Forest Ecosystem Services: An Analysis of Worldwide Research

The relevance of forests to sustain human well-being and the serious threats they face have led to a notable increase of research works on forest ecosystem services during the last few years. This paper analyses the worldwide research dynamics on forest ecosystem services in the period from 1998 to 2017. A bibliometric analysis of 4284 articles was conducted. The results showed that the number of published research articles has especially increased during the last five years. In total, 68.63% of the articles were published in this period. This research line experiences a growing trend superior to the general publishing trend on forest research. In spite of this increase, its relative significance within the forest research is still limited. The most productive subject areas corresponded to Environmental Science, Agricultural and Biological Sciences and Social Sciences Economic topics are understudied. The scientific production is published in a wide range of journals. The three first publishing countries are United States, China and the United Kingdom. The most productive authors are attached to diverse research centres and their contributions are relatively recent. A high level of international cooperation has been observed between countries, institutions and authors. The findings of this study are useful for researchers since they give them an overview of the worldwide research trends on forest ecosystem services

Perceptions of Heritage among Students of Early Childhood and Primary Education

In recent decades, a growing awareness of the importance of preserving cultural heritage as a means of promoting sustainable development has been accompanied by a similar re-evaluation of the role of heritage education as a key driver of citizen engagement. The development and implementation of heritage education at all levels, particularly in the context of teacher training, is of vital importance. The aim of this study is to analyse student teachers’ understanding of heritage and its potential as an educational tool, in order to identify measures to enhance teacher training and practice with respect to heritage and heritage education. The research design consists of a comparative study of a non-random sample of 149 trainee teachers undertaking Bachelor’s degrees in Early Childhood Education and Primary Education at the University of Córdoba (Spain). The results reveal a mainly cultural conception of heritage among both groups, based on local material elements, and little sense of the link between heritage and present-day life. The students studying early childhood education were found to display a more specific knowledge of heritage in their answers, while the primary education students showed a greater awareness of identity and values as features of cultural heritage

Potential of a Two-Stage Variable Compression Ratio Downsized Spark Ignition Engine for Passenger Cars under different driving conditions

[EN] With the aim of reducing pollutant emissions from internal combustion engines (ICE), the application of stoichiometrically operated spark ignition (SI) engines, for light-duty vehicles, has been overcoming the compression ignition (CI) engines market share throughout the past years. The ability of a substantial reduction of the primary harmful emissions (HC, CO, and NOx) through the use of the simple three-way catalyst (TWC) is the main reason for that. Nonetheless, with increasing attention to CO2 emissions, the development of highly efficient downsized SI engines turn to be of enormous interest. The synergies of multiple systems such as direct injection, turbocharger, and variable valve actuation are able to lead the SI efficiencies closer to those of CI engines. However, to enable high load operation on such downsized engines, the compression ratio (CR) must be reduced due to knock limitations, reducing the partial-load operations efficiency. The implementation of two-stage variable compression ratio (VCR) systems enables the extraction of high thermal efficiency with high CR at lower loads and extended knock-free high load operation with low CR. In this study, the evaluation of a two-stage VCR system applied to a state-of-the-art downsized SI engine was made through standard driving cycle simulations. The VCR mechanism is composed of an eccentric element in the small end of the connecting rod, which is rotated to increase/decrease the effective connecting rod length, achieving the CRs of 12.11:1 and 9.56:1. The engine was run in an eddy-current dynamometer test bench throughout the essential operating range to obtain the brake specific fuel consumption (BSFC) map. The VCR mechanism CR switching delay was also experimentally characterized to derive a function of the operating conditions. The measured map was entered into the map-based driving cycle simulation with a sub-model to account for the isolated effects of the transient period encompassing the compression ratio switching. The results show that slow CR transitions lead to fuel consumption penalties, which suggests the need for optimizing the control strategies of the VCR system. Even though this penalty, once the gear up-shift speed is optimized for each driving cycle, the VCR system still enables fuel consumption reductions up to 3% on the WLTC driving cycle, up to 4% on the proposed urban driving cycles and up to 3% on highway driving cycles with respect to the fixed CR.This research has been partially funded by FEDER and the Spanish Government through project RTI2018-102025-B-I00. 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Machine learning for mortality analysis in patients with COVID-19

This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis where the endpoint variable is the reason for hospital discharge (home or deceased). The different methods applied show the importance of variables such as age, O2 saturation at Emergency Rooms (ER), and whether the patient comes from a nursing home. In addition, biclustering is used to globally analyze the patient-drug dataset, extracting segments of patients. We highlight the validity of the classifiers developed to predict the mortality, reaching an appreciable accuracy. Finally, interpretable decision rules for estimating the risk of mortality of patients can be obtained from the decision tree, which can be crucial in the prioritization of medical care and resources.This research was funded by Agencia Estatal de Investigación AEI/FEDER Spain, Project PGC2018-095895-B-I00, and Comunidad Autónoma de Madrid, Spain, Project S2017/BMD-368

Profiled support vector machines for antisense oligonucleotide efficacy prediction

BACKGROUND: This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises 315 AO molecules including 68 features each, inducing a problem well-suited to SVMs. The task of feature selection is crucial given the presence of noisy or redundant features, and the well-known problem of the curse of dimensionality. We propose a two-stage strategy to develop an optimal model: (1) feature selection using correlation analysis, mutual information, and SVM-based recursive feature elimination (SVM-RFE), and (2) AO prediction using standard and profiled SVM formulations. A profiled SVM gives different weights to different parts of the training data to focus the training on the most important regions. RESULTS: In the first stage, the SVM-RFE technique was most efficient and robust in the presence of low number of samples and high input space dimension. This method yielded an optimal subset of 14 representative features, which were all related to energy and sequence motifs. The second stage evaluated the performance of the predictors (overall correlation coefficient between observed and predicted efficacy, r; mean error, ME; and root-mean-square-error, RMSE) using 8-fold and minus-one-RNA cross-validation methods. The profiled SVM produced the best results (r = 0.44, ME = 0.022, and RMSE= 0.278) and predicted high (>75% inhibition of gene expression) and low efficacy (<25%) AOs with a success rate of 83.3% and 82.9%, respectively, which is better than by previous approaches. A web server for AO prediction is available online at . CONCLUSIONS: The SVM approach is well suited to the AO prediction problem, and yields a prediction accuracy superior to previous methods. The profiled SVM was found to perform better than the standard SVM, suggesting that it could lead to improvements in other prediction problems as well

Approaching sales forecasting using recurrent neural networks and transformers

Accurate and fast demand forecast is one of the hot topics in supply chain for enabling the precise execution of the corresponding downstream processes (inbound and outbound planning, inventory placement, network planning, etc). We develop three alternatives to tackle the problem of forecasting the customer sales at day/store/item level using deep learning techniques and the Corporaci\'on Favorita data set, published as part of a Kaggle competition. Our empirical results show how good performance can be achieved by using a simple sequence to sequence architecture with minimal data preprocessing effort. Additionally, we describe a training trick for making the model more time independent and hence improving generalization over time. The proposed solution achieves a RMSLE of around 0.54, which is competitive with other more specific solutions to the problem proposed in the Kaggle competition.Comment: Accepted for publication in Expert Systems and Application

Use of self-organizing maps for analyzing the behavior of canines displaced towards midline under interceptive treatment

Displaced maxillary permanent canine is one of the more frequent findings in canine eruption process and it?s easy to be outlined and early diagnosed by means of x-ray images. Late diagnosis frequently needs surgery to rescue the impacted permanent canine. In many cases, interceptive treatment to redirect canine eruption is needed. However, some patients treated by interceptive means end up requiring fenestration to orthodontically guide the canine to its normal occlusal position. It would be interesting, therefore, to discover the dental characteristics of patients who will need additional surgical treatment to interceptive treatment. To study the dental characteristics associated with canine impaction, conventional statistics have traditionally been used. This approach, although serving to illustrate many features of this problem, has not provided a satisfactory response or not provided an overall idea of the characteristics of these types of patients, each one of them with their own particular set of variables. Faced with this situation, and in order to analyze the problem of impaction despite interceptive treatment, we have used an alternative method for representing the variables that have an influence on this syndrome. This method is known as Self-Organizing Maps (SOM), a method used for analyzing problems with multiple variables. We analyzed 78 patients with a PMC angulation higher than 100º. All of them were subject to interceptive treatment and in 21 cases it was necessary to undertake the above-mentioned fenestration to achieve the final eruption of the canine. In this study, we describe the process of debugging variables and selecting the appropriate number of cells in SOM so as to adequately visualize the problem posed and the dental characteristics of patients with regard to a greater or lesser probability of the need for fenestration

Distribution and biogeographic trends of decapod assemblages from Galicia Bank (NE Atlantic) at depths between 700 and 1800m, with connexions to regional water masses

The GaliciaBank(NEAtlantic,42167′N–11174′W) isanisolatedseamount,nearNWSpain,acomplex geomorphological andsedimentarystructurethatreceivesinfluences fromcontrastingwatermassesof both northernandsouthernorigins.WithintheprojectINDEMARES,threecruiseswereperformedon the bankin2009(Ecomarg0709),2010(BanGal0810)and2011(BanGal0811)allinJuly–August. Decapods andothermacrobenthiccrustaceans(eucaridsandperacarids)werecollectedwithdifferent sampling systems,mainlybeamtrawls(BT,10mmofmeshsizeatcodend)andaGOC73ottertrawl (20 mmmeshsize).Sixty-sevenspeciesofdecapodcrustaceans,6euphausiids,19peracaridsand 1 ostracodwerecollectedatdepthsbetween744and1808m.Wefoundtwonewspecies,oneamember of theChirostylidae, Uroptychuscartesi Baba &Macpherson,2012,theotherofthePetalophthalmidae (Mysida) Petalophthalmus sp. A,inadditiontoanumberofnewbiogeographicspeciesrecordsfor European orIberianwaters.Ananalysisofassemblagesshowedageneralizedspeciesrenewalwith depth, withdifferentassemblagesbetween744and ca. 1400m(theseamounttopassemblage,STA)and between ca. 1500and1800m(thedeep-slopeassemblageoverseamount flanks,DSA).Thesewere respectivelyassociatedwithMediterraneanoutflow waters(MOW)andwithLabradorSeaWater(LSW). Another significant factorseparatingdifferentassemblagesovertheGalicianBankwastheco-occurrence of corals(bothcoloniesofhardcoralssuchas Lophelia pertusa and Madreporaoculata and/or gorgonians) in hauls.Munidopsids(Munidopsis spp.), chirostylids(Uroptychus spp.), andthehomolodromiid Dicranodromiamahieuxii formed apartofthiscoral-associatedassemblage.Dominantspeciesatthe STAwerethepandalid Plesionika martia (a shrimpofsubtropical-southerndistribution)andthecrabs Bathynectes maravigna and Polybiushenslowii, whereasdominantspeciesintheDSAwereofnorthern origin, thelithodid Neolithodes grimaldii and thecrangonid Glyphocrangonlongiristris, likelyassociated with LSW.Thediversity(H and J) ofsmallcrustaceans(collectedwithBT)seemedtobecontrolledbythe phytoplanktonblooms(satelliteChl a data) overbanksurface3monthsbeforethesamplings,bothatthe top (Spearman r¼0.57, p¼0.03) andonthe flanks (r¼0.74, p¼0.02) ofGaliciaBank,whilenosignificant relationships withChl a werefoundforthelargerdecapodscollectedwithGOC73,onaveragetheyfeed at thehighertrophiclevelsthanthosecollectedwithBT.Postprin