bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Birkhead and Murta formations—organic geochemistry and organic petrography of Mesozoic fluvio-lacustrine source rocks in the Eromanga Basin, central Australia
Authors: Röth J. , Baniasad A. , Froidl F. , Ostlender J. , Boreham C. , Hall L. , Littke R. 
Published: August 2022

AbstractDue to a historic focus on the underlying Cooper Basin and a growing demand for energy in Australia, a reassessment of the Eromanga Basin in central and eastern Australia is necessary, including a more detailed characterization of its Jurassic-Cretaceous petroleum system elements. The Jurassic Birkhead Formation and the Cretaceous Murta Formation are considered the most important source rocks of the Eromanga Basin. To study the petroleum generation potential of these two formations, a set of 55 rock cores from eight petroleum exploration wells was analysed. The sample set was subject to multiple-organic geochemical and petrographical analyses to evaluate organic richness, hydrocarbon potential (Rock–Eval S1 and S2), maceral composition, thermal maturity (e.g. vitrinite reflectance), and saturated and aromatic biomarker composition. The investigated fluvio-lacustrine siltstones and carbonaceous shales exhibit low to excellent total organic carbon (TOC) content, very low sulphur and low inorganic carbon content. Thermal maturity of both formations is at the onset of the oil window (immature to early mature). The Cretaceous Murta Formation shows good hydrocarbon generation potential and, in part, high production indices, while the Jurassic Birkhead Formation generally shows low kerogen to bitumen conversion and a good to very good hydrocarbon generation potential. Dispersed, rather coarse organic matter of terrigenous origin in fine-grained siliciclastic matrix with well-preserved plant remnants including “cutinite flames” is typical. Liptinite (mainly lamalginite) content is generally higher in the Murta Formation (including the occurrence of Botryococcus green algae), while vitrinite is clearly dominant in the Birkhead Formation. The Birkhead solvent extracts exhibit a more heterogeneous distribution of n-alkanes with distinct maxima in the long-chain range, whereas shorter-chain n-alkanes dominate the Murta extracts. Based on their quality and quantity of incorporated organic matter as well as thermal maturity, the petroleum generation potential of the Murta and Birkhead formations is discussed in detail.
Synthesis and analytical characterization of N-methylated derivatives of α-tocopheramine and their oxidation products
Authors: Patel Anjan , Rosenau Thomas 
Published: August 2022

AbstractN-Methylated derivatives of α-tocopheramine, which have preliminarily been shown to have good performance as stabilizers of cellulose solutions in ionic liquids for production of cellulosic manmade fibers, have not been accessible in sufficient amounts by green syntheses. In this study, theN-methyl-,N,N-dimethyl-, andN,N,N-trimethylammonium derivatives of α-tocopheramine were synthesized and fully analytically characterized. The procedures used dimethyl carbonate as solvent and methylating agent as well as aluminum oxide as the reusable catalyst. Care was taken to ensure that the procedures conformed to green chemistry principles and were easily upscalable.Graphical abstract
Pseudospectral Shattering, the Sign Function, and Diagonalization in Nearly Matrix Multiplication Time
Authors: Banks Jess , Garza-Vargas Jorge , Kulkarni Archit , Srivastava Nikhil 
Published: August 2022

AbstractWe exhibit a randomized algorithm which, given a square matrix $$A\in \mathbb {C}^{n\times n}$$

A
∈

C

n
×
n

with $$\Vert A\Vert \le 1$$

‖
A
‖
≤
1

and $$\delta >0$$

δ
>
0

, computes with high probability an invertible V and diagonal D such that $$ \Vert A-VDV^{-1}\Vert \le \delta $$

‖
A
-
V
D

V

-
1

‖
≤
δ

using $$O(T_\mathsf {MM}(n)\log ^2(n/\delta ))$$

O
(

T
MM

(
n
)

log
2

(
n
/
δ
)

)

arithmetic operations, in finite arithmetic with $$O(\log ^4(n/\delta )\log n)$$

O
(

log
4

(
n
/
δ
)

log
n
)

bits of precision. The computed similarity V additionally satisfies $$\Vert V\Vert \Vert V^{-1}\Vert \le O(n^{2.5}/\delta )$$

‖
V
‖
‖

V

-
1

‖
≤
O

(

n

2.5

/
δ
)

. Here $$T_\mathsf {MM}(n)$$

T
MM

(
n
)

is the number of arithmetic operations required to multiply two $$n\times n$$

n
×
n

complex matrices numerically stably, known to satisfy $$T_\mathsf {MM}(n)=O(n^{\omega +\eta })$$

T
MM

(
n
)

=
O

(

n

ω
+
η

)

for every $$\eta >0$$

η
>
0

where $$\omega $$
ω
is the exponent of matrix multiplication (Demmel et al. in Numer Math 108(1):59–91, 2007). The algorithm is a variant of the spectral bisection algorithm in numerical linear algebra (Beavers Jr. and Denman in Numer Math 21(1-2):143–169, 1974) with a crucial Gaussian perturbation preprocessing step. Our result significantly improves the previously best-known provable running times of $$O(n^{10}/\delta ^2)$$

O
(

n
10

/

δ
2

)

arithmetic operations for diagonalization of general matrices (Armentano et al. in J Eur Math Soc 20(6):1375–1437, 2018) and (with regard to the dependence on n) $$O(n^3)$$

O
(

n
3

)

arithmetic operations for Hermitian matrices (Dekker and Traub in Linear Algebra Appl 4:137–154, 1971). It is the first algorithm to achieve nearly matrix multiplication time for diagonalization in any model of computation (real arithmetic, rational arithmetic, or finite arithmetic), thereby matching the complexity of other dense linear algebra operations such as inversion and QR factorization up to polylogarithmic factors. The proof rests on two new ingredients. (1) We show that adding a small complex Gaussian perturbation to any matrix splits its pseudospectrum into n small well-separated components. In particular, this implies that the eigenvalues of the perturbed matrix have a large minimum gap, a property of independent interest in random matrix theory. (2) We give a rigorous analysis of Roberts’ Newton iteration method (Roberts in Int J Control 32(4):677–687, 1980) for computing the sign function of a matrix in finite arithmetic, itself an open problem in numerical analysis since at least 1986.
Detecting non-natural language artifacts for de-noising bug reports
Authors: Hirsch Thomas , Hofer Birgit 
Published: August 2022

AbstractTextual documents produced in the software engineering process are a popular target for natural language processing (NLP) and information retrieval (IR) approaches. However, issue tickets often contain artifacts such as code snippets, log outputs and stack traces. These artifacts not only inflate the issue ticket sizes, but also can this noise constitute a real problem for some NLP approaches, and therefore has to be removed in the pre-processing of some approaches. In this paper, we present a machine learning based approach to classify textual content into natural language and non-natural language artifacts at line level. We show how data from GitHub issue trackers can be used for automated training set generation, and present a custom preprocessing approach for the task of artifact removal. The training sets are automatically created from Markdown annotated issue tickets and project documentation files. We use these generated training sets to train a Markdown agnostic model that is able to classify un-annotated content. We evaluate our approach on issue tickets from projects written in C++, Java, JavaScript, PHP, and Python. Our approach achieves ROC-AUC scores between 0.92 and 0.96 for language-specific models. A multi-language model trained on the issue tickets of all languages achieves ROC-AUC scores between 0.92 and 0.95. The provided models are intended to be used as noise reduction pre-processing steps for NLP and IR approaches working on issue tickets.
Classification and evaluation of educational apps for early childhood: Security matters
Authors: Vaiopoulou Julie , Papadakis Stamatios , Sifaki Eirini , Kalogiannakis Michail , Stamovlasis Dimitrios 
Published: August 2022

AbstractThis study explored certain popular educational apps’ vital characteristics and potential profiles (n1 = 50) for kindergarten kids. The profile analysis involved a categorization ascended from an evaluation process conducted by pre-service early childhood teachers’ (n2 = 295) at the University of Crete, Greece, using a new instrument, validated in the present research, the ETEA-2 scale. The categorization criteria were the five dimensions of the ETEA-2: Learning, Suitability, Usability, Security, and Parental Control. The classification based on Latent Class Analysis led to three apps' profiles: Cluster/profile 1 includes apps that have high values in Learning, Usability, Suitability, and medium Parental Control and Security; Cluster/Profile 2 includes apps with medium Learning, Usability, Suitability, but low Parental Control and High Security; Cluster/Profile 3 includes apps with medium Learning, Usability, Suitability, but low Parental Control and low Security. This profile scheme is an indicative categorization summarizing the crucial features that popular apps possess and can help parents and/or educators’ decision-making on choosing the desirable application for their kids. Moreover, from an independent evaluation of these specific fifty apps sought on the internet, the members of Cluster2/Profile 2 were the most popular and preferable, as suggested by the number of downloads. This profile is distinguished for the security dimension.
Fostering pre-service primary school teachers’ ability to recognize differences in pupils’ understanding of technical systems
Authors: Wammes Dannie , Slof Bert , Schot Willemijn , Kester Liesbeth 
Published: August 2022

AbstractPupils benefit from adaptive instruction and feedback from their teachers. A prerequisite for providing adaptive instruction is that teachers’ diagnostic ability enables them to correctly perceive their pupils’ skill level. A short course has been developed to improve primary school teachers’ diagnostic ability for engineering. Based on Nickerson’s anchoring and adjustment model, the participants became aware of the differences their own and pupils’ use of information when constructing technical systems. The Fischer scale was used as a model to understand and identify pupils’ development in using such information. The participants were given examples of pupils’ reconstructions of technical systems. They were asked to evaluate these work products in four ways: relative and absolute, combined with intuitive and explicit. The results reveal that relative and absolute diagnoses can differ considerably for the same teacher and between teachers, depending on whether they are implicit or explicit. Post-test results show that the course improved the ability to explain the differences between pupils’ use of information to construct a technical system. The course also had a strong, significant, positive impact on teachers’ self-efficacy beliefs about technology education.
Impact of convolutional neural network and FastText embedding on text classification
Authors: Umer Muhammad , Imtiaz Zainab , Ahmad Muhammad , Nappi Michele , Medaglia Carlo , Choi Gyu Sang , Mehmood Arif 
Published: August 2022

AbstractEfficient word representation techniques (word embeddings) with modern machine learning models have shown reasonable improvement on automatic text classification tasks. However, the effectiveness of such techniques has not been evaluated yet in terms of insufficient word vector representation for training. Convolutional Neural Network has achieved significant results in pattern recognition, image analysis, and text classification. This study investigates the application of the CNN model on text classification problems by experimentation and analysis. We trained our classification model with a prominent word embedding generation model, Fast Text on publically available datasets, six benchmark datasets including Ag News, Amazon Full and Polarity, Yahoo Question Answer, Yelp Full, and Polarity. Furthermore, the proposed model has been tested on the Twitter US airlines non-benchmark dataset as well. The analysis indicates that using Fast Text as word embedding is a very promising approach.
Severe Housing Deprivation in the European Union: a Joint Analysis of Measurement and Theory
Authors: Hick Rod , Pomati Marco , Stephens Mark 
Published: August 2022

AbstractConcerns about the quality of housing feature prominently in academic and policy discussion on housing, yet there is little agreement about how housing deprivation should be measured or monitored. In empirical studies, measures of housing deprivation are typically examined for one of two purposes—either to compare incidences of housing quality problems for different groups, which typically leads to an examination of performance of different measures of housing deprivation, or as dependent variables to examine competing theories about what explains cross-national variation in such problems, which typically ignores these measurement considerations. Our paper seeks to analyse measurement and theory jointly, focussing in particular on the EU’s severe housing deprivation measure, and its subcomponents—overcrowding and housing conditions problems. In descriptive analysis, we show that the two components of the severe housing deprivation measure are weakly related and pattern differently across nations and that the aggregation rule of the main measure has a substantial influence on observed incidences of this problem. We subsequently construct multi-level regression-based models and demonstrate that the two components have quite different determinants. Our paper has implications for the measurement of severe housing deprivation in Europe, for theories that seek to account for differences in housing outcomes, and for policy that seeks to tackle housing deprivation problems.
Cysteine Cathepsins in Breast Cancer: Promising Targets for Fluorescence-Guided Surgery
Authors: Linders Daan G. J. , Bijlstra Okker D. , Fallert Laura C. , Hilling Denise E. , Walker Ethan , Straight Brian , March Taryn L. , Valentijn A. Rob P. M. , Pool Martin , Burggraaf Jacobus , Basilion James P. , Vahrmeijer Alexander L. , Kuppen Peter J. K. 
Published: August 2022

AbstractThe majority of breast cancer patients is treated with breast-conserving surgery (BCS) combined with adjuvant radiation therapy. Up to 40% of patients has a tumor-positive resection margin after BCS, which necessitates re-resection or additional boost radiation. Cathepsin-targeted near-infrared fluorescence imaging during BCS could be used to detect residual cancer in the surgical cavity and guide additional resection, thereby preventing tumor-positive resection margins and associated mutilating treatments. The cysteine cathepsins are a family of proteases that play a major role in normal cellular physiology and neoplastic transformation. In breast cancer, the increased enzymatic activity and aberrant localization of many of the cysteine cathepsins drive tumor progression, proliferation, invasion, and metastasis. The upregulation of cysteine cathepsins in breast cancer cells indicates their potential as a target for intraoperative fluorescence imaging. This review provides a summary of the current knowledge on the role and expression of the most important cysteine cathepsins in breast cancer to better understand their potential as a target for fluorescence-guided surgery (FGS). In addition, it gives an overview of the cathepsin-targeted fluorescent probes that have been investigated preclinically and in breast cancer patients. The current review underscores that cysteine cathepsins are highly suitable molecular targets for FGS because of favorable expression and activity patterns in virtually all breast cancer subtypes. This is confirmed by cathepsin-targeted fluorescent probes that have been shown to facilitate in vivo breast cancer visualization and tumor resection in mouse models and breast cancer patients. These findings indicate that cathepsin-targeted FGS has potential to improve treatment outcomes in breast cancer patients.
Heidegger’s Unlikely Alliance with Locke in Identifying Truth and Knowledge
Authors: Knowles Atina 
Published: August 2022

AbstractThe paper examines Heidegger's notions of truth and knowledge in the context of Locke's theory of same. It argues that when Heidegger's expositions of "primordial truth" and knowledge as a "retainment of assertion" are analyzed in their Beings, new and improved definitions emerge which support Locke's ideas of truth and knowledge. It shows that Heidegger's primordial truth is the process which uncovers Locke's propositional truth and on which any knowledge must be based. Wherefrom, to solve the problem of what knowledge is and how one defines it, one must start with Heidegger's conceptions of truth and knowledge.
Drink for drink: measurement of preloading motivations for field and survey research with correlates of alcohol related harms
Authors: Sorbello Jacob G. , Devilly Grant J. 
Published: August 2022

AbstractField researchers often use categorical systems to record primary preloading motivations, while survey researchers use continuous systems to examine preloading motivation ratings. We tested the psychometric properties of the two systems for measuring preloading motivations. Six hundred and eight-one undergraduate students and social media recruited participants (178 males; 503 females) completed an online survey pertaining to their last preloading experience. We measured preloading motivations by the categorical and continuous systems, general drinking motivations, estimations of preloaded standard drinks and harm. Measurements of preloading motivations by categorical (primary motivation) and continuous systems (motivation ratings) were concordant. The continuous system of preloading motivations held mix concurrence with general drinking motivations, implying conceptual differences between the two constructs. ‘Enhancement-based’ preloading motivations had strong relationships with estimations of preloaded standard drinks, while general drinking motivations for ‘coping’ were strong correlates of harm. Preloading motivations can be measured through either categorical or continuous systems. Implications for future psychometric measurement development is discussed.
On the Dirac Spectrum of Homogeneous 3-Spheres
Authors: Kling Jordi , Schueth Dorothee 
Published: August 2022

AbstractWe show that any two left-invariant metrics on $$S^3\cong {{\text {SU}}}(2)$$

S
3

≅
SU

(
2
)

which are isospectral for the associated classical Dirac operator D must be isometric. In the case of left-invariant metrics of positive scalar curvature, we compute and use the smallest eigenvalue of $$D^2$$

D
2

. We show analogous results for left-invariant metrics on $${{\text {SO}}}(3)=S^3/\{\pm 1\}$$

SO

(
3
)

=

S
3

/

{
±
1
}

for each of its two spin structures.
The position of renal denervation in treatment of hypertension: an expert consensus statement
Authors: Zeijen V. J. M. , Kroon A. A. , van den Born B. H. , Blankestijn P. J. , Meijvis S. C. A. , Nap A. , Lipsic E. , Elvan A. , Versmissen J. , van Geuns R. J. , Voskuil M. , Tonino P. A. L. , Spiering W. , Deinum J. , Daemen J. 
Published: August 2022

AbstractHypertension is an important risk factor for cardiovascular disease. In the Netherlands, there are approximately 2.8 million people with hypertension. Despite treatment recommendations including lifestyle changes and antihypertensive drugs, most patients do not meet guideline-recommended blood pressure (BP) targets. In order to improve BP control and lower the risk of subsequent cardiovascular events, renal sympathetic denervation (RDN) has been introduced and studied as a non-pharmacological approach. While early data on the efficacy of RDN showed conflicting results, improvements in treatment protocols and study design resulted in robust new evidence supporting the potential of the technology to improve patient care in hypertensive subjects. Recently, 5 randomised sham-controlled trials demonstrated the safety and efficacy of the technology. Modelling studies have further shown that RDN is cost-effective in the Dutch healthcare setting. Given the undisputable disease burden along with the shortcomings of current therapeutic options, we postulate a new, clearly framed indication for RDN as an adjunct in the treatment of hypertension. The present consensus statement summarises current guideline-recommended BP targets, proposed workup and treatment for hypertension, and position of RDN for those patients with primary hypertension who do not meet guideline-recommended BP targets (see central illustration).
Manual Placenta Removal is Associated with Increased Postpartum Prescriptions of Antibiotics: a Retrospective Cohort Study of Data from the Anti-Infection Tool
Authors: Janson Amanda , Ignell Claes , Stuart Andrea 
Published: August 2022

AbstractPurposeNo consensus exists whether to administer prophylactic antibiotics in conjunction with manual placenta removal. This study aimed to investigate the postpartum risk of a new prescription of antibiotic treatment, a possible indirect variable for infection, after manual placenta removal.MethodsObstetric data were merged with data from the Anti-Infection Tool (Swedish antibiotic registry). All vaginal deliveries (n = 13 877) at Helsingborg Hospital, Helsingborg, Sweden, from January 1st, 2014 until June 13th, 2019 were included. Diagnosis codes for infection can be lacking, while the Anti-Infection Tool is complete as it is unavoidable in the computerized prescription system. Logistic regression analyses were performed. The risk of a prescription of antibiotics 24 h to 7 days postpartum was analyzed in the entire study population, and in a subgroup of women not having received any antibiotics 48 h prior to delivery until 24 h after delivery, referred to as “antibiotic-naïve.”ResultsManual placenta removal was associated with an increased risk of an antibiotic prescription, adjusted (a) OR = 2.9 (95%CI 1.9–4.3). In the antibiotic-naïve subgroup, manual placenta removal was associated with an increased risk of antibiotic prescription, in general, aOR = 2.2 (95%CI 1.2–4.0), endometritis-specific antibiotics, aOR = 2.7 (95%CI 1.5–4.9), and intravenous antibiotics, aOR = 4.0 (95%CI 2.0–7.9).ConclusionManual placenta removal is associated with an increased risk of antibiotic treatment postpartum. An antibiotic-naïve population might benefit from prophylactic antibiotics to reduce the risk of infection, and prospective studies are needed.