Miracle-dz/UniFAR-FTUs huggingface dataset:
Combining pattern matching with word embeddings for the extraction of experimental variables from scientific literature

Scientists frequently use experiments published in other articles or reports by governing entities (e.g. NIH) as templates for reporting on their own experiments. Those templates occasionally change to reflect new discoveries. For creating retrospective studies and meta-analyses, finding the template parameters associated with scientific results can be critical. To aid in the extraction of experimental parameters (e.g. animal housing temperature) in a corpus of ∼8M scientific reports, we used a combination of pattern matching, part of speech tagging, units and measures extraction, and machine learning. We describe a use case where the housing temperature used for experiments involving mice was shown to impact their response to tumor reduction drugs. We show that 1) combining deep learning and pattern matching is a good model to address the problem described and 2) that researcher's behavior and experimental template usage takes a while to change after the publication of an important discovery.
A Small Secreted Virulence-Related Protein Is Essential for the Necrotrophic Interactions of Sclerotinia sclerotiorum with Its Host Plants

Small, secreted proteins have been found to play crucial roles in interactions between biotrophic/hemi-biotrophic pathogens and plants. However, little is known about the roles of these proteins produced by broad host-range necrotrophic phytopathogens during infection. Here, we report that a cysteine-rich, small protein SsSSVP1 in the necrotrophic phytopathogen Sclerotinia sclerotiorum was experimentally confirmed to be a secreted protein, and the secretion of SsSSVP1 from hyphae was followed by internalization and cell-to-cell movement independent of a pathogen in host cells. SsSSVP1∆SP could induce significant plant cell death and targeted silencing of SsSSVP1 resulted in a significant reduction in virulence. Through yeast two-hybrid (Y2H), coimmunoprecipitation (co-IP) and bimolecular fluorescence complementation (BiFC) assays, we demonstrated that SsSSVP1∆SP interacted with QCR8, a subunit of the cytochrome b-c1 complex of mitochondrial respiratory chain in plants. Double site-directed mutagenesis of two cysteine residues (C38 and C44) in SsSSVP1∆SP had significant effects on its homo-dimer formation, SsSSVP1∆SP-QCR8 interaction and plant cell death induction, indicating that partial cysteine residues surely play crucial roles in maintaining the structure and function of SsSSVP1. Co-localization and BiFC assays showed that SsSSVP1∆SP might hijack QCR8 to cytoplasm before QCR8 targeting into mitochondria, thereby disturbing its subcellular localization in plant cells. Furthermore, virus induced gene silencing (VIGS) of QCR8 in tobacco caused plant abnormal development and cell death, indicating the cell death induced by SsSSVP1∆SP might be caused by the SsSSVP1∆SP-QCR8 interaction, which had disturbed the QCR8 subcellular localization and hence disabled its biological functions. These results suggest that SsSSVP1 is a potential effector which may manipulate plant energy metabolism to facilitate the infection of S. sclerotiorum. Our findings indicate novel roles of small secreted proteins in the interactions between host-non-specific necrotrophic fungi and plants, and highlight the significance to illuminate the pathogenic mechanisms of this type of interaction.
Who profits from peer-to-peer file-sharing? Traffic optimization potential in BitTorrent swarms

BitTorrent-based peer-to-peer networks constitute a significant share of Internet traffic. Therefore, the IETF working group on application layer traffic optimization (ALTO) discusses several approaches for guiding the BitTorrent traffic that aim at reducing the large amount of inter-ISP traffic costs caused by these networks. However, performance evaluations of these approaches are mostly limited to artificial scenarios that do not take into account the real Internet topology with its inter-ISP relationships and the actual distribution of BitTorrent users across autonomous systems (AS). In this study, we use measurements of the distribution of a large number of live BitTorrent networks and combine them with the AS-level Internet topology provided by Caida.org. Based on this data, we estimate in which tier of the Internet hierarchy BitTorrent traffic is mainly located and how much optimization potential exists for the different types of ISPs. Therewith, traffic flow and revenue implications of guiding Internet-wide BitTorrent swarms are analyzed. Our results show that tier-1 ISPs profit from the un-managed exchange of peer-to-peer traffic and that these profits significantly decrease when the other ISPs would apply ALTO solutions.
Proper and Improper Multiple Imputation

Multiple imputation has become viewed as a general solution to missing data problems in statistics. However, in order to lead to consistent asymptotically normal estimators, correct variance estimators and valid tests, the imputations must be proper. So far it seems that only Bayesian multiple imputation, i.e. using a Bayesian predictive distribution to generate the imputations, or approximately Bayesian multiple imputations has been shown to lead to proper imputations in some settings. In this paper, we shall see that Bayesian multiple imputation does not generally lead to proper multiple imputations. Furthermore, it will be argued that for general statistical use, Bayesian multiple imputation is inefficient even when it is proper.
3D information visualization for time dependent data on maps

The visual analysis of time dependent data is an essential task in many application fields. However, visualizing large time dependent data collected within a spatial context is still a challenging task. In this paper, we therefore describe an approach for visualizing spatio-temporal data on maps. The approach is based on two commonly used concepts: 3D information visualization and information hiding. These concepts are realized by means of novel embeddings of 3D icons into a map display for representing spatio-temporal data, and an integration of event-based methods for reducing the amount of information to be represented. Our approach is capable of visualizing multiple time dependent attributes on maps, and of emphasizing the characteristics constituted by either linear or cyclic temporal dependencies.
Variation in Expression and Protein Localization of the PIN Family of Auxin Efflux Facilitator Proteins in Flavonoid Mutants with Altered Auxin Transport in Arabidopsis thaliana

Aglycone flavonols are thought to modulate auxin transport in Arabidopsis thaliana via an as yet undefined mechanism. Biochemical studies suggest that flavonoids interact with regulatory proteins rather than directly with the PIN auxin efflux facilitator proteins. Auxin transport is enhanced in the absence of flavonoids (transparent testa4 [tt4]) and reduced in the presence of excess flavonols (tt7 and tt3). Steady state PIN mRNA levels in roots inversely correlate with auxin movement in tt mutants. PIN gene transcription and protein localization in flavonoid-deficient mutants appear to be modulated by developmental cues and are auxin responsive. Modulation of PIN gene expression and protein distribution by localized auxin accumulations occurs in the wild type as well. Flavonoids inhibit auxin transport primarily at the shoot apex and root tip and appear to modulate vesicular cycling of PIN1 at the root tip. In some auxin-accumulating tissues, flavonoid increases and changes in flavonoid speciation are subsequent to auxin accumulation.
Comparison of Different Types of Blood Pool Agents (P792, MS325, USPIO) in a Rabbit MR Angiography-like Protocol

Rationale and objectivesThe objective of this study is to determine the influence of the pharmacokinetic behaviors of different classes of blood pool agents (BPA) on a rabbit experimental model that mimics a magnetic resonance angiographic protocol. BPA were as follows: P792, a macromolecular agent (RCBPA), USPIO, an ultrasmall superparamagnetic iron oxide particle agent (SCBPA), and MS-325, a small gadolinium chelate that expresses intravascular behavior by reversible albumin binding. MethodsThe 2 main phases of early distribution following contrast agent injection, that is, the bolus phase and the steady-state phase, are investigated by measuring Gd or Fe blood concentrations in the first 5 minutes postinjection. T1 relaxation times and r1 relaxivity were calculated at each time point of blood sampling. Furthermore, in the case of MS-325, the concentrations of the free and bound forms were calculated, according to the measured concentrations and the apparent r1 relaxivities. ResultsInjected under similar conditions, the 3 BPA have, during the bolus phase, a comparable profile to Gd-DOTA. Signal enhancement was maximum during this short bolus phase, as were the T1 relaxation times under 30 ms for all agents.At 1 minute postinjection, P792 (r1 = 39 seconds−1.mmol/L−1, 20 MHz) demonstrated the same pharmacokinetic behavior as USPIO (r1 = 33 seconds−1.mmol/L−1, 20 MHz): C1 minute/C0 values were 91 ± 6% and 92 ± 12%, respectively.Immediately after the injection at clinical dose, 74% of MS-325 was in free form, resulting in an apparent r1 relaxivity of only 13 seconds−1.mmol/L−1 (20 MHz); 1 minute postinjection, the C1 minute/C0 value of 61 ± 4% was the lowest as compared with P792 and USPIO and the bound form represented 75% of the MS-325 molecules. ConclusionsThe BPA P792 and USPIO have favorable properties that result from their intravascular retention and their lack of extravasation, allowing optimal contrast between the vessel and the adjacent tissue for several minutes postinjection. Combining a rapid body clearance and a marked T1 effect, P792 presents optimal blood pool characteristics for angiographic applications. During the bolus phase, MS-325 is mainly in free form, which presents the disadvantage of increasing the tissue signal background, due to extravasation of the free form.
Decision tree acoustic models for ASR

This paper presents a summary of our research progress using decision-tree acoustic models (DTAM) for large vocabulary speech recognition. Various conﬁgurations of training DTAMs are proposed and evaluated on wall-street journal (WSJ) task. A number of different acoustic and categorical features have been used for this purpose. Various ways of realizing a forest instead of a single tree have been presented and shown to improve recognition accuracy. Although the performance is not shown to be better than Gaussian mixture models (GMMs), several advantages of DTAMs have been highlighted and exploited. These include compactness, computational simplicity and ability to handle unordered information.
Automatic building of Arabic multi dialect text corpora by bootstrapping dialect words

The principle objective of this work is to build multi dialect Arabic texts corpora using a web corpus as a resource. A survey has been conducted to categorize distinct words and phrases that are common to a specific dialect only, and not used in other dialects, the purpose being to download a specific dialect text corpus. From this experiment we obtained 48M tokens from different Arabic dialects. These dialects were categorised into four main dialects Gulf, Levantine, Egyptian and North African, resulting in 14.5M, 10.4M, 13M and 10.1M tokens being obtained respectively. The total number of distinct types in all the corpora is 2M types. In this paper we describe how the corpora were constructed by using distinct words.
Positive Evolutionary Selection of an HD Motif on Alzheimer Precursor Protein Orthologues Suggests a Functional Role

HD amino acid duplex has been found in the active center of many different enzymes. The dyad plays remarkably different roles in their catalytic processes that usually involve metal coordination. An HD motif is positioned directly on the amyloid beta fragment (Aβ) and on the carboxy-terminal region of the extracellular domain (CAED) of the human amyloid precursor protein (APP) and a taxonomically well defined group of APP orthologues (APPOs). In human Aβ HD is part of a presumed, RGD-like integrin-binding motif RHD; however, neither RHD nor RXD demonstrates reasonable conservation in APPOs. The sequences of CAEDs and the position of the HD are not particularly conserved either, yet we show with a novel statistical method using evolutionary modeling that the presence of HD on CAEDs cannot be the result of neutral evolutionary forces (p<0.0001). The motif is positively selected along the evolutionary process in the majority of APPOs, despite the fact that HD motif is underrepresented in the proteomes of all species of the animal kingdom. Position migration can be explained by high probability occurrence of multiple copies of HD on intermediate sequences, from which only one is kept by selective evolutionary forces, in a similar way as in the case of the “transcription binding site turnover. ” CAED of all APP orthologues and homologues are predicted to bind metal ions including Amyloid-like protein 1 (APLP1) and Amyloid-like protein 2 (APLP2). Our results suggest that HDs on the CAEDs are most probably key components of metal-binding domains, which facilitate and/or regulate inter- or intra-molecular interactions in a metal ion-dependent or metal ion concentration-dependent manner. The involvement of naturally occurring mutations of HD (Tottori (D7N) and English (H6R) mutations) in early onset Alzheimer's disease gives additional support to our finding that HD has an evolutionary preserved function on APPOs.
Multivariate High Order Fuzzy Time Series Forecasting for Car Road Accidents

In this paper, we have presented a new multivariate fuzzy time series forecasting method. This method assumes mfactors with one main factor of interest. History of past three years is used for making new forecasts. This new method is applied in forecasting total number of car accidents in Belgium using four secondary factors. We also make comparison of our proposed method with existing methods of fuzzy time series forecasting. Experimentally, it is shown that our proposed method perform better than existing fuzzy time series forecasting methods. Practically, actuaries are interested in analysis of the patterns of causalities in road accidents. Thus using fuzzy time series, actuaries can define fuzzy premium and fuzzy underwriting of car insurance and life insurance for car insurance. National Institute of Statistics, Belgium provides region of risk classification for each road. Thus using this risk classification, we can predict premium rate and underwriting of insurance policy holders. Keywords—Average forecasting error rate (AFER), Fuzziness of fuzzy sets Fuzzy, If-Then rules, Multivariate fuzzy time series.
A Forward-Looking User Interface for CBIR and CFIR Systems

This demonstration highlights the benefits that image retrieval systems can enjoy by use of a thoughtful interface. We present a live demonstration of PRISM, a new Web-based application that, through a simple set of natural actions, allows the user the ability to elicit sophisticated responses from easily-formed queries. Additionally, the system was designed with not only content-based, but also content-free image retrieval and semantic annotation in mind. The demonstration system uses an attention-based method for extracting and determining the relevance of salient regions of interest in an unsupervised way, but can be adapted to a variety of implementations
Macroalgal blooms in shallow estuaries: Controls and ecophysiological and ecosystem consequences

Macroalgal blooms are produced by nutrient enrichment of estuaries in which the sea floor lies within the photic zone. We review features of macroalgal blooms pointed out in recent literature and summarize work done in the Waquoit Bay Land Margin Ecosystems Research project which suggests that nutrient loads, water residence times, presence of fringing salt marshes, and grazing affect macroalgal blooms.
XMap results for OAEI 2017

We describe in this paper the XMap system and the results achieved during the 2017 edition of the Ontology Alignment Evaluation Initiative. XMap aims to tackle the issue of matching large scale ontologies by involving particular parallel matching on multiple cores or machines. 1 Presentation of the system XMap, as for eXtended Mapping, is one of the leading ontology matching systems for large-scale ontology matching relying on the notion of context in order to deal with lexical ambiguity as well as a divide-and-conquer approach to tackle the issue of matching large ontologies. In XMap, the measurement of lexical similarity in ontology matching is performed using a synset, defined in WordNet [1] and UMLS [2]. In our approach, the similarity between two entities of different ontologies is evaluated not only by investigating the semantics of the entities names, but also taking into account the context, through which the effective meaning is described. The translation into many languages is based on the Microsoft R ⃝Translator. Our system stores locally all translation results from Microsoft R ⃝Translator in dictionary files. The translator will also be queried only when no stored translation are found in order to gain time and avoid overloading the server. 2 State, purpose, general statement XMap using an oracle by modifying the validation process of the candidate mappings according to the quality of the interactive matching in terms of F-measure and number of required interactions. This process is performed after each round of candidate retrieving. Our approach is based on semantic techniques and on a parallel execution strategy adapted from [3], to address the challenge of scalability and efficiency of matching techniques. One of the main trusts of the introduced approach is the increasing scalability and speed of ontology alignment by matching linguistic and structural features. At a glance, the mapping process of XMap is depicted in Figure 1. XMap uses various similarity measures of different categories such as string, linguistic, and structural based similarity measures, each contributing to some extent to the alignment results. Afterwards, the alignments from all matchers can be aggregated to obtain a final alignment through the use of sequential composition [4]. Finally, a fast repair method is applied Fig. 1. The different steps for scoring a multiple network alignment. so as to detect and remove the inconsistent classes by ”‘Applying Logical Constraints on Matching Ontologies”’ (ALCOMO) [5]. The main goal is to try to remove less unsatisfiable classes (discovering disjointness relationships) without having an impact on the F-measure score.
Predicting recurring crash stacks

Software crash is one of the most severe bug manifestations and developers want to fix crash bugs quickly and efficiently. The Crash Reporting System (CRS) is widely deployed for this purpose. Even with the help of CRS, fixes are largely by manual effort, which is error-prone and results in recurring crashes even after the fixes. Our empirical study reveals that 48% of fixed crashes in Firefox CRS are recurring mostly due to incomplete or missing fixes. It is desirable to automatically check if a crash fix misses some reported crash traces at the time of the first fix. This paper proposes an automatic technique to predict recurring crash traces. We first extract stack traces and then compare them with bug fix locations to predict recurring crash traces. Evaluation using the real Firefox crash data shows that the approach yields reasonable accuracy in prediction of recurring crashes. Had our technique been deployed earlier, more than 2,225 crashes in Firefox 3.6 could have been avoided.
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This paper examines the health and well-being of the Irish population in the late 20 th century, the period popularly referred to as the Celtic Tiger. This period saw unprecedented increases in economic activity in Ireland. Using statistical data from administrative and survey sources, I examine whether this period of growth improved well-being and welfare in Ireland. The paper draws from theories of the development of societies such as those of Fogel and Easterlin, as well as theories from behavioural economics and econometric techniques to examine this question. In particular, I examine the extent to which Ireland fits into a pattern of declining correlation between GDP and well-being at later stages of development, a phenomenon known as the Easterlin Paradox. I also examine the extent to which individual well-being is predicted by income as compared to other aspects of welfare such as health and employment status.
Trypsin Cleaves Exclusively C-terminal to Arginine and Lysine Residues*S

Almost all large-scale projects in mass spectrometry-based proteomics use trypsin to convert protein mixtures into more readily analyzable peptide populations. When searching peptide fragmentation spectra against sequence databases, potentially matching peptide sequences can be required to conform to tryptic specificity, namely, cleavage exclusively C-terminal to arginine or lysine. In many published reports, however, significant numbers of proteins are identified by non-tryptic peptides. Here we use the sub-parts per million mass accuracy of a new ion trap Fourier transform mass spectrometer to achieve more than a 100-fold increased confidence in peptide identification compared with typical ion trap experiments and show that trypsin cleaves solely C-terminal to arginine and lysine. We find that non-tryptic peptides occur only as the C-terminal peptides of proteins and as breakup products of fully tryptic peptides N-terminal to an internal proline. Simulating lower mass accuracy led to a large number of proteins erroneously identified with non-tryptic peptide hits. Our results indicate that such peptide hits in previous studies should be re-examined and that peptide identification should be based on strict trypsin specificity.
Optimal Production and Biochemical Properties of a Lipase from Candida albicans

Lipases from microorganisms have multi-faceted properties and play an important role in ever-growing modern biotechnology and, consequently, it is of great significance to develop new ones. In the present work, a lipase gene from Candida albicans (CaLIP10) was cloned and two non-unusual CUG serine codons were mutated into universal codons, and its expression in Pichia pastoris performed optimally, as shown by response surface methodology. Optimal conditions were: initial pH of culture 6.86, temperature 25.53 °C, 3.48% of glucose and 1.32% of yeast extract. The corresponding maximal lipolytic activity of CaLIP10 was 8.06 U/mL. The purified CaLIP10 showed maximal activity at pH 8.0 and 25 °C, and a good resistance to non-ionic surfactants and polar organic solvent was noticed. CaLIP10 could effectively hydrolyze coconut oil, but exhibited no obvious preference to the fatty acids with different carbon length, and diacylglycerol was accumulated in the reaction products, suggesting that CaLIP10 is a potential lipase for the oil industry.