bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study progression and degree completion of autistic students in higher education: a longitudinal study
Authors: Bakker Theo , Krabbendam Lydia , Bhulai Sandjai , Meeter Martijn , Begeer Sander 
Published: March 2022

AbstractIndividuals with autism increasingly enroll in universities, but researchers know little about how their study progresses over time towards degree completion. This exploratory population study uses structural equation modeling to examine patterns in study progression and degree completion of bachelor’s students with autism spectrum disorder (n = 101) in comparison to students with other recorded conditions (n = 2,465) and students with no recorded conditions (n = 25,077) at a major Dutch university. Propensity score weighting is applied to balance outcomes. The research shows that most outcomes (grade point average, dropout rates, resits, credits, and degree completion) were similar across the three groups. Students with autism had more no-shows in the second year than their peers, which affected degree completion after 3 years. The overall performance of autistic students appeared to be adequate and comparable to their peers. However, addressing participation and inclusivity is vital to improve academic support for students with autism. These insights can enable universities to develop appropriate and timely support for all talented students to progress in their studies and complete their degrees.
On Reconstructing Parts of Quantum Theory from Two Related Maximal Conceptual Variables
Authors: Helland Inge S. 
Published: March 2022

AbstractIn the book Helland (2021) the general problem of reconstructing the Hilbert space formulation in quantum theory is discussed from the point of view of what I called conceptual variables, any variables defined by a person or by a group of persons. These variables may be inaccessible, i.e., impossible to assign numerical value to by experiments or by measurements, or accessible. One basic assumption in Helland (2021) and here is that group actions g ∈ G are defined on a space where some maximally accessible variable varies, and then accessible functions of these maximal variables are introduced. By using group representation theory the basic Hilbert space formalism is restored under the assumption that the observator or the set of observators has two related maximally accessible variables in his (their) mind(s). The notion of relationship is precisely defined here. Symmetric (self-adjoint) operators are connected to each variable, and in the discrete case the possible values of the variables are given by the eigenvalues of the operators. In this paper the main results from Helland (2021) are made more precise and more general. It turns out that the conditions of the main theorem there can be weakened in two essential ways: 1) No measurements need to be assumed, so the result is also applicable to general decision situations; 2) States can have arbitrary phase factors. Some consequences of this approach towards quantum theory are also discussed here.
Epoxy resin reinforced with graphene derivatives: physical and dielectric properties
Authors: Rehim Mona Abdel , Turky Gamal 
Published: March 2022

AbstractEpoxy resins are important industrial polymers due to their versatile properties and ease of preparation. They are used on a large scale in coating and adhesives applications. Epoxy resins are prepared by photo-curing technique or thermal curing method in presence of different hardeners. The first method is used for small areas while the latter is utilized mainly for coating applications. Graphene and its oxide have proved themselves as good fillers for epoxy resin since the formed composites demonstrated enhanced mechanical, thermal and electrical properties. This article gives insight view for synthesis techniques and properties of these composites with a deep discussion for electrical and dielectric investigations of epoxy resins loaded with threshold concentration of graphene oxide. A case study of dielectric properties of epoxy resin/modified graphene oxide composite, is presented in which effect of curing technique on dielectric behavior is explored. Although the amount of filler was kept at the threshold concentration (1% by weight) obvious change in the dielectric properties could be observed unlike the rest of properties.
The impact of pre-freezing storage time and temperature on gene expression of blood collected in EDTA tubes
Authors: Martire Serena , Valentino Paola , Marnetto Fabiana , Mirabile Luca , Capobianco Marco , Bertolotto Antonio 
Published: March 2022

Abstract
Background
Blood is a common source of RNA for gene expression studies. However, it is known to be vulnerable to pre-analytical variables. Although RNA stabilization systems have been shown to reduce such influence, traditional EDTA tubes are still widely used since they are less expensive and enable to study specific leukocyte populations. This study aimed to assess the influence of storage time and temperature between blood sampling and handling on RNA from peripheral blood mononuclear cells (PBMCs).

Methods and results
Nine blood samples were collected in EDTA tubes from 10 healthy donors. One tube from each donor was immediately processed for PBMC isolation, while the others were first incubated at either 4 degrees Celsius (°C) or room temperature for 2, 4, 6 and 24 h. RNA yield and quality and the expression level of fourt housekeeping (B2M, CASC3, GAPDH, HPRT1) and 8 target genes (CD14, CD19, CD20, IL10, MxA, TNF, TNFAIP3, NR4A2) were compared between samples.
RNA yield, quality and integrity did not vary significantly with time and temperature. B2M was the most stable housekeeping gene, while the others were increasingly influenced by storing time, especially at 4 °C. Even when normalized to B2M, the expression level of some target genes, particularly TNFAIP3 and NR4A2, was highly affected by delays in blood processing at either temperature, already from 2 h.

Conclusion
Pre-analytical processing has a great impact on transcript expression from blood collected in EDTA tubes, especially on genes related to inflammation. Standardized procedure of blood handling are needed to obtain reliable results.
Sexual reproduction trait expressions of grassland species along a gradient of nitrogen: phosphorus stoichiometry
Authors: Wang Shuqiong , van Dijk Jerry , Wassen Martin J. 
Published: March 2022

Abstract
Aims
Plant investment in sexual reproduction is affected by nitrogen (N): phosphorus (P) stoichiometry. It has been suggested that an important adaptation to strong P limitation is reduced investment in sexual reproduction. We aim to investigate the specific influence of N:P on sexual reproduction performance within and between grassland species.

Methods
Eleven grassland species were selected in ten plots covering N limitation, co-limitation and P limitation. Nutrients in soil and above-ground biomass were determined, plus soil pH and soil moisture. A range of sexual reproduction traits were measured as a proxy for investment in sexual reproduction.

Results
At the intraspecific level: compared with N-limited plots, in P-limited/co-limited plots, flowering time was later, flowering period in individuals was shorter, and number of flowers (inflorescences) per individual was smaller. At the interspecific level, in P-limited/co-limited plots, species had a significantly earlier flowering time and a longer seed stalk and seed panicle, than those in N-limited plots. However, flowering period was shorter and number of flowers (inflorescences) per individual was smaller under P limitation/co-limitation. Moreover, significant correlations between soil pH and soil moisture, and sexual reproduction performance of the selected grassland species were also found.

Conclusions
P limitation/co-limitation restrict the sexual reproduction of grassland species, which may hamper their dispersal capacity. We recommend future studies further analyze the relationship between soil pH and N:P stoichiometry and the influence of soil pH, as well as soil moisture on sexual reproduction performance of grassland species in addition to analyzing N:P stoichiometry.
A loss function to evaluate agricultural decision-making under uncertainty: a case study of soil spectroscopy
Authors: Breure T. S. , Haefele S. M. , Hannam J. A. , Corstanje R. , Webster R. , Moreno-Rojas S. , Milne A. E. 
Published: March 2022

AbstractModern sensor technologies can provide detailed information about soil variation which allows for more precise application of fertiliser to minimise environmental harm imposed by agriculture. However, growers should lose neither income nor yield from associated uncertainties of predicted nutrient concentrations and thus one must acknowledge and account for uncertainties. A framework is presented that accounts for the uncertainty and determines the cost–benefit of data on available phosphorus (P) and potassium (K) in the soil determined from sensors. For four fields, the uncertainty associated with variation in soil P and K predicted from sensors was determined. Using published fertiliser dose–yield response curves for a horticultural crop the effect of estimation errors from sensor data on expected financial losses was quantified. The expected losses from optimal precise application were compared with the losses expected from uniform fertiliser application (equivalent to little or no knowledge on soil variation). The asymmetry of the loss function meant that underestimation of P and K generally led to greater losses than the losses from overestimation. This study shows that substantial financial gains can be obtained from sensor-based precise application of P and K fertiliser, with savings of up to £121 ha−1for P and up to £81 ha−1for K, with concurrent environmental benefits due to a reduction of 4–17 kg ha−1applied P fertiliser when compared with uniform application.
Processing of remote sensing information to retrieve leaf area index in barley: a comparison of methods
Authors: Rosso Pablo , Nendel Claas , Gilardi Nicolas , Udroiu Cosmin , Chlebowski Florent 
Published: March 2022

AbstractLeaf area index (LAI) is a key variable in understanding and modeling crop-environment interactions. With the advent of increasingly higher spatial resolution satellites and sensors mounted on remotely piloted aircrafts (RPAs), the use of remote sensing in precision agriculture is becoming more common. Since also the availability of methods to retrieve LAI from image data have also drastically expanded, it is necessary to test simultaneously as many methods as possible to understand the advantages and disadvantages of each approach. Ground-based LAI data from three years of barley experiments were related to remote sensing information using vegetation indices (VI), machine learning (ML) and radiative transfer models (RTM), to assess the relative accuracy and efficacy of these methods. The optimized soil adjusted vegetation index and a modified version of the Weighted Difference Vegetation Index performed slightly better than any other retrieval method. However, all methods yielded coefficients of determination of around 0.7 to 0.9. The best performing machine learning algorithms achieved higher accuracies when four Sentinel-2 bands instead of 12 were used. Also, the good performance of VIs and the satisfactory performance of the 4-band RTM, strongly support the synergistic use of satellites and RPAs in precision agriculture. One of the methods used, Sen2-Agri, an open source ML-RTM-based operational system, was also able to accurately retrieve LAI, although it is restricted to Sentinel-2 and Landsat data. This study shows the benefits of testing simultaneously a broad range of retrieval methods to monitor crops for precision agriculture.
From indexation policies through citation networks to normalized citation impacts: Web of Science, Scopus, and Dimensions as varying resonance chambers
Authors: Stahlschmidt Stephan , Stephen Dimity 
Published: March 2022

AbstractDimensions was introduced as an alternative bibliometric database to the well-established Web of Science (WoS) and Scopus, however all three databases have fundamental differences in coverage and content, resultant from their owners’ indexation philosophies. In light of these differences, we explore here, using a citation network analysis and assessment of normalized citation impact of overlapping publications indexed in all three databases, whether the three databases offer structurally different perspectives of the bibliometric landscape or if they are essentially homogenous substitutes. Our citation network analysis of core and exclusive 2016–2018 publications revealed a large set of core publications indexed in all three databases that are highly self-referential. In comparison, each database selected a set of exclusive publications that appeared to hold similarly low levels of relevance to the core set and to one another, with slightly more internal communication between exclusive publications in Scopus and Dimensions than WoS. Our comparison of normalized citations for 41,848 publications indexed in all three databases found that German sectors were valuated as more impactful in Scopus and Dimensions compared to WoS, particularly for sectors with an applied research focus. We conclude that the databases do present structurally different perspectives, although Scopus and Dimensions with their additional circle of applied research vary more from the more base research-focused WoS than they do from one another.
Impact of model settings on the text-based Rao diversity index
Authors: Zielinski Andrea 
Published: March 2022

AbstractPolicymakers and funding agencies tend to support scientific work across disciplines, thereby relying on indicators for interdisciplinarity. Recently, text-based quantitative methods have been proposed for the computation of interdisciplinarity that hold promise to have several advantages over the bibliometric approach. In this paper, we provide a systematic analysis of the computation of the text-based Rao index, based on probabilistic topic models, comparing a classical LDA model versus a neural network topic model. We provide a systematic analysis of model parameters that affect the diversity scores and make the interaction between its different components explicit. We present an empirical study on a real data set, upon which we quantify the diversity of the research within several departments of Fraunhofer and Max Planck Society by means of scientific abstracts published in Scopus between 2008 and 2018. Our experiments show that parameter variations, i.e. the choice of the Number of topics, hyper-parameters, and size and balance of the underlying data used for training the model, have a strong effect on the topic model-based Rao metrics. In particular, we could observe that the quality of the topic models impacts on the downstream task of computing the Rao index. Topic models that yield semantically cohesive topics are less affected by fluctuations when varying over the number of topics, and result in more stable measurements of the Rao index.
Citation of retracted research: a case-controlled, ten-year follow-up scientometric analysis of Scott S. Reuben’s malpractice
Authors: Szilagyi Istvan-Szilard , Schittek Gregor A. , Klivinyi Christoph , Simonis Holger , Ulrich Torsten , Bornemann-Cimenti Helmar 
Published: March 2022

AbstractA major problem in scientific literature is the citation of retracted research. Until now, no long-term follow-up of the course of citations of such articles has been published. In the present study, we determined the development of citations of retracted articles based on the case of anaesthesiologist and pain researcher Scott S. Reuben, over a period of 10 years and compared them to matched controls. We screened four databases to find retracted publications by Scott S. Ruben and reviewed full publications for indications of retraction status. To obtain a case-controlled analysis, all Reuben’s retracted articles were compared with the respective citations of the preceeding and subsequent neighbouring articles within the same journal. There were 420 citations between 2009 and 2019, of which only 40% indicated the publication being retracted. Over a 10-year period, an increasing linear trend is observed in citations of retracted articles by Scott S. Ruben that are not reported as retracted (R2 = 0.3647). Reuben’s retracted articles were cited 92% more often than the neighbouring non-retracted articles. This study highlights a major scientific problem. Invented or falsified data are still being cited after more than a decade, leading to a distortion of the evidence and scientometric parameters.
Four problems of the h-index for assessing the research productivity and impact of individual authors
Authors: Bi Henry H. 
Published: March 2022

AbstractThis paper reveals that when the h-index is used to assess the research productivity and impact of individual authors, four major problems exist because the h-index does not take into account the number of authors in each publication. This paper shows that the fractional h-index (or the individual hi-index in this paper), which distributes each publication’s received citations among its authors, can solve these problems effectively. This paper recommends that websites (such as scholar.google.com and researchgate.net) should add the hi-index for the sake of building a fairer and more ethical research community.
Introducing CARESSER: A framework for in situ learning robot social assistance from expert knowledge and demonstrations
Authors: Andriella Antonio , Torras Carme , Abdelnour Carla , Alenyà Guillem 
Published: March 2022

AbstractSocially assistive robots have the potential to augment and enhance therapist’s effectiveness in repetitive tasks such as cognitive therapies. However, their contribution has generally been limited as domain experts have not been fully involved in the entire pipeline of the design process as well as in the automatisation of the robots’ behaviour. In this article, we present aCtive leARning agEnt aSsiStive bEhaviouR (CARESSER), a novel framework that actively learns robotic assistive behaviour by leveraging the therapist’s expertise (knowledge-driven approach) and their demonstrations (data-driven approach). By exploiting that hybrid approach, the presented method enables in situ fast learning, in a fully autonomous fashion, of personalised patient-specific policies. With the purpose of evaluating our framework, we conducted two user studies in a daily care centre in which older adults affected by mild dementia and mild cognitive impairment (N = 22) were requested to solve cognitive exercises with the support of a therapist and later on of a robot endowed with CARESSER. Results showed that: (i) the robot managed to keep the patients’ performance stable during the sessions even more so than the therapist; (ii) the assistance offered by the robot during the sessions eventually matched the therapist’s preferences. We conclude that CARESSER, with its stakeholder-centric design, can pave the way to new AI approaches that learn by leveraging human–human interactions along with human expertise, which has the benefits of speeding up the learning process, eliminating the need for the design of complex reward functions, and finally avoiding undesired states.
MinerAlert: an hybrid approach for web mining detection
Authors: Tommasi Franco , Catalano Christian , Corvaglia Umberto , Taurino Ivan 
Published: March 2022

AbstractThe introduction of new memory-based crypto-mining techniques and the rise of new web technologies like WebAssembly, made the use of browsers for crypto-currencies mining more and more convenient and popular. That, in turn, originated a new form of computer piracy, called cryptojacking, which is rapidly gaining ground on the web. A cryptojacking site exploits its visitors’ hardware resources to secretly mine crypto-currencies. This paper analyzes current web-based cryptojacking detection methods in order to propose a novel hybrid strategy. Current detection methods are found to require either considerable computer administration skills or execution privileges usually not available to common users. In this view, a method, named MinerAlert, has been designed and proposed, aiming at detecting in real-time sites performing cryptojacking. To address the limitations of current methods, the method implementation has been achieved through a browser extension. The present paper describes the method’s details and its implementation. It also reports the experimental results of its utilization, showing its positive performances in terms of ease of use, successful detections and speed.
Self-calibration of C-arm imaging system using interventional instruments during an intracranial biplane angiography
Authors: Chabi Negar , Iuso Domenico , Beuing Oliver , Preim Bernhard , Saalfeld Sylvia 
Published: March 2022

Abstract

Purpose

To create an accurate 3D reconstruction of the vascular trees, it is necessary to know the exact geometrical parameters of the angiographic imaging system. Many previous studies used vascular structures to estimate the system’s exact geometry. However, utilizing interventional devices and their relative features may be less challenging, as they are unique in different views. We present a semi-automatic self-calibration approach considering the markers attached to the interventional instruments to estimate the accurate geometry of a biplane X-ray angiography system for neuroradiologic use.

Methods

A novel approach is proposed to detect and segment the markers using machine learning classification, a combination of support vector machine and boosted tree. Then, these markers are considered as reference points to optimize the acquisition geometry iteratively.

Results

The method is evaluated on four clinical datasets and three pairs of phantom angiograms. The mean and standard deviation of backprojection error for the catheter or guidewire before and after self-calibration are $$7.13\pm 6.47$$

7.13
±
6.47

mm and $$0.10\pm 0.06$$

0.10
±
0.06

mm, respectively. The mean and standard deviation of the 3D root-mean-square error (RMSE) for some markers in the phantom reduced from $$0.51\pm 0.11$$

0.51
±
0.11

to $$0.31\pm 0.08$$

0.31
±
0.08

mm.

Conclusion

A semi-automatic approach to estimate the accurate geometry of the C-arm system was presented. Results show the reduction in the 2D backprojection error as well as the 3D RMSE after using our proposed self-calibration technique. This approach is essential for 3D reconstruction of the vascular trees or post-processing techniques of angiography systems that rely on accurate geometry parameters.