17 research outputs found
Story Culture Framework: A Cross Cultural Study
No full textDigital storytelling has emerged as a powerful tool to engage with communities in the last few years. However, little attention has been paid for the challenges and failures faced around using digital storytelling as a tool. The paper talks about digital storytelling as a participatory method explored within three culturally different transforming communities. The key finding in the study is revealing the importance of the preliminary activities that helped design the innovative methods. In this paper the author assesses how the participatory research methods, such as story interviews, digital storytelling workshops and story kits, helped to gather participants’ personal experiences within the three chosen communities. The study proposes story culture framework a technique to explore cross cultural communities using stories as its principal focus. The author concludes by highlighting challenges for HCI researchers working with digital technologies and cross cultural communities
A Novel Relay Station Deployment Scheme for beyond 4G Multi-hop Network
No full textAbstractIn Long Term Evolution-Advanced (LTE-A) and Worldwide interoperability for microwave access (WiMAX) systems, the coverage area, signal strength and transmission quality are affected by white Gaussian noise, shadowing, wireless interference etc. This effect can be decreased by using more number of evolved NodeBs (eNB), but problem is that eNBs are expensive and it will increase network cost. Relay Stations (RS) are less expensive than eNBs, hence we go for RS deployment instead of eNBs. Thus this paper proposes a cost effective deployment of RSs using dynamic cost based deployment of RS (DCDR) approach. This approach first analyse the impact parameters and then finds the dynamic weighting and network cost for different deployment combination. Simulation result shows that DCDR approach gives a cost effective solution for the deployment of RSs
A Novel Fuzzy Based Relay Node Deployment Scheme for Multi-hop Relay Network
No full textAbstractIn cellular communication, a multi-hop relay (MHR) network plays an important role by reducing the cost of deployment and extending the coverage area. To achieve high transmission rate and coverage, an efficient placement of relay nodes (RN) is needed in MHR network. In this paper, a suitable deployment scheme is proposed for the RNs to obtain high system performance. By using fuzzy logic, optimum deployment sites are selected for RNs, which results in better throughput and coverage. Simulation results shows that our proposed scheme gives a better throughput and coverage performance than the existing uniform clustering and joint base station and relay station placement (JBRP) scheme
Coarse-grained molecular dynamics simulations of mixtures of polysulfamides
No full textThis article was originally published in RSC Applied Polymers. The version of record is available at: https://doi.org/10.1039/D4LP00362D.
© 2025 The Author(s). Published by the Royal Society of Chemistry.
This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence (https://creativecommons.org/licenses/by-nc/3.0/).Polysulfamides are a new class of polymers that exhibit favorable chemical and physical properties, making them a sustainable alternative to commodity polymers like polyurea. To advance the fundamental understanding of this new class of polymers, Wu et al. [Z. Wu, J. W. Wu, Q. Michaudel and A. Jayaraman, Macromolecules, 2023, 56, 5033–5049]conducted experiments and coarse-grained (CG) molecular dynamics (MD) simulations to connect the polysulfamide backbone design to the assembled structure of polysulfamides due to hydrogen bonding between sulfamides. Their CG MD simulations qualitatively reproduced experimentally observed trends in crystallinity for analogous variations in polysulfamide backbone designs. To bring chemical specificity to this generic CG model of Wu et al. and to facilitate quantitative agreement with experiments in the future, in this work, we modify this older CG model of Wu et al. using structural information from atomistic simulations. Atomistic angle and dihedral distributions involving the sulfamide functional groups are used to modify the donor and acceptor bead positions in the new CG model. Using MD simulations with this new atomistically informed CG model, we confirm that we obtained the structural trends with varying polysulfamide backbone length, bulkiness, and non-uniformity of the segments in repeat units as seen in the previous work by Wu et al. These key structural trends are as follows: (a) shorter contour lengths of segments between sulfamide groups enhance H-bonding between sulfamides, (b) increased bulkiness in the segment hinders sulfamide–sulfamide H-bonding and reduces orientational order among chains in the assembled structure, and (c) non-uniformity in the segments along the backbone does not affect orientational order in the assembled structure. While the trends qualitatively matched between the two models, we observe quantitatively higher positional order and lower orientational order among the assembled chains in the new CG model as compared to the older CG model. This difference in local chain packing arises from a change in the donor–acceptor H-bonding pattern between the two models. In this work, we also use the new CG model to study mixing and demixing in two types of mixtures of polysulfamides: one mixture has chains with varying segment lengths between sulfamide groups and another mixture has chains with different degrees of bulkiness in the backbone. We find that increasing dissimilarity (bulkiness or length) between the two types of chains promotes demixing despite the presence of sulfamide–sulfamide H-bonding interactions.The authors thank DOE Grant DE-SC0023264 for their financial support. The simulations in this paper were conducted on Bridges-2 at the Pittsburgh Supercomputing Center through the allocation NSF-funded ACCESS #MCB100140. The authors thank Dr. Quentin Michaudel, Dr. Ryan Hayward, Dr. Nitish Nair, Dr. Zijie Wu and Mr. Stephen Kronenberger for valuable input during this work
User experience and usability requirements of a physical activity smartphone application for wheelchair users with spinal cord injury
No full textData availability statement:
The quantitative datasets generated and/or analysed during the current study are available at https://doi.org/10.17633/rd.brunel.28524245.v1. The qualitative datasets generated and/or analysed during the current study are not publicly available because they contain information that could compromise participant privacy and/or consent.Supplemental material is available online at: https://www.tandfonline.com/doi/full/10.1080/17483107.2026.2628898# .Purpose:
Usability considerations for wheelchair users remain underexplored. This study evaluated usability requirements of a smartphone App (MvBii) for monitoring physical activity and sedentary behaviour in manual wheelchair users with spinal cord injury (SCI).
Materials and methods:
A mixed-methods design was adopted. Manual wheelchair users with SCI completed System Usability Scale, e-loyalty and user experience questionnaires, think-aloud sessions and scenario-based workshops. Six design and research evaluators undertook think-aloud sessions. Qualitative data was analysed thematically and mapped against heuristics.
Results:
Ten participants with SCI (C5-L1; three females) with a mean age of 51 ± 9 years took part. The App received positive ratings on e-loyalty (mean scores, 5.6 ± 1.51 to 6.10 ± 0.99 across items) and user experience (4.3 ± 1.03 to 5.93 ± 0.78) from participants with SCI. A novel heuristics principle was developed to explore “accessibility and inclusion” usability issues. Thematic analysis captured patterned meanings across tasks and heuristics including “Navigating with autonomy” (e.g., challenges with interface clarity and understanding terminology), “Language and representation” (e.g., simplifying using inclusive language and icons), and “Seeing progress not noise” (e.g., physical activity notifications that encouraged self-competition without external pressure).
Conclusions:
This study demonstrates the value of a mixed-methods approach to usability and heuristic evaluation for identifying effective, accessible and inclusive tailoring of physical activity Apps universally and for wheelchair users specifically. These findings can inform refinements to the MvBii app and provide broader insights for designing inclusive and effective mobile health Apps across diverse populations.
IMPLICATIONS FOR REHABILITATION:
• Wheelchair users with spinal cord injury demonstrated high intention to use the physical activity smartphone App.
• Key usability issues were identified that should be considered in physical activity Apps include interface clarity, terminology, and visual accessibility.
• A novel heuristic principle was proposed that will aid in effective design for accessible digital experiences.
• Recommendations for physical Apps for wheelchair users include enhanced customisation, inclusivity and simplified language.The author(s) reported there is no funding associated with the work featured in this article
Calculations of multipole transitions in Sn II for kilonova analysis
No full textThis article was originally published in The European Physical Journal D. The version of record is available at: https://doi.org/10.1140/epjd/s10053-023-00695-5. © The Author(s) 2023.We use the method that combines linearized coupled-cluster and configuration interaction approaches for calculating energy levels and multipole transition probabilities in singly ionized tin ions. We show that our calculated energies agree very well with the experimental data. We present probabilities of magnetic dipole and electric quadrupole transitions and use them for the analysis of the AT2017gfo kilonova emission spectra. This study demonstrates the importance and utility of accurate atomic data for forbidden transitions in the examination of future kilonova events.We thank M. G. Kozlov for the valuable discussions. This work was supported in part by the US NSF grant PHY-2012068. This research was supported in part through the use of DARWIN computing system: DARWIN—A Resource for Computational and Data-intensive Research at the University of Delaware and in the Delaware Region, Rudolf Eigenmann, Benjamin E. Bagozzi, Arthi Jayaraman, William Totten, and Cathy H. Wu, University of Delaware, 2021, URL: https://udspace.udel.edu/handle/19716/29071. The publication is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 491382106, and by the Open Access Publishing Fund of GSI Helmholtzzentrum fuer Schwerionenforschung.
Open Access funding enabled and organized by Projekt DEAL
Machine learning for analyzing atomic force microscopy (AFM) images generated from polymer blends
No full textThis article was originally published in Digital Discovery. The version of record is available at: https://doi.org/10.1039/D4DD00215F.
© 2024 The Author(s). Published by the Royal Society of Chemistry.
This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence (http://creativecommons.org/licenses/by-nc/3.0/).In this paper, we present a new machine learning (ML) workflow with unsupervised learning techniques to identify domains within atomic force microscopy (AFM) images obtained from polymer films. The goal of the workflow is to (i) identify the spatial location of two types of polymer domains with little to no manual intervention (Task 1) and (ii) calculate the domain size distributions, which in turn can help qualify the phase separated state of the material as macrophase or microphase ordered/disordered domains (Task 2). We briefly review existing approaches used in other fields – computer vision and signal processing – that can be applicable to the above tasks frequently encountered in the field of polymer science and engineering. We then test these approaches from computer vision and signal processing on the AFM image dataset to identify the strengths and limitations of each of these approaches for our first task. For our first domain segmentation task, we found that the workflow using discrete Fourier transform (DFT) or discrete cosine transform (DCT) with variance statistics as the feature works the best. The popular ResNet50 deep learning approach from the computer vision field exhibited relatively poorer performance in the domain segmentation task for our AFM images as compared to the DFT and DCT based workflows. For the second task, for each of the 144 input AFM images, we then used an existing Porespy Python package to calculate the domain size distribution from the output of that image from the DFT-based workflow. The information and open-source codes we share in this paper can serve as a guide for researchers in the fields of polymers and soft materials who need ML modeling and workflows for automated analyses of AFM images from polymer samples that may have crystalline/amorphous domains, sharp/rough interfaces between domains, or micro- or macro-phase separated domains.A. J. and A. P. are grateful for financial support from the Multi University Research Initiative (MURI) from the Army Research Office, Award Number W911NF2310260. Y. W. and X. G. are grateful for financial support from the Department of Energy under the award number of DE-SC0024432. A portion of this work was done at the Molecular Foundry, which is supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231
Using immersive technologies to facilitate location scouting in audiovisual media production: a user requirements study and proposed framework
No full textCopyright © The Author(s) 2022. In common with many industries, the audiovisual sector is likely to be transformed by real-time graphic engines in combination with immersive technologies such as Virtual Reality and Augmented Reality. This technological mix enables what is presently known as Virtual Production, introducing a new process to the audiovisual professional, capable of fostering creativity, collaboration, and decision making, while at the same time increasing efficiency. The potential for Virtual Production to transform workflows and creative processes within large-scale productions in the audiovisual sector is significant and includes the prospective introduction of new capabilities for remote co-creation of content. However, barriers to democratisation need to be overcome, particularly in relation to adoption of the technology by small and medium independent productions that generally have limited access to resources and technical knowledge. Following an extensive study of the current literature and involvement in the research of professionals working in the field through online interviews, this article documents a first step towards filling this gap by investigating Virtual Production adoption scenarios for small and medium independent productions. The primary aim is to design intuitive, engaging, and effective solutions to address the needs of Directors, Cinematographers, and Producers.
Thanks to the valuable time and experience of industry professionals, this study has gathered user requirements for a Virtual Production design solution capable of facilitating location scouting and pre-production. A novel framework for remote exploration of target locations within immersive environments, co-created with relevant stakeholders, is presented to lay the foundations of future co-design work.This work was supported by StoryFutures: Gateway Cluster Partnership for Audiovisual Digital Creativity (AH/S002758/1), a research and development grant by the Arts and Humanities Research Council (AHRC), UK
Lipohypertrophy in China: Prevalence, Risk Factors, Insulin Consumption, and Clinical Impact
No full textBackground: Lipohypertrophy (LH) is a complication of insulin therapy. We assessed LH prevalence, risk factors, insulin usage, and clinical and health economic effects in China. Methods: In four cities, 401 adult patients injecting insulin >= 1 year were surveyed for diabetes/insulin injection history and practices, pen needle reimbursement (PNR), and health resource utilization, followed by structured examination and HbA1c testing. Differences between those with and without LH were evaluated by Student's t-test or the Wilcoxon rank sum test. Insulin costs were calculated. Results: Patients were 59.6 +/- 11.5 years old; 50% male; 93.5% type 2 diabetes. LH prevalence was 53.1%. Compared to those without LH, patients with LH had higher body mass index (BMI; 26 vs. 24.8 kg/m(2)) and HbA1c (8.2% vs. 7.7% [66 vs. 61 mmol/mol]), took 11 IU (0.13 IU/kg or 31.7%) more insulin costing 1.0 (RMB 9.5 vs. 6.8) daily, reused PNs more times, and had less PNR (all P <= 0.003). LH patients correctly rotated injection sites less often (67.6% vs. 92.3%, P < 0.0001). By stepwise logistic regression, BMI, needle reuse frequency, and PNR remained modestly associated with LH prevalence (odds ratios [OR] <1.9; P <= 0.03); weight-adjusted insulin dose and incorrect site rotation showed ORs of nearly 7 and 8.4, respectively (P <= 0.001). Extrapolated to 9 million insulin-injecting patients in China and adjusted for therapy adherence, LH-related excess annual insulin consumption cost is estimated at nearly $297 million (RMB 2 billion). Conclusions: LH is common in China and associated with worse glycemic control, despite nearly one-third greater insulin consumption, with large cost implications. Proper injection technique education may reduce LH prevalence.BD (Becton, Dickinson Co., Inc.); PNsSCI(E)ARTICLE161-671
High Positive End-expiratory Pressure (PEEP) with Recruitment Maneuvers versus Low PEEP during General Anesthesia for Surgery: A Bayesian Individual Patient Data Meta-analysis of Three Randomized Clinical Trials
No full textBackground: The influence of high positive end-expiratory pressure (PEEP) with recruitment maneuvers on the occurrence of postoperative pulmonary complications after surgery is still not definitively established. Bayesian analysis can help to gain further insights from the available data and provide a probabilistic framework that is easier to interpret. Our objective was to estimate the posterior probability that the use of high PEEP with recruitment maneuvers is associated with reduced postoperative pulmonary complications in patients with intermediate-to-high risk under neutral, pessimistic, and optimistic expectations regarding the treatment effect. Methods: Multilevel Bayesian logistic regression analysis on individual patient data from three randomized clinical trials carried out on surgical patients at Intermediate-to-High Risk for postoperative pulmonary complications. The main outcome was the occurrence of postoperative pulmonary complications in the early postoperative period. We studied the effect of high PEEP with recruitment maneuvers versus Low PEEP Ventilation. Priors were chosen to reflect neutral, pessimistic, and optimistic expectations of the treatment effect. Results: Using a neutral, pessimistic, or optimistic prior, the posterior mean odds ratio (OR) for High PEEP with recruitment maneuvers compared to Low PEEP was 0.85 (95% Credible Interval [CrI] 0.71 to 1.02), 0.87 (0.72 to 1.04), and 0.86 (0.71 to 1.02), respectively. Regardless of prior beliefs, the posterior probability of experiencing a beneficial effect exceeded 90%. Subgroup analysis indicated a more pronounced effect in patients who underwent laparoscopy (OR: 0.67 [0.50 to 0.87]) and those at high risk for PPCs (OR: 0.80 [0.53 to 1.13]). Sensitivity analysis, considering severe postoperative pulmonary complications only or applying a different heterogeneity prior, yielded consistent results. Conclusion: High PEEP with recruitment maneuvers demonstrated a moderate reduction in the probability of PPC occurrence, with a high posterior probability of benefit observed consistently across various prior beliefs, particularly among patients who underwent laparoscopy
