bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microscale flow dynamics and particle capture in scleractinian corals: I. Role of the tentacles
Authors: Price Wm. Stephen , Patterson Mark R. 
Published: May 2023

AbstractThe size, shape, and arrangement of tentacles in scleractinian coral polyps are likely to affect particle capture yet have not been investigated in a systematic way. Morphometric measurements of tentacles of several coral species found in the Caribbean Sea were taken from macro-photographs, and from these, models were constructed in three postures: straight, upstream-facing, and downstream-facing. These models were placed in a flume to video the flow paths of particles around them. Video analysis indicates tentacles, and their specific postures, have a dramatic effect on micro-flow patterns. The expanded soft tissue tentacles, and their specific postures, greatly increase probability of particle capture by direct impaction, inertial impaction, and gravitational deposition. All tentacle postures cause increased retention time relative to freestream travel in their immediate proximity, as well as increasing both contact with the tentacle surface, and tumbling of particles. Straight and upstream-facing tentacles deflect particles downward to their base, while downstream-facing tentacles deflect particles upwards. When results from individual tentacles are considered in geometric combination, the secondary radial symmetry of the tentacular whorls in simple coral polyps appears to be an optimal strategy to filter suspended particulate material in an oscillating and omni-directional flow environment. In meandrine corals, the hedgerows of straight and curved tentacles appear to draw particles downward, retain them, and direct them onto the oral feeding areas below the thecal ridges. The size, shape, and arrangement of tentacles are thus of key importance in understanding suspension feeding in scleractinian corals.
The nature of the Karoo mantle source region from the perspective of olivine in the Luenha picrites: an oxygen isotopic and chemical study
Authors: Iles Kieran A. , Luttinen Arto V. , Beier Christoph , Heinonen Jussi S. , Whitehouse Martin J. , Turunen Sanni T. 
Published: May 2023

AbstractThe Karoo large igneous province has been divided into rift zone and basin-related groups, with picrites from the Luenha river, Mozambique, representing an end-member of the latter. New O isotope, major and trace element data for olivine have been combined with MELTS crystallisation modelling to deconvolve compositional diversity associated with magma differentiation from source-derived heterogeneity. Three olivines populations have been discerned as follows: (1) the ‘main trend’, which records crystallisation from a variety of magma compositions; (2) the ‘low Cu trend’, which is inferred to represent xenocrysts or antecrysts; and (3) the ‘high CaO’ olivines, which record polybaric crystallisation of a primitive, little fractionated magma. The trace element variability in olivine phenocrysts relates partially to sampling of different parts of the same overall magma transport and storage systems, and partly to heterogeneity of parental magmas and their mantle sources. When the measured δ18Oolivine values have been converted into δ18Omelt values, the mean δ18Omelt values for the ‘main trend’ and ‘low Cu’ groups are indistinguishable from each other (5.7 ± 0.1‰, 2σ); however, the mean δ18Omelt value of 6.1 ± 0.1‰ for the ‘high CaO’ group is distinctly enriched. These data record source heterogeneity and suggest contributions from two mantle sources, one with elevated δ18O, and another with more ‘typical’ mantle δ18O. Combining these data with previously reported trace element and Nd and Sr isotope data support derivation from a mantle source similar to non-chondritic bulk silicate earth, but with minor contributions (1–2% for the enriched magmas) from a recycled sedimentary component. This points to the importance of a primitive mantle source for the basin-related successions in Karoo.
Sensorgestützte Sortierung
Authors: Jürgensen Stefan , Flachberger Helmut 
Published: May 2023

ZusammenfassungSensorgestützte Sortierung ist eine etablierte Standardtechnologie in der Verarbeitung von Sekundärrohstoffen. Ihr Einsatz in der Aufbereitung von Primärrohstoffen ist dagegen noch nicht im selben Maße verbreitet. Neue Sortieranlagen haben in den letzten Jahren bewiesen, dass sensorgestützte Sortierung bisherige Aufbereitungsverfahren durch höhere Effizienz ergänzen und ersetzen kann.
Refinement of ensemble strategy for acute lymphoblastic leukemia microscopic images using hybrid CNN-GRU-BiLSTM and MSVM classifier
Authors: Mohammed Kamel K. , Hassanien Aboul Ella , Afify Heba M. 
Published: May 2023

AbstractAcute lymphocytic leukemia (ALL) is a common serious cancer in white blood cells (WBC) that advances quickly and produces abnormal cells in the bone marrow. Cancerous cells associated with ALL lead to impairment of body systems. Microscopic examination of ALL in a blood sample is applied manually by hematologists with many defects. Computer-aided leukemia image detection is used to avoid human visual recognition and to provide a more accurate diagnosis. This paper employs the ensemble strategy to detect ALL cells versus normal WBCs using three stages automatically. Firstly, image pre-processing is applied to handle the unbalanced database through the oversampling process. Secondly, deep spatial features are generated using a convolution neural network (CNN). At the same time, the gated recurrent unit (GRU)-bidirectional long short-term memory (BiLSTM) architecture is utilized to extract long-distance dependent information features or temporal features to obtain active feature learning. Thirdly, a softmax function and the multiclass support vector machine (MSVM) classifier are used for the classification mission. The proposed strategy has the resilience to classify the C-NMC 2019 database into two categories by using splitting the entire dataset into 90% as training and 10% as testing datasets. The main motivation of this paper is the novelty of the proposed framework for the purposeful and accurate diagnosis of ALL images. The proposed CNN-GRU-BiLSTM-MSVM is simply stacked by existing tools. However, the empirical results on C-NMC 2019 database show that the proposed framework is useful to the ALL image recognition problem compared to previous works. The DenseNet-201 model yielded an F1-score of 96.23% and an accuracy of 96.29% using the MSVM classifier in the test dataset. The findings exhibited that the proposed strategy can be employed as a complementary diagnostic tool for ALL cells. Further, this proposed strategy will encourage researchers to augment the rare database, such as blood microscopic images by creating powerful applications in terms of combining machine learning with deep learning algorithms.
Cynipid galls on oak leaves are resilient to leaf vein disruption
Authors: Giertych Marian J. , Łukowski Adrian , Karolewski Piotr 
Published: May 2023

AbstractOaks serve as host plants for numerous insects, including those forming galls. Galls induced on oaks are completely dependent on leaf resources. Many other folivores damage veins of leaves, which may result in cutting galls off from sources of assimilates, nutrients and water. We hypothesised that the disruption of the continuity of leaf vascular tissues stops gall development, leading to the death of the larva. Leaves of sessile oak (Quercus petraea) with Cynips quercusfolii galls in the initial stage of development were marked. The diameter of the galls was measured, and the vein on which the gall was present was cut. Four experimental treatments were established: control – with no cutting, cutting the vein distal to the gall relative to the petiole, cutting the vein basal to the gall and cutting both sides. The average survival rate (live galls at the end of the experiment including healthy larvae, pupae or imagines inside) – was 28.9%. The rate varied depending on the treatment and was 13.6% in the treatment with the vein cut on both sides and about 30% in the remaining treatments. However, this difference was not statistically significant. The growth dynamics of galls are highly dependent on the experimental treatment. The largest galls grew in the control treatment, and the smallest galls were in the treatments with the veins cut on both sides. Unexpectedly, even cutting veins on both sides did not result in the immediate dieback of the galls. The results suggest that the galls are very strong nutrient and water sinks. The functions of the cut vein are likely taken over by other lower-order veins, allowing nourishment of the gall to complete larva development.
Automatic generation of creative text in Portuguese: an overview
Authors: Gonçalo Oliveira Hugo 
Published: May 2023

AbstractCreativity is an inherently human skill, and thus one of the goals of Artificial Intelligence. Specifically, linguistic computational creativity deals with the autonomous generation of linguistically-creative artefacts. Here, we present four types of text that can be tackled in this scope—poetry, humour, riddles, and headlines—and overview computational systems developed for their generation in Portuguese. Adopted approaches are described and illustrated with generated examples, and the key role of underlying computational linguistic resources is highlighted. The future of such systems is further discussed together with the exploration of neural approaches for text generation. While overviewing such systems, we hope to disseminate the area among the community of the computational processing of the Portuguese language.
CsFEVER and CTKFacts: acquiring Czech data for fact verification
Authors: Ullrich Herbert , Drchal Jan , Rýpar Martin , Vincourová Hana , Moravec Václav 
Published: May 2023

AbstractIn this paper, we examine several methods of acquiring Czech data for automated fact-checking, which is a task commonly modeled as a classification of textual claim veracity w.r.t. a corpus of trusted ground truths. We attempt to collect sets of data in form of a factual claim, evidence within the ground truth corpus, and its veracity label (supported, refuted or not enough info). As a first attempt, we generate a Czech version of the large-scale FEVER dataset built on top of Wikipedia corpus. We take a hybrid approach of machine translation and document alignment; the approach and the tools we provide can be easily applied to other languages. We discuss its weaknesses, propose a future strategy for their mitigation and publish the 127k resulting translations, as well as a version of such dataset reliably applicable for the Natural Language Inference task—the CsFEVER-NLI. Furthermore, we collect a novel dataset of 3,097 claims, which is annotated using the corpus of 2.2 M articles of Czech News Agency. We present an extended dataset annotation methodology based on the FEVER approach, and, as the underlying corpus is proprietary, we also publish a standalone version of the dataset for the task of Natural Language Inference we call CTKFactsNLI. We analyze both acquired datasets for spurious cues—annotation patterns leading to model overfitting. CTKFacts is further examined for inter-annotator agreement, thoroughly cleaned, and a typology of common annotator errors is extracted. Finally, we provide baseline models for all stages of the fact-checking pipeline and publish the NLI datasets, as well as our annotation platform and other experimental data.
Filled Pauses Produced by Autistic Adults Differ in Prosodic Realisation, but not Rate or Lexical Type
Authors: Wehrle Simon , Grice Martine , Vogeley Kai 
Published: May 2023

AbstractWe examined the use of filled pauses in conversations between homogeneous pairs of autistic and non-autistic adults. A corpus of semi-spontaneous speech was used to analyse the rate, lexical type (nasal “uhm” or non-nasal “uh”), and prosodic realisation (rising, level or falling) of filled pauses. We used Bayesian modelling for statistical analysis. We found an identical rate of filled pauses and an equivalent preference of “uhm” over “uh” across groups, but also a robust group-level difference regarding the intonational realisation of filled pauses: non-autistic controls produced a considerably higher proportion of filled pause tokens realised with the canonical level pitch contour than autistic speakers. Despite the fact that filled pauses are a frequent and impactful part of speech, previous work on their conversational use in autism spectrum disorder (ASD) is limited. Our account is the first to analyse the intonational realisation of filled pauses in ASD and the first to investigate conversations between autistic adults in this context. Our results on rate and lexical type can help to contextualise previous research, while the novel findings on intonational realisation set the stage for future investigations.
A deep learning framework for defect prediction based on thermographic in-situ monitoring in laser powder bed fusion
Authors: Oster Simon , Breese Philipp P. , Ulbricht Alexander , Mohr Gunther , Altenburg Simon J. 
Published: May 2023

AbstractThe prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers. Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. The model is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) µm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity.
Human Factors Evaluation of HeartMate 3 Left Ventricular Assist Device Peripherals: An Eye Tracking Supported Simulation Study
Authors: Widhalm Gregor , Abart Theodor , Noeske Moritz , Kumer Lisa , Ebenberger Katharina , Atteneder Clemens , Berger Angelika , Laufer Günther , Wiedemann Dominik , Zimpfer Daniel , Schima Heinrich , Wagner Michael , Schlöglhofer Thomas 
Published: May 2023

Abstract
Background
Despite recent design improvements, human factors issues continue to challenge left ventricular assist device (LVAD) therapy. The aim of this study was to evaluate user experience of former non-HeartMate 3 (HM3) LVAD patients post heart transplantation (HTX) and laypersons (LP) with HM3 LVAD peripherals in simulated everyday and emergency scenarios.

Methods
This single center cohort study included untrained HTX and LP. Seven scenarios, including battery exchanges (without alarm, advisory alarm, dim light, consolidated bag), change of power supply, driveline dis-/reconnection and controller exchange were simulated. Subjects’ gaze behavior was recorded using eye tracking technology. Success rate, pump-off-time, duration to success (DTS), percental fixation duration per areas of interest and post-scenario-survey results were defined as outcome measures.

Results
Thirty subjects completed 210 scenarios, initially solving 82.4% (HTX vs. LP, p = 1.00). Changing power supply revealed highest complexity (DTS = 251 ± 93s, p = 0.76): 26.7% succeeded at first attempt (p = 0.68), 56.7% at second attempt, with significantly more LP failing (p = 0.04), resulting in 10 hazards from driveline disconnections (pump-off-time 2-118s, p = 0.25). Comparison on initial success showed differences in fixation durations for seven areas of interest (p < 0.037). Decreasing DTS during battery exchanges (p < 0.001) indicate high learnability. Exchanging batteries within the bag took longer (median DTS = 75.0 (IQR = 45.0)s, p = 0.09), especially in elderly subjects (r = 0.61, p < 0.001). Subjects with less initial success were more afraid of making mistakes (p = 0.048).

Conclusion
This eye tracking based human factors study provided insights into user experiences in handling HM3 peripherals. It highlights unintuitive and hazardous characteristics, providing guidance for future user-centered design of LVAD wearables.
Thermal decomposition of calcium propionate: films and powders
Authors: Zaidi Sihem , Sanchez-Rodriguez Daniel , Farjas Jordi , Mohamed Dammak , Roura-Grabulosa Pere 
Published: April 2023

AbstractThe thermal decomposition of calcium propionate, in inert and oxidative atmospheres, has been investigated by thermogravimetry combined with infrared evolved gas analysis; the main volatiles formed during thermal decomposition have been identified. The intermediate and final products have been characterized by infrared spectroscopy, x-ray diffraction, elemental analysis and scanning electron microscopy. The different mechanisms involved in thermal decomposition are discussed as a function of atmosphere and sample structure. The kinetics of the decomposition and the ability of powders to undergo a thermal runaway are also investigated.
Crystallisation and characterisation of muscle proteins: a mini-review
Authors: Govada Lata , Chayen Naomi E. 
Published: May 2023

AbstractThe techniques of X-ray protein crystallography, NMR and high-resolution cryo-electron microscopy have all been used to determine the high-resolution structure of proteins. The most-commonly used method, however, remains X-ray crystallography but it does rely heavily on the production of suitable crystals. Indeed, the production of diffraction quality crystals remains the rate-limiting step for most protein systems. This mini-review highlights the crystallisation trials that used existing and newly developed crystallisation methods on two muscle protein targets - the actin binding domain (ABD) of α-actinin and the C0-C1 domain of human cardiac myosin binding protein C (cMyBP-C). Furthermore, using heterogenous nucleating agents the crystallisation of the C1 domain of cMyBP-C was successfully achieved in house along with preliminary actin binding studies using electron microscopy and co-sedimentation assays .
Anchor practices that guide horizontal performance measurement: an interventionist case study of the financial aspect of new technology implementation in healthcare
Authors: Korhonen Tuomas , Sillanpää Virpi , Jääskeläinen Aki 
Published: May 2023

AbstractWith the demand for elderly care increasing in many countries, digital technologies offer the potential for organising such care while also increasing value for money. However, public administrators need tools to make sense of their own complex environment and the possible impacts of new technologies. The current paper examines this issue by applying horizontal performance measurement, where practitioners can give financial value to issues that span across many functions and thus avoid sub-optimisation. We use an interventionist case study to illustrate a situation in which a Nordic city attempted to calculate the financial impact of introducing new digital technologies into elderly care. As our contribution to the literature on horizontal performance measurement, we show how economic (financial) and wellbeing anchors influence horizontal performance measurement in a healthcare digitalisation project. We also contribute to the development of our method theory, i.e., anchor practices, by providing evidence of the usage of multiple simultaneous anchors and make a methodological contribution by showing that interventionist researchers can support operationalising anchor practices.
A critical evaluation of the safety datasheets of graphene materials
Authors: Theodoropoulou Anastasia , Gkika Despina A. , Alodhayb Abdullah , Kyzas George Z. 
Published: May 2023

Abstract
Graphene, a single layer of carbon atoms, is a material that has held a leading position in material research owing to its excellent properties, allowing its use in innovative technologies. In spite of many advantages, the graphene’s potentially hazardous effect on the environment as well as human health constitutes a major drawback. Year after year, safety data sheets (SDS) constitute the main reference on a material’s potential hazards and the methods to prevent or address them if needed. However, SDS content has been heavily criticized due to incomplete, incorrect, or missing information and the cost required to produce and maintain it. The primary objective of this work is to introduce a stepwise process of knowledge management regarding SDSs, by identifying unexplored or neglected sections in a holistic approach. In this light, this work examines 37 graphene SDS, using modified Hodson’s criteria. The quality evaluation revealed that approximately 5% (2/37) of the datasheets were deemed reliable without restrictions (excellent), the majority 49% (18/37) were categorized as reliable with restrictions (good), while about reaching almost 46% (17/37) were deemed non-informative. It is noteworthy that approximately 73% of the SDS require major improvements; thus, the majority did not provide adequate data to be properly assessed. Section 15 could potentially trigger fundamental changes in the product status. The comprehensive evaluation of all 16 sections will enhance the capacity to conduct research mapping and formulate opinions on nanomaterials, thereby stimulating innovation.
The predictive power of risk elicitation tasks
Authors: Garagnani Michele 
Published: May 2023

AbstractThis work reports the results of two online experiments with a general-population sample examining the performance of different tasks for the elicitation of risk attitudes. First, I compare the investment task of Gneezy and Potters (1997), the standard choice-list method of Holt and Laury (2002), and the multi-alternative procedure of Eckel and Grossman (2002) and evaluate their performance in terms of the number of correctly-predicted binary decisions in a set of out-of-sample lottery choices. There are limited differences between the tasks in this sense, and performance is modest. Second, I included three additional budget-choice tasks (selection of a lottery from a linear budget set) where optimal decisions should have been corner solutions, and find that a large majority of participants provided interior solutions instead, casting doubts on people’s understanding of tasks of this type. Finally, I investigate whether these two results depend on cognitive ability, numerical literacy, and education. While optimal choices in budget-choice tasks are related to numerical literacy and cognitive ability, the predictive performance of the risk-elicitation tasks is unaffected.