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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.

Recently, powerful instruments for biomedical engineering research studies, including disease modeling, drug designing and nano-drug delivering, have been extremely investigated by researchers. Particularly, investigation in various microfluidics techniques and novel biomedical approaches for microfluidic-based substrate have progressed in recent years, and therefore, various cell culture platforms have been manufactured for these types of approaches. These microinstruments, known as tissue chip platforms, mimic in vivo living tissue and exhibit more physiologically similar vitro models of human tissues. Using lab-on-a-chip technologies in vitro cell culturing quickly caused in optimized systems of tissues compared to static culture. These chipsets prepare cell culture media to mimic physiological reactions and behaviors.

The authors used the application of lab chip instruments as a versatile tool for point of health-care (PHC) applications, and the authors applied a current progress in various platforms toward biochip DNA sensors as an alternative to the general bio electrochemical sensors. Basically, optical sensing is related to the intercalation between glass surfaces containing biomolecules with fluorescence and, subsequently, its reflected light that arises from the characteristics of the chemical agents. Recently, various techniques using optical fiber have progressed significantly, and researchers apply highlighted remarks and future perspectives of these kinds of platforms for PHC applications.

The authors assembled several microfluidic chips through cell culture and immune-fluorescent, as well as using microscopy measurement and image analysis for RNA sequencing. By this work, several chip assemblies were fabricated, and the application of the fluidic routing mechanism enables us to provide chip-to-chip communication with a variety of tissue-on-a-chip. By lab-on-a-chip techniques, the authors exhibited that coating the cell membrane via poly-dopamine and collagen was the best cell membrane coating due to the monolayer growth and differentiation of the cell types during the differentiation period. The authors found the artificial membrane, through coating with Collagen-A, has improved the growth of mouse podocytes cells-5 compared with the fibronectin-coated membrane.

The authors could distinguish the differences across the patient cohort when they used a collagen-coated microfluidic chip. For instance, von Willebrand factor, a blood glycoprotein that promotes hemostasis, can be identified and measured through these type-coated microfluidic chips.

With proper design and work planning, falls through fragile skylights are preventable. Skylights pose a hazard to workers when their work tasks for operations, maintenance and repair require them to be on roofs. The National Institute of Occupational Health and Safety produced guidelines and special alerts to address the dangers that are present around skylights, and the Occupational Safety and Health Administration regulations have prescriptive requirements for work performed around skylights, and yet incidents still occur. The purpose of this study is to investigate and raise awareness for the causality of the incidents involving skylights in the USA.

The authors investigated and analyzed 204 incidents involving skylights recorded by the Bureau of Labor Statistics to characterize their nature and to determine any correlation with the roof environment or the nature of the work performed. Using Google Earth and Google Maps roof geometry, proximity of skylights to roof edge and rooftop mechanical equipment was determined.

The majority of falls through skylights occur during roof maintenance and repair activities. Falls through skylights are underreported. Because of a general lack of good design to reduce or eliminate the risk of falling through skylights, facility managers carry the burden to properly assess work and access on roofs where fragile skylights are present.

The phenomenon of falling through skylights was made aware on a national level in the USA in 1989; however, little has been done from a design and planning perspective to reduce these incidents. This paper presents a unique perspective on the role of facility managers in understanding the hazards associated with roof maintenance near skylights.

The study aims to develop a multilayer high-effective ensemble of ensembles predictive model (stacking ensemble) using several hyperparameter optimized ensemble machine learning (ML) methods (bagging and boosting ensembles) trained with high-volume data points retrieved from Internet of Things (IoT) emission sensors, time-corresponding meteorology and traffic data.

For a start, the study experimented big data hypothesis theory by developing sample ensemble predictive models on different data sample sizes and compared their results. Second, it developed a standalone model and several bagging and boosting ensemble models and compared their results. Finally, it used the best performing bagging and boosting predictive models as input estimators to develop a novel multilayer high-effective stacking ensemble predictive model.

Results proved data size to be one of the main determinants to ensemble ML predictive power. Second, it proved that, as compared to using a single algorithm, the cumulative result from ensemble ML algorithms is usually always better in terms of predicted accuracy. Finally, it proved stacking ensemble to be a better model for predicting PM_2.5 concentration level than bagging and boosting ensemble models.

A limitation of this study is the trade-off between performance of this novel model and the computational time required to train it. Whether this gap can be closed remains an open research question. As a result, future research should attempt to close this gap. Also, future studies can integrate this novel model to a personal air quality messaging system to inform public of pollution levels and improve public access to air quality forecast.

The outcome of this study will aid the public to proactively identify highly polluted areas thus potentially reducing pollution-associated/ triggered COVID-19 (and other lung diseases) deaths/ complications/ transmission by encouraging avoidance behavior and support informed decision to lock down by government bodies when integrated into an air pollution monitoring system

This study fills a gap in literature by providing a justification for selecting appropriate ensemble ML algorithms for PM_2.5 concentration level predictive modeling. Second, it contributes to the big data hypothesis theory, which suggests that data size is one of the most important factors of ML predictive capability. Third, it supports the premise that when using ensemble ML algorithms, the cumulative output is usually always better in terms of predicted accuracy than using a single algorithm. Finally developing a novel multilayer high-performant hyperparameter optimized ensemble of ensembles predictive model that can accurately predict PM_2.5 concentration levels with improved model interpretability and enhanced generalizability, as well as the provision of a novel databank of historic pollution data from IoT emission sensors that can be purchased for research, consultancy and policymaking.

Face masks are the most recommended precautionary measure since the emergence of SARS-CoV-2 since 2020 and the most useful PPE against this virus and its variants so far. This study aims to develop reusable and biodegradable mask from 100% regenerated bamboo or/and its blend. Selection of natural and regenerated textile materials is to minimize generation of solid waste. This attempt will eventually protect our earth by minimizing or better discontinuing the production of the disposable nonbiodegradable face masks available worldwide.

Hundred percent regenerated bamboo and 50:50 bamboo:cotton were selected to knit plain and interlock fabrics for manufacturing of reusable sustainable face masks. A 2³ 3²-mixed-level factorial design was applied to study the effect of liquor ratio and temperatures, fabric structure, blend ratios and finishes at three different levels. Model 2³ 3² has two factors (liquor ratio and temperatures) at three levels and three factors (fabric structure, blend ratios and type of finish) at two levels. Knitted fabrics were then applied with antibacterial finishes; sanitized T99-19 and sanitized T27-22, separately at three different liquor ratios (1:10, 1:12 and 1:15) and temperatures (45, 55 and 65 °C) via exhaust method. After completing processing, fabric thickness, pilling resistance, dimensional stability, bursting strength, Berger whiteness index, air permeability and antibacterial properties of each trial were evaluated using standard test procedures.

Selected fabrics treated either by sanitized T27 or sanitized T99 in a liquor ratio of 1:15 against 65 °C, showed excellent bacteriostatic/bactericidal activity. However, 100% regenerated bamboo interlock knitted fabric treated with sanitized T99 in a liquor ratio of 1:15 at 65 °C has the most desired values of dimensional stability, pilling resistance, Berger whiteness, fabric thickness, air permeability and bursting strength which made it the best for the manufacturing of the masks. Reusable mask is comprised of three layers in which the first and the third layers were of selected 100% regenerated bamboo fabric while a PM2.5 filter was inserted in between. Bacterial filtration efficiency, particle filtration efficiency, biocompatibility and microbial cleanliness will be evaluated in future, to compare the performance of proposed reusable and biodegradable face mask with N95 masks and other fabric masks available commercially.

This study resulted in a development of reusable eco-friendly facemask which was not attempted by the preceding investigations. Outcomes of this work pave the way for a greener and safer earth by using easily obtainable regenerated bamboo fabrics, antibacterial finishes and knitted structures.

This study aims to investigate the influence of commercially available resins in water-based magenta pigment inkjet ink formulations on the properties of ink printability and the characteristics of ink application in food packaging. The impact of the resin on the jettability of the existing printability phase diagrams was also assessed.

Inks with different resin loadings were tested for selected properties, such as viscosity, particle size and surface tension. Stability was determined using a Turbiscan AGS turbidimeter and LumiFuge photocentrifuge analyzer. The ink layer fastness against abrasion and foodstuffs was evaluated using an Ugra device and according to PN-EN 646, respectively. JetXpert was used to assess Ricoh printhead jetting performance.

Printability diagrams successfully characterized the jettability of polyurethane inkjet inks on a multi-nozzle printhead and the binder improved droplet formation and printing precision.

Magenta water-based inkjet inks with commercial resins have been developed for printing on paper substrates. To the best of the authors’ knowledge, for the first time, inkjet ink stability was evaluated using the Turbiscan AGS and LumiFuge analyzers, and jettability models were verified using an industrial multi-nozzle printhead.

This paper aims to investigate the corrosion resistance of two types of coatings – one is ceria sol coating and the other is ceria sol coating modified by ZnO nanoparticles on 7075 aluminum alloy in 3.5% NaCl solution.

Aluminum alloys were dipped into ceria sol and ceria sol modified by ZnO nanoparticles separately and removed after 10 min from the solutions and dried at 110°C for 30 min and heated at 500 °C for 30 min to form the coatings. The coatings have been characterized by using field emission scanning electron microscopy (FE-SEM), electrochemical impedance spectroscopy (EIS), X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS). The EIS tests were performed in a corrosive solution of 3.5% NaCl.

The results showed that the coating of ceria sol modified by ZnO nanoparticles has higher corrosion resistance than the ceria sol coating and the bare sample. Also, the best efficiency is related to aluminum sample immersion after 1 h in NaCl corrosive solution for coating modified by ZnO nanoparticles.

In this research, the modification of ceria sol coating by ZnO nanoparticles had an effect on improving the corrosion behavior of aluminum alloy. It is also understood that modification of coatings is an effective parameter on corrosion resistance.

Polyethylene terephthalate (PET) as a fiber molding polymer is widely used in aerospace, electrical and electronic, clothing and other fields. The purpose of this study is to improve the thermal insulation performance of polyethylene terephthalate (PET), the SiO₂ aerogel/PET composites slices and fibers were prepared, and the effects of the SiO₂ aerogel on the morphology, structure, crystallization property and thermal conductivity of the SiO₂ aerogel/PET composites slices and their fibers were systematically investigated.

The mass ratio of purified terephthalic acid and ethylene glycol was selected as 1:1.5, which was premixed with Sb₂O₃ and the corresponding mass of SiO₂ aerogel, and SiO₂ aerogel/PET composites were prepared by direct esterification and in-situ polymerization. The SiO₂ aerogel/PET composite fibers were prepared by melt-spinning method.

The results showed that the SiO₂ aerogel was uniformly dispersed in the PET matrix. The thermal insulation coefficient of PET was significantly reduced by the addition of SiO₂ aerogel, and the thermal conductivity of the 1.0 Wt.% SiO₂ aerogel/PET composites was reduced by 75.74 mW/(m · K) compared to the pure PET. The thermal conductivity of the 0.8 Wt.% SiO₂ aerogel/PET composite fiber was reduced by 46.06% compared to the pure PET fiber. The crystallinity and flame-retardant coefficient of the SiO₂ aerogel/PET composite fibers showed an increasing trend with the addition of SiO₂ aerogel.

The SiO₂ aerogel/PET composite slices and their fibers have good thermal insulation properties and exhibit good potential for application in the field of thermal insulation, such as warm clothes. In today’s society where the energy crisis is becoming increasingly serious, improving the thermal insulation performance of PET to reduce energy loss will be of great significance to alleviate the energy crisis.

In this study, SiO₂ aerogel/PET composite slices and their fibers were prepared by an in situ polymerization process, which solved the problem of difficult dispersion of nanoparticles in the matrix and the thermal conductivity of PET significantly reduced.

The incompatibility of natural fibers with polymer matrices is one of the key obstacles restricting their use in polymer composites. The interfacial connection between the fibers and the matrix was weak resulting in a lack of mechanical properties in the composites. Chemical treatments are often used to change the surface features of plant fibers, yet these treatments have significant drawbacks such as using substantial amounts of liquid and chemicals. Plasma modification has recently become very popular as a viable option as it is easy, dry, ecologically friendly, time-saving and reduces energy consumption. This paper aims to explore plasma treatment for improving the surface adhesion characteristics of sisal fibers (SFs) without compromising the mechanical attributes of the fiber.

A cold glow discharge plasma (CGDP) modification using N₂ gas at varied power densities of 80 W and 120 W for 0.5 h was conducted to improve the surface morphology and interfacial compatibility of SF. The mechanical characteristics of unmodified and CGDP-modified SF-reinforced epoxy composite (SFREC) were examined as per the American Society for Testing and Materials standards.

The cold glow discharge nitrogen plasma treatment of SF at 120 W (30 min) enhanced the SFREC by nearly 122.75% superior interlaminar shear strength, 71.09% greater flexural strength, 84.22% higher tensile strength and 109.74% higher elongation. The combination of improved surface roughness and more effective lignocellulosic exposure has been responsible for the increase in the mechanical characteristics of treated composites. The development of hydrophobicity in the SF had been induced by CGDP N₂ modification and enhanced the size of crystals and crystalline structure by removing some unwanted constituents of the SF and etching the smooth lignin-rich surface layer of the SF particularly revealed via FTIR and XRD.

Chemical and physical treatments have been identified as the most efficient ways of treating the fiber surface. However, the huge amounts of liquids and chemicals needed in chemical methods and their exorbitant performance in terms of energy expenditure have limited their applicability in the past decades. The use of appropriate cohesion in addition to stimulating the biopolymer texture without changing its bulk polymer properties leads to the formation and establishment of plasma surface treatments that offer a unified, repeatable, cost-effective and environmentally benign replacement.

The authors are sure that this technology will be adopted by the polymer industry, aerospace, automotive and related sectors in the future.