bluuebunny/crossref_metadata_2025_split huggingface dataset:
A zero-waste approach for the production and use of Arthrospira platensis as a protein source in foods and as a plant biostimulant in agriculture
Authors: Villaró Silvia , Acién Gabriel , Alarcón Javier , Ruiz Ángela , Rodríguez-Chikri Laura , Viviano Emanuele , Lafarga Tomás 
Published: June 2023

Abstract
Food production will have to increase significantly to meet the nutritional needs of the global population. There is also an urgent need to increase the sustainability of food production. Microalgae are a potential sustainable alternative to conventional protein sources and they can also be used in other industries such as agriculture or aquaculture. In this work, the cyanobacterium Arthrospira platensis was produced in Almeria (Spain) in a pilot-scale reactor (80 m2). The biomass produced was used as a protein source and a plant biostimulant following a biorefinery approach. Biomass productivity reached 5.6 g m−2 day−1. The biomass was rich in proteins (67.8 g (100 g)−1) and pigments, namely chlorophyll (7.6 mg (100 g)−1) and phycocyanin (134.2 mg (100 g)−1). An isoelectric solubilisation/precipitation method assisted by ultrasound led to the recovery of a protein extract with a protein content of 91.3 g (100 g)−1. The protein isolate was evaluated as a source of essential amino acids in tagliatelle, leading to an increase in the content of histidine, leucine, lysine, methionine, phenylalanine, threonine, and valine of 36.3, 75.2, 26.3, 30.0, 45.7, 57.8, and 70.0%, respectively. The protein content also increased from 9.6 to 13.9 g (100 g)−1 when the protein isolate was incorporated at a flour substitution level of 4%. The leftovers from the protein extraction were evaluated as plant biostimulants, for which auxin- and cytokinin-like effects were observed. Root development was especially promoted. The results demonstrated the feasibility of producing Spirulina during the winter in Europe and the potential simultaneous use of the biomass as a food ingredient and as a plant biostimulant.
Applications of Natural Language Processing to Geoscience Text Data and Prospectivity Modeling
Authors: Lawley Christopher J. M. , Gadd Michael G. , Parsa Mohammad , Lederer Graham W. , Graham Garth E. , Ford Arianne 
Published: June 2023

AbstractGeological maps are powerful models for visualizing the complex distribution of rock types through space and time. However, the descriptive information that forms the basis for a preferred map interpretation is typically stored in geological map databases as unstructured text data that are difficult to use in practice. Herein we apply natural language processing (NLP) to geoscientific text data from Canada, the U.S., and Australia to address that knowledge gap. First, rock descriptions, geological ages, lithostratigraphic and lithodemic information, and other long-form text data are translated to numerical vectors, i.e., a word embedding, using a geoscience language model. Network analysis of word associations, nearest neighbors, and principal component analysis are then used to extract meaningful semantic relationships between rock types. We further demonstrate using simple Naive Bayes classifiers and the area under receiver operating characteristics plots (AUC) how word vectors can be used to: (1) predict the locations of “pegmatitic” (AUC = 0.962) and “alkalic” (AUC = 0.938) rocks; (2) predict mineral potential for Mississippi-Valley-type (AUC = 0.868) and clastic-dominated (AUC = 0.809) Zn-Pb deposits; and (3) search geoscientific text data for analogues of the giant Mount Isa clastic-dominated Zn-Pb deposit using the cosine similarities between word vectors. This form of semantic search is a promising NLP approach for assessing mineral potential with limited training data. Overall, the results highlight how geoscience language models and NLP can be used to extract new knowledge from unstructured text data and reduce the mineral exploration search space for critical raw materials.
Transforming Attitudes Towards the Turk in Edward Ravenscroft’s Mamamouchi, or The citizen turn’d gentleman (1672) and Molière’s Le bourgeois Gentilhomme (1668)
Authors: Caro Partridge Eneas 
Published: June 2023

AbstractWhen Edward Ravenscroft approached the polarising figure of the Turk in The citizen turn’d gentleman (1672), an adaptation of Molière’s Le bourgeois gentilhomme (1668), he inherited certain structures and motivations that stem out of very specific attitudes towards the Ottomans that were not easily transposed onto the English context. This did not stop him from penning one of the most successful plays of his time, but it also did not stop the critics from deeming his adaptation a cheap knock-off that hardly altered the original and was closer to a translation than to any exercise of real talent. His adaptation, however, builds on the expectations of his London audiences and the trends on narrative-building regarding East–West relations to cleverly alter the reception of the play rather than the execution thereof, resulting in a minimal style of adaptation that produced a profound outcome. This study explores Ravenscroft’s way of dealing with the very central figure of the Turk in The citizen turn’d gentleman and the relation to the original source material in order to prove that his decision was a conscious act, part of a much more complex adaptative procedure than he is given credit for.
Bifurcation scenarios in the hardware-in-the-loop experiments of highly interrupted milling processes
Authors: Toth Rudolf R. , Stepan Gabor 
Published: June 2023

AbstractHardware-in-the-loop (HIL) measurements of highly interrupted milling processes were conducted. A real spindle was used with a dummy tool on which the cutting forces were emulated with contactless sensors and actuators. During the experiments, Hopf- and period-doubling bifurcations were identified. The nonlinear dynamics of these period-doubling bifurcations are analyzed for a discrete model of highly interrupted milling. This investigation found the bifurcation to be subcritical, which draws the attention to the limited practical validity of linear stability analysis.
Merely statistical evidence: when and why it justifies belief
Authors: Silva Paul 
Published: June 2023

AbstractIt is one thing to hold that merely statistical evidence issometimesinsufficient for rational belief, as in typical lottery and profiling cases. It is another thing to hold that merely statistical evidence isalwaysinsufficient for rational belief. Indeed, there are cases where statistical evidence plainly does justify belief. This project develops a dispositional account of the normativity of statistical evidence, where the dispositions that ground justifying statistical evidence are connected to the goals (= proper function) of objects. There are strong intuitive motivations for doing this. For we can turn almost any case ofnon-justifyingmerely statistical evidence into a case ofjustifyingmerely statistical evidence by adding information about the dispositions and goals of the objects involved. The resulting view not only helps us understand when and why merely statistical evidence is normatively significant, but it also helps us understand how statistical evidence relates to more standard forms of evidence (perceptual, testimonial). The emerging view also has surprising applications, as it imposes limitations on the epistemic value of fine-tuning arguments for theism as well as undermines a standard class of case-based arguments for moral encroachment.
Thirty-six years of contributions to queueing systems: a content analysis, topic modeling, and graph-based exploration of research published in the QUESTA journal
Authors: Shausan Aminath , Vuorinen Aapeli 
Published: June 2023

AbstractWe investigate the 36-year history of research published in the journal Queueing Systems: Theory and Applications (QUESTA), to uncover trends over time in the research topics and themes covered as well as in authorship, co-authorship, and institutional affiliation. Our analysis includes three different approaches. First, we conduct a content analysis of titles and abstracts using selected keywords to examine trends in the three themes of models, methods, and concepts applied in each article. Second, we employ unsupervised topic modeling to identify more hidden topics discussed in the journal. Finally, we analyze the co-authorship graph to identify trends in co-authorship and changes in collaboration practices between authors and their research institutions. Our findings reveal a persistent popularity of studies focused on the basic modeling of queues, queueing networks, and queueing systems. We also confirm an increase in collaboration among authors over time.
The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification
Authors: Palias Efstratios , Kabán Ata 
Published: June 2023

AbstractHigh-dimensionality is a common hurdle in machine learning and pattern classification; mitigating its effects has attracted extensive research efforts. It has been found in a recent NeurIPS paper that, when the data possesses a low effective dimension, the predictive performance of a discriminative quadratic classifier with nuclear norm regularisation enjoys a reduced (logarithmic) dependence on the ambient dimension and depends on the effective dimension instead, while other regularisers are insensitive to the effective dimension. In this paper, we show that dependence on the effective dimension is also exhibited by the Bayes error of the generative Quadratic Discriminant Analysis (QDA) classifier, without any explicit regularisation, under three linear dimensionality reduction schemes. Specifically, we derive upper bounds on the Bayes error of QDA, which adapt to the effective dimension, and entirely bypass any dependence on the ambient dimension. Our findings complement previous results on compressive QDA that were obtained under compressive sensing type assumptions on the covariance structure. In contrast, our bounds make no a-priori assumptions on the covariance structure, in turn they tighten in the presence of benign traits of the covariance. We corroborate our findings with numerical experiments.
Potential toxic effects of titanium oxide (TiO2) nanoparticles on the biological, biochemical, and histological aspects of the land snail Helix aspersa
Authors: Abdel-Azeem Hoda H. , Osman Gamalat Y. , Mohamed Azza H. 
Published: June 2023

Abstract
Nanotechnology has come a long way in our lives. However, it maintains some negative effects on the environment. This study aims to use the land snail Helix aspersa as a bioindicator. Titanium dioxide nanoparticles (TiO2NPs) had been used at 70 and 140 µg/L for two weeks by the spraying method. The oxidative biomarkers, condition index (CI), DNA damage, hemocyte count, and phagocytic activity were estimated. The toxicity of TiO2NPs was determined (LC50 = 544 µg/L). The exposure to TiO2NPs caused a significant reduction of the activities of superoxide dismutase (SOD) and catalase (CAT) in the digestive gland of Helix aspersa (the activity of CAT was 3.4 ± 0.1 (P = 0.001), SOD was 11 ± 1 (P = 0.0002) at concentration 140 µg/L after two weeks). The activity of glutathione peroxidase (GPX) was (1.13 ± 0.01 µ/mg protein at 140 µg/L compared with controls (5.47 ± 0.01 µ/mg protein). The treatment caused DNA damage in the hemocytes (tail DNA % = 8.66 ± 0.02 and tail moment = 52.99 ± 0 at140 µg/L (P = 0.002)). In the digestive gland, both tail DNA % and tail moment increased (tail moment = 78.38 ± 0.08 compared with control = 2.29 ± 0.09 (P = 0.0001)). The total count of hemocytes significantly decreased after two weeks (the average number was 71 ± 1.5 compared with controls 79 ± 1.1 at 140 µg/L). Furthermore, TiO2NPs caused histological alterations in the digestive gland of Helix aspersa. It can be concluded that the Helix aspersa can be used as environmental pollution bioindicator. A comprehensive evaluation of toxic effects induced by TiO2NPs in vivo assays must be investigated.
Sources of performance variability in deep learning-based polyp detection
Authors: Tran T. N. , Adler T. J. , Yamlahi A. , Christodoulou E. , Godau P. , Reinke A. , Tizabi M. D. , Sauer P. , Persicke T. , Albert J. G. , Maier-Hein L. 
Published: June 2023

Abstract
Purpose
Validation metrics are a key prerequisite for the reliable tracking of scientific progress and for deciding on the potential clinical translation of methods. While recent initiatives aim to develop comprehensive theoretical frameworks for understanding metric-related pitfalls in image analysis problems, there is a lack of experimental evidence on the concrete effects of common and rare pitfalls on specific applications. We address this gap in the literature in the context of colon cancer screening.

Methods
Our contribution is twofold. Firstly, we present the winning solution of the Endoscopy Computer Vision Challenge on colon cancer detection, conducted in conjunction with the IEEE International Symposium on Biomedical Imaging 2022. Secondly, we demonstrate the sensitivity of commonly used metrics to a range of hyperparameters as well as the consequences of poor metric choices.

Results
Based on comprehensive validation studies performed with patient data from six clinical centers, we found all commonly applied object detection metrics to be subject to high inter-center variability. Furthermore, our results clearly demonstrate that the adaptation of standard hyperparameters used in the computer vision community does not generally lead to the clinically most plausible results. Finally, we present localization criteria that correspond well to clinical relevance.

Conclusion
We conclude from our study that (1) performance results in polyp detection are highly sensitive to various design choices, (2) common metric configurations do not reflect the clinical need and rely on suboptimal hyperparameters and (3) comparison of performance across datasets can be largely misleading. Our work could be a first step towards reconsidering common validation strategies in deep learning-based colonoscopy and beyond.
Diameter distributions in Pinus sylvestris L. stands: evaluating modelling approaches including a machine learning technique
Authors: Güner Şükrü Teoman , Diamantopoulou Maria J. , Özçelik Ramazan 
Published: June 2023

AbstractThe diameter distribution of trees in a stand provides the basis for determining the stand’s ecological and economic value, its structure and stability and appropriate management practices. Scots pine (Pinus sylvestris L.) is one of the most common and important conifers in Turkey, so a well-planned management schedule is critical. Diameter distribution models to accurately describe the stand structure help improve management strategies, but developing reliable models requires a deep understanding of the growth, output and constraints of the forests. The most important information derived by diameter distribution models is primary data on horizontal stand structure for each diameter class of trees: basal area and volume per unit area. These predictions are required to estimate the range of products and predicted volume and yield from a forest stand. Here, to construct an accurate, reliable diameter distribution model for natural Scots pine stands in the Türkmen Mountain region, we used Johnson’s SB distribution to represent the empirical diameter distributions of the stands using ground-based measurements from 55 sample plots that included 1219 trees in natural distribution zones of the forests. As an alternative, nonparametric approach, which does not require any predefined function, an artificial intelligence model was constructed based on support vector machine methodology. An error index was calculated to evaluate the results. Overall, both Johnson’s SB probability density function with a three-parameter recovery approach and the support vector regression methodology provided reliable estimates of the diameter distribution of these stands.
Acute dyspnea in the emergency department: a clinical review
Authors: Santus Pierachille , Radovanovic Dejan , Saad Marina , Zilianti Camilla , Coppola Silvia , Chiumello Davide Alberto , Pecchiari Matteo 
Published: June 2023

AbstractAcute dyspnea represents one of the most frequent symptoms leading to emergency room evaluation. Its significant prognostic value warrants a careful evaluation. The differential diagnosis of dyspnea is complex due to the lack of specificity and the loose association between its intensity and the severity of the underlying pathological condition. The initial assessment of dyspnea calls for prompt diagnostic evaluation and identification of optimal monitoring strategy and provides information useful to allocate the patient to the most appropriate setting of care. In recent years, accumulating evidence indicated that lung ultrasound, along with echocardiography, represents the first rapid and non-invasive line of assessment that accurately differentiates heart, lung or extra-pulmonary involvement in patients with dyspnea. Moreover, non-invasive respiratory support modalities such as high-flow nasal oxygen and continuous positive airway pressure have aroused major clinical interest, in light of their efficacy and practicality to treat patients with dyspnea requiring ventilatory support, without using invasive mechanical ventilation. This clinical review is focused on the pathophysiology of acute dyspnea, on its clinical presentation and evaluation, including ultrasound-based diagnostic workup, and on available non-invasive modalities of respiratory support that may be required in patients with acute dyspnea secondary or associated with respiratory failure.
Co-creating educational consumer journeys: A sensemaking perspective
Authors: Beverland Michael B. , Cankurtaran Pınar , Micheli Pietro , Wilner Sarah JS 
Published: June 2023

AbstractTo date, customer education has been framed in terms of one-way information provision, at odds with much of the literature on meaning co-creation. Drawing on an ethnography of a specialty coffee purveyor, we show how staff and consumers co-create educational consumer journeys through the deployment of seven practices: auditing, realignment, marrying competing logics, negotiating scripts, evangelizing, expanding collective knowledge, and impression management. These practices require staff and consumers to enact three different educational roles (educator, student, and peer), which are necessary for the co-creation and extension of consumer journeys. The roles, practices and the journeys themselves emerge iteratively through sensebreaking, sensegiving, and sensemaking processes among staff, consumers and the servicescape. Our findings frame customer education as a dynamic process in which meaning is co-created between participants. Furthermore, the cues and touchpoints needed for meaning-making shift as power relations between participants change. Managerially, these findings highlight the potential of co-created educational consumer journeys to expand established market categories.
Intracoronary Imaging Assessment of Stent Thrombosis
Authors: Jolly George , Ghatnekar Nikhil , Kaki Amir , Bharadwaj Aditya 
Published: June 2023

Abstract
Purpose of Review
This review focuses on the benefits, limitations, and evidence regarding the use of various intravascular imaging modalities in evaluating the etiology of stent thrombosis (ST).

Recent Findings
Intravascular ultrasound and optical coherence tomography can be used clinically to evaluate the etiology of ST including malapposition, underexpansion, stent fracture, and neoatherosclerosis. Near-infrared fluorescence has also been shown to have niche benefits in ST due to abnormal stent endothelization. Additionally, intravascular imaging also helps guide intervention depending on the etiology of stent thrombosis.

Summary
Intravascular imaging has been shown to provide valuable information regarding the etiology of ST and helps in guiding intervention for these lesions.
Systematic assessment of SpaceLiner passenger cabin emergency separation using multi-body simulations
Authors: Sippel Martin , Stappert Sven , Bayrak Yusuf Mete , Bussler Leonid 
Published: June 2023

AbstractThe SpaceLiner ultra-high-speed rocket-propelled passenger transport is in Phase A conceptual design. The ongoing concept evolution is addressing system aspects of the next configuration release 8. The space transportation role of the SpaceLiner concept as a TSTO-launcher is further refined and suitable precursor steps with expendable upper stages are investigated. In the central part of the paper, the separation of the passenger cabin and rescue capsule and its subsystems is systematically investigated for relevant emergency conditions. The separation process is studied taking into account multi-body dynamics of the up to three vehicles. A critical assessment of the baseline procedure and potential improvements of components’ design and sequences are discussed.
Input data resolution affects the conservation prioritization outcome of spatially sparse biodiversity features
Authors: Tanhuanpää Topi , Mikkonen Ninni , Kujala Heini , Heinaro Einari , Mäyrä Janne , Kumpula Timo 
Published: June 2023

AbstractDetailed spatial data are an essential part of land use planning and decision-making. Their spatial resolution sets limitations to their use, as coarse datasets are not suitable for detecting small-scale phenomena. In this study, we explored the effects of spatial resolution on the ecological outcome of a conservation prioritization process in Zonation software. Our study area was in Evo, southern Finland, covering a mosaic of managed and conserved forests. We produced the feature layers describing the forest characteristics using high-resolution remote sensing datasets, object-based mapping methods, and forest site type data. We found that increasing the resolution above the 16 m baseline resolution resulted in substantial errors. The conservation errors were the highest for rare features related to European Aspen, whereas the common features related to dominant tree species could benefit from the growth of cell size. We conclude that adequate spatial resolution is a prerequisite for efficient conservation prioritization, and that the size and spatial distribution of the features affect the resolution requirements.
Mental and Physical Health Conditions Among U.S. Veterans with Cannabis Use and Cannabis Use Disorders
Authors: Livne Ofir , Mannes Zachary L. , McDowell Yoanna E. , Shmulewitz Dvora , Malte Carol A. , Saxon Andrew J. , Hasin Deborah S. 
Published: June 2023

Abstract
Purpose of Review
Veterans are a large population that is disproportionately affected by various physical and mental health conditions. The primary aim of this review is to provide a concise overview of recent literature on the prevalence of cannabis use and cannabis use disorder (CUD) among US veterans, and associations with mental and physical health conditions. We also addressed gaps in the literature by investigating associations between CUD and mental and physical health conditions in 2019 data from the Veterans Health Administration (VHA; N = 5,657,277).

Recent Findings
In total, 25 studies were reviewed. In 2019, the prevalence of Veteran cannabis use ranged from 11.9–18.7%. Cannabis use and CUD were associated with bipolar disorders, psychotic disorders, suicidality, pain conditions, and other substance use, but less consistently associated with depressive disorders, anxiety disorders, and posttraumatic stress disorder. Analyses of 2019 VHA data indicated that CUD was strongly associated with a broad array of physical and mental health conditions and mortality.

Summary
Cannabis use and CUD are prevalent and highly comorbid with other conditions among US veterans. Harm reduction methods tailored to these populations are needed.