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TiO₂ thin films were deposited by Pulsed Laser Deposition (PLD) on glass substrates at 27°C and 100°C. The extraction efficiency of evanescent light from the deposited nanolayers and their thickness profiles in the range of (1-100) nm was evaluated using the Differential Evanescent Light Intensity (DELI) imaging method. This optical microscopy technique is based on capturing the evanescent light emitted by the material layer deposited on the substrate. The results were analyzed and discussed in terms of the effective penetration depth parameter. The effective scattering cross-section of the TiO₂ nanometer particles was estimated.

Avant‐propos sous les auspices de l'Institut international de Coopération intellectuelle, paraissait en 1934 le t. I, consacré à l'Europe, du Guide international des Archives. Le questionnaire envoyé à tous les États européens comportait sous les points 4 et 6 les questions suivantes: ‘Existe‐t‐il un guide général pour les diverses catégories d'Archives ou des guides particuliers pour l'une ou l'autre d'entre elles?’ et ‘Existe‐t‐il des catalogues imprimés, des publications tant officielles que privées, susceptibles de constituer un instrument complet de référence pour tout ou partie importante des fonds d'archives?’ Les réponses des divers pays à ces questions, malgré leur caractère très inégal, ont fait du Guide international un bon instrument d'information générale sur les Archives. Malheureusement les circonstances ont empêché la publication du volume consacré aux États non européens, tandis que le temps qui s'écoulait tendait à rendre périmés les renseignements fournis sur les Archives européennes.

This chapter critically examines the impact of Web3 technologies on financial, digital, and future-focused inclusion through three case studies: El Salvador’s adoption of Bitcoin, Soulbound tokens for digital identity, and the Helium network for decentralised wireless infrastructure and environmental monitoring. By applying an insider–outsider lens, the chapter reveals the complex dynamics of inclusion and exclusion in Web3 initiatives, highlighting the gap between decentralisation promises and real-world implementation. The analysis demonstrates how top-down technological solutions can create new forms of exclusion, particularly when they fail to consider local needs and practices. The chapter also explores the potential of Web3 to transcend human-centric paradigms and include non-human actors in digital ecosystems. Policy recommendations provided address the identified challenges, emphasising the need for context-sensitive implementation and careful regulation. The chapter concludes by advocating for a nuanced understanding of Web3 technologies that recognises both their transformative potential and limitations. It sets the stage for discussing the future of Web3 in creating a more inclusive digital landscape that not only expands human access but also fosters sustainable coexistence with our planet’s ecosystems, challenging us to reimagine digital infrastructure beyond purely human interests.

This paper aims to develop efficient and simple models for thermal distribution, melt pool dimensions and controlled phase change in the laser additive manufacturing (AM) of bulk and powder particles ceramic materials.

This paper proposes new analytical models for the AM of bulk and powder bed ceramic materials. A volumetric moving heat source, along with the complete melting of bulk and powder particle materials, is taken into account. Different values of laser absorption coefficient in solid and liquid states have been used to investigate the phase transformation. Furthermore, the pores and voids dimensions are also included in the modeling. Theoretical predictions have been compared with the experimental analyses and finite element simulations in laser to silicon nitride and laser to alumina interaction. The analysis focuses on the impact of laser power and scanning speed on the melt pool width and depth evolution into the bulk substrate and powder bed.

This study shows that the powder particles exhibit a higher thermal distribution value than the bulk substrate because of voids in the powder layer. The laser beam experiences multiple reflections in the presence of porosity/voids, thus increasing the surface absorption coefficient, which becomes relevant with the increment in the pore/void dimension. A direct relationship has been found between the laser power and melt pool dimensions, while the scanning speed displayed an inverse relationship for the melt pool width and length. Larger melt dimensions were inferred in the case of laser–powder particle interaction compared with laser–bulk substrate interaction. A close correlation was found between the analytical simulations, experimental investigations and numerical simulation results within the range of 4%–8%.

This paper fulfills an identified need to develop efficient and simplified models for ceramics laser AM by taking into account different laser absorption coefficients in solid and liquid form, voids and pores dimensions and controlled phase transformation to avoid vapors and plasma formation. The limitation of the finite element simulation model is that the solution is strongly dependent on the mesh quality and accuracy directly linked to the computation efficiency and time. A finer mesh requires a longer computing time than a coarse mesh. Finite element simulations require, however, specialized skills.

This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.

I-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.

This study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.

The fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.

This study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.

The proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.

The purpose of this paper is to present the results of interaction occurring during the exposition of some specific carbon textile materials obtained in laboratory conditions to beams of various laser types.

Carbon fabric materials – fiber, felt and cloth – obtained from different precursor materials and prepared at various process conditions (oxidized, partially carbonized, carbonized, graphitized), were exposed to pulses of various lasers (Nd3+: YAG, alexandrite, ruby).

Depending on the laser power, plasma and destructive phenomena occurred. In the case of an interaction between a Nd3+: YAG laser beam and specimens of thickness in millimeter range, the authors have estimated the threshold of the energy density for drilling and discussed the possible models of the interaction.

The results have implications in the estimations of quality as well as in the improvement of material processing, giving some new light to the changes of mechanical and optical constants of the material, as well as to the changes of carbon groups of the material, which would be useful for different types of modeling. Future research will be in the interaction of laser beams with various textile materials, where the investigation would cover the microstructure changes and the implications on cloth cutting and welding, concerning the damages as well as relief structures, specially renew for fs laser regimes.

The area of laser applications in the textile industry is supported by scientific and applicative exploration. However, fewer results are concerned with deep introspection into the microstructure of the damages considering the laser interaction with carbon fiber and other carbon-based textiles.

Strategic decision-making is a complex process and encompasses an exhaustive knowledge base, collective guidance, contemporary foresight, analytical capabilities, paradigmatic congruence, and risk assessment and optimization within mission space. Employing advanced sciences convergence and analytical methodologies, the aim of this report is to provide a set of plausible solution trajectories to complex scenarios.

Three methodologies are reported here which provide policymakers with plausible solution pathways and alternatives. The methodologies, namely: TechFARM, ADAMS, and NESTTS, involve convergence of scientific disciplines, cutting edge technologies, social dynamics, astute extraction, and principles of foresight to support the process of informed decision-making, as comprehensive tools to develop a plausible solution space and future trends.

The methodologies provided in this report provide scientific basis to trends analysis and foresight. Few selected examples are reported here indicating its practical implications. The methodologies are currently applied to and likely to be used for many applications in trends analysis for government, industry, and even academics. These applications are particularly relevant to policy-making due to their capacity for identification of emerging trends.

Being highly adaptable, these methodologies were initially generated for defense applications, but have since been applied to clean water, cyber-security, the medical sector, and environmental health and safety (EHS) and evaluating eco-toxicity of nanomaterials, to strategically address a variety of global challenges. Additionally, these methodologies support investment recommendations and implementation of policies that promise significant benefit to the public at large.

Education 4.0 (E 4.0) represents a new paradigm in the field of education, which emphasizes a student-centric approach that allows learners to access education anytime, anywhere, tailored to their individual needs through modern-day technologies. The purpose of the study was to unearth the critical success factors (CSFs) essential for the successful implementation of E 4.0.

The CSFs were unearthed using a literature review and further the interrelationships were analysed using multi-criteria decision making (MCDM) approach.

The study unearthed 15 CSFs for the successful implementation of E 4.0. The most important factor for the successful implementation of E 4.0 was personalized learning which was found to be the casual factor. The other causal CSFs were clear vision and leadership for E 4.0, stakeholder involvement, data analytics in teaching and learning, inter-disciplinary learning and blended learning environments. The effect factors were digital citizenship-based education, teacher training and development for E 4.0, supportive environment, curriculum redesign for E 4.0, open educational resources, digital technologies, formative assessments, infrastructure for E 4.0 and sustainability in education.

This is the first study which unearthed the CSFs and found the interrelationships among them, thus contributing to the theory of technology organization environment.

This study represented a pioneering effort in understanding the CSFs underpinning the successful adoption of E 4.0, paving the way for a more personalized, tech-savvy and effective education system.

This paper aims to detect the printing failures (such as warpage and collapse) in material extrusion (MEX) process effectively and timely to reduce the waste of printing time, energy and material.

The approach is designed based on the frequently observed fact that printing failures are accompanied by abnormal material phenomena occurring close to the nozzle. To effectively and timely capture the phenomena near the nozzle, a camera is delicately installed on a typical MEX printer. Then, aided by the captured phenomena (images), a smart printing failure predictor is built based on the artificial neural network (ANN). Finally, based on the predictor, the printing failures, as well as their types, can be effectively detected from the images captured by the camera in real-time.

Experiments show that printing failures can be detected timely with an accuracy of more than 98% on average. Comparisons in methodology demonstrate that this approach has advantages in real-time printing failure detection in MEX.

A novel real-time approach for failure detection is proposed based on ANN. The following characteristics make the approach have a great potential to be implemented easily and widely: (1) the scheme designed to capture the phenomena near the nozzle is simple, low-cost, and effective; and (2) the predictor can be conveniently extended to detect more types of failures by using more abnormal material phenomena that are occurring close to the nozzle.

The purpose of this paper is to present the results of measuring a sample of engineering students’ perceived achievement of complex thinking at different stages of their professional training. This study intended to analyze and predict the differences in the self-perception of achieved complex thinking competency by gender, semester, course of study and high school of origin.

The methodology included applying the E-Complexity instrument to 225 university students from northern Mexico. The initial comparison of groups used the chi-square test and two supervised learning algorithms (logit regression with Lasso regularization and a classification tree).

The findings of this study indicated that the selected undergraduate degree did not reveal differences in self-perceived performance in complex thinking, while gender, semester and high school of origin had significant differences.

Among the limitations of the study is the size of the sample and the fact that it only focused on engineering students from a single educational institution; however, this limitation responds to the exploratory nature of this study and the guidance of the institutional ethics committee. With these results, it is feasible to request an extension of the sample to include other disciplines to evaluate these findings, which, although relevant, cannot be considered exhaustive.

Regarding possible lines of research, the authors propose that given the difference between students who graduated from the high school of the same institution and those who did not, a possible line of research could explore new hypotheses on whether the policies and practices of the institution’s high school emphasize the development of complex thinking skills; the teachers of this high school are trained to teach complex thinking; and the learning materials of this high school are designed to develop complex thinking skills.