Adaptive Excitation Control for the Underactuated Biped Robot

AbstractA control method to make the chaotic gait converge to a stable cycle gait is proposed for the biped robot with knees. This control method is called adaptive excitation control. It is based on the principle of bionics and the principle of self-excited. The control law is a combination of sinusoidal input and sensory feedback control. The control torque is only inputted into the robot's hip. Therefore, the walking process is low energy consuming. Simulation results show that the control method proposed in this paper is effective. It can enlarge the basin of attraction of limit cycle and increase the gait stability

Two Modified Three-Term Type Conjugate Gradient Methods and Their Global Convergence for Unconstrained Optimization

Two modified three-term type conjugate gradient algorithms which satisfy both the descent condition and the Dai-Liao type conjugacy condition are presented for unconstrained optimization. The first algorithm is a modification of the Hager and Zhang type algorithm in such a way that the search direction is descent and satisfies Dai-Liao’s type conjugacy condition. The second simple three-term type conjugate gradient method can generate sufficient decent directions at every iteration; moreover, this property is independent of the steplength line search. Also, the algorithms could be considered as a modification of the MBFGS method, but with different zk. Under some mild conditions, the given methods are global convergence, which is independent of the Wolfe line search for general functions. The numerical experiments show that the proposed methods are very robust and efficient

Joint Extraction of Entities and Relations with a Hierarchical Multi-task Tagging Model

Entity extraction and relation extraction are two indispensable building blocks for knowledge graph construction. Recent works on entity and relation extraction have shown the superiority of solving the two problems in a joint manner, where entities and relations are extracted simultaneously to form relational triples in a knowledge graph. However, existing methods ignore the hierarchical semantic interdependency between entity extraction (EE) and joint extraction (JE), which leaves much to be desired in real applications. In this work, we propose a hierarchical multi-task tagging model, called HMT, which captures such interdependency and achieves better performance for joint extraction of entities and relations. Specifically, the EE task is organized at the bottom layer and JE task at the top layer in a hierarchical structure. Furthermore, the learned semantic representation at the lower level can be shared by the upper level via multi-task learning. Experimental results demonstrate the effectiveness of the proposed model for joint extraction in comparison with the state-of-the-art methods.Comment: 10 pages, 3 figure

PhysBench: A Benchmark Framework for rPPG with a New Dataset and Baseline

In recent years, due to the widespread use of internet videos, physiological remote sensing has gained more and more attention in the fields of affective computing and telemedicine. Recovering physiological signals from facial videos is a challenging task that involves a series of preprocessing, image algorithms, and post-processing to finally restore waveforms. We propose a complete and efficient end-to-end training and testing framework that provides fair comparisons for different algorithms through unified preprocessing and post-processing. In addition, we introduce a highly synchronized lossless format dataset along with a lightweight algorithm. The dataset contains over 32 hours (3.53M frames) of video from 58 subjects; by training on our collected dataset both our proposed algorithm as well as existing ones can achieve improvements

Intraoperative assessment of anastomotic blood supply using indocyanine green fluorescence imaging following esophagojejunostomy or esophagogastrostomy for gastric cancer

ObjectiveThis retrospective study aimed to evaluate the feasibility and safety of intraoperative assessment of anastomotic blood supply in patients undergoing esophagojejunostomy or esophagogastrostomy for gastric cancer using Indocyanine Green Fluorescence Imaging (IGFI).Materials and methodsFrom January 2019 to October 2021, we conducted a retrospective analysis of patients who had undergone laparoscopic gastrectomy for the treatment of gastric cancer. The patients were consecutively enrolled and categorized into two study groups: the Indocyanine Green Fluorescence Imaging (IGFI) group consisting of 86 patients, and the control group comprising 92 patients. In the IGFI group, intravenous administration of Indocyanine Green (ICG) was performed, and we utilized a fluorescence camera system to assess anastomotic blood supply both before and after the anastomosis.ResultsThe demographic characteristics of patients in both groups were found to be comparable. In the IGFI group, the mean time to observe perfusion fluorescence was 26.3 ± 12.0 seconds post-ICG injection, and six patients needed to select a more proximal resection point due to insufficient fluorescence at their initial site of choice. Notably, the IGFI group exhibited a lower incidence of postoperative anastomotic leakage, with no significant disparities observed in terms of pathological outcomes, postoperative recovery, or other postoperative complication rates when compared to the control group (p > 0.05).ConclusionThis study underscores the potential of IGFI as a dependable and pragmatic tool for the assessment of anastomotic blood supply following esophagojejunostomy or esophagogastrostomy for gastric cancer. The use of IGFI may potentially reduce the occurrence of postoperative anastomotic leakage

Lobaplatin-based prophylactic hyperthermic intraperitoneal chemotherapy for T4 gastric cancer patients: A retrospective clinical study

ObjectiveTo explore the clinical efficacy of lobaplatin-based prophylactic hyperthermic intraperitoneal chemotherapy (HIPEC) for patients with T4 gastric cancer after surgery and to evaluate its impact on survival.Materials and methodsData on patients with T4 gastric cancer who underwent radical gastric resection between March 2016 and August 2017 were collected from the National Cancer Center and Huangxing Cancer Hospital. Enrolled patients were divided into two groups according to receiving or not receiving HIPEC.ResultsA total of 106 patients were included in this study; among them, 51 patients underwent radical gastric resection plus prophylactic HIPEC, and 55 patients underwent radical gastric resection only. The baseline characteristics were well balanced between the two groups. The postoperative platelet counts in the HIPEC group were significantly lower than those in the non-HIPEC group (P < 0.05); however, we did not observe any occurrences of serious bleeding in the HIPEC group. There were no significant differences in the postoperative complication rates between the two groups (P > 0.05). The postoperative (1 month) CEA, CA19-9, and CA72-4 levels in the HIPEC group were significantly decreased in the HIPEC group (P < 0.05). At a median follow-up of 59.3 months, 3 (5.5%) patients in the HIPEC group experienced peritoneal recurrence, and 10 (18.2%) patients in the non-HIPEC group experienced peritoneal recurrence (P < 0.05). Both groups had comparable 5-year overall survival (OS) rates (41.1% HIPEC group vs. 34.5% non-HIPEC group, P = 0.118). The 5-year disease-free survival was significantly higher in the HIPEC group than in the non-HIPEC group (28.6% versus 39.7%, p = 0.046).ConclusionsLobaplatin-based prophylactic HIPEC is feasible and safe for patients with T4 gastric cancer and does not increase postoperative adverse effects. The use of HIPEC showed a significant decrease in the incidence of local recurrence rates and blood tumor marker levels. The 5-year disease-free survival was significantly higher in the HIPEC group; however, the 5-year OS benefit was not found in T4 stage patients

A new fault diagnosis and fault-tolerant control method for mechanical and aeronautical systems with neural estimators

A new method of fault detection and fault tolerant control is proposed in this paper for mechanical systems and aeronautical systems. The faults to be estimated and diagnosed are malfunctions occurred within the control loops of the systems, rather than some static faults, such as gearbox fault, component cracks, etc. In the proposed method two neural networks are used as on-line estimators, the fault will be accurately estimated when the estimators are adapted on-line with the post fault dynamic information. Furthermore, the estimated value of faults are used to compensate for the impact of the faults, so that the stability and performance of the system with the faults are maintained until the faulty components to be repaired. The sliding mode control is used to maintain system stability under the post fault dynamics. The control law and the neural network learning algorithms are derived using the Lyapunov method, so that the neural estimators are guaranteed to converge to the fault to be diagnosed, while the entire closed-loop system stability is guaranteed with all variables bounded. The main contribution of this paper to the knowledge in this field is that the proposed method cannot only diagnose and tolerant with constant fault, also diagnose and tolerant with the time-varying faults. This is very important because most faults occurred in industrial systems are time-varying in nature. A simulation example is used to demonstrate the design procedure and the effectiveness of the method. The simulation results are compared with two existing methods that can cope with constant faults only, and the superiority is demonstrated

Insight Into the Pico- and Nano-Phytoplankton Communities in the Deepest Biosphere, the Mariana Trench

As photoautotrophs, phytoplankton are generally present in the euphotic zone of the ocean, however, recently healthy phytoplankton cells were found to be also ubiquitous in the dark deep sea, i.e., at water depths between 2000 and 4000 m. The distributions of phytoplankton communities in much deeper waters, such as the hadal zone, are unclear. In this study, the vertical distribution of the pico- and nano-phytoplankton (PN) communities from the surface to 8320 m, including the epipelagic, mesopelagic, bathypelagic, and hadal zones, were investigated via both 18S and p23S rRNA gene analysis in the Challenger Deep of the Mariana Trench. The results showed that Dinoflagellata, Chrysophyceae, Haptophyta, Chlorophyta, Prochloraceae, Pseudanabaenaceae, Synechococcaceae, and Eustigmatophyceae, etc., were the predominant PN in the Mariana Trench. Redundancy analyses revealed that depth, followed by temperature, was the most important environmental factors correlated with vertical distribution of PN community. In the hadal zone, the PN community structure was considerably different from those in the shallower zones. Some PN communities, e.g., Eustigmatophyceae and Chrysophyceae, which have the heterotrophic characteristics, were sparse in shallower waters, while they were identified with high relative abundance (94.1% and 20.1%, respectively) at the depth of 8320 m. However, the dinoflagellates and Prochloraceae Prochlorococcus were detected throughout the entire water column. We proposed that vertical sinking, heterotrophic metabolism, and/or the transition to resting stage of phytoplankton might contribute to the presence of phytoplankton in the hadal zone. This study provided insight into the PN community in the Mariana Trench, implied the significance of phytoplankton in exporting organic matters from the euphotic to the hadal zone, and also hinted the possible existence of some undetermined energy metabolism (e.g., heterotrophy) of phytoplankton making themselves adapt and survive in the hadal environment

Isoflurane Preconditioning at Clinically Relevant Doses Induce Protective Effects of Heme Oxygenase-1 on Hepatic Ischemia Reperfusion in Rats

<p>Abstract</p> <p>Background</p> <p>Activation of heme oxygenase-1 (HO-1) has been proved to reduce damages to the liver in ischemia reperfusion injury. The objective of present study was to determine whether clinic relevant doses of isoflurane treatment could be sufficient to activate HO-1 inducing, which confers protective effect against hepatic ischemia-reperfusion injury.</p> <p>Methods</p> <p>The hepatic artery and portal vein to the left and the median liver lobes of forty male Sprague-Dawley rats were occluded for 60 minutes. Reperfusion was allowed for 4 hours before the animal subjects were sacrificed. Six groups (n = 12) were included in the study. A negative control group received sham operation and positive control group a standard ischemia-reperfusion regimen. The third group was pretreated with isoflurane prior to the ischemia-reperfusion. The fourth group received an HO-1 inhibitor zinc protoporphyrin (Znpp) prior to the isoflurane pretreatment and the ischemia-reperfusion. The fifth group received Znpp alone before ischemia-reperfusion procedure, and the sixth group was administrated with a HO-1 inducer hemin prior to IR. HO-1 in the liver was measured using an enzymatic activity assay, a Western blot analysis, as well as immunohistochemical method. Extent of liver damage was estimated by determination of the serum transaminases, liver lipid peroxidation and hepatic histology. Infiltration of the liver by neutrophils was measured using a myeloperoxidase activity assay. TNFα mRNA in the liver was measured using RT-PCR.</p> <p>Results</p> <p>Isoflurane pretreatment significantly attenuated the hepatic injuries and inflammatory responses caused by the ischemia reperfusion. Selectively inhibiting HO-1 with ZnPP completed blocked the protective effects of isoflurane. Inducing HO-1 with hemin alone produced protective effects similar in magnitude to that of isoflurane.</p> <p>Conclusions</p> <p>Clinic relevant doses of isoflurane attenuate ischemia reperfusion injury in rats by increasing the HO-1 expression and activity.</p