Previous fMRI research has applied a variety of tasks to examine brain activity underlying emotion processing. While task characteristics are known to have a substantial influence on the elicited activations, direct comparisons of tasks that could guide study planning are scarce. We aimed to provide a comparison of four common emotion processing tasks based on the same analysis pipeline to suggest tasks best suited for the study of certain target brain regions. We studied an n-back task using emotional words (EMOBACK) as well as passive viewing tasks of emotional faces (FACES) and emotional scenes (OASIS and IAPS). We compared the activation patterns elicited by these tasks in four regions of interest (the amygdala, anterior insula, dorsolateral prefrontal cortex (dlPFC) and pregenual anterior cingulate cortex (pgACC)) in three samples of healthy adults (N = 45). The EMOBACK task elicited activation in the right dlPFC and bilateral anterior insula and deactivation in the pgACC while the FACES task recruited the bilateral amygdala. The IAPS and OASIS tasks showed similar activation patterns recruiting the bilateral amygdala and anterior insula. We conclude that these tasks can be used to study different regions involved in emotion processing and that the information provided is valuable for future research and the development of fMRI biomarkers.

Objectives Habit formation has been identified as one of the key determinants of behaviour change. To initiate habit formation, self-regulation interventions can support individuals to form a cue-behaviour plan and to repeatedly enact the plan in the same context. This randomized controlled trial aimed to model habit formation of an everyday nutrition behaviour and examined whether habit formation and plan enactment differ when individuals plan to enact their behaviour in response to a routine-based versus time-based cue.

Design Following a baseline assessment, N = 192 adults (aged 18–77 years) were randomly assigned to a routine-based cue or a time-based cue planning intervention, in which they selected an everyday nutrition behaviour and linked it to a daily routine or a time cue.

Methods Participants responded to daily questionnaires over 84 days assessing plan enactment and the behaviour’s automaticity (as an indicator of habit formation). Multilevel models with days nested in participants were fitted.

Results As indicated by asymptotic curves, it took a median of 59 days for participants who successfully formed habits to reach peak automaticity. Group-level analyses revealed that both routine-based and time-based cue planning led to increases in automaticity and plan enactment, but no between-condition differences were found. Repeated plan enactment was a key predictor for automaticity.

Conclusions Linking one’s nutrition behaviour to a daily routine or a specific time was similarly effective for habit formation. Interventions should encourage persons to repeatedly carry out their planned behaviour in response to the planned cue to facilitate habit formation.

1. Ecological restoration increasingly aims at improving ecosystem multifunctionality and making landscapes resilient to future threats, especially in biodiversity hotspots such as Mediterranean-type ecosystems. Plants and their traits play a major role in the functioning of an ecosystem. Therefore, successful restoration towards long-term multifunctionality requires a fundamental mechanistic understanding of this link under changing climate. An integrated approach of empirical research and simulation modelling with a focus on plant traits can allow this understanding. 2. Based on empirical data from a large-scale restoration project in a Mediterranean-type ecosystem in Western Australia, we developed and validated the spatially explicit simulation model Modelling Ecosystem Functions and Services based on Traits (ModEST), which calculates coupled dynamics of nutrients, water and individual plants characterised by functional traits. We then simulated all possible combinations of eight plant species with different levels of diversity to assess the role of plant diversity and traits on multifunctionality, the provision of six ecosystem functions that can be linked to ecosystem services, as well as trade-offs and synergies among the functions under current and future climatic conditions. 3. Our results show that multifunctionality cannot fully be achieved because of trade-offs among functions that are attributable to sets of traits that affect functions differently. Our measure of multifunctionality was increased by higher levels of planted species richness under current, but not future climatic conditions. In contrast, single functions were differently impacted by increased plant diversity and thus the choice and weighting of these functions affected multifunctionality. In addition, we found that trade-offs and synergies among functions shifted with climate change due to different direct and indirect (mediated via community trait changes) effects of climate change on functions. 4. Synthesis and application. With our simulation model Modelling Ecosystem Functions and Services based on Traits (ModEST), we show that restoration towards multifunctionality might be challenging not only under current conditions but also in the long-term. However, once ModEST is parameterised and validated for a specific restoration site, managers can assess which target goals can be achieved given the set of available plant species and site-specific conditions. It can also highlight which species combinations can best achieve long-term improved multifunctionality due to their trait diversity.

Nanoparticles occur in various environments as a consequence of man-made processes, which raises concerns about their impact on the environment and human health. To allow for proper risk assessment, a precise and statistically relevant analysis of particle characteristics (such as size, shape, and composition) is required that would greatly benefit from automated image analysis procedures. While deep learning shows impressive results in object detection tasks, its applicability is limited by the amount of representative, experimentally collected and manually annotated training data. Here, an elegant, flexible, and versatile method to bypass this costly and tedious data acquisition process is presented. It shows that using a rendering software allows to generate realistic, synthetic training data to train a state-of-the art deep neural network. Using this approach, a segmentation accuracy can be derived that is comparable to man-made annotations for toxicologically relevant metal-oxide nanoparticle ensembles which were chosen as examples. The presented study paves the way toward the use of deep learning for automated, high-throughput particle detection in a variety of imaging techniques such as in microscopies and spectroscopies, for a wide range of applications, including the detection of micro- and nanoplastic particles in water and tissue samples.

Engineered quantum systems play a central role in quantum information processing. Typically, these systems are strongly coupled to their environments, which presents challenges and opportunities to harness controllable quantum effects in such systems. One of the outstanding challenges is to characterize the quantum correlations that develop in such out-of-equilibrium quantum systems. Here we present a method that utilizes low-dimensional projections of eigenvectors to distinguish different types of correlations in an N-mode open system. The proposed method presents a nontrivial extension of eigenvalue-based analysis employed for such systems; specifically, it not only diagnoses crossovers between weak and strong coupling regimes (also known as “exceptional points”) but also can identify the physical systems of interest spanning the correlated subspaces in different regions of the multimode strong-coupling regime. As a demonstration of this feature, we apply our method to study hybridization physics in a three-mode optomechanical system and determine the parameter regime for efficient sideband cooling of the system in the presence of reservoir correlations.

It is now a decade since The International Commission on the Taxonomy of Fungi (ICTF) produced an overview of requirements and best practices for describing a new fungal species. In the meantime the International Code of Nomenclature for algae, fungi, and plants (ICNafp) has changed from its former name (the International Code of Botanical Nomenclature) and introduced new formal requirements for valid publication of species scientific names, including the separation of provisions specific to Fungi and organisms treated as fungi in a new Chapter F. Equally transformative have been changes in the data collection, data dissemination, and analytical tools available to mycologists. This paper provides an updated and expanded discussion of current publication requirements along with best practices for the description of new fungal species and publication of new names and for improving accessibility of their associated metadata that have developed over the last 10 years. Additionally, we provide: (1) model papers for different fungal groups and circumstances; (2) a checklist to simplify meeting (i) the requirements of the ICNafp to ensure the effective, valid and legitimate publication of names of new taxa, and (ii) minimally accepted standards for description; and, (3) templates for preparing standardized species descriptions.

Many geomorphic phenomena such as bank failures, landslide dams, riffle-pool sequences and knickpoints can be modelled as spatial point processes. However, as the locations of these phenomena are constrained to lie on or alongside rivers, their analysis must account for the geometry and topology of river networks. Here, we introduce a new numeric class in TopoToolbox called Point Pattern on Stream networks (PPS), which supports exploratory analysis, statistical modelling, simulation and visualization of point processes. We present three case studies that aim at inferring processes and factors that control the spatial density of geomorphic phenomena along river networks: analysis of a synthetic dataset of points on a stream network, the analysis of knickpoints in river profiles, and modelling spatial locations of beaver dams based on topographic metrics. The case studies rely on exploratory analysis and statistical inference using inhomogeneous Poisson point processes. Thereby, statistical and probabilistic procedures implemented in PPS provide a systematic approach for treating and quantifying uncertainties. PPS offers a consistent numeric framework for modelling point processes on river networks with a wide range of applications in fluvial geomorphology, but also other disciplines such as ecology.

The exact anatomical location for an iron particle-based magnetic sense remains enigmatic in vertebrates. For mammals, findings from a cornea anaesthesia experiment in mole rats suggest that it carries the primary sensors for magnetoreception. Yet, this has never been tested in a free-ranging mammal. Here, we investigated whether intact corneal sensation is crucial for navigation in migrating Nathusius’ bats, Pipistrellus nathusii, translocated from their migratory corridor. We found that bats treated with corneal anaesthesia in both eyes flew in random directions after translocation and release, contrasting bats with a single eye treated, and the control group, which both oriented in the seasonally appropriate direction. Using a Y-maze test, we confirmed that light detection remained unaffected by topical anaesthesia. Therefore our results suggest the cornea as a possible site of magnetoreception in bats, although other conceivable effects of the anaesthetic are also explored. Furthermore, we demonstrate that the corneal based sense is of bilateral nature but can function in a single eye if necessary.

Determining the architecture of multi-planetary systems is one of the cornerstones of understanding planet formation and evolution. Resonant systems are especially important as the fragility of their orbital configuration ensures that no significant scattering or collisional event has taken place since the earliest formation phase when the parent protoplanetary disc was still present. In this context, TOI-178 has been the subject of particular attention since the first TESS observations hinted at the possible presence of a near 2:3:3 resonant chain. Here we report the results of observations from CHEOPS, ESPRESSO, NGTS, and SPECULOOS with the aim of deciphering the peculiar orbital architecture of the system. We show that TOI-178 harbours at least six planets in the super-Earth to mini-Neptune regimes, with radii ranging from 1.152−0.070+0.073 to 2.87−0.13+0.14 Earth radii and periods of 1.91, 3.24, 6.56, 9.96, 15.23, and 20.71 days. All planets but the innermost one form a 2:4:6:9:12 chain of Laplace resonances, and the planetary densities show important variations from planet to planet, jumping from 1.02−0.23+0.28 to 0.177−0.061+0.055 times the Earth’s density between planets c and d. Using Bayesian interior structure retrieval models, we show that the amount of gas in the planets does not vary in a monotonous way, contrary to what one would expect from simple formation and evolution models and unlike other known systems in a chain of Laplace resonances. The brightness of TOI-178 (H = 8.76 mag, J = 9.37 mag, V = 11.95 mag) allows for a precise characterisation of its orbital architecture as well as of the physical nature of the six presently known transiting planets it harbours. The peculiar orbital configuration and the diversity in average density among the planets in the system will enable the study of interior planetary structures and atmospheric evolution, providing important clues on the formation of super-Earths and mini-Neptunes.

This paper presents a new rapid, low-cost method for the large-scale documentation of pottery sherds through simultaneous multiple 3D model capture using Structure from Motion (SfM). The method has great potential to enhance and replace time-consuming and expensive conventional approaches for pottery documentation, i.e., 2D photographs and drawing on paper with subsequent digitization of the drawings. To showcase the method’s effectiveness and applicability, a case study was developed in the context of an investigation of the Phoenician economy at the Lebanese site of Tell el-Burak, which is based on a large collection of amphora sherds. The same set of sherds were drawn by an experienced draftsperson and then documented through SfM using our new workflow to allow for a direct comparison. The results show that the new technique detailed here is accessible, more cost-effective, and allows for the documentation of ceramic data at a far-greater scale, while producing more consistent and reproducible results. We expect that these factors will enable excavators to greatly increase digital access to their material, which will significantly enhance its utility for subsequent research.

Fluorenyl cations are textbook examples of 4π electron antiaromatic five-membered ring systems. So far, they were reported only as short-lived intermediates generated under superacidic conditions or by flash photolysis. Attempts to prepare a m-terphenyl acylium cation by fluoride abstraction from a benzoyl fluoride gave rise to an isolable 9-hydroxy fluorenyl cation that formed by an intramolecular electrophilic attack at a flanking mesityl group prior to a 1,2-methyl shift and proton transfer to oxygen.

Anisotropic magnetoresistance (AMR) is a ubiquitous and versatile probe of magnetic order in contemporary spintronics research. Its origins are usually ascribed to extrinsic effects (i.e., spin-dependent electron scattering), whereas intrinsic (i.e., scattering-independent) contributions are neglected. Here, we measure AMR of polycrystalline thin films of the standard ferromagnets Co, Ni, Ni81Fe19, and Ni50Fe50 over the frequency range from dc to 28 THz. The large bandwidth covers the regimes of both diffusive and ballistic intraband electron transport and, thus, allows us to separate extrinsic and intrinsic AMR components. Analysis of the THz response based on Boltzmann transport theory reveals that the AMR of the Ni, Ni81Fe19, and Ni50Fe50 samples is of predominantly extrinsic nature. However, the Co thin film exhibits a sizable intrinsic AMR contribution, which is constant up to 28 THz and amounts to more than 2/3 of the dc AMR contrast of 1%. These features are attributed to the hexagonal structure of the Co crystallites. They are interesting for applications in terahertz spintronics and terahertz photonics. Our results show that broadband terahertz electromagnetic pulses provide new and contact-free insights into magnetotransport phenomena of standard magnetic thin films on ultrafast timescales.

Phytoliths are plant microfossils commonly used as qualitative archive markers in archaeological and paleoecological studies. Their potential uniqueness to the vegetation cover, robustness to weathering, and lack of chemical alteration along the transport paths make them potentially suitable tracers for quantitative erosion studies. In this pilot study, we explore the potential of phytoliths in a sediment fingerprinting study in the Ceguera catchment (28 km2) in NE Spain. The phytolith concentrations and morphologies of four land cover classes (agricultural land, badland, forest, and shrubland) were analysed, and their contributions to four natural sediment mixture samples along the river course were modelled. Phytolith concentrations allowed us to discriminate sources sufficiently, albeit with limited sample size. The performance of the phytoliths as tracer was tested by reproducing the sources of artificial sediment mixture samples with satisfactory recall ratio. Results identified badlands to be the main contributor, with 84–96% of the sediment load to the sinks, followed by shrublands (median 5%) and agricultural lands (median 2%). These major findings can be reproduced by other conventional erosion studies from this area, indicating that phytoliths are suited to quantifying erosion patterns in mesoscale catchments.

Pausing of transcribing RNA polymerase is regulated and creates opportunities to control gene expression. Research in metazoans has so far mainly focused on RNA polymerase II (Pol II) promoter-proximal pausing leaving the pervasive nature of pausing and its regulatory potential in mammalian cells unclear. Here, we developed a pause detecting algorithm (PDA) for nucleotide-resolution occupancy data and a new native elongating transcript sequencing approach, termed nested NET-seq, that strongly reduces artifactual peaks commonly misinterpreted as pausing sites. Leveraging PDA and nested NET-seq reveal widespread genome-wide Pol II pausing at single-nucleotide resolution in human cells. Notably, the majority of Pol II pauses occur outside of promoter-proximal gene regions primarily along the gene-body of transcribed genes. Sequence analysis combined with machine learning modeling reveals DNA sequence properties underlying widespread transcriptional pausing including a new pause motif. Interestingly, key sequence determinants of RNA polymerase pausing are conserved between human cells and bacteria. These studies indicate pervasive sequence-induced transcriptional pausing in human cells and the knowledge of exact pause locations implies potential functional roles in gene expression.

Scenario analysis has emerged as a key tool to analyze complex and uncertain future socio-ecological developments. However, currently existing global scenarios (narratives of how the world may develop) have neglected biological invasions, a major threat to biodiversity and the economy. Here, we use a novel participatory process to develop a diverse set of global biological invasion scenarios spanning a wide range of plausible global futures through to 2050. We adapted the widely used “two axes” scenario analysis approach to develop four families of four scenarios each, resulting in 16 scenarios that were later clustered into four contrasting sets of futures. Our analysis highlights that socioeconomic developments and technological innovation have the potential to shape biological invasions, in addition to well-known drivers, such as climate and human land use change and global trade. Our scenarios partially align with the shared socioeconomic pathways created by the climate change research community. Several factors that drive differences in biological invasions were underrepresented in the shared socioeconomic pathways; in particular, the implementation of biosecurity policies. We argue that including factors related to public environmental awareness and technological and trade development in global scenarios and models is essential to adequately consider biological invasions in global environmental assessments and thereby obtain a more integrative picture of future social–ecological developments.

Modern biomedical research with the aim of translating research findings into novel therapies to benefit patients relies to a large extent on animal models of human pathophysiology. However, success stories of translational research – i.e. preclinical research that successfully predicts positive outcome of a clinical trial – are scarce. Here, we therefore address the current state of preclinical disease modeling as well as actions that have been taken to improve the translational value of animal models.

Magnetic skyrmions can be created and annihilated in ferromagnetic multilayers using single femtosecond infrared laser pulses above a material-dependent fluence threshold. From the perspective of applications, optical control of skyrmions offers a route to a faster and, potentially, more energy-efficient new class of information-technology devices. Here, we investigate laser-induced skyrmion generation in two different materials, mapping out the dependence of the process on the applied field and the laser fluence. We observe that sample properties like strength of the Dzyaloshinskii–Moriya interaction and pinning do not considerably influence the initial step of optical creation. In contrast, the number of skyrmions created can be directly and robustly controlled via the applied field and the laser fluence. Based on our findings, we propose concepts for applications, such as all-optical writing and deletion, an ultrafast skyrmion reshuffling device for probabilistic computing, and a combined optical and spin–orbit torque-controlled racetrack.

Ternary II–IV–N2 materials have been considered as a promising class of materials that combine photovoltaic performance with earth-abundance and low toxicity. When switching from binary III–V materials to ternary II–IV–N2 materials, further structural complexity is added to the system that may influence its optoelectronic properties. Herein, we present a systematic study of the reaction of Zn2GeO4 with NH3 that produces zinc germanium oxide nitrides, and ultimately approach stoichiometric ZnGeN2, using a combination of chemical analyses, X-ray powder diffraction and DFT calculations. Elucidating the reaction mechanism as being dominated by Zn and O extrusion at the later reaction stages, we give an insight into studying structure–property relationships in this emerging class of materials.

The dielectric constant and the viscosity of water at the interface of hydrophilic surfaces differ from their bulk values, and it has been proposed that the deviation is caused by the strong electric field and the high ion concentration in the interfacial layer. We calculate the dependence of the dielectric constant and the viscosity of bulk electrolytes on the electric field and the salt concentration. Incorporating the concentration and field-dependent dielectric constant and viscosity in the extended Poisson–Boltzmann and Stokes equations, we calculate the electro-osmotic mobility. We compare the results to literature experimental data and explicit molecular dynamics simulations of OH-terminated surfaces and show that it is necessary to additionally include the presence of a subnanometer wide interfacial water layer, the properties of which are drastically transformed by the sheer presence of the interface. We conclude that the origin of the anomalous behavior of aqueous interfacial layers cannot be found in electrostriction or electroviscous effects caused by the interfacial electric field and ion concentration. Instead, it is primarily caused by the intrinsic ordering and orientation of the interfacial water layer.

A peculiar habitat type found in the savannahs of Central Cuba, Villa Clara Province and characterised by the presence of a surface gravel layer of “perdigones”, an assemblage of small ferralitic concretions, upon the “mocarrero” soil prevailing in the area, is described. On sterile gravel patches, only one species grows: Elytraria serpens, a new species described and named here. It is noteworthy for possessing long and wide creeping, stoloniform subterranean peduncles with apical gemmae developing into rooting leaf rosettes enabling vegetative propagation. The new species is close to E. shaferi and considered to derive from the latter by adaptive evolution, enabling it to survive in its hostile habitat, sheltered from the competition of other plant species. Small soil insects, for example, ants, are believed to act as pollinators.