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Designing Health Recommender Systems to Promote Health Equity:A Socioecological Perspective
Get PDFHealth recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities. We use the socioecological model, which provides representations of how multiple, nested levels of influence (eg, community, institutional, and policy factors) interact to shape individual health. This perspective helps illustrate how HRS could address not just individual health factors but also the structural barriers-such as access to health care, social support, and access to healthy food-that shape health outcomes at various levels. Based on this analysis, we then discuss the challenges and future research priorities. We find that despite the potential for targeting more complex systemic challenges to obtaining good health, current HRS are still focused on individual health behaviors, often do not integrate the lived experiences of users in the design, and have had limited reach and effectiveness for individuals from low socioeconomic status and racial or ethnic minoritized backgrounds. In this viewpoint, we argue that a new design paradigm is necessary in which HRS focus on incorporating structural barriers to good health in addition to user preferences. HRS should be designed with an emphasis on health systems, which also includes incorporating decolonial perspectives of well-being that challenge prevailing medical models. Furthermore, potential lies in evaluating the health equity effects of HRS and leveraging collected data to influence policy. With changes in practices and with an intentional equity focus, HRS could play a crucial role in health promotion and decreasing health inequities.</p
Wavefront Shaping Demo-Setup
No full textWavefront shaping is a versatile technique that allows control over the scattering processes of light in opaque samples. It was invented by our group in 2007 and has since been shown to be of major importance in the field of optics. Applications include microscopy, speckle noise reduction in imaging, beam steering, generation of arbitrary light modes, imaging deep in scattering samples and many more.Our demo-setup shows the power of wavefront shaping by turning a normally scattering sample into a lens. After optimisation of the wavefront a clearly visible spot appears behind the sample.For the wavefront shaping we use phase modulation of a frequency doubled ND-YAG laser. The phase modulation is obtained using a deformable micromirror device in combination with Lee holography. The visualisation of wavefront shaping with our demo-setup helps understanding the underlying principles
Non-Interchangeability between Heart Rate Variability and Pulse Rate Variability During Supine-to-Stand Tests
Get PDFHeart rate variability (HRV) is widely recognized as a valuable biomarker for assessing autonomic cardiac regulation. Pulse rate variability (PRV) is a common surrogate of HRV given the wide usability of PPG in commercially available devices. However, there is no clear conclusion on whether PRV can replace HRV given their different physiological mechanisms. This study evaluates the interchangeability of young adults HRV and PRV during supine-to-stand (STS) tests which are known as common posture transitions in daily life monitoring. Fifteen features from time, frequency and nonlinear domains were extracted from both electrocardiography and PPG signals. Paired t-tests and Wilcoxon signed-rank tests examined the difference between the extracted HRV and PRV features during supine, transition and standing phases separately. One feature showed significant difference in the supine phase, and this discrepancy increased to four in the transition and standing phases. These findings suggested that PRV is different from HRV in the STS tests, despite the fact that both metrics can reflect the sympathetic activation triggered by the posture changes
Thermal-solutal-induced bistability of evaporating multicomponent liquid thin films
Get PDFVolatile multicomponent liquid films show rich dynamics, due to the complex interplay of gradients in temperature and in solute concentrations. Here, we study the evaporation dynamics of a tricomponent liquid film, consisting of water, ethanol, and trans-anethole oil (known as "ouzo"). With the preferential evaporation of ethanol, cellular convective structures are observed both in the thermal patterns and in the nucleated oil droplet patterns. However, the feature sizes of these two patterns can differ, indicating dual instability mechanisms dominated by either temperature or solute concentration. Using numerical simulations, we quantitatively compare the contributions of temperature and solute concentration on the surface tension. Our results reveal that the thermal Marangoni effect predominates at the initial evaporation stage, resulting in cellular patterns in thermal images, while the solutal Marangoni effect gradually becomes dominant. By regulating the transition time of this thermal-solutal-induced bistability and the nucleation time of oil microdroplets in the ternary mixture, the oil droplet patterns can be well controlled. This capability not only enhances our understanding of the evaporation dynamics but also paves the way for precise manipulation of nucleation and deposition processes at larger scales.</p
Soil organic carbon stocks as driven by land use in Mato Grosso State:the Brazilian Cerrado agricultural frontier
Get PDFTo address national and global demand for agro-based products, agricultural expansion has rapidly become a norm in Brazil since 1950s to date. In recent decades, agricultural expansion and technological advancement have placed the country among the top producers and exporters of agricultural products. The paradigm shifts in farming system from conventional to integrated approach has brought significant changes in land use, which consequently influenced carbon sequestration and soil organic carbon (SOC). This is more prevalent in the State of Mato Grosso, one of the most producers of food in Brazil. On this background, we hypothesized that though forests have potential for SOC stock, which decreases due to conversion to cropland but in longer-term with sustainable management, carbon might accrual significantly in cropland. Therefore, this paper aimed to unveil the nexus between long term land use and carbon stock changes and estimate future SOC stocks in Mato Grosso State of Brazil. To achieve this aim, a hybridization of machine learning and the InVEST prediction models was applied to estimate the land use changes and the SOC stocks between 1990 and 2020 and estimate for 2050. The study revealed that between 1990, 2020, and 2050, croplands increased significantly by at least 78%, pastures decreased by 32%, while forests decreased marginally by about 4% due to agricultural expansions. However, in 1990 and 2020, the SOC stock was slightly up to 147.34 Mg ha−1, it recorded an increase after a longer-time (i.e., in 2050). This increase was substantially under the forests, and marginally in the croplands. Climate-smart agricultural systems such as crop-livestock forest, integrated crop-livestock, and other conservation agricultural practices have great potential to contribute to sustainable development by increasing the levels of carbon in agricultural soils especially, after a longer period. Therefore, agricultural policies geared towards low carbon agriculture should be fully integrated into the various government decision making processes as this will guarantee food security and maximize soil carbon sequestration and stocks in the long term. Simultaneously, it is crucial to promote the dissemination of best practices for implementing and sustaining conservation efforts, thereby safeguarding the carbon stocks established to prevent their depletion. This will also support the Brazilian government in achieving its Nationally determined contributions (NDCs) through agricultural soils
Expert level of detection of interictal discharges with a deep neural network
Get PDFObjective: Deep learning methods have shown potential in automating the detection of interictal epileptiform discharges (IEDs) in electroencephalography (EEG). We compared IED detection using our previously trained deep neural network with a group of experts to assess its potential applicability.Methods: First, we performed clinical validation on an internal data set. Seven experts reviewed all EEG studies. Performance agreement between experts and the network was compared at both the EEG and IED levels. All EEG recordings were also processed with Persyst. Subsequently, we performed external validation, with data from four centers, using a hybrid approach, where detections by the deep neural network were reviewed by an expert. In case of disagreement with the original report, the EEG recording was annotated independently by five experts.Results: For internal validation we included 22 EEG studies with IEDs and 28 EEG studies from controls. At the EEG level, our network showed performance similar to that of the experts. For individual IED detection, the sensitivities between experts ranged from 20.7%–86.4%, whereas the sensitivity of our network was 82.5% (confidence interval [CI]: 77.7%–87.4%) at 99% specificity and a false detection rate (FDR) of <.2/min, outperforming Persyst, with 64.6% sensitivity (CI: 61.4%–67.9%) at 98% specificity. External validation in 174 EEG studies demonstrated that all 85 EEG recordings classified as normal in the original report were classified correctly, with an FDR of.10/min. Of the 89 EEG studies with IEDs according to the report, 56 were correctly classified (Cohen's κ =.62). Visual analysis of the remaining 33 EEG recordings showed high interobserver variability among the five experts (Fleiss’ κ =.13).Significance: Our deep neural network detects IEDs on par with clinical experts. The external validation in a hybrid approach showed substantial agreement with the original report. Disagreement was due mainly to high interobserver variability. Our deep neural network may support visual EEG analysis and assist in diagnostics, particularly when human resources are limited.</p
Integrating plasmasphere, ionosphere and thermosphere observations and models into a standardised open access research environment: The PITHIA-NRF international project
Get PDFThe PITHIA-NRF project “Plasmasphere Ionosphere Thermosphere Integrated Research Environment and Access services: a Network of Research Facilities” aims at building a European distributed network that integrates observations from space and ground, data processing tools and models to support scientific research on the Plasmasphere-Ionosphere-Thermosphere system. PITHIA-NRF is designed to provide formalised open access to experimental facilities, data and models, standardised data products, and training services. Participating organisations that operate these facilities, formed twelve nodes in eleven European countries. These nodes work on optimising their observing facilities and offer trans-national access to scientists and engineers. The PITHIA-NRF e-Science Centre is a core element of the project. Its design and evolution are controlled by a systematic ontology which governs the collection of scientific observations and research models, jointly termed data collections, which are registered with the e-Science Centre. Several tens of data collections are being registered. Data collection registrations adhere to FAIR principles and transparent quality measures to a large extent. The e-Science Centre facilitates the execution of research projects proposed by researchers from inside and outside the PITHIA-NRF consortium which require trans-national access to and understanding of data collections (observations and models) residing at one or several PITHIA-NRF nodes. Upon completion of the project a comprehensive collection of observations and models will have been gathered by the e-Science Centre for the benefit of efficient scientific research which relies on Europe-wide collaboration
Low rank specialisations of elliptic surfaces
Get PDFLet E/ℚ(T) be a nonisotrivial elliptic curve of rank r. A theorem due to Silverman [ Heights and the specialization map for families of abelian varieties , J. reine angew. Math. 342 (1983), 197 211] implies that the rank rt of the specialisation Et/ℚ is at least r for all but finitely many t ∈ ℚ. Moreover, it is conjectured that rt ≤ r + 2, except for a set of density 0. When E/ℚ(T) has a torsion point of order 2, under an assumption on the discriminant of a Weierstrass equation for E/ℚ(T), we produce an upper bound for rt that is valid for infinitely many t.We also present two examples of nonisotrivial elliptic curves E/ℚ(T) such that rt ≤ r + 1 for infinitely many t.</p
Homogeneous reactive distillation:The influence of pressure drop on separation and reaction kinetics
Get PDFThis study investigates the Total Annual Cost (TAC) optimization of a reactive distillation (RD) process for methyl acetate (MA) production as a function of tray pressure drop, focusing on the trade-off between chemical reaction kinetics and separation efficiency. The analysis examines how variations in column diameter and weir height influence the TAC across different liquid hold-ups with and without incorporating a tray pressure drop in the simulations. Results indicate that for larger liquid hold-ups, the decrease in separation efficiency predominates over kinetic advantages, leading to higher energy costs when pressure drop is considered. Despite the loss in separation efficiency with a high weir height, a pressure drop-incorporated column design featuring a high weir height and small diameter is shown to achieve lower TAC due to the comparatively lower installed costs. A reduction of tray liquid hold-up of more than 50 % is found for the optimal column design in the considered case study when the tray pressure drop is considered. A sensitivity analysis towards a hypothetical infinite fast reaction is conducted to illustrate how the energy costs are affected by the kinetic rate of the chemical reaction.</p
Quantitative photoacoustic imaging using known chromophores as fluence marker
Get PDFPhotoacoustic imaging offers optical contrast images of human tissue at acoustic resolution, making it valuable for diverse clinical applications. However, quantifying tissue composition via optical contrast remains challenging due to the unknown light fluence within the tissue. Here, we propose a method that leverages known chromophores (e.g., arterial blood) to improve the accuracy of quantitative photoacoustic imaging. By using the optical properties of a known chromophore as a fluence marker and integrating it into the optical inversion process, we can estimate the unknown fluence within the tissue. Experimentally, we demonstrate that this approach successfully recovers both the spectral shape and magnitude of the optical absorption coefficient of an unknown chromophore. Additionally, we show that the fluence marker method enhances conventional optical inversion techniques, specifically (i) a straightforward iterative approach and (ii) a gradient-based method. Our results indicate an improvement in accuracy of up to 24.4% when comparing optical absorption recovery with and without the fluence marker. Finally, we present the method's performance and illustrate its applications in carotid plaque quantification.</p