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Next-generation sequencing methods provide comprehensive data for the analysis of structural and functional analysis of the genome. The draft genomes with low contig number and high N50 value can give insight into the structure of the genome as well as provide information on the annotation of the genome. In this study, we designed a pipeline that can be used to assemble prokaryotic draft genomes with low number of contigs and high N50 value. We aimed to use combination of two de novo assembly tools (SPAdes and IDBA-Hybrid) and evaluate the impact of this approach on the quality metrics of the assemblies. The followed pipeline was tested with the raw sequence data with short reads (< 300) for a total of 10 species from four different genera. To obtain the final draft genomes, we firstly assembled the sequences using SPAdes to find closely related organism using the extracted 16 s rRNA from it. IDBA-Hybrid assembler was used to obtain the second assembly data using the closely related organism genome. SPAdes assembler tool was implemented using the second assembly, produced by IDBA-hybrid as a hint. The results were evaluated using QUAST and BUSCO. The pipeline was successful for the reduction of the contig numbers and increasing the N50 statistical values in the draft genome assemblies while preserving the coverage of the draft genomes.
Extreme value statistics is a popular and frequently used tool to model the occurrence of large earthquakes. The problem of poor statistics arising from rare events is addressed by taking advantage of the validity of general statistical properties in asymptotic regimes. In this note, I argue that the use of extreme value statistics for the purpose of practically modeling the tail of the frequency-magnitude distribution of earthquakes can produce biased and thus misleading results because it is unknown to what degree the tail of the true distribution is sampled by data. Using synthetic data allows to quantify this bias in detail. The implicit assumption that the true M-max is close to the maximum observed magnitude M-max,M-observed restricts the class of the potential models a priori to those with M-max = M-max,M-observed + Delta M with an increment Delta M approximate to 0.5... 1.2. This corresponds to the simple heuristic method suggested by Wheeler (2009) and labeled :M-max equals M-obs plus an increment." The incomplete consideration of the entire model family for the frequency-magnitude distribution neglects, however, the scenario of a large so far unobserved earthquake.
Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision-making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene-to-individual level and the community-to-ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision-making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier-to-use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best-practise guidelines for applying these models. Further, more robust decision-making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long-term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.
Marine sedimentary archives are routinely used to reconstruct past environmental changes. In many cases, bioturbation and sedimentary mixing affect the proxy time-series and the age-depth relationship. While idealized models of bioturbation exist, they usually assume homogeneous mixing, thus that a single sample is representative for the sediment layer it is sampled from.
However, it is largely unknown to which extent this assumption holds for sediments used for paleoclimate reconstructions.
To shed light on
1) the age-depth relationship and its full uncertainty,
2) the magnitude of mixing processes affecting the downcore proxy variations, and
3) the representativity of the discrete sample for the sediment layer, we designed and performed a case study on South China Sea sediment material which was collected using a box corer and which covers the last glacial cycle.
Using the radiocarbon content of foraminiferal tests as a tracer of time, we characterize the spatial age-heterogeneity of sediments in a three-dimensional setup. In total, 118 radiocarbon measurements were performed on defined small- and large-volume bulk samples ( similar to 200 specimens each) to investigate the horizontal heterogeneity of the sediment. Additionally, replicated measurements on small numbers of specimens (10 x 5 specimens) were performed to assess the heterogeneity within a sample volume. Visual assessment of X-ray images and a quantitative assessment of the mixing strength show typical mixing from bioturbation corresponding to around 10 cm mixing depth.
Notably, our 3D radiocarbon distribution reveals that the horizontal heterogeneity (up to 1,250 years), contributing to the age uncertainty, is several times larger than the typically assumed radiocarbon based age-model error (single errors up to 250 years). Furthermore, the assumption of a perfectly bioturbated layer with no mixing underneath is not met.
Our analysis further demonstrates that the age-heterogeneity might be a function of sample size; smaller samples might contain single features from the incomplete mixing and are thus less representative than larger samples.
We provide suggestions for future studies, optimal sampling strategies for quantitative paleoclimate reconstructions and realistic uncertainty in age models, as well as discuss possible implications for the interpretation of paleoclimate records.
A comparative whole-genome approach identifies bacterial traits for marine microbial interactions
(2022)
Luca Zoccarato, Daniel Sher et al. leverage publicly available bacterial genomes from marine and other environments to examine traits underlying microbial interactions.
Their results provide a valuable resource to investigate clusters of functional and linked traits to better understand marine bacteria community assembly and dynamics.
Microbial interactions shape the structure and function of microbial communities with profound consequences for biogeochemical cycles and ecosystem health. Yet, most interaction mechanisms are studied only in model systems and their prevalence is unknown. To systematically explore the functional and interaction potential of sequenced marine bacteria, we developed a trait-based approach, and applied it to 473 complete genomes (248 genera), representing a substantial fraction of marine microbial communities.
We identified genome functional clusters (GFCs) which group bacterial taxa with common ecology and life history. Most GFCs revealed unique combinations of interaction traits, including the production of siderophores (10% of genomes), phytohormones (3-8%) and different B vitamins (57-70%). Specific GFCs, comprising Alpha- and Gammaproteobacteria, displayed more interaction traits than expected by chance, and are thus predicted to preferentially interact synergistically and/or antagonistically with bacteria and phytoplankton. Linked trait clusters (LTCs) identify traits that may have evolved to act together (e.g., secretion systems, nitrogen metabolism regulation and B vitamin transporters), providing testable hypotheses for complex mechanisms of microbial interactions.
Our approach translates multidimensional genomic information into an atlas of marine bacteria and their putative functions, relevant for understanding the fundamental rules that govern community assembly and dynamics.
This paper consists of two parts: In the first part, some of the challenges with which the Internationaal Criminal Court is currently confronted are being presented. First of all, the article will describe the current state of the International Criminal Court and the Rome Statue. Afterwards, the article analyses the Court’s efforts to deal with cases against third-country nationals and the challenges it is facing in that regard. In addition, the Court’s case law will be analyzed in order to determine an increasing ‘emancipation’ of the case law of the International Criminal Court from international humanitarian law. The second part of the paper will briefly discuss the role of domestic international criminal law and domestic courts in the further development and enforcement of international criminal law. As an example of the role that domestic courts may have in clarifying classic issues in international law, the judgment of the German Supreme Court of January 28, 2021 (3 StR 564/19), which deals with the status of costumary international law on functional immunity of State officials before domestic courts, shall be assessed.
Das Völkerstrafrecht steht fast zwanzig Jahre nach dem Inkrafttreten des Römischen Statuts – der völkervertraglichen Grundlage des Internationalen Strafgerichtshofs – angesichts einer inzwischen deutlich veränderten Weltlage an einem Scheideweg. Daher erscheint es geboten, wenn nicht gar zwingend, die Herausforderungen, mit denen sich der Internationale Strafgerichtshof heute konfrontiert sieht, zu analysieren.
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge, we are the first to directly compare the impact of differentially private training on two different neural network architectures, DenseNet121 and ResNet50. Extending the federated learning environments previously analyzed in terms of privacy, we simulated a heterogeneous and imbalanced federated setting by distributing images from the public CheXpert and Mendeley chest X-ray datasets unevenly among 36 clients. Both non-private baseline models achieved an area under the receiver operating characteristic curve (AUC) of 0.940.94 on the binary classification task of detecting the presence of a medical finding. We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients. The attack was particularly successful during later training stages. To mitigate the risk of a privacy breach, we integrated Rényi differential privacy with a Gaussian noise mechanism into local model training. We evaluate model performance and attack vulnerability for privacy budgets ε∈{1,3,6,10}�∈{1,3,6,10}. The DenseNet121 achieved the best utility-privacy trade-off with an AUC of 0.940.94 for ε=6�=6. Model performance deteriorated slightly for individual clients compared to the non-private baseline. The ResNet50 only reached an AUC of 0.760.76 in the same privacy setting. Its performance was inferior to that of the DenseNet121 for all considered privacy constraints, suggesting that the DenseNet121 architecture is more robust to differentially private training.
Earthquake site responses or site effects are the modifications of surface geology to seismic waves. How well can we predict the site effects (average over many earthquakes) at individual sites so far? To address this question, we tested and compared the effectiveness of different estimation techniques in predicting the outcrop Fourier site responses separated using the general inversion technique (GIT) from recordings. Techniques being evaluated are (a) the empirical correction to the horizontal-to-vertical spectral ratio of earthquakes (c-HVSR), (b) one-dimensional ground response analysis (GRA), and (c) the square-root-impedance (SRI) method (also called the quarter-wavelength approach). Our results show that c-HVSR can capture significantly more site-specific features in site responses than both GRA and SRI in the aggregate, especially at relatively high frequencies. c-HVSR achieves a "good match" in spectral shape at similar to 80%-90% of 145 testing sites, whereas GRA and SRI fail at most sites. GRA and SRI results have a high level of parametric and/or modeling errors which can be constrained, to some extent, by collecting on-site recordings.
Bimetallic nanostructures comprising plasmonic and catalytic components have recently emerged as a promising approach to generate a new type of photo-enhanced nanoreactors. Most designs however concentrate on plasmon-induced charge separation, leaving photo-generated heat as a side product.
This work presents a photoreactor based on Au-Pd nanorods with an optimized photothermal conversion, which aims to effectively utilize the photo-generated heat to increase the rate of Pd-catalyzed reactions. Dumbbell-shaped Au nanorods were fabricated via a seed-mediated growth method using binary surfactants. Pd clusters were selectively grown at the tips of the Au nanorods, using the zeta potential as a new synthetic parameter to indicate the surfactant remaining on the nanorod surface.
The photothermal conversion of the Au-Pd nanorods was improved with a thin layer of polydopamine (PDA) or TiO2.
As a result, a 60% higher temperature increment of the dispersion compared to that for bare Au rods at the same light intensity and particle density could be achieved.
The catalytic performance of the coated particles was then tested using the reduction of 4-nitrophenol as the model reaction. Under light, the PDA-coated Au-Pd nanorods exhibited an improved catalytic activity, increasing the reaction rate by a factor 3.
An analysis of the activation energy confirmed the photoheating effect to be the dominant mechanism accelerating the reaction. Thus, the increased photothermal heating is responsible for the reaction acceleration.
Interestingly, the same analysis shows a roughly 10% higher reaction rate for particles under illumination compared to under dark heating, possibly implying a crucial role of localized heat gradients at the particle surface.
Finally, the coating thickness was identified as an essential parameter determining the photothermal conversion efficiency and the reaction acceleration.
We present observations of three-dimensional magnetic power spectra in wavevector space to investigate the anisotropy and scalings of sub-Alfvenic solar wind turbulence at magnetohydrodynamic (MHD) scale using the Magnetospheric Multiscale spacecraft. The magnetic power distributions are organized in a new coordinate determined by wavevectors ((kappa) over cap) and background magnetic field ((b) over cap (0)) in Fourier space. This study utilizes two approaches to determine wavevectors: the singular value decomposition method and multispacecraft timing analysis. The combination of the two methods allows an examination of the properties of magnetic field fluctuations in terms of mode compositions without any spatiotemporal hypothesis. Observations show that fluctuations (delta B-perpendicular to 1) in the direction perpendicular to (kappa) over cap and (b) over cap (0) prominently cascade perpendicular to (b) over cap (0), and such anisotropy increases with wavenumbers. The reduced power spectra of 6.8 11 follow Goldreich-Sridhar scalings: (P) over cap (k(perpendicular to)) proportional to k(perpendicular to)(-5/3) and (P) over cap (k(parallel to)) proportional to k(parallel to)(-2). In contrast, fluctuations within the (k) over cap(b) over cap (0) plane show isotropic behaviors: perpendicular power distributions are approximately the same as parallel distributions. The reduced power spectra of fluctuations within the (k) over cap(b) over cap (0) plane follow the scalings (P) over cap (k(perpendicular to)) proportional to k(perpendicular to)(-3/2) and (P) over cap (k(parallel to)) proportional to k(parallel to)(-3/2). Comparing frequency-wavevector spectra with theoretical dispersion relations of MHD modes, we find that delta B-perpendicular to 1 are probably associated with Alfven modes. On the other hand, magnetic field fluctuations within the (k) over cap(b) over cap (0) plane more likely originate from fast modes based on their isotropic behaviors. The observations of anisotropy and scalings of different magnetic field components are consistent with the predictions of current compressible MHD theory. Moreover, for the Alfvenic component, the ratio of cascading time to the wave period is found to be a factor of a few, consistent with critical balance in the strong turbulence regime. These results are valuable for further studies of energy compositions of plasma turbulence and their effects on energetic particle transport.
Collagen-based biomaterials with oriented fibrils have shown great application potential in medicine. However, it is still challenging to control the type I collagen fibrillogenesis in ultrathin films. Here, we report an approach to produce cohesive and well-organized type I collagen ultrathin films of about 10 nm thickness using the Langmuir-Blodgett technique. Ellipsometry, rheology, and Brewster angle microscopy are applied to investigate in situ how the molecules behave at the air-water interface, both at room temperature and 37 degrees C. The interfacial storage modulus observed at room temperature vanishes upon heating, indicating the existence and disappearance of the network structure in the protein nanosheet. The films were spanning over holes as large as 1 mm diameter when transferred at room temperature, proving the strong cohesive interactions. A highly aligned and fibrillar structure was observed by atomic force microscopy (AFM) and optical microscopy.
Biodegradation of polyester polyurethane by the marine fungus Cladosporium halotolerans 6UPA1
(2022)
Lack of degradability and the accumulation of polymeric wastes increase the risk for the health of the environment. Recently, recycling of polymeric waste materials becomes increasingly important as raw materials for polymer synthesis are in short supply due to the rise in price and supply chain disruptions. As an important polymer, polyurethane (PU) is widely used in modern life, therefore, PU biodegradation is desirable to avoid its accumulation in the environment. In this study, we isolated a fungal strain Cladosporium halotolerans from the deep sea which can grow in mineral medium with a polyester PU (Impranil DLN) as a sole carbon source. Further, we demonstrate that it can degrade up to 80% of Impranil PU after 3 days of incubation at 28 celcius by breaking the carbonyl groups (1732 cm(-1)) and C-N-H bonds (1532 cm(-1) and 1247 cm(-1)) as confirmed by Fourier-transform infrared (FTIR) spectroscopy analysis. Gas chromatography-mass spectrometry (GC-MS) analysis revealed polyols and alkanes as PU degradation intermediates, indicating the hydrolysis of ester and urethane bonds. Esterase and urease activities were detected in 7 days-old cultures with PU as a carbon source. Transcriptome analysis showed a number of extracellular protein genes coding for enzymes such as cutinase, lipase, peroxidase and hydrophobic surface binding proteins A (HsbA) were expressed when cultivated on Impranil PU. The yeast two-hybrid assay revealed that the hydrophobic surface binding protein ChHsbA1 directly interacts with inducible esterases, ChLip1 (lipase) and ChCut1 (cutinase). Further, the KEGG pathway for "fatty acid degradation " was significantly enriched in Impranil PU inducible genes, indicating that the fungus may use the degradation intermediates to generate energy via this pathway. Taken together, our data indicates secretion of both esterase and hydrophobic surface binding proteins by C. halotolerans plays an important role in Impranil PU absorption and subsequent degradation. Our study provides a mechanistic insight into Impranil PU biodegradation by deep sea fungi and provides the basis for future development of biotechnological PU recycling.
The origin of the First Bend of the Yangtze River is key to understanding the birth of the modern Yangtze River. Despite considerable efforts, the timing and mechanism of formation of the First Bend remain highly debated. Inverse river-profile modeling of three tributaries (Chongjiang, Lima, and Gudu) of the Jinsha River, integrated with regional tectonic and geomorphic interpretations, allows the onset of incision at the First Bend to be constrained to 28-20 Ma. The spatio-temporal coincidence of initial river incision and activity of Yulong Thrust Belt in southeastern Tibet highlights thrusting to be fundamental in reshaping the pre-existing stream network at the First Bend. These results enable us to reinterpret a change in sedimentary environment from a braided river to a swamp-like lake in the Jianchuan Basin south of the First Bend, recording the destruction of the hypothesized southwards-flowing paleo-Jinsha and Shuiluo Rivers at ~36-35 Ma by magmatism. During the late Oligoceneearly Miocene, the paleo-Shuiluo River was diverted to the north by focused rock uplift due to thrusting along the Yulong Thrust Belt, which also led to exhumation of the Jianchuan Basin. Diversion of the paleo-Shuiluo River can be explained by capture from a downstream river in the footwall of the Yulong Thrust Belt. Subsequent rapid headward erosion, that was caused by thrusting-induced drop of local base level, is recorded by upstream younging ages for the onset of incision and led to the formation of the First Bend. The combination of new ages for the onset of incision at 28-20 Ma at the First Bend and younger ages upstream indicates northwards expansion of the Jinsha River at a rate of 62 +/- 18 mm/yr. Our results suggest that the origin of the First Bend was likely triggered by thrusting at 28-20 Ma, after which the Yangtze River formed.
Based on micromagnetic simulations and experimental observations of the magnetization and lattice dynamics after the direct optical excitation of the magnetic insulator Bi : YIG or indirect excitation via an optically opaque Pt/Cu double layer, we disentangle the dynamical effects of magnetic anisotropy and magneto-elastic coupling. The strain and temperature of the lattice are quantified via modeling ultrafast x-ray diffraction data. Measurements of the time-resolved magneto-optical Kerr effect agree well with the magnetization dynamics simulated according to the excitation via two mechanisms: the magneto-elastic coupling to the experimentally verified strain dynamics and the ultrafast temperature-induced transient change in the magnetic anisotropy. The numerical modeling proves that, for direct excitation, both mechanisms drive the fundamental mode with opposite phase. The relative ratio of standing spin wave amplitudes of higher-order modes indicates that both mechanisms are substantially active.
StudyMe
(2022)
N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, there is a gap in supporting non-experts in conducting their own user-centric trials. In this study, we present StudyMe, an open-source mobile application that is freely available from https://play.google.com/store/apps/details?id=health.studyu.me and offers users flexibility and guidance in configuring every component of their trials. We also present research that informed the development of StudyMe, focusing on trial creation. Through an initial survey with 272 participants, we learned that individuals are interested in a variety of personal health aspects and have unique ideas on how to improve them. In an iterative, user-centered development process with intermediate user tests, we developed StudyMe that features an educational part to communicate N-of-1 trial concepts. A final empirical evaluation of StudyMe showed that all participants were able to create their own trials successfully using StudyMe and the app achieved a very good usability rating. Our findings suggest that StudyMe provides a significant step towards enabling individuals to apply a systematic science-oriented approach to personalize health-related interventions and behavior modifications in their everyday lives.
The stability of the Greenland Ice Sheet under global warming is governed by a number of dynamic processes and interacting feedback mechanisms in the ice sheet, atmosphere and solid Earth.
Here we study the long-term effects due to the interplay of the competing melt-elevation and glacial isostatic adjustment (GIA) feedbacks for different temperature step forcing experiments with a coupled ice-sheet and solid-Earth model.
Our model results show that for warming levels above 2 degrees C, Greenland could become essentially ice-free within several millennia, mainly as a result of surface melting and acceleration of ice flow. These ice losses are mitigated, however, in some cases with strong GIA feedback even promoting an incomplete recovery of the Greenland ice volume. We further explore the full-factorial parameter space determining the relative strengths of the two feedbacks: our findings suggest distinct dynamic regimes of the Greenland Ice Sheets on the route to destabilization under global warming - from incomplete recovery, via quasi-periodic oscillations in ice volume to ice-sheet collapse.
In the incomplete recovery regime, the initial ice loss due to warming is essentially reversed within 50 000 years, and the ice volume stabilizes at 61 %-93 % of the present-day volume. For certain combinations of temperature increase, atmospheric lapse rate and mantle viscosity, the interaction of the GIA feedback and the melt-elevation feedback leads to self-sustained, long-term oscillations in ice-sheet volume with oscillation periods between 74 000 and over 300 000 years and oscillation amplitudes between 15 %-70 % of present-day ice volume.
This oscillatory regime reveals a possible mode of internal climatic variability in the Earth system on timescales on the order of 100 000 years that may be excited by or synchronized with orbital forcing or interact with glacial cycles and other slow modes of variability. Our findings are not meant as scenario-based near-term projections of ice losses but rather providing insight into of the feedback loops governing the "deep future" and, thus, long-term resilience of the Greenland Ice Sheet.
In crystalline and amorphous semiconductors, the temperature-dependent Urbach energy can be determined from the inverse slope of the logarithm of the absorption spectrum and reflects the static and dynamic energetic disorder. Using recent advances in the sensitivity of photocurrent spectroscopy methods, we elucidate the temperature-dependent Urbach energy in lead halide perovskites containing different numbers of cation components. We find Urbach energies at room temperature to be 13.0 +/- 1.0, 13.2 +/- 1.0, and 13.5 +/- 1.0 meV for single, double, and triple cation perovskite. Static, temperature-independent contributions to the Urbach energy are found to be as low as 5.1 ?+/- 0.5, 4.7 +/- 0.3, and 3.3 +/- 0.9 meV for the same systems. Our results suggest that, at a low temperature, the dominant static disorder in perovskites is derived from zero-point phonon energy rather than structural disorder. This is unusual for solution-processed semiconductors but broadens the potential application of perovskites further to quantum electronics and devices.
The photogeneration of free charges in light-harvesting devices is a multistep process, which can be challenging to probe due to the complexity of contributing energetic states and the competitive character of different driving mechanisms. In this contribution, we advance a technique, integral-mode transient charge extraction (ITCE), to probe these processes in thin-film solar cells. ITCE combines capacitance measurements with the integral-mode time-of-flight method in the low intensity regime of sandwich-type thin-film devices and allows for the sensitive determination of photogenerated charge-carrier densities. We verify the theoretical framework of our method by drift-diffusion simulations and demonstrate the applicability of ITCE to organic and perovskite semiconductor-based thin-film solar cells. Furthermore, we examine the field dependence of charge generation efficiency and find our ITCE results to be in excellent agreement with those obtained via time-delayed collection field measurements conducted on the same devices.
Überzeugungen zum Lehren und Lernen sind als Teil der professionellen Kompetenz von Lehrkräften bereits im Lehramtsstudium relevant und haben insbesondere in längeren Praxisphasen Entwicklungspotenzial. Welche Faktoren für die Entwicklung von Überzeugungen in Praxisphasen von Bedeutung sind, ist bislang aber nur unzureichend erforscht. In Interviews haben wir N = 16 Studierende befragt, welche Lerngelegenheiten für die Entwicklung ihrer Überzeugungen im Praxissemester eine Rolle spielten. Dabei konnten wir mittels Inhaltsanalyse vier übergeordnete Faktoren identifizieren: die universitäre Lernbegleitung, die Mentorinnen und Mentoren, die Schülerinnen und Schüler und die Reflexion eigener Unterrichtserfahrungen. Den Faktoren wurden untergeordnete Faktoren (z. B. Hospitationen durch Universitätsdozierende) zugeordnet und es wird dargestellt, warum und unter welchen Umständen diese Lerngelegenheiten für die Entwicklung der Überzeugungen aus Studierendensicht relevant sind.
We here present the results from a detailed analysis of nebular abundances of commonly observed ions in the collisional ring galaxy Cartwheel using the Very Large Telescope (VLT) Multi-Unit Spectroscopic Explorer (MUSE) data set. The analysis includes 221 H II regions in the star-forming ring, in addition to 40 relatively fainter H a-emitting regions in the spokes, disc, and the inner ring. The ionic abundances of He, N, O, and Fe are obtained using the direct method (DM) for 9, 20, 20, and 17 ring H II regions, respectively, where the S++ temperature-sensitive line is detected. For the rest of the regions, including all the nebulae between the inner and the outer ring, we obtained O abundances using the strong-line method (SLM). The ring regions have a median 12 + log O/H = 8.19 +/- 0.15, log N/O = -1.57 +/- 0.09 and log Fe/O = -2.24 +/- 0.09 using the DM. Within the range of O abundances seen in the Cartwheel, the N/O and Fe/O values decrease proportionately with increasing O, suggesting local enrichment of O without corresponding enrichment of primary N and Fe. The O abundances of the disc H II regions obtained using the SLM show a well-defined radial gradient. The mean O abundance of the ring H II regions is lower by similar to 0.1 dex as compared to the extrapolation of the radial gradient. The observed trends suggest the preservation of the pre-collisional abundance gradient, displacement of most of the processed elements to the ring, as predicted by the recent simulation by Renaud et al., and post-collisional infall of metal-poor gas in the ring.
Food preferences are crucial for diet-related decisions, which substantially impact individual health and global climate. However, the persistence of unfavorable food preferences is a significant obstacle to changing eating behavior.
Here we explored the effects of posthypnotic suggestions (PHS) on food-related decisions by measuring food choices, subjective ratings, and indifference points. In Session 1, demographic data and hypnotic susceptibility of participants were assessed. In Session 2, following hypnosis induction, PHS aiming to increase the desirability of healthy food was delivered.
Afterward, a task set was administrated twice, once when PHS was activated and once deactivated. The order of PHS activation was counterbalanced across participants. The task set included a liking-rating task for 170 pictures of different food items, followed by an online supermarket where participants were instructed to select enough food for a fictitious week of quarantining from the same item pool. After 1 week, Session 3 repeated Session 2 without hypnosis induction in order to assess the persistence of PHS.
The crucial dependent measures were food choices, subjective ratings, and the indifference points as a function of time and PHS condition.
The alpha-Al2O3(0001) surface has been extensively studied because of its significance in both fundamental research and application. Prior work suggests that in ultra-high-vacuum (UHV), in the absence of water, the so-called Al-I termination is thermodynamically favored, while in ambient, in contact with liquid water, a Gibbsite-like layer is created. While the view of the alpha- Al2O3(0001)/H2O(l) interface appears relatively clear in theory, experimental characterization of this system has resulted in estimates of surface acidity, i.e., isoelectric points, that differ by 4 pH units and surface structure that in some reports has non-hydrogen-bonded surface aluminol (Al-OH) groups and in others does not. In this study, we employed vibrational sum frequency spectroscopy (VSFS) and density functional theory (DFT) simulation to study the surface phonon modes of the differently terminated alpha-Al2O3(0001) surfaces in both UHV and ambient. We find that, on either water dosing of the Al-I in UHV or heat-induced dehydroxylation of the Gibbsite-like in ambient, the surfaces do not interconvert. This observation offers a new explanation for disagreements in prior work on the alpha-Al2O3(0001)/liquid water interface -different preparation methods may create surfaces that do not interconvert-and shows that the surface phonon spectral response offers a novel probe of interfacial hydrogen bonding structure.
Southeastern Tibetan Plateau growth revealed by inverse analysis of landscape evolution model
(2022)
The Cenozoic history of the Tibetan Plateau topography is critical for understanding the evolution of the Indian-Eurasian collision, climate, and biodiversity. However, the long-term growth and landscape evolution of the Tibetan Plateau remain ambiguous, it remains unclear if plateau uplift occurred soon after the India-Asia collision in the Paleogene (similar to 50-25 Ma) or later in the Neogene (similar to 20-5 Ma). Here, we reproduce the uplift history of the southeastern Tibetan Plateau using a 2D landscape evolution model, which simultaneously solves fluvial erosion and sediment transport processes in the drainage basins of the Three Rivers region (Yangtze, Mekong, and Salween Rivers). Our model was optimized through a formal inverse analysis with 20,000 forward simulations, which aims to reconcile the transient states of the present-day river profiles. The results, compared to existing paleoelevation and thermochronologic data, suggest initially low elevations (similar to 300-500 m) during the Paleogene, followed by a gradual southeastward propagation of topographic uplift of the plateau margin.
Organic solar cells (OSCs) have progressed rapidly in recent years through the development of novel organic photoactive materials, especially non-fullerene acceptors (NFAs). Consequently, OSCs based on state-of-the-art NFAs have reached significant milestones, such as similar to 19% power conversion efficiencies (PCEs) and small energy losses (less than 0.5 eV). Despite these significant advances, understanding of the interplay between molecular structure and optoelectronic properties lags significantly behind. For example, despite the theoretical framework for describing the energetic disorder being well developed for the case of inorganic semiconductors, the question of the applicability of classical semiconductor theories in analyzing organic semiconductors is still under debate. A general observation in the inorganic field is that inorganic photovoltaic materials possessing a polycrystalline microstructure exhibit suppressed disorder properties and better charge carrier transport compared to their amorphous analogs. Accordingly, this principle extends to the organic semiconductor field as many organic photovoltaic materials are synthesized to pursue polycrystalline-like features. Yet, there appears to be sporadic examples that exhibit an opposite trend. However, full studies decoupling energetic disorder from aggregation effects have largely been left out. Hence, the potential role of the energetic disorder in OSCs has received little attention. Interestingly, recently reported state-of-the-art NFA-based devices could achieve a small energetic disorder and high PCE at the same time; and interest in this investigation related to the disorder properties in OSCs was revived. In this contribution, progress in terms of the correlation between molecular design and energetic disorder is reviewed together with their effects on the optoelectronic mechanism and photovoltaic performance. Finally, the specific challenges and possible solutions in reducing the energetic disorder of OSCs from the viewpoint of materials and devices are proposed.
In this article, we examine the effects of political change on name changes of units within central government ministries. We expect that changes regarding the policy position of a government will cause changes in the names of ministerial units. To this end we formulate hypotheses combining the politics of structural choice and theories of portfolio allocation to examine the effects of political changes at the cabinet level on the names of intra-ministerial units. We constructed a dataset containing more than 17,000 observations on name changes of ministerial units between 1980 and 2013 from the central governments of Germany, the Netherlands, and France. We regress a series of generalized estimating equations (GEE) with population averaging models for binary outcomes. Finding variations across the three political-bureaucratic systems, we overall report positive effects of governmental change and ideological positions on name changes within ministries.
Ground motion with strong-velocity pulses can cause significant damage to buildings and structures at certain periods; hence, knowing the period and velocity amplitude of such pulses is critical for earthquake structural engineering.
However, the physical factors relating the scaling of pulse periods with magnitude are poorly understood.
In this study, we investigate moderate but damaging earthquakes (M-w 6-7) and characterize ground- motion pulses using the method of Shahi and Baker (2014) while considering the potential static-offset effects.
We confirm that the within-event variability of the pulses is large. The identified pulses in this study are mostly from strike-slip-like earthquakes. We further perform simulations using the freq uency-wavenumber algorithm to investigate the causes of the variability of the pulse periods within and between events for moderate strike-slip earthquakes.
We test the effect of fault dips, and the impact of the asperity locations and sizes. The simulations reveal that the asperity properties have a high impact on the pulse periods and amplitudes at nearby stations.
Our results emphasize the importance of asperity characteristics, in addition to earthquake magnitudes for the occurrence and properties of pulses produced by the forward directivity effect.
We finally quantify and discuss within- and between-event variabilities of pulse properties at short distances.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C₆₀ interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C₆₀ interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110 mV, and retain >97% of the initial efficiency after 400 h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C-60 interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C-60 interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110mV, and retain >97% of the initial efficiency after 400h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells. Effective transport layers are essential to suppress non-radiative recombination losses. Here, the authors introduce phenylamino-functionalized ortho-carborane as an interfacial layer, and realise inverted perovskite solar cells with efficiency of over 23% and operational stability of T97=400h.
This study examined the spoken narrative skills of a group of bilingual Mandarin–English speaking 3–6-year-olds (N = 25) in Australia, using a remote online story-retell task. Bilingual preschoolers are an understudied population, especially those who are speaking typologically distinct languages such as Mandarin and English which have fewer structural overlaps compared to language pairs that are typologically closer, reducing cross-linguistic positive transfer. We examined these preschoolers’ spoken narrative skills as measured by macrostructures (the global organization of a story) and microstructures (linguistic structures, e.g., total number of utterances, nouns, verbs, phrases, and modifiers) across and within each language, and how various factors such as age and language experiences contribute to individual variability. The results indicate that our bilingual preschoolers acquired spoken narrative skills similarly across their two languages, i.e., showing similar patterns of productivity for macrostructure and microstructure elements in both of their two languages. While chronological age was positively correlated with macrostructures in both languages (showing developmental effects), there were no significant correlations between measures of language experiences and the measures of spoken narrative skills (no effects for language input/output). The findings suggest that although these preschoolers acquire two typologically diverse languages in different learning environments, Mandarin at home with highly educated parents, and English at preschool, they displayed similar levels of oral narrative skills as far as these macro−/micro-structure measures are concerned. This study provides further evidence for the feasibility of remote online assessment of preschoolers’ narrative skills.
When new covalent organic frameworks (COFs) are designed, the main efforts are typically focused on selecting specific building blocks with certain geometries and properties to control the structure and function of the final COFs. The nature of the linkage (imine, boroxine, vinyl, etc.) between these building blocks naturally also defines their properties. However, besides the linkage type, the orientation, i.e., the constitutional isomerism of these linkages, has rarely been considered so far as an essential aspect. In this work, three pairs of constitutionally isomeric imine-linked donor-acceptor (D-A) COFs are synthesized, which are different in the orientation of the imine bonds (D-C=N-A (DCNA) and D-N=C-A (DNCA)). The constitutional isomers show substantial differences in their photophysical properties and consequently in their photocatalytic performance. Indeed, all DCNA COFs show enhanced photocatalytic H2 evolution performance than the corresponding DNCA COFs. Besides the imine COFs shown here, it can be concluded that the proposed concept of constitutional isomerism of linkages in COFs is quite universal and should be considered when designing and tuning the properties of COFs.
Magnetic reconnection is a multi-faceted process of energy conversion in astrophysical, space and laboratory plasmas that operates at microscopic scales but has macroscopic drivers and consequences.
Solar flares present a key laboratory for its study, leaving imprints of the microscopic physics in radiation spectra and allowing the macroscopic evolution to be imaged, yet a full observational characterization remains elusive.
Here we combine high resolution imaging and spectral observations of a confined solar flare at multiple wavelengths with data-constrained magnetohydrodynamic modeling to study the dynamics of the flare plasma from the current sheet to the plasmoid scale. The analysis suggests that the flare resulted from the interaction of a twisted magnetic flux rope surrounding a filament with nearby magnetic loops whose feet are anchored in chromospheric fibrils. Bright cusp-shaped structures represent the region around a reconnecting separator or quasi-separator (hyperbolic flux tube).
The fast reconnection, which is relevant for other astrophysical environments, revealed plasmoids in the current sheet and separatrices and associated unresolved turbulent motions.
Solar flares provide wide range of observational details about fundamental processes involved. Here, the authors show evidence for magnetic reconnection in a strong confined solar flare displaying all four reconnection flows with plasmoids in the current sheet and the separatrices.
We introduce and study a Lévy walk (LW) model of particle spreading with a finite propagation speed combined with soft resets, stochastically occurring periods in which an harmonic external potential is switched on and forces the particle towards a specific position. Soft resets avoid instantaneous relocation of particles that in certain physical settings may be considered unphysical. Moreover, soft resets do not have a specific resetting point but lead the particle towards a resetting point by a restoring Hookean force. Depending on the exact choice for the LW waiting time density and the probability density of the periods when the harmonic potential is switched on, we demonstrate a rich emerging response behaviour including ballistic motion and superdiffusion. When the confinement periods of the soft-reset events are dominant, we observe a particle localisation with an associated non-equilibrium steady state. In this case the stationary particle probability density function turns out to acquire multimodal states. Our derivations are based on Markov chain ideas and LWs with multiple internal states, an approach that may be useful and flexible for the investigation of other generalised random walks with soft and hard resets. The spreading efficiency of soft-rest LWs is characterised by the first-passage time statistic.
Levy walks are continuous-time random-walk processes with a spatiotemporal coupling of jump lengths and waiting times. We here apply the Hermite polynomial method to study the behavior of LWs with power-law walking time density for four different cases. First we show that the known result for the infinite density of an unconfined, unbiased LW is consistently recovered. We then derive the asymptotic behavior of the probability density function (PDF) for LWs in a constant force field, and we obtain the corresponding qth-order moments. In a harmonic external potential we derive the relaxation dynamic of the LW. For the case of a Poissonian walking time an exponential relaxation behavior is shown to emerge. Conversely, a power-law decay is obtained when the mean walking time diverges. Finally, we consider the case of an unconfined, unbiased LW with decaying speed v(r ) = v0/./r. When the mean walking time is finite, a universal Gaussian law for the position-PDF of the walker is obtained explicitly.
Poly(ionic liquid)s (PIL) are common precursors for heteroatom-doped carbon materials. Despite a relatively higher carbonization yield, the PIL-to-carbon conversion process faces challenges in preserving morphological and structural motifs on the nanoscale. Assisted by a thin polydopamine coating route and ion exchange, imidazoliumbased PIL nanovesicles were successfully applied in morphology-maintaining carbonization to prepare carbon composite nanocapsules. Extending this strategy further to their composites, we demonstrate the synthesis of carbon composite nanocapsules functionalized with iron nitride nanoparticles of an ultrafine, uniform size of 3-5 nm (termed "FexN@C "). Due to its unique nanostructure, the sulfur-loaded FexN@C electrode was tested to efficiently mitigate the notorious shuttle effect of lithium polysulfides (LiPSs) in Li-S batteries. The cavity of the carbon nanocapsules was spotted to better the loading content of sulfur. The well-dispersed iron nitride nanoparticles effectively catalyze the conversion of LiPSs to Li2S, owing to their high electronic conductivity and strong binding power to LiPSs. Benefiting from this well-crafted composite nanostructure, the constructed FexN@C/S cathode demonstrated a fairly high discharge capacity of 1085 mAh g(-1) at 0.5 C initially, and a remaining value of 930 mAh g(-1 )after 200 cycles. In addition, it exhibits an excellent rate capability with a high initial discharge capacity of 889.8 mAh g(-1) at 2 C. This facile PIL-to-nanocarbon synthetic approach is applicable for the exquisite design of complex hybrid carbon nanostructures with potential use in electrochemical energy storage and conversion.
Li-S battery has been considered as the next-generation energy storage device, which still suffers from the shuttle effect of lithium polysulfides (LiPSs). In this work, mesoporous hollow carbon-coated MnO nanospheres (C@MnO) have been designed and synthesized using spherical polyelectrolyte brushes (SPB) as template, KMnO4 as MnO precursor, and polydopamine as carbon source to improve the electrochemical performance of Li-S battery. The hollow C@MnO nanospheres enable the combination of physical confinement and chemical adsorption of the LiPSs. The thin carbon coating layer can provide good electrical conductivity and additional physical confinement to polysulfides. Moreover, the encapsulated MnO inside the carbon shell exhibits strong chemical adsorption to polysulfides. The constructed C@MnO/S cathode shows the discharge capacity of 1026 mAh g(-1) at 0.1 C with 79% capacity retention after 80 cycles. The synthesized hollow C@MnO nanoparticles can work as highly efficient sulfur host materials, providing an effective solution to suppress the shuttle effect in Li-S battery.
Flood risk management in Germany follows an integrative approach in which both private households and businesses can make an important contribution to reducing flood damage by implementing property-level adaptation measures. While the flood adaptation behavior of private households has already been widely researched, comparatively less attention has been paid to the adaptation strategies of businesses. However, their ability to cope with flood risk plays an important role in the social and economic development of a flood-prone region. Therefore, using quantitative survey data, this study aims to identify different strategies and adaptation drivers of 557 businesses damaged by a riverine flood in 2013 and 104 businesses damaged by pluvial or flash floods between 2014 and 2017. Our results indicate that a low perceived self-efficacy may be an important factor that can reduce the motivation of businesses to adapt to flood risk. Furthermore, property-owners tended to act more proactively than tenants. In addition, high experience with previous flood events and low perceived response costs could strengthen proactive adaptation behavior. These findings should be considered in business-tailored risk communication.
Flood risk management in Germany follows an integrative approach in which both private households and businesses can make an important contribution to reducing flood damage by implementing property-level adaptation measures. While the flood adaptation behavior of private households has already been widely researched, comparatively less attention has been paid to the adaptation strategies of businesses. However, their ability to cope with flood risk plays an important role in the social and economic development of a flood-prone region. Therefore, using quantitative survey data, this study aims to identify different strategies and adaptation drivers of 557 businesses damaged by a riverine flood in 2013 and 104 businesses damaged by pluvial or flash floods between 2014 and 2017. Our results indicate that a low perceived self-efficacy may be an important factor that can reduce the motivation of businesses to adapt to flood risk. Furthermore, property-owners tended to act more proactively than tenants. In addition, high experience with previous flood events and low perceived response costs could strengthen proactive adaptation behavior. These findings should be considered in business-tailored risk communication.
Der Gründungszuschuss wurde 2011 umfassend reformiert. Insgesamt ist das Arbeitsmarktinstrument weiterhin ein Erfolg: Die meisten Geförderten sind auch knapp dreieinhalb Jahre nach der Gründung noch selbstständig. Die Förderung erhöht ihren Arbeitsmarkterfolg und ihre Jobzufriedenheit deutlich, aber bei ihrer sozialen Absicherung besteht Verbesserungsbedarf.
Computer-based analysis of preservice teachers' written reflections could enable educational scholars to design personalized and scalable intervention measures to support reflective writing. Algorithms and technologies in the domain of research related to artificial intelligence have been found to be useful in many tasks related to reflective writing analytics such as classification of text segments. However, mostly shallow learning algorithms have been employed so far. This study explores to what extent deep learning approaches can improve classification performance for segments of written reflections. To do so, a pretrained language model (BERT) was utilized to classify segments of preservice physics teachers' written reflections according to elements in a reflection-supporting model. Since BERT has been found to advance performance in many tasks, it was hypothesized to enhance classification performance for written reflections as well. We also compared the performance of BERT with other deep learning architectures and examined conditions for best performance. We found that BERT outperformed the other deep learning architectures and previously reported performances with shallow learning algorithms for classification of segments of reflective writing. BERT starts to outperform the other models when trained on about 20 to 30% of the training data. Furthermore, attribution analyses for inputs yielded insights into important features for BERT's classification decisions. Our study indicates that pretrained language models such as BERT can boost performance for language-related tasks in educational contexts such as classification.
Science education researchers typically face a trade-off between more quantitatively oriented confirmatory testing of hypotheses, or more qualitatively oriented exploration of novel hypotheses. More recently, open-ended, constructed response items were used to combine both approaches and advance assessment of complex science-related skills and competencies. For example, research in assessing science teachers' noticing and attention to classroom events benefitted from more open-ended response formats because teachers can present their own accounts. Then, open-ended responses are typically analyzed with some form of content analysis. However, language is noisy, ambiguous, and unsegmented and thus open-ended, constructed responses are complex to analyze. Uncovering patterns in these responses would benefit from more principled and systematic analysis tools. Consequently, computer-based methods with the help of machine learning and natural language processing were argued to be promising means to enhance assessment of noticing skills with constructed response formats. In particular, pretrained language models recently advanced the study of linguistic phenomena and thus could well advance assessment of complex constructs through constructed response items. This study examines potentials and challenges of a pretrained language model-based clustering approach to assess preservice physics teachers' attention to classroom events as elicited through open-ended written descriptions. It was examined to what extent the clustering approach could identify meaningful patterns in the constructed responses, and in what ways textual organization of the responses could be analyzed with the clusters. Preservice physics teachers (N = 75) were instructed to describe a standardized, video-recorded teaching situation in physics. The clustering approach was used to group related sentences. Results indicate that the pretrained language model-based clustering approach yields well-interpretable, specific, and robust clusters, which could be mapped to physics-specific and more general contents. Furthermore, the clusters facilitate advanced analysis of the textual organization of the constructed responses. Hence, we argue that machine learning and natural language processing provide science education researchers means to combine exploratory capabilities of qualitative research methods with the systematicity of quantitative methods.
This study investigated the role of medium (face-to-face, cyber) and publicity (public, private) in adolescents' perceptions of severity and coping strategies (i.e., avoidant, ignoring, helplessness, social support seeking, retaliation) for victimization, while accounting for gender and cultural values. There were 3432 adolescents (ages 11-15, 49% girls) in this study; they were from China, Cyprus, the Czech Republic, India, Japan, and the United States. Adolescents completed questionnaires on individualism and collectivism, and ratings of coping strategies and severity for public face-to-face victimization, private face-to-face victimization, public cyber victimization, and private cyber victimization. Findings revealed similarities in adolescents' coping strategies based on perceptions of severity, publicity, and medium for some coping strategies (i.e., social support seeking, retaliation) but differential associations for other coping strategies (i.e., avoidance, helplessness, ignoring). The results of this study are important for prevention and intervention efforts because they underscore the importance of teaching effective coping strategies to adolescents, and to consider how perceptions of severity, publicity, and medium might influence the implementation of these coping strategies.
There has been little research attention given to how Gay-Straight Alliances might mitigate mental health consequences associated with experiencing homophobic cyberbullying. To address this gap in knowledge, the purpose of this one-year longitudinal study was to investigate the moderating effect of perceived social support from Gay-Straight Alliances in the relationships among homophobic cyberbullying victimization and bystanding and depressive and anxiety symptoms among 466 LGBTQIA adolescents (M-age = 15.76; 52% female). The findings revealed that perceived social support was related negatively to homophobic cyberbullying involvement and depressive and anxiety symptoms. Homophobic cyberbullying involvement was related positively to depressive and anxiety symptoms. High perceived social support buffered against the depressive and anxiety symptoms resulting from homophobic victimization and bystanding among LGBTQIA adolescents but low levels and average levels did not moderate these associations. These findings highlight the importance of expanding Gay-Straight Alliances in schools.
The purpose of this study was to examine the longitudinal relationship between problematic online gaming and subjective health complaints and depressive symptoms, and the moderation of console-gaming aggression (i.e. verbal aggression, camping, trolling) in this relationship. Participants were 202 adolescents (86% boys; M age = 12.99 years) in the 7(th) or 8(th) grade who played first-person shooter games. They completed questionnaires on problematic online gaming, console-gaming aggression, subjective health complaints, and depressive symptoms. Six months later (Time 2), they completed questionnaires on subjective health complaints and depressive symptoms again. Findings revealed that problematic online gaming and console-gaming aggression were positive predictors of Time 2 subjective health complaints and depressive symptoms, while controlling for Time 1 levels and gender. Moderating effects were found as well, indicating that high levels of console-gaming aggression increased the positive relationship between problematic online gaming and depressive symptoms. These effects were also replicated for verbal aggression, problematic online gaming, and subjective health complaints. These findings suggest the importance of considering the implications of console-gaming aggression and problematic online gaming for the physical and mental health of adolescents.
IMPACT SUMMARY
Prior State of Knowledge. Problematic online gaming and aggressive behaviors are linked to negative outcomes, including depression and subjective health complaints. Longitudinal research further supports this connection for depression, but not for subjective health complaints or various types of aggression via console games.
Novel Contributions. Few studies have focused on various types of aggression and the longitudinal associations among problematic online gaming, depression, and subjective health complaints, while controlling for previous levels of depression and subjective health complaints. The present research addresses these gaps.
Practical Implications. Findings of the present research has implications for clinicians and researchers concerned with identifying adolescents who might be at risk for negative outcomes.
The purpose of the present study was to investigate the moderating effect of perceived social support from friends in the associations between self-isolation practices during the COVID-19 pandemic and adolescents' mental health (i.e., depression, subjective health complaints, self-harm), measured six months later (Time 2). Participants were 1,567 7(th) and 8(th) graders (51% female; 51% white; M age = 13.67) from the United States. They completed questionnaires on perceived social support from friends, depression, subjective health complaints, and self-harm at Time 1, and self-isolation practices during COVID-19, depression, subjective health complaints, and self-harm at Time 2. The findings revealed that self-isolation practices during COVID-19 was related positively to Time 1 perceived social support from friends, and negatively to Time 2 depression, subjective health complaints, and self-harm, while accounting for Time 1 mental health outcomes. Higher perceived social support from friends at Time 1 buffered against the negative impacts on adolescents' mental health outcomes at Time 2 when they practiced greater self-isolation during COVID-19, while lower perceived social support at Time 1 had the opposite effects on Time 2 mental health outcomes.
Not much is known about how bystanders' emotional reactions after not intervening in cyberbullying might impact their health issues. Narrowing this gap in the literature, the present study focused on examining the moderating effects of emotional reactions (i.e., guilt, sadness, anger) after not intervening in cyberbullying on the longitudinal relationship between cyberbullying bystanding and health issues (i.e., subjective health complaints, suicidal ideation, non-suicidal self-harm). Participants were 1,067 adolescents between 12 and 15 years old included in this study (M-age = 13.67; 51% girls). The findings showed a positive association between Time 1 cyberbullying bystanding and Time 2 health issues. Guilt moderated the positive relationships among Time 1 cyberbullying bystanding, Time 2 subjective health complaints, suicidal ideation, and non-suicidal self-harm. Time 1 sadness also moderated the relationship between Time 1 cyberbullying bystanding and Time 2 suicidal ideation and non-suicidal self-harm. However, anger did not moderate any of the associations.
The purpose of the present study was to investigate the moderating effect of technology use for friendship maintenance in the associations between self-isolation during the COVID-19 pandemic and friendship quality, measured 6 months later (Time 2). Participants were 1,567 seventh and eighth graders (51% female; 51% white; M-age = 13.47) from the United States. They completed questionnaires on friendship quality at Time 1, and self-isolation during COVID-19 and technology use for friendship maintenance and friendship quality at Time 2. The findings revealed that self-isolation during COVID-19 was related positively to technology use for friendship maintenance and negatively to Time 2 friendship quality. Higher technology use for friendship maintenance buffered against the negative impacts on friendship quality associated with self-isolation during COVID-19, while lower technology use had the opposite effects on Time 2 friendship quality.
Purpose
The purpose of this paper is to investigate how learning solely via an assistance system influences work performance compared with learning with a combination of an assistance system and additional training. While the training literature has widely emphasised the positive role of on-the-job training, particularly for groups that are often underrepresented in formalised learning situations, organisational studies have stressed the risks that emerge when holistic process knowledge is lacking and how this negatively affects work performance. This study aims at testing these negative effects within an experimental design.
Design/methodology/approach
This paper uses a laboratory experimental design to investigate how assistance-system-guided learning influences the individuals’ work performance and work satisfaction compared with assistance-system-guided learning combined with theoretical learning of holistic process knowledge. Subjects were divided into two groups and assigned to two different settings. In the first setting, the participants used the assistance systems as an orientation and support tool right at the beginning and learned the production steps exclusively in this way. In the second setting, subjects received an additional 10-min introduction (treatment) at the beginning of the experiment, including detailed information regarding the entire work process.
Findings
This study provides evidence that learners provided with prior process knowledge achieve a better understanding of the work process leading to higher levels of productivity, quality and work satisfaction. At the same time, the authors found evidence for differences among workers’ ability to process and apply this additional information. Subjects with lower productivity levels faced more difficulties processing and applying additional process information.
Research limitations/implications
Methodologically, this study goes beyond existing research on assistance systems by using a laboratory experimental design. Though the external validity of this method is limited by the artificial setting, it is a solid way of studying the impact of different usages of digital assistance systems in terms of training. Further research is required, however, including laboratory experiments with larger case numbers, company-level case studies and analyses of survey data, to further confirm the external validity of the findings of this study for the workplace.
Practical implications
This study provides some first evidence that holistic process knowledge, even in low-skill tasks, has an added value for the production process. This study contributes to firms' training policies by exploring new, digitalised ways of guided on-the-job training and demonstrates possible training benefits for people with lower levels of (initial) abilities and motivation.
Social implications
This study indicates the advantage for companies and societies to invest in additional skills and training and points at the limitations of assistance systems. This paper also contributes to training policies by exploring new, digitalised ways of guided on-the-job training and demonstrates possible training benefits for people with lower levels of (initial) abilities and motivation.
Originality/value
This study extends existing research on digital assistance systems by investigating their role in job-related-training. This paper contributes to labour sociology and organisational research by confirming the importance of holistic process knowledge as opposed to a solely task-oriented digital introduction.