In this study, a novel lifting motion simulation model was developed based on a multi-objective optimization (MOO) approach. Two performance criteria, minimum physical effort and maximum load motion ...smoothness, were selected to define the multi-objective function in the optimization procedure using a weighted-sum MOO approach. Symmetric lifting motions performed by younger and older adults under varied task conditions were simulated. The results showed that the proposed MOO approach led to up to 18.9% reductions in the prediction errors compared to the single-objective optimization approach. This finding suggests that both minimum physical effort and maximum load motion smoothness play an important role in lifting motion planning. Age-related differences in the mechanisms for planning lifting motions were also investigated. In particular, younger workers tend to rely more on the criterion of minimizing physical effort during lifting motion planning, while maximizing load motion smoothness seems to be the dominant objective for older workers.
Lifting tasks are closely associated with occupational low back pain (LBP). In this study, a novel lifting motion simulation model was developed to facilitate the analysis of lifting biomechanics and LBP prevention. Age-related differences in lifting motion planning were discussed for better understanding LBP injury mechanisms during lifting.
•A novel lifting motion simulation model was proposed based on a MOO approach.•The model resulted in improved simulation accuracy.•Age-related differences in lifting motion planning mechanisms were investigated.•Younger workers rely more on the criterion of minimizing physical effort.•Maximizing load motion smoothness is the dominant objective for older workers.
Real-world data on the effectiveness of glecaprevir/pibrentasvir (GLE/PIB) for patients with HCV infection and compensated cirrhosis is limited, especially for the 8-week regimen and in an Asian ...population. This retrospective study enrolled 159 consecutive patients with HCV and compensated cirrhosis who were treated with GLE/PIB at a single center in Taiwan. Sustained virological response (SVR) and adverse events (AEs) were evaluated. Among the 159 patients, 91 and 68 were treated with GLE/PIB for 8 and 12 weeks, respectively. In the per protocol analysis, both the 8- and 12-week groups achieved 100% SVR (87/87 vs. 64/64); and in the evaluable population analysis, 95.6% (87/91) of the 8-week group and 94.1% (64/68) of the 12-week group achieved SVR. The most commonly reported AEs, which included pruritus (15.4% vs. 26.5%), abdominal discomfort (9.9% vs. 5.9%), and skin rash (5.5% vs. 5.9%), were mild for the 8- and 12-week groups. Two patients in the 8-week group exhibited total bilirubin elevation over three times the upper normal limit. One of these two patients discontinued GLE/PIB treatment after 2 weeks but still achieved SVR. Both 8- and 12-week GLE/PIB treatments are safe and effective for patients of Taiwanese ethnicity with HCV and compensated cirrhosis.
Abstract
Clinical trials showed pangenotypic direct-acting antivirals’ (DAAs) excellent efficacy and safety when treating hepatitis C virus (HCV). Two pangenotypic regimens were examined, ...glecaprevir/pibrentasvir (GLE/PIB) and sofosbuvir/velpatasvir (SOF/VEL), in a real-world Taiwanese setting, including all HCV patients treated with GLE/PIB or SOF/VEL from August 2018 to April 2020. The primary endpoint was sustained virologic response 12 weeks after treatment cessation (SVR12), including adverse events (AEs). A total of 1,356 HCV patients received pangenotypic DAA treatment during the study: 742 and 614 received GLE/PIB and SOF/VEL, respectively. The rates of SVR12 for GLE/PIB and SOF/VEL were 710/718 (98.9%) and 581/584 (99.5%), respectively, by per-protocol analysis, and 710/742 (95.7%) and 581/614 (94.6%), respectively, by evaluable population analysis. Eleven (GLE/PIB: 8, SOF/VEL: 3) did not achieve SVR12. The most common AEs for GLE/PIB and SOF/VEL were pruritus (17.4% vs. 2.9%), abdominal discomfort (5.8% vs. 4.4%), dizziness (4.2% vs. 2%), and malaise (3.1% vs. 2.9%). Laboratory abnormalities were uncommon; only < 1% exhibited elevated total bilirubin or aminotransferase levels with both regimens. Five drug discontinuations occurred due to AEs (bilirubin elevation: 3; dermatological issues: 2). Pangenotypic DAAs GLE/PIB and SOF/VEL are effective and well tolerated, achieving high SVR12 rates for patients with all HCV genotypes.
Smart product-service systems (Smart PSS), as an emerging digital servitization paradigm, leverages smart, connected products and their generated services as a solution bundle to meet individual ...customer needs. Owing to the advanced information and communication technologies, Smart PSS development differs from the existing product and/or service design mainly in three aspects: (1) closed-loop design/redesign iteration; (2) value co-creation in the context; and (3) design with context-awareness. These unique characteristics bring up new design challenges, and to the authors' best knowledge, none of the existing design theories can address them well. Aiming to fill this gap, a novel design methodology for the Smart PSS development is proposed based on the information theory, where both the system and stakeholders can be regarded as the information containers. Hence, the closed-loop design/redesign iteration can be treated as the dynamic change of information and entropy in a balanced ecosystem. Meanwhile, the value co-creation process is considered as the exchange of accumulated information via the container. Lastly, the design context-awareness represents the process of reducing entropy. As a novel prescriptive design theory, it follows Shannon’s information theory to determine the best design/redesign solutions by considering the three characteristics integrally. It is hoped that the proposed design entropy theory can largely facilitate today's Smart PSS development with better performance and user satisfaction.
PurposeAlthough the sense of entitlement was traditionally associated with a range of maladaptive personality characteristics, the purpose of the current study is to take an initial step to explore a ...positive implication of psychological entitlement.Design/methodology/approachThe target population for this study comprises employees from various industries in Taiwan. To examine the research hypotheses, structural equation modeling techniques were employed to perform a mediation analysis and conditional process analysis.FindingsThe results of this research showed that career ambition mediates the relationship between psychological entitlement and job involvement, where psychological entitlement is positively related to career ambition, and career ambition is positively related to job involvement. Nonetheless, the authors' data did not support the proposed moderation effect of self-efficacy on the relationship between career ambition and job involvement.Originality/valueThis work is among the first to investigate how an employee's psychological entitlement is associated with his/her job involvement and the boundary conditions that affect this relationship.
The rapid development of information and communication technology enables a promising market of information densely product, i.e. smart, connected product (SCP), and also changes the way of ...user–designer interaction in the product development process. For SCP, massive data generated by users drives its design innovation and somehow determines its final success. Nevertheless, most existing works only look at the new functionalities or values that are derived in the one-way communication by introducing novel data analytics methods. Few work discusses about an effective and systematic approach to enable individual user innovation in such context, i.e. co-development process, which sets the fundamental basis of the prevailing concept of data-driven design. Aiming to fill this gap, this paper proposes a generic data-driven cyber-physical approach for personalised SCP co-development in a cloud-based environment. A novel concept of smart, connected, open architecture product is hence introduced with a generic cyber-physical model established in a cloud-based environment, of which the interaction processes are enabled by co-development toolkits with smartness and connectedness. Both the personalized SCP modelling method and the establishment of its cyber-physical product model are described in details. To further demonstrate the proposed approach, a case study of a smart wearable device (i.e. i-BRE respiratory mask) development process is given with general discussions.
Local color: Gold nanoparticles (GNPs) bifunctionalized with a crown ether and thioctic acid can be used for the rapid sensing of a target analyte with the naked eye. A color transformation occurs ...when the interparticle hydrogen bonds of aggregated GNPs are broken forming a dispersion. For example, the detection of PbII takes only 1 s (see picture).
In the Industry 4.0 environment, the new manufacturing transformation of mass customization for high-complexity and low-volume production is moving forward. Based on cyber-physical system (CPS) and ...Internet of things (IoT) technology, the flexible transformation of the manufacturing process to suit diverse customer manufacturing requirements is very possible, with the potential to provide digital “make-to-order” (MTO) services with a quick response time. To achieve this potential, a product configuration system, which translates the voice of customers to technical specifications, is needed. The purpose of this study is to propose a methodology for developing a quick-response product configuration system to enhance the communication between the customer and the manufacturer. The aim is to find an approach to receive requests from customers as inputs and generate a product configuration as outputs that maximizes customer satisfaction. In this approach, engineering characteristics (ECs) are defined, and selection pools are initially constructed. Then, quality function deployment (QFD) is modified and integrated with the Kano model to qualitatively and quantitatively analyze the relationship between customer requirements (CRs) and customer satisfaction (CS). Next, a mathematical programming model is applied to maximize the overall customer satisfaction level and recommend an optimal product configuration. Finally, sensitivity analysis is conducted to suggest revisions for customers and determine the final customized product specification. A case study and an OrderAssistant system are implemented to demonstrate the procedure and effectiveness of the proposed quick response product configuration system.
The use of artificial intelligence (AI) in the medical domain has attracted considerable research interest. Inference applications in the medical domain require energy-efficient AI models. In ...contrast to other types of data in visual AI, data from medical laboratories usually comprise features with strong signals. Numerous energy optimization techniques have been developed to relieve the burden on the hardware required to deploy a complex learning model. However, the energy efficiency levels of different AI models used for medical applications have not been studied.
The aim of this study was to explore and compare the energy efficiency levels of commonly used machine learning algorithms-logistic regression (LR), k-nearest neighbor, support vector machine, random forest (RF), and extreme gradient boosting (XGB) algorithms, as well as four different variants of neural network (NN) algorithms-when applied to clinical laboratory datasets.
We applied the aforementioned algorithms to two distinct clinical laboratory data sets: a mass spectrometry data set regarding Staphylococcus aureus for predicting methicillin resistance (3338 cases; 268 features) and a urinalysis data set for predicting Trichomonas vaginalis infection (839,164 cases; 9 features). We compared the performance of the nine inference algorithms in terms of accuracy, area under the receiver operating characteristic curve (AUROC), time consumption, and power consumption. The time and power consumption levels were determined using performance counter data from Intel Power Gadget 3.5.
The experimental results indicated that the RF and XGB algorithms achieved the two highest AUROC values for both data sets (84.7% and 83.9%, respectively, for the mass spectrometry data set; 91.1% and 91.4%, respectively, for the urinalysis data set). The XGB and LR algorithms exhibited the shortest inference time for both data sets (0.47 milliseconds for both in the mass spectrometry data set; 0.39 and 0.47 milliseconds, respectively, for the urinalysis data set). Compared with the RF algorithm, the XGB and LR algorithms exhibited a 45% and 53%-60% reduction in inference time for the mass spectrometry and urinalysis data sets, respectively. In terms of energy efficiency, the XGB algorithm exhibited the lowest power consumption for the mass spectrometry data set (9.42 Watts) and the LR algorithm exhibited the lowest power consumption for the urinalysis data set (9.98 Watts). Compared with a five-hidden-layer NN, the XGB and LR algorithms achieved 16%-24% and 9%-13% lower power consumption levels for the mass spectrometry and urinalysis data sets, respectively. In all experiments, the XGB algorithm exhibited the best performance in terms of accuracy, run time, and energy efficiency.
The XGB algorithm achieved balanced performance levels in terms of AUROC, run time, and energy efficiency for the two clinical laboratory data sets. Considering the energy constraints in real-world scenarios, the XGB algorithm is ideal for medical AI applications.
A one‐pot synthesis of large size and high quality AuAg alloy nanoparticles (NPs) with well controlled compositions via hot organic media is demonstrated. Amid the synthesis, complexation between ...trioctylphosphine (TOP) and metal precursors is found, which slows down the rate of nucleation and leads to the growth of large‐size AuAg nanoalloys. The wavelength and relative intensities of the resulting plasmon bands are readily fine‐tuned during the synthetic process using different Au/Ag precursors molar ratios. In the polymer solar cells, a key step in achieving high efficiency is the utilization of 1% Au11Ag89 alloy NPs embedded in the active layer to promote the power conversion efficiency (PCE) up to 4.73%, which outperforms the reference device based on the control standard device of poly(3‐hexylthiophene) (P3HT):phenyl‐C61‐butyric acid methyl ester (PC61BM) under identical conditions. Corresponding increases in short‐circuit current density (Jsc), open‐circuit voltage (Voc), fill factor (FF), and incident photon‐to‐current efficiency (IPCE) enable 31% PCE improvement due to the enhancement of the light‐trapping and the improvement of charge transport in the active layer. The findings advance the fundamental understanding and point to the superiority of Au11Ag89 nanoalloys as a promising metallic additive over Au, Ag, and Au28Ag72 alloy NPs to boost the solar cell performance.
A one‐pot synthesis of large size and monodispersed AuAg nanoalloys is developed in hot organic media and the mechanism of production is elaborated in detail. Simultaneous enhancements of the short circuit current density, open circuit voltage, fill factor, and incident photon‐to‐current efficiency are achieved in high‐performance bulk heterojunction solar cells with incorporation of 1% Au11Ag89 nanoalloys embedded in the active layer.
PDF
