A global multinational survey of cefotaxime-resistant coliforms in urban wastewater treatment plants

The World Health Organization Global Action Plan recommends integrated surveillance programs as crucial strategies for monitoring antibiotic resistance. Although several national surveillance programs are in place for clinical and veterinary settings, no such schemes exist for monitoring antibiotic-resistant bacteria in the environment. In this transnational study, we developed, validated, and tested a low-cost surveillance and easy to implement approach to evaluate antibiotic resistance in wastewater treatment plants (WWTPs) by targeting cefotaxime-resistant (CTX-R) coliforms as indicators. The rationale for this approach was: i) coliform quantification methods are internationally accepted as indicators of fecal contamination in recreational waters and are therefore routinely applied in analytical labs; ii) CTX-R coliforms are clinically relevant, associated with extended-spectrum ?-lactamases (ESBLs), and are rare in pristine environments. We analyzed 57 WWTPs in 22 countries across Europe, Asia, Africa, Australia, and North America. CTX-R coliforms were ubiquitous in raw sewage and their relative abundance varied significantly (< 0.1% to 38.3%), being positively correlated (p < 0.001) with regional atmospheric temperatures. Although most WWTPs removed large proportions of CTX-R coliforms, loads over 103 colony-forming units per mL were occasionally observed in final effluents. We demonstrate that CTX-R coliform monitoring is a feasible and affordable approach to assess wastewater antibiotic resistance status

Study of Working Medium Performance by Acoustic Emission in EDM Machining of Ti6Al4V

In electrical discharge machining (EDM), the working medium plays an important role in the material removal process. Lots of methods have been utilized to study this process, but a widely accepted explanation about this process has not been yet accomplished. In this study, the acoustic emission (AE) sensor was fixed on EDM machine to study the material removal process by observing the expansion and contraction process of gas bubble surrounding the discharge plasma. The machining performance in different working mediums was studied for Ti-6Al-4V machining in air, kerosene, and water-based emulsion. Discharge in different working mediums would result in different material removal rates and surface quality. The difference of AE wave frequency domain distribution for discharge in different working mediums was studied. It was observed that the frequency of acoustic emission wave generated by discharge in different working mediums would be different. The characteristic difference of single AE wave generated by discharge in air, kerosene, and water-based emulsion was compared. It was found that the duration time and peak amplitude of acoustic emission wave generated by discharge in different working mediums were different, and the acoustic emission wave generated by discharge in water-based emulsion would last longer and get higher peak amplitude compared to discharge in air and kerosene. The significant difference of AE wave generated by discharge in water-based emulsion from that in kerosene was found. Based on the acoustic emission wave observation, the special characteristic of the material removal process for discharge in water-based emulsion was found

A Closed-Form Solution for the Inverse Kinematics of the 2<i>n</i>-DOF Hyper-Redundant Manipulator Based on General Spherical Joint

This paper presents a closed-form inverse kinematics solution for the 2n-degree of freedom (DOF) hyper-redundant serial manipulator with n identical universal joints (UJs). The proposed algorithm is based on a novel concept named as general spherical joint (GSJ). In this work, these universal joints are modeled as general spherical joints through introducing a virtual revolution between two adjacent universal joints. This virtual revolution acts as the third revolute DOF of the general spherical joint. Remarkably, the proposed general spherical joint can also realize the decoupling of position and orientation just as the spherical wrist. Further, based on this, the universal joint angles can be solved if all of the positions of the general spherical joints are known. The position of a general spherical joint can be determined by using three distances between this unknown general spherical joint and another three known ones. Finally, a closed-form solution for the whole manipulator is solved by applying the inverse kinematics of single general spherical joint section using these positions. Simulations are developed to verify the validity of the proposed closed-form inverse kinematics model

A Closed-Form Solution for the Inverse Kinematics of the 2n-DOF Hyper-Redundant Manipulator Based on General Spherical Joint

This paper presents a closed-form inverse kinematics solution for the 2n-degree of freedom (DOF) hyper-redundant serial manipulator with n identical universal joints (UJs). The proposed algorithm is based on a novel concept named as general spherical joint (GSJ). In this work, these universal joints are modeled as general spherical joints through introducing a virtual revolution between two adjacent universal joints. This virtual revolution acts as the third revolute DOF of the general spherical joint. Remarkably, the proposed general spherical joint can also realize the decoupling of position and orientation just as the spherical wrist. Further, based on this, the universal joint angles can be solved if all of the positions of the general spherical joints are known. The position of a general spherical joint can be determined by using three distances between this unknown general spherical joint and another three known ones. Finally, a closed-form solution for the whole manipulator is solved by applying the inverse kinematics of single general spherical joint section using these positions. Simulations are developed to verify the validity of the proposed closed-form inverse kinematics model

Self-Calibration for the General Cable-Driven Serial Manipulator with Multi-Segment Cables

This paper focuses on the kinematic calibration problem for the general cable-driven serial manipulator (CDSM) with multi-segment cables to improve its motion control accuracy. Firstly, to fully describe the calibration parameters of cables, links, joint positions, and the transmission system, this paper proposes a new cable routing description method named cable-routing configuration struct (CRCS), which provides a complete set of parameters to be calibrated for the proposed self-calibration algorithm. Then, a self-calibration algorithm for CDSM with motor incremental encoders is proposed, which can calibrate the robot at one time only using sufficient measured motor and joint positions. Its premise, the initial cable length, needs to be calibrated. Finally, the parameters of a three-DOF (degree of freedom) six-cable CDSM were described using the CRCS description method, and a comparative experiment was carried out on the same motion controller using the parameters before and after calibration. The experiment results of trajectory tracking error showed that the calibration parameters obtained by the proposed calibration algorithm can significantly improve the motion control accuracy of the three-DOF six-cable CDSM. This verified the correctness and effectiveness of the proposed calibration algorithm

Enhancing Safety in Automatic Electric Vehicle Charging: A Novel Collision Classification Approach

With the rise of electric vehicles, autonomous driving, and valet parking technologies, considerable research has been dedicated to automatic charging solutions. While the current focus lies on charging robot design and the visual positioning of charging ports, a notable gap exists in addressing safety aspects during the charging plug-in process. This study aims to bridge this gap by proposing a collision classification scheme for robot manipulators in automatic electric vehicle charging scenarios. In situations with minimal visual positioning deviation, robots employ impedance control for effective insertion. Significant deviations may lead to potential collisions with other vehicle parts, demanding discrimination through a global visual system. For moderate deviations, where a robot’s end-effector encounters difficulty in insertion, existing methods prove inadequate. To address this, we propose a novel data-driven collision classification method, utilizing vibration signals generated during collisions, integrating the robust light gradient boosting machine (LightGBM) algorithm. This approach effectively discerns the acceptability of collision contacts in scenarios involving moderate deviations. Considering the impact of passing vehicles introducing environmental noise, a noise suppression module is introduced into the proposed collision classification method, leveraging empirical mode decomposition (EMD) to enhance its robustness in noisy charging scenarios. This study significantly contributes to the safety of automatic charging processes, offering a practical and applicable collision classification solution tailored to diverse noisy scenarios and potential contact forms encountered by charging robots. The experimental results affirm the effectiveness of the collision classification method, integrating LightGBM and EMD, and highlight its promising prediction accuracy. These findings offer valuable perspectives to steer future research endeavors in the domain of autonomous charging systems