Service humanoid robotics : a novel interactive system based on bionic-companionship framework

At present, industrial robotics focuses more on motion control and vision, whereas humanoid service robotics (HSRs) are increasingly being investigated and researched in the field of speech interaction. The problem and quality of human-robot interaction (HRI) has become a widely debated topic in academia. Especially when HSRs are applied in the hospitality industry, some researchers believe that the current HRI model is not well adapted to the complex social environment. HSRs generally lack the ability to accurately recognize human intentions and understand social scenarios. This study proposes a novel interactive framework suitable for HSRs. The proposed framework is grounded on the novel integration of Trevarthen ’s (2001) companionship theory and neural image captioning (NIC) generation algorithm. By integrating image-to-natural interactivity generation and communicating with the environment to better interact with the stakeholder, thereby changing from interaction to a bionic-companionship. Compared to previous research a novel interactive system is developed based on the bionic-companionship framework. The humanoid service robot was integrated with the system to conduct preliminary tests. The results show that the interactive system based on the bionic-companionship framework can help the service humanoid robot to effectively respond to changes in the interactive environment, for example give different responses to the same character in different scenes

Service Humanoid Robotics: Review and Design of A Novel Bionic-Companionship Framework

At present, industrial robotics focused more on motion control and vision; whereas Humanoid Service Robotics (HSRs) are increasingly being investigated among researchers' and practitioners' field of speech interactions. The problematic and quality of human-robot interaction (HRI) has become one of the hot potatoes concerned in academia. This paper proposes a novel interactive framework suitable for HSRs. The proposed framework is grounded on the novel integration of Trevarthen Companionship Theory and neural image generation algorithm in computer vision. By integrating the image-to-natural interactivities generation, and communicate with the environment to better interact with the stakeholder, thereby changing from interaction to a bionic-companionship. In addition, the article also reviews the research of neural image generation algorithms and summarizes the application cases of the algorithm structure in the field of robotics from a critical perspective. We believe that the new interactive bionic-companionship framework can enable HSRs to further develop towards robot companions

Rational design of dibenzo[a,c]phenazine-derived isomeric thermally activated delayed fluorescence luminophores for efficient orange-red organic light-emitting diodes

It is an immense challenge to develop efficient long-wavelength (orange-to-red) thermally activated delayed fluorescence (TADF) materials due to the increasing nonradiative decay rates following the energy-gap law. Herein, two pairs of asymmetric isomers; DPyPzTPA and TPAPzDPy, and PyPzDTPA and DTPAPzPy based on electron-deficient moieties dibenzo[a,c]phenazine (Pz) and pyridine (Py) combined with electron-donor units of triphenylamine (TPA) were designed and synthesized. Their photophysical properties could be finely modulated by changing the position and number of Py groups as well as TPA fragments onto Pz cores. DPyPzTPA and DTPAPzPy possess much more rigidity and thus less geometry relaxation and non-radiative decay between ground states and excited states than those of PyPzDTPA and TPAPzDPy. Intriguingly, DPyPzTPA exhibits the highest relative photoluminescence quantum yield (ΦPL) and the fastest reverse intersystem crossing (rISC) rate among them owing to relatively stronger rigidity and spin-orbit coupling (SOC) interactions between the lowest singlet (S1) and energetically close-lying excited triplet state and therefore, the device showed the highest maximum external quantum efficiency (EQEmax) of 16.6% (60.9 lm/W, 53.3 cd/A) with Commission Internationale de I'Eclairage (CIE) coordinates of (0.43, 0.55), peak wavelength 556 nm. In stark contrast, due to its lower rigidity and extremely weak delayed fluorescence (DF) characteristic and thus the much lower ΦPL, TPAPzDPy-based devices are only half as efficient (30.8 lm/W, 27.5 cd/A, 8.3% EQE) despite the isomers possessing equal singlet-triplet energy gaps (ΔEST) of 0.43 eV. On the other hand, the device based on DTPAPzPy also demonstrated a strongly enhanced performance (59.1 lm/W, 52.7 cd/A, 16.1% EQE) than its isomer PyPzDTPA-based device (39.5 lm/W, 35.2 cd/A, 10.3% EQE). This work explicitly implicates that the asymmetric and isomeric molecular design is a potential strategy for promoting the development of highly efficient long-wavelength TADF materials

Microglia exacerbate white matter injury via complement C3/C3aR pathway after hypoperfusion.

Microglial activation participates in white matter injury after cerebral hypoperfusion. However, the underlying mechanism is unclear. Here, we explore whether activated microglia aggravate white matter injury via complement C3-C3aR pathway after chronic cerebral hypoperfusion. Methods: Adult male Sprague-Dawley rats (n = 80) underwent bilateral common carotid artery occlusion for 7, 14, and 28 days. Cerebral vessel density and blood flow were examined by synchrotron radiation angiography and three-dimensional arterial spin labeling. Neurobehavioral assessments, CLARITY imaging, and immunohistochemistry were performed to evaluate activation of microglia and C3-C3aR pathway. Furthermore, C3aR knockout mice were used to establish the causal relationship of C3-C3aR signaling on microglia activation and white matter injury after hypoperfusion. Results: Cerebral vessel density and blood flow were reduced after hypoperfusion (p<0.05). Spatial learning and memory deficits and white matter injury were shown (p<0.05). These impairments were correlated with aberrant microglia activation and an increase in the number of reactive microglia adhering to and phagocytosed myelin in the hypoperfusion group (p<0.05), which were accompanied by the up-regulation of complement C3 and its receptors C3aR (p<0.05). Genetic deletion of C3ar1 significantly inhibited aberrant microglial activation and reversed white matter injury after hypoperfusion (p<0.05). Furthermore, the C3aR antagonist SB290157 decreased the number of microglia adhering to myelin (p<0.05), attenuated white matter injury and cognitive deficits in chronic hypoperfusion rats (p<0.05). Conclusions: Our results demonstrated that aberrant activated microglia aggravate white matter injury via C3-C3aR pathway during chronic hypoperfusion. These findings indicate C3aR plays a critical role in mediating neuroinflammation and white matter injury through aberrant microglia activation, which provides a novel therapeutic target for the small vessel disease and vascular dementia

Prevalence of depression and its correlation with anxiety, headache and sleep disorders among medical staff in the Hainan Province of China

ObjectiveThis cross-sectional survey aimed to investigate the prevalence of depression among medical staff and its risk factors as well as the association between depression, anxiety, headache, and sleep disorders.MethodsStratified random cluster sampling was used to select medical staff from various departments of four hospitals in Sanya City. The Self-Rating Depression Scale (SDS), Self-Rating Anxiety Scale (SAS), and Pittsburgh Sleep Quality Index (PSQI) were used to quantitatively assess depression, anxiety, and sleep disorders. Correlation and regression analyses were performed to determine factors affecting the depression occurrence and scores.ResultsAmong 645 medical staff members, 548 (85%) responded. The 1-year prevalence of depression was 42.7% and the prevalence of depression combined with anxiety, headache, and sleep disorders was 23, 27, and 34.5%, respectively. The prevalence of depression in women, nurses, the unmarried or single group, and the rotating-shift population was significantly higher than that in men (48.3% vs. 27.1%, odds ratio OR = 2.512), doctors (55.2% vs. 26.7%, OR = 3.388), the married group (50.5% vs. 35.8%, OR = 1.900), and the day-shift population (35.2% vs. 7.5%, OR = 1.719). The occurrence of depression was correlated with anxiety, sleep disorders, headache, and migraines, with anxiety having the highest correlation (Spearman’s Rho = 0.531). The SDS was significantly correlated with the SAS and PSQI (Spearman’s Rho = 0.801, 0.503) and was also related to the presence of headache and migraine (Spearman Rho = 0.228, 0.159). Multiple logistic regression indicated that nurse occupation and anxiety were risk factors for depression, while grades of anxiety, sleep disorders and nurse occupation were risk factors for the degree of depression in multiple linear regression.ConclusionThe prevalence of depression among medical staff was higher than that in the general population, especially among women, nurses, unmarried people, and rotating-shift workers. Depression is associated with anxiety, sleep disorders, headache, and migraines. Anxiety and nursing occupation are risk factors for depression. This study provides a reference for the promotion of occupational health among medical professionals

MCR-ALS-based muscle synergy extraction method combined with LSTM neural network for motion intention detection

IntroductionThe time-varying and individual variability of surface electromyographic signals (sEMG) can lead to poorer motor intention detection results from different subjects and longer temporal intervals between training and testing datasets. The consistency of using muscle synergy between the same tasks may be beneficial to improve the detection accuracy over long time ranges. However, the conventional muscle synergy extraction methods, such as non-negative matrix factorization (NMF) and principal component analysis (PCA) have some limitations in the field of motor intention detection, especially in the continuous estimation of upper limb joint angles.MethodsIn this study, we proposed a reliable multivariate curve-resolved-alternating least squares (MCR-ALS) muscle synergy extraction method combined with long-short term memory neural network (LSTM) to estimate continuous elbow joint motion by using the sEMG datasets from different subjects and different days. The pre-processed sEMG signals were then decomposed into muscle synergies by MCR-ALS, NMF and PCA methods, and the decomposed muscle activation matrices were used as sEMG features. The sEMG features and elbow joint angular signals were input to LSTM to establish a neural network model. Finally, the established neural network models were tested by using sEMG dataset from different subjects and different days, and the detection accuracy was measured by correlation coefficient.ResultsThe detection accuracy of elbow joint angle was more than 85% by using the proposed method. This result was significantly higher than the detection accuracies obtained by using NMF and PCA methods. The results showed that the proposed method can improve the accuracy of motor intention detection results from different subjects and different acquisition timepoints.DiscussionThis study successfully improves the robustness of sEMG signals in neural network applications using an innovative muscle synergy extraction method. It contributes to the application of human physiological signals in human-machine interaction

Asymmetric Fraunhofer pattern in Josephson junctions from inversion symmetry broken V5_5S8_8

Introduction of spin orbit coupling (SOC) in a Josephson junction (JJ) gives rise to unusual Josephson effects. We investigate JJs based on a newly discovered heterodimensional superlattice V$_5$S$_8$ with broken inversion symmetry and a special form of SOC. The unique homointerface of our JJs enables elimination of extrinsic effects due to interfaces and disorder. We observe asymmetric Fraunhofer patterns with respect to both the perpendicular magnetic field and the current. The asymmetry is influenced by an in-plane magnetic field. Analysis of the pattern points to a nontrivial spatial distribution of the Josephson current that is intrinsic to the SOC in V$_5$S$_8$.Comment: 16 pages,5 figure

Isolation and characterization of NY-ESO-1–specific T cell receptors restricted on various MHC molecules

Tumor-specific T cell receptor (TCR) gene transfer enables specific and potent immune targeting of tumor antigens. Due to the prevalence of the HLA-A2 MHC class I supertype in most human populations, the majority of TCR gene therapy trials targeting public antigens have employed HLA-A2–restricted TCRs, limiting this approach to those patients expressing this allele. For these patients, TCR gene therapy trials have resulted in both tantalizing successes and lethal adverse events, underscoring the need for careful selection of antigenic targets. Broad and safe application of public antigen-targeted TCR gene therapies will require (i) selecting public antigens that are highly tumor-specific and (ii) targeting multiple epitopes derived from these antigens by obtaining an assortment of TCRs restricted by multiple common MHC alleles. The canonical cancer-testis antigen, NY-ESO-1, is not expressed in normal tissues but is aberrantly expressed across a broad array of cancer types. It has also been targeted with A2-restricted TCR gene therapy without adverse events or notable side effects. To enable the targeting of NY-ESO-1 in a broader array of HLA haplotypes, we isolated TCRs specific for NY-ESO-1 epitopes presented by four MHC molecules: HLA-A2, -B07, -B18, and -C03. Using these TCRs, we pilot an approach to extend TCR gene therapies targeting NY-ESO-1 to patient populations beyond those expressing HLA-A2