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The purpose of this paper is to evaluate the influence of nanoparticles as an additive on the tribological properties of calcium grease.

The nano additives in this research are with different concentration of multi carbon nanotubes (MWCNTs) and Talc powder (1, 2, 3, 3 and 5 per cent). The ratio of MWCNTs to Talc powder is 1:1. The tribological properties of hyper MWCNTs/Talc powder to calcium grease were evaluated using a pin-on-disk wear testing. The results show that the nano additives MWCNTs/Talc to calcium grease exhibit good performance in anti-wear and friction reduction. The action mechanism was estimated through analysis of the worm surface with x-ray diffraction and transmission electron microscope.

The result indicates that boundary film mainly composed of MWCNT and Talc powder, and other organic compound was formed on the worm surface during the friction test. In addition, the wear rate and coefficient of friction of nanogreases have shown excellent improvement about 80.62 and 63.44 per cent, respectively, at 4 Wt.% of MWCNTs/Talc powder. Moreover, the thermal conductivity of nanogrease increased about 51.72 per cent.

This study describes the inexpensive and simple fabrication of nanogrease for improving properties of lubricants, which improve power efficiency and extend lifetimes of mechanical equipment.

The main objective of this study is to test whether firms with a higher level of intellectual capital (IC) perform better in terms of their supply chain resilience compared to those with lower levels of IC. Likewise, the study also examines the impact of IC (characterized by human capital, relational capital and structural capital) on supply chain resilience directly and through supply chain learning.

Data were collected from the 159 processed-food sector firms using a close-ended questionnaire during the corona virus 2019 (COVID-19) pandemic. Partial least squares structural equation modelling (PLS-SEM), partial least squares multigroup analysis (PLS-MGA) and one-way analysis of variance (ANOVA) were used to test a set of hypotheses emanating from a conceptual model of IC and supply chain resilience.

Empirical results revealed a significant influence of all dimension of IC on a firm's supply chain learning and supply chain resilience. Likewise, findings also exhibit a momentous role of supply chain learning in reinforcing the impact of IC on supply chain resilience. Cross-firm size comparison reveals that supply chain resilience of firms with a higher level of IC performed significantly better than those with lower levels of IC. Firms with a higher level of structural capital had a highly resilient supply chain.

Findings of the study imply that IC and supply chain learning should be considered as a strategic tool and should be strategically developed for uplifting a supply chain performance of a firm. The development of IC and supply chain learning (SCL) not only improves the supply chain resilience of a firm but also can help to integrate the internal and external knowledge for harnessing supply chain resilience.

This research study was conducted during the COVID-19 pandemic which provides a unique setting to examine resiliency and learning.

This paper aims to develop a new isogeometric boundary element formulation based on non-uniform rational basis splines (NURBS) curves for solving Reissner’s shear-deformable plates.

The generalized displacements and tractions along the problem boundary are approximated as NURBS curves having the same rational B-spline basis functions used to describe the geometrical boundary of the problem. The source points positions are determined over the problem boundary by the well-known Greville abscissae definition. The singular integrals are accurately evaluated using the singularity subtraction technique.

Numerical examples are solved to demonstrate the validity and the accuracy of the developed formulation.

This formulation is considered to preserve the exact geometry of the problem and to reduce or cancel mesh generation time by using NURBS curves employed in computer aided designs as a tool for isogeometric analysis. The present formulation extends such curves to be implemented as a stress analysis tool.

The need for seeking alternate materials with increased performance in the field of composites revived this research, to prepare and evaluate the mechanical properties of e-glass and aloe vera fiber-reinforced with polyester and epoxy resin matrices.

The composites are prepared by hand layup method using E-glass and aloe vera fibers with length 5-6 mm. The resin used in the preparation of composites was epoxy and polyester. Fiber-reinforced composites were synthesized at 18:82 fiber–resin weight percentages. Samples prepared were tested to evaluate its mechanical and physical properties, such as tensile strength, flexural strength, impact strength, hardness and scanning electron microscope (SEM).

SEM analysis revealed the morphological features. E-glass fiber-reinforced epoxy composite exhibited better mechanical properties than other composite samples. The cross-linking density of monomers of the epoxy resin and addition of the short chopped E-glass fibers enhanced the properties of E-glass epoxy fiber-reinforced composite.

This research work enlists the properties of e-glass and aloe vera fiber-reinforced with polyester and epoxy resin matrices which has not been attempted so far.

The purpose of this research is to propose an evaluation framework for analyzing learning objects usage, with the aim of extracting useful information for improving the quality of the metadata used to describe the learning objects, but also for personalization purposes, including user models and adaptive itineraries.

The paper presents experimental results from the log usage analysis during one academic semester of two different subjects, 350 students. The experiment examines raw server log data generated from the interactions of the students with the classroom learning objects, in order to find relevant information that can be used to improve the metadata used for describing both the learning objects and the learning process.

Preliminary studies have been carried out in order to obtain an initial picture of the interactions between learners and the virtual campus, including both services and resources usage. These studies try to establish relationships between user profiles and their information and navigational behavior in the virtual campus, with the aim of promoting personalization and improving the understanding of what learning in virtual environments means.

During the formal learning process, students use learning resources from the virtual classroom provided by the academic library, but they also seek information outside the virtual campus. All these usage data are not considered in the model proposed here. Further research is needed in order to obtain a complete view of the seeking information behavior of students for improving the users' profile and creating better personalized services.

This paper suggests how a selection of fields used in the LOM standard could be used for enriching the description of learning objects, automatically in some cases, from the learning objects usage performed by an academic community.

From libraries beginnings, they have been a “quiet storage place”. With the development of digital libraries, they become a meeting place where explicit and implicit recommendations about information sources can be shared among users. Social and learning process interactions, therefore, can be considered another knowledge source.

To contribute to the identification of the parameters influencing the behavior of textile-reinforced concrete (TRC), the purpose of this paper is to investigate the flexural behavior of TRC-based plates under four-point bending notably designed in the context of sustainable development and the substitution of mortar components with natural and abundant materials.

An extensive experimental campaign was focused about two main parameters. The first one emphases the textile reinforcements, such as the number of layers, the nature and the textile mesh size. In the second step, the composition of the mortar matrix was explored through the use of dune sand as a substitute of the river one.

Test results in terms of load-displacement response and failure patterns were highlighted, discussed and confronted to literature ones. As key findings, an increase of the load-bearing capacity and ductility, comparable to the use of an industrially produced second textile layer was recorded with the use of dune sand in the mortar mix design. The designed ecofriendly samples with economic concerns denote the significance of obtained outcomes in this research study.

The novelty of the present work was to valorize the use of natural dune sand to design new TRC samples to respond to the environmental and economical requirements. The obtained values provide an improved textiles–matrix interface performance compared to classical TRC samples issued from the literature.

The purpose of this research is to study the physical and mechanical properties beside the durability of concrete as well as corrosion resistance of reinforced concrete by replacing Ordinary Portland cement (OPC) with different ratios of silica fume and meta-kaolin and applying two paint formulations to enhance corrosion resistance and mechanical properties. In this work, modified concrete mixes containing pozzolanic materials of industrial wastes such as silica fume (SF) with ratios ranging between (0, 10 and 15%) and calcined raw material such as meta-kaolin (MK) with ratios (0, 3, 5 and 10%), were introduced using water binder ratio (w/b) 0.45 to study their effect on the physico-mechanical properties and durability of concrete as well as corrosion protection performance of reinforced concrete. Two paint formulations containing the same ingredients except that one of them is free from talc (G1) and the other contains talc (G2) were applied on the rebars embedded in these modified mixes. Talc is known to offer high pH to the surrounding media.

Modified concrete mixes containing the coated reinforced concrete steel with the different paint formulations in presence and absence of talc were tested, and the corrosion behavior was studied using electrochemical impedance spectroscopy (EIS) in 3.5% NaCl, and the concrete mixes were also tested through their compressive strength, chloride permeability, scanning electron microscope/energy dispersive X-ray analysis and bond strength.

The results revealed that the hardened reinforced concrete mix containing 10% SF with 5% MK with embedded rebars coated with G2 (paint containing talc) was the best concrete system which offers concrete sustainability besides high corrosion protection performance, i.e. presence of talc in the paints combined with the effect of cement blended with SF and MK showed positive effect on the reinforced concrete properties that leads to more durability and workability.

The integrity of using two efficient methods of corrosion protection beside the effect of the different replacements in concrete mixes containing coated reinforced concrete steel with paint formulations free from talc (G1) and others containing talc (G2), which lead to fatal changes in the pH of the surrounding media (i.e. concrete which has high alkaline pH) to achieve good concrete properties aside with convenient paint formulations together.

This study aims to evaluate the effect of pH on the reinforced concrete steel protection for rebars coated with paint formulations containing talc and free from it. As the presence of talc in paints can offer high pH which cordially affects the protection behavior of the coated rebars. Additionally, this study includes evaluating the durability of concrete mixes in presence of some replacements of ordinary cement such as meta-kaolin (MK) and ground granulated blast furnace slag (GGBFS).

Two paint formulations were prepared containing the same ingredients except that (P1) is free from talc and (P2) contains talc. The anticorrosive behavior of painted steel in the blended concrete mixes containing MK and GGBFS was studied by using different electrochemical techniques in chloride solution. The concrete durability was evaluated by the means of compressive and bond strength beside chloride permeability. Different concrete mixes containing mineral groups or pozzolanic materials were prepared by replacing (10, and 30%) GGBFS and (5, 10 and 15%) MK as binary from cement CEM I with (w/b) 0.45 with superplasticizer ratio (SP) 2% of the binder

It was found that the presence of talc, in spite of its ability to offer high pH, has affected positively the corrosion behavior of reinforced concrete steel by forming a complex with concrete even if it is present in paint formulation and not free in the medium.

The results revealed that concrete blended with (30% GGBFS and 10% MK) with coated rebars with P2 containing talc showed the highest corrosion protection performance in addition to modified permeability and compression resistance.

The use of huge quantity of natural fine aggregate (NFA) and cement in civil construction work which have given rise to various ecological problems. The industrial waste like blast furnace slag (GGBFS), fly ash, metakaolin and silica fume can be partly used as a replacement for cement and manufactured sand obtained from crusher and partly used as fine aggregate. The purpose of this paper is to predict the shear strength of concrete using artificial neural network (ANN) for concrete made by using different pozzolans and partly replacing NFA by manufactured sand (MS) which can reduce the time and experimental cost.

In this work, MATLAB software model is developed using neural network toolbox to predict the shear strength of concrete made by using pozzolanic materials and partly replacing NFA by manufactured sand (MS). Shear strength was experimentally calculated, and results obtained from experiment were used to develop the ANN model. A total of 131 results values were used to modeling formation, and from that 30% data record was used for testing purpose and 70% data record was used for training purpose. In total, 25 input materials properties were used to find the 28 days shear strength of concrete obtained from partly replacing cement with pozzolans and partly replacing NFA by manufactured sand (MS).

The results obtained from ANN model provide very strong accuracy to predict shear strength of concrete obtained from partly replacing cement with pozzolans and NFA by manufactured sand.

This research study is on determining shear strength of concrete using ANN. The use of this study is to predict the shear strength of concrete using ANN for concrete made by using different pozzolans and partly replacing NFA by manufactured sand (MS) which can reduce the time and experimental cost.

This study aims to study the mechanisms and conditions of users' intention to continue to use online health platforms from an information technology (IT) affordance perspective.

b This research proposes that a critical affordance effect on an online health platform, users' intention to continue the use of the platform, is affected by five platform affordances via two actualized affordances (i.e. perceived benefits (PBs) and online engagement (OE)). Perceived health threat moderates the effect generated by affordance actualization. A dataset involving 409 users from the “Ping An Health” platform was collected through an online survey and analyzed to validate the research hypotheses.

The data analysis results confirm that the proposed online health platform affordances affect users' PBs and OE, which influence users' intentions to continue using the platform. Perceived threats (perceived vulnerability (PVU) and perceived severity (PSE)) moderate the relationship between PBs and continuance intention (CI) and between OE and CI.

The research provides important recommendations for online health platform designers to develop IT affordances that can support users' needs for healthcare services.

Limited studies investigated why users continue participating in online diagnosis and treatment. This study provides a new perspective to expand the affordance framework by combining technology features and user health behavior. The study also emphasizes the importance of perceived threats in IT use.