The Holocene Cedrus pollen record from Sierra Nevada (S Spain), a proxy for climate change in N Africa

Comprehending the effects of climate variability and disturbance on forested ecosystems is paramount to successfully managing forest environments under future climate scenarios (e.g., global warming, aridi-fication increase). Changes in fossil pollen abundance in sedimentary archives record past vegetation dynamics at regional scales, mainly related to climate changes and, in the last few millennia, to human impact. Pollen records can thus provide long databases with information on how the environment reacted to climate change before the historical record. In this study, we synthesized fossil pollen data from seven sites from the Sierra Nevada in southern Spain to investigate the response of forests in the western Mediterranean area to millennial-scale climate changes and to human impact during the Holocene. In particular, here we focused on Cedrus pollen abundances, which most-likely originated from Northern Africa and were carried to Sierra Nevada by wind. Cedrus pollen has received little attention in the Iberian Peninsula palynological records, for it occurs in low concentrations and has an African source, and thus this article explores the potential to reconstruct its past history and climate. Although Cedrus abundances are generally lower than 1% in the studied pollen samples, a comparison with North African (Moroccan) Cedrus pollen records shows similar trends at long- and short-term time-scales. Therefore, this record could be used as a proxy for changes in this forest species in North Africa. As observed in the Sierra Nevada synthetic record, the increasing trend of Cedrus pollen during the Middle and Late Holocene closely correlates with decreasing summer insolation. This would have produced overall cooler annual temperatures in Northern Africa (Middle Atlas and Rif Mountains) as well as lower summer evaporation, benefiting the growth of this cool-adapted montane tree species while increasing available moisture during the summer, which is critical for this water-demanding species. Millennial-scale variability also characterizes the Sierra Nevada Cedrus synthetic pollen record. Cedrus abundance oscillations co-vary with well-known millennial-scale climatic variability that controlled cedar abundance and altitudinal distribution in montane areas of N Africa. (C) 2020 Elsevier Ltd. All rights reserved.Peer reviewe

High-affinity chemotaxis to histamine of the human pathogen Pseudomonas aeruginosa

FEMS 2019: 8th congress of European Microbiologists, in Glasgow, Scotland, 7-11 July 201

Fine‐tuning modulation of oxidation-mediated posttranslational control of Bradyrhizobium diazoefficiens FixK2 transcription factor

FixK2 is a CRP/FNR‐type transcription factor that plays a central role in a sophisticated regulatory network for the anoxic, microoxic and symbiotic lifestyles of the soybean endosymbiont Bradyrhizobium diazoefficiens. Apart of the balanced expression of the fixK2 gene under microoxic conditions (induced by the two‐component regulatory system FixLJ and negatively auto‐repressed), FixK2 activity is posttranslationally controlled by proteolysis, and by oxidation of a singular cysteine residue (C183) near its DNA‐binding domain. To simulate permanent oxidation of FixK2, we replaced C183 for aspartic acid. Purified C183D FixK2 protein showed both low DNA binding and in vitro transcriptional activation from the promoter of the fixNOQP operon, required for respiration under symbiosis. However, in a B. diazoefficiens strain coding for C183D FixK2, expression of a fixNOQP’‐‘lacZ fusion was similar to that in the wild type, when both strains were grown microoxically. The C183D FixK2 encoding strain also showed a wild‐type phenotype in symbiosis with soybeans, and increased fixK2 gene expression levels and FixK2 protein abundance in cells. These two latter observations together with a global transcriptional profile of the microoxically cultured C183D FixK2 encoding strain suggest the existence of a finely tuned regulatory strategy to counterbalance the oxidation‐mediated inactivation of FixK2 in vivo

Paleoenvironmental evolution of Laguna Seca lake (Sierra Nevada, southern Iberia) since the Late Glacial

Comunicación oral en XXI INQUA Congress. Rome (Italy). 14-20th july 2023Laguna Seca lake at 2259 masl has provided the longest alpine sedimentary record in southern Iberia, registering the last ~18 kyr in a ~14-meter-long sediment core. The oldest part of the sedimentary record represents a phase of subaerial debris flows and a small glacier/nivation hollow. The sediment characteristics abruptly changed at ~15.7 cal kyr BP, when a lake environment was established. A multi-proxy approach (magnetic susceptibility, organic geochemical analyses in bulk sediment, XRF core scanner data, and algae identification) has allowed the characterization of three different environmental phases in this lake. Deep lake conditions are identified from ~15.7 to ~10.6 cal kyr BP, agreeing with overall increasing precipitation in southern Iberia coinciding with augmenting summer insolation. This part of the record is characterized by grey lutites with high total organic carbon (TOC) content, high algae productivity, high vascular plant inputs (high C/N ratio) from the catchment and low Fe/S ratio, suggesting low oxygen conditions in the water-sediment interphase. Between ~10.6 and 8.2-8.0 cal kyr BP higher TOC and low Fe/S ratio are also recorded as well as higher algae content and low C/N ratio suggesting high aquatic production and more algae contribution to the local organic matter pool. This period registered the highest lake levels agreeing with summer insolation maximum and highest precipitation in southern Iberia. An abrupt lowering of the lake level is recorded after 8.0 cal kyr BP in the area. This is deduced by the decrease in TOC and algae in the sediments and more siliciclastic contribution from the catchment basin, evidenced by a high increase in siliciclastic elements (Si, Al, K, Ti, among others), with increased oxic conditions in the water-sediment interphase pointed out by the high increase in Fe/S ratio. Additionally, a potential increase in north African aeolian inputs (rich in Fe cations and Fe compounds) can be interpreted for the Middle and Late Holocene, evidenced by high Fe/Al values. This environmental change agrees with an aridification trend previously observed in the southern Iberian Peninsula

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

Computational approaches to Explainable Artificial Intelligence:Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.</p

The Eurasian Modern Pollen Database (EMPD), version 2

The Eurasian (nee European) Modern Pollen Database (EMPD) was established in 2013 to provide a public database of high-quality modern pollen surface samples to help support studies of past climate, land cover, and land use using fossil pollen. The EMPD is part of, and complementary to, the European Pollen Database (EPD) which contains data on fossil pollen found in Late Quaternary sedimentary archives throughout the Eurasian region. The EPD is in turn part of the rapidly growing Neotoma database, which is now the primary home for global palaeoecological data. This paper describes version 2 of the EMPD in which the number of samples held in the database has been increased by 60% from 4826 to 8134. Much of the improvement in data coverage has come from northern Asia, and the database has consequently been renamed the Eurasian Modern Pollen Database to reflect this geographical enlargement. The EMPD can be viewed online using a dedicated map-based viewer at https://empd2.github.io and downloaded in a variety of file formats at https://doi.pangaea.de/10.1594/PANGAEA.909130 (Chevalier et al., 2019).Peer reviewe