bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cargo-Hitching in Long-Distance Bus Transit: An Acceptance Analysis
Authors: Meyer Vanessa , Lang Sarah , Dehdari Payam 
Published: October 2022

AbstractThe combination of freight transport and mobility—also known as cargo-hitching—is a form of delivery that has been implemented in various modes of transport. This concept is already widely used in Europe, Africa and North America in long-distance bus transport and ensures parcel delivery via the cargo compartment of long-distance buses. This paper aims to investigate the acceptance of cargo-hitching in long-distance bus transport in Germany. For this purpose, first the term cargo-hitching is defined, and an overview of cargo-hitching concepts in long-distance bus transport worldwide is given. In the following, the principles of attitudinal acceptance are explained. A modified version of the UTAUT2 model was used as the basis for an empirical study in the form of a quantitative online survey (n = 245). The results provide information about factors influencing acceptance as well as wishes and requirements of potential users. Parts of the UTAUT2 model were verified by regression analysis. It was shown that the variables’ habit, price value, hedonic motivation, performance expectancy and social influence predict the behavioural intention to use cargo-hitching in our sample significantly (p < 0.05). Furthermore, risks, benefits and willingness to pay were determined, which could contribute to the development of a business model. These included measures to improve transparency, security and information flow of the cargo-hitching process.
Promoting Zero-Emission Urban Logistics: Efficient Use of Electric Trucks Through Intelligent Range Estimation
Authors: Stütz Sebastian , Gade Andreas , Kirsch Daniela 
Published: October 2022

AbstractCritical success factors for the efficient use of electric trucks are the operational range and the total costs of ownership. For both range and efficient use, power consumption is the key factor. Increasing precision in forecasting power consumption and, hence, maximum range will pave the way for efficient vehicle deployment. However, not only electric trucks are scarce, but also is knowledge with respect to what these vehicles are actually technically capable of. Therefore, this article focuses on power consumption and range of electric vehicles. Following a discussion on how current research handles the mileage of electric vehicles, the article illustrates how to find simple yet robust and precise models to predict power consumption and range by using basic parameters from transport planning only. In the paper, we argue that the precision of range and consumption estimates can be substantially improved compared to common approaches which usually posit a proportional relationship between energy consumption and travel distance and require substantial safety buffers.
Increased Efficiency Through Intelligent Networking of Producers and Consumers in Commercial Areas Using the Example of Robert Bosch GmbH
Authors: Biesinger Andreas , Pesch Ruben , Cotrado Mariela , Pietruschka Dirk 
Published: October 2022

AbstractEnergy-efficient heating and cooling systems as well as intelligent systems for energy distribution are urgently required in order to be able to meet the ambitious goals of the European Union to reduce greenhouse gas emissions. The present article is intended to show that intelligent system extensions for the area of heating, cooling and electricity production for the industrial sector can lead to significant increase in efficiency. For this purpose, a simulation study for the expansion of a combined heat and power (CHP) plant with 2 MW thermal output using a 1.4 MW absorption chiller has been carried out. This shows that a heat-controlled CHP unit can significantly increase its running time. A system model was created for the initial situation and validated with existing measurement data. In the second step, this model was expanded to include the ACM module. The simulation was able to prove that in the event of a system expansion, the run time of the CHP unit can be increased by 35%. In addition to then increase of energy efficiency in the supply system, the analysis also focuses on the efficiency of the energy distribution via thermal networks in an industrial environment. The presented paper therefore also highlights the optimization potentials in the operation of thermal supply networks for industrial applications. For this purpose, a mathematical model has been developed which in addition to the components of the thermal network itself also comprises the producers and consumers. The specific construction of thermal networks for the supply of industrial properties requires adapted solutions for the simulation of such systems. Therefore, amongst other things, in the paper, solutions are shown for the modelling of direct flow local heating networks as well as for the operation of a cascade-controlled pump group.
GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs
Authors: Pflueger Maximilian , Tena Cucala David J. , Kostylev Egor V. 
Published: October 2022

AbstractReal-world knowledge graphs (KGs) are usually incomplete—that is, miss some facts representing valid information. So, when applied to such KGs, standard symbolic query engines fail to produce answers that are expected but not logically entailed by the KGs. To overcome this issue, state-of-the-art ML-based approaches first embed KGs and queries into a low-dimensional vector space, and then produce query answers based on the proximity of the candidate entity and the query embeddings in the embedding space. This allows embedding-based approaches to obtain expected answers that are not logically entailed. However, embedding-based approaches are not applicable in the inductive setting, where KG entities (i.e., constants) seen at runtime may differ from those seen during training. In this paper, we propose a novel neuro-symbolic approach to query answering over incomplete KGs applicable in the inductive setting. Our approach first symbolically augments the input KG with facts representing parts of the KG that match query fragments, and then applies a generalisation of the Relational Graph Convolutional Networks (RGCNs) to the augmented KG to produce the predicted query answers. We formally prove that, under reasonable assumptions, our approach can capture an approach based on vanilla RGCNs (and no KG augmentation) using a (often substantially) smaller number of layers. Finally, we empirically validate our theoretical findings by evaluating an implementation of our approach against the RGCN baseline on several dedicated benchmarks.
ISSA: Generic Pipeline, Knowledge Model and Visualization Tools to Help Scientists Search and Make Sense of a Scientific Archive
Authors: Toulet Anne , Michel Franck , Bobasheva Anna , Menin Aline , Dupré Sébastien , Deboin Marie-Claude , Winckler Marco , Tchechmedjiev Andon 
Published: October 2022

AbstractFaced with the ever-increasing number of scientific publications, researchers struggle to keep up, find and make sense of articles relevant to their own research. Scientific open archives play a central role in helping deal with this deluge, yet keyword-based search services often fail to grasp the richness of the semantic associations between articles. In this paper, we present the methods, tools and services implemented in the ISSA project to tackle these issues. The project aims to (1) provide a generic, reusable and extensible pipeline for the analysis and processing of articles of an open scientific archive, (2) translate the result into a semantic index stored and represented as an RDF knowledge graph; (3) develop innovative search and visualization services that leverage this index to allow researchers, decision makers or scientific information professionals to explore thematic association rules, networks of co-publications, articles with co-occurring topics, etc. To demonstrate the effectiveness of the solution, we also report on its deployment and user-driven customization for the needs of an institutional open archive of 110,000+ resources. Fully in line with the open science and FAIR dynamics, the presented work is available under an open license with all the accompanying documents necessary to facilitate its reuse. The knowledge graph produced on our use-case is compliant with common linked open data best practices.
Hashing the Hypertrie: Space- and Time-Efficient Indexing for SPARQL in Tensors
Authors: Bigerl Alexander , Conrads Lixi , Behning Charlotte , Saleem Muhammad , Ngonga Ngomo Axel-Cyrille 
Published: October 2022

AbstractTime-efficient solutions for querying RDF knowledge graphs depend on indexing structures with low response times to answer SPARQL queries rapidly. Hypertries—an indexing structure we recently developed for tensor-based triple stores—have achieved significant runtime improvements over several mainstream storage solutions for RDF knowledge graphs. However, the space footprint of this novel data structure is still often larger than that of many mainstream solutions. In this work, we detail means to reduce the memory footprint of hypertries and thereby further speed up query processing in hypertrie-based RDF storage solutions. Our approach relies on three strategies: (1) the elimination of duplicate nodes via hashing, (2) the compression of non-branching paths, and (3) the storage of single-entry leaf nodes in their parent nodes. We evaluate these strategies by comparing them with baseline hypertries as well as popular triple stores such as Virtuoso, Fuseki, GraphDB, Blazegraph and gStore. We rely on four datasets/benchmark generators in our evaluation: SWDF, DBpedia, WatDiv, and WikiData. Our results suggest that our modifications significantly reduce the memory footprint of hypertries by up to 70% while leading to a relative improvement of up to 39% with respect to average Queries per Second and up to 740% with respect to Query Mixes per Hour.
How to Agree to Disagree
Authors: Álvarez Lucía Gómez , Rudolph Sebastian , Strass Hannes 
Published: October 2022

AbstractThe importance of taking individual, potentially conflicting perspectives into account when dealing with knowledge has been widely recognised. Many existing ontology management approaches fully merge knowledge perspectives, which may require weakening in order to maintain consistency; others represent the distinct views in an entirely detached way.As an alternative, we proposeStandpoint Logic, a simple, yet versatile multi-modal logic “add-on” for existing KR languages intended for the integrated representation of domain knowledge relative to diverse, possibly conflictingstandpoints, which can be hierarchically organised, combined, and put in relation with each other.Starting from the generic framework ofFirst-Order Standpoint Logic(FOSL), we subsequently focus our attention on the fragment ofsententialformulas, for which we provide a polytime translation into the standpoint-free version. This result yields decidability and favourable complexities for a variety of highly expressive decidable fragments of first-order logic. Using some elaborate encoding tricks, we then establish a similar translation for the very expressive description logic$$\mathcal {SROIQ}b_s$$SROIQbsunderlying the OWL 2 DL ontology language. By virtue of this result, existing highly optimised OWL reasoners can be used to provide practical reasoning support for ontology languages extended by standpoint modelling.
Axiogenesis with a heavy QCD axion
Authors: Co Raymond T. , Gherghetta Tony , Harigaya Keisuke 
Published: October 2022

Abstract
We demonstrate that the observed cosmological excess of matter over anti-matter may originate from a heavy QCD axion that solves the strong CP problem but has a mass much larger than that given by the Standard Model QCD strong dynamics. We investigate a rotation of the heavy QCD axion in field space, which is transferred into a baryon asymmetry through weak and strong sphaleron processes. This provides a strong cosmological motivation for heavy QCD axions, which are of high experimental interest. The viable parameter space has an axion mass ma between 1 MeV and 10 GeV and a decay constant fa< 105 GeV, which can be probed by accelerator-based direct axion searches and observations of the cosmic microwave background.
Strange processes in general two Higgs doublet model
Authors: Hou Wei-Shu , Kumar Girish 
Published: October 2022

Abstract
In the general two Higgs doublet model (g2HDM) that has extra Yukawa couplings, we analyze their New Physics (NP) contributions to kaon mixing parameter εK, direct CP violation parameter ε′/ε, and rare $$ {K}^{+}\to {\pi}^{+}\nu \overline{\nu} $$

K
+

→

π
+

ν

ν
¯

, $$ {K}_L\to {\pi}^0\nu \overline{\nu} $$

K
L

→

π
0

ν

ν
¯

, and KL,S→ μ+μ− decays. We study correlations between these observables, and call special attention to a unique complementarity of kaon mixing and rare $$ K\to \pi \nu \overline{\nu} $$
K
→
πν

ν
¯

decays in probing the exotic Higgs mass spectrum of g2HDM. The importance of kaon physics in probing NP vis-à-vis B physics is stressed. One unexpected feature we uncover is the special sensitivity of $$ {K}^{+}\to {\pi}^{+}\nu \overline{\nu} $$

K
+

→

π
+

ν

ν
¯

to TeV scale charged Higgs boson.
What Has Immunology Brought to Periodontal Disease in Recent Years?
Authors: Kowalski Jan , Nowak Maciej , Górski Bartłomiej , Górska Renata 
Published: October 2022

AbstractRecent decades have shed a new light on the pathomechanism of periodontal inflammation. While classic periodontology concentrates on biofilm control, oral hygiene improvement, professional tooth cleaning and surgical correction of damaged periodontal tissues, new aspects of the destruction mechanisms are being raised. Among them, the greatest attention is paid to the influence of host response on the clinical manifestations of the disease. Numerous studies have proved that the shift from gingivitis to periodontitis is not a simple progress of the disease, but an event occurring only in susceptible individuals. Susceptibility may result from appearance of local factors facilitating biofilm accumulation and/or maturation, or from systemic features, among which over-reaction and prolonged agitation of non-specific component of inflammatory response is crucial. The present paper summarizes the association between periodontology and immunology and updates the knowledge accrued mostly in the recent years. After a brief explanation of advances in understanding of the disease aetiology, the most studied and potentially viable immunological markers of periodontal disease are presented. Possible new therapeutic strategies, exploiting knowledge about the nature of host response—immunomodulation and reduction of chronic oxidative stress—are also presented.
A simple approach of applying blended learning to problem-based learning is feasible, accepted and does not affect evaluation and exam results—a just pre-pandemic randomised controlled mixed-method study
Authors: Servos Ulrike , Reiß Birger , Stosch Christoph , Karay Yassin , Matthes Jan 
Published: October 2022

AbstractWe tested for feasibility, acceptance, and “non-inferiority” of small-group teaching applying blended learning (i.e., the integration of face-to-face and online instruction) to problem-based learning (bPbL) compared to conventional PbL (cPbL). In a just pre-pandemic, randomised controlled trial, 317 students attended either bPbL or cPbL groups. The first meeting of the bPbL groups took place online via written internet chat, while cPbL groups met on site. All groups met on site the second time. All students had the opportunity to attend lectures either on site or as videos on demand. We analysed student evaluation data, results in a final summative exam, attendance of lectures on site and use of lecture videos. Furthermore, we performed a qualitative analysis of student statements made in semi-structured group interviews about pros and cons of the bPbL approach. There was no difference between students of either bPbL or cPbL groups with respect to exam results (score: 14.3 ± 2.8 vs. 13.8 ± 2.7) or course evaluation. However, relatively more bPbL than cPbL students reported having used lecture videos, while the proportion of those attending lectures on-site was higher among cPbL students. Interviews revealed that some of the bPbL students’ experiences were unexpected and feared disadvantages seemed to be less severe than expected. Participation in a blended PbL format did not worsen course evaluations or exam results, but seemed to influence lecture attendance. The combination of face-to-face and digital elements could be suitable as a hybrid approach to digital instruction in the post-pandemic era.
Postoperative Complications and Outcome After Emergency Laparotomy: A Retrospective Study
Authors: Ylimartimo Aura T. , Nurkkala Juho , Koskela Marjo , Lahtinen Sanna , Kaakinen Timo , Vakkala Merja , Hietanen Siiri , Liisanantti Janne 
Published: October 2022

AbstractBackgroundEmergency laparotomy (EL) is a common urgent surgical procedure with high risk for postoperative complications. Complications impair the prognosis and prolong the hospital stay. This study explored the incidence and distribution of complications and their impact on short‐term mortality after EL.MethodsThis was a retrospective single‐center register‐based cohort study of 674 adults undergoing midline EL between May 2015 and December 2017. The primary outcome was operation‐related or medical complication after EL. The secondary outcome was mortality in 90‐day follow‐up. Multivariate logistic regression analyses were used to identify independent risk factors for complications.ResultsA total of 389 (58%) patients developed complications after EL, including 215 (32%) patients with operation‐related complications and 361 (54%) patients with medical complications. Most of the complications were Clavien‐Dindo classification type 4b (28%) and type 2 (22%). Operation‐related complications occurred later compared to medical complications. Respiratory complications were the most common medical complications, and infections were the most common operation‐related complications. The 30‐ and 90‐day mortalities were higher in both the medical (17.2%, 26.2%) and operation‐related complication groups (13.5%, 24.2%) compared to patients without complications (10.5% and 4.8%, 14.8% and 8.0%). Low albumin, high surgical urgency, excessive alcohol consumption and medical complications were associated with operation‐related complications. Older age, high ASA class and operation‐related complications were associated with medical complications.ConclusionsThis study demonstrated that EL is associated with a high risk of complications and poor short‐term outcome. Complications impair the prognosis regardless of which kind of EL is in question.
Feeding ecology of an inshore population of Notothenia coriiceps from the Argentine Islands, Bellingshausen Sea
Authors: Trokhymets Vladen , Zinkovskyi Artem , Dykyy Ihor , La Mesa Mario 
Published: October 2022

AbstractThe inshore waters off the Argentine Islands host a diversified benthic fish community largely dominated by the black rockcod, Notothenia coriiceps. Compared to other areas along the western Antarctic Peninsula, the feeding habits of this species in this location are poorly known. Hence, the aim of the study is to assess food preferences by the stomach content examination, applying a sophisticated analytical approach. As reported elsewhere, the black rockcod is omnivorous, relying primarily on algae, gastropods, amphipods, euphausiids and fishes, each consumed with different foraging strategies. Based on multidimensional scaling statistical procedures, fish size and water depth are the primarily contributers to prey resource diversification and partitioning. Overall the sampled population of the black rockcod are generalist feeders with a relatively high between-phenotype component to the niche width, consisting of specialized individuals with little or no overlap in food resource use.
Onset of zooplanktivory and optimal water flow rates for prey capture in newly settled polyps of ten Caribbean coral species
Authors: Geertsma Robbert C. , Wijgerde Tim , Latijnhouwers Kelly R. W. , Chamberland Valérie F. 
Published: October 2022

AbstractZooplanktivory is an important source of nutrients in corals, providing up to 35% of daily metabolic energy requirements in some species. However, little is known about coral zooplanktivory shortly after larval settlement and metamorphosis. In most species it is unclear if, when and under which conditions newly settled polyps are able to capture and ingest prey. This remains a critical knowledge gap, as zooplanktivory could allow coral settlers to replenish energy reserves shortly after metamorphosis, possibly improving settler condition during one of their most vulnerable life stages. Here, we documented the onset of prey (Artemia salina nauplii) capture in ten Caribbean coral species and assessed optimal water flow rates (WFR) for prey capture in five of these species. All species initiated zooplanktivory within six days following metamorphosis, with the exception of Acropora palmata which was never observed capturing nauplii during our 20-day study. Optimal WFR for prey capture varied among species, with Favia fragum displaying maximum prey capture rates in zero flow and Diploria labyrinthiformis most effectively capturing nauplii under WFR of 5–20 cm s−1. Under each species’ optimum WFR, prey capture abilities varied considerably, with F. fragum capturing up to one nauplius every two minutes compared to one nauplius every nine minutes in Colpophyllia natans. Using these findings, we make species-specific recommendations to optimize coral husbandry and larval-based restoration practices for these ten coral species.
Free surface effects and the utility of a skim plate for experiments in a water towing tank at steady and unsteady model velocity
Authors: Jentzsch Marvin , Dahms Jona Maria , Woszidlo René , Nayeri Christian Navid , Paschereit Christian Oliver 
Published: October 2022

AbstractA towing tank is utilized to investigate the flow field around a two-dimensional submerged foil model operating near the free surface. Free surface effects are analyzed for steady and unsteady model velocity. The model’s submergence depth and angle of attack are varied. Tests are conducted for the model facing upside-up and upside-down. The surface deflection is recorded and the experimental results are utilized to validate an analytic model that is deployed to predict wake wave patterns at arbitrary model velocity. The flow mechanism leading to load alterations when the foil is in the vicinity of the free surface is explored in detail using experimental and analytic results. The imposed wave-induced velocity perturbations alter the effective angle of attack experienced by the foil. Flow separation is delayed when the model is facing upside-up and promoted when facing upside-down. For test cases with unsteady sinusoidal model velocity, forward traveling waves are generated, leading to a time-varying change in the inflow condition of the submerged foil. Increasing the model’s submergence depth alleviates free surface effects. A skim plate is installed in-between the free surface and model. It shows similar wave alleviating effects as obtained when increasing the model submergence depth by locally blocking wave-induced velocities. The skim plate position is varied in the longitudinal direction to determine its most advantageous position. Surface wave effects at unsteady model velocity are alleviated most effectively when the skim plate protrudes upstream of the model.
Graphical abstract