Solving Robotic Trajectory Sequential Writing Problem via Learning Character's Structural and Sequential Information

The writing sequence of numerals or letters often affects aesthetic aspects of the writing outcomes. As such, it remains a challenge for robotic calligraphy systems to perform, mimicking human writers' implicit intention. This article presents a new robot calligraphy system that is able to learn writing sequences with limited sequential information, producing writing results compatible to human writers with good diversity. In particular, the system innovatively applies a gated recurrent unit (GRU) network to generate robotic writing actions with the support of a prelabeled trajectory sequence vector. Also, a new evaluation method is proposed that considers the shape, trajectory sequence, and structural information of the writing outcome, thereby helping ensure the writing quality. A swarm optimization algorithm is exploited to create an optimal set of parameters of the proposed system. The proposed approach is evaluated using Arabic numerals, and the experimental results demonstrate the competitive writing performance of the system against state-of-the-art approaches regarding multiple criteria (including FID, MAE, PSNR, SSIM, and PerLoss), as well as diversity performance concerning variance and entropy. Importantly, the proposed GRU-based robotic motion planning system, supported with swarm optimization can learn from a small dataset, while producing calligraphy writing with diverse and aesthetically pleasing outcomes.

Off-the-shelf CAR-engineered natural killer cells targeting FLT3 enhance killing of acute myeloid leukemia

The majority of patients with acute myeloid leukemia (AML) succumb to the disease or its complications, especially among older patients. Natural killer (NK) cells have been shown to have antileukemic activity in patients with AML; however, to our knowledge, primary NK cells armed with a chimeric antigen receptor (CAR) targeting antigens associated with AML as an "off-the-shelf" product for disease control have not been explored. We developed frozen, off-the-shelf allogeneic human NK cells engineered with a CAR recognizing FLT3 and secreting soluble interleukin-15 (IL-15) (FLT3 CAR_sIL-15 NK) to improve in vivo NK cell persistence and T-cell activation. FLT3 CAR_sIL-15 NK cells had higher cytotoxicity and interferon gamma secretion against FLT3+ AML cell lines when compared with activated NK cells lacking an FLT3 CAR or soluble IL-15. Frozen and thawed allogeneic FLT3 CAR_sIL-15 NK cells prolonged survival of both the MOLM-13 AML model as well as an orthotopic patient-derived xenograft AML model when compared with control NK cells. FLT3 CAR_sIL-15 NK cells showed no cytotoxicity against healthy blood mononuclear cells or hematopoietic stem cells. Collectively, our data suggest that FLT3 is an AML-associated antigen that can be targeted by frozen, allogeneic, off-the-shelf FLT3 CAR_sIL-15 NK cells that may provide a novel approach for the treatment of AML.

Decoder Choice Network for Metalearning

Metalearning has been widely applied for implementing few-shot learning and fast model adaptation. Particularly, existing metalearning methods have been exploited to learn the control mechanism for gradient descent processes, in an effort to facilitate gradient-based learning in gaining high speed and generalization ability. This article presents a novel method that controls the gradient descent process of the model parameters in a neural network, by limiting the model parameters within a low-dimensional latent space. The main challenge for implementing this idea is that a decoder with many parameters may be required. To tackle this problem, the article provides an alternative design of the decoder with a structure that shares certain weights, thereby reducing the number of required parameters. In addition, this work combines ensemble learning with the proposed approach to improve the overall learning performance. Systematic experimental studies demonstrate that the proposed approach offers results superior to the state of the art in performing the Omniglot classification and miniImageNet classification tasks.

Encryption and Decryption of Audio Signal and Image Secure Communications Using Chaotic System Synchronization Control by TSK Fuzzy Brain Emotional Learning Controllers

In this article, a new idea of chaos synchronization and chaos-based secure communication is developed. First, the chaotic master system is used as a transmitter in chaos-based secure communication, then a drive signal is constructed, and the information message is encrypted into the drive signal to form a transmitted signal for secure communication. Second, in the receiver, a recurrent Takagi-Sugeno-Kang (TSK) fuzzy brain emotional learning cerebellar model articulation controller (RTFBECAC) is developed to control the slave system to follow the master system in the transmitter. Third, after descripting the chaotic signal, the embedded information message can be recovered. Besides, the stability problem is analyzed in detail based on the stability theory. Finally, two simulation examples, including audio signal and image, are introduced to illustrate the effectiveness and the advantages of the proposed method.

Survival of an HLA-mismatched, bioengineered RPE implant in dry age-related macular degeneration

Cell-based therapies face challenges, including poor cell survival, immune rejection, and integration into pathologic tissue. We conducted an open-label phase 1/2a clinical trial to assess the safety and preliminary efficacy of a subretinal implant consisting of a polarized monolayer of allogeneic human embryonic stem cell-derived retinal pigmented epithelium (RPE) cells in subjects with geographic atrophy (GA) secondary to dry age-related macular degeneration. Postmortem histology from one subject with very advanced disease shows the presence of donor RPE cells 2 years after implantation by immunoreactivity for RPE65 and donor-specific human leukocyte antigen (HLA) class I molecules. Markers of RPE cell polarity and phagocytosis suggest donor RPE function. Further histologic examination demonstrated CD34⁺ structures beneath the implant and CD4⁺, CD68⁺, and FoxP3⁺ cells in the tissue. Despite significant donor-host HLA mismatch, no clinical signs of retinitis, vitreitis, vasculitis, choroiditis, or serologic immune response were detected in the deceased subject or any other subject in the study. Subretinally implanted, HLA-mismatched donor RPE cells survive, express functional markers, and do not elicit clinically detectable intraocular inflammation or serologic immune responses even without long-term immunosuppression.

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Clinical trial of allogeneic RPE cell transplant as AMD therapeutic

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Postmortem histology shows 2-year survival and function of donor RPE cells

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Transplanted RPE cells are mature, polarized, and phagocytic

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Serologic immune and clinical cellular inflammatory responses are not detected

One-Year Follow-Up in a Phase 1/2a Clinical Trial of an Allogeneic RPE Cell Bioengineered Implant for Advanced Dry Age-Related Macular Degeneration

Purpose

To report 1-year follow-up of a phase 1/2a clinical trial testing a composite subretinal implant having polarized human embryonic stem cell (hESC)-derived retinal pigment epithelium (RPE) cells on an ultrathin parylene substrate in subjects with advanced non-neovascular age-related macular degeneration (NNAMD)

Methods

The phase 1/2a clinical trial included 16 subjects in two cohorts. The main endpoint was safety assessed at 365 days using ophthalmic and systemic exams. Pseudophakic subjects with geographic atrophy (GA) and severe vision loss were eligible. Low-dose tacrolimus immunosuppression was utilized for 68 days in the peri-implantation period. The implant was delivered to the worst seeing eye with a custom subretinal insertion device in an outpatient setting. A data safety monitoring committee reviewed all results.

Results

The treated eyes of all subjects were legally blind with a baseline best-corrected visual acuity (BCVA) of ≤ 20/200. There were no unexpected serious adverse events. Four subjects in cohort 1 had serious ocular adverse events, including retinal hemorrhage, edema, focal retinal detachment, or RPE detachment, which was mitigated in cohort 2 using improved hemostasis during surgery. Although this study was not powered to assess efficacy, treated eyes from four subjects showed an increased BCVA of >5 letters (6–13 letters). A larger proportion of treated eyes experienced a >5-letter gain when compared with the untreated eye (27% vs. 7%; P = not significant) and a larger proportion of nonimplanted eyes demonstrated a >5-letter loss (47% vs. 33%; P = not significant).

Conclusions

Outpatient delivery of the implant can be performed routinely. At 1 year, the implant is safe and well tolerated in subjects with advanced dry AMD.

Translational Relevance

This work describes the first clinical trial, to our knowledge, of a novel implant for advanced dry AMD.

Global feather orientations changed by electric current

During chicken skin development, each feather bud exhibits its own polarity, but a population of buds organizes with a collective global orientation. We used embryonic dorsal skin, with buds aligned parallel to the rostral-caudal body axis, to explore whether exogenous electric fields affect feather polarity. Interestingly, brief exogenous current exposure prior to visible bud formation later altered bud orientations. Applying electric pulses perpendicular to the body rostral-caudal axis realigned bud growth in a collective swirl, resembling an electric field pointing toward the anode. Perturbed buds show normal molecular expression and morphogenesis except for their altered orientation. Epithelial-mesenchymal recombination demonstrates the effects of exogenous electric fields are mediated through the epithelium. Small-molecule channel inhibitor screens show Ca2+ channels and PI3 Kinase are involved in controlling feather bud polarity. This work reveals the importance of bioelectricity in organ development and regeneration and provides an explant culture platform for experimentation.

State of health estimation and remaining useful life prediction for lithium-ion batteries using FBELNN and RCMNN

This study proposes the novel method of lithium-ion battery state of health (SoH) estimation and remaining useful life (RUL) prediction to ensure the safety and reliability of the energy storage system. A fuzzy brain emotional learning neural network (FBELNN) is employed to estimate SoH and a recurrent cerebellar model neural network (RCMNN) is used for the RUL prediction. The inputs of FBELNN are extracted features from the monitoring curve of the constant voltage and current, because the lithium-ion battery is seldom completely discharged and the discharging situation in actual operating process is complex. The FBELNN learns the battery aging features that are extracted and selected by discrete wavelet transform and principal component analysis, respectively. The SoH estimation results from the FBELNN are accurate due to the special structure and parameters adaptive laws. The RCMNN and online training again can improve the performance of RUL prediction, because recurrent units can capture the dynamic features. Experimental data are performed by using NASA Prognostics Center of Excellence battery datasets to verify the effectiveness of the proposed method. The results show that the root mean square error of SoH estimation is smaller by the FBELNN and the prediction accuracy of RUL is higher by RCMNN under the different starting points.

A hybrid PSO-parallel fuzzy brain emotional learning classifier for medical diseases diagnosis

This study presents a fuzzy brain emotional learning classifier (FBELC), combined with a modified particle swarm optimization (PSO) algorithm, that allows a network to automatically determine the optimum values for a reward signal and a classification threshold. The designed FBELC model imitates the brain decision process including the emotion information. To verify the predictive performance, a novel fitness function based on the accuracy of the training and cross-validation datasets is used for a PSO algorithm. This PSO-FBELC model is used to diagnose breast tumors and heart diseases. A comparison of simulations using the proposed PSO-FBELC with other processes shows that the proposed model performs better in terms of recognition accuracy.

Hybrid Neural Network Cerebellar Model Articulation Controller Design for Non-linear Dynamic Time-Varying Plants

This study proposes a hybrid method to control dynamic time-varying plants that comprises a neural network controller and a cerebellar model articulation controller (CMAC). The neural-network controller reduces the range and quantity of the input. The cerebellar-model articulation controller is the main controller and is used to compute the final control output. The parameters for the structure of the proposed network are adjusted using adaptive laws, which are derived using the steepest-descent gradient approach and back-propagation algorithm. The Lyapunov stability theory is applied to guarantee system convergence. By using the proposed combination architecture, the designed CMAC structure is reduced, and it makes it easy to design the network size and the initial membership functions. Finally, numerical-simulation results demonstrate the effectiveness of the proposed method.

Type-2 Fuzzy Hybrid Controller Network for Robotic Systems

Dynamic control, including robotic control, faces both the theoretical challenge of obtaining accurate system models and the practical difficulty of defining uncertain system bounds. To facilitate such challenges, this paper proposes a control system consisting of a novel type of fuzzy neural network and a robust compensator controller. The new fuzzy neural network is implemented by integrating a number of key components embedded in a Type-2 fuzzy cerebellar model articulation controller (CMAC) and a brain emotional learning controller (BELC) network, thereby mimicking an ideal sliding mode controller. The system inputs are fed into the neural network through a Type-2 fuzzy inference system (T2FIS), with the results subsequently piped into sensory and emotional channels which jointly produce the final outputs of the network. That is, the proposed network estimates the nonlinear equations representing the ideal sliding mode controllers using a powerful compensator controller with the support of T2FIS and BELC, guaranteeing robust tracking of the dynamics of the controlled systems. The adaptive dynamic tuning laws of the network are developed by exploiting the popular brain emotional learning rule and the Lyapunov function. The proposed system was applied to a robot manipulator and a mobile robot, demonstrating its efficacy and potential; and a comparative study with alternatives indicates a significant improvement by the proposed system in performing the intelligent dynamic control.

[Analysis of CT features of 15 children with 2019 novel coronavirus infection]

Objective: To explore imaging characteristics of children with 2019 novel coronavirus (2019-nCoV) infection. Methods: A retrospective analysis was performed on clinical data and chest CT images of 15 children diagnosed with 2019-nCoV infection. They were admitted to the Third People's Hospital of Shenzhen from January 16 to February 6, 2020. The distribution and morphology of pulmonary lesions on chest CT images were analyzed. Results: Among the 15 children, 5 were males and 10 females, aged from 4 to 14 years. Five of the 15 children were febrile and 10 were asymptomatic on the first visit. The first nasal or pharyngeal swab samples in all the 15 cases were positive for 2019-nCoV nucleic acid. For their first chest CT images, 6 patients had no lesions, while 9 patients had pulmonary inflammatory lesions. Seven cases had small nodular ground glass opacities and 2 cases had speckled ground glass opacities. After 3 to 5 days of treatment, 2019-nCoV nucleic acid in a second respiratory sample turned negative in 6 cases. Among them, chest CT images showed less lesions in 2 cases, no lesion in 3 cases, and no improvement in 1 case. The remaining 9 cases were still positive in a second nucleic acid test. Six patients showed similar chest CT inflammation, while 3 patients had new lesions, which were all small nodular ground glass opacities. Conclusions: The early chest CT images of children with 2019-nCoV infection are mostly small nodular ground glass opacities. The clinical symptoms of children with 2019-nCoV infection are nonspecific. Dynamic reexamination of chest CT and nucleic acid are important.

[Analysis of CT features of 15 Children with 2019 novel coronavirus infection]

Objective: To explore imaging characteristics of children with 2019 novel coronavirus (2019-nCoV) infection. Methods: A retrospective analysis was performed on clinical data and chest CT images of 15 children diagnosed with 2019-nCoV. They were admitted to the third people's Hospital of Shenzhen from January 16 to February 6, 2020. The distribution and morphology of pulmonary lesions on chest CT images were analyzed. Results: Among the 15 children, there were 5 males and 10 females, aged from 4 to 14 years old. Five of the 15 children were febrile and 10 were asymptomatic on first visit. The first nasal or pharyngeal swab samples in all the 15 cases were positive for 2019-nCoV nucleic acid. For their first chest CT images, 6 patients had no lesions, while 9 patients had pulmonary inflammation lesions. Seven cases of small nodular ground glass opacities and 2 cases of speckled ground glass opacities were found. After 3 to 5 days of treatment, 2019-nCoV nucleic acid in a second respiratory sample turned negative in 6 cases. Among them, chest CT images showed less lesions in 2 cases, no lesion in 3 cases, and no improvement in 1 case. Other 9 cases were still positive in a second nucleic acid test. Six patients showed similar chest CT inflammation, while 3 patients had new lesions, which were all small nodular ground glass opacities. Conclusions: The early chest CT images of children with 2019-nCoV infection are mostly small nodular ground glass opacities. The clinical symptoms of children with 2019-nCoV infection are nonspecific. Dynamic reexamination of chest CT and nucleic acid are important.

Ultra-broadband near-infrared emission CuInS2/ZnS quantum dots with high power efficiency and stability for the theranostic applications of mini light-emitting diodes

Broadband near-infrared CuInS₂/ZnS quantum with up to 94.8% quantum yield was synthesized with fast precursor decomposition. The better power efficiency and stability of CuInS₂/ZnS mini-LED were performed with penetration tests and vein imaging.

Robust Adaptive Recurrent Cerebellar Model Neural Network for Non-linear System Based on GPSO

A robust adaptive recurrent cerebellar model articulation controller (RARC) neural network for non-linear systems using the genetic particle swarm optimization (GPSO) algorithm is presented in this study. The RARC is used as the principal tracking controller and the robust compensation controller is designed to recover the residual of the approximation error. In the RARC neural network, the steepest descent gradient method and the Lyapunov function are used for deriving the adaptive law parameter of the system. Besides, the learning rates play an important role in these adaptive laws and they have a great effect on the functions of control systems. In this paper, the combination of the genetic algorithm with the mutation particle swarm optimization algorithm is applied to seek for the optimal learning rates of the RARC adaptation laws. The numerical simulations about the inverted pendulum system as well as the robot manipulator system are given to confirm the effectiveness and practicability of the GPSO-RARC-based control system. Compared with other control schemes, the proposed control scheme is testified to be reliable and can obtain the optimal parameter about the learning rates and the minimum root mean square error for non-linear systems.

An Improved Fuzzy Brain Emotional Learning Model Network Controller for Humanoid Robots

The brain emotional learning (BEL) system was inspired by the biological amygdala-orbitofrontal model to mimic the high speed of the emotional learning mechanism in the mammalian brain, which has been successfully applied in many real-world applications. Despite of its success, such system often suffers from slow convergence for online humanoid robotic control. This paper presents an improved fuzzy BEL model (iFBEL) neural network by integrating a fuzzy neural network (FNN) to a conventional BEL, in an effort to better support humanoid robots. In particular, the system inputs are passed into a sensory and emotional channels that jointly produce the final outputs of the network. The non-linear approximation ability of the iFBEL is achieved by taking the BEL network as the emotional channel. The proposed iFBEL works with a robust controller in generating the hand and gait motion of a humanoid robot. The updating rules of the iFBEL-based controller are composed of two parts, including a sensory channel followed by the updating rules of the conventional BEL model, and the updating rules of the FNN and the robust controller which are derived from the "Lyapunov" function. The experiments on a three-joint robot manipulator and a six-joint biped robot demonstrated the superiority of the proposed system in reference to a conventional proportional-integral-derivative controller and a fuzzy cerebellar model articulation controller, based on the more accurate and faster control performance of the proposed iFBEL.

Wavelet Fuzzy Brain Emotional Learning Control System Design for MIMO Uncertain Nonlinear Systems

This paper aims to present a novel efficient scheme in order to more effectively control the multiple input and multiple output (MIMO) uncertain nonlinear systems. A wavelet fuzzy brain emotional learning controller (WFBELC) model is proposed, which is comprises the benefit of wavelet function, fuzzy theory and brain emotional neural network. When it is used as the main tracking controller for a MIMO uncertain nonlinear systems, the performances of the system, such as the approximation ability, the learning performance and the convergence rate, will be effectively improved. Meanwhile, the gradient descent method is used to adjust the parameters online of WFBELC and the Lyapunov function is employed to guarantee the rapid convergence of the control systems. For the sake of the further illustrating the superiority of this model, two examples of uncertain nonlinear systems, a Duffing-Holmes chaotic system and a Chua's chaotic circuit, are studied. After compared with other models, the test results show that the proposed model can be applied to obtain more satisfactory control performance and be more suitable to deal with the influence of the uncertainty of the MIMO nonlinear systems.

[The clinical characteristics of the evoked nystagmus in the non-affected side during Dix-Hallpike test in the unilateral posterior semicircular canal benign paroxysmal positional vertigo]

Objective: To investigate the clinical characteristics of the evoked nystagmus in the non-affected side during Dix-Hallpike test(D-H test)in unilateral posterior semicircular canal benign paroxysmal positional vertigo(PC-BPPV). Method: Two hundred and thirty-six patients were diagnosed with unilateral PC-BPPV in the Tinnitus and Dizziness clinic.Among them,14 patients exhibited positive nystagmus when the non-affected side was stimulated by D-H test. The clinical data from this subgroup of patients were retrospectively analyzed. Result: The upbeat and torsional nystagmus of 14 patients were all evoked by D-H test in the affected side. 11 cases were right PC-BPPV and 3 cases were left PC-BPPV. Among these 14 patients, 5 patients exhibited the upbeat and torsional nystagmus during D-H test in the non-affected side, which was in the same direction as that evoked in the affected side. Among them, 4 cases were right PC-BPPV and 1 case was left PC-BPPV. However, the downbeat nystagmus of the remaining 9 patients were evoked by D-H test in the non-affected side, in which 7 cases were right PC-BPPV and 2 cases were left PC-BPPV.The nystagmus and vertigo of all patients completely disappeared after performing the Epley or Semont repositioning maneuvers on the affected side. Conclusion: The bilateral positive nystagmus of unilateral PC-BPPV can be evoked by D-H test. The form of nystagmus on the non-affected side is related with the initial position of otoconia in affected semicircular canal and the moving direction of otoconia during the positional test. It is effective to perform Epley or Semont repositioning maneuvers on the affected side. Meanwhile, both the effect of maneuvers and the type of nystagmus evoked by D-H test can verify which side is affected.

[Preliminary analysis of the effects of individualized sound therapy on chronic subjective tinnitus]

Objective:To explore the effect of individualized multi-compound sound therapy on chronic subjective tinnitus and the relationship between tinnitus frequency," notch " hearing loss and the treatment effect of sound therapy.Method: Seventy-eight cases of chronic subjective tinnitus with the pure tone test threshold (PTA)in normal range (≤25 dB HL)were enrolled in this study. Their hearing threshold were re-evaluated using the precise pure-tone audiogram (P-PTA).Tinnitus was evaluated on pitch and loudness matching, and the effectiveness of tinnitus was measured using Tinnitus Handicap Inventory (THI) before they received the individualized customized multi-compound sound therapy for 3 months. THI were re-evaluated on the 30th day and 90th day after treatment.Result: ①The averaged THI score of these patients before the sound treatment was 24.62±15.65 (n=78). The score dropped significantly to 15.82±13.02 and 13.62 ±10.98 on the 30th day and 90th day after treatment, respectively (P<0.01). ②Patient' s gender, age, and the side of tinnitus has no effect on the sound treatment of tinnitus. ③Of these 78 tinnitus patients, 31 patients who showed "notch " hearing loss and 47 patients without "notch " hearing loss in the P-PTA. The averaged THI score between the patients with and without "notch " showed no statistical difference after the treatment (P>0.05).These data suggested that "notch " hearing loss in P-PTA has no effect on the sound therapy.④Of 31 tinnitus patients with "notch " hearing loss, the tinnitus frequency of 22 cases was at the "notch " hearing loss and that of 9 cases was not at the "notch " hearing loss. Sound treatment showed significant between the former and the latter(P<0.05). After 30 days of treatment, tinnitus frequency of four patients whose tinnitus was not at the notch hearing loss drifted to the "notch " hearing loss frequency. Conclusion: Customized multi-compound sound therapy can reduce the THI score of chronic subjective tinnitus patients.The treatment reduced patient's anxiety and improved their quality of life.Sound treatment showed a better improvement in the patients whose tinnitus frequency was located at their notch hearing loss.

Glucohexaose-induced protein phosphatase 2C regulates cell redox status of cucumber seedling

Protein Phosphatase 2C (PP2C) is an important phosphatase-like protein in eukaryotic organisms that can negatively regulate protein kinase cascade abscisic acid (ABA) signal system through phosphorylation and carry out vital roles in various cell processes. The previous study indicated that the accumulation of reactive oxygen species (ROS) is a part of mechanism of glucohexaose-induced resistance in cucumber cotyledons, and CsPP2C80s might play a crucial role in processes related to ROS produce and signal transduction. To identify the mechanism of CsPP2C80s involved in glucohexaose and ABA signaling regulating cell redox status, the effects of glucohexaose and ROS inhibitor pretreatment on endogenous ABA content and ABA signaling genes expression levels of cucumber seedlings were analysed. These results suggest that cucumber CsPP2C80s are involved in ROS accumulation and ABA signal transduction pathway induced by glucohexaose, CsPP2C80s play a positive regulatory role in process of ABA combined with ABA receptors (PYLs) to activate SNF1-related protein kinases 2 (SnRK2s) and regulate NADPH oxidase to produce extracellular hydrogen peroxide (H2O2), providing unequivocal molecular evidence of PP2C-mediated ABA response mechanisms functioning in cell redox status induced by glucohexaose.

A Developmental Learning Approach of Mobile Manipulator via Playing

Inspired by infant development theories, a robotic developmental model combined with game elements is proposed in this paper. This model does not require the definition of specific developmental goals for the robot, but the developmental goals are implied in the goals of a series of game tasks. The games are characterized into a sequence of game modes based on the complexity of the game tasks from simple to complex, and the task complexity is determined by the applications of developmental constraints. Given a current mode, the robot switches to play in a more complicated game mode when it cannot find any new salient stimuli in the current mode. By doing so, the robot gradually achieves it developmental goals by playing different modes of games. In the experiment, the game was instantiated into a mobile robot with the playing task of picking up toys, and the game is designed with a simple game mode and a complex game mode. A developmental algorithm, "Lift-Constraint, Act and Saturate," is employed to drive the mobile robot move from the simple mode to the complex one. The experimental results show that the mobile manipulator is able to successfully learn the mobile grasping ability after playing simple and complex games, which is promising in developing robotic abilities to solve complex tasks using games.

[Features of peripheral nerve injuries in workers exposed to vibration: an analysis of 197 cases]

Objective: To investigate the features of peripheral nerve injuries in workers exposed to vibration. Methods: A total of 197 male workers [median age: 34 years (21-50 years) ; median working years of vibration exposure: 7.3 years (1-20 years) ] engaged in grinding in an enterprise were enrolled. Their clinical data and electromyography results were analyzed to investigate the features of peripheral nerve impairment. Results: Of all workers, 96 (48.73%) had abnormal electromyography results. Of all workers, 88 (44.7%) had simple mild median nerve injury in the wrist, who accounted for 91.7% (88/96) of all workers with abnormal electromy-ography results. Six workers had ulnar nerve injury, superficial radial nerve injury, or/and superficial peroneal nerve injury and accounted for 6.3% of all workers with abnormal electromyography results. Of all workers, 88 had a reduced amplitude of median nerve sensory transduction, and 28 had slowed median nerve sensory transduction. A total of 46 workers were diagnosed with occupational hand-arm vibration disease and hospitalized for treatment. They were followed up for more than 4 months after leaving their jobs, and most of them showed improvements in neural electromyography results and returned to a normal state. Conclusion: Workers exposed to vibration have a high incidence rate of nerve injury in the hand, mainly sensory function impairment at the distal end of the median nerve, and all injuries are mild peripheral nerve injuries. After leaving the vibration job and being treated, most workers can achieve improvements and return to a normal state.

Interferon Gamma and Contact-dependent Cytotoxicity Are Each Rate Limiting for Natural Killer Cell-Mediated Antibody-dependent Chronic Rejection

Natural killer (NK) cells are key components of the innate immune system. In murine cardiac transplant models, donor-specific antibodies (DSA), in concert with NK cells, are sufficient to inflict chronic allograft vasculopathy independently of T and B cells. In this study, we aimed to determine the effector mechanism(s) required by NK cells to trigger chronic allograft vasculopathy during antibody-mediated rejection. Specifically, we tested the relative contribution of the proinflammatory cytokine interferon gamma (IFN-γ) versus the contact-dependent cytotoxic mediators of perforin and the CD95/CD95L (Fas/Fas ligand [FasL]) pathway for triggering these lesions. C3H/HeJ cardiac allografts were transplanted into immune-deficient C57BL/6 rag-/- γc-/- recipients, who also received monoclonal anti-major histocompatibility complex (MHC) class I DSA. The combination of DSA and wild-type NK cell transfer triggered aggressive chronic allograft vasculopathy. However, transfer of IFN-γ-deficient NK cells or host IFN-γ neutralization led to amelioration of these lesions. Use of either perforin-deficient NK cells or CD95 (Fas)-deficient donors alone did not alter development of vasculopathy, but simultaneous disruption of NK cell-derived perforin and allograft Fas expression resulted in prevention of these abnormalities. Therefore, both NK cell IFN-γ production and contact-dependent cytotoxic activity are rate-limiting effector pathways that contribute to this form of antibody-induced chronic allograft vasculopathy.

Lack of the P2X7 receptor protects against AMD-like defects and microparticle accumulation in a chronic oxidative stress-induced mouse model of AMD

The P2X₇ receptor (P2X₇R) is an ATP-gated ion channel that is a key player in oxidative stress under pathological conditions. The P2X₇R is expressed in the retinal pigmented epithelium (RPE) and neural retina. Chronic oxidative stress contributes to the pathogenesis of age-related macular degeneration (AMD). Mice lacking Cu, Zn superoxide dismutase (Sod1) developed chronic oxidative stress as well as AMD-like features, but whether the P2X₇R plays a causative role in oxidative stress-induced AMD is unknown. Thus, the main purpose of this study was to test if concurrent knockout (KO) of P2X₇R could block AMD-like defects seen in Sod1 KO mice. Using multiple approaches, we demonstrate that Sod1 KO causes AMD-like defects, including positive staining for oxidative stress markers, 3-nitrotyrosine and carboxymethyl lysine, thinning of the RPE and retina, thickening of Bruch's membrane, presence of basal laminar and linear deposits, RPE barrier disruption and accumulation of microglia/macrophages. Moreover, we find that Sod1 KO mice accumulate more microparticles (MPs) within RPE/choroid tissues. Concurrent KO of the P2X₇R protects against AMD-like defects and MP accumulation in Sod1 KO mice. Together, we show for the first time, that deficiency of P2X₇R prevents in vivo oxidative stress-induced accumulation of MPs and AMD-like defects. This work could potentially lead to novel therapies for AMD and other oxidative stress-driven diseases.

Adaptive Filter Design Using Type-2 Fuzzy Cerebellar Model Articulation Controller

This paper aims to propose an efficient network and applies it as an adaptive filter for the signal processing problems. An adaptive filter is proposed using a novel interval type-2 fuzzy cerebellar model articulation controller (T2FCMAC). The T2FCMAC realizes an interval type-2 fuzzy logic system based on the structure of the CMAC. Due to the better ability of handling uncertainties, type-2 fuzzy sets can solve some complicated problems with outstanding effectiveness than type-1 fuzzy sets. In addition, the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so that the convergence of the filtering error can be guaranteed. In order to demonstrate the performance of the proposed adaptive T2FCMAC filter, it is tested in signal processing applications, including a nonlinear channel equalization system, a time-varying channel equalization system, and an adaptive noise cancellation system. The advantages of the proposed filter over the other adaptive filters are verified through simulations.

Segment-specific targeting via RNA interference mediates down-regulation of OPN expression in hepatocellular carcinoma cells

Osteopontin (OPN) plays an important role in the metastasis and recurrence of tumors after resection of hepatocellular carcinoma (HCC). In this study, the down-regulation effect on OPN expression in HCC cells of RNA interference (RNAi) molecules designed to target different segments of OPN was investigated to identify a more effective site for OPN knockdown. Specific small interfering RNAs (siRNAs A, B, and C) of OPN were synthesized and transfected into an HCC cell line (HEP-G2; representing the OPNi-A, OPNi-B, and OPNi-C groups). Fluorescent quantitative polymerase chain reaction and immunohistochemical methods were used to detect the mRNA and protein expression of OPN before and after RNAi. Results showed that after transfection, the fluorescence intensity of the OPNi-A group was greater than those of the OPNi-B and OPNi-C groups. After 48 h of transfection, the ΔCT values of OPN mRNA expression in the OPNi-A-C groups increased from 8.31 ± 1.58, 8.78 ± 1.49, and 8.25 ± 1.51 to 12.14 ± 1.43, 10.22 ± 1.97, and 10.48 ± 1.88, respectively (P < 0.05), and the OPN protein levels (immunohistochemistry scores) decreased from 6.44 ± 1.67, 5.43 ± 2.05, and 5.45 ± 2.52 to 2.84 ± 1.52, 4.43 ± 1.65, and 3.95 ± 1.43 points, respectively. These results indicated that RNAi based on different segments of the OPN gene had different down-regulatory effects on OPN expression. Synthesis of targeted siRNA aimed at specific OPN segments might have important significance for dealing with the invasiveness and metastasis of HCC cells.

An Efficient Interval Type-2 Fuzzy CMAC for Chaos Time-Series Prediction and Synchronization

This paper aims to propose a more efficient control algorithm for chaos time-series prediction and synchronization. A novel type-2 fuzzy cerebellar model articulation controller (T2FCMAC) is proposed. In some special cases, this T2FCMAC can be reduced to an interval type-2 fuzzy neural network, a fuzzy neural network, and a fuzzy cerebellar model articulation controller (CMAC). So, this T2FCMAC is a more generalized network with better learning ability, thus, it is used for the chaos time-series prediction and synchronization. Moreover, this T2FCMAC realizes the un-normalized interval type-2 fuzzy logic system based on the structure of the CMAC. It can provide better capabilities for handling uncertainty and more design degree of freedom than traditional type-1 fuzzy CMAC. Unlike most of the interval type-2 fuzzy system, the type-reduction of T2FCMAC is bypassed due to the property of un-normalized interval type-2 fuzzy logic system. This causes T2FCMAC to have lower computational complexity and is more practical. For chaos time-series prediction and synchronization applications, the training architectures with corresponding convergence analyses and optimal learning rates based on Lyapunov stability approach are introduced. Finally, two illustrated examples are presented to demonstrate the performance of the proposed T2FCMAC.