dataesr/scientific-paragraphs-categorization huggingface dataset:
(2013)  developed a new pair of degenerate primers with a broad scope of amplification success across a phylogenetically diverse range of marine metazoan taxa. In the very first study based on molecular data of freshwater diatom communities in Portugal, the total number of diatom taxa identified was 125 from 88 river samples which corresponded to about 41 % of the number of taxa identified by using the light microscope  (Mortágua et al. , AIL2018; Mortágua et al. , 2019). These results, somewhat unexpected, were in accordance with results registered in studies performed in other countries  (Vasselon et al. , 2017b; Rivera et al. , 2018 and Keck et al. , 2018). A possible explanation might be the high number of unassigned reads, which is a consequence of the incompleteness of the reference database.
New records of cyanobacteria species presence were detected in the Azores through molecular analyses  (Cordeiro et al. , AIL2018). In addition, some of the sampled lakes cyanotoxins production potential was confirmed, mainly associated with eutrophication and anthropogenic effects, which shows the potential of molecular tools for monitoring cyanotoxin risk in aquatic systems. In Russia, a unique dataset of early winter lake water microbial communities was produced as winter dynamics are usually out of the scope of limnological studies in Siberia, due to the harsh fieldwork conditions (Diaz-de-Quijano et al. , AIL2018). The Cryptomycota clade LKM11, which was previously found in ice-covered lakes of Antarctica  (Rojas-Jimenez et al. , 2017) , represented up to 6-10 % of the reads in intermediate and deep layers of the water column of the ice-covered Oiskoe lake.
Taxonomic gaps In the SS it was often referred to the existence of taxonomic gaps in the reference databases when considering local fauna. One example is the study in the Lima estuary and in the Tua river in Portugal with benthic invertebrates, where a fair number of OTUs could not be assigned to phylum or other lower taxonomic rank due to the primers used for targeting the COI region  (Mortágua et al. , 2019). A similar issue was reported for the diatoms as previously referred, in spite of the large database and diatom cultures existing in Thonon-les-Bains, INRA, with a high number of unassigned reads (67 %). The increase in the number of diatom barcodes in reference databases will allow for a complete study of diversity, namely in what concerns to rare taxa. In some cases, databases are not sufficient for assigning species and they must be assigned at genus level; in these cases, previous taxonomic work is necessary.
CONCLUSIONS Studies presented in AIL2018 meeting enhanced the importance and applicability of molecular techniques in environmental studies, towards fast and significant information acquisition. This information can be used in biodiversity and ecological quality assessments, conservation and management of aquatic water bodies. During the SS, it became clear that molecular tools, and particularly the metabarcoding approach, could provide fine-scale taxonomical resolution data, contribute to detect new invasions and allow for unveiling hidden biodiversity resulting from low-abundance, small sizes and poor-developmental stages. Yet, a lot of work and investment is still needed before molecular tools can be used routinely in monitoring programs, namely in the completion of databases, optimization and standardization of both laboratory and field protocols, in automation in sample handling and bioinformatics analyses and ultimately in reducing analyses costs.
Feio et al. program ( UID/MAR/04292/2013 ); SFP Almeida is supported by GeoBioTec strategic program  UID/GEO/04035/2019. R. Cordeiro was supported by a  Ph. D. Grant  ( M3. 1. a/F/017/2011 )from  Fundo Regional da Ciência e Tecnologia (FRCT) ;  A. F. Filipe  and  A. Garcia-Raventos  were supported by  FRESHING  Project "Next-generation biomonitoring: freshwater bioassessment and species conservation improved with metagenomics" funded by the  Portuguese Foundation for Science and Technology (FCT)  and  COMPETE  ( PTDC/AAG-MAA/2261/2014 -POCI-01-0145-FEDER-356 016824 );  F. M. S. Martins  was supported by a  FCT PhD grant  ( SFRH/BD/ 104703/2014 ); A. R. Calapez was supported by a grant from the  FCT-PhD programme FLUVIO  ( PD\BD\52510\2014 ); A. M. Pujante acknowledges the BIOWAT-KIT_E!11892Eurostars project;  Maria Fais  and Sofia Duarte were supported, respectively, by a PhD ( SFRH/BD/ 113547/2015 ) and a post-doc fellowship ( SFRH/BPD/109842/2015 ), from  FCT ; and  C.
Study Design, Patients, and End Point Definitions The design and primary findings of the FOURIER trial have been published previously. 10, 13 A total of 27 564 patients with atherosclerotic cardiovascular disease at increased cardiovascular (CV) risk were randomized to evolocumab or placebo and followed for a median of 2. 2 (interquartile range [IQR], 1. 8-2. 5) years. Eligible patients had an LDL-C concentration of 70 mg/dL or more (to convert to mmol/L, multiply by 0. 0259) while taking statin therapy. There was no exclusion criterion for AS or prior AVR. The FOURIER trial was approved by all relevant institutional review boards, and written informed consent was obtained from all participants. For this post hoc analysis, the safety database was searched for events of new or worsening AS or aortic valve replacement (termed AS events).
10 The proportional hazards assumption was tested using Schoenfeld residuals, with a P value of. 22. A sensitivity analysis was performed removing patients who experienced a major adverse CV event (CV death, myocardial infarction, stroke, hospitalization for unstable angina, or coronary revascularization) prior to or concurrent with the AS event (including if the AS event was concurrent with CV death). All analyses were performed by the TIMI Study Group using commercially available statistical software (SAS version 9.
Amgen. Dr Mach  received research grants to his institution from  Amgen ,  AstraZeneca ,  BMS ,  Eli Lilly ,  MSD ,  Sanofi , and  Pfizer. Dr Huber  reports lecture fees from  Amgen ,  AstraZeneca ,  Pfizer , and  Sanofi Aventis. Dr Jensen  is supported by the  Novo Nordisk Foundation  (grant  NNF18OC0031258 ); reports lecture fees from  Amgen ,  Pfizer , and  Sanofi ; and has received research grants from  Amgen ,  Pfizer , and  Sanofi. Dr Gaciong  reports personal fees from  Amgen. Dr Lewis  reports research support and honoraria from  Amgen ,  Pfizer ,  Bayer Healthcare ,  Merck Sharp & Dohme , and  Kowa  pharmaceuticals and grants from  Resverlogix. Dr Schiele  reports consulting fees from  Amgen ,  Sanofi ,  Bayer ,  Merck Sharp & Dohme ,  Servier ,  Novonordisk ,  AstraZeneca , and  Lilly.
Materials and Methods The guideline was developed according to a well-documented methodology that is universal to ESHRE guidelines  (Vermeulen et al. , 2017). In short, 18 key questions were formulated by the Guideline Development Group (GDG) and structured in PICO format  (Patient, Intervention, Comparison, Outcome). For each question, databases (PUBMED/MEDLINE and the Cochrane library) were searched from inception to 8 November 2018, with a limitation to studies written in English. From the literature searches, studies were selected based on the PICO questions, assessed for quality and summarized in evidence tables and summary of findings tables. The critical outcomes for this guideline are efficacy in terms of cumulative live birth rate (CLBR) per started cycle and LBR per started cycle, as well as safety in terms of moderate and/or severe OHSS.
Clin Exp Obstet Gynecol 2013;40:98-100. Youssef MA, Abou-Setta AM, Lam WS. Recombinant versus urinary human chorionic gonadotrophin for final oocyte maturation triggering in IVF and ICSI cycles. Cochrane Database Syst Rev 2016;4: Cd003719. Youssef MA, Van der Veen F, Al-Inany HG, Mochtar MH, Griesinger G, Nagi Mohesen M, Aboulfoutouh I, van Wely M. Gonadotropinreleasing hormone agonist versus HCG for oocyte triggering in.
Clin Exp Obstet Gynecol 2013;40:98-100. Youssef MA, Abou-Setta AM, Lam WS. Recombinant versus urinary human chorionic gonadotrophin for final oocyte maturation triggering in IVF and ICSI cycles. Cochrane Database Syst Rev 2016;4: Cd003719. Youssef MA, Van der Veen F, Al-Inany HG, Mochtar MH, Griesinger G, Nagi Mohesen M, Aboulfoutouh I, van Wely M. Gonadotropinreleasing hormone agonist versus HCG for oocyte triggering in. vitro.
The sulfuric acid dimer : monomer ratio is significantly lower than that seen in experiments involving sulfuric acid and dimethylamine (DMA) in chambers, indicating that stabilisation of sulfuric acid clusters by bases is weaker in this dataset than in chambers, either due to rapid evaporation due to high summertime temperatures or limited pools of stabilising amines. Such a mechanism cannot be verified in these data, as no higher-order H 2 SO 4 -amine clusters nor H 2 SO 4 -HOM clusters were measured. The high concentrations of HOMs arise from isoprene, alkylbenzene, monoterpene and polycyclic aromatic hydrocarbon (PAH) oxidation, with alkylbenzenes providing greater concentra-tions of HOMs due to significant local sources. The concentration of these HOMs shows a dependence on temperature.
, 2013) , while typical concentrations of DMA and other alkylamines vary from zero to a few pptv in the boundary layer  (Ge et al. , 2011a). Barcelona has been shown to contain ppbv levels of ammonia  (Pandolfi et al. , 2012)  arising from both agriculture to the north  (Van Damme et al. , 2018)  and anthropogenic activities such as waste management and traffic, with waste management being the primary ammonia source. The highest ammonia mixing ratios are found in the densely populated old city centre  (Reche et al. , 2015). Agriculture, waste management, and traffic are also all significant sources of low molecular weight alkylamines, such as DMA  (Ábalos et al. , 1999; Cadle and Mulawa, 1980; Hutchinson et al. , 1982; Ge et al. , 2011a) , and are likely the source of amines found in this dataset.
Activities such as composting and food industry are especially strong sources of trimethylamine (TMA)  (Ge et al. , 2011a). Although high emission fluxes of TMA are expected in this environment, they are not present in our spectra. The TMA ion has been reported previously with a similar ionisation setup to that utilised in this study  (Kürten et al. , 2016). On full-event days, the signal for C 2 and C 4 amines has a midday elevation concurrent with peaks to solar radiation (Fig. S2 ) and can help explain the high formation rates we see in this dataset (see Sect. 3. 2). The relative strengths of these signals are shown in Fig. S3 , with significantly higher signals attributed to ammonia compared to amines, despite a likely lower sensitivity  (Simon et al. , 2016). HOM concentrations were greatly enhanced during fullevent periods (factor of 1.
, 2001) , and thus minimal declustering of the dimer is expected within the CI-Api-ToF instrument -however, declustering of higher-order sulfuric acid clusters has been shown to be sensitive to voltage tune  (Passananti et al. , 2019) , and this likely extends to the dimer also, and as such discrepancies between sets of results due to instrument setup cannot be ruled out. The ratio of sulfuric acid dimer : monomer is also highly sensitive to condensation sinks, with a difference in dimer concentration of approximately a factor of 4 expected at 10 7 cm -3 between 0. 001 s -1 (a clean environment) and 0. 03 s -1 (condensation sinks during these NPF events measured in this dataset)  (Yao et al. , 2018) , and thus our low dimer : monomer ratio can, in part, be explained by elevated condensation sinks.
Acknowledgements. María Cruz Minguillón  acknowledges the  Ramón y Cajal Fellowship  awarded by the  Spanish Ministry of Science, Innovation and Universities. Financial support. This research has been supported by the  Spanish Ministry of Science, Innovation and Universities and Competitiveness and FEDER funds  (project  HOUSE  (grant no. CGL2016-78594-R) ), the  Generalitat de Catalunya  (grant no. AGAUR 2017 SGR41 ), and the  Natural Environment Research Council  (grant no. R8/H12/83/011 ). Review statement. This paper was edited by  Veli-Matti Kerminen  and reviewed by two anonymous referees.
The idea of transferring money without involving a financial institution attracted several investors toward Bitcoin. As Bitcoin gained popularity, several other cryptocurrencies emerged, and cryptocurrency exchanges were formed to trade cryptocurrencies with fiat currencies. After the development of Bitcoin, researchers realized that the underlying technology of Bitcoin is blockchain technology, which provides an immutable ledger that replaces the requirement of having third-party governance for the safety and security of transactions. It is like understanding the importance of the internet after the invention of email  (Kaiserman, 2018). Blockchain is a decentralized database that is distributed across a number of nodes (i. e. , computers) and in which all transactions recorded on the database are made immutable using cryptographic techniques  (Narayanan et al.
They are rather protected by the cryptographic algorithms used in the blockchain. Hence, studying the attributes of technology that create trust in cryptocurrencies is a topic of interest. Once the attributes of the technology that create trust in cryptocurrencies are understood, it is extremely important to know how these attributes can create trust in other areas. Because blockchain has the potential to disrupt several domains, including supply chain management, asset management, digital identity, electronic voting systems, and healthcare data management, I want to implement blockchain in an area that is less discussed, the hiring process, to make the recruitment of new employees more reliable and less expensive. The research in this area allows us to understand how the attributes of technology bring trust to the business process.
The solution not only helps to elucidate how to implement blockchain for a business problem, but it also helps us to evaluate the benefits of using blockchain. Cryptocurrencies do not just rely on blockchain, they also depend on exchanges and wallet technologies for trading and storing cryptocurrencies. A cryptocurrency wallet is a software program that stores the public and private keys of an account and can interact with the blockchain to enable the management of the account. A cryptocurrency wallet can be an online wallet, software wallet, or hardware wallet  (Bierer, 2016). A cryptocurrency exchange is an online platform that allows customers to trade cryptocurrencies with fiat currencies or other digital assets  (DeVries, 2016). Customers of these exchanges often have online wallets with the exchanges.
Background and Motivation Cryptocurrencies can be defined as digital currencies (or assets), where the security of the transactions and the generation of new crypto-coins is governed by cryptographic algorithms  (Narayanan et al. , 2016). Cryptocurrencies are not governed by any central authority, unlike fiat currencies, which are governed by the monetary policies framed by the central banks of their countries  (He, 2019). Several governments in various countries have abused their monetary policies for temporary benefits and devalued their currency. Hence, cryptocurrencies are a good alternative to traditional fiat currencies in countries like Iran and Venezuela, which have extremely volatile currencies  (Gail, 2018). Unlike traditional centralized databases, blockchain provides immutability to the transactions, and hence no record can be tampered with or deleted  (Politou et al.
, 2019). Apart from immutability, the digital signature on each of the transactions helps to authenticate the party who initiated the transaction  (Agrawal, 2018). The distributed nature of the ledger brings openness to the system, and any node in the system can access the data on the blockchain. These features of blockchain eliminate the requirement of a third party (central authority) in a business transaction. The role of the intermediaries in a business transaction is to perform the careful verification of the background of the party involved, along with a chain of intermediaries  (Nofer et al. , 2017). The process of human or institutional intermediation is costly, time-consuming, and lacks transparency in its operations  (Quentson, 2016). Cryptocurrencies replace financial intermediaries with blockchain technology.
Data Collection and Analysis This section provides an overview of the datasets used for all the research papers in this thesis and the various analysis methods used to extract meaningful knowledge from these datasets. For the paper titled "Bitcoin: A social movement under attack," data were collected from reputed websites like BitCoinTalk, CoinDesk, CNBC, and The Register. Data collected from one website were triangulated with information available on other websites. I performed a content analysis on the data collected from these websites. Content analysis is a technique for compressing many words from a text into fewer content categories based on explicit rules of coding  (Stemler, 2001). Framing theory was used to establish Bitcoin as a social movement. The trust deficit created among the investors in the traditional financial institutions due to the collapse of Lehmann Brothers during the 2008 global financial crisis was projected as a problem using diagnostic framing.
I used Doc2Vec textual analysis, as proposed by Le and Mikolov's (2014) model, on the forum data, which generates the vector representation of words and documents through paragraph vectors. After the vector representation of the words and documents, I computed the semantic similarity to identify the closeness of the posts and words to trust. Semantic similarity is a metric defined over a corpus, by which the similarity is based on the likeness of semantic meaning instead of syntactical representation. Like a classification problem, the model learns the network weight to maximize the prediction of the nearest word. But these networks output the learned weight as a vector and semantic representation of the text rather than the final prediction from the model. To train the Doc2Vec model, I relied on the implementation provided by the Python package Gensim  (Rehurek & Sojka, 2010).
I excluded cyber-attacks that were not discussed extensively on the online forum. Finally, I selected seven major cyber-attacks on different cryptocurrency exchanges. Then, I gathered information on how they informed their customers about a given cyber-attack and how they apologized for the violation. I collected the apology information via email, Twitter, website announcements, and press releases. I also gathered information about other trust rebuilding measures that the exchanges took during the months following the cyber-attack. Finally, I extracted the response of the customers and potential customers to the cyber-attacks on the Bitcointalk. org online forum. I used the Beautifulsoup package in Python for web scraping of the posts made by the current and potential customers of the exchange on the apologies made by the exchanges, analyzing a total of over 500 posts.
Sentiment analysis is a process through which text is analyzed using natural language processing, and the sentiments of the text are categorized as negative, positive, or neutral  (White, 2020). VADER is a lexicon-and rule-based sentiment analysis tool that is specifically attuned to the sentiments expressed in social media. For each statement in the text, VADER provides a fraction of positive, negative, and neutral sentiments. Finally, I focused more deeply on the users' responses for each exchange and conducted a qualitative analysis using the Atlas. ti software. I aimed to identify the factors that contribute to positive and negative sentiments. For this purpose, I started with open coding of the users' responses for each exchange. Next, I clustered the open codes into larger categories that formed positive and negative themes.
41 9. Venkata Marella Part II: RESEARCH PAPERS………………………………………………. 51 Satoshi Nakamoto combined cryptography with databases in a distributed network to develop an open and immutable ledger, which can bring trust to the system without intermediaries. This motivated me to research the trust issues in Blockchain technology and cryptocurrencies. My background in computer science has helped me understand the workings of blockchain and cryptocurrencies. The Dagstuhl workshop on blockchain provided me an opportunity to network with reputed researchers in both information systems and computer science. In the blockchain summer school at the University of Copenhagen, I learned how blockchain can be implemented for various business use cases. The IRIS conference in 2017 helped me network with fellow researchers in my field, and successfully present my research to them.
Patients The modeled patient cohort included adult patients with CCS or symptomatic PAD. The COMPASS trial population baseline characteristics (Table  1 ) and treatments were similar to those of the typical Finnish CCS or PAD patient   [3, 9, 19]. These were also generally in line with the international REACH  [36, 37]  and Polish TERCET-CAD registries  [38]. Results based on different patient characteristics (Table  1 ) were explored from the subgroup analyses of COMPASS (see Table  S1  in the electronic supplementary material). The patient characteristics impacted mortality and HRQoL in the analysis. In addition, the patient subgroups impacted the transition probabilities and HRQoL. The modeling was based on previously conducted studies and did not include any new studies with human participants or animals performed by any of the authors and was not registered with any clinical trial database.
839 in the Finnish population. Because HRQoL generally decreases with age  [10]  and there was an estimated 0. 004 difference in the EFH state HRQoL between the COMPASS trial patients and a similar Finnish population, adjustment to the local setting was done using age group-specific multipliers applied to the COMPASS-based HRQoL values (Table  2 ). As expected, the COMPASS trial did not include enough data for the estimation of a second CVE HRQoL. The HRQoL associated with the second main CVE was determined as the lower HRQoL that a patient with two main CVEs was modeled to experience. The base-case analysis did not consider that both main CVEs may affect HRQoL independently and additively, which is conservative.
OV declares no other potential conflicts of interest. Jean-Baptiste Briere is an employee of Bayer AG. Kevin Bowrin is an employee of Bayer Plc. Aurelie Millier is an employee of Creativ-Ceutical and declares no other potential conflicts of interest. Compliance with Ethics Guidelines. This study was based on previously conducted studies and did not include any new studies with human participants or animals performed by any of the authors and was not registered with any clinical trial database. Data Availability. Data sharing is not applicable as no new datasets were generated or analyzed during this study. No data are deposited in publicly available repositories or published alongside the paper as supplementary material. Open Access. This article is licensed under a Creative Commons Attribution-Non-Commercial 4.
ACKNOWLEDGEMENTS Funding. The study was financially supported by  Bayer Oy, Espoo, Finland. The financial supporter ( Bayer Oy, Espoo, Finland ) participated in the identification, design, conduct, and reporting of the study. The study sponsor also funded Journal's  Rapid Service  and  Open Access Fees. Authorship. All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.