Critical Design Factors Research Articles

Critical Factors and Trends in NFT Technology Innovations

Non-fungible token (NFT) products are important for industrial applications. In recent years, they have rapidly gained importance in the field of blockchain combined with metaverse. The concept of NFTs has developed gradually, as many industries have begun using NFTs creatively to raise new business innovation opportunities in entrepreneurship. However, few studies have been conducted analyzing critical features of NFTs for success, trends, and challenges in NFT products. In this study, group discussions, case analysis methods, and the OpenSea database were used to analyze fashion trends among NFT products. A mixed method was used in this study. Quantitative and qualitative data derived from the questionnaire and group discussions were analyzed using the case study method, and the actual historical trading data of NFT products obtained from the OpenSea platform were analyzed. This study analyzed NFT products, fashion characteristics, and trends in NFT artwork. The opportunities and challenges of NFT applications and sustainable NFTs are discussed in this study. Our research results show that the most attractive NFT product types are collectible digital works and creative artworks. The critical design characteristics are lovely (cute), beautiful, and interesting. We recommend that NFT makers use the above-mentioned characteristics to create NFT artworks with special design characteristics to increase NFT values. The advantage of NFTs is that makers can freely create their works through the NFT platform, which can decrease the limitations of traditional methods such as the need for venues, exhibition setup costs, and intermediaries’ commissions. The major challenges of current NFT applications include usability challenges, security and privacy issues, and governance considerations. We believe that our research results can provide useful directions and strategies for future researchers, makers, and ventures seeking to develop NFT applications. Our research results, such as identifying the critical design factors and current trends in NFTs, can provide guidelines for art design and innovation education. In addition, this study discusses the applications of NFTs in sustainable education, which can provide benefits for sustainable educational development to meet the goal of quality education in SDG4.

High-Throughput Screening of Natural Product and Synthetic Molecule Libraries for Antibacterial Drug Discovery.

Due to the continued emergence of resistance and a lack of new and promising antibiotics, bacterial infection has become a major public threat. High-throughput screening (HTS) allows rapid screening of a large collection of molecules for bioactivity testing and holds promise in antibacterial drug discovery. More than 50% of the antibiotics that are currently available on the market are derived from natural products. However, with the easily discoverable antibiotics being found, finding new antibiotics from natural sources has seen limited success. Finding new natural sources for antibacterial activity testing has also proven to be challenging. In addition to exploring new sources of natural products and synthetic biology, omics technology helped to study the biosynthetic machinery of existing natural sources enabling the construction of unnatural synthesizers of bioactive molecules and the identification of molecular targets of antibacterial agents. On the other hand, newer and smarter strategies have been continuously pursued to screen synthetic molecule libraries for new antibiotics and new druggable targets. Biomimetic conditions are explored to mimic the real infection model to better study the ligand-target interaction to enable the designing of more effective antibacterial drugs. This narrative review describes various traditional and contemporaneous approaches of high-throughput screening of natural products and synthetic molecule libraries for antibacterial drug discovery. It further discusses critical factors for HTS assay design, makes a general recommendation, and discusses possible alternatives to traditional HTS of natural products and synthetic molecule libraries for antibacterial drug discovery.

Facile synthesis of A‐π‐D‐π‐A architecture organic small molecules. Experimental and theoretical investigation of the effect of a π‐conjugated spacer

AbstractUnderstanding the structure‐property relationship is one of the critical factors in the practical design of organic small molecules for bulk heterojunction organic solar cells (BHJ‐OSCs). In this study, we designed and synthesized two low‐band‐gap organic small molecule donors, TRh and PhRh. To study the effect of the π‐conjugated spacer, the A‐π‐D‐π‐A architecture was constructed with an efficient dithienopyrrole donor (D) and rhodanine acceptor (A) units. Two types of π‐conjugated spacers, thiophene in TRh and phenyl in PhRh, are used to fine‐tune the various properties. A detailed investigation of the effect of π‐conjugated spacers on optoelectronic, thermal, and photovoltaic properties have carried out. TRh is planar, more conjugated, has a more prolonged absorption wavelength and leads to a low band gap of 1.48 eV. DFT studies demonstrate that TRh has lower BLA (Bond length alternation) and has more quinoid structure than PhRh. PhRh is thermally more stable than TRh. PhRh displayed a high glass transition temperature (Tg) at 193 °C and a 5% decomposition temperature at 402 °C. The inverted device architecture of BHJ‐OSCs blended with PC71BM displayed the PCE of 2.78% for TRh and 1.10% for PhRh. TRh : PC71BM blend exhibits higher hole and electron mobilities than PhRh : PC71BM blend.

Asynchronous federated learning with directed acyclic graph-based blockchain in edge computing: Overview, design, and challenges

Asynchronous Federated Learning (AFL) has been introduced to improve the efficiency of FL by reducing the latency of Machine Learning (ML) model aggregation, particularly in the Internet of Things (IoT) environment. Meanwhile, decentralized FL, such as leveraging blockchain and directed acyclic graph (DAG)-based ledgers, also has drawn much attention to the integration of FL owing to the security benefit against single-point-failure and Byzantine fault tolerant consensus. We observe that the inherent network asynchrony of DAG-based ledgers is beneficial for implementing asynchronous FL particularly in edge computing domains, even though there is no existing survey work that provides a fundamental overview of such integration. This paper surveys on the integration of asynchronous FL with DAG, which we call AFL-DAG, as a promising approach to realize the intersection of decentralized FL and asynchronous FL. Motivated by the lack of a concrete taxonomy of asynchronous FL and a global model, especially with decentralized FL, we introduce universally applicable terminologies and the extensive classification method of FL in terms of asynchrony. Based on the proposed taxonomy, we present a generic system model of AFL-DAG for edge computing applications. To provide a horizontal overview and cover fundamental concepts in AFL-DAG, we identify four critical design factors and the state-of-the-art solutions are discussed accordingly. Future directions to achieve a practical AFL-DAG are also highlighted. Finally, we explore the opportunities of AFL-DAG by investigating a popular edge computing application, the on-device crowdsourcing, and provide a high-level evaluation of AFL-DAG compared to blockchained-FL.

Case study on thermal design improvement of hydrazine monopropellant pipelines for satellite propulsion system

The present research investigates a case study on thermal design and improvement of hydrazine monopropellant pipelines based on actual cases, in order to highlight the critical factors for thermal design when developing an onboard propulsion system for a satellite. A simple 1-D thermal math model was developed for thermal analysis using the lumped-parameter assumption, and three different thermal design cases of hydrazine propellant pipeline layouts were considered. By increasing heater power densities and applying modified worst cold boundary conditions for thermal analysis, the thermal design performance for the propellant pipelines of an actual satellite could be improved and verified through thermal vacuum test.After the successful operation of the pipeline heaters in the real space environment, some important lessons learned on thermal design improvements of hydrazine monopropellant pipeline layout could be attained from the present case study. These lessons learned will be useful for the future development of satellite onboard propulsion systems.

Critically Assessing Undergraduate Field Experiences: Understanding Conceptualizations and Opportunities for Building Inclusive Programs.

Undergraduate field experiences (UFEs) are key components of many biology, ecology, and geoscience programs and important steps to successful recruitment into careers. Through semistructured interviews of diverse field program leaders, we seek to understand how field program leaders conceptualize both their scientific disciplines and the intentional design factors they implemented within the UFE itself. Additionally, this study explores critical considerations these program leaders use to approach designing inclusive UFEs as well as the institutional and practical challenges of designing and implementing their UFEs. We acknowledge the limitations of the small sample of respondents, and our intent with this article is to explore these responses as a way to share critical design factors for designing and implementing inclusive UFEs with the broader geoscience community. Building an early understanding of these factors will help new field program leaders address multiple, simultaneous challenges that currently foment the underrepresentation of students from marginalized backgrounds in biology, ecology, and the geosciences. Through these explicit conversations, we hope to support the professional development of a scientific community that values the creation of safe, encouraging field experiences in which students can enhance their self-identity in the sciences, build peer and professional networks, and develop memorable field experiences that support their trajectories toward successful careers.

Adopting distributed pair programming as an effective team learning activity: a systematic review.

As online learning has become an inevitable trend in the post-peak era of the COVID-19 pandemic, distributed pair programming (DPP) is gaining momentum in both education and industry. DDP serves as a collaborative programming approach and also benefits the development of computational thinking, a fundamental skill in today's world. This study conducted a systematic review of studies on DPP published after 2010 to understand the themes and factors that impact the team effectiveness of DPP and thus inform future research and practices on how to better leverage this approach for teaching and learning. The results showed that individual characteristics attracted major investigations in the selected 23 studies, including prior programming experience, actual skill, perceived skill, gender, personality, time management, confidence, and self-esteem, with pair compatibility identified as a critical team design factor that significantly affects programmers' satisfaction. Although the feel-good factor in the team process was investigated, no significant impact was found. Under the team environment theme, we compared different opinions on the orientation (e.g., scripted roles) and the use of technology (e.g., integrated development environment tools). Future research should investigate how task structure influences team effectiveness of DPP and relates to computational thinking education. Additionally, because most studies were conducted in higher education contexts, more research in primary and secondary educational contexts is also needed.

Enhancing the Fatigue of Mechanical Systems Such as Dispensers Entrenched on Generalized Life-Stress Models and Sample Sizes

To lengthen the life of a mechanical system, parametric accelerated life testing (ALT) is recommended as an established way to help identify structural imperfections and reduce fatigue-related failures. It involves (1) a parametric ALT scheme, (2) fatigue design, (3) ALTs with alterations, and (4) an estimate of whether design(s) achieve the BX lifetime. The application of a quantum-transported time to failure prototype and a sample size expression is also suggested. The improvements in the reliability of a water dispenser made of stainless steel or polypropylene (PP) in a bottom-mount domestic refrigerator was used as a case study. In the first ALT, the hinge and front corner of the dispensing system was cracked. The water dispenser lever was altered by increasing the thickness of its ribs and fillets. In the second ALT, the altered dispensing lever system cracked because there was an insufficient thickness in its front corner for impact loading. The critical design factors for improving reliability were corner fillet rounding and rib thickening in a dispenser lever. As there were no difficulties in the third ALT, the dispenser life was verified to have a B1 life of 10 years.

Matrices Activated with Messenger RNA.

Over two decades of preclinical and clinical experience have confirmed that gene therapy-activated matrices are potent tools for sustained gene modulation at the implantation area. Matrices activated with messenger RNA (mRNA) are the latest development in the area, and they promise an ideal combination of efficiency and safety. Indeed, implanted mRNA-activated matrices allow a sustained delivery of mRNA and the continuous production of therapeutic proteins in situ. In addition, they are particularly interesting to generate proteins acting on intracellular targets, as the translated protein can directly exert its therapeutic function. Still, mRNA-activated matrices are incipient technologies with a limited number of published records, and much is still to be understood before their successful implementation. Indeed, the design parameters of mRNA-activated matrices are crucial for their performance, as they affect mRNA stability, device immunogenicity, translation efficiency, and the duration of the therapy. Critical design factors include matrix composition and its mesh size, mRNA chemical modification and sequence, and the characteristics of the nanocarriers used for mRNA delivery. This review aims to provide some background relevant to these technologies and to summarize both the design space for mRNA-activated matrices and the current knowledge regarding their pharmaceutical performance. Furthermore, we will discuss potential applications of mRNA-activated matrices, mainly focusing on tissue engineering and immunomodulation.

Early design stage evaluation of architectural factors in fire emergency evacuation of the buildings using Pix2Pix and explainable XGBoost model

ABSTRACT As a critical factor in architectural design, emergency evacuation is influenced by numerous parameters. Designers utilize modelling software to evaluate their sketches after completion ofbasic design. However, no various alternatives of early design stages could be assessed via simulations, since it is a time-consuming procedure. In this study, deep-learning algorithms have been adapted for the assessment of the evacuation process at early design stages. The main methods applied include an image-to-image translation with a conditional GAN (Pix2Pix) and Extreme Gradient Boosting (XGBoost). The developed Pix2Pix model generates the heat maps of possible route congestions with a Structural Similarity Index (SSIM) of 0.89. Besides, the XGBoost model predicts the evacuation time with the mean absolute error (MAE) and R2 values of 36 s and 0.94, respectively. This method generates the results of intended analyses at high speed and is a reliable alternative for time-consuming evacuation simulations in early design stages.

Topology Optimization for Minimum Compliance with Material Volume and Buckling Constraints under Design-Dependent Loads

Stability is a critical factor in structural design. Although buckling-constrained topology optimization has been investigated in previous work, the problem has not been considered under design-dependent loads. In this study, a model of buckling constraints in topology optimization problems under design-dependent loads was proposed to solve the above problem. First, the Kreisselmeier–Steinhauser aggregation function was employed to reduce multiple constraints to a single constraint. Then, the problem was sequentially approximated using the optimality criteria method tailored to update the variables. After that, a gradient-based optimization algorithm was established based on finite element and sensitivity analyses for the topology optimization problem with design-dependent loads. Finally, four numerical examples with design-dependent loads were comparatively analyzed, with and without bucking-constrained solutions. The calculation results proved the effectiveness and reliability of the optimization algorithm. Therefore, in this study, it was suggested that the developed optimization algorithm gained improved applicability.

Shearing friction behaviour of synthetic polymers compared to a functionalized polysaccharide on biomimetic surfaces: models for the prediction of performance of eco-designed formulations.

The substitution of natural, bio-based and/or biodegradable polymers for those of petrochemical origin in consumer formulations has become an active area of research and development as the sourcing and destiny of material components becomes a more critical factor in product design. These polymers often differ from their petroleum-based counterparts in topology, raw material composition and solution behaviour. Effective and efficient reformulation that maintains comparable cosmetic performance to existing products requires a deep understanding of the differences in frictional behaviour between polymers as a function of their molecular structure. In this work, we simulate the tribological behaviour of three topologically distinct polymers in solution with surfactants and in contact with hair-biomimetic patterned surfaces. We compare a generic functionalized polysaccharide to two performant polymers used in shampoo formulations: a strongly positively charged polyelectrolyte and a zwitterionic copolymer. Topological differences are expected to affect rheological properties, as well as their direct interaction with structured biological substrates. Using a refined Martini-style coarse-grained model we describe the polymer-dependent differences in aggregation behaviour as well as selective interactions with a biomimetic model hair surface. Additionally, we introduce a formalism to characterize the response of the solution to shear as an initial study on lubrication properties, which define the sensorial performance of these systems in cosmetics (i.e., manageability, touch, etc.). The tools and techniques presented in this work illustrate the strength of molecular simulation in eco-design of formulation as a complement to experiment. These efforts help advance our understanding of how we can relate complex atomic-scale solution behaviour to relevant macroscopic properties. We expect these techniques to play an increasingly important role in advancing strategies for green polymer formulation design by providing an understanding for how new polymers could reach and even exceed the level of performance of existing polymers.

PERSONALIZATION: Why the relational modes between Generative AI chatbots and human users are critical factors for product design and safety

PERSONALIZATION: Why the relational modes between Generative AI chatbots and human users are critical factors for product design and safety

Probe the nanoparticle-nucleus interaction via coarse-grained molecular model.

The present study reports on a computational model that systematically evaluates the effect of physical factors, including size, surface modification, and rigidity, on the nuclear uptake of nanoparticles (NPs). The NP-nucleus interaction is a crucial factor in biomedical applications such as drug delivery and cellular imaging. While experimental studies have provided evidence for the influence of size, shape, and surface modification on nuclear uptake, theoretical investigations on how these physical factors affect the entrance of NPs through the nuclear pore are lacking. Our results demonstrate that larger NPs require a higher amount of energy to enter the nucleus compared to smaller NPs. This highlights the importance of size as a critical factor in NP design for nuclear uptake. Additionally, surface modification of NPs can impact the nuclear uptake pathway, indicating the potential for tailored NP design for specific applications. Notably, our findings also reveal that the rigidity of NPs has a significant effect on the transport process. The interplay between physicochemical properties and nuclear pore is found to determine nuclear uptake efficiency. Taken together, our study provides new insights into the design of NPs for precise and controllable NP-nucleus interaction, with potential implications for the development of efficient and targeted drug delivery systems and imaging agents.

Critical business design factors in the internet of things service supply chain: a review and typology

The internet of things (IoT) is a relatively new concept that combines ubiquitous and pervasive computing, sensing and communication technologies, and embedded devices to form a system where the real and digital worlds meet and are continuously in interdependent communication. In this context, IoT acts as an intelligent service supply chain linking objects, information, and people through computer, smart object and sensor networks. This service supply chain creates numerous business design challenges. This article addresses these challenges by providing a cohesive typology matrix to explain the IoT service supply chain. The matrix has been developed through a systematic literature review of 78 academic papers, identifies the key contributors and influences at each stage of the service supply chain and their inter-relationships, to facilitate the rectification of business design and integration challenges that may emerge at the different stages of the sequence.

Factors affecting the efficiency of closed-loop geothermal wells

Geothermal energy has a promising prospect of becoming a feasible source of clean energy in the future. However, conventional open-loop geothermal systems need continuous water circulation, which limits their application in dry areas. On the other hand, long-term fluid injection into the reservoir may cause issues such as seismicity. To overcome these shortcomings, closed-loop geothermal systems are not requiring water withdrawal or water injection. However, the mechanism controlling the efficiency of closed-loop systems has not been well analyzed. To resolve the issue, a systematic study was conducted on factors affecting production efficiency of a closed-loop geothermal well. First, a coupled three-dimensional model was established, which was then validated against experimental results available in the literature. Using this model, the effects of several critical design factors were investigated quantitatively. These factors include cement thermal conductivity, cement thickness, fluid circulation rate, injected fluid temperature, heat capacity of circulating fluid, heat exchanger height, and tubing outer diameter. Our simulation results indicate that increasing the cement thermal conductivity enhances both produced fluid temperature and thermal power. The effect of cement thickness is correlated with the value of its thermal conductivity. As the circulation rate increases, the temperature of produced fluid decreases while thermal power increases asymptotically. Using a circulating fluid with high heat capacity would result in higher thermal power. A large heat exchanger height would boost both the production temperature and thermal power significantly. Finally, a dimensionless analysis was conducted, through which two dimensionless numbers were derived to integrate the effects of different factors. By comparison analysis, the accuracy of the dimensionless numbers was validated. Also, the impact of the dimensionless numbers on dimensionless produced fluid temperature was determined. With the dimensionless numbers, the effects of different individual factors can be evaluated comprehensively, which brings convenience to parameter design. The potential applications of the derived dimensionless numbers in parameter design of closed-loop systems were discussed. Results and conclusions obtained in this paper may provide a reference for optimally designing closed-loop systems.

Learning as a design factor for innovation contests: a bidirectional model

ABSTRACT This study aims to develop a more comprehensive understanding of design factors as they relate to the role of learning when implementing innovation contests. Through synthesising the principles of knowledge transfer and absorptive capacity, this study provides novel findings on the role of learning when implementing innovation contests. Using a unique data set from a six-year engagement (2015–2020), this paper presents case studies of seven firms implementing innovation contests. Firms ranged in size, industry, and type, which led to four primary data sources including 28 interviews and a range of data from 414 problem-solvers. This research contributes to the literature by demonstrating that learning is a critical design factor in innovation contests and occurs in a bidirectional way with differing levels of intensity for problem-solvers and solution-seeking firms. We find that learning is a salient factor that has direct and indirect effects on innovation contests, differing from what has been previously outlined in the innovation literature which solely focused on learning from a firm's perspective. The study contributes to practice by providing a blueprint for practitioners to make more informed decisions about the role of learning and its importance as a factor in the design and implementation of innovation contests.

Student wellbeing and technostress: critical learning design factors

In higher education, student wellbeing is now the responsibility of all of us. During the Covid-19 pandemic, the pivot by universities to online learning positioned technology as a panacea, and saw students being signposted to digital resources for digital skills and wellbeing support. Our use of the concept, technostress, is derived from the Student Minds report (2021) entitled ’Life in a pandemic’. It refers to the stress experienced by students when using technology within higher education, given the sector's expectations of their technical abilities. Our paper reported on the results of a digital health and wellbeing survey (n=103) with surprising responses from 80 students to the survey question about technostress. The findings indicate students feel let down by teaching staff who struggle with the mediating tools of their online trade – technology – and show little empathy for those they teach. McDougall and Potter (2018) argue that human-centred approaches, prioritising staff and students’ immediate and lifelong wellbeing rather than the mere use of digital tools, are key to success in developing policies for student wellbeing. The findings indicate that the formulaic approaches offered by academic staff to students in response to their digital health and wellbeing challenges will chime with learning developers championing student support as emancipatory practice. Attendees were invited to reflect on their own experience of technostress and share their considerations as to how to widen understanding of this phenomenon. The presentation concluded by recommending an integrated model for framing student wellbeing underpinned with exceptional learning design and considered the optimum on a continuum for the use of technological tools.

Design and analysis of electrothermal metasurfaces

Electrothermal metasurfaces have attracted extensive attention due to their ability to dynamically control thermal infrared radiation. Although previous studies were mainly focused on the metasurfaces with infinite unit cells, the finite-size effect can be a critical design factor for developing thermal metasurfaces with fast response and broad temperature uniformity in practice. Here, we study the thermal metasurfaces consisting of gold nanorods with a finite array size, which, with only several periods, can achieve a resonance close to that of the infinite case. More importantly, such a small footprint due to the finite array size results in the response time down to a nanosecond level. Furthermore, the number of the unit cells in the direction perpendicular to the axis of the nanorods is found to be insensitive to the resonance and response time, thus providing a tunability in aspect ratio that can boost the temperature uniformity in the sub-Kelvin level.

Thermal Benefits of a Cooling Guide Vane for an Electrical Machine in an Electric Ducted Fan

Equipped with a distributed electric propulsion system, eVTOL is the primary vehicle for future urban air mobility. The electrical machine determines the weight of the distributed electric propulsion system, and the cooling capability determines the electrical machine’s weight. The electrical machine with air cooling is preferred for eVTOL due to its simplicity and light weight. This paper presents a new air-cooling system for an electrical machine in an electric ducted fan propulsion system. The novel cooling system consists of a cooling guide vane with a heat pipe (CGVHP), which is located downstream of the ducted fan rotating blade. The heated end of the heat pipe is inserted into the stator end windings and the cold end is inserted into the cooling guide vane. The heat generated in the windings is transmitted to the cooling guide vane by the heat pipe and dissipated by the forced convection using low-temperature air passing through the ducted fan. The cooling performance of the cooling guide vane with the heat pipe was numerically simulated, considering several critical design factors. The simulation results showed that the proposed CGVHP can be helpful for reducing the winding temperature of the electrical machine by over 25.5 °C at the peak power condition of 15.7 kW.