Design Goals Research Articles

Phenomenological Modeling of Antibody Response from Vaccine Strain Composition

The elicitation of broadly neutralizing antibodies (bnAbs) is a major goal of vaccine design for highly mutable pathogens, such as influenza, HIV, and coronavirus. Although many rational vaccine design strategies for eliciting bnAbs have been devised, their efficacies need to be evaluated in preclinical animal models and in clinical trials. To improve outcomes for such vaccines, it would be useful to develop methods that can predict vaccine efficacies against arbitrary pathogen variants. As a step in this direction, here, we describe a simple biologically motivated model of antibody reactivity elicited by nanoparticle-based vaccines using only antigen amino acid sequences, parametrized with a small sample of experimental antibody binding data from influenza or SARS-CoV-2 nanoparticle vaccinations. Results: The model is able to recapitulate the experimental data to within experimental uncertainty, is relatively insensitive to the choice of the parametrization/training set, and provides qualitative predictions about the antigenic epitopes exploited by the vaccine, which are testable by experiment. For the mosaic nanoparticle vaccines considered here, model results suggest indirectly that the sera obtained from vaccinated mice contain bnAbs, rather than simply different strain-specific Abs. Although the present model was motivated by nanoparticle vaccines, we also apply it to a mutlivalent mRNA flu vaccination study, and demonstrate good recapitulation of experimental results. This suggests that the model formalism is, in principle, sufficiently flexible to accommodate different vaccination strategies. Finally, we show how the model could be used to rank the efficacies of vaccines with different antigen compositions. Conclusion: Overall, this study suggests that simple models of vaccine efficacy parametrized with modest amounts of experimental data could be used to compare the effectiveness of designed vaccines.

Chinese herbal medicine recognition network based on knowledge distillation and cross-attention

In order to reduce the number of parameters in the Chinese herbal medicine recognition model while maintaining accuracy, this paper takes 20 classes of Chinese herbs as the research object and proposes a recognition network based on knowledge distillation and cross-attention – ShuffleCANet (ShuffleNet and Cross-Attention). Firstly, transfer learning was used for experiments on 20 classic networks, and DenseNet and RegNet were selected as dual teacher models. Then, considering the parameter count and recognition accuracy, ShuffleNet was determined as the student model, and a new cross-attention mechanism was proposed. This cross-attention model replaces Conv5 in ShuffleNet to achieve the goal of lightweight design while maintaining accuracy. Finally, experiments on the public dataset NB-TCM-CHM showed that the accuracy (ACC) and F1_score of the proposed ShuffleCANet model reached 98.8%, with only 128.66M model parameters. Compared with the baseline model ShuffleNet, the parameters are reduced by nearly 50%, but the accuracy is improved by about 1.3%, proving this method’s effectiveness.

Exploring Engagement Opportunities for Autistic Children: Using AAC as a Controller in a Wizard-of-Oz Coloring Game

Autistic children face significant challenges in vocal communication and social interaction, often leading to social isolation. There is evidence that Augmentative and Alternative Communication (AAC) offers support to mitigate these challenges, enabling them to communicate with non-vocal means through forms of AAC, such as speech-generation devices (SGDs). However, the adoption and use of SGDs are hindered by several factors, including the large amount of practice required to learn to use SGDs and the limited options for highly engaging social learning contexts. Our study introduces the novel approach of using SGDs as game controller for digital and interactive games. With three design goals guiding our work, we conducted a Wizard-of-Oz formative case study with five participants aged 3-5 years, who were learning to use their SGD. We simulated a digital coloring game, integrating the speech-generated output of the participant's SGD to function as the game's controller. From this case study, we observed that all participants engaged with the game using their SGD for at least one turn, and two participants also engaged in emerging joint attention responses with the game and game's facilitator. This paper discusses these findings and contributes directions for future research, with suggestions for the design of future SGD-controlled games and exploration of social connection and collaboration between autistic children who use AAC and their caregivers, siblings, and peers.

Prompting for products: investigating design space exploration strategies for text-to-image generative models

Abstract Text-to-image models are enabling efficient design space exploration, rapidly generating images from text prompts. However, many generative AI tools are imperfect for product design applications as they are not built for the goals and requirements of product design. The unclear link between text input and image output further complicates their application. This work empirically investigates design space exploration strategies that can successfully yield product images that are feasible, novel and aesthetic – three common goals in product design. Specifically, users’ actions within the global and local editing modes, including their time spent, prompt length, mono versus multi-criteria prompts, and goal orientation of prompts, are analyzed. Key findings reveal the pivotal role of mono versus multi-criteria and goal orientation of prompts in achieving specific design goals over time and prompt length. The study recommends prioritizing the use of multi-criteria prompts for feasibility and novelty during global editing while favoring mono-criteria prompts for aesthetics during local editing. Overall, this article underscores the nuanced relationship between the AI-driven text-to-image models and their effectiveness in product design, urging designers to carefully structure prompts during different editing modes to better meet the unique demands of product design.

Research on Green and Low-Carbon Design of Hainan Rural Residences Based on VR Technology

In order to realize the goal of green and low-carbon design of Hainan rural residence, this paper, based on VR technology, researches and designs the Hoppe algorithm of scattered point cloud data, bidirectional reflective distribution function (BRDF) of data processing and real-time realistic rendering technology in the process of structured mesh generation, and real-time realistic rendering technology in the indoor visualization design system of residential house. Secondly, by screening the experimental scenes, the differences in the perception of the screened scenes are analyzed from the perspectives of public gender, education and profession. Finally, the application effect of VR technology in Hainan rural residential design is compared and analyzed. The results show that the ratings of males on the four indicators in the LP group are 3.08, 3.37, 3.23 and 3.49, respectively, and the ratings of females are 3, 3.68, 3.51 and 3.78, respectively.The ratings of undergraduates on each indicator are higher than those of postgraduates and above in the PP group, the DP group and the SE group. The scores of all indicators on the LP group of the professional population were lower than those of the non-professional population. The use of VR technology can allow users to produce visual, auditory, and tactile changes at the same time, but also to display static and dynamic space, and to do the interaction of the scene. Its display effect is better than other programs. The average satisfaction of the public with the 8 aspects of VR technology design residential houses is greater than 80%. Obviously, VR technology has advantages in the green and low-carbon design of Hainan rural residence.

BASICS OF DESIGNING CHEMICAL EQUIPMENT FOR ENERGY-EFFICIENT CHEMICAL PRODUCTIONS – GENERAL CHARACTERISTICS AND CAPABILITIES

The materials of the article consider the possibilities for studying the goals and objectives of the discipline in order to form in students the necessary knowledge about the basics of designing equipment for energy-saving chemical productions: detailed consideration of the scientific justification; analysis, general characteristics and features of equipment design; selection of types of analysis methods for solving problems using innovative methods and programs, their features; study of possible causes of equipment inconsistency with the design goal and methods for their prediction. When writing the article, the experience of teaching the discipline “Fundamentals of Designing Chemical Production Equipment” at the National Technical University “Kharkiv Polytechnic Institute” at the Department of Integrated Technologies, Processes and Devices in 2022-2024 was used. Complex systems for determining the components of the discipline have determined the competence and quality of the material, and the issues considered are overlooked through the prism of one's own creative perception, which makes the material especially valuable. Examples and some features of possible learning solutions are presented, which are based on experimental data on the development of mechanisms for identifying and classifying processes and their scientific justification in the form of intellectual property objects.

Public Library Interior Design with Biophilic Concept in Sleman Regency

The Sleman Regency Library is an educational facility established by the government to provide educational services and fulfill the government's responsibility to enlighten the nation. It also reflects the vision and mission of Sleman Regency, articulated through the Smart City concept, which aims to manage resources effectively and efficiently, maximize public services, and support sustainable development. However, the library in Sleman still requires design improvements, as it currently has a rigid design, with a need for better space planning, circulation, and additional facilities to meet visitor needs and enhance their comfort. The interior design is based on David K. Ballast’s 1992 design method. This public library design incorporates the Biophilic concept, which aims to enhance human well-being both physically and mentally while fostering a positive connection between people and nature. The goal of this interior design is to improve the quality of the library as an educational space, make it appealing to the community, and optimize space planning and facilities to better meet public needs.

Tolerance allocation of mechanical assemblies including thermal deformation: A machine learning – based method

Tolerance allocation is one of the prominent tools to achieve the optimal manufacturing cost and the best performance for mechanical assemblies. Variations in dimensions and geometry shape due to different working temperatures for various components within an assembly can make initially assigned tolerances ineffective. Therefore, it is necessary to consider the component’s deformation caused by thermal gradients during the tolerance design. In this paper, a new method is presented for optimal tolerance allocation of mechanical assemblies under thermal deformation. First, the system’s temperature working conditions and tolerance design goals are specified, followed by the finite element simulation of the assembly at the desired working temperature. Then, the assembly equation is determined according to the complexity of the problem by using analytical methods and some machine learning (ML) algorithms such as XGBoost. The optimal tolerance design is formulated into a constrained multi-objective optimization problem. Then, to obtain the Pareto front of optimal tolerances, the multi-objective optimization is solved by the NSGA-II algorithm. Finally, to illustrate the capability of the proposed method, two case studies are considered, and obtained results from the presented method and conventional approaches are compared.

A 2x2 Mimo Microstrip Patch Antenna Design For X-Band Applications Using Inverted Array Orientation Approach

Objective: The main goal of this research is to design and simulate a unique 2x2 multiple-input and multiple-output, (MIMO) Rectangular Microstrip Patch antenna (RMPA) using an inverted array orientation approach with keen interest in improving the radiation efficiency and performance characteristics of the X- band based antenna. Theoretical Framework: This work integrates principles from Electromagnetic theory, communication theory, and basic Microstrip antenna design concepts. The framework is built upon crucial design goals such as radiation efficiency, reliability, element orientation and compactness of the antenna elements. Method: This research adopted a design and simulation approach. All the antenna design modules and analysis were conducted using MATLAB R2023b simulator. Firstly, this work modelled and designed a unique single-element RMPA after iterations and optimisations of the antenna parameters to achieve enhanced performance. The achieved single element was used to model a 2x2 MIMO antenna with specified element spacing. The design applied an inverted element array orientation and streamlined feed trace mechanism to achieve a high gain and enhanced radiation efficiency. Results and Discussion: The unique antenna design recorded a return loss of -15.2 dB, directivity of 7.33 dB, bandwidth of 484.8 MHz, gain of 7.16 dB, VSWR of 1.41, and radiation efficiency of 96.2%. Further analysis on the designed MIMO antenna to ascertain the mutual coupling effect showed that Envelope Correlation Coefficient (ECC) values remained below 0.2 within the 10 GHz frequency band, representing good diversity and significantly reducing the mutual coupling effect between array elements. The Diversity Gain (DG) of 9.87 and 9.84 dB were obtained. These values are near the optimal value of 10 dB, which is diversity for MIMO applications. Research Implications: The findings show the viability of the proposed design based on the performance metrics considered when compared to the previously designed Microstrip Patch Antennas (MPA). Thus, the designed MIMO antenna is suggested for use in embedded wireless communication devices within 8-12 GHz frequency bands for X-band applications such as radar systems and WiMAX. Originality/Value: This study presents an innovative approach to improving the radiation efficiency of a designed 2x2 MIMO antenna. The work showed that enhancement of the radiation efficiency has a direct effect on the mutual coupling, which this work applied inverted orientation and streamlined feed trace method to minimise.

Modal analysis and lightweight design of key components of the anchor windlass

To improve the rationality of the mechanical design of traditional ship anchor windlass, based on modal analysis, lightweight research was conducted on key components. Taking the first-order natural frequency as the constraint condition, topological optimization design was carried out for the base, and size optimization design based on the response surface algorithm was carried out for the anchor chain wheel. On the premise of meeting the overall structural strength and stiffness requirements of the anchor windlass, its weight was reduced as much as possible. Through the finite element analysis and strength check of the optimized model, it was verified that the optimization results met the design requirements. The research shows that the weight reduction rate of the base reached 13.34 %, and the weight reduction rate of the anchor sprocket reached 10.5 %. After analysis and verification, the optimized structure can still meet the overall mechanical performance of the anchor windlass and achieve the expected design goal, which also provides an important reference for the structural optimization and lightweight research of other ship equipment.

Epihiper-A high performance computational modeling framework to support epidemic science.

This paper describes Epihiper, a state-of-the-art, high performance computational modeling framework for epidemic science. The Epihiper modeling framework supports custom disease models, and can simulate epidemics over dynamic, large-scale networks while supporting modulation of the epidemic evolution through a set of user-programmable interventions. The nodes and edges of the social-contact network have customizable sets of static and dynamic attributes which allow the user to specify intervention target sets at a very fine-grained level; these also permit the network to be updated in response to nonpharmaceutical interventions, such as school closures. The execution of interventions is governed by trigger conditions, which are Boolean expressions formed using any of Epihiper's primitives (e.g. the current time, transmissibility) and user-defined sets (e.g. people with work activities). Rich expressiveness, extensibility, and high-performance computing responsiveness were central design goals to ensure that the framework could effectively target realistic scenarios at the scale and detail required to support the large computational designs needed by state and federal public health policymakers in their efforts to plan and respond in the event of epidemics. The modeling framework has been used to support the CDC Scenario Modeling Hub for COVID-19 response, and was a part of a hybrid high-performance cloud system that was nominated as a finalist for the 2021 ACM Gordon Bell Special Prize for high performance computing-based COVID-19 Research.

HeritageSite AR: Design and Evaluation of a Mobile Augmented Reality Exploration Game for a Chinese Heritage Site

This article explores the use of a mobile Augmented Reality (AR) exploration game to enhance immersive storytelling and enrich cultural experiences. Specifically, we present the prototype design and evaluation of HeritageSite AR, an AR exploration game for a Chinese heritage site known as the Relics of Arhat Monastery and Twin Pagoda , or Shuangta . To develop the AR game for use in heritage sites, we employed a holistic approach, beginning with a review of technical means for cultural application development. We then conducted semi-structured interviews with domain experts and administered an online survey to identify user requirements and design goals, which informed our prototype design. An evaluation study showed positive feedback regarding the impact of game design on meaningful and playful cultural heritage site experience and identified areas for potential refinements in future iterations. We discuss the implications and lessons learned for our future work, which may also interest researchers and practitioners exploring the use of AR technologies and game design in heritage site contexts.

The Story of Building Hedy: A Programming Language with Cognitive Science in Mind

This autoethnographic paper is part of a special issue trying to answer the question “How to design or choose languages for programming novices?” I will describe howmy programming language Hedy was created, how the initial design goals were formed, how my perspectives on learning and teaching changed along the way, and how Hedy changed with it. The paper also discusses how the Hedy community came to be. Hedy was initially made for my own classroom and teaching, but quickly attracted a community, which I learned a lot from. This special issue has given me a unique opportunity, after 5 years of working on Hedy, to reflect on the process and to learn from it myself, and will hopefully also allow other programming language designers to learn from.

AI-assisted design of lightweight and strong 3D-printed wheels for electric vehicles.

The automotive industry is undergoing a transformative shift towards electric vehicles (EVs), driven by environmental concerns and technological advancements. One critical aspect of EV design is the development of lightweight yet robust components, including 3D vehicle wheels. This research explores the implementation of generative models in Computer-Aided Design (CAD) systems to optimize the design of 3D vehicle wheels for electric vehicles. Through the use of generative design and additive manufacturing, we aim to create vehicle wheels that are energy-efficient, aesthetically pleasing, and structurally sound. Electric vehicles are gaining popularity due to their environmental benefits and reduced operating costs, making lightweight and strong wheels an important design goal. This research proposes a novel approach for designing lightweight and strong 3D vehicle wheels for EVs using generative models. The proposed approach involves the following steps: collect and prepare data, choose a generative model architecture, train the generative model, and generate new wheel designs. The approach methods show potential to revolutionize the design and manufacturing of lightweight and strong 3D-printed wheels for electric vehicles. In conclusion, generative models can be used to design and optimize wheel designs, making it possible to create safer, more efficient, and more cost-effective wheels.

BiG-Fed: Bilevel Optimization Enhanced Graph-Aided Federated Learning

In federated learning (FL), due to the non-i.i.d. nature of distributedly owned local datasets, personalization is an important design goal. In this paper, we investigate FL scenarios in which data owners are related by a network topology (e.g., traffic prediction based on sensor networks). Existing personalized FL approaches cannot take this information into account. To address this limitation, we propose the Bilevel Optimization enhanced Graph-aided Federated Learning (BiG-Fed) approach. The inner weights enable local tasks to evolve towards personalization, and the outer shared weights on the server side target the non-i.i.d problem enabling individual tasks to evolve towards a global constraint space. To the best of our knowledge, BiG-Fed is the first bilevel optimization technique to enable FL approaches to cope with two nested optimization tasks at the FL server and FL clients simultaneously. Theoretical analysis shows that BiG-Fed is guaranteed to converge in an efficient manner. Extensive experiments on both synthetic and real-world data demonstrate significant superior performance of BiG-Fed over seven state-of-the-art methods.

Universal NIR-II fluorescence image enhancement via square and square root network

The second near-infrared (NIR-II) fluorescence imaging has attracted widespread attention from researchers due to its powerful advantage of assisting doctors in real-time tumor removal during surgery. Light has different penetration capabilities in different bands. Although NIR-IIb window (1,500-1,700 nm) imaging is clearer than NIR-IIa window (1,000-1,300 nm), there are no effective molecular probes for NIR-IIb clinical transformation. NIR-II images are rich in variety, including animals, tissues, etc., and the huge differences in structure also bring difficulties to image enhancement. In order to solve the above problems, we propose a universal NIR-II fluorescence image enhancement model based on arbitrary style transfer, and simultaneously achieve the quality enhancement of multiple types of NIR-IIa fluorescence images. The goal of this model design is to completely preserve the important information of the original image to prevent artifacts and meet the high demand for real-time imaging during NIR-II surgery. To this end, we design a fusion network based on the calculation method of square-square root-sign assignment, in which the content information of NIR-IIa is integrated into the style representation of NIR-IIb to increase the maintenance of the original content structure, so that the stylized feature map tends to show the content. In addition, we propose an attention matching loss, which extracts key structural information through the attention mechanism and maintains the structure of the enhanced image consistent with the original image. Extensive experiments demonstrate that our proposed model has a great advantage in maintaining the original content information, with the SSIM of 0.625 and the content loss of 0.279 compared to the original images. In addition, the quality of enhanced images is satisfactory, with the PSNR of 31.20 and the SSIM of 0.501 compared to the real images.

Lessons Learnt from Testing Three Spatial Observation Tools in a Hospital Ward.

Observation tools are increasingly important in healthcare building design research. They enable us to understand how the design of healthcare buildings affects users' health and organisational outcomes. Observations are used in case studies and pre- and post-occupancy evaluations. However, these case studies often struggle to pinpoint the specific design features responsible for observed outcomes. Additionally, harnessing collective knowledge from multiple cases can be challenging. This underscores the need for structured observations. The paper describes the lessons learnt from using three spatial observation tools as part of a study to assess a hospital ward design. Its goal is to reflect on the purpose, usability, advantages, disadvantages, and future improvements of these tools and to offer insights into their potential to support research on hospital ward design. The first tool, by the Centre for Health Design, utilizes a checklist-style matrix to evaluate the design of patient rooms, assessing 17 Evidence Based Design goals, including patient safety, worker safety and effectiveness, quality of care, patient experience, and organizational performance. The second tool is a one-time observation tool, a structured spatial inventory aimed at documenting design features throughout the entire hospital ward, covering elements such as room size, access to daylight, natural elements, furniture, safety measures, and more. It can be combined with the third tool; the recurring observation tool, which focuses on monitoring usage, users, their activities, and behaviour across various types of environments, including patient, staff, care, and supportive spaces. The last two observation tools were developed for the research project, adapting the Smart Sustainable Offices method for healthcare environments. This paper emphasizes the importance of selecting suitable observation tools for specific research objectives, providing guidance for working with observations and conducting pre-and post-studies. While not aimed at validating observation tools, it offers reflections to aid in development and use of observation tools. Finally, documenting spatial contexts enhances understanding of study findings, and reusing observation tools enables cross-study comparisons, with future potential for leveraging artificial intelligence.

A Single Acoustic Quantity Index as Part of an Early-Stage Digitalized Procedure for the Restoration of Baroque Theatres to Be Used as Multipurpose Spaces

Historic theatres with a horseshoe shape, the so-called baroque theatres, constitute an architectural heritage and are of enormous importance. For these reasons, this paper aimed to identify a single acoustic quantity index as part of an early-stage digitalized procedure to improve the management of the complexity of their restoration process, both better preserving the original room acoustic field and making it variable for new different uses of the theatre space. The procedure introduces technical policies and design tools in a BIM execution plan (BEP) and is supported by a digitalization that inserts the restoration of theatres into industry 4.0. This choice was taken according to the new design goals and the new Procurement Code Directives, which underlie the use of digital technologies in this context. The described acoustic single number quantity, called a “multipurpose index”, summarizes the main room acoustic goals for when a baroque theatre is used as a multipurpose space after renovation, specifying and better controlling the requested room acoustic quality for people other than acoustics specialists, such as theater directors, and more generally for the management. As an example of this possible transition, the case study of “Teatro Ristori” is presented.

Using Collective Intelligence to Develop Design Requirements for a Complex Intervention for Advance Care Planning in the Community.

Engaging people in advance care planning is a challenging systemic problem that requires a social innovation approach and a conceptual framework to guide behavioural and social change efforts. To identify stakeholders' perspectives on barriers to advance care planning engagement, options for overcoming these barriers, and user needs. The findings will inform the design of a health behaviour change intervention for engaging older adults (50+) in advance care planning. To advance co-production and intervention design goals, the study used collective intelligence and scenario-based design methods. Following a systematic stakeholder analysis, 22 participants were recruited to three online collective intelligence sessions. The socioecological perspective informed framing of integrated findings and specifying factors at the individual, interpersonal, service, and system levels. Identified barriers (n = 109) were grouped into seven categories: (i) Psychological, (ii) Advance Care Planning Literacy, (iii) Interpersonal and Interprofessional, (iv) Service-Related, (v) Resources and Supports, (vi) Advance Care Planning Process and Methods, (vii) Cultural and Societal. Stakeholders generated 222 options for overcoming these barriers and specified 230 service user needs. The need to change perceptions of advance care planning, increase psychological readiness, and target advance care planning literacy was highlighted (individual-level). Timely, focused, and meaningful interaction between the key ACP actors must be facilitated using creative strategies (interpersonal-level). Need- and value-based services, including high quality resources, support systems, and infrastructure, should be co-designed (service-level). Cultural and societal transformation is required (system-level). Findings integration offered insight into the complexity of the design context and problem situation and identified directions for context-specific advance care planning intervention development. The use of design thinking methodologies is recommended for the next phase of complex intervention development. The study presents a roadmap of actions required from policy-makers, practitioners, and researchers to ensure the design of adequate advance care planning interventions. Quality of reporting was assured by adherence to Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines (International Journal for Quality in Health Care, 19, 2007, 349). Patient and public representatives participated in the collective intelligence sessions. Members of the All Ireland Institute of Hospice and Palliative Care Voices4Care facilitated that process. Findings from the first CI session (involving patients and caregivers) informed the content, format, and methods used in subsequent CI sessions.

Advanced design and analysis of dual element MIMO antenna for Ultra-Wideband Applications

This investigation uses the Genetic Optimization Method to convert a wide-band MIMO antenna into a UWB (3.1GHz–10.6 GHz) MIMO antenna. Initially, a 22 × 42, mm2 wideband 2X2 MIMO antenna was designed using commercial Flame Retardant-4 material. The structure of the antenna patch was designed using half-circular forms on the half-ground plane. The designed MIMO antenna operates throughout a large frequency range of 4.8–9.8 GHz. While it was successful in achieving broad band characteristics, this MIMO antenna was unable to reach ultra-wide band characteristics. The MIMO antenna was operated in UWB ranges by a parametric study, which indicated that the resonating characteristics can be significantly modified by inserting a rectangular slot into the ground plane. Throughout the operational range, it was important to be concerned about improved gain and good isolation. Accordingly, optimization was carried out in order to accomplish the essential, multi-objective goals. The difficult multi-objective design goal is now reduced to an optimization challenge by means of genetic algorithm based random search. One of the performance goals that this optimization strategy aimed to fulfil was an increase in isolation to –20 dB across the entire Ultra-Wideband, with S11 being below –10 dB from 3.1 to 10.6 GHz. It is recommended to randomly select the parameters from their respective ranges for this work. This led to the selection of an optimizer based on random searches. In the operating range, the UWB has a respectable gain of 4 dB to 6 dB and increased isolation to –20 dB, according to the genetic algorithm optimizer’s execution of the predefined multiple-objective task.