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We perform direct numerical simulations of soluble bubbles dissolving in a Taylor–Couette (TC) flow reactor with a radius ratio of $\eta =0.5$ and Reynolds number in the range $0 \leq Re \leq 5000$, which covers the main regimes of this flow configuration, up to fully turbulent Taylor vortex flow. The numerical method is based on a geometric volume-of-fluid framework for incompressible flows coupled with a phase-change solver that ensures mass conservation of the soluble species, whilst boundary conditions on solid walls are enforced through an embedded boundary approach. The numerical framework is validated extensively against single-phase TC flows and competing mass transfer in multicomponent mixtures for an idealised infinite cylinder and for a bubble rising in a quiescent liquid. Our results show that when bubbles in a TC flow are mainly driven by buoyancy, theoretical formulae derived for spherical interfaces on a vertical trajectory still provide the right fundamental relationship between the bubble Reynolds and Sherwood numbers, which reduces to $Sh \propto \sqrt {Pe}$ for large Péclet values. For bubbles mainly transported by TC flows, the dissolution of bubbles depend on the TC Reynolds number and, for the turbulent configurations, we show that the smallest characteristic turbulent scales control mass transfer, in agreement with the small-eddy model of Lamont & Scott (AIChE J., vol. 16, 1970, pp. 513–519). Finally, the interaction between two aligned bubbles is investigated and we show that a significant increase in mass transfer can be obtained when the rotor of the apparatus is operated at larger speeds.
Supported by an unrestricted educational grant from Avanir
The prevalence of agitation in Alzheimer’s Disease (AAD) approaches 80%. Patients with AAD have more severe behavioral,depressive, and frontal lobe symptoms and are at increased risk for hospitalization and nursing home placement.
Early agitation is a robust predictor of accelerated progression and mortality and is distressing and dangerous for patients and care partners.
This presentation was recently developed by the Gerontologic Society of America (GSA) which convened an expert AD Working Group to develop a “Decision Tree” for healthcare providers relative to the assessment of AAD and the employment of Non-Pharmacologic and Pharmacologic treatment options
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
Aims
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Method
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Results
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
Conclusions
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Quantitative plant biology is an interdisciplinary field that builds on a long history of biomathematics and biophysics. Today, thanks to high spatiotemporal resolution tools and computational modelling, it sets a new standard in plant science. Acquired data, whether molecular, geometric or mechanical, are quantified, statistically assessed and integrated at multiple scales and across fields. They feed testable predictions that, in turn, guide further experimental tests. Quantitative features such as variability, noise, robustness, delays or feedback loops are included to account for the inner dynamics of plants and their interactions with the environment. Here, we present the main features of this ongoing revolution, through new questions around signalling networks, tissue topology, shape plasticity, biomechanics, bioenergetics, ecology and engineering. In the end, quantitative plant biology allows us to question and better understand our interactions with plants. In turn, this field opens the door to transdisciplinary projects with the society, notably through citizen science.
We describe an ultra-wide-bandwidth, low-frequency receiver recently installed on the Parkes radio telescope. The receiver system provides continuous frequency coverage from 704 to 4032 MHz. For much of the band (
${\sim}60\%$
), the system temperature is approximately 22 K and the receiver system remains in a linear regime even in the presence of strong mobile phone transmissions. We discuss the scientific and technical aspects of the new receiver, including its astronomical objectives, as well as the feed, receiver, digitiser, and signal processor design. We describe the pipeline routines that form the archive-ready data products and how those data files can be accessed from the archives. The system performance is quantified, including the system noise and linearity, beam shape, antenna efficiency, polarisation calibration, and timing stability.
The process-based model dominates contemporary American research on police-community relations and perceptions of police. A sizable literature has examined the linkages between procedural justice, legitimacy, compliance with the law, and cooperation with police. Less examined is the relationship between legitimacy and public empowerment of police. This study examines this relationship, focusing on police militarization. We first examine the direct effect of legitimacy on public willingness to allow police to become more militarized. Drawing from cognitive psychology and rational choice theories, we then consider indirect paths between legitimacy and empowerment, concentrating on two anticipated consequences of militarization—an increase in police effectiveness and possible harm to civil liberties. Using a national sample of over 700 American adults, and structural equation modeling, results indicate legitimacy has both direct and indirect effects on police empowerment, in part by shaping assessments of the possible consequences of empowerment. Implications for theory and policy are discussed.
Regulatory impact analyses (RIAs) weigh the benefits of regulations against the burdens they impose and are invaluable tools for informing decision makers. We offer 10 tips for nonspecialist policymakers and interested stakeholders who will be reading RIAs as consumers.
1. Core problem: Determine whether the RIA identifies the core problem (compelling public need) the regulation is intended to address.
2. Alternatives: Look for an objective, policy-neutral evaluation of the relative merits of reasonable alternatives.
3. Baseline: Check whether the RIA presents a reasonable “counterfactual” against which benefits and costs are measured.
4. Increments: Evaluate whether totals and averages obscure relevant distinctions and trade-offs.
5. Uncertainty: Recognize that all estimates involve uncertainty, and ask what effect key assumptions, data, and models have on those estimates.
6. Transparency: Look for transparency and objectivity of analytical inputs.
7. Benefits: Examine how projected benefits relate to stated objectives.
8. Costs: Understand what costs are included.
9. Distribution: Consider how benefits and costs are distributed.
10. Symmetrical treatment: Ensure that benefits and costs are presented symmetrically.
The persistence of hormone-type herbicides in tissues of susceptible crop plants was studied under growth-chamber and field conditions. The susceptible plants selected were tomatoes (Lycopersicon esculentum Mill.), soybeans [Glycine max (L.) Merr.], and turnips (Brassica rapa L.). Foliage of each species was exposed to herbicides at levels that represented spray drift situations, and the decline of residues was investigated through subsequent chemical analysis. The disappearance of 2,4-D [(2,4-dichlorophenoxy)-acetic acid], 2,4-DB [4-(2,4-dichlorophenoxy)butyric acid], mecoprop {2-[(4-chloro-o-tolyl)oxy]propionic acid}, 2,4,5-T [(2,4,5-trichlorophenoxy)acetic acid], and dicamba (3,6-dichloro-o-anisic acid) was almost linear when concentration data were plotted against the logarithm of time. The results indicate that for practical purposes a kinetic rate equation [conc. = a – b log (time)] would describe the residue decline.
The Monχey project will provide a large and homogeneous set of stellar yields for the low- and intermediate- mass stars and has applications particularly to galactic chemical evolution modelling. We describe our detailed grid of stellar evolutionary models and corresponding nucleosynthetic yields for stars of initial mass 0.8 M⊙ up to the limit for core collapse supernova (CC-SN) ≈ 10 M⊙. Our study covers a broad range of metallicities, ranging from the first, primordial stars (Z = 0) to those of super-solar metallicity (Z = 0.04). The models are evolved from the zero-age main-sequence until the end of the asymptotic giant branch (AGB) and the nucleosynthesis calculations include all elements from H to Bi. A major innovation of our work is the first complete grid of heavy element nucleosynthetic predictions for primordial AGB stars as well as the inclusion of extra-mixing processes (in this case thermohaline) during the red giant branch. We provide a broad overview of our results with implications for galactic chemical evolution as well as highlight interesting results such as heavy element production in dredge-out events of super-AGB stars. We briefly introduce our forthcoming web-based database which provides the evolutionary tracks, structural properties, internal/surface nucleosynthetic compositions and stellar yields. Our web interface includes user- driven plotting capabilities with output available in a range of formats. Our nucleosynthetic results will be available for further use in post processing calculations for dust production yields.