Laplacian Distribution and Domination

Let $m_G(I)$ denote the number of Laplacian eigenvalues of a graph $G$ in an interval $I$, and let $\gamma(G)$ denote its domination number. We extend the recent result $m_G[0,1) \leq \gamma(G)$, and show that isolate-free graphs also satisfy $\gamma(G) \leq m_G[2,n]$. In pursuit of better understanding Laplacian eigenvalue distribution, we find applications for these inequalities. We relate these spectral parameters with the approximability of $\gamma(G)$, showing that $\frac{\gamma(G)}{m_G[0,1)} \not\in O(\log n)$. However, $\gamma(G) \leq m_G[2, n] \leq (c + 1) \gamma(G)$ for $c$-cyclic graphs, $c \geq 1$. For trees $T$, $\gamma(T) \leq m_T[2, n] \leq 2 \gamma(G)$

Remote sensing observatory validation of surface soil moisture using Advanced Microwave Scanning Radiometer E, Common Land Model, and ground based data: Case study in SMEX03 Little River Region, Georgia, U.S.

Optimal soil moisture estimation may be characterized by intercomparisons among remotely sensed measurements, ground‐based measurements, and land surface models. In this study, we compared soil moisture from Advanced Microwave Scanning Radiometer E (AMSR‐E), ground‐based measurements, and a Soil‐Vegetation‐Atmosphere Transfer (SVAT) model for the Soil Moisture Experiments in 2003 (SMEX03) Little River region, Georgia. The Common Land Model (CLM) reasonably replicated soil moisture patterns in dry down and wetting after rainfall though it had modest wet biases (0.001–0.054 m3/m3) as compared to AMSR‐E and ground data. While the AMSR‐E average soil moisture agreed well with the other data sources, it had extremely low temporal variability, especially during the growing season from May to October. The comparison results showed that highest mean absolute error (MAE) and root mean squared error (RMSE) were 0.054 and 0.059 m3/m3 for short and long periods, respectively. Even if CLM and AMSR‐E had complementary strengths, low MAE (0.018–0.054 m3/m3) and RMSE (0.023–0.059 m3/m3) soil moisture errors for CLM and soil moisture low biases (0.003–0.031 m3/m3) for AMSR‐E, care should be taken prior to employing AMSR‐E retrieved soil moisture products directly for hydrological application due to its failure to replicate temporal variability. AMSR‐E error characteristics identified in this study should be used to guide enhancement of retrieval algorithms and improve satellite observations for hydrological sciences

Macro Dark Matter

Dark matter is a vital component of the current best model of our universe, $\Lambda$CDM. There are leading candidates for what the dark matter could be (e.g. weakly-interacting massive particles, or axions), but no compelling observational or experimental evidence exists to support these particular candidates, nor any beyond-the-Standard-Model physics that might produce such candidates. This suggests that other dark matter candidates, including ones that might arise in the Standard Model, should receive increased attention. Here we consider a general class of dark matter candidates with characteristic masses and interaction cross-sections characterized in units of grams and cm$^2$, respectively -- we therefore dub these macroscopic objects as Macros. Such dark matter candidates could potentially be assembled out of Standard Model particles (quarks and leptons) in the early universe. A combination of Earth-based, astrophysical, and cosmological observations constrain a portion of the Macro parameter space. A large region of parameter space remains, most notably for nuclear-dense objects with masses in the range $55 - 10^{17}$ g and $2\times10^{20} - 4\times10^{24}$ g, although the lower mass window is closed for Macros that destabilize ordinary matter.Comment: 13 pages, 1 table, 4 figures. Submitted to MNRAS. v3: corrected small errors and a few points were made more clear, v4: included CMB bounds on dark matter-photon coupling from Wilkinson et al. (2014) and references added. Final revision matches published versio

El enfoque neogibsoniano como marco conceptual y metodológico para el diseño de programas de entrenamiento deportivo

The neogibsonian approach holds that the processes of perceptual and perceptual-motor learning consist of improving the detection and use of the abundant information that exists in task environments. This claim is the starting point for a conceptual and methodological framework used for the analysis of learning. The conceptual framework includes the concepts of the education of attention and calibration and, more recently, the ones of potential-based and direct learning. The present article introduces the neogibsonian approach and describes the implications of that approach for the design of training programs. In particular, the article addresses an explanation for the beneficial effects of variability in practice methods, and it considers the way in which variability should be introduced so as to achieve the beneficial effects

Attempted DNA extraction from a Rancho La Brea Columbian mammoth (Mammuthus columbi): prospects for ancient DNA from asphalt deposits.

Fossil-bearing asphalt deposits are an understudied and potentially significant source of ancient DNA. Previous attempts to extract DNA from skeletons preserved at the Rancho La Brea tar pits in Los Angeles, California, have proven unsuccessful, but it is unclear whether this is due to a lack of endogenous DNA, or if the problem is caused by asphalt-mediated inhibition. In an attempt to test these hypotheses, a recently recovered Columbian mammoth (Mammuthus columbi) skeleton with an unusual pattern of asphalt impregnation was studied. Ultimately, none of the bone samples tested successfully amplified M. columbi DNA. Our work suggests that reagents typically used to remove asphalt from ancient samples also inhibit DNA extraction. Ultimately, we conclude that the probability of recovering ancient DNA from fossils in asphalt deposits is strongly (perhaps fatally) hindered by the organic compounds that permeate the bones and that at the Rancho La Brea tar pits, environmental conditions might not have been ideal for the general preservation of genetic material