bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of Usage Data with the Help of Data Classifications
Authors: Panzner Melina , von Enzberg Sebastian , Meyer Maurice , Dumitrescu Roman 
Published: October 2022

AbstractComprehensive data understanding is a key success driver for data analytics projects. Knowing the characteristics of the data helps a lot in selecting the appropriate data analysis techniques. Especially in data-driven product planning, knowledge about the data is a necessary prerequisite because data of the use phase is very heterogeneous. However, companies often do not have the necessary know-how or time to build up solid data understanding in connection with data analysis. In this paper, we develop a methodology to organize and categorize and thus understand use phase data in a way that makes it accessible to general data analytics workflows, following a design science research approach. We first present a knowledge base that lists typical use phase data from a product planning view. Second, we develop a taxonomy based on standard literature and real data objects, which covers the diversity of the data considered. The taxonomy provides 8 dimensions that support classification of use phase data and allows to capture data characteristics from a data analytics view. Finally, we combine both views by clustering the objects of the knowledge base according to the taxonomy. Each of the resulting clusters covers a typical combination of analytics relevant characteristics occurring in practice. By abstracting from the diversity of use phase data into artifacts with manageable complexity, our approach provides guidance to choose appropriate data analysis and AI techniques.
Potential flood-prone area identification and mapping using GIS-based multi-criteria decision-making and analytical hierarchy process in Dega Damot district, northwestern Ethiopia
Authors: Negese Ajanaw , Worku Dessalegn , Shitaye Alazar , Getnet Haile 
Published: October 2022

AbstractFlood is one of the natural hazards that causes widespread destruction such as huge infrastructural damages, considerable economic losses, and social disturbances across the world in general and in Ethiopia, in particular. Dega Damot is one of the most vulnerable districts in Ethiopia to flood hazards, and no previous studies were undertaken to map flood-prone areas in the district despite flood-prone areas identification and mapping being crucial tasks for the residents and decision-makers to reduce and manage the risk of flood. Hence, this study aimed to identify and map flood-prone areas in Dega Damot district, northwestern Ethiopia, using the integration of Geographic Information System and multi-criteria decision-making method with analytical hierarchy process. Flood-controlling factors such as elevation, slope, flow accumulation, distance from rivers, annual rainfall, drainage density, topographic wetness index, land use and land cover, Normalized Difference Vegetation Index, soil type, and curvature were weighted and overlayed together to achieve the objective of the study. The result shows that about 86.83% of the study area has moderate to very high susceptibility to flooding, and 13.17% of the study area has low susceptibility to flooding. The northeastern and southwestern parts of the study area dominated by low elevation and slope, high drainage density, flow accumulation, topographic wetness index, and cropland land use were found to be more susceptible areas to flood hazards. The final flood susceptibility map generated by the model was found to be consistent with the historical flood events on the ground in the study area, revealing the method’s effectiveness used in the study to identify and map areas susceptible to flood.
Types of Technological Innovation in the Face of Uncertainty
Authors: Chiffi Daniele , Moroni Stefano , Zanetti Luca 
Published: October 2022

Abstract
Technological innovation is almost always investigated from an economic perspective; with few exceptions, the specific technological and social nature of innovation is often ignored. We argue that a novel way to characterise and make sense of different types of technological innovation is to start considering uncertainty. This seems plausible since technological development and innovation almost always occur under conditions of uncertainty. We rely on the distinction between, on the one hand, uncertainty that can be quantified (e.g. probabilistic risk) and, on the other, deep forms of uncertainty that may resist the possibility of being quantified (e.g. severe or fundamental uncertainties). On the basis of these different ingredients of uncertainty in technological innovation, we propose a new taxonomy that reveals the technological nature of innovation. Unlike previous taxonomies employed to handle different types of technological innovations, our taxonomy does not consider the economic value of innovation alone; it is much more oriented towards societal preferences and forms of technological uncertainty. Finally, we investigate the coherence of our proposal with the dual nature of technological artefacts, showing that innovation can be grounded on structural and functional factors and not just on economic ones.
Lattice zonotopes of degree 2
Authors: Beck Matthias , Janssen Ellinor , Jochemko Katharina 
Published: October 2022

AbstractThe Ehrhart polynomial$${\text {ehr}}_P (n)$$

ehr
P

(
n
)

of a lattice polytope P gives the number of integer lattice points in the n-th dilate of P for all integers $$n\ge 0$$

n
≥
0

. The degree of P is defined as the degree of its $$h^*$$

h
∗

-polynomial, a particular transformation of the Ehrhart polynomial with many useful properties which serves as an important tool for classification questions in Ehrhart theory. A zonotope is the Minkowski (pointwise) sum of line segments. We classify all Ehrhart polynomials of lattice zonotopes of degree 2 thereby complementing results of Scott (Bull Aust Math Soc 15(3), 395–399, 1976), Treutlein (J Combin Theory Ser A 117(3), 354–360, 2010), and Henk and Tagami (Eur J Combin 30(1), 70–83, 2009). Our proof is constructive: by considering solid-angles and the lattice width, we provide a characterization of all 3-dimensional zonotopes of degree 2.
Prediction of biomass corrosiveness over different coatings in fluidized bed combustion
Authors: Contreras M. L. , Benito M. , Bahillo A. 
Published: October 2022

AbstractEnergy production in biomass fired boilers is increasing rapidly due to the advantages of CO2 neutrality and renewability, however damaging agents present in biomass composition accelerates power plant components corrosion. This study evaluates the influence of the biomass burned in fluidized bed combustion processes on high-temperature corrosion, by means of thermodynamic equilibrium modelling, considering those reactions occurring between the combustion atmosphere and different protective coatings (isFeAl, isNiAl and isSiCrAl). Fuels composition and operating conditions from a 10 kW BFB boiler were introduced as input data to improve the performance of the model. Representative samples from agricultural waste, industrial wood and forestry wood waste were selected for evaluation. Results showed industrial wood waste as highly damaging for most coatings studied, with high risk of salt stickiness, deposits formation and release of acidic gases. The elevated volatiles percentage together with significant ash content determined might lead to a major ash components release to the gas phase, available to later condense in the metals surfaces. Silication of alkali and deposited alkali chlorides were the dominant corrosion mechanisms observed for most cases. An increase in alloys corrosion resistance was detected through the model when nickel or chromium was present, showing isSiCrAl as the most resistant. However, alloys protection exhibited significant variations depending upon the biomass burned, thus materials selection should consider the compatibility with conditions for its final use. Thermodynamic modelling, based on real conditions and fuels composition, provides a useful tool to identify key factors for protective coatings design when employing new waste fuels.
Self-healing behavior of Ti2AlC at a low oxygen partial pressure
Authors: Yao Boxiang , Li Shibo , Zhang Weiwei , Yu Wenbo , Zhou Yang , Fan Shukai , Bei Guoping 
Published: October 2022

AbstractTi2AlC, a MAX phase ceramic, has an attractive self-healing ability to restore performance via the oxidation-induced crack healing mechanism upon healing at high temperatures in air (high oxygen partial pressures). However, such healing ability to repair damages in vacuum or low oxygen partial pressure conditions remains unknown. Here, we report on the self-healing behavior of Ti2AlC at a low oxygen partial pressure of about 1 Pa. The experimental results showed that the strength recovery depends on both healing temperature and time. After healing at 1400 °C for 1–4 h, the healed samples exhibited the recovered strengths even exceeding the original strength of 375 MPa. The maximum recovered strength of ∼422 MPa was achieved in the healed Ti2AlC sample after healing at 1400 °C for 4 h, about 13% higher than the original strength. Damages were healed by the formed TiCx from the decomposition of Ti2AlC. The decomposition-induced crack healing as a new mechanism in the low oxygen partial pressure condition was disclosed for the MAX ceramics. The present study illustrates that key components made of Ti2AlC can prolong their service life and keep their reliability during use at high temperatures in low oxygen partial pressures.
AI-Assisted Decision-making: a Cognitive Modeling Approach to Infer Latent Reliance Strategies
Authors: Tejeda Heliodoro , Kumar Aakriti , Smyth Padhraic , Steyvers Mark 
Published: October 2022

AbstractAI assistance is readily available to humans in a variety of decision-making applications. In order to fully understand the efficacy of such joint decision-making, it is important to first understand the human’s reliance on AI. However, there is a disconnect between how joint decision-making is studied and how it is practiced in the real world. More often than not, researchers ask humans to provide independent decisions before they are shown AI assistance. This is done to make explicit the influence of AI assistance on the human’s decision. We develop a cognitive model that allows us to infer the latent reliance strategy of humans on AI assistance without asking the human to make an independent decision. We validate the model’s predictions through two behavioral experiments. The first experiment follows a concurrent paradigm where humans are shown AI assistance alongside the decision problem. The second experiment follows a sequential paradigm where humans provide an independent judgment on a decision problem before AI assistance is made available. The model’s predicted reliance strategies closely track the strategies employed by humans in the two experimental paradigms. Our model provides a principled way to infer reliance on AI-assistance and may be used to expand the scope of investigation on human-AI collaboration.
Optimum Auxiliary Fan Location to Control Air Recirculation
Authors: Morla Ramakrishna , Karekal Shivakumar , Godbole Ajit , Tukkaraja Purushotham , Chang Ping 
Published: October 2022

AbstractThis paper presents the optimum auxiliary fan(s) location to control air recirculation in dead-end workings where diesel-powered vehicles operate. Investigations were conducted with various secondary fan locations from the dead-end crosscut with varying the intake air quantities using a 30 m3/s capacity twin 75 kW auxiliary fan and 45 m3/s capacity twin 110 kW auxiliary fan to control air recirculation and DPM. The results showed that if the drive intake airflow rate matches the fan capacity, air recirculation will occur even when the fan is located 10 m away from the crosscut entry. Results also showed that if the intake drive air quantity was greater than or equal to 150% of fan capacity, no recirculation was observed when the twin 75 kW fan location was at least 5 m and the twin 110 kW fan location was at least 10 m away from the dead-end crosscut access.
Supervised learning of sheared distributions using linearized optimal transport
Authors: Khurana Varun , Kannan Harish , Cloninger Alexander , Moosmüller Caroline 
Published: October 2022

AbstractIn this paper we study supervised learning tasks on the space of probability measures. We approach this problem by embedding the space of probability measures into $$L^2$$

L
2

spaces using the optimal transport framework. In the embedding spaces, regular machine learning techniques are used to achieve linear separability. This idea has proved successful in applications and when the classes to be separated are generated by shifts and scalings of a fixed measure. This paper extends the class of elementary transformations suitable for the framework to families of shearings, describing conditions under which two classes of sheared distributions can be linearly separated. We furthermore give necessary bounds on the transformations to achieve a pre-specified separation level, and show how multiple embeddings can be used to allow for larger families of transformations. We demonstrate our results on image classification tasks.
The Growth of Financial Technology in Indonesia: Implications for Terrorism Financing
Authors: Fabe Amparo Pamela , Toledo Joan Andrea , Laksmi Sylvia 
Published: October 2022

AbstractIndonesia has the largest financial technology (FinTech) industry in Southeast Asia: 167 FinTech companies offer payment, lending, personal finance, crypto and blockchain, crowdfunding, Insurtech and point-of-sale (POS) services. Two entities regulate the FinTech industry: Bank Indonesia and Otoritas Jasa Keuangan (OJK). The Indonesian FinTech ecosystem encompasses savings and investments, money transfer and payments, POS, lending and borrowing, accounting, comparison, financial planning, crowdfunding and cryptocurrency. Money transfer and payments take up the highest percentage, currently at 50%, in all FinTech ecosystems with the most digitally active customers. Peer-to-peer lending dominates the Indonesian market. The FinTech subsectors offer financial management, crowdfunding and insurance services. The abuse of this technology in facilitating terrorist financing, the weaknesses of the laws and policies, and the need for reform and remedies are discussed.
Allocation of food resource by experimentally evolved lines of developmental variants of Propylea dissecta: a food exploitation strategy
Authors: Siddiqui Arshi , Omkar  , Mishra Geetanjali 
Published: October 2022

AbstractThe effects of selection on developmental variants have not yet been rigorously investigated on variable prey quantities. We investigated the food exploitation strategy of first (F1) and fifteenth (F15) generation slow and fast developers of Propylea dissecta (Mulsant) in the presence of scarce and abundant quantities of pea aphid, Acyrthosiphon pisum (Harris), and its effect on adult body mass and reproductive attributes. Both selected slow developers and selected fast developers were higher in number than their counter unselected generation on scarce and abundant diets, respectively. Immature survivals of selected slow developers were depressed after the selection process while it was enhanced for selected fast developers on both diet regimes. On both diets, the total developmental duration was longer for selected slow developers and shorter for selected fast developers. Fecundity and percent egg viability were greater in selected fast developers with plentiful prey supply and lower in control slow developers with inadequate prey supply. More adult body mass was found for pre-selected slow developers than selected slow developers on a scarce diet but selected fast developers enhanced their body weight than unselected individuals of fast developers on an abundant diet. The present experimental evolution findings point to the presence and persistence of developmental variations with variability in their developmental and reproductive traits on allocating scarce and abundant prey supplies.
Contribution of coffee plants to carbon sequestration in agroforestry systems of Southwestern Ethiopia
Authors: Niguse Gezahegn , Iticha Birhanu , Kebede Getenet , Chimdi Achalu 
Published: October 2022

AbstractCoffee forests are the most valuable land-use systems that provide multiple benefits such as biodiversity conservation, carbon sequestration and source of income. This study aimed to estimate the carbon stock of coffee agroforestry systems and the contribution of coffee plants (Coffea arabicaL.) to carbon sequestration in the entire coffee agroforestry systems in southwestern Ethiopia. The carbon stock in trees was estimated by field-based measurements and allometric equations, whereas the carbon stocks in litter and soil were determined using field sampling and laboratory analysis. The carbon stocks of the coffee agroforestry systems in the study site ranged from 254.9 t C/ha in the Syzygium-shaded coffee forest to 321.8 t C/ha in the Albizia-shaded coffee forest. The overall mean carbon sequestration in the present coffee agroforestry systems was 287.1 t C/ha. The net carbon sequestered by coffee plants in the agroforestry systems ranged from 18.8 t C/ha in the Syzygium-shaded coffee stratum to 48.5 t C/ha in the Albizia-shaded coffee stratum. This demonstrates that Albizia is the most compatible shade tree for coffee plants. On average, coffee plants contributed 37.5 t C/ha, accounting for approximately 12.8% of the total carbon sequestered in the coffee agroforestry systems. Hence, we recommend coffee forests for all-in-one benefits such as climate change mitigation, sustainable landscape management and income generation.
Three decades of remote sensing subarctic vegetation in northern Russia: A case study in science diplomacy
Authors: Rees W.G. , Tutubalina O.V. , Medvedev A. , Marshall G.J. , Golubeva E.I. , Telnova N. , Zimin M. , Mikhaylykova P. , Terskaia A. , Sklyar E. , Tomaney J.A. 
Published: October 2022

Abstract
The vegetation at and beyond the northern edge of the world’s boreal forest plays an important though imperfectly understood role in the climate system. This is particularly true within Russia, where only a small proportion of the boreal land area has been studied in depth, and little is known about its recent evolution over time. We describe a long-term collaboration between institutions in Russia and the United Kingdom, aimed at developing a better understanding of high-latitude vegetation in Russia using remote sensing methods. The focus of the collaboration has varied over time; in its most recent form, it is concerned with the dynamics of the Russian boreal forest during the 21st century and its relation to climate change. We discuss the support framework within which it has been developed and reflect on its relationship to science diplomacy. We consider the factors that have contributed to the success of a decades-long international collaboration and make recommendations as to how such joint efforts can be encouraged in future.
Attentional bias toward negative stimuli in PTSD: an eye-tracking study
Authors: Veerapa Emilie , Grandgenevre Pierre , Vaiva Guillaume , Duhem Stéphane , Fayoumi Mohamed El , Vinnac Benjamin , Szaffarczyk Sébastien , Wathelet Marielle , Fovet Thomas , D'Hondt Fabien 
Published: October 2022

AbstractBackgroundResearch on biased processing of aversive stimuli in posttraumatic stress disorder (PTSD) has produced inconsistent results between response time (RT) and eye-tracking studies. Recent RT-based results of dot-probe studies showed no attentional bias (AB) for threat while eye-tracking research suggested heightened sustained attention for this information. Here, we used both RT-based and eye-tracking measures to explore the dynamics of AB to negative stimuli in PTSD.MethodsTwenty-three individuals diagnosed with PTSD, 23 trauma-exposed healthy controls, and 23 healthy controls performed an emotional dot-probe task with pairs of negative and neutral scenes presented for either 1 or 2 s. Analyses included eye movements during the presentation of the scenes and RT associated with target localization.ResultsThere was no evidence for an AB toward negative stimuli in PTSD from RT measures. However, the main eye-tracking results revealed that all three groups showed longer dwell times on negative pictures than neutral pictures at 1 s and that this AB was stronger for individuals with PTSD. Moreover, although AB disappeared for the two groups of healthy controls with prolonged exposure, it persisted for individuals with PTSD.ConclusionPTSD is associated with an AB toward negative stimuli, characterized by heightened sustained attention toward negative scenes once detected. This study sheds light on the dynamics of AB to negative stimuli in PTSD and encourages us to consider optimized therapeutic interventions targeting abnormal AB patterns.
The puzzle of ideography
Authors: Morin Olivier 
Published: October 2022

AbstractAn ideography is a general-purpose code made of pictures that do not encode language, which can be used autonomously – not just as a mnemonic prop – to encode information on a broad range of topics. Why are viable ideographies so hard to find? I contend that self-sufficient graphic codes need to be narrowly specialized. Writing systems are only an apparent exception: At their core, they are notations of a spoken language. Even if they also encode nonlinguistic information, they are useless to someone who lacks linguistic competence in the encoded language or a related one. The versatility of writing is thus vicarious: Writing borrows it from spoken language. Why is it so difficult to build a fully generalist graphic code? The most widespread answer points to a learnability problem. We possess specialized cognitive resources for learning spoken language, but lack them for graphic codes. I argue in favor of a different account: What is difficult about graphic codes is not so much learning or teaching them as getting every user to learn and teach the same code. This standardization problem does not affect spoken or signed languages as much. Those are based on cheap and transient signals, allowing for easy online repairing of miscommunication, and require face-to-face interactions where the advantages of common ground are maximized. Graphic codes lack these advantages, which makes them smaller in size and more specialized.
Three quarters of a century of phonetic research on common Danish stød
Authors: Grønnum Nina 
Published: October 2022

AbstractDespite many attempts, we do not yet know how to answer the question exhaustively and adequately: What is common Danish stød phonetically? Specifically, is there an underlying physiological constancy behind the considerable acoustic variability? And is there a common denominator to the different acoustic manifestations that might explain their perceptual equivalence? Systematic acoustic, physiological, and perceptual investigations of common Danish stød now span (a little more than) three quarters of a century. This is a review of that research, to determine what may be considered established phonetic facts about common Danish stød and the open questions that remain for future research.