Miracle-dz/UniFAR-FTUs huggingface dataset:
Time-Updated Changes in Estimated GFR and Proteinuria and Major Adverse Cardiac Events: Findings from the Chronic Renal Insufficiency Cohort (CRIC) Study.

RATIONALE AND OBJECTIVE Evaluating repeated measures of estimated glomerular filtration rate (eGFR) and urine protein-to-creatinine ratio (UPCR) over time may enhance our ability to understand the association between changes in kidney parameters and cardiovascular disease risk. STUDY DESIGN Prospective cohort study. SETTING AND PARTICIPANTS Annual visit data from 2,438 participants in the Chronic Renal Insufficiency Cohort. EXPOSURES Average and slope of eGFR and UPCR in time-updated, one-year exposure windows. OUTCOMES Incident heart failure, atherosclerotic cardiovascular disease events, death, and a composite of incident heart failure, atherosclerotic cardiovascular disease events, and death. ANALYTIC APPROACH A landmark analysis, a dynamic approach to survival modeling that leverages longitudinal, iterative profiles of laboratory and clinical information to assess the time-updated three-year risk of adverse cardiovascular outcomes. RESULTS Adjusting for baseline and time-updated covariates, every standard deviation lower mean eGFR (19 mL/min/1.73m2) and declining slope of eGFR (8 mL/min/1.73m2/year) were independently associated with a higher risk of heart failure (mean eGFR hazard ratio [HR] 1.82, 95% confidence interval 1.39-2.44; slope HR 1.28, 1.12-1.45) and the composite outcome (mean HR 1.32, 1.11-1.54; slope HR 1.11, 1.03-1.20). Every standard deviation higher mean UPCR (136 mg/g) and rising UPCR (240 mg/g/year) were also independently associated with a higher risk of heart failure (mean HR 1.58, 1.28-1.97; slope HR 1.20, 1.10-1.29) and the composite outcome (mean HR 1.33, 1.17-1.50; slope HR 1.12, 1.06-1.18). LIMITATIONS Limited generalizability of annual eGFR and UPCR measurements; several biomarkers for cardiovascular disease risk were not available annually. CONCLUSIONS Using the landmark approach to account for time-updated patterns of kidney function, average and slope of eGFR and proteinuria were independently associated with three-year cardiovascular risk. Short-term changes in kidney function provide information about cardiovascular risk incremental to level of kidney function, representing possible opportunities for more effective management of patients with chronic kidney disease.
Social Presence in Computer-Based Receptionists: Experimental Study Towards Organizational Automation

This study investigated how computer-based receptionists were perceived by visitors. Considering the perceived degree of social presence in four types of receptionists, we tested perceptions in source credibility, communication competence, satisfaction with interaction, and organizational attraction. Data from 473 participants indicated that the highest social presence was perceived in a text-based check-in system when compared to (a) human receptionist on a monitor, (b) avatar, and (c) holographic receptionist. Our findings also reveal that users would treat text-based computers in the same way as human agents in terms of the cognitive and affective aspects. The challenge in the behavioral aspect suggests that communication skills would be key for successful human-computer interaction.
Prioritisation of targets for weed biological control II: the South African Biological Control Target Selection system

ABSTRACT Invasive alien plants (IAPs) are considered one of the greatest threats to biodiversity in South Africa and are often associated with negative socio-economic and human health consequences. Biocontrol is seen as an effective strategy for managing IAPs however it can realistically only be considered for a subset of such plants given the limited funding resources available. Some plants are also better targets for biocontrol than others. This paper develops a prioritisation system to create an objective, transparent and easily usable method in which to target IAPs plants that are most suited to biocontrol in South Africa. The Biological Control Target Selection (BCTS) system builds on twelve previously developed prioritisation systems. The system uses three sections encompassing thirteen attributes that are combined to present the highest predicative powers to rank potential target IAPs as biocontrol targets.
Multiword expressions as discourse markers in Hebrew and Lithuanian

Multiword expressions are of key importance in language generation and processing. Certain multiword expressions also could operate as discourse markers. In this research, we combined the alignment model of the phrase-based statistical machine translation and manual treatment of the data in order to examine English multiword discourse markers and their equivalents in Lithuanian and Hebrew, by researching their changes in translation. After establishing a full list of multiword discourse markers in our generated parallel corpus, we focused on the two most frequent ones functioning as stance attitudinal discourse markers: I think and you know aiming to research if they demonstrate their functional stability as stance attitudinal discourse markers in translation and what changes they undergo in Lithuanian and Hebrew translation. Our research proves that the examined multiword discourse markers preserve their function as stance attitudinal discourse markers and tend to remain multiword discourse markers in the Hebrew translation but turn into one-word discourse markers in Lithuanian due to the translation tendency relying on inflections.
CombAlign: a Tool for Obtaining High-Quality Word Alignments

Being able to generate accurate word alignments is useful for a variety of tasks. While statistical word aligners can work well, especially when parallel training data are plentiful, multilingual embedding models have recently been shown to give good results in unsupervised scenarios. We evaluate an ensemble method for word alignment on four language pairs and demonstrate that by combining multiple tools, taking advantage of their different approaches, substantial gains can be made. This holds for settings ranging from very low-resource to high-resource. Furthermore, we introduce a new gold alignment test set for Icelandic and a new easy-to-use tool for creating manual word alignments.
Towards cross-lingual application of language-specific PoS tagging schemes

We describe the process of conversion between the PoS tagging schemes of two languages, the Icelandic MIM-GOLD tagging scheme and the Faroese Sosialurin tagging scheme. These tagging schemes are functionally similar but use separate ways to encode fine-grained morphological information on tokenised text. As Faroese and Icelandic are lexically and grammatically similar, having a systematic method to convert between these two tagging schemes would be beneficial in the field of language technology, specifically in research on transfer learning between the two languages. As a product of our work, we present a provisional version of Icelandic corpora, prepared in the Faroese PoS tagging scheme, ready for use in cross-lingual NLP applications.
Leveraging Task Information in Grammatical Error Correction for Short Answer Assessment through Context-based Reranking

One of the issues in automatically evaluating learner input in the context of Intelligent Tutoring Systems is learners’ use of incorrect forms and non-standard language. Grammatical Error Correction (GEC) systems have emerged as a way of automatically correcting grammar and spelling mistakes, often by approaching the task as machine translation of individual sentences from non-standard to standard language. However, due to the inherent lack of context awareness, GEC systems often do not produce a contextually appropriate correction. In this paper, we investigate how current neural GEC systems can be optimized for educationally relevant tasks such as Short Answer Assessment. We build on a recent GEC system and train a reranker based on context (e.g. similarity to prompt), task (e.g. type and format) and answer-level (e.g. language modeling) features on a Short Answer Assessment data set augmented with crowd worker corrections. Results show that our approach successfully gives preference to corrections that are closer to the reference.
DaNLP: An open-source toolkit for Danish Natural Language Processing

We present an open-source toolkit for Danish Natural Language Processing, enabling easy access to Danish NLP’s latest advancements. The toolkit features wrapper-functions for loading models and datasets in a unified way using third-party NLP frameworks. The toolkit is developed to enhance community building, understanding the need from industry and knowledge sharing. As an example of this, we present Angry Tweets: An Annotation Game to create awareness of Danish NLP and create a new sentiment-annotated dataset.
Creating and Evaluating a Synthetic Norwegian Clinical Corpus for De-Identification

Building tools to remove sensitive information such as personal names, addresses, and telephone numbers - so called Protected Health Information (PHI) - from clinical free text is an important task to make clinical texts available for research. These de-identification tools must be assessed regarding their quality in the form of the measurements precision and re- call. To assess such tools, gold standards - annotated clinical text - must be available. Such gold standards exist for larger languages. For Norwegian, how- ever, there are no such resources. Therefore, an already existing Norwegian synthetic clinical corpus, NorSynthClinical, has been extended with PHIs and annotated by two annotators, obtaining an inter-annotator agreement of 0.94 F1-measure. In total, the corpus has 409 annotated PHI instances and is called NorSynthClinical PHI. A de-identification hybrid tool (machine learning and rule-based meth- ods) for Norwegian was developed and trained with open available resources, and obtained an overall F1-measure of 0.73 and a recall of 0.62, when tested using NorSynthClinical PHI. NorSynthClinical PHI is made open and available at Github to be used by the research community.
Translation Competence in Machines: A Study of Adjectives in English-Swedish Translation

Recent improvements in neural machine translation calls for increased efforts on qualitative evaluations so as to get a better understanding of differences in translation competence between human and machine. This paper reports the results of a study of 1170 adjectives in translation from English to Swedish, using the Parallel Universal Dependencies Treebanks for these languages. The comparison covers two dimensions: the types of solutions employed and the incidence of debatable or incorrect translations. It is found that the machine translation uses all of the solution types that the human translation does, but in different proportions and less competently.
Multilingual ELMo and the Effects of Corpus Sampling

Multilingual pretrained language models are rapidly gaining popularity in NLP systems for non-English languages. Most of these models feature an important corpus sampling step in the process of accumulating training data in different languages, to ensure that the signal from better resourced languages does not drown out poorly resourced ones. In this study, we train multiple multilingual recurrent language models, based on the ELMo architecture, and analyse both the effect of varying corpus size ratios on downstream performance, as well as the performance difference between monolingual models for each language, and broader multilingual language models. As part of this effort, we also make these trained models available for public use.
Learning to Lemmatize in the Word Representation Space

Lemmatization is often used with morphologically rich languages to address issues caused by morphological complexity, performed by grammar-based lemmatizers. We propose an alternative for this, in form of a tool that performs lemmatization in the space of word embeddings. Word embeddings as distributed representations natively encode some information about the relationship between base and inflected forms, and we show that it is possible to learn a transformation that approximately maps the embeddings of inflected forms to the embeddings of the corresponding lemmas. This facilitates an alternative processing pipeline that replaces traditional lemmatization with the lemmatizing transformation in downstream processing for any application. We demonstrate the method in the Finnish language, outperforming traditional lemmatizers in example task of document similarity comparison, but the approach is language independent and can be trained for new languages with mild requirements.
Using Broad Linguistic Complexity Modeling for Cross-Lingual Readability Assessment

We investigate the readability classiﬁcation of English and German reading materials for language learners based on a broad linguistic complexity feature set supporting the parallel analysis of both German and English. After illustrating the quality of the feature set by showing that it yields state-of-the-art classiﬁcation performance for the established OneStopEnglish corpus (Vajjala and Luˇci´c, 2018), we introduce the Spotlight corpus. This new data set contains graded reading materials produced by the same publisher for English and German, which supports an analysis comparing the linguistic characteristics of texts at different reading levels across languages. As far as we are aware, this is both the ﬁrst readability corpus for German L2 learners, as well as the ﬁrst corpus with comparably classiﬁed reading material for learners across multiple languages. After discussing the ﬁrst results for a read-ability classiﬁer for German L2 learners, we show that the linguistic complexity analyses for the cross-language experiments identify features successfully characterizing the readability of texts for language learners across languages, as well as some language-speciﬁc characteristics of different reading levels.
Spectral modification for recognition of children’s speech undermismatched conditions

In this paper, we propose spectral modification by sharpening formants and by reducing the spectral tilt to recognize children’s speech by automatic speech recognition (ASR) systems developed using adult speech. In this type of mismatched condition, the ASR performance is degraded due to the acoustic and linguistic mismatch in the attributes between children and adult speakers. The proposed method is used to improve the speech intelligibility to enhance the children’s speech recognition using an acoustic model trained on adult speech. In the experiments, WSJCAM0 and PFSTAR are used as databases for adults’ and children’s speech, respectively. The proposed technique gives a significant improvement in the context of the DNN-HMM-based ASR. Furthermore, we validate the robustness of the technique by showing that it performs well also in mismatched noise conditions.
Applying and Sharing pre-trained BERT-models for Named Entity Recognition and Classification in Swedish Electronic Patient Records

To be able to share the valuable information in electronic patient records (EPR) they first need to be de-identified in order to protect the privacy of their subjects. Named entity recognition and classification (NERC) is an important part of this process. In recent years, general-purpose language models pre-trained on large amounts of data, in particular BERT, have achieved state of the art results in NERC, among other NLP tasks. So far, however, no attempts have been made at applying BERT for NERC on Swedish EPR data. This study attempts to fine-tune one Swedish BERT-model and one multilingual BERT-model for NERC on a Swedish EPR corpus. The aim is to assess the applicability of BERT-models for this task as well as to compare the two models in a domain-specific Swedish language task. With the Swedish model, recall of 0.9220 and precision of 0.9226 is achieved. This is an improvement to previous results on the same corpus since the high recall does not sacrifice precision. As the models also perform relatively well when fine-tuned with pseudonymised data, it is concluded that there is good potential in using this method in a shareable de-identification system for Swedish clinical text.
Getting Hold of Villains and other Rogues

In this paper, we introduce the first corpus specifying negative entities within sentences. We discuss indicators for their presence, namely particular verbs, but also the linguistic conditions when their prediction should be suppressed. We further show that a fine-tuned Bert-based baseline model outperforms an over-generating rule-based approach which is not aware of these further restrictions. If a perfect filter were applied, both would be on par.
Multiple trans-Torres Strait colonisations by tree frogs in the Litoria caerulea group, with the description of a new species from New Guinea

Abstract. Australia and New Guinea (together referred to as Sahul) were linked by land for much of the late Tertiary and share many biotic elements. However, New Guinea is dominated by rainforest, and northern Australia by savannah. Resolving patterns of biotic interchange between these two regions is critical to understanding the expansion and contraction of both habitat types. The green tree frog (Litoria caerulea) has a vast range across northern and eastern Australia and New Guinea. An assessment of mitochondrial and morphological diversity in this nominal taxon in New Guinea reveals two taxa. True Litoria caerulea occurs in disjunct savannahs of the Trans-Fly, Central Province and across northern Australia, with very low genetic divergence, implying late Pleistocene connectivity. A previously unrecognised taxon is endemic to New Guinea and widespread in lowland swampy rainforest. Date estimates for the divergence of the new species suggest Pliocene connectivity across lowland tropical habitats of northern Australia and New Guinea. In contrast, the new species shows shallow phylogeographic structuring across the central mountains of New Guinea, implying recent dispersal between the northern and southern lowlands. These results emphasise that the extent and connectivity of lowland rainforest and savannah environments across northern Australia and southern New Guinea have undergone profound shifts since the late Pliocene.
Warts Galore – on Three New Lamprospora De Not. Species (Pezizales) from Southern Europe and Macaronesia and a Type Revision of Three Species Described from the US by F. J. Seaver in the 1910s

ABSTRACT Lamprospora bulbiformis M.Vega & Janošík, sp. nov., L. gibbosa M.Vega & Janošík, sp. nov. and L. thelespora Martínez-Gil, M.Vega & E.Rubio, sp. nov. are described and illustrated based on live collections from Cyprus, France, Portugal and Spain. Phylogenetic analyses of the concatenated LSU, SSU and EF1-α gene sequences show the studied collections of the three species form well supported monophyletic clades. Lamprospora bulbiformis sp. nov. infects Fissidens viridulus (Sw. ex anon.) Wahlenb. , L. gibbosa sp. nov. has F. crassipes Wilson ex Bruch & Schimp. as host and L. thelespora sp. nov. grows on Cheilothela chloropus (Brid.) Broth. Three Lamprospora De Not. species namely L. tuberculata Seaver, L. tuberculatella Seaver and L. spinulosa Seaver with a slightly similar ascospore ornamentation were described by Seaver from US collections. Results of our studies of their types and additional material collected by Seaver are presented. The host of L. tuberculata is Pleuridium subulatum (Hedw.) Rabenh. , that of L. tuberculatella is a species of Weissia Hedw. and that of L. spinulosa is Physcomitrium pyriforme (Hedw.) Bruch & Schimp. It has yet to be proven that species of Lamprospora described from North America also occur in Europe. European collections assigned to any Lamprospora described from North America require revision. It is not unlikely that many or even all of them represent taxa yet to be described. A considerable part of existing literature on bryophilous Pezizales needs to be reevaluated.
Finding Treatment Effects in Alzheimer Trials in the Face of Disease Progression Heterogeneity

Objective To investigate the influence of heterogeneity in disease progression for detecting treatment effects in Alzheimer disease (AD) trials, using a simulation study. Methods Individuals with an abnormal amyloid PET scan, diagnosis of mild cognitive impairment or dementia, baseline Mini-Mental State Examination (MMSE) score ≥24, global Clinical Dementia Rating (CDR) score of 0.5, and ≥1 follow-up cognitive assessment were selected from the Alzheimer's Disease Neuroimaging Initiative database (n = 302, age 73 ± 6.7; 44% female; 16.1 ± 2.7 years of education; 69% APOE ε4 carrier). We simulated a clinical trial by randomly assigning individuals to a “placebo” and “treatment” group and subsequently computed group differences on the CDR–sum of boxes (CDR-SB), Alzheimer’s Disease Assessment Scale–cognitive subscale–13 and MMSE after 18 months follow-up. We repeated this simulation 10,000 times to determine the 95% range of effect sizes. We further studied the influence of known AD risk factors (age, sex, education, APOE ε4 status, CSF total tau levels) on the variability in effect sizes. Results Individual trajectories on all cognitive outcomes were highly variable, and the 95% ranges of possible effect sizes at 18 months were broad (e.g., ranging from 0.35 improvement to 0.35 decline on the CDR-SB). Results of recent anti-amyloid trials mostly fell within these 95% ranges of effect sizes. APOE ε4 carriers and individuals with abnormal baseline tau levels showed faster decline at group level, but also greater within-group variability, as illustrated by broader 95% effect size ranges (e.g., ±0.70 points for the CDR-SB). Conclusions Individuals with early AD show heterogeneity in disease progression, which increases when stratifying on risk factors associated with progression. We provide guidance for a priori effect sizes on cognitive outcomes for detecting true change, which is crucial for future AD trials.
Daytime

Abstract:Early on in the pandemic, I was setting up a video meeting time with a friend and I responded with a blank “I have daytime. ” Stunned by the bluntness and vagueness of such a statement, I then searched “I have daytime” on the internet and this poem was fed to me by the search. The search results echo my feelings about pandemic time. My handwritten words trace the presence of my body during this time.Mariana Valencia is a performer and choreographer who works through the presence of the body and writing. She currently activates her work on any axis the world can lend, and looks forward to redefining the meaning of reunion once we can convene again. www.marianavalencia. work