dataesr/scientific-paragraphs-categorization huggingface dataset:
The first classifier detects particular DNP3 cyberattacks (i. e. , multiclass classification), including (a) DNP3 injection, (b) DNP3 Flooding, (c) DNP3 reconnaissance, (d) DNP3 replay attacks and (e) DNP3 masquerading. If the first classifier classifies a network flow as normal, then the second classifier is activated to distinguish a possible anomaly (i. e. , binary classification). The functionality of the first classifier relies on a decision tree, while the second adopts the DIDEROT autoencoder. Finally, based on the outcome of the DIDEROT Analysis Engine, the Response Module generates security events and informs the Ryu SDN controller in order to corrupt the malicious network flow. The evaluation results demonstrate the efficacy of DIDEROT to detect DNP3 cyberattacks. In  [25] , P. Manso et al.
The conceptual frameworks and their components are placed within the Application Plane. In this plane, the most important operational decisions take place, such as the detection of a cyberattack or the decision to isolate a malicious network flow. Finally, the Management Plane provides all complementary functionalities related to the system usability, including dashboard, databases, and privacy preserving mechanisms to ensure the privacy of data subjects affected by the SDN-microSENSE operation. It is worth mentioning that the Management Plane is placed vertically since it provides complementary services to all planes. Indicatively, the Asset Inventory database is used by all components of the Application Plane in order to access information related to the underlying EPES/SG components. Concurrently, the SDN Synchronisation and Coordination Service (SCS) is accessed by both the Application Plane and the Controller Plane to retrieve the master SDN-C for a particular switch and carry out the master SDN-C election process, respectively.
XL-SIEM and Detectors XL-SIEM composes a SIEM system capable of detecting multiple EPES cyberattacks by allowing the interconnection with a myriad of security detectors. In particular, the XL-SIEM consists of (a) XL-SIEM agents for processing information received from security detectors and distributed across the EPES infrastructure and (b) the XL-SIEM core, which integrates an event correlation engine, a database and a management dashboard. The security detectors are deployed throughout the EPES infrastructure and undertake to recognise various EPES cyberattacks and anomalies, generating the respective security logs. To this end, both signature/specification-based techniques and ML/DL-based methods are applied. First, Suricata is used with the Quickdraw ICS signatures and specification rules developed during the project.
Next, the XL-SIEM agents are responsible for collecting and normalising the various security logs generated by the XL-SIEM detectors with a standardised format. The normalised events are called security events and are transmitted by the XL-SIEM agents to the XL-SIEM engine or external components. Subsequently, the XL-SIEM engine receives the security events and correlates them, thus producing security alerts. A security alert is defined as a set of security events related to each other through the correlation rules defined by security experts. Finally, the XL-SIEM database and XL-SIEM dashboard store and visualise the security events and alerts generated by XL-SIEM, respectively.
SDN-SELF: SDN-enabled Self-hEaLing Framework The goal of the SDN-SELF framework is twofold. First, it mitigates the possible anomalies and intrusions detected by XL-EPDS. Secondly, SDN-SELF is responsible for the energy management and optimisation required after the mitigation processes. In particular, SDN-SELF comprises five components: (a) Electric Data Analysis Engine (EDAE), (b) the Islanding and optImisation fraMework (IIM), (c) the rEstoration Machine-learning frame-wOrk (EMO) and (d) the Blockchain-based Energy Trading System. Each component of the SDN-SELF framework is further analysed in the following subsections, respectively.
SDN Controller The SDN-C undertakes to program the underlying intermediary network devices (i. e. , SDN switches) according to the instructions from the Application Plane, using OpenFlow v1. 3. Based on the Ryu SDN controller  [48] , the SDN-C is a multi-modular application that deploys multiple modules that extend the Ryu functionalities. In particular, SDN-C integrates the following new modules: (a) simpleswitch_enhanced, and (b) the ZooClient module. In more detail, the simpleswitch_enhanced module undertakes to re-actively fill the OpenFlow tables of the underlying SDN switches. In comparison to the original Ryu implementation, the enhanced reactive application of SDN-microSENSE keeps a record of source MAC addresses and ingress ports of Ethernet frames; therefore, the SDN-C can detect cases of broadcast storms and inserts the corresponding OpenFlow rules to prevent them.
The loop-free topology relies on EDAE in order to apply optimisations and enable redundant paths. The SDN-C undertakes to program the underlying intermediary network devices (i. e. , SDN switches) according to the instructions from the Application Plane, using OpenFlow v1. 3. Based on the Ryu SDN controller  [48] , the SDN-C is a multi-modular application that deploys multiple modules that extend the Ryu functionalities. In particular, SDN-C integrates the following new modules: (a) simpleswitch_enhanced, and (b) the ZooClient module. In more detail, the simpleswitch_enhanced module undertakes to re-actively fill the OpenFlow tables of the underlying SDN switches. In comparison to the original Ryu implementation, the enhanced reactive application of SDN-microSENSE keeps a record of source MAC addresses and the ingress ports of Ethernet frames; therefore, the SDN-C can detect cases of broadcast storms and inserts the corresponding Open-Flow rules to prevent them.
Origin of Vertebrate ZP Genes Studies on the evolution of the ZP genes in vertebrates greatly benefitted from the increase in molecular data and complete genomes available. Using a phylogenetic approach and analyzing the cDNA sequences available in Genbank, Spargo and Hope divided the different ZP genes of vertebrates into four subfamilies (named ZPA, ZPB, ZPC, and ZPX)  [33]. They proposed that at least one ZP gene evolved during the earliest stages of vertebrate evolution, probably before the divergence of fish and amphibians. This ancestral ZP gene gave rise to four different subfamilies as a result of at least three duplication events  [33]. Some of these genes were later lost in some lineages and remain present only in fish or amphibians. Goudet et al. (2008)  established a more complete list of vertebrate ZP genes, and classified them into at least six subfamilies: ZP1, ZP2, ZP3, ZP4, ZPAX, and ZPD.
In a study made in our lab, we identified three ZP3-related genes in marsupials, which were named ZP3-a, ZP3-b, and ZP3-c  [34]. The presence of this duplication in ZP3 gene further complicates the models of ZP composition. In a recent study,  Feng et al. (2018)  identified eight ZP gene subfamilies (ZP1/4, ZP2, ZPAX, ZPY, ZPD, ZP3-1, ZP3-2, and ZP3-3), which were grouped into three clusters. The first cluster grouped ZP1/4, ZP2, ZPAX, and ZPY, the second one contained only ZPD and the third ZP3-1, ZP3-2, and ZP3-3  [35]. A phylogenetic analysis of the two ZP3 datasets  [26, 27]  indicated that our ZP3-a, b, and c sequences belong to the ZP3-1 subfamily of  Feng et al. (2018)  and should be named ZP3-1a, 1b, and 1c (Figure  S1 ). Based on their phylogenetic analysis, Feng et al. also suggested that their three clusters have separate origins, the three ancestral genes expanding into eight subfamilies during the evolution of vertebrates  [35].
Data Availability Statement: The sequences used to reconstruct the phylogeny presented in Figure S1 were retrieved from Genbank (https://www. ncbi. nlm. nih. gov/genbank/, accessed on 22 March 2021) and Ensembl (http://www. ensembl. org/index. html, accessed on 22 March 2021) following Feng et al. , 2018 and Moros-Nicolas et al. , 2018.
As such, it has been shown that an extension of the ion channel into the reservoir, referred to as an "ion selective cap" can expand the desired ohmic regime. The ion selective cap increases the effective inlet area and thus provides an increased supply of ions at the ion channel inlet. [16] In other membrane separation processes, it is well known that the overall resistance has a strong dependency on flow rates at the feeding side of the membrane, especially at low concentrations (<100 × 10 -3 m). [17] ith the hybrid geometry presented here, we investigate if the addition of a constant flow, together with extension of the ion channel into the reservoir, can expand the ohmic regime further. We investigated the hybrid microfluidic iontronic probe concept with a finite element model based on the Nernst-Planck-Poisson and Navier-Stokes equations using COMSOL Multiphysics software.
Acknowledgements The authors wish to thank  Kosala Wijeratne  for the electropolymerization of PEDOT:Tos, and  Tobias Abrahamsson  for providing C-HPG. Mikhail Vagin , and  Erik Gabrielsson  for their input and critical discussion, and  Henrik Ekström  for his assistance with COMSOL. This work was funded by grants from the  Swedish Foundation for Strategic Research , the  Knut and Alice Wallenberg Foundation ,  Vinnova , and the  FLAG-ERA   JTC2017  project  EPIGRAPH  ( ANR-17-GRF2-0001 ). Additional funding was provided by the  Swedish Research Council , the  European Research Council  ( ERC Advanced Grant   2018 ,  Magnus Berggren ), the  Swedish Government Strategic Research Area in Materials Science on Advanced Functional Materials at Linköping University  (Faculty Grant  SFO-Mat-LiU No.
However, the drawbacks of these processes are their long life cycle. The Table  1  summarizes the main methods and processes for recycling batteries. The Li-ion battery leachate composition remains complex and requires a new recycling processes development to best meet industrial needs. In this study, the leachate studied results from an innovative and more environmentally friendly process of the material battery NMC dissolution  [24]. The leachate contains copper, cobalt, nickel, manganese and lithium in sulfate media as presented in Table  2. The separation of these metals remains a challenge in terms of cost, environmental friendliness, and efficiency. Based on the literature and the thermodynamic study carriedout with Visual Minteq 3. 0 (KTH Royal Institute of Technology, Stockholm, Sweden) software, it has been possible to identify the optimum experimental conditions for cobalt (II) hydroxide recovery.
Materials and Methods 2. 1. Material 2. 1. 1. Thermodynamic Prediction on Visual Minteq 3. 0 Software Visual Minteq 3. 0 is a software for the simulation of thermodynamic equilibria, used in the calculation of metal speciation, solubility, and sorption equilibria. The advantage of using this software is the time saving, the accuracy of the results and especially the prediction of dissolution or precipitation in a complex medium, which is fundamental in this context of study. The thermodynamic database used in this software is thermos. vdb and comp_2008. vdb for inorganic species. The input data of the model are the total concentrations of the different components in solution, presented in Table  2. For all calculations, the system under study is at thermodynamic equilibrium. Thus, kinetic considerations are not taken into account in the simulations.
Genome evolution is driven by the activity of transposable elements (TEs). The spread of TEs can have deleterious effects including the destabilization of genome integrity and expansions. However, the precise triggers of genome expansions remain poorly understood because genome size evolution is typically investigated only among deeply divergent lineages. Here, we use a large population genomics dataset of 284 individuals from populations across the globe of Zymoseptoria tritici, a major fungal wheat pathogen. We built a robust map of genome-wide TE insertions and deletions to track a total of 2456 polymorphic loci within the species. We show that purifying selection substantially depressed TE frequencies in most populations, but some rare TEs have recently risen in frequency and likely confer benefits.
tritici an ideal model to recapitulate the process of TE insertion dynamics, adaptive evolution, and changes in genome size at the population level. Here, we retrace the population-level context of TE insertion dynamics and genome size changes across the species range by analyzing populations sampled on four continents for a total of 284 genomes. We developed a robust pipeline to detect newly inserted TEs using short read sequencing datasets. Combining analyses of selection and knowledge of the colonization history of the pathogen, we tested whether population bottlenecks were associated with substantial changes in the TE content and the size of genomes.
Detection of candidate TE loci underlying recent adaptation The TE transposition activity can generate adaptive genetic variation. To identify the most likely candidate loci, we analyzed insertion frequency variation among populations as an indicator for recent selection. Across all populations, the insertion frequencies differed only weakly with a strong skew toward extremely low F ST values (mean = 0. 0163; Figure  3A, B , Figure  3 -figure supplement 1). To further analyze evidence for TE-mediated adaptive evolution, we screened a genome-wide SNP dataset for evidence of selective sweeps using selection scans. We found 16. 5 % of all TE loci located in regions of selective sweep. Given our population sampling of two population pairs, we tested for adaptive TE insertions in selective sweep regions either in the North American or European population pairs.
Retrotransposons Unusual patterns in population differentiation at TE loci suggests that TE activity may substantially vary across populations (Figure  6 , Figure  4 -source data 1). To analyze this, we first identified the total TE content across all loci per isolate. We found generally lower TE numbers in the Middle Eastern population from Israel (Figure  6A-C , Figure  6 -figure supplement 1), which is close to the pathogen's center of origin  (Stukenbrock et al. , 2007). Populations that underwent at least one migration bottleneck showed a substantial burst of TEs across all major superfamilies. These populations included the two populations from Europe collected in 1999 and 2016 and the North American population from 1990, as well as the Australian population. We found a second stark increase in TE content in the North American population sampled in 2015 at the same site as the population from 1990.
We corrected for variation in the GC content of different sequencing datasets by downsampling reads to generate balanced sequencing read sets prior to assembly (see Materials and methods). We also excluded all reads mapping to accessory chromosomes because different isolates are known to differ in the number of these chromosomes. Genome assemblies were checked for completeness by retrieving the phylogenetically conserved BUSCO genes (Figure  7A ). Genome assemblies across different populations carry generally >99% complete BUSCO gene sets, matching the completeness of reference-quality genomes of the same species  (Badet et al. , 2020). The completeness of the assemblies showed no correlation with either TE or GC content of the genomes. GC content was inversely correlated with genome size consistent with the expansion of repetitive regions having generally low GC content (Figure  7B ).
Population genomic datasets can be used to identify the most likely candidate loci underlying recent adaptation. The shallow genomewide differentiation of Z. tritici populations provides a powerful background to test for outlier loci  (Hartmann et al. , 2018). We found the same TE families to have experienced genome-wide copy number expansions, suggesting that the availability of adaptive TE insertions may be a by-product of TE bursts in individual populations. -4 -2 0 2 R L C _ D e im o s _ c h r 1 R L G _ L u n a _ c h r 9 R L G _ L u n a _ c h r 1 2 R L G _ M e r c u r iu s _ c h r 2 R L G _ L u n a _ c h r 2 R L G _ L u n a _ c h r 1 4 R L G _ L u n a _ c.
By establishing large population genetic datasets, such as those possible for crop pathogens, analyses of genome size evolution become tractable at the population level. TEs might not only contribute to genome expansion directly by adding length through additional copies, but also by increasing the rate of chromosomal rearrangements and ectopic recombination  (Bourque et al. , 2018; Blommaert, 2020). However, TEs are not the only repetitive elements that can lead to a genome size expansion. In Arabidopsis thaliana genomes, the 45 S rDNA has been shown to have the strongest impact on genome size variation, followed by 5 S rDNA variation, and contributions by centromeric repeats and TEs  (Long et al. , 2013). In conjunction, recent work demonstrates how repetitive sequences are drivers of genome size evolution over short evolutionary timescales.
Fungal isolate collection and sequencing We analyzed 295 Z. tritici isolates covering six populations originating from four geographic locations and four continents (Figure  1 -source data 1), including: Middle East 1992 (n = 30 isolates, Nahal Oz, Israel), Australia 2001 (n = 27, Wagga Wagga), Europe 1999 (n = 33, Berg am Irchel, Switzerland), Europe 2016 (n = 52, Eschikon, ca. 15 km from Berg am Irchel, Switzerland), and North  America 1990 and 2015 (n = 56 and n = 97, Willamette Valley, Oregon; McDonald et al. , 1996; Linde et al. , 2002; Zhan et al. , 2002; Zhan et al. , 2003; Zhan et al. , 2005). Illumina short-read data from the Middle Eastern, Australian, European 1999, and North American 1990 populations were obtained from the NCBI Sequence Read Archive (SRA) under the BioProject PRJNA327615  (Hartmann et al.
, 2017). For the Switzerland 2016 and Oregon 2015 populations, asexual spores were harvested from infected wheat leaves from naturally infected fields and grown in YSB liquid media including 50 mgL -1 kanamycin and stored in silica gel at -80 °C. High-quality genomic DNA was extracted from liquid cultures using the DNeasy Plant Mini Kit from Qiagen (Venlo, The Netherlands). The isolates were sequenced on an Illumina HiSeq in paired-end mode and raw reads were deposited at the NCBI SRA under the BioProject PRJNA596434.
TE insertion detection The quality of Illumina short reads was determined with FastQC version 0. 11. 5 (https://www. bioinformatics. babraham. ac. uk/ projects/ fastqc/) (Figure  1A ). To remove spuriously sequenced Illumina Spearman correlation matrix of BUSCO completeness, core genome size, number of detected TEs, and genome-wide GC content. The online version of this article includes the following figure supplement(s) for figure  7 :  adaptors and low-quality reads, we trimmed the sequences with Trimmomatic version 0. 36, using the following filter parameters: illuminaclip: TruSeq3-PE-2. fa: 2: 30: 10 leading:10 trailing:10 slidingwindow:5:10 minlen:50  (Bolger et al. , 2014). We created repeat consensus sequences for TE families (sequences are available on https:// github. com/ crolllab/ datasets (copy archived at swh:1:rev:364745 6a2f7ed986b690501d690f09d02d3f586e); Laboratory of Evolutionary Genetics @ UNINE, 2021; Figure  1 -source data 2) in the complete reference genome IPO323  (Goodwin et al.
, 2011)  with RepeatModeler version open-4. 0. 7 (http://www. repeatmasker. org/ RepeatModeler/) based on the RepBase Sequence Database and de novo  (Bao et al. , 2015). TE classification into superfamilies and families was based on an approach combining detection of conserved protein sequences and tools to detect non-autonomous TEs  (Badet et al. , 2020). To detect TE insertions, we used the R-based tool ngs_te_mapper version 79ef861f1d52cdd08eb2d51f145223fad0b2363c integrated into the McClintock pipeline version 20cb912497394fabddcdaa175402adacf5130bd1, using bwa version 0. 7. 4-r385 to map Illumina short reads, samtools version 0. 1. 19 to convert alignment file formats and R version 3. 2. 3 (Li and Durbin, 2009; Li et al. , 2009; Linheiro and Bergman, 2012; R Development Core Team, 2017; Nelson et al.
Clustering of TE insertions into loci We identified insertions across isolates as being the same locus if all detected TEs belonged to the same TE family and insertion sites differed by ≤100 bp (Figure  1 -figure supplement 2). We used the R package GenomicRanges version 1. 28. 6 with the functions makeGRangesFromDataFrame and find-Overlaps and the R package devtools version 1. 13. 4  (Lawrence et al. , 2013; Wickham and Chang, 2016). We used the R package dplyr version 0. 7. 4 to summarize datasets (https:// dplyr. tidyverse. org/). Population-specific frequencies of insertions were calculated with the function allele. count in the R package hierfstat version 0. 4. 22  (Goudet, 2005). We conducted a principal component analysis for TE insertion frequencies filtering for a minor allele frequency ≥5 %.
Evaluation of singleton insertions To evaluate the reliability of singleton TE insertion loci, we analyzed singleton loci in isolates for which we had both Illumina datasets and complete reference-quality genomes  (Badet et al. , 2020). From a set of 19 long-read PacBio reference genomes spanning the global distribution of Z. tritici, one isolate each from Australia, Israel, North America (1990) and four isolates from Europe (1999) were also included in the TE insertion screening. To assess the reliability of singleton TE insertions, we first investigated structural variation analyses among the reference genomes  (Badet et al. , 2021:  Supplementary Data 1 and 2). The structural variation was called both based on split read mapping of PacBio reads and pairwise whole-genome alignments. Using bedtools intersect, we recovered for the 31 singleton TE loci in the seven analyzed genomes a total of 17 loci showing either an indel, translocation, copy number polymorphism, duplication, inverted duplication, inversion, or inverted translocation at the same location.
Then, we performed multiple sequence alignments for each locus across all isolates with MAFFT version 7. 407 with parameter --maxiterate 1000  (Katoh and Standley, 2013). We performed visual inspections to ensure correct alignments across isolates using Jalview version 2. 10. 5  (Waterhouse et al. , 2009). To generate phylogenetic trees of individual gene or TE loci, we extracted specific sections of the alignment using the function extractalign in EMBOSS version 6. 6. 0  (Rice et al. , 2000)  and converted the multiple sequence alignment into PHYLIP format with jmodeltest version 2. 1. 10 using the -getPhylip parameter. We then estimated maximum likelihood phylogenetic trees with the software PhyML version 3. 0, the K80 substitution model, and 100 bootstraps on the ATGC South of France bioinformatics platform  (Guindon and Gascuel, 2003; Guindon et al.
, 2010; Darriba et al. , 2012). Bifurcations with a supporting value lower than 10 % were collapsed in TreeGraph version 2. 15. 0-887 beta, and trees were visualized as circular phylograms in Dendroscope version 2. 7. 4  (Huson et al. , 2007; Stöver and Müller, 2010). For loci showing complex rearrangements, we generated synteny plots using 19 completely sequenced genomes from the same species using the R package genoplotR version 0. 8. 9  (Guy et al. , 2010; Badet et al. , 2020). We calculated the population-specific allele frequency for TE loci and estimated the exponential decay curve with a self-starting Nls asymptomatic regression model nls(p_loci ~ SSasymp(p_round, Asym, R0, lrc)) in R. We analyzed signatures of selective sweeps based on genome-wide SNPs using the extended haplotype homozygosity (EHH) tests implemented in the R package REHH  (Sabeti et al.