Atomic: an open-source software platform for multi-level corpus annotation

This paper presents Atomic, an open-source platform-independent desktop application for multi-level corpus annotation. Atomic aims at providing the linguistic community with a user-friendly annotation tool and sustainable platform through its focus on extensibility, a generic data model, and compatibility with existing linguistic formats. It is implemented on top of the Eclipse Rich Client Platform, a pluggable Java-based framework for creating client applications. Atomic - as a set of plug-ins for this framework - integrates with the platform and allows other researchers to develop and integrate further extensions to the software as needed. The generic graph-based meta model Salt serves as Atomic’s domain model and allows for unlimited annotation levels and types. Salt is also used as an intermediate model in the Pepper framework for conversion of linguistic data, which is fully integrated into Atomic, making the latter compatible with a wide range of linguistic formats. Atomic provides tools for both less experienced and expert annotators: graphical, mouse-driven editors and a command-line data manipulation language for rapid annotation

Towards a corpus-based analysis of evaluative scales associated with even

Scalar focus operators like even, only, etc. interact with scales, i. e., ordered sets of alternatives that are referenced by focus structure. The scaling dimensions interacting with focus operators have been argued to be semantic (e. g. entailment relations, probability) in earlier work, but it has been shown that purely semantic analyses are too restrictive, and that the specific scale that a given operator interacts with is often pragmatic, in the sense of being a function of the context. If that is true, the question arises what exactly determines the (types of) scales interacting with focus operators. The present study addresses this question by investigating the distributional behaviour of the additive scalar particle even relative to scales whose focus alternatives are ordered in terms of evaluative attitudes (positive, negative). Our hypothesis is that such evaluative attitudinal scales are at least partially functions of the lexical material in the sentential environment. This hypothesis is tested by determining correlations between sentence-level attitudes and lexically encoded attitudes in the relevant sentences. We use data from the Europarl corpus, a corpus of scripted and highly elaborated political speech, which is rich in argumentative discourse and thus lends itself to the study of attitudes in context. Our results show that there are in fact significant correlations between (manual) sentence-level evaluations and lexical evaluations (determined through machine learning) in the textual environment of the relevant operators. We conclude with an outlook on possible extensions of the method applied in the present study by identifying attitudinal patterns beyond the sentence, showing that positively and negatively connotated instances of even differ in terms of their argumentative function, with positive even often marking the climax and endpoint of an argument, while negative even often occurs in qualifying insertions like concessive parentheses. While we regard our results as valid, some refinements and extensions of the method are pointed out as necessary steps towards the establishment of an empirical sentence semantics, in the domain of scalar additive operators as well as more generally speaking

Household Disposal of Pharmaceuticals in Low-Income Settings: Practices, Health Hazards, and Research Needs

Pharmaceuticals are widely used in Africa due to the high burden of human and animal diseases. However, a review of the current practices and pollution risks arising from the disposal of pharmaceuticals in low-income settings in Africa is still lacking. Therefore, the present review examined the literature to address the following questions: (1) what are the key factors driving the accumulation of unused and expired pharmaceuticals?, (2) what are the current disposal practices for unused and expired pharmaceuticals, and wastewater (feces and urine) containing excreted pharmaceuticals?, (3) what are the potential environmental and human health hazards posed by current disposal practices?, and (4) what are the key research needs on the disposal of pharmaceuticals in low-income settings? Evidence shows that, in low-income settings, wastewater comprising predominantly of feces and urine containing excreted pharmaceuticals often end up in on-site sanitation systems such as pit latrines, septic tanks, and the environment in the case of open defecation. Unused and expired pharmaceuticals are disposed of in pit latrines, household solid waste, and/or burned. The pollution risks of current disposal practices are poorly understood, but pharmaceutical pollution of groundwater sources, including those used for drinking water supply, may occur via strong hydrological connectivity between pit latrines and groundwater systems. Potential high-risk pollution and human exposure hotspots are discussed. However, compared to other environmental compartments, the occurrence, dissemination, fate, and human health risks of pharmaceuticals in the pit latrine-groundwater continuum are still understudied. Future research directions are discussed to address these gaps using the Source-Pathway-Receptor-Impact-Mitigation (SPRIM) continuum as an organizing framework

Lexibank, a public repository of standardized wordlists with computed phonological and lexical features

The past decades have seen substantial growth in digital data on the world’s languages. At the same time, the demand for cross-linguistic datasets has been increasing, as witnessed by numerous studies devoted to diverse questions on human prehistory, cultural evolution, and human cognition. Unfortunately, most published datasets lack standardization which makes their comparison difficult. Here, we present a new approach to increase the comparability of cross-linguistic lexical data. We have designed workflows for the computer-assisted lifting of datasets to Cross-Linguistic Data Formats, a collection of standards that make these datasets more Findable, Accessible, Interoperable, and Reusable (FAIR). We test the Lexibank workflow on 100 lexical datasets from which we derive an aggregated database of wordlists in unified phonetic transcriptions covering more than 2000 language varieties. We illustrate the benefits of our approach by showing how phonological and lexical features can be automatically inferred, complementing and expanding existing cross-linguistic datasets

Cell Death in Cyanobacteria: Current Understanding and Recommendations for a Consensus on Its Nomenclature

Cyanobacteria are globally widespread photosynthetic prokaryotes and are major contributors to global biogeochemical cycles. One of the most critical processes determining cyanobacterial eco-physiology is cellular death. Evidence supports the existence of controlled cellular demise in cyanobacteria, and various forms of cell death have been described as a response to biotic and abiotic stresses. However, cell death research in this phylogenetic group is a relatively young field and understanding of the underlying mechanisms and molecular machinery underpinning this fundamental process remains largely elusive. Furthermore, no systematic classification of modes of cell death has yet been established for cyanobacteria. In this work, we analyzed the state of knowledge in the field of cyanobacterial cell death. Based on that, we propose unified criterion for the definition of accidental, regulated, and programmed forms of cell death in cyanobacteria based on molecular, biochemical, and morphologic aspects following the directions of the Nomenclature Committee on Cell Death (NCCD). With this, we aim to provide a guide to standardize the nomenclature related to this topic in a precise and consistent manner, which will facilitate further ecological, evolutionary, and applied research in the field of cyanobacterial cell death.Fil: Aguilera, Anabella. Linnaeus University; SueciaFil: Klemenčič, Marina. University of Ljubljana; EsloveniaFil: Sueldo, Daniela Jorgelina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rzymski, Piotr. Universal Scientific Education and Research Network; PoloniaFil: Giannuzzi, Leda. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Martin, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Biodiversidad y Biotecnología; Argentin