154092 research outputs found
Sort by
A comparative study about the performance of multi-language tools in computation offloading scenarios
No full textComputational offloading is a common technique used to alleviate the limitations of mobile devices. However, the programming languages used in this process can be inefficient and resource intensive. Multi-language offloading enables computational offloading between processes written with different languages through gRPC with ProtocolBuffers framework. However, there are few published experiments with infrastructures supporting multi-language offloading. This paper evaluates multi-language offloading with two new frameworks: (i) gRPC with FlatBuffers and (ii) Apache Thrift. Tests involved offloading three tasks (sorting integers, multiplying matrices, and filtering images) to remote processes developed in Go, C++, or Java using the aforementioned frameworks. The results validate earlier findings, demonstrating the advantages of adopting a multi-language approach in computational offloading and the significant impact of the network performance, regardless of the framework employed. They also offered new insights, such as the weak performance of gRPC with Protocol Buffers, being the slowest framework in 81% and the most energy consuming in 78% of cases, while Apache Thrift was the fastest framework in 83% and the most energy efficient in 66% of scenarios. The study suggests that Go is the best language to build server processes among the three and Apache Thrift is the preferred framework for multi-language offloading. However, further studies are required with additional devices and programming languages to improve the external validity of this study.</p
Can unsupervised machine learning gain new insights into urodynamic pressure flow pattern analysis?
Full text linkObjectives: To explore the use of unsupervised machine learning (UML) to analyse segments of the pressure flow study (PFS) curve after maximum flow, and subsequently to analyse the urodynamic and patient characteristics of men in the detected clusters.Subjects and Methods: In this study, we considered 1650 PFSs of men with lower urinary tract symptoms, without relevant interventions in the past. After datapoint reduction and normalisation of the PFS curve segments, the k-Shape clustering algorithm was used to identify different pattern clusters. Differences in patient and urodynamic characteristics among those clusters were explored.Results: The UML approach identified four prominent clusters, with significantly different patient and urodynamic characteristics. Two pairs of these clusters were visually similar, and included similar urethral resistance values; however, they differed with regard to detrusor voiding contraction (DVC) and prostate size. In two clusters, the PFS curve pattern was significantly different from the commonly assumed ‘normal’ urethral resistance pattern in elderly men.Conclusion: In males, PFS patterns are considered to be uniform in shape. However, this study shows that UML can help to identify clusters of pressure–flow urethral resistance subtype patterns in men. We found that these subtype patterns were associated with DVC strength and prostate size. This feasibility study has shown that UML clustering of urodynamic PFSs in men holds promise for improving the diagnosis of urethral resistance and DVC properties and dynamics.</p
Brillouin Laser and High-Resolution Filter Using an Integrated Tellurite Covered Silicon Nitride Microdisk
No full textWe demonstrate an intermodal Brillouin laser with an intrinsic RF-linewidth of 7-Hz, multi-wavelength Brillouin lasing and a tunable microwave photonic filter with a 2.2- MHz linewidth in an integrated microdisk in silicon nitride covered with tellurite.</p
A Transparent, Antimicrobial, Bio-Ionic Liquid Functionalized Hydrogel for Corneal Injury Repair
No full textCurrent approaches for corneal injury repair include suturing and cyanoacrylate glue, which are associated with numerous severe adverse events like astigmatism, necrosis, microbial infection, and vitreous fluid leakage, all of which hinder corneal healing. To address this clinical challenge, we propose an innovative, transparent, highly adhesive, supple, flexible, and antimicrobial bioadhesive hydrogel, BioPEG, composed of synthetic polyethylene glycol diacrylate (PEGDA) and a cholinium-based bio-ionic liquid (BIL), to facilitate corneal repair and regeneration. This BioPEG hydrogel platform is based on visible light photoconjugation of PEGDA with choline-based BIL. High corneal adhesion, strength, repair, and regeneration were demonstrated ex vivo as well as in vivo using rabbit and porcine stromal defect models. Experimental models infected with Staphylococcus aureus and Pseudomonas aeruginosa underscored BioPEG’s ability for infection suppression while promoting re-epithelialization, showing BioPEG’s safety and efficacy as an alternative, superior to the currently used modality of care for rapid corneal repair and regeneration.</p
Plausible Values and Multilevel Models in Large-Scale Assessments
No full textInstitutional datasets of large-scale assessments (LSAs) typically contain a set of multiple imputations known as plausible values (PVs) that serve as a proxy for measures of latent proficiency. These are a set of draws from the posterior distribution of latent proficiency that account for measurement error. The PVs are typically drawn from a conditioning model that also includes information from covariates. The advantage of using PVs is that they can be readily used to provide estimates of population quantities of interest at the individual and group levels in secondary analysis of institutional datasets. In this study, the suitability of the PV methodology for secondary multilevel analyses is investigated. It is theoretically shown that consistent estimates for multilevel regression effects are obtained, even when using a single-level conditioning model for the PVs. However, when ignoring the hierarchical structure in the data in constructing PVs, simulation studies showed that the statistical inference is biased and that Type-1 errors, standard errors, and confidence intervals are invalid. The implications for school-level analyses in LSAs are discussed in light of the results.</p
Vascular Blood Flow Imaging:Pushing Boundaries, Shaping the Future
No full textAmong all vascular imaging modalities currently used in clinical practice, Doppler ultrasound is the only modality that provides real-time physiological information of blood flow. However, Doppler ultrasound lacks accurate visualization and quantification of blood flow patterns in multiple dimensions, potentially leading to erroneous velocity estimates and restricting diagnostic capabilities. Since hemodynamic forces play an essential role in the initiation and progression of vascular pathologies, 2D and 3D flow imaging and quantification techniques are needed for improving cardiovascular health care. This perspective review addresses novel techniques that can be used to analyze blood flow in a clinical setting, covering 4D flow magnetic resonance imaging (4D flow MRI), patient-specific image-based computational fluid dynamics (CFD), and ultrasound-based velocity vector imaging (US-VVI). Moreover, different US-VVI methods and clinical applications, along with potential future directions, will be extensively discussed.</p
Factors affecting the use and option use of shared mopeds and bicycles: Evidence from Dutch metropolitan cities
No full textShared micromobility services (SMMS) can provide alternative travel options during disruptive conditions (e.g., public transport disruptions). This is defined as “option use”, indicating that people who don’t normally use shared micromobility can consider using it when their main mode is unavailable. However, not everyone can benefit from it due to barriers that limit access to these shared modes. Therefore, this study aims to examine and explain the use and option use of shared micromobility services. A combined revealed preference and stated choice survey was conducted in the Netherlands, and binary logit models were estimated. Our results indicate that option users are more likely to be Dutch, own private e-bikes, cars, and have advanced digital skills. Moreover, we found that respondents lacking advanced digital skills are unlikely to consider app-based shared modes (e.g., shared mopeds) as a backup option in disruptions, but do consider shared modes which do not require a smartphone
Cross-sectoral digital planning Drinking Water-Urban Heat-Housing Provision indicators dataset
No full textThis dataset paper presents a comprehensive compilation of indicators covering three major domains: drinking water supply, urban heat, and housing provision. The data were systematically collected from a wide range of peer-reviewed papers to ensure a robust foundation for both academic research and practical policy analysis. The dataset includes a total of 280 indicators, each categorized and described. The indicators are organized into a relational database format, which allows for easy access and manipulation. The dataset was collected to facilitate cross-sectoral analysis, enabling researchers and practitioners to explore the interconnections between these critical areas of urban planning. The key indicators are described with clear definitions, calculations, and provenance information. Additionally, the dataset is organized in a relational SQL database, allowing users to perform advanced queries, join operations, and custom analyses. Potential applications span a range of research areas, including urban planning, environmental impact assessment, public health, and socio-economic studies
Kelvin–Helmholtz instabilities and mixing in surface-propagating gravity currents
No full textGravity currents are stratified shear flows common in various geophysical settings. During propagation, mixing between the current and the ambient fluid can occur via Kelvin–Helmholtz instabilities, leading to the formation of billows (vortices) on the current surface. Although the Kelvin–Helmholtz instability has implications for the transport of heat, solutes and sediments, the properties of the billows remain poorly quantified, particularly for free-surface gravity currents. This study presents laboratory experiments on buoyant, full-depth, lock-release gravity currents propagating at a free surface during the slumping regime. By varying the density contrast, we show that current propagation speeds and mean shapes align with two-layer shallow water theory, with most of the fluid contained in a temporally thinning, spatially uniform thick head. Kelvin–Helmholtz billows consistently form at the current front, becoming more coherent with increasing current velocity. We find that billows are generated at intervals equal to the time required for the current to advance a distance equal to its thickness, and they propagate forward at 25% of the current speed. Billows also undergo merging, with spacing approaching the total flow depth. Volume-based entrainment coefficients increase with Reynolds number, mirroring trends in basal currents. These findings quantify key properties of finite-amplitude Kelvin–Helmholtz billows in free-surface gravity currents and provide a foundation for understanding mixing and transport in environmental stratified shear flows
Adaptive Motor Unit Decomposition During Walking: Towards Systematic Validation
No full textUnderstanding motor unit (MU) behavior during locomotion is essential for uncovering the neural control of human movement and advancing the development of assistive technologies. Although high-density electromyography (RDEMG) allows for the extraction of individual MU firing activity, conventional methods are typically restricted to isometric or slow dynamic contractions. Additionally, accurate characterization of MU twitch responses is essential for decoding the mechanical output of muscle contractions. In this study, we present an adaptive online-capable methodology for decoding soleus' MU firing events and MU-specific activation dynamics along with a conservative validation during locomotion. Our proposed framework incorporates advanced blind source separation techniques, adapted for the detection of low-threshold MUs and capable of addressing non-stationary MU action potential variations. The framework is built on three main components: (1) an offline process to derive decomposition parameters and optimal twitch characteristics from isometric and walking trials, (2) an online approach that includes both static and adaptive decomposition strategies to refine MU firing event estimation and apply derived twitch properties for real-time MU-specific activation, and (3) a validation of the decoded MU spike trains against those derived from intramuscular EMG, as well as a comparison of MU-specific activation against ankle joint moments. Experimental results demonstrated that the adaptive approach improved the agreement with intramuscular EMG-derived spike trains and provided strong correlations between MU-specific activation and ankle joint moments. This work holds significant promise for future real-time applications in assistive devices that can more effectively adapt to individual patient needs and track their progress over time