bluuebunny/crossref_metadata_2025_split huggingface dataset:
A satellite‐based climatology of fog and low stratus formation and dissipation times in central Europe
Authors: Pauli Eva , Cermak Jan , Andersen Hendrik 
Published: March 2022

AbstractKnowledge of fog and low stratus (FLS) cloud patterns and life cycles is important for traffic safety, for the production of solar energy and for the analysis of cloud processes in the climate system. While meteorological stations provide information on FLS, a data set describing FLS formation and dissipation times on large spatial and temporal scales does not yet exist. In this study, we use logistic regression to extract FLS formation and dissipation times from a satellite‐based 10‐year FLS data set covering central Europe. The resulting data set is the first to provide a geographic perspective on FLS formation and dissipation at a continental scale. The patterns found show a clear dependency of FLS formation and dissipation times on topography. In mountainous areas, FLS forms in the night and dissipates in the morning. In river valleys, the typical FLS life cycle shifts to formation after sunrise and dissipation in the afternoon. Seasonal patterns of FLS formation and dissipation show similar FLS formation and dissipation times in winter and autumn, and in spring and summer, with longer events in the former two seasons.
Identifying behavioural patterns of coupled water‐agriculture systems using system archetypes
Authors: Nyam Yong Sebastian , Kotir Julius H. , Jordaan Andries , Ogundeji Abiodun Akintunde 
Published: March 2022

AbstractManaging water and food systems in South Africa is complex given the factors involved in sustainably managing the sector. To ensure sustainable management of water and agricultural systems, equal access to natural resources, and economic equality, the government has implemented policies to regulate the systems and ensure economic growth. However, the unintended consequences of these policies on the sustainability of water and agricultural systems have not been fully understood in South Africa. This paper identified and analysed four system archetypes believed to have implications for current water and agricultural development policies in South Africa. These are ‘Limits to Growth’, ‘Fixes that Fail’, ‘Shifting the Burden’, and the ‘Attractiveness Principle’. The results show that policies implemented by the government ensure inclusiveness, equal access to natural resources, and improve productivity in the short‐term; the unintended consequences will ultimately undermine sustainability and food security over time.
Geo‐eco‐hydrology of the Upper Yellow River
Authors: Brierley Gary J. , Han Meiqin , Li Xilai , Li Zhiwei , Huang He Qing 
Published: March 2022

AbstractA climate‐induced vegetation gradient induces marked variability in the character and behavior of anabranching reaches of the Upper Yellow River. Analysis of satellite imagery and field appraisal of biogeomorphic attributes shows that these reaches retain a good condition in geo‐eco‐hydrological terms. Degradational trends experienced in the late 20th century have been transformed into recovery pathways in recent decades. Changing land use practices, especially reduced stocking rates, and creation of various reserves have engendered environmental improvement. Recent climate change has supported improvements in geo‐eco‐hydrological conditions in the study reaches. A comprehensive suite of environmental protection programs of unprecedented scope and scale enhances the buffering capacity of landscapes and ecosystems in this region, supporting their ability to adapt to increasingly uncertain environmental futures.
Mortality management and climate action: A review and reference for using Terror Management Theory methods in interdisciplinary environmental research
Authors: Smith Lauren K. M. , Ross Hanna C. , Shouldice Stephanie A. , Wolfe Sarah Elizabeth 
Published: March 2022

AbstractGlobal climate change awareness is increasing, but efforts to convey information can trigger undesirable behaviors, including denial, skepticism, and increased resource consumption. It is therefore essential to more fully investigate social–psychological responses to climate information and messaging if we are to prompt, support, and sustain pro‐environmental behaviors. Yet consideration of these responses is typically absent from interdisciplinary environmental study designs. Of specific relevance is research using social psychology's Terror Management Theory (TMT) showing that people's efforts to repress mortality salience (MS) or awareness significantly influence their attitudes, beliefs, and behaviors. Research on MS's influence on climate change beliefs is progressing but, to date, a systematic scoping review of the literature has been unavailable. Here, we provide such a review. We propose that TMT insights and methods should be better integrated into research designs to guide climate communications and to generate the comprehensive cultural and behavioral changes needed to address societies' climate problems. We introduce a methodological framework for interdisciplinary researchers to incorporate TMT into their research designs and to help practitioners anticipate how their mortality‐laden messaging could trigger unintentional social‐psychological responses that degrade climate communication strategies.This article is categorized under:
Perceptions, Behavior, and Communication of Climate Change > Behavior Change and Responses
The Development of the EQ-5D-5L and its Value Sets
Authors: Devlin Nancy , Pickard Simon , Busschbach Jan 
Published: March 2022

AbstractThis chapter introduces the EQ-5D-5L questionnaire and its development by the EuroQol Group. The availability of the EQ-5D-5L, and the growing evidence of its pivotal role as a measurement system, generated a demand for ‘values’ to accompany it that would enable the use of EQ-5D-5L data in the estimation of quality-adjusted life-years (QALYs) and other applications where EQ-5D-5L profile data needs to be summarised by a single number. Chapter 1 sets out the main aim of the book: to provide an accessible source of information and guidance to support users of EQ-5D-5L and its value sets. Specifically, the book aims to improve users’ understanding of how EQ-5D-5L value sets are generated using the internationally standardised EQ-VT protocol; to raise awareness of the characteristics and properties of value sets; and to inform users’ choice of which value set to select for which purpose, and how that choice may affect analysis. The chapter concludes with an overview of the content of the book.
EQ-5D-5L Value Set Summaries
Authors: Roudijk Bram , Ludwig Kristina , Devlin Nancy 
Published: March 2022

AbstractThis chapter provides structured summaries of all 25 currently published national EQ-5D-5L value sets. The summaries were developed by extracting information from the published manuscripts of each value set and conducting secondary data analyses of the original valuation data generated in each country/region. The summaries include the mathematical formula for the preferred model for each national value set; information on the representativeness of the samples that were used to generate the value set; the mean values observed for each health state valued using composite time trade-off, the distribution of responses in the discrete choice experiment; information on the number of interviewers and whether any interviewer effects were present in the valuation data; key characteristics of the predicted values and relative importance of the EQ-5D-5L dimensions; and information on the uptake of the value set by local decision makers and health technology assessment bodies. This chapter serves as a compendium of EQ-5D-5L value sets, which may inform users of these value sets about the characteristics of all published EQ-5D-5L value sets.
Guidance to Users of EQ-5D-5L Value Sets
Authors: Devlin Nancy , Finch Aureliano Paolo , Parkin David 
Published: March 2022

AbstractOne of the most common questions that the EuroQol Group is asked by users of the EQ-5D-5L is: ‘Which value set should I use?’. The aim of this chapter is to provide guidance on this issue for users. There are two principal ways that EQ-5D-5L value sets are applied and used. The first is for summarising health-related quality of life to estimate quality-adjusted life-years (QALYs) and changes in QALYs that result from the health care use. This kind of evidence is often part of health technology assessment (HTA). The second category of use is when value sets are employed as a way of summarising and statistically analysing EQ-5D-5L profile data without the aim of estimating QALYs. In each case, the stated requirements of those who use this evidence in decision making is a key consideration. This chapter summarises the relevant considerations to be taken into account when choosing a value set for QALY estimation purposes; and the considerations which are relevant to choosing a value set to use in other, ‘non-QALY’ applications.
Event Log Sampling for Predictive Monitoring
Authors: Fani Sani Mohammadreza , Vazifehdoostirani Mozhgan , Park Gyunam , Pegoraro Marco , van Zelst Sebastiaan J. , van der Aalst Wil M. P. 
Published: March 2022

AbstractPredictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances. Such predictions are of significant interest to the process stakeholders. However, state-of-the-art methods for predictive monitoring require the training of complex machine learning models, which is often inefficient. This paper proposes an instance selection procedure that allows sampling training process instances for prediction models. We show that our sampling method allows for a significant increase of training speed for next activity prediction methods while maintaining reliable levels of prediction accuracy.
Online Prediction of Aggregated Retailer Consumer Behaviour
Authors: Spenrath Yorick , Hassani Marwan , van Dongen Boudewijn F. 
Published: March 2022

AbstractPredicting the behaviour of consumers provides valuable information for retailers, such as the expected spend of a consumer or the total turnover of the retailer. The ability to make predictions on an individual level is useful, as it allows retailers to accurately perform targeted marketing. However, with the expected large number of consumers and their diverse behaviour, making accurate predictions on an individual consumer level is difficult. In this paper we present a framework that focuses on this trade-off in an online setting. By making predictions on a larger number of consumers at a time, we improve the predictive accuracy but at the cost of usefulness, as we can say less about the individual consumers. The framework is developed in an online setting, where we update the prediction model and make new predictions over time. We show the existence of the trade-off in an experimental evaluation on a real-world dataset consisting of 39 weeks of transaction data.
PErrCas: Process Error Cascade Mining in Trace Streams
Authors: Wimbauer Anna , Richter Florian , Seidl Thomas 
Published: March 2022

AbstractEfficient and quick detection of problems is an essential task in online process monitoring. Many anomaly detection approaches excel in finding local deviations. We propose a novel approach that tracks local deviations over multiple process instances and visualizes correlations of deviation points. PErrCas provides knowledge about current cascades of deviations to give process analysts a starting point for rational root-cause analysis if processes leave their in-control parameters. PErrCas monitors deviations online and maintains cascades of varying timespans. Hence, our approach avoids defining an observation window beforehand, which is a significant advantage due to its impracticability to predefine expected cascade properties in exploratory scenarios.
Towards a Natural Language Conversational Interface for Process Mining
Authors: Barbieri Luciana , Madeira Edmundo Roberto Mauro , Stroeh Kleber , van der Aalst Wil M. P. 
Published: March 2022

AbstractDespite all the recent advances in process mining, making it accessible to non-technical users remains a challenge. In order to democratize this technology and make process mining ubiquitous, we propose a conversational interface that allows non-technical professionals to retrieve relevant information about their processes and operations by simply asking questions in their own language. In this work, we propose a reference architecture to support a conversational, process mining oriented interface to existing process mining tools. We combine classic natural language processing techniques (such as entity recognition and semantic parsing) with an abstract logical representation for process mining queries. We also provide a compilation of real natural language questions (aiming to form a dataset of that sort) and an implementation of the architecture that interfaces to an existing commercial tool: Everflow. Last but not least, we analyze the performance of this implementation and point out directions for future work.
xPM: A Framework for Process Mining with Exogenous Data
Authors: Banham Adam , Leemans Sander J. J. , Wynn Moe T. , Andrews Robert 
Published: March 2022

AbstractProcess mining facilitates analysis of business processes using event logs derived from historical records of process executions stored in organisations’ information systems. Most existing process mining techniques only consider data directly related to process execution (endogenous data). Data not directly representable as attributes of either events or traces (which includes exogenous data), are generally not considered. Exogenous data may be used by process participants in making decisions about execution paths. However, as exogenous data is not represented in event logs, its impact on such decision making is opaque and cannot currently be assessed by existing process mining techniques. This paper shows how exogenous data can be used in process mining, in particular discovery and enhancement techniques, to understand its influence on process decisions. In particular, we focus on time series which represent periodic observations of e.g. weather measurements, city health alerts or patient vital signs. We show that exogenous time series can be aligned and transformed into new attributes to annotate events in an event log. Then, we use these attributes to discover preconditions in a Petri net with exogenous data (xDPN), thus revealing the exogenous data’s influence on the process. Using our framework and a real-life data set from the medical domain, we evaluate the influence of exogenous data on decision points that are non-deterministic in an xDPN.
A Bridging Model for Process Mining and IoT
Authors: Bertrand Yannis , De Weerdt Jochen , Serral Estefanía 
Published: March 2022

AbstractContextualisation is an important challenge in process mining. While Internet of Things (IoT) devices are collecting more and more data on the physical context in which business processes are executed, the IoT and process mining fields are still considerably disintegrated. Important concepts, such as event or context, are not understood in the same way, which causes confusion and hinders cooperation between the two domains. Based on IoT ontologies and business process context models, this paper proposes a model to bridge the conceptualisation gap between the IoT and the process mining fields. The model defines the necessary concepts and relationships to build process mining techniques that take the physical context into account. As a first validation, the model is used to describe a lifelike process example, showing how IoT data and process events are related. Using this conceptualisation, both practitioners and researchers from the IoT and the process mining communities can reason about the use of IoT data in process mining and find support for data understanding, event abstraction and IoT and process data integration.
How to Overcome the Combination of Crises?
Authors: Iida Tetsunari 
Published: March 2022

AbstractToday, wind power and solar power have become the main stream of energy sources; from major electric power utilities to mega capital investors, many have entered the renewable energy sector. Mass-capital investment projects are also increasingly and rapidly expanding globally. It is not rare to find cases of such mega projects facing confrontations with local communities. Since the 1990s, the privatization of the energy sector has been significant, with Nordic countries and Germany seeing the advancement of privatization among community-operated energy utilities. Recently, however, there has been a movement to re-review this trend in order to revive public utilities. The recent reversal of the privatization trend means that the conventional way of decision-making with the participation of local governments and a few corporations is no longer appropriate, and there is a rise in the common understanding that the decision-making and governance method of local communities must be open and horizontally distributed. The rapid progress of ICT in recent years has raised awareness of risks in a governance system dominated by private companies, while raising technical capabilities to realize new and open decision-making and governance in local communities.
Energy Democracy for Energy Transition in South Korea?: Focusing on Politicization of Media
Authors: Yun Sun-Jin , Ahn Seunghyeok , Soh Regina Yoonmie 
Published: March 2022

AbstractSouth Korea has been pursuing energy transition as a national task since 2017 when the first nuclear reactor, Kori-1, was permanently stopped and President Moon Jae-in gave a commemorative speech on June 19, 2017. This study aims to identify who the main speakers of the conventional electricity system are and how they resist the movement of such changes. This study focused on the role of the media and found that the issue of energy transition has been highly politicized. Conservative media have criticized the Moon government’s post-nuclear policy as a leverage and have highlighted problems surrounding renewable energy as it is a hotbed of great corruption. Those who oppose locating renewable energy facilities to their community have taken advantage of such press reports. Energy transition requires more energy citizens who recognize not only their right to enjoy basic energy needs, but also their responsibility for the socio-economic and environmental impacts of their energy use. The realization of energy democracy pursuing energy and climate justice will take time but social dialogue based on scientific evidence and deliberation will open the way toward energy transition while identifying fake news and opposing interests adhering to the conventional electricity system.
Japanese Green New Deal to Bring Happiness and Prosperity
Authors: Asuka Jusen 
Published: March 2022

AbstractIn Japan, Prime Minister Suga announced in October 2020 a new goal of “carbon neutrality by 2050.” However, the energy/climate policy issued by the government after the announcement did not show any major changes in the current targets or policies. At this rate, there is a very high possibility that “carbon neutral by 2050” and the current “46% reduction by 2030 compared with 2013” pledge will become nothing but a mere political slogan. In February 2021, the “Energy Conversion for the Future Research Group” published “Report 2030: A Roadmap to 2030 for Green Recovery and Carbon Neutrality in 2050” as a Japanese version of the Green New Deal. This is an alternative to the government’s current energy/climate policies. This report presents a roadmap to the year 2030 which clarifies Japan’s essential aims and actions to be realized by 2030 in order to achieve carbon neutrality by 2050. Specifically, the report draws a systematic roadmap for investment, economic benefits, greenhouse gas emission reduction benefits, air pollution control benefits, unemployment measures, and financial resources by 2030. This chapter provides a concrete picture of Japan’s ideal green recovery by conveying the essence of the report as well as global trends.
Efficient localization in warehouse logistics: a comparison of LMS approaches for 3D multilateration of passive UHF RFID tags
Authors: Tripicchio Paolo , D’Avella Salvatore , Unetti Matteo 
Published: March 2022

AbstractThe Fourth Industrial Revolution, or Industry 4.0, aims at automating traditional manufacturing and industrial practices using modern smart technology. Autonomous mobile robots equipped with different sensors and employing different techniques have been proposed in the literature in the logistics and inventory warehouse management contexts. Efficient robot motion and planning depend on precise localization, mapping, and awareness of the environment. To properly localize items, recent attempts have been made employing radio frequency identification (RFID) in a 3D environment. This manuscript introduces four least mean squares methods to estimate the 3D positions of tags employing synthetic apertures and phase unwrapping. The proposed methods approach the localization problem solving a system of equations typical of multilateration methods to find the intersections of multiple hyperboloids. The novelty introduced here is the use of unwrapped phase distances to compute pseudo ranges for the multilateration problem. The use of such a technique is feasible thanks to precise mobile robot localization and custom navigation policies. All the analyzed methods are suitable for online localization due to reduced computation timings and have been tested on three different datasets. Two of them contain virtual data that has been generated by simulation, while the other one comes from an indoor experimental setup. Simulated tests show that combined antenna motions in 3D space (including Z-axis) improve the localization obtaining errors under the centimeter for 3D localization. Experimental tests obtained results as low as 13 cm of mean accuracy for 3D localization and 0.21 cm for 2D localization.
The effect of a natural polyphenol supplement on iron absorption in adults with hereditary hemochromatosis
Authors: Buerkli Simone , Salvioni Laura , Koller Natalie , Zeder Christophe , Teles Maria José , Porto Graça , Habermann Jana Helena , Dubach Irina Léa , Vallelian Florence , Frey Beat M. , Moretti Diego , Baumgartner Jeannine , Zimmermann Michael B. 
Published: March 2022

AbstractObjectivesWe developed a natural polyphenol supplement that strongly chelates iron in vitro and assessed its effect on non-heme iron absorption in patients with hereditary hemochromatosis (HH).MethodsWe performed in vitro iron digestion experiments to determine iron precipitation by 12 polyphenol-rich dietary sources, and formulated a polyphenol supplement (PPS) containing black tea powder, cocoa powder and grape juice extract. In a multi-center, single-blind, placebo-controlled cross-over study, we assessed the effect of the PPS on iron absorption from an extrinsically labelled test meal and test drink in patients (n = 14) with HH homozygous for the p.C282Y variant in theHFEgene. We measured fractional iron absorption (FIA) as stable iron isotope incorporation into erythrocytes.ResultsBlack tea powder, cocoa powder and grape juice extract most effectively precipitated iron in vitro. A PPS mixture of these three extracts precipitated ~ 80% of iron when 2 g was added to a 500 g iron solution containing 20 µg Fe/g. In the iron absorption study, the PPS reduced FIA by ~ 40%: FIA from the meal consumed with the PPS was lower (3.01% (1.60, 5.64)) than with placebo (5.21% (3.92, 6.92)) (p = 0.026)), and FIA from the test drink with the PPS was lower (10.3% (7.29 14.6)) than with placebo (16.9% (12.8 22.2)) (p = 0.002).ConclusionOur results indicate that when taken with meals, this natural PPS can decrease dietary iron absorption, and might thereby reduce body iron accumulation and the frequency of phlebotomy in patients with HH.Trial registry: clinicaltrials.gov (registration date: 9.6.2019, NCT03990181).