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The present study describes a technique for the virtual design of a three-piece stackable auricular mold for unilateral auricular defect rehabilitation using an open-source software program. An optical intraoral scanner is used to scan the patient's ears on both the affected and unaffected side. To maintain the relationship between the mold parts, a stackable attachment is designed and joined to the mold. The mold is 3D printed in resin. This technique provides the patient with a precise auricular prosthesis with perfect thickness, adaptation, and appearance. The workflow introduced in this technique could be considered as an alternative for the fabrication of auricular prostheses and decreased both the clinical and laboratory time compared to the conventional workflow. [ABSTRACT FROM AUTHOR]

Uncertainty in the evolution of opponent behavior creates a non-stationary environment for the agent, reducing the reliability of value estimation and strategy selection while compromising security during the exploration process. Previous studies have developed various uncertainty quantification techniques and designed uncertainty-aware exploration methods for multi-agent reinforcement learning (MARL). However, existing methods have gaps in theoretical research and experimental verification of decoupling uncertainty between opponents and environment, which can decrease learning efficiency and lead to an unstable training process. Due to inaccurate opponent modeling, the agent is vulnerable to harm from opponents, which is undesirable in real-world tasks. To address these issues, this study proposes a novel uncertainty-guided safe exploration strategy for MARL that decouples the two types of uncertainty originating from the environment and opponents. Specifically, we introduce an uncertainty decoupling quantification technique based on a novel variance decomposition method for action-value functions. Furthermore, we present an uncertainty-aware policy optimization mechanism to facilitate safe exploration in MARL. Finally, we propose a new adaptive parameter scaling method to ensure efficient exploration by the agents. Theoretical analysis establishes the proposed approach's convergence rate, and its effectiveness is demonstrated empirically. Extensive experiments on benchmark tasks spanning differential games, multi-agent particle environments, and RoboSumo validate the proposed uncertainty-guided method's significant advantages in attaining higher scores and facilitating safe agent exploration. [ABSTRACT FROM AUTHOR]

In this paper, we undertake a comprehensive examination of quasinormal modes (QNMs) linked to Morris–Thorne, also known as Bronnikov–Ellis wormholes, delving into scalar, electromagnetic, and gravitational perturbations using the spectral method. Our research corrects inaccuracies previously reported in the literature and addresses areas where the Wentzel–Kramers–Brillouin (WKB) approximation proves inadequate. Moreover, we introduce and evaluate a novel spectral technique designed to consolidate recent advancements in formulating QNM boundary conditions at both the wormhole throat and space-like infinity. This innovative approach bridges critical gaps in existing methodologies and enhances the accuracy and applicability of QNM analysis in the study of wormhole physics. [ABSTRACT FROM AUTHOR]

Proper modeling of the dynamic behavior of the soil significantly affects the accuracy of the soil–structure interaction analysis results. Using nonlinear constitutive models has the highest accuracy in modeling soil behavior under earthquake loading. However, it is not functional for practical engineering purposes because of the high cost and complexity. The equivalent linear method also has many limitations, such as filtering out the high-frequency components of the input excitation, underestimating surface ground motion over long periods, and considerable error in high soil strain levels. The current study aims to present an accurate, simple, and low-cost method to model the nonlinear behavior of clays. This method does not meet the limitations of the traditional methods and fully considers the effect of the influential parameters. The novel central composite design technique was adopted to evaluate the effect of influential variables on the nonlinear behavior of clay and formulate the proposed method. The introduced method is applicable to various building structures, power planets, etc. Numerical analyses performed on the proposed method and nonlinear modeling confirm the accuracy, efficiency, and generality of the proposed method. [ABSTRACT FROM AUTHOR]

We propose a novel ray reordering technique designed to accelerate the ray tracing process by encoding and sorting rays prior to traversal. Our method, called “hierarchy cut code”, involves encoding rays based on the cuts of the hierarchical acceleration structure, rather than relying solely on spatial coordinates. This approach allows for a more effective adaptation to the acceleration structure, resulting in a more reliable and efficient encoding outcome. Furthermore, our research identifies “bounding drift” as a major obstacle in achieving better acceleration effects using longer sorting keys in existing reordering methods. Fortunately, our hierarchy cut code successfully overcomes this issue, providing improved performance in ray tracing. Experimental results demonstrate the effectiveness of our approach, showing up to a 1.81 times faster secondary ray tracing compared to existing methods. These promising results highlight the potential for further enhancement in the acceleration effect of reordering techniques, warranting further exploration and research in this exciting field. [ABSTRACT FROM AUTHOR]

Light field (LF) image super-resolution (SR) is a technique designed to enhance the details and clarity of low-resolution (LR) light field images by leveraging the additional information and structure present within the LF data. With the rise of deep learning, the performance of LF image super-resolution has been significantly improved, but it has led to an increase in model parameters and computational complexity, resulting in a phenomenon of excessive reliance on computational resources. To address this problem, this paper proposes a lightweight but effective model. In our approach, we employ Swin Attention to extract features from LF images. Window and Shifted Window are the main components of Swin Attention. Therefore, the local features of the LF images are captured using Window, and feature correlations are established through Shifted Window. Furthermore, we introduce Extensive Attention (EA) blocks to capture the global features of the LF image. In addition to the aforementioned configurations, we have also engineered an iteration of the Low Computation Convolution (LCC) that is capable of eliminating redundant information prior to the feature extraction process in LF images. This design aims to mitigate superfluous computations, thereby enhancing computational efficiency. Experimental results show that our approach achieves suboptimal performance compared to other state-of-the-art models, while having fewer parameters, lower computational complexity, and faster inference speed. [ABSTRACT FROM AUTHOR]

A comprehensive design methodology for the realization of ultra‐wideband and highly miniaturized capacitively loaded Marchand baluns (MBs), suitable for integration into balanced antenna systems is presented. A design technique to maximize the fractional bandwidth (FBW) for a given manufacturing process is demonstrated for the first time. Furthermore, a novel MB integration scheme using broadside‐coupled lines and 3D vertically integrated capacitors in a two‐material inkjet printing process is uniquely proposed. The concept has been experimentally validated within the S and C bands. It exhibits a footprint of 0.128 × 0.098 λg2, centre frequency of 4.4 GHz, and FBW of 121%. Its power loss, phase imbalance and amplitude imbalance were measured between 0.8 and 2.2 dB, 3 ± 2°, and 0.4 ± 0.4 dB, respectively. [ABSTRACT FROM AUTHOR]

In response to the COVID-19 pandemic, governments worldwide have implemented mandatory face mask regulations in crowded public spaces, making the development of automatic face mask detection systems critical. To achieve robust face mask detection performance, a high-quality and comprehensive face mask dataset is required. However, due to the difficulty in obtaining face samples with masks in the real-world, public face mask datasets are often imbalanced, leading to the data imbalance problem in model training and negatively impacting detection performance. To address this problem, this paper proposes a novel recursive model-training technique designed to improve detection accuracy on imbalanced datasets. The proposed method recursively splits and merges the dataset based on the attribute characteristics of different classes, enabling more balanced and effective model training. Our approach demonstrates that the carefully designed splitting and merging of datasets can significantly enhance model-training performance. This method was evaluated using two imbalanced datasets. The experimental results show that the proposed recursive learning technique achieves a percentage increase (PI) of 84.5% in mean average precision (mAP@0.5) on the Kaggle dataset and of 186.3% on the Eden dataset compared to traditional supervised learning. Additionally, when combined with existing oversampling techniques, the PI on the Kaggle dataset further increases to 88.9%, highlighting the potential of the proposed method for improving detection accuracy in highly imbalanced datasets. [ABSTRACT FROM AUTHOR]

Introduction: One of the factors that makes robot‐assisted nephroureterectomy difficult is that the optimal port position differs between nephrectomy and bladder cuff excision. In addition, how best to retrieve the specimen after resection while minimizing the size of the wound is a challenge in robot‐assisted surgery. To solve these problems, we designed a surgical technique for robot‐assisted nephroureterectomy using the GelPoint Platform with a focus on port position optimization and specimen retrieval. This study describes the surgical technique of GelPoint robot‐assisted nephroureterectomy and reports our initial experience with this technique. Methods: Between January 2023 and May 2024, seven patients underwent robot‐assisted nephroureterectomy using the GelPoint Platform and 11 underwent conventional robot‐assisted nephroureterectomy. We compared the patients' characteristics and surgical outcomes between the two groups. Results: Compared with the conventional robot‐assisted nephroureterectomy group, the median operative time tended to be shorter in the GelPoint robot‐assisted nephroureterectomy group (280 vs. 357 min, respectively; p =.135). The maximum incision length tended to be longer in the GelPoint robot‐assisted nephroureterectomy group (7.0 vs. 6.0 cm, respectively; p =.078). The incidence of 30‐day complications was similar between the two groups (28.5% vs. 18.2%, respectively; p = 1.000). No complications were associated with the use of the GelPoint Platform. Conclusion: The surgical outcomes of GelPoint robot‐assisted nephroureterectomy are comparable to those of conventional robot‐assisted nephroureterectomy, and it can be performed safely and effectively. GelPoint robot‐assisted nephroureterectomy can be considered a feasible alternative for selected patients with upper tract urothelial carcinoma. [ABSTRACT FROM AUTHOR]

Blinding and randomisation are important methods for increasing the robustness of pre-clinical studies, as incomplete or improper implementation thereof is recognised as a source of bias. Randomisation ensures that any known and unknown covariates introducing bias are randomly distributed over the experimental groups. Thereby, differences between the experimental groups that might otherwise have contributed to false positive or -negative results are diminished. Methods for randomisation range from simple randomisation (e.g. rolling a dice) to advanced randomisation strategies involving the use of specialised software. Blinding on the other hand ensures that researchers are unaware of group allocation during the preparation, execution and acquisition and/or the analysis of the data. This minimises the risk of unintentional influences resulting in bias. Methods for blinding require strong protocols and a team approach. In this review, we outline methods for randomisation and blinding and give practical tips on how to implement them, with a focus on animal studies. [ABSTRACT FROM AUTHOR]

This paper presents a semester-long bottle design project for an undergraduate Numerical Analysis course. Students implement numerical methods in MATLAB to design and 3D print a bottle. Employing mathematical methods to compute features of their designs enhances students' understanding of numerical techniques in design applications. Student feedback highlights the project's efficacy in demonstrating the intersection of mathematics and design, fostering creativity, and instilling a deeper appreciation for mathematical principles in real-world contexts. [ABSTRACT FROM AUTHOR]

The study of the physico-chemical modification of Yucca filamentosa (Yf) natural fiber by graft copolymerization with ethylmethacrylate using ferrous ammonium sulfate-potassium persulfate as a redox initiator has been reported in the article. Initially, six process parameters; reaction duration, reaction temperature, solvent amount, pH, FAS:KPS ratio, and monomer concentration were used in the study in a sequential experimental design technique, and the significant process variables affecting the yield of the graft copolymer were identified. The Resolution-V design method identified the significant parameters as the reaction temperature, amount of solvent, and the concentration of monomer. In second phase of the study, the screened variables were utilized in the development of a model through the technique of response surface methodology (RSM) for the prediction of the yields, and its optimization. The developed RSM model fitted well with the experimental data, and predicted for the optimal conditions of reactions as temperature 50 °C, solvent 100 ml, and the monomer 3.05 × 10−3 mol/L; at which the highest graft yield percentage obtained was 124.2%. The techniques of FTIR, SEM, and XRD were used for the characterization graft copolymers. Studies of the various physico-chemical properties showed that the produced graft copolymers were more resistant than the natural fibers. [ABSTRACT FROM AUTHOR]

Multimode spacecraft propulsion has the potential to greatly increase the maneuvering capability of spacecraft in comparison to traditional architectures. This technology combines two or more propulsive modes (e.g., chemical and electric) into a single system with a single propellant. Trajectory design techniques for spacecraft with this capability, however, are presently limited and typically require manual selection of the burn sequence. In this study, indirect optimal control formulations with automatic mode selection are developed and applied for the first time to multimode spacecraft with two modes of propulsion. Minimum-fuel transfers are solved using polar coordinates as well as using Modified Equinoctial Elements with perturbations. Propellant-constrained minimum-time problems are also solved for the first time using a penalty function approach. An interior-point constraint formulation is also provided. Sample transfers are developed for each coordinate choice and optimization objective and are compared to trajectories that use a single mode of propulsion. The results demonstrate viability of the proposed techniques and show that the multimode approach can reduce the time-of-flight in comparison to a low-thrust only trajectory while providing mass savings over high-thrust only solutions. • Indirect optimal control methods are used to solve multimode mission design problems. • Minimum-fuel and propellant-constrained minimum-time problems are solved. • The techniques extend immediately to hybrid propulsion. [ABSTRACT FROM AUTHOR]

Adaptive design optimization (ADO) is a state-of-the-art technique for experimental design (Cavagnaro et al., 2010). ADO dynamically identifies stimuli that, in expectation, yield the most information about a hypothetical construct of interest (e.g., parameters of a cognitive model). To calculate this expectation, ADO leverages the modeler's existing knowledge, specified in the form of a prior distribution. Informative priors align with the distribution of the focal construct in the participant population. This alignment is assumed by ADO's internal assessment of expected information gain. If the prior is instead misinformative, i.e., does not align with the participant population, ADO's estimates of expected information gain could be inaccurate. In many cases, the true distribution that characterizes the participant population is unknown, and experimenters rely on heuristics in their choice of prior and without an understanding of how this choice affects ADO's behavior. Our work introduces a mathematical framework that facilitates investigation of the consequences of the choice of prior distribution on the efficiency of experiments designed using ADO. Through theoretical and empirical results, we show that, in the context of prior misinformation, measures of expected information gain are distinct from the correctness of the corresponding inference. Through a series of simulation experiments, we show that, in the case of parameter estimation, ADO nevertheless outperforms other design methods. Conversely, in the case of model selection, misinformative priors can lead inference to favor the wrong model, and rather than mitigating this pitfall, ADO exacerbates it. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study is to utilise the Theoretical Domains Framework (TDF) to identify the main barriers and facilitators of positive attitude towards trying Virtual Active Sports (VAS). Design/methodology/approach: 200 individuals took part in an online cross-sectional survey based on 11 domains within the TDF. Linear logistic regression analysis was performed on the participant's self-reported attitudes and believes. Based on the results from the regression analyses, a list of suggested behaviour change techniques was designed using the Behaviour Change Wheel (BCW) framework and the BCT taxonomy (BCTTv1). Findings: This research suggested that Beliefs about Consequences, Beliefs about Capabilities, Goal Conflict, Coping Planning, and Environmental Context and Resources are the main factors, influencing the positive attitude towards VAS and the self-reported desire to try it in the future. Future interventions were recommended and supported by 22 possible BCTs identified using the BCW approach. The TDF and BCW proved to be useful models for identifying both internal and external factors influencing fitness fans during the adoption of the new sportstech. Originality/value: The main contribution of the present work was the implementation of a structured and effective approach derived from the healthcare domain to design solutions for behaviour change in the emerging and expanding virtual sports context. [ABSTRACT FROM AUTHOR]

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The emerging demand for high-data-rate wireless communication systems and high-resolution radars, particularly in the millimeter-wave (mm-wave) spectrum, has captured significant attention within both the industrial and academic landscape. Recognized as the fundamental building block for satellite receivers, the low noise amplifier (LNA) plays a pivotal role in meeting these growing requirements. In Today's world a continuously increasing number of connected devices and resource-intensive digital content load to an incessant data being generated, transformed, and facilitated. In this paper, authors summarize the different technologies and techniques employed to design various LNAs with enhanced bandwidth, higher gain, low noise figure (NF), minimal power consumption, and less chip area. [ABSTRACT FROM AUTHOR]

This paper shows the design and implementation of a multimode optical source in the VPIphotonics software. Considering all the powerful features this software provides, the absence of a device such as a multimode source in its library constitutes a limitation for particular simulations. The use of single‐mode optical sources available in the library allows for obtaining a multimode spectrum. The mathematical relationship that describes a multimode optical source is numerically evaluated in MATLAB. Afterward, this graphical result is compared with the obtained in the VPIphotonics software. The importance of using this type of optical source resides in its applications for modern optical communications systems, microwave photonic filters (MPFs), opto‐electronic oscillators (OEOs), and sensors. This implementation aims to drive virtual systems where required, and by setting its parameters similar to the real ones, it allows good studying and understanding of system responses. Even more, it predicts or ensures the results of experimental systems by having the possibility to vary different parameters. A practical application of the obtained multimode optical spectrum is shown with its use in the implementation of an MPF. This last simulation is experimentally corroborated. This work presents a technique for designing a multimode optical source in this particular software and provides also academics and students, with a methodology for the use of this software for this kind of photonic design. [ABSTRACT FROM AUTHOR]

The circular scan architecture (CSA) is a widely used scan design technique in digital circuit testing that involves scanning test data through a circuit in a circular pattern. Several optimization approaches have been suggested so far to lessen the Test Data Volume (TDV), but no one has shown satisfactory results. Therefore, this paper proposes a Modified and Customized Wingsuit Flying Search algorithm to decrease the test data volume time. The proposed MCWFS-SBA-CSA introduces some novel features that distinguish it from traditional circular scan approaches. The concept of wingsuit flying is an innovative approach in the field of scan systems. This allows the scan that moves more dynamically and efficiently, enabling it to cover a larger area in a shorter time than traditional circular-scan approaches. After this phase, only scan-chosen inputs are required to obtain the next test pattern from the captured response. Therefore, required less Automatic test equipment (ATE) memory in this research so there is a Decreased cost in system-on-chip (SOC). The proposed method attains fast global searching capacity. The efficiency of the proposed technique attains 26.42%, 32.45%, and 29.34% higher compression ratio (CR), Test Application Time (TAT) reduction of SC-128 attains 29.45%, 34.67%, and 40.22% higher, TDV of SC-256 attains 32.23%, 36.34%, and 39.23% higher than existing methods, such as TDV for Circular Scan Approaches utilizing Modified Shuffled Shepard Optimization (TDV-CSA-MSSO), Effectual Very-large-scale integration Test data compression system for CSA under modified and colony metaheuristic (ETDC-CSA-MACMH), and Test Data Compression Utilizing Tetrad state Skip System (TDC-DC-TSSC) for Digital Circuits, respectively. [ABSTRACT FROM AUTHOR]

Analog design productivity remains a challenge in the digitally driven semiconductor chip design field. Knowledge-based and simulation-based analog automation approaches have not achieved widespread acceptance in the analog design community. Systematic analog design using precomputed lookup tables (LUTs) is a promising approach that can address the design productivity challenge. Although modern computing systems have powerful memory capabilities, which make the LUT approach viable, reducing the memory footprint of the LUTs remains a challenge. A memory-efficient design technique using LUTs is proposed by using an incomplete grid in the MOSFET degrees-of-freedom (DoFs) space. An efficient indexing technique for the incomplete grid is also proposed, using a precomputed offset array in various scenarios, such as two-sided constraints and three-dimensional LUTs. The results show that the proposed technique can achieve up to a 67% reduction in memory footprint, in addition to improving LUT generation time and query performance. [ABSTRACT FROM AUTHOR]

We introduce a novel approach to evaluate how the design properties of morphing metamaterial influence shape-changing experiences. We leverage parametric design to create cutting patterns that change the Density and Geometry material properties. Using laser-cutting, we apply the patterns to a non-stretchable woven textile, resulting in a stretchable metamaterial that we actuate using an electromagnetic coil. This systematic design approach leads to programmatic control over the material movement, making it suitable for controlled evaluation of perceived experience. In a 2×2 mixed-method study, we assess how the metamaterial’s Density and Geometry properties impact the observed experience. Our findings indicate that such changes significantly and independently affect participants’ perceived emotions, mood, associations, and preferences. Our research contributes to the body of work of systematic studies in the shape-changing community. By using our morphing metamaterial design and implementation technique, coupled with our controlled evaluation of specific design properties, we have revealed new insights about the influencing factors of shape-changing experiences. We have incorporated these insights into our morphing metamaterial design guidelines, which outline the impact of Density and Geometry properties on an observer’s perceived emotions. We hope our work will open up new possibilities for expressive, evocative metamaterial-focused shape-changing experiences. [ABSTRACT FROM AUTHOR]

This study aimed to assess the role of the combination of design techniques of the engineered substrates, and the effect of encapsulating Marjoram (Origanum Majorana L.) into the matrix network was studied. To this end, PVA-PEG matrices were designed through 3 techniques of freeze–thaw (FT), the combination of both methods of freeze-drying and freeze-thawing(FT-FD), and ternary technique(freeze-drying,freeze-thawing,cross-linking(FT-FD/CL)), by combining equal volume ratios of both polymers. The results indicated the ternary technique can provide better physicochemical properties(porosity: 96%, lower degradation rate, higher modulus) compared to FT and FT-FD methods. Afterward, encapsulation of Marjoram-extracted bio-actives in the matrix network designed with the ternary technique demonstrated that the increase in the extract concentration up to 3% can increase encapsulation efficiency. The encapsulation also caused a more cohesive network by better bonding between functional groups in herbal biomolecules and polymer chains of the matrix. Mass transport mechanisms and release kinetics of matrix-encapsulated bio-actives indicated a deviation from Fickian diffusion and the release by diffusion and swelling process. Biologically, matrix-loaded herbal carbohydrate(Epi-alpha-Cadinol) improved fibroblast adhesion and distribution on the substrate surface, and led to the better synthesis of collagen fibers, especially in 3% herbal extract, and antibacterial activities owing to the controlled release of sesquiterpenoids and N-Acetyl-l-proline. [ABSTRACT FROM AUTHOR]

AbstractPurposeMethodsResultsConclusionsThis comprehensive review is designed to elucidate the transformative role and multifaceted applications of ocular hydrogels in contemporary ophthalmic therapeutic strategies, with a particular emphasis on their capability to revolutionize drug delivery mechanisms and optimize patient outcomes.A systematic and structured methodology is employed, initiating with a succinct exploration of prevalent ocular pathologies and delineating the corresponding therapeutic agents. This serves as a precursor for an extensive examination of the diverse methodologies and fabrication techniques integral to the design, development, and application of hydrogels specifically tailored for ophthalmic pharmaceutical delivery. The review further scrutinizes the pivotal manufacturing processes that significantly influence hydrogel efficacy and delves into an analysis of the current spectrum of hydrogel-centric ocular formulations.The review yields illuminating insights into the escalating prominence of ocular hydrogels within the medical community, substantiated by a plethora of ongoing clinical investigations. It reveals the dynamic and perpetually evolving nature of hydrogel research and underscores the extensive applicability and intricate progression of transposing biologics-loaded hydrogels from theoretical frameworks to practical clinical applications.This review accentuates the immense potential and promising future of ocular hydrogels in the realm of ophthalmic care. It not only serves as a comprehensive guide but also as a catalyst for recognizing the transformative potential of hydrogels in augmenting drug delivery mechanisms and enhancing patient outcomes. Furthermore, it draws attention to the inherent challenges and considerations that necessitate careful navigation by researchers and clinicians in this progressive field. [ABSTRACT FROM AUTHOR]

To increase the energy-absorbing capability of frontal collision management systems and improve vehicle crash safety, foam-filled crash boxes should be optimized. On the basis of a double tubular construction, a novel foam-filled crash box with a different design is developed. The energy absorption capacity, initial peak force, and deformation modes of the original and improved crash boxes were examined using impact models. As opposed to the full-filling design, it is demonstrated that the filling design may utilize less foam while increasing specific energy absorption. The stability of continuing deformation after the first buckling is determined by the foam-filled crash box. For the foam-filled crash box, a better-optimized design technique is suggested using the Taguchi method and principal component analysis (PCA). Compression tests are used to validate the design concept. Therefore, the optimal design technique of the crash box is suitable and practical for the crashworthiness design of crash boxes, considering the combined effect of significant indicators for electric vehicles. [ABSTRACT FROM AUTHOR]

For several decades after Moore's Law is proposed, there is a continuous effort to reduce the feature‐size of transistors. However, as the size of transistors continues to decrease, numerous challenges and obstacles including severe short channel effects (SCEs) are emerging. Recently, low‐dimensional materials have provided new opportunities for constructing small feature‐size transistors due to their superior electrical properties compared to silicon. Here, state‐of‐the‐art low‐dimensional materials‐based transistors with small feature‐sizes are reviewed. Different from other works that mainly focus on material characteristics of a specific device structure, the discussed topics are utilizing device structure design including vertical structure and nano‐gate structure, and nanofabrication techniques to achieve small feature‐sizes of transistors. A comprehensive summary of these small feature‐size transistors is presented by illustrating their operation mechanism, relevant fabrication processes, and corresponding performance parameters. Besides, the role of small feature‐size transistors based on low‐dimensional materials in further reducing the small footprint is also clarified and their cutting‐edge applications are highlighted. Finally, a comparison and analysis between state‐of‐art transistors is made, as well as a glimpse into the future research trajectory of low dimensional materials‐based small feature‐size transistors is briefly outlined. [ABSTRACT FROM AUTHOR]

The advent of generative AI has profoundly influenced contemporary design, offering a cost-effective method for creating a wide array of digital elements through Artificial Intelligence Generated Content (AIGC). This innovation signifies a pivotal change in how humans collaborate with machines in the design process, necessitating new adaptations in product styling workflows. Unfortunately, a clear and practical design process has not yet been established, despite the pioneering efforts of several leaders in the product design domain who have begun to incorporate AIGC technology. This study aims to integrate AIGC with product styling design to enhance workflow efficiency and explore new dimensions of human-machine collaboration. Leveraging an ethnographic research methodology, we comprehensively analyzed the AIGC and product design communities. Building upon this foundation, we propose an AIGC-enabled product design methodology. Based on our findings, we developed an AIGC-enabled product design technique, which we then tested in practical scenarios through specific design cases. Our results demonstrate the methodology’s effectiveness in improving the product styling design workflow. Additionally, this study points toward new pathways for human-machine collaboration within the context of AI creation, shedding light on potential avenues for integrating AIGC more broadly in the product design field. [ABSTRACT FROM AUTHOR]

The operation and control of electric power grids is becoming increasingly challenging owing to the integration of numerous diverse nonlinear control strategies for subcontrollers situated at various locations within the grid. Some of these sub-controllers have degrading effects on each other when not coordinated for effective operation. This paper proposes a simple technique for designing a coordinated control scheme for the sub-controllers to boost the global transient stability of the power grid. The proposed approach relies on the coordination of second order sliding mode decentralized steam valve, excitation and SSSC adaptive controllers. The impact of the coordinated control design approach has been investigated through simulations in different power system fault contingencies. A comparative evaluation of the proposed strategy with existing techniques in the literature demonstrates its effectiveness and superiority, especially in terms of swiftness and robustness to disturbances and uncertainties. [ABSTRACT FROM AUTHOR]

Introduction: A prosthetic limb technology has grown tremendously in the past few years, offering hope for increased functioning and better quality of life to people with upper limb amputation. However, the phenomenon of prosthetic rejection remains a challenge, particularly among paediatric users because of the prosthesis-related factors in functionality and appearance as well as the training and prosthetics services. Aim: One solution is to involve an Occupational therapist (OT), engineer (3D printed prosthesis expert), prosthesis user (experienced child), and their parent in designing the prosthesis. However, these collaborations have not been implemented as intended in the engineering field. Hence, this current study aimed to report on a comprehensive study protocol based on 3-corner collaborative design in order to develop and improve three-dimensional (3D) printed upper limb prosthesis design and a home-based self-care training module. Methods: The 3D upper limb prosthesis and training module was designed using a 3-corner collaborative design (participatory design approach). The participatory design process (involved experienced children with transradial deficiency; parent; OT and engineer) and data collection techniques included semi-structured interviews, participant observation, the Delphi technique, and face-to-face discussion. Discussion: The 3-corner collaborative design (participatory design approach) process helped us design an interactive platform to design a new 3D printed upper limb prosthesis features such as sizes, weight, control, and obtaining information on training that possible to manufacture tailor-made, customized, and personalized parts according to the users' deficiency; making them more suitable for the development of prostheses for each user, which must be customized. [ABSTRACT FROM AUTHOR]

This article aims to assess the usability of selected map portals with a checklist. The methods employed allowed the author to conduct user experience tests from a longer temporal perspective against a retrospective analysis of the evolution of design techniques for presenting spatial data online. The author performed user experience tests on three versions of Tomice Municipality's geoportal available on the Internet. The desktop and mobile laboratory tests were performed by fourteen experts following a test scenario. The study employs the exploratory approach, inspection method, and System Usability Scale (SUS). The author calculated the Geoportal Overall Quality (GOQ) index to better illustrate the relationships among the subjective perceptions of the usability quality of the three geoportals. The usability results were juxtaposed with performance measurements. Normalised and aggregated results of user experience demonstrated that the expert assessments of the usability of geoportals G1 and G3 on mobile devices were similar despite significant development differences. The overall results under the employed research design have confirmed that geoportal G2 offers the lowest usability in both mobile and desktop modes. The study has demonstrated that some websites can retain usability even considering the dynamic advances in hardware and software despite their design, which is perceived as outdated today. Users still expect well-performing and quick map applications, even if this means limited functionality and usability. Moreover, the results indirectly show that the past resolution of the 'large raster problem' led to the aggravation of the issue of 'large scripts'. [ABSTRACT FROM AUTHOR]

Photocatalysis is a promising technology for efficient sewage treatment, and designing a reactor with a stable loading technique is crucial for achieving long-term stability. However, there is a need to improve the current state of the art in both reactor design and loading techniques to ensure reliable and efficient performance. In this study, we propose an innovative solution by employing polydimethylsiloxane as a bonding layer on a substrate of 3D-printed polyacrylic resin. By means of mechanical extrusion, the active layer interacts with the bonding layer, ensuring a stable loading of the active layer onto the substrate. Simultaneously, 3D printing technology is utilized to construct a photocatalytic reactor resembling a "Kongming Lantern", guaranteeing both high activity and durability. The reactor exhibited remarkable performance in degrading organic dyes and eliminating microbes and displayed a satisfactory purification effect on real water samples. Most significantly, it maintained its catalytic activity even after 50 weeks of cyclic degradation. This study contributes to the development of improved photocatalysis technologies for long-term sewage treatment applications. [ABSTRACT FROM AUTHOR]

The floating‐gate transistor is commonly employed as a non‐volatile memory device, leveraging a floating node at its gate to store electrical charge over extended periods. This stored charge effectively alters the threshold voltage of the transistor. Utilizing standard CMOS technologies, floating‐gate transistors can be designed and fabricated using conventional CMOS processes. This study focuses on characterizing the performance of a PMOS‐based floating‐gate transistor, specifically fabricated using the open‐source Skywater 130 nm process. The modulation of charge on the floating node is explored through both hot‐electron injection and Fowler–Nordheim tunnelling, providing insight into the resolution of these programming mechanisms. Additionally, the study includes a preliminary analysis of the retention time of the programmed charge in these devices. This work contributes to the open‐source electronics community by detailing the design and programming techniques of floating‐gate transistors developed with an open‐source process design kit, and makes the corresponding FG cell designs available for public use. [ABSTRACT FROM AUTHOR]

This paper constructs a nonlinear iterative filtering framework based on a neural network prediction model. It uses recurrent neural networks (RNNs) to achieve accurate regression of complex maneuvering target dynamic models and integrates them into the nonlinear iterative filtering system via Unscented Transformation (UT). In constructing the neural network prediction model, the Temporal Convolutional Network (TCN) modules that capture long-term dependencies and the Long Short-Term Memory (LSTM) modules that selectively forget non-essential information were utilized to achieve accurate regression of the maneuvering models. When embedding the neural network prediction model, this paper proposes a method for extracting Sigma points using the UT transformation by 'unfolding' multi-sequence vectors and explores design techniques for the time sliding window length of recurrent neural networks. Ultimately, an intelligent tracking algorithm based on unscented filtering, called TCN-LSTM-UKF, was developed, effectively addressing the difficulties of constructing models and transition delays under high-maneuvering conditions and significantly improving the tracking performance of highly maneuvering targets. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusion The COVID‐19 pandemic has not only tested the resilience of public health systems but also underscored the criticality of allocative choices on health resources. These choices, however, are not confined to health emergencies but are integral to public health decisions, which inherently grapple with limited resources. In this context, physicians play a pivotal role as the architects of clinical actions in various scenarios. Therefore, doctors are called upon to make their decisions by considering not only the criteria of clinical appropriateness but also the ethical aspects linked, in particular, to the principle of justice. Indeed, the assessment of the effectiveness of a treatment for a particular patient must be balanced against criteria of equity and justice for the whole. To be fully applied, the principle of justice presupposes the use of economic evaluation techniques designed to drive the organisation decisions by effectiveness and efficiency.The present paper aims to empirically analyse whether and to what extent economic evaluation is known and used by doctors in healthcare decision‐making and, therefore, what the most widespread approaches are used in such processes.In particular, this paper intends to present the results of an empirical study on a sample of doctors registered with the Order of Physicians in Lombardy (Italy), one of the areas most affected by the COVID‐19 pandemic.The research reveals a particular awareness of the criticality of allocation issues accompanied by a lack of knowledge of the economic evaluation techniques or, more broadly, by an almost total disuse of financial criteria. The main reasons are doctors’ need for more knowledge of these tools and insufficient availability of economic information at the country system level.In the conclusion, we propose some suggestions to facilitate the transition to more current decision‐making models consistent with the characteristics of more advanced national healthcare contexts. [ABSTRACT FROM AUTHOR]

In classical graph theory, the minimal spanning tree (MST) is a subgraph that lacks cycles and efficiently connects every vertex by utilizing edges with the minimum weights. The computation of a minimum spanning tree for a graph has been a pervasive problem over time. However, in practical scenarios, uncertainty often arises in the form of fuzzy edge weights, leading to the emergence of the Fuzzy Minimum Spanning Tree (FMST). This specialized approach is adept at managing the inherent uncertainty present in edge weights within a fuzzy graph, a situation commonly encountered in real-world applications. This study introduces the initial optimization approach for the Minimum Spanning Tree Problem within the context of interval-valued fermatean neutrosophic domain. The proposed solution involves the adaptation of the Dhouib-Matrix-MSTP (DM-MSTP) method, an innovative technique designed for optimal resolution. The DM-MSTP method operates by employing a column-row navigation strategy through the adjacency matrix. To the best of our knowledge, instances of this specific problem have not been addressed previously. To address this gap, a case study is generated, providing a comprehensive application of the novel DM-MSTP method with detailed insights into its functionality and efficacy. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive overview of Gallium nitride (GaN)-based power amplifier (PA) design for various frequency bands. GaN-based technology has emerged as a promising alternative to traditional silicon-based amplifiers due to its superior performance characteristics, which are discussed in this paper. This paper also discusses the key design parameters and challenges associated with PA design. Various design techniques and topologies for GaN power amplifiers are explored besides addressing theoretical considerations of PA design along with a complete systematic design procedure for L-Band amplifier using the wolfspeed large signal GaN HEMT model. To further demonstrate the useful methodology, the designs of S-band and C-band PAs are also presented. GaN-based devices are very promising candidates for high-power applications. It is widely used in various high-power applications including communication and radar. [ABSTRACT FROM AUTHOR]

Object manipulation is one of the most fundamental tasks in 3D user interfaces. Compared with interacting with objects within reach, remote object manipulation is often more challenging, which is often an iterative process that need clutching. However, while there are many interaction techniques designed for manipulating remote objects, it is not well studied the effects of clutching mechanism on remote object manipulation tasks. In this paper, we present a controlled experiment to evaluate the effects of two clutching mechanisms (Normal Clutching vs. Easy Clutching) on 3-DOF translation, 3-DOF rotation and 6-DOF docking tasks under various tasks settings. The results show that easy clutching can significantly save more completion time and clutching time compared with Normal Clutching. In addition, the results also reveal that easy clutching can be more effective especially when dealing with hard tasks and long user-target distance. We also find that users prefer easy clutching over Normal Clutching, indicating that well designed clutching mechanism can effectively improve user experience in manipulation tasks. [ABSTRACT FROM AUTHOR]

Doping Sr has the potential to enhance bioceramic properties. However, controlling purity, Sr concentration, and properties is crucial. Therefore, precise evaluation of synthesis variables is essential, achieved through experimental design techniques. This study synthesized Sr-doped calcium silicate wollastonite using a Plackett–Burman design with 11 variables to identify key factors affecting synthesis yield and physical, structural, and chemical attributes for tissue engineering. Results indicate that the strontium proportion significantly impacts material properties, affecting porosity, surface area, and pore volume. Moreover, observations reveal that calcination temperature contributes to heightened crystallinity and strontium doping. Adjusting calcium and strontium precursor concentrations while reducing the silicon to calcium and strontium ratio improves efficiency crystallinity, purity, and promotes the formation of the preferred β-CaSiO 3 phase. Overall, consistent and reproducible findings provide valuable insights into the variables influencing the process and facilitate optimization for future ceramic synthesis. [Display omitted] [ABSTRACT FROM AUTHOR]

Homomorphic encryption (HE) is an innovative privacy protection technique supporting homomorphic addition and multiplication. It has been widely applied in the applications of peer-to-peer networks, such as secure data sharing and privacy-preserving search. Existing HE schemes can be roughly categorized into partially HE and fully HE (FHE). The former is computationally efficient but only supports either additive or multiplicative homomorphic operations. The latter can simultaneously support both additive and multiplicative operations, but the corresponding computational costs are intensive. Recently, some works leverage trusted execution environment (TEE) to optimize the efficiency of FHE. However, they suffer from the limitations of ciphertext expansion and the strong trust assumption for TEE. To address these limitations, we present a new fully homomorphic encryption scheme named Paillier FHE (PFHE) by employing TEE to extend the additive Paillier HE to support multiplicative operations and further optimizing the computational efficiency, where TEE is assumed to be semi-honest to avoid the strong trust assumption. Specifically, we first design a Paillier multiplication protocol (PMUL) to achieve the ciphertext multiplication without bootstrapping. Based on the protocol, we utilize the packing technique to design a Paillier inner product protocol (PVMUL) and a Paillier matrix multiplication protocol (PMMUL) to support the inner product and matrix multiplication operations efficiently. Moreover, we provide the detailed security analysis for our protocols. We compare our PFHE with typical fully homomorphic encryption libraries by experiments, and at the same security level, our scheme demonstrates significant advantages. [ABSTRACT FROM AUTHOR]

Flexible electrochemical sensors can adhere to any bendable surface with conformal contact, enabling continuous data monitoring without compromising the surface's dynamics. Among various materials that have been explored for flexible electronics, metal–organic frameworks (MOFs) exhibit dynamic responses to physical and chemical signals, offering new opportunities for flexible electrochemical sensing technologies. This review aims to explore the role of electrocatalysis in MOF films specifically designed for flexible electrochemical sensing applications, with a focus on their design, fabrication techniques, and applications. We systematically categorize the design and fabrication techniques used in preparing MOF films, including in situ growth, layer-by-layer assembly, and polymer-assisted strategies. The implications of MOF-based flexible electrochemical sensors are examined in the context of wearable devices, environmental monitoring, and healthcare diagnostics. Future research is anticipated to shift from traditional microcrystalline powder synthesis to MOF thin-film deposition, which is expected to not only enhance the performance of MOFs in flexible electronics but also improve sensing efficiency and reliability, paving the way for more robust and versatile sensor technologies. [ABSTRACT FROM AUTHOR]

Molecular field-coupled nanocomputing (molFCN) encodes information in the molecule charge distribution and elaborates it through electrostatic coupling. Despite the advantageous sub-nanometric size and low-power dissipation, only a few attempts have been made to validate the technology experimentally. One of the obstacles is the difficulty in measuring molecule charges to validate information encoding or integrate molFCN with complementary-metal-oxide-semiconductor (CMOS). In this work, we propose a paradigm preserving the advantages of molFCN, which exploits the position of waiving molecules to augment the information encoding. We validate the paradigm, named bend-boosted molFCN, with density functional theory using 6-(ferrocenyl)hexanethiol cations. We demonstrate that the encoded information can be electrically read by constituting a molecular junction. The paradigm is compatible with the charge-based molFCN, thus acting as a readout system. The obtained results favor the experimental assessment of the molFCN principle through scanning probe microscopy techniques and the design of molFCN-CMOS heterogeneous circuits. [ABSTRACT FROM AUTHOR]

Many sustainable products require innovative design techniques but the same materials as regular products. In practice, whether pooling the material procurement orders via procurement sharing can be a strategic decision when an OEM produces both sustainable and regular products. In this paper, we formulate a multi-tier production system comprising of an OEM, a CM, and two material suppliers, and study two typical strategies: (1) procurement sharing, where the procurement functions of the sustainable and regular products are outsourced to the CM, and (2) independent procurement, where the OEM independently procures materials for the sustainable product. We solve the four-stage-four-player optimisation problem and find that the change of the market potential of the sustainable product heavily determines the OEM's overall procurement cost, and consequently the procurement sharing decisions. Under independent procurement, the wholesale prices of the sustainable and regular products show opposite characteristics when the market potential of the sustainable product varies, because the two suppliers have opposite pricing incentives. We derive three interactive effects that alter the OEM's procurement sharing incentives, which makes the OEM prefer independent procurement only when the market potential of the sustainable product is in a moderate range. [ABSTRACT FROM AUTHOR]

The diagnostic accuracy and reliability of an unsupervised electrocardiogram (ECG) analysis system entirely depend on the response of ECG preprocessing stage. Unfortunately, ECG signal analysis faces the challenge of getting distorted by various noises and artifacts (physiological and non-physiological origin). Thus, designing a denoising technique capable of dealing with different noises in real time is challenging, so selecting a noise analysis model is particularly important. Based on the extensive survey of state-of-the-art techniques, it is noticed that all the denoising techniques are designed with an implicit assumption that noises distorting ECG signals are of Gaussian nature and therefore, are based on the Gaussian distribution noise analysis model. However, in practical scenarios, noises may not always have a Gaussian nature. Therefore, this paper puts forward a non-Gaussian α -stable distribution model for noise analysis from the perspective of ECG signal analysis. This distribution model encompasses Gaussian distribution as a special case. From rigorous simulations and analytical studies, this research offers statistical proof that the α -stable distribution noise model may effectively capture background noises corrupting ECG signals. Ultimately, the effectiveness of R-peak detection techniques and deep learning models is evaluated in the presence of two types of noise: Gaussian distribution and α -stable distribution. Finally, through intensive simulation studies, it is discovered that relying on the assumption of Gaussian background noise can be misleading when the actual noise follows a non-Gaussian α -stable nature. [ABSTRACT FROM AUTHOR]

Internal flue gas recirculation (IFGR) is one of the most effective techniques for NOx reduction in boilers. Previous studies mainly focused on premixed combustion; however, the NOx formation principles in non-premixed methane/air flames are still unclear. This work aims to investigate the NOx formation mechanisms in non-premixed methane combustion at various IFGR rates. A series of three-dimensional computational fluid dynamics (CFD) simulations with detailed mechanisms was conducted. The results show that NOx is generated below 30 mg/m3 for IFGR rates higher than 17.7%, corresponding to the oxygen concentration in the oxidant mixture below 0.15. In high IFGR rates, the incompletely mixed oxidants and the presence of the central recirculation zones weakens the NOx reduction performance. Influenced by the decreased temperature by IFGR, the generation of thermal NOx is largely eliminated from 66 to 1 mg/m3. Prompt NOx contributes more than thermal NOx for the IFGR rates above 12.2%. The reaction range of thermal NOx is found moving upstream toward the nozzle with the axial distance of 0.1 m at most. IFGR gradually reduces prompt NOx but its spatial reaction ranges are hardly influenced. IFGR has no obvious effects both on the reaction rates and ranges on the minorities of the N2O and the NNH routes. This work connects the IFGR rates and the NOx formation pathways in non-premixed methane combustion, and highlights the importance of eliminating prompt NOx to achieve low-NOx combustion rather than sole NOx suppression method, which can provide foundation for designing low-NOx techniques. [ABSTRACT FROM AUTHOR]

Product development durations are being drastically reduced, thanks, amongst other reasons, to the use of design automation techniques. But this trend is observed in large companies and to a much lesser extent in SMEs. This article seeks to research the possibility of finding suitable automation technologies for this type of enterprises. Automating the development of commercial offers in SMEs can be a good starting point to the change in this trend. Focusing on this objective, the necessary requirements that a tool of this type must have are established. Different models of assistants have been developed and analysed on different products, deducing from their results an ideal system architecture and methodology. This solution is based on design tables, a technology that links data from a spreadsheet, implements the company’s design process, with parameters of a three-dimensional CAD model, which represents the solution. The rest of the documents that constitute the commercial offer and the possibility of linking them with verification tools are derived from this design core. The main conclusion is the current viability of this method, anticipating the improvement of many aspects, mainly highlighting the link with the rest of the life cycle phases through interoperability tools. [ABSTRACT FROM AUTHOR]

Data-driven machine learning techniques can be useful for the rapid evaluation of material properties in extreme environments, particularly in cases where direct access to the materials is not possible. Such problems occur in high-throughput material screening and material design approaches where many candidates may not be amenable to direct experimental examination. In this paper, we perform an exhaustive examination of the applicability of machine learning for the estimation of isothermal shock compression properties, specifically the shock Hugoniot, for diverse material systems. A comprehensive analysis is conducted where effects of scarce data, variances in source data, feature choices, and model choices are systematically explored. New modeling strategies are introduced based on feature engineering, including a feature augmentation approach, to mitigate the effects of scarce data. The findings show significant promise of machine learning techniques for design and discovery of materials suited for shock compression applications. [ABSTRACT FROM AUTHOR]

Short-pulsed lasers can treat dermal pigmented lesions through selective photothermolysis. The irradiated light experiences multiple scattering by the skin and is absorbed by abnormal melanosomes as well as by normal blood vessels above the target. Because the fluence is extremely high, the absorbed light can cause thermal damage to the adjacent tissue components, leading to complications. To minimize radiant exposure and reduce the risk of burns, a model of the melanosome-disruption threshold fluence (MDTF) has been developed that accounts for the light-propagation efficiency in the skin. However, the light-propagation efficiency is attenuated because of multiple scattering, which limits the extent to which the radiant exposure required for treatment can be reduced. Here, this study demonstrates the principle of melanosome disruption with localized thermal damage through a turbid medium by ultralow radiant exposure of a short-pulsed laser. The MDTF model was combined with a wavefront-shaping technique to design an irradiation condition that can increase the light-propagation efficiency to the target. Under this irradiation condition, melanosomes were disrupted at a radiant exposure 25 times lower than the minimal value used in conventional laser treatments. Furthermore, almost no thermal damage to the skin was confirmed through a numerical simulation. These experimental and numerical results show the potential for noninvasive melanosome disruption and may lead to the improvement of the safety of short-pulsed laser treatment. [ABSTRACT FROM AUTHOR]