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The sub-cycle interaction of light and matter is one of the key frontiers of inquiry made accessible by attosecond science. Here, we show that when light excites a pair of charge carriers inside of a solid, the transition probability is strongly localized to instants slightly after the extrema of the electric field. The extreme temporal localization is utilized in a simple electronic circuit to record the waveforms of infrared to ultraviolet light fields. This form of petahertz-bandwidth field metrology gives access to both the modulated transition probability and its temporal offset from the laser field, providing sub-fs temporal precision in reconstructing the sub-cycle electronic response of a solid state structure. Characterization of light pulses is important in order to understand their interaction with matter. Here the authors demonstrate a nonlinear photoconductive sampling method to measure electric field wave-forms in the infrared, visible and ultraviolet spectral ranges.

Innovative ideas are essential to sustainable development. Students' innovative potential in higher education for sustainable development (HESD) has so far been neglected. Innovation is often associated with an interdisciplinary approach. However, the results of research on diversity and its role in innovation are inconsistent. The present study takes a longitudinal approach to investigating student teams in project-based learning courses in HESD in Germany. This study examines how innovation develops in interdisciplinary student teams in contrast to monodisciplinary student teams. The results of the latent change approach from a sample of 69 student teams indicate significant changes in students' innovation over time. Monodisciplinary student teams outperform interdisciplinary student teams in idea promotion (convincing potential allies) at the beginning, whereas interdisciplinary student teams outperform monodisciplinary student teams in idea generation (production of novel and useful ideas) in the midterm. There is no difference in the long term. The results indicate that interdisciplinary student teams have an advantage in the generation of novel ideas but need time to leverage their access to different discipline-based knowledge. We discuss practical implications for the design of interdisciplinary learning with strategies to support students in the formation phase in project-based learning in HESD. (ZPID).

Electron transfer from valence to conduction band states in semiconductors is the basis of modern electronics. Here, attosecond extreme ultraviolet (XUV) spectroscopy is used to resolve this process in silicon in real time. Electrons injected into the conduction band by few-cycle laser pulses alter the silicon XUV absorption spectrum in sharp steps synchronized with the laser electric field oscillations. The observed ∼450-attosecond step rise time provides an upper limit for the carrier-induced band-gap reduction and the electron-electron scattering time in the conduction band. This electronic response is separated from the subsequent band-gap modifications due to lattice motion, which occurs on a time scale of 60 ± 10 femtoseconds, characteristic of the fastest optical phonon. Quantum dynamical simulations interpret the carrier injection step as light-field–induced electron tunneling.

Reliable and valid measurement of the various components of prosociality calls for tools that capture its diverse behavioral expressions. Here, we evaluate how economic game measures derived from the Dictator Game, Public Goods Game, and Ultimatum Game as well as a novel Third-Party Intervention Paradigm correspond with their self-reported counterparts within a design informed by a multitrait–multimethod approach. The self-report scales described Help Giving, Peer Punishment, and Moral Courage as behavioral traits in real life. Each game decision was regressed on all three of these scales using data from 22 studies. Convergent validity emerged, with the strongest associations for help giving and the weakest for peer punishment. Discriminant validity was evidenced by the lack of significant cross-correlations, with one minor exception regarding the Peer Punishment scale and the Dictator Game. Overall, the findings support the distinctiveness of the facets, particularly for help giving and moral courage, while highlighting challenges in capturing punishment-related altruism. While several procedures for improving correspondence are discussed, the descriptively higher correlations within methods than across traits suggest a persistent gap in criterion validation.

The resilience of natural systems may be severely compromised by anthropogenic influences. In this paper, the principal anthropogenic influences on the ecosystem of the Armenian highland lake Sevan during the past century are identified. The diversity and severity of the pressures were influenced by national priorities and the catchment's growth. Changes in the lake's morphometry and the littoral's morphology, as well as unsustainable usage of the lake's fish resources, were among the repercussions. They are discussed depending on how each sort of disturbance affects the ecosystem. Although the timing and degree of each stressor were specified, identifying the direct effects of each stressor was often challenging. The current management decisions and future threats to the lake's ecosystem are discussed. This article describes the history of the anthropogenic change of Lake Sevan and, using it as an example, assesses the ecological footprint of people on natural resources and their repercussions.

A large body of research has examined the link between personality and face-to-face (FtF) communication knowledge, skills, abilities, and other characteristics (KSAOs). With the rise of digital media, text-based computer-mediated (CM) communication KSAOs have gained increasing attention. We conducted two studies to investigate how personality relates to KSAOs in the different contexts of FtF and CM communication. Contrasting perspectives hypothesize that the results in the FtF and CM contexts would be very similar or distinctly different. In Study 1 ( n = 454), an online panel study, the Big Five personality dimensions were assessed and their relationships to FtF and CM communication KSAOs were investigated. Structural equation models and relative weight regression analyses showed that these personality dimensions, mostly extraversion and neuroticism, explained more variance in FtF as compared to CM communication KSAOs. Study 2 ( n = 173), conducted in a laboratory context, showed similar results compared to Study 1. In addition, when the Big Five personality dimensions were assessed with a CM frame of reference, more variance was explained in CM than in FtF communication KSAOs. These results point to the importance of considering context effects in communication and in personality research: FtF and CM communication KSAOs need to be differentiated. If not properly contextualized, the relevance of personality and communication competencies in predicting criteria may be underestimated due to contextual mismatches.

Global warming is shifting the thermal dynamics of lakes, with resulting climatic variability heavily affecting their mixing dynamics. We present a dual ensemble workflow coupling climate models with lake models. We used a large set of simulations across multiple domains, multi‐scenario, and multi GCM‐ RCM combinations from CORDEX data. We forced a set of multiple hydrodynamic lake models by these multiple climate simulations to explore climate change impacts on lakes. We also quantified the contributions from the different models to the overall uncertainty. We employed this workflow to investigate the effects of climate change on Lake Sevan (Armenia). We predicted for the end of the 21st century, under RCP 8.5, a sharp increase in surface temperature (4.3±0.7K)$(4.3\\pm 0.7\\,\\mathrm{K})$and substantial bottom warming (1.7±0.7K)$(1.7\\pm 0.7\\,\\mathrm{K})$ , longer stratification periods (+55 days) and disappearance of ice cover leading to a shift in mixing regime. Increased insufficient cooling during warmer winters points to the vulnerability of Lake Sevan to climate change. Our workflow leverages the strengths of multiple models at several levels of the model chain to provide a more robust projection and at the same time a better uncertainty estimate that accounts for the contributions of the different model levels to overall uncertainty. Although for specific variables, for example, summer bottom temperature, single lake models may perform better, the full ensemble provides a robust estimate of thermal dynamics that has a high transferability so that our workflow can be a blueprint for climate impact studies in other systems. Plain Language Summary Lakes are threatened by climate change because of effects related to the increasing temperature, long stratification, and ice disappearance. One of the best tools to predict these effects on lakes is numerical modeling of lakes that benefit from climate modeling. Climate modeling is normally done globally or in the so‐called general circulation model (GCM) or more detailed simulations on regional levels (RCM) like the CORDEX data set. In this study, we used the CORDEX data, which employed several climate models from several regions (domains) for several climatic scenarios (emissions scenarios) to force multiple lake models. This approach gave us an extensive prediction about various possible outputs. We applied this approach to Lake Sevan (Armenia), a large mountain lake. Our study predicted for the worst‐case scenario, an increase of the surface temperature by almost 4.3 K by the end of the 21st century, 1.75 K for bottom temperature, a total disappearance of ice cover, and about 55 extra days of stratification, showing its vulnerability for climate change. This optimized workflow uses the strength of a wide variety of models on the climate and lake levels to better understand the impact of climate change and quantify the sources of uncertainty in the workflow. Key Points Dual multi‐model ensemble of climate data and lake models is used for robust projections of climate change impacts Variance decomposition effectively identified the sources of uncertainty and contributions of different models to the overall uncertainty Significant warming, longer stratification periods, and loss of ice cover are predicted for Lake Sevan by the end of the 21st century

Lake Sevan, located in the Armenian Highlands, is one of the world’s largest high-altitude freshwater lakes (1900 m a.s.l.). Hydrobiological investigations in the lake have an almost century-long history; however, the bacterial diversity has never been studied. In this study, bacterioplankton composition in Lake Sevan has been characterized for the first time. The samples were collected from different depths at the deepest points of both subbasins, Big and Small Sevan, once per season in 2018 and analyzed genetically by high-throughput sequencing of the V3-V4 region of 16 S rRNA gene. According to the 16 S rRNA gene sequencing, the majority of the bacterioplankton consisted of well-known freshwater microorganisms of the phyla Pseudomonadota, Actinomycetota, Bacteroidota, Cyanobacteriota, and Candidatus Kapabacteria. Representatives from Verrucomicrobiota, Planctomycetota, Bdellovibrionota, Gemmatimonadota, Myxococcota, and other phyla were found sporadically or in minor abundance. Alpha diversity was generally high, except during the summer cyanobacterial bloom. Two types of cyanobacterial occurrence were identified: (1) filamentous, potentially harmful cyanobacteria, such as Dolichospermum flos-aquae , which bloomed in summer, and (2) autotrophic picocyanobacteria, primarily Synechococcus , which dominated the cyanobacterial community in spring, autumn, and winter. In addition, pathogenic bacteria were detected in the lake, including species pathogenic to fish and humans, as well as intracellular parasites.

Lake Sevan in Armenia is a unique, large, alpine lake given its surface, volume, and geographic location. The lake suffered from progressing eutrophication and, since 2018, massive cyanobacterial blooms repeatedly occurred. Although the lake is comparatively intensely monitored, the feasibility to reliably detect the algal bloom events appeared to be limited by the established in situ monitoring, mostly because algal bloom dynamics are far more dynamic than the realized monitoring frequency of monthly samplings. This mismatch of monitoring frequency and ecosystem dynamics is a notorious problem in lakes, where plankton dynamics often work at relatively short time scales. Satellite-based monitoring with higher overpass frequency, e.g., by Sentinel-3 OLCI with its daily overcasts, are expected to fill this gap. The goal of our study was therefore the establishment of a fast detection of algal blooms in Lake Sevan that operates at the time scale of days instead of months. We found that algal bloom detection in Lake Sevan failed, however, when it was only based on chlorophyll due to complications with optical water properties and atmospheric corrections. Instead, we obtained good results when true-color RGB images were analyzed or a specifically designed satellite-based HAB indicator was applied. These methods provide reliable and very fast bloom detection at a scale of days. At the same time, our results indicated that there are still considerable limitations for the use of remote sensing when it comes to a fully quantitative assessment of algal dynamics in Lake Sevan. The observations made so far indicate that algal blooms are a regular feature in Lake Sevan and occur almost always when water temperatures surpass approximately 20 °C. Our satellite-based method effectively allowed for bloom detection at short time scales and identified blooms over several years where classical sampling failed to do so, simply because of the unfortunate timing of sampling dates and blooming phases. The extension of classical in situ sampling by satellite-based methods is therefore a step towards a more reliable, faster, and more cost-effective detection of algal blooms in this valuable lake.

We predicted that chronic pain patients have a more negative stress mindset and a lower level of social identification than people without chronic pain and that this, in turn, influences well-being through less adaptive coping. 1240 participants (465 chronic pain patients; 775 people in the control group) completed a cross-sectional online-survey. Chronic pain patients had a more negative stress mindset and a lower level of social identification than people without chronic pain. However, a positive stress mindset was linked to better well-being and fewer depressive symptoms, through the use of the adaptive coping behaviors positive reframing and active coping . A higher level of social identification did not impact well-being or depression through the use of instrumental and emotional support coping , but through the more frequent use of positive reframing and active coping . For chronic pain therapy, we propose including modules that foster social identification and a positive stress mindset.