Interactions of naturally occurring compounds with antimicrobials

Antibiotics are among the most often used medications in human healthcare and agriculture.Overusing these substances can lead to complications such as increasing antibiotic resistance in bacteria or a toxic effect when administering large amounts.To solve these problems,new solutions in antibacterial therapy are needed.The use of natural products in medicine has been known for centuries.Some of them have antibacterial activity,hence the idea to combine their activity with commercial antibiotics to reduce the latter's use.This review presents collected information on natural compounds(terpenes,alkaloids,flavonoids,tannins,sulfoxides,and mycotoxins),of which various drug interactions have been observed.Many of the indicated compounds show synergistic or additive interactions with antibiotics,which suggests their potential for use in antibacterial therapy,reducing the toxicity of the antibiotics used and the risk of further development of bacterial resistance.Unfortunately,there are also compounds which interact antagonistically,potentially hindering the therapy of bacterial infection.Depending on its mechanism of action,each compound can behave differently in combination with different antibiotics and when acting against various bacterial strains.

Voices of Mother's Interaction with Midwives in Natural Childbirth: A Qualitative Study

Interaction between mothers and midwives during natural childbirth is one of the important factors in relationship between mothers and midwives in natural childbirth. In this qualitative study we explored experiences of mothers and midwives in interaction with each other in natural childbirth. This study was a part of a larger study which was carried out in Iran in 2013-2014. A total of 23 participants participated in this study. 12 primiparous and multiparous women planned to have natural deliveries and 11 midwives were purposefully included for semi-structured in-depth interviews in this study. For analysis and interpretation of mothers’ and midwives’ experience, conventional content analysis was used. Data were coded in MAXqda software (version 2). Interaction between mothers and midwives could be organized and categorized in one theme “relationship”. This theme consists of two subthemes: “respect for the mother” and “interaction” and five categories: “Feeling confidence, Feeling satisfaction, Associated with sensory relationship, Understanding mother’s situation, Understanding the meaning of interaction”. Good relationship between mothers and midwives in natural childbirth could improve the experience of natural childbirth for mothers. This experience could increase woman’s tendency toward natural birth instead of cesarean section in future pregnancies. Findings of this study can be seen as a challenge for health care professionals and policy makers to upgrade care of natural childbirth based on women’s preferences and needs.

An investigation into natural vibrations of fluid-structure interaction systems subject to Sommerfeld radiation condition

A fluid-structure interaction system subject to Sommerfeld＇s condition is defined as a Sommerfeld system which is divided into three categories： Fluid Sommerfeld （FS） System, Solid Sommerfeld （SS） System and Fluid Solid Sommerfeld （FSS） System of which Sommerfeld conditions are imposed on a fluid boundary only, a solid boundary only and both fluid and solid boundaries, respectively. This paper follows the previous initial results claimed by simple examples to further mathematically investigate the natural vibrations of generalized Sommerfeld systems. A new parameter representing the speed of radiation wave for generalized 3-D problems with more complicated boundary conditions is introduced into the Sommerfeld condition which allows investigation of the natural vibrations of a Sommerfeld system involving both free surface and compressible waves. The mathematical demonstrations and selected examples confirm and reveal the natural behaviour of generalized Sommerfeld systems defined above. These generalized conclusions can be used in theoretical or engineering analysis of the vibrations of various Sommerfeld systems in engineering.

Interpreting and Extracting Open Knowledge for Human-Robot Interaction

A more natural way for non-expert users to express their tasks in an open-ended set is to use natural language. In this case,a human-centered intelligent agent/robot is required to be able to understand and generate plans for these naturally expressed tasks. For this purpose, it is a good way to enhance intelligent robot's abilities by utilizing open knowledge extracted from the web, instead of hand-coded knowledge. A key challenge of utilizing open knowledge lies in the semantic interpretation of the open knowledge organized in multiple modes, which can be unstructured or semi-structured, before one can use it.Previous approaches used a limited lexicon to employ combinatory categorial grammar(CCG) as the underlying formalism for semantic parsing over sentences. Here, we propose a more effective learning method to interpret semi-structured user instructions. Moreover, we present a new heuristic method to recover missing semantic information from the context of an instruction. Experiments showed that the proposed approach renders significant performance improvement compared to the baseline methods and the recovering method is promising.

A Facial Expression Emotion Recognition Based Human-robot Interaction System

A facial expression emotion recognition based human-robot interaction(FEER-HRI) system is proposed, for which a four-layer system framework is designed. The FEERHRI system enables the robots not only to recognize human emotions, but also to generate facial expression for adapting to human emotions. A facial emotion recognition method based on2D-Gabor, uniform local binary pattern(LBP) operator, and multiclass extreme learning machine(ELM) classifier is presented,which is applied to real-time facial expression recognition for robots. Facial expressions of robots are represented by simple cartoon symbols and displayed by a LED screen equipped in the robots, which can be easily understood by human. Four scenarios,i.e., guiding, entertainment, home service and scene simulation are performed in the human-robot interaction experiment, in which smooth communication is realized by facial expression recognition of humans and facial expression generation of robots within 2 seconds. As a few prospective applications, the FEERHRI system can be applied in home service, smart home, safe driving, and so on.

Understanding Nonverbal Communication Cues of Human Personality Traits in Human-Robot Interaction

With the increasing presence of robots in our daily life,there is a strong need and demand for the strategies to acquire a high quality interaction between robots and users by enabling robots to understand users’mood,intention,and other aspects.During human-human interaction,personality traits have an important influence on human behavior,decision,mood,and many others.Therefore,we propose an efficient computational framework to endow the robot with the capability of understanding the user’s personality traits based on the user’s nonverbal communication cues represented by three visual features including the head motion,gaze,and body motion energy,and three vocal features including voice pitch,voice energy,and mel-frequency cepstral coefficient(MFCC).We used the Pepper robot in this study as a communication robot to interact with each participant by asking questions,and meanwhile,the robot extracts the nonverbal features from each participant’s habitual behavior using its on-board sensors.On the other hand,each participant’s personality traits are evaluated with a questionnaire.We then train the ridge regression and linear support vector machine(SVM)classifiers using the nonverbal features and personality trait labels from a questionnaire and evaluate the performance of the classifiers.We have verified the validity of the proposed models that showed promising binary classification performance on recognizing each of the Big Five personality traits of the participants based on individual differences in nonverbal communication cues.

Data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the robot.The presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller design.The task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the inner-loop.Data-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance parameters.In the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity measurement.On this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task space.The simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.

Implementation of natural hand gestures in holograms for 3D object manipulation

Holograms provide a characteristic manner to display and convey information, and have been improved to provide better user interactions Holographic interactions are important as they improve user interactions with virtual objects. Gesture interaction is a recent research topic, as it allows users to use their bare hands to directly interact with the hologram. However, it remains unclear whether real hand gestures are well suited for hologram applications. Therefore, we discuss the development process and implementation of three-dimensional object manipulation using natural hand gestures in a hologram. We describe the design and development process for hologram applications and its integration with real hand gesture interactions as initial findings. Experimental results from Nasa TLX form are discussed. Based on the findings, we actualize the user interactions in the hologram.

Information perception and feedback mechanism and key techniques of multi-modality human-robot interaction for service robots

With the increasing of the elderly population and the growing hearth care cost, the role of service robots in aiding the disabled and the elderly is becoming important. Many researchers in the world have paid much attention to heaRthcare robots and rehabilitation robots. To get natural and harmonious communication between the user and a service robot, the information perception/feedback ability, and interaction ability for service robots become more important in many key issues.

Augmented Virtual Stiffness Rendering of a Cable-driven SEA for Human-Robot Interaction

Human-robot interaction(HRI) is fundamental for human-centered robotics, and has been attracting intensive research for more than a decade. The series elastic actuator(SEA) provides inherent compliance, safety and further benefits for HRI, but the introduced elastic element also brings control difficulties. In this paper, we address the stiffness rendering problem for a cable-driven SEA system, to achieve either low stiffness for good transparency or high stiffness bigger than the physical spring constant, and to assess the rendering accuracy with quantified metrics. By taking a velocity-sourced model of the motor, a cascaded velocity-torque-impedance control structure is established. To achieve high fidelity torque control, the 2-DOF(degree of freedom) stabilizing control method together with a compensator has been used to handle the competing requirements on tracking performance, noise and disturbance rejection,and energy optimization in the cable-driven SEA system. The conventional passivity requirement for HRI usually leads to a conservative design of the impedance controller, and the rendered stiffness cannot go higher than the physical spring constant. By adding a phase-lead compensator into the impedance controller,the stiffness rendering capability was augmented with guaranteed relaxed passivity. Extensive simulations and experiments have been performed, and the virtual stiffness has been rendered in the extended range of 0.1 to 2.0 times of the physical spring constant with guaranteed relaxed passivity for physical humanrobot interaction below 5 Hz. Quantified metrics also verified good rendering accuracy.

Teaching the User By Learning From the User:Personalizing Movement Control in Physical Human-robot Interaction

This paper proposes a novel approach for physical human-robot interactions(pHRI), where a robot provides guidance forces to a user based on the user performance. This framework tunes the forces in regards to behavior of each user in coping with different tasks, where lower performance results in higher intervention from the robot. This personalized physical human-robot interaction(p2HRI) method incorporates adaptive modeling of the interaction between the human and the robot as well as learning from demonstration(LfD) techniques to adapt to the users' performance. This approach is based on model predictive control where the system optimizes the rendered forces by predicting the performance of the user. Moreover, continuous learning of the user behavior is added so that the models and personalized considerations are updated based on the change of user performance over time. Applying this framework to a field such as haptic guidance for skill improvement, allows a more personalized learning experience where the interaction between the robot as the intelligent tutor and the student as the user,is better adjusted based on the skill level of the individual and their gradual improvement. The results suggest that the precision of the model of the interaction is improved using this proposed method,and the addition of the considered personalized factors to a more adaptive strategy for rendering of guidance forces.

Inquiring Natural Language Processing Capabilities on Robotic Systems through Virtual Assistants:A Systemic Approach

This paper attempts to approach the interface of a robot from the perspective of virtual assistants.Virtual assistants can also be characterized as the mind of a robot,since they manage communication and action with the rest of the world they exist in.Therefore,virtual assistants can also be described as the brain of a robot and they include a Natural Language Processing(NLP)module for conducting communication in their human-robot interface.This work is focused on inquiring and enhancing the capabilities of this module.The problem is that nothing much is revealed about the nature of the human-robot interface of commercial virtual assistants.Therefore,any new attempt of developing such a capability has to start from scratch.Accordingly,to include corresponding capabilities to a developing NLP system of a virtual assistant,a method of systemic semantic modelling is proposed and applied.For this purpose,the paper briefly reviews the evolution of virtual assistants from the first assistant,in the form of a game,to the latest assistant that has significantly elevated their standards.Then there is a reference to the evolution of their services and their continued offerings,as well as future expectations.The paper presents their structure and the technologies used,according to the data provided by the development companies to the public,while an attempt is made to classify virtual assistants,based on their characteristics and capabilities.Consequently,a robotic NLP interface is being developed,based on the communicative power of a proposed systemic conceptual model that may enhance the NLP capabilities of virtual assistants,being tested through a small natural language dictionary in Greek.

Research and Application of AI-Based Interactive Exhibits in Wuhan Museum of Science and Technology

This article aims to explore the development and application of AI-based interactive exhibits in Wuhan Museum of Science and Technology.By utilizing computer vision,natural language processing,and machine learning technologies,an innovative exhibit development and application system is proposed.This system employs deep learning algorithms and data analysis methods to achieve real-time perception of visitor behavior and adaptive interaction.The development process involves designing user interfaces and interaction methods to effectively enhance visitor engagement and learning outcomes.Through evaluation and comparison in practical applications,the potential of this system in enhancing exhibit interaction,increasing visitor engagement,improving educational effectiveness,and expanding avenues for scientific knowledge dissemination are validated.

Humanoid robot heads for human-robot interaction:A review

The humanoid robot head plays an important role in the emotional expression of human-robot interaction(HRI).They are emerging in industrial manufacturing,business reception,entertainment,teaching assistance,and tour guides.In recent years,significant progress has been made in the field of humanoid robots.Nevertheless,there is still a lack of humanoid robots that can interact with humans naturally and comfortably.This review comprises a comprehensive survey of state-of-the-art technologies for humanoid robot heads over the last three decades,which covers the aspects of mechanical structures,actuators and sensors,anthropomorphic behavior control,emotional expression,and human-robot interaction.Finally,the current challenges and possible future directions are discussed.

Natural killer cells in hepatitis C:Current progress

Patients infected with the hepatitis C virus(HCV) are characterized by a high incidence of chronic infection, which results in chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma. The functional impairment of HCV-specific T cells is associated with the evolution of an acute infection to chronic hepatitis. While T cells are the important effector cells in adaptive immunity, natural killer(NK) cells are the critical effector cells in innate immunity to virus infections. The findings of recent studies on NK cells in hepatitis C suggest that NK cell responses are indeed important in each phase of HCV infection. In the early phase, NK cells are involved in protective immunity to HCV. The immune evasion strategies used by HCV may target NK cells and might contribute to the progression to chronic hepatitis C. NK cells may control HCV replication and modulate hepatic fibrosis in the chronic phase. Further investigations are, however, needed, because a considerable number of studies observed functional impairment of NK cells in chronic HCV infection. Interestingly, the enhanced NK cell responses during interferon-α-based therapy of chronic hepatitis C indicate successful treatment. In spite of the advances in research on NK cells in hepatitis C, establishment of more physiological HCV infection model systems is needed to settle unsolved controversies over the role and functional status of NK cells in HCV infection.

Digital Twin for Human-Robot Interactive Welding and Welder Behavior Analysis

This paper presents an innovative investigation on prototyping a digital twin(DT)as the platform for human-robot interactive welding and welder behavior analysis.This humanrobot interaction(HRI)working style helps to enhance human users'operational productivity and comfort;while data-driven welder behavior analysis benefits to further novice welder training.This HRI system includes three modules:1)a human user who demonstrates the welding operations offsite with her/his operations recorded by the motion-tracked handles;2)a robot that executes the demonstrated welding operations to complete the physical welding tasks onsite;3)a DT system that is developed based on virtual reality(VR)as a digital replica of the physical human-robot interactive welding environment.The DT system bridges a human user and robot through a bi-directional information flow:a)transmitting demonstrated welding operations in VR to the robot in the physical environment;b)displaying the physical welding scenes to human users in VR.Compared to existing DT systems reported in the literatures,the developed one provides better capability in engaging human users in interacting with welding scenes,through an augmented VR.To verify the effectiveness,six welders,skilled with certain manual welding training and unskilled without any training,tested the system by completing the same welding job;three skilled welders produce satisfied welded workpieces,while the other three unskilled do not.A data-driven approach as a combination of fast Fourier transform(FFT),principal component analysis(PCA),and support vector machine(SVM)is developed to analyze their behaviors.Given an operation sequence,i.e.,motion speed sequence of the welding torch,frequency features are firstly extracted by FFT and then reduced in dimension through PCA,which are finally routed into SVM for classification.The trained model demonstrates a 94.44%classification accuracy in the testing dataset.The successful pattern recognition in skilled welder operations should benefit to accelerate novice welder training.

Dynamic Analysis of A 5-MW Tripod Offshore Wind Turbine by Considering Fluid–Structure Interaction

Fixed offshore wind turbines usually have large underwater supporting structures. The fluid influences the dynamic characteristics of the structure system. The dynamic model of a 5-MW tripod offshore wind turbine considering the pile-soil system and fluid structure interaction （FSI） is established, and the structural modes in air and in water are obtained by use of ANSYS. By comparing low-order natural frequencies and mode shapes, the influence of sea water on the free vibration characteristics of offshore wind turbine is analyzed. On basis of the above work, seismic responses under excitation by E1-Centro waves are calculated by the time-history analysis method. The results reveal that the dynamic responses such as the lateral displacement of the foundation and the section bending moment of the tubular piles increase substantially under the influence of the added-mass and hydrodynamic pressure of sea water. The method and conclusions presented in this paper can provide a theoretical reference for structure design and analysis of offshore wind turbines fixed in deep seawater.

Theoretical Study on the Intermolecular Interactions of Tetrazole Dimers

Tetrazole monomers （Ⅰ, Ⅱ） and all of their possible stable dimers （1, 2, 3, 4, 5, 6, 7 and 8） were fully optimized by DFT method at the B3LYP/6-311＋＋G^＊＊ level. Among the eight dimers, there were two 1H-tetrazole dimers, three 2H-tetrazole dimers and three hetero dimers of 1H-tetrazole and 2H-tetrazole. Vibrational frequencies were calculated to ascertain that each structure was stable （no imaginary frequencies）. The basis set superposition errors （BSSE） are 2.78, 2.28, 2.97, 2.75, 2.74, 2.18, 1.23 and 3.10 kJ/mol, and the zero point energy （ZPE） corrections for the interaction energies are 4.88, 4.18, 3.87, 3.65, 3.54, 3.22, 2.87 and 4.34 kJ/mol for 1, 2, 3, 4, 5, 6, 7 and 8, respectively. After BSSE and ZPE corrections, the greatest corrected intermolecular interaction energy of the dimers is -43.71 kJ/mol. The charge redistribution mainly occurs on the adjacent N-H…N atoms between submolecules. The charge transfer between two subsystems is very small. Natural bond orbital （NBO） analysis was performed to reveal the origin of the interaction. Based on the statistical thermodynamic method, the standard thermodynamic functions, heat capacities （C^0P）, entropies （S^0T） and thermal corrections to enthalpy （H^0T）, and the changes of thermodynamic properties from monomer to dimer in the temperature range of 200.00 K to 700 K have been obtained. 1H-tetrazole monomer can spontaneously turn into two stable dimers at 298.15 K.

Failure Patterns and Mechanisms of Hydraulic Fracture Propagation Behavior in the Presence of Naturally Cemented Fractures

In this study,we use the extended finite element method(XFEM)with a consideration of junction enrichment functions to investigate the mechanics of hydraulic fractures related to naturally cemented fractures.In the proposed numerical model,the lubrication equation is adopted to describe the fluid flow within fractures.The fluid-solid coupling systems of the hydraulic fracturing problem are solved using the Newton-Raphson method.The energy release rate criterion is used to determine the cross/arrest behavior between a hydraulic fracture(HF)and a cemented natural fracture(NF).The failure patterns and mechanisms of crack propagation at the intersection of natural fractures are discussed.Simulation results show that after crossing an NF,the failure mode along the cemented NF path may change from the tensile regime to the shear or mixed-mode regime.When an advancing HF kinks back toward the matrix,the failure mode may gradually switch back to the tensile-dominated regime.Key factors,including the length of the upper/lower portion of the cemented NF,horizontal stress anisotropy,and the intersection angle of the crack propagation are investigated in detail.An uncemented or partially cemented NF will form a more complex fracture network than a cemented NF.This study provides insight into the formation mechanism of fracture networks in formations that contain cemented NF.

Covalent intermolecular interaction of the nitric oxide dimer (NO)_2

Covalent bonds arise from the overlap of the electronic clouds in the internucleus region, which is a pure quantum effect and cannot be obtained in any classical way. If the intermolecular interaction is of covalent character, the result from direct applications of classical simulation methods to the molecular system would be questionable. Here, we analyze the special intermolecular interaction between two NO molecules based on quantum chemical calculation. This weak intermolecular interaction, which is of covalent character, is responsible for the formation of the NO dimer,（NO）2, in its most stable conformation, a cis conformation. The natural bond orbital（NBO） analysis gives an intuitive illustration of the formation of the dimer bonding and antibonding orbitals concomitant with the breaking of the πbonds with bond order 0.5of the monomers. The dimer bonding is counteracted by partially filling the antibonding dimer orbital and the repulsion between those fully or nearly fully occupied nonbonding dimer orbitals that make the dimer binding rather weak. The direct molecular mechanics（MM） calculation with the UFF force fields predicts a trans conformation as the most stable state, which contradicts the result of quantum mechanics（QM）. The lesson from the investigation of this special system is that for the case where intermolecular interaction is of covalent character, a specific modification of the force fields of the molecular simulation method is necessary.