Search results

This study aims to assess the efficacy of thermal analysis of concrete slabs by including different insulation materials using ANSYS. Regression equations were proposed to predict the thermal conductivity using concrete density. As these simulation and regression analyses are essential tools in designing the thermal insulation concretes with various densities, they sequentially reduce the associated time, effort and cost.

Two grades of concretes were taken for thermal analysis. They were designed by replacing the natural fine aggregates with thermal insulation aggregates: expanded polystyrene, exfoliated vermiculite and light expanded clay. Density, temperature difference, specific heat capacity, thermal conductivity and time were measured by conducting experiments. This data was used to simulate concrete slabs in ANSYS. Regression analysis was performed to obtain the relation between density and thermal conductivity. Finally, the quality of the predicted regression equations was assessed using root mean square error (RMSE), mean absolute error (MAE), integral absolute error (IAE) and normal efficiency (NE).

ANSYS analysis on concrete slabs accurately estimates the thermal behavior of concrete, with lesser error value ranges between 0.19 and 7.92%. Further, the developed regression equations proved accurate with lower values of RMSE (0.013 to 0.089), MAE (0.009 to 0.088); IAE (0.216 to 5.828%) and higher values of NE (94.16 to 99.97%).

The thermal analysis accurately simulates the experimental transfer of heat across the concrete slab. Obtained regression equations proved helpful while designing the thermal insulation concrete.

This study aims to investigate the compressive strength of concretes incorporating Linz-Donawitz slag (LD slag) as partial replacement for natural fine and coarse aggregates and compare them with traditional concrete.

The natural fine and coarse aggregates were replaced by weight simultaneously up to 100% with LD slag aggregates at an incremental increase of 20%. Concrete of grades M20, M25, M30, M35 and M40 were cast, cured and tested with standard cube specimens to study the density and compressive strength of reference and LD slag aggregate concretes (LDSACs). The concrete specimens were exposed to elevated temperatures, i.e. 100 to 900 °C at an equal interval of 100 °C and tested to study the variation in density and residual compressive strength.

The results from the experiments reveal that the LDSAC yields a higher density than that of the reference concrete and also undergo less density variation when exposed to elevated temperatures. In addition, the residual compressive strength of LDSAC specimens was significantly higher than that of the reference concrete.

LD slag is believed to be stronger and more durable than locally available limestone aggregates or blast furnace slag. Moreover, it is necessary to study its strength and other properties to determine whether it can be successfully used as an aggregate in concrete universally.

Use of LD slag as aggregates in concrete will convert LD slag into a value added product and as an alternative to the existing natural aggregates which will help in maintaining ecological balance and save valuable lands.

The economically weaker section of the society may now use LDSAC as waste utilization will bring down the overall cost and hence it will benefit people on large scale.

Use of LD slag as aggregate in concrete can help find an alternative to the existing natural aggregates which will save the ecosystem and at the same time help in reducing the industrial waste on a large scale.

The purpose of the study is to compare methodologies for mapping a historic building, with image capture by smartphones and drones, using photogrammetric techniques for three-dimensional (3D) modeling of the structure. Processes and products are also analyzed, as well as possibilities for storing and visualizing data for structuring a cadastre of historical and artistic heritage are studied.

For mapping with smartphones, the overlapping of photographs was guaranteed, with data acquisition using three different cameras, on the same date as the aerial survey. The models were made from different combinations of camera use. For storage, a conceptual model based on ISO 19.152:2012 is proposed, which was implemented in the MongoDB, resulting in a database for storage. The visualization was carried out on the Cesium ion platform.

The results indicate that the terrestrial 3D reconstruction using smartphones is an efficient alternative to the historical and artistic cadastre, presenting texture quality superior to the aerial survey in a shorter production time. When dealing with the conceptual model, the LADM (Land Administration Domain Model) standardization guarantees interoperability and facilitates data exchange. In addition, it proved to be flexible for the creation of thematic profiles, supporting their effective storage. The insertion of data in the visualization platform was simple and effective, and it even generated sharing links for visualization of the models.

The study analyses a low-cost method with the use of easily accessible devices, with a combination of methodologies and applied techniques. The data storage and visualization method is also simple and flexible, suitable for application in the cadastre of historical heritage.

This research aims to explore how social media influences the academic performance of university students in Bangladesh and examines the benefits and drawbacks of its usage.

We distributed a well-structured questionnaire among students enrolled in various programs at different universities in Bangladesh to collect data. We analyzed the data using factor analysis and regression models to uncover the impact of social media on academic performance.

Our research findings demonstrate that social media plays a crucial role in facilitating communication, information sharing and content development among university students in Bangladesh. Excessive reliance on social media can lead to dependence and hinder innovation, as students tend to excessively rely on readily available resources.

We relied on self-reported data from a limited sample size, which may affect the generalizability of our findings.

This study highlights the need to promote responsible use of social media among university students in Bangladesh to enhance their academic performance. We recommend implementing effective policy measures to control and manage undesired usage patterns, foster an intellectually equipped student body and contribute to the development of a knowledgeable and successful Bangladesh.

This research makes a significant contribution by examining the influence of social media on academic performance among university students in Bangladesh. It proposes practical policy measures to address the drawbacks associated with excessive reliance on social media, thereby contributing to decision-making and intervention strategies for promoting responsible usage.

With rapidly changing marketing landscape, nowadays, the formulation of various marketing strategies is increasingly focused on how consumers tend to make decisions. To meet the highly demanding consumer expectations, market segmentation can be used as an important marketing strategy. Due to gender marketing concept familiarity in the contemporary world, gender difference is one of the reference features in the process of market segmentation for marketers. This research is aimed to examine various determining factors that foster consumer purchase decision-making and the differences between consumers of different genders while making shopping and purchase decisions with special reference to an emerging economy, i.e. Pakistan.

Based on a cross-sectional sample of 367 consumers, the study adapted Sproles and Kendall's (1986) Consumer Style Inventory (CSI) to scrutinize the decision-making of both genders in Pakistan. For data analysis, the exploratory and confirmatory factor analysis in addition to the structural equation modeling has been used.

The study emphasized that, with the exception of quality awareness, brand consciousness, fashion consciousness, option overload and price consciousness greatly affect buying decisions. In addition, when it comes to consumer purchase decision-making, significant gender variations were discovered for both fashion consciousness and price consciousness.

Drawing upon the distinctive cultural characteristics of Pakistan and its people, in-depth research was conducted on purchasing behaviors of Pakistani consumers and the decision-making characteristics of customers of different genders were summarized. The outcomes are expected to make a significant contribution to the field of gender marketing by organizations.

Sharing patient health information (PHI) among hospitals has been much slower than the adoption of health record systems. This paper aims to investigate if privacy regulation (PR) or security measures (SMs) influence hospitals’ use of health information exchange (HIE) to share PHI with other providers (e.g. physicians, labs, hospitals). The study specifically focuses on how multiple PRs can impede and a strong national security infrastructure (NSI) can support HIE.

The study uses secondary data from a multi-national and multi-hospital survey administered by the European Union. The multi-level structure of the cross-sectional panel data is used to test the influence of both hospital-level (e.g. PR) and national-level variables (e.g. NSI) on HIE. A total of nine types of HIE, three types of PRs, nine SMs and other relevant control variables are considered. This study uses a two-level random intercept generalized linear model to test the hypothesis proposed in the study.

The study finds that national-level PRs (NLPR) have the strongest positive influence on HIE in comparison to regional (RLPR) and hospital-level (HLPR) PRs. Moreover, the study finds evidence that the presence of RLPR and HLPR, on average, decreases the positive impact of NLPR by 264%. The SMs also have a significant and positive impact on HIE. Adoption of an additional SM can increase the odds of engaging in a certain type of HIE between 21% and 61%. On the other hand, a strong NSI can also amplify the positive impact of SM on certain types of HIE.

This study extends prior research on the role of PRs in enabling HIE by considering the complexities brought up by adopting multiple PRs. NLPRs have the strongest impact on HIE in comparison to RLPRs or HLPRs. Moreover, public infrastructure initiatives such as those related to secure communications can also complement SMs adopted by the providers by encouraging HIE.

Food sustainability is a world-acknowledged issue that requires urgent integrated solutions at multi-levels. This study aims to explore how food firms can improve their sustainability performance through digital traceability practices, considering the mediating effect of sustainability-oriented innovation (SOI) and the moderating effect of supply chain learning (SCL) for the food supply chain therein.

Hierarchical regression with a moderated mediation model is used to test the proposed hypotheses with a sample of 359 food firms from four provinces in China.

Digital traceability has a significant positive impact on the three pillars of sustainability performances among food firms. SOI (product innovation, process innovation and organisational innovation) mediates the relationship between digital traceability and sustainability performance. SCL plays moderating roles in the linkage between digital traceability and both product and process innovation, respectively.

This paper contributes as one of the first studies to develop digital traceability practices and their sustainability-related improvements for Chinese food firms; it extends studies on supply chain traceability to a typical emerging market. This finding can support food sustainability practice in terms of where and how to invest in sustainability innovation and how to improve economic, environmental and social performance.

The purpose of this study is to determine the material extrusion (MEX) printability envelope of a new kind of low-viscosity powder-binder feedstocks using rheological properties.

Formulation of 13 feedstocks (variation of solid loading 60–67 Vol.% and thickening agent proportion 3–15 Vol.%) that were characterized and printed at different temperatures.

Three rheological models were successfully used to define the viscosity envelope, producing stable and defect-free printing. At a shear deformation rate experienced by the feedstock in the nozzle ranging from 100 to 300 s^–1, it was confirmed that metal injection molding (MIM) feedstocks exhibiting a low viscosity between 100 and 150 Pa s could be printed using an extrusion temperature as low as 85 °C.

MEX can be used in synergy with MIM to accelerate mold development for a new injected part or simply as a replacement for MIM when the cost of the mold becomes too high for very small production volumes.

Correlation between the rheological properties of this new generation of low-viscosity feedstocks and MEX printability has been demonstrated for the first time.

The current review aims to focus on how risk and protective factors for self-harm in secure mental health hospitals are captured in the literature.

Fifty-seven articles were included in a systematic review, drawn from an initial 1,119 articles, post duplicate removal. Databases included Psycinfo, Psycarticles, Psycnet, Web of Science and EBSCO host. A thematic analysis was used, which included a meta-ethnographic approach for considering qualitative papers.

There was a clear focus on risk factors, with eight identified (in order of occurrence): raised emotional reactivity and poor emotion regulation; poor mental health; traumatic experiences; personality disorder diagnosis and associated traits; increased use of outward aggression – dual harm; constraints of a secure environment and lack of control; previous self-harm and suicide attempts; and hopelessness. Protective factors featured less, resulting in only three themes emerging (in order of occurrence): positive social support and communication; positive coping skills; and hope/positive outlook.

This includes a proposal to move focus away from “risk” factors, to incorporate “needs”, in terms of individual and environmental factors. There is also a need for more attention to focus on developing high quality research in this area.

The research captures an area where a synthesis of research has not been comprehensively undertaken, particularly with regards to capturing protective as well as risk factors.

Fused deposition modeling (FDM) is an extensively used additive manufacturing method with the capacity to build complex functional components. Due to the machinery and environmental factors during manufacturing, the FDM parts inevitably demonstrated uncertainty in properties and performance. This study aims to identify the stochastic constitutive behaviors of FDM-fabricated polylactic acid (PLA) tensile specimens induced by the manufacturing process.

By conducting the tensile test, the effects of the printing machine selection and three major manufacturing parameters (i.e., printing speed S, nozzle temperature T and layer thickness t) on the stochastic constitutive behaviors were investigated. The influence of the loading rate was also explained. In addition, the data-driven models were established to quantify and optimize the uncertain mechanical behaviors of FDM-based tensile specimens under various printing parameters.

As indicated by the results, the uncertain behaviors of the stiffness and strength of the PLA tensile specimens were dominated by the printing speed and nozzle temperature, respectively. The manufacturing-induced stochastic constitutive behaviors could be accurately captured by the developed data-driven model with the R² over 0.98 on the testing dataset. The optimal parameters obtained from the data-driven framework were T = 231.3595 °C, S = 40.3179 mm/min and t = 0.2343 mm, which were in good agreement with the experiments.

The developed data-driven models can also be integrated into the design and characterization of parts fabricated by extrusion and other additive manufacturing technologies.

Stochastic behaviors of additively manufactured products were revealed by considering extensive manufacturing factors. The data-driven models were proposed to facilitate the description and optimization of the FDM products and control their quality.