Finite Frames and Graph Theoretic Uncertainty Principles

The subject of analytical uncertainty principles is an important field within harmonic analysis, quantum physics, and electrical engineering. We explore uncertainty principles in the context of the graph Fourier transform, and we prove additive results analogous to the multiplicative version of the classical uncertainty principle. We establish additive uncertainty principles for finite Parseval frames. Lastly, we examine the feasibility region of simultaneous values of the norms of a graph differential operator acting on a function $f\in l^2(G)$ and its graph Fourier transform

Cytokeratin 18 in plasma of patients with gastrointestinal adenocarcinoma as a biomarker of tumour response

BACKGROUND: Plasma biomarkers may be particularly useful as a predictor or early marker of clinical response to treatment in addition to radiological imaging. Cytokeratin 18 (CK18) is an epithelial-specific cytokeratin that undergoes cleavage by caspases during apoptosis. Measurement of caspase-cleaved (CK18-Asp396) or total cytokeratin 18 (CK18) from epithelial-derived tumours could be a simple, non-invasive way to monitor or predict responses to treatment. METHODS: Soluble plasma CK18-Asp396 and CK18 were measured by ELISA from 73 patients with advanced gastrointestinal adenocarcinomas before treatment and during chemotherapy, as well as 100 healthy volunteers. RESULTS: Both CK18-Asp396 and total CK18 plasma levels were significantly higher in patients compared with the healthy volunteers (P = 0.015, P < 0.001). The total CK18 baseline plasma levels before treatment were significantly higher (P = 0.009) in patients who develop progressive disease than those who achieve partial response or stable disease and this correlation was confirmed in an independent validation set. The peak plasma levels of CK18 occurring in any cycle following treatment were also found to be associated with tumour response, but peak levels of CK18-Asp396 did not reach significance (P = 0.01, and P = 0.07, respectively). CONCLUSION: Plasma levels CK18 are a potential marker of tumour response in patients with advanced gastrointestinal malignancy

Tropical tree growth driven by dry-season climate variability

Interannual variability in the global land carbon sink is strongly related to variations in tropical temperature and rainfall. This association suggests an important role for moisture-driven fluctuations in tropical vegetation productivity, but empirical evidence to quantify the responsible ecological processes is missing. Such evidence can be obtained from tree-ring data that quantify variability in a major vegetation productivity component: woody biomass growth. Here we compile a pantropical tree-ring network to show that annual woody biomass growth increases primarily with dry-season precipitation and decreases with dry-season maximum temperature. The strength of these dry-season climate responses varies among sites, as reflected in four robust and distinct climate response groups of tropical tree growth derived from clustering. Using cluster and regression analyses, we find that dry-season climate responses are amplified in regions that are drier, hotter and more climatically variable. These amplification patterns suggest that projected global warming will probably aggravate drought-induced declines in annual tropical vegetation productivity. Our study reveals a previously underappreciated role of dry-season climate variability in driving the dynamics of tropical vegetation productivity and consequently in influencing the land carbon sink.We acknowledge financial support to the co-authors provided by Agencia Nacional de Promoción Científica y Tecnológica, Argentina (PICT 2014-2797) to M.E.F.; Alberta Mennega Stichting to P.G.; BBVA Foundation to H.A.M. and J.J.C.; Belspo BRAIN project: BR/143/A3/HERBAXYLAREDD to H.B.; Confederação da Agricultura e Pecuária do Brasil - CNA to C.F.; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES, Brazil (PDSE 15011/13-5 to M.A.P.; 88881.135931/2016-01 to C.F.; 88887.199858/2018-00 to G.A.-P.; Finance Code 001 for all Brazilian collaborators); Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq, Brazil (ENV 42 to O.D.; 1009/4785031-2 to G.C.; 311874/2017-7 to J.S.); CONACYT-CB-2016-283134 to J.V.-D.; CONICET to F.A.R.; CUOMO FOUNDATION (IPCC scholarship) to M.M.; Deutsche Forschungsgemeinschaft - DFG (BR 1895/15-1 to A.B.; BR 1895/23-1 to A.B.; BR 1895/29-1 to A.B.; BR 1895/24-1 to M.M.); DGD-RMCA PilotMAB to B.T.; Dirección General de Asuntos del Personal Académico of the UNAM (Mexico) to R.B.; Elsa-Neumann-Scholarship of the Federal State of Berlin to F.S.; EMBRAPA Brazilian Agricultural Research Corporation to C.F.; Equatorian Dirección de Investigación UNL (21-DI-FARNR-2019) to D.P.-C.; São Paulo Research Foundation FAPESP (2009/53951-7 to M.T.-F.; 2012/50457-4 to G.C.; 2018/01847‐0 to P.G.; 2018/24514-7 to J.R.V.A.; 2019/08783-0 to G.M.L.; 2019/27110-7 to C.F.); FAPESP-NERC 18/50080-4 to G.C.; FAPITEC/SE/FUNTEC no. 01/2011 to M.A.P.; Fulbright Fellowship to B.J.E.; German Academic Exchange Service (DAAD) to M.I. and M.R.; German Ministry of Education, Science, Research, and Technology (FRG 0339638) to O.D.; ICRAF through the Forests, Trees, and Agroforestry research programme of the CGIAR to M.M.; Inter-American Institute for Global Change Research (IAI-SGP-CRA 2047) to J.V.-D.; International Foundation for Science (D/5466-1) to M.I.; Lamont Climate Center to B.M.B.; Miquelfonds to P.G.; National Geographic Global Exploration Fund (GEFNE80-13) to I.R.; USA’s National Science Foundation NSF (IBN-9801287 to A.J.L.; GER 9553623 and a postdoctoral fellowship to B.J.E.); NSF P2C2 (AGS-1501321) to A.C.B., D.G.-S. and G.A.-P.; NSF-FAPESP PIRE 2017/50085-3 to M.T.-F., G.C. and G.M.L.; NUFFIC-NICHE programme (HEART project) to B.K., E.M., J.H.S., J.N. and R. Vinya; Peru ‘s CONCYTEC and World Bank (043-2019-FONDECYT-BM-INC.INV.) to J.G.I.; Peru’s Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (FONDECYT-BM-INC.INV 039-2019) to E.J.R.-R. and M.E.F.; Programa Bosques Andinos - HELVETAS Swiss Intercooperation to M.E.F.; Programa Nacional de Becas y Crédito Educativo - PRONABEC to J.G.I.; Schlumberger Foundation Faculty for the Future to J.N.; Sigma Xi to A.J.L.; Smithsonian Tropical Research Institute to R. Alfaro-Sánchez.; Spanish Ministry of Foreign Affairs AECID (11-CAP2-1730) to H.A.M. and J.J.C.; UK NERC grant NE/K01353X/1 to E.G.Peer reviewe

Graph theoretical uncertainty principles

Abstract-We develop a graph theoretic set of uncertainty principles with tight bounds for difference estimators acting simultaneously in the graph domain and the frequency domain. We show that the eigenfunctions of a modified graph Laplacian operator dictate the upper and lower bounds for the inequalities

Editorial: Advances in thermal imaging

No abstract available

Mean (± SD) posterior distributions estimated from Bayesian stable isotope mixing models of the proportional contribution of six potential prey species to wolf diet in northwestern Montana, USA, 2009.

<p>Four models were specified with two different prior distributions (i.e., non-informative [N], and informative [I]) and two different discrimination factors (i.e., red fox [F] and wolf [W]).</p><p>Mean (± SD) posterior distributions estimated from Bayesian stable isotope mixing models of the proportional contribution of six potential prey species to wolf diet in northwestern Montana, USA, 2009.</p