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Breathing resistance is the main factor that influences the wearing comfort of respirators. This paper aims to demonstrate the feasibility of using the gene expression programming (GEP) for the purpose of predicting subjective perceptions of breathing resistances of wearing respirators via surface electromyography (sEMG) and respiratory signals (RSP) sensors.

The authors developed a physiological signal monitoring system with a specific garment. The inputs included seven physical measures extracted from (RSP) and (sEMG) signals. The output was the subjective index of breathing resistances of wearing respirators derived from the category partitioning-100 scale with proven levels of reliability and validity. The prediction model was developed and validated using data collected from 30 subjects and 24 test combinations (12 respirator conditions × 2 motion conditions). The subjects evaluated 24 conditions of breathing resistances in repeated measures fashion.

The results show that the GEP model can provide good prediction performance (R² = 0.71, RMSE = 0.11). This study demonstrates that subjective perceptions of breathing resistance of wearing respirators on the human body can be predicted using the GEP via sEMG and RSP in real-time, at little cost, non-invasively and automatically.

This is the first paper suggesting that subjective perceptions of subjective breathing resistances can be predicted from sEMG and RSP sensors using a GEP model, which will remain helpful to the scientific community to start further human-centered research work and product development using wearable biosensors and evolutionary algorithms.

Choice overload in e-commerce induces choice difficulty, which is detrimental to shopping decision-making. The purpose of this paper is to provide relatively simple and effective methods and indicators to detect and assess the choice difficulty states of customers during clothing online shopping.

In order to find out the behavioral performance of choice difficulty states during clothing online shopping, the authors performed the following steps: at first, the authors conducted an experiment to record the videos of the purchasing process during clothing online shopping. Then, the authors carried out the behavioral analysis of customers, correlating each behavioral index to choice difficulty states.

The results of the behavioral analysis in this study have indicated that three types of behavior were significantly correlated to the choice difficulty states of customers.

It is expected that it would be possible to use the threshold values of behavioral indicators to determine whether and when the customer is suffering from choice phobia disorder. Based on the findings, a recommender system with timely interventions to help customers with choice difficulty to make shopping decisions will be developed in the future.

This is the first reported study that explores the possibility of using behavioral indicators to detect choice difficulty, which will remain helpful to the scientific community to start further customer-centered research work and development of clothing online shopping.

Investigating the subjective breathing resistance of wearing respirators requires a valid and reliable technique to measure breathing resistance. The purpose of this study is to test the validity and reliability of several rating scales and select the best for investigation of breathing resistance.

The authors designed three scales, that is, BRX scale, CP-100 scale and RVAS scale, and 30 subjects were separated into three groups, each group with a different scale. They sat for 5 min and walked for 5 min while wearing three models of respirators. After each trial, subjects were asked to complete subjective ratings of breathing resistance. Reliability was examined by the coefficient of Cronbach’s α, and validity was examined through content validity, discriminant validity and criterion validity. Generally, subjects were capable of reporting their sensation of breathing resistance by using the rating scale technique. However, the accuracy of rating strongly depended upon the properties of the scale.

The CP-100 scale was found to be highly reliable and most valid for rating subjective breath resistance. The validated CP-100 scale is very sensitive and accurate.

This is the first paper to select the best subjective scale for investigation of breathing resistance of respirators. The CP-100 scale will find wide applications in subjective breathing resistance evaluation for the use of respirators in industrial benchmarking activities. It will introduce the human factor engineering into the respirator manufacturing to improve the comfort of respirators.

The purpose of this paper is to provide an overview of the human factors/ergonomics (HFE) studies for respirator.

This review paper describes and discusses the various factors and methodologies of HFE, for the purpose of better considering human factors, used in respirator studies and further human-centered product development.

Many attempts have been made to study human factors for respirators mainly including fit, human performance, comfort, and mood. Physical, psychological, and physiological indices of people are extremely valuable to HFE studies for respirator. Objective and subjective measures were methodologies widely used. Quantitative and qualitative approaches were adopted to illustrate the human performance and well-being influenced by respirators. A summary table presented with major methods used for indices of respirators in the field of HFE. According to the current researches, this review indicated three particular challenges facing HFE studies of respirators now.

With the ever increasing role of protection from air pollution in society, respirator has become an increasingly important part of our daily lives. HFE intervene in optimizing the relationships between respirators and the human using them. Plenty of efforts have been dedicated for the development of protection capability, but HFE studies for respirators are lacking. In recent years, there has been a tremendous interest in introducing HFE research methods that can evaluate respirators from the perspective of human and translate them into constraints for designing human-centered respirators.

This is a first paper in the field of HFE studies for respirator, which will remain helpful to the scientific community to start further human-centered research work and product development.

The purpose of this paper is to investigate the influence of the oxidation on the cracks of DZ125L nickel-based superalloy thin-walled parts in laser metal direct forming (LMDF).

Thin-walled cylinders were fabricated in protective atmosphere with different oxygen contents in order to reveal the influence of oxidation on the morphology of cracks. The influence of oxidation on the cracks was investigated in detail by measuring the wall thicknesses of cylinders, the residual stress in the top surface of the cylinders and the composition of the cracks. Finally, the validity of the results was verified by fabricating a thin-walled turbine blade in protective atmosphere.

The experimental results showed that wall thickness fluctuation of cylinders, unequal residual stress distribution of cylinders and the oxides in the crack were all the critical factors which led to crack of DZ125L thin-walled parts. Thin-walled turbine blades with no cracks can be fabricated when the oxygen content was about less than 150 ppm in protective atmosphere.

The appropriate oxygen content in protective atmosphere is helpful for fabricating thin-walled parts of nickel-based superalloy like DZ125L, and the results can show what will happen at different oxygen levels. Moreover, the results show that the cracks can be eliminated as the oxygen content reduce to less than 150 ppm rather less than 10 ppm or even less, which can reduce the cost of protective gas as forming thin-walled parts of nickel-based superalloy such as DZ125L.

The appropriate oxygen content in protective atmosphere is helpful for fabricating thin-walled parts of nickel-based superalloy like DZ125L. However, when heavy solid parts of some other material other than DZ125L were fabricated, the oxygen content of less than 150 ppm may be not suitable.

The influence of oxidation on the cracks of DZ125L thin-walled parts in LMDF was investigated in detail, and a DZ125L thin-walled turbine blade with no cracks was fabricated by adjusting the oxygen content in protective atmosphere.

This paper aim to take the ship shaft stern bearing as the research object, and studies the influence of journal axial vibration on bearing dynamic characteristics under different misaligned angles and rotation speeds.

Computational fluid dynamics (CFD) and harmonic excitation method were used to build bearing unstable lubrication model, and the dynamic mesh technology was used in calculation.

The results indicate that journal axial vibration has a significant effect on bearing dynamic characteristics, like maximum oil film pressure, bearing stiffness and damping coefficients, and the effect is positively correlated with journal misaligned angle. The effect of shaft rotation speed and journal axial vibration on bearing dynamics characteristics are independent; they have no coupling. Bearing axial stiffness is mainly affected by the journal axial displacement, bearing axial damping is mainly affected by journal axial velocity and they are positively correlated with the misaligned angle. The influence of rotational speed on bearing axial stiffness and axial damping is not obvious.

This paper establishes the bearing dynamic model by CFD and harmonic excitation method with consideration of cavitation effect and analyzing the influence of journal axial vibration on the dynamic characteristics. The results are benefit to the design of ship propulsion shaft and the selection of stern bearing. Also, they are of great significance to improve the operation stability of the shaft bearing system and the vitality of the ship.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2022-0337/

This paper aims to design, optimize and simulate the Radio Frequency (RF) micro electromechanical system (MEMS) Switch which is stimulated by electrostatically voltage.

The geometric structure of the switch was extracted based on the design of Taguchi-based experiment using the mathematical programming and obtaining objective function by the genetic meta-heuristic algorithm.

The RF parameters of the switch were calculated for the design of Taguchi-based S11 = −5.649 dB and S21 = −46.428 dB at the working frequency of 40 GHz. The pull-in voltage of the switch was 2.8 V and the axial residual stress of the proposed design was obtained 28 MPa and the design of Taguchi-based S11 = −4.422 dB and S21 = −48.705dB at the working frequency of 40 GHz. The pull-in voltage of the switch was 2.5 V and the axial residual stress of the proposed design was obtained 25 MPa.

A novel complex strategy in the design and optimization of capacitive RF switch MEMS modeling is proposed.