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This letter presents a state estimation algorithm for the legged robot by defining the problem as a Maximum A Posteriori (MAP) estimation problem and solving the problem with the Gauss-Newton algorithm. Moreover, marginalization by the Schur Complement method is adopted to make a fixed size problem. Each component of the cost function and its Jacobian are derived utilizing the SO(3) manifold structure, while we reparameterize the state with nominal state and variation to make linear algebra and vector calculus applied properly. Furthermore, a slip rejection method is proposed to reduce the erroneous effect of fault modeling of kinematics models. The proposed algorithm is verified by comparison with the Invariant Extended Kalman Filter (IEKF) in real robot experiments on various environments.

In this work, a non-gaited framework for legged system locomotion is presented. The approach decouples the gait sequence optimization by considering the problem as a decision-making process. The redefined contact sequence problem is solved by utilizing a Monte Carlo Tree Search (MCTS) algorithm that exploits optimization-based simulations to evaluate the best search direction. The proposed scheme has proven to have a good trade-off between exploration and exploitation of the search space compared to the state-of-the-art Mixed-Integer Quadratic Programming (MIQP). The model predictive control (MPC) utilizes the gait generated by the MCTS to optimize the ground reaction forces and future footholds position. The simulation results, performed on a quadruped robot, showed that the proposed framework could generate known periodic gait and adapt the contact sequence to the encountered conditions, including external forces and terrain with unknown and variable properties. When tested on robots with different layouts, the system has also shown its reliability.

The reduction of energy consumption in the reverse osmosis (RO) process is critical. The forward osmosis (FO)-RO hybrid process can be suggested to reduce RO energy consumption. In this study, a numerical FO-RO process model was developed to analyze the FO-RO hybrid process. The performance of the FO-RO hybrid process was compared with the stand-alone RO process. In addition, the impacts of the control parameters for operation, and the intrinsic membrane parameters, were analyzed using sensitivity analysis. In conclusion, the FO-RO hybrid process involves less RO energy consumption than the stand-alone RO process. The FO draw flow velocity and the RO applied pressure were derived as the major factors for controlling the FO-RO process. In addition, the control parameters for operation were found to be more important than the intrinsic membrane parameters in the minimization of RO energy consumption. Subsequently, the FO elements installed in front of the RO process should be configured with a parallel connection, in order to minimize RO energy consumption. The results in this study could be used to develop guidelines for the optimal design of the FO-RO hybrid process.

The potassium (K) sorption characteristics with three adsorbents, natural zeolite, ammonium acetate-treated zeolite, and manganese nodule, were studied and compared to see the potential use of manganese nodule as an alternative K adsorbent. In general, the Langmuir isotherm could fit the K sorption in the KCl solutions at different pH conditions better than the Freundlich isotherm. Based on the Langmuir parameters, the maximum K sorption was greater for the zeolite-based adsorbents (i.e., 40–42 mg g−1) than the manganese nodule (i.e., 2.0 mg g−1) at acidic conditions, while the manganese nodule (i.e., 9.7 mg g−1) showed better K sorption at neutral conditions. With the seawater samples, the zeolite-based adsorbents showed higher K recovery (4–14%) than the manganese nodule (0–8.8%). The K sorption on the zeolite-based adsorbents followed the pseudo-second-order kinetics and the K sorption rates were higher for the treated zeolite than the natural zeolite. The repeated sorption tests showed that the natural zeolite could potentially be reused up to three times without any significant loss of K sorption capacity, while the ammonium acetate-treated zeolite lost its K sorption capacity after the single sorption test. Overall, the results show that the manganese nodule may potentially be the alternative to zeolite for K recovery under certain conditions, yet the zeolite-based adsorbents are generally better than the manganese nodule. Thus, more studies to enhance the K recovery using zeolite, including surface modified zeolite, are recommended.

Despite many kinds of research on pressure-retarded osmosis (PRO), feasibility studies for PRO are still insufficient. To provide a better understanding of PRO-hybridized processes, an energy efficiency analysis should reflect the hybridization features of three processes, including PRO, seawater reverse osmosis (SWRO), and membrane distillation (MD). To this end, a new dimensionless (i.e., unitless or scale-free) performance index is proposed to facilitate a fair comparison of energy efficiency between SWRO-PRO and SWRO-MD-PRO. The new performance index physically implies a ratio of the total energy recovered by PRO to the total energy consumed by SWRO and MD. The performances of hybridized processes were estimated with the new index and compared to each other after running several simulations. The simulation results showed that SWRO-MD-PRO generally has a higher energy efficiency than SWRO-PRO if an inexpensive heat source, such as waste heat, is used. However, the energy efficiencies of both PRO-hybridized processes were different according to the simulation conditions. Therefore, it can be concluded that energy optimization for PRO-hybridized processes should be conducted differently than for SWRO. The results from this study are expected to play a key role in providing a new roadmap for PRO-hybridized process research.

Heavy metals are naturally occurring trace elements present in the environment, including soil, water, and air. However, high heavy metal concentration contamination from waste is a serious environmental problem brought on by industrial activities. The research in this study evaluated different biomineralized CaCO3 forms from individual bacteria species in heavy-metal-contaminated soils and mine tailings. Scanning electron microscope (SEM) images of the crystals were used to characterize the precipitated CaCO3. Generally, urea-hydrolysis bacteria form minerals via a microbiologically induced calcite precipitation (MICP) process. These bacteria produce the urease enzyme, which leads to urea-hydrolysis. These bacteria were isolated from heavy-metal-contaminated soils and characterized for their potential utilization in the S/S process. Optimum conditions for indigenous bacterial growth were 30 °C and a pH range of 7–8; and growth patterns were further affected by the growth medium salinity. SEM and X-ray diffraction (XRD) analyses demonstrated that bioaccumulated heavy metal ions were deposited around the cell envelope as rhombohedral and sphere shaped crystalline carbonate minerals in optimum conditions. In this study, the authors hypothesize that the indigenous bacteria can effectively precipitate heavy metals in soil and mine tailing with the urea-hydrolysis enzyme, and play an important role in heavy metal stabilization.

Climate change is a primary driver that alters water pollution hotspots in watersheds, which complicates the use of Best management practices (BMPs) for diffuse pollution mitigation strategies. The objective of this study is to evaluate future changes in BMPs on total phosphorus (TP) loads to the river system, depending on climate change. Current weather data were collected from 2000 to 2010 and future weather data from 2040 to 2050 were obtained from regional climate model simulations based on Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 scenarios. This study describes various BMP implementation plans at affordable cost that are adapted to different weather conditions, current (for 2000–2010) and future climate scenarios (for 2040–2050). The Soil and Water Assessment Tool (SWAT), i.e., one of the deterministic models for watershed management, was used to estimate total phosphorus (TP) removal efficiency of various types of BMP at two crop fields (rice paddy and soybean fields) in the Yeongsan River (YR) watershed of Korea. The Non-dominated Sorting Genetic Algorithm II (NSGA-II), i.e., one of the artificial intelligence (AI) models for decision support framework, was applied to obtain allow for trade-off analysis between two conflict objectives, the maximum TP load reduction against implementation costs. The SWAT simulation results showed that the model performance based on the Nash-Sutcliffe efficiency and percent bias was acceptable for simulating three parameters; daily flow discharge, monthly sediment loads, and TP loads in the river. As a result, monthly sediment loads and TP loads increase remarkably under all future climate change scenarios except for July, when a comparable amount of precipitation is recorded during the present and future conditions. New implementation of BMPs, therefore, will be required for future climate change scenarios to achieve 50% TP load reduction in the given watershed condition. Interestingly, parallel terraces which showed good efficiency in reducing TP loads at both fields under the current weather condition cannot be effective any more under the worst-case weather scenario in the future climate. In such a case, detention ponds can be proposed as BMP alternative to parallel terraces. Overall, this study not only demonstrates that watershed management plans using BMPs should be adjusted according to climate change scenarios, but also that the hybrid use of SWAT model and AI can help in refining existing and future BMPs at affordable cost.

Background and aims The nonalcoholic fatty liver disease fibrosis score (NFS) is comprised of metabolic risk indicators that may accurately predict residual cardiovascular risk in patients with CAD. Method This is a nested case control study of the post PCI registry from single tertiary hospital. Among 5589 patients who underwent PCI from 2010 through 2014, previously diagnosed 1510 NAFLD patients and 296 consecutive NAFLD patients who had undergone both PCI and ultrasonography of abdomen within 1 year between the tests were enrolled. (median age, 64y (IQR 55–73)). We applied the NFS to the patients at baseline, using validated NFS cut-offs and 201 patients with higher NFS, defined as NFS >0.67 at PCI, were 1:1 matched with controls, based on propensity scores for higher NFS >0.67. Results Higher NFS (NFS >0.67) was more prevalent in patients with left ventricle (LV) dysfuction (LVEF at PCI Conclusion With a longitudinal assessment of the association between NAFLD status by NFS and the risk of CV death, we found post-PCI patients with persistent higher NFS were at higher risk of CV death compared with those without. KM rates of CV death according to NFS Funding Acknowledgement Type of funding source: None

Background Electrocardiographs (ECG) are obtained by a digital signal. However, they are still printed out of paper to read by physicians. Digitizing the analog ECG from the paper to digital signal make us much easier to access of bid data pool form the daily clinical practice and previous resources. Objective The goal of this study is to digitize paper ECG to detect premature ventricular contraction (PVC). Methods This system consists of 2 steps; digitization and PVC detection. Results First, for digitization, ECG are filtered by the specific cut-off value of red, green and blue, then the filtered ECG image is changed into gray scale. In order to extract ECG signal, the algorithm fine the only one of the biggest white body throughout the X-axis. The X and Y axis is matched with distance and amplitude, depending on dots per inch (DPI). Second, to detect PVC, ECG signal is filtered to eliminate baseline wandering. The characteristics of PVC is higher amplitude and longer duration than normal sinus rhythm, we set two criteria to detect the PVC: 1.5 times the duration, 1.2 points out of the amplitude. For the synchronization of timing, lead II rhythm strip was used by PVC detection and then the rest of 12-lead ECG is matched based on lead II synchronization (Figure 1). We applied this algorithm to the 300 real patient's ECG. 290 of 300 (96.7%) ECG are successfully digitized signal and PVC detection. Conclusion We successfully developed the algorithm analog ECG signal into digital signal to detect PVC. In the future, this method helps to gather big data from ECG papers to develop a new algorithm to localization of PVC. Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Korean Heart Rhythm Society 2019 Research Fund

This paper presents a constrained nonlinear model predictive control (NMPC) framework for legged locomotion. The framework assumes a legged robot as a floating base single rigid body with contact forces being applied to the body as external forces. With consideration of orientation dynamics evolving on the rotation manifold SO(3), analytic Jacobians which are necessary for constructing the gradient and the Gauss-Newton Hessian approximation of the objective function are derived. This procedure also includes the reparameterization of the robot orientation on SO(3) to orientation error in the tangent space of that manifold. Obtained gradient and Gauss-Newton Hessian approximation are utilized to solve nonlinear least squares problems formulated from NMPC in a computationally efficient manner. The proposed algorithm is verified on various types of legged robots and gaits in a simulation environment.

In this study, we conducted a numerical simulation to evaluate stability in the seawater reverse osmosis (SWRO) process against seasonal variations of feed water. The impact of element configuration on SWRO operation was analyzed using a process model consisting of the solution–diffusion model. Seawater quality and temperature data collected from the intake of the Fujairah desalination plant (United Arab Emirates) were used to identify optimum internally staged design (ISD) configurations. Monitoring data were also used to simulate changes in SWRO performance. The process performance of the ISD configurations as compared to conventional design configurations in terms of specific energy consumption, permeate total dissolved solids concentration and recovery ratio. The results showed that SWRO processes with four ISD configurations met the performance requirements over 12 months despite the fluctuations in seawater quality and temperature. The pre-diction results of the ISD configurations showed stable operation during the 12 month simulation period. These configurations had a significant advantage with respect to membrane maintenance. This study’s findings could be used to optimize the element configuration of the SWRO process by predicting the process performance while accounting for seasonal variations of seawater quality and temperature.