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The aim of the study was to investigate the associations between dietary patterns and chronic disease mortality in Switzerland using an ecologic design and to explore the spatial dependence of these associations, i.e. the tendency of near locations to present more similar values than randomly expected and distant locations to present more different values. Data of the cross-sectional National Nutrition Survey menuCH (n = 2,057) were used to compute hypothesis- (Alternate Healthy Eating Index, AHEI) and data-driven dietary patterns. District-level standardised mortality ratios (SMR) were calculated using the Swiss Federal Statistical Office mortality data and were linked to dietary data by the participants’ place of residence. Quasipoisson regression models were fitted to investigate the associations between dietary patterns and chronic disease mortality; Moran’s I statistics were used to explore the spatial dependence. Compared to the first, the fifth AHEI quintile (representing the highest diet quality) was associated with district-level SMR (95% confidence interval) of 0.95 (0.93-0.97) for cardiovascular disease, 0.91 (0.88-0.95) for ischemic heart disease, 0.97 (0.95-0.99) for stroke, 0.99 (0.98-1.00) for all-cancer, 0.98 (0.96-0.99) for colorectal cancer, and 0.93 (0.89-0.96) for diabetes. Additionally, the Swiss traditional and Western-like patterns were associated with significantly higher district-level SMR for cardiovascular disease, ischemic heart disease, stroke, and diabetes (ranging from 1.02 to 1.08) compared to the Prudent pattern. Finally, significant global and local spatial dependence was identified, with very similar results observed across hypothesis- and data-driven dietary patterns. To conclude, significant associations were observed between dietary patterns and mortality from various chronic diseases, and chronic disease mortality clustered locally, with high similarities between hypothesis- and data-driven dietary patterns. Further analyses including spatial components in regression models would allow to better understand local factors influencing diet-disease associations and to identify regions where nutritional interventions are needed the most.
The UK Biobank contains data with varying degrees of reliability and completeness for assessing depression. A third of participants completed a Mental Health Questionnaire (MHQ) containing the gold-standard Composite International Diagnostic Interview (CIDI) criteria for assessing mental health disorders.
To investigate whether multiple observations of depression from sources other than the MHQ can enhance the validity of major depressive disorder (MDD).
In participants who did not complete the MHQ, we calculated the number of other depression measures endorsed, for example from hospital episode statistics and interview data. We compared cases defined this way with CIDI-defined cases for several estimates: the variance explained by polygenic risk scores (PRS), area under the curve attributable to PRS, single nucleotide polymorphisms (SNPs)-based heritability and genetic correlations with summary statistics from the Psychiatric Genomics Consortium MDD genome-wide association study.
The strength of the genetic contribution increased with the number of measures endorsed. For example, SNP-based heritability increased from 7% in participants who endorsed only one measure of depression, to 21% in those who endorsed four or five measures of depression. The strength of the genetic contribution to cases defined by at least two measures approximated that for CIDI-defined cases. Most genetic correlations between UK Biobank and the Psychiatric Genomics Consortium MDD study exceeded 0.7, but there was variability between pairwise comparisons.
Multiple measures of depression can serve as a reliable approximation for case status where the CIDI measure is not available, indicating sample size can be optimised using the entire suite of UK Biobank data.
The mechanics of extreme intensity events in the buffer and logarithmic layers of a turbulent channel at $Re_\tau =2000$ is investigated. The 99.9th percentile of the most intense events in the dissipation of turbulent kinetic energy is analysed by means of conditional space–time proper orthogonal decomposition. The computed spatio-temporal modes are coherent in space and over the considered time frame, and optimally capture the energy of the ensemble. The most energetic mode with transverse symmetric structure describes a turbulent burst event. The underlying mechanism is a varicose instability which generates localized extrema in the dissipation and production of turbulent kinetic energy and drives the formation of a hairpin vortex. The most energetic anti-symmetric mode is related to a sinuous-type instability that is situated in the shear layer between two very-large-scale streaks. Statistical results show the energy in the symmetric mode to exceed that in the anti-symmetric mode by a near constant factor for the considered wall distances. Both mechanisms occur throughout the range of wall distances in an effectively self-similar manner that is consistent with the attached-eddy hypothesis. By analogy with transitional flows, the results suggest that the events are induced by an exponential growth mechanism.
Glyphosate-tolerant and glyphosate-resistant weeds are becoming increasingly problematic in cotton fields in Australia, necessitating a return from a glyphosate dominated system to a more integrated approach to weed management. The development of an integrated weed management system can be facilitated by identifying the critical period for weed control (CPWC), a model that enables cotton growers to optimize the timing of their weed control inputs. Using data from field studies conducted from 2003 to 2015, CPWC models using extended functions, including weed biomass in the relationships, were developed for the mimic weeds, common sunflower and Japanese millet, in high-yielding, fully irrigated cotton. A multispecies CPWC model was developed after combining these data sets with data for mungbean in irrigated cotton, using weed height and weed biomass as descriptors in the models. Comparison of observed and predicted relative cotton-lint yields from the multispecies CPWC model demonstrated that the model reasonably described the competition from these three very different mimic weeds, opening the possibility for cotton growers to use a multispecies CPWC model in their production systems.
Recent technological advances have led to a novel class of microfluidic devices which can be rapidly fabricated by printing a fluid onto a solid substrate with flows generated passively via surface tension. The nonlinear dependence between flow and the heights of the conduits, however, prevent straightforward calculation of the resulting dynamics. In this paper we use matched asymptotic expansions to predict how flow through these devices can be tuned by changing their geometry. We begin with the simple ‘dumbbell’ configuration in which two fluid drops with different sizes are connected by a long, thin and narrow conduit. We calculate the time scale required for one drop to drain into the other and how this depends both on the geometry of the pinned contact line and volume of fluid deposited into the drops. Our model therefore provides the mechanistic basis to design conduits with a particular fluid flux and/or shear stress, which are often key experimental constraints. Our asymptotic predictions are shown to be in excellent agreement with numerical simulations even for moderate aspect ratios (the ratio of conduit width to length). Next, we show how our results for the simple dumbbell configuration can be extended to predict the flow through networks of conduits with multiple drops and nodes, and hence may assist in their design and implementation. This new mathematical framework has the potential to increase the use of surface tension driven microfluidics across a wide range of disciplines as it allows alternate designs to be rapidly assessed.
Approximately, 1.7 million individuals in the United States have been infected with SARS-CoV-2, the virus responsible for the novel coronavirus disease-2019 (COVID-19). This has disproportionately impacted adults, but many children have been infected and hospitalised as well. To date, there is not much information published addressing the cardiac workup and monitoring of children with COVID-19. Here, we share the approach to the cardiac workup and monitoring utilised at a large congenital heart centre in New York City, the epicentre of the COVID-19 pandemic in the United States.
This paper presents the integration and channel characterization of a highly integrated dual-band digital beamforming space-borne synthetic aperture radar (SAR) receiver. The proposed SAR sensor is a low-cost, lightweight, low-power consumption, and dual-band (X/Ka) dual-polarized module ready for the next-generation space-borne SAR missions. In previous works, by the authors, the design and experimental characterization of each sub-system was already presented and discussed. This work expands upon the previous characterization by providing an exhaustive experimental assessment of the fully integrated system. As it will be shown, the proposed tests were used to validate all the instrument channels in a set-up where the SAR sensor was illuminated by an external source minim the ground reflected waves. Test results demonstrate how the system channels are properly operating allowing the reception of the input signals and their processing in the digital domain. The possibility to easily implement a calibration procedure has also been validated to equalize, in the digital domain, the unavoidable amplitude differences between the different channels.
Stress-induced stimulation of corticotropic function involves the activation of hypothalamic corticotropin-releasing hormone (CRH) and arginine vasopressin (AVP), which can be measured by improved methods of neuroendocrine investigation. The antiserotoninergic tricyclic antidepressant, tianeptine, reduces the corticotropic response to stress, as shown by a reduction in hypothalamo-hypophyseal portal CRH and AVP levels.
Upcoming VLBI observations will resolve nearby supermassive black holes, most notably Sagittarius A* and M87, on event horizon-scales. Recent observations of Sagittarius A* with the Event Horizon Telescope have revealed horizon-scale structure. Accordingly, the detection and measurement of the back hole “shadow” is expected to enable the existence of astrophysical black holes to be verified directly. Although the theoretical description of the shadow is straightforward, its observational appearance is largely determined by the properties of the surrounding accretion flow, which is highly turbulent. We introduce a new polarised general-relativistic radiative transfer code, BHOSS, which accurately solves the equations of polarised radiative transfer in arbitrary strong-gravity environments, providing physically-realistic images of astrophysical black holes on event horizon-scales, as well as also providing insight into the fundamental properties and nature of the surrounding accretion flow environment.
Research using the critical period for weed control (CPWC) has shown that high-yielding cotton crops are very sensitive to competition from grasses and large broadleaf weeds, but the CPWC has not been defined for smaller broadleaf weeds in Australian cotton. Field studies were conducted over five seasons from 2003 to 2015 to determine the CPWC for smaller broadleaf weeds, using mungbean as a mimic weed. Mungbean was planted at densities of 1, 3, 6, 15, 30, and 60 plants m−2 with or after cotton emergence and added and removed at approximately 0, 150, 300, 450, 600, 750, and 900 degree days of crop growth (GDD). Mungbean competed strongly with cotton, with season-long interference; 60 mungbean plants m−2 resulted in an 84% reduction in cotton yield. A dynamic CPWC function was developed for densities of 1 to 60 mungbean plants m−2 using extended Gompertz and exponential curves including weed density as a covariate. Using a 1% yield-loss threshold, the CPWC defined by these curves extended for the full growing season of the crop at all weed densities. The minimum yield loss from a single weed control input was 35% at the highest weed density of 60 mungbean plants m−2. The relationship for the critical time of weed removal was further improved by substituting weed biomass for weed density in the relationship.
Airborne radio-echo sounding (RES) surveys are widely used to measure ice-sheet bed topography. Measuring bed topography as accurately and widely as possible is of critical importance to modelling ice dynamics and hence to constraining better future ice response to climate change. Measurement accuracy of RES surveys is influenced both by the geometry of bed topography and the survey design. Here we develop a novel approach for simulating RES surveys over glaciated terrain, to quantify the sensitivity of derived bed elevation to topographic geometry. Furthermore, we investigate how measurement errors influence the quantification of glacial valley geometry. We find a negative bias across RES measurements, where off-nadir return measurement error is typically −1.8 ± 11.6 m. Topographic highlands are under-measured an order of magnitude more than lowlands. Consequently, valley depth and cross-sectional area are largely under-estimated. While overall estimates of ice thickness are likely too high, we find large glacier valley cross-sectional area to be under-estimated by −2.8 ± 18.1%. Therefore, estimates of ice flux through large outlet glaciers are likely too low when this effect is not taken into account. Additionally, bed mismeasurements potentially impact our appreciation of outlet-glacier stability.
Suitable for both senior-level and first-year graduate courses, this fully revised edition provides a unique and systematic treatment of engineering dynamics that covers Newton–Euler and Lagrangian approaches. New to this edition are: two completely revised chapters on the constraints on, and potential energies for, rigid bodies, and the dynamics of systems of particles and rigid bodies; clearer discussion on coordinate singularities and their relation to mass matrices and configuration manifolds; additional discussion of contravariant basis vectors and dual Euler basis vectors, as well as related works in robotics; improved coverage of navigation equations; inclusion of a 350-page solutions manual for instructors, available online; a fully updated reference list. Numerous structured examples, discussion of various applications, and exercises covering a wide range of topics are included throughout, and source code for exercises, and simulations of systems are available online.