Two-Stage Water Jet Landing Point Prediction Model for Intelligent Water Shooting Robot.

In this paper, an intelligent water shooting robot system for situations of carrier shake and target movement is designed, which uses a 2 DOF (degree of freedom) robot as an actuator, a photoelectric camera to detect and track the desired target, and a gyroscope to keep the robot's body stable when it is mounted on the motion carriers. Particularly, for the accurate shooting of the designed system, an online tuning model of the water jet landing point based on the back-propagation algorithm was proposed. The model has two stages. In the first stage, the polyfit function of Matlab is used to fit a model that satisfies the law of jet motion in ideal conditions without interference. In the second stage, the model uses the back-propagation algorithm to update the parameters online according to the visual feedback of the landing point position. The model established by this method can dynamically eliminate the interference of external factors and realize precise on-target shooting. The simulation results show that the model can dynamically adjust the parameters according to the state relationship between the landing point and the desired target, which keeps the predicted pitch angle error within 0.1°. In the test on the actual platform, when the landing point is 0.5 m away from the position of the desired target, the model only needs 0.3 s to adjust the water jet to hit the target. Compared to the state-of-the-art method, GA-BP (genetic algorithm-back-propagation), the proposed method's predicted pitch angle error is within 0.1 degree with 1/4 model parameters, while costing 1/7 forward propagation time and 1/200 back-propagation calculation time.

[Identification of pyrrosiae folium and its adulterants based on psbA-trnH sequence].

In this study, the psbA-trnH sequence as DNA barcode was used to evaluate the accuracy and stability for identification pteridophyte medicinal material Pyrrosiae Foliumas from adulterants. Genomic DNA from 106 samples were extracted successfully. The Kimura 2-Parameter (K2P) distances and ML tree were calculated using software MEGA 6.0. The intra-specific genetic distances of 3 original plants were lower than inter-specific genetic distances of adulterants. The ML tree indicated that Pyrrosiae Folium can be distinguished from its adulterants obviously. Therefore, the psbA-trnH sequence as a barcode of the pteridophyte, can accurately and stably distinguish Pyrrosiae Folium from its adulterants.

[Identification of plantaginis semen based on ITS2 and psbA-trnH sequences].

In order to evaluate the efficiency of ITS2 and psbA-trnH sequences used as DNA barcodes to distinguish Plantaginis Semen from its adulterants, we collected 71 samples of Plantaginis Semen and its adulterants. The ITS2 and psbA-trnH sequences were aligned through Clustal W, and the genetic distances were calculated by kimura 2-parameter (K2P) model and the Neighbor-Joining (NJ) phylogenetic trees were constructed using MEGA 5.1. The results indicated that the ITS2 sequence lengths of Plantago asiatica and P. depressa were 199 bp and 200 bp, respectively; the maximum intra-specific K2P distance were lower than the minimum inter-specific K2P distance; the NJ tree based on ITS2 sequence indicated that Plantaginis Semen and its adulterants could be distinguished clearly. The sequence lengths of psbA-trnH of both P. asiatica and P. depressa were 340 bp; the maximum intra-specific K2P distances were lower than the minimum inter-specific K2P distance; the NJ tree based on psbA-trnH sequence showed that Plantaginis Semen can be distinguished clearly from its adulterants except for P. major. Therefore, ITS2 sequences can be used as an ideal DNA barcode to distinguish Plantaginis Semen from its adulterants.

Velocity-aware spatial-temporal attention LSTM model for inverse dynamic model learning of manipulators.

Introduction: An accurate inverse dynamics model of manipulators can be effectively learned using neural networks. However, further research is required to investigate the impact of spatiotemporal variations in manipulator motion sequences on network learning. In this work, the Velocity Aware Spatial-Temporal Attention Residual LSTM neural network (VA-STA-ResLSTM) is proposed to learn a more accurate inverse dynamics model, which uses a velocity-aware spatial-temporal attention mechanism to extract dynamic spatiotemporal features selectively from the motion sequence of the serial manipulator. Methods: The multi-layer perception (MLP) attention mechanism is adopted to capture the correlation between joint position and velocity in the motion sequence, and the state correlation between hidden units in the LSTM network to reduce the weight of invalid features. A velocity-aware state fusion approach of LSTM network hidden units' states is proposed, which utilizes variation in joint velocity to adapt to the temporal characteristics of the manipulator dynamic motion, improving the generalization and accuracy of the neural network. Results: Comparative experiments have been conducted on two open datasets and a self-built dataset. Specifically, the proposed method achieved an average accuracy improvement of 61.88% and 43.93% on the two different open datasets and 71.13% on the self-built dataset compared to the LSTM network. These results demonstrate a significant advancement in accuracy for the proposed method. Discussion: Compared with the state-of-the-art inverse dynamics model learning methods of manipulators, the modeling accuracy of the proposed method in this paper is higher by an average of 10%. Finally, by visualizing attention weights to explain the training procedure, it was found that dynamic modeling only relies on partial features, which is meaningful for future optimization of inverse dynamic model learning methods.

Eye movements as predictor of cognitive improvement after cognitive remediation therapy in patients with schizophrenia.

Aim: Baseline cognitive functions of patients predicted the efficacy of cognitive remediation therapy (CRT), but results are mixed. Eye movement is a more objective and advanced assessment of cognitive functions than neuropsychological testing. We aimed to investigate the applicability of eye movements in predicting cognitive improvement after patients with schizophrenia were treated with CRT. Methods: We recruited 79 patients with schizophrenia to complete 8 weeks of CRT and assessed their cognitive improvement outcomes. Eye movements were assessed by prosaccades, antisaccades, and free-viewing tasks at baseline, and neuropsychological tests in four cognitive domains were assessed before and after treatment to calculate treatment outcomes. Predictors of demographic information, clinical characteristics, and eye movement measures at baseline on cognitive improvement outcomes were analyzed using logistic regression analysis. We further compared the predictive performance between eye movement measurements and neuropsychological test regarding the effect of CRT on cognitive improvement, and explored factors that could be affect the treatment outcomes in different cognitive domains. Results: As operationally defined, 33 patients showed improved in cognition (improved group) and 46 patients did not (non-improved group) after CRT. Patients with schizophrenia being employed, lower directional error rate in antisaccade task, and lower the gap effect (i.e., the difference in saccadic latency between the gap condition and overlap condition) in prosaccade task at baseline predicted cognitive improvement in CRT. However, performance in the free-viewing task not associated with cognitive improvement in patients in CRT. Our results show that eye-movement prediction model predicted the effect of CRT on cognitive improvement in patients with schizophrenia better than neuropsychological prediction model in CRT. In addition, baseline eye-movements, cognitive reserve, antipsychotic medication dose, anticholinergic cognitive burden change, and number of training sessions were associated with improvements in four cognitive domains. Conclusion: Eye movements as a non-invasiveness, objective, and sensitive method of evaluating cognitive function, and combined saccadic measurements in pro- and anti-saccades tasks could be more beneficial than free-viewing task in predicting the effect of CRT on cognitive improvement in patients with schizophrenia.

[Study on extraction and purification technology of Hubei ophiopogon saponins].

OBJECTIVE: To explore the extraction and purification technology of total saponins from the effective parts of Liriope spicata. METHODS: Orthogonal design was used. Macroporous resin was selected to separate and purify total saponin from the effective parts of Liriope spicata. The process validation was conducted. The total saponins was determined by Ultraviolet Spectrophotometry. RESULTS: The optimal extraction conditions were as follows: 10 times the amount of ethanol (70%) for each occasion and hot reflux (3 x 2 h). Total saponins was purified by D101 macroporous resin. The concentration of eluting ethanol was 50% - 70%. Ethanol (70%) was selected as the best eluent. The result of process validation was consistent with the study. CONCLUSION: The process is simple and stable enough to significantly improve the extraction rate of the effective parts. The study can provide reference for the research and production of effective parts of traditional Chinese medicine such as Liriope spicata.

A deep learning-based model for detecting depression in senior population.

Objectives: With the attention paid to the early diagnosis of depression, this study tries to use the biological information of speech, combined with deep learning to build a rapid binary-classification model of depression in the elderly who use Mandarin and test its effectiveness. Methods: Demographic information and acoustic data of 56 Mandarin-speaking older adults with major depressive disorder (MDD), diagnosed with the Mini-International Neuropsychiatric Interview (MINI) and the fifth edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5), and 47 controls was collected. Acoustic data were recorded using different smart phones and analyzed by deep learning model which is developed and tested on independent validation set. The accuracy of the model is shown by the ROC curve. Results: The quality of the collected speech affected the accuracy of the model. The initial sensitivity and specificity of the model were respectively 82.14% [95%CI, (70.16-90.00)] and 80.85% [95%CI, (67.64-89.58)]. Conclusion: This study provides a new method for rapid identification and diagnosis of depression utilizing deep learning technology. Vocal biomarkers extracted from raw speech signals have high potential for the early diagnosis of depression in older adults.

Mass-size distributions of particulate sulfate, nitrate, and ammonium in a particulate matter nonattainment region in southern Taiwan.

Concentrations and distributions of three major water-soluble ion species (sulfate, nitrate, and ammonium) contained in ambient particles were measured at three sampling sites in the Kao-ping ambient air quality basin, Taiwan. Ambient particulate matter (PM) samples were collected in a Micro-orifice Uniform Deposit Impactor from February to July 2003 and were analyzed for water-soluble ion species with an ion chromatograph. The PM1/ PM2.5 and PM1/PM10 concentration ratios at the emission source site were 0.73 and 0.53 and were higher than those (0.68 and 0.48) at the background site because there are more combustion sources (i.e., industrial boilers and traffic) around the emission source site. Mass-size distributions of PM NO3- were found in both the fine and coarse modes. SO4(2-)and NH4+ were found in the fine particle mode (PM2.5), with significant fractions of submicron particles (PM1). The source site had higher PM1/PM10(79, 42, and 90%) and PM1/PM2.5 concentration ratios (90, 58, and 93%) for the three major inorganic secondary aerosol components (SO4(2-), NO3-, and NH4+) than the receptor site (65, 27, and 65% for PM1/PM10, 69, 51, and 70% for PM1/PM2.5. Results obtained in this study indicate that the PM1 (submicron aerosol particles) fraction plays an important role in the ambient atmosphere at both emission source and receptor sites. Further studies regarding the origin and formation of ambient secondary aerosols are planned.

A rat model of thrombosis in common carotid artery induced by implantable wireless light-emitting diode device.

This work has developed a novel approach to form common carotid artery (CCA) thrombus in rats with a wireless implantable light-emitting diode (LED) device. The device mainly consists of an external controller and an internal LED assembly. The controller was responsible for wirelessly transmitting electrical power. The internal LED assembly served as an implant to receive the power and irradiate light on CCA. The thrombus formation was identified with animal sonography, 7 T magnetic resonance imaging, and histopathologic examination. The present study showed that a LED assembly implanted on the outer surface of CCA could induce acute occlusion with single irradiation with 6 mW/cm(2) LED for 4 h. If intermittent irradiation with 4.3-4.5 mW/cm(2) LED for 2 h was shut off for 30 min, then irradiation for another 2 h was applied; the thrombus was observed to grow gradually and was totally occluded at 7 days. Compared with the contralateral CCA without LED irradiation, the arterial endothelium in the LED-irradiated artery was discontinued. Our study has shown that, by adjusting the duration of irradiation and the power intensity of LED, it is possible to produce acute occlusion and progressive thrombosis, which can be used as an animal model for antithrombotic drug development.

Differences between chondrocytes and bone marrow-derived chondrogenic cells.

Implantation of autologous chondrogenic cells has become the mainstay strategy for repairing articular cartilage defects. Because the availability of autologous chondrocytes is extremely limited, many recent studies have used artificially induced mesenchymal stem cells (iMSCs) as substitutes for chondrocytes. In this study, we analyzed the differences between the iMSCs and chondrocytes, including their molecular biological and mechanical properties. Human bone marrow-derived MSCs were collected and induced to exhibit the chondrogenic phenotype by culturing the pelleted MSCs in a chemically defined culture medium supplemented with transforming growth factor-beta 1. The molecular biological properties of iMSCs and culture-expanded chondrocytes, including their mRNA profiles and surface proteomics, were analyzed using reverse transcription-polymerase chain reaction (RT-PCR) and flow cytometry, respectively. The biomechanical properties of iMSCs and native chondrocytes, including their surface topology, adhesion force, and membrane stiffness, were analyzed using atomic force microscopy (AFM). Both iMSCs and chondrocytes presented type II collagen and glycosaminoglycan, whereas only chondrocytes presented type X collagen. Flow cytometric assays showed that the expression of type II collagen and integrin-1 was higher in the chondrocytes than in the iMSCs. AFM revealed that the MSCs, iMSCs, and chondrocytes greatly differed in their shape. The MSCs were spindle shaped and easily distinguishable from the spherical chondrocytes. The iMSCs appeared round and resembled the spherical chondrocytes; however, the iMSCs were flatter with a central hump of condensed mass and a surrounding thin and broad pleat. The mean adhesion force and mean surface stiffness were significantly lower for the iMSCs (4.54 nN and 0.109 N/m, respectively) than for the chondrocytes (6.86 nN and 0.134 N/m, respectively). To conclude, although the iMSCs exhibited the chondrogenic phenotype, they differed from the chondrocytes in their molecular biological and mechanical properties.

Significance of the pH-induced conformational changes in the structure of C-reactive protein measured by dual polarization interferometry.

Emerging evidence indicates that the conformation of C-reactive protein (CRP) plays important roles in human inflammation and cardiovascular disease (CVD). The different conformations in the structure of CRP under different pH conditions remain an important issue to be investigated for explaining various functions of CRP under certain physiologic and pathologic conditions. We directly measured the pH-induced conformational changes in the structure of CRP by dual polarization interferometry (DPI). The CRP was attached to an aldehyde-functionalized DPI sensor chip at a concentration of 50 µg/ml, and attained 2.019 ng/mm2 to form a surface coverage with a 1.71×10(-14) mol/mm2 CRP monolayer. A pentagonal structure with an average monolayer thickness value of 5.70±0.12nm and a layer density of 0.374±0.058 g/cm2 was obtained at pH 7.0. Moreover, the DPI biosensor signals directly reflected the considerable structural parameters and phenomena of conformational changes of CRP in a pH range of 2.0-10.0. The results obtained showed that the pentameric structure of CRP might dissociated into monomers or monomer aggregates as the pH shifts toward both acidic and alkaline conditions, but only partial rearrangements of CRP subunits might occur at extremely acidic physiological conditions. Considering the proinflammatory effect and subclinical chronic inflammation, pH-induced conformational changes in the structure of CRP between monomeric and pentameric formations may strongly relate to vascular atherosclerosis and subsequent CVD.