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Adhesively bonded joints are used in many fields, especially in the automotive, marine, aviation, defense and outdoor industries. Adhesive bonding offers advantages over traditional mechanical methods, including the ability to join diverse materials, even load distribution and efficient thermal-electrical insulation. This study aims to investigate the mechanical properties of adhesively bonded joints, focusing on adherends produced with auxetic and flat surfaces adhered with varying adhesive thicknesses.

The research uses three-dimensional (3D)-printed materials, polyethylene terephthalate glycol and polylactic acid, and two adhesive types with ductile and brittle properties for single lap joints, analyzing their mechanical performance through tensile testing. The adhesion region of one of these adherends was formed with a flat surface and the other with an auxetic surface. Adhesively bonded joints were produced with 0.2, 0.3 and 0.4 mm bonding thickness.

Results reveal that auxetic adherends exhibit higher strength compared to flat surfaces. Interestingly, the strength of ductile adhesives in auxetic bonded joints increases with adhesive thickness, while brittle adhesive strength decreases with thicker auxetic bonds. Moreover, the auxetic structure displays reduced elongation under comparable force.

The findings emphasize the intricate interplay between adhesive type, bonded surface configuration of adherend and bonding thickness, crucial for understanding the mechanical behavior of adhesively bonded joints in the context of 3D-printed materials.

Responding to the continuing separation of participants and researchers in LIS participatory research, a new methodology is proposed: action partnership research design (APRD). It is asserted that APRD can mitigate or remove the hierarchical structures often inherent in the research process, thus allowing for equal contribution from all.

Building on the bonded design (BD) methodology and informed by a scoping literature review conducted by the same authors, APRD is a human-centered research approach with the goal of empowering and valuing community partnerships. APRD originates from research investigating the use of participatory design methods to foster collaboration between two potentially disparate groups, firstly with adult researchers/designers and elementary school children, and secondly with university faculty and IT professionals.

To achieve this goal, in addition to BD techniques, APRD draws inspiration from elements of indigenous and decolonization research methodologies, particularly those with an emphasis on destabilizing power hierarchies and involving research participants as full partners.

APRD, which emerged from findings from previous participatory design studies, especially those of BD, is based on the premise of partnership, recognizing that each member of a design team, whether researcher or participant/user, has unique expertise to contribute. By considering participants/users as full research partners, APRD aims to flatten the hierarchies exhibited in some LIS participatory research methodologies, where participants are treated more like research subjects than partners.

Through a review of the literature, this article seeks to outline and understand the evolution and extent of user–participant involvement in the existing library and information science (LIS) research to identify gaps and existing research approaches that might inform further methodological development in participant-oriented and design-based LIS research.

A scoping literature review of LIS research, from the 1960s onward, was conducted, assessing the themes and trends in understanding the user/participant within the LIS field. It traces LIS research from its early focus on information and relevancy to the “user turn”, to the rise of participatory research, especially design-based, as well as the recent inclusion of Indigenous and decolonial methodologies.

The literature review indicates that despite the reported “user turn”, LIS research often does not include the user as an active and equal participant within research projects.

The findings from this review support the development of alternative design research methodologies in LIS that fully include and involve research participants as full partners – from planning through dissemination of results – and suggests avenues for continuing the development of such design-based research. To that end, it lays the foundations for the introduction of a novel methodology, Action Partnership Research Design (APRD).

This paper aims to explore the quantile-specific short- and long-term effects of economic policy uncertainty (EPU) on the efficiency of the green bond market.

This study examines the long-term cointegration relationship and the short-term fluctuation relationship of EPU, WTI crude oil price (WTI) and European Union Allowances price (EUA) with the green bond market efficiency (GBE) using the quantile autoregressive distributed lag method. Additionally, the authors analyze the differences before and after the Covid-19 pandemic.

EPU has a significant positive impact on the GBE before the outbreak. However, during the crisis period, the impact of EPU and WTI was greatly weakened, whereas the impact of EUA was strengthened.

This paper demonstrates the dynamics of GBE and its influencing factors under different periods. The findings provide insights for market participants and policymakers to gain a clearer understanding of the green bond market.

This paper extends the study of green bonds by quantifying the GBE and elucidating the nonlinear relationship between efficiency and independent variables at different quantiles over different periods.

The time-varying equivalent linear temperature gradient (ELTG) significantly affects the development of faulting and must therefore be accounted for in pavement design. The same is true for faulting of bonded concrete overlays of asphalt (BCOA) with slabs larger than 3 x 3 m. However, the evaluation of ELTG in Mechanistic-Empirical (ME) BCOA design is highly time-consuming. The use of an effective ELTG (EELTG) is an efficient alternative to calculating ELTG. In this study, a model to quickly evaluate EELTG was developed for faulting in BCOA for panels 3 m or longer in size, whose faulting is sensitive to ELTG.

A database of EELTG responses was generated for 144 BCOAs at 169 locations throughout the continental United States, which was used to develop a series of prediction models. Three methods were evaluated: multiple linear regression (MLR), artificial neural networks (ANNs), and multi-gene genetic programming (MGGP). The performance of each method was compared, considering both accuracy and model complexity.

It was shown that ANNs display the highest accuracy, with an R² of 0.90 on the validation dataset. MLR and MGGP models achieved R² of 0.73 and 0.71, respectively. However, these models consisted of far fewer free parameters as compared to the ANNs. The model comparison performed in this study highlights the need for researchers to consider the complexity of models so that their direct implementation is feasible.

This research produced a rapid EELTG prediction model for BCOAs that can be incorporated into the existing faulting model framework.

This paper aims to examine the effects of bonding temperature, bonding time, bonding pressure and the presence of a Pt catalyst on the bonding strength of Cu/SB/P-Cu/SB/Cu joints by transient liquid phase bonding (TLPB).

TLPB is promising to assemble die-attaching packaging for power devices. In this study, porous Cu (P-Cu) foil with a distinctive porous structure and Sn-58Bi solder (SB) serve as the bonding materials for TLPB under a formic acid atmosphere (FA). The high surface area of P-Cu enables efficient diffusion of the liquid phase of SB, stimulating the wetting, spreading and formation of intermetallic compounds (IMCs).

The higher bonding temperature decreased strength due to the coarsening of IMCs. The longer bonding time reduced the bonding strength owing to the coarsened Bi and thickened IMC. Applying optimal bonding pressure improved bonding strength, whereas excessive pressure caused damage. The presence of a Pt catalyst enhanced bonding efficiency and strength by facilitating reduction–oxidation reactions and oxide film removal.

Overall, this study demonstrates the feasibility of low-temperature TLPB for Cu/SB/P-Cu/SB/Cu joints and provides insights into optimizing bonding strength for the interconnecting materials in the applications of power devices.

In recent years, there has been growing interest in the use of stainless steel (SS) in reinforced concrete (RC) structures due to its distinctive corrosion resistance and excellent mechanical properties. To ensure effective synergy between SS and concrete, it is necessary to develop a time-saving approach to accurately determine the ultimate bond strength τ_u between the two materials in RC structures.

Three robust machine learning (ML) models, including support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost), are employed to predict τ_u between ribbed SS and concrete. Model hyperparameters are fine-tuned using Bayesian optimization (BO) with 10-fold cross-validation. The interpretable techniques including partial dependence plots (PDPs) and Shapley additive explanation (SHAP) are also utilized to figure out the relationship between input features and output for the best model.

Among the three ML models, BO-XGBoost exhibits the strongest generalization and highest accuracy in estimating τ_u. According to SHAP value-based feature importance, compressive strength of concrete f_c emerges as the most prominent feature, followed by concrete cover thickness c, while the embedment length to diameter ratio l/d, and the diameter d for SS are deemed less important features. Properly increasing c and f_c can enhance τ_u between ribbed SS and concrete.

An online graphical user interface (GUI) has been developed based on BO-XGBoost to estimate τ_u. This tool can be utilized in structural design of RC structures with ribbed SS as reinforcement.

This study aims to explore the determinants of viewers’ gifting and social sharing behaviours in online streaming from a dual-attachment perspective and to explain how live streaming fosters attachment through a social interaction aspect.

This study conducted an online survey with 316 valid responses to test the research model. The structural equation modelling approach was applied to assess both the measurement and structural models.

The results show that both bond-based and identity-based attachments promote gifting and social sharing behaviours. Participation and cognitive communion motivate viewers to establish bond-based attachment, while group interaction among viewer crowds encourages viewers to create identity-based attachment. In addition, group interaction can moderate the relationship between participation and bond-based attachment.

This study is one of the earliest attempts to highlight the significance of viewer crowd and viewer-viewer interaction in promoting viewers’ behaviours in live streaming context. This study also indicates that viewer-viewer interaction can moderate the impact of viewer–streamer interaction, which is among the first to investigate the interaction effects of viewer-viewer interaction and viewer–streamer interaction.

This paper compares the benefits of direct international real estate investments in a mixed asset portfolio from the perspective of a passive investor with high and low bond allocation.

Due to high data availability and its professionalism, the Norwegian sovereign wealth fund was used as a representative example. Real estate indices from 8 countries were used for the portfolio analysis. The data were desmoothed according to Geltners’s 1993 approach.

The optimal real estate ratio in the present case is around 20–55%. However, this is strongly dependent on the bond ratio of the multi-asset portfolio. Portfolios with a high equity ratio benefit more from the additional direct real estate investments than portfolios with high bond ratios.

A rebalancing of individual stocks and bonds was not analysed. Only indexes from MSCI (Morgan Stanley Capital International) were available.

Concludes that the weighting of stocks and bonds has a strong influence on the optimal real estate ratio and therefore structural changes that affect this weighting.

The originality of the paper lies in the analysis with different weights of stocks and bonds, the consideration of 8 real estate markets and the observation period. The results of the work highlight areas of interest for further research.

This study aims to identify the ability of gold and cryptocurrency (Cryptocurrency Uncertainty Index (UCRY) Price) as safe haven assets (SHA) for stocks and bonds in both conventional (i.e. stock indices and government bonds) and Islamic markets (i.e. Islamic stock indices and Islamic bonds (IB)).

The authors employed the nonadditive panel quantile regression model by Powell (2016). It measured the safe haven characteristics of gold and UCRY Price for stock indices, government bonds, Islamic stocks, and IB under gold circumstances and level of cryptocurrency uncertainty, respectively. The period spanned from 11 March 2020 to 31 December 2021.

This study discovered three findings, including: (1) gold is a strong safe haven for stocks and bonds in conventional and Islamic markets under bearish conditions; (2) UCRY Price is a strong safe haven for conventional stocks and bonds but only a weak safe haven for Islamic stocks under high crypto uncertainty; and (3) gold offers a safe haven in both emerging and developed countries, while UCRY Price provides a better safe haven in developed than in emerging countries.

Gold always wins big for safe haven properties during unstable economy. It can also win over investors who consider shariah compliant products. Therefore, it should be included in an investor's portfolio. Meanwhile, cryptocurrencies are more common for developed countries. Thus, the governments and regulators of emerging countries need to provide more guidance around cryptocurrency so that the societies have better literacy. On top of that, the investors can consider crypto to mitigate risks but with limited safe haven functions.

The originality aspects of this study include: (1) four chosen assets from conventional and Islamic markets altogether (i.e. stock indices, government bonds, Islamic stock indices and IB); (2) indicator countries selected based on the most used and owned cryptocurrencies for the SHA study; and (3) the utilization of UCRY Price as a crypto indicator and a further examination of the SHA study toward four financial assets.