Search

In this paper, a quantitative, descriptive, and correlational research is carried out on the perceptions of the digital competence of Latin American engineering professors, their assessment of the didactic use of Information and Communication Technologies (ICT) in different didactic areas (interaction, communication, distribution, and administration and evaluation), and on the growth or decrease in the frequency of their use after the COVID-19 pandemic. In particular, the Latin American engineering professors' perceptions of digital competence is studied. Also, the existence of gender gaps (both in general and differentiating between private and public universities, and between professors with a more or less teaching experience) has been explored in the assessment of the perceptions of digital competence and the didactic use of ICT by engineering professors, as well as in the influence that the pandemic has had on the habits of ICT use. The results reveal that the use of ICT by engineering professors has achieved increases of over 40% in some educational activities due to the pandemic, and it has had a homogenizing effect on the frequency of use of ICT tools in the different activities. Female engineering professors have increased their use of ICT more than males, and engineering professors in private universities more than those in public universities. Consequently, it is suggested to the universities to reinforce the continuous training of engineering professors, considering the pedagogical specificities of engineering education and the necessary integration of ICT in the teaching activity of female engineering professors. [ABSTRACT FROM AUTHOR]

Strain engineering, as a cutting-edge method for modulating the electronic structure of catalysts, plays a crucial role in regulating the interaction between the catalytic surface and the adsorbed molecules. The electrocatalytic performance is influenced by the electronic structure, which can be achieved by introducing the external forces or stresses to adjust interatomic spacing between surface atoms. The challenges in strain engineering research lie in accurately understanding the mechanical impact of strain on performance. This paper first introduces the basic strategy for generating the strain, summarizes the different strain generation forms and their advantages and disadvantages. The progress in researching the characterization means for the lattice strains and their applications in the field of electrocatalysis is also emphasized. Finally, the challenges of strain engineering are introduced, and an outlook on the future research directions is provided. [ABSTRACT FROM AUTHOR]

Scientists have designed a liquid that behaves as both a solid and a fluid owing to the presence of tiny gas-filled capsules. An unusual relationship between pressure and volume enables this material to grasp fragile objects. Capsule-filled liquid straddles solid and fluid phases. [ABSTRACT FROM AUTHOR]

Highlights: The boosted heterogeneous interfaces in titanium nitride (TiN) nanotube/polydimethylsiloxane (PDMS) composite contributed to strong polarization loss relaxation ability. The TiN nanotubes/PDMS composite possessed both good impedance matching behavior and strong dielectric loss ability in wide temperature spectrum. The TiN nanotubes/PDMS composite exhibited excellent EMWA performances (effective absorption bandwidth value of 3.23 GHz and minimum reflection loss value of − 44.15 dB) at the varied temperature from 298 to 573 K. Currently, the microwave absorbers usually suffer dreadful electromagnetic wave absorption (EMWA) performance damping at elevated temperature due to impedance mismatching induced by increased conduction loss. Consequently, the development of high-performance EMWA materials with good impedance matching and strong loss ability in wide temperature spectrum has emerged as a top priority. Herein, due to the high melting point, good electrical conductivity, excellent environmental stability, EM coupling effect, and abundant interfaces of titanium nitride (TiN) nanotubes, they were designed based on the controlling kinetic diffusion procedure and Ostwald ripening process. Benefiting from boosted heterogeneous interfaces between TiN nanotubes and polydimethylsiloxane (PDMS), enhanced polarization loss relaxations were created, which could not only improve the depletion efficiency of EMWA, but also contribute to the optimized impedance matching at elevated temperature. Therefore, the TiN nanotubes/PDMS composite showed excellent EMWA performances at varied temperature (298–573 K), while achieved an effective absorption bandwidth (EAB) value of 3.23 GHz and a minimum reflection loss (RLmin) value of − 44.15 dB at 423 K. This study not only clarifies the relationship between dielectric loss capacity (conduction loss and polarization loss) and temperature, but also breaks new ground for EM absorbers in wide temperature spectrum based on interface engineering. [ABSTRACT FROM AUTHOR]

Complex systems are difficult to manage, operate and maintain. This is why we see teams of highly specialised engineers in industries such as aerospace, nuclear and subsurface. Condition based monitoring is also employed to maximise the efficiency of extensive maintenance programmes instead of using periodic maintenance. A level of automation is often required in such complex engineering platforms in order to effectively and safely manage them. Advances in Artificial Intelligence related technologies have offered greater levels of automation but this potentially pivots the weight of decision making away from the operator to the machine. Implementing AI or complex algorithms into a platform can mean that the Operators' control over the system is diminished or removed altogether. For example, in the Boeing 737 Air Max Disaster, AI had been added to a platform and removed the operators' control of the system. This meant that the operator could not then move outside the extremely reserved, algorithm defined, "envelope" of operation. This paper analyses the challenges of AI driven condition based monitoring where there is a potential to see similar consequences to those seen in control engineering. As the future of society becomes more about algorithm driven technology, it is prudent to ask, not only whether we should implement AI into complex systems, but how this can be achieved ethically and safely in order to reduce risk to life. [ABSTRACT FROM AUTHOR]

A newly invented structure called Multi-Fin-based FinFET (M-FinFET) device is a promising candidate for future improvisation of the semiconductor industry. In this article, Multi-channel FinFET (Mch-FinFET) is proposed. A comparative investigation of various DC, analog/linearity attributes is studied for gate length variation and oxide thickness through a Sentaurus TCAD tool. The simulation study concluded that the increased number of channels (= 3no.) has enhanced ION by 409.71% compared to single-channel FinFET. The decreased value of Fin width and Fin height has shown an impressive improvement of sub-threshold swing (SS) and leakage current, which helps achieve a better switching ratio. Mch-FinFET device with lower oxide thickness (Tox=1 nm) enhances the transconductance (Gm), drain conductance (Gd), intrinsic gain (Av), and transconductance gain factor (TGF) by 52.42%, 41.17%, 85.03%, respectively. Various linearity parameters like higher-order harmonics (Gm2 and Gm3), voltage intercepts points (VIP2 and VIP3), and 1-dB compression point has improved by 32.32%, 110.71% 77%, 60.09%, 418.86%, 411.5% respectively gate length of 10 nm. Besides that, a symmetric dual spacer material is introduced to the proposed structure to analyze the importance of spacer engineering. The simulation study reveals that the Mch-FinFET device with HfO2 spacer has improved driving current by 21.42%. The optimization of various short channel effects (SCEs) such as threshold voltage roll-off, sub-threshold swing (SS), and leakage current is reflected in introducing HfO2 spacer material. This detailed study is expected to design low-power RF circuits that would benefit future CMOS technology. [ABSTRACT FROM AUTHOR]

Understanding teachers' experiences as they lived them and as they told them is important for conceptualizing a well-rounded view of the state of science education and the role teachers play in it. Journey mapping, a way of visualizing one's processes and experiences as they progress towards a goal, is a tool with the potential to capture teachers' lived experiences. The purpose of this study was to explore elementary teachers' lived experiences as they work to provide science and engineering learning experiences for their students. This paper highlights the use of STEM journey mapping as a way of exploring teachers' lived experiences in their day-to-day practice. This study features the STEM journey map and subsequent narrative of a fourth-grade teacher, Elliot. The data analysis supported the argument that journey mapping was a powerful tool for exploring teachers' lived experiences. [ABSTRACT FROM AUTHOR]

Due to the substantial emphasis on engineering in K-12 science education efforts in the USA, it is important for teachers to develop a deeper understanding of the nature of engineering (NOE) and the relationship between engineering and science. A deep understanding is characterized not only by the presence or absence of ideas but also by the interconnections among the ideas. There are few ways to measure the interconnections among the ideas associated with a deep understanding of NOE. The present proof-of-concept study addresses this need by providing a preliminary testing of card sort epistemic network analysis (cENA) and network models' potential to extend what can be learned about how preservice teachers conceptualize NOE. To test the potential of cENA, we used cENA with 52 preservice elementary teachers enrolled in a course emphasizing science and engineering practices. Our findings indicated a shift within the participant community's epistemic frame for NOE toward more expert-like views of NOE, including some emphasis on the application of science in engineering. The findings from this study suggest cENA may be a productive and fruitful methodology for capturing changes in students' understandings of NOE. cENA has the potential to guide science teacher educators' approaches in designing evidence-based learning experiences and interventions to improve learners' depth of understanding about NOE. Rigorous validation of cENA is now warranted. [ABSTRACT FROM AUTHOR]

Diamond layers can help to dissipate the heat generated by high-power semiconductor devices. This effect has now been enhanced by adding layers of materials and engineering their crystal-lattice vibrations to be compatible at the interfaces. Layers engineered to maximize heat flow in semiconductor devices. [ABSTRACT FROM AUTHOR]

An array of robots has been set up so that pushes between them produce movements that do not conform to the usual laws of motion. Fascinating behaviour emerges from these interactions: wave phenomena known as solitons.Wave phenomena in an array of robots. [ABSTRACT FROM AUTHOR]

Autoencoders are frequently used to embed molecules for training of downstream deep learning models. However, evaluation of the chemical information quality in the latent spaces is lacking and the model architectures are often arbitrarily chosen. Unoptimized architectures may not only negatively affect latent space quality but also increase energy consumption during training, making the models unsustainable. We conducted systematic experiments to better understand how the autoencoder architecture affects the reconstruction and latent space quality and how it can be optimized towards the encoding task as well as energy consumption. We can show that optimizing the architecture allows us to maintain the quality of a generic architecture but using 97% less data and reducing energy consumption by around 36%. We additionally observed that representing the molecules as SELFIES reduced the reconstruction performance compared to SMILES and that training with enumerated SMILES drastically improved latent space quality. Scientific Contribution: This work provides the first comprehensive systematic analysis of how choosing the autoencoder architecture affects the reconstruction performance of small molecules, the chemical information content of the latent space as well as the energy required for training. Demonstrated on the MOSES benchmarking dataset it provides first valuable insights into how autoencoders for the embedding of small molecules can be designed to optimize their utility and simultaneously become more sustainable, both in terms of energy consumption as well as the required amount of training data. All code, data and model checkpoints are made available on Zenodo (Oestreich et al. Small molecule autoencoders: architecture engineering to optimize latent space utility and sustainability. Zenodo, 2024). Furthermore, the top models can be found on GitHub with scripts to encode custom molecules: https://github.com/MarieOestreich/small-molecule-autoencoders. [ABSTRACT FROM AUTHOR]

The Data Science and Engineering (DSE) Journal is a reputable publication that has been publishing cutting-edge research in data technologies and data-intensive applications since 2016. The journal has received recognition from important indexes such as SCOPUS, Emerging Sources Citation Index (ESCI), and EI. Professor Elena Ferrari has recently become the new Editor-in-Chief, bringing her extensive research credentials and leadership experience to guide the journal's growth and development. The journal expresses gratitude to Prof. Timos Sellis for his previous stewardship and looks forward to maintaining high standards of scholarly publishing under Professor Ferrari's leadership. [Extracted from the article]

This work is the extended version of a paper presented at the conference HMM2021, about the history of mechanical engineering. First, the initial cultural and industrial steps in the robotic field in Japan are introduced, to display the beginning of this interlaced path, before WW2; then, in the context of the aftermaths of the war, some famous anime heroes are presented as ancestors of the coming mecha anime series. The rising research in the field of robotics and more generally the developments of contemporary Japanese automation industry are then drawn, as a technological substrate for mecha conception. In particular, Masahiro Mori studies are taken into consideration to identify an actual robot design pattern to apply to the following comparative description and examination of the different mecha; finally, thanks to this analysis, the common breeding ground whence robotics and mecha (and their reciprocal influences) arise, is outlined. [ABSTRACT FROM AUTHOR]

This paper introduces a new design strategy for the development of highly sensitive Multimode Interference (MMI) sensors by employing an engineered slot-waveguide as the foundation for the device. Waveguides typically adopted in MMI sensors have the evanescent field of their modes interact with the sample in the sensing region and, by doing that, the device sensitivity is limited by how distinctly confined the propagating modes are. Even though one propagating mode has a greater interaction with the sample than the other, they both are sensitive to changes in the refractive index in the sensing area, when the ideal situation is to keep one of them virtually insensitive to such changes. A multimode slot-waveguide with a central defect was proposed to improve two aspects: first, obtain one mode that is guided through the high-index central defect of the core and that is, by construction, physically separated from the sensing region; second, utilize another high-order mode that propagates through the low-index regions of the core and not only in direct contact with the sample, but with maximum field intensity in the region of interaction. For aqueous samples (refractive index approximately 1.33), the achieved sensitivity per sensor length was 6.0 rad · RIU - 1 · μ m - 1 and an estimated Limit-Of-Detection of 3.5 · 10 - 8 RIU - 1 , which places the slot-MMI sensor among the most sensitive devices in the current literature. [ABSTRACT FROM AUTHOR]

This editorial article discusses recent findings in the optimization and engineering for sustainable development. The current Special Issue (SI) of the Optimization and Engineering journal stems from the 2022 Sustainable Development of Energy, Water and Environment Systems Conferences. These events included the 5th South East European, 3rd Latin American, and 17th SDEWES Conferences. Being selected from conference presentations, the papers in SI represent the main topics in optimization approaches that integrate various life-supporting systems discussed during these three events. After careful selection, the current SI accepted ten excellent papers summarized here. These contributions use differentiated modeling approaches and supporting tools, such as P-graph and network-flow modeling, computational fluid dynamics, pinch analysis (PA), and the Geographic Information System. The range of optimization methods includes mixed-integer linear and mixed-integer nonlinear programming (MILP and MINLP), dynamic programming, stochastic optimization, and PA and P-graph extensions. [ABSTRACT FROM AUTHOR]

Papers in engineering are under-represented, even neglected, in the journal. We want to change that. [ABSTRACT FROM AUTHOR]

Although strain engineering and soft-clamping techniques for attaining high Q-factors in nanoresonators have received much attention, their impact on nonlinear dynamics is not fully understood. In this study, we show that nonlinearity of high-Q Si3N4 nanomechanical string resonators can be substantially tuned by support design. Through careful engineering of support geometries, we control both stress and mechanical nonlinearities, effectively tuning nonlinear stiffness of two orders of magnitude. Our approach also allows control over the sign of the Duffing constant resulting in nonlinear softening of the mechanical mode that conventionally exhibits hardening behavior. We elucidate the influence of support design on the magnitude and trend of the nonlinearity using both analytical and finite element-based reduced-order models that validate our experimental findings. Our work provides evidence of the role of soft-clamping on the nonlinear dynamic response of nanoresonators, offering an alternative pathway for nullifying or enhancing nonlinearity in a reproducible and passive manner. In the design optimization of resonance frequencies and Q-factor of nanomechanical resonators, the influence of geometric design on the nonlinear dynamics has been rarely investigated. Here, the authors tune the stress field via soft-clamping, simultaneously increasing both the Q-factor and the onset of nonlinearity of a Si3N4 string resonator. [ABSTRACT FROM AUTHOR]

Understanding the anomalies generated by various subsurface targets and their responses to different geophysical techniques in various subsoil types is critical to near-surface geophysical investigations. Geophysical test site (GTS) plays a vital role in near-surface geophysical investigations and related Earth sciences to adequately predict the geometries and anomalies generated by the subsurface targets. Therefore, developing a GTS on a site requires some technical efficiencies, mechanical procedures, engineering concepts and scientific approach, depending on the operating environment and the purpose of construction. This paper reviews the evolving roles of GTS in engineering, sciences, and technology via remarkable pedagogical and scientific research. The procedures for designing and installing GTS were also discussed. Every constructed GTS is unique and has its operating environment and sets of scientific requirements. As a result, the execution of GTS should be subjected to numerous factors that invariably affect the overall long time usage and performance. Comparative studies of GTS activities indicate that GTS is a vital geophysical research and academic platform to enrich the outcomes of the geophysical modelling for near-surface geophysical applications in engineering, science and technology. The evolving application of GTS has greatly impacted the field of science and engineering by enhancing the knowledge and understanding of the earth's interior, which invariably affects the engineers, geophysicists, archaeologists and geologists to be critical in the analysis, interpretation, and providing precise and accurate information of subsurface anomalies underlying the uppermost soil of the earth's crust. After a critical investigation, it was noted that the installation of GTSs is usually conceived to replicate situations often encountered in field investigation contexts. Examination shows that GTS can provide an ideal platform for young geoscientists, engineers and archaeologists to acquire the requisite skills, knowledge, technical know-how, and professional techniques for resolving near-surface challenges in real-life work situations. More also, a well-developed and equipped GTS could be a watershed in technological advancement, research development, and new scientific ideas. The GTS platform also indicates a promising pedagogical approach to geophysical educational usage, research mobilization, and development of new shallow geophysical techniques for various near-surface investigation and calibrating/testing geophysical equipment, which invariably catalyzed engineering designs, scientific concepts and technological advancement. [ABSTRACT FROM AUTHOR]

This study explored young children's perceptions of engineers and engineering through their drawings and narratives. Twenty-six children ranging from four-to eight-years-old participated. Results indicated that although children in this group had limited knowledge of engineers and engineering, most of them, regardless of gender, not only drew engineers reflecting their own gender, but they also identified themselves as engineers already. More than half of them would like to become engineers when they grow up. This study supports the idea that young children are capable engineering learners and calls for age-appropriate, play-based engineering learning experiences in the early years. [ABSTRACT FROM AUTHOR]

Background: Students' academic self-efficacy maximizes likelihood for success and retention, yet prior research suggests that historically underrepresented (minoritized) undergraduate students in higher education and in college-level engineering show lower self-efficacy, which has been linked to histories of systemic exclusion. To address such gaps in student success, this work examines the effect of a new first-year undergraduate engineering design course on students' self-efficacy, as measured by students' assessment of their ability to achieve engineering design goals, and their confidence in their professional skills such as teamwork, communication, and leadership. It draws upon two aligned survey studies that examine this development (a) among the students participating in the course during the academic semester and (b) among both course participants and non-participants in the year following the course. Survey results for all students were considered, with attention to specific demographic subgroups traditionally underrepresented in engineering. Results: Analyses indicate effect of the course on self-efficacy and other examined constructs, such as communication and teamwork, during the course semester and continued effects in engineering design self-efficacy and tinkering self-efficacy in the year following course participation. Results also reveal differences for specific racial/ethnic and gender/sex subgroups in numerous constructs, including suggestion of specific effect for female students. Conclusions: This study's focus on the implication of engineering design education on self-efficacy and other critical professional outcomes, as well as its attention to specific demographic subgroups, adds to research on engineering education and the effect of design-focused coursework using project-based learning. The study indicates an increased potential role for such coursework, as early as the first year of a university trajectory, in fostering student growth and increased representation in the field. Findings on differences by gender/sex and by racial/ethnic groups, including clearer positive effect for female students but more complexity in effect for underrepresented racial/ethnic groups, support added research probing experience and outcomes within and across these groups. [ABSTRACT FROM AUTHOR]

This paper presents a novel and powerful population-based metaheuristic algorithm called Nizar Optimization Algorithm (NOA). This algorithm is based on two techniques. The first technique is to use effective mappings, which are divided into two types: mixing and transformation mappings. The mixing mappings return a mixed vector by replacing or shuffling the elements of two selected vectors, and the transformation mappings return the translation, dilation, or transfer of a selected vector. The second technique is to determine the effective points by using the effective mappings and individuals of the population, and then, these points are used in the learning process of NOA. To validate and demonstrate the performance of the proposed algorithm and its ability to balance exploration and exploitation, NOA is tested on 60 unconstrained benchmark functions and four classic constrained real-world engineering problems. The experimental results are verified by a comparative study with over 20 well-known and recently developed optimization algorithms. These results show that the proposed algorithm outperforms all other algorithms in terms of solution accuracy, convergence curve speed, statistical measurements, and computational expenses. [ABSTRACT FROM AUTHOR]

A technique for embedding fibres with semiconductor devices produces defect-free strands that are hundreds of metres long. Garments woven with these threads offer a tantalizing glimpse of the wearable electronics of the future.Fabrication method for defect-free semiconductor fibre. [ABSTRACT FROM AUTHOR]

Model-driven engineering (MDE) uses models as first-class artefacts during the software development lifecycle. MDE often relies on domain-specific languages (DSLs) to develop complex systems. The construction of a new DSL implies a deep understanding of a domain, whose relevant knowledge may be scattered in heterogeneous artefacts, like XML documents, (meta-)models, and ontologies, among others. This heterogeneity hampers their reuse during (meta-)modelling processes. Under the hypothesis that reusing heterogeneous knowledge helps in building more accurate models, more efficiently, in previous works we built a (meta-)modelling assistant called Extremo. Extremo represents heterogeneous information sources with a common data model, supports its uniform querying and reusing information chunks for building (meta-)models. To understand how and whether modelling assistants—like Extremo—help in designing a new DSL, we conducted an empirical study, which we report in this paper. In the study, participants had to build a meta-model, and we measured the accuracy of the artefacts, the perceived usability and utility and the time to completion of the task. Interestingly, our results show that using assistance did not lead to faster completion times. However, participants using Extremo were more effective and efficient, produced meta-models with higher levels of completeness and correctness, and overall perceived the assistant as useful. The results are not only relevant to Extremo, but we discuss their implications for future modelling assistants. [ABSTRACT FROM AUTHOR]

Background: Teacher efficacy is one of the most influential components for effective instruction, highlighting the importance of providing preservice teachers (PSTs) with opportunities to learn how to teach engineering during their college preparatory coursework. Making space for engineering instruction within science methods coursework could provide opportunities for PSTs to enhance their engineering teaching efficacy but also requires course instructors to give up some time previously devoted to science-focused instruction. The purpose of the current study was to explore how infusing engineering learning opportunities into a science methods course impacts PSTs' engineering and science teaching efficacy and outcome expectancy. Results: Pre/post-surveys were completed by PSTs enrolled in a Kindergarten-8th grade science methods course offered in four modalities (i.e., face-to-face, hybrid, online, rapid shift online). The course offered multiple engineering-focused learning activities and vicarious experiences. PSTs' science teaching efficacy beliefs, engineering teaching efficacy beliefs, science teaching outcome expectancy, and engineering teaching outcome expectancy all significantly increased from pre- to post-test. There was no significant difference between efficacy gains based on course modality. The purposeful inclusion of multiple engineering activities and vicarious experiences allows for significant gains in science and engineering teaching efficacy and outcome expectancy regardless of the modality in which the course is taken. Conclusions: This study shows that having varied efficacy source experiences while learning engineering design can result in increased efficacy, even in the absence of field experience and face-to-face coursework, and that the inclusion of these engineering experiences with science methods coursework does not detract from enhancing science teaching efficacy beliefs and outcome expectancy. Further research is needed to more closely examine individual components of science methods courses and the impacts each component has when implemented using different course modalities. [ABSTRACT FROM AUTHOR]

Highlights: Atomically substitutional engineering in binary transition metal dichalcogenides (TMDs) enables the facile production of ternary or quaternary TMDs with tunable (opto)electronic properties spanning the entire compositional spectrum. A comprehensive overview is provided on multinary TMDs, including Janus-type structures, aiming to elaborate on their theoretical foundations, synthetic strategies, tailored properties, and superior applications. The challenges and opportunities faced in accelerating the exploitation of multinary TMDs as highly promising nanomaterials are discussed. Transition metal dichalcogenides (TMDs) are a promising class of layered materials in the post-graphene era, with extensive research attention due to their diverse alternative elements and fascinating semiconductor behavior. Binary MX2 layers with different metal and/or chalcogen elements have similar structural parameters but varied optoelectronic properties, providing opportunities for atomically substitutional engineering via partial alteration of metal or/and chalcogenide atoms to produce ternary or quaternary TMDs. The resulting multinary TMD layers still maintain structural integrity and homogeneity while achieving tunable (opto)electronic properties across a full range of composition with arbitrary ratios of introduced metal or chalcogen to original counterparts (0–100%). Atomic substitution in TMD layers offers new adjustable degrees of freedom for tailoring crystal phase, band alignment/structure, carrier density, and surface reactive activity, enabling novel and promising applications. This review comprehensively elaborates on atomically substitutional engineering in TMD layers, including theoretical foundations, synthetic strategies, tailored properties, and superior applications. The emerging type of ternary TMDs, Janus TMDs, is presented specifically to highlight their typical compounds, fabrication methods, and potential applications. Finally, opportunities and challenges for further development of multinary TMDs are envisioned to expedite the evolution of this pivotal field. [ABSTRACT FROM AUTHOR]

Ultrathin materials have long been touted as a solution to the problems faced by the ever-growing semiconductor industry. Evidence that 3D chips can be built from 2D semiconductors suggests that the hype was justified.Tiered device made from ultrathin transistors. [ABSTRACT FROM AUTHOR]

The integration of non-silicon semiconductors into systems on chips is needed for advanced power and sensing technologies. A semiconducting graphene ‘buffer’ layer grown on silicon carbide is a step on this path.Semiconducting graphene buffer layer grown on silicon carbide. [ABSTRACT FROM AUTHOR]

Wave phenomena can be artificially engineered by scattering from metasurfaces, which aids in the design of radio-frequency and optical devices for wireless communication, sensing, imaging, wireless power transfer and bio/medical applications. Scattering responses vary with changing frequency; conversely, they remain unchanged at a constant frequency, which has been a long-standing limitation in the design of devices leveraging wave scattering phenomena. Here, we present metasurfaces that can scatter incident waves according to two variables—the frequency and pulse width—in multiple bands. Significantly, these scattering profiles are characterized by how the frequencies are used in different time windows due to transient circuits. In particular, by using more than one frequency with coupled transient circuits, we demonstrate variable scattering profiles in response to unique frequency sequences, which can break a conventional linear frequency concept and markedly increase the available frequency channels in accordance with a factorial number of frequencies used. Our proposed concept, which is analogous to frequency hopping in wireless communication, advances wave engineering in electromagnetics and related fields. Metasurfaces show variable scattering with frequency sequence. This frequency-hopping response breaks a conventional linear frequency concept and markedly expands available frequency channels from a linear number to its factorial number. [ABSTRACT FROM AUTHOR]

The Human Resources Development Service of Korea developed a digital exam for five representative engineering categories and conducted a pilot study comparing the findings with the paper-and-pencil exam results from the last three years. This study aimed to compare the test efficiency between digital and paper-and-pencil examinations. A digital examination was conducted with 93 participants through two rounds of test-status measurements. We collected the following data: early check-out rate, pass rate, and the average total response time per grade. The composition ratio of each question type in the digital exam was determined per the "Exam Operation Regulation" and selected from a databank spanning five years by experienced instructors. The early check-out rate of the digital exam at the Engineer level was 90% (percentage points), approximately 15%p higher than that for the paper-and-pencil exam, but the pass rate was low (9.8%p); the response time per question for the digital exam was approximately 0.2 min shorter. The results for both exams were similar in the Industrial Engineer category. The early check-out rate did not positively affect the exam pass rate, but the time taken depended on the number and characteristics of the subjects. It is necessary to improve the simplification and convenience of digital examinations, optimize test environments, and establish operation and management systems in line with the change in the Korean Technical Qualification Framework. We also suggest a gradual shift to digital examination by developing questions and tools using technologies to accurately measure individual abilities. [ABSTRACT FROM AUTHOR]

Thin-walled parts such as blades are widely used in aerospace field, and their machining quality directly affects the service performance of core components. Due to obvious time-varying nonlinear effect and complex machining system, it is a great challenge to realize accurate and fast prediction of machining errors of such parts. To solve the above problems, an engineering knowledge based sparse Bayesian learning approach is proposed to realize in-situ prediction of machining errors of thin-walled blades. Firstly, an engineering knowledge based strategy is proposed to improve the generalization ability of the model by integrating multi-source engineering knowledge, including machining information, physical information and online monitoring information. Then, principal component analysis method is utilized for the dimensional reduction of features. Sparse Bayesian learning approach is developed for model training, which significantly reduce the complexity of the regression model. Finally, the superiority and effectiveness of the proposed approach have been proven in blade milling experiments. Experimental results show that the average deviation of the proposed in-situ prediction model is about 11 μm, and the model complexity is reduced by 66%. [ABSTRACT FROM AUTHOR]

This paper explores the transformative potential of Large Language Models Artificial Intelligence (LLM AI) in educational contexts, particularly focusing on the innovative practice of prompt engineering. Prompt engineering, characterized by three essential components of content knowledge, critical thinking, and iterative design, emerges as a key mechanism to access the transformative capabilities of LLM AI in the learning process. This paper charts the evolving trajectory of LLM AI as a tool poised to reshape educational practices and assumptions. In particular, this paper breaks down the potential of prompt engineering practices to enhance learning by fostering personalized, engaging, and equitable educational experiences. The paper underscores how the natural language capabilities of LLM AI tools can help students and educators transition from passive recipients to active co-creators of their learning experiences. Critical thinking skills, particularly information literacy, media literacy, and digital citizenship, are identified as crucial for using LLM AI tools effectively and responsibly. Looking forward, the paper advocates for continued research to validate the benefits of prompt engineering practices across diverse learning contexts while simultaneously promoting potential defects, biases, and ethical concerns related to LLM AI use in education. It calls upon practitioners to explore and train educational stakeholders in best practices around prompt engineering for LLM AI, fostering progress towards a more engaging and equitable educational future. [ABSTRACT FROM AUTHOR]

A transistor made from atomically thin materials mimics the way in which connections between neurons are strengthened by activity. Two perspectives reveal why physicists and neuroscientists share equal enthusiasm for this feat of engineering.Two views on a transistor that mimics synaptic plasticity. [ABSTRACT FROM AUTHOR]

Overview of some recent research advancements in ultracold Rydberg atoms with laser-cooled trapped ions control is presented. We show also an effective way to create multi-q-bit gates on such a system. We demonstrate how to implement a gate similar to C-PHASE and discuss the prospects of atom-ion coupling approach. [ABSTRACT FROM AUTHOR]

Aquila optimizer (AO) is a nascent meta-heuristic algorithm that draws its inspiration from the four distinct hunting strategies employed by Aquila in nature.While prior research has demonstrated that AO performs admirably on numerous optimization cases, the algorithm faces significant challenges when confronted with complex multidimensional optimization problems. Specifically, unbalanced exploration and development, inefficiency in identifying optimal solutions, and premature convergence all present significant obstacles to the algorithm's performance. To address these challenges, this study proposes a novel spiral aquila optimizer based on dynamic Gaussian mutation (SGAO). The algorithm introduces a novel nonlinear control factor and combines it with the spiral search strategy derived from the whale optimization algorithm, thereby accelerating the convergence speed of the algorithm. Additionally, to enhance the probability of escaping local optima in the AO, Gaussian mutant solutions are generated using the positional information of the current new particle and the best particle. Diverging from other improved versions of AO, this research analyzes the motion patterns of traditional AO and purposefully introduces fresh optimization approach, enabling the proposed SGAO to exhibit exceptional performance. In order to validate the efficacy of the proposed method, the newly developed SGAO is subjected to extensive simulation experiments across 39 benchmark problems and five engineering application problems, and is compared against other advanced meta-heuristic algorithms. The experimental results demonstrate that SGAO significantly outperforms traditional AO and other advanced meta-heuristic algorithms, exhibiting exceptional performance and competitiveness. [ABSTRACT FROM AUTHOR]

Highlights: To precisely engineer complex helical hierarchies at nano/microscales, reactive inks with chiral nematic anisotropy are designed for 3D printing. The phase transformations and chiral evolution in response to parallel and orthogonal shear forces are meticulously investigated to finely adjust the 3D printing parameters for programming oriented chiral assemblies. The interplay between chiral relaxation dynamics and photo-polymerization kinetics is finely tuned to enable well-controlled chiral reformation, while simultaneously ensuring high print quality. Helical hierarchy found in biomolecules like cellulose, chitin, and collagen underpins the remarkable mechanical strength and vibrant colors observed in living organisms. This study advances the integration of helical/chiral assembly and 3D printing technology, providing precise spatial control over chiral nano/microstructures of rod-shaped colloidal nanoparticles in intricate geometries. We designed reactive chiral inks based on cellulose nanocrystal (CNC) suspensions and acrylamide monomers, enabling the chiral assembly at nano/microscale, beyond the resolution seen in printed materials. We employed a range of complementary techniques including Orthogonal Superposition rheometry and in situ rheo-optic measurements under steady shear rate conditions. These techniques help us to understand the nature of the nonlinear flow behavior of the chiral inks, and directly probe the flow-induced microstructural dynamics and phase transitions at constant shear rates, as well as their post-flow relaxation. Furthermore, we analyzed the photo-curing process to identify key parameters affecting gelation kinetics and structural integrity of the printed object within the supporting bath. These insights into the interplay between the chiral inks self-assembly dynamics, 3D printing flow kinematics and photo-polymerization kinetics provide a roadmap to direct the out-of-equilibrium arrangement of CNC particles in the 3D printed filaments, ranging from uniform nematic to 3D concentric chiral structures with controlled pitch length, as well as random orientation of chiral domains. Our biomimetic approach can pave the way for the creation of materials with superior mechanical properties or programable photonic responses that arise from 3D nano/microstructure and can be translated into larger scale 3D printed designs. [ABSTRACT FROM AUTHOR]

Highlights: Fe3+, Co2+, H3BTC, and collagen peptide are used to achieve a one-step assembly of stable FeCo-MOG/CP by manipulating the complexation effect and solution polarity. By optimizing pyrolysis, two kinds of nitrogen-doped carbon aerogels loaded with virus-shaped and nanospherical magnetic particles are obtained. FeCo/Fe3O4/NC and FeCo/NC aerogels exhibit excellent electromagnetic wave absorbing and radar stealth performances. Metal–organic gel (MOG) derived composites are promising multi-functional materials due to their alterable composition, identifiable chemical homogeneity, tunable shape, and porous structure. Herein, stable metal–organic hydrogels are prepared by regulating the complexation effect, solution polarity and curing speed. Meanwhile, collagen peptide is used to facilitate the fabrication of a porous aerogel with excellent physical properties as well as the homogeneous dispersion of magnetic particles during calcination. Subsequently, two kinds of heterometallic magnetic coupling systems are obtained through the application of Kirkendall effect. FeCo/nitrogen-doped carbon (NC) aerogel demonstrates an ultra-strong microwave absorption of − 85 dB at an ultra-low loading of 5%. After reducing the time taken by atom shifting, a FeCo/Fe3O4/NC aerogel containing virus-shaped particles is obtained, which achieves an ultra-broad absorption of 7.44 GHz at an ultra-thin thickness of 1.59 mm due to the coupling effect offered by dual-soft-magnetic particles. Furthermore, both aerogels show excellent thermal insulation property, and their outstanding radar stealth performances in J-20 aircraft are confirmed by computer simulation technology. The formation mechanism of MOG is also discussed along with the thermal insulation and electromagnetic wave absorption mechanism of the aerogels, which will enable the development and application of novel and lightweight stealth coatings. [ABSTRACT FROM AUTHOR]

Due to the influence of the Next Generation Science Standards (NGSS), the National Research Council's (NRC) Framework for K-12 Science Education, and a socio-workforce push to increase diverse representation in STEM fields, engineering education has become more prevalent in K-12 classrooms over the past decade. Although this shift is seemingly optimistic, critical consideration must be given to the ways engineering education tends to be reductive and positivistic, mimicking engineering practices decontextualized from high-stakes socio-political and socio-ecological realities through the adherence of a closed, systematic design process. Teaching and learning that is situated within the confines of normative engineering learning fail to nurture and cultivate students' intellectual health and ontological security, and further promotes destructive settler ecologics. This study took up efforts to disrupt and desettle engineering education, which opened space for children to critically speculate about real-world engineering entanglements deeply connected to their futurities. The aims of this paper are to (1) establish the need for anticolonial engineering, and engineering education, (2) promote approaches for doing so (3) and elevate the just worlding engineering design principles put forward by radically caring children committed to socio-ecological and multispecies justice. The learning shared in this paper suggests not only why science and engineering fields and education should be reformed, but also provides guidance for evolving the designing of shared worlds, for kincentric flourishing. [ABSTRACT FROM AUTHOR]

An adaptive system is able to adapt at runtime to dynamically changing environments and to new requirements. Adaptive systems can be single adaptive entities or collective ones that consist of several collaborating entities. Rigorous engineering requires appropriate methods and tools that help guaranteeing that an adaptive system lives up to its intended purpose. This paper introduces the special section on "Rigorous Engineering of Collective Adaptive Systems." It presents the 11 contributions of the section categorizing them into five distinct research lines: correctness by design and synthesis, computing with bio-inspired communication, new system models, machine learning, and programming and analyzing ensembles. [ABSTRACT FROM AUTHOR]

The creation of blockchain-based software applications requires today considerable technical knowledge, particularly in software design and programming. This is regarded as a major barrier in adopting this technology in business and making it accessible to a wider audience. As a solution, low-code and no-code approaches have been proposed that require only little or no programming knowledge for creating full-fledged software applications. In this paper we extend a review of academic approaches from the discipline of model-driven engineering as well as industrial low-code and no-code development platforms for blockchains. This includes a content-based, computational analysis of relevant academic papers and the derivation of major topics. In addition, the topics were manually evaluated and refined. Based on these analyses we discuss the spectrum of approaches in this field and derive opportunities for further research. [ABSTRACT FROM AUTHOR]

Based on the greening and low interference disposal requirements of coal gangue in high-yield and high-efficiency mines in Inner Mongolia and Shaanxi, and by integrating the existing theories and technologies such as underground filling technology of coal gangue, mine yellow mud grouting technology, and the evolution law of mining overburden fractures, a technology of filling goaf with coal gangue slurry for green disposal of coal gangue is proposed. The principle and technical framework of the technology of filling goaf with coal gangue slurry are clarified. This paper expounds on the technological process of technology of filling goaf with coal gangue slurry, establishes three types of slurry filling systems, such as centralized ground layout, ground and underground coordinated layout, and centralized underground layout, and constructs three slurry filling methods, including low-level grouting, adjacent level grouting, and high-level grouting, forming seven kinds of technology models of filling goaf with coal gangue slurry, including ground centralized pulping + high-level grouting, ground centralized pulping + adjacent grouting, ground centralized pulping + low level grouting, ground and underground coordinated pulping + adjacent grouting, ground and underground coordinated pulping + low level grouting, underground centralized pulping + adjacent grouting, and underground centralized pulping + low level grouting, and gives the selection process of technology models of filling goaf with coal gangue slurry. Based on the different conditions and requirements of Haidaze Coal Mine and Huangling No. 2 Coal Mine, engineering tests were carried out on two different technology modes, namely, ground and underground coordinated pulping + low level grouting and ground and underground coordinated pulping + adjacent grouting, based on simulation tests of low level grouting and adjacent grouting. The tests prove the feasibility of filling goaf with coal gangue slurry and explore the way for the theoretical research of the technology of filling goaf with coal gangue slurry and greening and low interference disposal of coal gangue. [ABSTRACT FROM AUTHOR]

Text Sentiment Analysis (TSA) for blogs on major microblogging platforms has grown drastically and is also very important as a field of research study. However, the paper focuses on the emotion in short text like Twitter which is exceedingly difficult due to the complexity of natural language and the informal structure employed in it, which has a restriction of 280 characters per tweet. In this proposed work, the combination of data filtering and feature engineering approaches are used to recognize the emotion in the short text. A Multi-Layered Perceptron-based Simplified Deep Learning Model (MLP-SDLM) is used in the proposed work to concatenates the filtering and feature engineering serially and parallelly. The third approach introduces the K-map based technique to combine the filtered and unfiltered textual and non-textual features efficiently. The results of proposed models are compared with traditional machine learning and deep learning classifiers and the performances of the proposed MLP-SDLM model gives 95.13% accuracy, K-map based technique produces 89.17% accuracy and MLP gives 88.7% significantly. [ABSTRACT FROM AUTHOR]

Numerical simulations of seismic site response require the characterization of the nonlinear behaviour of shallow subsoil. When extensive evaluations are of concern, as in the case of seismic microzonation studies, funding problems prevent from the systematic use of laboratory tests to provide detailed evaluations. For this purpose, 485 shear modulus reduction, G\G0(γ) and damping ratio, D(γ) curves were collected from multiple literature sources available in Italy. Each curve was associated with the related engineering geological units considered in seismic microzonation studies. A statistical analysis of the data was carried out with the aim of shedding light on the significant difference between the laboratory classification of samples and the macroscopic/engineering geological one, provided during seismic microzonation studies. Since the engineering geological classification plays a prominent role in extensive site response evaluations, the outcomes of the present work may be of help at least when preliminary seismic response estimates are of concern. The dataset provides reference information that can serve as key data for large-scale hazard assessments worldwide. [ABSTRACT FROM AUTHOR]

Design of metallosupramolecular materials encompassing more than one kind of supramolecular interaction can become deceptive, but it is necessary to better understand the concept of the controlled formation of supramolecular systems. Herein, we show the structural diversity of the bis-compartmental phenoxo-benzimidazole ligand H3L1 upon self-assembly with variety of d-block metal ions, accounting for factors such as: counterions, pH, solvent and reaction conditions. Solid-state and solution studies show that the parent ligand can accommodate different forms, related to (de)protonation and proton-transfer, resulting in the formation of mono-, bi- or tetrametallic architectures, which was also confirmed with control studies on the new mono-compartmental phenoxo-benzimidazole H2L2 ligand analogue. For the chosen architectures, structural variables such as porous character, magnetic behaviour or luminescence studies were studied to demonstrate how the form of H3L1 ligand affects the final form of the supramolecular architecture and observed properties. Such complex structural variations within the benzimidazole-phenoxo-type ligand have been demonstrated for the first time and this proof-of-concept can be used to integrate these principles in more sophisticated architectures in the future, combining both the benzimidazole and phenoxide subunits. Ultimately, those principles could be utilized for targeted manipulation of properties through molecular tectonics and crystal engineering aspects. [ABSTRACT FROM AUTHOR]

A 3D printer uses machine vision to solve a problem that has plagued 3D inkjet printers, increasing the range of materials that can be used, and enabling the rapid production of complex objects such as a robot hand.Automatic correction of errors in printed surfaces. [ABSTRACT FROM AUTHOR]

With quantum technologies heading for the mainstream, undergraduate courses are preparing the workforce of the future. [ABSTRACT FROM AUTHOR]

Highlights: The electrochemical principles/mechanism of Li–S batteries and origin of the shuttle effect have been discussed. The efficient strategies have been summarized to inhibit the shuttle effect. The recent advances of inhibition of shuttle effect in Li–S batteries for all components from anode to cathode. Lithium–sulfur (Li–S) batteries are supposed to be one of the most potential next-generation batteries owing to their high theoretical capacity and low cost. Nevertheless, the shuttle effect of firm multi-step two-electron reaction between sulfur and lithium in liquid electrolyte makes the capacity much smaller than the theoretical value. Many methods were proposed for inhibiting the shuttle effect of polysulfide, improving corresponding redox kinetics and enhancing the integral performance of Li–S batteries. Here, we will comprehensively and systematically summarize the strategies for inhibiting the shuttle effect from all components of Li–S batteries. First, the electrochemical principles/mechanism and origin of the shuttle effect are described in detail. Moreover, the efficient strategies, including boosting the sulfur conversion rate of sulfur, confining sulfur or lithium polysulfides (LPS) within cathode host, confining LPS in the shield layer, and preventing LPS from contacting the anode, will be discussed to suppress the shuttle effect. Then, recent advances in inhibition of shuttle effect in cathode, electrolyte, separator, and anode with the aforementioned strategies have been summarized to direct the further design of efficient materials for Li–S batteries. Finally, we present prospects for inhibition of the LPS shuttle and potential development directions in Li–S batteries. [ABSTRACT FROM AUTHOR]

Optical metasurfaces performing analog image processing – such as spatial differentiation and edge detection – hold the potential to reduce processing times and power consumption, while avoiding bulky 4 F lens systems. However, current designs have been suffering from trade-offs between spatial resolution, throughput, polarization asymmetry, operational bandwidth, and isotropy. Here, we show that dispersion engineering provides an elegant way to design metasurfaces where all these critical metrics are simultaneously optimized. We experimentally demonstrate silicon metasurfaces performing isotropic and dual-polarization edge detection, with numerical apertures above 0.35 and spectral bandwidths of 35 nm around 1500 nm. Moreover, we introduce quantitative metrics to assess the efficiency of these devices. Thanks to the low loss nature and dual-polarization response, our metasurfaces feature large throughput efficiencies, approaching the theoretical maximum for a given NA. Our results pave the way for low-loss, high-efficiency and broadband optical computing and image processing with free-space metasurfaces. Here the authors demonstrate a path to design metasurfaces that perform broadband, high-NA, high-efficiency and dual-polarization edge detection without using bulky 4 f systems. This work introduces new approaches towards passive, ultra-compact optical computing and image processing. [ABSTRACT FROM AUTHOR]

Low-noise microwave signals can be efficiently generated with microresonator-based dissipative Kerr solitons (microcombs). However, the phase noise level in integrated microcombs is presently several orders of magnitude above the limit imposed by fundamental thermorefractive noise, resulting from residual pump laser frequency noise transduction to the soliton repetition rate. This effect can be substantially reduced by accessing a quiet point (QP) in the parameter space, where the transduction is compensated by the dispersive wave (DW) recoil, which conventionally relies on accidental mode crossings. Here we present a method to deterministically engineer the QP, both in terms of spectral width and position, and we discover a continuum of possible QPs within the soliton existence region. Using two controlled mode crossings, we obtain regions where the QPs interact with each other, extending the noise suppression range. Our work demonstrates a promising way to reach the fundamental limit of low-noise microwave generation in integrated microcombs. Quiet points (QPs) in chip-integrated microcomb platforms allow the cancellation of transduction noise arising due to the presence of Raman self-frequency shifts, but the conditions to exploit them are fortuitous and system-dependent. The authors propose a strategy to deterministically engineer QPs both in terms of spectral width and position. [ABSTRACT FROM AUTHOR]

An electrically conductive hydrogel injected into an injured muscle can help the muscle to regenerate and reconnect with the nervous system. This effective soft prosthesis has enabled rats to walk soon after muscular injury.A conductive prosthesis that reconnects injured muscle to nerve. [ABSTRACT FROM AUTHOR]

The rational design and implementation of synthetic mammalian communication systems can unravel fundamental design principles of cell communication circuits and offer a framework for engineering of designer cell consortia with potential applications in cell therapeutics. Here, we develop the foundations of an orthogonal, and scalable mammalian synthetic communication platform that exploits the programmability of synthetic receptors and selective affinity and tunability of diffusing coiled-coil peptides. Leveraging the ability of coiled-coils to exclusively bind to a cognate receptor, we demonstrate orthogonal receptor activation and Boolean logic operations at the receptor level. We show intercellular communication based on synthetic receptors and secreted multidomain coiled-coils and demonstrate a three-cell population system that can perform AND gate logic. Finally, we show CC-GEMS receptor-dependent therapeutic protein expression. Our work provides a modular and scalable framework for the engineering of complex cell consortia, with the potential to expand the aptitude of cell therapeutics and diagnostics. The rational design and implementation of synthetic mammalian communication systems can unravel fundamental design principles of cell communication circuits and offer a framework for engineering of designer cell consortia with potential applications in cell therapeutics. Here the authors present a synthetic communication platform in mammalian cells based on diffusible dipeptide ligands and synthetic receptors, that is by design highly orthogonal, scalable, and programmable. [ABSTRACT FROM AUTHOR]