bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring Constraints in Business Processes Using Object-Centric Constraint Graphs
Authors: Park Gyunam , van der Aalst Wil M. P. 
Published: March 2023

AbstractConstraint monitoring aims to monitor the violation of constraints in business processes, e.g., an invoice should be cleared within 48 h after the corresponding goods receipt, by analyzing event data. Existing techniques for constraint monitoring assume that a single case notion exists in a business process, e.g., a patient in a healthcare process, and each event is associated with the case notion. However, in reality, business processes are object-centric, i.e., multiple case notions (objects) exist, and an event may be associated with multiple objects. For instance, an Order-To-Cash (O2C) process involves order, item, delivery, etc., and they interact when executing an event, e.g., packing multiple items together for a delivery. The existing techniques produce misleading insights when applied to such object-centric business processes. In this work, we propose an approach to monitoring constraints in object-centric business processes. To this end, we introduce Object-Centric Constraint Graphs (OCCGs) to represent constraints that consider the interaction of objects. Next, we evaluate the constraints represented by OCCGs by analyzing Object-Centric Event Logs (OCELs) that store the interaction of different objects in events. We have implemented a web application to support the proposed approach and conducted two case studies using a real-life SAP ERP system.
Identifying the Steps in an Exploratory Data Analysis: A Process-Oriented Approach
Authors: Daele Seppe Van , Janssenswillen Gert 
Published: March 2023

AbstractBest practices in (teaching) data literacy, specifically Exploratory Data Analysis, remain an area of tacit knowledge until this day. However, with the increase in the amount of data and its importance in organisations, analysing data is becoming a much-needed skill in today’s society. Within this paper, we describe an empirical experiment that was used to examine the steps taken during an exploratory data analysis, and the order in which these actions were taken. Twenty actions were identified. Participants followed a rather iterative process of working step by step towards the solution. In terms of the practices of novice and advanced data analysts, few relevant differences were yet discovered.
Discovering Students’ Learning Strategies in a Visual Programming MOOC Through Process Mining Techniques
Authors: Rohani Narjes , Gal Kobi , Gallagher Michael , Manataki Areti 
Published: March 2023

AbstractUnderstanding students’ learning patterns is key for supporting their learning experience and improving course design. However, this is particularly challenging in courses with large cohorts, which might contain diverse students that exhibit a wide range of behaviours. In this study, we employed a previously developed method, which considers process flow, sequence, and frequency of learning actions, for detecting students’ learning tactics and strategies. With the aim of demonstrating its applicability to a new learning context, we applied the method to a large-scale online visual programming course. Four low-level learning tactics were identified, ranging from project- and video-focused to explorative. Our results also indicate that some students employed all four tactics, some used course assessments to strategize about how to study, while others selected only two or three of all learning tactics. This research demonstrates the applicability and usefulness of process mining for discovering meaningful and distinguishable learning strategies in large courses with thousands of learners.
A Survey on the Application of Process Mining to Smart Spaces Data
Authors: Bertrand Yannis , Van den Abbeele Bram , Veneruso Silvestro , Leotta Francesco , Mecella Massimo , Serral Estefanía 
Published: March 2023

AbstractDuring the last years, a number of studies have experimented with applying process mining (PM) techniques to smart spaces data. The general goal has been to automatically model human routines as if they were business processes. However, applying process-oriented techniques to smart spaces data comes with its own set of challenges. This paper surveys existing approaches that apply PM to smart spaces and analyses how they deal with the following challenges identified in the literature: choosing a modelling formalism for human behaviour; bridging the abstraction gap between sensor and event logs; and segmenting logs in traces. The added value of this article lies in providing the research community with a common ground for some important challenges that exist in this field and their respective solutions, and to assist further research efforts by outlining opportunities for future work.
Building User Journey Games from Multi-party Event Logs
Authors: Kobialka Paul , Mannhardt Felix , Tapia Tarifa Silvia Lizeth , Johnsen Einar Broch 
Published: March 2023

AbstractTo improve the user experience, service providers may systematically record and analyse user interactions with a service using event logs. User journeys model these interactions from the user’s perspective. They can be understood as event logs created by two independent parties, the user and the service provider, both controlling their share of actions. We propose multi-party event logs as an extension of event logs with information on the parties, allowing user journeys to be analysed as weighted games between two players. To reduce the size of games for complex user journeys, we identify decision boundaries at which the outcome of the game is determined. Decision boundaries identify subgames that are equivalent to the full game with respect to the final outcome of user journeys. The decision boundary analysis from multi-party event logs has been implemented and evaluated on the BPI Challenge 2017 event log with promising results, and can be connected to existing process mining pipelines.
Discrimination-Aware Process Mining: A Discussion
Authors: Pohl Timo , Qafari Mahnaz Sadat , van der Aalst Wil M. P. 
Published: March 2023

AbstractOrganizations increasingly use process mining techniques to gain insight into their processes. Process mining techniques can be used to monitor and/or enhance processes. However, the impact of processes on the people involved, in terms of unfair discrimination, has not been studied. Another neglected area is the impact of applying process mining techniques on the fairness of processes. In this paper, we overview and categorize the existing fairness concepts in machine learning. Moreover, we summarize the areas where fairness is relevant to process mining and provide an approach to applying existing fairness definitions in process mining. Finally, we present some of the fairness-related challenges in processes.
Electric-field driven nonequilibrium phase transitions in AdS/CFT
Authors: Endo Daisuke , Fukazawa Yuichi , Matsumoto Masataka , Nakamura Shin 
Published: March 2023

Abstract
We study phase transitions and critical phenomena in nonequilibrium steady states controlled by an electric field. We employ the D3/D7 model in the presence of a charge density and electric field at finite temperatures. The system undergoes the first-order and the second-order phase transitions under the variation of the electric field in the presence of dissipation. We numerically find that the critical exponents which we define for the nonequilibrium phase transition in this model take the mean-field values.
Decoherence and thermalization of Unruh-DeWitt detector in arbitrary dimensions
Authors: Xu Hao 
Published: March 2023

Abstract
We study the decoherence and thermalization of an Unruh-DeWitt detector linearly coupled to the free massless scalar field in flat spacetime with arbitrary dimensions d ≥ 2. The initial state of the detector is chosen to be a pure state consisting of a linear superposition of ground and excited states, and we calculate the time evolution of reduced density matrix of the detector. Using perturbation method, we analytically derive the transition rate of the detector (the rate of change of the diagonal elements in the density matrix) and the decoherence rate (the rate of change of the off-diagonal elements in the density matrix). We find that the results are not the same in odd and even dimensional spacetimes, but the unitarity of the qubit is preserved in both cases. The real part of the decoherence rate is related to the transition rate, while the imaginary part may contain different forms of divergence terms in different dimensions due to the temporal order product operator and the singularities of the Wightman function for quantum field theory. We derive the recurrence formula to obtain the divergence terms in each dimension and analyze the renormalization problem.
Medium-induced radiation with vacuum propagation in the pre-hydrodynamics phase
Authors: Andres Carlota , Apolinário Liliana , Dominguez Fabio , Martinez Marcos Gonzalez , Salgado Carlos A. 
Published: March 2023

Abstract
The recent discovery of the potential of jet quenching observables to constrain the initial stages after a heavy-ion collision makes imperative to have a better understanding of the process of medium-induced radiation before the formation of the quark-gluon plasma (QGP) and its impact on observables at high-pT. In this work, we generalize the BDMPS-Z framework for medium-induced radiation to account for additional emissions occurring before the creation of the QGP. For simplicity, we assume that during the pre-hydrodynamics phase the hard parton propagates as in vacuum. This set-up, allows us to isolate the contribution from the additional initial radiation by comparing with the usual scenarios in which the emitter is created inside the medium but with different starting points. Using both a numerical implementation of the fully resummed emission spectrum and the usual analytical approximations, we find that replacing an initial slab of the medium by vacuum yields to a significant reduction of the emission spectrum for low radiated gluon energies, while the high-energy tails remain largely unmodified. Finally, we assess the effect of replacing the initial medium by vacuum propagation on the single-inclusive particle suppression RAA and high-pT azimuthal asymmetry v2. Our findings indicate that considering vacuum propagation prior to hydrodynamization leads to an increase in the v2, thus corroborating the importance of the treatment of jet quenching in the initial stages for the correct description of both observables.
On pentagon identity in Ding-Iohara-Miki algebra
Authors: Zenkevich Yegor 
Published: March 2023

Abstract
We notice that the famous pentagon identity for quantum dilogarithm functions and the five-term relation for certain operators related to Macdonald polynomials discovered by Garsia and Mellit can both be understood as specific cases of a general “master pentagon identity” for group-like elements in the Ding-Iohara-Miki (or quantum toroidal, or elliptic Hall) algebra. We prove this curious identity and discuss its implications.
Non-audible acoustic emission characterization of Reticulitermes termites in pine wood
Authors: Suarez Elisabet , Fuentes Yaiza , Gaju-Ricart Miquel , Gallego Antolino 
Published: March 2023

AbstractThis research evaluates and characterizes the acoustic emission activity generated by Reticulitermes termites as recorded by piezoelectric sensors with sensitivity in the ultrasound range (greater than 20 kHz). To this end, the acoustic emission activity was recorded under controlled conditions of temperature and moisture content in three pine wood samples in which termites were artificially inoculated: only soldiers, only workers, or a colony of workers and soldiers. Different traditional parameters of the acoustic emission signals were analyzed, in both the time and frequency domains. This study proved feasible to use acoustic emission to detect the activity of this kind of termites, although it was not possible to distinguish between workers and soldiers. It is also demonstrated that, by using several sensors, one can locate the activity of the insects, a finding of great practical interest for the accurate detection of colonies in real buildings.
Diabetes and climate change: current evidence and implications for people with diabetes, clinicians and policy stakeholders
Authors: Ratter-Rieck Jacqueline M. , Roden Michael , Herder Christian 
Published: March 2023

AbstractClimate change will be a major challenge for the world’s health systems in the coming decades. Elevated temperatures and increasing frequencies of heat waves, wildfires, heavy precipitation and other weather extremes can affect health in many ways, especially if chronic diseases are already present. Impaired responses to heat stress, including compromised vasodilation and sweating, diabetes-related comorbidities, insulin resistance and chronic low-grade inflammation make people with diabetes particularly vulnerable to environmental risk factors, such as extreme weather events and air pollution. Additionally, multiple pathogens show an increased rate of transmission under conditions of climate change and people with diabetes have an altered immune system, which increases the risk for a worse course of infectious diseases. In this review, we summarise recent studies on the impact of climate-change-associated risk for people with diabetes and discuss which individuals may be specifically prone to these risk conditions due to their clinical features. Knowledge of such high-risk groups will help to develop and implement tailored prevention and management strategies to mitigate the detrimental effect of climate change on the health of people with diabetes.
Graphical abstract
Postoperative full leg radiographs exhibit less residual coronal varus deformity compared to intraoperative measurements in robotic arm-assisted total knee arthroplasty with the MAKO™ system
Authors: Glowalla Claudio , Langer Severin , Lenze Ulrich , Lazic Igor , Hirschmann Michael T. , Hinterwimmer Florian , von Eisenhart-Rothe Rüdiger , Pohlig Florian 
Published: March 2023

Abstract
Purpose
Robotic arm-assisted total knee arthroplasty (raTKA), currently a major trend in knee arthroplasty, aims to improve the accuracy of implant positioning and limb alignment. However, it is unclear whether and to what extent manual radiographic and navigation measurements with the MAKO™ system correlate. Nonetheless, a high agreement would be crucial to reliably achieve the desired limb alignment.

Methods
Thirty-six consecutive patients with osteoarthritis and a slight-to-moderate varus deformity undergoing raTKA were prospectively included in this study. Prior to surgery and at follow-up, a full leg radiograph (FLR) under weight-bearing conditions was performed. In addition, a computed tomography (CT) scan was conducted for preoperative planning. The hip–knee–ankle angle (HKA), mechanical lateral distal femur angle (mLDFA), mechanical medial proximal tibial angle (mMPTA) and joint line convergence angle (JLCA) were measured in the preoperative and follow-up FLR as well as in the CT scout (without weight-bearing) by three independent raters. Furthermore, the HKA was intraoperatively assessed with the MAKO™ system before and after raTKA.

Results
Significantly higher HKA values were identified for intraoperative deformity assessment using the MAKO system compared to the preoperative FLR and CT scouts (p = 0.006; p = 0.05). Intraoperative assessment of the HKA with final implants showed a mean residual varus deformity of 3.2° ± 1.9°, whereas a significantly lower residual varus deformity of 1.4° ± 1.9° was identified in the postoperative FLR (p < 0.001). The mMPTA was significantly higher in the preoperative FLR than in the CT scouts (p < 0.001). Intraoperatively, the mMPTA was adjusted to a mean of 87.5° ± 0.9° with final implants, while significantly higher values were measured in postoperative FLRs (p < 0.001). Concerning the mLDFA, no significant differences could be identified.

Conclusion
The clinical importance of this study lies in the finding that there is a difference between residual varus deformity measured intraoperatively with the MAKO™ system and those measured in postoperative FLRs. This has implications for preoperative planning as well as intraoperative fine-tuning of the implant position during raTKA to avoid overcorrection of knees with slight-to-moderate varus osteoarthritis.

Level of evidence
Level IV.
Epidemic modeling with heterogeneity and social diffusion
Authors: Berestycki Henri , Desjardins Benoît , Weitz Joshua S. , Oury Jean-Marc 
Published: March 2023

AbstractWe propose and analyze a family of epidemiological models that extend the classic Susceptible-Infectious-Recovered/Removed (SIR)-like framework to account for dynamic heterogeneity in infection risk. The family of models takes the form of a system of reaction–diffusion equations given populations structured by heterogeneous susceptibility to infection. These models describe the evolution of population-level macroscopic quantities S, I, R as in the classical case coupled with a microscopic variable f, giving the distribution of individual behavior in terms of exposure to contagion in the population of susceptibles. The reaction terms represent the impact of sculpting the distribution of susceptibles by the infection process. The diffusion and drift terms that appear in a Fokker–Planck type equation represent the impact of behavior change both during and in the absence of an epidemic. We first study the mathematical foundations of this system of reaction–diffusion equations and prove a number of its properties. In particular, we show that the system will converge back to the unique equilibrium distribution after an epidemic outbreak. We then derive a simpler system by seeking self-similar solutions to the reaction–diffusion equations in the case of Gaussian profiles. Notably, these self-similar solutions lead to a system of ordinary differential equations including classic SIR-like compartments and a new feature: the average risk level in the remaining susceptible population. We show that the simplified system exhibits a rich dynamical structure during epidemics, including plateaus, shoulders, rebounds and oscillations. Finally, we offer perspectives and caveats on ways that this family of models can help interpret the non-canonical dynamics of emerging infectious diseases, including COVID-19.
Validation of the SSTR-RADS 1.0 for the structured interpretation of SSTR-PET/CT and treatment planning in neuroendocrine tumor (NET) patients
Authors: Grawe Freba , Ebner Ricarda , Geyer Thomas , Beyer Leonie , Winkelmann Michael , Sheikh Gabriel T. , Eschbach Ralf , Schmid-Tannwald Christine , Cyran Clemens C. , Ricke Jens , Bartenstein Peter , Heimer Maurice M. , Faggioni Lorenzo , Spitzweg Christine , Fabritius Matthias P. , Auernhammer Christoph J. , Ruebenthaler Johannes 
Published: March 2023

Abstract

Objectives
The recently proposed standardized reporting and data system for somatostatin receptor (SSTR)–targeted PET/CT SSTR-RADS 1.0 showed promising first results in the assessment of diagnosis and treatment planning with peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NET). This study aimed to determine the intra- and interreader agreement of SSTR-RADS 1.0.

Methods
SSTR-PET/CT scans of 100 patients were independently evaluated by 4 readers with different levels of expertise according to the SSTR-RADS 1.0 criteria at 2 time points within 6 weeks. For each scan, a maximum of five target lesions were freely chosen by each reader (not more than three lesions per organ) and stratified according to the SSTR-RADS 1.0 criteria. Overall scan score and binary decision on PRRT were assessed. Intra- and interreader agreement was determined using the intraclass correlation coefficient (ICC).

Results
Interreader agreement using SSTR-RADS 1.0 for identical target lesions (ICC ≥ 0.91) and overall scan score (ICC ≥ 0.93) was excellent. The decision to state “functional imaging fulfills requirements for PRRT and qualifies patient as potential candidate for PRRT” also demonstrated excellent agreement among all readers (ICC ≥ 0.86). Intrareader agreement was excellent even among different experience levels when comparing target lesion–based scores (ICC ≥ 0.98), overall scan score (ICC ≥ 0.93), and decision for PRRT (ICC ≥ 0.88).

Conclusion
SSTR-RADS 1.0 represents a highly reproducible and accurate system for stratifying SSTR-targeted PET/CT scans with high intra- and interreader agreement. The system is a promising approach to standardize the diagnosis and treatment planning in NET patients.

Key Points
• SSTR-RADS 1.0 offers high reproducibility and accuracy.
• SSTR-RADS 1.0 is a promising method to standardize diagnosis and treatment planning for patients with NET.
Genomic distribution and polymorphism of G-quadruplex motifs occupying ovine promoters and enhancers
Authors: Stefos Georgios C. , Theodorou Georgios , Politis Ioannis 
Published: March 2023

AbstractG-quadruplexes are non-canonical DNA structures that are formed in regions with short runs of guanines. During the last decade they have gained considerable attention due to their involvement in basic cellular processes, linking them to several physiological processes and pathological conditions. Regulation of gene transcription is among the crucial roles that G-quadruplexes play in the cells. Several ways in which these structures affect transcription have been described, both negatively and positively. Recently, G-quadruplexes have been shown to be implicated in the three-dimensional rearrangement of the chromosomes that enables the interaction of enhancers and gene promoters during regulation of transcription. Sheep is a species for which almost no G-quadruplex-related studies have been conducted and thus research on this species is kept out from the progress that has been made in the G-quadruplex field. In this context, we investigated the DNA sequences with potential to form G-quadruplexes (G4-motifs) in the ovine enhancers and promoters. We describe the distribution of G4-motifs within the regulatory regions which is shown to be enriched in G4-motifs in a way similar to other mammals. Furthermore, our data suggest that G4-motifs promote promoter-enhancer interactions in sheep. The single nucleotide polymorphisms colocalizing with promoter- and enhancer-associated ovine G4-motifs constitute a considerable pool of polymorphism and given the crucial role of these specific G4-motifs on regulation of transcription, we suggest this polymorphism as an interesting target for ovine genetic studies.
Investigation of fluidic thrust vectoring for scramjets
Authors: Hambidge Chris , Ivison William , Steuer David , Neely Andrew , McGilvray Matthew 
Published: March 2023

Abstract
Fluidic thrust vectoring (FTV) offers a novel approach to aerodynamic control, circumventing some of the issues associated with mechanical systems. One method is shock vector control which involves injecting a fluid into the exhaust nozzle of an engine to redirect the gases and thus, produce a control force. An experimental model which incorporated FTV was designed and tested at Mach 6 in the Oxford high density tunnel (HDT). The model was a simplified two-dimensional scramjet geometry with two different configurations to compare an internal and external exhaust nozzle. The FTV injection system consisted of a slot at the rear edge of the exhaust nozzle fed from an internal plenum. In the experimental campaign, a range of gas injection pressures and free stream stagnation pressures were tested to assess the effectiveness of both configurations. Two new measurement methods were successfully implemented in the HDT: pressure sensitive paint and a 6-axis load cell. The FTV system has been shown to be effective with observable increases in lift and pitching moment. A linear relation between the injection pressure ratio and the control forces could be observed for both configurations.

Graphical abstract