Design Kit Research Articles

Rapid and Ultra‐Sensitive SARS‐CoV‐2 Subgenomic RNA Detection Using Single‐Molecule With a Large Transistor‐SiMoT Bioelectronic Platform

AbstractThe replication of Coronaviridae viruses depends on the synthesis of structural proteins expressed through the discontinuous transcription of subgenomic RNAs (sgRNAs). Thus, detecting sgRNAs, which reflect active viral replication, provides valuable insights into infection status. Current diagnostic methods, such as PCR‐based assays, often involve high costs, complex equipment, and reliance on highly trained personnel. Additionally, their specificity can be compromised by technical limitations in kit design. While viral culture remains highly accurate, it is impractical for routine diagnostics. In this study, the single‐molecule‐with‐a‐large‐transistor (SiMoT) technology is presented for detecting sgRNA encoding the nucleocapsid (N) protein in clinical samples. SiMoT incorporates a stable layer of complementary DNA strands on the sensing gate electrode, facilitating rapid, sensitive, and specific sgRNA detection. Among 90 tested samples, SiMoT achieved a diagnostic sensitivity of 98.0% and a specificity of 87.8%, delivering results within 30 min. This user‐friendly platform requires minimal sample preparation and offers a cost‐effective point‐of‐care (POC) diagnostic solution. With its demonstrated diagnostic accuracy and scalability, SiMoT represents a promising tool for detecting active viral replication in SARS‐CoV‐2 and other coronaviruses. It addresses the limitations of existing molecular and culture‐based methods while enhancing accessibility to reliable diagnostics.

Using design kits to test the problem-solving abilities of engineering students

Problem Solving; Application of Scientific and Engineering Knowledge; as well as Engineering Design, are core attributes the Accreditation Board for Engineering and Technology (ABET) requires in engineering graduates. The author investigated these three skills in two classes of second year students at the Botswana International University of Science & Technology (BIUST) in the 2019/2020 and the 2020/2021 academic years. Two different practical engineering problems were given to the participants. The 2019/2020 class designed a sanitizer dispenser, while the 2020/2021 designed a vehicle and trailer locking system. In both cases, participants were given problems to solve and corresponding toolkits of components to use. The toolkits were, essentially, illustrated scrambled lists of components, which, if correctly put together would achieve the solutions to the posed problems. The participants were first asked to generate functional steps to be achieved by the designs. Secondly, the participants were asked to use the generated functional steps to arrange the given components in meaningful ways to achieve the functionalities stipulated in design problems. The works of the participants were evaluated against moderated functional and design models generated by the module instructor. The time limit in both investigations was 90 min. The results show poor performance by the participants who did not only fail to deliver meaningfully functional models in both cases but also produced below average schematic designs. This paper presents the two investigations as follows. The vehicle/trailer project of the 2020/2021 class is presented in the main body of this paper as a representative case study given that both investigations used similar approaches and delivered comparable performance levels. The 2019/2020 sanitizer dispenser project, whose results were slightly lower than the former, is presented as an addendum.

Efficient Detection of West Nile Virus in Urine Specimens by a Novel In-House RT-qPCR Detection Kit.

West Nile Virus (WNV) infection represents a major global public health challenge. Even though most of the patients are asymptomatic, some cases progress to critical condition which may be fatal. Diagnosis traditionally relies on serological methods, but their limitations, including cross-reactivity, highlight the need for alternative approaches. Here, we present the development and validation of a novel RT-qPCR assay for precise and rapid detection of WNV RNA in urine, emerging as a promising specimen due to its noninvasive collection and high viral load. The assay demonstrates high efficiency and sensitivity, with a detection limit comparable to commercially available kits. This study highlights the importance of in-house kit design as a diagnostic tool in regions affected by emerging tropical infections, such as WNV, exemplified Cyprus. It emphasizes the critical role of low-cost, early detection with high sensitivity and specificity in infection control and surveillance efforts.

Cryo-SIMPLY: A Reliable STT-MRAM-Based Smart Material Implication Architecture for In-Memory Computing.

This paper presents Cryo-SIMPLY, a reliable smart material implication (SIMPLY) operating at cryogenic conditions (77 K). The assessment considers SIMPLY schemes based on spin-transfer torque magnetic random access memory (STT-MRAM) technology with single-barrier magnetic tunnel junction (SMTJ) and double-barrier magnetic tunnel junction (DMTJ). Our study relies on a temperature-aware macrospin-based Verilog-A compact model for MTJ devices and a 65 nm commercial process design kit (PDK) calibrated down to 77 K under silicon measurements. The DMTJ-based SIMPLY demonstrates a significant improvement in read margin at 77 K, overcoming the conventional SIMPLY scheme at room temperature (300 K) by approximately 2.3 X. When implementing logic operations with the SIMPLY scheme operating at 77 K, the DMTJ-based scheme assures energy savings of about 69%, as compared to its SMTJ-based counterpart operating at 77 K. Overall, our results prove that the SIMPLY scheme at cryogenic conditions is a promising solution for reliable and energy-efficient logic-in-memory (LIM) architectures.

Trainer Kit Module for DC Motor Speed Control Using Voice Commands Based on Arduino

Based on the results of observations made by researchers through direct observation of lecturers in the field of electricity, Electrical Engineering Education Study Program, it was found that there is a need for additional trainers as learning media in the electrical machine control course. This study aims to find out how to design a trainer kit design module for DC motor speed control using voice commands by utilizing the Arduino microcontroller. We also learned the results of testing the design of a trainer kit design module for DC motor speed control using voice commands by utilizing the Arduino microcontroller. The research method researchers use is the Research and Development (R&D) method, which aims to develop new products or innovations that benefit. Based on the results of expert validation, it can be concluded that the Arduino Microcontroller-Based Trainer Kit Practical Module obtained a high percentage of media experts at 96%, material experts at 95.5%, and language experts at 80%. These results indicate that this module gets the "Very Eligible" category to be applied to the Electrical Machine Control course.

Modeling of HCI effect in nFinFET for circuit reliability simulation

This paper proposes an equivalent circuit model for simulating the Hot Carrier Injection (HCI) effect. This model is developed based on the N-FinFET in the 12 nm Process Design Kit (PDK) and incorporates arithmetic units and electrical components from the Electronic Design Automatic (EDA) software. Input parameters can be freely modified by the user, such as stress time, ambient temperature, gate length, gate width and process corner. The model also considers the influence of the voltage at each end of the transistor on the HCI effect. The model can be accessed in the EDA tool just like a normal transistor and can be used to evaluate the HCI effect on circuits without modifying the SPICE model. The accuracy and applicability of this model has been verified by comparing it with measured results from other published literature.

A Proof-of-Concept Open-Source Platform for Neural Signal Modulation and Its Applications in IoT and Cyber-Physical Systems

This paper presents the design, implementation, and characterization of a digital IoT platform capable of generating brain rhythm frequencies using synchronous digital logic. Designed with the Google SkyWater 130 nm open-source process design kit (PDK), this platform emulates Alpha, Beta, and Gamma rhythms. As a proof of concept and the first of its kind, this device showcases its potential applications in both industrial and academic settings. The platform was integrated with an IoT device to optimize and accelerate research and development efforts in embedded systems. Its cost-effective and efficient performance opens opportunities for real-time neural signal processing and integrated healthcare. The presented digital platform serves as a valuable educational tool, enabling researchers to engage in hands-on learning and experimentation with IoT technologies and system-level hardware–software integration at the device level. By utilizing open-source tools, this research demonstrates a cost-effective approach, fostering innovation and bridging the gap between theoretical knowledge and practical application. Furthermore, the proposed system-level design can be interfaced with various serial devices, Wi-Fi modules, ARM processors, and mobile applications, illustrating its versatility and potential for future integration into broader IoT ecosystems. This approach underscores the value of open-source solutions in driving technological advancements and addressing skills shortages.

AI Concepts Integration in Developing E-Muhadathat Kits For Non-Arabic Speakers

Recent educational reforms focus on strategically integrating technology into teaching, aligning with the principles of the fourth industrial revolution (IR 4.0). Among the swiftly evolving technologies in language learning is Artificial Intelligence (AI), particularly in the form of Natural Language Processing (NLP). This technology has been applied to create the E-Muhadathat kit, an interactive Arabic conversation simulation tool designed to enhance communication skills for non-Arabic speaking students in Malaysian public universities. This study aims to investigate the role of AI in education, address the challenges in developing AI-based Arabic language learning software, and propose a model for the E-Muhadathat kit tailored for non-Arabic speakers. This literature review uses documentary methods to gather information from journals, conference proceedings, articles, dissertations, and digital books from databases such as Google Scholar, Springer Link, Science Direct, and Research Gate. The collected data undergoes descriptive analysis based on thematic categorization. The findings indicate that the concept of AI consists of three core components: machine learning, deep learning, and neural networks. Arabic linguists have recognized several challenges in developing AI-based software, such as orthographic, morphological, syntactic, anaphoric, and semantic ambiguities. Moreover, the E-Muhadathat kit's design integrates machine learning and deep learning techniques, featuring applications for both spoken and written language. The study's findings support educators and researchers aiming to create Arabic language software tailored for non-native speakers in Malaysian higher education institutions. As a result, the study advocates for further investigation into the use of AI in Arabic language education to enhance the communication abilities of non-native speakers in Malaysia.

Synthetic biology education and pedagogy: a review of evolving practices in a growing discipline

Synthetic biology is a growing field with an increasing number of successful applications. Yet, synthetic biology (SynBio) education initiatives are underreported and disconnected from each other. In this review we survey the literature on SynBio education and stratify this body of work into three categories: classroom activities, course designs, and program-level curricula-planning. For each category, we discuss the methods used to assess students’ experiences and achievement of learning objectives. Throughout, we identify trends and opportunities for further development in SynBio education. We determined that the design of low-cost education kits is a growing opportunity to support student learning at the level of classroom activities. In support of that work, we present a mapping of published education kits onto Bloom’s taxonomy, taking into account increasing accumulation of knowledge through continued experience. We further found that project-based learning is used widely and has proven effective in course designs. To facilitate such activities, we provide a high-level guide for the conversion of a didactic course into a project-based learning course. Further, we note that, currently, programs are delivered primarily at the graduate level, taking inspiration from traditional degree programs while incorporating interdisciplinary training. Finally, we find that design-based research may provide an effective framework for an iterative, mixed-method study design. To support such efforts, we provide a schematic overview of design-based research and its application to a learning progression for interdisciplinary skills. We conclude with a discussion of specific learning concepts that may be useful to SynBio educators and education researchers.

State‐of‐the‐Art 3DES Pipelined Cryptographic Engine Design Against Side‐Channel Attacks

ABSTRACTIn this paper, a high‐speed, low‐latency, and high‐security hardware‐implemented triple data encryption standard (3DES) cryptographic algorithm is proposed for securing data privacy. In order to achieve a high throughput for the 3DES architecture, the whole circuit is optimized with a 24‐stage pipelined design at first. For breaking the correlation between the processed data and power dissipation of the 3DES circuit against differential power analysis (DPA) attacks, two pseudo‐random number generators (PRNGs) are embedded to randomly alter the number of pipelined stages and data substitution locations within the 3DES circuit, respectively. Under such a circumstance, the proposed 3DES circuit is able to achieve high performance and strong robustness against DPA attacks without causing much overhead. As shown in the results, under the synthesis of SMIC 14‐nm process design kits (PDK), the clock frequency, area, power dissipation, and throughput of the proposed 3DES circuit, respectively, are achieved as 1.2 GHz, 26,435 m2, 21.05 mW, and 64 Gbps. Furthermore, when DPA attacks are executed on the proposed 3DES circuit, the corresponding secret key cannot be revealed even if 2 million plaintexts are enabled. In contrast, only 40,000 plaintexts are adequate to disclose the secret key of a regular pipelined 3DES circuit.

Usability, Engagement, and Report Usefulness of Chatbot-Based Family Health History Data Collection: Mixed Methods Analysis.

Family health history (FHx) is an important predictor of a person's genetic risk but is not collected by many adults in the United States. This study aims to test and compare the usability, engagement, and report usefulness of 2 web-based methods to collect FHx. This mixed methods study compared FHx data collection using a flow-based chatbot (KIT; the curious interactive test) and a form-based method. KIT's design was optimized to reduce user burden. We recruited and randomized individuals from 2 crowdsourced platforms to 1 of the 2 FHx methods. All participants were asked to complete a questionnaire to assess the method's usability, the usefulness of a report summarizing their experience, user-desired chatbot enhancements, and general user experience. Engagement was studied using log data collected by the methods. We used qualitative findings from analyzing free-text comments to supplement the primary quantitative results. Participants randomized to KIT reported higher usability than those randomized to the form, with a mean System Usability Scale score of 80.2 versus 61.9 (P<.001), respectively. The engagement analysis reflected design differences in the onboarding process. KIT users spent less time entering FHx information and reported more conditions than form users (mean 5.90 vs 7.97 min; P=.04; and mean 7.8 vs 10.1 conditions; P=.04). Both KIT and form users somewhat agreed that the report was useful (Likert scale ratings of 4.08 and 4.29, respectively). Among desired enhancements, personalization was the highest-rated feature (188/205, 91.7% rated medium- to high-priority). Qualitative analyses revealed positive and negative characteristics of both KIT and the form-based method. Among respondents randomized to KIT, most indicated it was easy to use and navigate and that they could respond to and understand user prompts. Negative comments addressed KIT's personality, conversational pace, and ability to manage errors. For KIT and form respondents, qualitative results revealed common themes, including a desire for more information about conditions and a mutual appreciation for the multiple-choice button response format. Respondents also said they wanted to report health information beyond KIT's prompts (eg, personal health history) and for KIT to provide more personalized responses. We showed that KIT provided a usable way to collect FHx. We also identified design considerations to improve chatbot-based FHx data collection: First, the final report summarizing the FHx collection experience should be enhanced to provide more value for patients. Second, the onboarding chatbot prompt may impact data quality and should be carefully considered. Finally, we highlighted several areas that could be improved by moving from a flow-based chatbot to a large language model implementation strategy.

How Far Is the Nanocellulose Chip and Its Production in Reach? A Literature Survey.

The slowdown of Moore's Law necessitates an exploration of novel computing methodologies, new materials, and advantages in chip design. Thus, carbon-based materials have promise for more energy-efficient computing systems in the future. Moreover, sustainability emerges as a new concern for the semiconductor industry. The production and recycling processes associated with current chips present huge environmental challenges. Electronic waste is a major problem, and sustainable solutions in computing must be found. In this review, we examine an alternative chip design based on nanocellulose, which also features semiconductor properties and transistors. Our review highlights that nanocellulose (NC) is a versatile material and a high-potential composite, as it can be fabricated to gain suitable electronic and semiconducting properties. NC provides ideal support for ink-printed transistors and electronics, including green paper electronics. Here, we summarise various processing procedures for nanocellulose and describe the structure of exclusively nanocellulose-based transistors. Furthermore, we survey the recent scientific efforts in organic chip design and show how fully automated production of such a full NC chip could be achieved, including a Process Design Kit (PDK), expected variation models, and a standard cell library at the logic-gate level, where multiple transistors are connected to perform basic logic operations-for instance, the NOT-AND (NAND) gate. Taking all these attractive nanocellulose features into account, we envision how chips based on nanocellulose can be fabricated using Electronic Design Automation (EDA) tool chains.

300-nm-thick, ultralow-loss silicon nitride photonic integrated circuits by 8-in. foundry production

Silicon nitride (Si3N4) photonic integrated circuits are rapidly developing in recent decades. The low loss of Si3N4 attracts significant attention and facilitates a wide range of applications in integrated photonics. In this work, we demonstrate the foundry fabrication of a 300-nm-thick 8-in. wafer-scale Si3N4 platform, with a microresonator intrinsic quality factor of up to 15×106, corresponding to an ultralow loss of 2.2 dB/m. Leveraging this platform, we develop a mature process design kit, achieving a single-mode waveguide propagation loss of less than 5 dB/m, an edge coupler loss of 1.3 dB, and an insertion loss of 0.07 dB for multimode interference couplers. Utilizing the processed Si3N4 chip, we realize a hybrid integrated tunable external cavity laser with a tuning range from 1534 to 1602 nm, a record-high side-mode suppression ratio of up to 76 dB, an optical power of 26 mW, and an intrinsic linewidth of down to 314 Hz. Our work lays a solid foundation for the further development of applications, including nonlinear optics, quantum optics, optical communications, and ranging.

Securing the IoT ecosystem: ASIC-based hardware realization of Ascon lightweight cipher

The Internet of Things (IoT) nodes consist of sensors that collect environmental data and then perform data exchange with surrounding nodes and gateways. Cybersecurity attacks pose a threat to the data security that is being transmitted in any IoT network. Cryptographic primitives are widely adopted to address these threats; however, the substantial computation demands limit their applicability in the IoT ecosystem. In addition, each IoT node varies with respect to the area and throughput (TP) requirements, thus demanding flexible implementation for encryption/decryption processes. To solve these issues, this work implements the NIST lightweight cryptography standard, Ascon, on a SAED 32 nm process design kit (PDK) library by employing loop folded, loop unrolled and fully unrolled architectures. The fully unrolled architecture can achieve the highest TP but at the cost of higher area utilisation. Unrolling by a lower factor results in lower area implementations, enabling the exploration of design space to tackle the trade-off between area and TP performance of the design. The implementation results show that, for loop folded architecture, Ascon-128 and Ascon-128a require 36.7k μm2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu \ extrm{m}^{2}$$\\end{document} and 38.5k μm2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu \ extrm{m}^{2}$$\\end{document} chip area, respectively compared to 277.1k μm2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu \ extrm{m}^{2}$$\\end{document} and 306.6k μm2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu \ extrm{m}^{2}$$\\end{document} required by their fully unrolled implementations. The proposed implementation strategies can adjust the number of rounds to accommodate the varied requirements of IoT ecosystems. An implementation with an open-source 45 nm PDK library is also undertaken for enhanced generalization and reproducibility of the results.

A High-Quality and Space-Efficient Design for Memristor Emulation

The paper presents a new design for a compact memristor emulator that uses a single active component and a grounded capacitor. This design incorporates a current backward transconductance amplifier as the active element, enabling the emulation of both grounded and floating memristors in incremental and decremental modes. The paper provides an in-depth analysis of the circuit, covering ideal, non-ideal, and parasitic factors. The theoretical performance of the memristor emulator is confirmed through post-layout simulations with 180 nm generic process design kit (gpdk) technology, demonstrating its capability to operate at low voltages (±1 V) with minimal power consumption. Additionally, the emulator shows strong performance under variations in process, voltage, and temperature (PVT) and functions effectively at a frequency of 2 MHz. Experimental validation using commercially available integrated circuits further supports the proposed design.

Cryo-CMOS Multi-Frequency Modulator for 2-Qubit Controller

This paper addresses the design of a CMOS modulator to control two quantum bits. The proposed architecture offers several advantages that are addressed and discussed in this paper. The proposed architecture is investigated through both mathematical modeling and Verilog simulations. Moreover, the circuit was designed using the cryogenic Design Kit of the 130 nm SiGe BiCMOS technology of the IHP foundry. The observed agreement between the modeling, Verilog, and transistor-level simulations proves the physical feasibility of the proposed architecture.

Analysis of the Design of Household First Aid Kits

In the post-epidemic era today, people are increasingly concerned about health issues and have a newer understanding of home health, which in turn is accompanied by the expansion of home healthcare needs. As an important household healthcare device, the demand for first aid kits is also gradually rising, further highlighting the need for them. Although it plays an important role as a home medical care device, deficiencies such as simple structure, lack of function, and lack of intelligence are also presented. Based on this the first aid kit will be transformed and upgraded, innovating the design of its internal and external structure, overall function, and other aspects, to create a set of diverse functions and an intelligent medical care system, so that the family health care can better integrated into people’s lives.

Ultra-Efficient Low-Power Retinal Nano Electronic Circuit for Edge Enhancement and Detection Using 7 nm FinFET Technology

Ultra-Efficient Low-Power Retinal Nano Electronic Circuit for Edge Enhancement and Detection Using 7 nm FinFET Technology

Evaluation of a Simplified Modeling Approach for SEE Cross-Section Prediction: A Case Study of SEU on 6T SRAM Cells

Electrical models play a crucial role in assessing the radiation sensitivity of devices. However, since they are usually not provided for end users, it is essential to have alternative modeling approaches to optimize circuit design before irradiation tests, and to support the understanding of post-irradiation data. This work proposes a novel simplified methodology to evaluate the single-event effects (SEEs) cross-section. To validate the proposed approach, we consider the 6T SRAM cell a case study in four technological nodes. The modeling considers layout features and the doping profile, presenting ways to estimate unknown parameters. The accuracy and limitations are determined by comparing our simulations with actual experimental data. The results demonstrated a strong correlation with irradiation data, without requiring any fitting of the simulation results or access to process design kit (PDK) data. This proves that our approach is a reliable method for calculating the single-event upset (SEU) cross-section for heavy-ion irradiation.

Development of an Educational Kit Using CAD Software for Simple Machine Learning

Traditional simple machine topic is frequently theoretical and does not provide enough hands-on practise. Students may as a result fail to comprehend the fundamentals of simple machines and their applications. This research presents an innovative educational kit for simple machine learning. Students can utilize this kit to understand the fundamental concepts behind simple machines like levers, gears, and pulleys. This study investigates the creation of a simple machine kit using CAD software as a teaching tool for fundamental mechanics. A survey study is employed as part of this technique in order to ascertain audience needs and expectations. Beginning with idea generation and followed by rigorous evaluation, the process of developing the kit focuses on aligning pedagogical viability, marketability, and profitability. The selected concept is then transformed into a detailed technical drawing specifying dimensions, components, and assembly instructions, ensuring coherence between educational goals and machine learning integration. Iterative prototyping and testing further refine the kit's design, ensuring seamless interaction between machine learning elements and LEGO-based components. This approach culminates in an innovative educational kit that effectively imparts foundational machine learning principles through an engaging platform. The simple machine kit made through this research can then be utilized as an educational tool in primary, secondary, or higher education environments to facilitate students' grasp of basic mechanics. Students learning product design may find this novel approach both enjoyable and useful in their studies.