bluuebunny/crossref_metadata_2025 huggingface dataset:
Geo‐eco‐hydrology of the Upper Yellow River
Authors: Brierley Gary J. , Han Meiqin , Li Xilai , Li Zhiwei , Huang He Qing
Published: March 2022

A 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

Global 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

This 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

This 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

One 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

Predictive 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

Predicting 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

Efficient 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

Despite 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

Process 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

Contextualisation 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

Today, 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

South 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

In 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

The 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

Objectives

We 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).

Methods

We 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.

Results

Black 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).

Conclusion

Our 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).
Associations between maternal awakening salivary cortisol levels in mid-pregnancy and adverse birth outcomes
Authors: Vlenterie Richelle , Prins Judith B. , Roeleveld Nel , van Gelder Marleen M. H. J.
Published: March 2022

Purpose

Elevated levels of maternal cortisol have been hypothesized as the intermediate process between symptoms of depression and psychosocial stress during pregnancy and adverse birth outcomes. Therefore, we examined associations between cortisol levels in the second trimester of pregnancy and risks of three common birth outcomes in a nested case–control study.

Methods

This study was embedded in the PRIDE Study (n = 3,019), from which we selected all cases with preterm birth (n = 64), low birth weight (n = 49), and small-for-gestational age (SGA; n = 65), and 260 randomly selected controls, among the participants who provided a single awakening saliva sample in approximately gestational week 19 in 2012–2016. Multivariable linear and logistic regression was performed to assess the associations between continuous and categorized cortisol levels and the selected outcomes.

Results

We did not observe any associations between maternal cortisol levels and preterm birth and low birth weight. However, high cortisol levels (≥ 90th percentile) seemed to be associated with SGA (adjusted odds ratio 2.1, 95% confidence interval 0.9–4.8), in particular among girls (adjusted odds ratio 3.7, 95% confidence interval 1.1–11.9, based on eight exposed cases) in an exploratory analysis.

Conclusion

The results of this study showed no suggestions of associations between maternal awakening cortisol levels in mid-pregnancy and adverse birth outcomes, except for an increased risk of SGA.
A joint alignment and reconstruction algorithm for electron tomography to visualize in-depth cell-to-cell interactions
Authors: Bogensperger Lea , Kobler Erich , Pernitsch Dominique , Kotzbeck Petra , Pieber Thomas R. , Pock Thomas , Kolb Dagmar
Published: March 2022

Electron tomography allows one to obtain 3D reconstructions visualizing a tissue’s ultrastructure from a series of 2D projection images. An inherent problem with this imaging technique is that its projection images contain unwanted shifts, which must be corrected for to achieve reliable reconstructions. Commonly, the projection images are aligned with each other by means of fiducial markers prior to the reconstruction procedure. In this work, we propose a joint alignment and reconstruction algorithm that iteratively solves for both the unknown reconstruction and the unintentional shift and does not require any fiducial markers. We evaluate the approach first on synthetic phantom data where the focus is not only on the reconstruction quality but more importantly on the shift correction. Subsequently, we apply the algorithm to healthy C57BL/6J mice and then compare it with non-obese diabetic (NOD) mice, with the aim of visualizing the attack of immune cells on pancreatic beta cells within type 1 diabetic mice at a more profound level through 3D analysis. We empirically demonstrate that the proposed algorithm is able to compute the shift with a remaining error at only the sub-pixel level and yields high-quality reconstructions for the limited-angle inverse problem. By decreasing labour and material costs, the algorithm facilitates further research directed towards investigating the immune system’s attacks in pancreata of NOD mice for numerous samples at different stages of type 1 diabetes.
Transcriptional control of Arabidopsis seed development
Authors: Verma Subodh , Attuluri Venkata Pardha Saradhi , Robert Hélène S.
Published: March 2022

Main conclusion

The entire process of embryo development is under the tight control of various transcription factors. Together with other proteins, they act in a combinatorial manner and control distinct events during embryo development.

Seed development is a complex process that proceeds through sequences of events regulated by the interplay of various genes, prominent among them being the transcription factors (TFs). The members of WOX, HD-ZIP III, ARF, and CUC families have a preferential role in embryonic patterning. While WOX TFs are required for initiating body axis, HD-ZIP III TFs and CUCs establish bilateral symmetry and SAM. And ARF5 performs a major role during embryonic root, ground tissue, and vasculature development. TFs such as LEC1, ABI3, FUS3, and LEC2 (LAFL) are considered the master regulators of seed maturation. Furthermore, several new TFs involved in seed storage reserves and dormancy have been identified in the last few years. Their association with those master regulators has been established in the model plant Arabidopsis. Also, using chromatin immunoprecipitation (ChIP) assay coupled with transcriptomics, genome-wide target genes of these master regulators have recently been proposed. Many seed-specific genes, including those encoding oleosins and albumins, have appeared as the direct target of LAFL. Also, several other TFs act downstream of LAFL TFs and perform their function during maturation. In this review, the function of different TFs in different phases of early embryogenesis and maturation is discussed in detail, including information about their genetic and molecular interactors and target genes. Such knowledge can further be leveraged to understand and manipulate the regulatory mechanisms involved in seed development. In addition, the genomics approaches and their utilization to identify TFs aiming to study embryo development are discussed.
A Trichinella spiralis new born larvae-specific protein, Ts-NBL1, interacts with host’s cell vimentin
Authors: Wang A. , Liu X. , Heckmann A. , Caignard G. , Vitour D. , Hirchaud E. , Liu M. , Boireau P. , Karadjian G. , Vallée I.
Published: March 2022

The parasitic nematode Trichinella has a special relationship with its host as it has a unique intracellular location within the feeder cell which is a structure derived from skeletal muscle fiber. It has been proposed that “parakines” secreted by Trichinella larvae serve as messengers to implement communication between the parasite and the muscle cells through a molecular cross-talk to ensure permanent coexistence within the host. The Ts-NBL1 protein is considered to be a potential key “parakine” involved in the early invasion of the muscle fiber and its transformation into a feeder cell during Trichinella spiralis infection. This study used for the first time yeast two-hybrid (Y2H) technology in Trichinella to identify Ts-NBL1 interacting proteins. GST co-affinity purification experiments confirmed vimentin as an important interactor. The discovery of the new host proteins interacting with Ts-NBL1 will help to suggest that Ts-NBL1 contributes to participate in the capsule formation of feeder cells and provide ideas for understanding the molecular and cellular mechanisms involved in the survival of Trichinella in the host.
Strukturdynamische Werkstoffdämpfung von Blechpaketen elektrischer Maschinen
Authors: Franck Marius , Jaeger Markus , Groschup Benedikt , Hameyer Kay
Published: March 2022

Für die Modellierung des akustischen Verhaltens von elektrischen Antrieben werden präzise mechanische Werkstoffmodelle insbesondere für das Rotor- und Statorblechpaket benötigt. Die Modellierung der Werkstoffdämpfung spielt dabei eine entscheidene Rolle. Häufig werden zur Abbildung der Dämpfung Ergebnisse von experimentellen Modalanalysen, die an einem Prototyp durchgeführt werden, genutzt. Diese Ergebnisse erlauben nach aktuellem Stand der Technik keine Übertragbarkeit und Vorhersage für elektrische Maschinen. Des Weiteren zeigen die Messungen, dass neben den Steifigkeitseigenschaften eines Blechpakets auch die Dämpfungseigenschaften aufgrund des Aufbaus richtungsabhängig sind. In dieser Arbeit wird deshalb ein werkstoffspezifisches Dämpfungsmodell auf Basis einer analytischen Homogenisierung hergeleitet. Wie anhand von Messungen für ein exemplarisches Statorblechpaket gezeigt wird, kann mit diesem Modell die Richtungsabhängigkeit der Werkstoffdämpfung abgebildet werden. Das Modell ermöglicht zudem eine Übertragbarkeit und die Vorhersage für andere Maschinen.
Evolution of a Miocene canyon and its carbonate fill in the pre-evaporitic eastern Mediterranean
Authors: Reolid J. , Bialik O. M. , Puga-Bernabéu Á. , Zilberman E. , Cardenal J. , Makovsky Y.
Published: March 2022

Extensive canyons, excavated into the margins of the Levant Basin during the Oligocene–Miocene, are interesting case-studies for canyon fills in carbonate settings. The carbonate Pattish Formation, developed along the margins of the pre-evaporitic Messinian Beer Sheva Canyon in Israel, was investigated using both onshore seismic imaging and field data. The canyon has three main seismic facies of fill (1) Subparallel reflections mimicking the canyon´s morphology; (2) chaotic reflections overlying the subparallel ones, and (3) sigmoidal reflections, locally with sharp edges at the canyon margins. The first seismic facies corresponds to the pelagic marls of the Bet Eshel Formation. The other two seismic facies are, respectively, equivalent to bioclastic calcarenite clinobeds with slumps and channels, and to coral–stromatolite reefs and reef slopes of the Pattish Formation observed at outcrop. There were three phases of canyon development: (1) slope incision and headward erosion due to tectonic uplift and eustatic sea-level fall during the Early Oligocene, and large slope failure during the latest Middle Miocene; (2) platform incision and connection with a fluvial system in the Late Miocene related to falling sea level and tectonic uplift; and (3) canyon filling first by pelagic marls at the centre of the canyon, followed by calcarenite clinobeds at the canyon flanks formed by gravity flows. Finally, carbonate production at the margins of the canyon resulted in reefs and associated slopes prograding towards the canyon axis. The late canyon filling phase ended with the deposition of evaporites during the Messinian Salinity Crisis.
The interplay between expressive suppression, emotional self-efficacy and internalizing behavior in middle adolescence
Authors: Lonigro Antonia , Longobardi Emiddia , Laghi Fiorenzo
Published: March 2022

Background

Maladaptive emotion regulation strategies are predictive of negative outcomes in adolescence which, in turn, may impact on later well-being.

Objective

The current study aimed at testing the moderating role of emotional self-efficacy on the relation between expressive suppression and the engagement in internalizing behavior, controlling for gender effect.

Method

A total of 526 adolescents (Mage = 14.7 years, age range = 14–17 years) filled out self-report questionnaires evaluating expressive suppression, emotional regulatory self-efficacy, and internalizing behavior, respectively.

Results

Suppressors with lower positive emotion self-efficacy were more likely to engage in internalizing behavior than suppressors with higher positive emotion self-efficacy.

Conclusions

Despite several limitations, the study provided preliminary insights on the role played by emotional self-efficacy in the relation between expressive suppression and internalizing behavior in middle adolescence.
Predicting lexical complexity in English texts: the Complex 2.0 dataset
Authors: Shardlow Matthew , Evans Richard , Zampieri Marcos
Published: March 2022

Identifying words which may cause difficulty for a reader is an essential step in most lexical text simplification systems prior to lexical substitution and can also be used for assessing the readability of a text. This task is commonly referred to as complex word identification (CWI) and is often modelled as a supervised classification problem. For training such systems, annotated datasets in which words and sometimes multi-word expressions are labelled regarding complexity are required. In this paper we analyze previous work carried out in this task and investigate the properties of CWI datasets for English. We develop a protocol for the annotation of lexical complexity and use this to annotate a new dataset, CompLex 2.0. We present experiments using both new and old datasets to investigate the nature of lexical complexity. We found that a Likert-scale annotation protocol provides an objective setting that is superior for identifying the complexity of words compared to a binary annotation protocol. We release a new dataset using our new protocol to promote the task of Lexical Complexity Prediction.
The Generalised Mooney Space for Modelling the Response of Rubber-Like Materials
Authors: Anssari-Benam Afshin , Bucchi Andrea , Destrade Michel , Saccomandi Giuseppe
Published: March 2022

Soft materials such as rubbers, silicones, gels and biological tissues have a nonlinear response to large deformations, a phenomenon which in principle can be captured by hyperelastic models. The suitability of a candidate hyperelastic strain energy function is then determined by comparing its predicted response to the data gleaned from tests and adjusting the material parameters to get a good fit, an exercise which can be deceptive because of nonlinearity. Here we propose to generalise the approach of Rivlin and Saunders (Philos. Trans. R. Soc. A, Math. Phys. Eng. Sci. 243:251–288, 1951) who, instead of reporting the data as stress against stretch, manipulated these measures to create the ‘Mooney plot’, where the Mooney-Rivlin model is expected to produce a linear fit. We show that extending this idea to other models and modes of deformation (tension, shear, torsion, etc.) is advantageous, not only (a) for the fitting procedure, but also to (b) delineate trends in the deformation which are not obvious from the raw data (and may be interpreted in terms of micro-, meso-, and macro-structures) and (c) obtain a bounded condition number$\kappa $
κ
over the whole range of deformation, a robustness which is lacking in other plots and spaces.
Climate Change Influence On Ontario Corn Farms’ Income
Authors: Kornprobst Antoine , Davison Matt
Published: March 2022

Our study quantifies the impact of climate change on the income of corn farms in Ontario, at the 2068 horizon, under several warming scenarios. It is articulated around a discrete-time dynamic model of corn farm income with an annual time-step, corresponding to one agricultural cycle from planting to harvest. At each period, we compute the income of a farm given the corn yield, which is highly dependent on weather variables: temperature and rainfall. We also provide a reproducible forecast of the yearly distribution of corn yield for the regions around ten cities in Ontario, located where most of the corn growing activity takes place in the province. The price of corn futures at harvest time is taken into account and we fit our model by using 49 years of county-level historical climate and corn yield data. We then conduct out-of-sample Monte-Carlo simulations in order to obtain the farm income forecasts under a given climate change scenario, from 0$$^\circ$$

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C to + 4$$^\circ$$

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C.
If Nudges Treat their Targets as Rational Agents, Nonconsensual Neurointerventions Can Too
Authors: Douglas Thomas
Published: March 2022

Andreas Schmidt and Neil Levy have recently defended nudging against the objection that nudges fail to treat nudgees as rational agents. Schmidt rejects two theses that have been taken to support the objection: that nudges harness irrational processes in the nudgee, and that they subvert the nudgee’s rationality. Levy rejects a third thesis that may support the objection: that nudges fail to give reasons. I argue that these defences can be extrapolated from nudges to some nonconsensual neurointerventions; if Schmidt’s and Levy’s defences succeed, then some nonconsensual neurointerventions neither harness irrationality, nor subvert rationality, nor fail to give reasons. This, I claim, poses a challenge both to opponents of nonconsensual neurointerventions, and to defenders of nudging.
Transmission Characteristics of Terahertz Imaging Detection in Smoke Environments
Authors: Zhang Dan , Qu Jingchao , Ouyang Yintao , Li Sen , Song Yinmao
Published: March 2022

The terahertz imaging detection technology is applied to low-visibility fire environments to improve the traditional imaging detection equipment affected by the changes in the morphology and particle size distribution of smoke particles. This study focus on the transmission characteristics of terahertz waves in fire and smoke environments. A model for the propagation of terahertz waves is obtained. Terahertz imaging equipment is used to experimentally investigate the flue gas environment generated by three standard fires and combined with numerical simulations to analyze the influence of the terahertz wave transmission under different flue gas environments. The results show that the transmission of terahertz waves in a flue gas environment is affected by factors such as the smoke particle size and flue gas concentration; however, the transmission is significantly better than that obtained with traditional detection methods. In standard fire experiments, the terahertz equipment can achieve good imaging results, and the transmittance of terahertz waves is maintained above 88%.
Does Parenting Moderate the Association Between Adverse Childhood Experiences and Adolescents’ Future Orientation?
Authors: Chainey Carys , Burke Kylie , Haynes Michele
Published: March 2022

Adolescents who think and act towards the future are more likely to thrive. This future orientation may, however, be affected by adversity and the parenting they receive. The influence of cumulative adversity, and of parenting in the context of adversity, is yet to be explored. We investigated whether adolescents’ future orientation is associated with experiences of singular and multiple types of adversity, and if parenting moderates these associations. Data from the Longitudinal Study of Australian Children K Cohort (n = 1177; 51.5% male; aged 16–17 years) were used to measure future orientation at age 16–17, the number of adversities experienced from age 4/5 to age 14/15 (parental separation and divorce, household substance use problem, household mental health condition, domestic violence), and parenting received at age 14/15 (warmth, hostility, communication, monitoring). Relationships and moderations were tested using stepwise moderated logistic regression analyses, controlling for demographic characteristics. Adolescents were at risk for low future orientation if they had experienced singular or multiple types of adversity, higher hostility, lower communication, and lower monitoring. We did not find a moderating effect of parenting. These results indicate that while young people are less likely to have future-related thoughts and actions if they have experienced singular or multiple types of adversity, their future orientation may be supported by effective parenting and non-hostile parent-adolescent relationships. Young people who experience both adversity and poor parenting may be at higher risk than others. Further investigation is warranted, to explore the causal relationships between adverse experiences, parenting, and future orientation.
Different landscape features within a simplified agroecosystem support diverse pollinators and their service to crop plants
Authors: Fijen Thijs P. M. , Read Samantha F. J. , Walker Melanie K. , Gee Megan , Nelson Warrick R. , Howlett Brad G.
Published: March 2022

Context

Landscape simplification is a main driver of insect decline, threatening crop pollination services. Changes in functional features in simplified agroecosystems may impact the abundance of wild pollinators.

Objectives

Here, we studied whether different pollinator groups based on life-history are differentially associated to landscape features, and how this affects crop pollination service delivery.

Methods

Using window traps in a highly simplified agroecosystem, we surveyed pollinator abundances and diversity associated with: (1) bare fence-lines separating pastures (control), (2) conifer hedgerows (3) farm gardens of diverse exotic plant species (4) effluent-ponds, (5) newly established native-plantings, (6) gorse (Ulex europaeus) hedgerows and (7) open water channels across six to twelve dairy farms. We also measured pollination service delivery to potted pak choi (Brassica rapa) plots near features 1–5 on six farms.

Results

Pollinators at gardens, native-plantings, and effluent-ponds delivered significantly more pollination service than at bare fence-lines, with flies being more effective pollinators than bees at all features assessed. Taxa delivering the service also differed across features. The native bee Lasioglossum sordidum delivered more pollination at garden and native-planting features than at other features, drone flies (Eristalis tenax) contributed the majority of pollination service at effluent-ponds and bare fence-lines, while calliphorid flies contributed most pollination at conifer hedgerows.

Conclusions

Conversion of functional features to bare fence-lines negatively affects on-farm pollinator diversity and its service to crop plants. However, farmers can benefit from enhancing features containing diverse plant species that support non-bee and bee species proven to deliver measurable crop pollination services.
Deep Brain Stimulation in Parkinson Disease: A Meta-analysis of the Long-term Neuropsychological Outcomes
Authors: Bucur Madalina , Papagno Costanza
Published: March 2022

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) or globus pallidum internus (GPi) improves motor functions in patients with Parkinson’s disease (PD) but may cause a decline in specific cognitive domains. The aim of this systematic review and meta-analysis was to assess the long-term (1–3 years) effects of STN or GPi DBS on four cognitive functions: (i) memory (delayed recall, working memory, immediate recall), (ii) executive functions including inhibition control (Color-Word Stroop test) and flexibility (phonemic verbal fluency), (iii) language (semantic verbal fluency), and (iv) mood (anxiety and depression). Medline and Web of Science were searched, and studies published before July 2021 investigating long-term changes in PD patients following DBS were included. Random-effects model meta-analyses were performed using the R software to estimate the standardized mean difference (SMD) computed as Hedges’ g with 95% CI. 2522 publications were identified, 48 of which satisfied the inclusion criteria. Fourteen meta-analyses were performed including 2039 adults with a clinical diagnosis of PD undergoing DBS surgery and 271 PD controls. Our findings add new information to the existing literature by demonstrating that, at a long follow-up interval (1–3 years), both positive effects, such as a mild improvement in anxiety and depression (STN, Hedges’ g = 0,34, p = 0,02), and negative effects, such as a decrease of long-term memory (Hedges’ g = -0,40, p = 0,02), verbal fluency such as phonemic fluency (Hedges’ g = -0,56, p < 0,0001), and specific subdomains of executive functions such as Color–Word Stroop test (Hedges’ g = -0,45, p = 0,003) were observed. The level of evidence as qualified with GRADE varied from low for the pre- verses post-analysis to medium when compared to a control group.
Accuracy of a pre-trained sentiment analysis (SA) classification model on tweets related to emergency response and early recovery assessment: the case of 2019 Albanian earthquake
Authors: Contreras Diana , Wilkinson Sean , Alterman Evangeline , Hervás Javier
Published: March 2022

Traditionally, earthquake impact assessments have been made via fieldwork by non-governmental organisations (NGO's) sponsored data collection; however, this approach is time-consuming, expensive and often limited. Recently, social media (SM) has become a valuable tool for quickly collecting large amounts of first-hand data after a disaster and shows great potential for decision-making. Nevertheless, extracting meaningful information from SM is an ongoing area of research. This paper tests the accuracy of the pre-trained sentiment analysis (SA) model developed by the no-code machine learning platform MonkeyLearn using the text data related to the emergency response and early recovery phase of the three major earthquakes that struck Albania on the 26th November 2019. These events caused 51 deaths, 3000 injuries and extensive damage. We obtained 695 tweets with the hashtags: #Albania #AlbanianEarthquake, and #albanianearthquake from the 26th November 2019 to the 3rd February 2020. We used these data to test the accuracy of the pre-trained SA classification model developed by MonkeyLearn to identify polarity in text data. This test explores the feasibility to automate the classification process to extract meaningful information from text data from SM in real-time in the future. We tested the no-code machine learning platform's performance using a confusion matrix. We obtained an overall accuracy (ACC) of 63% and a misclassification rate of 37%. We conclude that the ACC of the unsupervised classification is sufficient for a preliminary assessment, but further research is needed to determine if the accuracy is improved by customising the training model of the machine learning platform.