bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Acquisition of Relative Clauses in Autism: The Role of Executive Functions and Language
Authors: Peristeri Eleni , Kamona Xanthi , Varlokosta Spyridoula 
Published: October 2023

Abstract
Purpose
Relative clauses present a well-known processing asymmetry between object-extracted and subject-extracted dependencies across both typical and atypical populations. The present study aimed at exploring the comprehension of object and subject relative clauses as conceptualized by the Relativized Minimality framework in autistic children and in a group of age- and IQ-matched typically-developing children. The study also explored the way performance in relative clauses would be affected by the children’s language and executive function skills.

Method
Relative clause comprehension was tested through a sentence-picture matching task and language was tested with a receptive vocabulary task. Executive functions were assessed through backward digit recall and a Flanker test.

Results
Object relative clauses were harder to parse for both groups than subject relatives, while number mismatch between the moved object Noun Phrase and the intervening subject Noun Phrase in object relatives boosted both groups’ performances. Typically-developing children’s performance in object relatives was predicted by both language and executive functions, while autistic children failed to use language and did not systematically draw on their executive functions in object relative clause comprehension.

Conclusion
The findings suggest that relative clause processing in autism follows a normal developmental trajectory, and that difficulty with parsing object relative clauses stems from reduced language and executive functions rather than deficits in the children’s morphosyntactic skills.
The Role of Social Support and Acculturation Factors on Postpartum Mental Health Among Latinas in the MADRES Pregnancy Cohort
Authors: Corona Karina , Yang Tingyu , Dunton Genevieve , Toledo-Corral Claudia , Grubbs Brendan , Eckel Sandrah P. , Johnston Jill , Chavez Thomas , Lerner Deborah , Lurvey Nathana , Al-Marayati Laila , Habre Rima , Farzan Shohreh F. , Breton Carrie V. , Bastain Theresa M. 
Published: October 2023

AbstractWe examined the associations between social support and postpartum mental health in 137 U.S. and foreign-born Latinas in the MADRES pregnancy cohort. We also examined whether language, years in the U.S., and country of birth moderates these relationships. Participants were administered PROMIS support measures 1 month postpartum; the Perceived Stress and Postpartum Distress Measure 3, 6, and 12 months postpartum; and the CESD scale 12 months postpartum. Perceived stress was lower at 6 months postpartum for women reporting higher emotional (p = 0.01), informational (p = 0.03), and instrumental support (p < 0.001); and lower at 12 months postpartum for women reporting higher emotional support (p = 0.01). Distress at 6 months was lower in women reporting higher emotional support (p = 0.03). Interactions suggest that associations were stronger for mothers that speak Spanish, spent fewer years in the U.S., and were born in Central America.
Online Altruism: What it is and how it Differs from Other Kinds of Altruism
Authors: Lou Katherine , Floridi Luciano 
Published: October 2023

AbstractAltruism is a well-studied phenomenon in the social sciences, but online altruism has received relatively little attention. In this article, we examine several cases of online altruism, and analyse the key characteristics of the phenomenon, in particular comparing and contrasting it against models of traditional donor behaviour. We suggest a novel definition of online altruism, and provide an in-depth, mixed-method study of a significant case, represented by the r/Assistance subreddit. We argue that online altruism can be characterized by its differing experiences compared to traditional giving, from a giver’s point of view, and unique mechanisms and actions made possible by the internet. These findings explain why people give to anonymous strangers online and provide a new perspective on altruism that is important in building a more altruistic internet and society.
Rank 5 Trivializable Subriemannian Structure on $$\mathbb {S}^7$$ and Subelliptic Heat Kernel
Authors: Bauer Wolfram , Laaroussi Abdellah , Tarama Daisuke 
Published: October 2023

AbstractWe present an explicit form of the subelliptic heat kernel of the intrinsic sublaplacian $$\Delta _{\textrm{sub}}^5$$

Δ

sub

5

induced by a rank 5 trivializable subriemannian structure on the Euclidean seven dimensional sphere $$\mathbb {S}^7$$

S

7

. This completes the heat kernel analysis of trivializable subriemannian structures on $$\mathbb {S}^7$$

S

7

induced by a Clifford module action on $$\mathbb {R}^8$$

R

8

. As an application we derive the spectrum of $$\Delta _{\textrm{sub}}^5$$

Δ

sub

5

and the Green function of the conformal sublaplacian in an explicit form.
Some thoughts on transparency of the data and analysis behind the Highly Cited Researchers list
Authors: Klein Alexandra-Maria , Kranke Nina 
Published: October 2023

AbstractClarivate’s Highly Cited Researchers (HCR) list is one of the most important quantitative performance indicators in science and influences individual careers and also the reputation of research institutions. However, many researchers and representatives of institutions and funding agencies are not familiar with the method that is applied to generate the HCR lists. We therefore provide a detailed description of Clarivate’s method and give an example to illustrate how HCR are identified. While Clarivate provides the complete HCR lists and a detailed description of the method used for identifying HCR, the detailed analysis with actual numbers is not published. It is therefore not entirely transparent how exactly the HCR were identified, and which authors were excluded from the initial list, e.g. due to scientific misconduct. It is also impossible to check the analysis for errors. Given the prestige and weight that is attributed to Clarivate’s HCR list, we call for transparency of the data and analysis behind the HCR list.
A between-cluster approach for clustering skew-symmetric data
Authors: Vicari Donatella , Di Nuzzo Cinzia 
Published: October 2023

AbstractIn order to investigate exchanges between objects, a clustering model for skew-symmetric data is proposed, which relies on the between-cluster effects of the skew-symmetries that represent the imbalances of the observed exchanges between pairs of objects. The aim is to detect clusters of objects that share the same behaviour of exchange so that origin and destination clusters are identified. The proposed model is based on the decomposition of the skew-symmetric matrix pertaining to the imbalances between clusters into a sum of a number of off-diagonal block matrices. Each matrix can be approximated by a skew-symmetric matrix by using a truncated Singular Value Decomposition (SVD) which exploits the properties of the skew-symmetric matrices. The model is fitted in a least-squares framework and an efficient Alternating Least Squares algorithm is provided. Finally, in order to show the potentiality of the model and the features of the resulting clusters, an extensive simulation study and an illustrative application to real data are presented.
Neuroanatomical findings in isolated REM sleep behavior disorder and early Parkinson’s disease: a Voxel-based morphometry study
Authors: Donzuso Giulia , Cicero Calogero E. , Giuliano Loretta , Squillaci Raffaele , Luca Antonina , Palmucci Stefano , Basile Antonello , Lanza Giuseppe , Ferri Raffaele , Zappia Mario , Nicoletti Alessandra 
Published: October 2023

AbstractIsolated rapid eye movement (REM) sleep behavior disorder (iRBD) is a parasomnia characterized by loss of physiological atonia of skeletal muscles with abnormal behaviors arising during REM sleep. RBD is often the early manifestation of neurodegenerative diseases, particularly alpha-synucleinopathies, such as Parkinson’s disease (PD). Both structural and functional neuroimaging studies suggest that iRBD might share, or even precede, some of the features commonly found in PD, although without a definitive conclusion. Aim of the study is to evaluate the presence of structural abnormalities involving cortical and subcortical areas in PD patients with RBD and iRBD. Patients with video-polysomnographic (VPSG)-confirmed iRBD, and patients with a diagnosis of PD were recruited. In all PD patients, the presence of probable RBD was assessed during the follow-up visits (PD/pRBD). A group of healthy controls (HC) subjects was also recruited. Each subject underwent a structural brain MRI using a 3-D T1-weighted spoiled gradient echo sequence. Twenty-three patients with iRBD, 24 PD/pRBD, and 26 HC were enrolled. Voxel-based morphometry-AnCOVA analysis revealed clusters of grey matter changes in iRBD and PD/pRBD compared to HC in several regions, involving mainly the frontal and temporal regions. The involvement of cortical brain structures associated to the control of sleep cycle and REM stage both in PD/pRBD and iRBD might suggest the presence of a common structural platform linking iRBD and PD, although this pattern may not underlie exclusively RBD-related features. Further longitudinal studies are needed to clarify the patterns of changes occurring at different time points of RBD-related neurodegeneration.
Random simple-homotopy theory
Authors: Benedetti Bruno , Lai Crystal , Lofano Davide , Lutz Frank H. 
Published: October 2023

AbstractWe implement an algorithm RSHT (random simple-homotopy) to study the simple-homotopy types of simplicial complexes, with a particular focus on contractible spaces and on finding substructures in higher-dimensional complexes. The algorithm combines elementary simplicial collapses with pure elementary expansions. For triangulated d-manifolds with $$d\le 6$$

d
≤
6

, we show that RSHT reduces to (random) bistellar flips. Among the many examples on which we test RSHT, we describe an explicit 15-vertex triangulation of the Abalone, and more generally, $$(14k+1)$$

(
14
k
+
1
)

-vertex triangulations of a new series of Bing’s houses with k rooms, $$k\ge 3$$

k
≥
3

, which all can be deformed to a point using only six pure elementary expansions.
Numerical Modelling and Predicting Performance of Geogrid-Reinforced Low-Volume Unpaved Roads over Soft Subgrades
Authors: Chua Boon Tiong , Nepal Kali Prasad 
Published: October 2023

AbstractPavement performance is usually predicted by large-scale laboratory experiments, expensive field tests and/or comparatively cheaper numerical modelling alternative. In this study, a finite element limiting strain model has been developed to investigate the strain response of both unreinforced and geogrid-reinforced pavements on unpaved roads where the geogrid is placed at the bottom of the unbound granular base layer. A two-dimensional (2D) axisymmetric finite element model (FEM) is used to analyse the behaviour of both unreinforced and geogrid-reinforced granular base. The critical pavement responses (vertical surface deformation, compressive strain and compressive stress at the top of subgrade, etc.) are simulated numerically using ABAQUS. These critical responses are used to develop the pavement performance models (strain limiting models) and to predict long-term service life of pavement or the reduction of thickness of granular base for equivalent service life or a combination of both. The parametric results are then used to develop design charts to aid practitioners to use directly in designs. The numerical model is verified using published literature-based information and found to be reasonable. The results show that the traffic benefit ratio (TBR) of 3.1 at a 20 mm rut depth can be achieved for a thin granular base built over soft subgrade using a medium stiff geogrid.
A Distributed Microservice Architecture Pattern for the Automated Generation of Information Extraction Pipelines
Authors: Sildatke Michael , Karwanni Hendrik , Kraft Bodo , Zündorf Albert 
Published: October 2023

AbstractCompanies often build their businesses based on product information and therefore try to automate the process of information extraction (IE). Since the information source is usually heterogeneous and non-standardized, classic extract, transform, load techniques reach their limits. Hence, companies must implement the newest findings from research to tackle the challenges of process automation. They require a flexible and robust system that is extendable and ensures the optimal processing of the different document types. This paper provides a distributed microservice architecture pattern that enables the automated generation of IE pipelines. Since their optimal design is individual for each input document, the system ensures the ad-hoc generation of pipelines depending on specific document characteristics at runtime. Furthermore, it introduces the automated quality determination of each available pipeline and controls the integration of new microservices based on their impact on the business value. The introduced system enables fast prototyping of the newest approaches from research and supports companies in automating their IE processes. Based on the automated quality determination, it ensures that the generated pipelines always meet defined business requirements when they come into productive use.
Sustainable Short-Term Production Planning Optimization
Authors: Zanella Fernando , Vaz Clara Bento 
Published: October 2023

AbstractThis study proposes a framework for short-term production planning of a Portuguese company operating as a tier 2 supplier in the automotive sector. The framework is intended to support the decision-making process regarding a single progressive hydraulic press, which is used to manufacture cold-stamped parts for exhaust systems. The framework consists of two sequential levels: (1) a Mixed-Integer Linear Programming (MILP) model to determine the optimal production quantities per week while minimizing the total cost; (2) a dynamic production sequencing rule for scheduling operations on the hydraulic press. The two levels are combined and implemented in Excel, where the MILP model is solved using the Solver add-in, and the second level uses the optimal production quantities as inputs to determine the production sequence using a dynamic priority rule. To validate the framework, a proposed optimal plan was compared to a real plan executed by the company, and it was found that the framework could save up to 22.1% of the total cost observed in reality while still satisfying demand. To address uncertainties, the framework requires a rolling weekly planning horizon.
MLOps Challenges in Industry 4.0
Authors: Faubel Leonhard , Schmid Klaus , Eichelberger Holger 
Published: October 2023

AbstractAn important part of the Industry 4.0 vision is the use of machine learning (ML) techniques to create novel capabilities and flexibility in industrial production processes. Currently, there is a strong emphasis on MLOps as an enabling collection of practices, techniques, and tools to integrate ML into industrial practice. However, while MLOps is often discussed in the context of pure software systems, Industry 4.0 systems received much less attention. So far, there is only little research focusing on MLOps for Industry 4.0. In this paper, we discuss whether MLOps in Industry 4.0 leads to significantly different challenges compared to typical Internet systems. We provide an initial analysis of MLOps approaches and identify both context-independent MLOps challenges (general challenges) as well as challenges particular to Industry 4.0 (specific challenges) and conclude that MLOps works very similarly in Industry 4.0 systems to pure software systems. This indicates that existing tools and approaches are also mostly suited for the Industry 4.0 context.
New Ways in Municipal Flood Mitigation: a Mixed-Integer Programming Approach and its Practical Application
Authors: Boeckmann Jan , Thielen Clemens 
Published: October 2023

AbstractAdapting to the consequences of climate change is one of the central challenges faced by humanity in the next decades. One of these consequences are intense heavy rain events, which can cause severe damage to buildings due to flooding. In this paper, we present the first use of optimization techniques that scales well enough to be applicable for supporting decision-making in planning precautionary measures for flash floods caused by heavy rain events in realistic scenarios. Our mixed-integer programming model has been implemented as an innovative decision support tool in the form of a web application, which has already been used by more than 30 engineering offices, municipalities, universities, and other institutions. The model aims to minimize the damage caused in the case of a heavy rain event by taking best-possible actions subject to a limited budget and constraints on the cooperation of residents. We further present an efficient, graph-based representation and preprocessing of the surface terrain, a combinatorial algorithm for computing an initial solution of the mixed-integer program, and computational results obtained on real-word data from different municipalities.
Growth, morphology, and formation of cinnabarin in Pycnoporus cinnabarinus in relation to different irradiation spectra
Authors: Schinagl Christoph W. , Siewert Bianka , Hammerle Fabian , Spes Gaja , Peintner Ursula , Schlierenzauer Michael , Vrabl Pamela 
Published: October 2023

Abstract
Background
The demand for natural pigments in general, and for fungi-derived pigments in particular, is constantly rising. Wood-decomposing fungi represent a promising source for natural pigments and they are usually easy to cultivate in pure culture. One of them, i.e., Pycnoporus cinnabarinus, offers a highly interesting spectrum of bioactivity, partly due to the formation of the orange–red pigment cinnabarin. However, apart from a few studies addressing its diverse potential biotechnological applications, there is still a large gap of knowledge concerning the influence of light on the formation of cinnabarin. The aim of this work was to investigate the effect of different irradiations on the cinnabarin content, the growth, and the morphology of three different P. cinnabarinus strains. We used highly standardized irradiation conditions and cultivation techniques in combination with newly developed methods for the extraction and direct quantification of cinnabarin.

Results
Red, green, blue, and UV-A irradiation (mean irradiance Ee = 1.5 ± 0.18 W m−2) had considerable effects on the growth and colony appearance of all three P. cinnabarinus strains tested. The cinnabarin content determined was, thus, dependent on the irradiation wavelength applied, allowing strain-specific thresholds to be defined. Irradiation with wavelengths below this strain-specific threshold corresponded to a lower cinnabarin content, at least at the intensity applied. The orange–red pigment appeared by light microscopy as incrusted extracellular plaques present on the hyphal walls. Highly efficient vegetative propagation occurred by arthroconidia, and we observed the tendency that this asexual reproduction was (i) most frequent in the dark but (ii) never occurred under UV-A exposure.

Conclusion
This study highlights a differential photo-dependence of growth, morphology, and cinnabarin formation in P. cinnabarinus. This confirms that it is advisable to consider the wavelength of the light used in future biotechnological productions of natural pigments.

Graphical abstract
Machine Learning-Based Screening Solution for COVID-19 Cases Investigation: Socio-Demographic and Behavioral Factors Analysis and COVID-19 Detection
Authors: Uddin K. M. Aslam , Prity Farida Siddiqi , Tasnim Maisha , Jannat Sumiya Nur , Faruk Mohammad Omar , Islam Jahirul , Murad Saydul Akbar , Adhikary Apurba , Bairagi Anupam Kumar 
Published: October 2023

AbstractThe COVID-19 pandemic has unleashed an unprecedented global crisis, releasing a wave of illness, mortality, and economic disarray of unparalleled proportions. Numerous societal and behavioral aspects have conspired to fuel the rampant spread of COVID-19 across the globe. These factors encompass densely populated areas, adherence to mask-wearing protocols, inadequate awareness levels, and various behavioral and social practices. Despite the extensive research surrounding COVID-19 detection, an unfortunate dearth of studies has emerged to meticulously evaluate the intricate interplay between socio-demographic and behavioral factors and the likelihood of COVID-19 infection. Thus, a comprehensive online-based cross-sectional survey was methodically orchestrated, amassing data from a substantial sample size of 500 respondents. The precisely designed survey questionnaire encompassed various variables encompassing socio-demographics, behaviors, and social factors. The Bivariate Pearson’s Chi-square association test was deftly employed to unravel the complex associations between the explanatory variables and COVID-19 infection. The feature importance approach was also introduced to discern the utmost critical features underpinning this infectious predicament. Four distinct Machine Learning (ML) algorithms, specifically Decision Tree, Random Forest, CatBoost, and XGBoost, were employed to accurately predict COVID-19 infection based on a comprehensive analysis of socio-demographic and behavioral factors. The performance of these models was rigorously assessed using a range of evaluation metrics, including accuracy, recall, precision, ROC-AUC score, and F1 score. Pearson’s Chi-square test revealed a statistically significant association between vaccination status and COVID-19 infection. The use of sanitizer and masks, the timing of infection, and the interval between the first and second vaccine doses were significantly correlated with the likelihood of contracting the COVID-19 virus. Among the ML models tested, the XGBoost classifier demonstrated the highest classification accuracy, achieving an impressive 97.6%. These findings provide valuable insights for individuals, communities, and policymakers to implement targeted strategies aimed at mitigating the impact of the COVID-19 pandemic.
Concomitantly combined anterior cruciate ligament and posterolateral corner reconstruction: A case report
Authors: Van Hoc Nguyen , Manh Khanh Nguyen 
Published: October 2023

Abstract

Introduction
Combined posterolateral corner (PLC) - anterior cruciate ligament (ACL) tears account for 10% of complex knee injuries. In an ACL-PLC injured knee, an untreated PLC injury causes a significant increase in force on the ACL graft and may be a leading cause of graft failure.

Case presentation
A 26-year-old male patient with combined ACL and PLC injury. He was concurrently reconstructed in both ACL and PLC. We used 2 semitendinosus (1 in each knee) and 1 glacilis tendon (in the injured knee). The ACL was reconstructed by one 4-stranded simitendinosus with an all-inside technique and TightRope fixation. The PLC reconstruction utilized one femoral tunnel at the isometric point, graft fixation at the femoral tunnel by TightRope, and at the tibial tunnel by absorbable screw. After a follow-up of 9 months, Cincinnati’s score was 70/100 and the IKDC score was B type.

Discussion
The main advantage is that surgeons do not have to care about tendon length and graft diameter compared to the previous method.

Conclusion
Concomitantly combined ACL and PLC reconstruction has good results in remaining knee functions and decreasing ACL reconstruction failure. However, femoral tunnel creation needs to be careful to avoid femoral tunnel intersections.

Highlights