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This study aims to present a sustainable approach in the natural dyeing of cellulose fabric followed by nanosilver finishing through a green crosslinker of citric acid for potential antibacterial surgical gown fabrication.

The nanosilver finish was reproduced using the chemical reduction method. The fabric dyeing was performed on a lab-scale dyeing machine, whereas silver nano-finishing through a pad-dry-cure approach. Citric acid was used as an eco-friendly crosslinker. The specimens were characterized for antibacterial activity, surface chemical, textile, color properties and finish release trend.

The results demonstrated the successful application of curcumin dye followed by silver nano-finishing. The resultant fabric exhibited appropriate textile, dyeing performance indicators, hydrophobic behavior and sustainable broad-spectrum antibacterial activity.

The prepared nanosilver-finished/curcumin-treated fabric expressed desirable properties for potential applications in the fabrication of surgical gowns.

The authors found no reports on an extensive examination of nanosilver finishing on the color parameters of curcumin-dyed cellulose fabric while retaining its textile and comfort properties for possible surgical gown fabrication.

Machine learning (ML), and deep learning in particular, is gaining traction across a myriad of real-life applications. Portfolio management is no exception. This paper provides a systematic literature review of deep learning applications for portfolio management. The findings are likely to be valuable for industry practitioners and researchers alike, experimenting with novel portfolio management approaches and furthering investment management practice.

This review follows the guidance and methodology of Linnenluecke et al. (2020), Massaro et al. (2016) and Fisch and Block (2018) to first identify relevant literature based on an appropriately developed search phrase, filter the resultant set of publications and present descriptive and analytical findings of the research itself and its metadata.

The authors find a strong dominance of reinforcement learning algorithms applied to the field, given their through-time portfolio management capabilities. Other well-known deep learning models, such as convolutional neural network (CNN) and recurrent neural network (RNN) and its derivatives, have shown to be well-suited for time-series forecasting. Most recently, the number of papers published in the field has been increasing, potentially driven by computational advances, hardware accessibility and data availability. The review shows several promising applications and identifies future research opportunities, including better balance on the risk-reward spectrum, novel ways to reduce data dimensionality and pre-process the inputs, stronger focus on direct weights generation, novel deep learning architectures and consistent data choices.

Several systematic reviews have been conducted with a broader focus of ML applications in finance. However, to the best of the authors’ knowledge, this is the first review to focus on deep learning architectures and their applications in the investment portfolio management problem. The review also presents a novel universal taxonomy of models used.

High packaging density in the present VLSI era builds an acute power crisis, which limits the use of MOSFET device as a constituent block in CMOS technology. This leads researchers in looking for alternative devices, which can replace the MOSFET in CMOS VLSI logic design. In a quest for alternative devices, tunnel field effect transistor emerged as a potential alternative in recent times. The purpose of this study is to enhance the performances of the proposed device structure and make it compatible with circuit implementation. Finally, the performances of that circuit are compared with CMOS circuit and a comparative study is made to find the superiority of the proposed circuit with respect to conventional CMOS circuit.

Silicon–germanium heterostructure is currently one of the most promising architectures for semiconductor devices such as tunnel field effect transistor. Analytical modeling is computed and programmed with MATLAB software. Two-dimensional device simulation is performed by using Silvaco TCAD (ATLAS). The modeled results are validated through the ATLAS simulation data. Therefore, an inverter circuit is implemented with the proposed device. The circuit is simulated with the Tanner EDA tool to evaluate its performances.

The proposed optimized device geometry delivers exceptionally low OFF current (order of 10^−18 A/um), fairly high ON current (5x10^−5 A/um) and a steep subthreshold slope (20 mV/decade) followed by excellent ON–OFF current ratio (order of 10^13) compared to the similar kind of heterostructures. With a very low threshold voltage, even lesser than 0.1 V, the proposed device emerged as a good replacement of MOSFET in CMOS-like digital circuits. Hence, the device is implemented to construct a resistive inverter to study the circuit performances. The resistive inverter circuit is compared with a resistive CMOS inverter circuit. Both the circuit performances are analyzed and compared in terms of power dissipation, propagation delay and power-delay product. The outcomes of the experiments prove that the performance matrices of heterojunction Tunnel FET (HTFET)-based inverter are way ahead of that of CMOS-based inverter.

Germanium–silicon HTFET with stack gate oxide is analytically modeled and optimized in terms of performance matrices. The device performances are appreciable in comparison with the device structures published in contemporary literature. CMOS-like resistive inverter circuit, implemented with this proposed device, performs well and outruns the circuit performances of the conventional CMOS circuit at 45-nm technological node.

Research into older adults' use of social media remains limited. Driven by increasing digitalisation in China, the authors focus on Chinese older adults (aged 60–75)’ use of WeChat.

This study used a qualitative interpretive approach and interviewed Chinese older adults to uncover their social practices of WeChat use in everyday life.

By using social practice theory (SPT), the paper unfolds Chinese older adults' social practices of WeChat use in everyday life and reveals how they adopt and resist the drastic changes in Chinese society.

The study contributes to new understandings of SPT from technology use by emphasising the dynamic characteristics of its three elements. The authors synthesise both adoptions and resistance in SPT and highlight the importance of understanding three elements interdependently within specific contexts, which are conditioned by structure and agency.

Waiting time, as an important predictor of queue abandonment and patient satisfaction, is important for resource utilization and patient experience management. Medical institutions have given top priority to reforming the appointment system for many years; however, whether the increased information transparency brought about by the appointment scheduling mechanism could improve patient waiting time is not well understood. In this study, the authors examine the effects of information transparency in reducing patient waiting time from an uncertainty perspective.

Leveraging a quasi-natural experiment in a tertiary academic hospital, the authors analyze over one million observational patient visit records and design the propensity score matching plus the difference in difference (PSM-DID) model and hierarchical linear modeling (HLM) to address this issue.

The authors confirm that, on average, improved information transparency significantly reduces the waiting time for patients by approximately 6.43 min, a 4.90% reduction. The authors identify three types of uncertainties (resource, process and outcome uncertainty) in the patient visit process that affect patients' waiting time. Moreover, information transparency moderates the relationship between three sources of uncertainties and waiting time.

The authors’ work not only provides important theoretical explanations for the patient-level factors of in-clinic waiting time and the reasons for information technology (IT)-enabled appointment scheduling by time slot (ITASS) to shorten patient waiting time and improve patient experience but also provides potential solutions for further exploration of measures to reduce patient waiting time.

Prefabricated construction is an innovative technique for decreasing carbon emissions in the construction industry. However, as the investors of housing projects, a majority of developers are unwilling to adopt prefabricated housing in practice. To promote prefabricated housing, this study aims to develop an integrated framework of fuzzy-decision making trial and evaluation laboratory (fuzzy-DEMATEL) and system dynamics (SD) to understand the underlying influencing mechanism of developers' willingness.

Through literature review, a total of 17 influencing factors were identified. Then, the interrelationships among the factors were evaluated by 10 experienced professionals, and the impacts given and received by each factor were further analyzed through fuzzy-DEMATEL. Based on the technology acceptance model (TAM), a SD model was developed to explore the influencing mechanism.

The major cause factors were identified, including mandatory implementation policies, economic incentive policies, environmental protection policies, component standardization and developers' economic strength. This group of factors was expected to be given priority attention in the case of limited resources. On the other hand, the results indicated that economic incentive policies and mandatory implementation policies could affect the developers' willingness via perceived usefulness, while the others mainly influenced perceived ease of use.

Little research has focused on the interrelationships among the influencing factors of developers' willingness to adopt prefabricated housing. This study contributed to understanding the mechanism of developers' willingness from a systematic view and providing the priority of influencing factors. Several strategies were proposed to improve the practical implementation of prefabricated housing development.

This study empirically investigates the impacts of technological innovation and operational efficiency on environmental performance and the moderating effects of environmental orientation.

We develop a conceptual framework based on the Porter Hypothesis. We collect a sample of 850 listed firms in China between 2010 and 2019. The fixed effect model was used to analyse the data.

The empirical findings reveal that technological innovation indirectly enhances environmental performance through operational efficiency and partially mediates this impact. We also find that environmental orientation strengthens the positive impacts of technological innovation and operational efficiency on environmental performance.

This study contributes to the literature by revealing that technological innovation is positively associated with operational efficiency and environmental performance, which suggests that technological innovation can simultaneously enhance business and environmental performance. Hence, this study provides empirical support for the Porter Hypothesis. The results also extend the Porter Hypothesis by revealing how technological innovation affects environmental performance and under what conditions technological innovation has a greater impact on environmental performance.

Many waste-to-energy (WTE) plants are constructed and operated using the public-private partnership (PPP) mode in China. However, risk events of PPP WTE incineration projects sometimes occur. This study aims to clarify the relationship of risks in China's PPP WTE incineration projects and identify the key risks accordingly and risk transmission paths.

A risk list of PPP WTE incineration projects was obtained based on literature analysis. Moreover, a hybrid approach combining fuzzy sets, decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) was developed to analyze the causality of risks, explore critical risks and reveal the risk transmission paths. The quantitative analysis process was implemented in MATLAB.

The results show that government decision-making risk, government credit risk, government supervision behavior risk, legal and policy risk, revenue and cost risk and management capacity risk are the critical risks of PPP WTE incineration projects in China. These critical risks are at different levels in the risk hierarchy and often trigger other risks.

Currently, there is a lack of exploration on the interaction between the risks of PPP WTE incineration projects. This study fills this gap by examining the key risks and risk transfer pathways of PPP WTE incineration projects from the perspective of risk interactions. The findings can help the public and private sectors to systematically understand the risks in PPP WTE incineration projects, thus enabling them to identify the risks that need to be focused on when making decisions and to optimize risk prevention strategies. The proposed hybrid approach can offer methodological ideas for risk analysis of other types of PPP projects.

This paper aims to investigate whether the effects of children's current learning are related to their learning efficiency and behavior when they are exposed to two different gaming media.

In this paper the authors used a quasi-experimental design to determine whether game-based learning can be improved by using mobile devices equipped with augmented reality (AR).

The control group using the card game was careful to find the correct answer, with the intention of “obtaining the maximum score with the highest rate of correctness,” whereas the experimental group using the AR board game played aggressively by “obtaining the maximum score with the highest number.”

Although integrating an AR board game into the curriculum is an effective approach, the need to implement such a game in response to different learning attitudes and behaviors of students should be addressed.

Depending on the learning situation, different teaching methods and aids can be used to help students effectively learn. The recommendations based on this experiment can broaden the teaching field and allow for a wider range of experimental studies.

Learning behavior was observed, and user attention was interpreted using MindWave Mobile.

This study aims to dye silk with natural pigments extract of Coreopsis tinctoria, by treating the fabrics with appropriate mordant under suitable dyeing conditions, to achieve good dyeing depth, fastness and ultraviolet (UV) protection.

Firstly, single factor experiments were used to determine the basic dyeing conditions of Coreopsis tinctoria. The optimal process conditions for direct dyeing were determined through orthogonal experiments. After that, the dyeing with mordant was used. Based on the previously determined optimal process conditions, silk fabrics were dyed with different mordanting methods, with different mordants and mordant dosages. The dyeing results were compared, in terms of the K/S values of the dyed fabrics, to determine the most appropriate dyeing conditions with mordant.

The extract of Coreopsis tinctoria can dye silk fabrics satisfactorily. Good dyeing depth and fastness can be obtained by using suitable dyeing methods and dyeing conditions, especially when using the natural mordant pomegranate rind and the rare earth mordant neodymium oxide. The silk fabrics dyed with Coreopsis tinctoria have good UV resistance, which allows a desirable finishing effect to be achieved while dyeing, using a safe and environmentally friendly method.

The composition of Coreopsis tinctoria is complex, and the specific composition of colouring the silk fibre has not been determined. There are many factors that affect the dyeing experiment, which have an impact on the experimental results.

The results of this study may help expand the application of Coreopsis tinctoria beyond medicine.

To the best of the authors’ knowledge, this paper is the first report on dyeing silk with the extract of Coreopsis tinctoria achieving good dyeing results. Its depth of staining and staining fastness were satisfactory. Optimum dyeing method and dyeing conditions have been identified. The fabric dyed with Coreopsis tinctoria has good UV protection effect, which is conducive to improving the application value of the dyeing fabric. The findings help offer a new direction for the application of medicinal plants in the eco-friendly dyeing of silk.