bluuebunny/crossref_metadata_2025_split huggingface dataset:
Protective effects of education on the cognitive decline in a mental rotation task using real models: a pilot study with middle and older aged adults
Authors: Rahe Martina , Quaiser-Pohl Claudia 
Published: July 2022

AbstractMental rotation is the ability to rotate objects in one’s mind. Large age-related decreases in accuracy and processing time are often found in studies using paper-and-pencil or computerized mental rotation tests. For older participants, these tests are often too difficult. In the present study, real models consisting of cube figures were used to assess the mental rotation performance of middle and older aged adults. It should be investigated whether these tests were comparable to paper-and-pencil or chronometric tests and if very old participants were able to solve them. Eighty-four participants (49 females) between 40 and 90 years took part and were divided into middle (40–68 years) and older aged (69–90 years) and groups with higher (with college degree) and lower education (without college degree). For accuracy, main effects of gender and age group as well as interactions of age group and education were found. Younger participants outperformed older ones only in the group with lower education. For processing time, a main effect of age group as well as an interaction of age group and education was found. The age-related cognitive decline in the higher educated group was moderate, while a large effect appeared for the group without college degree. Age and gender effects of our new test with real objects were comparable to paper–pencil and computerized tests. Furthermore, a protective effect of education on the cognitive decline in mental rotation performance is discussed.
Real world data on IO-based therapy for metastatic renal cell carcinoma
Authors: Stühler Viktoria , Herrmann Lisa , Rausch Steffen , Stenzl Arnulf , Bedke Jens 
Published: July 2022

Abstract
Purpose
Immune-based (IO)-combinations are the backbone in the systemic therapy of metastatic renal cell carcinoma (mRCC). Despite phase III clinical trial data, real world data are of special importance to reflect clinical practice.

Methods
This retrospective study included 201 mRCC patients receiving first-line systemic therapy from January 2006. Clinicopathological and treatment-related data were recorded. Progression-free (PFS) and overall survival (OS) were analyzed using descriptive statistics and Kaplan–Meier analysis.

Results
Over the years, IO-based therapies have increased significantly. The collective comprises 76 patients with first-line IO-based therapy (IO-IO:55, TKI-IO:21) and 125 patients with TKI-monotherapy. PFS was significantly improved with TKI-IO combinations if compared to both TKI-monotherapy (23.9 vs. 10.3 months, HR 0.48, p = 0.034) and IO-IO combination (23.9 vs. 6.1 months, HR 0.37, p = 0.012). OS for TKI-IO treated patients was longer compared to TKI-monotherapy (HR 0.37, p = 0.050) at median follow-up of 24.1 versus 29.9 months. In a subanalysis of nivolumab treated patients, starting from second-line (n = 40), PFS was 5.5 months. The addition of nivolumab either in second-or later lines improved OS compared to repeated TKI- or mTOR-therapies alone (6.13 vs. 2.61 years, HR 0.46, p = 0.003).

Conclusion
Both first-line IO-based combinations and nivolumab after first-line TKI-monotherapy prolong OS in a real-world setting.
A survey of historical document image datasets
Authors: Nikolaidou Konstantina , Seuret Mathias , Mokayed Hamam , Liwicki Marcus 
Published: July 2022

AbstractThis paper presents a systematic literature review of image datasets for document image analysis, focusing on historical documents, such as handwritten manuscripts and early prints. Finding appropriate datasets for historical document analysis is a crucial prerequisite to facilitate research using different machine learning algorithms. However, because of the very large variety of the actual data (e.g., scripts, tasks, dates, support systems, and amount of deterioration), the different formats for data and label representation, and the different evaluation processes and benchmarks, finding appropriate datasets is a difficult task. This work fills this gap, presenting a meta-study on existing datasets. After a systematic selection process (according to PRISMA guidelines), we select 65 studies that are chosen based on different factors, such as the year of publication, number of methods implemented in the article, reliability of the chosen algorithms, dataset size, and journal outlet. We summarize each study by assigning it to one of three pre-defined tasks: document classification, layout structure, or content analysis. We present the statistics, document type, language, tasks, input visual aspects, and ground truth information for every dataset. In addition, we provide the benchmark tasks and results from these papers or recent competitions. We further discuss gaps and challenges in this domain. We advocate for providing conversion tools to common formats (e.g., COCO format for computer vision tasks) and always providing a set of evaluation metrics, instead of just one, to make results comparable across studies.
Finding geodesics joining given points
Authors: Noakes Lyle , Zhang Erchuan 
Published: July 2022

AbstractFinding a geodesic joining two given points in a complete path-connected Riemannian manifold requires much more effort than determining a geodesic from initial data. This is because it is much harder to solve boundary value problems than initial value problems. Shooting methods attempt to solve boundary value problems by solving a sequence of initial value problems, and usually need a good initial guess to succeed. The present paper finds a geodesic$$\gamma :[0,1]\rightarrow M$$γ:[0,1]→Mon the Riemannian manifoldMwithγ(0) =x0andγ(1) =x1by dividing the interval [0,1] into several sub-intervals, preferably just enough to enable a good initial guess for the boundary value problem on each subinterval. Then a geodesic joining consecutive endpoints (local junctions) is found by single shooting. Our algorithm then adjusts the junctions, either (1) by minimizing the total squared norm of the differences between associated geodesic velocities using Riemannian gradient descent, or (2) by solving a nonlinear system of equations using Newton’s method. Our algorithm is compared with the knownleapfrog algorithmby numerical experiments on a 2-dimensional ellipsoid Ell(2) and on a left-invariant 3-dimensional special orthogonal groupSO(3). We find Newton’s method (2) converges much faster than leapfrog when more junctions are needed, and that a good initial guess can be found for (2) by starting with Riemannian gradient descent method (1).
Intersectional Stigma and Implementation of HIV Prevention and Treatment Services for Adolescents Living with and at Risk for HIV: Opportunities for Improvement in the HIV Continuum in Sub-Saharan Africa
Authors: Embleton Lonnie , Logie Carmen H. , Ngure Kenneth , Nelson LaRon , Kimbo Liza , Ayuku David , Turan Janet M. , Braitstein Paula 
Published: July 2022

AbstractAdolescents in sub-Saharan Africa, specifically adolescent girls and young women, young men who have sex with men, transgender persons, persons who use substances, and adolescents experiencing homelessness experience intersectional stigma, have a high incidence of HIV and are less likely to be engaged in HIV prevention and care. We conducted a thematic analysis informed by the Health and Discrimination Framework using a multiple case study design with five case studies in 3 sub-Saharan African countries. Our analysis found commonalities in adolescents’ intersectional stigma experiences across cases, despite different contexts. We characterize how intersectional stigma impacts the uptake and implementation of HIV prevention and treatment services along the continuum for adolescents. Findings reveal how intersectional stigma operates across social-ecological levels and worsens HIV-related outcomes for adolescents. We identify opportunities for implementation science research to address stigma-related barriers to the uptake and delivery of HIV services for adolescents in sub-Saharan Africa.
Incorporating causality in energy consumption forecasting using deep neural networks
Authors: Sharma Kshitij , Dwivedi Yogesh K. , Metri Bhimaraya 
Published: July 2022

AbstractForecasting energy demand has been a critical process in various decision support systems regarding consumption planning, distribution strategies, and energy policies. Traditionally, forecasting energy consumption or demand methods included trend analyses, regression, and auto-regression. With advancements in machine learning methods, algorithms such as support vector machines, artificial neural networks, and random forests became prevalent. In recent times, with an unprecedented improvement in computing capabilities, deep learning algorithms are increasingly used to forecast energy consumption/demand. In this contribution, a relatively novel approach is employed to use long-term memory. Weather data was used to forecast the energy consumption from three datasets, with an additional piece of information in the deep learning architecture. This additional information carries the causal relationships between the weather indicators and energy consumption. This architecture with the causal information is termed as entangled long short term memory. The results show that the entangled long short term memory outperforms the state-of-the-art deep learning architecture (bidirectional long short term memory). The theoretical and practical implications of these results are discussed in terms of decision-making and energy management systems.
Supporting thinking about thinking: examining the metacognition theory-practice gap in higher education
Authors: Dennis Jayne L. , Somerville Matthew P. 
Published: July 2022

AbstractMetacognition is the knowledge and regulation of one’s cognition and has been associated with academic performance across all levels of education, including higher education (HE). Previously, a gap has been reported between extensive metacognition research and elaboration of theory versus minimal inclusion of metacognition in teaching practice in primary and secondary education. The present study investigated whether this theory-practice gap extends to HE. Furthermore, we took a novel approach to evaluating academics’ broad and implicit inclusion of metacognitive supportive practices (MSPs) in their teaching practice. A questionnaire and semi-structured interviews were used to evaluate awareness of metacognition and inclusion of 16 MSPs in undergraduate teaching among 72 academics in scientific disciplines at a UK research-intensive university. We found that a minority of academics (27/72, 37.5%) were familiar with metacognition and, of those who were, they typically emphasised knowledge of cognition, rather than regulation of cognition. Nonetheless, all respondents incorporated at least two MSPs in their teaching, although typically in a limited fashion, emphasising knowledge and understanding of discipline content rather than cognitive regulation. Compared to academics without a teaching qualification, respondents holding or working towards a teaching qualification used significantly more MSPs, earlier in their career, and used significantly more MSPs aligned with regulation of cognition. This study demonstrates that the metacognition theory-practice gap extends to HE and highlights the scope for staff development programmes to better support students’ metacognitive development relevant for their studies and post-graduation careers.
Adoption of Artificial Intelligence and Cutting-Edge Technologies for Production System Sustainability: A Moderator-Mediation Analysis
Authors: Chatterjee Sheshadri , Chaudhuri Ranjan , Kamble Sachin , Gupta Shivam , Sivarajah Uthayasankar 
Published: July 2022

Abstract
Cutting-edge technologies like big data analytics (BDA), artificial intelligence (AI), quantum computing, blockchain, and digital twins have a profound impact on the sustainability of the production system. In addition, it is argued that turbulence in technology could negatively impact the adoption of these technologies and adversely impact the sustainability of the production system of the firm. The present study has demonstrated that the role of technological turbulence as a moderator could impact the relationships between the sustainability the of production system with its predictors. The study further analyses the mediating role of operational sustainability which could impact the firm performance. A theoretical model has been developed that is underpinned by dynamic capability view (DCV) theory and firm absorptive capacity theory. This model was verified by PLS-SEM with 412 responses from various manufacturing firms in India. There exists a positive and significant influence of AI and other cutting-edge technologies for keeping the production system sustainable.
The Eurovision Song Contest: voting rules, biases and rationality
Authors: Ginsburgh Victor , Moreno-Ternero Juan D. 
Published: July 2022

AbstractWe analyze and evaluate the rules and results at the 2021 Eurovision Song Contest. We first concentrate on the various voting procedures and explore several alternatives (inspired by classical contributions in social choice and game theory) that could make a difference for the results. We also discuss other important issues, such as simplicity, contrast effects and whether experts are better judges than tele-voters. Our findings raise the question of whether the voting procedures used by the Eurovision Song Contest authorities are fail-safe. We endorse instead the use of the so-called Shapley voting procedure for judges as well as tele-voters.
Mother-Child Relationship Representations of Children Born of Sexual Violence in Post-WWII Germany
Authors: Roupetz Sophie , Stein Jacob Y. , Anderson Kimberley , Kaiser Marie , Mitreuter Saskia , Glaesmer Heide 
Published: July 2022

AbstractIt is estimated around 1.9 million German women were raped in the post-World War II period. Unwanted pregnancies were common and many women went on to raise these children born of sexual violence (CBSV). Now more than 70 years later, we sought to explore the perceptions of past and present relationships of CBSV with their mothers. Using a combination of qualitative methodologies, we analyzed autobiographical interviews of participants born between 1945–1955 across Germany. Narratives were first coded for mother-child content (allowing a comparison between participants), and later examined as a holistic unit (to address within-participant data). Three categories of mother-child relationships were identified: conflictual relationships, an emotionally absent parent, and positive upbringings. By employing a collective case study, we were then able to place these along three axes of relationality that positioned the participants’ perception of their relationships with their mothers and allowed interactions between the different perceived roles in those relationships to emerge: accountability and agency vs. exoneration and victimhood of the mother; accountability and agency vs. exoneration and victimhood of the child and longing vs. detachment. This study complements other research among those born during post-WWII occupation in Germany and Austria and highlights the diverse experiences CBSV have with their mothers. It serves as a reminder of the necessity for personal narratives to continue being documented, particularly given the frequency with which children are born of sexual violence in conflicts today. Appreciating the potential life-long impact for these individuals is key to initiating change.
Stay home, stay safe? High habitat suitability and environmental connectivity increases road mortality in a colonizing mesocarnivore
Authors: Frangini Lorenzo , Sterrer Ursula , Franchini Marcello , Pesaro Stefano , Rüdisser Johannes , Filacorda Stefano 
Published: July 2022

AbstractContextAnthropogenic structures have considerable effects on ecosystems, disrupting natural population processes and representing a serious risk in terms of vehicle collisions. The golden jackal (Canis aureus) is a mesocarnivore species whose range is expanding in Europe. Roadkills are one of the main human-induced mortalities in Italy to the species.ObjectivesIdentify road-related characteristics and ecological factors related to golden jackal roadkill risk in Italy.MethodsWe used habitat suitability (Maxent) and connectivity (Circuit theory) models to derive 15 metrics potentially affecting roadkill risk. We tested their influence using Bayesian generalized linear models and generalized linear models comparing golden jackal roadkill locations to random locations. Furthermore, we tested if there were significant sex, age-related and seasonal differences among road-killed individuals.ResultsWe found that roadkill risk was higher in areas characterized by higher values of habitat suitability and connectivity, habitat fragmentation and along highways. It was lower with increasing distance to the source population and in the presence of guardrails. No significant differences were detected in terms of roadkill risk between sexes, age classes and seasonConclusionsThe identified factors affecting road mortality of golden jackals in Italy provide insights on how to mitigate wildlife-vehicle collisions. Crossing areas, and visual and acoustic warnings for wildlife, as well as the importance of managing fences along high traffic volume roads could help mitigate further damage. Finally, there is a need to further investigate the effectiveness of mitigation measures in the light of the golden jackal’s ongoing expansion in a human-modified landscape.
New and emerging forms of data and technologies: literature and bibliometric review
Authors: Radanliev Petar , De Roure David 
Published: July 2022

AbstractWith the increased digitalisation of our society, new and emerging forms of data present new values and opportunities for improved data driven multimedia services, or even new solutions for managing future global pandemics (i.e., Disease X). This article conducts a literature review and bibliometric analysis of existing research records on new and emerging forms of multimedia data. The literature review engages with qualitative search of the most prominent journal and conference publications on this topic. The bibliometric analysis engages with statistical software (i.e. R) analysis of Web of Science data records. The results are somewhat unexpected. Despite the special relationship between the US and the UK, there is not much evidence of collaboration in research on this topic. Similarly, despite the negative media publicity on the current relationship between the US and China (and the US sanctions on China), the research on this topic seems to be growing strong. However, it would be interesting to repeat this exercise after a few years and compare the results. It is possible that the effect of the current US sanctions on China has not taken its full effect yet.
Digital Corporate Social Responsibility Reporting in the Water Industry
Authors: Almeida Rita , Pérez-López José Ángel , Abreu Rute 
Published: July 2022

AbstractCompanies in the Water Industry present digital Corporate Social Responsibility (CSR) agenda and, also, the social and environmental commitment to their stakeholders through the websites. The purpose of this research is to assess the digital CSR in Portuguese companies of the Water Industry. Furthermore, the research examines factors that impacts on the digital status of the online disclosure. The authors analyze the CSR information published on their websites of the Portuguese companies, operating in bottle water industry using empirical analysis. The data was collected based on the Global Reporting Initiative (GRI 2021a) standards that details the level of disclosure in this industry and highlight areas of underreporting. The results point to factors that need to improve to companies’ digital CSR report good practices and weak points based on the companies’ size, number of employees and turnover as factors that influence this level of disclosure.
Inverse Flood Routing Using Simplified Flow Equations
Authors: Gąsiorowski Dariusz , Szymkiewicz Romuald 
Published: July 2022

AbstractThe paper considers the problem of inverse flood routing in reservoir operation strategy. The aim of the work is to investigate the possibility of determining the hydrograph at the upstream end based on the hydrograph required at the downstream end using simplified open channel flow models. To accomplish this, the linear kinematic wave equation, the diffusive wave equation and the linear Muskingum equation are considered. To achieve the hydrograph at the upstream end, an inverse solution of the afore mentioned equations with backward integration in the x direction is carried out. The numerical solution of the kinematic wave equation and the Muskingum equation bases on the finite difference scheme. It is shown that both these equations are able to provide satisfying results because of their exceptional properties related to numerical diffusion. In the paper, an alternative approach to solve the inverse routing using the diffusive wave model is also presented. To this end, it is described by a convolution which involves the instantaneous unit hydrograph (IUH) corresponding to the linear diffusive wave equation. Consequently, instead of a solution of partial or ordinary differential equations, the integral equation with Laguerre polynomials, used for the expansion of the upstream hydrograph, is solved. It was shown that the convolution approach is more reliable comparing to the inverse solution of the simplified models in the form of differential equations.