bluuebunny/crossref_metadata_2025_split huggingface dataset:
AquaZoom – eine integrative Methode zur Bewertung des Fischzuchtpotenzials entlang österreichischer Fließgewässer
Authors: Seliger Carina , Haslauer Melanie , Schmutz Stefan , Borgwardt Florian 
Published: August 2022

ZusammenfassungWeltweit ist die Aquakultur der am schnellsten wachsende Sektor in der tierischen Lebensmittelproduktion. Dieser Sektor wird voraussichtlich immer wichtiger werden, um den zukünftigen Nahrungsmittelbedarf zu decken. Im Binnenland Österreich ist der Selbstversorgungsgrad von Fisch mit 6 % insgesamt bzw. 48 % bei Süßwasserfischen eher gering. Um ein nachhaltiges Wachstum des Sektors zu ermöglichen und gleichzeitig negative Auswirkungen auf die verwendeten aquatischen Ökosysteme und andere Nutzungen der Ressource Wasser zu vermeiden, wurde ein räumlicher Analyse-Ansatz zur nachhaltigen Zonierung von Forellenzuchtbetrieben, mit einem Schwerpunkt auf Durchflussanlagen, entwickelt. Dabei wurden 17 land- und 17 gewässerbezogene räumliche Kriterien identifiziert und hinsichtlich ihrer Eignung für die Errichtung eines Forellenzuchtbetriebs klassifiziert. Anschließend wurden die Kriterien in einem integrativen GIS-basierten Modellierungsansatz kombiniert, um eine landesweite und räumlich explizite Zonierung von Eignungsgebieten innerhalb Österreichs vorzunehmen. Von insgesamt 8113 Teileinzugsgebieten (TEZG) mit einer mittleren Größe von 10 km2 wurden so 1295 TEZG als geeignet eingestuft. Für diese TEZG wurde eine potenzielle Produktionsmenge an Fisch abgeschätzt. Mit einer mittleren Produktion von 48,7 t pro Standort könnten in Summe 63.088 t Fisch in Durchflussanlagen österreichweit produziert werden. Die Ergebnisse sollen in weiterer Folge in einem Online-Tool zu Verfügung gestellt werden und so die Entscheidungsfindung von Investoren und Behörden unterstützen. Als Schnittstelle zwischen den unterschiedlichen Anwender:innen kann das Tool dazu beitragen, eine nachhaltige Entwicklung der Aquakultur in Österreich voranzutreiben und Konflikte und Fehlinvestitionen frühzeitig zu vermeiden.
Heuristics for a cash-collection routing problem with a cluster-first route-second approach
Authors: Singh Bismark , Oberfichtner Lena , Ivliev Sergey 
Published: August 2022

AbstractMotivated by a routing problem faced by banks to enhance their encashment services in the city of Perm, Russia, we solve versions of the traveling salesman problem (TSP) with clustering. To minimize the risk of theft, suppliers seek to operate multiple vehicles and determine an efficient routing; and, a single vehicle serves a set of locations that forms a cluster. This need to form independent clusters—served by distinct vehicles—allows the use of the so-called cluster-first route-second approach. We are especially interested in the use of heuristics that are easily implementable and understandable by practitioners and require only the use of open-source solvers. To this end, we provide a short survey of 13 such heuristics for solving the TSP, five for clustering the set of locations, and three to determine an optimal number of clusters—all using data from Perm. To demonstrate the practicality and efficiency of the heuristics, we further compare our heuristic solutions against the optimal tours. We then provide statistical guarantees on the quality of our solution. All of our anonymized code is publicly available allowing extensions by practitioners, and serves as a decision-analytic framework for both clustering data and solving a TSP.
Boosting the Scalability of Farm-Level Models: Efficient Surrogate Modeling of Compositional Simulation Output
Authors: Troost Christian , Parussis-Krech Julia , Mejaíl Matías , Berger Thomas 
Published: August 2022

AbstractSurrogate modeling can overcome computational and data-privacy constraints of micro-scale economic models and support their incorporation into large-scale simulations and interactive simulation experiments. We compare four data-driven methods to reproduce the aggregated crop area response simulated by farm-level modeling in response to price variation. We use the isometric log-ratio transformation to accommodate the compositional nature of the output and sequential sampling with stability analysis for efficient model selection. Extreme gradient boosting outperforms multivariate adaptive regressions splines, random forest regression, and classical multinomial-logistic regression and achieves high goodness-of-fit from moderately sized samples. Explicitly including ratio terms between price input variables considerably improved prediction, even for highly automatic machine learning methods that should in principle be able to detect such input variable interaction automatically. The presented methodology provides a solid basis for the use of surrogate modeling to support the incorporation of micro-scale models into large-scale integrated simulations and interactive simulation experiments with stakeholders.
Developing College students’ computational thinking multidimensional test based on Life Story situations
Authors: Kang Chunhua , Liu Na , Zhu Yinrui , Li Feiming , Zeng Pingfei 
Published: August 2022

AbstractAt present, research on computational thinking in universities is gaining interest, and more attention is being paid to the cultivation and teaching of computational thinking. However, there is a lack of computational thinking assessment tools for college students, which makes it difficult to understand the current status and development of their computational thinking. In this study, computational thinking is regarded as the ability to solve practical problems. By analyzing the relevant literature, we identified five dimensions of computational thinking – decomposition, generalization, abstraction, algorithm and evaluation – and described their operational definitions. Referring to the Bebras and the problem situations in Google computational thinking education, we set up a life-based situation that college students are familiar with. Based on the life story situation, we developed a multidimensional assessment for college students’ computational thinking. This assessment tool contains 14 items, all of which are multiple-choice questions, and the structure and quality of the tool are verified by multidimensional item response theory. The results show that the assessment tool has good internal validity and can discriminate different disciplines of college students. The college students’ computational thinking test developed in this study can be used as an effective tool to assess college students’ computational thinking.
Towards 3D characterisation of site-controlled InGaAs pyramidal QDs at the nanoscale
Authors: Holsgrove Kristina M. , O’Reilly Tamsin I. , Varo Simone , Gocalinska Agnieszka , Juska Gediminas , Kepaptsoglou Demie M. , Pelucchi Emanuele , Arredondo Miryam 
Published: August 2022

AbstractIn this work, we report an extensive investigation via transmission electron microscopy (TEM) techniques of InGaAs/GaAs pyramidal quantum dots (PQDs), a unique site-controlled family of quantum emitters that have proven to be excellent sources of single and entangled photons. The most striking features of this system, originating from their peculiar fabrication process, include their inherently 3-dimensional nature and their interconnection to a series of nanostructures that are formed alongside them, such as quantum wells and quantum wires. We present structural and chemical data from cross-sectional and plan view samples of both single and stacked PQDs structures. Our findings identify (i) the shape of the dot, being hexagonal and not triangular as previously assumed, (ii) the chemical distribution at the facets and QD area, displaying clear Indium diffusion, and (iii) a near absence of Aluminium (from the AlAs marker) at the bottom of the growth profile. Our results shed light on previously unreported structural and chemical features of PQDs, which is of extreme relevance for further development of this family of quantum emitters.
Graphical abstract
Discriminative and Affective Processing of Touch: Associations with Severity of Skin-picking
Authors: Schienle Anne , Wabnegger Albert 
Published: August 2022

AbstractSkin-picking is a common behavior in the general population that generally serves emotion regulation (e.g., reduction of tension). However, recent research suggests it may also be associated with changes in tactile processing sensitivity. Along these lines, the present study examined whether the severity of skin-picking (SOSP) is related to discriminative and affective touch processing. A total of 160 participants (59 males, 101 females, mean age = 31 years) completed two tactile discrimination tests (two-point discrimination, surface texture discrimination), as well as a well-validated affective touch paradigm (delivery of soft/slow touch, which is found to be generally pleasant). A hierarchical regression analysis was carried out to investigate the association between SOSP, age, sex, and indicators of tactile sensitivity. Replicating previous findings, females reported higher SOSP. While the performance in the discrimination tests did not predict SOSP, affective touch processing was associated with SOSP. Participants with high SOSP reported an urge to pick their skin after being softly touched. This seems paradoxical since previous findings have suggested skin-picking may be carried out to manage negative affective states. Our findings add to the literature describing altered sensitivity and responsivity to specific tactile stimuli in individuals with excessive skin-picking.
Thinking Thru Making: Mapping Computational Thinking Practices onto Scientific Reasoning
Authors: Tofel-Grehl Colby , Searle Kristin A. , Ball Douglas 
Published: August 2022

AbstractThis paper shares findings from a teacher designed physics and computing unit that engaged students in learning physics and computing concurrently thru inquiry. Using scientific inquiry skills and practices, students were tasked with assessing the validity of local rollercoaster g-force ratings as posted to the public. Students used computational electronic textile circuits (e-textiles) to engage in “myth busting” amusement park g-force ratings. In doing so, students engaged computing and computational thinking skills in service to answering their scientific inquiry. Findings from this study indicate that physics classes are ideal spaces for engaging in computing’s Big Ideas as laid out by Grover and Pea (Educational Researcher 42, 38–43, 2013) as well as the pillars of computational thinking (Wing, Communications of the ACM 49, 33–35, 2006). However, essential to this dual engagement is a need for computing content to act in service to the better acquisition of physics content within the physics classroom space. Findings indicate that the teachers’ use of e-textiles to integrate physics and computing broadened and deepened student learning by providing affordances for computational thinking within the structure of physical science inquiry.
Soil, climate, and variety impact on quantity and quality of maize root mucilage exudation
Authors: Nazari Meisam , Bilyera Nataliya , Banfield Callum C. , Mason-Jones Kyle , Zarebanadkouki Mohsen , Munene Rosepiah , Dippold Michaela A. 
Published: August 2022

Abstract
Aims
This study investigated the influence of climate and soil on the exudation rate and polysaccharide composition of aerial nodal root mucilage from drought-resistant and drought-susceptible maize varieties.

Methods
Two maize varieties were grown in two different soils (sandy-clay loam Acrisol and loam Luvisol) under simulated climatic conditions of their agroecological zones of origin in Kenya and Germany. The exudation rate of mucilage from the aerial nodal roots was quantified as dry weight per root tip per day and the mucilage was characterized for its polysaccharide composition.

Results
On average, the mucilage exudation rate was 35.8% higher under the Kenyan semi-arid tropical than under the German humid temperate climatic conditions. However, cultivation in the loam Luvisol soil from Germany led to 73.7% higher mucilage exudation rate than cultivation in the sandy-clay loam Acrisol soil from Kenya, plausibly due to its higher microbial biomass and nutrient availability. The drought-resistant Kenyan maize variety exuded 58.2% more mucilage than the drought-susceptible German variety. On average, mucilage polysaccharides were composed of 40.6% galactose, 26.2% fucose, 13.1% mannose, 11% arabinose, 3.5% glucose, 3.2% xylose, 1.3% glucuronic acid, and 1% an unknown uronic acid. Overall, significantly higher proportions of the uronic acids were found in the mucilage of the plants grown in the Kenyan sandy-clay loam soil and under the Kenyan semi-arid tropical climatic conditions.

Conclusions
Maize is able to enhance its mucilage exudation rate under warm climatic conditions and in soils of high microbial activity to mitigate water stress and support the rhizosphere microbiome, respectively.

Graphical abstract
Code Ethnography and the Materiality of Power in Internet Governance
Authors: Rosa Fernanda R. 
Published: August 2022

AbstractThe purpose of this article is to discuss an ethnography of code, specifically code ethnography, a method for examining code as a socio-technical actor, considering its social, political, and economic dynamics in the context of digital infrastructures. While it can be applied to any code, the article presents the results of code ethnography application in the study of internet interconnection dynamics, having the Border Gateway Protocol (BGP) as code and two of the largest internet exchange points (IXPs) in the world as points of data collection, DE-CIX Frankfurt, and IX.br São Paulo. The results show inequalities in the flows of information between the global North and the global South and concentration of power at the level of interconnection infrastructure hitherto unknown in the context of the political economy of the internet. Code ethnography is explained in terms of code assemblage, code literacy, and code materiality. It demonstrates the grammar of BGP in context, making its logical and physical dimensions visible in the analysis of the formation ofgiant internet nodesandinfrastructural interdependenciesin the circulation information infrastructure of the internet.
Risk information, investor learning, and informational feedback
Authors: Smith Kevin 
Published: August 2022

AbstractThis paper studies how public information regarding a firm’s riskiness affects investors’ incentives to acquire information about the firm and the firm’s ability to learn decision-useful information from its price. I find that risk information complements investor learning by informing investors of when it is most lucrative to investigate the firm, thereby reducing liquidity. Furthermore, risk information causes the firm’s price to contain more information when the firm’s investment decisions have the greatest impact on its value, thereby improving real efficiency. Extensions of the model suggest that the impact of risk information on real efficiency may deteriorate when the firm’s manager is excessively exposed to idiosyncratic risk, when the firm’s shareholders are excessively averse to such risk, or when the disclosure concerns a “downside risk.” In sum, my analysis suggests that information regarding firms’ expected values and information regarding firms’ risks significantly differ in their effects on the capital market.
A new improved maximal relevance and minimal redundancy method based on feature subset
Authors: Xie Shanshan , Zhang Yan , Lv Danjv , Chen Xu , Lu Jing , Liu Jiang 
Published: August 2022

AbstractFeature selection plays a very significant role for the success of pattern recognition and data mining. Based on the maximal relevance and minimal redundancy (mRMR) method, combined with feature subset, this paper proposes an improved maximal relevance and minimal redundancy (ImRMR) feature selection method based on feature subset. In ImRMR, the Pearson correlation coefficient and mutual information are first used to measure the relevance of a single feature to the sample category, and a factor is introduced to adjust the weights of the two measurement criteria. And an equal grouping method is exploited to generate candidate feature subsets according to the ranking features. Then, the relevance and redundancy of candidate feature subsets are calculated and the ordered sequence of these feature subsets is gained by incremental search method. Finally, the final optimal feature subset is obtained from these feature subsets by combining the sequence forward search method and the classification learning algorithm. Experiments are conducted on seven datasets. The results show that ImRMR can effectively remove irrelevant and redundant features, which can not only reduce the dimension of sample features and time of model training and prediction, but also improve the classification performance.
Quality Control Metrics to Assess MoS2 Sputtered Films for Tribological Applications
Authors: Babuska Tomas F. , Curry John F. , Dugger Michael T. , Jones Morgan R. , DelRio Frank W. , Lu Ping , Xin Yan , Grejtak Tomas , Chrostowski Robert , Mangolini Filippo , Strandwitz Nicholas C. , Chowdhury Md Istiaque , Doll Gary L. , Krick Brandon A. 
Published: August 2022

AbstractPure molybdenum disulfide (MoS2) solid lubricant coatings could attain densities comparable to doped films (and the associated benefits to wear rate and environmental stability) through manipulation of the microstructure via deposition parameters. Unfortunately, pure films can exhibit highly variable microstructures and mechanical properties due to processes that are not controlled during deposition (i.e., batch-to-batch variation). This work focuses on developing a relationship between density, hardness, friction, and wear for pure sputtered MoS2 coatings. Results show that dense films (ρ = 4.5 g/cm3) exhibit a 100 × lower wear rate compared to porous coatings (ρ = 3.04–3.55 g/cm3). The tribological performance of high density pure MoS2 coatings is shown to surpass that of established composite coatings, achieving a wear rate 2 × (k = 5.74 × 10–8 mm3/Nm) lower than composite MoS2/Sb2O3/Au in inert environments.
Mesh selection strategies of the code TOM for Boundary Value Problems
Authors: Mazzia Francesca 
Published: August 2022

AbstractThis paper presents new hybrid mesh selection strategies for boundary value problems implemented in the code TOM. Originally the code was proposed for the numerical solution of stiff or singularly perturbed problems. The code has been now improved with the introduction of three classes of mesh selection strategies, that can be used for different categories of problems. Numerical experiments show that the mesh selection and, in the nonlinear case, the strategy for solving the nonlinear equations are determinant for the good behaviour of a general purpose code. The possibility to choose the mesh selection should be considered for all general purposes codes to make them suitable for wider classes of problems.
All is not lost that is delayed: overconfidence and investment outcomes
Authors: Betzer André , van den Bongard Inga , Schweder Felix , Theissen Erik , Volkmann Christine 
Published: August 2022

AbstractWe use a unique panel data set of private German firms to analyze the relation between managerial overconfidence and investment policy in small and medium-sized firms. We find that overconfident managers invest more, and that this relation is driven by expansion investments. When considering the outcome of investment projects, we find that projects initiated by overconfident managers are less likely to be completed as planned. When we differentiate between three types of non-completion (downsizing, delaying, and abandoning), we find that overconfident managers are more likely to delay, rather than to abandon or downsize a project.
Masculinity, Perceived Vulnerability to COVID-19, and Adoption of Protective Behaviors
Authors: Roccato Michele , Pacilli Maria Giuseppina , Orlando Giovanni , Russo Silvia 
Published: August 2022

AbstractEpidemiological data show that men and women have similar probabilities of contracting COVID-19. However, men with COVID-19 tend to have more severe outcomes than women. We performed two studies to analyze the associations between gender, adherence to traditional masculinity ideology, perceived vulnerability to COVID-19, and the adoption of protective behaviors against COVID-19. In Study 1 (quota sample of the Italian adult population,N = 1,142), we found no differences between men and women in terms of the perceived probability of contracting COVID-19. However, compared to women, men perceived themselves to be less likely to suffer severe consequences if falling ill. In Study 2 (Italian community sample,N = 305), a moderated mediation model showed that adherence to traditional masculinity ideology moderated the association between being man and the perceived severity of the consequences of COVID-19, which, in turn, showed negative associations with three protective behaviors against COVID-19. The article ends with a discussion of the strengths and limitations of this research.
Review on Metallization Approaches for High-Efficiency Silicon Heterojunction Solar Cells
Authors: Zeng Yulian , Peng Chen-Wei , Hong Wei , Wang Shan , Yu Cao , Zou Shuai , Su Xiaodong 
Published: August 2022

AbstractCrystalline silicon (c-Si) heterojunction (HJT) solar cells are one of the promising technologies for next-generation industrial high-efficiency silicon solar cells, and many efforts in transferring this technology to high-volume manufacturing in the photovoltaic (PV) industry are currently ongoing. Metallization is of vital importance to the PV performance and long-term reliability of HJT solar cells. In this review, we summarize the development status of metallization approaches for high-efficiency HJT solar cells. For conventional screen printing technology, to avoid the degradation of the passivation properties of the amorphous silicon layer, a low-temperature-cured (< 250 ℃) paste and process are needed. This process, in turn, leads to high line/contact resistances and high paste costs. To improve the conductivity of electrodes and reduce the metallization cost, multi-busbar, fine-line printing, and low-temperature-cured silver-coated copper pastes have been developed. In addition, several potential metallization technologies for HJT solar cells, such as the Smart Wire Contacting Technology, pattern transfer printing, inkjet/FlexTrailprinting, and copper electroplating, are discussed in detail. Based on the summary, the potential and challenges of these metallization technologies for HJT solar cells are analyzed.
Vom Ein- zum Vielzeller — Cyanobakterien als Modellsystem
Authors: Taubenheim Claudia , Hammerschmidt Katrin 
Published: August 2022

AbstractThe evolution of multicellularity is an example of an evolutionary transition in individuality (ETI). As in other ETIs, independent units form new reproducing entities — the first step en route to higher complexity. How and why this happens, is not clear. Using cyanobacteria, we study the ETI to multicellularity by combining experimental evolution, phylogenetics, and theory. Our results feature phenotypic plasticity and (functional) differentiation of single cells as a first step of an ETI.