Miracle-dz/UniFAR-FTUs huggingface dataset:
Notes on New Zealand mammals 7. An extension of the known range for pacific rat (Rattus exulans, kiore) in New Zealand

Pacific rats or kiore (Rattus exulans) were commensal with Polynesians, and accompanied them to New Zealand in the 13th century or possibly earlier (Atkinson & Towns 2005). Apart from endemic bats no terrestrial mammals lived on the New Zealand archipelago at that stage. Pacific rats colonised both main islands and many others, and had a deleterious impact on native plant seeds, invertebrates, lizards and birds. With the introduction, by Europeans, of other rodent species and mustelids during the 18th century, the previously ubiquitous distribution of Pacific rats became severely restricted (Atkinson & Towns 2005). On mainland New Zealand, Pacific rats are now known only from seven sites in south-west South Island (Atkinson & Towns 2005). All other locations are on Stewart Island and small offshore islands. It has been suggested that the real distribution of Pacific rats may be more extensive, but disguised by m isidentification or lack of trapping effort (Ruscoe 2004).
Multi-lingual Mathematical Word Problem Generation using Long Short Term Memory Networks with Enhanced Input Features

A Mathematical Word Problem (MWP) differs from a general textual representation due to the fact that it is comprised of numerical quantities and units, in addition to text. Therefore, MWP generation should be carefully handled. When it comes to multi-lingual MWP generation, language specific morphological and syntactic features become additional constraints. Standard template-based MWP generation techniques are incapable of identifying these language specific constraints, particularly in morphologically rich yet low resource languages such as Sinhala and Tamil. This paper presents the use of a Long Short Term Memory (LSTM) network that is capable of generating elementary level MWPs, while satisfying the aforementioned constraints. Our approach feeds a combination of character embeddings, word embeddings, and Part of Speech (POS) tag embeddings to the LSTM, in which attention is provided for numerical values and units. We trained our model for three languages, English, Sinhala and Tamil using separate MWP datasets. Irrespective of the language and the type of the MWP, our model could generate accurate single sentenced and multi sentenced problems. Accuracy reported in terms of average BLEU score for English, Sinhala and Tamil languages were 22.97%, 24.49% and 20.74%, respectively.
Urdu Pitch Accents and Intonation Patterns in Spontaneous Conversational Speech

An intonational inventory of Urdu for spontaneous conversational speech is determined based on the analysis of a hand-labelled data set of telephone conversations. An inventory of Urdu pitch accents and the basic Urdu intonation patterns observed in the data are summarised and presented using a simplified version of the Rhythm and Pitch (RaP) labelling system. The relation between pitch accents and parts of speech (PoS) is also explored. The data confirm the important role played by low pitch accents in Urdu spontaneous speech, in line with previous studies on Urdu/Hindi scripted speech. Typical pitch contours such as falling tone in statements and WH-questions, and rising tone for yes/no questions are also exhibited. Pitch accent distribution is quite free in Urdu, but the data indicate a stronger association of pitch accent with some PoS categories of content word (e.g. Nouns) when compared with function words and semantically lighter PoS categories (such as Light Verbs). Contrastive focus is realised by an L*+H accent with a relatively large pitch excursion for the +H tone, and longer duration of the stressed syllable. The data suggest that post-focus compression (PFC) is used in Urdu as a focus-marking strategy.
Lesser Flamingo Phoeniconaias minor as a nomadic species in African shallow alkaline lakes and pans: genetic structure and future perspectives

The Lesser Flamingo Phoeniconaias minor is a nomadic species, which inhabits shallow alkaline lakes and pans in sub-Saharan Africa and southern Asia. The extent of genetic diversity and the degree of differentiation within and among populations are important factors to determine in order to help manage and conserve the species, categorised as Near Threatened by the IUCN. This study provides an assessment of the population structure of the two largest African populations of P. minor by genotyping six microsatellite loci from 30 individuals sampled on Lake Bogoria (Kenya) and 11 individuals from Makgadikgadi Sua Pan (Botswana). The alleles detected per locus ranged from four to 13. The Lake Bogoria population harboured 15 specific alleles, whereas the Makgadikgadi Sua Pan population only six alleles. Moderate genetic diversity (He = 0.64–0.69) was comparable with populations that have not suffered from demographic bottlenecks or inbreeding. The populations are genetically similar with little differentiation (FST and RST not significantly different from zero). Small but continuous gene flow (the estimated average number of individuals exchanged is 3–4 per generation) was found, probably reflecting the bird's nomadic behaviour and the natural presence of temporary shallow waters between the two sampled populations. The results suggest that inbreeding effects at present are unlikely, and hence that the loss and/or degradation of its specialised habitat remains the primary concern for the species’ continued survival.
Treebanking User-Generated Content: A Proposal for a Unified Representation in Universal Dependencies

The paper presents a discussion on the main linguistic phenomena of user-generated texts found in web and social media, and proposes a set of annotation guidelines for their treatment within the Universal Dependencies (UD) framework. Given on the one hand the increasing number of treebanks featuring user-generated content, and its somewhat inconsistent treatment in these resources on the other, the aim of this paper is twofold: (1) to provide a short, though comprehensive, overview of such treebanks - based on available literature - along with their main features and a comparative analysis of their annotation criteria, and (2) to propose a set of tentative UD-based annotation guidelines, to promote consistent treatment of the particular phenomena found in these types of texts. The main goal of this paper is to provide a common framework for those teams interested in developing similar resources in UD, thus enabling cross-linguistic consistency, which is a principle that has always been in the spirit of UD.
Getting More Data for Low-resource Morphological Inflection: Language Models and Data Augmentation

We investigate how to improve quality of low-resource morphological inflection without annotating more data. We examine two methods, language models and data augmentation. We show that the model whose decoder that additionally uses the states of the langauge model improves the model quality by 1.5% in combination with both baselines. We also demonstrate that the augmentation of data improves performance by 9% in average when adding 1000 artificially generated word forms to the dataset.
A Broad-coverage Corpus for Finnish Named Entity Recognition

We present a new manually annotated corpus for broad-coverage named entity recognition for Finnish. Building on the original Universal Dependencies Finnish corpus of 754 documents (200,000 tokens) representing ten different genres of text, we introduce annotation marking person, organization, location, product and event names as well as dates. The new annotation identifies in total over 10,000 mentions. An evaluation of inter-annotator agreement indicates that the quality and consistency of annotation are high, at 94.5% F-score for exact match. A comprehensive evaluation using state-of-the-art machine learning methods demonstrates that the new resource maintains compatibility with a previously released single-domain corpus for Finnish NER and makes it possible to recognize named entity mentions in texts drawn from most domains at precision and recall approaching or exceeding 90%. Remaining challenges such as the identification of names in blog posts and transcribed speech are also identified. The newly introduced Turku NER corpus and related resources introduced in this work are released under open licenses via https://turkunlp.org/turku-ner-corpus .
MuDoCo: Corpus for Multidomain Coreference Resolution and Referring Expression Generation

This paper proposes a new dataset, MuDoCo, composed of authored dialogs between a fictional user and a system who are given tasks to perform within six task domains. These dialogs are given rich linguistic annotations by expert linguists for several types of reference mentions and named entity mentions, either of which can span multiple words, as well as for coreference links between mentions. The dialogs sometimes cross and blend domains, and the users exhibit complex task switching behavior such as re-initiating a previous task in the dialog by referencing the entities within it. The dataset contains a total of 8,429 dialogs with an average of 5.36 turns per dialog. We are releasing this dataset to encourage research in the field of coreference resolution, referring expression generation and identification within realistic, deep dialogs involving multiple domains. To demonstrate its utility, we also propose two baseline models for the downstream tasks: coreference resolution and referring expression generation.
A Corpus of German Reddit Exchanges (GeRedE)

GeRedE is a 270 million token German CMC corpus containing approximately 380,000 submissions and 6,800,000 comments posted on Reddit between 2010 and 2018. Reddit is a popular online platform combining social news aggregation, discussion and micro-blogging. Starting from a large, freely available data set, the paper describes our approach to filter out German data and further pre-processing steps, as well as which metadata and annotation layers have been included so far. We explore the Reddit sphere, what makes the German data linguistically peculiar, and how some of the communities within Reddit differ from one another. The CWB-indexed version of our final corpus is available via CQPweb, and all our processing scripts as well as all manual annotation and automatic language classification can be downloaded from GitHub.
Occurrence of Caligus lalandei Barnard, 1948 (Copepoda, Siphonostomatoida) on Amberjacks (Seriola spp.) in the Western North Pacific

Abstract Caligus lalandei Barnard, 1948 (Caligidae, Siphonostomatoida) is redescribed based on the materials occurring in the waters of East Asia. This parasitic copepod is so far known only from the amber-jacks (Seriola spp.) outside of the western North Pacific. However, in 1989 it was discovered on “mojako” (juveniles) of Seriola quinqueradiata collected off Azuma-cho and Yamakawa-cho in Kogoshima Prefecture, Japan. In 1998 it appeared on Seriola lalandi caught in a set net installed off the coast near Kangreung, Korea and in the following year it was found parasitic on S. lalandi cultured in Tsukumi of Oita Prefecture, Japan. The possible origin of the occurrence of C. lalandei in Japan and Korea is discussed; but, due to several unknown factors, it is inconclusive at this point of time whether the occurrence of C. lalandei in Japan and Korea is due to the “natural” or “artificial” process. However, the parasite has well established in its new habitat - the northern region of the western North Pacific.
Recovery of Estrus and Ovulatory Response in Cows after Intrauterine Injection of Chitin Suspension

The purpose of the present study was to evaluate the therapeutic effect of intrauterine chitin suspension on endometritis in cows. In experiment 1, 50 ml chitin suspension (60 and 80 mg/ml in saline), definitely induced estrus. Therefore, 50 ml of the 60 mg/ml suspension was injected into the uteri of Japanese Black cows (3-5 years old, average weight 530 kg) with a normal estrus cycle or endometritis in further experiments. In experiment 2, 21 parous Japanese Black cows with a normal estrus cycle received chitin on day 8-12 of estrus (the day on which estrus occurred was designated day 0). Nineteen of the 21 (90.5%) came into estrus 5-8 days after administration, and 3 control cows receiving saline solution came into estrus 13 days after administration (21 days after the preceding estrus). Progesterone levels in 3 randomly selected cows were reduced from 6.3, 6.3 and 2.6 ng/ml on the day of chitin administration to 0.3, 0.2 and 0.2 ng/ml, respectively, 6 days after administration. In addition, many leucocytes were detected in uterine mucosal biopsy specimens 2 to 3 days after chitin administration. In experiment 3, estrus was induced in 5 cows with endometritis 6-8 days after chitin administration and the endometritis was improved with the disappearance of pus. Normal embryos were obtained in 2 of 4 cows (8/12 ova; 75%) that received superovulatory treatment during the estrus cycle induced by chitin. These findings suggest that the intrauterine injection of chitin can induce estrus and subsequent ovulatory response by its therapeutic effect on endometritis in cattle.
Towards a Gold Standard for Evaluating Danish Word Embeddings

This paper presents the process of compiling a model-agnostic similarity goal standard for evaluating Danish word embeddings based on human judgments made by 42 native speakers of Danish. Word embeddings resemble semantic similarity solely by distribution (meaning that word vectors do not reflect relatedness as differing from similarity), and we argue that this generalization poses a problem in most intrinsic evaluation scenarios. In order to be able to evaluate on both dimensions, our human-generated dataset is therefore designed to reflect the distinction between relatedness and similarity. The goal standard is applied for evaluating the “goodness” of six existing word embedding models for Danish, and it is discussed how a relatively low correlation can be explained by the fact that semantic similarity is substantially more challenging to model than relatedness, and that there seems to be a need for future human judgments to measure similarity in full context and along more than a single spectrum.
Providing Semantic Knowledge to a Set of Pictograms for People with Disabilities: a Set of Links between WordNet and Arasaac: Arasaac-WN

This article presents a resource that links WordNet, the widely known lexical and semantic database, and Arasaac, the largest freely available database of pictograms. Pictograms are a tool that is more and more used by people with cognitive or communication disabilities. However, they are mainly used manually via workbooks, whereas caregivers and families would like to use more automated tools (use speech to generate pictograms, for example). In order to make it possible to use pictograms automatically in NLP applications, we propose a database that links them to semantic knowledge. This resource is particularly interesting for the creation of applications that help people with cognitive disabilities, such as text-to-picto, speech-to-picto, picto-to-speech. In this article, we explain the needs for this database and the problems that have been identified. Currently, this resource combines approximately 800 pictograms with their corresponding WordNet synsets and it is accessible both through a digital collection and via an SQL database. Finally, we propose a method with associated tools to make our resource language-independent: this method was applied to create a first text-to-picto prototype for the French language. Our resource is distributed freely under a Creative Commons license at the following URL: https://github.com/getalp/Arasaac-WN.
Analyzing Word Embedding Through Structural Equation Modeling

Many researchers have tried to predict the accuracies of extrinsic evaluation by using intrinsic evaluation to evaluate word embedding. The relationship between intrinsic and extrinsic evaluation, however, has only been studied with simple correlation analysis, which has difficulty capturing complex cause-effect relationships and integrating external factors such as the hyperparameters of word embedding. To tackle this problem, we employ partial least squares path modeling (PLS-PM), a method of structural equation modeling developed for causal analysis. We propose a causal diagram consisting of the evaluation results on the BATS, VecEval, and SentEval datasets, with a causal hypothesis that linguistic knowledge encoded in word embedding contributes to solving downstream tasks. Our PLS-PM models are estimated with 600 word embeddings, and we prove the existence of causal relations between linguistic knowledge evaluated on BATS and the accuracies of downstream tasks evaluated on VecEval and SentEval in our PLS-PM models. Moreover, we show that the PLS-PM models are useful for analyzing the effect of hyperparameters, including the training algorithm, corpus, dimension, and context window, and for validating the effectiveness of intrinsic evaluation.
Legal-ES: A Set of Large Scale Resources for Spanish Legal Text Processing

Legal-ES is an open source resource kit for legal Spanish. It consists of a large scale Spanish corpus of open legal texts and different kinds of language models including word embeddings and topic models. The corpus includes over 1000 million words covering a collection of legislative and administrative open access documents in Spanish from different sources representing international, national and regional entities. The corpus is pre-processed and tokenized using Spacy. For the word embeddings, gensim was used on the collection of tokens, producing a representation space that is especially suited to reflect the inherent characteristics of the legal domain. We calculate also topic models to obtain a convenient tool to understand the main topics in the corpus and to navigate through the documents exploiting the semantic similarity among documents. We will analyse the time structure of a dynamic topic model to infer changes in the legal production of Spanish jurisdiction that have occurred over the analysed time framework.
WorldTree V2: A Corpus of Science-Domain Structured Explanations and Inference Patterns supporting Multi-Hop Inference

Explainable question answering for complex questions often requires combining large numbers of facts to answer a question while providing a human-readable explanation for the answer, a process known as multi-hop inference. Standardized science questions require combining an average of 6 facts, and as many as 16 facts, in order to answer and explain, but most existing datasets for multi-hop reasoning focus on combining only two facts, significantly limiting the ability of multi-hop inference algorithms to learn to generate large inferences. In this work we present the second iteration of the WorldTree project, a corpus of 5,114 standardized science exam questions paired with large detailed multi-fact explanations that combine core scientific knowledge and world knowledge. Each explanation is represented as a lexically-connected “explanation graph” that combines an average of 6 facts drawn from a semi-structured knowledge base of 9,216 facts across 66 tables. We use this explanation corpus to author a set of 344 high-level science domain inference patterns similar to semantic frames supporting multi-hop inference. Together, these resources provide training data and instrumentation for developing many-fact multi-hop inference models for question answering.
Developmental Control of Net Productivity in Typha Latifolia Ecotypes

Population samples of broad-leaved cattail (Typha latifolia L.) from a variety of climates were studied to determine the extent to which net productivity, as dry matter production rate, was determined by (a) net assimilation rate per unit leaf tissue and (b) rate of production of leaf tissue. Assimilation rates of the eight populations studied were identical. Similarly, acclimation responses stabilized the net carbon balance of the same genotype under different environmental conditions. In contrast, rates of biomass production varied widely in different genotypes in the same environment, and in the same genotype in different environ- ments. Variations in net productivity were regulated primarily by the rate of production of leaf tissue. This relationship held for different genotypes in the same environment, and the same genotype in different environments. Therefore, I conclude that the efficiency of net production in cattails is determined primarily by the rate at which leaf tissue is produced, rather than by inherent differences in the assimilation efficiency of that tissue.
Efeito do uso de óleo de vísceras de aves oxidado na ração de frangos de corte sobre o desempenho, a composição da carcaça e a estabilidade oxidativa da carne da sobrecoxa

Two hundred male Ross broiler chicks were raised from 10 to 40 days of age and fed a corn-soy diet with 4% of fresh or oxidized poultry offal fat to evaluate the effects of dietary fat quality on broiler performance and on oxidative stability of frozen thigh meat during storage. Fresh poultry fat, characterized by low concentration of oxidation products determined by specific absorbances of 5.80 and 0.69 at 232 and 270 nm, respectively, was supplied by a local renderer and stored frozen (-18oC) until diets were produced. Oxidized poultry fat was obtained by heating the fresh poultry fat in a fryer at 110-120 oC until specific absorbances reached 11.33 (at 232 nm) and 2.31 (at 270 nm), which show increased concentration of oxidation compounds. At 41 days of age, 136 birds were slaughtered and carcass characteristics were evaluated. Skinless and deboned raw thigh meat was packed and stored for 9 months in a non-illuminated freezer at -20oC. Thiobarbituric acid reactive substances (TBARS) were assessed monthly in the frozen samples to evaluate the oxidative status of stored meat. Birds performance and carcass characteristics were not affected by the presence of oxidized poultry fat in the diet. After six months of storage, the oxidative stability of frozen thigh meat from broilers fed oxidized poultry fat was reduced, indicated by higher TBARS values.
Evaluation of Crop Rotation and Other Cultural Practices for Management of Root‐Knot and Lesion Nematodes

Root-knot [Meloidogyne incognita (Kofoid & White) Chitwood] and lesion [Pralylenchus penetrans (Cobb) Chitwood & Oteifa] nematodes are important pathogens that cause yield and quality losses for most vegetable and field crops in Maryland when they exceed certain threshold levels and if control measures are not applied. Chemical nematicides are the primary control tactic, but their use is both costly and raises environmental concerns. This study was conducted to evaluate the efficacy of crop rotation and other cultural practices for management of southern root-knot nematodes (RKNs) and lesion nematodes. Three nonhost crops, a RKN-resistant soybean [Glycine max (L.) Merr. ] cultivar, and poultry litter/tillage (Year 1) and fallow (Year 2) were used as summer rotation crops/management options following production of nematode-susceptible crops on two sites in Dorchester County, MD, on Downer and Hammonton sandy loam soils (coarse-loamy, siliceous, mesic Typic and Aquic Hapludults), respectively. Sorghum sudangrass [Sorghum bicolor (L.) x S. arundinaceum (Desv.) Stapf var. sudanense (Stapf) Hitchc. ], grown annually as a green manure crop following a nematode-susceptible crop [potato (Solanum tuberosum L.) or cucumber (Cucumis sativus L.)], reduced the RKN population as effectively as the control treatment (soybean cultivar with no known RKN resistance and one nematicide application). Sorghum sudangrass and poultry litter/tillage/fallow were equally effective in managing the lesion nematode population. Annual inclusion of these practices was necessary to maintain the reduced population levels that were attained for these two nematode species. Finally, either summer or early-fall sampling dates were determined to be more effective than a midspring sampling date for identifying threshold levels of these two pests.