Revisiting Salvucci’s Semi-analytical Solution for Bare Soil Evaporation with New Consideration of Vapour Diffusion and Film Flow

Bare soil evaporation is controlled by a combination of capillary flow, vapour diffusion and film flow. Relevant analytical solutions mostly assume horizontal flow conditions and ignore gravitational effects. Salvucci (1997) provided a rare example of a semi-analytical solution for vertical bare soil evaporation. However, they did not explicitly represent vapour diffusion and film flow, which are likely to account for a significant proportion of total flow during vertical evaporation from soils. Vapour diffusion and film flow can be incorporated via Salvucci’s desorptivity parameter, which represents the proportionality constant relating Stage 2 cumulative evaporation to the square root of time under horizontal flow conditions. The objective of this article is to implement vapour diffusion and film flow within Salvucci’s semi-analytical solution and test its performance by comparison with isothermal numerical simulation and relevant experimental data. The following important conclusions are drawn. Analytical solutions that assume horizontal flow conditions are inadequate for understanding vertical evaporation problems because they overestimate evaporation rates and mostly predict vapour diffusion and film flow to be of negligible influence. Salvucci’s semi-analytical solution is effective at predicting the order-of-magnitude reduction in evaporation caused by gravitational effects. However, it is unable to identify the correct importance of vapour diffusion and film flow because these processes can only be represented through its desorptivity parameter

Finite-Field Matrix Channels for Network Coding

In 2010, Silva et al. studied certain classes of finite-field matrix channels in order to model random linear network coding where exactly t random errors are introduced. In this paper, we consider a generalization of these matrix channels where the number of errors is not required to be constant, indeed the number of errors may follow any distribution. We show that a capacity-achieving input distribution can always be taken to have a very restricted form (the distribution should be uniform given the rank of the input matrix). This result complements, and is inspired by a paper of Nobrega et al., which establishes a similar result for a class of matrix channels that model network coding with link erasures. Our result shows that the capacity of our channels can be expressed as maximization over probability distributions on the set of possible ranks of input matrices: a set of linear rather than exponential size

Hepatitis B in Sub-Saharan Africa

No Abstrac

Evidence of strategic periodicities in collective conflict dynamics

We analyze the timescales of conflict decision-making in a primate society. We present evidence for multiple, periodic timescales associated with social decision-making and behavioral patterns. We demonstrate the existence of periodicities that are not directly coupled to environmental cycles or known ultraridian mechanisms. Among specific biological and socially-defined demographic classes, periodicities span timescales between hours and days, and many are not driven by exogenous or internal regularities. Our results indicate that they are instead driven by strategic responses to social interaction patterns. Analyses also reveal that a class of individuals, playing a critical functional role, policing, have a signature timescale on the order of one hour. We propose a classification of behavioral timescales analogous to those of the nervous system, with high-frequency, or $\alpha$-scale, behavior occurring on hour-long scales, through to multi-hour, or $\beta$-scale, behavior, and, finally $\gamma$ periodicities observed on a timescale of days.Comment: 22 pages, 7 figures, 1 table. Accepted for publication in Journal of the Royal Society Interfac

Adoption of Mobile Apps for Depression and Anxiety: Cross-Sectional Survey Study on Patient Interest and Barriers to Engagement

BACKGROUND: Emerging research suggests that mobile apps can be used to effectively treat common mental illnesses like depression and anxiety. Despite promising efficacy results and ease of access to these interventions, adoption of mobile health (mHealth; mobile device-delivered) interventions for mental illness has been limited. More insight into patients\u27 perspectives on mHealth interventions is required to create effective implementation strategies and to adapt existing interventions to facilitate higher rates of adoption. OBJECTIVE: The aim of this study was to examine, from the patient perspective, current use and factors that may impact the use of mHealth interventions for mental illness. METHODS: This was a cross-sectional survey study of veterans who had attended an appointment at a single Veterans Health Administration facility in early 2016 that was associated with one of the following mental health concerns: unipolar depression, any anxiety disorder, or posttraumatic stress disorder. We used the Veteran Affairs Corporate Data Warehouse to create subsets of eligible participants demographically stratified by gender (male or female) and minority status (white or nonwhite). From each subset, 100 participants were selected at random and mailed a paper survey with items addressing the demographics, overall health, mental health, technology ownership or use, interest in mobile app interventions for mental illness, reasons for use or nonuse, and interest in specific features of mobile apps for mental illness. RESULTS: Of the 400 potential participants, 149 (37.3%, 149/400) completed and returned a survey. Most participants (79.9%, 119/149) reported that they owned a smart device and that they use apps in general (71.1%, 106/149). Most participants (73.1%, 87/149) reported interest in using an app for mental illness, but only 10.7% (16/149) had done so. Paired samples t tests indicated that ratings of interest in using an app recommended by a clinician were significantly greater than general interest ratings and even greater when the recommending clinician was a specialty mental health provider. The most frequent concerns related to using an app for mental illness were lacking proof of efficacy (71.8%, 107/149), concerns about data privacy (59.1%, 88/149), and not knowing where to find such an app (51.0%, 76/149). Participants expressed interest in a number of app features with particularly high-interest ratings for context-sensitive apps (85.2%, 127/149), and apps focused on the following areas: increasing exercise (75.8%, 113/149), improving sleep (73.2%, 109/149), changing negative thinking (70.5%, 105/149), and increasing involvement in activities (67.1%, 100/149). CONCLUSIONS: Most respondents had access to devices to use mobile apps for mental illness, already used apps for other purposes, and were interested in mobile apps for mental illness. Key factors that may improve adoption include provider endorsement, greater publicity of efficacious apps, and clear messaging about efficacy and privacy of information. Finally, multifaceted apps that address a range of concerns, from sleep to negative thought patterns, may be best received

ALE Meta-Analysis Workflows Via the Brainmap Database: Progress Towards A Probabilistic Functional Brain Atlas

With the ever-increasing number of studies in human functional brain mapping, an abundance of data has been generated that is ready to be synthesized and modeled on a large scale. The BrainMap database archives peak coordinates from published neuroimaging studies, along with the corresponding metadata that summarize the experimental design. BrainMap was designed to facilitate quantitative meta-analysis of neuroimaging results reported in the literature and supports the use of the activation likelihood estimation (ALE) method. In this paper, we present a discussion of the potential analyses that are possible using the BrainMap database and coordinate-based ALE meta-analyses, along with some examples of how these tools can be applied to create a probabilistic atlas and ontological system of describing function–structure correspondences

Modulation of renal oxygenation and perfusion in rat kidney monitored by quantitative diffusion and blood oxygen level dependent magnetic resonance imaging on a clinical 1.5T platform

ARRIVE Checklist. (DOCX 42 kb

Interferon lambda is required for interferon gamma-expressing NK cell responses but does not afford antiviral protection during acute and persistent murine cytomegalovirus infection

Interferon lambda (IFNλ) is a group of cytokines that belong to the IL-10 family. They exhibit antiviral activities against certain viruses during infection of the liver and mucosal tissues. Here we report that IFNλ restricts in vitro replication of the β-herpesvirus murine cytomegalovirus (mCMV). However, IFNλR1-deficient (Ifnλr1-/-) mice were not preferentially susceptible to mCMV infection in vivo during acute infection after systemic or mucosal challenge, or during virus persistence in the mucosa. Instead, our studies revealed that IFNλ influences NK cell responses during mCMV infection. Ifnλr1-/- mice exhibited defective development of conventional interferon-gamma (IFNγ)-expressing NK cells in the spleen during mCMV infection whereas accumulation of granzyme B-expressing NK cells was unaltered. In vitro, development of splenic IFNγ+ NK cells following stimulation with IL-12 or, to a lesser extent, IL-18 was abrogated by IFNλR1-deficiency. Thus, IFNλ regulates NK cell responses during mCMV infection and restricts virus replication in vitro but is redundant in the control of acute and persistent mCMV replication within mucosal and non-mucosal tissues