Miracle-dz/UniFAR-FTUs huggingface dataset:
SoxS represses flagellar gene expression through RflP in Salmonella enterica Serovar Typhimurium

Flagellar gene expression is subject to regulation by many global transcription factors in response to environmental and nutritional signals. One of the primary ways this occurs in Salmonella enterica serovar Typhimurium, and its close relatives, is through controlling levels of FlhD4C2 (the flagellar master regulator) via transcriptional, post-transcriptional, and post-translational mechanisms. Recently, we found the homologous transcription factors MarA, Rob, and SoxS repress flhDC expression by distinct mechanisms. MarA and Rob, regulators involved in inducible multidrug resistance, repressed flhDC transcription by interacting directly with the flhDC promoter. Alternatively, SoxS, the oxidative stress response regulator, altered FlhD4C2 levels independent of flhDC transcription by post-transcriptional or post-translational mechanism. Here, using a forward genetic screen, we discovered that SoxS-dependent repression of flagellar gene expression occurs through RflP, an anti-FlhD4C2 factor that targets FlhD4C2 for proteolytic degradation. Elevated soxS expression resulted in concomitant increases in rflP expression, indicating SoxS may work through RflP at the level of rflP transcription. Mapping of the rflP promoter and a bioinformatic search yielded a putative SoxS binding site proximal to the rflP transcription start site. Comparison of the rflP promoter region in S. Typhimurium and Escherichia coli indicate substantial differences, providing a possible mechanism for differential expression of rflP between these species. IMPORTANCE Salmonella enterica is a major cause of foodborne illness. Understanding environmental and intracellular signals used by Salmonella to control expression of virulence-associated traits is critical to advancing treatment and prevention of Salmonella-related disease. Reduced expression of flagella at key points during Salmonella infection aids in evasion of the host innate immune system. Within macrophages Salmonella is non-flagellated and exposed to oxidative stress. SoxS-dependent repression of flagellar genes may provide a potential link between oxidative stress and reductions in flagellar expression.
Exploring the Use of Lexicons to aid Deep Learning towards the Detection of Abusive Language

Detecting abusive language is a significant research topic, which has received a lot of attention recently. Our work focused on detecting personal attacks in online conversations. State-of-the-art research on this task has largely used deep learning with word embeddings. We explored the use of sentiment lexicons as well as semantic lexicons towards improving the accuracy of the baseline Convolutional Neural Network (CNN) using regular word embeddings. This is a work in progress, limited by time constraints and appropriate infrastructure. Our preliminary results showed promise for utilizing lexicons, especially semantic lexicons, for the task of detecting abusive language.
Verification of CRISPR editing by XdropTM Indirect Sequence Capture followed by short- and long- read sequencing Blondal

Validation of CRISPR-Cas9 editing typically explore the immediate vicinity of the target site and distal off-target sequences, which have led to the conclusion that CRISPR-Cas9 editing is very specific. However, an increasing number of studies suggest that on-target unintended editing events like deletions and insertions are relatively frequent but unfortunately often missed in the validation of CRISPR-Cas9 editing. The deletions may be several kb and only affect one allele. The golden standard in molecular validation of gene editing is direct sequencing of relatively short PCR amplicons. This approach will allow detection of smaller editing events but will fail to detect larger rearrangements in particular when these only affect one of the two alleles. Detection of larger rearrangements requires that an extended region is analyzed and the characterization of events may benefit from long-read sequencing. Here we present a new microfluidic technology XdropTM that allows targeted enrichment of longer regions (~ 100 kb) using just a standard PCR primer set. We sequenced the enriched region on longand shortread sequencing platforms to unravel unknown and unintended genome edits resulting from CRISPR-Cas9 gene editing. We show how loss of heterozygosity, due to an accidental insertion in one of the alleles, remained undetected using standard procedures but was discovered implementing the XdropTM system. This demonstrates the potential of such technology in CRISPR gene editing assessments, providing an extremely accurate tool.
Rediscovering 15 Years of Discoveries in Language Resources and Evaluation: The LREC Anthology Analysis

This paper aims at analyzing the content of the LREC conferences contained in the ELRA Anthology over the past 15 years (1998-2013). It follows similar exercises that have been conducted, such as the survey on the IEEE ICASSP conference series from 1976 to 1990, which served in the launching of the ESCA Eurospeech conference, a survey of the Association of Computational Linguistics (ACL) over 50 years of existence, which was presented at the ACL conference in 2012, or a survey over the 25 years (1987-2012) of the conferences contained in the ISCA Archive, presented at Interspeech 2013. It contains first an analysis of the evolution of the number of papers and authors over time, including the study of their gender, nationality and affiliation, and of the collaboration among authors. It then studies the funding sources of the research investigations that are reported in the papers. It conducts an analysis of the evolution of the research topics within the community over time. It finally looks at reuse and plagiarism in the papers. The survey shows the present trends in the conference series and in the Language Resources and Evaluation scientific community. Conducting this survey also demonstrated the importance of a clear and unique identification of authors, papers and other sources to facilitate the analysis. This survey is preliminary, as many other aspects also deserve attention. But we hope it will help better understanding and forging our community in the global village.
Genetic Diversity Among Pseudomonas syringae pv. morsprunorum Isolates from Prunus mume in Korea and Japan by Comparative Sequence Analysis of 16S rRNA Gene

Genetic diversity among Pseudomonas syringae pv. morsprunorum isolates from Prunus mume in Korea and Japan was investigated by comparative sequence analysis of the 16S rRNA gene. The strains included 24 field isolates recovered from P. mume in Korea along with seven Japanese strains. Two strains isolated from P. salicina in Japan, one strain from P. avium in the United Kingdom, and the pathotype strain were also used for comparison with their 16S rRNA gene sequences. Nearly complete 16S rRNA gene sequences were sequenced in all 35 strains, and three sequence types, designated types I, II and III, were identified. Eleven strains consisting of five Korean isolates, five Japanese strains, and one strain from the United Kingdom belonged to type I, whereas the pathotype strain and another 19 Korean isolates belonged to type III. Another four Japanese strains belonged to type II. Type I showed 98.9% sequence homology with type III. Type I and II had only two heterogeneous bases. The 16S rRNA sequence types were correlated with the races of P. syringae pv. morsprunorum. Type I and II strains belonged to race 1, whereas type III isolates were included in race 2. Sequence analyses of the 16S rRNA gene from P. syringae pv. morsprunorum were useful in identifying the races and can further be used for epidemiological surveillance of this pathogen.
Which Dependency Parser to Use for Distributional Semantics in a Specialized Domain?

We present a study whose objective is to compare several dependency parsers for English applied to a specialized corpus for building distributional count-based models from syntactic dependencies. One of the particularities of this study is to focus on the concepts of the target domain, which mainly occur in documents as multi-terms and must be aligned with the outputs of the parsers. We compare a set of ten parsers in terms of syntactic triplets but also in terms of distributional neighbors extracted from the models built from these triplets, both with and without an external reference concerning the semantic relations between concepts. We show more particularly that some patterns of proximity between these parsers can be observed across our different evaluations, which could give insights for anticipating the performance of a parser for building distributional models from a given corpus
Spectral Learning Techniques for Weighted Automata, Transducers, and Grammars

In recent years we have seen the development of efficient and provably correct algorithms for learning weighted automata and closely related function classes such as weighted transducers and weighted context-free grammars. The common denominator of all these algorithms is the so-called spectral method, which gives an efficient and robust way to estimate recursively defined functions from empirical estimations of observable statistics. These algorithms are appealing because of the existence of theoretical guarantees (e.g. they are not susceptible to local minima) and because of their efficiency. However, despite their simplicity and wide applicability to real problems, their impact in NLP applications is still moderate. One of the goals of this tutorial is to remedy this situation.The contents that will be presented in this tutorial will offer a complementary perspective with respect to previous tutorials on spectral methods presented at ICML-2012, ICML-2013 and NAACL-2013. Rather than using the language of graphical models and signal processing, we tell the story from the perspective of formal languages and automata theory (without assuming a background in formal algebraic methods). Our presentation highlights the common intuitions lying behind different spectral algorithms by presenting them in a unified framework based on the concepts of low-rank factorizations and completions of Hankel matrices. In addition, we provide an interpretation of the method in terms of forward and backward recursions for automata and grammars. This provides extra intuitions about the method and stresses the importance of matrix factorization for learning automata and grammars. We believe that this complementary perspective might be appealing for an NLP audience and serve to put spectral learning in a wider and, perhaps for some, more familiar context. Our hope is that this will broaden the understanding of these methods by the NLP community and empower many researchers to apply these techniques to novel problems.The content of the tutorial will be divided into four blocks of 45 minutes each, as follows. The first block will introduce the basic definitions of weighted automata and Hankel matrices, and present a key connection between the fundamental theorem of weighted automata and learning. In the second block we will discuss the case of probabilistic automata in detail, touching upon all aspects from the underlying theory to the tricks required to achieve accurate and scalable learning algorithms. The third block will present extensions to related models, including sequence tagging models, finite-state transducers and weighted context-free grammars. The last block will describe a general framework for using spectral techniques in more general situations where a matrix completion pre-processing step is required; several applications of this approach will be described.
Late Holocene vegetation dynamics and lake geochemistry at Laguna Miranda, XI Region, Chile

Analisis palinologicos y geoquimicos de sedimentos lacustres del holoceno tardio y analisis dendrocronologicos de Pilgerodendron uviferum en una zona volcanica activa del sur de Chile revelan el impacto a largo plazo de diversas caidas de tefra y actividad tectonica en la sedimentacion lacustre y la vegetacion de la zona. Una seccion sedimentaria superior de 0,75 m traslapa una columna de piston Livingstone de 4,35 m de largo para dar un registro de sedimentacion de 4,60 m de longitud extendiendose 4800 anos AP. Datos geoquimicos muestran el cambio de dominancia alogenica a dominancia autigena y biogenica segun se formaban los terrenos anegadizos dentro de la cuenca. Se presume que esto pudo producirse bajo la influencia de la llegada constante de nutrientes a la cuenca del lago procedentes del deposito de materias volcanicas conjuntamente con una alta sedimentacion. El registro palinologico de este lugar esta dominado por el tipo Nothofagus dombeyi y Filicales. Los cambios mas notables que registra el polen son, no obstante, la declinacion gradual del polen Podocarpus nubigena durante los ultimos 4800 anos; la aparicion y aumento del polen Geamineae durante los pasados 2100 anos; y el rapido aumento del polen Pilgerodendron uviferum en los ultimos 300 a 400 anos. El analisis de los anillos de leno de Pilgerodendron y los resultados que da el polen en los ultimos 400 anos muestran que la expansion mas reciente de Pilgerodendron en las margenes norte y este del lugar es una respuesta, bien a cambios periodicos de la capa freatica por interaccion tectonica, o es parte de un lento proceso de desarrollo de gimnospermas en las margenes poco profundas del lago. La disminucion de Weinmannia y Podocarpus, hace alrededor de 2100 anos AP, se podria deber a procesos autogenicos resultando en el desarrollo de terrenos anegadizos, o a cambios en el regimen de perturbacion, mas bien que a un episodio de enfriamiento climatico. En la reconstruccion de la dinamica de vegetaciones pasadas y partiendo de los registros del polen, es importante reconocer los efectos potenciales de los procesos autogenicos que pueden derivarse de perturbaciones tales como actividad volcanico/tectonica
Relations among Habitat and Population Characteristics of Spotted Bass in Kansas Streams

Abstract Spotted bass Micropterus punctulatus are popular sport fish in streams and reservoirs throughout the southeastern United States. Despite their popularity, there is a paucity of information on population characteristics and habitat requirements of spotted bass in streams. The purpose of this study was to document the factors that influence spotted bass populations in Kansas streams. Study sites were selected throughout the native range of spotted bass in Kansas. Spotted bass were sampled by electrofishing, and 31 habitat variables were measured at 16 study sites. Linear regression analyses (single and multiple) were used to determine relationships between habitat variables and spotted bass density (number/ha), biomass (kg/ha), catch per effort (CPE; number per minute of electrofishing), relative weight (Wr ), and growth. Variability in density of spotted bass 180 mm or longer was best explained by rootwad area (m2/ha). However, variability in biomass and CPE of spotted bass 180 mm or longer was be.
DNA fingerprints from blood mixes in chickens and in Turkeys

Abstract Although DNA fingerprints are useful in individual identification and genetic linkage studies, expensive and time‐consuming laboratory procedures limit their practical application. By mixing blood from individuals within a population, a DNA fingerprint pattern representing the population can be obtained. The pattern was identical to that in which DNA from individuals was mixed, and was not improved by adjusting blood volumes according to hemoglobin levels.
How Machine Learning is Improving U.S. Navy Customer Support

The U.S. Navy is successfully using natural language processing (NLP) and common machine-learning (ML) algorithms to categorize and automatically route plain text support requests at a Navy fleet support center. The algorithms enhance routine IT support tasks with automation and reduce the workload of service desk agents. The ML pipeline works in a five-step process. First, an archive of documents is created from various sources, including standard operating procedure (SOP) memos, frequently asked questions (FAQs), knowledge articles, Wikipedia articles, encyclopedia articles, previously closed support requests, and other relevant documents. Next, a library of words and phrases is generated from the archive. Then, this library is used to vectorize an incoming support request, producing a term frequency inverse document frequency (TF-IDF) vector. Following, the TF-IDF vector is used to compute similarity scores between the support request and the documents in the previously-created archive. Finally, the similarity scores are processed by support vector machine (SVM) classifiers to categorize and route the incoming support request to the correct support provider. This algorithm was deployed at a U.S. Navy customer support center as part of a pilot study, where it decreased the amount of time agents spend on tickets by 35%; the amount of time required to assign tickets by 74%; and the amount of time to close tickets by 60%. Our internal tests show that, with an error rate of 2%, a 35% reduction in ticket volume could be achieved by fully deploying these algorithms.
GENDER-RELATED effects of THE AUGMENTED REALITY GLASSES ON COGNITIVE LOAD

In recent years, the development of Industry 4.0 has led to the introduction of wearable technologies in manufacturing processes. The effects of these new and smart technologies on processes and working people are examined. In this context, both physical and cognitive load formation on people should be controlled. In this study, the effect of the augmented reality (AR) glasses on the cognitive load of the operators in an automotive company was examined. Cognitive load was measured with electroencephalography (EEG). The experiments were carried out with four (two female, two male) healthy and volunteer participants. The cases where the augmented reality glasses were used and not used were compared. The difference between these cases was also examined on a gender basis. Thus, it was observed whether the use of wearable technology has a different effect on men and women.
Influence of Organizational Culture on Green IT Adoption: Study Literature

Green IT (Information Technology) becomes one of the latest considerations to increase environmental sustainability and reduce the cost of Information Technology operation. However, the successful adoption of Green IT needs Green IT readiness measurement taken for the considerations of organizations leader. Green IT readiness focused on capability and maturity the Green IT effects on the organization. G-Readiness Molla was the integrated framework that usually used for Green IT Readiness. G-Readiness framework had five important dimensions, which were attitude, policy, practice, technology, and governance. Without considering how organization culture affected Green IT adoption. This research purpose was to build the appropriate model for inspecting the effect of organizational culture on the five dimensions of Green IT Readiness, that was Green IT Attitude, Green IT Policy, Green IT Practice, Green IT Technology, and Green IT Governance. Based on our literature review, we proposed a hypothesis: organizational culture was one of the key determinant factors in Green IT Readiness. Thus we updated the G-Readiness Molla framework by adding organizational culture as one of its dimensions
STS-korpus: A Sign Language Web Corpus Tool for Teaching and Public Use

In this paper we describe STS-korpus, a web corpus tool for Swedish Sign Language (STS) which we have built during the past year, and which is now publicly available on the internet. STS-korpus uses the data of Swedish Sign Language Corpus (SSLC) and is primarily intended for teachers and students of sign language. As such it is created to be simple and user-friendly with no download or setup required. The user interface allows for searching – with search results displayed as a simple concordance – and viewing of videos with annotations. Each annotation also provides additional data and links to the corresponding entry in the online Swedish Sign Language Dictionary. We describe the corpus, its appearance and search syntax, as well as more advanced features like access control and dynamic content. Finally we say a word or two about the role we hope it will play in the classroom, and something about the development process and the software used. STS-korpus is available here: https://teckensprakskorpus.su. se
Development of a subsurface chlorophyll maximum at the entrance to the Gulf of Finland, Baltic Sea

Horizontal, vertical, and temporal variability of chlorophyll a (Chl a), stratification, currents, and pelagial biology (phytoplankton, size‐fractionated primary productivity and Chl a, ciliates, picocyanobacteria, bacterial production) were followed at the entrance to the Gulf of Finland during a 12‐day cast study in July–August 1994. The study was carried out during weak wind conditions when hydrodynamic activity was minimal and when an intense blooming of diazotrophic cyanobacteria Aphanizomenon flos‐aquae (Linné) Ralfs, Anabaena lemmermannii Richter, and Noduluria spumigena Mertens was in its decaying phase. The property conservation equation was used to differentiate the contributions of physical and biological processes to the local Chl a changes in the layer above the thermocline. Subtraction of the Chl a change due to physical processes, mainly advection, gave a biologically induced mean decrease of 0.18 mg Chl a m−3 d−1. Sampling data confirmed the calculated decrease and revealed the basin‐wide character of the phenomenon. The observed plankton dynamics showed that the pelagial system was “top‐down” controlled and that about half the decrease of Chl a was due to a size‐specific grazing of ciliates on the dominating flagellates Chrysochromulina spp. 2–5 µm and Ochromonas spp. 7–8 µm in the upper layer. The grazers were confined to the layer above the thermocline, while the flagellates inhabited both the thermocline and the layer above. This led to the formation of a subsurface Chl a maximum in the thermocline.
PKU: Combining Supervised Classifiers with Features Selection

This paper presents the word sense disambiguation system of Peking University which was designed for the SemEval-2007 competition. The system participated in the Web track of task 11 "English Lexical Sample Task via English-Chinese Parallel Text". The system is a hybrid model by combining two supervised learning algorithms SVM and ME. And the method of entropy-based feature chosen was experimented. We obtained precision (and recall) of 81.5%.
Overview of the 4th Workshop on Asian Translation

This paper presents the results of the shared tasks from the 4th workshop on Asian translation (WAT2017) including J↔E, J↔C scientific paper translation subtasks, C↔J, K↔J, E↔J patent translation subtasks, H↔E mixed domain subtasks, J↔E newswire subtasks and J↔E recipe subtasks. For the WAT2017, 12 institutions participated in the shared tasks. About 300 translation results have been submitted to the automatic evaluation server, and selected submissions were manually evaluated.