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Achieving natural interactions by means of vision and speech between humans and robots is one of the major goals that many researchers are working on. This paper aims to describe a gesture‐based human‐robot interaction (HRI) system using a knowledge‐based software platform.

A frame‐based knowledge model is defined for the gesture interpretation and HRI. In this knowledge model, necessary frames are defined for the known users, robots, poses, gestures and robot behaviors. First, the system identifies the user using the eigenface method. Then, face and hand poses are segmented from the camera frame buffer using the person's specific skin color information and classified by the subspace method.

The system is capable of recognizing static gestures comprised of the face and hand poses, and dynamic gestures of face in motion. The system combines computer vision and knowledge‐based approaches in order to improve the adaptability to different people.

Provides information on an experimental HRI system that has been implemented in the frame‐based software platform for agent and knowledge management using the AIBO entertainment robot, and this has been demonstrated to be useful and efficient within a limited situation.

Recent U.S. Treasury yields have been constrained to some extent by the zero lower bound (ZLB) on nominal interest rates. Therefore, we compare the performance of a standard affine Gaussian dynamic term structure model (DTSM), which ignores the ZLB, to a shadow-rate DTSM, which respects the ZLB. Near the ZLB, we find notable declines in the forecast accuracy of the standard model, while the shadow-rate model forecasts well. However, 10-year yield term premiums are broadly similar across the two models. Finally, in applying the shadow-rate model, we find no gain from estimating a slightly positive lower bound on U.S. yields.

Polyphenols possess anti-allergic activities. Catechin is one of the polyphenols that are abundantly present in the Acacia catechu. In this study, the authors investigated the effect of catechin isolated from A. catechu in an experimental mouse model of ovalbumin (OVA)-induced allergic asthma.

Catechin was isolated from A. catechu, and phytochemical analysis was carried out by ultraviolet visible and thin-layer chromatography (TLC), high pressure thin-layer chromatography was used for the determination of an amount of catechin present. In a first set of an experiment, the authors have carried out dose-dependent evaluation of catechin on histamine synthesis in normal rats. In another study, allergic asthma was induced in BALB/c mice by intraperitoneal injection of 50 mg OVA dissolved in 4 mg aluminum hydroxide dissolved in 0.2 ml saline on Days 0 and 14. Catechin was given orally at the dose of 100 mg/kg, once a day from Day 1 to Day 35 and after which various respiratory parameters such as tidal volume, respiratory rate and airflow rate, biochemical parameters such as histamine release from mast cells, bronchoalveolar (BAL) lavage fluid analysis and histopathology of lungs were carried out.

Catechin showed significant (p < 0.05) improvement in respiratory parameters such as tidal volume, respiratory rate and airflow rate, as well as biochemical and hematological parameters such as blood histamine, serum bicarbonate and nitric oxide levels as compared to the disease control group. The treatment also showed inhibitory effects on histamine synthesis in rat peritoneal as well as BAL mast cells. Also, a significant (p < 0.05) improvement in lung histopathology was observed with catechin.

From the present study, the authors can conclude that catechin exhibited potent anti-allergic activity by inhibition of histamine synthesis by inhibition of histidine decarboxylase enzyme. The study suggests that catechin has therapeutic potential for the treatment of allergic inflammatory disease in humans.

The purpose of this paper is to develop a set of ground experiment system to verify the basic functions of space effector and the capturing reliability of space end-effector for the free-floating target payload in the three-dimensional space. The development of ground experiment system for space end-effector is essential and significant, because it costs too much to launch a space robot or other spacecraft and carry out operation tasks in space. Owing to the negligible gravity in space, which is different from that in the ground environment, ground experiment system for space end-effector should have the capability of verifying the basic functions of space effector and the reliability of space end-effector in capturing the free-floating target payload in space.

The ground experiment system for space end-effector mainly adopts the hybrid simulation method, which includes the real hardware experiment and software simulation. To emulate the micro-gravity environment, the contact dynamics simulator is applied to emulating the motion state of the free-floating target payload, while the admittance control is used to realize the “soft” capturing of space end-effector to simulate the real situation in space.

With the gravity compensation, the influence of gravity is almost eliminated and the results meet the requirements of the experiment. In the ground experiment, the admittance control is effective and the actual motion state of space end-effector capturing the target in space can be simulated. The experiment results show that space end-effector can capture the free-floating target payload successfully and hopefully have the ability to capture a free-floating target in space.

The system can verify space end-effector capturing the free-floating target payload in three-dimensional space and imitate the motion of space end-effector capturing the free-floating target in space. The system can also be modified and improved for application in the verification of space robot capturing and docking the target, which is valuable for the ground verification of space applications.

Rapid satellite capture by a free-floating space robot is a challenge problem because of no-fixed base and time-delay issues. This paper aims to present a modified target capturing control scheme for improving the control performance.

For handling such control problem including time delay, the modified scheme is achieved by adding a delay calibration algorithm into the visual servoing loop. To identify end-effector motions in real time, a motion predictor is developed by partly linearizing the space robot kinematics equation. By this approach, only ground-fixed robot kinematics are involved in the predicting computation excluding the complex space robot kinematics calculations. With the newly developed predictor, a delay compensator is designed to take error control into account. For determining the compensation parameters, the asymptotic stability condition of the proposed compensation algorithm is also presented.

The proposed method is conducted by a credible three-dimensional ground experimental system, and the experimental results illustrate the effectiveness of the proposed method.

Because the delayed camera signals are compensated with only ground-fixed robot kinematics, this proposed satellite capturing scheme is particularly suitable for commercial on-orbit services with cheaper on-board computers.

This paper is original as an attempt trying to compensate the time delay by taking both space robot motion predictions and compensation error control into consideration and is valuable for rapid and accurate satellite capture tasks.

Health scientists and urban planners have long been interested in the influence that the built environment has on the physical activities in which we engage, the environmental hazards we face, the kinds of amenities we enjoy, and the resulting impacts on our health. However, it is widely recognized that the extent of this influence, and the specific cause-and-effect relationships that exist, are still relatively unclear. Recent reviews highlight the need for more individual-level data on daily activities (especially physical activity) over long periods of time linked spatially to real-world characteristics of the built environment in diverse settings, along with a wide range of personal mediating variables. While capturing objective data on the built environment has benefited from wide-scale availability of detailed land use and transport network databases, the same cannot be said of human activity. A more diverse history of data collection methods exists for such activity and continues to evolve owing to a variety of quickly emerging wearable sensor technologies. At present, no “gold standard” method has emerged for assessing physical activity type and intensity under the real-world conditions of the built environment; in fact, most methods have barely been tested outside of the laboratory, and those that have tend to experience significant drops in accuracy and reliability. This paper provides a review of these diverse methods and emerging technologies, including biochemical, self-report, direct observation, passive motion detection, and integrated approaches. Based on this review and current needs, an integrated three-tiered methodology is proposed, including: (1) passive location tracking (e.g., using global positioning systems); (2) passive motion/biometric tracking (e.g., using accelerometers); and (3) limited self-reporting (e.g., using prompted recall diaries). Key development issues are highlighted, including the need for proper validation and automated activity-detection algorithms. The paper ends with a look at some of the key lessons learned and new opportunities that have emerged at the crossroads of urban studies and health sciences.

We do have a vision for a world in which people can walk to shops, school, friends' homes, or transit stations; in which they can mingle with their neighbors and admire trees, plants, and waterways; in which the air and water are clean; and in which there are parks and play areas for children, gathering spots for teens and the elderly, and convenient work and recreation places for the rest of us. (Frumkin, Frank, & Jackson, 2004, p. xvii)

This paper aims to examine the effect of high-involvement work systems (HIWSs) on completing work and avoiding distraction as two dimensions of presenteeism. It also investigates competence as a mediator of the effect of HIWS on presenteeism.

Data were collected from 343 Bangladeshi bank employees using an online survey. The partial least squares-structural equation modelling (PLS-SEM) was employed to assess the abovementioned linkages.

The findings demonstrate HIWS directly avoid distraction but do not significantly impact the completing work dimension of presenteeism. The findings also indicate that competence mediates the effect of HIWS on completing work but not on avoiding distraction.

Drawing on the job demands-resources (JD-R) model, this study empirically demonstrates the contrasting role of HIWS in completing work and avoiding distraction related to presenteeism. It also provides a novel perspective on the unexplored mediating mechanism of competence on the relationship between HIWS and presenteeism and offers new directions for HIWS and presenteeism research.

In the recent past, mobile technologies that track the movement of people, freight and vehicles have evolved rapidly. The major categories of such technologies are reviewed and a number of attributes for classification are proposed. The willingness of people to engage in such technologically based surveys and the reported biases in the make-up of the sample obtained are reviewed. Lessons are drawn about the nature of the samples that can be achieved and the representativeness of such samples is discussed. Data processing is addressed, particularly in terms of the processing requirements for logged data, where additional travel characteristics required for travel analysis may need to be imputed. Another issue explored is the reliability of data entered by respondents in interactive devices and concerns that may arise in processing data collected in real time for prompting or interrogating respondents. Differences, in relation to the data user, between data from mobile devices and data from conventional self-report surveys are discussed. Potentials that may exist for changes in modelling from using such data are explored. Conclusions are drawn about the usefulness and limitations of mobile technologies to collect and process data. The extent to which such mobile technologies may be used in future, either to supplement or replace conventional methods of data collection, is discussed along with the readiness of the technology for today and the advances that may be expected in the short and medium term from this form of technology.

The objective of this paper is to present the existing state of research relating to the steel industries.

Gamma-aminobutyric acid (GABA) is a four-carbon and nonprotein amino acid, made by various microorganisms, especially lactic acid bacteria (LAB) and probiotics. GABA has various physiological roles, for instance, insomnia, depression, hypotensive activity as well as diuretic effects. The production of GABA-based foods is a favorable result from GABA’s biological and functional properties. The purpose of this study is to investigate different methods of improving GABA production in probiotics and LAB to select the superlative method and bacterial strain.

In this review paper, all articles from five electronic databases containing Google Scholar, Web of Science, PubMed, Scopus and Science Direct were considered from 2000 to January 11, 2023, with keywords “Optimization” OR “Enhance” OR “Increase” AND “Gamma-aminobutyric acid” OR “GABA” AND “Probiotics” OR “Lactic acid bacteria” and selected according to the purpose of the study.

It seems that among all the investigated methods, an effective fermentation procedure with optimal conditions including fermentation medium, 5 L; glutamic acid, 295 g/L; incubation temperature, 32°C; inoculum, 10% (v/v); and agitation, 100 rpm, after 48 h of fermentation led to producing 205,800 mg/L of GABA from the effective bacterial strain Lactobacillus brevis NCL912.

With a simple but optimized fermentation, L. brevis NCL912 can be used for the efficient GABA production in the pharmacy and food factories.