bluuebunny/crossref_metadata_2025_split huggingface dataset:
Talented athletes as high achievers—only in sports? Analysis of academic performance and the impact of dual career assistance programmes in upper secondary school
Authors: Sallen Jeffrey , Wendeborn Thomas , Gerlach Erin 
Published: April 2023

AbstractThe simultaneous pursuit of success in elite sport and the highest school qualification is considered to be one of the challenges for adolescents who are sporting talents. Dual career assistance programmes (DCAPs) for student-athletes are designed to help master this challenge in the best possible way. This study focusses on the upper secondary school performance of 200 student-athletes from an elite sports school. First, the school performance of student-athletes enrolled in two different DCAPs was compared. In addition to the educational services in DCAP‑1, DCAP‑2 includes a 1-year extension of the school period and the option of spreading the final exam phase out over several school years. Second, the school performance of student-athletes was compared with the performance of the entire student population. The analyses yielded the following findings: 1) student-athletes’ school performance is well above the average of the entire student population. 2) Although, DCAP‑2 users are much more involved in elite sport, their school performance and performance development do not differ from DCAP‑1 users. These results do not provide any indication of a systematic neglect of student-athletes’ academic career in favour of their athletic career. DCAPs appear to ensure the success of student-athletes’ academic careers effectively.
Minimally invasive technique for gastric GIST at challenging locations: single incision surgical gastroscopy
Authors: Stiekema Jurrien , Luttikhold Joanna , Heineman David , Neerincx Maarten , Daams Freek 
Published: April 2023

AbstractOrgan sparing resection of gastrointestinal stromal tumors (GISTs) located in the proximal stomach or esophagogastric junction can be challenging, resulting in proximal or total gastrectomy to facilitate a radical resection without tumor spill. We developed and evaluated a single incision surgical gastroscopy (SISG) procedure to provide a technically feasible alternative for the removal of gastric GISTs at these challenging locations. We developed an endoluminal resection of gastric GISTs through a small single abdominal incision and longitudinal ventral gastrotomy. Patients with a proximal tumor location, in whom a wedge resection was deemed challenging on pre-operative investigation were included in the current series. Safety, short-term oncological and surgical outcome were evaluated. We performed SISG in six consecutive patients with histopathological proven or suspected gastric GIST. In all patients, the procedure was performed successfully with no tumor rupture. The mean operative time was 61 min and there were no significant complications. Pathological examination showed a microscopically radical resection in all patients. Single incision surgical gastroscopy is a feasible technique with excellent short-term oncological and surgical outcomes. This technique serves as a good alternative for complicated resections for gastric GISTs at challenging locations.
StringENT test suite: ENT battery revisited for efficient P value computation
Authors: Almaraz Luengo Elena , Alaña Olivares Bittor , García Villalba Luis Javier , Hernandez-Castro Julio , Hurley-Smith Darren 
Published: April 2023

AbstractRandom numbers play a key role in a wide variety of applications, ranging from mathematical simulation to cryptography. Generating random or pseudo-random numbers is not an easy task, especially when hardware, time and energy constraints are considered. In order to assess whether generators behave in a random fashion, there are several statistical test batteries. ENT is one of the simplest and most popular, at least in part due to its efficacy and speed. Nonetheless, only one of the tests of this suite provides a p value, which is the most useful and standard way to determine whether the randomness hypothesis holds, for a certain significance level. As a consequence of this, rather arbitrary and at times misleading bounds are set in order to decide which intervals are acceptable for its results. This paper introduces an extension of the battery, named StringENT, which, while sticking to the fast speed that makes ENT popular and useful, still succeeds in providing p values with which sound decisions can be made about the randomness of a sequence. It also highlights a flagrant randomness flaw that the classical ENT battery is not capable of detecting but the new StringENT notices, and introduces two additional tests.
Functional surface homogenization of nanobiochar with cation exchanger for improved removal performance of methylene blue and lead pollutants
Authors: Mahmoud Safe ELdeen M. E. , Ursueguia David , Mahmoud Mohamed E. , Abdel-Fattah Tarek M. , Díaz Eva 
Published: April 2023

AbstractBiochar materials are good examples of sustainable adsorbents with appreciable recent interests and applications in water treatment. The disadvantage of using unmodified pristine biochars in water treatment is mainly related to the inhomogeneous distribution of various surface functional groups. Therefore, the current study is designed to functionalize and homogenize the surface of a selected nanobiochar with a cation exchanger using hydrothermal and solvothermal microwave irradiation. The adsorption behavior of immobilized Amberlite cation exchanger onto Cynara scolymus nanobiochar (ACE@CSNB) was compared versus the pristine Cynara scolymus nanobiochar (CSNB). ACE@CSNB was categorized as a typical mesoporous material (mean pore size = 2.238 nm) and the FT-IR spectra confirmed surface modification via two characteristic peaks at 1140–1250 cm−1 and 1030–1070 cm−1 for R-SO3− with S = O. The TPD–MS analysis of CSNB and ACE@CSNB referred to the presence of carboxyl, lactonic, and acid anhydride groups as well as phenolic moieties. The adsorption behavior of methylene blue dye and lead ions by ACE@CSNB was found much higher than those concluded by CSNB providing maximum adsorptive capacity values owing to the played clear role by Amberlite cation exchanger. Moreover, ACE@CSNB was efficiently regenerated and confirmed MB and Pb(II) removal with 92.26% and 1000 µmol g−1, respectively Finally, the removal efficiency values from three water matrices by ACE@CSNB biochar were characterized as 91.74–98.19% and 96.27–99.14% for Pb(II) and MB, respectively to refer to the validity and applicability of the investigated ACE@CSNB biochar for treatment of these two pollutants from real water samples with excellent efficiency.
Graphical Abstract
Antifungal alkaloids from Mahonia fortunei against pathogens of postharvest fruit
Authors: Wang Xiao-Na , Wang Zhao-Jie , Zhao Yun , Wang Huan , Xiang Mei-Ling , Liu Yang-Yang , Zhao Li-Xing , Luo Xiao-Dong 
Published: April 2023

AbstractPostharvest pathogens can affect a wide range of fresh fruit and vegetables, including grapes, resulting in significant profit loss. Isoquinoline alkaloids of Mahoniafortunei, a Chinese herbal medicine, have been used to treat infectious microbes, which might be effective against postharvest pathogens. The phytochemical and bioactive investigation of this plant led to the isolation of 18 alkaloids, of which 9 compounds inhibited the growth of Botrytiscinerea and 4 compounds against Penicilliumitalicum. The antifungal alkaloids could change the mycelium morphology, the total lipid content, and leak the cell contents of B.cinerea. Furthermore, the two most potent antifungal alkaloids, berberine (13) completely inhibited effect on gray mold of table grape at 512 mg L−1, while jatrorrhizine (18) exhibited an inhibition rate > 90% on grape rot at the same concentration, with lower cytotoxicity and residue than chlorothalonil, which suggested that ingredients of M.fortunei might be a low-toxicity, low-residue, eco-friendly botanical fungicide against postharvest pathogens.
Graphical Abstract
Compression Therapy in Dermatology
Authors: Romanelli Marco , Manzo Margiotta Flavia , Michelucci Alessandra , Granieri Giammarco , Janowska Agata , Dini Valentina 
Published: April 2023

Abstract

Purpose of Review
The compression therapy provides valuable support during management of vascular and inflammatory lower leg skin disorders. The review outlines the mechanism of action and the treatment options available with indications for use in wound management and general dermatology.

Recent Findings
Atypical wounds such as pyoderma gangrenosum, cutaneous vasculitis and other inflammatory skin diseases may benefit from the use of compression therapy. Adherence to treatment is always a challenging aspects for patients and caregiver, but modern technologies and specific materials have improved the compliance during treatment.

Summary
Compression therapy is a main option in vascular ulcer management. The technology provided by different devices together with new methods of bandaging application have increased the outcomes and acceptability from patients. Physicians should be aware of the advantages provided by compression therapy in skin diseases.
Primes and G-primes in $$\mathbb {Z}$$-nearalgebras
Authors: Chandel Shalini , Sharma Ram Parkash 
Published: April 2023

AbstractLet N be a $$\mathbb {Z}$$
Z
-nearalgebra; that is, a left nearring with identity satisfying $$ k(nn^{\prime })=(kn)n^{\prime }=n(kn^{\prime })$$

k

(
n

n
′

)

=

(
k
n
)

n
′

=
n

(
k

n
′

)

for all $$k\in \mathbb {Z}$$

k
∈
Z

, $$n,n^{\prime }\in N$$

n
,

n
′

∈
N

and G be a finite group acting on N. Then the skew group nearring $$N*G$$

N

∗
G

of the group G over N is formed. If N is 3-prime ($$aNb=0$$

a
N
b
=
0

implies $$a=0$$

a
=
0

or $$b=0$$

b
=
0

), then a nearring of quotients $$ Q_{0}(N)$$

Q
0

(
N
)

is constructed using semigroup ideals $$A_{i}$$

A
i

(a multiplicative closed set $$A_{i}\subseteq N$$

A
i

⊆
N

such that $$A_{i}N\subseteq A_{i}\supseteq NA_{i}$$

A
i

N
⊆

A
i

⊇
N

A
i

) of N and the maps $$f_{i}:A_{i}\rightarrow N$$

f
i

:

A
i

→
N

satisfying $$ (na)f_{i}=n(af_{i})$$

(
n
a
)

f
i

=
n

(
a

f
i

)

, $$n\in N$$

n
∈
N

and $$a\in A_{i}$$

a
∈

A
i

. Through $$Q_{0}(N)$$

Q
0

(
N
)

, we discuss the relationships between invariant prime subnearrings (I-primes) of $$N*G$$

N

∗
G

and G-invariant prime subnearrings (GI-primes) of N. Particularly we describe all the I-primes $$P_{i}$$

P
i

of $$N*G$$

N

∗
G

such that each $$ P_{i}\cap N=\{0\}$$

P
i

∩
N
=

{
0
}

, a GI-prime of N. As an application, we settle Incomparability and Going Down Problem for N and $$N*G$$

N

∗
G

in this situation.
A Novel Framework for the Generation of Multiple Choice Question Stems Using Semantic and Machine-Learning Techniques
Authors: Kumar Archana Praveen , Nayak Ashalatha , K Manjula Shenoy , Chaitanya  , Ghosh Kaustav 
Published: April 2023

Abstract
Multiple Choice Questions (MCQs) are a popular assessment method because they enable automated evaluation, flexible administration and use with huge groups. Despite these benefits, the manual construction of MCQs is challenging, time-consuming and error-prone. This is because each MCQ is comprised of a question called the "stem", a correct option called the "key" along with alternative options called "distractors" whose construction demands expertise from the MCQ developers. In addition, there are different kinds of MCQs such as Wh-type, Fill-in-the-blank, Odd one out, and many more needed to assess understanding at different cognitive levels. Automatic Question Generation (AQG) for developing heterogeneous MCQ stems has generally followed two approaches: semantics-based and machine-learning-based. Questions generated via AQG techniques can be utilized only if they are grammatically correct. Semantics-based techniques have been able to generate a range of different types of grammatically correct MCQs but require the semantics to be specified. In contrast, most machine-learning approaches have been primarily able to generate only grammatically correct Fill-in-the-blank/Cloze by reusing the original text. This paper describes a technique for combining semantic-based and machine-learning-based techniques to generate grammatically correct MCQ stems of various types for a technical domain. Expert evaluation of the resultant MCQ stems demonstrated that they were promising in terms of their usefulness and grammatical correctness.
A novel ensemble learning-based model for network intrusion detection
Authors: Thockchom Ngamba , Singh Moirangthem Marjit , Nandi Utpal 
Published: April 2023

AbstractThe growth of Internet and the services provided by it has been growing exponentially in the past few decades. With such growth, there is also an ever-increasing threat to the security of networks. Several efficient countermeasures have been placed to deal with these threats in the network, such as the intrusion detection system (IDS). This paper proposes an ensemble learning-based method for building an intrusion detection model. The model proposed in this paper has relatively better overall performance than its individual classifiers. This ensemble model is constructed using lightweight machine learning models, i.e., Gaussian naive Bayes, logistic regression and decision tree as the base classifier and stochastic gradient descent as the meta-classifier. The performance of this proposed model and the individual classifiers used to build the ensemble model is trained and evaluated using three datasets, namely, KDD Cup 1999, UNSW-NB15 and CIC-IDS2017. The performance is evaluated for binary class as well as multiclass classifications. The proposed method also incorporates the usage of a feature selection method called Chi-square test to select only the most relevant features. The empirical results definitively prove that using an ensemble classifier can be immensely helpful in the field of intrusion detection system with unbalanced datasets where misclassifications can be costly.
A time-sensitive learning-to-rank approach for cloud simulation resource prediction
Authors: Xiao Yuhao , Yao Yiping , Chen Kai , Tang Wenjie , Zhu Feng 
Published: April 2023

AbstractPredicting the computing resources required by simulation applications can provide a more reasonable resource-allocation scheme for efficient execution. Existing prediction methods based on machine learning, such as classification/regression, typically must accurately predict the runtime of simulation applications and select the optimal computing resource allocation scheme by sorting the length of the simulation runtime. However, the ranking results are easily affected by the simulation runtime prediction accuracy. This study proposes a time-sensitive learning-to-rank (LTR) approach for cloud simulations resource prediction. First, we use the Shapley additive explanation (SHAP) value from the field of explainable artificial intelligence (XAI) to analyze the impact of relevant factors on the simulation runtime and to extract the feature dimensions that significantly affect the simulation runtime. Second, by modifying the target loss function of the rankboost algorithm and training a time-sensitive LTR model based on simulation features, we can accurately predict the computing resource allocation scheme that maximizes the execution efficiency of simulation applications. Compared with the traditional machine learning prediction algorithm, the proposed method can improve the average sorting performance by 3%–48% and can accurately predict the computing resources required for the simulation applications to execute in the shortest amount of time.
Effect of thermal treatment and moisture content on the mechanical properties of soft sandstone under triaxial extension: an experimental study
Authors: Liu Zelin , Ma Chunde , Wei Xin’ao 
Published: April 2023

AbstractThe problem of deformation damage of soft rocks and the effect of temperature and moisture content on the mechanical properties of rocks has received wide attention in recent decades. To investigate the effect of thermal treatment and moisture content on the triaxial extension mechanical properties and fracture characteristics of soft rock, triaxial extension tests were conducted on sandstone specimens with good homogeneity at different heating temperatures (T = 25, 100, 200, 300, 400, 500, 800 °C) and moisture contents (Kt = 0, 20, 50, 80, 100%) with the help of MTS815 testing machine. The results showed that: For rock specimens with Kt = 0, the mass of the specimens decreased monotonically with the increase of temperature, the elastic modulus (E) showed an overall decreasing trend, and the axial ultimate strain (εamax) was Ω-like pattern. The P-wave velocity (Vp) and axial stress showed a trend of increasing first and then decreasing around T = 200 °C. All the specimens fractured instantaneously, and the SEM images showed some grain expansion before T ≤ 200 °C. At the same time, microcracks expand and become more intense after T > 200 °C. In addition, the multiple mineral compositions in the specimens showed more complex changes after different thermal treatments, which was another main reason for the deterioration of the specimens. Furthermore, the E decreases while εamax increases with the moisture content, and before T = 500 °C and Kt = 20%, the Kt significantly influences the triaxial extension strength; after that, however, the effect is minimal.
Impact of liquid nitrogen freeze–thaw on multistage gas flow: differences between shallow and deep coal in Qinshui Basin
Authors: Sun Yingfeng , Zhao Yixin , Li Yulin , Danesh Nima Noraei , Zhang Zetian 
Published: April 2023

AbstractLiquid nitrogen freeze–thaw (LNFT) is an environmentally-friendly permeability enhancement technology. There are significant differences between shallow and deep coal in their composition and stress history. Therefore, it is necessary to reveal the difference in the impact of LNFT on the multistage gas flow between shallow and deep coal. In this paper, the differences in multistage gas flow were revealed from the perspective of a multiscale structure evolution, and the differences in the multiscale structure evolution were analyzed from the coal compositions and stress history. Nuclear magnetic resonance method was used in the multiscale structure evolution characterization. As for the multistage gas flow evolution, gas ad/de-sorption, diffusion, and seepage evolution characterization were investigated. There is a quadratic relationship between the total porosity and LNFT cycles in both shallow and deep coal. The fracture expansion is dominant in deep coal, while pores connectivity enhancement is dominant in shallow coal. The permeability of both shallow and deep coal increases during the LNFT cycling, presenting a logarithmic correlation between permeability and the number of cycles. With the same porosity, shallow coal has a higher permeability. LNFT cycling can improve the Langmuir volume. Langmuir volume and gas diffusion coefficients of deep coal is smaller both pre- and post-LNFT cycling. Except for CH4in deep coal, the Langmuir pressure and gas diffusion coefficients in both coals are improved by LNFT cycling.
Combined microflotation effects in polymetallic ores beneficiation
Authors: Turysbekov D. , Tussupbayev N. , Narbekova S. , Kaldybayeva Z. 
Published: April 2023

AbstractProducing of heterogeneous concentrates with good recovery in the processing of polymetallic ores is a challenge. Many factors must be taken into account including ore grinding, reagent mode, water composition, pulp density and the volume of supplied bubbles when producing high-quality selective concentrates. Microbubbles smaller than 50 μm in size were produced based on the frother oxal T-92 at different concentrations using a generator. The most optimal number of microbubbles smaller than 50 µm was produced at a T-92 concentration of 0.5 g/dm3. Polymetallic ore of Kazakhstan deposit was used for flotation studies. The studies were conducted in the copper-lead rough concentrate producing cycle. Flotation active minerals chalcopyrite and galena pass into the foam product, while sphalerite and pyrite remain in the chamber product in this cycle. In this paper, the density of pulp (20, 30 and 50%) as one of the main factors that effects the selectivity of flotation is studied. The kinetics of ore flotation in the base mode and with the use of a microbubble generator has been studied at these densities. Test experiments have been performed at the optimum density. The use of a water–air microemulsion generator makes it possible to maintain the quality of the copper-lead concentrate and increase the extraction of copper into the rough concentrate by 7.41%, lead by 5.98%.
Offline Mining of Microservice-Based Architectures (Extended Version)
Authors: Soldani Jacopo , Khalili Javad , Brogi Antonio 
Published: April 2023

AbstractDesigning applications adhering to the key design principles of microservice-based architectures (MSAs) enables fully exploiting the potentials of cloud computing platforms. A specification of an application’s MSA can help determining whether it adheres to such principles, and reasoning on how to refactor it when this is not the case. However, manually generating such a specification is complex and costly, mainly due to the multitude of heterogeneous software services and service interactions forming an MSA. The main objective of this article is to automate the generation of the specification of an existing MSA. We introduce an offline technique for automatically mining the specification of an MSA from its Kubernetes deployment. The mined MSA is expressed in $$\mu$$
μ
TOSCA, a microservice-oriented profile of the OASIS standard TOSCA. We also provide an open-source prototype implementation of the proposed mining technique, called $$\mu$$
μ
TOM. Four case studies based on four different third-party applications show that our technique can effectively mine the MSAs of existing applications, being it more accurate than its state-of-the-art competitor. The proposed offline mining technique can help researchers and practitioners working with microservices, by enabling them to automatically mine the MSAs of their applications. The obtained MSAs can then be visualised and analysed with existing tools to enhance their adherence to the key design principles of MSAs.
How COVID-19 impacted cultural consumption: an explorative analysis of Gen Z’s digital museum experiences
Authors: Bonel Elena , Capestro Mauro , Di Maria Eleonora 
Published: April 2023

AbstractSince the outbreak of the COVID-19 pandemic, arts and culture have experienced a paradoxical situation. The sector has been one of the most negatively affected due to both mobility restrictions and social distancing; yet for the same reasons, demand for online cultural experiences has intensified, and digital access has become more critical than ever. While extant research has focused mainly on the offering side of such changes and developments, this paper investigates how the pandemic impacted on cultural consumption online, and particularly for museum products. The research takes on a demand perspective, an often neglected one when analyzing digitalization and innovation in museums’ offering. Through a direct survey approach, the paper addresses a gap in research on younger subjects, the Generation Z, typically a non-demand segment. It specifically investigates their reactions to digital museum experiences, a realm that research based on museum data has pointed out as a probable route to their involvement. The research is based on two surveys on cultural consumption of a sample of Italian university students of over 1000 respondents, before and during lockdown. Results show that during COVID-19 not only has online cultural consumption increased, but so has the quality of the associated experience, where online museum visits are concerned. Results indicate that learning processes occurred during the pandemic, suggesting potential changes in cultural consumption mediated by digital technologies, with implications for multi-channel strategies of museums in the post-pandemic scenario.