bluuebunny/crossref_metadata_2025_split huggingface dataset:
Falsch informiert?! Die (Fehl‑)Einschätzungen der Bevölkerung über die Wirkungen eines Tempolimits auf deutschen Autobahnen
Authors: Maltritz Dominik 
Published: July 2024

ZusammenfassungBasierend auf einer repräsentativen Befragung untersuchen wir die Informiertheit der Bevölkerung über die Wirkungen einer allgemeinen Geschwindigkeitsbeschränkung auf deutschen Autobahnen hinsichtlich der möglichen Reduktion des CO2-Ausstoßes im Verkehrssektor einerseits und der Vermeidung von Opfern tödlicher Verkehrsunfälle andererseits. Im Rahmen einer ökonomischen Analyse der Wirkungen eines Tempolimits müssen neben positiven Wirkungen auch dessen negativen Konsequenzen betrachtet werden. Wir stellen daher im ersten Teil des Papiers die Ergebnisse der wissenschaftlichen Literatur hinsichtlich der wichtigsten positiven und negativen Konsequenzen überblicksartig dar.Die Ergebnisse der Befragung zeigen, dass die Bevölkerung sehr schlecht über die Wirkungen eines Tempolimits informiert ist. Deutlich weniger als die Hälfte der Befragten fühlt sich überhaupt in der Lage, eine Antwort zu geben. Die Teilnehmer der Befragung, die eine Antwort geben, überschätzen die tatsächlichen positiven Wirkungen, wie sie nach der wissenschaftlichen Literatur zu erwarten sind, im Mittel um ein Vielfaches. Hierbei sind die Einschätzungen der Wirksamkeit, und damit auch die Fehleinschätzungen, unter den Befürwortern deutlich höher als unter den Gegnern, bei denen ein Großteil Antworten in der richtigen Größenordnung gibt.Die Einschätzung der Wirksamkeit hat dabei einen deutlich ausgeprägten Zusammenhang zur Befürwortung bzw. Ablehnung eines Tempolimits. Geht man von einem kausalen Einfluss der Einschätzung der Wirksamkeit auf die Präferenzen aus, deuten unsere Ergebnisse darauf hin, dass die Bevölkerung ein Tempolimit mehrheitlich ablehnen würde, wenn die Menschen die positiven Wirkungen ungefähr entsprechend den Ergebnissen der wissenschaftlichen Literatur einschätzen würden.
Network embedding based on DepDist contraction
Authors: Dopater Emanuel , Ochodkova Eliska , Kudelka Milos 
Published: July 2024

AbstractNetworks provide an understandable and, in the case of small size, visualizable representation of data, which allows us to obtain essential information about the relationships between pairs of nodes, e.g., their distances. In visualization, networks have an alternative two-dimensional vector representation to which various machine-learning methods can be applied. More generally, networks can be transformed into a low-dimensional space using so-called embedding methods, which bridge the gap between network analysis and traditional machine learning by creating numerical representations that capture the essence of the network structure. In this article, we present a new embedding method that uses non-symmetric dependency to find the distance between nodes and applies an iterative procedure to find a satisfactory distribution of nodes in space. For dimension 2 and the visualization of the result, we demonstrate the method’s effectiveness on small networks. For higher dimensions and several larger networks, we present the results of two experiments comparing our results with two well-established methods in the research community, namely node2vec and DeepWalk. The first experiment focuses on a qualitative comparison of the methods, while the second focuses on applying and comparing the classification results to embeddings in a higher dimension. Although the presented method does not outperform the two chosen methods, its results are still comparable. Therefore, we also explain the limitations of our method and a possible way to overcome them.
Soft Margin Spectral Normalization for GANs
Authors: Rogachev Alexander , Ratnikov Fedor 
Published: July 2024

AbstractIn this paper, we explore the use of Generative Adversarial Networks (GANs) to speed up the simulation process while ensuring that the generated results are consistent in terms of physics metrics. Our main focus is the application of spectral normalization for GANs to generate electromagnetic calorimeter (ECAL) response data, which is a crucial component of the LHCb. We propose an approach that allows to balance between model’s capacity and stability during training procedure, compare it with previously published ones and study the relationship between proposed method’s hyperparameters and quality of generated objects. We show that the tuning of normalization method’s hyperparameters boosts the quality of generative model.
An Anger-based Approach-Avoidance Modification Training Targeting Dysfunctional Beliefs in Adults with Elevated Stress – Results from a Randomized Controlled Pilot Study
Authors: Keinert Marie , Schindler-Gmelch Lena , Eskofier Bjoern M. , Berking Matthias 
Published: July 2024

AbstractWe examined the feasibility, acceptability, and clinical potential of a smartphone-based Approach-Avoidance Modification Training (AAMT) that required users to deliberately display anger and positive emotions (AAMT-AP) to move (dys-)functional stress-related beliefs away from and towards themselves, respectively. The per protocol sample consisted of N = 30 participants randomized to an AAMT-AP condition, a swipe control condition, or an inactive control condition. Feasibility and acceptability of the intervention and study design were assessed directly and changes in clinical outcomes (perceived stress (primary outcome), dysfunctional beliefs, symptoms of depression, and emotion regulation skills) one week after intervention completion. The results indicated that AAMT-AP was feasible and acceptable to participants. Moreover, notable effect sizes for clinical outcomes in comparison with both control conditions provided preliminary evidence for its therapeutic potential. Future research should evaluate the efficacy of AAMT-AP in sufficiently powered randomized controlled trials.
A survey of multi-population optimization algorithms for tracking the moving optimum in dynamic environments
Authors: Yazdani Delaram , Yazdani Danial , Blanco-Davis Eduardo , Nguyen Trung Thanh 
Published: July 2024

AbstractThe solution spaces of many real-world optimization problems change over time. Such problems are called dynamic optimization problems (DOPs), which pose unique challenges that necessitate adaptive strategies from optimization algorithms to maintain optimal performance and responsiveness to environmental changes. Tracking the moving optimum (TMO) is an important class of DOPs where the goal is to identify and deploy the best-found solution in each environments Multi-population dynamic optimization algorithms are particularly effective at solving TMOs due to their flexible structures and potential for adaptability. These algorithms are usually complex methods that are built by assembling multiple components, each of which is responsible for addressing a specific challenge or improving the tracking performance in response to changes. This survey provides an in-depth review of multi-population dynamic optimization algorithms, focusing on describing these algorithms as a set of multiple cooperating components, the synergy between these components, and their collective effectiveness and/or efficiency in addressing the challenges of TMOs. Additionally, this survey reviews benchmarking practices within this domain and outlines promising directions for future research.
Schreibflüssigkeit fördern in der Grundschule – Wirksamkeit eines Trainingsprogramms
Authors: Stephany Sabine , Griepentrog Anne , Koch Alina Marlene , Becker-Mrotzek Michael 
Published: July 2024

ZusammenfassungTexte schreiben zu können gehört zu den Schlüsselkompetenzen in unserer Gesellschaft. Eine wesentliche Voraussetzung für eine entwickelte Schreibfähigkeit ist das mühelose Beherrschen der basalen Schreibfertigkeiten, insbesondere der Schreibflüssigkeit. Flüssiges Schreiben wird jedoch nicht von allen Schülerinnen und Schülern in der Grundschule in ausreichendem Maße beherrscht. Schreibflüssigkeit setzt sich aus zwei Teilprozessen zusammen: dem automatisierten Verschriften von Buchstaben, Wörtern und grammatikalisch korrekten Sätzen und dem zügigen Formulieren kohärenter sprachlicher Einheiten. Sind diese Fertigkeiten noch nicht automatisiert, stehen nicht genügend kognitive Ressourcen für hierarchiehohe Schreibprozesse zur Verfügung, wie das Planen des Textes. Unflüssiges Schreiben wirkt sich daher negativ auf die Textqualität aus. Trotz ihrer Relevanz steht die Schreibflüssigkeit bisher kaum im Fokus von schreibdidaktischer Forschung und Unterrichtspraxis. Es gibt kaum empirisch erprobte Förderkonzepte. Daher wurde ein Schreibflüssigkeitstraining entwickelt, das aus 18 Einheiten à 15 min bestand und in einem Prä-Post-Kontrollgruppendesign mit 469 Grundschülerinnen und Grundschülern durchgeführt wurde. Die Transkriptionsflüssigkeit wurde auf Buchstaben‑, Wort- und Satzebene gemessen. Die Formulierungsflüssigkeit wurde mit digitalen Smart-Pens in Form von Bursts erhoben. Zusätzlich wurde die Schreibkompetenz erfasst. Die Ergebnisse zeigen positive Effekte für die Transkriptionsflüssigkeit und die Schreibkompetenz. Der Beitrag gibt einen Einblick in das Training und berichtet die Effekte auf die Schreibflüssigkeit und die Schreibkompetenz. Darüber hinaus werden die Ergebnisse für verschiedene Untergruppen diskutiert.
Quantum state reconstruction in a noisy environment via deep learning
Authors: Morgillo Angela Rosy , Mangini Stefano , Piastra Marco , Macchiavello Chiara 
Published: July 2024

AbstractQuantum noise is currently limiting efficient quantum information processing and computation, impacting on the fidelity and reliability of quantum states. In this work, we consider the tasks of reconstructing and classifying quantum states corrupted by the action of an unknown noisy channel using classical feed-forward neural networks. By framing reconstruction as a regression problem, we show how such an approach can be used to recover with fidelities exceeding 99% the noiseless density matrices of quantum states of up to three qubits undergoing noisy evolution, and we test its performance with both single-qubit (bit-flip, phase-flip, depolarizing, and amplitude damping) and two-qubit quantum channels (correlated amplitude damping). Furthermore, a critical aspect of our investigation involves also a comprehensive comparison between mean squared error and infidelity as loss functions. Our findings reveal that these two metrics yield comparable results in the context of state reconstruction. Moreover, we also consider the task of distinguishing between different quantum noisy channels, and show how a neural network-based classifier is able to solve such a classification problem with perfect accuracy.
Material Characterisation of Deflated Structured Fabrics
Authors: Rustighi E. , Gardonio P. , Baldini S. , Malacarne C. , Perini M. 
Published: July 2024

AbstractStructured fabrics are made by interwoven rigid elements that form flexible garments such as chain mail armours. Traditionally, the mechanical properties of these materials were considered fixed. However, recent research has revealed their mechanical properties may be varied. Notably, studies have demonstrated that applying vacuum pressure between layers of 3D-printed chain mails enclosed in a bag induces particle and layer jamming of the elements, thereby affecting the material’s bending modulus. This arises from both compressive frictional forces and the complex geometrical interlocking of the rigid elements. This paper presents a comprehensive set of experimental tests for the characterisation of the stiffness and damping properties with respect to the type and number of fabrics and with respect to the vacuum pressure. More specifically, the study examines experimentally the changes in static properties in response to vacuum pressure changes evaluated on a four- and six-point bending setups. The outcome of this measurement campaign is then reported into the Ashby diagrams to compare the mechanical properties of the in-vacuum structured fabrics with those of classical materials. The potential applications of this research include the development of lightweight adaptive and semi-active vibration mitigation devices.
Early Season Wheat Response to Electrochemically Precipitated Struvite in Various Soils in the Greenhouse
Authors: Simms Tatum , Brye Kristofor R. , Roberts Trenton L. , Greenlee Lauren F. 
Published: July 2024

AbstractFertilizer-phosphorus (P) materials can be recovered from wastewater and used to supplement mined phosphate rock, where one such material is struvite [MgNH4PO4·6(H2O)]. This study aimed to compare electrochemically precipitated struvite (ECST) reclaimed from synthetic wastewater to other commercial fertilizer-P sources in cultivated soils from Arkansas [silty clay loam (AR-SiCL) and silt loam (AR-SiL)], Missouri [(silt loam; MO-SiL 1 and 2)], and Nebraska [silt loam (NE-SiL) and sandy loam (NE-SL)]. A greenhouse pot study was conducted for 60 days with unvernalized wheat (Triticum aestivum) using five fertilizer-P sources [ECST, chemically precipitated struvite (CPST), monoammonium phosphate (MAP), triple superphosphate (TSP), and an unamended control (UC)] to evaluate treatment effects on below (BG)- and aboveground (ABG) and total dry matter (DM) and tissue-N, -P, -K, -Ca, -Mg, and -Fe uptakes. The ECST treatment produced 44 g m−2 larger ABG-DM than CPST in the AR-SiCL, but 181 g m−2 larger than the UC in the MO-SiL 1. The ECST had similar or larger nutrient uptakes than CPST, MAP, TSP, and UC. Belowground-P, -N, and -Mg uptakes for ECST were generally similar for all soil-fertilizer-P source combinations, where ECST was 0.3 to 2.6 g m−2 larger than all other fertilizer-P sources. Plant property response from ECST was generally similar to or greater than CPST, MAP, TSP, and the UC across all soils. Results suggest that ECST is a prime candidate to be used as an effective, alternative fertilizer-P source, suitable for use in wheat production across multiple soil textures.
Algal-biochar and Chlorella vulgaris microalgae: a sustainable approach for textile wastewater treatment and biodiesel production
Authors: Rehman Rabia , Iqbal Javed , Ur Rehman Muhammad Saif , Hamid Shanawar , Wang Yuze , Rasool Kashif , Fazal Tahir 
Published: July 2024

AbstractMicroalgae technology is a viable solution for environmental conservation (carbon capture and wastewater treatment) and energy production. However, the nutrient cost, slow-kinetics, and low biosorption capacity of microalgae hindered its application. To overcome them, algal-biochar (BC) can be integrated with microalgae to treat textile wastewater (TWW) due to its low cost, its ability to rapidly adsorb pollutants, and its ability to serve as a nutrient source for microalgal-growth to capture CO2 and biodiesel production. Chlorella vulgaris (CV) and algal-BC were combined in this work to assess microalgal growth, carbon capture, TWW bioremediation, and biodiesel production. Results showed the highest optical density (3.70 ± 0.07 OD680), biomass productivity (42.31 ± 0.50 mg L−1 d−1), and dry weight biomass production (255.11 ± 6.01 mg L−1) in an integrated system of CV-BC-TWW by capturing atmospheric CO2 (77.57 ± 2.52 mg L−1 d−1). More than 99% bioremediation (removal of MB-pollutant, COD, nitrates, and phosphates) of TWW was achieved in CV-BC-TWW system due to biosorption and biodegradation processes. The addition of algal-BC and CV microalgae to TWW not only enhanced the algal growth but also increased the bioremediation of TWW and biodiesel content. The highest fatty acid methylesters (biodiesel) were also produced, up to 76.79 ± 2.01 mg g−1 from CV-BC-TWW cultivated-biomass. Biodiesel’s oxidative stability and low-temperature characteristics are enhanced by the presence of palmitoleic (C16:1) and linolenic (C18:3) acids. Hence, this study revealed that the integration of algal-biochar, as a biosorbent and source of nutrients, with living-microalgae offers an efficient, economical, and sustainable approach for microalgae growth, CO2 fixation, TWW treatment, and biodiesel production.
Graphical Abstract
Sustainability agency in unsustainable structures: rhetoric of a capable transformative individual
Authors: Salovaara Janne J. , Hagolani-Albov Sophia E. 
Published: July 2024

AbstractWhile sustainability as a practice has been implemented in education for a long time, the conceptualisation of an impactful sustainability actor has not been as thoroughly formulated. The theory of structuration is relevant as a lens for critical reflection on the transformative potential of individuals educated in sustainability as a practice, who are often described as change-makers and mandated to enact sustainability. This paper examines sustainability agency using materials produced for a set of online sustainability courses. This text corpus is utilised as a representation of climate and sustainability education. The materials repeat systemic framings present in sustainability rhetoric, such as the contexts and targets in which sustainability transformation occurs. Additionally, through a qualitative content analysis of the textual corpus descriptions emerged as attributes of the agents to enact sustainability. This uncovers the juxtaposition between the often-repeated perception that sustainability must be achieved by capable agents and the capacities they possess. Further, our content analysis suggests a rhetorical process of othering within sustainability, for example by positioning “people”—the general population—as the cause of the sustainability crisis, and “us”—the educated—as the solution. Through our findings, the article concludes that when utilising the concept of sustainability agency—be it in theoretical, educational, or practical work—one ought to pay significant attention to the structures wherein the activities take place. The full comprehension of the transformative potential of individual agents ought to include an acknowledgement of the difference between educated capability and capacity—the latter of which necessitates dominance over the structural resources.
Shallow Microtremor Array Survey Using Miniature and Small Arrays: Strategy for Efficient and Feasible Dense Survey
Authors: Cho I. , Nakazawa T. 
Published: July 2024

AbstractWe investigated the applicability of miniature microtremor arrays with a radius of a few meters or less to shallow surveys (up to a few tens of meters). It is shown that the upper limit wavelength normalized by the seismometer separation distance s that is analyzable by a miniature array does not depend on the observation instrument as long as the instrument has a self‐noise level that is sufficiently lower than the microtremor intensities; however, it generally depends on the average S‐wave velocity of the ground. This means that a miniature array is useful at soft‐soil sites but not hard‐soil sites. A statistical study in central Japan showed that the penetration depth by a miniature array with s = 1 m ranges from 6 to 12 m; specifically, the depth exceeds 12 m in one quarter of the cases but remains below 6 m in one quarter of the cases. This large variation is due to the variation in the average S‐wave velocity. A miniature array should thus be used in combination with a larger array with an s value of several meters to 20 m. In urbanized areas with high industrial activity, where the microtremor wavefield is likely isotropic, these arrays can be replaced by a linear array. In environments with extremely low signal‐to‐noise ratios, a less efficient zero‐crossing method should be applied to the larger array. An appropriate observation strategy should be selected for a given geoenvironment. Field examples show that our strategy enables efficient and feasible dense surveys.
Summer Hydrography Conditions at Proglacial Fjord Entrances Along East Greenland
Authors: Rysgaard S. , Mortensen J. , Haxen M. , Gillard L. C. , Risgaard‐Petersen N. 
Published: July 2024

AbstractClimate change is causing widespread melting of land and sea ice in the Arctic, leading to an increase in freshwater input to the ocean. This may have an impact on ocean circulation, marine ecosystems, and biodiversity in the region. Our findings provide new insights into the summer hydrography conditions at proglacial fjord entrances along large parts of the east coast of Greenland. As most freshwater exits the Arctic Ocean through Fram Strait this study focuses on understanding the origin of spatial distribution of temperature and freshwater in the coastal waters in East Greenland. We find that Polar Water and the Atlantic Water variants (Eurasian Basin Atlantic Water/Subpolar Mode Water) dominate coastal waters north and south of Denmark Strait, respectively, and that coastal waters are influenced by advected meltwater from the Arctic Ocean, glacier meltwater and local precipitation. Combining hydrographic observations, water isotope data, and water source fraction analysis, we show that glacier meltwaters can be detected at fjord entrances and down to approximately 200 m. Integrated over the upper 200 m of the water column, glacial meltwater account for approximately 9%, precipitation for around 8% and Polar Water (including sea ice melt) for approximately 83% of the freshwater observed along the East Greenland coast. Below 200 m, Atlantic Water variants dominate the entire coastal section. The freshwater along East Greenland stays close to the coast and we could not detect any glacier meltwater at the slope.
Mechanisms of Suprapermafrost Groundwater Recharge Streamflow in Alpine Permafrost Regions: Insights From Young Water Fraction Analysis
Authors: Du Fa , Li Zongxing , Gui Juan , Zhang Baijuan , Xue Jian , Zhou Huiling 
Published: July 2024

AbstractThis study investigates the temporal processes of suprapermafrost groundwater (SPG)‐supplied streamflow in alpine permafrost regions, aiming to fill the gap in understanding this process from a water‐age perspective. Precipitation, streamflow, and SPG samples were collected from the Three‐Rivers Headwaters Region (TRHR). We defined the physical meaning of Fyw (the young water fraction) of the SPG and calculated it for the first time. The results showed that in the TRHR, the SPG mean travel time (MTT) was 159 days, and approximately 46.4% of SPG was younger than 77 days, whereas the streamflow MTT was 342 days, and approximately 12.2% of the streamflow was younger than 97 days. The correlation analysis revealed that various climatic factors played dominant roles in the recharge time variations of the SPG‐supplied streamflow within the TRHR. The SPG recharge rate did not significantly affect the streamflow Fyw; however, the thickness of the active layer ultimately controlled the SPG transit time distribution. Regression analysis further demonstrated the nonlinear impact of precipitation, average temperature, and average freezing days on SPG Fyw, which is closely related to seasonal freeze–thaw heat conduction and groundwater heat advection in the active layer. During the initial ablation period, the streamflow was primarily recharged by young SPG, resulting in a short‐tail travel time distribution. Our findings provide valuable insights into runoff generation and concentration processes in permafrost regions and have important implications for water resource management.