bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blackout and supply chains: Cross-structural ripple effect, performance, resilience and viability impact analysis
Authors: Ivanov Dmitry 
Published: June 2022

AbstractIncreased electricity consumption along with the transformations of the energy systems and interruptions in energy supply can lead to a blackout, i.e., the total loss of power in an area (or a set of areas) of a longer duration. This disruption can be fatal for production, logistics, and retail operations. Depending on the scope of the affected areas and the blackout duration, supply chains (SC) can be impacted to different extent. In this study, we perform a simulation analysis using anyLogistix digital SC twin to identify potential impacts of blackouts on SCs for scenarios of different severity. Distinctively, we triangulate the design and evaluation of experiments with consideration of SC performance, resilience, and viability. The results allow for some generalizations. First, we conceptualize blackout as a special case of SC risks which is distinctively characterized by a simultaneous shutdown of several SC processes, disruption propagations (i.e., the ripple effect), and a danger of viability losses for entire ecosystems. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of blackouts, mitigation and recovery strategies. The major observation from the simulation experiments is that the dynamics of the power loss propagation across different regions, the blackout duration, simultaneous unavailability of supply and logistics along with the unpredictable customer behavior might become major factors that determine the blackout impact and influence selection of an appropriate recovery strategy. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of blackouts on the SCs and viability and develop mitigation and recovery strategies. The paper is concluded by summarizing the most important insights and outlining future research agenda toward SC viability, reconfigurable SC, multi-structural SC dynamics, intertwined supply networks, and cross-structural ripple effects.
Exploring data-driven innovation: What’s missing in the relationship between big data analytics capabilities and supply chain innovation?
Authors: Bhatti Sabeen Hussain , Hussain Wan Mohd Hirwani Wan , Khan Jabran , Sultan Shahbaz , Ferraris Alberto 
Published: June 2022

AbstractData-driven innovations (DDI) have significantly impacted firms’ operations thanks to the massive exploitation of huge data. However, to leverage big data and achieve supply chain innovation, a variety of complementary resources are necessary. In this study, we hypothesise that supply chain innovation (SCI) is dependent on firms’ big data analytics capabilities (BAC). Furthermore, we propose that this relation is mediated by two crucial capabilities of agility and adaptability that enable firms to efficiently meet the challenges of supply chain ambidexterity. Finally, we also test the moderating role of technology uncertainty in our research model. We collected data from 386 manufacturing firms in Pakistan and tested our model using structural equation modelling. The results confirmed our initial hypotheses that agility and adaptability both mediated our baseline relationship of BAC and big data innovation in supply chains. We further found support for the moderating role of technology uncertainty. Furthermore, technology uncertainty moderates the relationship between BAC and SCI. This study extends the current literature on digital analytics capabilities and innovation along the supply chain. Practically, our research suggests that investment in big data can result in affirmative consequences, if firms cultivate capabilities to encounter supply chain ambidexterity through agility and adaptability. Accordingly, we suggest that managers belonging to manufacturing firms need to build up these internal capabilities and to monitor and assess technology uncertainty in the environment.
Spatial performance analysis in basketball with CART, random forest and extremely randomized trees
Authors: Zuccolotto Paola , Sandri Marco , Manisera Marica 
Published: June 2022

AbstractThis paper proposes tools for spatial performance analysis in basketball. In detail, we aim at representing maps of the court visualizing areas with different levels of scoring probability of the analysed player or team. To do that, we propose the adoption of algorithmic modeling techniques. Firstly, following previous studies, we examine CART, highlighting strengths and weaknesses. With respect to what done in the past, here we propose the use of polar coordinates, which are more consistent with the basketball court geometry. In order to overcome CART’s drawbacks while maintaining its points of force, we propose to resort to CART-based ensemble learning algorithms, namely to Random Forest and Extremely Randomized Trees, which are shown to be able to give excellent results in terms of interpretation and robustness. Finally, an index is defined in order to measure the map’s graphical goodness, which can be used—jointly with measures of the out-of-sample error—to tune the algorithm’s parameters. The functioning of the proposed approaches is shown by the analysis of real data of the NBA regular season 2020/2021.
A stochastic optimization algorithm for analyzing planar central and balanced configurations in the n-body problem
Authors: Doicu Alexandru , Zhao Lei , Doicu Adrian 
Published: June 2022

AbstractA stochastic optimization algorithm for analyzing planar central and balanced configurations in then-body problem is presented. We find a comprehensive list of equal mass central configurations satisfying the Morse equality up to$$n=12$$n=12. We show some exemplary balanced configurations in the case$$n=5$$n=5, as well as some balanced configurations without any axis of symmetry in the cases$$n=4$$n=4and$$n=10$$n=10.
Psychological Safety at Local Union Meetings: A Key to Unlock Meeting Attendance
Authors: Mellor Steven 
Published: June 2022

AbstractWe take a psychological view of local union meetings in reference to the problem of chronic low meeting attendance. This view suggests that local meetings are designed to encourage employees to experience safe environments in which they can strive to fulfill psychological needs, examples of which include a need to voice concerns and opinions, a need to participate in decision-making, and a need to be counted as a valued contributor to “our collective effort.” As such, we constructed a model to predict likely meeting attendance informed by literatures on team effectiveness, meeting design, and union participation. Extracting relationships from the cited literature relevant to local meetings, we positioned psychological safety experienced at meetings as a predictor of likely attendance in the next 12 months, with meeting effectiveness as rated by attending employees positioned as a mediator of the relationship. A test of the mediated model based on data collected from employees in 20 unions and 42 locals (N = 132) suggested support for the model, in which the effect of psychological safety on likely attendance was shown to unfold through meeting effectiveness. Future models of local attendance are discussed and an intervention aimed at solving the attendance problem is suggested.
The role of brokers in cultivating an inter-institutional community around open educational resources in higher education
Authors: Baas Marjon , Schuwer Robert , van den Berg Ellen , Huizinga Tjark , van der Rijst Roeland , Admiraal Wilfried 
Published: June 2022

AbstractBrokers are individuals who facilitate transfer of knowledge and resources, and coordinate efforts across boundaries of organizations. They are defined by their role rather than their organizational position. Brokers might be imperative for the formation and maintenance of inter-institutional relationship as they have the responsibility and the necessary structural position to connect otherwise separate groups. In the context of this study, brokers had the role to cultivate an inter-institutional community around open educational resources (OER) by connecting groups of teachers across higher education institutes. OER provide higher education institutes with an aid to face the challenges of improving teaching and learning. Yet most OER users encounter challenges that relate to finding resources that are relevant, up-to-date, and of good quality. Communities could minimize this issue, but many OER initiatives fizzle out as expanding their impact is an arduous task. This qualitative descriptive study draws upon cultural-historical activity theory to understand the complexities associated with the role of brokers in creating sustainable collaboration on OER across 15 higher education institutes in the Netherlands. Data was collected from project documents, process reports, reflections reports, and a retrospective focus group. The findings show that brokers engaged in a wide variety of actions but that a small-scale, personal, and content-oriented approach to encourage teachers to engage with the OER repository and the online community was perceived as the most valuable. Brokers also experienced conflicts due to the demanding context they were operating in, the ambiguity of their role, and the organizational constraints they were confronted with. Practical implications refer to supporting higher education institutes that wish to initiate sustainable collaboration across institutes.
Exploring the effects of mobility and foreign nationality on internal career progression in universities
Authors: Seeber Marco , Debacker Noëmi , Meoli Michele , Vandevelde Karen 
Published: June 2022

AbstractThis article explores how organizational mobility and foreign nationality affect a researcher’s chances of an internal career promotion in university systems that do not have rules preventing inbreeding and where teaching occurs mostly not in English but a local language. As a case study, we have examined the Flemish university system, the Dutch speaking part of Belgium, and developed expectations on the chances of promotion for mobile and foreign researchers compared to non-mobile and nationals. We use data for all postdoctoral and professorial staff between 1991 and 2017, for a total of 14,135 scientists. We calculated the chances of promotion with a competing risk model to take time into account and to disentangle the probability of two mutually exclusive risk events: promotion and leaving the university. The results show that international mobility and foreign nationality reduced the chances of promotion in the same university, and that mobile and foreign scientists were also more likely to leave any given university. These effects were particularly strong at an early stage: in the study period, 21.9% of non-mobile national postdocs became professor compared to just 1.2% of internationally mobile foreigners. These results would suggest that internationally mobile and foreign scientists struggle to advance in universities that lack rules preventing inbreeding and with little opportunity to teach in English.
Divergence/Connection Preservation Scheme in the Curvilinear Domain with a Small Geometric Approximation Error
Authors: Chun Sehun , Oh Taejin 
Published: June 2022

AbstractAdditional grid points are often introduced for the higher-order polynomial of a numerical solution with curvilinear elements. However, those points are likely to be located slightly outside the domain, even when the vertices of the curvilinear elements lie within the curved domain. This misallocation of grid points generates a mesh error, calledgeometric approximation error. This error is smaller than the discretization error but large enough to significantly degrade a long-time integration. Moreover, this mesh error is considered to be the leading cause of conservation error. Two novel schemes are proposed to improve conservation error and/or discretization error for long-time integration caused by geometric approximation error: The first scheme retrieves the original divergence of the original domain; the second scheme reconstructs the original path of differentiation, calledconnection, thus retrieving the original connection. The increased accuracies of the proposed schemes are demonstrated by the conservation error for various partial differential equations with moving frames on the sphere.
Impact of Opioid Use on Duration of Time Loss After Work-Related Lower Limb Injury
Authors: Szucs Katrina , Gray Shannon E. 
Published: June 2022

AbstractPurpose This study sought to determine patterns of opioid use among workers with a compensated lower limb injury, factors associated with opioid use, and how opioid use is associated with time loss duration. Methods Claims and medication data were provided by the workers’ compensation regulator of Victoria, Australia, for claims lodged 2008–2018 from workers aged 15+ years with a lower limb injury. Descriptive statistics showed the number and prevalence of each opioid type (weak/strong) by demographic, claim and injury predictors. Binary and multinomial logistic regression determined the likelihood of any opioid use, and use of strong, weak or a combination of strong and weak opioids by predictors. Cox regression determined the effect of each opioid type on duration of time loss, controlling for predictors. Results There were 51,334 claims and of these 23.6% were dispensed opioids (9.2% for strong opioids only, 6.6% for weak opioids only and 7.8% for a combination). Weak opioids, on average, were dispensed 15 days earlier than strong opioids. Time loss claims and workers with fractures or hip injuries were most likely to be dispensed opioids. All opioids were associated with increased duration of time loss, with those dispensed both weak and strong opioids having the longest duration of time loss. Conclusions Any opioid use was associated with longer time loss duration, with increasing opioid strength having a greater effect. Review of pain management methods should be undertaken to reduce opioid use, which may have a positive impact on duration of time loss and long-term function.
Intergenerational Transmission of Peer Aggression
Authors: Wiertsema Maria , Vrijen Charlotte , van der Ploeg Rozemarijn , Kretschmer Tina 
Published: June 2022

AbstractIt is plausible that peer aggression—like general forms of aggression—is transmitted from one generation to the next. As such, parental behavior in childhood and adolescence may be associated with offspring aggressive behavior against peers. This study used 1970 British Cohort Study data to test intergenerational transmission of peer aggression. The baseline sample consisted of 13,135 participants. At the first assessment that was used in this study, participants were on average 4.95 years old (SD = 0.79; 48.20% female). At the last assessment, participants were on average 33.88 years old (SD = 0.36; 52.1% female). Models were computed for early and middle childhood, and adolescence. Significant associations between parents’ and offspring peer aggression were found in most models – especially when correlating aggression in similar developmental periods for parents and children. Other transmission mechanisms such as genetic transmission may be relevant and should be taken into account in future studies.
Uncertainty estimation based adversarial attack in multi-class classification
Authors: Alarab Ismail , Prakoonwit Simant 
Published: June 2022

AbstractModel uncertainty has gained popularity in machine learning due to the overconfident predictions derived from standard neural networks which are not trustworthy. Recently, Monte-Carlo based adversarial attack (MC-AA) has been proposed as a simple uncertainty estimation method which is powerful in capturing data points that lie in the overlapping distribution of the decision boundary. MC-AA produces uncertainties by performing back-and-forth perturbations of a given data point towards the decision boundary using the idea of adversarial attacks. Despite its efficacy against other uncertainty estimation methods, this method has been only examined on binary classification problems. Thus, we present and examine MC-AA with multi-class classification tasks. We point out the limitation of this method with multiple classes which we tackle by converting multiclass problem into ‘one-versus-all’ classification. We compare MC-AA against other recent model uncertainty methods on Cora – a graph structured dataset – and MNIST – an image dataset. Thus, the conducted experiments are performed using a variety of deep learning algorithms to perform the classification. Consequently, we discuss the best results of model uncertainty with Cora data using LEConv model of AUC-score 0.889 and MNIST data using CNN of AUC-score 0.98 against other uncertainty estimation methods.
Designing postures for rehabilitation therapies in a multimodal system based on a 3D virtual environment and movement-based interaction
Authors: Penichet Víctor M. R. , Lozano María D. , Garrido Juan E. , Albertos-Marco Félix , Bond Raymond , Mulvenna Maurice D. 
Published: June 2022

AbstractTechnological advances have facilitated new approaches to support different needs in healthcare environments. In particular, in the field of rehabilitation therapies, we can find software applications that have been developed to support the performance of specific exercises, often with different customization options. However, there are still many gaps that need to be addressed to provide more and better global solutions. In this article, we present a novel system aimed at physiotherapists, which allows them to create new rehabilitation exercises designed to meet the specific needs of their patients. This implies the creation of individualized therapies that contribute to a better and faster recovery of patients. The system consists of a virtual 3D environment with a 3D skeleton representing the patient. The physiotherapist can interact with the skeleton to design the desired postures that the patient should practice according to their personal limitations. The system allows physiotherapists to compose a complete and personalized set of exercises. Alternatively, the physiotherapist may also create the postures by means of a motion sensing device using motion- and voice-based interaction. Both options pose research challenges that the authors have addressed to provide the solution presented in this paper.
Current Account Imbalances, Real Exchange Rates, and Nominal Exchange Rate Variability
Authors: Velic Adnan 
Published: June 2022

AbstractThis paper globally analyzes the bivariate relation between large current account imbalances and the real exchange rate over different degrees of nominal exchange rate variability. Employing both linear and nonlinear panel estimation procedures, we typically find an inverse long-run link between large imbalances and the real exchange rate at lower nominal exchange rate rigidity levels. This is in contrast to the often non-existent or positive comovement that materializes under lower nominal exchange rate variation. Our results thus suggest that greater nominal exchange rate adjustment can induce a stabilizing “current account”-“real exchange rate” relation. Meanwhile, current account adjustment speeds up with more flexible nominal exchange rates. Along the cross-section, the most salient findings are i) the striking positive relation between current account persistence and real exchange rate persistence based on country-specific estimates and ii) the inverse correlation between persistence in either the current account or real exchange rate and nominal exchange rate volatility.
The Effects of Solid Particle Containing Inks on the Printing Quality of Porous Pharmaceutical Structures Fabricated by 3D Semi-Solid Extrusion Printing
Authors: Teoh Xin-Yi , Zhang Bin , Belton Peter , Chan Siok-Yee , Qi Sheng 
Published: June 2022

Abstract
Purpose
Semi-solid extrusion (SSE) 3D printing has potential pharmaceutical applications for producing personalised medicine. However, the effects of ink properties and drug incorporation on the quality of printed medication have not been thoroughly studied, particularly for porous geometries. This study aimed to investigate the effects of the presence of solid drug particles in SSE inks on the printing quality of porous structures.

Method
The rheological behaviour of model inks of paracetamol (PCM)-hypromellose (HPMC) with different drug loadings were investigated and correlated to their printing qualities.

Results
For the inks with PCM loading above the drug solubility in which suspended solid drug particulates were present, the results confirmed that PCM loading and particle size significantly affected the ink viscosities at a low shear rate. At a low shear rate, the highest viscosity was identified when the highest drug loading and the smallest PCM particles were incorporated into the inks. However, the results indicated that the SSE printing parameters and printing quality of porous structures (with less porous structural deformation) have no clear correlation with the shear viscosity data, but a strong correlation with the dynamic oscillatory rheology of the inks.

Conclusion
The key rheological parameters including storage modulus, loss modulus and complex viscosity of the ink increased with increasing drug loading for the inks containing solid drug particles. However, decreasing the particle size did not have a clear effect on the oscillatory rheology of the inks which can be potentially used for optimising the SSE 3D printing quality of porous geometries.
Biocompatible Cationic Lipoamino Acids as Counterions for Oral Administration of API-Ionic Liquids
Authors: Lai Anthony , Leong Nathania , Zheng Dan , Ford Leigh , Nguyen Tri-Hung , Williams Hywel D. , Benameur Hassan , Scammells Peter J. , Porter Christopher J. H. 
Published: June 2022

Abstract
Purpose
The use of ionic liquids (ILs) in drug delivery has focused attention on non-toxic IL counterions. Cationic lipids can be used to form ILs with weakly acidic drugs to enhance drug loading in lipid-based formulations (LBFs). However, cationic lipids are typically toxic. Here we explore the use of lipoaminoacids (LAAs) as cationic IL counterions that degrade or digest in vivo to non-toxic components.

Methods
LAAs were synthesised via esterification of amino acids with fatty alcohols to produce potentially digestible cationic LAAs. The LAAs were employed to form ILs with tolfenamic acid (Tol) and the Tol ILs loaded into LBF and examined in vitro and in vivo.

Results
Cationic LAAs complexed with Tol to generate lipophilic Tol ILs with high drug loading in LBFs. Assessment of the LAA under simulated digestion conditions revealed that they were susceptible to enzymatic degradation under intestinal conditions, forming biocompatible FAs and amino acids. In vitro dispersion and digestion studies of Tol ILs revealed that formulations containing digestible Tol ILs were able to maintain drug dispersion and solubilisation whilst the LAA were breaking down under digesting conditions. Finally, in vivo oral bioavailability studies demonstrated that oral delivery of a LBF containing a Tol IL comprising a digestible cationic lipid counterion was able to successfully support effective oral delivery of Tol.

Conclusions
Digestible LAA cationic lipids are potential IL counterions for weakly acidic drug molecules and digest in situ to form non-toxic breakdown products.