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Sharing project information is critical for the success of medical crowdfunding campaigns. However, few users share medical crowdfunding projects on their social networks, and the sharing behavior of medical crowdfunding projects on social networking sites has not been well studied. Therefore, this study explored the factors and potential mechanisms influencing users’ sharing behaviors on networking sites.

A research model was developed based on the attribution-affect model of helping and social capital theory. Data were collected using a longitudinal survey. Partial least squares structural equation modeling was used to analyze the collected data. We conducted post hoc analyses to validate the results of the quantitative analysis.

The analysis results verified the effects of perceived external attribution, perceived uncontrollable attributions, and perceived unstable attributions on sympathy and identified the effect of sympathy and social characteristics of medical crowdfunding users on sharing behavior.

This research provides a comprehensive theoretical understanding of users’ sharing behavior characteristics and provides implications for enhancing the efficiency of medical crowdfunding activities.

For ranking aggregation in crowdsourcing task, the key issue is how to select the optimal working group with a given number of workers to optimize the performance of their aggregation. Performance prediction for ranking aggregation can solve this issue effectively. However, the performance prediction effect for ranking aggregation varies greatly due to the different influencing factors selected. Although questions on why and how data fusion methods perform well have been thoroughly discussed in the past, there is a lack of insight about how to select influencing factors to predict the performance and how much can be improved of.

In this paper, performance prediction of multivariable linear regression based on the optimal influencing factors for ranking aggregation in crowdsourcing task is studied. An influencing factor optimization selection method based on stepwise regression (IFOS-SR) is proposed to screen the optimal influencing factors. A working group selection model based on the optimal influencing factors is built to select the optimal working group with a given number of workers.

The proposed approach can identify the optimal influencing factors of ranking aggregation, predict the aggregation performance more accurately than the state-of-the-art methods and select the optimal working group with a given number of workers.

To find out under which condition data fusion method may lead to performance improvement for ranking aggregation in crowdsourcing task, the optimal influencing factors are identified by the IFOS-SR method. This paper presents an analysis of the behavior of the linear combination method and the CombSUM method based on the optimal influencing factors, and optimizes the task assignment with a given number of workers by the optimal working group selection method.

Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.

A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.

The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R²) is 0.93 for the validation set, and the R² for the test set A and test set B are 0.93 and 0.94, respectively.

This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.

Component positioning is an important part of aircraft assembly, aiming at the problem that it is difficult to accurately fall into the corresponding ball socket for the ball head connected with aircraft component. This study aims to propose a ball head adaptive positioning method based on impedance control.

First, a target impedance model for ball head positioning is constructed, and a reference positioning trajectory is generated online based on the contact force between the ball head and the ball socket. Second, the target impedance parameters were optimized based on the artificial fish swarm algorithm. Third, to improve the robustness of the impedance controller in unknown environments, a controller is designed based on model reference adaptive control (MRAC) theory and an adaptive impedance control model is built in the Simulink environment. Finally, a series of ball head positioning experiments are carried out.

During the positioning of the ball head, the contact force between the ball head and the ball socket is maintained at a low level. After the positioning, the horizontal contact force between the ball head and the socket is less than 2 N. When the position of the contact environment has the same change during ball head positioning, the contact force between the ball head and the ball socket under standard impedance control will increase to 44 N, while the contact force of the ball head and the ball socket under adaptive impedance control will only increase to 19 N.

In this paper, impedance control is used to decouple the force-position relationship of the ball head during positioning, which makes the entire process of ball head positioning complete under low stress conditions. At the same time, by constructing an adaptive impedance controller based on MRAC, the robustness of the positioning system under changes in the contact environment position is greatly improved.

Industry 4.0 has an inimitable potential to create competitive advantages for the apparel industry by enhancing productivity, production, profitability, efficiency and effectiveness. This study, thus, aims to assess the digitalisation level of the Tanzanian apparel industry through the Industry 4.0 perspectives.

A mixed-methods-based approach was deployed. This study deployed semi-structured interviews, document review and observation methods for the qualitative approach. For the quantitative approach, closed-ended questionnaires were used to ascertain the digitalisation levels and maturity level of the textiles and apparel (T&A) factories and small and medium-sized textile enterprises in Tanzania. The sample size was 110, with participants engaged through the purposive sampling technique.

Industry 4.0 frameworks evolved into practices mainly since 2011 in several service and manufacturing industries globally. For Tanzania, the findings indicate that the overall maturity level of the T&A industries is 2.5 out of 5.0, demonstrating a medium level of adoption. Thus, the apparel industries are not operating under the industry 4.0 framework; they are operating within the third industrial revolution – Industry 3.0 – framework. For such industries to operate within the fourth industrial revolution – Industry 4.0 – that is only possible if there is significantly well-developed industrial infrastructure, availability of engineering talent, stable commercial partnerships, demand from the marketplace and transactional relationship with customers.

This study’s limitations include: firstly, Industry 4.0 is an emerging area; this resulted in limited theoretical underpinnings in the Tanzanian perspectives. Secondly, the studied industries may not suffice the need to generalise the findings for the entire country, thus needing another study.

Although Industry 4.0 conceptual frameworks have been on trial in several industries since 2011, this is amongst the first empirical research on Industry 4.0 in the Tanzanian apparel industry that assesses the digitalisation levels.

To develop electrode materials for supercapacitor with superior electrochemical performance and simple preparation process, the purpose of this study is to prepare flexible CC/NiS/a-NiS electrodes with self-supporting structure by loading hydrothermally synthesized a-NiS particles along with nano-NiS on carbon cloth by electroplating method.

The effects of current densities, temperatures and pH values on the loading amount and uniformity of the active substances during the plating process were investigated on the basis of optimization of surface morphology, crystalline structure and electrochemical evaluation as the cyclic voltammetry curves, constant current charge–discharge curves and AC impedance.

The a-NiS particles on CC/NiS/a-NiS were mostly covered by the plated nano-NiS, which behaved as a bulge and provided a larger specific surface area. The CC/NiS/a-NiS electrode prepared with the optimized parameter exhibited a specific capacitance of 115.13 F/g at a current density of 1 A/g and a Coulomb efficiency of 84% at 5 A/g, which is superior to that of CC/NiS electrode prepared by electroplating at a current density of 10 mA/cm², a temperature of 55°C and a pH of 4, demonstrating its fast charge response of the electrode and potential application in wearable electronics.

This study provides an integrated solution for the development of specifically structured NiS-based electrode for supercapacitor with simple process, low cost and high electrochemical charge/discharge performance, and the simple and easy-to-use method is also applicable to other electrochemically active composites.

Mianzi can powerfully influence tourists’ behavior. Compared with product brands, destination brands are more multidimensional, consisting of intangible and tangible elements. Therefore, this paper aims to explore the relationships among the Chinese culture-related variable mianzi, destination product quality, destination service quality, destination brand value, destination brand resonance, destination brand self-congruity and destination overall brand equity.

A questionnaire survey was conducted in 2021, yielding 475 valid responses from tourists who had traveled to Hainan, China. Data was analyzed using structural equation modeling.

The results showed that mianzi plays a significant role in shopping destination brand equity, and the mianzi effect shapes tourists’ positive perceptions of destination product and service quality. Meanwhile, destination product quality and service quality enhance shopping destinations’ overall brand equity through destination brand value, brand resonance and brand self-congruity.

This study, focusing on shopping destinations, presents a novel view of brand equity. The research also uncovers influencing factors (e.g. product quality and service quality) that further enrich the destination brand equity model. Finally, findings offer valuable insights for academic research and the practical development of shopping destinations.

面子能有力地影响游客的行为。与产品品牌相比, 目的地品牌更加多维, 由无形要素和有形要素构成。因此, 本文旨在探讨与中国文化相关的变量面子、目的地产品质量、目的地服务质量、目的地品牌价值、目的地品牌共鸣、目的地品牌自我一致和目的地整体品牌资产之间的关系。

2021年对去过中国海南旅游的游客进行问卷调查, 最终获取了 475 份有效问卷。

果表明, 结果表明面子在购物目的地品牌资产中发挥着重要作用, 面子效应塑造了游客对目的地产品和服务质量的积极认知。同时, 目的地产品质量和服务质量通过目的地品牌价值、品牌共鸣和品牌自我一致提升了购物目的地的整体品牌资产。

本研究以购物目的地为重点, 提出了一种新颖的品牌资产观点。研究还发现了一些影响因素（如产品质量和服务质量）, 进一步丰富了目的地品牌资产模型。最后, 研究结果为学术研究和购物目的地的实际发展提供了宝贵的见解。

Mianzi puede influir poderosamente en el comportamiento de los turistas. En comparación con las marcas de producto, las marcas de destino son más multidimensionales y constan de elementos intangibles y tangibles. Por lo tanto, este artículo pretende explorar las relaciones entre la variable mianzi relacionada con la cultura china, la calidad del producto del destino, la calidad del servicio del destino, el valor de la marca del destino, la resonancia de la marca del destino, la autocongruencia de la marca del destino y el valor general de la marca del destino.

En 2021 se llevó a cabo una encuesta por cuestionario, que arrojó 475 respuestas válidas de turistas que habían viajado a Hainan, China. Los datos se analizaron mediante un modelo de ecuaciones estructurales.

Los resultados mostraron que el mianzi desempeña un papel significativo en el valor de marca de los destinos de compras, y que el efecto mianzi determina las percepciones positivas de los turistas sobre la calidad de los productos y servicios del destino. Por su parte, la calidad de los productos y servicios del destino mejora el valor de marca global de los destinos de compras a través del valor de marca del destino, la resonancia de la marca y la autocongruencia de la marca.

Este estudio, centrado en los destinos de compras, presenta una visión novedosa del valor de marca. La investigación también descubre factores influyentes (por ejemplo, la calidad del producto y la calidad del servicio) que enriquecen aún más el modelo de valor de marca del destino. Por último, los resultados ofrecen valiosas perspectivas para la investigación académica y el desarrollo práctico de los destinos de compras.

The major objective of this research work was to evaluate various physico-chemical characteristics, such as, chemical composition, antioxidant capacity, objective color and texture profile analysis (TPA) of the wheat flour/chickpea flour (CF) blends, so that nutritious baked products could be consumed by the type-2 diabetic persons.

Wholegrain wheat flour (WGF) and white wheat flour (WWF) were substituted with CF at 0 to 40% levels. These wheat flour/CF blends were analyzed for proximate composition, the prepared dough and baked breads were tested for objective color, antioxidant capacity as trolox equivalent antioxidant capacity (TEAC), malondialdehyde (MDA) and total phenolic content (TPC) and TPA.

WGF had the highest TEAC (117.42 mM/100g) value, followed by WWF (73.98 mM/100g) and CF (60.67 mM/100g). TEAC, MDA and TPC values varied significantly among all the three flour samples.

Inclusion of whole chickpea (without dehulling) flour in such type of blends would be another interesting investigation during the future research studies.

These research findings have a great potential for the production of these baked products for human consumption on an industrial scale.

Production of breads using wheat flour and CF blends would benefits the consumers.

Production of Arabic and pan breads using wheat flour and CF blends would, therefore, combine the benefits of both the needed proteins of plant origin and the health-promoting bioactive compounds, in a most sustainable way for the consumers.

This study aims to provide a salt ready-mix to instant fried noodles manufacturers.

Response surface methodology was used to get optimized salt ready-mix based on carbonate salt, disodium phosphate, tripotassium phospahte, sodium hexametaphosphate and sodium chloride. Peak viscosity of flour and yellowness, cooking loss and hardness of noodles were considered as response factors for finding optimized salt formulation.

The results showed that salts have an important role in governing quality of noodles. Optimum levels of five independent variables of salts, namely, carbonate salt (1:1 mixture of sodium to potassium carbonate), disodium phosphate, sodium hexametaphosphate, tripotassium phosphate and sodium chloride were 0.64%, 0.29%, 0.25%, 0.46% and 0.78% on flour weight basis, respectively.

To the best of the authors’ knowledge, this is the first study to assess the effect of different combinations of different salts on the quality of noodles. These findings will also benefit noodle manufacturers, assisting in production of superior quality noodles.

Ulam is a traditional salad that contains high levels of antioxidants and is commonly consumed in raw form. However, the average ulam consumption among the low-income Malaysian population was only ½ serving daily. Thus, this study aimed to explore the motivators and barriers to ulam consumption among residents of low-cost housing areas (household income RM4849 or $1015.50) in Kuala Lumpur, Malaysia.

Six focus group discussions were conducted with 27 Malay residents aged 18–59 years in Kuala Lumpur, Malaysia. The researchers asked the participants a series of semi-structured questions. All the interviews were audio-recorded and transcribed verbatim. Two researchers coded the transcripts independently, and several themes were identified. The data were analysed using Nvivo version 12 software.

Three main factors for ulam consumption were identified in this study: personal, environmental and behavioural. The motivators and barriers were identified based on nine main themes and 16 sub-themes.

The results of this study identified potential areas for an effective intervention to increase ulam intake among residents in low-cost housing areas.

This work has the potential to identify the factors that have an impact on consumers' ulam preferences to help fulfil daily vegetable recommendations.