Hunting spectro-temporal information in unevenly spaced paleoclimate time series

18 p.Here we present some preliminary results of a statistical–computational implementation to estimate the wavelet spectrum of unevenly spaced paleoclimate time series by means of the Morlet Weighted Wavelet Z-Transform (MWWZ). A statistical significance test is performed against an ensemble of first-order auto-regressive models (AR1) by means of Monte Carlo simulations. In order to demonstrate the capabilities of this implementation, we apply it to the oxygen isotope ratio (?18O) data of the GISP2 deep ice core (Greenland)

Hierarchical core-periphery structure in networks

We study core-periphery structure in networks using inference methods based on a flexible network model that allows for traditional onion-like cores within cores, but also for hierarchical tree-like structures and more general non-nested types of structure. We propose an efficient Monte Carlo scheme for fitting the model to observed networks and report results for a selection of real-world data sets. Among other things, we observe an empirical distinction between networks showing traditional core-periphery structure with a dense core weakly connected to a sparse periphery, and an alternative structure in which the core is strongly connected both within itself and to the periphery. Networks vary in whether they are better represented by one type of structure or the other. We also observe structures that are a hybrid between core-periphery structure and community structure, in which networks have a set of non-overlapping cores that correspond roughly to communities, surrounded by a single undifferentiated periphery. Computer code implementing our methods is available.Comment: code available: https://github.com/apolanco115/hc

Insulin-like growth factor 1 signaling in motor neuron and polyglutamine diseases: From molecular pathogenesis to therapeutic perspectives

The pleiotropic peptide insulin-like growth factor 1 (IGF-I) regulates human body homeostasis and cell growth. IGF-I activates two major signaling pathways, namely phosphoinositide-3-kinase (PI3K)/protein kinase B (PKB/Akt) and Ras/extracellular signal-regulated kinase (ERK), which contribute to brain development, metabolism and function as well as to neuronal maintenance and survival. In this review, we discuss the general and tissue-specific effects of the IGF-I pathways. In addition, we present a comprehensive overview examining the role of IGF-I in neurodegenerative diseases, such as spinal and muscular atrophy, amyotrophic lateral sclerosis, and polyglutamine diseases. In each disease, we analyze the disturbances of the IGF-I pathway, the modification of the disease protein by IGF-I signaling, and the therapeutic strategies based on the use of IGF-I developed to date. Lastly, we highlight present and future considerations in the use of IGF-I for the treatment of these disorders

Rainbow trapping of guided waves

We study theoretically the propagation of a wave packet that is a superposition of three s-polarized guided waves with different frequencies in a planar waveguide consisting of a dielectric medium with a graded index of refraction, sandwiched between perfectly conducting walls. The electric field at each point within the waveguide is calculated, and it is shown that each of the constituent modes ceases to propagate at a specific distance along the waveguide that depends on its frequency and on the geometrical and material parameters defining the waveguide. This simple model displays the phenomenon of rainbow trapping of guided waves in an explicit fashion, without the use of a negative index metamaterial

Dynamic wavelet correlation analysis for multivariate climate time series

The wavelet local multiple correlation (WLMC) is introduced for the first time in the study of climate dynamics inferred from multivariate climate time series. To exemplify the use of WLMC with real climate data, we analyse Last Millennium (LM) relationships among several large‑scale reconstructed climate variables characterizing North Atlantic: i.e. sea surface temperatures (SST) from the tropical cyclone main developmental region (MDR), the El Niño‑Southern Oscillation (ENSO), the North Atlantic Multidecadal Oscillation (AMO), and tropical cyclone counts (TC). We examine the former three large‑scale variables because they are known to influence North Atlantic tropical cyclone activity and because their underlying drivers are still under investigation. WLMC results obtained for these multivariate climate time series suggest that: (1) MDRSST and AMO show the highest correlation with each other and with respect to the TC record over the last millennium, and: (2) MDRSST is the dominant climate variable that explains TC temporal variability. WLMC results confirm that this method is able to capture the most fundamental information contained in multivariate climate time series and is suitable to investigate correlation among climate time series in a multivariate contextJ.M.P.M was funded by the PIC 444/18 – EU Interreg project MOSES (EAPA 224/2016), FEDER funds and the SEPE (Spanish Public Service of Employment). J.F.M. acknowledges research funding received from UPV/EHU Econometrics Research Group (Basque Government Dpt. of Education grant IT-1359-19) and Spanish Ministry of Economy and Business (grant MTM2016-74931-P)

A multi-resolution and multivariate analysis of the dynamic relationships between crude oil and petroleum-product prices

This paper proposes the use of a novel multivariate, dynamic approach wavelet local multiple correlation (WLMC) (Fernández-Macho, 2018) to analyse the relationship between oil time series in the time-scale domain. This approach is suitable for use with energy data of any kind that change over time and involve heterogeneous agents who make decisions across different time horizons and operate on different time scales. The study of the links between multivariate oil time series is of great importance in energy research, e.g., it is extremely important for petroleum industry refiners and investors to know the relationships and margins between output prices and crude oil costs. The estimation of wavelet correlations in a multivariate framework between such prices is a suitable way to analyse crude oil and petroleum products as a system. To exemplify the use of WLMC, we analyse the relationships between the prices of seven commodities: West Texas Intermediate crude oil and six distilled products (conventional gasoline, regular gasoline, heating oil, diesel fuel, kerosene and propane) from 10/06/2006 to 17/01/2017. The results reveal that the wavelet correlations are strong throughout the period studied and there is a strong decay in correlation values from 2013 to 2015. The most plausible explanation for this decay is overproduction of tight oil in the U.S. and a slowdown in global demand for oil. Furthermore, our results also reveal that heating oil, diesel and kerosene maximise the multiple correlation with respect to the other oil variables on different scales, indicating that these products are the most dependent variables in the crude-product/price system. WLMC offers new opportunities for applications in energy research and other fields. © 2018 Elsevier Lt

Controle da podridão cinzenta da maçã por produtos naturais biologicamente ativos

Indexación: Web of Science; ScieloBiorend SC (chitosan), BC-1000 EC (grapefruit extract plus bioflavonoids) and ECO-100 SC (bioflavonoids plus organic acids, citric phytoalexins, fatty acids, glycerides and sugars), respectively, suppressed grey rot of apple caused by B. cinerea by 80.1%, 79.0% and 76.5% when used as post-harvest treatments under controlled conditions. When applied as combined pre- and post-harvest treatments Biorend SC inhibited fruit rot by 49.9 %, while BC-1000 EC and ECO-100 SC were ineffective. None of the products inhibited fruit rot when applied as pre-harvest treatments under controlled conditions or as post-harvest treatments under commercial conditions. The algal polysaccharide ulvan used in post-harvest treatments suppressed grey rot by 56.0% under controlled conditions, but had no inhibitory effect on combined pre- and post-harvest treatments. The inability of products to activate defense mechanisms (chitinase and peroxidase) of fruits was consistent with the unsuccessful control of rot by pre-harvest treatment. The results suggest that the natural products used have potential for use in integrated management of Botrytis rot when applied after harvest.Biorend SC (quitosana), BC-1000 EC (extrato de toranja mais flavonóides), e ECO-100 SC (bioflavonóides mais ácidos orgânicos, fitoalexinas cítricas, ácidos graxos glicerídeos e açúcares) inibiram em 80,1%, 79,0% e 76,5%, respectivamente, a podridão causada por Botrytis cinerea quando utilizados no tratamento pós-colheita de frutos de maçã sob condições controladas.Tratamento combinado de Biorend SC, com aplicação tanto em pré como no pós-colheita, proporcionou 49,9% de inibição da podridão, enquanto BC-1000 e ECO-100 EC não foram efetivos. Nenhum desses produtos inibiu a podridão cinzenta, quando utilizados em tratamento de pré-colheita em condições controladas ou em tratamento de pós-colheita em condições comerciais. O polissacarídeo algal ulvana, utilizado nos tratamentos de pós-colheita, reduziu em 56% a podridão cinzenta das maçãs em condições controladas, mas não teve efeito inibitório nos tratamentos combinados de pré e pós-colheita. A incapacidade dos produtos em ativar mecanismos de defesa (quitinases e peroxidases) nos frutos, após o tratamento em pré-colheita, foi consistente com a falta de controle da podridão nesse tipo de ensaio. Pelos resultados, sugere-se que os produtos naturais utilizados apresentam potencial para a utilização no manejo integrado da podridão de Botrytis quando aplicados em pós-colheita.http://ref.scielo.org/kcxb9

A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causality test

This paper presents an analysis of EU peripheral (so-called PIIGS) stock market indices and the SandP Europe 350 index (SPEURO), as a European benchmark market, over the pre-crisis (2004 2007) and crisis (2008 2011) periods. We computed a rolling-window wavelet correlation for the market returns and applied a non-linear Granger causality test to the wavelet decomposition coefficients of these stock market returns. Our results show that the correlation is stronger for the crisis than for the pre-crisis period. The stock market indices from Portugal, Italy and Spain were more interconnected among themselves during the crisis than with the SPEURO. The stock market from Portugal is the most sensitive and vulnerable PIIGS member, whereas the stock market from Greece tends to move away from the European benchmark market since the 2008 financial crisis till 2011. The non-linear causality test indicates that in the first three wavelet scales (intraweek, weekly and fortnightly) the number of uni-directional and bi-directional causalities is greater during the crisis than in the pre-crisis period, because of financial contagion. Furthermore, the causality analysis shows that the direction of the Granger cause effect for the pre-crisis and crisis periods is not invariant in the considered time-scales, and that the causality directions among the studied stock markets do not seem to have a preferential direction. These results are relevant to better understand the behaviour of vulnerable stock markets, especially for investors and policymakers. © 2017 Elsevier B.V

La apuesta ética por la inteligencia artificial. Una perspectiva europea

Las noticias sobre inteligencia artificial siempre general alarma, sobre todo acerca de crear entes autónomos que emulen a los humanos. El estado actual de la tecnología hace pensar que eso es todavía irrealizable. Sin embargo, existen riesgos en el uso de esas tecnologías que demandan un control socia

Impact of sitagliptin on endometrial mesenchymal stem-like progenitor cells : a randomised, double-blind placebo-controlled feasibility trial

Background: Recurrent pregnancy loss (RPL) is associated with the loss of endometrial mesenchymal stem-like progenitor cells (eMSC). DPP4 inhibitors may increase homing and engraftment of bone marrow-derived cells to sites of tissue injury. Here, we evaluated the effect of the DPP4 inhibitor sitagliptin on eMSC in women with RPL, determined the impact on endometrial decidualization, and assessed the feasibility of a full-scale clinical trial. Methods: A double-blind, randomised, placebo-controlled feasibility trial on women aged 18 to 42 years with a history of 3 or more miscarriages, regular menstrual cycles, and no contraindications to sitagliptin. Thirty-eight subjects were randomised to either 100 mg sitagliptin daily for 3 consecutive cycles or identical placebo capsules. Computer generated, permuted block randomisation was used to allocate treatment packs. Colony forming unit (CFU) assays were used to quantify eMSC in midluteal endometrial biopsies. The primary outcome measure was CFU counts. Secondary outcome measures were endometrial thickness, study acceptability, and first pregnancy outcome within 12 months following the study. Tissue samples were subjected to explorative investigations. Findings: CFU counts following sitagliptin were higher compared to placebo only when adjusted for baseline CFU counts and age (RR: 1.52, 95% CI: 1.32–1.75, P<0.01). The change in CFU count was 1.68 in the sitagliptin group and 1.08 in the placebo group. Trial recruitment, acceptability, and drug compliance were high. There were no serious adverse events. Explorative investigations showed that sitagliptin inhibits the expression of DIO2, a marker gene of senescent decidual cells. Interpretation: Sitagliptin increases eMSCs and decreases decidual senescence. A large-scale clinical trial evaluating the impact of preconception sitagliptin treatment on pregnancy outcome in RPL is feasible and warranted. Funding: Tommy's Baby Charity. Clinical trial registration: EU Clinical Trials Register no. 2016-001120-54