On The Determination of MDI High-Degree Mode Frequencies

The characteristic of the solar acoustic spectrum is such that mode lifetimes get shorter and spatial leaks get closer in frequency as the degree of a mode increases for a given order. A direct consequence of this property is that individual p-modes are only resolved at low and intermediate degrees, and that at high degrees, individual modes blend into ridges. Once modes have blended into ridges, the power distribution of the ridge defines the ridge central frequency and it will mask the true underlying mode frequency. An accurate model of the amplitude of the peaks that contribute to the ridge power distribution is needed to recover the underlying mode frequency from fitting the ridge. We present the results of fitting high degree power ridges (up to l = 900) computed from several two to three-month-long time-series of full-disk observations taken with the Michelson Doppler Imager (MDI) on-board the Solar and Heliospheric Observatory between 1996 and 1999. We also present a detailed discussion of the modeling of the ridge power distribution, and the contribution of the various observational and instrumental effects on the spatial leakage, in the context of the MDI instrument. We have constructed a physically motivated model (rather than some ad hoc correction scheme) resulting in a methodology that can produce an unbiased determination of high-degree modes, once the instrumental characteristics are well understood. Finally, we present changes in high degree mode parameters with epoch and thus solar activity level and discuss their significance.Comment: 59 pages, 38 figures -- High-resolution version at http://www-sgk.harvard.edu:1080/~sylvain/preprints/ -- Manuscript submitted to Ap

On the efficiency of pseudo-marginal random walk Metropolis algorithms

We examine the behaviour of the pseudo-marginal random walk Metropolis algorithm, where evaluations of the target density for the accept/reject probability are estimated rather than computed precisely. Under relatively general conditions on the target distribution, we obtain limiting formulae for the acceptance rate and for the expected squared jump distance, as the dimension of the target approaches infinity, under the assumption that the noise in the estimate of the log-target is additive and is independent of the position. For targets with independent and identically distributed components, we also obtain a limiting diffusion for the first component. We then consider the overall efficiency of the algorithm, in terms of both speed of mixing and computational time. Assuming the additive noise is Gaussian and is inversely proportional to the number of unbiased estimates that are used, we prove that the algorithm is optimally efficient when the variance of the noise is approximately 3.3 and the acceptance rate is approximately 7.0%. We also find that the optimal scaling is insensitive to the noise and that the optimal variance of the noise is insensitive to the scaling. The theory is illustrated with a simulation study using the particle random walk Metropolis

Cognitive Effects of Vitamin D Supplementation in Older Outpatients Visiting a Memory Clinic: A Pre–Post Study

International audienc

Evaluating and improving the Community Land Model's sensitivity to land cover

Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remote-sensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate

Upregulation of PD-L1 expression in breast cancer cells through the formation of 3D multicellular cancer aggregates under different chemical and mechanical conditions

© 2019 Elsevier B.V. Expression of programmed death-ligand 1 (PD-L1) in cancer cells plays an important role in cancer-immune cell interaction. The emerging evidence suggests regulation of PD-L1 expression by several tumor microenvironmental cues. However, the association of PD-L1 expression with chemical and mechanical features of the tumor microenvironment, specifically epidermal growth factor receptor (EGFR) signaling and matrix stiffness, remains elusive. Herein, we determine whether EGFR targeting and substrate stiffness affect the regulation of PD-L1 expression. Breast carcinoma cell lines, MCF7 and MDA-MB-231, were cultured under different conditions targeting EGFR and exposing cells to distinct substrate stiffness to evaluate PD-L1 expression. Furthermore, the ability to form aggregates in short-term culture of breast carcinoma cells and its effect on expression level of PD-L1 was probed. Our results indicated that PD-L1 expression was altered in response to both EGFR inhibition and substrate stiffness. Additionally, a positive association between the formation of multicellular aggregates and PD-L1 expression was observed. MDA-MB-231 cells expressed the highest PD-L1 level on a stiff substrate, while inhibition of EGFR reduced expression of PD-L1. The results suggested that both physical and chemical features of tumor microenvironment regulate PD-L1 expression through alteration of tumor aggregate formation potential. In line with these results, the in-silico study highlighted a positive correlation between PD-L1 expression, EGFR signaling, epithelial to mesenchymal transition related transcription factors (EMT-TFs) and stemness markers in metastatic breast cancer. These findings improve our understanding of regulation of PD-L1 expression by tumor microenvironment leading to evasion of tumor cells from the immune system

Can climate‐effective land management reduce regional warming?

Limiting global warming to well below 2°C is an imminent challenge for humanity. However, even if this global target can be met, some regions are still likely to experience substantial warming relative to others. Using idealized global climate simulations, we examine the potential of land management options in affecting regional climate, with a focus on crop albedo enhancement and irrigation (climate-effective land management). The implementation is performed over all crop regions globally to provide an upper bound. We find that the implementation of both crop albedo enhancement and irrigation can reduce hot temperature extremes by more than 2°C in North America, Eurasia, and India over the 21st century relative to a scenario without management application. The efficacy of crop albedo enhancement scales with the magnitude, where a cooling response exceeding 0.5°C for hot temperature extremes was achieved with a large (i.e., ≥0.08) change in crop albedo. Regional differences were attributed to the surface energy balance response with temperature changes mostly explained by latent heat flux changes for irrigation and net shortwave radiation changes for crop albedo enhancement. However, limitations do exist, where we identify warming over the winter months when climate-effective land management is temporarily suspended. This was associated with persistent cloud cover that enhances longwave warming. It cannot be confirmed if the magnitude of this feedback is reproducible in other climate models. Our results overall demonstrate that regional warming of hot extremes in our climate model can be partially mitigated when using an idealized treatment of climate-effective land management

Associations between anxiety, body mass index, and sex hormones in women

Background: Several studies have shown a positive association between anxiety and obesity, particularly in women. We aimed to study whether sex hormone alterations related to obesity might play a role in this association. Patients and methods: Data for this study were obtained from a population-based cohort study (the LIFE-Adult-Study). A total of 3,124 adult women (970 premenopausal and 2,154 postmenopausal) were included into the analyses. The anxiety symptomatology was assessed using the GAD-7 questionnaire (cut-off ≥ 10 points). Sex hormones were measured from fasting serum samples. Results: We did not find significant differences in anxiety prevalence in premenopausal obese women compared with normal-weight controls (4.8% vs. 5.5%). Both obesity and anxiety symptomatology were separately associated with the same sex hormone alteration in premenopausal women: higher total testosterone level (0.97 ± 0.50 in obese vs. 0.86 ± 0.49 nmol/L in normal-weight women, p = 0.026 and 1.04 ± 0.59 in women with vs. 0.88 ± 0.49 nmol/L in women without anxiety symptomatology, p = 0.023). However, women with anxiety symptomatology had non-significantly higher estradiol levels than women without anxiety symptomatology (548.0 ± 507.6 vs. 426.2 ± 474.0 pmol/L), whereas obesity was associated with lower estradiol levels compared with those in normal-weight group (332.7 ± 386.5 vs. 470.8 ± 616.0 pmol/L). Women with anxiety symptomatology had also significantly higher testosterone and estradiol composition (p = 0.006). No associations of sex hormone levels and BMI with anxiety symptomatology in postmenopausal women were found. Conclusions: Although both obesity and anxiety symptomatology were separately associated with higher testosterone level, there was an opposite impact of anxiety and obesity on estradiol levels in premenopausal women. We did not find an evidence that the sex hormone alterations related to obesity are playing a significant role in anxiety symptomatology in premenopausal women. This could be the explanation why we did not find an association between obesity and anxiety. In postmenopausal women, other mechanisms seem to work than in the premenopausal group