Leading-edge Technology Research Articles

Fluid-Infiltrated Metalens-Driven Reconfigurable Intelligent Surfaces for Optical Wireless Communications.

A reconfigurable intelligent surface (RIS), a leading-edge technology, represents a new paradigm for adaptive control of electromagnetic waves between a source and a user. While RIS technology has proven effective in manipulating radio frequency waves using passive elements such as diodes and MEMS, its application in the optical domain is challenging. The main difficulty lies in meeting key performance indicators, with the most critical being accurate and self-adjusting positioning. This work presents an alternative RIS design methodology driven by an all-silicon structure and fluid infiltration, to achieve real-time control of focal length toward a designated user, thereby enabling secure data transmission. To validate the concept, both numerical simulations and experimental investigations of the RIS design methodology are conducted to demonstrate the performance of fluid-infiltrated metalens-driven RIS for this application. When combined with different fluids, the resulting ultra-compact RIS exhibits exceptional varifocal abilities, ranging from 0.4 to 0.5 mm, thereby confirming the adaptive tuning capabilities of the design. This may significantly enhance the modulation of optical waves and promote the development of RIS-based applications in wireless communications and secure data-transmission integrated photonic devices.

Postsecondary organizations and their role in advancing sustainable smart cities: towards a system-oriented perspective

Postsecondary institutions such as public and private universities have a key role to play in the development of sustainable smart cities. This paper discusses aspects of this role in terms of historical contributions, examples of contributions from the standpoint of two universities, and potential future contributions. The treatment of these aspects from a system-oriented perspective is also addressed. Researchers working on leading edge technologies have resources that enable them to introduce disruptive solutions that enhance the well-being of society. On the other hand, it is clear that different university realities demand unique actions depending on whether they reside in developing or developed countries, although common social problems have also been identified. Overall, there is an opportunity for universities to test new ideas and implement them in communities, especially where they reside. We discuss the role of universities in a broad sense, where contributions are briefly described and acknowledged. The focus is on applications for sustainability and social good that have been or could be developed in universities as new research opportunities to improve the quality of life of the general population. We also argue that it is essential to consider university contributions to the creation of smart cities in the context of a system-oriented perspective.

Laser-Printed All-Carbon Responsive Material and Soft Robot.

Responsive materials and actuators are the basis for the development of various leading-edge technologies but have so far mostly been designed based on polymers, incurring key limitations related to sensitivity and environmental tolerance. This work reports a new responsive material, laser-printed carbon film (LPCF), produced via direct laser transformation of a liquid organic precursor and consists of graphitic and amorphous carbons. The high activity of amorphous carbon combined with the dual-gradient structure enables the LPCF to have a actuation speed of 9400°s-1 in response to the stimulus of organic vapor. LPCF exhibits a conductivity of 950Sm-1 and excellent resistance to various extreme environmental conditions, which are unachievable for polymer-based materials. Additionally, an LPCF-based all-carbon soft robot that can mimic the complex continuous backward somersaulting motions without manual intervention is constructed. The locomotion velocity of the robot reaches a value of 1.19BLs-1, which is almost one to two orders of magnitude faster than that of reported soft robots. This work not only offers a new paradigm for highly responsive materials but also provides a great design and engineering example for the next generation of biomimetic robots with life-like performance.

Innovative machine learning based approach for reliable and accurate measurement of guide roll alignment in continuous casting plants

Continuous casting (strand casting) is the leading-edge technology in modern steel production. Even slight improvements of the casting process offer a range of benefits, such as improved quality, higher productivity, energy savings and a reduced environmental impact. The precise alignment of a plants guiding rolls is a crucial factor for its performance. Strand condition monitoring systems usually incorporate modules to gauge the alignment of the guiding rolls. These modules measure the angle formed by two successive rolls by using metal rulers fitted with inclination sensors. However, the angle of the ruler only represents a valid measurement where it maintains firm contact with two successive rolls. Most of these systems rely on inductive switches that trigger a measurement at these locations. Yet this approach provides unreliable results due to the trigger’s insufficient accuracy. Furthermore, this method stores only one data point per roll, which is problematic due to significant measurement noise. Apparently, a reliable and accurate alignment measurement remains a significant challenge. As part of an ongoing research project, this paper presents the development of a novel alignment measurement module. The module will provide continuous readings from the inclination sensors without the need for a trigger. In addition, an innovative machine learning based approach to distinguish between valid and invalid measurements is developed. This method enables the averaging of multiple measurements per roll, drastically reducing the impact of measurement noise while providing reliable alignment angles. To overcome the limited availability of real-world data, which is insufficient for model training, the measurement module is simulated to generate artificial training data. Our machine learning model achieves excellent performance on this artificially generated dataset. The paper concludes by outlining how the new approach will be applied to real-world data generated by the new module

Digital Twin for mitigating solar energy resources challenges: A Perspective

The leading-edge technology of Digital Twin (DT) presents potential solutions for challenges associated with renewable energy resources (RER), particularly solar energy, such as optimal management, random nature and unpredictability, maintenance, security, and energy efficiency. These issues are more elevated today due to the widespread adoption of solar energy in the power system. A DT leverages advanced technologies including the Internet of Things (IoT), artificial intelligence, and computing techniques, to observe and confirm the state of physical entities, analyze data and derive valid information to monitor and optimize the entity's operation. This Perspective strives to trace the growing body of advances in the field and proposes opportunity areas for DT of RER (RERDT) and DT of solar energy (DTSE) in various application domains including forecasting, reliability analysis, security, and resiliency. Barriers that hinder the adoption of RERDT and DTSE technologies to meet its continuous operation are discussed, and also possible views as future trends to deal with the challenges are presented. RERDT and DTSE technologies promise to be transformative in enabling flexible and sustainable energy sources as well as in active real-time management since it provides a full comprehension of the resources.

Influence of Passive Pre-Chamber Nozzle Diameter on Jet Ignition in a Constant-Volume Optical Engine under Varying Load and Dilution Conditions

<div>Despite the growing prominence of electrified vehicles, internal combustion engines remain essential in future transportation. This study delves into passive pre-chamber jet ignition, a leading-edge combustion technology, offering a comprehensive visualization of its operation under varying load and dilution conditions in light-duty GDI engines. Our primary objectives are to gain fundamental insights into passive pre-chamber jet ignition and subsequent main combustion processes and evaluate their response to different load and dilution conditions. We conducted experimental investigations using a light-duty, optical, single-cylinder engine equipped with three passive pre-chamber designs featuring varying nozzle diameters. Optical diagnostic imaging and heat release analysis provided critical insights. Findings reveal that as load decreases, fuel availability and flow conditions deteriorate, leading to delayed and suboptimal jet characteristics impacting main chamber ignition and combustion. Notably, at high and medium loads without dilution, the 1.2 mm-PC (smallest nozzle diameter) excels, exhibiting superior jet ignition and main combustion. This is attributed to earlier jet ejection, improved penetration, and intensified jets, all enabled by the smaller nozzle diameter. Conversely, under low load conditions, the 1.6 mm-PC (largest nozzle diameter) performs better due to enhanced scavenging and reduced pre-chamber residuals, resulting in more balanced pre-chamber combustion and jet characteristics. Furthermore, nozzle diameter significantly influences cycle-to-cycle variations, with smaller diameters enhancing jet ignition but intensifying variability. The impact of external residuals (dilution) on jet ignition performance varies with nozzle diameter, with the 1.6 mm-PC displaying less degradation and demonstrating earlier jet ejection and CA50 timing under higher dilution conditions. In summary, this research underscores the importance of scavenging and residual levels in pre-chamber design, influencing dilution tolerance, and extending possibilities for high-efficiency engines. It contributes essential insights into the behavior of passive pre-chamber jet ignition systems, facilitating their optimization for future internal combustion engines.</div>

Biologics in Interventional Spinal Procedure: The Past, the Present, and the Vision

BACKGROUND: Orthobiologics have shown promise in repair, restoration and regeneration of damaged and degenerated spine, joint and musculoskeletal tissues. The role of MSCs is to reduce inflammation, gliosis, and oxidative stress, while encouraging angiogenesis, neuronal proliferation, cell survival, and differentiation. While autologous MSCs have homologous advantages, they present with challenges related to donor predisposition, harvesting skills, and processing times. In this regard, allogenic MSCs show promise, but face ethical challenges, contamination, and survival risks. Ongoing efforts to overcome challenges and enhance performance include bioprinting, tissue engineering, artificial intelligence, nanotechnology, and microenvironmental alteration, among many others. Genetically programmed MSCs are being explored and tissue regeneration is now considered a real possibility. In this article, we discuss some of the leading-edge technologies in the process of being developed and perfected for widespread clinical application. OBJECTIVES: The aim of this narrative review is both to update on orthobiologics, especially MSCs and provide a vision for their future potential in interventional spine medicine. STUDY DESIGN: Narrative review. METHODS: The PubMed database of the National Institute of Medicine and Google Scholar were searched for keywords “mesenchymal stem cell,” “mesenchymal stem cell + regenerative medicine,” and “mesenchymal stem cell + spine.” The bibliographies of these articles and authoritative Web sites were also consulted. RESULTS: There are hundreds of ongoing clinical trials exploring the role of MSCs in regenerative medicine for treating a wide range of diverse conditions, including spine conditions, neurodegenerative disorders, and cardiovascular disease. LIMITATIONS: This visionary narrative review has several limitations. It is a narrative, rather than a systematic review. Many of the ideas and treatments presented here are not perfected and are still in development. CONCLUSIONS: The role of MSCs in regenerative medicine is still emerging, but their promise for spinal cord injury and other disorders of the spine is clear. Using allogenic or autologous MSCs can help stimulate healing and neural regeneration remains a tantalizing possibility. KEY WORDS: Mesenchymal stem cell, regenerative medicine, spine, spinal cord injury, nanotechnology, bioprinting, neural regeneration, degenerative disc disease, low back pain

The EDFAS FA Technology Roadmap—Die-Level Roadmap Council (DLRC)

Abstract The EDFAS Die-Level Roadmap Committee was formed to identify forthcoming challenges related to electrical fault isolation within the next five years and collaborate with various stakeholders, including industry, academia, and tool vendors, to devise practical solutions. To that end, the team has pinpointed five critical areas of focus: (1) laser-based, photon emission, and thermal; (2) 2D/2.5D/3D packaging; (3) product yield, test, and diagnostics; (4) general (leading edge technologies); and (5) system level, analog/RF, and digital functional.

Optimal load balancing in cloud: Introduction to hybrid optimization algorithm

One of the leading-edge technologies that have made it possible to pay as you go and distribute appropriate resources on demand is cloud computing. The process of optimizing the resource on cloud virtual machines (VMs) is called load balancing. The main goal is to evenly distribute tasks and resources among all machines to ensure that no node is overloaded or inactive. However, the load balancing methods currently used in cloud environments are ineffective in lowering the amount of time needed to respond to requests. This work intends to propose a novel optimal load balancing (LB) method in the cloud. For this a new Intercrossed Chimp and Bald Eagle Algorithm (IC&BA) algorithm is introduced that combines the algorithms like bald eagle search (BES) optimization and chimp optimization (CA) algorithm. Thereby, the proposed load balancing model works under the consideration of (i) Energy Consumption (ii) execution cost (iii) migration cost (iv) Make span and (v) load balancing parameters like response time, Turnaround time.

Leading-Edge Technologies for Architectural Design: A Comprehensive Review

Leading-Edge Technologies for Architectural Design: A Comprehensive Review

Detect and Engage: A New American Way of War

The threat that paces American force planning is not from Russia, but rather from China. This is leading to a new way of warfare. The authors call it ‘detect and engage’. The confluence of artificial intelligence, applied quantum mechanics and satellite networking permits dispersed and diverse units and platforms to operate as a unified joint force across sea, air, land and space. Cyber operations, practically indifferent to location, further enable the United States to reduce reliance on geographically concentrated and exposed forces. Advanced technology is just one step in operationalising new forms of warfare. Others include anticipating adversary responses; building robust inventories of extended-range weapons; knowing when and how to conduct close-in operations; integrating and empowering defence allies; and maintaining US forward presence. Harnessing leading-edge technology to improve global US military effectiveness reflects neither an isolationist nor an insular policy, but rather one of ongoing engagement.

Towards a citizen development andragogy: Low-code platforms, design thinking and knowledge-based dynamic capabilities

Addressing the ongoing deficit in technical skills and talent necessitates an effective management approach that can harness the power of accelerating innovation. In response to the challenge, this paper presents a comprehensive learning model called Citizen Development Andragogy (CDA), specifically tailored for adult learners. CDA is an integrative learning framework, designed for an array of academic programs from micro-credentialing to four-year degrees, which combines leading-edge technology, such as low-code tools and platforms and generative AI, design thinking for creativity, and the institutionally oriented, knowledge-based dynamic capabilities (KBDC) model. Additionally, CDA is epistemologically rooted in the individually focused constructivist learning theory, providing a consistent structure that caters to the learning needs of working adults, enhancing their ability to conceive, design, build, and implement digital solutions. The andragogical learning theory is designed for adult learners and has important implications regarding teaching and program differences for reaching traditional aged college students, emerging learners, versus more seasoned individuals. Emerging strategic components conveyed in this paper—via a discursive style—represent some first steps towards considering and building a citizen development andragogy. An initial CDA framework conceptualization is detailed in this paper, which explores its theoretical constructs, practical considerations, current limitations, and it also shares insights from early implementation efforts, and presents a variety of potential future research avenues. Importantly, the paper emphasizes CDA's role as an accessible gateway for introducing citizen development into adult education and upskilling programs. In a broader societal context, citizen development, facilitated by CDA, can serve as a vital influencer for larger 'citizen' involvement movements like citizen scientists, human rights observers, and environmentalists. As such, an effective, scalable CDA prototype has the potential to yield meaningful benefits, empowering individuals, and organizations to achieve impact on an unprecedented scale, ultimately benefiting society at large.

Leading Edge Technologies and Perspectives in Industrial Oilseed Extraction.

With the increase in the world's population and per capita wealth, oil producers must not only increase edible oil production but also meet the demand for a higher quality and variety of products. Recently, the focus has shifted from single processing steps to the entire vegetable oil production process, with an emphasis on introducing innovative technologies to improve quality and production efficiency. In this review, conventional methods of oilseed storage, processing and extraction are presented, as well as innovative processing and extraction techniques. Furthermore, the parameters most affecting the products' yields and quality at the industrial level are critically described. The extensive use of hexane for the extraction of most vegetable oils is undoubtedly the main concern of the whole production process in terms of health, safety and environmental issues. Therefore, special attention is paid to environmentally friendly solvents such as ethanol, supercritical CO2, 2-methyloxolane, water enzymatic extraction, etc. The state of the art in the use of green solvents is described and an objective assessment of their potential for more sustainable industrial processes is proposed.

Vision-based dirt distribution mapping using deep learning

Cleaning is a fundamental routine task in human life that is now handed over to leading-edge technologies such as robotics and artificial intelligence. Various floor-cleaning robots have been developed with different cleaning functionalities, such as vacuuming and scrubbing. However, failures can occur when a robot tries to clean an incompatible dirt type. These situations will not only reduce the efficiency of the robot but also impose severe damage to the robots. Therefore, developing effective methods to classify the cleaning tasks performed in different regions and assign them to the respective cleaning agent has become a trending research domain. This article proposes a vision-based system that employs YOLOv5 and DeepSORT algorithms to detect and classify dirt to create a dirt distribution map that indicates the regions to be assigned for different cleaning requirements. This map would be useful for a collaborative cleaning framework for deploying each cleaning robot to its respective region to achieve an uninterrupted and energy-efficient operation. The proposed method can be executed with any mobile robot and on any surface and dirt, achieving high accuracy of 81.0%, for dirt indication in the dirt distribution map.

Editorial: Special Section from the International Society of Asphalt Pavements (ISAP) Symposium 2022

Abstract This Special Section of the ASTM International Journal of Testing and Evaluation is composed of 33 papers from the International Society for Asphalt Pavements (ISAP) 2022 Symposium in Costa Rica. ISAP is a volunteer organization of professionals and experts in asphalt engineering whose goal is to share the latest in leading-edge asphalt pavement technology worldwide. Every 4 years, ISAP organizes the ISAP Symposium, which in 2022 was held in San José, Costa Rica, from October 25 to 27. Researchers and engineers from different countries attended, presenting and discussing ideas on a wide range of topics related to pavement infrastructure. The event made it possible to share and increase knowledge to allow the development of increasingly innovative and sustainable solutions to improve infrastructure while respecting the environment and people. The 33 original technical manuscripts in this Special Section are improved versions of selected 6-page papers from the ISAP 2022 Symposium. They were all peer-reviewed according to the high standards of the Journal of Testing and Evaluation. The ISAP 2022 Symposium was coordinated with the activities of the ISAP Technical committees: Asphalt Pavement and Environment and Pavement Field Evaluation. The ISAP 2022 Symposium was organized by Professor Luis G. Loria-Salazar (Conference Chairman, Isaac Newton University, Costa Rica) and Professor Gabriele Tebaldi (Conference Chairman, University of Parma, Italy, and University of Florida, USA).

Technology Trends for Massive MIMO towards 6G.

At the dawn of the next-generation wireless systems and networks, massive multiple-input multiple-output (MIMO) in combination with leading-edge technologies, methodologies, and architectures are poised to be a cornerstone technology. Capitalizing on its successful integration and scalability within 5G and beyond, massive MIMO has proven its merits and adaptability. Notably, a series of evolutionary advancements and revolutionary trends have begun to materialize in recent years, envisioned to redefine the landscape of future 6G wireless systems and networks. In particular, the capabilities and performance of future massive MIMO systems will be amplified through the incorporation of cutting-edge technologies, structures, and strategies. These include intelligent omni-surfaces (IOSs)/intelligent reflecting surfaces (IRSs), artificial intelligence (AI), Terahertz (THz) communications, and cell-free architectures. In addition, an array of diverse applications built on the foundation of massive MIMO will continue to proliferate and thrive. These encompass wireless localization and sensing, vehicular communications, non-terrestrial communications, remote sensing, and inter-planetary communications, among others.

IMPLICATIONS OF SPEECH RECOGNITION THROUGH NLP: AN OVERVIEW

In the current state of digitalization researchers have found a leading-edge technology that delivers information to users from the digital machine and vice-versa and i.e. Natural Language Processing (NLP), one of an AI branch that made a difference. NLP is a computational representation and analysis of human language, which globally aims to facilitate naturally occurring interaction between computers and individuals whether phonically, calligraphically or textual. NLP has various booming sides in advanced world and has expands its applications in different domains. One of its application Speech recognition is a large field of research for modern-day researchers. Speech recognition, also known as automatic speech recognition (ASR) or speech-to-text, is capable of handling human speech in a written format. The main focus is on development of recognition system which enhances human-to-human communication by permitting man-machine communication through the processing of texts or speeches. It is a technology that makes it possible for people to communicate with devices. Several applications of voice recognition systems are in place and all understand diverse scrutiny challenges.This paper captures the necessity of how speech recognition actually functions, types of model, resolving challenges of ASR. Deep study on functioning of Alexa and Siri.

Recent developments in photoresists for extreme-ultraviolet lithography

This report describes recent developments and current needs in the field of high-resolution photopolymers and photomolecules briefly describing prior generation lithographic patterning materials. It subsequently concentrates on recent advances in both inorganic and polymeric materials for extreme ultraviolet (EUV) lithography. It is also part of a series of papers written in celebration of the centenary of the Polymeric Materials: Science and Engineering (PMSE) division of the American Chemical Society (ACS). PMSE has long been home to polymer chemists who have made important contributions to advances in semiconductor manufacturing as a result of PMSE's focus on polymer coatings research. While EUV lithography has been an area of research for several decades, only within the last 5 years has the combination of new light sources, EUV optics, tool advances and resist discoveries come together to transition this area from the patterning method of the future to a leading-edge manufacturing technology. (148 words).

Building the future of synthetic organ manufacturing and healthcare

Organ reconstruction and manufacturing is a field that aims to create functional organs for transplantation or therapeutic purposes. The development of this field has been driven by rapid advances in various technologies, including three-dimensional (3D) bioprinting, organs-on-chips, organoids, stem cell reprogramming, genome editing and artificial intelligence (AI). Take, for example, the development of organoids and organs-on-chips, which has completely revolutionized the way scientists study organ development, disease progression and drug effects in vitro. 3D bioprinting, which can produce tissues and organs with customized shapes, sizes and functions, has also made it possible to create complex structures with high precision and accuracy, including livers, kidneys, hearts, ears and skin grafts. Bioprinted tissues and organs may soon be used for transplantation on demand in the clinic. Furthermore, manipulation of cell fates and genomes with the latest techniques in reprogramming, genome editing and AI-based computational modelling has allowed us to unlock the hidden potential within human cells and produce new human cell types with new capabilities. Genome editing of patient-derived cells to correct any underlying defects could also ensure that synthetic organs are created with improved functionality and compatibility with the recipient's body. Advancements like these have paved the way for new biomedical applications such as personalized medicine and regenerative therapies. In this special issue on Organ Reconstruction and Manufacturing, we have assembled a corpus of the latest studies that shed light on the cutting-edge progress and challenges in this field. Our special issue highlights the most significant new findings, technologies and therapies that are emerging in this burgeoning field, providing a platform for experts in the field to share their thoughts and predict future trends. The topics covered in this special issue include leading-edge technologies like 3D bioprinting, organs-on-chips and organoids, as well as genetically engineered cells and animals—all of which are critical pieces in the quest for regenerative medicine. If this dream is realized, scientists may well be able to use patient-derived cells to complete drug testing at warp speed, and make it possible to create synthetic organs for transplantation, potentially addressing the shortage of donor organs on a global scale. As we rapidly make technological progress towards this dream, a final piece in the puzzle is the development of ethical guidelines and manufacturing standards to ensure that the production and applications of synthetic organs remain safe, ethical and properly regulated. The creation of synthetic organs raises many ethical questions, including issues related to patient privacy, informed consent and accessibility to healthcare. Therefore it is crucial for us to establish ethical guidelines and manufacturing standards in a collaborative manner, based on multinational and global consensus, to regulate the proper development and use of synthetic organs. We believe our efforts in building such frameworks will help ensure that the benefits of technological breakthroughs in organ reconstruction and manufacturing are maximized, while minimizing potential risks and negative consequences for all of humanity. In conclusion, synthetic organ reconstruction and manufacturing is a rapidly evolving field that has the potential to revolutionize the healthcare industry. I believe recent advancements in biotechnology, computational methods, therapeutic applications, ethics and standards will pave the way for a quantum leap in innovation for the field in the near future.

Leading Edge Use of Technology for Teacher Professional Development in Indian Schools

This paper presents a case study of a decade-long technology-enabled teacher professional development (TPD) initiative for government-run school teachers in India. The TPD aimed at capacitating teachers in integrating project-based or constructivist learning with technology in curriculum and pedagogy. Teachers are central to the teaching–learning processes, and hence capacitating them to leverage digital technologies confidently is essential to improve the quality of education imparted to learners. This paper focuses on the use of innovative technologies leading to the education of teachers. A decade of TPD is divided into three phases providing an analytical framework for the evolving technologies and pedagogies across the phases. Documents, resources and tools used for the TPD activities, researchers’ first-hand experiences and documented research studies supported the comparative analysis of the three phases of TPD. This comparison highlighted leading-edge technologies influencing changes in TPD delivery mode, learning support, pedagogy, scale, etc., across the phases. The paper also maps the interrelationship between technologies and pedagogies of TPD, suggesting various features of innovations such as continuous, practice-based, collaborative, scalable, shareable, transferable, and adaptable.