Learning Human-Robot Collaboration Insights through the Integration of Muscle Activity in Interaction Motion Models

Recent progress in human-robot collaboration makes fast and fluid interactions possible, even when human observations are partial and occluded. Methods like Interaction Probabilistic Movement Primitives (ProMP) model human trajectories through motion capture systems. However, such representation does not properly model tasks where similar motions handle different objects. Under current approaches, a robot would not adapt its pose and dynamics for proper handling. We integrate the use of Electromyography (EMG) into the Interaction ProMP framework and utilize muscular signals to augment the human observation representation. The contribution of our paper is increased task discernment when trajectories are similar but tools are different and require the robot to adjust its pose for proper handling. Interaction ProMPs are used with an augmented vector that integrates muscle activity. Augmented time-normalized trajectories are used in training to learn correlation parameters and robot motions are predicted by finding the best weight combination and temporal scaling for a task. Collaborative single task scenarios with similar motions but different objects were used and compared. For one experiment only joint angles were recorded, for the other EMG signals were additionally integrated. Task recognition was computed for both tasks. Observation state vectors with augmented EMG signals were able to completely identify differences across tasks, while the baseline method failed every time. Integrating EMG signals into collaborative tasks significantly increases the ability of the system to recognize nuances in the tasks that are otherwise imperceptible, up to 74.6% in our studies. Furthermore, the integration of EMG signals for collaboration also opens the door to a wide class of human-robot physical interactions based on haptic communication that has been largely unexploited in the field.Comment: 7 pages, 2 figures, 2 tables. As submitted to Humanoids 201

SHON expression predicts response and relapse risk of breast cancer patients after anthracycline-based combination chemotherapy or tamoxifen treatment

BACKGROUND: SHON nuclear expression (SHON-Nuc+) was previously reported to predict clinical outcomes to tamoxifen therapy in ERα+ breast cancer (BC). Herein we determined if SHON expression detected by specific monoclonal antibodies could provide a more accurate prediction and serve as a biomarker for anthracycline-based combination chemotherapy (ACT).METHODS: SHON expression was determined by immunohistochemistry in the Nottingham early-stage-BC cohort (n=1,650) who, if eligible, received adjuvant tamoxifen; the Nottingham ERα- early-stage-BC (n=697) patients who received adjuvant ACT; and the Nottingham locally advanced-BC cohort who received pre- operative ACT with/without taxanes (Neo-ACT, n=120) and if eligible, 5-year adjuvant tamoxifen treatment. Prognostic significance of SHON and its relationship with the clinical outcome of treatments were analysed.RESULTS: As previously reported, SHON-Nuc+ in high risk/ERα+ patients was significantly associated with a 48% death risk reduction after exclusive adjuvant tamoxifen treatment compared with SHON-Nuc- [HR(95%CI)=0.52(0.34-0.78), p=0.002]. Meanwhile, in ERα- patients treated with adjuvant ACT, SHON cytoplasmic expression (SHON-Cyto+) was significantly associated with a 50% death risk reduction compared with SHON-Cyto- [HR(95%CI)=0.50(0.34-0.73), p=0.0003]. Moreover, in patients received Neo-ACT, SHON-Nuc- or SHON-Cyto+ was associated with an increased pathological complete response (pCR) compared with SHON-Nuc+ [21% vs 4%; OR(95%CI)=5.88(1.28-27.03), p=0.012], or SHON-Cyto- [20.5% vs 4.5%; OR(95%CI)=5.43(1.18-25.03), p=0.017], respectively. After receiving Neo-ACT, patients with SHON-Nuc+ had a significantly lower distant relapse risk compared to those with SHON-Nuc- [HR(95%CI)=0.41(0.19-0.87), p=0.038], whereas SHON-Cyto+ patients had a significantly higher distant relapse risk compared to SHON-Cyto- patients [HR(95%CI)=4.63(1.05-20.39), p=0.043]. Furthermore, multivariate Cox regression analyses revealed that SHON-Cyto+ was independently associated with a higher risk of distant relapse after Neo-ACT and 5- year tamoxifen treatment [HR(95%CI)=5.08(1.13-44.52), p=0.037]. The interaction term between ERα status and SHON-Nuc+ (p=0.005), and between SHON-Nuc+ and tamoxifen therapy (p=0.007), were both statistically significant.CONCLUSION: SHON-Nuc+ in tumours predicts response to tamoxifen in ERα+ BC while SHON-Cyto+ predicts response to ACT

Preliminary study on a depositional interface-based reservoir modeling method

According to the channel deposition process and response features, the reservoir modeling based on the depositional interface (DI) is extended from turbidite fans to fluvial sandstones, in order to reconstruct the deposition process and improve the architecture simulation of channel sands. The DI-based modeling of fluvial reservoir is conducted in four steps: (1) Use a simple harmonic oscillation (SHO) damping model with disturbance to generate river flow lines and then complete the beaded association of singe-genetic sands; (2) Identify the interfaces at ends of channels (point bars) to generate the point bar model; (3) Determine the stacking pattern inside channel (point bar), and fit the interfaces with such functions as hyperboloid, paraboloid and polynomial; and (4) Carry out random sampling using the trigonometric function of key parameters for lateral accretion bedding, to complete characterization of point bar. It is concluded that the DI-based modeling method well reproduces the depositional process of fluvial sandstones and finely characterizes the architecture units therein. Key words: DI-based modeling, depositional process, reservoir architecture unit, channel sand, reservoir modeling metho

A High-Sensitivity Flexible Direct X-ray Detector Based on Bi2O3/PDMS Nanocomposite Thin Film

The characteristics of mechanical flexibility, low health risk, and simple processing of polymer nanocomposite materials make them potentially applicable as flexible X-ray detectors. In this study, we report on a high sensitivity, environmentally friendly, and flexible direct X-ray detector using polymer nanocomposite material consisting of bismuth oxide (Bi2O3) nanoparticles and polydimethylsiloxane (PDMS). This detector was realized by printing patterned Ag electrodes on the polymer nanocomposite material. The response of PDMS to X-rays was verified for the first time, and the effect of doping different contents of Bi2O3 nanoparticles on the performance of the device was tested. The optoelectronic performance of the optimized detector indicated a high sensitivity (203.58 μC Gyair−1 cm−2) to low dose rate (23.90 μGyair s−1) at a 150 V bias voltage and the X-ray current density (JX-ray) was 10,000-fold higher than the dark current density (Jdark). The flexible direct X-ray detector could be curled for 10,000 cycles with slight performance degradation. The device exhibited outstanding stability after storage for over one month in air. Finally, this device provides new guidance for the design of high-performance flexible direct X-ray detectors

Ginsenoside Rc: A potential intervention agent for metabolic syndrome

Ginsenoside Rc, a dammarane-type tetracyclic triterpenoid saponin primarily derived from Panax ginseng, has garnered significant attention due to its diverse pharmacological properties. This review outlined the sources, putative biosynthetic pathways, extraction, and quantification techniques, as well as the pharmacokinetic properties of ginsenoside Rc. Furthermore, this study explored the pharmacological effects of ginsenoside Rc against metabolic syndrome (MetS) across various phenotypes including obesity, diabetes, atherosclerosis, non-alcoholic fatty liver disease, and osteoarthritis. It also highlighted the impact of ginsenoside Rc on multiple associated signaling molecules. In conclusion, the anti-MetS effect of ginsenoside Rc is characterized by its influence on multiple organs, multiple targets, and multiple ways. Although clinical investigations regarding the effects of ginsenoside Rc on MetS are limited, its proven safety and tolerability suggest its potential as an effective treatment option

Spread Mechanism and Control Strategies of Rumor Propagation Model Considering Rumor Refutation and Information Feedback in Emergency Management

The rumor-free equilibrium state and rumor-endemic equilibrium state are two symmetric descriptions of the status of a system. The constant spreading of rumors would affect the smooth operation of emergency management procedures and cause unnecessary social and economic loss. To reduce the negative effect of rumor propagation, in this paper, we introduce a compartmental model of rumor propagation, which considers the rumor refutation of public and information feedback. By deriving mean-field equations that describe the dynamics of the model, we use analytical and numerical solutions of these equations to investigate the threshold and dynamics of the model in both the closed system and open system. The results imply that the initial equilibrium point is not stable and there exists a rumor-free equilibrium point; in the open system, there exists a threshold beyond which rumors can spread; the stability of the initial equilibrium point is related to the threshold R0 = (φ*α)/μ, and there exists a rumor-endemic equilibrium point. The development process of rumor propagation can be divided into four stages: latent period, progressive period, intense period, and recession period. Under the influence of population, rumor spreading can exceed the threshold readily because the migration rate μ is usually less than the proportion of ignorants without critical ability φ, and the rumor spreading process in an open system presents a fluctuating development, the rumor would not disappear in this autonomous system. Based on the analysis, we propose some measures, such as providing open and efficient information queries and exchange platforms, etc

Propofol suppresses cell viability, cell cycle progression and motility and induces cell apoptosis of ovarian cancer cells through suppressing MEK/ERK signaling via targeting circVPS13C/miR-145 axis

Abstract Background Propofol is a kind of common intravenous anaesthetic agent that plays an anti-tumor role in a variety of cancers, including ovarian cancer. However, the working mechanism of Propofol in ovarian cancer needs further exploration. Methods The viability and metastasis of ovarian cancer cells were assessed by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and transwell assays. Flow cytometry was used to evaluate the cell cycle and apoptosis. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to examine the abundance of circular RNA vacuolar protein sorting 13 homolog C (circVPS13C) and microRNA-145 (miR-145). The target relationship between miR-145 and circVPS13C was predicted by circinteractome database and verified by dual-luciferase reporter assay, RNA-binding protein immunoprecipitation (RIP) assay and RNA-pull down assay. Western blot assay was used to detect the levels of phosphorylated extracellular regulated MAP kinase (p-ERK), ERK, p-MAP kinse-ERK kinase (p-MEK) and MEK, in ovarian cancer cells. Results Propofol treatment suppressed the viability, cell cycle and motility and elevated the apoptosis rate of ovarian cancer cells. Propofol up-regulated miR-145 in a dose-dependent manner. Propofol exerted an anti-tumor role partly through up-regulating miR-145. MiR-145 was a direct target of circVPS13C. Propofol suppressed the progression of ovarian cancer through up-regulating miR-145 via suppressing circVPS13C. Propofol functioned through circVPS13C/miR-145/MEK/ERK signaling in ovarian cancer cells. Conclusion Propofol suppressed the proliferation, cell cycle, migration and invasion and induced the apoptosis of ovarian cancer cells through circVPS13C/miR-145/MEK/ERK signaling in vitro