• Digital Humanities and Cultural Heritage
• Research data close
• Netherlands Organisation for Scient... close
• NL close
• Digital Humanities and Cultural Her... close

Rooted in the novel and the mysterious, awe is a common experience in childhood, but research is almost silent with respect to the import of this emotion for children. Awe makes individuals feel small, thereby shifting their attention to the social world. Here, we studied the effects of art-elicited awe on children’s prosocial behavior toward an out-group and its unique physiological correlates. In two preregistered studies (Study 1: N = 159, Study 2: N = 353), children between 8 and 13 years old viewed movie clips that elicited awe, joy, or a neutral (control) response. Children who watched the awe-eliciting clip were more likely to spend their time on an effortful task (Study 1) and to donate their experimental earnings (Studies 1 and 2), all toward benefiting refugees. They also exhibited increased respiratory sinus arrhythmia, an index of parasympathetic nervous system activation associated with social engagement. We discuss implications for fostering prosociality by reimagining children’s environments to inspire awe at a critical age.

Data consist of a continuous millennially-resolved record of oxgyen and carbon stable isotope composition of planktonic and benthic foraminifera at IODP Site U1385 and piston core MD01-2444 from the southwestern Iberian margin for the last 1.5 million years. Elemental ratios (Ca/Ti and Zr/Sr) are also reported from the composite section of Site U1385 and core MD01-2444. Oxygen and carbon isotope measurements of planktic and benthic foraminifera were made at an average temporal resolution of ~200 years for the last 1.45 million years. For planktic foraminifera, the surface-dwelling species Globigerina bulloides from the 250 - 350 um size fraction was used. Benthic foraminifer data consists mostly of Cibicidoides wuellerstorfi and occasionally other species of Cibicidoides were measured from the >212 um size fraction. In samples where specimens of Cibicidoides spp. were absent, we used d18O of Uvigerina peregrina or Globobulimina affinis. All δ18O values for each species were corrected to Uvigerina using the offsets suggested by Shackleton et al. (2000) -- i.e., +0.64 for Cibicidoides and -0.3 for G. affinis. Stable isotope measurements were made in the Godwin Laboratory for Palaeoclimate research at the University of Cambridge. Foraminifer tests were crushed and soaked in a solution of 1% hydrogen per-oxide for 30 min in individual vials. Acetone was added and the samples placed in an ultra-sonic bath for 10 s, after which the liquid was carefully decanted to remove any contaminants. The samples were dried in an oven at 50 °C overnight. Isotopic analyses of the samples were per-formed using a VG SIRA mass spectrometer with a Multicarb system for samples with a mass exceeding 80 μg. Analytical precision is estimated to be ±0.08‰ for both δ18O and δ13C. For smaller samples (<80 μg), measurements were performed on a Thermo Finnigan MAT253 mass spectrometer fitted with a Kiel device. Analytical precision is estimated to be ±0.08‰ for δ18O and ±0.06‰ for δ13C, respectively. All results are reported relative to VPDB. Elemental ratios (Ca/Ti and Zr/Sr) were obtained using an Avaatech X-ray fluorescence (XRF) core scanner at 1-cm spatial resolution. Cores from Holes U1385A and U1385B were measured at the Royal Netherlands Institute for Sea Research (NIOZ) and Holes U1385D and U1385E and MD01-2444 were measured at the Godwin Laboratory for Palaeoclimate Reseach at the University of Cambridge. The core surface was carefully scraped cleaned and covered with a 4-μm thin SPEXCertiPrep Ultralene foil to avoid contamination and reduce desiccation. All XRF scanners irradiated a surface of 10-mm high by 12-mm wide every 1 cm with identical instrument settings used at both NIOZ and Cambridge. Cores were scanned at 3 voltages: 10kv (750 μamps, 10 sec count time with no filter); 30 kv (500 μamps, 10 sec count time with Pd thin filter); and 50 kv (1000 μramps, 60 sec count time with Cu vilter). Element intensities were obtained by post-processing of the XRF spectra using the Canberra WinAxil software with standard soft-ware settings and spectrum-fit models. The purpose of the analyses were to produce records of millennial-scale climate variability (MCV) during the last 1.45 million years. Questions to be addressed with the data included: How common was MCV during older glacial periods of the Pleistocene? Did the nature (intensity, duration, pacing) of MCV change with orbital configuration or climate background state (ice volume, sea-level, ice sheet height)? What is the relationship between MCV and longer-term, orbitally-driven glacial-interglacial cycles – how do they interact? How did MCV change across the Middle Pleistocene Transition (MPT) when ice sheets grew larger in size and the amplitude of glacial-interglacial cycles increased? Was the thermal bipolar seesaw mechanism active during older glacial periods of the Pleistocene? What role did millennial variability play in atmospheric CO2 variations or vice-versa?

Attributing the start of peat growth to an absolute timescale requires dating the bottom of peat deposits overlying mineral sediment, often called the basal peat. Peat initiation is reflected in the stratigraphy as a gradual transition from mineral sediment to increasingly organic material, up to where it is called peat. So far, varying criteria have been used to define basal peat, resulting in divergent approaches to date peat initiation. The lack of a universally applicable and quantitative definition, combined with multiple concerns that have been raised previously regarding the radiocarbon dating of peat, may result in apparent ages that are either too old or too young for the timing of peat initiation. Here, we aim to formulate updated recommendations for dating peat initiation. We provide a conceptual framework that supports the use of the organic matter (OM) gradient for a quantitative and reproducible definition of the mineral-to-peat transition (i.e., the stratigraphical range reflecting the timespan of the peat initiation process) and the layer defined as basal peat (i.e., the stratigraphical layer that is defined as the bottom of a peat deposit). Selection of dating samples is often challenging due to poor preservation of plant macrofossils in basal peat, and the representativity of humic and humin dates for the age of basal peat is uncertain. We therefore analyse the mineral-to-peat transition based on three highly detailed sequences of radiocarbon dates, including dates of plant macrofossils and the humic and humin fractions obtained from bulk samples. Our case study peatland in the Netherlands currently harbours a bog vegetation, but biostratigraphical analyses show that during peat initiation the vegetation was mesotrophic. Results show that plant macrofossils provide the most accurate age in the mineral-to-peat transition and are therefore recommendable to use for 14C dating basal peat. If these are unattainable, the humic fraction provides the best alternative and is interpreted as a terminus-ante-quem for peat initiation. The potential large age difference between dates of plant macrofossils and humic or humin dates (up to ~1700 years between macrofossil and humic ages, and with even larger differences for humins) suggests that studies reusing existing bulk dates of basal peat should take great care in data interpretation. The potentially long timespan of the peat initiation process (with medians of ~1000, ~1300 and ~1500 years within our case study peatland) demonstrates that choices regarding sampling size and resolution need to be well substantiated. We summarise our findings as a set of recommendations for dating basal peats, and advocate the widespread use of OM determination to obtain a low-cost, quantitative and reproducible definition of basal peat that eases intercomparison of studies.

Much has yet to be learned of the spatial patterning of pre-Columbian people across the Tropical Andes. Using compiled archaeological data and a suite of environmental variables, we generate an ensemble species distribution model (SDM) that incorporates general additive models, random forest models and Maxent models to reconstruct spatial patterns of pre-Columbian people that inhabited the Tropical Andes east of the continental divide, within the modern countries of Bolivia, Peru and Ecuador. Within this region, here referred to as the eastern Andean flank, elevation, mean annual cloud frequency, distance to rivers and precipitation of the driest quarter are the environmental variables most closely related to human occupancy. Our model indicates that 11.04% of our study area (65 368 km2) was likely occupied by pre-Columbian people. Our model shows that 30 of 351 forest inventory plots, which are used to generate ecological understanding of Andean ecosystems, were likely occupied in the pre-Columbian period. In previously occupied sites, successional trajectories may still be shaping forest dynamics, and those forests may still be recovering from the ecological legacy of pre-Columbian impacts. Our ensemble SDM links palaeo- and neo-ecology and can also be used to guide both future archaeological and ecological studies.This article is part of the theme issue ���The role of tropical rainforests in the deep human past���.

Abstract Background Developing predictive models for precision psychiatry is challenging because of unavailability of the necessary data: extracting useful information from existing electronic health record (EHR) data is not straightforward, and available clinical trial datasets are often not representative for heterogeneous patient groups. The aim of this study was constructing a natural language processing (NLP) pipeline that extracts variables for building predictive models from EHRs. We specifically tailor the pipeline for extracting information on outcomes of psychiatry treatment trajectories, applicable throughout the entire spectrum of mental health disorders (“transdiagnostic”). Methods A qualitative study into beliefs of clinical staff on measuring treatment outcomes was conducted to construct a candidate list of variables to extract from the EHR. To investigate if the proposed variables are suitable for measuring treatment effects, resulting themes were compared to transdiagnostic outcome measures currently used in psychiatry research and compared to the HDRS (as a gold standard) through systematic review, resulting in an ideal set of variables. To extract these from EHR data, a semi-rule based NLP pipeline was constructed and tailored to the candidate variables using Prodigy. Classification accuracy and F1-scores were calculated and pipeline output was compared to HDRS scores using clinical notes from patients admitted in 2019 and 2020. Results Analysis of 34 questionnaires answered by clinical staff resulted in four themes defining treatment outcomes: symptom reduction, general well-being, social functioning and personalization. Systematic review revealed 242 different transdiagnostic outcome measures, with the 36-item Short-Form Survey for quality of life (SF36) being used most consistently, showing substantial overlap with the themes from the qualitative study. Comparing SF36 to HDRS scores in 26 studies revealed moderate to good correlations (0.62—0.79) and good positive predictive values (0.75—0.88). The NLP pipeline developed with notes from 22,170 patients reached an accuracy of 95 to 99 percent (F1 scores: 0.38 – 0.86) on detecting these themes, evaluated on data from 361 patients. Conclusions The NLP pipeline developed in this study extracts outcome measures from the EHR that cater specifically to the needs of clinical staff and align with outcome measures used to detect treatment effects in clinical trials.

Table of the archaeological sites used in the final ensemble model (N=1965). Data were compiled from published literature (see additional SOM for full citations of each archaeological site).

Additional file 2:

Additional file 2: Table S1. Description of the studies included in the analyses.