Reinforcing the polymer with nanoparticles and fibers improves the mechanical, thermal and electrical properties. Owing to this, the functional parts produced by the FDM process of such materials can be used in industrial applications. However, optimal parameters’ selection is crucial to produce parts with optimal properties, such as mechanical strength. This paper focuses on the analysis of influential process parameters on the tensile strength of FDM printed parts. Two statistical methods, RSM and ANN, were applied to investigate the effect the layer thickness, printing speed, raster angle and wall thickness on the tensile strength of test specimens printed with a short carbon fiber reinforced polyamide composite. The reduced cubic model was developed by the RSM method, and the correlation between the input parameters and the output response was analyzed by ANOVA. The results show that the layer thickness and raster angle have the most significant influence on tensile strength. As for machine learning, among the nine different tested ANN topologies, the best configuration was found based on the lowest MAE and MSE test sample result. The results show that the proposed model could be a useful tool for predicting tensile strength. Its main advantage is the reduction in time needed for experiments with the LOSO (leave one subject out) k-fold cross validation scheme, offering better generalization ability, given the small set of learning examples.

Abstract Despite increasing number of studies on incidental vocabulary learning through viewing in a foreign language, glosses, which have been proven to have facilitative effects in incidental vocabulary learning via other modes of input, have remained underexplored in audiovisual input. The current study investigates the effects of (1) traditional gloss (TG), (2) multiple-choice gloss (MCG) and (3) no gloss (NG) conditions on incidental L2 vocabulary learning through viewing animated short videos. Turkish-L1 upper-intermediate to advanced EFL learners (N = 127), who were randomly assigned to three conditions, watched three short, animated videos twice. The results revealed that while the MCG group and the TG group significantly outperformed the NG group in vocabulary meaning recall test, there was not a significant difference between the glossed conditions. The results also suggested that the participants learnt new words through interacting with MCGs. Furthermore, the participants’ prior vocabulary knowledge positively correlated with incidental vocabulary learning from the videos. The results are discussed within the framework of previous research and the Involvement Load Hypothesis.

This convergent mixed methods study aims to compare effectiveness of using three online consultation resources entailing deductive vs. data-driven learning on learning and retention of 18 verb-noun collocations by EFL learners. The participants ( N =45) randomly assigned to treatment conditions consulted three different online resources in different orders to complete the same online error correction tasks and gap-fill exercises in three sessions. The participants were given the Vocabulary Size Test (VST), and a productive collocation translation test (CTT) as the pretest, the posttest and the retention test. A sub-set of the participants also performed think aloud protocols during the treatment. After the treatment, the participants were given the CTT and responded a rating scale and an open-ended question. The results indicated that all of the resources led to significantly higher learning and retention rates with no significant differences among the resources. It was also found that the participants rate the resources differently and go through different cognitive processes when consulting resources. The VST scores positively correlated with the posttest scores, suggesting that participants’ vocabulary sizes can be a moderating variable. The findings are discussed based on previous research and within the framework of data-driven learning

Microneedles (MNs) represent the concept of attractive, minimally invasive puncture devices of micron-sized dimensions that penetrate the skin painlessly and thus facilitate the transdermal administration of a wide range of active substances. MNs have been manufactured by a variety of production technologies, from a range of materials, but most of these manufacturing methods are time-consuming and expensive for screening new designs and making any modifications. Additive manufacturing (AM) has become one of the most revolutionary tools in the pharmaceutical field, with its unique ability to manufacture personalized dosage forms and patient-specific medical devices such as MNs. This review aims to summarize various 3D printing technologies that can produce MNs from digital models in a single step, including a survey on their benefits and drawbacks. In addition, this paper highlights current research in the field of 3D printed MN-assisted transdermal drug delivery systems and analyzes parameters affecting the mechanical properties of 3D printed MNs. The current regulatory framework associated with 3D printed MNs as well as different methods for the analysis and evaluation of 3D printed MN properties are outlined.

The study’s primary purpose was to explore the abrasive water jet (AWJ) cut machinability of stainless steel X5CrNi18-10 (1.4301). The study analyzed the effects of such process parameters as the traverse speed (TS), the depth of cut (DC), and the abrasive mass flow rate (AR) on the surface roughness (Ra) concerning the thickness of the workpiece. Three different thicknesses were cut under different conditions; the Ra was measured at the top, in the middle, and the bottom of the cut. Experimental results were used in the developed feed-forward artificial neural network (ANN) to predict the Ra. The ANN’s model was validated using k-fold cross-validation. A lowest test root mean squared error (RMSE) of 0.2084 was achieved. The results of the predicted Ra by the ANN model and the results of the experimental data were compared. Additionally, as TS and DC were recognized, analysis of variance at a 95% confidence level was used to determine the most significant factors. Consequently, the ANN input parameters were modified, resulting in improved prediction; results show that the proposed model could be a useful tool for optimizing AWJ cut process parameters for predicting Ra. Its main advantage is the reduced time needed for experimentation.

Microneedles (MNs) have been manufactured using a variety of methods from a range of materials, but most of them are expensive and time-consuming for screening new designs and making any modifications. Therefore, stereolithography (SLA) has emerged as a promising approach for MN fabrication due to its numerous advantages, including simplicity, low cost, and the ability to manufacture complex geometrical products at any time, including modifications to the original designs. This work aimed to print MNs using SLA technology and investigate the effects of post-printing curing conditions on the mechanical properties of 3D-printed MNs. Solid MNs were designed using CAD software and printed with grey resin (Formlabs, UK) using Form 3 printer (Formlabs, UK). MNs dimensions were 1.2 × 0.4 × 0.05 mm, arranged in 6 rows and 6 columns on a 10 × 10 mm baseplate. MNs were then immersed in an isopropyl alcohol bath to remove unpolymerized resin residues and cured in a UV-A heated chamber (Formlabs, UK). In total, nine samples were taken for each combination of curing temperature (35°C, 50°C, and 70°C) and curing time (5 min, 20 min, and 60 min). Fracture tests were conducted using a hardness apparatus TB24 (Erweka, Germany). MNs were placed on the moving probe of the machine and compressed until fracture. The optimization of the SLA process parameters for improving the strength of MNs was performed using the Taguchi method. The design of experiments was carried out based on the Taguchi L9 orthogonal array. Experimental results showed that the curing temperature has a significant influence on MN strength improvements. Improvement of the MN strength can be achieved by increasing the curing temperature and curing time.

The Internet and the software stores for mobile devices come with a huge number of digital tools for any task, and those intended for digital formative assessment (DFA) have burgeoned exponentially in the last decade. These tools vary in terms of their functionality, pedagogical quality, cost, operating systems and so forth. Teachers and learners need guidance on how to choose the most effective digital formative software to make the most out of it. This study provides an in-depth critical review of the features of most popular formative assessment tools available on the Internet. It aims to unearth what current DFA tools can do and what further developments are needed for more effective use. The tools for analysis were sampled using frequency of mentions in educational technology websites and blogs and two scholarly databases (Web of Science and Scopus). After identifying the most frequently recommended, reviewed and researched formative assessment tools, the researchers inspected 14 tools in terms of various issues, ranging from platforms and devices used, item-types offered by the software, features related with monitoring student performance and providing feedback (through student/instructor dashboards), grading, scoring of open-response items and collaborative responses. The results indicated that all closed-ended items were common to all the tools examined and they were automatically scored, while only a few of them offered underdeveloped methods of grading open-ended items. All the tools provided learner analytics with diverse forms of data and different mechanisms for feedback, yet the most common form of data were immediate answers and numerical scores. It was also clear that popularity did not necessarily mean offering more functionalities and better tools. Based on the status of the tools, avenues for further research are discussed.

Multimodality of input in incidental L2 vocabulary learning has recently been a topic of interest among language acquisition researchers, yet the results have been somewhat contradictory. This study seeks to compare the impacts of two different multimodalities on incidental L2 vocabulary learning, namely, reading-plus-watching (experimental group I) vs. reading-plus-listening (experimental group II), as compared to the reading only condition, which is included as a control measure. Experimental group I watched and read the transcriptions of four news texts with electronic glosses for the target words, while experimental group II read and listened to the same news texts again with electronic glosses for the same 20 target words. Next, the two experimental groups swapped roles with a new set of four news texts glossed for another group of 20 target words. The control group only read the same eight news texts without glosses. The results suggest that reading-plus-listening can be a more conducive multimodal presentation for incidental vocabulary learning as compared to reading-plus-watching. The results also challenge the validity of some principles of the Cognitive Theory of Multimedia Learning in incidental L2 vocabulary learning, while providing supporting evidence for some other principles.

Many different and innovative approaches have been investigated to reduce the barrier effects of the stratum corneum (SC) and one of those are microneedles. Microneedles (MNs) are micron-sized needles which assist drug delivery through skin by creating microchannels (micron-scale pores) in SC that are large enough to enable drugs, including macromolecules, to enter the skin while being small enough to avoid pain, irritation and needle phobia. They have the capacity to play a role in modern healthcare as they reduce pain, tissue damage and transmission of infection and have potential for selfadministration in comparison to traditional needles. MNs have been fabricated by a variety of methods, from a range of materials (including silicon, glass, metal, carbohydrates and polymers) and in varying geometries (Quinn et al., 2014). Additive manufacturing (AM), more commonly known as three-dimensional (3D) printing represents a new, cutting-edge technology of 3D objects fabricated from a digital model generated using computer-aided design (CAD) software by fusing or depositing proper material (e.g., ceramics, liquids, metal, plastic, powders or even living cells) in layers. Suitable thermoplastic material in the form of a filament is fed into the printer by rollers, where it is heated to just above its softening point (glass transition temperature, Tg) by heating elements into a molten state. The melted or softened material guided by gears is moved towards heat end where it is extruded from the printer’s head, through a nozzle and subsequently deposited layer-by-layer on a build plate, cooling and solidifying in under a second. The printer’s head moves within the xand y-axes, whereas the platform can move within the z-axis, thus creating 3D structures (Alhnan et al., 2016; Goole and Amighi, 2016; Jamróz, 2018; Prased and Smyth, 2016). The aim of this work was to fabricate biodegradable PLA microneedles using innovative FDM 3D-printing technology on two different 3D printers and then chemically etch their arrays to obtain ideally sized and shaped needles.