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In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

This study aims to enhance merging of additive manufacturing (AM) techniques with powder injection molding (PIM). In this way, the prototypes could be 3D-printed and mass production implemented using PIM. Thus, the surface properties and mechanical performance of parts produced using powder/polymer binder feedstocks [material extrusion (MEX) and PIM] were investigated and compared with powder manufacturing based on direct metal laser sintering (DMLS).

PIM parts were manufactured from 17-4PH stainless steel PIM-quality powder and powder intended for powder bed fusion compounded with a recently developed environmentally benign binder. Rheological data obtained at the relevant temperatures were used to set up the process parameters of injection molding. The tensile and yield strengths as well as the strain at break were determined for PIM sintered parts and compared to those produced using MEX and DMLS. Surface properties were evaluated through a 3D scanner and analyzed with advanced statistical tools.

Advanced statistical analyses of the surface properties showed the proximity between the surfaces created via PIM and MEX. The tensile and yield strengths, as well as the strain at break, suggested that DMLS provides sintered samples with the highest strength and ductility; however, PIM parts made from environmentally benign feedstock may successfully compete with this manufacturing route.

This study addresses the issues connected to the merging of two environmentally efficient processing routes. The literature survey included has shown that there is so far no study comparing AM and PIM techniques systematically on the fixed part shape and dimensions using advanced statistical tools to derive the proximity of the investigated processing routes.

This paper comprehensively addresses the influence of chopped strand mat glass fiber-reinforced polymer (GFRP) patch configurations such as geometry, dimensions, position and the number of layers of patches, whether a single or double patch is used and how well debonding the area under the patch improves the strength of the cracked aluminum plates with different crack lengths.

Single-edge cracked aluminum specimens of 150 mm in length and 50 mm in width were tested using the tensile test. The cracked aluminum specimens were then repaired using GFRP patches with various configurations. A three-dimensional (3D) finite element method (FEM) was adopted to simulate the repaired cracked aluminum plates using composite patches to obtain the stress intensity factor (SIF). The numerical modeling and validation of ABAQUS software and the contour integral method for SIF calculations provide a valuable tool for further investigation and design optimization.

The width of the GFRP patches affected the efficiency of the rehabilitated cracked aluminum plate. Increasing patch width WP from 5 mm to 15 mm increases the peak load by 9.7 and 17.5%, respectively, if compared with the specimen without the patch. The efficiency of the GFRP patch in reducing the SIF increased as the number of layers increased, i.e. the maximum load was enhanced by 5%.

This study assessed repairing metallic structures using the chopped strand mat GFRP. Furthermore, it demonstrated the superiority of rectangular patches over semicircular ones, along with the benefit of using double patches for out-of-plane bending prevention and it emphasizes the detrimental effect of defects in the bonding area between the patch and the cracked component. This underlines the importance of proper surface preparation and bonding techniques for successful repair.

This paper aims to explore the mechanisms by which employees’ happiness at work (HAW) can be promoted. Drawing on the social exchange theory (SET), this study examined the relationships among discretionary human resource (HR) practices, perceived organizational support (POS), meaning of work (MOW) and HAW.

A three-path mediation model was developed to test the proposed relationships. The data were collected from Pakistani business professionals (n = 361), and hypotheses were tested using the PROCESS macro for SPSS .

The results suggest that POS mediates the relationship between discretionary HR practices and HAW. Also, MOW mediated the relationship between discretionary HR practices and HAW. Hence, both POS and MOW were found to be independent mediators. Further, the data provided support for the serial mediation of POS and MOW in the relationship between discretionary HR practices and HAW.

This research provides insights to organizations and their management on how discretionary HR practices can enhance employees’ POS, MOW and HAW.

The findings show that discretionary HR practices are associated with employees’ HAW. In addition, two mediators (POS and MOW) were found to serially mediate the aforesaid relationships. These findings are novel, as no prior research has used this nascent methodological approach to deepen our understanding by examining the associations between discretionary HR practices, POS, MOW and employees’ HAW.