Population expansion of the invasive Pomacentridae Chromis limbata (Valenciennes, 1833) in Southern Brazilian coast: long-term monitoring, fundamental niche availability and new records

Human-mediated species invasions are recognized as a leading cause of global biotic homogenization and extinction. Studies on colonization events since early stages, establishment of new populations and range extension are scarce because of their rarity, difficult detection and monitoring. Chromis limbata is a reef-associated and non-migratory marine fish from the family Pomacentridae found in depths ranging between 3 and 45 m. The original distribution of the species encompassed exclusively the eastern Atlantic, including the Azores, Madeira and the Canary Islands. It is also commonly reported from West Africa between Senegal and Pointe Noire, Congo. In 2008, vagrant individuals of C. limbata were recorded off the east coast of Santa Catarina Island, South Brazil (27° 41' 44″ S, 48° 27' 53″ W). This study evaluated the increasing densities of C. limbata populations in Santa Catarina State shoreline. Two recent expansions, northwards to São Paulo State and southwards to Rio Grande do Sul State, are discussed, and a niche model of maximum entropy (MaxEnt) was performed to evaluate suitable C. limbata habitats. Brazilian populations are established and significantly increasing in most sites where the species has been detected. The distributional boundaries predicted by the model are clearly wider than their known range of occurrence, evidencing environmental suitability in both hemispheres from areas where the species still does not occur. Ecological processes such as competition, predation and specially habitat selectivity may regulate their populations and overall distribution range. A long-term monitoring programme and population genetics studies are necessary for a better understanding of this invasion and its consequences to natural communities.CNPq, Grant/Award Number: CNPq 475367/2006-5; ECOPERE-SE Project; FAPES, Grant/Award Number: PROFIX program No 10/2018 -T.O.: 348/2018; FAPESC, Grant/Award Number: Biodiversidade Marinha do Estado de Santa Catarina Project PI: A.L. FAPESC 4302/2010-8; FAPESC/CNPq, Grant/Award Number: SISBIOTA-Mar project PI: S.R.F. CNPq 563276/2010-0; FAPESC 6308/2011-8; Petrobras (BR), Grant/Award Number: MAArE Project; King Abdullah University of Science and Technology; Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorinfo:eu-repo/semantics/publishedVersio

A new evaluation of the uncertainty associated with CDIAC estimates of fossil fuel carbon dioxide emission

Three uncertainty assessments associated with the global total of carbon dioxide emitted from fossil fuel use and cement production are presented. Each assessment has its own strengths and weaknesses and none give a full uncertainty assessment of the emission estimates. This approach grew out of the lack of independent measurements at the spatial and temporal scales of interest. Issues of dependent and independent data are considered as well as the temporal and spatial relationships of the data. The result is a multifaceted examination of the uncertainty associated with fossil fuel carbon dioxide emission estimates. The three assessments collectively give a range that spans from 1.0 to 13% (2 σ). Greatly simplifying the assessments give a global fossil fuel carbon dioxide uncertainty value of 8.4% (2 σ). In the largest context presented, the determination of fossil fuel emission uncertainty is important for a better understanding of the global carbon cycle and its implications for the physical, economic and political world

Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Clustering patients on the basis of their individual course of low back pain over a six month period

<p>Abstract</p> <p>Background</p> <p>Several researchers have searched for subgroups in the heterogeneous population of patients with non-specific low back pain (LBP). To date, subgroups have been identified based on psychological profiles and the variation of pain.</p> <p>Methods</p> <p>This multicentre prospective observational study explored the 6- month clinical course with measurements of bothersomeness that were collected from weekly text messages that were sent by 176 patients with LBP. A hierarchical cluster analysis, Ward's method, was used to cluster patients according to the development of their pain.</p> <p>Results</p> <p>Four clusters with distinctly different clinical courses were described and further validated against clinical baseline variables and outcomes. Cluster 1, a "stable" cluster, where the course was relatively unchanged over time, contained young patients with good self- rated health. Cluster 2, a group of "fast improvers" who were very bothered initially but rapidly improved, consisted of patients who rated their health as relatively poor but experienced the fewest number of days with bothersome pain of all the clusters. Cluster 3 was the "typical patient" group, with medium bothersomeness at baseline and an average improvement over the first 4-5 weeks. Finally, cluster 4 contained the "slow improvers", a group of patients who improved over 12 weeks. This group contained older individuals who had more LBP the previous year and who also experienced most days with bothersome pain of all the clusters.</p> <p>Conclusions</p> <p>It is possible to define clinically meaningful clusters of patients based on their individual course of LBP over time. Future research should aim to reproduce these clusters in different populations, add further clinical variables to distinguish the clusters and test different treatment strategies for them.</p

Climatic Variability Leads to Later Seasonal Flowering of Floridian Plants

Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses

Fungal diversity associated to the olive moth, prays oleae Bernard : a survey for potential entomopathogenic fungi

Olive production is one of the main agricultural activities in Portugal. In the region of Trás-os-Montes this crop has been considerably affected by Prays oleae. In order to evaluate the diversity of fungi on P. oleae population of Trás-os-Montes olive orchards, larvae and pupae of the three annual generations (phyllophagous, antophagous and carpophagous) were collected and evaluated for fungal growth on their surface. From the 3828 larvae and pupae, a high percentage of individuals exhibited growth of a fungal agent (40.6%), particularly those from the phyllophagous generation. From all the moth generations, a total of 43 species from 24 genera were identified, but the diversity and abundance of fungal species differed between the three generations. Higher diversity was found in the carpophagous generation, followed by the antophagous and phyllophagous generations. The presence of fungi displaying entomopathogenic features was highest in the phyllophagous larvae and pupae, being B. bassiana the most abundant taxa. The first report of B. bassiana presence on P. oleae could open new strategies for the biocontrol of this major pest in olive groves, since the use of an already adapted species increases the guarantee of success of a biocontrol approach. The identification of antagonistic fungi able to control agents that cause major olive diseases, such as Verticillium dahliae, will benefit future biological control approaches for limiting this increasingly spreading pathogen.This work was supported by Science and Technology Foundation (Fundação para a Ciência e Tecnologia – FCT) project PTDC/AGR-AAM/102600/2008 “Entomopathogenic fungi associated to olive pests: isolation, characterization and selection for biological control”. The first author is grateful to the Science and Technology Foundation for the PhD grant SFRH/BD/44265/2008

Detection of inconsistencies in geospatial data with geostatistics

Almost every researcher has come through observations that “drift” from the rest of the sample, suggesting some inconsistency. The aim of this paper is to propose a new inconsistent data detection method for continuous geospatial data based in Geostatistics, independently from the generative cause (measuring and execution errors and inherent variability data). The choice of Geostatistics is based in its ideal characteristics, as avoiding systematic errors, for example. The importance of a new inconsistent detection method proposal is in the fact that some existing methods used in geospatial data consider theoretical assumptions hardly attended. Equally, the choice of the data set is related to the importance of the LiDAR technology (Light Detection and Ranging) in the production of Digital Elevation Models (DEM). Thus, with the new methodology it was possible to detect and map discrepant data. Comparing it to a much utilized detections method, BoxPlot, the importance and functionality of the new method was verified, since the BoxPlot did not detect any data classified as discrepant. The proposed method pointed that, in average, 1,2% of the data of possible regionalized inferior outliers and, in average, 1,4% of possible regionalized superior outliers, in relation to the set of data used in the study

An Ensemble Analysis of Electromyographic Activity during Whole Body Pointing with the Use of Support Vector Machines

We explored the use of support vector machines (SVM) in order to analyze the ensemble activities of 24 postural and focal muscles recorded during a whole body pointing task. Because of the large number of variables involved in motor control studies, such multivariate methods have much to offer over the standard univariate techniques that are currently employed in the field to detect modifications. The SVM was used to uncover the principle differences underlying several variations of the task. Five variants of the task were used. An unconstrained reaching, two constrained at the focal level and two at the postural level. Using the electromyographic (EMG) data, the SVM proved capable of distinguishing all the unconstrained from the constrained conditions with a success of approximately 80% or above. In all cases, including those with focal constraints, the collective postural muscle EMGs were as good as or better than those from focal muscles for discriminating between conditions. This was unexpected especially in the case with focal constraints. In trying to rank the importance of particular features of the postural EMGs we found the maximum amplitude rather than the moment at which it occurred to be more discriminative. A classification using the muscles one at a time permitted us to identify some of the postural muscles that are significantly altered between conditions. In this case, the use of a multivariate method also permitted the use of the entire muscle EMG waveform rather than the difficult process of defining and extracting any particular variable. The best accuracy was obtained from muscles of the leg rather than from the trunk. By identifying the features that are important in discrimination, the use of the SVM permitted us to identify some of the features that are adapted when constraints are placed on a complex motor task

A New Perspective on Transcriptional System Regulation (TSR): Towards TSR Profiling

It has been hypothesized that the net expression of a gene is determined by the combined effects of various transcriptional system regulators (TSRs). However, characterizing the complexity of regulation of the transcriptome is a major challenge. Principal component analysis on 17,550 heterogeneous human microarray experiments revealed that 50 orthogonal factors (hereafter called TSRs) are able to capture 64% of the variability in expression in a wide range of experimental conditions and tissues. We identified gene clusters controlled in the same direction and show that gene expression can be conceptualized as a process influenced by a fairly limited set of TSRs. Furthermore, TSRs can be linked to biological functions, as we demonstrate a strong relation between TSR-related gene clusters and biological functionality as well as cellular localization, i.e. gene products of similarly regulated genes by a specific TSR are located in identical parts of a cell. Using 3,934 diverse mouse microarray experiments we found striking similarities in transcriptional system regulation between human and mouse. Our results give biological insights into regulation of the cellular transcriptome and provide a tool to characterize expression profiles with highly reliable TSRs instead of thousands of individual genes, leading to a >500-fold reduction of complexity with just 50 TSRs. This might open new avenues for those performing gene expression profiling studies