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This paper identifies time calibration points for accurately rooting and dating the phylogeny of Arawakan, the largest Indigenous linguistic family of the Americas. We present and model a methodology for extracting calibration points from the archaeological record, based on principles of geographical overlap between archaeological sites and Arawakan peoples, and on continuity in material culture between archaeological finds and modern Arawakan practices. Based on a consensus model of the expansion of the Arawakan family from Central Amazonia, we focus on archaeological finds in Arawakan expansion zones, where Arawakan material culture abruptly appears in a given region, and where only a single major Arawakan subgroup/clade is present. We find 12 calibration points from archaeological sites in Arawakan expansion zones and also identify more recent calibration points from the historical record based on first mentions of ethnonyms and early sources of lexical data.

Purpose: Mineralogical and geochemical features of mining and processing wastes collected in Owen County, part of the Central Kentucky Lead-Zinc district, were investigated. The Gratz mine, abandoned in the 1940’s, is on a dairy farm. Aside from discerning the nature of mining refuse at the site, the investigation was part of the University of Kentucky College of Pharmacy’s mission to explore unusual environments in the search for unique microbiological communities. Materials and methods: Four samples of a soil-plus-spoils mix were collected from spoil piles and two samples, the sluice and coarse samples, were closely associated with the site of the ore processing. Optical petrology (polarized reflected-light, oil- immersion optics at a final magnification of 500x), X-ray diffraction, X-ray fluorescence, Inductively coupled plasma mass spectrometry, Field emission scanning electron microscopy (FE- SEM), and high-resolution transmission electron microscope (HR-TEM) with selected area electron diffraction (SAED) and/or microbeam diffraction (MBD), scanning transmission electron microscopy (STEM), and energy-dispersive X-ray spectrometer (EDS) analyses were employed to characterize the samples. Results and discussion: Calcite is the main mineral in most samples, followed by near equal amounts of quartz and dolomite. Sphalerite and galena are the principal sulfides and barite is the dominant sulfate. Geochemistry of major elements reflected the mineralogy ; whereas trace elements showed different groupings between the minerals. Scandium, Cu, Ga, Ge, Cd, and Sb were found predominantly associated with Zn and Pb and sulfide minerals ; Bi, Hf, In, Sn, and Zr with heavy mineral fraction ; while the remaining trace elements, including the rare earths, were mostly distributed among other present phases, i.e., oxyhalides, oxides, silicates, and carbonaceous material. The data were used to illustrate the processes and conditions that control the sulfide- mineral oxidation and its potential for the environmental release of associated reaction products. Conclusions: The wastes represent a potential source of environmentally disruptive concentrations of Zn, Pb, and other sulfide- associated elements. The high share of carbonates suggests near-neutral conditions in deposited wastes, restricting sulfide weathering and further limiting the oxidant activity of Fe. The low-Fe content and its predominant presence in highly resistant hematite also constrains sulfide weathering. Consequently, the spoils have a low potential for generation of acidity and release of heavy metal(loid)s in the surrounding environment.

Background: While mentally passive sedentary behavior such as television viewing (TV) is often related with depressive symptoms, some research shows that physical activity (PA) may attenuate this association. Thus, this study aimed to examine the associations between TV, PA, and depressive symptoms, considering sociodemographic covariates.Methods: A sample of 29,285 adults (13,943 men; 15,342 women) with a mean age of 50.9 ± 17.4 years (50.6 ± 17.3 men; 51.1 ± 17.5 women) from the European Social Survey agreed to be respondents for this study. Data for sociodemographic variables, TV watching, PA, and depressive symptoms were self-reported. Different statistical procedures were conducted to provide evidence for the association between study variables. ANCOVA was used to analyze the association between TV watching and depressive symptoms. Linear regression analysis was conducted to analyze the association between PA and depressive symptoms. General Linear Model was performed to analyze the association of TV watching and on depressive symptoms, controlling for PA.Results: European adults who responded watching more than 2 h per day showed higher scores for depressive symptoms. Higher participation in PA was negatively and significantly associated with depressive symptoms in men (β = −0.15, 95% CI: −0.18, −0.13), and women (β = −0.23, 95% CI: −0.26, −0.21). Men spending 1–2 h/day TV watching and engaging in PA ≥ 5 days/week presented the lowest scores on depressive symptoms. The lowest scores on depressive symptoms was observed in women engaging 2–4 days/week in PA and spending <1 h/day in TV watching.Conclusions: More time spent in TV watching is related with increased scores on depressive symptoms. However, regular PA participation can weaken this association.

In this paper, we introduce the concept of learning to sense, which aims to emulate a complex characteristic of human reasoning: the ability to monitor and understand a set of interdependent events for decision-making processes. Event datasets are composed of textual data and spatio-temporal features that determine where and when a given phenomenon occurred. In learning to sense, related events are mapped closely to each other in a semantic vector space, thereby identifying that they contain similar contextual meaning. However, learning a semantic vector space that satisfies both textual similarities and spatio-temporal constraints is a crucial challenge for event analysis and sensing. This paper investigates a Semantic Variational Autoencoder (SVAE) to fine-tune pre-trained embeddings according to both textual and spatio-temporal events of the class of interest. Experiments involving more than one hundred sensors show that our SVAE outperforms a competitive one-class classification baseline. Moreover, our proposal provides desirable learning requirements to sense scenarios, such as visualization of the sensor decision function and heat maps with the sensor’s geographic impact.

Generalized language models that are pre-trained with a large corpus have achieved great performance on natural language tasks. While many pre-trained transformers for English are published, few models are available for Japanese text, especially in clinical medicine. In this work, we demonstrate the development of a clinical specific BERT model with a huge amount of Japanese clinical text and evaluate it on the NTCIR-13 MedWeb that has fake Twitter messages regarding medical concerns with eight labels. Approximately 120 million clinical texts stored at the University of Tokyo Hospital were used as our dataset. The BERT-base was pre-trained using the entire dataset and a vocabulary including 25,000 tokens. The pre-training was almost saturated at about 4 epochs, and the accuracies of Masked-LM and Next Sentence Prediction were 0.773 and 0.975, respectively. The developed BERT did not show significantly higher performance on the MedWeb task than the other BERT models that were pre-trained with Japanese Wikipedia text. The advantage of pre-training on clinical text may become apparent in more complex tasks on actual clinical text, and such an evaluation set needs to be developed.

Miocene deposits of South America have yielded several species-rich assemblages of caviomorph rodents. They are mostly situated at high and mid-latitudes of the continent, except for the exceptional Honda Group of La Venta, Colombia, the faunal composition of which allowed to describe the late middle Miocene Laventan South American Land Mammal Age (SALMA). In this paper, we describe a new caviomorph assemblage from TAR-31 locality, recently discovered near Tarapoto in Peruvian Amazonia (San Martín Department). Based on mammalian biostratigraphy, this single-phased locality is unambiguously considered to fall within the Laventan SALMA. TAR-31 yielded rodent species found in La Venta, such as the octodontoid Ricardomys longidens Walton, 1990 (nom. nud.), the chinchilloids Microscleromys paradoxalis Walton, 1990 (nom. nud.) and M. cribriphilus Walton, 1990 (nom. nud.), or closely-related taxa. Given these strong taxonomic affinities, we further seize the opportunity to review the rodent dental material from La Venta described in the Ph.D. volume of Walton in 1990 but referred to as nomina nuda. Here we validate the recognition of these former taxa and provide their formal description. TAR-31 documents nine distinct rodent species documenting the four extant superfamilies of Caviomorpha, including a new erethizontoid: Nuyuyomys chinqaska gen. et sp. nov. These fossils document the most diverse caviomorph fauna for the middle Miocene interval of Peruvian Amazonia to date. This rodent discovery from Peru extends the geographical ranges of Ricardomys longidens, Microscleromys paradoxalis, and M. cribriphilus, 1,100 km to the south. Only one postcranial element of rodent was unearthed in TAR-31 (astragalus). This tiny tarsal bone most likely documents one of the two species of Microscleromys and its morphology indicates terrestrial generalist adaptations for this minute chinchilloid. International audience