targets for atherosclerosis-related aneurysms. Differentially-expressed genes (DEGs) shared by both AS and AAA patients were identified by bioinformatics analyses of Gene Expression Omnibus (GEO) datasets GSE100927 and GSE7084. These DEGs were then subjected to bioinformatic analyses of protein-protein interaction (PPI), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, the identified hub genes were further validated by qRT-PCR in AS (n = 4), AAA (n = 4), and healthy (n = 4) individuals. Differential expression analysis revealed a total of 169 and 37 genes that had increased and decreased expression levels, respectively, in both AS and AAA patients compared with healthy controls. The construction of a PPI network and key modules resulted in the identification of five hub genes (SPI1, TYROBP, TLR2, FCER1G, and MMP9) as candidate diagnostic biomarkers and treatment targets for patients with AS-related AAA. AS and AAA are indeed correlated; SPI1, TYROBP, TLR2, FCER1G and MMP9 genes are potential new genetic biomarkers for AS-related AAA.

The evaluation of casting allowance currently relies on manual operation, which is time-consuming and unstable. The structured-light three-dimensional (3D) sensor-based 3D shape measurement technology is characterized by non-contact, high accuracy, and fast measuring speed, which provides the complete 3D shape of casting for accurate allowance evaluation. However, measuring a complex shape casting still requires numerous manual operations, including attaching marks, planning the measurement process, and data processing. To solve these problems, a robot-driven structured-light 3D sensor-based measurement method is proposed, with a six-degree of freedom (6-DOF) industrial robot and a turntable to control the structured-light 3D measurement sensor, to transform the 3D results from different measuring viewpoints into a coherent coordinate system, and to form a complete 3D shape of the casting. Then, the mechanical processing allowance will be calculated by comparing the 3D measurement result and the standard CAD model automatically. The experiment results show that the proposed method is accurate and efficient, and the casting allowance evaluation time is about ten times faster than that of manual operation. Moreover, the proposed method would provide valuable experience for other industrial applications.

The evaluation of the complex workpiece allowance and the scribing the datum line now extremely rely on manual operation. The manual operation is time-consuming and prone to misjudgment, and has a large blind area. To solve these problems, the robot-driven automatic scribing via three-dimensional (3D) measurement sensor method (RAS3DM) is proposed. In this study, we solve the key technology of calibrating the rigid transformation between the 3D measurement coordinate system and laser scribing coordinate system. And a fast and accurate multiple coordinate systems calibration and unification method is proposed, a fixed calibration target and a mobile calibration target are designed. Hence, a structured-light 3D shape measurement sensor driven by an industrial robot with six-degree of freedom (6-DOF) is utilized to obtain the complete 3D shape of the complex workpiece automatically, and then by comparing the 3D measurement result and the standard CAD model, the laser scribing equipment can automatically scribe the mechanical processing datum line to assist further processing. The experiment results illustrate that the proposed method is accurate and efficient: the complex workpiece allowance evaluation and scribing time is about 5 times faster than that of manual operation, and the scribing accuracy is 0.15mm, which can effectively solve various problems of manual scribing. The proposed RAS3DM can be widely applied in factories and laboratories.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system related to autoimmunity and is characterized by demyelination, neuroinflammation, and neurodegeneration. Cell therapies mediated by dendritic cells (DCs) and regulatory T cells (Tregs) have gradually become accumulating focusing in MS, and the protective crosstalk mechanisms between DCs and Tregs provide the basis for the efficacy of treatment regimens. In MS and its animal model experimental autoimmune encephalomyelitis, DCs communicate with Tregs to form immune synapses and complete a variety of complex interactions to counteract the unbalanced immune tolerance. Through different co-stimulatory/inhibitory molecules, cytokines, and metabolic enzymes, DCs regulate the proliferation, differentiation and function of Tregs. On the other hand, Tregs inhibit the mature state and antigen presentation ability of DCs, ultimately improving immune tolerance. In this review, we summarized the pivotal immune targets in the interaction between DCs and Tregs, and elucidated the protective mechanisms of DC-Treg cell crosstalk in MS, finally interpreted the complex cell interplay in the manner of inhibitory feedback loops to explore novel therapeutic directions for MS.

BackgroundAcute sleep deprivation (ASD) can effect mood, attention, memory, alertness and metabolism. Especially, it is often accompanied by cognitive impairment of the brain. Acupuncture is safe and effective for improving cognitive function, but its underlying mechanism is not fully understood. In this study, an event-related potential (ERP) technique will be employed to measure the behavioral, cognitive, and physiological changes produced by electroacupuncture intervention after ASD.MethodsWe will recruit 60 healthy subjects. The participants will be randomly divided into a treatment group, a control group, a sham electroacupuncture group and a blank group, at a 1:1:1:1 ratio. The primary outcome will be determined by the change from baseline to 36 h in the MoCA score. The secondary results include the amplitude and latency of ERP N2 and P3, Go-hit rates, Go-RTs, No-Go-FA rates, the WCST, the Digit Span Subtest of the WAIS, the ESS score and FS-14. The 15 healthy subjects will not receive acupuncture treatment and ASD, but will receive EEG records and cognition functions test at the beginning and end of the experiment. Electroacupuncture intervention will be performed for 30 min once every 12 h, a total of three times. ERP measurements and other tests will be performed after baseline and ASD, and the statistician and outcome evaluator will be blinded to treatment allocation.DiscussionThis study is expected to investigate the effectiveness of electroacupuncture in improving cognition for ASD.Trial RegistrationChiCTR2200055999.

Gliomas are the most common primary brain cancer. While it has been known that calcium-related genes correlate with gliomagenesis, the relationship between calcium-related genes and glioma prognosis remains unclear. We assessed TCGA datasets of mRNA expressions with differentially expressed genes (DEGs) and enrichment analysis to specifically screen for genes that regulate or are affected by calcium levels. We then correlated the identified calcium-related genes with unsupervised/supervised learning to classify glioma patients into 2 risk groups. We also correlated our identified genes with immune signatures. As a result, we discovered 460 calcium genes and 35 calcium key genes that were associated with OS. There were 13 DEGs between Clusters 1 and 2 with different OS. At the same time, 10 calcium hub genes (CHGs) signature model were constructed using supervised learning, and the prognostic risk scores of the 3 cohorts of samples were calculated. The risk score was confirmed as an independent predictor of prognosis. Immune enrichment analysis revealed an immunosuppressive tumor microenvironment with upregulation of checkpoint markers in the high-risk group. Finally, a nomogram was generated with risk scores and other clinical prognostic independent indicators to quantify prognosis. Our findings suggest that calcium-related gene expression patterns could be applicable to predict prognosis and predict levels of immunosuppression.

Glioma is the most common and aggressive type of primary brain tumor. MicroRNA (miR)-130b functions as a tumor-associated miR. The dysregulation of miR-130b is involved in numerous biological characteristics and properties of certain types of cancer. The present study revealed the function and possible molecular mechanism of miR-130b in glioma cells, reporting that the level of miR-130b was markedly higher, increasing progressively as the histologic grade of the glioma increased, compared with the level in normal tissues. Additionally, the present study demonstrated that patients with high miR-130b expression exhibited a poor 3-year survival rate and miR-130b was an independent factor for predicting the prognosis of patients with glioma. The downregulation of miR-130b reduced invasion and migration in U373 and U87 cells. Furthermore, the downregulation of miR-130b increased peroxisome proliferator-activated receptor-γ (PPARγ) expression and inhibited epithelial-mesenchymal transition (EMT) in glioma cells. The present study identified PPARγ as a direct target of miR-130b in glioma in vitro. Furthermore, PPARγ knockdown was revealed to reduce the effect on EMT caused by the downregulation of miR-130b in U87 cells. The present study demonstrated that miR-130b promotes glioma proliferation, migration and invasion by suppressing PPARγ and subsequently inducing EMT. [ABSTRACT FROM AUTHOR]

Abstract Objective As an alternative of knee-protection surgery, unicompartmental knee arthroplasty has been widely used for the treatment of knee osteoarthritis and has achieved good clinical results. However, reports on its data and trend are scanty. This article reviewed current status and trend in the research of UKA, and compared different regions, organizations and authors in terms of their contributions to the field. Methods The literature on UKA ranging from 2009 to 2019 was searched in the “Web of Science” database, and the search results were visually presented by using Excel and VOS-viewer software packages, and the status quo and development trends of relevant studies were analyzed. Results A total of 1264 articles on UKA were identified, of which 330 were the larger studies conducted in the United States. The institution that published most papers was Oxford University, with a total of 109 papers published. MURRAY DW was the largest contributor in this field. The National Institutes of Health was the largest funding agencies of the UKA. Studies could be divided into six clusters in terms of prosthesis design, follow-up investigation, OA etiology, hip-knee association, joint replacement registration, and computer navigation. “Computer-aided navigation” and “gait analysis” promise to be future hot spots in the field of UKA research. Conclusion Global trend analysis suggests that UKA research is gradually deepening and the number of papers has been on the rise. The USA was the largest contributor to this field. More research effort should be directed to “Computer-aided navigation”and “gait analysis”, which might be the popular topics in the UKA field in not very distant future.

Neuromedin U (NMU) is a regulatory peptide that is widely distributed throughout the body and performs a variety of physiological functions through its corresponding receptors. In recent years, NMU has become the focus of attention in various fields of research as its diverse and essential functions have gradually been elucidated. However, there have been no bibliometrics studies on the development trend and knowledge structure of NMU research. Therefore, in this study, we used VOSviewer software to statistically analyze scientific data from articles related to NMU to track the developmental footprint of this research field, including relevant countries, institutions, authors, and keywords. We retrieved a total of 338 papers related to NMU, written by 1,661 authors from 438 organizations of 41 countries that were published in 332 journals. The first study on NMU was reported by a group in Japan in 1985. Subsequently, nine articles on NMU were published from 1987 to 2006. A small leap in this field could be detected in 2009, with 30 articles published worldwide. Among the various countries in which this research has been performed, Japan and the United States have made the most outstanding contributions. Miyazato M, Kangawa K, and Mori K from the Department of Biochemistry, National Retrain and Cardiovascular Center Research Institute in Japan were the most productive authors who have the highest number of citations. Keyword analysis showed six clusters: central-nervous-system, homeostasis, energy metabolism, cancer, immune inflammation, and food intake. The three most highly cited articles were associated with inflammation. Overall, this study demonstrates the research trends and future directions of NMU, providing an objective description of the contributions in this field along with reference value for future research.

Relapsing-remitting multiple sclerosis (RRMS) and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) are inflammatory demyelinating diseases of the central nervous system (CNS). Due to the shared clinical manifestations, detection of disease-specific serum antibody of the two diseases is currently considered as the gold standard for the diagnosis; however, the serum antibody levels are unpredictable during different stages of the two diseases. Herein, peripheral blood single-cell transcriptome was used to unveil distinct immune cell signatures of the two diseases, with the aim to provide predictive discrimination. Single-cell RNA sequencing (scRNA-seq) was conducted on the peripheral blood from three subjects, i.e., one patient with RRMS, one patient with MOGAD, and one patient with healthy control. The results showed that the CD19+ CXCR4+ naive B cell subsets were significantly expanded in both RRMS and MOGAD, which was verified by flow cytometry. More importantly, RRMS single-cell transcriptomic was characterized by increased naive CD8+ T cells and cytotoxic memory-like Natural Killer (NK) cells, together with decreased inflammatory monocytes, whereas MOGAD exhibited increased inflammatory monocytes and cytotoxic CD8 effector T cells, coupled with decreased plasma cells and memory B cells. Collectively, our findings indicate that the two diseases exhibit distinct immune cell signatures, which allows for highly predictive discrimination of the two diseases and paves a novel avenue for diagnosis and therapy of neuroinflammatory diseases.

Underwater images suffer from serious color distortion and detail loss because of the wavelength-dependent light absorption and scattering, which seriously influences the subsequent underwater object detection and recognition. The latest methods for underwater image enhancement are based on deep models, which focus on finding a mapping function from the underwater image subspace to a ground-truth image subspace. They neglect the diversity of underwater conditions which leads to different background colors of underwater images. In this paper, we propose a Class-condition Attention Generative Adversarial Network (CA-GAN) to enhance an underwater image. We build an underwater image dataset which contains ten categories generated by the simulator with different water attenuation coefficient and depth. Relying on the underwater image classes, CA-GAN creates a many-to-one mapping function for an underwater image. Moreover, in order to generate the realistic image, attention mechanism is utilized. In the channel attention block, the feature maps in the front-end layers and the back-end layers are fused along channels, and in the spatial attention block, feature maps are pixel-wise fused. Extensive experiments are conducted on synthetic and real underwater images. The experimental results demonstrate that CA-GAN can effectively recover color and detail of various scenes of underwater images and is superior to the state-of-the-art methods.

Abstract Background Glioma initiating cells (GICs), also known as glioma stem cells (GSCs), play an important role in the progression and recurrence of glioblastoma multiforme (GBM) due to their potential for self-renewal, multiple differentiation and tumor initiation. In the recent years, Notch1 has been found to be overexpressed in GICs. However, the regulatory mechanism of Notch1 in the self-renewal and invasion ability of GICs remains unclear. This study aims to explore the effect of Notch pathway on self-renewal and invasion of GICs and the underlying mechanisms. Methods Bioinformatic analysis and immunohistochemistry (IHC) were performed to evaluate the expression of Notch1 and Hes1 in GBM samples. Immunofluorescent (IF) staining was performed to observe the distribution of Notch1 and CXCR4 in GBM and GICs. Both pharmacological intervention and RNA interference were employed to investigate the role of Notch1 in GICs self-renewal, invasion and tumor growth in vitro or in vivo. The crosstalk effect of Notch1 and CXCL12/CXCR4 system on GIC self-renewal and invasion was explored by sphere formation assay, limiting dilution assay and Transwell assay. Western blots were used to verify the activation of Notch1/CXCR4/AKT pathway in self-renewal, invasion and tumor growth of GICs. Luciferase reporter assay was used to testify the potential binding site of Notch1 signaling and CXCR4. The orthotopic GICs implantations were established to analyze the role and the mechanism of Notch1 in glioma progression in vivo. Results Notch1 signaling activity was elevated in GBM tissues. Notch1 and CXCR4 were both upregulated in GICs, compared to Notch1 positive glioma cells comprised a large proportion in the CD133+ glioma cell spheres, CXCR4 positive glioma cells which usually expressed Notch1 both and dispersed in the periphery of the sphere, only represent a small subset of CD133+ glioma cell spheres. Furthermore, downregulation of the Notch1 pathway by shRNA and MK0752 significantly inhibited the PI3K/AKT/mTOR signaling pathway via the decreased expression of CXCR4 in GICs, and weakened the self-renewal, invasion and tumor growth ability of GICs. Conclusions These findings suggest that the cross-talk between Notch1 signaling and CXCL12/CXCR4 system could contribute to the self-renewal and invasion of GICs, and this discovery could help drive the design of more effective therapies in Notch1-targeted treatment of GBMs.

The expansion of high-speed communication needs due to explosive growth of subscribers each year has led the researchers to design the next generation communication systems which can cope with the current growing demand. Millimeter waves, operated within the range of 30 GHz to 300 GHz, can become potential carrier for delivering large amount of data. However, in hospital scenarios, these radio waves are subjected to strict regulations due to direct impact on patients’ health as well as high interference with other medical devices which again imposes critical challenge on patients. Thus, it is a challenge for the researchers to provide communication/broadband services for transmission of such sensitive biomedical sensor data in hospitals locations. Radio over Free space (Ro-FSO) systems may become the attractive solution to deliver millimeter waves over free space link with high speed. Further, to expand the capacity of Ro-FSO systems, mode division multiplexing (MDM) plays a vital role in addition to wavelength division multiplexing (WDM) scheme. In this work, we have demonstrated the MDM-WDM scheme to deliver four channels with each one having the capacity of 10 Gbps up-converted to 40 GHz over FSO link which is suitable for providing broadband and communication services within the hospital premises. Moreover, the proposed WDM-MDM-Ro-FSO link is evaluated under different fog conditions.

BackgroundNeuromyelitis optica spectrum disorders (NMOSDs) are severe inflammatory diseases mediated mainly by humoral and cellular immunity. Circulating follicular helper T (Tfh) cells are thought to be involved in the pathogenesis of NMOSD, and serum C-X-C motif ligand 13 (CXCL13) levels reflect the effects of Tfh cells on B-cell-mediated humoral immunity. Immune cell and cytokine changes during the dynamic relapsing and remitting processes in NMOSD require further exploration.Patients and methodsBlood samples were collected from 36 patients in acute and recovery phases of NMOSD, 20 patients with other noninflammatory neurological diseases (ONND) and 20 age- and sex-matched healthy volunteers. CD4+CXCR5+PD-1+ Tfh cells were detected by flow cytometry, and serum CXCL13 levels were assessed by enzyme-linked immunosorbent assay (ELISA).ResultsThe percentage of CD4+CXCR5+PD-1+ Tfh cells was significantly higher during the acute phase than during the recovery phase, and serum CXCL13 levels were significantly higher in patients in the acute and recovery phases of NMOSD than in the ONND and control groups. The Tfh cell percentage was positively correlated with CXCL13 levels, and both were positively correlated with Expanded Disability Status Scale (EDSS) scores and cerebrospinal fluid protein levels in patients with acute NMOSD.ConclusionCirculating Tfh cells level has the potential to be a biomarker of disease severity.

Adenosine triphosphatase inhibitory factor 1 (IF1) has previously been considered to be a driving oncogene in human cancers. Several studies have revealed that IF1 overexpression is present in a variety of tumor types and promotes tumor growth and metastasis. The present study aimed to investigate the clinical significance of IF1 in glioma and the role of IF1 in cell migration and invasion. The mRNA and protein expression of IF1 in glioma tissues was found to be significantly increased compared with the expression in normal brain tissues (P<0.05). The presence of IF1 expression was significantly associated with an advanced clinical stage in glioma (P<0.05). Furthermore, the presence of IF1 expression was found to be associated with a reduced overall survival rate of glioma patients (P<0.05). Multivariate Cox regression analysis indicated that IF1 was an independent factor for predicting the overall survival rate of patients with glioma (P<0.05). IF1 knockdown also significantly reduced the number of migratory and invasive U251 and U87 cells (P<0.05). In addition, IF1 knockdown inhibited the expression of nuclear factor-κB (NF-κB) and Snai1, and led to increased E-cadherin expression and reduced vimentin expression. In conclusion, the presence of IF1 expression is associated with poor clinicopathological features in glioma. IF1 expression is an independent prognostic marker for predicting the overall survival rate of patients with glioma. Mechanistically, IF1 may promote glioma cell migration and invasion through the NF-κB/Snai1 axis. [ABSTRACT FROM AUTHOR]

Considering the cognitive and synaptic deficits following intragastric administration of melamine, the aim of the current investigation was to test whether the hippocampal oscillations were affected. The local field potential (LFP) was recorded in the hippocampal CA3–CA1 pathway of Wistar rats during a spatial-dependent Y-maze task. The general partial directed coherence (gPDC) method was used to assess the directionality of neural information flow (NIF) between the CA3 and CA1 regions. The levels of acetylcholine (ACh) and its esterolytic protease, acetylcholinesterase (AChE), were detected in the hippocampus (HPC) following the behavioral test. The values of phase synchronization between the CA3 and CA1 regions in delta, low theta, and high theta oscillations were reduced significantly in the melamine-treated group. Moreover, the coupling directional index and the strength of CA3 driving CA1 were critically decreased in the above three frequency bands as well. Meanwhile, a reduction in ACh expression and an enhancement in AChE activity were found in the HPC of melamine-treated rats. Intrahippocampal infusion with ACh could mitigate the weakened neural coupling and directional NIF in parallel with spatial learning improvements. However, infusion of scopolamine, an acetylcholine receptor antagonist, could block the mitigative effects of ACh treatment in melamine rats. These findings provide first evidence that ACh-mediated neuronal coupling and NIF in the CA3–CA1 pathway are involved in spatial learning deficits induced by chronic melamine exposure.

To solve the problem of inflexibility of offline hand–eye calibration in “eye-in-hand” modes, an online hand–eye calibration method based on the ChArUco board is proposed in this paper. Firstly, a hand–eye calibration model based on the ChArUco board is established, by analyzing the mathematical model of hand–eye calibration, and the image features of the ChArUco board. According to the advantages of the ChArUco board, with both the checkerboard and the ArUco marker, an online hand–eye calibration algorithm based on the ChArUco board is designed. Then, the online hand–eye calibration algorithm, based on the ChArUco board, is used to realize the dynamic adjustment of the hand–eye position relationship. Finally, the hand–eye calibration experiment is carried out to verify the accuracy of the hand–eye calibration based on the ChArUco board. The robustness and accuracy of the proposed method are verified by online hand–eye calibration experiments. The experimental results show that the accuracy of the online hand–eye calibration method proposed in this paper is between 0.4 mm and 0.6 mm, which is almost the same as the offline hand–eye calibration accuracy. The method in this paper utilizes the advantages of the ChArUco board to realize online hand–eye calibration, which improves the flexibility and robustness of hand–eye calibration.

In this paper, we developed a new robust part-based model for facial landmark localization and detection via affine transformation. In contrast to the existing works, the new algorithm incorporates affine transformations with the robust regression to tackle the potential effects of outliers and heavy sparse noises, occlusions and illuminations. As such, the distorted or misaligned objects can be rectified by affine transformations and the patterns of occlusions and outliers can be explicitly separated from the true underlying objects in big data. Moreover, the search of the optimal parameters and affine transformations is cast as a constrained optimization programming. To mitigate the computations, a new set of equations is derived to update the parameters involved and the affine transformations iteratively in a round-robin manner. Our way to update the parameters compared to the state of the art of the works is relatively better, as we employ a fast alternating direction method for multiplier (ADMM) algorithm that solves the parameters separately. Simulations show that the proposed method outperforms the state-of-the-art works on facial landmark localization and detection on the COFW, HELEN, and LFPW datasets.

In this paper, we propose a novel robust algorithm for image recovery via affine transformations, the weighted nuclear, L∗,w, and the L2,1 norms. The new method considers the spatial weight matrix to account the correlated samples in the data, the L2,1 norm to tackle the dilemma of extreme values in the high-dimensional images, and the L∗,w norm newly added to alleviate the potential effects of outliers and heavy sparse noises, enabling the new approach to be more resilient to outliers and large variations in the high-dimensional images in signal processing. The determination of the parameters is involved, and the affine transformations are cast as a convex optimization problem. To mitigate the computational complexity, alternating iteratively reweighted direction method of multipliers (ADMM) method is utilized to derive a new set of recursive equations to update the optimization variables and the affine transformations iteratively in a round-robin manner. The new algorithm is superior to the state-of-the-art works in terms of accuracy on various public databases.

Abstract Inhibitor of nuclear factor kappa‐B kinase subunit epsilon (IKBKE) plays critical roles in the proliferation, invasion, and epithelial‐mesenchymal transition (EMT) of glioblastoma (GBM). However, as an immune response factor, few studies have focused on the role of IKBKE in the glioblastoma‐mediated immunosuppressive microenvironment. Here, we found a higher IKBKE expression level in gliomas corresponding to higher malignancy of the tumor. The highest level of IKBKE expression was examined in the core region of GBM tissues as well as the mesenchymal subtype, which are featured with necrosis, immunocyte infiltration, and immunosuppression. Further in silico analysis demonstrated that the JAK/STAT as the signaling pathway most associated with IKBKE in mesenchymal GBM. The co‐expression patterns of IKBKE, pSTAT3, and PD‐L1 were detected within GBM tissues. Mechanistically, IKBKE could interact with STAT3 and thus enhancing the phosphorylation level of STAT3 and its nuclear translocation. In addition, pSTAT3 could transcriptionally regulate the expression of PD‐L1 through binding to its promoter. In vivo results further confirmed the inhibitory effect of the IKBKE downregulation on tumor growth. Collectively, our findings suggest IKBKE as the central node in the crosstalk between NF‐κB and STAT3 signaling within mesenchymal GBM. Targeting GBM through inhibiting IKBKE could restrain tumor growth and tumor‐mediated immunosuppressive environment.

For the task of obstacle detection in a complex traffic environment, this paper proposes a road-free space extraction and obstacle detection method based on stereo vision. The proposed method combines the advantages of the V-disparity image and the Stixel method. Firstly, the depth information and the V-disparity image are calculated according to the disparity image. Then, the free space on the road surface is calculated through the RANSAC algorithm and dynamic programming (DP) algorithm. Furthermore, a new V-disparity image and a new U-disparity image are calculated by the disparity image after removing the road surface information. Finally, the height and width of the obstacles on the road are extracted from the new V-disparity image and U-disparity image, respectively. The detection of obstacles is realized by the height and width information of obstacles. In order to verify the method, we adopted the object detection benchmarks and road detection benchmarks of the KITTI dataset for verification. In terms of the accuracy performance indicators quality, detection rate, detection accuracy, and effectiveness, the method in this paper reaches 0.820, 0.863, 0.941, and 0.900, respectively, and the time consumption is only 5.145 milliseconds. Compared with other obstacle detection methods, the detection accuracy and real-time performance in this paper are better. The experimental results show that the method has good robustness and real-time performance for obstacle detection in a complex traffic environment.

Background/Aims: Jagged1 is the ligands of the Notch signaling and has been shown to promote glioma-initiating cells (GICs) in glioblastoma. The role of Jagged1 in GICs invasion and underlying molecular mechanisms remain unclear. Methods: Survival data from R2 genomics analysis, the Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA) and visualization platform database were used to evaluate the effects of Jagged1 on overall patient survival. we investigated Jagged1 induced the GICs cells’ invasion by matrix degradation assays and Transwell cell invasion assays in vitro, then we further explored the underlying molecular mechanisms using Co-immunoprecipitation (co-IP) analysis. Results: High expression of Jagged1 in human glioma was associated with poor survival. Clinical data analysis showed that the Jagged1 was positively correlated with NF-κB(p65). Jagged1-induced invasion of GICs cells through activation of NF-κB(p65) pathway. In vivo, knockdown of Jagged1 could suppress the tumorigenicity of GICs cells through NF-κB(p65) signaling. Conclusion: Insights gained from these findings suggest that Jagged1 plays an important oncogenic role in GICs malignancy by activation of NF-κB(p65) signaling, and Jagged1 could be employed as an effective therapeutic target for GICs.

In this work, we report that large area metal nanowire and polymer nanotube arrays were successfully patterned by photolithographic approach using anodic aluminum oxide (AAO) templates. Nanowires were produced by electrochemical deposition, and nanotubes by solution-wetting. The highly ordered patterns of nanowire and nanotube arrays were observed using scanning electron microscopy (SEM) and found to stand free on the substrate. The method is expected to play an important role in the application of microdevices in the future. [ABSTRACT FROM AUTHOR]

Human-robot collaboration (HRC) is a key feature to distinguish the new generation of robots from conventional robots. Relevant HRC topics have been extensively investigated recently in academic institutes and companies to improve human and robot interactive performance. Generally, human motor control regulates human motion adaptively to the external environment with safety, compliance, stability, and efficiency. Inspired by this, we propose an augmented approach to make a robot understand human motion behaviors based on human kinematics and human postural impedance adaptation. Human kinematics is identified by geometry kinematics approach to map human arm configuration as well as stiffness index controlled by hand gesture to anthropomorphic arm. While human arm postural stiffness is estimated and calibrated within robot empirical stability region, human motion is captured by employing a geometry vector approach based on Kinect. A biomimetic controller in discrete-time is employed to make Baxter robot arm imitate human arm behaviors based on Baxter robot dynamics. An object moving task is implemented to validate the performance of proposed methods based on Baxter robot simulator. Results show that the proposed approach to HRC is intuitive, stable, efficient, and compliant, which may have various applications in human-robot collaboration scenarios.

We have developed a new discrete-time algorithm of stiffness extraction from muscle surface electromyography (sEMG) collected from human operator’s arms and have applied it for antidisturbance control in robot teleoperation. The variation of arm stiffness is estimated from sEMG signals and transferred to a telerobot under variable impedance control to imitate human motor control behaviours, particularly for disturbance attenuation. In comparison to the estimation of stiffness from sEMG, the proposed algorithm is able to reduce the nonlinear residual error effect and to enhance robustness and to simplify stiffness calibration. In order to extract a smoothing stiffness enveloping from sEMG signals, two enveloping methods are employed in this paper, namely, fast linear enveloping based on low pass filtering and moving average and amplitude monocomponent and frequency modulating (AM-FM) method. Both methods have been incorporated into the proposed stiffness variance estimation algorithm and are extensively tested. The test results show that stiffness variation extraction based on the two methods is sensitive and robust to attenuation disturbance. It could potentially be applied for teleoperation in the presence of hazardous surroundings or human robot physical cooperation scenarios.

Due to the controllability of the stiffness and damping under the applied magnetic field, magnetorheological elastomer isolator has been proved effective in the field of vibration control. For the realization of vibration control application, an accurate MRE isolator model is a non-trivial task. However, the existing parametric modeling methods are required to identify too many parameters, which are difficult to implement. Moreover, the corresponding inverse dynamic model of the isolator cannot even be obtained by the identified model inversion. Therefore, this paper proposes a nonparametric neural network approach to approximate the dynamic behaviors of magnetorheological elastomer isolator with the characteristics of nonlinearity and hysteresis. Firstly, the dynamic characteristics of the isolator in shear-compression mixed mode are experimentally tested under different loading conditions. Secondly, based on the experimental data, a NARX neural network with three-layer structure is developed to approximate the functional relationship between inputs (displacement, velocity and current) and output (force) of magnetorheological elastomer isolator. Thirdly, the effectiveness of the network model is validated by comparing the predicted force and experimental force. Finally, considering the common occurrence of inputs with noise disturbance in real application, the robustness of the network is also verified for displacement and current inputs with noise disturbance, respectively. The results of the network generalization for experimental data show that the proposed NARX network is more robust and optimal than BP network. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of micro-vibration control of a precision vibration isolation system with a magnetorheological elastomer (MRE) isolator and fuzzy control strategy. Firstly, a polyurethane matrix MRE isolator working in the shear-compression mixed mode is introduced. The dynamic characteristic is experimentally tested, and the range of the frequency shift and the model parameters of the MRE isolator are obtained from experimental results. Secondly, a new semi-active control law is proposed, which uses isolation structure displacement and relative displacement between the isolation structure and base as the inputs. Considering the nonlinearity of the MRE isolator and the excitation uncertainty of an isolation system, the designed semi-active fuzzy logic controller (FLC) is independent of a system model and is robust. Finally, the numerical simulations and experiments are conducted to evaluate the performance of the FLC with single-frequency and multiple-frequency excitation, respectively, and the experimental results show that the acceleration transmissibility is reduced by 54.04% at most, which verifies the effectiveness of the designed semi-active FLC. Moreover, the advantages of the approach are demonstrated in comparison to the passive control and ON-OFF control. [ABSTRACT FROM AUTHOR]