bluuebunny/crossref_metadata_2025_split huggingface dataset:
Open-source optimization method for android smartphone single point positioning
Authors: Jiang Changhui , Chen Yuwei , Jia Jianxin , Sun Haibin , Wang Tinghuai , Duan Zhiyong , Hyyppa Juha 
Published: June 2022

AbstractNowadays, a chip-scale Global Navigation Satellite System (GNSS) receiver is ubiquitous in smartphones. In a smartphone GNSS receiver, the least square (LS) or Kalman Filter (KF) is implemented to estimate the position. With the aim to improve the smartphone GNSS position accuracy, we propose a position-smoothing method considering more historical information than the traditional methods, i.e., LS and KF. More past states are regarded as unknowns, and a cost function is constructed to optimize these states. An open-source smartphone dataset from Google was used for testing the proposed method. The experimental results indicate that the proposed method outperforms the other conventional methods in position errors. In addition, we open the source code. We expect that the optimization method implemented in the smartphone GNSS position smoothing application can be an illustrative example to clearly introduce such an optimization method and a reference for its implementation, which might inspire some other meaningful and exciting applications in GNSS.
The capital tax paradox in a greening economy
Authors: Borissov Kirill , Bretschger Lucas , Minabutdinov Aleksey 
Published: June 2022

AbstractWe adopt a simple model of endogenous growth with polluting capital and a fixed budget for aggregate emissions. Pollution abatement efficiency is growing over time due to technical progress. We find that long-run capital and consumption are inversely related to the initial capital stock. Capital taxation does not harm the economy but actually raises long-run consumption and production, which we call the “capital tax paradox.” The reason for this surprising result is that in an economy with a binding carbon policy, early abundance of polluting capital is not a blessing but a curse. It is preferable to have a large capital stock when abatement efficiency has grown sufficiently large. The paper also provides novel results on the impact of pollution intensity and the rate of technical progress on the greening of the economy and the pollution permit prices. In the quantitative part, we calibrate model and study economic growth under different assumptions on the basic model parameters.
Robust optimization of a bi-objective tactical resource allocation problem with uncertain qualification costs
Authors: Fotedar Sunney , Strömberg Ann-Brith , Åblad Edvin , Almgren Torgny 
Published: June 2022

AbstractIn the presence of uncertainties in the parameters of a mathematical model, optimal solutions using nominal or expected parameter values can be misleading. In practice, robust solutions to an optimization problem are desired. Although robustness is a key research topic within single-objective optimization, little attention is received within multi-objective optimization, i.e. robust multi-objective optimization.This work builds on recent work within robust multi-objective optimization and presents a new robust efficiency concept for bi-objective optimization problems with one uncertain objective. Our proposed concept and algorithmic contribution are tested on a real-world multi-item capacitated resource planning problem, appearing at a large aerospace company manufacturing high precision engine parts. Our algorithm finds all the robust efficient solutions required by the decision-makers in significantly less time than the approach of Kuhn et al. (Eur J Oper Res 252(2):418–431, 2016) on 28 of the 30 industrial instances.
Workplace ostracism and family social support: a moderated mediation model of personal reputation
Authors: Zhang Haina , Yang Ziwei , Kwan Ho Kwong , Wu Fangjian 
Published: June 2022

AbstractWork and family are important life domains. This study investigates the relationship between employees’ perceptions of workplace ostracism and their provision of family social support. Integrating social impact theory and self-verification theory, the study provides a novel theoretical framework for examining the influence of workplace ostracism on employees’ provision of family social support. Using a moderated mediation model, it reveals the mediating role of personal reputation and the moderating roles of job social support and perceived organizational support. The results of two three-wave surveys of married employees and their spouses in China demonstrate that the negative relationship between exposure to workplace ostracism and an employee’s provision of family social support is mediated by the employee’s personal reputation. In addition, job social support and perceived organizational support weaken the relationship between personal reputation and family social support and the mediating effect of personal reputation on the relationship between workplace ostracism and family social support. The theoretical and managerial implications of this study for human resource management are discussed.
Grouped feature importance and combined features effect plot
Authors: Au Quay , Herbinger Julia , Stachl Clemens , Bischl Bernd , Casalicchio Giuseppe 
Published: June 2022

AbstractInterpretable machine learning has become a very active area of research due to the rising popularity of machine learning algorithms and their inherently challenging interpretability. Most work in this area has been focused on the interpretation of single features in a model. However, for researchers and practitioners, it is often equally important to quantify the importance or visualize the effect of feature groups. To address this research gap, we provide a comprehensive overview of how existing model-agnostic techniques can be defined for feature groups to assess the grouped feature importance, focusing on permutation-based, refitting, and Shapley-based methods. We also introduce an importance-based sequential procedure that identifies a stable and well-performing combination of features in the grouped feature space. Furthermore, we introduce the combined features effect plot, which is a technique to visualize the effect of a group of features based on a sparse, interpretable linear combination of features. We used simulation studies and real data examples to analyze, compare, and discuss these methods.
Interpreting deep learning models with marginal attribution by conditioning on quantiles
Authors: Merz Michael , Richman Ronald , Tsanakas Andreas , Wüthrich Mario V. 
Published: June 2022

AbstractA vast and growing literature on explaining deep learning models has emerged. This paper contributes to that literature by introducing a global gradient-based model-agnostic method, which we call Marginal Attribution by Conditioning on Quantiles (MACQ). Our approach is based on analyzing the marginal attribution of predictions (outputs) to individual features (inputs). Specifically, we consider variable importance by fixing (global) output levels, and explaining how features marginally contribute to these fixed global output levels. MACQ can be seen as a marginal attribution counterpart to approaches such as accumulated local effects, which study the sensitivities of outputs by perturbing inputs. Furthermore, MACQ allows us to separate marginal attribution of individual features from interaction effects and to visualize the 3-way relationship between marginal attribution, output level, and feature value.
Assessing young Korean children’s computational thinking: A validation study of two measurements
Authors: Sung Jihyun 
Published: June 2022

AbstractComputational thinking (CT) in young children has recently gained attention. This study verified the applicability of the Korean version of the Bebras cards and TACTIC-KIBO in measuring CT among young children in South Korea. A total of 450 children responded to the Bebras cards, TACTIC-KIBO, and Early Numeracy tasks that were used for the following analyses. Item response theory analysis, confirmatory factor analysis, correlation analysis, and calculation of Cronbach’s alpha were conducted to examine the psychometric properties of the validity and reliability of the two measurements. The results showed that these two measurements are acceptable for assessing CT among young children, demonstrating good validity and reliability, despite limitations such as the weak factor loadings of some items and low internal consistency of subfactors. These two CT measurements were significantly and positively correlated with early mathematical ability. Thus, these two measurements are acceptable for assessing CT among young children with varying CT ability, as they present good psychometric properties of the overall scores even though they have low internal consistency of subfactors and slightly weak correlations between subfactors.
Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3d-qsar.com portal
Authors: Proia Eleonora , Ragno Alessio , Antonini Lorenzo , Sabatino Manuela , Mladenovič Milan , Capobianco Roberto , Ragno Rino 
Published: June 2022

AbstractThe main protease (Mpro) of SARS-Cov-2 is the essential enzyme for maturation of functional proteins implicated in viral replication and transcription. The peculiarity of its specific cleavage site joint with its high degree of conservation among all coronaviruses promote it as an attractive target to develop broad-spectrum inhibitors, with high selectivity and tolerable safety profile. Herein is reported a combination of three-dimensional quantitative structure–activity relationships (3-D QSAR) and comparative molecular binding energy (COMBINE) analysis to build robust and predictive ligand-based and structure-based statistical models, respectively. Models were trained on experimental binding poses of co-crystallized Mpro-inhibitors and validated on available literature data. By means of deep optimization both models’ goodness and robustness reached final statistical values of r2/q2 values of 0.97/0.79 and 0.93/0.79 for the 3-D QSAR and COMBINE approaches respectively, and an overall predictiveness values of 0.68 and 0.57 for the SDEPPRED and AAEP metrics after application to a test set of 60 compounds covered by the training set applicability domain. Despite the different nature (ligand-based and structure-based) of the employed methods, their outcome fully converged. Furthermore, joint ligand- and structure-based structure–activity relationships were found in good agreement with nirmatrelvir chemical features properties, a novel oral Mpro-inhibitor that has recently received U.S. FDA emergency use authorization (EUA) for the oral treatment of mild-to-moderate COVID-19 infected patients. The obtained results will guide future rational design and/or virtual screening campaigns with the aim of discovering new potential anti-coronavirus lead candidates, minimizing both time and financial resources. Moreover, as most of calculation were performed through the well-established web portal 3d-qsar.com the results confirm the portal as a useful tool for drug design.
Graphical abstract
Stem cells and common biomaterials in dentistry: a review study
Authors: Mosaddad Seyed Ali , Rasoolzade Boshra , Namanloo Reza Abdollahi , Azarpira Negar , Dortaj Hengameh 
Published: June 2022

AbstractStem cells exist as normal cells in embryonic and adult tissues. In recent years, scientists have spared efforts to determine the role of stem cells in treating many diseases. Stem cells can self-regenerate and transform into some somatic cells. They would also have a special position in the future in various clinical fields, drug discovery, and other scientific research. Accordingly, the detection of safe and low-cost methods to obtain such cells is one of the main objectives of research. Jaw, face, and mouth tissues are the rich sources of stem cells, which more accessible than other stem cells, so stem cell and tissue engineering treatments in dentistry have received much clinical attention in recent years. This review study examines three essential elements of tissue engineering in dentistry and clinical practice, including stem cells derived from the intra- and extra-oral sources, growth factors, and scaffolds.
Looking Beyond Linear: A Closer Examination of the Relationship Between Wisdom and Wellbeing
Authors: Glück Judith , Weststrate Nic M. , Scherpf Andreas 
Published: June 2022

AbstractThere has been some controversy about the relationship between wisdom and constructs of the well-being complex. Some wisdom researchers argue that the ability to maintain a high level of well-being, even in the face of very negative experiences, is a core characteristic of wisdom. Other researchers argue that the willingness of wise people to reflect on the darker sides of life might jeopardize well-being. Studies mostly found moderate positive correlations of well-being with self-report wisdom measures and negative, zero, or low positive correlations with open-ended measures of wisdom. This paper tests the hypothesis that the relationship between wisdom and well-being is triangular rather than linear, with highly wise people being high in well-being, but people high in well-being not necessarily being highly wise. A sample of 155 participants (age 23 to 90 years) completed four wisdom measures and three measures from the well-being complex. We analyzed both linear relationships (using correlations) and triangular relationships (using Necessary Condition Analysis). Correlations of well-being with open-ended measures of wisdom were mostly insignificant; correlations with self-report measures of wisdom were mostly significant. However, scatterplots showed the expected triangular relationships and Necessary Condition Analysis indicated medium to large effect sizes for both open-ended and self-report wisdom measures. In sum, our findings show that even if wise individuals think more deeply about difficult aspects of the human existence, they are still able to maintain high levels of well-being.
Pseudo-Boolean optimisation for RobinX sports timetabling
Authors: Lester Martin Mariusz 
Published: June 2022

AbstractWe report on the development of Reprobate, a tool for solving sports timetabling problems in a subset of the RobinX format. Our tool is based around a monolithic translation of a sports timetabling instance into a pseudo-Boolean (PB) optimisation problem; this instance can be solved using existing pseudo-Boolean solvers. Once the tool has found a feasible solution, it can improve it using a second encoding that alters only the home/away pattern of games. We entered our tool into the International Timetabling Competition 2021. While it was effective on many instances, it struggled to cope with schedules involving large break constraints. However, among instances for which it could initially find a feasible solution, the combination of use of a portfolio of solvers, a range of variations on the encoding and the aforementioned local improvement process yielded an average reduction in solution cost of 23%.
On the Strong Liouville Property of Covering Spaces
Authors: Polymerakis Panagiotis 
Published: June 2022

AbstractLyons and Sullivan conjectured in Lyons and Sullivan (J. Differential Geom. 19(2), 299–323, 1984) that if p : M → N is a normal Riemannian covering, with N closed, and M has exponential volume growth, then there are non-constant, positive harmonic functions on M. This was proved recently in Polymerakis (Adv. Math. 379, 107552–107558, 2021) exploiting the Lyons-Sullivan discretization and some sophisticated estimates on the green metric on groups. In this note, we provide a self-contained proof relying only on elementary properties of the Brownian motion.
Ankle fractures: a systematic review of patient-reported outcome measures and their measurement properties
Authors: Nguyen Michael Quan , Dalen Ingvild , Iversen Marjolein Memelink , Harboe Knut , Paulsen Aksel 
Published: June 2022

Abstract
Purpose
Ankle fractures are commonly occurring fractures, especially in the aging population, where they often present as fragility fractures. The disease burden and economic costs to the patient and society are considerable. Choosing accurate outcome measures for the evaluation of the management of ankle fractures in clinical trials facilitates better decision-making. This systematic review assesses the evidence for the measurement properties of patient-reported outcome measures (PROMs) used in the evaluation of adult patients with ankle fractures.

Methods
Searches were performed in CINAHL, EMBASE, Medline and Google Scholar from the date of inception to July 2021. Studies that assessed the measurement properties of a PROM in an adult ankle fracture population were included. The included studies were assessed according to the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology for systematic reviews of PROMs.

Results
In total, 13 different PROMs were identified in the 23 included articles. Only the Ankle Fracture Outcome of Rehabilitation Measure (A-FORM) presented some evidence on content validity. The Olerud-Molander Ankle Score (OMAS) and Self-reported Foot and Ankle Score (SEFAS) displayed good evidence of construct validity and internal consistency. The measurement properties of the OMAS, LEFS and SEFAS were most studied.

Conclusion
The absence of validation studies covering all measurement properties of PROMs used in the adult ankle fracture population precludes the recommendation of a specific PROM to be used in the evaluation of this population. Further research should focus on validation of the content validity of the instruments used in patients with ankle fractures.
Connections matter: a proxy measure for evaluating network membership with an application to the Seventh Research Framework Programme
Authors: Cinelli Matteo , Ferraro Giovanna , Iovanella Antonio 
Published: June 2022

AbstractAlthough the topic of networks has received significant attention from the scientific literature, it remains to be seen whether it is possible to quantify the degree to which an organisation benefits from being part of a network. Starting from the concept of network value and that of Metcalfe’s Law, this paper introduces and defines the collective network effect (CNE). CNE is based on the concept that a network member is not only affected by its friends but also by the friends of its friends. By taking into account network connection patterns, CNE provides a proxy for quantifying the benefit of network membership. We computed the CNE for the nodes of a large network built using the whole set of common projects among the participants of the 7th Framework Programme for Research and Technological Development of the European Commission. The obtained results show that nodes with a higher CNE have access to substantially more conspicuous fundings than nodes with a lower CNE. In general, such a measure could supplement other centrality measures and be useful for organisations and companies aiming to evaluate both their current situation and the potential partners they should link with in order to extract the highest benefits from network membership.
Occluded Video Instance Segmentation: A Benchmark
Authors: Qi Jiyang , Gao Yan , Hu Yao , Wang Xinggang , Liu Xiaoyu , Bai Xiang , Belongie Serge , Yuille Alan , Torr Philip H. S. , Bai Song 
Published: June 2022

AbstractCan our video understanding systems perceive objects when a heavy occlusion exists in a scene? To answer this question, we collect a large-scale dataset called OVIS for occluded video instance segmentation, that is, to simultaneously detect, segment, and track instances in occluded scenes. OVIS consists of 296k high-quality instance masks from 25 semantic categories, where object occlusions usually occur. While our human vision systems can understand those occluded instances by contextual reasoning and association, our experiments suggest that current video understanding systems cannot. On the OVIS dataset, the highest AP achieved by state-of-the-art algorithms is only 16.3, which reveals that we are still at a nascent stage for understanding objects, instances, and videos in a real-world scenario. We also present a simple plug-and-play module that performs temporal feature calibration to complement missing object cues caused by occlusion. Built upon MaskTrack R-CNN and SipMask, we obtain a remarkable AP improvement on the OVIS dataset. The OVIS dataset and project code are available at http://songbai.site/ovis.
CT-based radiomics for prediction of therapeutic response to Everolimus in metastatic neuroendocrine tumors
Authors: Caruso Damiano , Polici Michela , Rinzivillo Maria , Zerunian Marta , Nacci Ilaria , Marasco Matteo , Magi Ludovica , Tarallo Mariarita , Gargiulo Simona , Iannicelli Elsa , Annibale Bruno , Laghi Andrea , Panzuto Francesco 
Published: June 2022

Abstract
Aim
To test radiomic approach in patients with metastatic neuroendocrine tumors (NETs) treated with Everolimus, with the aim to predict progression-free survival (PFS) and death.

Materials and methods
Twenty-five patients with metastatic neuroendocrine tumors, 15/25 pancreatic (60%), 9/25 ileal (36%), 1/25 lung (4%), were retrospectively enrolled between August 2013 and December 2020. All patients underwent contrast-enhanced CT before starting Everolimus, histological diagnosis, tumor grading, PFS, overall survival (OS), death, and clinical data collected. Population was divided into two groups: responders (PFS ≤ 11 months) and non-responders (PFS > 11 months). 3D segmentation was performed on whole liver of naïve CT scans in arterial and venous phases, using a dedicated software (3DSlicer v4.10.2). A total of 107 radiomic features were extracted and compared between two groups (T test or Mann–Whitney), radiomics performance assessed with receiver operating characteristic curve, Kaplan–Meyer curves used for survival analysis, univariate and multivariate logistic regression performed to predict death, and interobserver variability assessed. All significant radiomic comparisons were validated by using a synthetic external cohort. P < 0.05 is considered significant.

Results
15/25 patients were classified as responders (median PFS 25 months and OS 29 months) and 10/25 as non-responders (median PFS 4.5 months and OS 23 months). Among radiomic parameters, Correlation and Imc1 showed significant differences between two groups (P < 0.05) with the best performance (internal cohort AUC 0.86–0.84, P < 0.0001; external cohort AUC 0.84–0.90; P < 0.0001). Correlation < 0.21 resulted correlated with death at Kaplan–Meyer analysis (P = 0.02). Univariate analysis showed three radiomic features independently correlated with death, and in multivariate analysis radiomic model showed good performance with AUC 0.87, sensitivity 100%, and specificity 66.7%. Three features achieved 0.77 ≤ ICC < 0.83 and one ICC = 0.92.

Conclusions
In patients affected by metastatic NETs eligible for Everolimus treatment, radiomics could be used as imaging biomarker able to predict PFS and death.