Design Sensitivity Research Articles

A Matched Design for Causal Inference With Survey Data: Evaluation of Medical Marijuana Legalization in Kentucky and Tennessee.

A concern surrounding marijuana legalization is that driving after marijuana use may become more prevalent. Survey data are valuable for estimating policy effects, however their observational nature and unequal sampling probabilities create challenges for causal inference. To estimate population-level effects using survey data, we propose a matched design and implement sensitivity analyses to quantify how robust conclusions are to unmeasured confounding. Both theoretical justification and simulation studies are presented. We found no support that marijuana legalization increased tolerant behaviors and attitudes toward driving after marijuana use, and these conclusions seem moderately robust to unmeasuredconfounding.

Design Process, Evaluation, and Sensitivity Analysis of an Activated Carbon Production Plant from Single-use Plastic Waste at the National University of Engineering

Objective: The objective of this study is to investigate the design process, economic evaluation, and sensitivity analysis for the construction of an activated carbon production plant from single-use plastic waste at the National University of Engineering. This project aims to transform plastic waste into a high-value-added product, thereby contributing to sustainability and aligning with circular economy principles. Theoretical Framework: The theoretical framework covers concepts related to the circular economy and sustainable waste management, emphasizing the need to reduce environmental impact through innovative alternatives such as recycling PET into activated carbon. Previous studies on pyrolysis and thermal or chemical activation of plastics for conversion into high-value materials are cited, establishing a solid foundation to contextualize the activated carbon production process. Method: The methodology adopted for this research includes a technical and economic study design based on the assessment of processes and equipment required for activated carbon production. An experimental approach is proposed, wherein plastic waste is collected, shredded, washed, dried, carbonized, activated, and finally packaged. Data collection involved detailed calculations of investment, energy consumption, and mass and energy balances for each stage of the production process. Results and Discussion: The results revealed that the project is economically viable, with a Net Present Value (NPV) of 59,733 USD and an Internal Rate of Return (IRR) of 13%. In the discussion, the project’s profitability is contextualized through a sensitivity analysis evaluating different scenarios of exchange rate and sale price. This analysis confirms that, in optimistic scenarios, the IRR can reach up to 341%, reducing the payback period to less than a year. Research Implications: The practical implications of this research include the potential to implement a circular economy model in educational institutions, promoting sustainability and efficient waste management. Theoretically, the study contributes to the field of plastic waste valorization through its transformation into activated carbon, which could positively impact sectors such as environmental management and industrial recycling. Originality/Value: This study contributes to the literature by presenting an innovative approach for plastic waste valorization into activated carbon within an educational institution, using pyrolysis and activation processes in a circular economy context. The relevance of this research lies in its practical applicability in academic settings and its potential impact on reducing plastic waste.

Quantifying the Impact of Career Preparedness Programs for Saudi Students with Disabilities

This study examines the impact of job readiness programs on Saudi students with impairments, utilizing a quantitative research methodology. Using a purposive selection strategy, people were selected, and a standardized survey questionnaire was used to gather data on program participation, perceived skill development, cultural factors, and employment outcomes. Descriptive data, t-tests, regression analyses, correlation analyses, and ANCOVA have been employed for data analysis. The findings track strong relationships between application components, perceived skill gain, and employment outcomes. Regression analyses indicate that both the extent of program engagement and the perceived learning of skills significantly impact employment outcomes. The ANCOVA analysis suggests that application involvement has a greater influence on employment outcomes compared to cultural factors, however, both factors contribute to the overall model. Suggestions entail addressing cultural sensitivity in program design, prolonging program durations, and cultivating a supportive environment for inclusive training and career advancement. The purpose of these insights is to provide information for improving career readiness programs for students with impairments in Saudi Arabia. Received: 9 June 2024 / Accepted: 28 October 2024 / Published: 05 November 2024

Rationalised experiment design for parameter estimation with sensitivity clustering

Quantitative experiments are essential for investigating, uncovering, and confirming our understanding of complex systems, necessitating the use of effective and robust experimental designs. Despite generally outperforming other approaches, the broader adoption of model-based design of experiments (MBDoE) has been hindered by oversimplified assumptions and computational overhead. To address this, we present PARameter SEnsitivity Clustering (PARSEC), an MBDoE framework that identifies informative measurable combinations through parameter sensitivity (PS) clustering. We combined PARSEC with a new variant of Approximate Bayesian Computation-based parameter estimation for rapid, automated assessment and ranking of experiment designs. Using two kinetic model systems with distinct dynamical features, we show that PARSEC-based experiments improve the parameter estimation of a complex system. By its inherent formulation, PARSEC can account for experimental restrictions and parameter variability. Moreover, we demonstrate that there is a strong correlation between sample size and the optimal number of PS clusters in PARSEC, offering a novel method to determine the ideal sampling for experiments. This validates our argument for employing parameter sensitivity in experiment design and illustrates the potential to leverage both model architecture and system dynamics to effectively explore the experimental design space.

Differential evolution-based topology optimization using Karhunen-Loève expansion

Topology optimization is a widely adopted structural optimization approach that aims to maximize desired performance based on mathematical and physical principles. Gradient-based methods are common for obtaining optimal configurations; however, they struggle with problems involving numerous local optima and non-differentiable problems, which prevent the derivation of design sensitivity. To address these issues, this study explores the application of the Success History-Based Differential Evolution with Linear Population Size Reduction and Semi-Parameter Adaptation, which is regarded as LSHADE-SPA algorithm, known for its strong search capabilities. Nevertheless, its computational cost makes it impractical for topology optimization, especially as the number of design variables increases. To overcome this challenge, a novel structure representation method utilizing the Karhunen-Loève (KL) expansion is constructed. Applying truncated KL expansion instead of conventional density methods to represent structural configurations reduces the number of design variables. This article introduces a differential evolution-based topology optimization method utilizing truncated KL expansion and validates its effectiveness through applications in various structural and fluid problems. The method is particularly suited to highly nonlinear problems, such as negative Poisson's ratio structures and micro-mixer designs. The findings here indicate that differential evolution with truncated KL expansion can serve as an efficient and robust topology optimization method, proving particularly effective for solving optimization problems that are challenging for conventional gradient-based approaches. Notably, the proposed methodology not only delivers superior results but also alleviates computational burdens, thereby advancing the prospects of topology optimization in various engineering applications.

Hybrid Refractive and Diffractive Testing Method for Free-Form Convex Mirror in High-Resolution Remote-Sensing Cameras

The development of high-resolution and large field of view remote-sensing cameras is inextricably linked to the application of free-form mirrors. The free-form mirror offers higher design of freedom and is more effective at correcting aberrations in optical systems. The surface shape error of a free-form mirror directly affects the imaging quality of remote-sensing cameras. Consequently, a high-precision free-form mirror detection method is of paramount importance. For the convex free-form surface mirror with a large aperture, a hybrid refractive and diffractive testing method combining computer-generated holography (CGH) and spherical mirrors for high-precision null test is proposed in this paper. When comparing the effect of error and the detection sensitivity of different designs, the results showed that the influence of the system error is reduced by about 42% and the sensitivity is increased by more than 2.6 times. The proposed method can achieve higher testing accuracy and represents an effective and feasible approach for the surface shape detection method.

Reusable gallium-based electrochemical sensor for efficient glucose detection

Among wearable sensing devices, electrochemical sensors are overwhelming in biochemical detection due to their simple design but high sensitivity. Most electrochemical sensors are disposable, which significantly impairs the service life. Here we present a reusable gallium (Ga)-based multilayer electrochemical glucose biosensor to extend noninvasive monitoring of glucose in the interstitial fluid. This multilayer sensor includes Ga as a conductive interconnector, poly(3,4-ethylenedioxythiophene) as an electrode layer to prevent oxidation and metal leakage, a nano-Pt layer to enhance the electrochemical properties, and a nano-Prussian blue layer for reducing the hydrogen peroxide reduction potential. The biosensor can be renewed without causing damage to its overall structure by automatically eliminating the modified nanocomposites via the electrolysis-induced bubbles. The biosensor showed high sensitivity (24.6 μA mM−1 cm−2), wide linear range (0.01–26 mM), excellent stability (i.e., pH, long-term use) and superior selectivity, that is comparable to those of the current electrochemical tools for glucose detection. More importantly, incorporated with the reverse iontophoresis, the Ga-based hybrid sensor was applied as a skin patch on rat for the in vivo noninvasive and continuous monitoring of interstitial fluid glucose. The results showed a good correlation with that measured by blood glucometer. As a whole, this Ga-based electrochemical biosensor should endow new functions like biochemical analysis in biofluids for Ga-based bioelectronic sensing devices, in which almost are physical sensors. We believe that the reusability of electrochemically controllable processes may further inspire the development of more integrated and long-term stable Ga-based biosensing devices.

The Jade Gateway to Exergaming: How Socio-Cultural Factors Shape Exergaming Among East Asian Older Adults

Exergaming, blending exercise and gaming, improves the physical and mental health of older adults. We currently do not fully know the factors that drive older adults to either engage in or abstain from exergaming. Large-scale studies investigating this are still scarce, particularly those studying East Asian older adults. To address this, we interviewed 64 older adults from China, Japan, and South Korea about their attitudes toward exergames. Most participants viewed exergames with a positive inquisitiveness. However, socio-cultural factors can obstruct this curiosity. Our study shows that perceptions of aging, lifestyle, the presence of support networks, and the cultural relevance of game mechanics are the crucial factors influencing their exergame engagement. Thus, we stress the value of socio-cultural sensitivity in game design and urge the HCI community to adopt more diverse design practices. We provide several design suggestions for creating more culturally approachable exergames.

Ultrasensitive Ultrasoft Buckled Crack‐Based Sensor for Respiration Measurement and Enhanced Human–Machine Interface

Wearable strain sensors have transformed the real‐time monitoring of health conditions and human–machine interactions. However, recently developed wearable strain sensors exhibit several limitations. For example, when a sensor is designed with high sensitivity to detect strain, it struggles to accurately measuring the deformation of low‐stiffness materials like skin. Additionally, finding the optimal balance between sensitivity, durability, hysteresis, and strain range in sensor design is challenging. To address these challenges, a Buckled, Ultrasoft, Crack‐based, Large strain, EpiDermal (BUCKLED) sensor is developed. This sensor integrates the benefits of soft structure engineering with high sensitivity of crack‐based sensing mechanisms to ensure optimal skin deformation measurements. The BUCKLED sensor exhibits significant improvements in compliance (18 500 mm N−1), stretchability (100%), hysteresis (2%), durability (10 000 cycles with 100% strain), and force sensitivity () owing to its buckled shape, confirming its ability to detect subtle movements with enhanced accuracy. The sensor's high compliance allows it to accurately measure low‐stiffness objects, ensuring reliable performance. Furthermore, the sensor's tunability is demonstrating its effectiveness in applications such as respiratory monitoring, facial expression recognition, and silent speech interfaces. Consequently, the proposed sensor is versatile and holds great potential for a wide range of sensing applications.

Flexible Electromagnetic Sensor with Inkjet-Printed Silver Nanoparticles on PET Substrate for Chemical and Biomedical Applications.

For this article, a low-cost, compact, and flexible inkjet-printed electromagnetic sensor was investigated for its chemical and biomedical applications. The investigated sensor design was used to estimate variations in the concentration of chemicals (ethanol and methanol) and biochemicals (hydrocortisone-a chemical derivative of cortisol, a biomarker of stress and cardiovascular effects). The proposed design's sensitivity was further improved by carefully choosing the frequency range (0.5-4 GHz), so that the analyzed samples showed approximately linear variations in their dielectric properties. The dielectric properties were measured using a vector network analyzer (VNA) and an Agilent 85070E Dielectric Probe Kit. The sensor design had a resonant frequency at 2.2 GHz when investigated without samples, and a consistent shift in resonant frequency was observed, with variation in the concentrations of the investigated chemicals. The sensitivity of the designed sensor is decent and is comparable to its non-flexible counterparts. Furthermore, the simulation and measured results were in agreement and were comparable to similar investigated sensor prototypes based on non-flexible Rogers substrates (Rogers RO4003C) and Rogers Droid/RT 5880), demonstrating true potential for chemical, biomedical applications, and healthcare.

Navigating HIV research among criminalized gender minority populations in Uganda: qualitative insights and lessons learned from novice researchers

BackgroundTransgender individuals often face stigma, discrimination, and various forms of abuse, which negatively impact their mental and physical health. They face a significantly greater risk of HIV, with a higher prevalence than the general population. Despite these challenges, transgender people have limited access to healthcare due to violence, legal barriers, and societal stigma, further exacerbated in countries like Uganda, where transgender identities are criminalized. Therefore, this study explored the lived experiences of HIV researchers working with gender minority populations in criminalizing contexts.MethodsThis was an interpretative phenomenological analysis (IPA) qualitative study. Twelve (12) research team members at all levels were involved in the study. Participants had less than five years of involvement in HIV research among gender minority populations. Data were collected using field notes, reflective journals, documentation from daily team debriefing sessions, and semi-structured interviews. The analysis used NVivo software.ResultsPositive experiences, barriers, and challenges were captured. The positive experiences were ‘respecting cultural diversity’, ‘expanding networks’, ‘addressing misconceptions’ and ‘finding allies’. The barriers included ‘experiencing stigma’, ‘lengthy research processes’, ‘feeling isolated’, ‘fearing for personal safety’, ‘unexpected logistical costs’, and ‘criminalization of sexual and gender minorities’. The key themes that emerged from the lessons learned were: ‘dealing with gatekeepers’, ‘diversity and sensitivity training’, ‘leveraging networks’, ’meaningful community engagement’, ‘reflexivity’, ‘ensuring safety’, ‘equal partnership’, ‘giving feedback’ and ‘awareness of legal implications’.ConclusionsThis study highlights the importance of cultural sensitivity, community engagement, and reflexivity in research design and implementation. The findings emphasize the need for innovative strategies to navigate legal, social, and logistical barriers that researchers and participants face. Despite these challenges, the study demonstrates that meaningful collaboration with community members and building trust can significantly enhance the research process and outcomes. Future research should continue to explore these strategies while addressing ethical and safety concerns.

Effects of color-typeface congruence on product evaluation

Product packaging is important for attracting consumer attention and creating expectations regarding a product, both of which can influence product evaluation. A key issue in package design is the coordinated selection of multiple package elements. This study investigates whether and when congruence between color and typeface in a product package can improve product evaluation. To this end, we analyze color and typeface on product packages based on semiotics and marketing, propose a conceptual model for the role of color-typeface congruence, and conduct three empirical studies that test the hypotheses implied from our model. Study 1 shows that color-typeface congruence is positively related to product evaluation. In Study 2, processing fluency is identified as a link between color-typeface congruence and product evaluation. Finally, Study 3 establishes the moderating role of design sensitivity in the relationship between processing fluency and product evaluation. Our findings contribute to more effective marketing communication for marketers and retailers through packaging.

Implementation of Skogestad’s Internal Model Control Rule in Tuning Proportional-Integral Controllers for Two-Input and Two-Output Systems Considering Individual Controller Performance Trade-off

Abstract In industrial plants, tuning of decentralized Proportional-Integral-Derivative feedback (PID) controllers in Multiple-Input and Multiple-Output (MIMO) systems is a complex problem, due to input and output interactions, that must be done to ensure individual control objectives are met, while system being sufficiently robust. In this study, a two-input and two-output (TITO) PI controller tuning algorithm was developed considering controller performance prioritization given performance trade-offs, expressed as the novel Individual Controller Performance Trade-off Coefficient (ICPTC), and system robustness, expressed as sensitivity peaks from the generalized Nyquist stability plot. Simplified effective open-loop transfer functions (EOTFs) of the two input-output channels were derived and used along with Skogestad’s Internal Model Control (SIMC) to calculate PI controller gains. Extensive simulations using Wood-Berry (WB) and Vinante-Luyben (VL) distillation column models were made to observe how the sensitivity peaks behave across the simulations, which was then used as the basis of the developed tuning algorithm. A simplified tuning algorithm, which requires less information compared to the main algorithm, was also derived. A mapping algorithm was also created, allowing specific controller gains from other studies to be mapped to an equivalent set of controller gains in the algorithm’s search field. The effectiveness of the three algorithms were tested using Wardle-Wood distillation column (WW) and Xiong and Cai (XC) process models. It was demonstrated using the main algorithm that there is a trade-off between controller performances when ICPTC is varied, at different values of design sensitivity peaks between 1.96 to 4. The usefulness of the simplified tuning and mapping algorithms were also illustrated in the study. This study is potentially useful in tuning TITO PI controllers in industrial plants, where meeting individual control objectives while maintaining robustness is more important than optimizing overall control performance.

Co-Designing Caregiver Support Groups: Rapid Review with a Non-Profit Organization

ABSTRACT This rapid review aims to synthesize literature on co-designing support groups for caregivers of older adults, focusing on how caregivers are involved in the co-design process. This synthesis is undertaken in collaboration with the Saskatoon Council on Aging to inform the development of caregiver support groups. Guided by the Cochrane Rapid Reviews Methods Group, this review follows a streamlined evidence synthesis approach. Our search strategy was run on June 5, 2023, on the MEDLINE, EMBASE, CINAHL, Cochrane CENTRAL, and PsycINFO databases. Three studies met the inclusion criteria, highlighting the importance of comprehensive initiatives and peer support. Key findings include the necessity of tailoring support groups to caregivers’ specific needs and preferences, the combination of online and offline support, and the importance of cultural sensitivity in service design. Methodological approaches to co-design varied across studies, with each emphasizing the importance of iterative feedback loops and engagement with diverse caregiver groups. The review underscores the value of co-designed support groups in effectively meeting caregivers’ needs. Engaging caregivers in the design process ensures that support groups are tailored to their requirements and empowers them to shape their support systems. The insights from this review can guide future co-design efforts, enhancing caregiver support initiatives.

Single- and Multilevel Perspectives on Covariate Selection in Randomized Intervention Studies on Student Achievement

Well-chosen covariates boost the design sensitivity of individually and cluster-randomized trials. We provide guidance on covariate selection generating an extensive compilation of single- and multilevel design parameters on student achievement. Embedded in psychometric heuristics, we analyzed (a) covariate types of varying bandwidth-fidelity, namely domain-identical (IP), cross-domain (CP), and fluid intelligence (Gf) pretests, as well as sociodemographic characteristics (SC); (b) covariate combinations quantifying incremental validities of CP, Gf, and/or SC beyond IP; and (c) covariate time lags of 1–7 years, testing validity degradation in IP, CP, and Gf. Estimates from six German samples (1868 ≤ N ≤ 10,543) covering various outcome domains across grades 1–12 were meta-analyzed and included in precision simulations. Results varied widely by grade level, domain, and hierarchical level. In general, IP outperformed CP, which slightly outperformed Gf and SC. Benefits from coupling IP with CP, Gf, and/or SC were small. IP appeared most affected by temporal validity decay. Findings are applied in illustrative scenarios of study planning and enriched by comprehensive Online Supplemental Material (OSM) accessible via the Open Science Framework (OSF; https://osf.io/nhx4w).

Time-harmonic finite element model for brushless doubly-fed induction machine in natural operating mode

The natural mode of operation for the brushless doubly-fed induction machine is a particular instance of synchronism at a so-called natural rotor velocity when one stator winding is powered by an AC and the other by a DC voltage source. Consequently, in addition to the rotating magnetic field, there exists a magnetic field that is fixed to the stator frame of reference. Analysis in this specific mode is essential as the natural velocity arises from the choice of pole numbers, thereby determining machine efficiency. However, this presents a significant challenge when it comes to mathematical modeling using complex-valued steady-state models through either equivalent-circuit or finite element analysis. This paper presents a study on the extension of the recently-proposed steady-state complex-valued finite element model for the brushless doubly-fed induction machine to enable its application in the natural operating mode. A high correlation with the data obtained from a time-stepping model is obtained for the extended model when subjected to both low and high levels of saturation of the magnetic circuit. This extension makes the whole approach applicable in all operating conditions and modes of the brushless doubly-fed induction machine. Considering the nearly two orders of magnitude lower computational costs associated with analysis via the proposed model compared to time-stepping analysis, it is particularly useful in scenarios that involve extensive computations and require multiple cases to be considered such as design sensitivity analysis, topology optimization or a connection with machine learning techniques.

Uncertainty quantification of acoustic metamaterial bandgaps with stochastic material properties and geometric defects

Acoustic metamaterials are a subject of increasing study and utility. Through designed combinations of geometries with material properties, acoustic metamaterials can be built to arbitrarily manipulate acoustic waves for various applications. Despite the theoretical advances in this field, however, acoustic metamaterials have seen limited penetration into industry and commercial use. This is largely due to the difficulty of manufacturing the intricate geometries that are integral to their function and the sensitivity of metamaterial designs to material batch variability and manufacturing defects. Capturing the effects of stochastic material properties and geometric defects requires empirical testing of manufactured samples, but this can quickly become prohibitively expensive with higher precision requirements or with an increasing number of input variables. This paper demonstrates how uncertainty quantification techniques, and more specifically the use of polynomial chaos expansions and spectral projections, can be used to greatly reduce sampling needs for characterizing acoustic metamaterial dispersion curves. With a novel method of encoding geometric defects in a 1D, interpretable, resolution-independent way, our uncertainty quantification approach allows for both stochastic material properties and geometric defects to be considered simultaneously. Two to three orders of magnitude sampling reductions down to ∼100 and ∼101 were achieved in 1D and 7D input space scenarios, respectively. Remarkably, this reduction in sampling was possible while preserving accurate output probability distributions of the metamaterial performance characteristics (bandgap size and location).

Cultivating ethics sensitivity in design: Impact of integrating ethics within K-12 digital design education

Cultivating ethics sensitivity in design: Impact of integrating ethics within K-12 digital design education

Programming Fast DNA Amplifier Circuits with Versatile Toehold Exchange Pathway.

DNA amplifier circuits establish powerful tools to dynamically control molecular assembly for computation, sensing, and biological applications. However, the slow reaction speed remains a major barrier to their practical utility. Here, diverse fast DNA amplifier circuits termed toehold exchange polymerization (TEP) and toehold exchange catalysis (TEC) using toehold exchange-mediated assembly as a fundamental mechanism are built. Both TEP and TEC with a duplex and a hairpin can respond within minutes to diverse nucleic acid inputs with high fidelity. In addition, the circuits can amplify live-cell signals for fluorescence imaging target RNA dynamics and discriminating different cell lines. Compared with existing DNA circuits that involve time scales of hours for transducing small signals, TEP and TEC exhibit much faster dynamics, simpler design, and comparable sensitivity. These features make TEP and TEC promising platforms to develop programmable nucleic acid tools and devices and to create fast sensing and processing systems, amenable to wide practical applications.

Finite Element Analysis of Skin Deformation and Puncture for Microneedle Array Design.

The mechanics of microneedle insertion have thus far been studied in a limited manner. Previous work has focused on buckling and failure of microneedle devices, while providing little insight into skin deformation, puncture, and the final positioning of needle tips under full microneedle arrays. The current study aims to develop a numerical approach capable of evaluating deformation and puncture conditions for full microneedle array designs. The analysis included a series of finite element submodels used to calibrate the microneedle-epidermal interface for failure properties using traction-separation laws. The single needle model is validated using experimental data and imaging, including results from a customized nanoindentation procedure to measure loads and displacements during microneedle insertion. Upon validation, full microneedle arrays are implemented in a 3 D finite element model and a design framework is developed, allowing evaluation of different design variables (i.e. needle shape, material, spacing) with respect to outputs relevant to successful microneedle performance. Results from the model include skin deformation, force to puncture, penetration depth, and the punctured state at each microneedle tip. In addition to microneedle parameters, patient parameters such as subcutaneous tissue thickness are included to evaluate the sensitivity of different microneedle designs to expected patient and anatomical region variability.