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Social recommendation has been recognized as a kind of e-commerce with large potential, but how social recommendations influence consumer decisions is still unclear. This paper aims to investigate how recommendations from different social ties influence consumers’ purchase intentions through both behavior and brain activity.

Utilizing behavioral (N = 70) and electroencephalogram (EEG) (N = 49) experiments, this study explored participants’ behavior and brain responses after being recommended by different social ties. The data were analyzed using statistical inference and event-related potential (ERP) analysis.

Behavioral results show that social tie strength positively impacts purchase intention, which can be fitted by a logarithmic model. Moreover, recommender-to-customer similarity and product affect mediate the effect of tie strength on purchase intention serially. EEG findings show that recommendations from weak tie strength elicit larger N100, N200 and P300 amplitudes than those from strong tie strength. These results imply that weak tie strength may motivate individuals to recruit more mental resources in social recommendation, including unconscious processing of consumer attention and conscious processing of cognitive conflict and negative emotion.

This study considers the effects of continuous social ties on purchase intention and models them mathematically, exploring the intrinsic mechanisms by which strong and weak ties influence purchase intentions through recommender-to-customer similarity and product affect, contributing to the applications of the stimulus-organism-response (SOR) model in the field of social recommendation. Furthermore, our study adopting EEG techniques bridges the gap of relying solely on self-report by providing an avenue to obtain relatively objective findings about the consumers’ early-occurred (unconscious) attentional responses and late-occurred (conscious) cognitive and emotional responses in purchase decisions.

This study aims to evaluate the development of composites made of epoxy (E) resin with different weight percentages of polypropylene (PP) and graphene oxide (Go) to form nanocomposite plates.

A hand lay-up process was used to develop 21 different composites, with varying concentrations of PP (5%–35%) and Go (5%–35%). A ternary composite of E matrix was produced by combining binary fillers PP and Go (5%–35%) in a 1:1 ratio to a (95%–5%) solution. With the help of adopting the melt condensation deal to extract Go, the modified Hummers method was used to make Go platelets.

Through field emission scanning electron microscopy (FESEM) and X-ray diffraction investigations, the particulate’s size and structural characteristics were identified. Based on the FESEM analysis of the collapsed zones of the composites, a warp-and-weft-like structure is evident, which endorses the growth yield strength, flexural modulus and impact strength of the composites.

The developed nanocomposites have exceptional mechanical capabilities compared to plain E resin, with E resin exhibiting better tensile strength, modulus and flexural strength when combined with 10% PP and 10% Go. When compared to neat E resin, materials formed from composites have exceptional mechanical properties. When mixed with 10% PP and 10% Go, E resin in particular displays improved tensile strength (23 MPa), tensile modulus (4.15 GPa), flexural strength (75.6 MPa) and other attributes. Engineering implications include automobile side door panels, spacecraft applications, brake pads and flexible battery guards.

Composite materials have revolutionized the aerospace industry by offering superior structural qualities over traditional elements. This study aims to focus on the development and testing of bamboo natural fiber-based composites enhanced with SiO₂ nanoparticles.

The investigation involved fabricating specimens with varying nanoparticle compositions (0, 10 and 20%) and conducting tensile, flexural, impact and fracture toughness tests. Results indicated significant improvements in mechanical properties with the addition of nanoparticles, particularly at a 10% composition level.

This study underscores the potential of natural fiber composites, highlighting their environmental friendliness, cost-effectiveness and improved structural properties when reinforced with nanoparticles. The findings suggest an optimal ratio for nanoparticle integration, emphasizing the critical role of precise mixing proportions in achieving superior composite performance.

The tensile strength, flexural strength, impact resistance and fracture toughness exhibited notable enhancements compared with the 0 and 20% nanoparticle compositions. The 10% composition showed the most promising outcomes, showcasing increased strength across all parameters.

This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.

I-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.

This study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.

The fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.

This study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.

The proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.

Gourd fibres (GF) are a natural biodegradable fibre material with excellent mechanical properties and high tensile strength. The use of natural fibres in composite materials has gained popularity in recent years due to their various advantages, including renewability, low cost, low density and biodegradability. Gourd fibre is one such natural fibre that has been identified as a potential reinforcement material for composites. However, it has low surface energy and hydrophobic nature, which makes it difficult to bond with matrix materials such as polyester. To overcome this problem, chemically adapted gourd fibre has been proposed as a solution. Chemical treatment is one of the most widely used methods to improve the properties of natural fibres. This research evaluates the feasibility and effectiveness of incorporating chemically adapted gourd fibre into polyester composites for industrial fabrication. The purpose of this study is to examine the application of chemically modified GF in the production of polyester composite engineering materials.

This work aims to evaluate the effectiveness of chemically adapted gourd fibre in improving the adhesion of gourd fibre with polyester resin in composite fabrication by varying the GF from 5 to 20 wt.%. The study involves the preparation of chemically treated gourd fibre through surface modification using sodium hydroxide (NaOH), permanganate (KMnO₄) and acetic acid (CH₃COOH) coupling agents. The mechanical properties of the modified fibre and composites were investigated. It was then characterized using scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) to determine the changes in surface morphology and functional groups.

FTIR characterization showed that NaOH treatment caused cellulose depolymerization and caused a significant increase in the hydroxyl and carboxyl groups, showing improved surface functional groups; KMnO₄ treatment oxidized the fibre surface and caused the formation of surface oxide groups; and acetic acid treatment induced changes that primarily affected the ester and hydroxyl groups. SEM study showed that NaOH treatment changed the surface morphology of the gourd fibre, introduced voids and reduced hydrophilic tendencies. The tensile strength of the modified gourd fibres increased progressively as the concentration of the modification chemicals increased compared to the untreated fibres.

This work presents the designed composite with density, mechanical properties and microstructure, showing remarkable improvements in the engineering properties. An 181.5% improvement in tensile strength and a 56.63% increase in flexural strength were got over that of the unreinforced polyester. The findings from this work will contribute to the understanding of the potential of chemically adapted gourd fibre as a reinforcement material for composites and provide insights into the development of sustainable composite materials.

The purpose of this paper is to examine the mechanical characteristics and optimization of wear parameters of hybrid (TiO₂ + Y₂O₃) nanoparticles with Al matrix using squeeze casting technique.

The hybrid aluminium matrix nanocomposites (HAMNCs) were fabricated with varying concentrations of titanium oxide (TiO₂) and yttrium oxide (Y₂O₃), from 2.5 to 10 Wt.% in 2.5 Wt.% increments. Dry sliding wear test variables were optimized using the Taguchi method.

The introduction of hybrid nanoparticles in the aluminium (Al) matrix was evenly distributed in contrast to the base matrix. HAMNC6 (5 Wt.% TiO₂ + 5 Wt.% Y₂O₃) reported the maximum enhancement in mechanical properties (tensile strength, flexural strength, impact strength and density) and decrease in porosity% and elongation% among other HAMNCs. The results showed that the optimal combination of parameters to achieve the lowest wear rate was A3B3C1, or 15 N load, 1.5 m/s sliding velocity and 200 m sliding distance. The sliding distance showed the greatest effect on the dry sliding wear rate of HAMNC6 followed by applied load and sliding velocity. The fractured surfaces of the tensile sample showed traces of cracking as well as substantial craters with fine dimples and the wear worn surfaces were caused by abrasion, cracks and delamination of HAMNC6.

Squeeze-cast Al-reinforced hybrid (TiO₂+Y₂O₃) nanoparticles have been investigated for their impact on mechanical properties and optimization of wear parameters.

The purpose of this study, most recent advancements in threedimensional (3D) printing have focused on the fabrication of components. It is typical to use different print settings, such as raster angle, infill and orientation to improve the 3D component qualities while fabricating the sample using a 3D printer. However, the influence of these factors on the characteristics of the 3D parts has not been well explored. Owing to the effect of the different print parameters in fused deposition modeling (FDM) technology, it is necessary to evaluate the strength of the parts manufactured using 3D printing technology.

In this study, the effect of three print parameters − raster angle, build orientation and infill − on the tensile characteristics of 3D-printed components made of three distinct materials − acrylonitrile styrene acrylate (ASA), polycarbonate ABS (PC-ABS) and ULTEM-9085 − was investigated. A variety of test items were created using a commercially accessible 3D printer in various configurations, including raster angle (0°, 45°), (0°, 90°), (45°, −45°), (45°, 90°), infill density (solid, sparse, sparse double dense) and orientation (flat, on-edge).

The outcome shows that variations in tensile strength and force are brought on by the effects of various printing conditions. In all possible combinations of the print settings, ULTEM 9085 material has a higher tensile strength than ASA and PC-ABS materials. ULTEM 9085 material’s on-edge orientation, sparse infill, and raster angle of (0°, −45°) resulted in the greatest overall tensile strength of 73.72 MPa. The highest load-bearing strength of ULTEM material was attained with the same procedure, measuring at 2,932 N. The tensile strength of the materials is higher in the on-edge orientation than in the flat orientation. The tensile strength of all three materials is highest for solid infill with a flat orientation and a raster angle of (45°, −45°). All three materials show higher tensile strength with a raster angle of (45°, −45°) compared to other angles. The sparse double-dense material promotes stronger tensile properties than sparse infill. Thus, the strength of additive components is influenced by the combination of selected print parameters. As a result, these factors interact with one another to produce a high-quality product.

The outcomes of this study can serve as a reference point for researchers, manufacturers and users of 3D-printed polymer material (PC-ABS, ASA, ULTEM 9085) components seeking to optimize FDM printing parameters for tensile strength and/or identify materials suitable for intended tensile characteristics.

This paper aims to reduce waste management and generate wealth by investigating the novelty of combining chicken feather fiber and bamboo particles to produce hybrid biocomposites. This is part of responsible production and sustainability techniques for sustainable development goals. This study aims to broaden animal and plant fiber utilization in the sustainable production of epoxy resins for engineering applications.

This research used two reinforcing materials [chicken feather fiber (CFF) and bamboo particles (BP)] to reinforce epoxy resin. The BPs were kept constant at 6 Wt.%, while the CFF was varied within 3–15 Wt.% in the composites to make CFF-BP polymer-reinforced composite (CFF-BP PRC). The mechanical experiment showed a 21% reduction in densities, making the CFF-BP PRC an excellent choice for lightweight applications.

It was discovered that fabricated composites with 10 mm CFF length had improved properties compared with the 15 mm CFF length and pristine samples, which confirmed that short fibers are better at enhancing randomly dispersed fibers in the epoxy matrix. However, the ballistic properties of both samples matched. There is a 40% increase in tensile strength and a 54% increase in flexural strength of the CFF-BP PRC compared to the pristine sample.

According to the literature review, to the best of the authors’ knowledge, this is a novel study of chicken fiber and bamboo particles in reinforcing epoxy composite.

The collection and use of personal medical information for mobile health (mHealth) service raise significant privacy concerns. In this context, this study aims to explore the privacy paradox and its impact from the perspective of paradox resolution.

Based on social support theory and privacy calculus theory, this study first studies the effect of social support on perceived benefits, and explores the moderating effect of perceived health status on the privacy trade-off process. Secondly, the study examines the path of “privacy concerns – disclosure intention – disclosure behavior” to verify the existence of the privacy paradox. Following this, based on rational choice theory, the rationality degree is introduced as a moderating variable to investigate both its impact on the central route and the strength of this impact on the privacy paradox.

Empirical results show that informational support and emotional support influence perceived benefits significantly. Perceived benefits significantly influence privacy concerns, and perceived health status has a significant positive moderating effect. The authors further find that there is a privacy paradox within the mHealth context, and the privacy paradox is moderated negatively by rationality degree. The findings indicate that the impact strength of the privacy paradox will decrease with increases in rationality degree.

The findings indicate that it is crucial to evaluate the privacy paradox and its impact from the perspective of paradox resolution.

This study offers a complete comprehension of the privacy paradox in mHealth and provides several valuable recommendations for enhancing both mHealth services and privacy controls.

This paper aims to examine dissimilar joints for various applications in chemical, petrochemical, oil, gas, shipbuilding, defense, rail and nuclear industry.

This study examined the effects of cold metal transfer welding on stainless steel welds for 316L austenitic and 430 ferritic dissimilar welds with ER316L, ER309L and without (autogenous) fillers. The microstructural observation was done with an optical microscope. The mechanical test was done to reveal the strength, hardness and toughness of the joint. The electrochemical polarization tests were done to reveal intergranular and pitting corrosion in the dissimilar joints.

This microstructural study shows the presence of austenitic and ferritic phases with vermicular ferrite for ER309L filler weld, and for ER316L filler weld specimen shows predominately martensitic phase in the weld region, whereas the autogenous weld shows lathy ferrite mixed with martensitic phase. Mechanical test results indicated that filler welded specimen (ER316L and ER309L) has relatively higher strength and hardness than the autogenous weld, whereas ER316L filler weld exhibited the highest impact toughness than ER309L filler weld and lowest in autogenous weld. The electrochemical corrosion results displayed the highest degree of sensitization (DOS) in without filler welded specimen (45.62%) and lower in case of filler welded specimen ER309L (4.95%) and least in case of ER316L filler welded specimen (3.51%). The high DOS in non-filler welded specimen is correlated with the chromium carbide formation. The non-filler welded specimen shows the highest pitting corrosion attack as compared to the ER316L filler weld specimen and relatively better in ER309L filler welded specimen. The highest pitting corrosion resistance is related with the high chromium content in ER309L composition.

This experimental study is original and conducted with 316L and 430 stainless steel with ER316L, ER309 and without fillers, which will help the oil, shipbuilding and chemical industries.